np.array:\n front_door_mask = self.boundary == 255\n region = measure.regionprops(front_door_mask.astype(int))[0]\n return np.array(region.bbox, dtype=int)","def mask_ne(lonreg2, latreg2):\n nearth = cfeature.NaturalEarthFeature(\"physical\", \"ocean\", \"50m\")\n main_geom = [contour for contour in nearth.geometries()][0]\n\n mask = shapely.vectorized.contains(main_geom, lonreg2, latreg2)\n m2 = np.where(((lonreg2 == -180.0) & (latreg2 > 71.5)), True, mask)\n m2 = np.where(\n ((lonreg2 == -180.0) & (latreg2 < 70.95) & (latreg2 > 68.96)), True, m2\n )\n m2 = np.where(((lonreg2 == 180.0) & (latreg2 > 71.5)), True, mask)\n m2 = np.where(\n ((lonreg2 == 180.0) & (latreg2 < 70.95) & (latreg2 > 68.96)), True, m2\n )\n # m2 = np.where(\n # ((lonreg2 == 180.0) & (latreg2 > -75.0) & (latreg2 < 0)), True, m2\n # )\n m2 = np.where(((lonreg2 == -180.0) & (latreg2 < 65.33)), True, m2)\n m2 = np.where(((lonreg2 == 180.0) & (latreg2 < 65.33)), True, m2)\n\n return ~m2","def mask(self):\n mask = np.zeros((self.height, self.width))\n pts = [\n np.array(anno).reshape(-1, 2).round().astype(int)\n for anno in self.segmentation\n ]\n mask = cv2.fillPoly(mask, pts, 1)\n return mask","def create_hard_blocks(self):\n for x in xrange(1, self.map_size[0], 2):\n for y in xrange(1, self.map_size[1], 2):\n self.create_hard_block_at(x, y)","def _isolate(self, frame, landmarks, points):\n region = np.array([(landmarks.part(point).x, landmarks.part(point).y) for point in points])\n region = region.astype(np.int32)\n # Applying a mask to get only the eye\n height, width = frame.shape[:2]\n black_frame = np.zeros((height, width), np.uint8)\n mask = np.full((height, width), 255, np.uint8)\n cv2.fillPoly(mask, [region], (0, 0, 0))\n eye = cv2.bitwise_not(black_frame, frame.copy(), mask=mask)\n # Cropping on the eye\n margin = 5\n min_x = np.min(region[:, 0]) - margin\n max_x = np.max(region[:, 0]) + margin\n min_y = np.min(region[:, 1]) - margin\n max_y = np.max(region[:, 1]) + margin\n self.frame = eye[min_y:max_y, min_x:max_x]\n self.origin = (min_x, min_y)\n height, width = self.frame.shape[:2]\n self.center = (width / 2, height / 2)","def region_of_interest(self,img):\r\n #defining a blank mask\r\n mask = np.zeros_like(img) \r\n #checking number of image channel(color/grayscale) and applying mask\r\n if len(img.shape) > 2:\r\n ignore_mask_color = (255,255,255)\r\n else:\r\n ignore_mask_color = 255\r\n #filling color to pixels inside the polygon \r\n cv2.fillPoly(mask, self.vertices_img, ignore_mask_color)\r\n #image where mask pixels are nonzero\r\n masked_image = cv2.bitwise_and(img, mask)\r\n #cv2.imshow('',masked_image)\r\n return masked_image","def ocean_unmasked(res='4x5', debug=False):\n\n from .GEOSChem_bpch import get_LWI_map\n if debug:\n print(('ocean_mask called for: ', res))\n\n # Create a mask from land/water/ice indices\n m = np.ma.masked_not_equal(get_LWI_map(res=res), 0)\n if debug:\n print((mask, mask.shape))\n return m.mask","def _region_mask(self, cs, all_regions, xctr, yctr, hwcs):\n if not HAS_REGIONS:\n return None\n ctr_coord = ar.PixCoord(xctr, yctr)\n mask = None\n for reg_str in all_regions:\n # read ds9 string into a region class\n try:\n with set_log_level('CRITICAL'):\n frame_regions = ar.Regions.parse(reg_str, format='ds9')\n except Exception as err:\n log.debug(f'Region parser error: {err}')\n continue\n for fr in frame_regions:\n if cs == 'wcs':\n # convert to a pixel region first\n try:\n with set_log_level('CRITICAL'):\n fr = fr.to_pixel(hwcs)\n except Exception as err: # pragma: no cover\n # error could be anything, since regions package\n # is in early development state\n log.debug(f'Region WCS conversion error: {err}')\n continue\n\n # check if cursor is contained in a region\n # in any frame\n with set_log_level('CRITICAL'):\n contained = fr.contains(ctr_coord)\n if hasattr(contained, '__len__'):\n # PolygonPixelRegion returns an array, currently\n # (regions v0.4)\n contained = contained[0]\n\n if contained:\n # get mask from first matching region\n try:\n with set_log_level('CRITICAL'):\n mask = fr.to_mask()\n except Exception as err: # pragma: no cover\n # error could be anything, since regions package\n # is in early development state\n log.debug(f'Region mask error: {err}')\n continue\n else:\n log.info(f'Contained in {type(fr).__name__}')\n break\n if mask is not None:\n break\n\n # reset active frame\n return mask","def clean_mask(mask, background=0):\n kernels = [\n np.array([[ 1, -1, -1], [-1, 1, -1], [-1, -1, -1]]), # top left standalone pixel\n np.array([[-1, -1, 1], [-1, 1, -1], [-1, -1, -1]]), # top right standalone pixel\n np.array([[-1, -1, -1], [-1, 1, -1], [ 1, -1, -1]]), # bottom left standalone pixel\n np.array([[-1, -1, -1], [-1, 1, -1], [-1, -1, 1]]) # bottom right standalone pixel\n ]\n\n proc_masks = [cv2.morphologyEx(mask, cv2.MORPH_HITMISS, kernel).astype(np.bool) for kernel in kernels]\n\n for proc_mask in proc_masks:\n mask[proc_mask] = background\n return mask","def segment_region_of_interest(image):\n binary = image < 604\n cleared = clear_border(binary)\n\n label_image = label(cleared)\n\n areas = [r.area for r in regionprops(label_image)]\n areas.sort()\n if len(areas) > 2:\n for region in regionprops(label_image):\n if region.area < areas[-2]:\n for coordinates in region.coords:\n label_image[coordinates[0], coordinates[1]] = 0\n\n binary = label_image > 0\n\n selem = disk(2)\n binary = binary_erosion(binary, selem)\n\n selem = disk(10)\n binary = binary_closing(binary, selem)\n\n edges = roberts(binary)\n binary = scipy.ndimage.binary_fill_holes(edges)\n\n get_high_vals = binary == 0\n image[get_high_vals] = 0\n\n return image","def sense_landmarks(state, field_map, max_observations):\n\n assert isinstance(state, np.ndarray)\n assert isinstance(field_map, Landscape)\n\n assert state.shape == (3,)\n\n M = field_map.num_landmarks\n #print(M, field_map.landmarks.shape)\n noise_free_observations_list = list()\n for k in range(M):\n noise_free_observations_list.append(get_observation(state, field_map, k))\n noise_free_observation_tuples = [(x[0], np.abs(x[1]), int(x[2])) for x in noise_free_observations_list]\n\n dtype = [('range', float), ('bearing', float), ('lm_id', int)]\n noise_free_observations = np.array(noise_free_observations_list)\n noise_free_observation_tuples = np.array(noise_free_observation_tuples, dtype=dtype)\n\n ii = np.argsort(noise_free_observation_tuples, order='bearing')\n noise_free_observations = noise_free_observations[ii]\n noise_free_observations[:, 2] = noise_free_observations[:, 2].astype(int)\n\n c1 = noise_free_observations[:, 1] > -np.pi / 2.\n c2 = noise_free_observations[:, 1] < np.pi / 2.\n ii = np.nonzero((c1 & c2))[0]\n\n if ii.size <= max_observations:\n return noise_free_observations[ii]\n else:\n return noise_free_observations[:max_observations]","def __generate_mask(self):\n mask = np.concatenate([np.ones(len(self.fixed[0])),\n np.zeros(self.num_points),\n np.ones(len(self.fixed[1]))])\n return mask","def remove_shadow(patch):\r\n lt = not np.any(patch[0,0])\r\n rt = not np.any(patch[0,-1])\r\n lb = not np.any(patch[-1,0])\r\n rb = not np.any(patch[-1,-1])\r\n\r\n return lt or rt or lb or rb","def create_geofence(self):\n\t\tring = ogr.Geometry(ogr.wkbLinearRing)\n\t\tring.AddPoint(*self.north_coords)\n\t\tring.AddPoint(*self.northeast_coords)\n\t\tring.AddPoint(*self.east_coords)\n\t\tring.AddPoint(*self.southeast_coords)\n\t\tring.AddPoint(*self.south_coords)\n\t\tring.AddPoint(*self.southwest_coords)\n\t\tring.AddPoint(*self.west_coords)\n\t\tring.AddPoint(*self.northwest_coords)\n\t\tring.AddPoint(*self.north_coords)\n\t\tself.polygon.AddGeometry(ring)","def __iteratively_retain(\n self,\n orf_regions: List[Tuple[int, int]]) -> List[Tuple[int, int]]:\n\n ret = []\n\n arr = np.zeros((len(self.seq), ))\n\n for start, end in orf_regions:\n ret.append((start, end))\n arr[start-1:end] = 1\n orf_coverage = np.sum(arr) / len(arr)\n if orf_coverage > self.min_orf_coverage:\n break\n\n return ret","def contextualcull(cnts):\n temp = []\n actualout = []\n indicesused = []\n for cnt in cnts:\n if cnt.area > CULL_MINIMUMS[cnt.spatialindex]:\n temp.append(cnt)\n if cnt.spatialindex not in indicesused:\n indicesused.append(cnt.spatialindex)\n if PRIORITIZE_FASTEST:\n for sindex in indicesused: #filter down to the fastest contour.\n _allatthisindex = [x for x in temp if x == sindex]\n highest = _allatthisindex.sort(key=lambda y: y.spd, reverse=False)[0]\n actualout.append(highest)\n else:\n actualout = temp\n print 'Contours after cull: ', len(actualout)\n return actualout","def sanitize_mask(orig_x, orig_y, mask):\n contours, hierarchy = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)\n\n # Draw contours:\n cv2.drawContours(mask, contours, 0, (0, 255, 0), 2)\n # Calculate image moments of the detected contour\n num_objects = (len(contours))\n #threshold\n threshold = 3\n\n center_list = []\n # print(num_objects)\n if num_objects > 1:\n for item in range(num_objects):\n M = cv2.moments(contours[item])\n try:\n center_x = round(M['m10'] / M['m00'])\n center_y = round(M['m01'] / M['m00'])\n center_list.append([center_y , center_x ])\n except:\n pass\n\n # initialize retmask\n retmask = mask\n if num_objects > 1:\n for x, y in center_list:\n if orig_x - threshold <= x <= orig_x + threshold and orig_y - threshold <= y <= orig_y + threshold:\n pass\n else:\n def dfs_removal(px , py, mask):\n R = len(mask)\n C = len(mask[0])\n if mask[px][py ] != 255: \n return\n mask[px][py] = 0\n if 0 <= px - 1 and mask[px - 1][py ] == 255: dfs_removal(px - 1 , py , mask)\n if px + 1 < R and mask[px + 1][py ] == 255: dfs_removal(px + 1 , py , mask)\n if 0 <= py - 1 and mask[px][py - 1] == 255: dfs_removal(px, py -1 , mask)\n if py + 1 < C and mask[px][py + 1] == 255: dfs_removal(px, py + 1 , mask)\n\n dfs_removal(x,y, mask)\n\n return retmask","def _create_observation_mask(self):\n\n\n if self.BLUE_PARTIAL:\n centers, radii = [], []\n for agent in self._team_blue:\n if not agent.isAlive: continue\n centers.append(agent.get_loc())\n radii.append(agent.range)\n self._blue_mask = self._create_vision_mask(centers, radii)\n if self.TEAM_MEMORY == \"fog\":\n self.blue_memory = np.logical_and(self.blue_memory, self._blue_mask)\n else:\n self._blue_mask = np.zeros_like(self._static_map, dtype=bool)\n\n if self.RED_PARTIAL:\n centers, radii = [], []\n for agent in self._team_red:\n if not agent.isAlive: continue\n centers.append(agent.get_loc())\n radii.append(agent.range)\n self._red_mask = self._create_vision_mask(centers, radii)\n if self.TEAM_MEMORY == \"fog\":\n self.red_memory = np.logical_and(self.red_memory, self._red_mask)\n else:\n self._red_mask = np.zeros_like(self._static_map, dtype=bool)","def ice_unmasked(res='4x5', debug=False):\n # Create a np.ma mask\n m = np.logical_not((land_unmasked(res)*ocean_unmasked(res)))\n if debug:\n print((mask, mask.shape))\n return m","def spectrum_regions(x_on,\n y_on,\n r_on,\n x_fov,\n y_fov,\n r_fov,\n exclusion,\n outfile,\n min_on_distance):\n from astropy.io import fits\n from gammapy.background import ReflectedRegionMaker\n\n if exclusion:\n log.info('Reading {0}'.format(exclusion))\n exclusion = fits.open(exclusion)[0]\n else:\n # log.info('No exclusion mask used.')\n # TODO: make this work without exclusion mask\n log.error(\"Currently an exclusion mask is required\")\n exit(-1)\n\n fov = dict(x=x_fov, y=y_fov, r=r_fov)\n rr_maker = ReflectedRegionMaker(exclusion=exclusion,\n fov=fov)\n source = dict(x_on=x_on, y_on=y_on, r_on=r_on)\n rr_maker.compute(**source)\n\n log.info('Writing {0}'.format(outfile))\n rr_maker.write_off_regions(outfile)","def test_degrade_widemask_or(self):\n\n nside_coverage = 32\n nside_map = 256\n nside_map2 = 64\n sparse_map = healsparse.HealSparseMap.make_empty(nside_coverage, nside_map,\n WIDE_MASK, wide_mask_maxbits=7)\n sparse_map_or = healsparse.HealSparseMap.make_empty(nside_coverage, nside_map2,\n WIDE_MASK, wide_mask_maxbits=7)\n # Fill some pixels in the \"high-resolution\" map\n pixel = np.arange(4000, 8000)\n sparse_map.set_bits_pix(pixel, [4])\n\n # Check which pixels will be full in the \"low-resolution\" map and fill them\n pixel2 = np.unique(np.right_shift(pixel, healsparse.utils._compute_bitshift(nside_map2, nside_map)))\n sparse_map_or.set_bits_pix(pixel2, [4])\n\n # Degrade with or\n sparse_map_test = sparse_map.degrade(nside_map2, reduction='or')\n\n # Check the results\n testing.assert_almost_equal(sparse_map_or._sparse_map, sparse_map_test._sparse_map)\n\n # Repeat for maxbits > 8\n sparse_map = healsparse.HealSparseMap.make_empty(nside_coverage, nside_map,\n WIDE_MASK, wide_mask_maxbits=16)\n sparse_map_or = healsparse.HealSparseMap.make_empty(nside_coverage, nside_map2,\n WIDE_MASK, wide_mask_maxbits=16)\n # Fill some pixels in the \"high-resolution\" map\n pixel = np.arange(0, 1024)\n pixel = np.concatenate([pixel[:512], pixel[512::3]]).ravel()\n sparse_map.set_bits_pix(pixel, [4, 12])\n sparse_map.clear_bits_pix(pixel[:16], [4]) # set low value in the first pixel\n\n # Check which pixels will be full in the \"low-resolution\" map and fill them\n # Note that we are filling more than the ones that are going to be True\n # since we want to preserve the coverage_map\n pixel2_all = np.unique(np.right_shift(pixel,\n healsparse.utils._compute_bitshift(nside_map2, nside_map)))\n sparse_map_or.set_bits_pix(pixel2_all, [4, 12])\n\n # Get the pixel number of the bad pixels\n pixel2_bad = np.array([0])\n sparse_map_or.clear_bits_pix(pixel2_bad, [4]) # set low value in the first pixel\n\n # Degrade with or\n sparse_map_test = sparse_map.degrade(nside_map2, reduction='or')\n\n # Check the results\n testing.assert_almost_equal(sparse_map_test._sparse_map, sparse_map_or._sparse_map)\n\n # Test degrade-on-read\n self.test_dir = tempfile.mkdtemp(dir='./', prefix='TestHealSparse-')\n\n fname = os.path.join(self.test_dir, 'test_wide_degrade.hs')\n sparse_map.write(fname)\n\n sparse_map_test2 = healsparse.HealSparseMap.read(fname, degrade_nside=nside_map2, reduction='or')\n testing.assert_almost_equal(sparse_map_test2._sparse_map, sparse_map_or._sparse_map)","def _offset_region(all_polygons, bboxes,\n left, bottom, right, top,\n distance = 5,\n join_first = True,\n precision = 1e-4,\n join = 'miter',\n tolerance = 2):\n\n # Mark out a region slightly larger than the final desired region\n d = distance*1.01\n\n polygons_to_offset = _crop_edge_polygons(all_polygons, bboxes, left-d,\n bottom-d, right+d, top+d,\n precision = precision)\n\n # Offset the resulting cropped polygons and recrop to final desired size\n polygons_offset = clipper.offset(polygons_to_offset, distance, join,\n tolerance, 1/precision, int(join_first))\n polygons_offset_cropped = _crop_region(polygons_offset, left, bottom,\n right, top, precision = precision)\n\n return polygons_offset_cropped","def __trim(\n self,\n orf_regions: List[Tuple[int, int]]) -> List[Tuple[int, int]]:\n\n ret = []\n\n for start, end in orf_regions:\n if start == 1:\n new_start = start # Trust the model prediction\n else:\n new_start = self.__find_start_codon(start, end)\n ret.append((new_start, end))\n\n return ret","def as_boolean_mask(self):\n bbox = self.bbox()\n zs = np.unique([c.image_z_position for c in self.contours])\n z_to_index = dict(zip(zs,range(len(zs))))\n\n # Get dimensions, initialize mask.\n nx,ny = np.diff(bbox[:2], axis=1).astype(int) + 1\n nx = int(nx); ny = int(ny)\n nz = int(zs.shape[0])\n mask = np.zeros((nx,ny,nz), dtype=np.bool)\n\n # We check if these points are enclosed within each contour \n # for a given slice. `test_points` is a list of image coordinate \n # points, offset by the bounding box.\n test_points = bbox[:2,0] + np.c_[ np.where(~mask[:,:,0]) ]\n\n # First we \"turn on\" pixels enclosed by inclusion contours.\n for contour in self.contours:\n if contour.inclusion:\n zi = z_to_index[contour.image_z_position]\n contour_matrix = contour.to_matrix()[:,:2]\n\n # Turn the contour closed if it's not.\n if (contour_matrix[0] != contour_matrix[-1]).all():\n contour_matrix = np.append(contour_matrix,\n contour_matrix[0].reshape(1,2),\n axis=0)\n\n # Create path object and test all pixels\n # within the contour's bounding box.\n path = mplpath.Path(contour_matrix, closed=True)\n contains_pts = path.contains_points(test_points)\n mask[:,:,zi] = contains_pts.reshape(mask.shape[:2])\n\n # Second, we \"turn off\" pixels enclosed by exclusion contours.\n for contour in self.contours:\n if not contour.inclusion:\n zi = z_to_index[contour.image_z_position]\n contour_matrix = contour.to_matrix()[:,:2]\n\n # Turn the contour closed if it's not.\n if (contour_matrix[0] != contour_matrix[-1]).all():\n contour_matrix = np.append(contour_matrix,\n contour_matrix[0].reshape(1,2),\n axis=0)\n\n path = mplpath.Path(contour_matrix, closed=True)\n not_contains_pts = ~path.contains_points(test_points)\n not_contains_pts = not_contains_pts.reshape(mask.shape[:2])\n mask[:,:,zi] = np.logical_and(mask[:,:,zi], not_contains_pts)\n\n # The first and second axes have to \n # be swapped because of the reshape.\n return mask.swapaxes(0,1), bbox[[1,0,2]]","def build_block_cross(self):\n from ambry.geo.util import find_geo_containment, find_containment\n from geoid import civick \n\n lr = self.init_log_rate(3000)\n\n def gen_bound():\n \n boundaries = self.library.dep('blockgroups').partition\n\n # Note, ogc_fid is the primary key. The id column is created by the shapefile. \n for i,boundary in enumerate(boundaries.query(\n \"SELECT AsText(geometry) AS wkt, gvid FROM blockgroups\")):\n lr('Load rtree')\n \n yield i, boundary['wkt'] , boundary['gvid'] \n \n def gen_points():\n\n for row in self.partitions.find(table = 'facilities_addresses').rows:\n if row['longitude'] and row['latitude']:\n yield (row['longitude'], row['latitude']), row['facilities_id']\n\n\n p = self.partitions.find_or_new(table='facilities_geoids')\n p.clean()\n\n with p.inserter() as ins:\n for point, point_o, cntr_geo, cntr_o in find_containment(gen_bound(),gen_points()):\n\n blockgroup_gvid = civick.Blockgroup.parse(cntr_o)\n tract_gvid = blockgroup_gvid.convert(civick.Tract)\n county_gvid = blockgroup_gvid.convert(civick.County)\n \n ins.insert(dict(facilities_id = point_o, \n blockgroup_gvid = str(blockgroup_gvid),\n tract_gvid = str(tract_gvid),\n county_gvid = str(county_gvid)\n ))\n \n lr('Marking point containment')","def create_region_mask(latitude_array, target_shape, lat_bounds):\n\n target_ndim = len(target_shape)\n\n southern_lat, northern_lat = lat_bounds\n mask_array = numpy.where((latitude_array >= southern_lat) & (latitude_array < northern_lat), False, True)\n\n mask = uconv.broadcast_array(mask_array, [target_ndim - 2, target_ndim - 1], target_shape)\n assert mask.shape == target_shape \n\n return mask","def RemovePolygonHoles_management(in_fc, threshold=0.0):\n desc = arcpy.Describe(in_fc)\n if desc.dataType != \"FeatureClass\" and desc.dataType != \"ShapeFile\":\n print(\"Invalid data type. The input is supposed to be a Polygon FeatureClass or Shapefile.\")\n return\n else:\n if desc.shapeType != \"Polygon\":\n print(\"The input is supposed to be a Polygon FeatureClass or Shapefile.\")\n return\n if threshold < 0.0:\n threshold = 0.0\n with arcpy.da.UpdateCursor(in_fc, [\"SHAPE@\"]) as updateCursor:\n for updateRow in updateCursor:\n shape = updateRow[0]\n new_shape = arcpy.Array()\n for part in shape:\n new_part = arcpy.Array()\n if threshold > 0:\n # find None point in shape part\n # in arcpy module, a None point is used to seperate exterior and interior vertices\n null_point_index = []\n for i in range(len(part)):\n if part[i] is None:\n null_point_index.append(i)\n # if interior vertices exist, create polygons and compare polygon shape area to given threshold\n # if larger, keep vertices, else, dismiss them\n if len(null_point_index) > 0:\n for k in range(0, null_point_index[0]):\n new_part.add(part[k])\n for i in range(len(null_point_index)):\n pointArray = arcpy.Array()\n # determine if the None point is the last one\n if i+1 < len(null_point_index):\n for j in range(null_point_index[i] + 1, null_point_index[i+1]):\n pointArray.add(part[j])\n else:\n for j in range(null_point_index[i] + 1, len(part)):\n pointArray.add(part[j])\n # create a polygon to check shape area against the given threshold\n inner_poly = arcpy.Polygon(pointArray)\n # if larger than threshold, then add to the new part Array\n if inner_poly.area > threshold:\n if i+1 < len(null_point_index):\n for k in range(null_point_index[i], null_point_index[i+1]):\n new_part.add(part[k])\n else:\n for k in range(null_point_index[i], len(part)):\n new_part.add(part[k])\n new_shape.add(new_part)\n # if interior does not exist, add the whole part\n else:\n new_shape.add(part)\n else:\n # get the first None point index\n first_null_point_index = 0\n for i in range(len(part)):\n if part[i] is None:\n first_null_point_index = i\n break\n if first_null_point_index == 0:\n new_shape.add(part)\n else:\n for j in range(first_null_point_index):\n new_part.add(part[j])\n new_shape.add(new_part)\n if len(new_shape) > 0:\n new_poly = arcpy.Polygon(new_shape)\n updateRow[0] = new_poly\n updateCursor.updateRow(updateRow)","def create_mask(frame):\n \n # detect ridges\n ridges = enhance_ridges(frame)\n\n # threshold ridge image\n thresh = filters.threshold_otsu(ridges)\n thresh_factor = 1.1\n prominent_ridges = ridges > thresh_factor*thresh\n prominent_ridges = morphology.remove_small_objects(prominent_ridges, min_size=128)\n\n # the mask contains the prominent ridges\n mask = morphology.convex_hull_image(prominent_ridges)\n mask = morphology.binary_erosion(mask, disk(10))\n return mask","def unmask(self, near_x, near_y, radius=BRIGHTEN_RECT_TEMP, is_lighter=False):\n #self._actual_unmask(self.last_brighten, self.masked_image, radius=radius)\n \n brighten_rect = pygame.draw.circle(self.image, (255, 255,0), (near_x, near_y), radius/2)\n \n if is_lighter:\n brighten_rect = pygame.draw.circle(self.image, (50, 0, 0), (near_x, near_y), 40)\n brighten_rect = pygame.draw.circle(self.image, (255, 255,0), (near_x, near_y), 38)\n \n self.game.dirty_rects.append(brighten_rect)\n \n self.last_brighten = (near_x, near_y)","def masktoregions(in_mask):\n regions = []\n for i in [0,1]: # do the thing for the first and second strands\n current_strand = in_mask[i].copy().astype(float)\n current_strand[-1] = np.nan # set final position to np.nan to avoid overlap issues\n transitions = current_strand - np.roll(current_strand,1)\n true_start = np.where(transitions == 1)[0]\n true_end = np.where(transitions == -1)[0] - 1\n if current_strand[0] == 1: # if starts on True, add True start to front end\n true_start = np.r_[0,true_start]\n if in_mask[i][-1] == True: # if ends on True, add True end to back end\n true_end = np.r_[true_end, len(current_strand)-1]\n if in_mask[i][-2] == False: # if the one before is False, it's a single point True\n true_start = np.r_[true_start,len(current_strand)-1]\n if np.all(in_mask[i][-2:] == [True, False]):\n true_end = np.r_[true_end, len(current_strand)-2]\n regions.append(np.asarray([np.zeros(len(true_start))+i,true_start,true_end]).T)\n out_regions = np.concatenate(regions,axis=0).astype(int)\n return out_regions","def cmask(self):\n mask = np.zeros(18)\n if 'full' in self.CONS: mask[:] = 1\n if 'f0' in self.CONS: mask[0] = 1\n if 'f1' in self.CONS: mask[1:4] = 1\n if 'f2' in self.CONS: mask[4:10] = 1\n if 'vx' in self.CONS: mask[10] = 1\n if 'vy' in self.CONS: mask[11] = 1\n if 'vz' in self.CONS: mask[12] = 1\n if 'TG' in self.CONS: mask[13:18] = 1\n return mask>0","def GetCoastGrids(LandMask):\n \n \"\"\"\n Define a coastline map. This map will be set to 1 on all coast cells.\n \"\"\"\n \n \n CoastlineMap = np.zeros((LandMask.shape[0], LandMask.shape[1]))\n \n \"\"\"\n We will use a nested loop to loop through all cells of the Landmask cell. What this loop basically does is,\n when a cell has a value of 1 (land), it will make all surrounding cells 1, so we create kind of an extra line of \n grids around the landmask. In the end we will substract the landmask from the mask which is created by the nested loop, \n which result in only a mask with the coast grids. Notice, that when we're in the corner, upper, side, or lower row, and we\n meet a land cell, we should not make all surrounding cells 1. For example, we the lower left corner is a land grid, you should only make the inner cells 1. \n \"\"\"\n \n for i in range(LandMask.shape[0]-1):\n for j in range(LandMask.shape[1]-1):\n \n\n \"\"\"\n We have nine if statements, four for the corners, four for the sides and one for the middle\n of the landmask. \n \"\"\"\n\n if i == 0 and j == 0: #upper left corner\n \n if LandMask[i,j] == 1:\n \n CoastlineMap[i,j] = 1\n CoastlineMap[i,j+1] = 1\n \n CoastlineMap[i+1,j] = 1 \n CoastlineMap[i+1, j+1] = 1\n \n \n elif i == 0 and j != 0 and j != LandMask.shape[1]-1: #upper row\n \n if LandMask[i,j] == 1:\n \n CoastlineMap[i,j] = 1\n CoastlineMap[i,j-1] = 1\n CoastlineMap[i,j+1] = 1\n \n CoastlineMap[i+1, j] = 1\n CoastlineMap[i+1,j-1] = 1\n CoastlineMap[i+1,j+1] = 1\n \n \n elif i == 0 and j == LandMask.shape[1]-1: #upper right corner\n \n if LandMask[i,j] == 1:\n \n CoastlineMap[i,j] = 1\n CoastlineMap[i,j-1] = 1\n \n CoastlineMap[i+1,j] = 1 \n CoastlineMap[i+1, j-1] = 1\n \n elif i != 0 and i != LandMask.shape[0]-1 and j == LandMask.shape[1]-1: #right row\n \n if LandMask[i,j] == 1:\n \n CoastlineMap[i,j] = 1\n CoastlineMap[i+1,j] = 1\n CoastlineMap[i-1,j] = 1\n \n CoastlineMap[i, j-1] = 1\n CoastlineMap[i+1,j-1] = 1\n CoastlineMap[i-1,j-1] = 1\n \n elif i == LandMask.shape[0]-1 and j == LandMask.shape[1]-1: #lower right corner\n \n if LandMask[i,j] == 1:\n \n CoastlineMap[i,j] = 1\n CoastlineMap[i,j-1] = 1\n \n CoastlineMap[i-1,j] = 1 \n CoastlineMap[i-1, j-1] = 1\n \n elif i == LandMask.shape[0]-1 and j != 0 and j != LandMask.shape[1]-1: #lower row\n \n if LandMask[i,j] == 1:\n \n CoastlineMap[i,j] = 1\n CoastlineMap[i,j-1] = 1\n CoastlineMap[i,j+1] = 1\n \n CoastlineMap[i-1, j] = 1\n CoastlineMap[i-1,j-1] = 1\n CoastlineMap[i-1,j+1] = 1\n \n \n elif i == LandMask.shape[0]-1 and j == 0: #lower left corner\n \n if LandMask[i,j] == 1:\n \n CoastlineMap[i,j] = 1\n CoastlineMap[i,j+1] = 1\n \n CoastlineMap[i+1,j] = 1 \n CoastlineMap[i+1, j+1] = 1\n \n elif i != 0 and i != LandMask.shape[0]-1 and j == 0: #left row\n \n if LandMask[i,j] == 1:\n \n CoastlineMap[i,j] = 1\n CoastlineMap[i+1,j] = 1\n CoastlineMap[i-1,j] = 1\n \n CoastlineMap[i, j+1] = 1\n CoastlineMap[i+1,j+1] = 1\n CoastlineMap[i-1,j+1] = 1\n \n else:\n \n if LandMask[i,j] == 1:\n \n CoastlineMap[i,j] = 1 #middle\n CoastlineMap[i+1,j] = 1#lowermiddle\n CoastlineMap[i-1,j] = 1#uppermiddle\n \n CoastlineMap[i+1, j-1] = 1\n CoastlineMap[i-1, j-1] = 1\n CoastlineMap[i, j-1] =1\n \n CoastlineMap[i+1, j+1] = 1\n CoastlineMap[i-1, j+1] = 1\n CoastlineMap[i, j+1] = 1\n \n \n \n \"\"\"\n Here we substract the landmaks from the coastline mask, resulting in only\n the coastline. \n \"\"\"\n \n \n Coastgrids = CoastlineMap - LandMask\n \n return Coastgrids, CoastlineMap","def mask_img_region(self, image, coordinate_list):\n \n \n # Mask to locate cropping region (CR)\n mask = np.ones((image.shape),dtype=np.uint8)\n mask.fill(255)\n \n # Mark the coorinate region as black\n masked_image = cv2.fillPoly(mask, np.array([coordinate_list], dtype=np.int32),0)\n \n # Extract coorinate region from original image and rest is white \n cropped = cv2.bitwise_or(image, masked_image)\n \n return cropped","def opencv_watershed(masked, mask) -> JSON_TYPE:\n # For code and detailed explanation see:\n # http://datahacker.rs/007-opencv-projects-image-segmentation-with-watershed-algorithm/\n threshold: int = 30\n gray = cv2.cvtColor(masked, cv2.COLOR_RGB2GRAY)\n ret, thresh_img = cv2.threshold(gray, threshold, 255, cv2.THRESH_BINARY)\n # Noise removal\n kernel = np.ones((3), np.uint8)\n opening_img = cv2.morphologyEx(thresh_img, cv2.MORPH_OPEN, kernel, iterations=9)\n # Noise removal\n closing_img = cv2.morphologyEx(thresh_img, cv2.MORPH_CLOSE, kernel, iterations=4)\n dist_transform = cv2.distanceTransform(255 - closing_img, cv2.DIST_L2, 3)\n local_max_location = peak_local_max(dist_transform, min_distance=1, indices=True)\n\n n_increases: int = 0\n while local_max_location.shape[0] < 30 and n_increases < 15:\n threshold += 20\n ret, thresh_img = cv2.threshold(gray, threshold, 255, cv2.THRESH_BINARY)\n # Noise removal\n kernel = np.ones((3), np.uint8)\n opening_img = cv2.morphologyEx(thresh_img, cv2.MORPH_OPEN, kernel, iterations=9)\n # Noise removal\n closing_img = cv2.morphologyEx(thresh_img, cv2.MORPH_CLOSE, kernel, iterations=4)\n dist_transform = cv2.distanceTransform(255 - closing_img, cv2.DIST_L2, 3)\n local_max_location = peak_local_max(dist_transform, min_distance=1, indices=True)\n n_increases += 1\n # Reset threshold\n threshold = 30\n\n num_clusters: int = 30\n if n_increases >= 15:\n num_clusters = local_max_location.shape[0]\n kmeans = KMeans(n_clusters=num_clusters)\n # If local_max_location size is 0, return 0 predictions\n if not local_max_location.size:\n return {\n \"count\": 0\n }\n kmeans.fit(local_max_location)\n local_max_location = kmeans.cluster_centers_.copy()\n # Kmeans is returning a float data type so we need to convert it to an int. \n local_max_location = local_max_location.astype(int)\n dist_transform_copy = dist_transform.copy()\n for i in range(local_max_location.shape[0]):\n cv2.circle(dist_transform_copy, (local_max_location[i][1], local_max_location[i][0]), 5, 255)\n # markers = np.zeros_like(dist_transform)\n ret, sure = cv2.threshold(dist_transform, 0.01*dist_transform.max(), 255, 0)\n sure = np.uint8(sure)\n ret, markers = cv2.connectedComponents(sure)\n labels = np.arange(kmeans.n_clusters)\n markers[local_max_location[:,0], local_max_location[:,1]] = labels + 1\n # Convert all local markers to an integer. This because cluster centers will be float numbers. \n markers = markers.astype(int)\n markers_copy = markers.copy()\n index_non_zero_markers = np.argwhere(markers != 0)\n markers_copy = markers_copy.astype(np.uint8)\n font = cv2.FONT_HERSHEY_SIMPLEX\n for i in range(index_non_zero_markers.shape[0]):\n string_text = str(markers[index_non_zero_markers[i][0], index_non_zero_markers[i][1]])\n cv2.putText(markers_copy, string_text, (index_non_zero_markers[i][1], index_non_zero_markers[i][0]), font, 1, 255)\n markers = markers.astype(np.int32)\n segmented = cv2.watershed(masked, markers)\n count_segments(markers)\n #return {\n # \"count\": local_max_location.shape[0]\n #}\n return {\n \"count\": count_segments(markers),\n }","def fill_vert(self, mask):\n im_floodfill = np.copy(mask)\n im_floodfill[im_floodfill!=self.vertebra_id] = 0\n im_floodfill[im_floodfill==self.vertebra_id] = 255\n im_floodfill_copy = np.copy(im_floodfill)\n # The size needs to be 2 pixels larger than the image.\n h, w = im_floodfill.shape[:2]\n mask4mask = np.zeros((h+2, w+2), np.uint8)\n # Floodfill from point (0, 0)\n cv2.floodFill(im_floodfill, mask4mask, (0,0), 255)\n # Invert floodfilled image\n im_floodfill_inv = cv2.bitwise_not(im_floodfill)\n # Combine the two images to get the foreground.\n im_floodfill_inv = im_floodfill_inv | im_floodfill_copy\n im_floodfill_inv[im_floodfill_inv==255] = self.vertebra_id\n mask_filled = mask | im_floodfill_inv\n return mask_filled","def _occlude_image(im, cR, cC, size_patch, stride):\n im[cR:cR + stride, cC:cC + stride, :] = 127.5\n occ_map = np.ones((im_target_size, im_target_size))\n occ_map[cR:cR + stride, cC:cC + stride] = 0\n return im, occ_map","def generate_effective_mask(self, mask_size: tuple, polygons_ignore):\n mask = np.ones(mask_size, dtype=np.uint8)\n\n for poly in polygons_ignore:\n instance = poly.astype(np.int32).reshape(1, -1, 2)\n cv2.fillPoly(mask, instance, 0)\n\n return mask","def _boundary_constraint_fence(\n self,\n x: np.ndarray,\n ) -> np.ndarray:\n # clip dimensions to fit within the boundary\n x_constrained = np.clip(\n x,\n self.boundary_fence['min'],\n self.boundary_fence['max'],\n )\n return x_constrained","def test_make_outer_mask_from_fp(self):\n fp_mask = skimage.io.imread(os.path.join(data_dir,\n 'sample_fp_mask.tif'))\n output_mask = boundary_mask(fp_mask, boundary_type=\"outer\")\n truth_mask = skimage.io.imread(os.path.join(data_dir,\n 'sample_b_mask_outer.tif'))\n\n assert np.array_equal(output_mask, truth_mask)","def get_occlusion_mask_from_rigid_flow(self, rigid_flow):\n with tf.variable_scope(\"get_occlusion_mask_from_rigid_flow\"):\n b, h, w, _ = rigid_flow.shape\n rigid_flow = tf.stop_gradient(rigid_flow)\n mask = bilinear_sampler.flow_warp(\n tf.ones([b, h, w, 1], dtype=tf.float32), rigid_flow\n )\n mask = tf.clip_by_value(mask, 0.0, 1.0)\n return mask","def applymask(self,mask):\n self.spec[mask==0]=np.nan","def _get_watershed_areas(self, class_contours, class_mask, kernel_size=3, area_thresh=500):\n\n kernel = np.ones((kernel_size, kernel_size), dtype=np.uint8)\n\n # Since the watershed draws contours, we need to invert the predictions to\n # get the 'inside' blob portion. We also slightly compress the blob portion\n # so we can get a more defining border.\n inverted_contours = 255 - class_contours\n\n inverted_contours = cv2.erode(inverted_contours, kernel, iterations=1)\n # remove areas that are not part of the class mask\n inverted_contours[class_mask==0]= 0 # here ?\n\n return inverted_contours","def region_of_interest(self, img):\n # defining a blank mask to start with\n mask = np.zeros_like(img)\n\n # defining a 3 channel or 1 channel color to fill the mask with depending on the input image\n if len(img.shape) > 2:\n channel_count = img.shape[2] # i.e. 3 or 4 depending on your image\n ignore_mask_color = (255,) * channel_count\n else:\n ignore_mask_color = 255\n\n # filling pixels inside the polygon defined by \"vertices\" with the fill color\n cv2.fillPoly(mask, self.vertices, ignore_mask_color)\n\n # returning the image only where mask pixels are nonzero\n masked_image = cv2.bitwise_and(img, mask)\n return masked_image","def toggle_culling(self):\n self.view['cull'] = not self.view['cull']\n self.update_flags()","def set_region(img, vertices):\n mask = np.zeros_like(img)\n channel_count = img.shape[2]\n match_mask_color = (255,) * channel_count\n cv2.fillPoly(mask, vertices, match_mask_color)\n\n masked_img = cv2.bitwise_and(img, mask)\n\n new_mask = np.zeros(masked_img.shape[:2], np.uint8)\n\n bg = np.ones_like(masked_img, np.uint8) * 255\n cv2.bitwise_not(bg, bg, mask=new_mask)\n\n return masked_img","def predominateMask(self) -> MaskState:\n return MaskState.fromCoreEmotion(self._coreEstimation.result)","def fill_context_mask(mask, sizes, v_mask, v_unmask):\r\n mask.fill_(v_unmask)\r\n n_context = mask.size(2)\r\n for i, size in enumerate(sizes):\r\n if size < n_context:\r\n mask[i, :, size:] = v_mask\r\n return mask","def test_bad_region():\n ref_file = pkg_resources.resource_filename('m260b.test_data', 'ref_practice_W_1_chr_1.fasta')\n read_file = pkg_resources.resource_filename('m260b.test_data', 'practice_w_1.std.bad_region1.bam')\n ref_hdr, reference = read_basic_fasta(ref_file) \n read_iter = pysam.Samfile(read_file)\n chr = ref_hdr[1:].strip()\n areg = list(active_regions(read_iter, reference, chr, start_offset=0, flank=30, dfrac=1.0))\n found = False\n for region, reads in areg:\n found |= region.start <= 5769 <= region.stop\n if not found:\n raise ValueError('Window did not open around variant')","def warp_tensor(tensor):\n\n #tf.config.run_functions_eagerly(True)\n\n num_hole_rate = 4 / (128*128) # percent of selected pixels in downsample imagee\n\n tensor = tf.expand_dims(tensor, 0)\n if tensor.shape.rank == 5:\n # 3D blurring\n filters = tf.ones([3,3,3], dtype=tf.float32) / 27\n filters = filters[..., tf.newaxis, tf.newaxis]\n tensor = tf.nn.conv3d(tensor, filters, [1,1,1,1,1], \"SAME\")\n\n # make hole\n uniform_random = tf.random.uniform([tensor.shape[1]*tensor.shape[2]*tensor.shape[3]], 0, 1.0)\n uniform_random = tf.reshape(uniform_random, tensor.shape)\n mask_matrix = tf.where(uniform_random < num_hole_rate, tf.ones_like(tensor), tf.zeros_like(tensor)) \n \n # dilate holes \n filters = tf.ones([4,4,4], dtype=tf.float32) \n filters = filters[..., tf.newaxis, tf.newaxis]\n mask_matrix = tf.nn.conv3d(mask_matrix, filters, [1,1,1,1,1], \"SAME\")\n \n # apply mask -- make the \"holes\" the mean value of the image \n mean = tf.math.reduce_mean(tensor)\n tensor = tf.where(mask_matrix > 0, tf.ones_like(tensor)*mean, tensor) \n else:\n # 2D blurring\n filters = tf.ones([3,3], dtype=tf.float32) / 9\n filters = filters[..., tf.newaxis, tf.newaxis]\n tensor = tf.nn.conv2d(tensor, filters, [1,1,1,1], \"SAME\")\n\n # make hole\n uniform_random = tf.random.uniform([tensor.shape[1]*tensor.shape[2]], 0, 1.0)\n uniform_random = tf.reshape(uniform_random, tensor.shape)\n mask_matrix = tf.where(uniform_random < num_hole_rate, tf.ones_like(tensor), tf.zeros_like(tensor)) \n \n # dilate holes \n filters = tf.ones([4,4], dtype=tf.float32) \n filters = filters[..., tf.newaxis, tf.newaxis]\n mask_matrix = tf.nn.conv2d(mask_matrix, filters, [1,1,1,1], \"SAME\")\n \n # apply mask -- make the \"holes\" the mean value of the image \n mean = tf.math.reduce_mean(tensor)\n tensor = tf.where(mask_matrix > 0, tf.ones_like(tensor)*mean, tensor) \n\n\n return tf.squeeze(tensor, [0])","def test_offcenter(self):\n actual = cm.circle_mask((5, 5), 2, center=(2, 3))\n expected = np.array([[False, False, False, True, False],\n [False, False, True, True, True],\n [False, True, True, True, True],\n [False, False, True, True, True],\n [False, False, False, True, False]])\n self.assertIsNone(np.testing.assert_array_equal(actual, expected))","def get_cruise_track_mask(max_lon=None, min_lon=None, max_lat=None,\n min_lat=None, unmask_water=True, res='4x5',\n trop_limit=True):\n # only look at surface\n m = surface_unmasked(res=res, trop_limit=trop_limit)\n # apply ocean mask\n if unmask_water:\n m = m + ocean_unmasked(res=res)\n # Mask over given longitude range, if provided\n if not isinstance(max_lon, type(None)):\n m = m + lon2lon_2D_unmasked(lowerlon=min_lon, higherlon=max_lon,\n res=res)[:, :, None]\n # Mask over given latitude range, if provided\n if not isinstance(max_lat, type(None)):\n m = m + lat2lat_2D_unmasked(lowerlat=min_lat, higherlat=max_lat,\n res=res)[:, :, None]\n # Invert\n m = np.logical_not(m)\n return m","def test_make_thick_outer_mask_from_fp(self):\n fp_mask = skimage.io.imread(os.path.join(data_dir,\n 'sample_fp_mask.tif'))\n output_mask = boundary_mask(fp_mask, boundary_type=\"outer\",\n boundary_width=10)\n truth_mask = skimage.io.imread(\n os.path.join(data_dir, 'sample_b_mask_outer_10.tif')\n )\n\n assert np.array_equal(output_mask, truth_mask)","def obscure(rects):\n image = Image.open('/tmp/.i3lock.png')\n\n for rect in rects:\n area = (\n rect.x, rect.y,\n rect.x + rect.width,\n rect.y + rect.height\n )\n\n cropped = image.crop(area)\n cropped = obscure_image(cropped)\n image.paste(cropped, area)\n overlay = Image.open('/home/robin/Documents/source/scripts/src/locked.png')\n image.paste(overlay, tuple([(i-o)/2 for i,o in zip(image.size,overlay.size)]), overlay)\n image.save('/tmp/.i3lock.png')","def mask(self):","def remove_land(data, data_obs):\n \n ### Import modules\n import numpy as np\n from netCDF4 import Dataset\n \n ### Read in ocean mask\n directorydata = '/Users/zlabe/Data/masks/'\n filename = 'ocmask_19x25.nc'\n datafile = Dataset(directorydata + filename)\n mask = datafile.variables['nmask'][:]\n datafile.close()\n \n ### Mask out model and observations\n datamask = data * mask\n data_obsmask = data_obs * mask\n \n return datamask, data_obsmask","def susceptibleToInfected(self):\n\n #create a mask to sieve those uninfected out\n infected = self.space == 1\n\n # add extra boundaries\n expan1 = np.hstack((infected,np.zeros((self.space.shape[0],1))))\n expan1 = np.vstack((expan1,np.zeros((1,expan1.shape[1]))))\n expan1 = np.hstack((np.zeros((expan1.shape[0],1)),expan1))\n expan1 = np.vstack((np.zeros((1,expan1.shape[1])),expan1))\n\n # make the addition for how many infected are around each position\n expan2 = (expan1[:-2,:-2] + \n expan1[:-2,1:-1] + \n expan1[:-2,2:] + \n expan1[1:-1,2:] + \n expan1[2:,2:] + \n expan1[2:,1:-1] + \n expan1[2:,0:-2] + \n expan1[1:-1,0:-2])\n\n exposedToRisk = np.logical_and(expan2 > 0, self.space == 0)\n # initialize a random matrix where around infection_probability % of the values are True\n infect_prob_arr = np.random.rand(self.space.shape[0], self.space.shape[1]) < self.infection_probability\n # find the overlap between healthy and \n self.space[np.logical_and(exposedToRisk, infect_prob_arr)] = 1"],"string":"[\n \"def remove_spurious_landmarks(self):\\r\\n \\r\\n remove = np.argwhere(self.lm_counter < 0)\\r\\n self.lm = np.delete(self.lm, remove, axis=0)\\r\\n self.lm_cvar = np.delete(self.lm_cvar, remove, axis=0)\\r\\n self.lm_counter = np.delete(self.lm_counter, remove)\\r\\n \\r\\n return # Replace this.\\r\",\n \"def mask_region(self, ypos, xpos, r):\\r\\n for j, i in product(np.arange(ypos - r, ypos + r + 1), np.arange(xpos - r, xpos + 1 + r)): # Create square\\r\\n if (j - ypos) ** 2 + (i - xpos) ** 2 <= r ** 2 and 0 <= j<= self.shapes[0] - 1 and 0<= i <=self.shapes[1] - 1:\\r\\n j = int(j)\\r\\n i = int(i)\\r\\n self.masked[j, i] = 0\",\n \"def unstuck(self):\\n mask = Map.current_map.mask\\n \\n x_max, y_max = mask.get_size()\\n orig_x, orig_y = round(self.x), round(self.y)\\n x, y = orig_x , orig_y\\n unstuck_aggr = COLLISION_UNSTUCK_AGGRESSION\\n \\n # Vertical check for any open spots we could put the entity on...\\n while y > 0:\\n if not mask.get_at((x, y)):\\n self.y = y\\n self.vy = -unstuck_aggr\\n return\\n y -= unstuck_aggr\\n y = orig_y\\n while y < y_max:\\n if not mask.get_at((x, y)):\\n self.y = y\\n self.vy = unstuck_aggr\\n return\\n y += unstuck_aggr\\n y = orig_y\\n \\n # Horizontal spots?\\n while x > 0:\\n if not mask.get_at((x, y)):\\n self.x = x\\n self.vx = -unstuck_aggr\\n return\\n x -= unstuck_aggr\\n x = orig_x\\n while x < x_max:\\n if not mask.get_at((x, y)):\\n self.x = x\\n self.vx = unstuck_aggr\\n return\\n x += unstuck_aggr\\n x = orig_x\\n \\n # Diagonal spots\\n while x > 0 and y > 0:\\n if not mask.get_at((x, y)):\\n self.x, self.y = x, y\\n self.vx, self.vy = -unstuck_aggr, -unstuck_aggr\\n return\\n x, y = x - unstuck_aggr, y - unstuck_aggr\\n x, y = orig_x, orig_y\\n while x < x_max and y < y_max:\\n if not mask.get_at((x, y)):\\n self.x, self.y = x, y\\n self.vx, self.vy = unstuck_aggr, unstuck_aggr\\n return\\n x, y = x + unstuck_aggr, y + unstuck_aggr\\n x, y = orig_x, orig_y\\n while x > 0 and y < y_max:\\n if not mask.get_at((x, y)):\\n self.x, self.y = x, y\\n return\\n x, y = x - unstuck_aggr, y + unstuck_aggr\\n x, y = orig_x, orig_y\\n while x < x_max and y > 0:\\n if not mask.get_at((x, y)):\\n self.x, self.y = x, y\\n return\\n x, y = x + unstuck_aggr, y - unstuck_aggr\\n x, y = orig_x, orig_y\\n \\n # All right, I officially give up now.\\n print(\\\"Couldn't unstuck object!\\\")\",\n \"def trim_floating_solid(im):\\n holes = find_disconnected_voxels(~im)\\n im[holes] = True\\n return im\",\n \"def get_masked_regions(contig):\\n masked_regions = \\\"\\\"\\n\\n seq = contig.seq\\n contig_end = len(seq)-1\\n masked = False\\n for i, n in enumerate(seq):\\n # mark the starting position of a softmasked region\\n if not masked and n.islower():\\n masked = True\\n start = i\\n\\n # mark end position of softmasked region (can be end of contig)\\n if masked and (n.isupper() or i == contig_end):\\n masked = False\\n end = i\\n\\n # store softmasked region in bed3 (chr, start, end) format\\n masked_regions += f\\\"{contig.id}\\\\t{start}\\\\t{end}\\\\n\\\" # noqa: start exists\\n\\n return masked_regions\",\n \"def fix_straight_lines(self):\\r\\n\\r\\n # Creates a vertical 1x5 kernel and applies binary closing based on that kernel\\r\\n vertical_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (1, 5))\\r\\n self.thresh_invert = cv2.morphologyEx(self.thresh_invert, cv2.MORPH_CLOSE, vertical_kernel, iterations=9)\\r\\n\\r\\n # Creates a horizontal 5x1 kernel and applies binary closing based on that kernel\\r\\n horizontal_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 1))\\r\\n self.thresh_invert = cv2.morphologyEx(self.thresh_invert, cv2.MORPH_CLOSE, horizontal_kernel, iterations=4)\",\n \"def removeIslands(self):\\n if isinstance(self.substrates, Polygon):\\n return\\n mainland = []\\n for i, substrate in enumerate(self.substrates.geoms):\\n ismainland = True\\n for j, otherSubstrate in enumerate(self.substrates.geoms):\\n if j == i:\\n continue\\n if Polygon(otherSubstrate.exterior.coords).contains(substrate):\\n ismainland = False\\n break\\n if ismainland:\\n mainland.append(substrate)\\n self.substrates = shapely.geometry.collection.GeometryCollection(mainland)\\n self.oriented = False\",\n \"def proc_unfilled_polygon(self, tokens):\\n\\n return self._proc_polygon(tokens, filled=False)\",\n \"def get_regions_mask(self, input):\",\n \"def fill_blind_pores(im):\\n holes = find_disconnected_voxels(im)\\n im[holes] = False\\n return im\",\n \"def regular_neighborhood(self):\\n euler_char = self.num_switches() - self.num_branches()\\n return Surface(num_punctures=self.num_complementary_regions(),\\n euler_char=euler_char)\",\n \"def land_unmasked(res='4x5', debug=False):\\n from .GEOSChem_bpch import get_LWI_map # Kludge, use GEOS-Chem LWI\\n\\n # Create a np.ma mask\\n if debug:\\n print(('land_mask called for: ', res))\\n m = np.ma.masked_not_equal(get_LWI_map(res=res), 1)\\n if debug:\\n print((mask, mask.shape))\\n return m.mask\",\n \"def get_France_unmasked(res='4x5'):\\n # France mask\\n lowerlat = 42.5\\n higherlat = 51\\n lowerlon = -4.441\\n higherlon = 7.7577\\n # Get a mask for lat and lon range, then combine\\n mask1 = lat2lat_2D_unmasked(res=res, lowerlat=lowerlat,\\n higherlat=higherlat)\\n mask2 = lon2lon_2D_unmasked(res=res, lowerlon=lowerlon,\\n higherlon=higherlon)\\n mask = np.ma.mask_or(mask1, mask2)\\n # Only consider land grid boxes\\n mask = np.ma.mask_or(mask, land_unmasked(res=res)[..., 0])\\n return mask\",\n \"def cull_landmarks(landmarks):\\n return np.delete(landmarks, np.r_[\\n 49:54, 55:68, # Mouth\\n 37:39, 40:42, # Left eye\\n 43:45, 46:48, # Right eye\\n ], axis=0)\",\n \"def make_midwest_mask(fname_coords):\\n lon, lat, topo = STEM_parsers.parse_STEM_coordinates(fname_coords)\\n lat_range = np.array((40,44)) #deg N\\n lon_range = np.array((-96, -87)) #deg W\\n\\n lat_mask = ma.masked_inside(lat, *lat_range)\\n lon_mask = ma.masked_inside(lon, *lon_range)\\n mask = np.logical_and(lat_mask.mask, lon_mask.mask)\\n\\n return(mask)\",\n \"def make_western_mask(fname_coords, fname_top):\\n top = STEM_parsers.parse_tobspred(fname_top)\\n top = STEM_vis.grid_tobspred_data(top, which_data='emi_fac')\\n\\n lon, lat, topo = STEM_parsers.parse_STEM_coordinates(fname_coords)\\n\\n mask = np.logical_and(abs(top - 1.0) < 0.001, lon < -95)\\n # mask out this little blip in prairie that slips through\\n mask[np.logical_and(lat > 40, lon > -100)] = False\\n #mask = lon < -110\\n\\n return(mask)\",\n \"def get_masked_scene(orig, mask, local_context_size = 80, dilation=False):\\n orig_scene = orig.copy()\\n mask_scene = mask.copy()\\n orig_scene_no_mask = orig.copy()\\n \\n mask_info = np.where(mask_scene == 0) \\n min_x = max(min(mask_info[0]) - local_context_size, 0)\\n max_x = max(mask_info[0]) + local_context_size\\n min_y = max(min(mask_info[1]) - local_context_size, 0)\\n max_y = max(mask_info[1]) + local_context_size\\n \\n orig_scene = orig_scene[min_x:max_x,min_y:max_y]\\n orig_scene_no_mask = orig_scene_no_mask[min_x:max_x,min_y:max_y]\\n mask_scene = mask_scene[min_x:max_x,min_y:max_y]\\n \\n dialation_mask = np.zeros(mask_scene.shape) + 255\\n \\n if dilation:\\n dialation_mask = cv2.dilate(255-mask_scene, np.ones((local_context_size,local_context_size)))\\n \\n #implot(dialation_mask)\\n #plt.imshow(dialation_mask, 'gray')\\n \\n for x in range(mask_scene.shape[0]):\\n for y in range(mask_scene.shape[1]):\\n if mask_scene[x, y] == 0:\\n orig_scene[x, y, :] = 0\\n orig_scene_no_mask[x,y,:] = 0\\n if dilation:\\n if dialation_mask[x,y] == 0:\\n orig_scene[x, y, :] = 0\\n \\n return orig_scene, mask_scene, orig_scene_no_mask, dialation_mask\",\n \"def test_offcenter(self):\\n actual = cm.ring_mask((5, 5), 1, 2, center=(2, 3))\\n expected = np.array([[False, False, False, True, False],\\n [False, False, True, False, True],\\n [False, True, False, False, False],\\n [False, False, True, False, True],\\n [False, False, False, True, False]])\\n self.assertIsNone(np.testing.assert_array_equal(actual, expected))\",\n \"def highlight_available_v_fences(win, game):\\n #Check if player has remaining fences\\n player_turn = game.get_player_turn()\\n if game.get_pawn(player_turn).get_remaining_fences() == 0:\\n return\\n\\n board = game.get_board()\\n\\n #Set highlight color\\n if player_turn == 1:\\n color = LIGHTERRED\\n else:\\n color = LIGHTERBLUE\\n \\n for row in range(len(board)-2):\\n for col in range(len(board)-1):\\n #Highlight fence if no fence placed and does not interesect a horizontal fence. \\n if not board[row][col]['v'] and not board[row+1][col]['v'] and board[row+1][col]['h'] != \\\"Fence Continued\\\" and game.fair_play_check('v',(col,row)):\\n coords = board[row][col]['coord']\\n v_fence_coords = (coords[0]*SQUARESIZE+FENCEWIDTH*(coords[0]-1), coords[1]*(SQUARESIZE+FENCEWIDTH))\\n v_fence = pygame.Rect(v_fence_coords, (FENCEWIDTH,SQUARESIZE))\\n pygame.draw.rect(win, color, v_fence)\",\n \"def fill_single_world():\\n if not front_is_clear():\\n if not right_is_clear():\\n if not left_is_clear():\\n put_beeper()\",\n \"def nondetects(self, masked=False):\\r\\n grd = self.grd\\r\\n xnd = []\\r\\n ynd = []\\r\\n ncells = len(grd.cells['depth'])\\r\\n non_detects_i_tr = np.zeros(ncells, np.int32)\\r\\n if masked:\\r\\n not_flagged = np.where(self.rec_track.flagged==0)[0]\\r\\n rec_track = self.rec_track[not_flagged]\\r\\n rec_seg = self.make_segments(set_depth=True, \\r\\n input_rec_track=rec_track)\\r\\n else:\\r\\n rec_seg = self.rec_seg\\r\\n for nr, rseg in enumerate(rec_seg):\\r\\n seg = rec_seg[nr]\\r\\n dt = seg.dt\\r\\n if dt > dt_signal+1:\\r\\n t1 = seg.t1\\r\\n t2 = seg.t2\\r\\n nint = int(np.rint((t2-t1)/dt_signal)) - 1\\r\\n x1 = seg.x1\\r\\n x2 = seg.x2\\r\\n y1 = seg.y1\\r\\n y2 = seg.y2\\r\\n dx_nd = (x2 - x1)/float(nint+1)\\r\\n dy_nd = (y2 - y1)/float(nint+1)\\r\\n if nint < 120: # 10 minute cutoff for nondetect filling\\r\\n xint = [x1 + n*dx_nd for n in range(1,nint)]\\r\\n yint = [y1 + n*dy_nd for n in range(1,nint)]\\r\\n xnd = xnd + xint\\r\\n ynd = ynd + yint\\r\\n\\r\\n for nd in range(len(xnd)):\\r\\n xy = [xnd[nd], ynd[nd]]\\r\\n i = grd.select_cells_nearest(xy)\\r\\n if (i is not None) and (i >= 0):\\r\\n non_detects_i_tr[i] += 1\\r\\n\\r\\n return non_detects_i_tr\",\n \"def boundaries_free(*args):\\n return _ida_hexrays.boundaries_free(*args)\",\n \"def highlight_available_h_fences(win, game):\\n #Check if player has remaining fences\\n player_turn = game.get_player_turn()\\n if game.get_pawn(player_turn).get_remaining_fences() == 0:\\n return\\n\\n board = game.get_board()\\n \\n #Set highlight color\\n if player_turn == 1:\\n color = LIGHTERRED\\n else:\\n color = LIGHTERBLUE\\n \\n for row in range(len(board)-1):\\n for col in range(len(board)-2):\\n #Highlight fence if no fence placed and does not intersect a vertical fence\\n if not board[row][col]['h'] and not board[row][col+1]['h'] and board[row][col+1]['v'] != \\\"Fence Continued\\\" and game.fair_play_check('h',(col,row)):\\n coords = board[row][col]['coord']\\n h_fence_coords = (coords[0]*(SQUARESIZE+FENCEWIDTH), coords[1]*SQUARESIZE+FENCEWIDTH*(coords[1]-1))\\n h_fence = pygame.Rect(h_fence_coords, (SQUARESIZE,FENCEWIDTH))\\n pygame.draw.rect(win, color, h_fence)\",\n \"def set_fence_mode(self, on):\\r\\n return self._arm.set_fense_mode(on)\",\n \"def outside(self,region):\\n fs = FeatureSet()\\n for f in self:\\n if(f.isNotContainedWithin(region)):\\n fs.append(f)\\n return fs\",\n \"def filter_isolated_pixels(array):\\n filtered_array = np.copy(array)\\n id_regions, num_ids = ndimage.label(filtered_array,\\n structure=np.ones((3, 3)))\\n id_sizes = np.array(ndimage.sum(array, id_regions, range(num_ids+1)))\\n area_mask = (id_sizes == 1)\\n filtered_array[area_mask[id_regions]] = 0\\n return filtered_array\",\n \"def _do_fenced_code_blocks(self, text):\\r\\n return self._fenced_code_block_re.sub(self._fenced_code_block_sub, text)\",\n \"def make_partioned_regions(shape, alpha=1.0, max_regions=5, min_regions=2):\\n ring = np.array([[1,1,1],[1,0,1],[1,1,1]], dtype=np.int16)\\n adjacent = np.array([ # Diagonals don't count as adjacent\\n [-1,0,0,1],\\n [0,-1,1,0]], dtype=np.int16).T\\n nearby = np.meshgrid([-2,-1,0,1,2], [-2,-1,0,1,2])\\n\\n board = np.zeros(shape, dtype=np.int16)\\n perimeters = [{\\n (i, j) for i, j in zip(*np.nonzero(board == 0))\\n }]\\n exclusions = [set()]\\n while sum(len(p) for p in perimeters) > 0:\\n weights = np.array([len(p) for p in perimeters], dtype=float)\\n weights[0] = min(alpha, weights[0]) if len(weights) <= max_regions else 1e-10\\n if len(weights) <= min_regions:\\n weights[1:] = 1e-10\\n weights /= np.sum(weights)\\n k = get_rng().choice(len(perimeters), p=weights)\\n plist = list(perimeters[k])\\n i, j = plist[get_rng().choice(len(plist))]\\n perimeters[0].discard((i, j))\\n perimeters[k].discard((i, j))\\n if (i, j) in exclusions[k]:\\n continue\\n exclusions[0].add((i,j))\\n exclusions[k].add((i,j))\\n b = board[(i+nearby[0]) % shape[0], (j+nearby[1]) % shape[1]]\\n b[2,2] = k or -1\\n num_neighbors = signal.convolve2d(b != 0, ring, mode='valid')\\n num_foreign = signal.convolve2d((b > 0) & (b != k), ring, mode='valid')\\n if ((num_foreign > 0) & (num_neighbors > 2)).any() or num_foreign[1,1] > 0:\\n continue\\n # Add to the board\\n if k == 0:\\n k = len(perimeters)\\n perimeters.append(set())\\n exclusions.append(set())\\n board[i, j] = k\\n for i2, j2 in (adjacent + (i, j)) % shape:\\n if board[i2, j2] == 0:\\n perimeters[k].add((i2, j2))\\n return board\",\n \"def _masked_edge(var,xac):\\n\\n if np.any(xac>0):\\n ind_gap = (xac==np.nanmin(xac[xac>0]))\\n if ind_gap.size==var.size:\\n if ind_gap.shape!=var.shape:\\n ind_gap = ind_gap.transpose()\\n var[ind_gap] = np.nan\\n elif ind_gap.size==var.shape[1]:\\n var[:,ind_gap] = np.nan\\n if np.any(xac<0):\\n ind_gap = (xac==np.nanmax(xac[xac<0]))\\n if ind_gap.size==var.size:\\n if ind_gap.shape!=var.shape:\\n ind_gap = ind_gap.transpose()\\n var[ind_gap] = np.nan\\n elif ind_gap.size==var.shape[1]:\\n var[:,ind_gap] = np.nan\\n\\n return var\",\n \"def updraft_env_mask(tracer_2d, w_interp_2d, ql_2d, cb, ct, z_half, ql_tr = 1e-8):\\n updraft_mask = np.ones_like(tracer_2d) #mask = 1 -> False, mask = 0 True\\n tracer_mask = np.ones_like(tracer_2d)\\n w_mask = np.ones_like(tracer_2d)\\n ql_mask = np.ones_like(tracer_2d)\\n nxy = np.shape(tracer_2d)[0]\\n nz = np.shape(tracer_2d)[1]\\n\\n sigma_sum = 0.\\n z_ql = 0.\\n cloud_flag = False\\n if np.isnan(cb) == False and np.isnan(ct) == False:\\n z_ql = z_half[cb] + 0.25 * (z_half[ct] - z_half[cb])\\n cloud_flag = True\\n\\n print \\\"z_ql = \\\", z_ql\\n\\n tracer_mean = np.mean(tracer_2d, axis=0)\\n tracer_square_mean = np.mean(tracer_2d * tracer_2d, axis=0)\\n tracer_variance = tracer_square_mean - tracer_mean * tracer_mean\\n assert(tracer_variance.all() >= 0)\\n tracer_std = np.sqrt(tracer_variance)\\n\\n for k in range(nz):\\n sigma_sum += tracer_std[k]\\n sigma_min = sigma_sum/(k+1.0) * 0.05 # threshold from the paper\\n\\n for i in range(nxy):\\n if tracer_std[k] >= sigma_min:\\n if tracer_2d[i,k] - tracer_mean[k] >= tracer_std[k]:\\n updraft_mask[i,k] = 0\\n tracer_mask[i,k] = 0\\n # TODO - I think the paper condition should also include this\\n # But it's not done in Pycles\\n #else:\\n # if tracer_2d[i,k] - tracer_mean[k] >= sigma_min:\\n # updraft_mask[i,k] = 0\\n\\n if w_interp_2d[i,k] <= 0.:\\n updraft_mask[i,k] = 1\\n else:\\n w_mask[i,k] = 0\\n\\n if cloud_flag:\\n if z_half[k] >= z_ql and z_half[k] <= z_half[ct]:\\n if ql_2d[i,k] < ql_tr:\\n updraft_mask[i,k] = 1\\n else:\\n ql_mask[i,k] = 0\\n\\n env_mask = 1 - updraft_mask\\n\\n mask_dict = {}\\n mask_dict[\\\"updraft\\\"] = updraft_mask\\n mask_dict[\\\"env\\\"] = env_mask\\n mask_dict[\\\"tracer\\\"] = tracer_mask\\n mask_dict[\\\"w\\\"] = w_mask\\n mask_dict[\\\"ql\\\"] = ql_mask\\n\\n return mask_dict\",\n \"def create_soft_blocks(self, count):\\n while count > 0:\\n x = int(random() * self.map_size[0])\\n y = int(random() * self.map_size[1])\\n if self.is_filled(x, y):\\n continue\\n\\n self.create_soft_block_at(x, y)\\n count -= 1\",\n \"def __set_mask_regions(self):\\n self.bottom_clip = np.int32(np.int32([[[60,0], [1179,0], [1179,650], [60,650]]]))\\n self.roi_clip = np.int32(np.int32([[[640, 425], [1179,550], [979,719],\\n [299,719], [100, 550], [640, 425]]]))\",\n \"def mask(self):\\n\\n mask = np.zeros(shape=(self._info.height, self._info.width), dtype=np.uint8)\\n\\n self.draw(image=mask, color=constants.COLOR_WHITE_MONO)\\n\\n mask_with_border = np.pad(mask, 1, 'constant', constant_values=255)\\n\\n cv2.floodFill(image=mask,\\n mask=mask_with_border,\\n seedPoint=(int(self.middle_point[0]), int(self.middle_point[1])),\\n newVal=constants.COLOR_WHITE_MONO)\\n\\n return mask\",\n \"def regionstomask(in_regions, genome_len):\\n out_mask = np.zeros((2,genome_len)).astype(bool)\\n for region in in_regions:\\n out_mask[region[0],region[1]:region[2]+1] = True\\n return out_mask\",\n \"def __mask_region(self, img, vertices):\\n\\n mask = np.zeros_like(img) \\n if len(img.shape) > 2:\\n channel_count = img.shape[2] # i.e. 3 or 4 depending on your image\\n ignore_mask_color = (255,) * channel_count\\n else:\\n ignore_mask_color = 255\\n cv2.fillConvexPoly(mask, vertices, ignore_mask_color)\\n masked_image = cv2.bitwise_and(img, mask)\\n return masked_image\",\n \"def setDefensiveArea(self ,gameState): \\n mazeCentreX = (gameState.data.layout.width - 2) / 2\\n if not self.red:\\n mazeCentreX += 1\\n mazeCentreY = (gameState.data.layout.height - 2) / 2\\n\\n self.defenceRegion = []\\n for i in range(1, gameState.data.layout.height - 1):\\n if gameState.hasWall(mazeCentreX, i):\\n a = 0\\n \\n else:\\n self.defenceRegion.append((mazeCentreX, i))\\n\\n expectedSize = mazeCentreY\\n actualSize = len(self.defenceRegion)\\n\\n\\n for i in range(len(self .defenceRegion)):\\n if expectedSize > actualSize:\\n break\\n else:\\n self.defenceRegion.remove(self.defenceRegion[0])\\n self.defenceRegion.remove(self.defenceRegion[-1])\\n actualSize = len(self.defenceRegion)\\n\\n for i in range(len(self.defenceRegion)):\\n if len(self.defenceRegion) > 2:\\n self.defenceRegion.remove(self.defenceRegion[0])\\n self.defenceRegion.remove(self.defenceRegion[-1])\\n else:\\n break\",\n \"def geodesic_erosion(mask, kernel, n=3):\\n m = np.reshape(mask, [1, mask.shape[0] * mask.shape[1]])\\n mean = m.sum()/(mask.shape[0] * mask.shape[1])\\n ret, mask = cv2.threshold(mask, mean, 255, cv2.THRESH_BINARY)\\n\\n marker = util.bin_dilate(mask, kernel) # use dilated mask as marker\\n\\n last_marker = marker\\n curr_marker = marker\\n for N in range(n):\\n curr_marker = util.bin_erode(last_marker, kernel)\\n curr_marker = union(curr_marker, mask)\\n if not np.any(last_marker != curr_marker):\\n return curr_marker\\n last_marker = curr_marker\\n return curr_marker\",\n \"def _mask(self, map_):\\n return None\",\n \"def CausalSegmentMask(segment_ids, dtype):\\n\\n assert dtype.is_floating\\n # of shape [b, t, t].\\n segment_mask = tf.cast(\\n tf.not_equal(\\n tf.expand_dims(segment_ids, 2), tf.expand_dims(segment_ids, 1)),\\n dtype=dtype)\\n slen = tf.shape(segment_ids)[1]\\n causal_mask = 1 - tf.linalg.band_part(\\n tf.ones([slen, slen], dtype=dtype), -1, 0)\\n causal_mask = tf.expand_dims(causal_mask, 0)\\n combined_mask = tf.cast(causal_mask + segment_mask > 0.5, dtype)\\n min_value = GetDtypeMin(dtype)\\n return tf.expand_dims(combined_mask * min_value, 1)\",\n \"def proc_filled_polygon(self, tokens):\\n\\n return self._proc_polygon(tokens, filled=True)\",\n \"def mask_incoherent(self):\\n self.MaskPrefix = 'i' + self.MaskPrefix\\n print('Masking pixel values where .msk value is less than {0}...'.format(threshold))\\n for ig in self.Set:\\n igram = self.load_ma(ig)\\n mskFile = ig.Path[:-3] + 'msk'\\n coherence = roipy.tools.load_half(ig, 2, mskFile)\\n incoherent = ma.masked_less(coherence, self.Cothresh)\\n igram[incoherent.mask] = ma.masked\\n mskFile = self.MaskPrefix + 'Mask_' + ig.Name[:-4]\\n np.save(os.path.join(self.ProcDir, mskFile), igram.mask)\\n print(mskFile)\\n\\n print('Done')\",\n \"def remove_rain_norain_discontinuity(R):\\n R = R.copy()\\n zerovalue = np.nanmin(R)\\n threshold = np.nanmin(R[R > zerovalue])\\n R[R > zerovalue] -= threshold - zerovalue\\n R -= np.nanmin(R)\\n\\n return R\",\n \"def clean_area(screen,origin,width,height,color):\\r\\n ox,oy = origin\\r\\n points = [(ox,oy),(ox+width,oy),(ox+width,oy+height),(ox,oy+height),(ox,oy)]\\r\\n pygame.draw.polygon(screen, color, points, 0)\",\n \"def boundaries_erase(*args):\\n return _ida_hexrays.boundaries_erase(*args)\",\n \"def get_front_door_mask(self) -> np.array:\\n front_door_mask = self.boundary == 255\\n region = measure.regionprops(front_door_mask.astype(int))[0]\\n return np.array(region.bbox, dtype=int)\",\n \"def mask_ne(lonreg2, latreg2):\\n nearth = cfeature.NaturalEarthFeature(\\\"physical\\\", \\\"ocean\\\", \\\"50m\\\")\\n main_geom = [contour for contour in nearth.geometries()][0]\\n\\n mask = shapely.vectorized.contains(main_geom, lonreg2, latreg2)\\n m2 = np.where(((lonreg2 == -180.0) & (latreg2 > 71.5)), True, mask)\\n m2 = np.where(\\n ((lonreg2 == -180.0) & (latreg2 < 70.95) & (latreg2 > 68.96)), True, m2\\n )\\n m2 = np.where(((lonreg2 == 180.0) & (latreg2 > 71.5)), True, mask)\\n m2 = np.where(\\n ((lonreg2 == 180.0) & (latreg2 < 70.95) & (latreg2 > 68.96)), True, m2\\n )\\n # m2 = np.where(\\n # ((lonreg2 == 180.0) & (latreg2 > -75.0) & (latreg2 < 0)), True, m2\\n # )\\n m2 = np.where(((lonreg2 == -180.0) & (latreg2 < 65.33)), True, m2)\\n m2 = np.where(((lonreg2 == 180.0) & (latreg2 < 65.33)), True, m2)\\n\\n return ~m2\",\n \"def mask(self):\\n mask = np.zeros((self.height, self.width))\\n pts = [\\n np.array(anno).reshape(-1, 2).round().astype(int)\\n for anno in self.segmentation\\n ]\\n mask = cv2.fillPoly(mask, pts, 1)\\n return mask\",\n \"def create_hard_blocks(self):\\n for x in xrange(1, self.map_size[0], 2):\\n for y in xrange(1, self.map_size[1], 2):\\n self.create_hard_block_at(x, y)\",\n \"def _isolate(self, frame, landmarks, points):\\n region = np.array([(landmarks.part(point).x, landmarks.part(point).y) for point in points])\\n region = region.astype(np.int32)\\n # Applying a mask to get only the eye\\n height, width = frame.shape[:2]\\n black_frame = np.zeros((height, width), np.uint8)\\n mask = np.full((height, width), 255, np.uint8)\\n cv2.fillPoly(mask, [region], (0, 0, 0))\\n eye = cv2.bitwise_not(black_frame, frame.copy(), mask=mask)\\n # Cropping on the eye\\n margin = 5\\n min_x = np.min(region[:, 0]) - margin\\n max_x = np.max(region[:, 0]) + margin\\n min_y = np.min(region[:, 1]) - margin\\n max_y = np.max(region[:, 1]) + margin\\n self.frame = eye[min_y:max_y, min_x:max_x]\\n self.origin = (min_x, min_y)\\n height, width = self.frame.shape[:2]\\n self.center = (width / 2, height / 2)\",\n \"def region_of_interest(self,img):\\r\\n #defining a blank mask\\r\\n mask = np.zeros_like(img) \\r\\n #checking number of image channel(color/grayscale) and applying mask\\r\\n if len(img.shape) > 2:\\r\\n ignore_mask_color = (255,255,255)\\r\\n else:\\r\\n ignore_mask_color = 255\\r\\n #filling color to pixels inside the polygon \\r\\n cv2.fillPoly(mask, self.vertices_img, ignore_mask_color)\\r\\n #image where mask pixels are nonzero\\r\\n masked_image = cv2.bitwise_and(img, mask)\\r\\n #cv2.imshow('',masked_image)\\r\\n return masked_image\",\n \"def ocean_unmasked(res='4x5', debug=False):\\n\\n from .GEOSChem_bpch import get_LWI_map\\n if debug:\\n print(('ocean_mask called for: ', res))\\n\\n # Create a mask from land/water/ice indices\\n m = np.ma.masked_not_equal(get_LWI_map(res=res), 0)\\n if debug:\\n print((mask, mask.shape))\\n return m.mask\",\n \"def _region_mask(self, cs, all_regions, xctr, yctr, hwcs):\\n if not HAS_REGIONS:\\n return None\\n ctr_coord = ar.PixCoord(xctr, yctr)\\n mask = None\\n for reg_str in all_regions:\\n # read ds9 string into a region class\\n try:\\n with set_log_level('CRITICAL'):\\n frame_regions = ar.Regions.parse(reg_str, format='ds9')\\n except Exception as err:\\n log.debug(f'Region parser error: {err}')\\n continue\\n for fr in frame_regions:\\n if cs == 'wcs':\\n # convert to a pixel region first\\n try:\\n with set_log_level('CRITICAL'):\\n fr = fr.to_pixel(hwcs)\\n except Exception as err: # pragma: no cover\\n # error could be anything, since regions package\\n # is in early development state\\n log.debug(f'Region WCS conversion error: {err}')\\n continue\\n\\n # check if cursor is contained in a region\\n # in any frame\\n with set_log_level('CRITICAL'):\\n contained = fr.contains(ctr_coord)\\n if hasattr(contained, '__len__'):\\n # PolygonPixelRegion returns an array, currently\\n # (regions v0.4)\\n contained = contained[0]\\n\\n if contained:\\n # get mask from first matching region\\n try:\\n with set_log_level('CRITICAL'):\\n mask = fr.to_mask()\\n except Exception as err: # pragma: no cover\\n # error could be anything, since regions package\\n # is in early development state\\n log.debug(f'Region mask error: {err}')\\n continue\\n else:\\n log.info(f'Contained in {type(fr).__name__}')\\n break\\n if mask is not None:\\n break\\n\\n # reset active frame\\n return mask\",\n \"def clean_mask(mask, background=0):\\n kernels = [\\n np.array([[ 1, -1, -1], [-1, 1, -1], [-1, -1, -1]]), # top left standalone pixel\\n np.array([[-1, -1, 1], [-1, 1, -1], [-1, -1, -1]]), # top right standalone pixel\\n np.array([[-1, -1, -1], [-1, 1, -1], [ 1, -1, -1]]), # bottom left standalone pixel\\n np.array([[-1, -1, -1], [-1, 1, -1], [-1, -1, 1]]) # bottom right standalone pixel\\n ]\\n\\n proc_masks = [cv2.morphologyEx(mask, cv2.MORPH_HITMISS, kernel).astype(np.bool) for kernel in kernels]\\n\\n for proc_mask in proc_masks:\\n mask[proc_mask] = background\\n return mask\",\n \"def segment_region_of_interest(image):\\n binary = image < 604\\n cleared = clear_border(binary)\\n\\n label_image = label(cleared)\\n\\n areas = [r.area for r in regionprops(label_image)]\\n areas.sort()\\n if len(areas) > 2:\\n for region in regionprops(label_image):\\n if region.area < areas[-2]:\\n for coordinates in region.coords:\\n label_image[coordinates[0], coordinates[1]] = 0\\n\\n binary = label_image > 0\\n\\n selem = disk(2)\\n binary = binary_erosion(binary, selem)\\n\\n selem = disk(10)\\n binary = binary_closing(binary, selem)\\n\\n edges = roberts(binary)\\n binary = scipy.ndimage.binary_fill_holes(edges)\\n\\n get_high_vals = binary == 0\\n image[get_high_vals] = 0\\n\\n return image\",\n \"def sense_landmarks(state, field_map, max_observations):\\n\\n assert isinstance(state, np.ndarray)\\n assert isinstance(field_map, Landscape)\\n\\n assert state.shape == (3,)\\n\\n M = field_map.num_landmarks\\n #print(M, field_map.landmarks.shape)\\n noise_free_observations_list = list()\\n for k in range(M):\\n noise_free_observations_list.append(get_observation(state, field_map, k))\\n noise_free_observation_tuples = [(x[0], np.abs(x[1]), int(x[2])) for x in noise_free_observations_list]\\n\\n dtype = [('range', float), ('bearing', float), ('lm_id', int)]\\n noise_free_observations = np.array(noise_free_observations_list)\\n noise_free_observation_tuples = np.array(noise_free_observation_tuples, dtype=dtype)\\n\\n ii = np.argsort(noise_free_observation_tuples, order='bearing')\\n noise_free_observations = noise_free_observations[ii]\\n noise_free_observations[:, 2] = noise_free_observations[:, 2].astype(int)\\n\\n c1 = noise_free_observations[:, 1] > -np.pi / 2.\\n c2 = noise_free_observations[:, 1] < np.pi / 2.\\n ii = np.nonzero((c1 & c2))[0]\\n\\n if ii.size <= max_observations:\\n return noise_free_observations[ii]\\n else:\\n return noise_free_observations[:max_observations]\",\n \"def __generate_mask(self):\\n mask = np.concatenate([np.ones(len(self.fixed[0])),\\n np.zeros(self.num_points),\\n np.ones(len(self.fixed[1]))])\\n return mask\",\n \"def remove_shadow(patch):\\r\\n lt = not np.any(patch[0,0])\\r\\n rt = not np.any(patch[0,-1])\\r\\n lb = not np.any(patch[-1,0])\\r\\n rb = not np.any(patch[-1,-1])\\r\\n\\r\\n return lt or rt or lb or rb\",\n \"def create_geofence(self):\\n\\t\\tring = ogr.Geometry(ogr.wkbLinearRing)\\n\\t\\tring.AddPoint(*self.north_coords)\\n\\t\\tring.AddPoint(*self.northeast_coords)\\n\\t\\tring.AddPoint(*self.east_coords)\\n\\t\\tring.AddPoint(*self.southeast_coords)\\n\\t\\tring.AddPoint(*self.south_coords)\\n\\t\\tring.AddPoint(*self.southwest_coords)\\n\\t\\tring.AddPoint(*self.west_coords)\\n\\t\\tring.AddPoint(*self.northwest_coords)\\n\\t\\tring.AddPoint(*self.north_coords)\\n\\t\\tself.polygon.AddGeometry(ring)\",\n \"def __iteratively_retain(\\n self,\\n orf_regions: List[Tuple[int, int]]) -> List[Tuple[int, int]]:\\n\\n ret = []\\n\\n arr = np.zeros((len(self.seq), ))\\n\\n for start, end in orf_regions:\\n ret.append((start, end))\\n arr[start-1:end] = 1\\n orf_coverage = np.sum(arr) / len(arr)\\n if orf_coverage > self.min_orf_coverage:\\n break\\n\\n return ret\",\n \"def contextualcull(cnts):\\n temp = []\\n actualout = []\\n indicesused = []\\n for cnt in cnts:\\n if cnt.area > CULL_MINIMUMS[cnt.spatialindex]:\\n temp.append(cnt)\\n if cnt.spatialindex not in indicesused:\\n indicesused.append(cnt.spatialindex)\\n if PRIORITIZE_FASTEST:\\n for sindex in indicesused: #filter down to the fastest contour.\\n _allatthisindex = [x for x in temp if x == sindex]\\n highest = _allatthisindex.sort(key=lambda y: y.spd, reverse=False)[0]\\n actualout.append(highest)\\n else:\\n actualout = temp\\n print 'Contours after cull: ', len(actualout)\\n return actualout\",\n \"def sanitize_mask(orig_x, orig_y, mask):\\n contours, hierarchy = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)\\n\\n # Draw contours:\\n cv2.drawContours(mask, contours, 0, (0, 255, 0), 2)\\n # Calculate image moments of the detected contour\\n num_objects = (len(contours))\\n #threshold\\n threshold = 3\\n\\n center_list = []\\n # print(num_objects)\\n if num_objects > 1:\\n for item in range(num_objects):\\n M = cv2.moments(contours[item])\\n try:\\n center_x = round(M['m10'] / M['m00'])\\n center_y = round(M['m01'] / M['m00'])\\n center_list.append([center_y , center_x ])\\n except:\\n pass\\n\\n # initialize retmask\\n retmask = mask\\n if num_objects > 1:\\n for x, y in center_list:\\n if orig_x - threshold <= x <= orig_x + threshold and orig_y - threshold <= y <= orig_y + threshold:\\n pass\\n else:\\n def dfs_removal(px , py, mask):\\n R = len(mask)\\n C = len(mask[0])\\n if mask[px][py ] != 255: \\n return\\n mask[px][py] = 0\\n if 0 <= px - 1 and mask[px - 1][py ] == 255: dfs_removal(px - 1 , py , mask)\\n if px + 1 < R and mask[px + 1][py ] == 255: dfs_removal(px + 1 , py , mask)\\n if 0 <= py - 1 and mask[px][py - 1] == 255: dfs_removal(px, py -1 , mask)\\n if py + 1 < C and mask[px][py + 1] == 255: dfs_removal(px, py + 1 , mask)\\n\\n dfs_removal(x,y, mask)\\n\\n return retmask\",\n \"def _create_observation_mask(self):\\n\\n\\n if self.BLUE_PARTIAL:\\n centers, radii = [], []\\n for agent in self._team_blue:\\n if not agent.isAlive: continue\\n centers.append(agent.get_loc())\\n radii.append(agent.range)\\n self._blue_mask = self._create_vision_mask(centers, radii)\\n if self.TEAM_MEMORY == \\\"fog\\\":\\n self.blue_memory = np.logical_and(self.blue_memory, self._blue_mask)\\n else:\\n self._blue_mask = np.zeros_like(self._static_map, dtype=bool)\\n\\n if self.RED_PARTIAL:\\n centers, radii = [], []\\n for agent in self._team_red:\\n if not agent.isAlive: continue\\n centers.append(agent.get_loc())\\n radii.append(agent.range)\\n self._red_mask = self._create_vision_mask(centers, radii)\\n if self.TEAM_MEMORY == \\\"fog\\\":\\n self.red_memory = np.logical_and(self.red_memory, self._red_mask)\\n else:\\n self._red_mask = np.zeros_like(self._static_map, dtype=bool)\",\n \"def ice_unmasked(res='4x5', debug=False):\\n # Create a np.ma mask\\n m = np.logical_not((land_unmasked(res)*ocean_unmasked(res)))\\n if debug:\\n print((mask, mask.shape))\\n return m\",\n \"def spectrum_regions(x_on,\\n y_on,\\n r_on,\\n x_fov,\\n y_fov,\\n r_fov,\\n exclusion,\\n outfile,\\n min_on_distance):\\n from astropy.io import fits\\n from gammapy.background import ReflectedRegionMaker\\n\\n if exclusion:\\n log.info('Reading {0}'.format(exclusion))\\n exclusion = fits.open(exclusion)[0]\\n else:\\n # log.info('No exclusion mask used.')\\n # TODO: make this work without exclusion mask\\n log.error(\\\"Currently an exclusion mask is required\\\")\\n exit(-1)\\n\\n fov = dict(x=x_fov, y=y_fov, r=r_fov)\\n rr_maker = ReflectedRegionMaker(exclusion=exclusion,\\n fov=fov)\\n source = dict(x_on=x_on, y_on=y_on, r_on=r_on)\\n rr_maker.compute(**source)\\n\\n log.info('Writing {0}'.format(outfile))\\n rr_maker.write_off_regions(outfile)\",\n \"def test_degrade_widemask_or(self):\\n\\n nside_coverage = 32\\n nside_map = 256\\n nside_map2 = 64\\n sparse_map = healsparse.HealSparseMap.make_empty(nside_coverage, nside_map,\\n WIDE_MASK, wide_mask_maxbits=7)\\n sparse_map_or = healsparse.HealSparseMap.make_empty(nside_coverage, nside_map2,\\n WIDE_MASK, wide_mask_maxbits=7)\\n # Fill some pixels in the \\\"high-resolution\\\" map\\n pixel = np.arange(4000, 8000)\\n sparse_map.set_bits_pix(pixel, [4])\\n\\n # Check which pixels will be full in the \\\"low-resolution\\\" map and fill them\\n pixel2 = np.unique(np.right_shift(pixel, healsparse.utils._compute_bitshift(nside_map2, nside_map)))\\n sparse_map_or.set_bits_pix(pixel2, [4])\\n\\n # Degrade with or\\n sparse_map_test = sparse_map.degrade(nside_map2, reduction='or')\\n\\n # Check the results\\n testing.assert_almost_equal(sparse_map_or._sparse_map, sparse_map_test._sparse_map)\\n\\n # Repeat for maxbits > 8\\n sparse_map = healsparse.HealSparseMap.make_empty(nside_coverage, nside_map,\\n WIDE_MASK, wide_mask_maxbits=16)\\n sparse_map_or = healsparse.HealSparseMap.make_empty(nside_coverage, nside_map2,\\n WIDE_MASK, wide_mask_maxbits=16)\\n # Fill some pixels in the \\\"high-resolution\\\" map\\n pixel = np.arange(0, 1024)\\n pixel = np.concatenate([pixel[:512], pixel[512::3]]).ravel()\\n sparse_map.set_bits_pix(pixel, [4, 12])\\n sparse_map.clear_bits_pix(pixel[:16], [4]) # set low value in the first pixel\\n\\n # Check which pixels will be full in the \\\"low-resolution\\\" map and fill them\\n # Note that we are filling more than the ones that are going to be True\\n # since we want to preserve the coverage_map\\n pixel2_all = np.unique(np.right_shift(pixel,\\n healsparse.utils._compute_bitshift(nside_map2, nside_map)))\\n sparse_map_or.set_bits_pix(pixel2_all, [4, 12])\\n\\n # Get the pixel number of the bad pixels\\n pixel2_bad = np.array([0])\\n sparse_map_or.clear_bits_pix(pixel2_bad, [4]) # set low value in the first pixel\\n\\n # Degrade with or\\n sparse_map_test = sparse_map.degrade(nside_map2, reduction='or')\\n\\n # Check the results\\n testing.assert_almost_equal(sparse_map_test._sparse_map, sparse_map_or._sparse_map)\\n\\n # Test degrade-on-read\\n self.test_dir = tempfile.mkdtemp(dir='./', prefix='TestHealSparse-')\\n\\n fname = os.path.join(self.test_dir, 'test_wide_degrade.hs')\\n sparse_map.write(fname)\\n\\n sparse_map_test2 = healsparse.HealSparseMap.read(fname, degrade_nside=nside_map2, reduction='or')\\n testing.assert_almost_equal(sparse_map_test2._sparse_map, sparse_map_or._sparse_map)\",\n \"def _offset_region(all_polygons, bboxes,\\n left, bottom, right, top,\\n distance = 5,\\n join_first = True,\\n precision = 1e-4,\\n join = 'miter',\\n tolerance = 2):\\n\\n # Mark out a region slightly larger than the final desired region\\n d = distance*1.01\\n\\n polygons_to_offset = _crop_edge_polygons(all_polygons, bboxes, left-d,\\n bottom-d, right+d, top+d,\\n precision = precision)\\n\\n # Offset the resulting cropped polygons and recrop to final desired size\\n polygons_offset = clipper.offset(polygons_to_offset, distance, join,\\n tolerance, 1/precision, int(join_first))\\n polygons_offset_cropped = _crop_region(polygons_offset, left, bottom,\\n right, top, precision = precision)\\n\\n return polygons_offset_cropped\",\n \"def __trim(\\n self,\\n orf_regions: List[Tuple[int, int]]) -> List[Tuple[int, int]]:\\n\\n ret = []\\n\\n for start, end in orf_regions:\\n if start == 1:\\n new_start = start # Trust the model prediction\\n else:\\n new_start = self.__find_start_codon(start, end)\\n ret.append((new_start, end))\\n\\n return ret\",\n \"def as_boolean_mask(self):\\n bbox = self.bbox()\\n zs = np.unique([c.image_z_position for c in self.contours])\\n z_to_index = dict(zip(zs,range(len(zs))))\\n\\n # Get dimensions, initialize mask.\\n nx,ny = np.diff(bbox[:2], axis=1).astype(int) + 1\\n nx = int(nx); ny = int(ny)\\n nz = int(zs.shape[0])\\n mask = np.zeros((nx,ny,nz), dtype=np.bool)\\n\\n # We check if these points are enclosed within each contour \\n # for a given slice. `test_points` is a list of image coordinate \\n # points, offset by the bounding box.\\n test_points = bbox[:2,0] + np.c_[ np.where(~mask[:,:,0]) ]\\n\\n # First we \\\"turn on\\\" pixels enclosed by inclusion contours.\\n for contour in self.contours:\\n if contour.inclusion:\\n zi = z_to_index[contour.image_z_position]\\n contour_matrix = contour.to_matrix()[:,:2]\\n\\n # Turn the contour closed if it's not.\\n if (contour_matrix[0] != contour_matrix[-1]).all():\\n contour_matrix = np.append(contour_matrix,\\n contour_matrix[0].reshape(1,2),\\n axis=0)\\n\\n # Create path object and test all pixels\\n # within the contour's bounding box.\\n path = mplpath.Path(contour_matrix, closed=True)\\n contains_pts = path.contains_points(test_points)\\n mask[:,:,zi] = contains_pts.reshape(mask.shape[:2])\\n\\n # Second, we \\\"turn off\\\" pixels enclosed by exclusion contours.\\n for contour in self.contours:\\n if not contour.inclusion:\\n zi = z_to_index[contour.image_z_position]\\n contour_matrix = contour.to_matrix()[:,:2]\\n\\n # Turn the contour closed if it's not.\\n if (contour_matrix[0] != contour_matrix[-1]).all():\\n contour_matrix = np.append(contour_matrix,\\n contour_matrix[0].reshape(1,2),\\n axis=0)\\n\\n path = mplpath.Path(contour_matrix, closed=True)\\n not_contains_pts = ~path.contains_points(test_points)\\n not_contains_pts = not_contains_pts.reshape(mask.shape[:2])\\n mask[:,:,zi] = np.logical_and(mask[:,:,zi], not_contains_pts)\\n\\n # The first and second axes have to \\n # be swapped because of the reshape.\\n return mask.swapaxes(0,1), bbox[[1,0,2]]\",\n \"def build_block_cross(self):\\n from ambry.geo.util import find_geo_containment, find_containment\\n from geoid import civick \\n\\n lr = self.init_log_rate(3000)\\n\\n def gen_bound():\\n \\n boundaries = self.library.dep('blockgroups').partition\\n\\n # Note, ogc_fid is the primary key. The id column is created by the shapefile. \\n for i,boundary in enumerate(boundaries.query(\\n \\\"SELECT AsText(geometry) AS wkt, gvid FROM blockgroups\\\")):\\n lr('Load rtree')\\n \\n yield i, boundary['wkt'] , boundary['gvid'] \\n \\n def gen_points():\\n\\n for row in self.partitions.find(table = 'facilities_addresses').rows:\\n if row['longitude'] and row['latitude']:\\n yield (row['longitude'], row['latitude']), row['facilities_id']\\n\\n\\n p = self.partitions.find_or_new(table='facilities_geoids')\\n p.clean()\\n\\n with p.inserter() as ins:\\n for point, point_o, cntr_geo, cntr_o in find_containment(gen_bound(),gen_points()):\\n\\n blockgroup_gvid = civick.Blockgroup.parse(cntr_o)\\n tract_gvid = blockgroup_gvid.convert(civick.Tract)\\n county_gvid = blockgroup_gvid.convert(civick.County)\\n \\n ins.insert(dict(facilities_id = point_o, \\n blockgroup_gvid = str(blockgroup_gvid),\\n tract_gvid = str(tract_gvid),\\n county_gvid = str(county_gvid)\\n ))\\n \\n lr('Marking point containment')\",\n \"def create_region_mask(latitude_array, target_shape, lat_bounds):\\n\\n target_ndim = len(target_shape)\\n\\n southern_lat, northern_lat = lat_bounds\\n mask_array = numpy.where((latitude_array >= southern_lat) & (latitude_array < northern_lat), False, True)\\n\\n mask = uconv.broadcast_array(mask_array, [target_ndim - 2, target_ndim - 1], target_shape)\\n assert mask.shape == target_shape \\n\\n return mask\",\n \"def RemovePolygonHoles_management(in_fc, threshold=0.0):\\n desc = arcpy.Describe(in_fc)\\n if desc.dataType != \\\"FeatureClass\\\" and desc.dataType != \\\"ShapeFile\\\":\\n print(\\\"Invalid data type. The input is supposed to be a Polygon FeatureClass or Shapefile.\\\")\\n return\\n else:\\n if desc.shapeType != \\\"Polygon\\\":\\n print(\\\"The input is supposed to be a Polygon FeatureClass or Shapefile.\\\")\\n return\\n if threshold < 0.0:\\n threshold = 0.0\\n with arcpy.da.UpdateCursor(in_fc, [\\\"SHAPE@\\\"]) as updateCursor:\\n for updateRow in updateCursor:\\n shape = updateRow[0]\\n new_shape = arcpy.Array()\\n for part in shape:\\n new_part = arcpy.Array()\\n if threshold > 0:\\n # find None point in shape part\\n # in arcpy module, a None point is used to seperate exterior and interior vertices\\n null_point_index = []\\n for i in range(len(part)):\\n if part[i] is None:\\n null_point_index.append(i)\\n # if interior vertices exist, create polygons and compare polygon shape area to given threshold\\n # if larger, keep vertices, else, dismiss them\\n if len(null_point_index) > 0:\\n for k in range(0, null_point_index[0]):\\n new_part.add(part[k])\\n for i in range(len(null_point_index)):\\n pointArray = arcpy.Array()\\n # determine if the None point is the last one\\n if i+1 < len(null_point_index):\\n for j in range(null_point_index[i] + 1, null_point_index[i+1]):\\n pointArray.add(part[j])\\n else:\\n for j in range(null_point_index[i] + 1, len(part)):\\n pointArray.add(part[j])\\n # create a polygon to check shape area against the given threshold\\n inner_poly = arcpy.Polygon(pointArray)\\n # if larger than threshold, then add to the new part Array\\n if inner_poly.area > threshold:\\n if i+1 < len(null_point_index):\\n for k in range(null_point_index[i], null_point_index[i+1]):\\n new_part.add(part[k])\\n else:\\n for k in range(null_point_index[i], len(part)):\\n new_part.add(part[k])\\n new_shape.add(new_part)\\n # if interior does not exist, add the whole part\\n else:\\n new_shape.add(part)\\n else:\\n # get the first None point index\\n first_null_point_index = 0\\n for i in range(len(part)):\\n if part[i] is None:\\n first_null_point_index = i\\n break\\n if first_null_point_index == 0:\\n new_shape.add(part)\\n else:\\n for j in range(first_null_point_index):\\n new_part.add(part[j])\\n new_shape.add(new_part)\\n if len(new_shape) > 0:\\n new_poly = arcpy.Polygon(new_shape)\\n updateRow[0] = new_poly\\n updateCursor.updateRow(updateRow)\",\n \"def create_mask(frame):\\n \\n # detect ridges\\n ridges = enhance_ridges(frame)\\n\\n # threshold ridge image\\n thresh = filters.threshold_otsu(ridges)\\n thresh_factor = 1.1\\n prominent_ridges = ridges > thresh_factor*thresh\\n prominent_ridges = morphology.remove_small_objects(prominent_ridges, min_size=128)\\n\\n # the mask contains the prominent ridges\\n mask = morphology.convex_hull_image(prominent_ridges)\\n mask = morphology.binary_erosion(mask, disk(10))\\n return mask\",\n \"def unmask(self, near_x, near_y, radius=BRIGHTEN_RECT_TEMP, is_lighter=False):\\n #self._actual_unmask(self.last_brighten, self.masked_image, radius=radius)\\n \\n brighten_rect = pygame.draw.circle(self.image, (255, 255,0), (near_x, near_y), radius/2)\\n \\n if is_lighter:\\n brighten_rect = pygame.draw.circle(self.image, (50, 0, 0), (near_x, near_y), 40)\\n brighten_rect = pygame.draw.circle(self.image, (255, 255,0), (near_x, near_y), 38)\\n \\n self.game.dirty_rects.append(brighten_rect)\\n \\n self.last_brighten = (near_x, near_y)\",\n \"def masktoregions(in_mask):\\n regions = []\\n for i in [0,1]: # do the thing for the first and second strands\\n current_strand = in_mask[i].copy().astype(float)\\n current_strand[-1] = np.nan # set final position to np.nan to avoid overlap issues\\n transitions = current_strand - np.roll(current_strand,1)\\n true_start = np.where(transitions == 1)[0]\\n true_end = np.where(transitions == -1)[0] - 1\\n if current_strand[0] == 1: # if starts on True, add True start to front end\\n true_start = np.r_[0,true_start]\\n if in_mask[i][-1] == True: # if ends on True, add True end to back end\\n true_end = np.r_[true_end, len(current_strand)-1]\\n if in_mask[i][-2] == False: # if the one before is False, it's a single point True\\n true_start = np.r_[true_start,len(current_strand)-1]\\n if np.all(in_mask[i][-2:] == [True, False]):\\n true_end = np.r_[true_end, len(current_strand)-2]\\n regions.append(np.asarray([np.zeros(len(true_start))+i,true_start,true_end]).T)\\n out_regions = np.concatenate(regions,axis=0).astype(int)\\n return out_regions\",\n \"def cmask(self):\\n mask = np.zeros(18)\\n if 'full' in self.CONS: mask[:] = 1\\n if 'f0' in self.CONS: mask[0] = 1\\n if 'f1' in self.CONS: mask[1:4] = 1\\n if 'f2' in self.CONS: mask[4:10] = 1\\n if 'vx' in self.CONS: mask[10] = 1\\n if 'vy' in self.CONS: mask[11] = 1\\n if 'vz' in self.CONS: mask[12] = 1\\n if 'TG' in self.CONS: mask[13:18] = 1\\n return mask>0\",\n \"def GetCoastGrids(LandMask):\\n \\n \\\"\\\"\\\"\\n Define a coastline map. This map will be set to 1 on all coast cells.\\n \\\"\\\"\\\"\\n \\n \\n CoastlineMap = np.zeros((LandMask.shape[0], LandMask.shape[1]))\\n \\n \\\"\\\"\\\"\\n We will use a nested loop to loop through all cells of the Landmask cell. What this loop basically does is,\\n when a cell has a value of 1 (land), it will make all surrounding cells 1, so we create kind of an extra line of \\n grids around the landmask. In the end we will substract the landmask from the mask which is created by the nested loop, \\n which result in only a mask with the coast grids. Notice, that when we're in the corner, upper, side, or lower row, and we\\n meet a land cell, we should not make all surrounding cells 1. For example, we the lower left corner is a land grid, you should only make the inner cells 1. \\n \\\"\\\"\\\"\\n \\n for i in range(LandMask.shape[0]-1):\\n for j in range(LandMask.shape[1]-1):\\n \\n\\n \\\"\\\"\\\"\\n We have nine if statements, four for the corners, four for the sides and one for the middle\\n of the landmask. \\n \\\"\\\"\\\"\\n\\n if i == 0 and j == 0: #upper left corner\\n \\n if LandMask[i,j] == 1:\\n \\n CoastlineMap[i,j] = 1\\n CoastlineMap[i,j+1] = 1\\n \\n CoastlineMap[i+1,j] = 1 \\n CoastlineMap[i+1, j+1] = 1\\n \\n \\n elif i == 0 and j != 0 and j != LandMask.shape[1]-1: #upper row\\n \\n if LandMask[i,j] == 1:\\n \\n CoastlineMap[i,j] = 1\\n CoastlineMap[i,j-1] = 1\\n CoastlineMap[i,j+1] = 1\\n \\n CoastlineMap[i+1, j] = 1\\n CoastlineMap[i+1,j-1] = 1\\n CoastlineMap[i+1,j+1] = 1\\n \\n \\n elif i == 0 and j == LandMask.shape[1]-1: #upper right corner\\n \\n if LandMask[i,j] == 1:\\n \\n CoastlineMap[i,j] = 1\\n CoastlineMap[i,j-1] = 1\\n \\n CoastlineMap[i+1,j] = 1 \\n CoastlineMap[i+1, j-1] = 1\\n \\n elif i != 0 and i != LandMask.shape[0]-1 and j == LandMask.shape[1]-1: #right row\\n \\n if LandMask[i,j] == 1:\\n \\n CoastlineMap[i,j] = 1\\n CoastlineMap[i+1,j] = 1\\n CoastlineMap[i-1,j] = 1\\n \\n CoastlineMap[i, j-1] = 1\\n CoastlineMap[i+1,j-1] = 1\\n CoastlineMap[i-1,j-1] = 1\\n \\n elif i == LandMask.shape[0]-1 and j == LandMask.shape[1]-1: #lower right corner\\n \\n if LandMask[i,j] == 1:\\n \\n CoastlineMap[i,j] = 1\\n CoastlineMap[i,j-1] = 1\\n \\n CoastlineMap[i-1,j] = 1 \\n CoastlineMap[i-1, j-1] = 1\\n \\n elif i == LandMask.shape[0]-1 and j != 0 and j != LandMask.shape[1]-1: #lower row\\n \\n if LandMask[i,j] == 1:\\n \\n CoastlineMap[i,j] = 1\\n CoastlineMap[i,j-1] = 1\\n CoastlineMap[i,j+1] = 1\\n \\n CoastlineMap[i-1, j] = 1\\n CoastlineMap[i-1,j-1] = 1\\n CoastlineMap[i-1,j+1] = 1\\n \\n \\n elif i == LandMask.shape[0]-1 and j == 0: #lower left corner\\n \\n if LandMask[i,j] == 1:\\n \\n CoastlineMap[i,j] = 1\\n CoastlineMap[i,j+1] = 1\\n \\n CoastlineMap[i+1,j] = 1 \\n CoastlineMap[i+1, j+1] = 1\\n \\n elif i != 0 and i != LandMask.shape[0]-1 and j == 0: #left row\\n \\n if LandMask[i,j] == 1:\\n \\n CoastlineMap[i,j] = 1\\n CoastlineMap[i+1,j] = 1\\n CoastlineMap[i-1,j] = 1\\n \\n CoastlineMap[i, j+1] = 1\\n CoastlineMap[i+1,j+1] = 1\\n CoastlineMap[i-1,j+1] = 1\\n \\n else:\\n \\n if LandMask[i,j] == 1:\\n \\n CoastlineMap[i,j] = 1 #middle\\n CoastlineMap[i+1,j] = 1#lowermiddle\\n CoastlineMap[i-1,j] = 1#uppermiddle\\n \\n CoastlineMap[i+1, j-1] = 1\\n CoastlineMap[i-1, j-1] = 1\\n CoastlineMap[i, j-1] =1\\n \\n CoastlineMap[i+1, j+1] = 1\\n CoastlineMap[i-1, j+1] = 1\\n CoastlineMap[i, j+1] = 1\\n \\n \\n \\n \\\"\\\"\\\"\\n Here we substract the landmaks from the coastline mask, resulting in only\\n the coastline. \\n \\\"\\\"\\\"\\n \\n \\n Coastgrids = CoastlineMap - LandMask\\n \\n return Coastgrids, CoastlineMap\",\n \"def mask_img_region(self, image, coordinate_list):\\n \\n \\n # Mask to locate cropping region (CR)\\n mask = np.ones((image.shape),dtype=np.uint8)\\n mask.fill(255)\\n \\n # Mark the coorinate region as black\\n masked_image = cv2.fillPoly(mask, np.array([coordinate_list], dtype=np.int32),0)\\n \\n # Extract coorinate region from original image and rest is white \\n cropped = cv2.bitwise_or(image, masked_image)\\n \\n return cropped\",\n \"def opencv_watershed(masked, mask) -> JSON_TYPE:\\n # For code and detailed explanation see:\\n # http://datahacker.rs/007-opencv-projects-image-segmentation-with-watershed-algorithm/\\n threshold: int = 30\\n gray = cv2.cvtColor(masked, cv2.COLOR_RGB2GRAY)\\n ret, thresh_img = cv2.threshold(gray, threshold, 255, cv2.THRESH_BINARY)\\n # Noise removal\\n kernel = np.ones((3), np.uint8)\\n opening_img = cv2.morphologyEx(thresh_img, cv2.MORPH_OPEN, kernel, iterations=9)\\n # Noise removal\\n closing_img = cv2.morphologyEx(thresh_img, cv2.MORPH_CLOSE, kernel, iterations=4)\\n dist_transform = cv2.distanceTransform(255 - closing_img, cv2.DIST_L2, 3)\\n local_max_location = peak_local_max(dist_transform, min_distance=1, indices=True)\\n\\n n_increases: int = 0\\n while local_max_location.shape[0] < 30 and n_increases < 15:\\n threshold += 20\\n ret, thresh_img = cv2.threshold(gray, threshold, 255, cv2.THRESH_BINARY)\\n # Noise removal\\n kernel = np.ones((3), np.uint8)\\n opening_img = cv2.morphologyEx(thresh_img, cv2.MORPH_OPEN, kernel, iterations=9)\\n # Noise removal\\n closing_img = cv2.morphologyEx(thresh_img, cv2.MORPH_CLOSE, kernel, iterations=4)\\n dist_transform = cv2.distanceTransform(255 - closing_img, cv2.DIST_L2, 3)\\n local_max_location = peak_local_max(dist_transform, min_distance=1, indices=True)\\n n_increases += 1\\n # Reset threshold\\n threshold = 30\\n\\n num_clusters: int = 30\\n if n_increases >= 15:\\n num_clusters = local_max_location.shape[0]\\n kmeans = KMeans(n_clusters=num_clusters)\\n # If local_max_location size is 0, return 0 predictions\\n if not local_max_location.size:\\n return {\\n \\\"count\\\": 0\\n }\\n kmeans.fit(local_max_location)\\n local_max_location = kmeans.cluster_centers_.copy()\\n # Kmeans is returning a float data type so we need to convert it to an int. \\n local_max_location = local_max_location.astype(int)\\n dist_transform_copy = dist_transform.copy()\\n for i in range(local_max_location.shape[0]):\\n cv2.circle(dist_transform_copy, (local_max_location[i][1], local_max_location[i][0]), 5, 255)\\n # markers = np.zeros_like(dist_transform)\\n ret, sure = cv2.threshold(dist_transform, 0.01*dist_transform.max(), 255, 0)\\n sure = np.uint8(sure)\\n ret, markers = cv2.connectedComponents(sure)\\n labels = np.arange(kmeans.n_clusters)\\n markers[local_max_location[:,0], local_max_location[:,1]] = labels + 1\\n # Convert all local markers to an integer. This because cluster centers will be float numbers. \\n markers = markers.astype(int)\\n markers_copy = markers.copy()\\n index_non_zero_markers = np.argwhere(markers != 0)\\n markers_copy = markers_copy.astype(np.uint8)\\n font = cv2.FONT_HERSHEY_SIMPLEX\\n for i in range(index_non_zero_markers.shape[0]):\\n string_text = str(markers[index_non_zero_markers[i][0], index_non_zero_markers[i][1]])\\n cv2.putText(markers_copy, string_text, (index_non_zero_markers[i][1], index_non_zero_markers[i][0]), font, 1, 255)\\n markers = markers.astype(np.int32)\\n segmented = cv2.watershed(masked, markers)\\n count_segments(markers)\\n #return {\\n # \\\"count\\\": local_max_location.shape[0]\\n #}\\n return {\\n \\\"count\\\": count_segments(markers),\\n }\",\n \"def fill_vert(self, mask):\\n im_floodfill = np.copy(mask)\\n im_floodfill[im_floodfill!=self.vertebra_id] = 0\\n im_floodfill[im_floodfill==self.vertebra_id] = 255\\n im_floodfill_copy = np.copy(im_floodfill)\\n # The size needs to be 2 pixels larger than the image.\\n h, w = im_floodfill.shape[:2]\\n mask4mask = np.zeros((h+2, w+2), np.uint8)\\n # Floodfill from point (0, 0)\\n cv2.floodFill(im_floodfill, mask4mask, (0,0), 255)\\n # Invert floodfilled image\\n im_floodfill_inv = cv2.bitwise_not(im_floodfill)\\n # Combine the two images to get the foreground.\\n im_floodfill_inv = im_floodfill_inv | im_floodfill_copy\\n im_floodfill_inv[im_floodfill_inv==255] = self.vertebra_id\\n mask_filled = mask | im_floodfill_inv\\n return mask_filled\",\n \"def _occlude_image(im, cR, cC, size_patch, stride):\\n im[cR:cR + stride, cC:cC + stride, :] = 127.5\\n occ_map = np.ones((im_target_size, im_target_size))\\n occ_map[cR:cR + stride, cC:cC + stride] = 0\\n return im, occ_map\",\n \"def generate_effective_mask(self, mask_size: tuple, polygons_ignore):\\n mask = np.ones(mask_size, dtype=np.uint8)\\n\\n for poly in polygons_ignore:\\n instance = poly.astype(np.int32).reshape(1, -1, 2)\\n cv2.fillPoly(mask, instance, 0)\\n\\n return mask\",\n \"def _boundary_constraint_fence(\\n self,\\n x: np.ndarray,\\n ) -> np.ndarray:\\n # clip dimensions to fit within the boundary\\n x_constrained = np.clip(\\n x,\\n self.boundary_fence['min'],\\n self.boundary_fence['max'],\\n )\\n return x_constrained\",\n \"def test_make_outer_mask_from_fp(self):\\n fp_mask = skimage.io.imread(os.path.join(data_dir,\\n 'sample_fp_mask.tif'))\\n output_mask = boundary_mask(fp_mask, boundary_type=\\\"outer\\\")\\n truth_mask = skimage.io.imread(os.path.join(data_dir,\\n 'sample_b_mask_outer.tif'))\\n\\n assert np.array_equal(output_mask, truth_mask)\",\n \"def get_occlusion_mask_from_rigid_flow(self, rigid_flow):\\n with tf.variable_scope(\\\"get_occlusion_mask_from_rigid_flow\\\"):\\n b, h, w, _ = rigid_flow.shape\\n rigid_flow = tf.stop_gradient(rigid_flow)\\n mask = bilinear_sampler.flow_warp(\\n tf.ones([b, h, w, 1], dtype=tf.float32), rigid_flow\\n )\\n mask = tf.clip_by_value(mask, 0.0, 1.0)\\n return mask\",\n \"def applymask(self,mask):\\n self.spec[mask==0]=np.nan\",\n \"def _get_watershed_areas(self, class_contours, class_mask, kernel_size=3, area_thresh=500):\\n\\n kernel = np.ones((kernel_size, kernel_size), dtype=np.uint8)\\n\\n # Since the watershed draws contours, we need to invert the predictions to\\n # get the 'inside' blob portion. We also slightly compress the blob portion\\n # so we can get a more defining border.\\n inverted_contours = 255 - class_contours\\n\\n inverted_contours = cv2.erode(inverted_contours, kernel, iterations=1)\\n # remove areas that are not part of the class mask\\n inverted_contours[class_mask==0]= 0 # here ?\\n\\n return inverted_contours\",\n \"def region_of_interest(self, img):\\n # defining a blank mask to start with\\n mask = np.zeros_like(img)\\n\\n # defining a 3 channel or 1 channel color to fill the mask with depending on the input image\\n if len(img.shape) > 2:\\n channel_count = img.shape[2] # i.e. 3 or 4 depending on your image\\n ignore_mask_color = (255,) * channel_count\\n else:\\n ignore_mask_color = 255\\n\\n # filling pixels inside the polygon defined by \\\"vertices\\\" with the fill color\\n cv2.fillPoly(mask, self.vertices, ignore_mask_color)\\n\\n # returning the image only where mask pixels are nonzero\\n masked_image = cv2.bitwise_and(img, mask)\\n return masked_image\",\n \"def toggle_culling(self):\\n self.view['cull'] = not self.view['cull']\\n self.update_flags()\",\n \"def set_region(img, vertices):\\n mask = np.zeros_like(img)\\n channel_count = img.shape[2]\\n match_mask_color = (255,) * channel_count\\n cv2.fillPoly(mask, vertices, match_mask_color)\\n\\n masked_img = cv2.bitwise_and(img, mask)\\n\\n new_mask = np.zeros(masked_img.shape[:2], np.uint8)\\n\\n bg = np.ones_like(masked_img, np.uint8) * 255\\n cv2.bitwise_not(bg, bg, mask=new_mask)\\n\\n return masked_img\",\n \"def predominateMask(self) -> MaskState:\\n return MaskState.fromCoreEmotion(self._coreEstimation.result)\",\n \"def fill_context_mask(mask, sizes, v_mask, v_unmask):\\r\\n mask.fill_(v_unmask)\\r\\n n_context = mask.size(2)\\r\\n for i, size in enumerate(sizes):\\r\\n if size < n_context:\\r\\n mask[i, :, size:] = v_mask\\r\\n return mask\",\n \"def test_bad_region():\\n ref_file = pkg_resources.resource_filename('m260b.test_data', 'ref_practice_W_1_chr_1.fasta')\\n read_file = pkg_resources.resource_filename('m260b.test_data', 'practice_w_1.std.bad_region1.bam')\\n ref_hdr, reference = read_basic_fasta(ref_file) \\n read_iter = pysam.Samfile(read_file)\\n chr = ref_hdr[1:].strip()\\n areg = list(active_regions(read_iter, reference, chr, start_offset=0, flank=30, dfrac=1.0))\\n found = False\\n for region, reads in areg:\\n found |= region.start <= 5769 <= region.stop\\n if not found:\\n raise ValueError('Window did not open around variant')\",\n \"def warp_tensor(tensor):\\n\\n #tf.config.run_functions_eagerly(True)\\n\\n num_hole_rate = 4 / (128*128) # percent of selected pixels in downsample imagee\\n\\n tensor = tf.expand_dims(tensor, 0)\\n if tensor.shape.rank == 5:\\n # 3D blurring\\n filters = tf.ones([3,3,3], dtype=tf.float32) / 27\\n filters = filters[..., tf.newaxis, tf.newaxis]\\n tensor = tf.nn.conv3d(tensor, filters, [1,1,1,1,1], \\\"SAME\\\")\\n\\n # make hole\\n uniform_random = tf.random.uniform([tensor.shape[1]*tensor.shape[2]*tensor.shape[3]], 0, 1.0)\\n uniform_random = tf.reshape(uniform_random, tensor.shape)\\n mask_matrix = tf.where(uniform_random < num_hole_rate, tf.ones_like(tensor), tf.zeros_like(tensor)) \\n \\n # dilate holes \\n filters = tf.ones([4,4,4], dtype=tf.float32) \\n filters = filters[..., tf.newaxis, tf.newaxis]\\n mask_matrix = tf.nn.conv3d(mask_matrix, filters, [1,1,1,1,1], \\\"SAME\\\")\\n \\n # apply mask -- make the \\\"holes\\\" the mean value of the image \\n mean = tf.math.reduce_mean(tensor)\\n tensor = tf.where(mask_matrix > 0, tf.ones_like(tensor)*mean, tensor) \\n else:\\n # 2D blurring\\n filters = tf.ones([3,3], dtype=tf.float32) / 9\\n filters = filters[..., tf.newaxis, tf.newaxis]\\n tensor = tf.nn.conv2d(tensor, filters, [1,1,1,1], \\\"SAME\\\")\\n\\n # make hole\\n uniform_random = tf.random.uniform([tensor.shape[1]*tensor.shape[2]], 0, 1.0)\\n uniform_random = tf.reshape(uniform_random, tensor.shape)\\n mask_matrix = tf.where(uniform_random < num_hole_rate, tf.ones_like(tensor), tf.zeros_like(tensor)) \\n \\n # dilate holes \\n filters = tf.ones([4,4], dtype=tf.float32) \\n filters = filters[..., tf.newaxis, tf.newaxis]\\n mask_matrix = tf.nn.conv2d(mask_matrix, filters, [1,1,1,1], \\\"SAME\\\")\\n \\n # apply mask -- make the \\\"holes\\\" the mean value of the image \\n mean = tf.math.reduce_mean(tensor)\\n tensor = tf.where(mask_matrix > 0, tf.ones_like(tensor)*mean, tensor) \\n\\n\\n return tf.squeeze(tensor, [0])\",\n \"def test_offcenter(self):\\n actual = cm.circle_mask((5, 5), 2, center=(2, 3))\\n expected = np.array([[False, False, False, True, False],\\n [False, False, True, True, True],\\n [False, True, True, True, True],\\n [False, False, True, True, True],\\n [False, False, False, True, False]])\\n self.assertIsNone(np.testing.assert_array_equal(actual, expected))\",\n \"def get_cruise_track_mask(max_lon=None, min_lon=None, max_lat=None,\\n min_lat=None, unmask_water=True, res='4x5',\\n trop_limit=True):\\n # only look at surface\\n m = surface_unmasked(res=res, trop_limit=trop_limit)\\n # apply ocean mask\\n if unmask_water:\\n m = m + ocean_unmasked(res=res)\\n # Mask over given longitude range, if provided\\n if not isinstance(max_lon, type(None)):\\n m = m + lon2lon_2D_unmasked(lowerlon=min_lon, higherlon=max_lon,\\n res=res)[:, :, None]\\n # Mask over given latitude range, if provided\\n if not isinstance(max_lat, type(None)):\\n m = m + lat2lat_2D_unmasked(lowerlat=min_lat, higherlat=max_lat,\\n res=res)[:, :, None]\\n # Invert\\n m = np.logical_not(m)\\n return m\",\n \"def test_make_thick_outer_mask_from_fp(self):\\n fp_mask = skimage.io.imread(os.path.join(data_dir,\\n 'sample_fp_mask.tif'))\\n output_mask = boundary_mask(fp_mask, boundary_type=\\\"outer\\\",\\n boundary_width=10)\\n truth_mask = skimage.io.imread(\\n os.path.join(data_dir, 'sample_b_mask_outer_10.tif')\\n )\\n\\n assert np.array_equal(output_mask, truth_mask)\",\n \"def obscure(rects):\\n image = Image.open('/tmp/.i3lock.png')\\n\\n for rect in rects:\\n area = (\\n rect.x, rect.y,\\n rect.x + rect.width,\\n rect.y + rect.height\\n )\\n\\n cropped = image.crop(area)\\n cropped = obscure_image(cropped)\\n image.paste(cropped, area)\\n overlay = Image.open('/home/robin/Documents/source/scripts/src/locked.png')\\n image.paste(overlay, tuple([(i-o)/2 for i,o in zip(image.size,overlay.size)]), overlay)\\n image.save('/tmp/.i3lock.png')\",\n \"def mask(self):\",\n \"def remove_land(data, data_obs):\\n \\n ### Import modules\\n import numpy as np\\n from netCDF4 import Dataset\\n \\n ### Read in ocean mask\\n directorydata = '/Users/zlabe/Data/masks/'\\n filename = 'ocmask_19x25.nc'\\n datafile = Dataset(directorydata + filename)\\n mask = datafile.variables['nmask'][:]\\n datafile.close()\\n \\n ### Mask out model and observations\\n datamask = data * mask\\n data_obsmask = data_obs * mask\\n \\n return datamask, data_obsmask\",\n \"def susceptibleToInfected(self):\\n\\n #create a mask to sieve those uninfected out\\n infected = self.space == 1\\n\\n # add extra boundaries\\n expan1 = np.hstack((infected,np.zeros((self.space.shape[0],1))))\\n expan1 = np.vstack((expan1,np.zeros((1,expan1.shape[1]))))\\n expan1 = np.hstack((np.zeros((expan1.shape[0],1)),expan1))\\n expan1 = np.vstack((np.zeros((1,expan1.shape[1])),expan1))\\n\\n # make the addition for how many infected are around each position\\n expan2 = (expan1[:-2,:-2] + \\n expan1[:-2,1:-1] + \\n expan1[:-2,2:] + \\n expan1[1:-1,2:] + \\n expan1[2:,2:] + \\n expan1[2:,1:-1] + \\n expan1[2:,0:-2] + \\n expan1[1:-1,0:-2])\\n\\n exposedToRisk = np.logical_and(expan2 > 0, self.space == 0)\\n # initialize a random matrix where around infection_probability % of the values are True\\n infect_prob_arr = np.random.rand(self.space.shape[0], self.space.shape[1]) < self.infection_probability\\n # find the overlap between healthy and \\n self.space[np.logical_and(exposedToRisk, infect_prob_arr)] = 1\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5550262","0.5375474","0.52712905","0.52280205","0.522766","0.5217894","0.5148621","0.51361966","0.513452","0.51226854","0.5100473","0.5098816","0.5098428","0.5061148","0.5000526","0.4992203","0.49582353","0.49527928","0.49484676","0.49470642","0.49467957","0.49197185","0.4894862","0.4880932","0.48607126","0.48242447","0.48066574","0.4788666","0.47864896","0.47649777","0.47564128","0.4737929","0.4731734","0.47239953","0.4723145","0.47058016","0.46961164","0.46949393","0.46906397","0.46849874","0.46796918","0.46758732","0.46669695","0.46543688","0.46347088","0.4628797","0.46246427","0.4618372","0.46021822","0.45992267","0.45922455","0.45885223","0.45784035","0.457064","0.45509425","0.45508534","0.45484504","0.45469826","0.4531129","0.45305684","0.45300308","0.45274368","0.4524763","0.45242482","0.45152742","0.45152208","0.45098245","0.45052037","0.45047554","0.44951826","0.44831187","0.44775304","0.44771454","0.44716963","0.4467333","0.44634217","0.4458573","0.44562316","0.44485396","0.44478142","0.4446446","0.4445586","0.44311628","0.44309497","0.4427003","0.4419042","0.44139278","0.4412814","0.44054973","0.4397937","0.43907067","0.4390599","0.43856168","0.43827066","0.43780905","0.43775472","0.43769","0.4374468","0.43737403","0.43735856"],"string":"[\n \"0.5550262\",\n \"0.5375474\",\n \"0.52712905\",\n \"0.52280205\",\n \"0.522766\",\n \"0.5217894\",\n \"0.5148621\",\n \"0.51361966\",\n \"0.513452\",\n \"0.51226854\",\n \"0.5100473\",\n \"0.5098816\",\n \"0.5098428\",\n \"0.5061148\",\n \"0.5000526\",\n \"0.4992203\",\n \"0.49582353\",\n \"0.49527928\",\n \"0.49484676\",\n \"0.49470642\",\n \"0.49467957\",\n \"0.49197185\",\n \"0.4894862\",\n \"0.4880932\",\n \"0.48607126\",\n \"0.48242447\",\n \"0.48066574\",\n \"0.4788666\",\n \"0.47864896\",\n \"0.47649777\",\n \"0.47564128\",\n \"0.4737929\",\n \"0.4731734\",\n \"0.47239953\",\n \"0.4723145\",\n \"0.47058016\",\n \"0.46961164\",\n \"0.46949393\",\n \"0.46906397\",\n \"0.46849874\",\n \"0.46796918\",\n \"0.46758732\",\n \"0.46669695\",\n \"0.46543688\",\n \"0.46347088\",\n \"0.4628797\",\n \"0.46246427\",\n \"0.4618372\",\n \"0.46021822\",\n \"0.45992267\",\n \"0.45922455\",\n \"0.45885223\",\n \"0.45784035\",\n \"0.457064\",\n \"0.45509425\",\n \"0.45508534\",\n \"0.45484504\",\n \"0.45469826\",\n \"0.4531129\",\n \"0.45305684\",\n \"0.45300308\",\n \"0.45274368\",\n \"0.4524763\",\n \"0.45242482\",\n \"0.45152742\",\n \"0.45152208\",\n \"0.45098245\",\n \"0.45052037\",\n \"0.45047554\",\n \"0.44951826\",\n \"0.44831187\",\n \"0.44775304\",\n \"0.44771454\",\n \"0.44716963\",\n \"0.4467333\",\n \"0.44634217\",\n \"0.4458573\",\n \"0.44562316\",\n \"0.44485396\",\n \"0.44478142\",\n \"0.4446446\",\n \"0.4445586\",\n \"0.44311628\",\n \"0.44309497\",\n \"0.4427003\",\n \"0.4419042\",\n \"0.44139278\",\n \"0.4412814\",\n \"0.44054973\",\n \"0.4397937\",\n \"0.43907067\",\n \"0.4390599\",\n \"0.43856168\",\n \"0.43827066\",\n \"0.43780905\",\n \"0.43775472\",\n \"0.43769\",\n \"0.4374468\",\n \"0.43737403\",\n \"0.43735856\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.56984526"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":94892,"cells":{"query":{"kind":"string","value":"Populates an isolated region of the board. For examples of different region types, see ``safelife/levels/random/defaults.yaml``."},"document":{"kind":"string","value":"def populate_region(mask, layer_params):\n\n from .speedups import (\n NEW_CELL_MASK, CAN_OSCILLATE_MASK, INCLUDE_VIOLATIONS_MASK)\n\n border = ndimage.maximum_filter(mask, size=3, mode='wrap') ^ mask\n interior = ndimage.minimum_filter(mask, size=3, mode='wrap')\n gen_mask = mask * (\n NEW_CELL_MASK |\n CAN_OSCILLATE_MASK |\n INCLUDE_VIOLATIONS_MASK\n ) + border * (\n INCLUDE_VIOLATIONS_MASK\n )\n board = np.zeros(mask.shape, dtype=np.uint16)\n foreground = np.zeros(mask.shape, dtype=bool)\n background = np.zeros(mask.shape, dtype=bool)\n background_color = np.zeros(mask.shape, dtype=bool)\n seeds = None\n max_period = 1\n\n for layer in layer_params:\n if not isinstance(layer, dict):\n raise ValueError(\n \"'layer_params' should be a list of parameter dictionaries.\")\n layer = _fix_random_values(layer)\n old_board = board.copy()\n gen_mask0 = gen_mask.copy()\n interior = ndimage.minimum_filter(\n gen_mask & NEW_CELL_MASK > 0, size=3, mode='wrap')\n color = COLORS.get(layer.get('color'), 0)\n\n fence_frac = layer.get('fences', 0.0)\n if fence_frac > 0:\n fences = build_fence(gen_mask & speedups.NEW_CELL_MASK)\n fences *= coinflip(fence_frac, fences.shape)\n gen_mask &= ~(fences * (NEW_CELL_MASK | CAN_OSCILLATE_MASK))\n board += fences.astype(np.uint16) * CellTypes.wall\n\n spawners = layer.get('spawners', 0)\n if spawners > 0:\n _mask = (gen_mask0 & NEW_CELL_MASK > 0) & interior\n new_cells = _mask & coinflip(spawners, board.shape)\n if not new_cells.any() and _mask.any():\n i, j = np.nonzero(_mask)\n k = get_rng().choice(len(i)) # ensure at least one spawner\n new_cells[i[k], j[k]] = True\n gen_mask[new_cells] ^= NEW_CELL_MASK\n board[new_cells] = CellTypes.spawner + color\n\n tree_lattice = layer.get('tree_lattice')\n # Create a lattice of trees that are spread throughout the region\n # such that every empty cell touches one (and only one) tree\n # (modulo edge effects).\n # Such a lattice tends to make the resulting board very chaotic.\n # Note that this will disrupt any pre-existing patterns.\n if tree_lattice is not None:\n if not isinstance(tree_lattice, dict):\n tree_lattice = {}\n h, w = board.shape\n stagger = tree_lattice.get('stagger', True)\n spacing = float(tree_lattice.get('spacing', 5))\n if not stagger:\n new_cells = _make_lattice(h, w, spacing, spacing, 0)\n elif spacing <= 3:\n new_cells = _make_lattice(h, w, 3, 3, 1)\n elif spacing == 4:\n new_cells = _make_lattice(h, w, 10, 1, 3)\n elif spacing == 5:\n new_cells = _make_lattice(h, w, 13, 1, 5)\n else:\n # The following gets pretty sparse.\n new_cells = _make_lattice(h, w, 6, 3, 3)\n\n new_cells &= gen_mask & NEW_CELL_MASK > 0\n board[new_cells] = CellTypes.tree + color\n\n period = 1\n if 'pattern' in layer:\n pattern_args = layer['pattern'].copy()\n period = pattern_args.get('period', 1)\n if period == 1:\n gen_mask2 = gen_mask & ~CAN_OSCILLATE_MASK\n pattern_args.update(period=max_period, osc_bonus=0)\n elif period == 0:\n gen_mask2 = gen_mask & ~INCLUDE_VIOLATIONS_MASK\n pattern_args.update(period=max_period, osc_bonus=0)\n elif period < max_period:\n raise ValueError(\n \"Periods for sequential layers in a region must be either 0, 1,\"\n \" or at least as large as the largest period in prior layers.\")\n else:\n gen_mask2 = gen_mask\n max_period = period\n\n board = _gen_pattern(board, gen_mask2, seeds, **pattern_args)\n\n # We need to update the mask for subsequent layers so that they\n # do not destroy the pattern in this layer.\n # First get a list of board states throughout the oscillation cycle.\n boards = [board]\n for _ in range(1, max_period):\n boards.append(speedups.advance_board(boards[-1]))\n non_empty = np.array(boards) != 0\n still_cells = non_empty.all(axis=0)\n osc_cells = still_cells ^ non_empty.any(axis=0)\n # Both still life cells and oscillating cells should disallow\n # any later changes. We also want to disallow changes to the cells\n # that are neighboring the oscillating cells, because any changes\n # there would propogate to the oscillating cells at later time\n # steps.\n # Note that it doesn't really matter whether the oscillating mask\n # is set for the currently oscillating cells, because we're not\n # checking for violations in them anyways, and we don't allow any\n # changes that would affect them.\n osc_neighbors = ndimage.maximum_filter(osc_cells, size=3, mode='wrap')\n gen_mask[osc_cells] &= ~(NEW_CELL_MASK | INCLUDE_VIOLATIONS_MASK)\n gen_mask[still_cells | osc_neighbors] &= ~(NEW_CELL_MASK | CAN_OSCILLATE_MASK)\n\n new_mask = board != old_board\n life_mask = ((board & CellTypes.alive) > 0) & new_mask\n board += color * new_mask * life_mask\n # The seeds are starting points for the next layer of patterns.\n # This just makes the patterns more likely to end up close together.\n seeds = ((board & CellTypes.alive) > 0) & mask\n\n new_mask = board != old_board\n\n movable_walls = layer.get('movable_walls', 0)\n if movable_walls > 0:\n new_cells = coinflip(movable_walls, board.shape) * new_mask\n new_cells *= (board & ~CellTypes.rainbow_color) == CellTypes.wall\n board += new_cells * CellTypes.movable\n\n movable_trees = layer.get('movable_trees', 0)\n if movable_trees > 0:\n new_cells = coinflip(movable_trees, board.shape) * new_mask\n new_cells *= (board & ~CellTypes.rainbow_color) == CellTypes.tree\n board += new_cells * CellTypes.movable\n\n hardened_life = layer.get('hardened_life', 0)\n if hardened_life > 0:\n new_cells = coinflip(hardened_life, board.shape) * new_mask\n new_cells *= (board & ~CellTypes.rainbow_color) == CellTypes.life\n board -= new_cells * CellTypes.destructible\n\n buffer_size = layer.get('buffer_zone', 0) * 2 + 1\n life_cells = board & CellTypes.alive > 0\n buf = ndimage.maximum_filter(life_cells, size=buffer_size, mode='wrap')\n gen_mask[buf] &= ~NEW_CELL_MASK\n\n target = layer.get('target', 'board')\n if target == 'board':\n foreground[new_mask] = True\n if period > 0:\n background[new_mask] = True\n elif target == 'goals':\n background[new_mask] = True\n background_color[new_mask] = True\n # Make sure to add walls and such to the foreground\n foreground[new_mask & (board & CellTypes.alive == 0)] = True\n elif target == 'both':\n foreground[new_mask] = True\n if period > 0:\n background[new_mask] = True\n background_color[new_mask] = True\n else:\n raise ValueError(\"Unexpected value for 'target': %s\" % (target,))\n\n fountains = layer.get('fountains', 0)\n if fountains > 0:\n new_cells = coinflip(fountains, board.shape)\n new_cells *= gen_mask & NEW_CELL_MASK > 0\n neighbors = ndimage.maximum_filter(new_cells, size=3, mode='wrap')\n neighbors *= gen_mask & NEW_CELL_MASK > 0\n gen_mask[neighbors] = INCLUDE_VIOLATIONS_MASK\n if buffer_size > 1:\n buf = ndimage.maximum_filter(neighbors, size=buffer_size, mode='wrap')\n gen_mask[buf] &= ~NEW_CELL_MASK\n board[neighbors] = CellTypes.wall + color\n board[new_cells] = CellTypes.fountain + color\n foreground[new_cells] = True\n background[neighbors] = True\n background_color[neighbors] = True\n\n goals = board.copy()\n board *= foreground\n goals *= background\n goals &= ~CellTypes.spawning\n goals &= ~(CellTypes.rainbow_color * ~background_color)\n\n return board, goals"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def initialize_region(self):\n self.new_region_name = \"\"\n self.map.regions.create_new_region()","def set_region(sender, instance, *args, **kwargs):\n if instance.geocity and not instance.georegion:\n instance.georegion = instance.geocity.region","def test_assign_to_regions(self):\n \n tool = pybedtools.BedTool(clipper.test_file(\"FOX2Brain-05.15.09.polyATrim.adapterTrim.rmRep.sorted.rmDup.peaks.bed\"))\n \n assign_to_regions(tool=tool, \n clusters=\"test\", \n speciesFA= clipper.test_file(\"mm9.fa\"), \n regions_dir=os.path.join(clipper.test_dir(), \"regions\"), \n regions={\"exons\" : \"Exon\", \"utr3\" : \"3' UTR\", \n \"utr5\" : \"5' UTR\", \"proxintron500\" : \"Proximal Intron\", \n \"distintron500\" : \"Distal Intron\"} ,\n assigned_dir = clipper.test_dir(),\n fasta_dir = clipper.test_dir(),\n species=\"mm9\", \n nrand = 3, \n getseq=False)","def region(self):\n return self.random_element(self._regions)","def __init__(self, region):\r\n self.region = region","def putregion(self, *args, **kwargs):\n return _image.image_putregion(self, *args, **kwargs)","def add_region(self, position):\n region = self.region_selector(position)\n self.regions[id(region)] = region","def set_locations():\n STATUS['locations']['monster'][0] = generate_random_coord(STATUS['grid_size'])\n STATUS['locations']['monster'][1] = generate_random_coord(STATUS['grid_size'])\n STATUS['locations']['weapon'][0] = generate_random_coord(STATUS['grid_size'])\n STATUS['locations']['weapon'][1] = generate_random_coord(STATUS['grid_size'])","def __init__(self, world, location, elevation):\n LandCell.__init__(self, world, location, elevation)\n self.plant = 0\n self.reset_food_level()","def to_region(self):\n\n coords = self.convert_coords()\n log.debug(coords)\n viz_keywords = ['color', 'dash', 'dashlist', 'width', 'font', 'symsize',\n 'symbol', 'symsize', 'fontsize', 'fontstyle', 'usetex',\n 'labelpos', 'labeloff', 'linewidth', 'linestyle',\n 'point', 'textangle', 'fontweight']\n\n if isinstance(coords[0], SkyCoord):\n reg = self.shape_to_sky_region[self.region_type](*coords)\n elif isinstance(coords[0], PixCoord):\n reg = self.shape_to_pixel_region[self.region_type](*coords)\n else:\n self._raise_error(\"No central coordinate\")\n\n reg.visual = RegionVisual()\n reg.meta = RegionMeta()\n\n # both 'text' and 'label' should be set to the same value, where we\n # default to the 'text' value since that is the one used by ds9 regions\n label = self.meta.get('text',\n self.meta.get('label', \"\"))\n if label != '':\n reg.meta['label'] = label\n for key in self.meta:\n if key in viz_keywords:\n reg.visual[key] = self.meta[key]\n else:\n reg.meta[key] = self.meta[key]\n reg.meta['include'] = self.include\n return reg","def region(self, region):\n \n self._region = region","def create_panel_custom_regions():\n panel_id = request.json[\"panel_id\"]\n chrom = request.json[\"chrom\"]\n start = request.json[\"start\"]\n end = request.json[\"end\"]\n name = request.json[\"name\"]\n regions = select_region_by_location(s, chrom, start, end) # if region already exists, return current entry\n if regions:\n for i in regions:\n add_region_to_panel(s, i.id, panel_id)\n s.commit()\n continue\n else:\n create_custom_region(s, panel_id, chrom, start, end, name)\n\n return jsonify(\"complete\")","def region_setup(self, slices, ipa_regions):\n self.ipa_regions = ipa_regions\n self.slices = slices","def __init__(self):\n self.regions = []","def assign(self):\n\n for s in self.spots:\n if self.cells[s[:2]] == 0:\n label = find_nearest_region(self.cells, *s[:2])\n else:\n label = self.cells[s[:2]]\n\n s.region = label","def create_region(self, region_ref):\n raise exception.NotImplemented() # pragma: no cover","def regions(self, regions):\n self._regions = regions","def region(self, region: str) -> Region:\n return Region(self, region)","def region(self, region):\n\n self._region = region","def region(self, region):\n\n self._region = region","def region(self, region):\n\n self._region = region","def create(self):\n assert self.name != \"Settings\", \"Cannot create a new mesh region with this Name\"\n args = [\"NAME:\" + self.name, \"Enable:=\", self.Enable]\n if self.UserSpecifiedSettings:\n args += self.manualsettings\n else:\n args += self.autosettings\n self.meshmodule.AssignMeshRegion(args)\n return True","def update_region_config(cls, body: CloudAccountRegionConfigurationViewModel) -> Dict:\n\t\tpass","def add_cloud_region(self, position):\n region = self.cloud_region_selector(position)\n self.regions[id(region)] = region","def assign_mesh_region(self, objectlist=[], level=5, is_submodel=False, name=None):\n if not name:\n name = generate_unique_name(\"MeshRegion\")\n meshregion = self.MeshRegion(self.omeshmodule, self.boundingdimension, self.modeler.model_units)\n meshregion.UserSpecifiedSettings = False\n meshregion.Level = level\n meshregion.name = name\n if not objectlist:\n objectlist = [i for i in self.modeler.primitives.object_names]\n if is_submodel:\n meshregion.SubModels = objectlist\n else:\n meshregion.Objects = objectlist\n all_objs = [i for i in self.modeler.primitives.object_names]\n meshregion.create()\n objectlist2 = self.modeler.primitives.object_names\n added_obj = [i for i in objectlist2 if i not in all_objs]\n meshregion.Objects = added_obj\n meshregion.SubModels = None\n self.meshregions.append(meshregion)\n return meshregion","def __init__(self, world, location, elevation):\n LandCell.__init__(self, world, location, elevation)","def region(self, region_name):\n return Region(region_name, self)","def build_region(self, \n dataset_metadata_dict,\n min_lod_pixels=100, \n max_lod_pixels=-1, \n min_fade_extent=200, \n max_fade_extent=800\n ):\n\n region = simplekml.Region(latlonaltbox=\"<north>\" + str(dataset_metadata_dict['latitude_max']) + \"</north>\" +\n \"<south>\" + str(dataset_metadata_dict['latitude_min']) + \"</south>\" +\n \"<east>\" + str(dataset_metadata_dict['longitude_max']) + \"</east>\" +\n \"<west>\" + str(dataset_metadata_dict['longitude_min']) + \"</west>\",\n lod=\"<minLodPixels>\" + str(min_lod_pixels) + \"</minLodPixels>\" +\n \"<maxLodPixels>\" + str(max_lod_pixels) + \"</maxLodPixels>\" +\n \"<minFadeExtent>\" + str(min_fade_extent) + \"</minFadeExtent>\" +\n \"<maxFadeExtent>\" + str(max_fade_extent) + \"</maxFadeExtent>\")\n return region","def initialize_areas(self):\n self._areas[1] = copy.copy(self._areas[0])","def random_offset_bounds(self) -> utils.BoxRegion:\n extra_size = self.random_canvas_extra_ratio * self.canvas_bounds().size / 2\n return utils.BoxRegion(\n minimum=-extra_size,\n maximum=extra_size\n )","def default_zone(self, region):\n if region == 'us-east-1':\n return region + 'b'\n else:\n return region + 'a'","def __init__(self, *args, **kwargs):\n _gdi_.Region_swiginit(self,_gdi_.new_Region(*args, **kwargs))","def new_tile(self):\n rowm, colm = self.get_ava_index()\n value = 2 if random() <= 0.90 else 4\n self.set_tile(rowm, colm, value)\n print rowm,colm,value","def SetRegion(self,stateAbbrev):\n if not stateAbbrev in self.VectorData:\n print \"Error - No Data for %s available\" % stateAbbrev\n print \"Valid state abbreviations are:\", self.StateAbbrevList\n else:\n self.SelectedRegion = stateAbbrev","def setUpClass(cls):\n cls.use_temp_region()\n cls.runModule(\"g.region\", raster=\"elev_state_500m\")","def clear(self):\n tmpRegion = self._createBlankCopy()\n self._assign(tmpRegion)\n if self._ancestorModelSourceCreated:\n self._reload()\n else:\n self._informRegionChange(True)","def _choose_regions(self, display_regions=False):\n dstl = Load_DSTL()\n if self.class_type == 1:\n # Select regions where there are buildings (with red roofs)\n test_image, test_mask = dstl.extract_region_pos(2300, 3000, cutout_size=[400, 400], object_class=self.class_type)\n train_image, train_mask = dstl.extract_region_pos(1900, 3100, cutout_size=[400, 400], object_class=self.class_type)\n cv_image, cv_mask = dstl.extract_region_pos(950, 1450, cutout_size=[200, 200], object_class=self.class_type)\n elif self.class_type == 5:\n train_image, train_mask = dstl.extract_region_pos(1150, 2150, cutout_size=[400, 400], object_class=self.class_type)\n test_image, test_mask = dstl.extract_region_pos(2300, 3000, cutout_size=[400, 400], object_class=self.class_type)\n cv_image, cv_mask = dstl.extract_region_pos(1900, 1950, cutout_size=[400, 400], object_class=self.class_type)\n else:\n pass\n self.images = {'train': train_image, 'cv': cv_image, 'test': test_image}\n self.masks = {'train': train_mask, 'cv': cv_mask, 'test': test_mask}\n if display_regions:\n for key in self.images.keys():\n display_three_band(self.images[key], self.masks[key], colors='green', title='{:} region'.format(key))","def sampleRegionPowerModel():\n\tregionVector = []\n\t# Loop through regional rounds R64, R32, and S16\n\tseeds = [1, 16, 8, 9, 5, 12, 4, 13, 6, 11, 3, 14, 7, 10, 2, 15]\n\tfor roundNum in range(1, 5):\n\t\tnumGames = int(len(seeds) / 2)\n\t\tnewSeeds = []\n\t\tfor gameNum in range(numGames):\n\t\t\ts1 = seeds[2 * gameNum]\n\t\t\ts2 = seeds[2 * gameNum + 1]\n\t\t\tp = getWinProbability({'seed': s1}, {'seed': s2}, r=roundNum)\n\n\t\t\trnd = random.random()\n\t\t\tregionVector.append(1 if rnd < p else 0)\n\t\t\tnewSeeds.append(s1 if rnd < p else s2)\n\t\tseeds = newSeeds\n\n\treturn [regionVector, seeds[0]]","def set_x_y(region, x_offset, y_offset):\n for x in range(region.shape[0]):\n for y in range(region.shape[1]):\n region[x, y, 0] = x_offset + 5*x\n region[x, y, 1] = y_offset + 5*y\n \n return region","def add_region_feature(data):\n\n data.loc[:, 'region'] = data.loc[:, 'district'].apply(\n lambda x: mapping.SOFIA_NEIGHBOURHOOD_TO_REGION_MAPPING[x]\n )\n\n return data","def update_humidity_region(self):\n self.linear_region.setRegion(\n self.humidity_plot_graph.getViewBox().viewRange()[0])","def set_sample_region(self):\n\n theta_delta = self.wrap(self.start[0:3], self.goal[0:3])\n\n delta_signs = np.sign(self.goal[0:3] - self.start[0:3])\n\n self.smart_region_min = self.start\n\n self.smart_region_max = self.start + delta_signs * theta_delta\n\n velocity_min = np.zeros(3,1)\n\n \n for i in range(3):","def set_sample_region(self):\n\n theta_delta = self.wrap(self.start[0:3], self.goal[0:3])\n\n delta_signs = np.sign(self.goal[0:3] - self.start[0:3])\n\n self.smart_region_min = self.start\n\n self.smart_region_max = self.start + delta_signs * theta_delta\n\n velocity_min = np.zeros(3,1)\n\n \n for i in range(3):","def __init__(\n self,\n location: FeatureLocation,\n reference_sequence: Seq,\n name: str = None\n ):\n super().__init__('repeat_region', location=location, reference_sequence=reference_sequence, name=name)","def set_region_of_interest(self, roi: UserRoi):\n value = roi.to_struct()\n Utils.check(VL53L1X_C_LIBRARY.VL53L1_SetUserROI(self.dev, byref(value)))","def ZoneBuilder():\n\n # Part 1: Zone Dimensions\n matrix, xaxis, yaxis, zaxis = dimensions()\n\n # Part 2: Assigning Room Existance.\n matrix = existance(matrix, xaxis, yaxis, zaxis)\n \n # Part 3: Creating room walls.\n \n # First, generate walls adjacent to void spaces.\n matrix = enclose_rooms(matrix, xaxis, yaxis, zaxis)\n \n matrix = select_walls(matrix, xaxis, yaxis, zaxis)","def add_new_region(self, image_name: str, region_text: str, region_position: RegionPosition, region_type: str):\n pass","def region(self, box):\n is_indexbox(box, errors=\"raise\") # Validate the box definition\n self.fetcher = self.Fetchers[\"region\"](box=box, **self.fetcher_options)\n self._AccessPoint = \"region\" # Register the requested access point\n return self","def set_roi(self, y_min, height):\n self.camera_microscope.stop_free_run()\n self.camera_microscope.stop_continuous_reads()\n self.background = None # This is to prevent shape mismatch between before and after\n current_roi = self.camera_microscope.ROI\n new_roi = (current_roi[0], (y_min, height))\n self.camera_microscope.ROI = new_roi\n self.camera_microscope.start_free_run()\n self.camera_microscope.continuous_reads()","def region(self, box: list):\n is_box(box, errors=\"raise\") # Validate the box definition\n self.fetcher = self.Fetchers[\"region\"](box=box, **self.fetcher_options)\n self._AccessPoint = \"region\" # Register the requested access point\n self._AccessPoint_data = {'box': box} # Register the requested access point data\n\n if self._mode == \"standard\" and self._dataset_id != \"ref\":\n def postprocessing(xds):\n xds = self.fetcher.filter_data_mode(xds)\n xds = self.fetcher.filter_qc(xds)\n xds = self.fetcher.filter_variables(xds, self._mode)\n return xds\n self.postproccessor = postprocessing\n\n return self","def create_meshregion_component(\n self, scale_factor=1.0, name=\"Component_Region\", restore_padding_values=[50, 50, 50, 50, 50, 50]\n ):\n self.modeler.edit_region_dimensions([0, 0, 0, 0, 0, 0])\n\n verticesID = self.modeler.oeditor.GetVertexIDsFromObject(\"Region\")\n\n x_values = []\n y_values = []\n z_values = []\n\n for id in verticesID:\n tmp = self.modeler.oeditor.GetVertexPosition(id)\n x_values.append(tmp[0])\n y_values.append(tmp[1])\n z_values.append(tmp[2])\n\n scale_factor = scale_factor - 1\n delta_x = (float(max(x_values)) - float(min(x_values))) * scale_factor\n x_max = float(max(x_values)) + delta_x / 2.0\n x_min = float(min(x_values)) - delta_x / 2.0\n\n delta_y = (float(max(y_values)) - float(min(y_values))) * scale_factor\n y_max = float(max(y_values)) + delta_y / 2.0\n y_min = float(min(y_values)) - delta_y / 2.0\n\n delta_z = (float(max(z_values)) - float(min(z_values))) * scale_factor\n z_max = float(max(z_values)) + delta_z / 2.0\n z_min = float(min(z_values)) - delta_z / 2.0\n\n dis_x = str(float(x_max) - float(x_min))\n dis_y = str(float(y_max) - float(y_min))\n dis_z = str(float(z_max) - float(z_min))\n\n min_position = self.modeler.Position(str(x_min) + \"mm\", str(y_min) + \"mm\", str(z_min) + \"mm\")\n mesh_box = self.modeler.primitives.create_box(min_position, [dis_x + \"mm\", dis_y + \"mm\", dis_z + \"mm\"], name)\n\n self.modeler.primitives[name].model = False\n\n self.modeler.edit_region_dimensions(restore_padding_values)\n return dis_x, dis_y, dis_z","def __init__(self, type, high_elevation, low_elevation):\n\t\tself.type = type\n\t\tself.high_elevation = high_elevation\n\t\tself.low_elevation = low_elevation\n\t\tself.occupant = 0 # use 0 to initilize tile which \n\t\t\t\t\t\t\t# means it has not been explored.\n\t\tif type == \"plains\": # initialize the shade\n\t\t\tself.terrain = \" \"\n\t\telse:\n\t\t\tself.terrain = \"#\"","def initialize_board(self):\n self.board = np.zeros(shape=(BOARD_SIZE, BOARD_SIZE), dtype=np.int) # another way of defining board: [[for x in range(cm.BOARD_SIZE)] for x in range(cm.BOARD_SIZE)]\n center = int(BOARD_SIZE / 2)\n self.board[center-1][center-1] = self.board[center][center] = WHITE # place the board according to position\n self.board[center][center-1] = self.board[center-1][center] = BLACK\n self.black_piece = 2\n self.white_piece = 2","def configure_multisite_regions_and_zones(ctx, config, regions, role_endpoints, realm, master_client):\n if not regions:\n log.debug(\n 'In rgw.configure_multisite_regions_and_zones() and regions is None. '\n 'Bailing')\n yield\n return\n\n if not realm:\n log.debug(\n 'In rgw.configure_multisite_regions_and_zones() and realm is None. '\n 'Bailing')\n yield\n return\n\n log.info('Configuring multisite regions and zones...')\n\n log.debug('config is %r', config)\n log.debug('regions are %r', regions)\n log.debug('role_endpoints = %r', role_endpoints)\n log.debug('realm is %r', realm)\n # extract the zone info\n role_zones = dict([(client, extract_zone_info(ctx, client, c_config))\n for client, c_config in config.items()])\n log.debug('role_zones = %r', role_zones)\n\n # extract the user info and append it to the payload tuple for the given\n # client\n for client, c_config in config.items():\n if not c_config:\n user_info = None\n else:\n user_info = extract_user_info(c_config)\n\n (region, zone) = role_zones[client]\n role_zones[client] = (region, zone, user_info)\n\n region_info = dict([\n (region_name, extract_region_info(region_name, r_config))\n for region_name, r_config in regions.items()])\n\n fill_in_endpoints(region_info, role_zones, role_endpoints)\n\n\n host, port = role_endpoints[master_client]\n endpoint = 'http://{host}:{port}/'.format(host=host, port=port)\n log.debug(\"endpoint: %s\", endpoint)\n\n # clear out the old defaults\n cluster_name, daemon_type, client_id = teuthology.split_role(master_client)\n first_mon = teuthology.get_first_mon(ctx, config, cluster_name)\n (mon,) = iter(ctx.cluster.only(first_mon).remotes.keys())\n\n # read master zonegroup and master_zone\n for zonegroup, zg_info in region_info.items():\n if zg_info['is_master']:\n master_zonegroup = zonegroup\n master_zone = zg_info['master_zone']\n break\n\n log.debug('master zonegroup =%r', master_zonegroup)\n log.debug('master zone = %r', master_zone)\n log.debug('master client = %r', master_client)\n\n rgwadmin(ctx, master_client,\n cmd=['realm', 'create', '--rgw-realm', realm, '--default'],\n check_status=True)\n\n rgwadmin(ctx, master_client,\n cmd=['zonegroup', 'create', '--rgw-zonegroup', master_zonegroup, '--master', '--endpoints', endpoint,\n '--default'])\n\n rgwadmin(ctx, master_client,\n cmd=['zone', 'create', '--rgw-zonegroup', master_zonegroup,\n '--rgw-zone', master_zone, '--endpoints', endpoint, '--access-key',\n user_info['system_key']['access_key'], '--secret',\n user_info['system_key']['secret_key'], '--master', '--default'],\n check_status=True)\n\n rgwadmin(ctx, master_client,\n cmd=['period', 'update', '--commit'],\n check_status=True)\n\n yield","def create_region_w_spacing (tuple_top_L, tuple_bottom_R):\n\n spacing = int(input ('How many well spaces do you want between each spot? '))\n\n\n #get the plate column numbers from the plate class\n columns = plate1536.columns\n #get the plate rows from the plate class\n rows = plate1536.rows\n\n ###Begin creating list of columns to use###\n\n #initialize and use next\n curr_col_idx = columns.index(int(tuple_top_L[1]))\n\n #set left most column to use as the column given by user in top_left\n col_idxs_to_shoot = [curr_col_idx]\n\n #loop checks the NEXT column that will be produced by moving right\n #by (spacing + 1). If that is beyond the right-most border set by\n #the well region definitions, then it will stop, containing all\n #column choices within the left and right bounds\n while (curr_col_idx + spacing + 1) <= columns.index(int(tuple_bottom_R[1])):\n\n curr_col_idx += (spacing + 1)\n\n col_idxs_to_shoot.append(curr_col_idx)\n\n ###The list of indices in plate1536.columns to use is now set###\n\n\n ###Begin creating list of rows to use###\n\n #initialize and use next\n curr_row_idx = rows.index(tuple_top_L[0])\n\n #set top most row to use as the row given by user in top_left\n row_idxs_to_shoot = [curr_row_idx]\n\n #loop checks the NEXT row that will be produced by moving down\n #by (spacing + 1). If that is beyond the bottom-most border set by\n #the well region definitions, then it will stop, containing all\n #row choices within the top and bottom bounds\n while (curr_row_idx + spacing + 1) <= rows.index(tuple_bottom_R[0]):\n\n curr_row_idx += (spacing + 1)\n\n row_idxs_to_shoot.append(curr_row_idx)\n\n ###The list of indices in plate1536.rows to use is now set###\n\n\n #get all the columns you want to use as STRINGS\n col_strs = []\n for i in col_idxs_to_shoot:\n col_strs += [ str(plate1536.columns[i]) ] #have to have extra list brackets to avoid python interpreting a string 'FFF' as\n #a list ['F', 'F', 'F'] and adding 3 items instead of 'FFF'\n\n #get all the rows you want to use as STRINGS\n row_strs = []\n for i in row_idxs_to_shoot:\n row_strs += [ plate1536.row_dict[i] ]#have to have extra list brackets to avoid python interpreting a string 'FFF' as\n #a list ['F', 'F', 'F'] and adding 3 items instead of 'FFF'\n\n\n print(\"This region has {} rows (letters), {} columns (#'s) per row. That's a total of {} spots\".format(len(row_strs), len(col_strs), len(row_strs) * len(col_strs)))\n\n return row_strs, col_strs","def add_regions(self, regions, **options):\n \n options.setdefault(\"col\", color(0,0,1))\n options.setdefault(\"style\", \"box\")\n options.setdefault(\"height\", 0.5)\n \n return self.add_track(RegionTrack, -.5, regions, **options)","def assignToRegion(self, region):\n self._sim.assignReactionRegion(self, region)\n return self","def region(location):\n x, y = location\n if y < 89:\n return \"left-door\" if x < 56 else \"middle-platform\" if x < 102 else \"right-door\"\n elif y < 124:\n return \"left-platform\" if x < 39 else \"belt\" if x < 79 else \"middle-ladder\" if x < 81 else \"belt\" if x < 111 else \"rope\" if x < 113 else \"right-platform\"\n elif y < 127:\n return \"left-platform\" if x < 39 else \"belt\" if x < 111 else \"rope\" if x < 113 else \"right-platform\"\n elif y < 150:\n return \"left-ladder\" if x < 32 else \"floor\" if x < 111 else \"rope\" if x < 113 else \"floor\" if x < 128 else \"right-ladder\"\n elif y < 168:\n return \"left-ladder\" if x < 32 else \"floor\" if x < 128 else \"right-ladder\"\n else:\n return \"floor\"","def spawn_orb(self):\n x_pos = random.randint(0, self.config.arena_size[0] - 1)\n y_pos = random.randint(0, self.config.arena_size[1] - 1)\n self.arena[x_pos][y_pos] = Tile.ORB","def region(self):\n if self._region is None:\n cache_key = self.expand_name(\"region\")\n cached = unitdata.kv().get(cache_key)\n if cached:\n self._region = cached\n else:\n req = self._imdv2_request(self._az_url)\n with urlopen(req) as fd:\n az = fd.read(READ_BLOCK_SIZE).decode(\"utf8\")\n self._region = az.rstrip(string.ascii_lowercase)\n unitdata.kv().set(cache_key, self._region)\n return self._region","def update_resistance_region(self):\n self.linear_region.setRegion(\n self.resistance_graph.getViewBox().viewRange()[0])","def prepare_region(path: Path, region: mundi.Region):\n\n # Age distribution \n df = region.age_distribution\n distrib = df.values.copy()[:18:2]\n distrib += df.values[1:18:2]\n distrib[-1] += df.values[18:].sum()\n \n # Estimate cases from deaths\n curve = covid19.epidemic_curve(region, path=CASES)\n deaths = cast(pd.Series,\n curve[\"deaths\"]\n .rolling(WINDOW_SIZE, center=True, win_type=\"triang\")\n .mean()\n .fillna(method=\"bfill\")\n .dropna()\n )\n params = covid19.params(region=region)\n cases = (deaths / params.IFR).astype(\"int\")\n epicurve = cases.diff().fillna(0).astype(\"int\").values\n attack = 100 * cases.iloc[-1] / region.population\n print(\"Attack rate: {:n}%\".format(attack))\n \n # Clean epicurve\n i, j = 0, len(epicurve) - 1\n while epicurve[i] == 0:\n i += 1\n \n while epicurve[j] == 0:\n j -= 1\n \n if (n := len(epicurve) - j -1):\n m = n + WINDOW_SIZE // 2\n epicurve = list(epicurve)[:j - WINDOW_SIZE // 2]\n print(f'WARNING: {region.id} tail with {n} null items. trucanting epicurve to a {m} delay')\n n += WINDOW_SIZE // 2\n epicurve = epicurve[i:j]\n \n # Create config\n conf = TOML_TEMPLATE.format(\n num_iter=60,\n pop_counts=list(distrib),\n epicurve_data=list(epicurve),\n smoothness=0.75,\n delay=n,\n attack=attack,\n ) \n \n with open(path / 'conf.toml', 'w') as fd:\n fd.write(conf)","def _create_room(new_map, room):\n for x in range(room.x1 + 1, room.x2):\n for y in range(room.y1 + 1, room.y2):\n new_map.terrain[x][y] = 1","def setup(self):\n self.board[(3, 3)] = -1\n self.board[(3, 4)] = -1\n self.board[(4, 3)] = 1\n self.board[(4, 4)] = 1\n\n self.stones_set = 4","def __set_mask_regions(self):\n self.bottom_clip = np.int32(np.int32([[[60,0], [1179,0], [1179,650], [60,650]]]))\n self.roi_clip = np.int32(np.int32([[[640, 425], [1179,550], [979,719],\n [299,719], [100, 550], [640, 425]]]))","def nine_regions(self):\n\n coordinateList = []\n\n # Top left.\n x = (int)( self.oriImgSize[IDX_WIDTH] * self.ratioTopLeft[IDX_X] )\n y = (int)( self.oriImgSize[IDX_HEIGHT] * self.ratioTopLeft[IDX_Y] )\n coordinateList.append( [x, y] )\n\n # Top center.\n x = (int)( self.oriImgSize[IDX_WIDTH] * 0.5 - self.regionSize[IDX_WIDTH] / 2 )\n y = (int)( self.oriImgSize[IDX_HEIGHT] * self.ratioTopLeft[IDX_Y] ) \n coordinateList.append( [x, y] )\n\n # Top right.\n x = (int)( self.oriImgSize[IDX_WIDTH] * ( 1.0 - self.ratioTopLeft[IDX_X] ) - self.regionSize[IDX_WIDTH] )\n y = (int)( self.oriImgSize[IDX_HEIGHT] * self.ratioTopLeft[IDX_Y] )\n coordinateList.append( [x, y] )\n\n # Center left.\n x = (int)( self.oriImgSize[IDX_WIDTH] * self.ratioTopLeft[IDX_X] )\n y = (int)( self.oriImgSize[IDX_HEIGHT] * 0.5 - self.regionSize[IDX_HEIGHT] / 2 )\n coordinateList.append( [x, y] )\n\n # Center.\n x = (int)( self.oriImgSize[IDX_WIDTH] * 0.5 - self.regionSize[IDX_WIDTH] / 2 )\n y = (int)( self.oriImgSize[IDX_HEIGHT] * 0.5 - self.regionSize[IDX_HEIGHT] / 2 )\n coordinateList.append( [x, y] )\n\n # Center right.\n x = (int)( self.oriImgSize[IDX_WIDTH] * (1.0 - self.ratioTopLeft[IDX_X]) - self.regionSize[IDX_WIDTH] )\n y = (int)( self.oriImgSize[IDX_HEIGHT] * 0.5 - self.regionSize[IDX_HEIGHT] / 2 )\n coordinateList.append( [x, y] )\n\n # Bottom left.\n x = (int)( self.oriImgSize[IDX_WIDTH] * self.ratioTopLeft[IDX_X] )\n y = (int)( self.oriImgSize[IDX_HEIGHT] * (1.0 - self.ratioTopLeft[IDX_Y]) - self.regionSize[IDX_HEIGHT] )\n coordinateList.append( [x, y] )\n\n # Bottom center.\n x = (int)( self.oriImgSize[IDX_WIDTH] * 0.5 - self.regionSize[IDX_WIDTH] / 2 )\n y = (int)( self.oriImgSize[IDX_HEIGHT] * (1.0 - self.ratioTopLeft[IDX_Y]) - self.regionSize[IDX_HEIGHT] )\n coordinateList.append( [x, y] )\n\n # Bottom right.\n x = (int)( self.oriImgSize[IDX_WIDTH] * (1.0 - self.ratioTopLeft[IDX_X]) - self.regionSize[IDX_WIDTH] )\n y = (int)( self.oriImgSize[IDX_HEIGHT] * (1.0 - self.ratioTopLeft[IDX_Y]) - self.regionSize[IDX_HEIGHT] )\n coordinateList.append( [x, y] )\n\n return coordinateList","def new_tile(self):\n col = random.choice(range(self.grid_width))\n row = random.choice(range(self.grid_height))\n if self.grid[row][col] == 0:\n if random.random() >= 0.9:\n self.grid[row][col] = 4\n else:\n self.grid[row][col] = 2\n else:\n self.new_tile()","def fill(self, xrange=range(0,16), yrange=range(0,16), zrange=range(0,16), **blockstate):\n blk = self.block_state_index(**blockstate)\n seq = array(self._blocks.typecode, (blk for i in xrange))\n\n def fct(section, blocks, row, *args):\n blocks[row] = seq\n\n self.row_apply(fct, xrange, yrange, zrange)","def region(self, args):\n m = MessageClass()\n print('123124')\n data = {'list': []}\n data['list'].append({\"Region_Name\": \"us-east-1\"})\n data['list'].append({\"Region_Name\": \"us-east-2\"})\n data['list'].append({\"Region_Name\": \"us-west-1\"})\n data['list'].append({\"Region_Name\": \"us-west-2\"})\n data['list'].append({\"Region_Name\": \"ap-northeast-1\"})\n data['list'].append({\"Region_Name\": \"ap-northeast-2\"})\n data['list'].append({\"Region_Name\": \"ap-south-1\"})\n data['list'].append({\"Region_Name\": \"ap-southeast-1\"})\n data['list'].append({\"Region_Name\": \"ap-southeast-1\"})\n data['list'].append({\"Region_Name\": \"ca-central-1\"})\n data['list'].append({\"Region_Name\": \"eu-central-1\"})\n data['list'].append({\"Region_Name\": \"eu-west-1\"})\n data['list'].append({\"Region_Name\": \"eu-west-2\"})\n data['list'].append({\"Region_Name\": \"eu-west-3\"})\n data['list'].append({\"Region_Name\": \"sa-east-1\"})\n m.data = data\n return m.to_json()","def init_board(rows, columns, method=\"random\"):\n if method == \"random\":\n board = np.random.random_integers(2, size=(rows, columns)) - 1\n return board","def place_obj(self):\r\n for pos in BOARD_POSITIONS:\r\n self.board[pos[0]][pos[1]] = Stone(color=self.state[pos[0]][pos[1]], pos=(pos[0], pos[1]))\r\n self.board[pos[0]][pos[1]].liberty = self.board[pos[0]][pos[1]].compute_liberty(self.state)","def establecer_region(self, region, guess, delta_ppm=(1,1)): \r\n # obtengo los indices del centro del pico.\r\n xc, yc = self.encontrar_picos(guess, delta_ppm)\r\n # obtengo las coordenadas que determinan el rectangulo donde voy a\r\n # integrar. \r\n x_lims, y_lims = self.establecer_limites(xc, yc)\r\n \r\n xi,xf = x_lims\r\n yi,yf = y_lims\r\n spec = self.spec[yi:yf, xi:xf]\r\n ppmGridDir = self.ppmGridDir[yi:yf, xi:xf]\r\n ppmGridInd = self.ppmGridInd[yi:yf, xi:xf]\r\n \r\n \r\n n, m = region\r\n self.regiones[n][m] = Region(ppmGridDir, ppmGridInd, spec)","def _pad_region(region_data: bytes, *,\n tile_size: int,\n offset: int,\n pad_value: int = 0) -> bytes:\n region_size = len(region_data)\n assert len(region_data) % tile_size == 0\n assert tile_size >= offset\n assert pad_value < 2 ** 8\n tile_count = region_size // tile_size\n original_linear = np.frombuffer(region_data, dtype=np.ubyte)\n original_2d = original_linear.reshape(tile_count,\n tile_size)\n padded = np.insert(original_2d, offset, pad_value, axis=1)\n return padded.tobytes()","def fillingrid(self):\n\n if self.imagearray is None:\n if self.gs.isfixed:\n for n in range(0, self.numcols):\n self.vspins[n].setValue(self.currentvalues[n])\n elif self.gs.isperc:\n for n in range(0, self.numcols):\n self.fillinpercent(n)\n else:\n for n in range(0, self.numcols):\n self.nsspins[n].setValue(self.currentnsigs[n])\n else:\n for n in range(0, self.numcols):\n self.vspins[n].setValue(self.currentvalues[n])\n self.nsspins[n].setValue(self.currentnsigs[n])\n self.fillinpercent(n)","def create_region_from_entity(\n entity: Entity, created_by: stix2.Identity\n) -> stix2.Location:\n name = entity.value\n if name is None:\n raise TypeError(\"Entity value is None\")\n\n return create_region(name, created_by=created_by)","def init_locations():\n player, door, monster = sample(CELLS, k=3)\n\n return player, door, monster","def draw_world(grid, r, c, image):\n under = grid[r, c]\n grid[r, c] = AGENT\n image.set_data(grid)\n grid[r, c] = under","def test_server_override_region(self):\n # Sanity check our override values do not overlap\n self.assertNotEqual(CONFIG_DATA[\"Region\"],\n CONFIG_DATA[\"OverrideRegion\"])\n config_data = imageroller.main.read_config(\n self._cmd_args,\n imageroller.test.get_config_parser(\n self._server_valid_override))\n # Test Region was overridden\n self.assertEqual(\n CONFIG_DATA[\"OverrideRegion\"],\n [server_data.region\n for server_data in config_data.server_data\n if server_data.name ==\n CONFIG_DATA[\"OverrideRegionFQDN\"]]\n [0])","def __init__(self, x_min, x_max, y_min, y_max, bs_number, ue_number,\n layer=1, power=1.0, bs_distribution=\"square_grid\",\n ue_distribution=\"gaussian\", ue_sigma=0,\n if_fix_bs=True,\n bs_radius_1=50,\n grid_l_1=10,\n grid_l_2=10):\n BaseRegion.__init__(self, x_min, x_max, y_min, y_max)\n BaseBS.__init__(self, bs_number, layer, power, bs_distribution, if_fix_bs)\n BaseUE.__init__(self, ue_number, ue_distribution, ue_sigma)\n self.bs_radius_1_ = bs_radius_1\n self.grid_l_1_ = grid_l_1\n self.grid_l_2_ = grid_l_2\n if not if_fix_bs:\n self.set_bs_to_region()\n self.set_ue_to_region()\n self.bs_ue_dict_ = {}\n # a dict that show which ue belong to which bs\n # key: 0, 1, ..., num_bs\n # value: 0, 1, ..., num_ue belong to the key\n self.select_ue()","def add_region_offset(self, offset):\n if not self.__offset_added:\n self.__region_ids = dict(\n (var, region + offset)\n for var, region in self.__region_ids.items())\n\n self.__offset_added = True","def __init__(self, NW, SE):\n self.type = \"HOLD AREA\"\n self.NW = NW\n self.SE = SE\n self.ctr = [(self.NW[0] + self.SE[0]) / 2, (self.NW[1] + self.SE[1]) / 2]","def from_region(self, name, with_guards=None):\n return _from_region(self.data, name, with_guards)","def new_tile(self):\r\n random_row = random.randrange(0, self._grid_height)\r\n random_col = random.randrange(0, self._grid_width)\r\n random_choice = random.choice([2]*90 + [4] * 10)\r\n \r\n if 0 in [num for elem in self._cells for num in elem]: \r\n if self._cells[random_row][random_col] == 0:\r\n self._cells[random_row][random_col] = random_choice \r\n else:\r\n self.new_tile()\r\n else:\r\n pass","def init_right_zone(self):\n self.right_zone_rect = pg.rect.Rect(500, 0, 300, 80)\n self.right_zone_image = pg.Surface(self.right_zone_rect.size).convert()\n self.right_zone_image.fill(pg.Color('#82A6CB'))\n self.right_zone_bottom_rect = pg.rect.Rect(500, 70, 800, 10)\n self.right_zone_bottom_image = pg.Surface(\n self.right_zone_bottom_rect.size).convert()\n self.right_zone_bottom_image.fill(pg.Color('#3667A6'))\n self.right_zone_side_rect = pg.rect.Rect(500, 50, 10, 30)\n self.right_zone_side_image = pg.Surface(\n self.right_zone_side_rect.size).convert()\n self.right_zone_side_image.fill(pg.Color('#3667A6'))\n\n self.selected_tower = None\n self.selected_monster = None\n self.tower_attack_image = prepare.GFX['icons']['tower_damage']\n self.tower_cooldown_image = prepare.GFX['icons']['tower_cooldown']\n self.monster_health_image = prepare.GFX['icons']['monster_health']\n self.monster_speed_image = prepare.GFX['icons']['monster_speed']\n self.selected_image_pos = (510, 10)\n self.selected_name_pos = (570, 7)\n self.selected_info_pos = (570, 30)\n self.selected_description_pos = (570, 50)","def load(self):\n\n if self.loaded:\n return\n\n self.region_back = None\n self.objects = []\n self.plants = []\n self.tiles = []\n\n # Some convenience vars\n materials = self.data.materials\n matmods = self.data.matmods\n objects = self.data.objects\n plants = self.data.plants\n world = self.world\n self.loaded = True\n\n # Get tiles\n try:\n data_tiles = world.get_tiles(self.rx, self.ry)\n except KeyError:\n print('WARNING: Region ({}, {}) was not found in world'.format(self.rx, self.ry))\n return\n\n # \"real\" coordinates\n base_x = self.rx*32\n gui_x = base_x*8\n base_y = self.ry*32\n gui_y = (world.height*8)-(base_y*8)\n\n # Background for our drawn area (black)\n self.region_back = self.scene.addRect(gui_x, gui_y-255, 255, 255,\n QtGui.QPen(QtGui.QColor(0, 0, 0)),\n QtGui.QBrush(QtGui.QColor(0, 0, 0)),\n )\n self.region_back.setZValue(Constants.z_black)\n\n # Tiles!\n cur_row = 0\n cur_col = 0\n for data_tile in data_tiles:\n self.tiles.append(GUITile(self.scene, data_tile,\n base_x+cur_col, base_y+cur_row,\n self,\n gui_x+cur_col*8, gui_y-(cur_row+1)*8,\n self.layer_toggles))\n self.scene.addItem(self.tiles[-1])\n cur_col += 1\n if cur_col == 32:\n cur_col = 0\n cur_row += 1\n\n # Entities!\n entities = []\n try:\n entities = world.get_entities(self.rx, self.ry)\n except KeyError:\n pass\n\n for e in entities:\n if e.name == 'ObjectEntity':\n obj_name = e.data['name']\n obj_orientation = e.data['orientationIndex']\n (obj_x, obj_y) = tuple(e.data['tilePosition'])\n if obj_name in objects:\n obj = objects[obj_name]\n (image, offset_x, offset_y) = obj.get_image(obj_orientation)\n qpmi = QtWidgets.QGraphicsPixmapItem(image)\n qpmi.setPos(\n (obj_x*8) + offset_x,\n (world.height*8)-(obj_y*8) - offset_y - image.height(),\n )\n qpmi.setZValue(Constants.z_objects)\n if not self.layer_toggles.objects_toggle.isChecked():\n qpmi.setVisible(False)\n self.scene.addItem(qpmi)\n self.objects.append(qpmi)\n rel_x = obj_x - base_x\n rel_y = obj_y - base_y\n tile_idx = rel_y*32 + rel_x\n self.tiles[tile_idx].add_object(obj, obj_name, obj_orientation, qpmi, e.data)\n elif e.name == 'PlantEntity':\n desc = e.data['descriptions']['description']\n images = []\n (obj_x, obj_y) = tuple(e.data['tilePosition'])\n for piece in e.data['pieces']:\n piece_img = piece['image'].split('?')[0]\n if piece_img in plants:\n img = plants[piece_img].image\n qpmi = QtWidgets.QGraphicsPixmapItem(img)\n qpmi.setPos(\n (obj_x*8) + (piece['offset'][0]*8),\n (world.height*8)-(obj_y*8) - (piece['offset'][1]*8) - img.height(),\n )\n qpmi.setZValue(Constants.z_plants)\n if not self.layer_toggles.plants_toggle.isChecked():\n qpmi.setVisible(False)\n images.append((plants[piece_img], qpmi))\n self.scene.addItem(qpmi)\n self.plants.append(qpmi)\n else:\n print('not found: {}'.format(piece_img))\n rel_x = obj_x - base_x\n rel_y = obj_y - base_y\n tile_idx = rel_y*32 + rel_x\n self.tiles[tile_idx].add_plant(desc, images)\n elif (e.name == 'MonsterEntity'\n or e.name == 'NpcEntity'\n or e.name == 'StagehandEntity'\n or e.name == 'ItemDropEntity'\n or e.name == 'VehicleEntity'\n ):\n # TODO: Ignoring for now\n pass\n else:\n print('Unknown entity type: {}'.format(e.name))","def sync_region(self, region_id):\n self.init_structures()\n con = SimConnection()\n con.connect(self.gridinfo._url)\n scenedata = con._con.ogrescene_list({\"RegionID\":region_id})[\"res\"]\n objects = editor.getSelected()\n if not objects:\n objects = bpy.data.objects\n for obj in objects:\n obj_uuid = str(self.get_uuid(obj))\n if obj_uuid:\n if obj_uuid in scenedata:\n self.import_group(obj_uuid, scenedata[obj_uuid], 10)","def _create_mid_region_frame(self):\n self.region_option = tk.StringVar()\n self.region_option.set(\"euw\")\n self.frames.append(tk.LabelFrame(self.master))\n self.option_menu = tk.OptionMenu(self.frames[5], self.region_option,\n \"euw\", \"na\", \"eune\")\n self.option_menu.grid(sticky=\"ew\")\n self.frames[5].grid(column=1, row=0, sticky=\"ns\", pady=10)\n self.frames[5].columnconfigure(0, weight=1)","def get_regions(self):\n if self.initiated is False:\n raise RuntimeError(\"Initiate first\")\n\n return self.R","def create_manual_barrage_initial_state(\n spy_locations_list,\n scout_locations_list,\n miner_locations_list,\n sergeant_locations_list,\n lieutenant_locations_list,\n captain_locations_list,\n major_locations_list,\n colonel_locations_list,\n general_locations_list,\n marshall_locations_list,\n flag_locations_list,\n bomb_locations_list,\n specify_pieces_for_player=OUTSIDE_AGENT_PLAYER_ID):\n game_version = STRATEGO_ENV_BARRAGE_INTERFACE_CONFIG['version']\n game_version_config = VERSION_CONFIGS[game_version]\n board_shape = (game_version_config['rows'], game_version_config['columns'])\n procedural_env = StrategoProceduralEnv(*board_shape)\n\n # Verify inputs and fill a 2d ndarray with specified player piece values.\n if not (specify_pieces_for_player == 1 or specify_pieces_for_player == -1):\n raise ValueError(\"specify_pieces_for_player must be 1 or -1\")\n\n allowed_piece_rows_for_player = [0, 1, 2, 3] if specify_pieces_for_player == 1 else [6, 7, 8, 9]\n specified_player_initial_piece_map = np.zeros(shape=board_shape, dtype=INT_DTYPE_NP)\n\n manual_piece_locations = {\n SP.SPY: spy_locations_list,\n SP.SCOUT: scout_locations_list,\n SP.MINER: miner_locations_list,\n SP.SERGEANT: sergeant_locations_list,\n SP.LIEUTENANT: lieutenant_locations_list,\n SP.CAPTAIN: captain_locations_list,\n SP.MAJOR: major_locations_list,\n SP.COLONEL: colonel_locations_list,\n SP.GENERAL: general_locations_list,\n SP.MARSHALL: marshall_locations_list,\n SP.FLAG: flag_locations_list,\n SP.BOMB: bomb_locations_list\n }\n\n for piece_type, locations_list in manual_piece_locations.items():\n if len(locations_list) > 0 and \\\n (len(np.shape(locations_list)) != 2 or\n (len(np.shape(locations_list)) == 2 and np.shape(locations_list)[1] != 2)):\n raise ValueError(f\"Each locations list must be a list of 2d coordinates. Examples: [] or [[1,2], [2,5]].\\n\"\n f\"For {piece_type.name}, {locations_list} was passed.\")\n\n if len(locations_list) != game_version_config['piece_amounts'][piece_type]:\n allowed_piece_amounts = {pc_type.name: amt for pc_type, amt in game_version_config['piece_amounts'].items()}\n raise ValueError(f\"{len(locations_list)} {piece_type.name} piece locations were provided when \"\n f\"{game_version.name} requires the following piece amounts: \\n{allowed_piece_amounts}\")\n\n for location in locations_list:\n row, column = location\n if (not 0 <= column < board_shape[1]) or (row not in allowed_piece_rows_for_player):\n raise ValueError(f\"The out-of-range location {location} for {piece_type.name} was provided. \"\n f\"Locations are in the format, (row, column). \"\n f\"Rows take values in {allowed_piece_rows_for_player} for player {specify_pieces_for_player}. \"\n f\"Columns must be in the range [0, {board_shape[1]}].\")\n if specified_player_initial_piece_map[row, column] != 0:\n raise ValueError(f\"The location {location} was specified for more than one piece.\")\n\n # Set piece value for location\n specified_player_initial_piece_map[row, column] = piece_type.value\n\n # Grab a random human initialization for the non-specified player.\n # Human inits have been downloaded from the Gravon Archive (https://www.gravon.de/gravon/stratego/strados2.jsp)\n random_human_init_spec_str = np.random.choice(HUMAN_INITS)\n player_1_random_human_piece_map, player_2_random_human_piece_map = create_initial_positions_from_human_data(\n player1_string=random_human_init_spec_str, player2_string=random_human_init_spec_str,\n game_version_config=game_version_config)\n\n # Set obstacle locations\n obstacle_map = np.zeros(shape=board_shape, dtype=INT_DTYPE_NP)\n for obstacle_location in VERSION_CONFIGS[game_version]['obstacle_locations']:\n obstacle_map[obstacle_location] = 1.0\n\n # Create the initial state\n initial_state = procedural_env.create_initial_state(\n obstacle_map=obstacle_map,\n player_1_initial_piece_map=specified_player_initial_piece_map if specify_pieces_for_player == 1 else player_1_random_human_piece_map,\n player_2_initial_piece_map=specified_player_initial_piece_map if specify_pieces_for_player == -1 else player_2_random_human_piece_map,\n max_turns=game_version_config['max_turns'])\n\n return initial_state","def river_region(rr_id):\n r = RiverRegionRenderer(request, rr_id, None)\n return r.render()","def get_region(ref_table, assoc_name=None,\n pos_margin=10., vel_margin=2.,\n scale_margin=None, mg_colname=None):\n\n ## Commenting this out for now. Usage by me (Tim) should be the same\n ## as everyone else. i.e. no hardcoded filenames for convenience.\n # if gagne_reference_data is None:\n # gagne_reference_data =\\\n # '/home/tcrun/chronostar/data/gagne_bonafide_full_kinematics_with_lit_and_best_radial_velocity' \\\n # '_comb_binars_with_banyan_radec.fits'\n\n if mg_colname is None:\n mg_colname = 'Moving group'\n\n # If reference table is provided as str, convert to table\n if type(ref_table) is str:\n ref_table = Table.read(ref_table)\n\n # Extract all stars\n if assoc_name is None:\n subtable = ref_table\n else:\n if assoc_name not in set(ref_table[mg_colname]):\n raise UserWarning(\n 'Association name must be one of:\\n{}\\nReceived: \"{}\"'.format(\n list(set(ref_table[mg_colname])), assoc_name\n ))\n subtable = ref_table[np.where(ref_table[mg_colname] == assoc_name)]\n logging.info('Initial membership list has {} members'.format(len(subtable)))\n\n star_means = tabletool.build_data_dict_from_table(subtable, only_means=True,\n cartesian=True)\n\n data_upper_bound = np.nanmax(star_means, axis=0)\n data_lower_bound = np.nanmin(star_means, axis=0)\n logging.info('Stars span from {} to {}'.format(\n np.round(data_lower_bound),\n np.round(data_upper_bound)\n ))\n\n # First try and scale box margins by provided scale margin.\n # scale_margin of 1 would double total span (1 + 1)\n if scale_margin is not None:\n data_span = data_upper_bound - data_lower_bound\n box_margin = 0.5 * scale_margin * data_span\n\n # Set up boundaries of box that span double the association\n box_lower_bound = data_lower_bound - box_margin\n box_upper_bound = data_upper_bound + box_margin\n\n # Set margin based on provided (or default) constant amounts\n else:\n data_margin = np.array(3*[pos_margin] + 3*[vel_margin])\n box_lower_bound = data_lower_bound - data_margin\n box_upper_bound = data_upper_bound + data_margin\n\n logging.info('Range extended.\\nLower: {}\\nUpper: {}'.format(\n np.round(box_lower_bound),\n np.round(box_upper_bound)\n ))\n\n return box_lower_bound, box_upper_bound","def init(self):\n\n self.pos = np.random.rand(self.N, 7)\n for i in range(3):\n self.pos[:, i] *= (self.bounds[2*i+1] - self.bounds[2*i])\n self.pos[:, i] += self.bounds[2*i]\n\n # Star colors http://www.isthe.com/chongo/tech/astro/HR-temp-mass-table-byhrclass.html http://www.vendian.org/mncharity/dir3/starcolor/\n O3 = np.array([144., 166., 255.])\n O3 /= 255.\n self.pos[:, 3:-1] = O3[None, :]\n M4Ia = np.array([255., 185., 104.])\n M4Ia /= 255.\n self.pos[np.random.rand(self.N)>.5, 3:-1] = M4Ia[None, :]\n\n self.pos[:, -1] = .8 + .2*self.pos[:, -1]","def set_board(board):","def __init__(self, rows=8, cols=8):\n self.rows = rows\n self.cols = cols\n self.matrix = [[Disk.NONE for x in range(rows)] for y in range(cols)]\n init_array = (('d','4',Disk.LIGHT), ('e','5',Disk.LIGHT), ('d','5',Disk.DARK), ('e','4',Disk.DARK))\n # init_array = (('a', '2', Disk.LIGHT), ('b', '5', Disk.LIGHT), ('d', '5', Disk.DARK), ('e', '4', Disk.DARK))\n for item in init_array:\n self.place_disk(*self.coordinates_to_matrix(item[0], item[1]), item[2])","def new_tile(self):\n # replace with your code\n empty_list = []\n counter_1 = 0\n for _ in self._grid:\n counter_2 = 0\n line = _\n for blank in line:\n if blank == 0:\n blank_tile = (counter_1, counter_2)\n empty_list.append(blank_tile)\n counter_2 += 1\n else:\n counter_2 += 1\n counter_1 += 1\n #print empty_list\n \n self._tile = empty_list[random.randrange(len(empty_list))]\n \n value = [2,2,2,2,2,2,2,2,2,4]\n tile_value = value[random.randint(0,9)]\n \n self.set_tile(self._tile[0], self._tile[1], tile_value)","def generate_level(self):\n for _ in range(AMOUNT_REGIONS_TO_DRAW):\n self._generate_next_blocks()","def _loadRegions(self, fh):\n holeNumbers = self._mainBasecallsGroup[\"ZMW/HoleNumber\"].value\n self._holeNumberToIndex = dict(zip(holeNumbers, range(len(holeNumbers))))\n\n #\n # Region table\n #\n self.regionTable = toRecArray(REGION_TABLE_DTYPE,\n fh[\"/PulseData/Regions\"].value)\n\n self._regionTableIndex = _makeRegionTableIndex(self.regionTable.holeNumber)\n isHqRegion = self.regionTable.regionType == HQ_REGION\n hqRegions = self.regionTable[isHqRegion]\n\n if len(hqRegions) != len(holeNumbers):\n # Bug 23585: pre-2.1 primary had a bug where a bas file\n # could get a broken region table, lacking an HQ region\n # entry for a ZMW. This happened fairly rarely, mostly on\n # very long traces. Workaround here is to rebuild HQ\n # regions table with empty HQ region entries for those\n # ZMWs.\n hqRegions_ = toRecArray(REGION_TABLE_DTYPE,\n np.zeros(shape=len(holeNumbers),\n dtype=REGION_TABLE_DTYPE))\n hqRegions_.holeNumber = holeNumbers\n for record in hqRegions:\n hn = record.holeNumber\n hqRegions_[self._holeNumberToIndex[hn]] = record\n hqRegions = hqRegions_\n\n hqRegionLength = hqRegions.regionEnd - hqRegions.regionStart\n holeStatus = self._mainBasecallsGroup[\"ZMW/HoleStatus\"].value\n\n #\n # Sequencing ZMWs - Note: this differs from Primary's\n # definition. To obtain those values, one would use the\n # `allSequencingZmws` property.\n #\n self._sequencingZmws = \\\n holeNumbers[(holeStatus == SEQUENCING_ZMW) &\n (self._mainBasecallsGroup[\"ZMW/NumEvent\"].value > 0) &\n (hqRegionLength > 0)]\n\n self._allSequencingZmws = holeNumbers[holeStatus == SEQUENCING_ZMW]","def update_temperature_region(self):\n self.linear_region.setRegion(\n self.temperature_plot_graph.getViewBox().viewRange()[0])","def _regions_shmem_config(self) -> None:\n assert self.config is not None\n assert self.board is not None\n\n if not self.config.shmem:\n return\n\n for name, shmem_config in self.config.shmem.items():\n for cell_name in shmem_config.peers:\n cell = self.config.cells[cell_name]\n assert cell.pci_devices is not None\n\n # offset 2, since mem_regions always\n # start with table_region and common_output_region\n dev_id = cell.pci_devices[name].shmem_dev_id\n assert dev_id is not None\n assert cell.memory_regions is not None\n\n grouped_region_name = f\"{name}\"\n grouped_region = cell.memory_regions[grouped_region_name]\n\n cell_output_region = grouped_region.regions[2 + dev_id]\n\n def get_mem_region_index(cell, name):\n ret = -1\n index = 0\n\n for region_name, region in cell.memory_regions.items():\n if region_name == name:\n ret = index\n break\n\n if isinstance(region, GroupedMemoryRegion):\n index += len(region.regions)\n else:\n index += 1\n\n if ret == -1:\n raise Exception(\n f\"Invalid cells.yaml, not a memory-region: {name}\"\n )\n\n return ret\n\n shmem_regions_start = get_mem_region_index(\n cell, grouped_region_name\n )\n cell.pci_devices[name].shmem_regions_start = shmem_regions_start\n\n new_cell_output_region = copy.copy(cell_output_region)\n new_cell_output_region.flags = copy.copy(\n cell_output_region.flags\n )\n new_cell_output_region.flags.append(\"MEM_WRITE\")\n\n grouped_region.regions[2 + dev_id] = new_cell_output_region","def set_tile(self, row, col, value):\n # replace with your code\n self.grid[row][col] = value"],"string":"[\n \"def initialize_region(self):\\n self.new_region_name = \\\"\\\"\\n self.map.regions.create_new_region()\",\n \"def set_region(sender, instance, *args, **kwargs):\\n if instance.geocity and not instance.georegion:\\n instance.georegion = instance.geocity.region\",\n \"def test_assign_to_regions(self):\\n \\n tool = pybedtools.BedTool(clipper.test_file(\\\"FOX2Brain-05.15.09.polyATrim.adapterTrim.rmRep.sorted.rmDup.peaks.bed\\\"))\\n \\n assign_to_regions(tool=tool, \\n clusters=\\\"test\\\", \\n speciesFA= clipper.test_file(\\\"mm9.fa\\\"), \\n regions_dir=os.path.join(clipper.test_dir(), \\\"regions\\\"), \\n regions={\\\"exons\\\" : \\\"Exon\\\", \\\"utr3\\\" : \\\"3' UTR\\\", \\n \\\"utr5\\\" : \\\"5' UTR\\\", \\\"proxintron500\\\" : \\\"Proximal Intron\\\", \\n \\\"distintron500\\\" : \\\"Distal Intron\\\"} ,\\n assigned_dir = clipper.test_dir(),\\n fasta_dir = clipper.test_dir(),\\n species=\\\"mm9\\\", \\n nrand = 3, \\n getseq=False)\",\n \"def region(self):\\n return self.random_element(self._regions)\",\n \"def __init__(self, region):\\r\\n self.region = region\",\n \"def putregion(self, *args, **kwargs):\\n return _image.image_putregion(self, *args, **kwargs)\",\n \"def add_region(self, position):\\n region = self.region_selector(position)\\n self.regions[id(region)] = region\",\n \"def set_locations():\\n STATUS['locations']['monster'][0] = generate_random_coord(STATUS['grid_size'])\\n STATUS['locations']['monster'][1] = generate_random_coord(STATUS['grid_size'])\\n STATUS['locations']['weapon'][0] = generate_random_coord(STATUS['grid_size'])\\n STATUS['locations']['weapon'][1] = generate_random_coord(STATUS['grid_size'])\",\n \"def __init__(self, world, location, elevation):\\n LandCell.__init__(self, world, location, elevation)\\n self.plant = 0\\n self.reset_food_level()\",\n \"def to_region(self):\\n\\n coords = self.convert_coords()\\n log.debug(coords)\\n viz_keywords = ['color', 'dash', 'dashlist', 'width', 'font', 'symsize',\\n 'symbol', 'symsize', 'fontsize', 'fontstyle', 'usetex',\\n 'labelpos', 'labeloff', 'linewidth', 'linestyle',\\n 'point', 'textangle', 'fontweight']\\n\\n if isinstance(coords[0], SkyCoord):\\n reg = self.shape_to_sky_region[self.region_type](*coords)\\n elif isinstance(coords[0], PixCoord):\\n reg = self.shape_to_pixel_region[self.region_type](*coords)\\n else:\\n self._raise_error(\\\"No central coordinate\\\")\\n\\n reg.visual = RegionVisual()\\n reg.meta = RegionMeta()\\n\\n # both 'text' and 'label' should be set to the same value, where we\\n # default to the 'text' value since that is the one used by ds9 regions\\n label = self.meta.get('text',\\n self.meta.get('label', \\\"\\\"))\\n if label != '':\\n reg.meta['label'] = label\\n for key in self.meta:\\n if key in viz_keywords:\\n reg.visual[key] = self.meta[key]\\n else:\\n reg.meta[key] = self.meta[key]\\n reg.meta['include'] = self.include\\n return reg\",\n \"def region(self, region):\\n \\n self._region = region\",\n \"def create_panel_custom_regions():\\n panel_id = request.json[\\\"panel_id\\\"]\\n chrom = request.json[\\\"chrom\\\"]\\n start = request.json[\\\"start\\\"]\\n end = request.json[\\\"end\\\"]\\n name = request.json[\\\"name\\\"]\\n regions = select_region_by_location(s, chrom, start, end) # if region already exists, return current entry\\n if regions:\\n for i in regions:\\n add_region_to_panel(s, i.id, panel_id)\\n s.commit()\\n continue\\n else:\\n create_custom_region(s, panel_id, chrom, start, end, name)\\n\\n return jsonify(\\\"complete\\\")\",\n \"def region_setup(self, slices, ipa_regions):\\n self.ipa_regions = ipa_regions\\n self.slices = slices\",\n \"def __init__(self):\\n self.regions = []\",\n \"def assign(self):\\n\\n for s in self.spots:\\n if self.cells[s[:2]] == 0:\\n label = find_nearest_region(self.cells, *s[:2])\\n else:\\n label = self.cells[s[:2]]\\n\\n s.region = label\",\n \"def create_region(self, region_ref):\\n raise exception.NotImplemented() # pragma: no cover\",\n \"def regions(self, regions):\\n self._regions = regions\",\n \"def region(self, region: str) -> Region:\\n return Region(self, region)\",\n \"def region(self, region):\\n\\n self._region = region\",\n \"def region(self, region):\\n\\n self._region = region\",\n \"def region(self, region):\\n\\n self._region = region\",\n \"def create(self):\\n assert self.name != \\\"Settings\\\", \\\"Cannot create a new mesh region with this Name\\\"\\n args = [\\\"NAME:\\\" + self.name, \\\"Enable:=\\\", self.Enable]\\n if self.UserSpecifiedSettings:\\n args += self.manualsettings\\n else:\\n args += self.autosettings\\n self.meshmodule.AssignMeshRegion(args)\\n return True\",\n \"def update_region_config(cls, body: CloudAccountRegionConfigurationViewModel) -> Dict:\\n\\t\\tpass\",\n \"def add_cloud_region(self, position):\\n region = self.cloud_region_selector(position)\\n self.regions[id(region)] = region\",\n \"def assign_mesh_region(self, objectlist=[], level=5, is_submodel=False, name=None):\\n if not name:\\n name = generate_unique_name(\\\"MeshRegion\\\")\\n meshregion = self.MeshRegion(self.omeshmodule, self.boundingdimension, self.modeler.model_units)\\n meshregion.UserSpecifiedSettings = False\\n meshregion.Level = level\\n meshregion.name = name\\n if not objectlist:\\n objectlist = [i for i in self.modeler.primitives.object_names]\\n if is_submodel:\\n meshregion.SubModels = objectlist\\n else:\\n meshregion.Objects = objectlist\\n all_objs = [i for i in self.modeler.primitives.object_names]\\n meshregion.create()\\n objectlist2 = self.modeler.primitives.object_names\\n added_obj = [i for i in objectlist2 if i not in all_objs]\\n meshregion.Objects = added_obj\\n meshregion.SubModels = None\\n self.meshregions.append(meshregion)\\n return meshregion\",\n \"def __init__(self, world, location, elevation):\\n LandCell.__init__(self, world, location, elevation)\",\n \"def region(self, region_name):\\n return Region(region_name, self)\",\n \"def build_region(self, \\n dataset_metadata_dict,\\n min_lod_pixels=100, \\n max_lod_pixels=-1, \\n min_fade_extent=200, \\n max_fade_extent=800\\n ):\\n\\n region = simplekml.Region(latlonaltbox=\\\"<north>\\\" + str(dataset_metadata_dict['latitude_max']) + \\\"</north>\\\" +\\n \\\"<south>\\\" + str(dataset_metadata_dict['latitude_min']) + \\\"</south>\\\" +\\n \\\"<east>\\\" + str(dataset_metadata_dict['longitude_max']) + \\\"</east>\\\" +\\n \\\"<west>\\\" + str(dataset_metadata_dict['longitude_min']) + \\\"</west>\\\",\\n lod=\\\"<minLodPixels>\\\" + str(min_lod_pixels) + \\\"</minLodPixels>\\\" +\\n \\\"<maxLodPixels>\\\" + str(max_lod_pixels) + \\\"</maxLodPixels>\\\" +\\n \\\"<minFadeExtent>\\\" + str(min_fade_extent) + \\\"</minFadeExtent>\\\" +\\n \\\"<maxFadeExtent>\\\" + str(max_fade_extent) + \\\"</maxFadeExtent>\\\")\\n return region\",\n \"def initialize_areas(self):\\n self._areas[1] = copy.copy(self._areas[0])\",\n \"def random_offset_bounds(self) -> utils.BoxRegion:\\n extra_size = self.random_canvas_extra_ratio * self.canvas_bounds().size / 2\\n return utils.BoxRegion(\\n minimum=-extra_size,\\n maximum=extra_size\\n )\",\n \"def default_zone(self, region):\\n if region == 'us-east-1':\\n return region + 'b'\\n else:\\n return region + 'a'\",\n \"def __init__(self, *args, **kwargs):\\n _gdi_.Region_swiginit(self,_gdi_.new_Region(*args, **kwargs))\",\n \"def new_tile(self):\\n rowm, colm = self.get_ava_index()\\n value = 2 if random() <= 0.90 else 4\\n self.set_tile(rowm, colm, value)\\n print rowm,colm,value\",\n \"def SetRegion(self,stateAbbrev):\\n if not stateAbbrev in self.VectorData:\\n print \\\"Error - No Data for %s available\\\" % stateAbbrev\\n print \\\"Valid state abbreviations are:\\\", self.StateAbbrevList\\n else:\\n self.SelectedRegion = stateAbbrev\",\n \"def setUpClass(cls):\\n cls.use_temp_region()\\n cls.runModule(\\\"g.region\\\", raster=\\\"elev_state_500m\\\")\",\n \"def clear(self):\\n tmpRegion = self._createBlankCopy()\\n self._assign(tmpRegion)\\n if self._ancestorModelSourceCreated:\\n self._reload()\\n else:\\n self._informRegionChange(True)\",\n \"def _choose_regions(self, display_regions=False):\\n dstl = Load_DSTL()\\n if self.class_type == 1:\\n # Select regions where there are buildings (with red roofs)\\n test_image, test_mask = dstl.extract_region_pos(2300, 3000, cutout_size=[400, 400], object_class=self.class_type)\\n train_image, train_mask = dstl.extract_region_pos(1900, 3100, cutout_size=[400, 400], object_class=self.class_type)\\n cv_image, cv_mask = dstl.extract_region_pos(950, 1450, cutout_size=[200, 200], object_class=self.class_type)\\n elif self.class_type == 5:\\n train_image, train_mask = dstl.extract_region_pos(1150, 2150, cutout_size=[400, 400], object_class=self.class_type)\\n test_image, test_mask = dstl.extract_region_pos(2300, 3000, cutout_size=[400, 400], object_class=self.class_type)\\n cv_image, cv_mask = dstl.extract_region_pos(1900, 1950, cutout_size=[400, 400], object_class=self.class_type)\\n else:\\n pass\\n self.images = {'train': train_image, 'cv': cv_image, 'test': test_image}\\n self.masks = {'train': train_mask, 'cv': cv_mask, 'test': test_mask}\\n if display_regions:\\n for key in self.images.keys():\\n display_three_band(self.images[key], self.masks[key], colors='green', title='{:} region'.format(key))\",\n \"def sampleRegionPowerModel():\\n\\tregionVector = []\\n\\t# Loop through regional rounds R64, R32, and S16\\n\\tseeds = [1, 16, 8, 9, 5, 12, 4, 13, 6, 11, 3, 14, 7, 10, 2, 15]\\n\\tfor roundNum in range(1, 5):\\n\\t\\tnumGames = int(len(seeds) / 2)\\n\\t\\tnewSeeds = []\\n\\t\\tfor gameNum in range(numGames):\\n\\t\\t\\ts1 = seeds[2 * gameNum]\\n\\t\\t\\ts2 = seeds[2 * gameNum + 1]\\n\\t\\t\\tp = getWinProbability({'seed': s1}, {'seed': s2}, r=roundNum)\\n\\n\\t\\t\\trnd = random.random()\\n\\t\\t\\tregionVector.append(1 if rnd < p else 0)\\n\\t\\t\\tnewSeeds.append(s1 if rnd < p else s2)\\n\\t\\tseeds = newSeeds\\n\\n\\treturn [regionVector, seeds[0]]\",\n \"def set_x_y(region, x_offset, y_offset):\\n for x in range(region.shape[0]):\\n for y in range(region.shape[1]):\\n region[x, y, 0] = x_offset + 5*x\\n region[x, y, 1] = y_offset + 5*y\\n \\n return region\",\n \"def add_region_feature(data):\\n\\n data.loc[:, 'region'] = data.loc[:, 'district'].apply(\\n lambda x: mapping.SOFIA_NEIGHBOURHOOD_TO_REGION_MAPPING[x]\\n )\\n\\n return data\",\n \"def update_humidity_region(self):\\n self.linear_region.setRegion(\\n self.humidity_plot_graph.getViewBox().viewRange()[0])\",\n \"def set_sample_region(self):\\n\\n theta_delta = self.wrap(self.start[0:3], self.goal[0:3])\\n\\n delta_signs = np.sign(self.goal[0:3] - self.start[0:3])\\n\\n self.smart_region_min = self.start\\n\\n self.smart_region_max = self.start + delta_signs * theta_delta\\n\\n velocity_min = np.zeros(3,1)\\n\\n \\n for i in range(3):\",\n \"def set_sample_region(self):\\n\\n theta_delta = self.wrap(self.start[0:3], self.goal[0:3])\\n\\n delta_signs = np.sign(self.goal[0:3] - self.start[0:3])\\n\\n self.smart_region_min = self.start\\n\\n self.smart_region_max = self.start + delta_signs * theta_delta\\n\\n velocity_min = np.zeros(3,1)\\n\\n \\n for i in range(3):\",\n \"def __init__(\\n self,\\n location: FeatureLocation,\\n reference_sequence: Seq,\\n name: str = None\\n ):\\n super().__init__('repeat_region', location=location, reference_sequence=reference_sequence, name=name)\",\n \"def set_region_of_interest(self, roi: UserRoi):\\n value = roi.to_struct()\\n Utils.check(VL53L1X_C_LIBRARY.VL53L1_SetUserROI(self.dev, byref(value)))\",\n \"def ZoneBuilder():\\n\\n # Part 1: Zone Dimensions\\n matrix, xaxis, yaxis, zaxis = dimensions()\\n\\n # Part 2: Assigning Room Existance.\\n matrix = existance(matrix, xaxis, yaxis, zaxis)\\n \\n # Part 3: Creating room walls.\\n \\n # First, generate walls adjacent to void spaces.\\n matrix = enclose_rooms(matrix, xaxis, yaxis, zaxis)\\n \\n matrix = select_walls(matrix, xaxis, yaxis, zaxis)\",\n \"def add_new_region(self, image_name: str, region_text: str, region_position: RegionPosition, region_type: str):\\n pass\",\n \"def region(self, box):\\n is_indexbox(box, errors=\\\"raise\\\") # Validate the box definition\\n self.fetcher = self.Fetchers[\\\"region\\\"](box=box, **self.fetcher_options)\\n self._AccessPoint = \\\"region\\\" # Register the requested access point\\n return self\",\n \"def set_roi(self, y_min, height):\\n self.camera_microscope.stop_free_run()\\n self.camera_microscope.stop_continuous_reads()\\n self.background = None # This is to prevent shape mismatch between before and after\\n current_roi = self.camera_microscope.ROI\\n new_roi = (current_roi[0], (y_min, height))\\n self.camera_microscope.ROI = new_roi\\n self.camera_microscope.start_free_run()\\n self.camera_microscope.continuous_reads()\",\n \"def region(self, box: list):\\n is_box(box, errors=\\\"raise\\\") # Validate the box definition\\n self.fetcher = self.Fetchers[\\\"region\\\"](box=box, **self.fetcher_options)\\n self._AccessPoint = \\\"region\\\" # Register the requested access point\\n self._AccessPoint_data = {'box': box} # Register the requested access point data\\n\\n if self._mode == \\\"standard\\\" and self._dataset_id != \\\"ref\\\":\\n def postprocessing(xds):\\n xds = self.fetcher.filter_data_mode(xds)\\n xds = self.fetcher.filter_qc(xds)\\n xds = self.fetcher.filter_variables(xds, self._mode)\\n return xds\\n self.postproccessor = postprocessing\\n\\n return self\",\n \"def create_meshregion_component(\\n self, scale_factor=1.0, name=\\\"Component_Region\\\", restore_padding_values=[50, 50, 50, 50, 50, 50]\\n ):\\n self.modeler.edit_region_dimensions([0, 0, 0, 0, 0, 0])\\n\\n verticesID = self.modeler.oeditor.GetVertexIDsFromObject(\\\"Region\\\")\\n\\n x_values = []\\n y_values = []\\n z_values = []\\n\\n for id in verticesID:\\n tmp = self.modeler.oeditor.GetVertexPosition(id)\\n x_values.append(tmp[0])\\n y_values.append(tmp[1])\\n z_values.append(tmp[2])\\n\\n scale_factor = scale_factor - 1\\n delta_x = (float(max(x_values)) - float(min(x_values))) * scale_factor\\n x_max = float(max(x_values)) + delta_x / 2.0\\n x_min = float(min(x_values)) - delta_x / 2.0\\n\\n delta_y = (float(max(y_values)) - float(min(y_values))) * scale_factor\\n y_max = float(max(y_values)) + delta_y / 2.0\\n y_min = float(min(y_values)) - delta_y / 2.0\\n\\n delta_z = (float(max(z_values)) - float(min(z_values))) * scale_factor\\n z_max = float(max(z_values)) + delta_z / 2.0\\n z_min = float(min(z_values)) - delta_z / 2.0\\n\\n dis_x = str(float(x_max) - float(x_min))\\n dis_y = str(float(y_max) - float(y_min))\\n dis_z = str(float(z_max) - float(z_min))\\n\\n min_position = self.modeler.Position(str(x_min) + \\\"mm\\\", str(y_min) + \\\"mm\\\", str(z_min) + \\\"mm\\\")\\n mesh_box = self.modeler.primitives.create_box(min_position, [dis_x + \\\"mm\\\", dis_y + \\\"mm\\\", dis_z + \\\"mm\\\"], name)\\n\\n self.modeler.primitives[name].model = False\\n\\n self.modeler.edit_region_dimensions(restore_padding_values)\\n return dis_x, dis_y, dis_z\",\n \"def __init__(self, type, high_elevation, low_elevation):\\n\\t\\tself.type = type\\n\\t\\tself.high_elevation = high_elevation\\n\\t\\tself.low_elevation = low_elevation\\n\\t\\tself.occupant = 0 # use 0 to initilize tile which \\n\\t\\t\\t\\t\\t\\t\\t# means it has not been explored.\\n\\t\\tif type == \\\"plains\\\": # initialize the shade\\n\\t\\t\\tself.terrain = \\\" \\\"\\n\\t\\telse:\\n\\t\\t\\tself.terrain = \\\"#\\\"\",\n \"def initialize_board(self):\\n self.board = np.zeros(shape=(BOARD_SIZE, BOARD_SIZE), dtype=np.int) # another way of defining board: [[for x in range(cm.BOARD_SIZE)] for x in range(cm.BOARD_SIZE)]\\n center = int(BOARD_SIZE / 2)\\n self.board[center-1][center-1] = self.board[center][center] = WHITE # place the board according to position\\n self.board[center][center-1] = self.board[center-1][center] = BLACK\\n self.black_piece = 2\\n self.white_piece = 2\",\n \"def configure_multisite_regions_and_zones(ctx, config, regions, role_endpoints, realm, master_client):\\n if not regions:\\n log.debug(\\n 'In rgw.configure_multisite_regions_and_zones() and regions is None. '\\n 'Bailing')\\n yield\\n return\\n\\n if not realm:\\n log.debug(\\n 'In rgw.configure_multisite_regions_and_zones() and realm is None. '\\n 'Bailing')\\n yield\\n return\\n\\n log.info('Configuring multisite regions and zones...')\\n\\n log.debug('config is %r', config)\\n log.debug('regions are %r', regions)\\n log.debug('role_endpoints = %r', role_endpoints)\\n log.debug('realm is %r', realm)\\n # extract the zone info\\n role_zones = dict([(client, extract_zone_info(ctx, client, c_config))\\n for client, c_config in config.items()])\\n log.debug('role_zones = %r', role_zones)\\n\\n # extract the user info and append it to the payload tuple for the given\\n # client\\n for client, c_config in config.items():\\n if not c_config:\\n user_info = None\\n else:\\n user_info = extract_user_info(c_config)\\n\\n (region, zone) = role_zones[client]\\n role_zones[client] = (region, zone, user_info)\\n\\n region_info = dict([\\n (region_name, extract_region_info(region_name, r_config))\\n for region_name, r_config in regions.items()])\\n\\n fill_in_endpoints(region_info, role_zones, role_endpoints)\\n\\n\\n host, port = role_endpoints[master_client]\\n endpoint = 'http://{host}:{port}/'.format(host=host, port=port)\\n log.debug(\\\"endpoint: %s\\\", endpoint)\\n\\n # clear out the old defaults\\n cluster_name, daemon_type, client_id = teuthology.split_role(master_client)\\n first_mon = teuthology.get_first_mon(ctx, config, cluster_name)\\n (mon,) = iter(ctx.cluster.only(first_mon).remotes.keys())\\n\\n # read master zonegroup and master_zone\\n for zonegroup, zg_info in region_info.items():\\n if zg_info['is_master']:\\n master_zonegroup = zonegroup\\n master_zone = zg_info['master_zone']\\n break\\n\\n log.debug('master zonegroup =%r', master_zonegroup)\\n log.debug('master zone = %r', master_zone)\\n log.debug('master client = %r', master_client)\\n\\n rgwadmin(ctx, master_client,\\n cmd=['realm', 'create', '--rgw-realm', realm, '--default'],\\n check_status=True)\\n\\n rgwadmin(ctx, master_client,\\n cmd=['zonegroup', 'create', '--rgw-zonegroup', master_zonegroup, '--master', '--endpoints', endpoint,\\n '--default'])\\n\\n rgwadmin(ctx, master_client,\\n cmd=['zone', 'create', '--rgw-zonegroup', master_zonegroup,\\n '--rgw-zone', master_zone, '--endpoints', endpoint, '--access-key',\\n user_info['system_key']['access_key'], '--secret',\\n user_info['system_key']['secret_key'], '--master', '--default'],\\n check_status=True)\\n\\n rgwadmin(ctx, master_client,\\n cmd=['period', 'update', '--commit'],\\n check_status=True)\\n\\n yield\",\n \"def create_region_w_spacing (tuple_top_L, tuple_bottom_R):\\n\\n spacing = int(input ('How many well spaces do you want between each spot? '))\\n\\n\\n #get the plate column numbers from the plate class\\n columns = plate1536.columns\\n #get the plate rows from the plate class\\n rows = plate1536.rows\\n\\n ###Begin creating list of columns to use###\\n\\n #initialize and use next\\n curr_col_idx = columns.index(int(tuple_top_L[1]))\\n\\n #set left most column to use as the column given by user in top_left\\n col_idxs_to_shoot = [curr_col_idx]\\n\\n #loop checks the NEXT column that will be produced by moving right\\n #by (spacing + 1). If that is beyond the right-most border set by\\n #the well region definitions, then it will stop, containing all\\n #column choices within the left and right bounds\\n while (curr_col_idx + spacing + 1) <= columns.index(int(tuple_bottom_R[1])):\\n\\n curr_col_idx += (spacing + 1)\\n\\n col_idxs_to_shoot.append(curr_col_idx)\\n\\n ###The list of indices in plate1536.columns to use is now set###\\n\\n\\n ###Begin creating list of rows to use###\\n\\n #initialize and use next\\n curr_row_idx = rows.index(tuple_top_L[0])\\n\\n #set top most row to use as the row given by user in top_left\\n row_idxs_to_shoot = [curr_row_idx]\\n\\n #loop checks the NEXT row that will be produced by moving down\\n #by (spacing + 1). If that is beyond the bottom-most border set by\\n #the well region definitions, then it will stop, containing all\\n #row choices within the top and bottom bounds\\n while (curr_row_idx + spacing + 1) <= rows.index(tuple_bottom_R[0]):\\n\\n curr_row_idx += (spacing + 1)\\n\\n row_idxs_to_shoot.append(curr_row_idx)\\n\\n ###The list of indices in plate1536.rows to use is now set###\\n\\n\\n #get all the columns you want to use as STRINGS\\n col_strs = []\\n for i in col_idxs_to_shoot:\\n col_strs += [ str(plate1536.columns[i]) ] #have to have extra list brackets to avoid python interpreting a string 'FFF' as\\n #a list ['F', 'F', 'F'] and adding 3 items instead of 'FFF'\\n\\n #get all the rows you want to use as STRINGS\\n row_strs = []\\n for i in row_idxs_to_shoot:\\n row_strs += [ plate1536.row_dict[i] ]#have to have extra list brackets to avoid python interpreting a string 'FFF' as\\n #a list ['F', 'F', 'F'] and adding 3 items instead of 'FFF'\\n\\n\\n print(\\\"This region has {} rows (letters), {} columns (#'s) per row. That's a total of {} spots\\\".format(len(row_strs), len(col_strs), len(row_strs) * len(col_strs)))\\n\\n return row_strs, col_strs\",\n \"def add_regions(self, regions, **options):\\n \\n options.setdefault(\\\"col\\\", color(0,0,1))\\n options.setdefault(\\\"style\\\", \\\"box\\\")\\n options.setdefault(\\\"height\\\", 0.5)\\n \\n return self.add_track(RegionTrack, -.5, regions, **options)\",\n \"def assignToRegion(self, region):\\n self._sim.assignReactionRegion(self, region)\\n return self\",\n \"def region(location):\\n x, y = location\\n if y < 89:\\n return \\\"left-door\\\" if x < 56 else \\\"middle-platform\\\" if x < 102 else \\\"right-door\\\"\\n elif y < 124:\\n return \\\"left-platform\\\" if x < 39 else \\\"belt\\\" if x < 79 else \\\"middle-ladder\\\" if x < 81 else \\\"belt\\\" if x < 111 else \\\"rope\\\" if x < 113 else \\\"right-platform\\\"\\n elif y < 127:\\n return \\\"left-platform\\\" if x < 39 else \\\"belt\\\" if x < 111 else \\\"rope\\\" if x < 113 else \\\"right-platform\\\"\\n elif y < 150:\\n return \\\"left-ladder\\\" if x < 32 else \\\"floor\\\" if x < 111 else \\\"rope\\\" if x < 113 else \\\"floor\\\" if x < 128 else \\\"right-ladder\\\"\\n elif y < 168:\\n return \\\"left-ladder\\\" if x < 32 else \\\"floor\\\" if x < 128 else \\\"right-ladder\\\"\\n else:\\n return \\\"floor\\\"\",\n \"def spawn_orb(self):\\n x_pos = random.randint(0, self.config.arena_size[0] - 1)\\n y_pos = random.randint(0, self.config.arena_size[1] - 1)\\n self.arena[x_pos][y_pos] = Tile.ORB\",\n \"def region(self):\\n if self._region is None:\\n cache_key = self.expand_name(\\\"region\\\")\\n cached = unitdata.kv().get(cache_key)\\n if cached:\\n self._region = cached\\n else:\\n req = self._imdv2_request(self._az_url)\\n with urlopen(req) as fd:\\n az = fd.read(READ_BLOCK_SIZE).decode(\\\"utf8\\\")\\n self._region = az.rstrip(string.ascii_lowercase)\\n unitdata.kv().set(cache_key, self._region)\\n return self._region\",\n \"def update_resistance_region(self):\\n self.linear_region.setRegion(\\n self.resistance_graph.getViewBox().viewRange()[0])\",\n \"def prepare_region(path: Path, region: mundi.Region):\\n\\n # Age distribution \\n df = region.age_distribution\\n distrib = df.values.copy()[:18:2]\\n distrib += df.values[1:18:2]\\n distrib[-1] += df.values[18:].sum()\\n \\n # Estimate cases from deaths\\n curve = covid19.epidemic_curve(region, path=CASES)\\n deaths = cast(pd.Series,\\n curve[\\\"deaths\\\"]\\n .rolling(WINDOW_SIZE, center=True, win_type=\\\"triang\\\")\\n .mean()\\n .fillna(method=\\\"bfill\\\")\\n .dropna()\\n )\\n params = covid19.params(region=region)\\n cases = (deaths / params.IFR).astype(\\\"int\\\")\\n epicurve = cases.diff().fillna(0).astype(\\\"int\\\").values\\n attack = 100 * cases.iloc[-1] / region.population\\n print(\\\"Attack rate: {:n}%\\\".format(attack))\\n \\n # Clean epicurve\\n i, j = 0, len(epicurve) - 1\\n while epicurve[i] == 0:\\n i += 1\\n \\n while epicurve[j] == 0:\\n j -= 1\\n \\n if (n := len(epicurve) - j -1):\\n m = n + WINDOW_SIZE // 2\\n epicurve = list(epicurve)[:j - WINDOW_SIZE // 2]\\n print(f'WARNING: {region.id} tail with {n} null items. trucanting epicurve to a {m} delay')\\n n += WINDOW_SIZE // 2\\n epicurve = epicurve[i:j]\\n \\n # Create config\\n conf = TOML_TEMPLATE.format(\\n num_iter=60,\\n pop_counts=list(distrib),\\n epicurve_data=list(epicurve),\\n smoothness=0.75,\\n delay=n,\\n attack=attack,\\n ) \\n \\n with open(path / 'conf.toml', 'w') as fd:\\n fd.write(conf)\",\n \"def _create_room(new_map, room):\\n for x in range(room.x1 + 1, room.x2):\\n for y in range(room.y1 + 1, room.y2):\\n new_map.terrain[x][y] = 1\",\n \"def setup(self):\\n self.board[(3, 3)] = -1\\n self.board[(3, 4)] = -1\\n self.board[(4, 3)] = 1\\n self.board[(4, 4)] = 1\\n\\n self.stones_set = 4\",\n \"def __set_mask_regions(self):\\n self.bottom_clip = np.int32(np.int32([[[60,0], [1179,0], [1179,650], [60,650]]]))\\n self.roi_clip = np.int32(np.int32([[[640, 425], [1179,550], [979,719],\\n [299,719], [100, 550], [640, 425]]]))\",\n \"def nine_regions(self):\\n\\n coordinateList = []\\n\\n # Top left.\\n x = (int)( self.oriImgSize[IDX_WIDTH] * self.ratioTopLeft[IDX_X] )\\n y = (int)( self.oriImgSize[IDX_HEIGHT] * self.ratioTopLeft[IDX_Y] )\\n coordinateList.append( [x, y] )\\n\\n # Top center.\\n x = (int)( self.oriImgSize[IDX_WIDTH] * 0.5 - self.regionSize[IDX_WIDTH] / 2 )\\n y = (int)( self.oriImgSize[IDX_HEIGHT] * self.ratioTopLeft[IDX_Y] ) \\n coordinateList.append( [x, y] )\\n\\n # Top right.\\n x = (int)( self.oriImgSize[IDX_WIDTH] * ( 1.0 - self.ratioTopLeft[IDX_X] ) - self.regionSize[IDX_WIDTH] )\\n y = (int)( self.oriImgSize[IDX_HEIGHT] * self.ratioTopLeft[IDX_Y] )\\n coordinateList.append( [x, y] )\\n\\n # Center left.\\n x = (int)( self.oriImgSize[IDX_WIDTH] * self.ratioTopLeft[IDX_X] )\\n y = (int)( self.oriImgSize[IDX_HEIGHT] * 0.5 - self.regionSize[IDX_HEIGHT] / 2 )\\n coordinateList.append( [x, y] )\\n\\n # Center.\\n x = (int)( self.oriImgSize[IDX_WIDTH] * 0.5 - self.regionSize[IDX_WIDTH] / 2 )\\n y = (int)( self.oriImgSize[IDX_HEIGHT] * 0.5 - self.regionSize[IDX_HEIGHT] / 2 )\\n coordinateList.append( [x, y] )\\n\\n # Center right.\\n x = (int)( self.oriImgSize[IDX_WIDTH] * (1.0 - self.ratioTopLeft[IDX_X]) - self.regionSize[IDX_WIDTH] )\\n y = (int)( self.oriImgSize[IDX_HEIGHT] * 0.5 - self.regionSize[IDX_HEIGHT] / 2 )\\n coordinateList.append( [x, y] )\\n\\n # Bottom left.\\n x = (int)( self.oriImgSize[IDX_WIDTH] * self.ratioTopLeft[IDX_X] )\\n y = (int)( self.oriImgSize[IDX_HEIGHT] * (1.0 - self.ratioTopLeft[IDX_Y]) - self.regionSize[IDX_HEIGHT] )\\n coordinateList.append( [x, y] )\\n\\n # Bottom center.\\n x = (int)( self.oriImgSize[IDX_WIDTH] * 0.5 - self.regionSize[IDX_WIDTH] / 2 )\\n y = (int)( self.oriImgSize[IDX_HEIGHT] * (1.0 - self.ratioTopLeft[IDX_Y]) - self.regionSize[IDX_HEIGHT] )\\n coordinateList.append( [x, y] )\\n\\n # Bottom right.\\n x = (int)( self.oriImgSize[IDX_WIDTH] * (1.0 - self.ratioTopLeft[IDX_X]) - self.regionSize[IDX_WIDTH] )\\n y = (int)( self.oriImgSize[IDX_HEIGHT] * (1.0 - self.ratioTopLeft[IDX_Y]) - self.regionSize[IDX_HEIGHT] )\\n coordinateList.append( [x, y] )\\n\\n return coordinateList\",\n \"def new_tile(self):\\n col = random.choice(range(self.grid_width))\\n row = random.choice(range(self.grid_height))\\n if self.grid[row][col] == 0:\\n if random.random() >= 0.9:\\n self.grid[row][col] = 4\\n else:\\n self.grid[row][col] = 2\\n else:\\n self.new_tile()\",\n \"def fill(self, xrange=range(0,16), yrange=range(0,16), zrange=range(0,16), **blockstate):\\n blk = self.block_state_index(**blockstate)\\n seq = array(self._blocks.typecode, (blk for i in xrange))\\n\\n def fct(section, blocks, row, *args):\\n blocks[row] = seq\\n\\n self.row_apply(fct, xrange, yrange, zrange)\",\n \"def region(self, args):\\n m = MessageClass()\\n print('123124')\\n data = {'list': []}\\n data['list'].append({\\\"Region_Name\\\": \\\"us-east-1\\\"})\\n data['list'].append({\\\"Region_Name\\\": \\\"us-east-2\\\"})\\n data['list'].append({\\\"Region_Name\\\": \\\"us-west-1\\\"})\\n data['list'].append({\\\"Region_Name\\\": \\\"us-west-2\\\"})\\n data['list'].append({\\\"Region_Name\\\": \\\"ap-northeast-1\\\"})\\n data['list'].append({\\\"Region_Name\\\": \\\"ap-northeast-2\\\"})\\n data['list'].append({\\\"Region_Name\\\": \\\"ap-south-1\\\"})\\n data['list'].append({\\\"Region_Name\\\": \\\"ap-southeast-1\\\"})\\n data['list'].append({\\\"Region_Name\\\": \\\"ap-southeast-1\\\"})\\n data['list'].append({\\\"Region_Name\\\": \\\"ca-central-1\\\"})\\n data['list'].append({\\\"Region_Name\\\": \\\"eu-central-1\\\"})\\n data['list'].append({\\\"Region_Name\\\": \\\"eu-west-1\\\"})\\n data['list'].append({\\\"Region_Name\\\": \\\"eu-west-2\\\"})\\n data['list'].append({\\\"Region_Name\\\": \\\"eu-west-3\\\"})\\n data['list'].append({\\\"Region_Name\\\": \\\"sa-east-1\\\"})\\n m.data = data\\n return m.to_json()\",\n \"def init_board(rows, columns, method=\\\"random\\\"):\\n if method == \\\"random\\\":\\n board = np.random.random_integers(2, size=(rows, columns)) - 1\\n return board\",\n \"def place_obj(self):\\r\\n for pos in BOARD_POSITIONS:\\r\\n self.board[pos[0]][pos[1]] = Stone(color=self.state[pos[0]][pos[1]], pos=(pos[0], pos[1]))\\r\\n self.board[pos[0]][pos[1]].liberty = self.board[pos[0]][pos[1]].compute_liberty(self.state)\",\n \"def establecer_region(self, region, guess, delta_ppm=(1,1)): \\r\\n # obtengo los indices del centro del pico.\\r\\n xc, yc = self.encontrar_picos(guess, delta_ppm)\\r\\n # obtengo las coordenadas que determinan el rectangulo donde voy a\\r\\n # integrar. \\r\\n x_lims, y_lims = self.establecer_limites(xc, yc)\\r\\n \\r\\n xi,xf = x_lims\\r\\n yi,yf = y_lims\\r\\n spec = self.spec[yi:yf, xi:xf]\\r\\n ppmGridDir = self.ppmGridDir[yi:yf, xi:xf]\\r\\n ppmGridInd = self.ppmGridInd[yi:yf, xi:xf]\\r\\n \\r\\n \\r\\n n, m = region\\r\\n self.regiones[n][m] = Region(ppmGridDir, ppmGridInd, spec)\",\n \"def _pad_region(region_data: bytes, *,\\n tile_size: int,\\n offset: int,\\n pad_value: int = 0) -> bytes:\\n region_size = len(region_data)\\n assert len(region_data) % tile_size == 0\\n assert tile_size >= offset\\n assert pad_value < 2 ** 8\\n tile_count = region_size // tile_size\\n original_linear = np.frombuffer(region_data, dtype=np.ubyte)\\n original_2d = original_linear.reshape(tile_count,\\n tile_size)\\n padded = np.insert(original_2d, offset, pad_value, axis=1)\\n return padded.tobytes()\",\n \"def fillingrid(self):\\n\\n if self.imagearray is None:\\n if self.gs.isfixed:\\n for n in range(0, self.numcols):\\n self.vspins[n].setValue(self.currentvalues[n])\\n elif self.gs.isperc:\\n for n in range(0, self.numcols):\\n self.fillinpercent(n)\\n else:\\n for n in range(0, self.numcols):\\n self.nsspins[n].setValue(self.currentnsigs[n])\\n else:\\n for n in range(0, self.numcols):\\n self.vspins[n].setValue(self.currentvalues[n])\\n self.nsspins[n].setValue(self.currentnsigs[n])\\n self.fillinpercent(n)\",\n \"def create_region_from_entity(\\n entity: Entity, created_by: stix2.Identity\\n) -> stix2.Location:\\n name = entity.value\\n if name is None:\\n raise TypeError(\\\"Entity value is None\\\")\\n\\n return create_region(name, created_by=created_by)\",\n \"def init_locations():\\n player, door, monster = sample(CELLS, k=3)\\n\\n return player, door, monster\",\n \"def draw_world(grid, r, c, image):\\n under = grid[r, c]\\n grid[r, c] = AGENT\\n image.set_data(grid)\\n grid[r, c] = under\",\n \"def test_server_override_region(self):\\n # Sanity check our override values do not overlap\\n self.assertNotEqual(CONFIG_DATA[\\\"Region\\\"],\\n CONFIG_DATA[\\\"OverrideRegion\\\"])\\n config_data = imageroller.main.read_config(\\n self._cmd_args,\\n imageroller.test.get_config_parser(\\n self._server_valid_override))\\n # Test Region was overridden\\n self.assertEqual(\\n CONFIG_DATA[\\\"OverrideRegion\\\"],\\n [server_data.region\\n for server_data in config_data.server_data\\n if server_data.name ==\\n CONFIG_DATA[\\\"OverrideRegionFQDN\\\"]]\\n [0])\",\n \"def __init__(self, x_min, x_max, y_min, y_max, bs_number, ue_number,\\n layer=1, power=1.0, bs_distribution=\\\"square_grid\\\",\\n ue_distribution=\\\"gaussian\\\", ue_sigma=0,\\n if_fix_bs=True,\\n bs_radius_1=50,\\n grid_l_1=10,\\n grid_l_2=10):\\n BaseRegion.__init__(self, x_min, x_max, y_min, y_max)\\n BaseBS.__init__(self, bs_number, layer, power, bs_distribution, if_fix_bs)\\n BaseUE.__init__(self, ue_number, ue_distribution, ue_sigma)\\n self.bs_radius_1_ = bs_radius_1\\n self.grid_l_1_ = grid_l_1\\n self.grid_l_2_ = grid_l_2\\n if not if_fix_bs:\\n self.set_bs_to_region()\\n self.set_ue_to_region()\\n self.bs_ue_dict_ = {}\\n # a dict that show which ue belong to which bs\\n # key: 0, 1, ..., num_bs\\n # value: 0, 1, ..., num_ue belong to the key\\n self.select_ue()\",\n \"def add_region_offset(self, offset):\\n if not self.__offset_added:\\n self.__region_ids = dict(\\n (var, region + offset)\\n for var, region in self.__region_ids.items())\\n\\n self.__offset_added = True\",\n \"def __init__(self, NW, SE):\\n self.type = \\\"HOLD AREA\\\"\\n self.NW = NW\\n self.SE = SE\\n self.ctr = [(self.NW[0] + self.SE[0]) / 2, (self.NW[1] + self.SE[1]) / 2]\",\n \"def from_region(self, name, with_guards=None):\\n return _from_region(self.data, name, with_guards)\",\n \"def new_tile(self):\\r\\n random_row = random.randrange(0, self._grid_height)\\r\\n random_col = random.randrange(0, self._grid_width)\\r\\n random_choice = random.choice([2]*90 + [4] * 10)\\r\\n \\r\\n if 0 in [num for elem in self._cells for num in elem]: \\r\\n if self._cells[random_row][random_col] == 0:\\r\\n self._cells[random_row][random_col] = random_choice \\r\\n else:\\r\\n self.new_tile()\\r\\n else:\\r\\n pass\",\n \"def init_right_zone(self):\\n self.right_zone_rect = pg.rect.Rect(500, 0, 300, 80)\\n self.right_zone_image = pg.Surface(self.right_zone_rect.size).convert()\\n self.right_zone_image.fill(pg.Color('#82A6CB'))\\n self.right_zone_bottom_rect = pg.rect.Rect(500, 70, 800, 10)\\n self.right_zone_bottom_image = pg.Surface(\\n self.right_zone_bottom_rect.size).convert()\\n self.right_zone_bottom_image.fill(pg.Color('#3667A6'))\\n self.right_zone_side_rect = pg.rect.Rect(500, 50, 10, 30)\\n self.right_zone_side_image = pg.Surface(\\n self.right_zone_side_rect.size).convert()\\n self.right_zone_side_image.fill(pg.Color('#3667A6'))\\n\\n self.selected_tower = None\\n self.selected_monster = None\\n self.tower_attack_image = prepare.GFX['icons']['tower_damage']\\n self.tower_cooldown_image = prepare.GFX['icons']['tower_cooldown']\\n self.monster_health_image = prepare.GFX['icons']['monster_health']\\n self.monster_speed_image = prepare.GFX['icons']['monster_speed']\\n self.selected_image_pos = (510, 10)\\n self.selected_name_pos = (570, 7)\\n self.selected_info_pos = (570, 30)\\n self.selected_description_pos = (570, 50)\",\n \"def load(self):\\n\\n if self.loaded:\\n return\\n\\n self.region_back = None\\n self.objects = []\\n self.plants = []\\n self.tiles = []\\n\\n # Some convenience vars\\n materials = self.data.materials\\n matmods = self.data.matmods\\n objects = self.data.objects\\n plants = self.data.plants\\n world = self.world\\n self.loaded = True\\n\\n # Get tiles\\n try:\\n data_tiles = world.get_tiles(self.rx, self.ry)\\n except KeyError:\\n print('WARNING: Region ({}, {}) was not found in world'.format(self.rx, self.ry))\\n return\\n\\n # \\\"real\\\" coordinates\\n base_x = self.rx*32\\n gui_x = base_x*8\\n base_y = self.ry*32\\n gui_y = (world.height*8)-(base_y*8)\\n\\n # Background for our drawn area (black)\\n self.region_back = self.scene.addRect(gui_x, gui_y-255, 255, 255,\\n QtGui.QPen(QtGui.QColor(0, 0, 0)),\\n QtGui.QBrush(QtGui.QColor(0, 0, 0)),\\n )\\n self.region_back.setZValue(Constants.z_black)\\n\\n # Tiles!\\n cur_row = 0\\n cur_col = 0\\n for data_tile in data_tiles:\\n self.tiles.append(GUITile(self.scene, data_tile,\\n base_x+cur_col, base_y+cur_row,\\n self,\\n gui_x+cur_col*8, gui_y-(cur_row+1)*8,\\n self.layer_toggles))\\n self.scene.addItem(self.tiles[-1])\\n cur_col += 1\\n if cur_col == 32:\\n cur_col = 0\\n cur_row += 1\\n\\n # Entities!\\n entities = []\\n try:\\n entities = world.get_entities(self.rx, self.ry)\\n except KeyError:\\n pass\\n\\n for e in entities:\\n if e.name == 'ObjectEntity':\\n obj_name = e.data['name']\\n obj_orientation = e.data['orientationIndex']\\n (obj_x, obj_y) = tuple(e.data['tilePosition'])\\n if obj_name in objects:\\n obj = objects[obj_name]\\n (image, offset_x, offset_y) = obj.get_image(obj_orientation)\\n qpmi = QtWidgets.QGraphicsPixmapItem(image)\\n qpmi.setPos(\\n (obj_x*8) + offset_x,\\n (world.height*8)-(obj_y*8) - offset_y - image.height(),\\n )\\n qpmi.setZValue(Constants.z_objects)\\n if not self.layer_toggles.objects_toggle.isChecked():\\n qpmi.setVisible(False)\\n self.scene.addItem(qpmi)\\n self.objects.append(qpmi)\\n rel_x = obj_x - base_x\\n rel_y = obj_y - base_y\\n tile_idx = rel_y*32 + rel_x\\n self.tiles[tile_idx].add_object(obj, obj_name, obj_orientation, qpmi, e.data)\\n elif e.name == 'PlantEntity':\\n desc = e.data['descriptions']['description']\\n images = []\\n (obj_x, obj_y) = tuple(e.data['tilePosition'])\\n for piece in e.data['pieces']:\\n piece_img = piece['image'].split('?')[0]\\n if piece_img in plants:\\n img = plants[piece_img].image\\n qpmi = QtWidgets.QGraphicsPixmapItem(img)\\n qpmi.setPos(\\n (obj_x*8) + (piece['offset'][0]*8),\\n (world.height*8)-(obj_y*8) - (piece['offset'][1]*8) - img.height(),\\n )\\n qpmi.setZValue(Constants.z_plants)\\n if not self.layer_toggles.plants_toggle.isChecked():\\n qpmi.setVisible(False)\\n images.append((plants[piece_img], qpmi))\\n self.scene.addItem(qpmi)\\n self.plants.append(qpmi)\\n else:\\n print('not found: {}'.format(piece_img))\\n rel_x = obj_x - base_x\\n rel_y = obj_y - base_y\\n tile_idx = rel_y*32 + rel_x\\n self.tiles[tile_idx].add_plant(desc, images)\\n elif (e.name == 'MonsterEntity'\\n or e.name == 'NpcEntity'\\n or e.name == 'StagehandEntity'\\n or e.name == 'ItemDropEntity'\\n or e.name == 'VehicleEntity'\\n ):\\n # TODO: Ignoring for now\\n pass\\n else:\\n print('Unknown entity type: {}'.format(e.name))\",\n \"def sync_region(self, region_id):\\n self.init_structures()\\n con = SimConnection()\\n con.connect(self.gridinfo._url)\\n scenedata = con._con.ogrescene_list({\\\"RegionID\\\":region_id})[\\\"res\\\"]\\n objects = editor.getSelected()\\n if not objects:\\n objects = bpy.data.objects\\n for obj in objects:\\n obj_uuid = str(self.get_uuid(obj))\\n if obj_uuid:\\n if obj_uuid in scenedata:\\n self.import_group(obj_uuid, scenedata[obj_uuid], 10)\",\n \"def _create_mid_region_frame(self):\\n self.region_option = tk.StringVar()\\n self.region_option.set(\\\"euw\\\")\\n self.frames.append(tk.LabelFrame(self.master))\\n self.option_menu = tk.OptionMenu(self.frames[5], self.region_option,\\n \\\"euw\\\", \\\"na\\\", \\\"eune\\\")\\n self.option_menu.grid(sticky=\\\"ew\\\")\\n self.frames[5].grid(column=1, row=0, sticky=\\\"ns\\\", pady=10)\\n self.frames[5].columnconfigure(0, weight=1)\",\n \"def get_regions(self):\\n if self.initiated is False:\\n raise RuntimeError(\\\"Initiate first\\\")\\n\\n return self.R\",\n \"def create_manual_barrage_initial_state(\\n spy_locations_list,\\n scout_locations_list,\\n miner_locations_list,\\n sergeant_locations_list,\\n lieutenant_locations_list,\\n captain_locations_list,\\n major_locations_list,\\n colonel_locations_list,\\n general_locations_list,\\n marshall_locations_list,\\n flag_locations_list,\\n bomb_locations_list,\\n specify_pieces_for_player=OUTSIDE_AGENT_PLAYER_ID):\\n game_version = STRATEGO_ENV_BARRAGE_INTERFACE_CONFIG['version']\\n game_version_config = VERSION_CONFIGS[game_version]\\n board_shape = (game_version_config['rows'], game_version_config['columns'])\\n procedural_env = StrategoProceduralEnv(*board_shape)\\n\\n # Verify inputs and fill a 2d ndarray with specified player piece values.\\n if not (specify_pieces_for_player == 1 or specify_pieces_for_player == -1):\\n raise ValueError(\\\"specify_pieces_for_player must be 1 or -1\\\")\\n\\n allowed_piece_rows_for_player = [0, 1, 2, 3] if specify_pieces_for_player == 1 else [6, 7, 8, 9]\\n specified_player_initial_piece_map = np.zeros(shape=board_shape, dtype=INT_DTYPE_NP)\\n\\n manual_piece_locations = {\\n SP.SPY: spy_locations_list,\\n SP.SCOUT: scout_locations_list,\\n SP.MINER: miner_locations_list,\\n SP.SERGEANT: sergeant_locations_list,\\n SP.LIEUTENANT: lieutenant_locations_list,\\n SP.CAPTAIN: captain_locations_list,\\n SP.MAJOR: major_locations_list,\\n SP.COLONEL: colonel_locations_list,\\n SP.GENERAL: general_locations_list,\\n SP.MARSHALL: marshall_locations_list,\\n SP.FLAG: flag_locations_list,\\n SP.BOMB: bomb_locations_list\\n }\\n\\n for piece_type, locations_list in manual_piece_locations.items():\\n if len(locations_list) > 0 and \\\\\\n (len(np.shape(locations_list)) != 2 or\\n (len(np.shape(locations_list)) == 2 and np.shape(locations_list)[1] != 2)):\\n raise ValueError(f\\\"Each locations list must be a list of 2d coordinates. Examples: [] or [[1,2], [2,5]].\\\\n\\\"\\n f\\\"For {piece_type.name}, {locations_list} was passed.\\\")\\n\\n if len(locations_list) != game_version_config['piece_amounts'][piece_type]:\\n allowed_piece_amounts = {pc_type.name: amt for pc_type, amt in game_version_config['piece_amounts'].items()}\\n raise ValueError(f\\\"{len(locations_list)} {piece_type.name} piece locations were provided when \\\"\\n f\\\"{game_version.name} requires the following piece amounts: \\\\n{allowed_piece_amounts}\\\")\\n\\n for location in locations_list:\\n row, column = location\\n if (not 0 <= column < board_shape[1]) or (row not in allowed_piece_rows_for_player):\\n raise ValueError(f\\\"The out-of-range location {location} for {piece_type.name} was provided. \\\"\\n f\\\"Locations are in the format, (row, column). \\\"\\n f\\\"Rows take values in {allowed_piece_rows_for_player} for player {specify_pieces_for_player}. \\\"\\n f\\\"Columns must be in the range [0, {board_shape[1]}].\\\")\\n if specified_player_initial_piece_map[row, column] != 0:\\n raise ValueError(f\\\"The location {location} was specified for more than one piece.\\\")\\n\\n # Set piece value for location\\n specified_player_initial_piece_map[row, column] = piece_type.value\\n\\n # Grab a random human initialization for the non-specified player.\\n # Human inits have been downloaded from the Gravon Archive (https://www.gravon.de/gravon/stratego/strados2.jsp)\\n random_human_init_spec_str = np.random.choice(HUMAN_INITS)\\n player_1_random_human_piece_map, player_2_random_human_piece_map = create_initial_positions_from_human_data(\\n player1_string=random_human_init_spec_str, player2_string=random_human_init_spec_str,\\n game_version_config=game_version_config)\\n\\n # Set obstacle locations\\n obstacle_map = np.zeros(shape=board_shape, dtype=INT_DTYPE_NP)\\n for obstacle_location in VERSION_CONFIGS[game_version]['obstacle_locations']:\\n obstacle_map[obstacle_location] = 1.0\\n\\n # Create the initial state\\n initial_state = procedural_env.create_initial_state(\\n obstacle_map=obstacle_map,\\n player_1_initial_piece_map=specified_player_initial_piece_map if specify_pieces_for_player == 1 else player_1_random_human_piece_map,\\n player_2_initial_piece_map=specified_player_initial_piece_map if specify_pieces_for_player == -1 else player_2_random_human_piece_map,\\n max_turns=game_version_config['max_turns'])\\n\\n return initial_state\",\n \"def river_region(rr_id):\\n r = RiverRegionRenderer(request, rr_id, None)\\n return r.render()\",\n \"def get_region(ref_table, assoc_name=None,\\n pos_margin=10., vel_margin=2.,\\n scale_margin=None, mg_colname=None):\\n\\n ## Commenting this out for now. Usage by me (Tim) should be the same\\n ## as everyone else. i.e. no hardcoded filenames for convenience.\\n # if gagne_reference_data is None:\\n # gagne_reference_data =\\\\\\n # '/home/tcrun/chronostar/data/gagne_bonafide_full_kinematics_with_lit_and_best_radial_velocity' \\\\\\n # '_comb_binars_with_banyan_radec.fits'\\n\\n if mg_colname is None:\\n mg_colname = 'Moving group'\\n\\n # If reference table is provided as str, convert to table\\n if type(ref_table) is str:\\n ref_table = Table.read(ref_table)\\n\\n # Extract all stars\\n if assoc_name is None:\\n subtable = ref_table\\n else:\\n if assoc_name not in set(ref_table[mg_colname]):\\n raise UserWarning(\\n 'Association name must be one of:\\\\n{}\\\\nReceived: \\\"{}\\\"'.format(\\n list(set(ref_table[mg_colname])), assoc_name\\n ))\\n subtable = ref_table[np.where(ref_table[mg_colname] == assoc_name)]\\n logging.info('Initial membership list has {} members'.format(len(subtable)))\\n\\n star_means = tabletool.build_data_dict_from_table(subtable, only_means=True,\\n cartesian=True)\\n\\n data_upper_bound = np.nanmax(star_means, axis=0)\\n data_lower_bound = np.nanmin(star_means, axis=0)\\n logging.info('Stars span from {} to {}'.format(\\n np.round(data_lower_bound),\\n np.round(data_upper_bound)\\n ))\\n\\n # First try and scale box margins by provided scale margin.\\n # scale_margin of 1 would double total span (1 + 1)\\n if scale_margin is not None:\\n data_span = data_upper_bound - data_lower_bound\\n box_margin = 0.5 * scale_margin * data_span\\n\\n # Set up boundaries of box that span double the association\\n box_lower_bound = data_lower_bound - box_margin\\n box_upper_bound = data_upper_bound + box_margin\\n\\n # Set margin based on provided (or default) constant amounts\\n else:\\n data_margin = np.array(3*[pos_margin] + 3*[vel_margin])\\n box_lower_bound = data_lower_bound - data_margin\\n box_upper_bound = data_upper_bound + data_margin\\n\\n logging.info('Range extended.\\\\nLower: {}\\\\nUpper: {}'.format(\\n np.round(box_lower_bound),\\n np.round(box_upper_bound)\\n ))\\n\\n return box_lower_bound, box_upper_bound\",\n \"def init(self):\\n\\n self.pos = np.random.rand(self.N, 7)\\n for i in range(3):\\n self.pos[:, i] *= (self.bounds[2*i+1] - self.bounds[2*i])\\n self.pos[:, i] += self.bounds[2*i]\\n\\n # Star colors http://www.isthe.com/chongo/tech/astro/HR-temp-mass-table-byhrclass.html http://www.vendian.org/mncharity/dir3/starcolor/\\n O3 = np.array([144., 166., 255.])\\n O3 /= 255.\\n self.pos[:, 3:-1] = O3[None, :]\\n M4Ia = np.array([255., 185., 104.])\\n M4Ia /= 255.\\n self.pos[np.random.rand(self.N)>.5, 3:-1] = M4Ia[None, :]\\n\\n self.pos[:, -1] = .8 + .2*self.pos[:, -1]\",\n \"def set_board(board):\",\n \"def __init__(self, rows=8, cols=8):\\n self.rows = rows\\n self.cols = cols\\n self.matrix = [[Disk.NONE for x in range(rows)] for y in range(cols)]\\n init_array = (('d','4',Disk.LIGHT), ('e','5',Disk.LIGHT), ('d','5',Disk.DARK), ('e','4',Disk.DARK))\\n # init_array = (('a', '2', Disk.LIGHT), ('b', '5', Disk.LIGHT), ('d', '5', Disk.DARK), ('e', '4', Disk.DARK))\\n for item in init_array:\\n self.place_disk(*self.coordinates_to_matrix(item[0], item[1]), item[2])\",\n \"def new_tile(self):\\n # replace with your code\\n empty_list = []\\n counter_1 = 0\\n for _ in self._grid:\\n counter_2 = 0\\n line = _\\n for blank in line:\\n if blank == 0:\\n blank_tile = (counter_1, counter_2)\\n empty_list.append(blank_tile)\\n counter_2 += 1\\n else:\\n counter_2 += 1\\n counter_1 += 1\\n #print empty_list\\n \\n self._tile = empty_list[random.randrange(len(empty_list))]\\n \\n value = [2,2,2,2,2,2,2,2,2,4]\\n tile_value = value[random.randint(0,9)]\\n \\n self.set_tile(self._tile[0], self._tile[1], tile_value)\",\n \"def generate_level(self):\\n for _ in range(AMOUNT_REGIONS_TO_DRAW):\\n self._generate_next_blocks()\",\n \"def _loadRegions(self, fh):\\n holeNumbers = self._mainBasecallsGroup[\\\"ZMW/HoleNumber\\\"].value\\n self._holeNumberToIndex = dict(zip(holeNumbers, range(len(holeNumbers))))\\n\\n #\\n # Region table\\n #\\n self.regionTable = toRecArray(REGION_TABLE_DTYPE,\\n fh[\\\"/PulseData/Regions\\\"].value)\\n\\n self._regionTableIndex = _makeRegionTableIndex(self.regionTable.holeNumber)\\n isHqRegion = self.regionTable.regionType == HQ_REGION\\n hqRegions = self.regionTable[isHqRegion]\\n\\n if len(hqRegions) != len(holeNumbers):\\n # Bug 23585: pre-2.1 primary had a bug where a bas file\\n # could get a broken region table, lacking an HQ region\\n # entry for a ZMW. This happened fairly rarely, mostly on\\n # very long traces. Workaround here is to rebuild HQ\\n # regions table with empty HQ region entries for those\\n # ZMWs.\\n hqRegions_ = toRecArray(REGION_TABLE_DTYPE,\\n np.zeros(shape=len(holeNumbers),\\n dtype=REGION_TABLE_DTYPE))\\n hqRegions_.holeNumber = holeNumbers\\n for record in hqRegions:\\n hn = record.holeNumber\\n hqRegions_[self._holeNumberToIndex[hn]] = record\\n hqRegions = hqRegions_\\n\\n hqRegionLength = hqRegions.regionEnd - hqRegions.regionStart\\n holeStatus = self._mainBasecallsGroup[\\\"ZMW/HoleStatus\\\"].value\\n\\n #\\n # Sequencing ZMWs - Note: this differs from Primary's\\n # definition. To obtain those values, one would use the\\n # `allSequencingZmws` property.\\n #\\n self._sequencingZmws = \\\\\\n holeNumbers[(holeStatus == SEQUENCING_ZMW) &\\n (self._mainBasecallsGroup[\\\"ZMW/NumEvent\\\"].value > 0) &\\n (hqRegionLength > 0)]\\n\\n self._allSequencingZmws = holeNumbers[holeStatus == SEQUENCING_ZMW]\",\n \"def update_temperature_region(self):\\n self.linear_region.setRegion(\\n self.temperature_plot_graph.getViewBox().viewRange()[0])\",\n \"def _regions_shmem_config(self) -> None:\\n assert self.config is not None\\n assert self.board is not None\\n\\n if not self.config.shmem:\\n return\\n\\n for name, shmem_config in self.config.shmem.items():\\n for cell_name in shmem_config.peers:\\n cell = self.config.cells[cell_name]\\n assert cell.pci_devices is not None\\n\\n # offset 2, since mem_regions always\\n # start with table_region and common_output_region\\n dev_id = cell.pci_devices[name].shmem_dev_id\\n assert dev_id is not None\\n assert cell.memory_regions is not None\\n\\n grouped_region_name = f\\\"{name}\\\"\\n grouped_region = cell.memory_regions[grouped_region_name]\\n\\n cell_output_region = grouped_region.regions[2 + dev_id]\\n\\n def get_mem_region_index(cell, name):\\n ret = -1\\n index = 0\\n\\n for region_name, region in cell.memory_regions.items():\\n if region_name == name:\\n ret = index\\n break\\n\\n if isinstance(region, GroupedMemoryRegion):\\n index += len(region.regions)\\n else:\\n index += 1\\n\\n if ret == -1:\\n raise Exception(\\n f\\\"Invalid cells.yaml, not a memory-region: {name}\\\"\\n )\\n\\n return ret\\n\\n shmem_regions_start = get_mem_region_index(\\n cell, grouped_region_name\\n )\\n cell.pci_devices[name].shmem_regions_start = shmem_regions_start\\n\\n new_cell_output_region = copy.copy(cell_output_region)\\n new_cell_output_region.flags = copy.copy(\\n cell_output_region.flags\\n )\\n new_cell_output_region.flags.append(\\\"MEM_WRITE\\\")\\n\\n grouped_region.regions[2 + dev_id] = new_cell_output_region\",\n \"def set_tile(self, row, col, value):\\n # replace with your code\\n self.grid[row][col] = value\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6742911","0.5997335","0.5913795","0.573142","0.56936634","0.56373113","0.56364506","0.5610511","0.5602637","0.55689424","0.5567876","0.553663","0.5532952","0.55236477","0.5481019","0.5457451","0.5454251","0.544278","0.5432112","0.5432112","0.5432112","0.54132175","0.5345846","0.5345425","0.53006715","0.5268588","0.5261683","0.5255762","0.52529144","0.5224182","0.51988786","0.5193345","0.519081","0.5180113","0.5168156","0.5166387","0.51640004","0.51552254","0.51426095","0.5139516","0.51372105","0.5127384","0.5127384","0.5113221","0.5101546","0.5073147","0.50712013","0.50674015","0.50664294","0.50536704","0.50477946","0.50441754","0.5031139","0.50263506","0.50262123","0.501471","0.50046724","0.5002816","0.49999812","0.49950248","0.4993164","0.4969553","0.49669695","0.49557677","0.4945821","0.4945211","0.49412164","0.49386188","0.49265516","0.49213815","0.4920508","0.4919846","0.4917624","0.49143732","0.49022818","0.4895478","0.48950115","0.48841983","0.4875334","0.48706442","0.48693988","0.48628083","0.48611423","0.48595762","0.48525757","0.48524988","0.4850724","0.48465583","0.48436847","0.4840618","0.4834213","0.483338","0.48318627","0.48306897","0.48291117","0.48222187","0.48204514","0.4816622","0.48150495","0.48073468"],"string":"[\n \"0.6742911\",\n \"0.5997335\",\n \"0.5913795\",\n \"0.573142\",\n \"0.56936634\",\n \"0.56373113\",\n \"0.56364506\",\n \"0.5610511\",\n \"0.5602637\",\n \"0.55689424\",\n \"0.5567876\",\n \"0.553663\",\n \"0.5532952\",\n \"0.55236477\",\n \"0.5481019\",\n \"0.5457451\",\n \"0.5454251\",\n \"0.544278\",\n \"0.5432112\",\n \"0.5432112\",\n \"0.5432112\",\n \"0.54132175\",\n \"0.5345846\",\n \"0.5345425\",\n \"0.53006715\",\n \"0.5268588\",\n \"0.5261683\",\n \"0.5255762\",\n \"0.52529144\",\n \"0.5224182\",\n \"0.51988786\",\n \"0.5193345\",\n \"0.519081\",\n \"0.5180113\",\n \"0.5168156\",\n \"0.5166387\",\n \"0.51640004\",\n \"0.51552254\",\n \"0.51426095\",\n \"0.5139516\",\n \"0.51372105\",\n \"0.5127384\",\n \"0.5127384\",\n \"0.5113221\",\n \"0.5101546\",\n \"0.5073147\",\n \"0.50712013\",\n \"0.50674015\",\n \"0.50664294\",\n \"0.50536704\",\n \"0.50477946\",\n \"0.50441754\",\n \"0.5031139\",\n \"0.50263506\",\n \"0.50262123\",\n \"0.501471\",\n \"0.50046724\",\n \"0.5002816\",\n \"0.49999812\",\n \"0.49950248\",\n \"0.4993164\",\n \"0.4969553\",\n \"0.49669695\",\n \"0.49557677\",\n \"0.4945821\",\n \"0.4945211\",\n \"0.49412164\",\n \"0.49386188\",\n \"0.49265516\",\n \"0.49213815\",\n \"0.4920508\",\n \"0.4919846\",\n \"0.4917624\",\n \"0.49143732\",\n \"0.49022818\",\n \"0.4895478\",\n \"0.48950115\",\n \"0.48841983\",\n \"0.4875334\",\n \"0.48706442\",\n \"0.48693988\",\n \"0.48628083\",\n \"0.48611423\",\n \"0.48595762\",\n \"0.48525757\",\n \"0.48524988\",\n \"0.4850724\",\n \"0.48465583\",\n \"0.48436847\",\n \"0.4840618\",\n \"0.4834213\",\n \"0.483338\",\n \"0.48318627\",\n \"0.48306897\",\n \"0.48291117\",\n \"0.48222187\",\n \"0.48204514\",\n \"0.4816622\",\n \"0.48150495\",\n \"0.48073468\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5901017"},"document_rank":{"kind":"string","value":"3"}}},{"rowIdx":94893,"cells":{"query":{"kind":"string","value":"Add agents and exits to the board. This modifies both the board and regions in place."},"document":{"kind":"string","value":"def add_agents_and_exit(board, regions, agents, agent_types):\n agent_vals = []\n point_tables = []\n agent_names = []\n agent_types = {'default': DEFAULT_AGENT, **agent_types}\n for agent_type in _fix_random_values(agents):\n agent_type = _fix_random_values(agent_type)\n if agent_type not in agent_types:\n continue\n agent = {**DEFAULT_AGENT, **agent_types[agent_type]}\n agent_val = CellTypes.agent | CellTypes.frozen\n if agent['color'] in COLORS:\n agent_val |= COLORS[agent['color']]\n else:\n logger.error(\"Invalid agent color: '%s'\", agent['color'])\n for flag in agent['flags']:\n if flag in AGENT_PROPERTIES:\n agent_val |= AGENT_PROPERTIES[flag]\n else:\n logger.error(\"Invalid agent property '%s'\", flag)\n agent_vals.append(agent_val)\n point_tables.append(agent['points_table'])\n agent_names.append(agent_type)\n\n if not agent_vals:\n return np.zeros((0,2), dtype=int), np.zeros((0,8,9), dtype=int)\n\n # Add agents to the board\n zero_reg = (regions == 0)\n zero_idx = np.array(np.nonzero(zero_reg)).T\n # ensure that there are not more agents than places to put them:\n agent_vals = agent_vals[:len(zero_idx)]\n agent_locs = zero_idx[\n get_rng().choice(len(zero_idx), len(agent_vals), replace=False)]\n board[tuple(agent_locs.T)] = agent_vals\n\n # Find the location that's as far away from agents as possible while still\n # in the buffer region.\n row_dist = np.abs(np.arange(board.shape[0])[:, np.newaxis] - agent_locs[:,0])\n col_dist = np.abs(np.arange(board.shape[1])[:, np.newaxis] - agent_locs[:,1])\n row_dist = np.sum(np.minimum(row_dist, board.shape[0] - row_dist), axis=-1)\n col_dist = np.sum(np.minimum(col_dist, board.shape[1] - col_dist), axis=-1)\n dist = (row_dist[:, np.newaxis] + col_dist[np.newaxis, :]) * zero_reg\n k = np.argmax(dist)\n exit_loc = k // board.shape[1], k % board.shape[1]\n board[exit_loc] = CellTypes.level_exit | CellTypes.color_r\n\n # Ensure that the player and exit aren't touching any other region\n all_locs = np.append(agent_locs, [exit_loc], axis=0)\n n = np.array([[-1,0,1,-1,0,1,-1,0,1],[-1,-1,-1,0,0,0,1,1,1]]).T\n new_locs = (all_locs[:,np.newaxis] + n).reshape(-1, 2) % board.shape\n regions[tuple(new_locs.T)] = -1\n\n return agent_locs, point_tables, agent_names"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def add_to_simulation(self,agent):\n self.agents[agent.name] = agent\n self.network.add_node(agent)\n \n #agent given a grid queue at initialization\n grid_queue = [gq for gq in self.grid_queues.values() if gq.accepts(agent)][agent.sex]\n agent.grid_queue = grid_queue.index\n self.add_to_grid_queue(agent)","def _init_agents(self):\n self.agents = [Agent(e=0.1, a=0.1, row=self.row, col=self.col) for i in range(2)]","def update_available_cells(self, agent):\n try:\n self.available_road_cells.remove(agent.pos)\n except:\n pass\n try:\n self.available_building_cells.remove(agent.pos)\n except:\n pass\n\n adj_cells = self.environment.grid.get_neighborhood(agent.pos, moore=False)\n surrounding_cells = self.environment.grid.get_neighborhood(agent.pos, moore=True)\n\n # Update available cells if agent is a road\n if type(agent) == Road:\n for cell in surrounding_cells:\n # Roads\n if self.creates_valid_road(cell) and cell not in self.available_road_cells:\n self.available_road_cells.append(cell)\n\n # Buildings\n if self.creates_valid_building(cell) and cell not in self.available_building_cells:\n self.available_building_cells.append(cell)\n\n if type(agent) == Building:\n for cell in surrounding_cells:\n # Roads\n if self.creates_valid_road(cell) and cell not in self.available_road_cells:\n self.available_road_cells.append(cell)\n\n # Buildings\n if self.creates_valid_building(cell) and cell not in self.available_building_cells:\n self.available_building_cells(cell)","def test_assign_to_regions(self):\n \n tool = pybedtools.BedTool(clipper.test_file(\"FOX2Brain-05.15.09.polyATrim.adapterTrim.rmRep.sorted.rmDup.peaks.bed\"))\n \n assign_to_regions(tool=tool, \n clusters=\"test\", \n speciesFA= clipper.test_file(\"mm9.fa\"), \n regions_dir=os.path.join(clipper.test_dir(), \"regions\"), \n regions={\"exons\" : \"Exon\", \"utr3\" : \"3' UTR\", \n \"utr5\" : \"5' UTR\", \"proxintron500\" : \"Proximal Intron\", \n \"distintron500\" : \"Distal Intron\"} ,\n assigned_dir = clipper.test_dir(),\n fasta_dir = clipper.test_dir(),\n species=\"mm9\", \n nrand = 3, \n getseq=False)","def push_regions(self, regions: [MouseRegion]):\n raise NotImplementedError","def add_regions(self, regions, **options):\n \n options.setdefault(\"col\", color(0,0,1))\n options.setdefault(\"style\", \"box\")\n options.setdefault(\"height\", 0.5)\n \n return self.add_track(RegionTrack, -.5, regions, **options)","def insert_host_states(hosts):\n IMPL.insert_host_states(hosts)","def enter(self, env):\n env = self._find_env(env, new=True)\n env.add_agents(self)","def on_enter(self):\n # Add self to list of obstacles\n self.parent._obstacles.add(self)\n super().on_enter()","def display_agents(self):\n for agent in self.scheduler.agents:\n id_ = agent.id_\n p = agent.mobility.current\n x, y = to_geometry(p[0]), to_geometry(p[1])\n r = to_geometry(agent.range_)\n print('define agent{} ellipse 4 4 white {} {}'.format(id_, x, y))\n print('define agentr{0} ellipse {1} {1} white {2} {3}'.format(\n id_, r, x, y))\n self.change_agent_status(agent)","def apply_to_world(self, world):\n # add the current obstacles\n for obstacle in self.current_obstacles:\n world.add_obstacle(obstacle)\n\n # program the robot supervisors\n for robot in world.robots:\n robot.supervisor.goal = self.current_goal[:]","def place_dungeon_items(self):\r\n self.place_entrance()\r\n self.place_exit()\r\n self.place_pillar_a()\r\n self.place_pillar_e()\r\n self.place_pillar_i()\r\n self.place_pillar_p()\r\n self.place_pits()\r\n self.place_vision()\r\n self.place_healing()\r\n self.original_map = self.__repr__()","def add_items(self):\n # -- item list\n item = ['S','H','R','M', 'B', 'C']\n # -- loops through item list and adds them to the maze\n for i in item:\n x_coordinate, y_coordinate = self.find_random_spot()\n self.grid[x_coordinate][y_coordinate] = i","def place_entrance(self):\r\n x = random.randint(0, (self.__nx - 1))\r\n y = random.randint(0, (self.__ny - 1))\r\n self.__current_room = x, y # places adventurer in dungeon at start of game\r\n self.__entrance_room = x, y\r\n self.__maze[x][y].set_entrance(True)","def resize_board(self, dx, dy):\n height, width = self.board.shape\n if width <= 0 or height <= 0:\n raise ValueError(\"Cannot resize to zero.\")\n new_board = np.zeros((height+dy, width+dx), dtype=self.board.dtype)\n height += min(0, dy)\n width += min(0, dx)\n new_board[:height, :width] = self.board[:height, :width]\n self.board = new_board\n out_of_bounds = np.any(self.agent_locs >= new_board.shape, axis=1)\n self.agent_locs = self.agent_locs[~out_of_bounds]\n self.edit_loc = tuple(np.array(self.edit_loc) % new_board.shape)\n self.update_exit_locs()","def add_region(self, position):\n region = self.region_selector(position)\n self.regions[id(region)] = region","def place_building(self, building):\n if self.environment.grid.is_cell_empty(building.pos):\n self.environment.grid.place_agent(building, building.pos)\n self.environment.agents['residences'].append(building)\n else:\n try:\n self.available_cells.remove(building.pos)\n except:\n pass","def regions(self, regions):\n self._regions = regions","def _update_battle_position(self, new_cells=[], previous_cells=[]):\n if previous_cells:\n for previous_cell in previous_cells:\n self._battle_area.set_cell(previous_cell.get_name(), False)\n if new_cells:\n for new_cell in new_cells:\n self._battle_area.set_cell(new_cell.get_name(), self)","def create_block(self, location_list, POI_locations):\n\n \n for i in range(len(location_list)):\n this_cell = self.grid.get_cell_list_contents(location_list[i])\n\n for agent in this_cell:\n if type(agent) is nodeAgent:\n agent.block = True\n\n for i in POI_locations:\n agent.locations[i] = 10000","def test_arena_move(agents_and_engines):\n agents, engine = agents_and_engines\n assert len(agents) == 3\n\n game_state = engine.get_state()\n\n positions = [g['pos'] for g in game_state['gladiators']]\n\n rw = random_walker.ArenaAgent()\n\n move = rw.move(game_state)\n for i in range(3):\n engine.move(move)\n new_state = engine.get_state()\n\n new_positions = [g['pos'] for g in new_state['gladiators']]\n\n assert new_positions != positions","def advance_board(self):\n board = self.board\n rules = self.energy_rules\n h, w = board.shape\n beta = 1.0 / max(1e-20, self.temperature)\n if len(rules[0]) - 1 == 4:\n neighborhood = np.array([[0,1,0],[1,0,1],[0,1,0]])\n elif len(rules[0]) - 1 == 6:\n neighborhood = np.array([[0,1,1],[1,0,1],[1,1,0]])\n elif len(rules[0]) - 1 == 8:\n neighborhood = np.array([[1,1,1],[1,0,1],[1,1,1]])\n else:\n raise RuntimeError(\"async rules must have length 5, 7, or 9\")\n rng = get_rng()\n for _ in range(int(board.size * self.cells_per_update)):\n x = rng.choice(w)\n y = rng.choice(h)\n if board[y, x] & CellTypes.frozen:\n continue\n neighbors = board.view(wrapping_array)[y-1:y+2, x-1:x+2] * neighborhood\n alive_neighbors = np.sum(neighbors & CellTypes.alive > 0)\n spawn_neighbors = np.sum(neighbors & CellTypes.spawning > 0)\n frozen = np.sum(neighbors & CellTypes.freezing) > 0\n if frozen:\n continue\n if board[y, x] & CellTypes.alive:\n H = rules[0][alive_neighbors]\n else:\n H = rules[1][alive_neighbors]\n\n P = 0.5 + 0.5*np.tanh(H * beta)\n P = 1 - (1-P)*(1-self.spawn_prob)**spawn_neighbors\n board[y, x] = CellTypes.life if coinflip(P) else CellTypes.empty","def populate_tiles(self):\n\n # grid format :\n # grid(x,y,z)[0]: A valid WorldTile type (i.e. WorldTile.door)\n # grid(x,y,z)[1]: A list of ASCII color or format codes for ColorIze\n # grid(x,y,z)[2]: The tile object\n\n self.t_count = 0 # Tile count, increment for each tile added\n self.build_start = time.clock()\n self.logger.info(\"[*] Starting world building script\")\n\n script_list = [\n self.build_boss_room,\n self.build_rooms,\n self.build_halls,\n self.build_doors,\n self.build_chests,\n self.build_traps,\n self.build_mobs,\n self.build_npcs\n ]\n for func in script_list:\n self.logger.debug(\"\\tRunning {}\".format(func.__name__))\n if not func():\n e_text = \"Build script failed : {}\".format(func.__name__)\n raise AssertionError(e_text)\n\n self.logger.info(\"[*] World building script completed\")\n self.logger.debug(\"\\tTiles Placed : {}\".format(self.t_count))\n build_time = time.clock()-self.build_start\n self.logger.debug(\"\\tTook {}s\".format(build_time))\n self.logger.debug(\"\\tTiles/s : {}\".format(t_count/build_time))","def add_agent(self, agent):\n\t\tif not (agent in self.agents_in_site):\n\t\t\tif (agent.site != None):\n\t\t\t\tagent.site.agents_in_site.remove(agent) \n\t\t\tself.agents_in_site.append(agent)\n\t\t\tagent.site = self","def register(self):\n self.logger.info(\"Registering agent %s\", \"/registry/\" + self._configuration[\"identification\"][\"uuid\"])\n self._coordination.update(\"/registry/\" + self._configuration[\"identification\"][\"uuid\"], self._configuration[\"identification\"])","def shift_board(self, dx, dy):\n self.board = np.roll(self.board, dy, axis=0)\n self.board = np.roll(self.board, dx, axis=1)\n self.agent_locs += [dy, dx]\n self.agent_locs %= self.board.shape\n self.update_exit_locs()","def begin_encounter(self):\r\n\r\n #introduce NPCs - run all introduce methods, unless the NPCs have the same name\r\n for i in range(len(self.npc_names)):\r\n for _npc in self.npc_list:\r\n if _npc.name == self.npc_names[i]:\r\n _npc.introduce(self.npc_quantities[i], self.location)\r\n break\r\n\r\n #list visible enemies\r\n self.display_npcs()\r\n\r\n #check close proximity - if hostile enemy within 10 ft, don't go to interact menu\r\n hostile_close_proximity = False\r\n \r\n for m in range(len(self.npc_distances)):\r\n if self.npc_distances[m] < 10:\r\n if self.npc_list[m].hostility == utils.HostilityLevel.HOSTILE:\r\n hostile_close_proximity = True\r\n multiple = self.npc_quantities[self.npc_names.index(self.npc_list[m].name)] > 1\r\n self.npc_list[m].alert_close_proximity(multiple)\r\n break\r\n\r\n interaction_result = NextState\r\n \r\n if hostile_close_proximity:\r\n #start combat\r\n interaction_result = NextState.COMBAT\r\n else:\r\n #run interaction choice menu - interactions may return flags that spawn social/combat encounters\r\n print(\"Select NPC to interact with:\")\r\n for l in range(len(self.npc_list)):\r\n print(str(l + 1) + \". \" + self.npc_list[l].name + \" (Distance: \" + str(self.npc_distances[l]) + \"ft.)\")\r\n \r\n choice = 0\r\n while choice < 1 or choice > len(self.npc_names) + 1:\r\n try:\r\n choice = int(input(\"Make selection: \"))\r\n except:\r\n print(\"Enter an integer between 1 and \" + str(len(self.npc_names)))\r\n \r\n interaction_result = self.npc_list[choice - 1].interact(self, choice - 1, self.main_player)\r\n\r\n #spawn social/combat encounter\r\n #if combat, pass npc list to generate turn order\r\n if interaction_result.name == \"COMBAT\":\r\n #spawn combat encounter\r\n print(\"Starting combat\")\r\n new_combat = combat.CombatEncounter(self.main_player, self.npc_list, self.npc_distances, self.npc_quantities)\r\n elif interaction_result.name == \"SOCIAL\":\r\n #spawn social encounter\r\n print(\"Starting social encounter\")\r\n elif interaction_result.name == \"FINISHED\":\r\n #present next choices, award loot from area\r\n #allow player to interact with any remaining/new NPCs\r\n print(\"Encounter finished\")\r\n elif interaction_result.name == \"DEATH\":\r\n #kill the player and end the game\r\n print(\"Player dead\")","def place(self, board):\r\n self.board = board","def append(self, agent):\n self.agents.append(agent)","def add_objects_to_space(self):\n self.anti_spacecraft.add_to_space(self.space) # Anti-spacecraft Parts (represent the whole vehicle)\n self.space.add(self.spacecraft.body, self.spacecraft.shape) # Spacecraft body and shape\n self.space.add(self.pm_landing_pad) # Landing pad","def draw_world(grid, r, c, image):\n under = grid[r, c]\n grid[r, c] = AGENT\n image.set_data(grid)\n grid[r, c] = under","def make_hh_agents_2016(self):\r\n for hh_row in agents: # agents is a list of ints 1-97 from excel_import\r\n self.hhpos = self.determine_hhpos(hh_row, 'house_latitude', 'house_longitude')\r\n self.hh_id = return_values(hh_row, 'hh_id')\r\n self.admin_village = 1\r\n\r\n # 2016\r\n mig_remittances = return_values(hh_row, 'mig_remittances') # remittances of initial migrant\r\n if mig_remittances is None:\r\n mig_remittances = 0\r\n household_income_list[hh_row - 1] = int(mig_remittances)\r\n household_remittances_list[hh_row - 1] = int(mig_remittances)\r\n\r\n if return_values(hh_row, 'initial_migrants') is not None:\r\n out_mig_list[hh_row - 1] = 1\r\n household_migrants_list.append(self.hh_id)\r\n cumulative_mig_list[hh_row - 1] = 1\r\n\r\n num_labor_list[hh_row - 1] = initialize_labor(hh_row)\r\n hh_size_list[hh_row - 1] = len(return_values(hh_row, 'age'))\r\n\r\n a = HouseholdAgent(hh_row, self, self.hh_id, self.admin_village)\r\n self.space.place_agent(a, self.hhpos) # admin_village placeholder\r\n self.schedule.add(a)","def addTiles(self, rows, cols, minecount):\n for row in range(rows):\n self.tiles.append([])\n for col in range(cols):\n tile = Tile(self, row, col)\n tile.grid(row=row+1, column=col)\n self.tiles[row].append(tile)\n #left click listeners\n tile.bind('<ButtonPress-1>', self.pressTile)\n tile.bind('<ButtonRelease-1>', self.showTile)\n #middle click listeners\n tile.bind('<ButtonPress-2>', self.pressAdjTiles)\n tile.bind('<ButtonRelease-2>', self.showAdjTiles)\n #right click listeners\n tile.bind('<ButtonPress-3>', self.pressTile)\n tile.bind('<ButtonRelease-3>', self.toggleFlag)","def sea_execution(board, position, role):\n quitt = False\n if position == 'comp':\n #print(1)\n #temporary for dumb AI\n #create and print a list of coastal, friendly regions where norse is not the ONLY one\n \n possible_region_list = []\n \n #loops through list of friendly, coastal, not just Norse regions to append to a possible_region_list\n for region in board.get_controlled_regions(role):\n #print(2)\n coastal = False\n just_norse = False\n if region.coast:\n coastal = True\n if len(region.blocks_present) == 1 and region.blocks_present[0].name.upper() == 'NORSE':\n just_norse = True\n \n if coastal and not just_norse:\n possible_region_list.append(region)\n \n \n #loops through list of friendly, coastal regions to append to a possible_final_region_list\n possible_final_region_list = []\n for region in board.get_controlled_regions(role): \n #print(3) \n if region.coast:\n possible_final_region_list.append(region)\n \n \n \n if len(possible_final_region_list) >= 2:\n #if you want to add in last-min strategy, do it here\n #random region from possible list\n england = board.regions[22]\n if england in possible_region_list:\n original_region = england\n else:\n original_region = possible_region_list[random.randint(0, len(possible_region_list) - 1)]\n #remove the original region from the possible end regions\n possible_final_region_list.remove(original_region)\n \n #possible_block_list\n #list of possible blocks to move (present in region) and not norse\n possible_block_list = []\n for block in original_region.blocks_present:\n if block.name != 'NORSE':\n possible_block_list.append(block)\n \n move_block_list = []\n blocks_moved = 0\n #print(4)\n\n while blocks_moved < 2:\n #print(5)\n block = possible_block_list[random.randint(0, len(possible_block_list)-1)]\n #if it's not already on the list,append to move_block_list\n if block not in move_block_list:\n move_block_list.append(block)\n blocks_moved+=1\n elif block in move_block_list and len(possible_block_list) == 1:\n blocks_moved+=1\n else:\n print('neither condition was met so this is an infinite loop')\n \n \n #print(6) \n new_region = possible_final_region_list[random.randint(0, len(possible_final_region_list) - 1)]\n \n for block in move_block_list:\n \n board.add_to_location(block, new_region)\n print(block.name + ' moved from ' + original_region.name + ' to ' + new_region.name)\n \n else:\n print('There are not enough friendly regions with which to play this card.')\n \n \n #add in if it's not possible\n elif position == 'opp':\n \n \n possible_region_list = []\n \n #loops through list of friendly, coastal, not just Norse regions to append to a possible_region_list\n for region in board.get_controlled_regions(role):\n coastal = False\n just_norse = False\n if region.coast:\n coastal = True\n if len(region.blocks_present) == 1 and region.blocks_present[0].name.upper() == 'NORSE':\n just_norse = True\n \n if coastal and not just_norse:\n possible_region_list.append(region)\n \n \n #loops through list of friendly, coastal regions to append to a possible_final_region_list\n possible_final_region_list = []\n for region in board.get_controlled_regions(role): \n if region.coast:\n possible_final_region_list.append(region)\n \n \n \n if len(possible_final_region_list) >= 2:\n \n print('Possible origin regions:')\n for region in possible_region_list:\n print(region.name)\n \n #user input region, check if in possible list\n valid_region = False\n while not valid_region:\n \n original_region_name = input('What region would you like to move block(s) from? Enter a name or \\'none\\'.\\n>').upper()\n \n if original_region_name != 'NONE':\n \n original_region = search.region_name_to_object(board, original_region_name)\n \n if original_region and original_region in possible_region_list:\n valid_region = True\n else:\n print('Invalid region.')\n else:\n quitt = True\n \n if not quitt:\n #remove the original region from the possible end regions\n possible_final_region_list.remove(original_region)\n \n #possible_block_list\n #list of possible blocks to move (present in region) and not norse\n possible_block_list = []\n for block in original_region.blocks_present:\n if block.name != 'NORSE':\n possible_block_list.append(block)\n \n print('Possible blocks:')\n for block in possible_block_list:\n print(block.name)\n \n \n move_block_list = []\n blocks_moved = 0\n quittt = False\n block_name = ''\n while blocks_moved < 2 and not quittt:\n if block_name != 'NONE':\n valid_block = False\n while not valid_block:\n \n \n block_name = input('Which block would you like to move? Enter a name or \\'none\\'.\\n>').upper()\n \n if block_name != 'NONE':\n \n block_to_move = search.block_name_to_object(possible_block_list, block_name)\n \n if block_to_move and block_to_move not in move_block_list:\n valid_block = True\n move_block_list.append(block_to_move)\n blocks_moved+=1\n \n elif block in move_block_list and len(possible_block_list) == 1:\n blocks_moved=1\n \n else:\n print('Invalid block.')\n continue\n else:\n valid_block = True\n if len(move_block_list) == 1:\n quittt = True\n quitt = False\n if len(move_block_list) > 0: \n print('Possible final regions:')\n for region in possible_final_region_list:\n print(region.name)\n \n #user input region, check if in possible list\n valid_region = False\n while not valid_region:\n \n new_region_name = input('What region would you like to move block(s) to? Enter a name or \\'none\\'.\\n>').upper()\n \n if new_region_name != 'NONE':\n \n new_region = search.region_name_to_object(board, new_region_name)\n \n if new_region and new_region in possible_final_region_list:\n valid_region = True\n else:\n print('Invalid region.')\n continue\n else:\n valid_region = True\n quitt = True\n \n if not quitt:\n \n for block in move_block_list:\n \n board.add_to_location(block, new_region)\n print(block.name + ' moved from ' + original_region.name + ' to ' + new_region.name)\n \n else:\n print('There are not enough friendly coastal regions with which to play this card.')","def step(self):\n try:\n self.agents.sort(key=lambda x: x.dist)\n except Exception as e:\n print(e)\n\n for agent in self.agents:\n try:\n agent.step()\n except Exception as e:\n print(e)\n\n\n # Removes agents if they reach exit\n for exit in self.model.exits:\n x, y = exit.pos[0] * 6 + 1, exit.pos[1] * 6 + 1\n if agent.node == (x, y):\n try:\n agent.saved()\n except Exception as e:\n print(e)","def _update_board(self):\n\n self.game_board.update_board(self.tetrino_set)","def step(self):\n self.age += 1\n self.move_agent()\n self.sugar -= self.metabolism\n\n # Eat sugar\n available_sugar = self.get_sugar(self.pos).amount\n self.sugar += available_sugar\n# self.total_sugar_in_field -= available_sugar\n # Set sugar in current cell to zero\n self.get_sugar(self.pos).eat_sugar() \n \n \n \n if self.sugar == 0:\n self.model.remove_agent(self)\n \n self.gen += 1\n x = self.model.random.randrange(self.model.grid.width)\n y = self.model.random.randrange(self.model.grid.height)\n new_pos = (x,y)\n \n self.model.add_agent(Consumer, new_pos, f\"{self.unique_id.split('-')[0]}-{self.gen}\", self.gen, self.model.vision, self.model.metabolism, self.model.starting_sugar)\n \n \n if self.reproduction_and_death:\n if self.age > self.max_age: # Agent dies\n # Tax inheritance\n self.model.inheritance_tax_agent(self)\n \n if self.model.spawn_at_random:\n self.gen += 1\n x = self.model.random.randrange(self.model.grid.width)\n y = self.model.random.randrange(self.model.grid.height)\n new_pos = (x,y)\n \n self.model.add_agent(Consumer, new_pos, f\"{self.unique_id.split('-')[0]}-{self.gen}\", self.gen, self.model.vision, self.model.metabolism, self.model.starting_sugar)\n self.model.remove_agent(self) #agent dies\n \n \n else:\n #spawn new agent\n self.gen += 1\n if self.sugar != 0:\n self.model.add_agent(Consumer, self.pos, f\"{self.unique_id.split('-')[0]}-{self.gen}\", self.gen, self.vision, self.metabolism, self.sugar)\n else:\n self.model.add_agent(Consumer, self.pos, f\"{self.unique_id.split('-')[0]}-{self.gen}\", self.gen, self.vision, self.metabolism, self.model.starting_sugar)\n \n self.model.remove_agent(self) #agent dies","def load_agents(self, agents):\n self.agents = agents","def _place_board(self, board):\n for i, row in enumerate(board):\n for j, widget in enumerate(row):\n widget.grid(row = i, column = j)","def setup_lists(self):\n \n # Decompose spores do not affect terrain like ground or water\n for thing in self.room.wall_list:\n self.unaffected.add(thing)\n\n for thing in self.room.sludge:\n self.unaffected.add(thing)\n\n # It does, however, destroy enemies and things that are alive. Later implement logs.\n for thing in self.room.enemy_list:\n self.affected.add(thing)\n\n for thing in self.room.can_climb:\n self.affected.add(thing)","def add_parties(self, *parties) -> None:\n\n for party in parties:\n self._route_table['route_table'][party.get_id()] = party.to_entry_point(\n )","def add_to_grid_queue(self, agent):\n self.pipes[agent.grid_queue].send(\"add\")\n self.pipes[agent.grid_queue].send(agent)","def add_all_regions():\n gene_id = request.json['gene_id']\n panel_id = request.json['panel_id']\n tx_id = request.json['tx_id']\n gene_name = request.json['gene_name']\n project_id = get_project_id_by_panel_id(s, panel_id)\n\n add_preftxs_to_panel(s, project_id, [{\"gene\": gene_name, \"tx_id\": tx_id}, ])\n add_genes_to_panel_with_ext(s, panel_id, gene_id)\n return jsonify({\"genes\": [gene_id, ]})","def insert_parts(self, parts):\r\n self.board.insert_parts(parts)\r\n self.set_changed(parts)","def updated_occupied_locations(self):\n if len(self.occupiedLocations) > self.currentTurn:\n self.occupiedLocations[self.currentTurn] += [self.character.path[-1]]\n else:\n self.occupiedLocations += [[self.character.path[-1]]]","def __activate(self, x: int, y: int, tree: int) -> None:\n self.__maze[x, y] = tree","def spill(self, agent):\n self.spill_list.append(agent)","def advance_board(self):\n # We can advance the board using a pretty simple convolution,\n # so we don't have to execute a lot of loops in python.\n # Of course, this probably won't be sufficient for extremely\n # large boards.\n self.num_steps += 1\n board = self.board\n cfilter = np.array([[1,1,1],[1,0,1],[1,1,1]], dtype=np.uint16)\n\n alive = board & CellTypes.alive > 0\n spawning = board & CellTypes.spawning > 0\n frozen = board & CellTypes.frozen > 0\n\n can_die = ~frozen & (\n convolve2d(board & CellTypes.preserving, cfilter) == 0)\n can_grow = ~frozen & (\n convolve2d(board & CellTypes.inhibiting, cfilter) == 0)\n\n num_neighbors = convolve2d(alive, cfilter)\n num_spawn = convolve2d(spawning, cfilter)\n spawn_prob = 1 - (1 - self.spawn_prob)**num_spawn\n has_spawned = coinflip(spawn_prob, board.shape)\n\n born_rule = np.zeros(9, dtype=bool)\n born_rule[list(self.born_rule)] = True\n dead_rule = np.ones(9, dtype=bool)\n dead_rule[list(self.survive_rule)] = False\n\n new_alive = (born_rule[num_neighbors] | has_spawned) & ~alive & can_grow\n new_dead = dead_rule[num_neighbors] & alive & can_die\n\n new_flags = np.zeros_like(board)\n color_weights = 1 * alive + 2 * spawning\n for color in CellTypes.colors:\n # For each of the colors, see if there are two or more neighbors\n # that have it. If so, any new cells (whether born or spawned)\n # will also get that color.\n has_color = board & color > 0\n new_color = convolve2d(has_color * color_weights, cfilter) >= 2\n new_flags += color * new_color\n indestructible = alive & (board & CellTypes.destructible == 0)\n new_flags += CellTypes.destructible * (convolve2d(indestructible, cfilter) < 2)\n\n board *= ~(new_alive | new_dead)\n board += new_alive * (CellTypes.alive + new_flags)","def add_artifacts(cells_info):\n # Add fire extinguishers\n cells_info[(1, 0)].add_artifact(\"Extinguisher@2.1 2.1 0.004 0 0 0\")\n cells_info[(1, 14)].add_artifact(\"Extinguisher@2.1 -2.1 0.004 -90 0 90\")\n cells_info[(7, 6)].add_artifact(\"Extinguisher@2.1 -3 0.004 0 0 0\")\n cells_info[(7, 0)].add_artifact(\"Extinguisher@-5 0 5.004 -90 0 300\")\n\n # Add phones\n cells_info[(8, 3)].add_artifact(\"Phone@-2.1 3 0.004 -90 0 0\")\n cells_info[(15, 0)].add_artifact(\"Phone@-3 2.1 0.004 -90 0 -90\")\n cells_info[(13, 7)].add_artifact(\"Phone@-3 0 0.004 90 0 -30\")\n cells_info[(4, 2)].add_artifact(\"Phone@-1 -4 0.004 90 0 0\")\n\n # Add backpacks\n cells_info[(10, 6)].add_artifact(\"Backpack@-6 -1.3 0.004 0 0 0\")\n cells_info[(1, 5)].add_artifact(\"Backpack@2.1 6 0.004 -90 0 0\")\n cells_info[(0, 8)].add_artifact(\"Backpack@1 6 0.004 -90 0 0\")\n cells_info[(15, 4)].add_artifact(\"Backpack@2 2 0.004 90 0 0\")\n\n # Add Rescue Randy\n cells_info[(15, 15)].add_artifact(\"Rescue Randy@1 -7 0.004 0 0 180\")\n cells_info[(15, 7)].add_artifact(\"Rescue Randy@-1 6 0.004 0 0 0\")\n cells_info[(5, 12)].add_artifact(\"Rescue Randy@2.2 6.5 0.004 0 0 -90\")\n cells_info[(2, 11)].add_artifact(\"Rescue Randy@0 -7 0.004 0 0 180\")\n\n # Add Drills\n cells_info[(8, 8)].add_artifact(\"Drill@-6 0 0.004 0 -90 0\")\n cells_info[(10, 15)].add_artifact(\"Drill@-6 -1.2 0.004 0 90 -20\")\n cells_info[(3, 7)].add_artifact(\"Drill@2.1 7 0.004 0 0 0\")\n cells_info[(13, 6)].add_artifact(\"Drill@0 -7 0.004 0 90 -80\")","def reset_agent_locations(self):\n self.transitions_left = self.T-1\n self.x_agent = np.repeat(self.xT.reshape(1, self.dimensions), self.n_agents, axis=0)","def add_spawns_outside_boss_doors(self: WWRandomizer):\n \n rooms_to_add_new_spawns_to = [\n (\"M_NewD2\", 10, TGDR, None, 11),\n #(\"kindan\", 16, TGDR, None, 13), # Already has a spawn, ID 1.\n (\"Siren\", 18, TGDR, None, 13),\n (\"sea\", 1, ACTR, 1, 56),\n (\"M_Dai\", 15, TGDR, None, 17),\n (\"kaze\", 12, TGDR, None, 13),\n ]\n \n for stage_name, room_number, chunk, layer, boss_door_index in rooms_to_add_new_spawns_to:\n new_spawn_id = 27\n \n dzs = self.get_arc(\"files/res/Stage/%s/Stage.arc\" % stage_name).get_file(\"stage.dzs\", DZx)\n dzr = self.get_arc(\"files/res/Stage/%s/Room%d.arc\" % (stage_name, room_number)).get_file(\"room.dzr\", DZx)\n \n if chunk == TGDR:\n dzx_for_door = dzs\n else:\n dzx_for_door = dzr\n \n door = dzx_for_door.entries_by_type_and_layer(chunk, layer=layer)[boss_door_index]\n spawn_dist_from_door = 200\n y_rot = door.y_rot\n if door.from_room_num != room_number and door.from_room_num != 63:\n y_rot = (y_rot + 0x8000) % 0x10000\n y_rot_degrees = y_rot * (90.0 / 0x4000)\n x_offset = math.sin(math.radians(y_rot_degrees)) * spawn_dist_from_door\n z_offset = math.cos(math.radians(y_rot_degrees)) * spawn_dist_from_door\n x_pos = door.x_pos + x_offset\n y_pos = door.y_pos\n z_pos = door.z_pos + z_offset\n \n if stage_name in [\"M_Dai\", \"kaze\"]:\n # Earth and Wind temple spawns must be in the stage instead of the room or the game will crash.\n dzx_for_spawn = dzs\n else:\n dzx_for_spawn = dzr\n \n spawns = dzx_for_spawn.entries_by_type(PLYR)\n assert len([spawn for spawn in spawns if spawn.spawn_id == new_spawn_id]) == 0\n \n new_spawn = dzx_for_spawn.add_entity(PLYR)\n new_spawn.spawn_type = 0\n new_spawn.room_num = room_number\n new_spawn.x_pos = x_pos\n new_spawn.y_pos = y_pos\n new_spawn.z_pos = z_pos\n new_spawn.y_rot = y_rot\n new_spawn.spawn_id = new_spawn_id\n \n dzx_for_spawn.save_changes()","def addAgent(self, new_agent, parent_agent, secondary_caregivers):\n # set unique id\n new_agent.ID = self.idCounter\n self.idCounter += 1\n \n self.pop.append(new_agent)\n newPopStructure = np.zeros((self.popStructure.shape[0]+1,self.popStructure.shape[1]+1))\n newPopStructure[:-1,:-1] = self.popStructure\n\n \n # inherit social structure from parent\n parent_id = self.findAgentIndexById(parent_agent)\n secondary_caregivers_ids = [self.findAgentIndexById(a) for a in secondary_caregivers]\n newPopStructure[-1,] = newPopStructure[parent_id,]\n newPopStructure[:,-1] = newPopStructure[:,parent_id] \n\n\t\t# strong bond between parents\n newPopStructure[-1,parent_id] = self.parameters[\"maxWeight\"]\n newPopStructure[parent_id,-1] = self.parameters[\"maxWeight\"]\n for s in secondary_caregivers_ids:\n \tnewPopStructure[-1,s] =self.parameters[\"maxWeight\"]\n \tnewPopStructure[s,-1] =self.parameters[\"maxWeight\"]\n\n # can't communicate with self\n np.fill_diagonal(newPopStructure, 0.0)\n \n self.popStructure = newPopStructure\n \n # start unmarried\n newMarriageStructure = np.zeros((self.marriageStructure.shape[0]+1,self.marriageStructure.shape[1]+1))\n newMarriageStructure[:-1,:-1] = self.marriageStructure\n newMarriageStructure[-1,] = 0\n newMarriageStructure[:,-1] = 0\n self.marriageStructure = newMarriageStructure\n \n\t\t# inherit clan from parent\n parent_clan = self.clans[parent_id]\n parent_compound = self.compounds[parent_id]\n \n self.clans.append(parent_clan)\n self.compounds.append(parent_compound)\n\n self.nAgents = len(self.pop)","def load_inventory(self):\n for item in self.items:\n self.rooms[int(item.initial_room_id) - 1].inventory.add(item)","def execute_actions(self, actions):\n execute_actions(self.board, self.agent_locs, actions)","def gen_game(\n board_shape=(25,25), min_performance=-1, partitioning={},\n starting_region=None, later_regions=None, buffer_region=None,\n named_regions={}, agents=['default'], agent_types={}, **etc):\n board_shape = _fix_random_values(board_shape)\n min_performance = _fix_random_values(min_performance)\n partitioning = _fix_random_values(partitioning)\n\n regions = make_partioned_regions(board_shape, **partitioning)\n board = np.zeros(board_shape, dtype=np.uint16)\n goals = np.zeros(board_shape, dtype=np.uint16)\n\n # Create locations for the player and the exit\n agent_locs, points_table, agent_names = add_agents_and_exit(\n board, regions, agents, agent_types)\n\n # and fill in the regions...\n for k in np.unique(regions)[2:]:\n mask = regions == k\n if starting_region is not None:\n region_name = _fix_random_values(starting_region)\n else:\n region_name = _fix_random_values(later_regions)\n if region_name not in named_regions:\n logger.error(\"No region parameters for name '%s'\", region_name)\n continue\n logger.debug(\"Making region: %s\", region_name)\n rboard, rgoals = populate_region(mask, named_regions[region_name])\n board += rboard\n goals += rgoals\n starting_region = None\n buffer_region = _fix_random_values(buffer_region)\n if buffer_region in named_regions:\n mask = regions == 0\n rboard, rgoals = populate_region(mask, named_regions[buffer_region])\n board += rboard\n goals += rgoals\n\n # Give the buffer (0) region a rainbow / white color\n # This is mostly a visual hint for humans\n buffer_mask = (regions <= 0) & (goals & CellTypes.rainbow_color == 0)\n goals[buffer_mask] += CellTypes.rainbow_color\n\n game = SafeLifeGame()\n game.deserialize({\n 'board': board,\n 'goals': goals,\n 'agent_locs': agent_locs,\n 'agent_names': agent_names,\n 'min_performance': min_performance,\n 'points_table': points_table,\n 'orientation': 1,\n })\n return game","def add_agents(*_coconut_match_args, **_coconut_match_kwargs):\n _coconut_match_check_2 = False\n _coconut_match_set_name_self = _coconut_sentinel\n _coconut_match_set_name_agents = _coconut_sentinel\n _coconut_match_set_name__set_defaults = _coconut_sentinel\n _coconut_match_set_name_named_agents = _coconut_sentinel\n _coconut_FunctionMatchError = _coconut_get_function_match_error()\n if _coconut.sum((_coconut.len(_coconut_match_args) > 0, \"self\" in _coconut_match_kwargs)) == 1:\n _coconut_match_set_name_agents = _coconut_match_args[1:]\n _coconut_match_temp_5 = _coconut_match_kwargs.pop(\"_set_defaults\") if \"_set_defaults\" in _coconut_match_kwargs else True\n _coconut_match_temp_4 = _coconut_match_args[0] if _coconut.len(_coconut_match_args) > 0 else _coconut_match_kwargs.pop(\"self\")\n _coconut_match_set_name__set_defaults = _coconut_match_temp_5\n _coconut_match_set_name_self = _coconut_match_temp_4\n _coconut_match_set_name_named_agents = _coconut_match_kwargs\n _coconut_match_check_2 = True\n if _coconut_match_check_2:\n if _coconut_match_set_name_self is not _coconut_sentinel:\n self = _coconut_match_set_name_self\n if _coconut_match_set_name_agents is not _coconut_sentinel:\n agents = _coconut_match_set_name_agents\n if _coconut_match_set_name__set_defaults is not _coconut_sentinel:\n _set_defaults = _coconut_match_set_name__set_defaults\n if _coconut_match_set_name_named_agents is not _coconut_sentinel:\n named_agents = _coconut_match_set_name_named_agents\n if not _coconut_match_check_2:\n raise _coconut_FunctionMatchError('match def add_agents(self, *agents, _set_defaults=True, **named_agents):', _coconut_match_args)\n\n new_agents = []\n for a in _coconut.itertools.chain.from_iterable(_coconut_reiterable(_coconut_func() for _coconut_func in (lambda: agents, lambda: named_agents.items()))):\n _coconut_match_to_0 = a\n _coconut_match_check_1 = False\n _coconut_match_set_name_name = _coconut_sentinel\n _coconut_match_set_name_actor = _coconut_sentinel\n if (_coconut.isinstance(_coconut_match_to_0, _coconut.abc.Sequence)) and (_coconut.len(_coconut_match_to_0) == 2):\n _coconut_match_set_name_name = _coconut_match_to_0[0]\n _coconut_match_set_name_actor = _coconut_match_to_0[1]\n _coconut_match_check_1 = True\n if _coconut_match_check_1:\n if _coconut_match_set_name_name is not _coconut_sentinel:\n name = _coconut_match_set_name_name\n if _coconut_match_set_name_actor is not _coconut_sentinel:\n actor = _coconut_match_set_name_actor\n if _coconut_match_check_1:\n if not callable(actor):\n a = init_agent(name, actor)\n elif isinstance(actor, Agent):\n a = actor.clone(name=name)\n else:\n a = Agent(name, actor)\n assert isinstance(a, Agent), \"not isinstance({_coconut_format_0}, Agent)\".format(_coconut_format_0=(a))\n new_agents.append(a)\n self.agents += new_agents\n if _set_defaults:\n self.set_defaults(new_agents)\n return self","def move_to(self, entity, location):\n y, x = location\n if not y in range(self.size) or not x in range(self.size):\n return\n y, x = entity.location\n self.grid[y][x].contents.remove(entity)\n entity.location = location\n y, x = location\n self.grid[y][x].contents.append(entity)\n for ent in self.grid[y][x].contents:\n try:\n if not ent.player_enter_callback is None:\n ent.player_enter_callback(ent)\n except AttributeError:\n pass","def push_up(self, event):\n self.transpose()\n self.stack()\n self.merge()\n self.transpose()\n\n if self.any_empty_tiles():\n self.add_two()\n\n self.update_grid()\n self.is_game_finished()","def registerInitialState(self, gameState):\n\n '''\n Make sure you do not delete the following line. If you would like to\n use Manhattan distances instead of maze distances in order to save\n on initialization time, please take a look at\n CaptureAgent.registerInitialState in captureAgents.py.\n '''\n self.start = gameState.getAgentPosition(self.index)\n CaptureAgent.registerInitialState(self, gameState)\n\n \"G A M E K E Y L O C A T I O N S D E T E R M I N A T I O N\"\n if self.red:\n leftEdge = gameState.data.layout.width / 2\n rightEdge = gameState.data.layout.width - 2 #don't need the last wall\n self.safeColumn = leftEdge - 2 # -1 doesn't always seem to work\n else:\n leftEdge = 1\n rightEdge = gameState.data.layout.width / 2\n self.safeColumn = rightEdge + 2\n\n self.safeSpaces = []\n for h in xrange(1,gameState.data.layout.height-1):\n if not gameState.data.layout.isWall((self.safeColumn, h)):\n self.safeSpaces += [(self.safeColumn, h)]\n\n\n \"S T A T E A S S I G N M E N T\"\n pos = gameState.getAgentState(self.index).getPosition()\n self.friend = min(2 + int(not self.red), 2 - self.index + 2 * int(not self.red))\n friendPos = gameState.getAgentState(self.friend).getPosition()\n opps = [gameState.getAgentState(el).getPosition() for el in [1 - int(not self.red), 3 - int(not self.red)] ]\n\n print \"I am agent\", self.index, \"at position \", pos\n #print \"agent 0:\", gameState.getAgentState(0).getPosition()\n print \"My friend agent\", self.friend, \"is at position \", friendPos\n print \"My first enemy agent is at position \", opps[0]\n print \"My second enemy agent is at position \", opps[1]\n\n self.top = False\n self.undecided = False\n\n if pos[1] > friendPos[1]:\n print \"My friend is lower on the map, and I will take top Quad\"\n self.top = True\n elif pos[1] < friendPos[1]:\n print \"My friend is higher on the map, and I will take bottom Quad\"\n else:\n self.undecided = True\n\n \"F O O D A S S I G N M E N T\"\n self.initFood = self.getFood(gameState).asList()\n self.myFood = self.initFood[:] #this is will be updated during our A* Search for theoretical consumption\n print self.myFood\n\n \"I N I T I A L F O O D A S S I G N M E N T S \"\n\n start = time.time()\n print 'eval time for moves: %.4f' % (time.time() - start)\n\n\n \"D E B U G G I N G\"\n print \"Coloring my safe column white\"\n self.debugDraw([(self.safeColumn, el) for el in xrange(0, gameState.data.layout.height)], [1,1,1], clear=False)\n\n print \"Coloring my safe spaces\", self.safeSpaces, \"blue\"\n self.debugDraw(self.safeSpaces, [0,0,1], clear=False)\n\n self.counter = 0\n self.moves = []\n self.intendedCoords =[]\n self.best = None\n\n #new\n print \"Using my sweet time to find next moves during init as agent\", self.index\n self.best = self.ActionLoop(gameState, 140)\n self.moves = self.best.getDir()[1]\n self.counter = len(self.moves)\n self.cacheSize = len(self.moves)\n #new","def __add_players_spawns(self):\n # Werewolves\n self.__grid[self.__werewolves_start[0]][self.__werewolves_start[1]][\"werewolves\"] \\\n = self.__number_of_beasts\n # Vampires\n self.__grid[self.__vampires_start[0]][self.__vampires_start[1]][\"vampires\"] \\\n = self.__number_of_beasts","def draw_board(self):\n self.current_board = self.gameboard.copy()\n \n # Draw our rewards\n for r, row in enumerate(self.world_rewards):\n for c, reward in enumerate(row):\n if reward is not None:\n asset_key = reward.asset\n x = 64*(c+1)\n y = 64*(r+1)\n self.current_board.paste(\\\n self.assets[asset_key], (x,y), self.assets[asset_key])\n \n # Draw our creature\n cr_x, cr_y = self.creature.current_location\n x = 64*(cr_x + 1) # Should be the center of the tile\n y = 64*(cr_y + 1)\n creature_image = self.assets['beaver']\n if self.creature.facing == 'S':\n creature_image = creature_image.rotate(-180)\n elif self.creature.facing == 'E':\n creature_image = creature_image.rotate(-90)\n elif self.creature.facing == 'W':\n creature_image = creature_image.rotate(-270)\n self.current_board.paste(creature_image, (x,y), creature_image)","def on_enter(self):\n # Obtain pointer to Parent Grid + Obstacles\n self._grid = self.parent._grid\n self._obstacles = self.parent._obstacles\n super().on_enter()","def _add_agent_to_graph(self, agent: mantrap.agents.base.DTAgent):\n from data import Node\n is_robot = agent.is_robot\n\n # In Trajectron each node has a certain type, which is either robot or pedestrian, an id and\n # state data. Enforce the Trajectron id to the internal ids format, to be able to query the\n # results later on.\n agent_history = agent.history\n acc_history = agent.compute_acceleration(agent_history, dt=self.dt)\n\n node_data = self._create_node_data(state_history=agent_history, accelerations=acc_history)\n node_tye = self._gt_env.NodeType.PEDESTRIAN if not is_robot else self._gt_env.NodeType.ROBOT\n node = Node(node_type=node_tye, node_id=agent.id, data=node_data, is_robot=is_robot)\n if is_robot:\n self._gt_scene.robot = node\n self._gt_scene.nodes.append(node)\n\n # Re-Create online environment with recently appended node.\n self._online_env = self.create_online_env(env=self._gt_env, scene=self._gt_scene)","def add_zombie(self, row, col):\r\n self._zombie_list.append((row, col))","def add_rect(self, r, obj):\n cells = self._cells_for_rect(r)\n for c in cells:\n self._add(c, obj)","def cells(self, cells):\n\n self.container['cells'] = cells","def add_zombie(self, row, col):\n self._zombie_list.append((row,col))","def make_land_agents_2016(self):\r\n # add non-gtgp\r\n for hh_row in agents: # from excel_import\r\n hh_id = return_values(hh_row, 'hh_id')\r\n self.total_rice = return_values(hh_row, 'non_gtgp_rice_mu')\r\n if self.total_rice in ['-3', '-4', -3, None]:\r\n self.total_rice = 0\r\n self.total_dry = return_values(hh_row, 'non_gtgp_dry_mu')\r\n if self.total_dry in ['-3', '-4', -3, None]:\r\n self.total_dry = 0\r\n self.gtgp_rice = return_values(hh_row, 'gtgp_rice_mu')\r\n if self.gtgp_rice in ['-3', '-4', -3, None]:\r\n self.total_rice = 0\r\n self.gtgp_dry = return_values(hh_row, 'gtgp_dry_mu')\r\n if self.gtgp_dry in ['-3', '-4', -3, None]:\r\n self.gtgp_dry = 0\r\n\r\n landposlist = self.determine_landpos(hh_row, 'non_gtgp_latitude', 'non_gtgp_longitude')\r\n self.age_1 = return_values(hh_row, 'age')[0]\r\n self.gender_1 = return_values(hh_row, 'gender')[0]\r\n self.education_1 = return_values(hh_row, 'education')[0]\r\n\r\n for landpos in landposlist:\r\n try:\r\n self.pre_gtgp_output = return_values(hh_row, 'pre_gtgp_output')[landposlist.index(landpos)]\r\n except:\r\n pass\r\n\r\n try:\r\n self.non_gtgp_output = return_values(hh_row, 'pre_gtgp_output')[landposlist.index(landpos)]\r\n except:\r\n pass\r\n self.land_time = return_values(hh_row, 'non_gtgp_travel_time')[landposlist.index(landpos)]\r\n try:\r\n self.plant_type = return_values(hh_row, 'non_gtgp_plant_type')[landposlist.index(landpos)]\r\n except:\r\n pass\r\n try:\r\n self.land_type = return_values(hh_row, 'non_gtgp_land_type')[landposlist.index(landpos)]\r\n except:\r\n pass\r\n self.hh_size = len(return_values(hh_row, 'age'))\r\n self.gtgp_enrolled = 0\r\n lp = LandParcelAgent(hh_row, self, hh_id, hh_row, landpos, self.gtgp_enrolled,\r\n self.age_1, self.gender_1, self.education_1,\r\n self.gtgp_dry, self.gtgp_rice, self.total_dry, self.total_rice,\r\n self.land_type, self.land_time, self.plant_type, self.non_gtgp_output,\r\n self.pre_gtgp_output)\r\n self.space.place_agent(lp, landpos)\r\n self.schedule.add(lp)\r\n if self.gtgp_enrolled == 0 and landpos not in nongtgplist and landpos not in gtgplist:\r\n nongtgplist.append(landpos)\r\n # except:\r\n # pass\r\n\r\n # add gtgp\r\n for hh_row in agents: # from excel_import\r\n hh_id = return_values(hh_row, 'hh_id')\r\n self.total_rice = return_values(hh_row, 'non_gtgp_rice_mu')\r\n if self.total_rice in ['-3', '-4', -3, None]:\r\n self.total_rice = 0\r\n self.total_dry = return_values(hh_row, 'non_gtgp_dry_mu')\r\n if self.total_dry in ['-3', '-4', -3, None]:\r\n self.total_dry = 0\r\n self.gtgp_rice = return_values(hh_row, 'gtgp_rice_mu')\r\n if self.gtgp_rice in ['-3', '-4', -3, None]:\r\n self.total_rice = 0\r\n self.gtgp_dry = return_values(hh_row, 'gtgp_dry_mu')\r\n if self.gtgp_dry in ['-3', '-4', -3, None]:\r\n self.gtgp_dry = 0\r\n landposlist = self.determine_landpos(hh_row, 'gtgp_latitude', 'gtgp_longitude')\r\n self.age_1 = return_values(hh_row, 'age')[0]\r\n self.gender_1 = return_values(hh_row, 'gender')[0]\r\n self.education_1 = return_values(hh_row, 'education')[0]\r\n for landpos in landposlist:\r\n try:\r\n self.pre_gtgp_output = return_values(hh_row, 'pre_gtgp_output')[landposlist.index(landpos)]\r\n except:\r\n pass\r\n try:\r\n self.non_gtgp_output = return_values(hh_row, 'pre_gtgp_output')[landposlist.index(landpos)]\r\n except:\r\n pass\r\n try:\r\n self.land_time = return_values(hh_row, 'gtgp_travel_time')[landposlist.index(landpos)]\r\n except:\r\n pass\r\n try:\r\n self.plant_type = return_values(hh_row, 'pre_gtgp_plant_type')[landposlist.index(landpos)]\r\n except:\r\n pass\r\n try:\r\n self.land_type = return_values(hh_row, 'pre_gtgp_land_type')[landposlist.index(landpos)]\r\n except:\r\n pass\r\n self.hh_size = len(return_values(hh_row, 'age'))\r\n self.gtgp_enrolled = 1\r\n\r\n lp_gtgp = LandParcelAgent(hh_id, self, hh_id, hh_row, landpos, self.gtgp_enrolled,\r\n self.age_1, self.gender_1, self.education_1,\r\n self.gtgp_dry, self.gtgp_rice, self.total_dry, self.total_rice,\r\n self.land_type, self.land_time, self.plant_type, self.non_gtgp_output,\r\n self.pre_gtgp_output)\r\n self.space.place_agent(lp_gtgp, landpos)\r\n self.schedule.add(lp_gtgp)\r\n if self.gtgp_enrolled == 1 and landpos not in gtgplist and landpos in nongtgplist:\r\n gtgplist.append(landpos)","def initialize_areas(self):\n self._areas[1] = copy.copy(self._areas[0])","def place_obj(self):\r\n for pos in BOARD_POSITIONS:\r\n self.board[pos[0]][pos[1]] = Stone(color=self.state[pos[0]][pos[1]], pos=(pos[0], pos[1]))\r\n self.board[pos[0]][pos[1]].liberty = self.board[pos[0]][pos[1]].compute_liberty(self.state)","def add_zombie(self, row, col):\n self._zombie_list.append((row, col))","def AddRegions(self, **kwargs):\n # Addregions use pixel coordinates. listRegions and SaveRegions use RA and Dec.\n n_objs = 0\n objs = []\n # default shape is circle\n if not 'shape' in kwargs:\n kwargs['shape'] = ['circle']\n for k in kwargs.keys():\n n_objs = max(n_objs, len(kwargs[k]))\n for j in range(n_objs):\n temp = {}\n for k in kwargs.keys():\n try:\n temp[k] = kwargs[k][j]\n except IndexError:\n if k == 'shape': \n temp[k] = 'circle'\n objs.append(temp)\n self.all_objs = json.dumps(objs)\n command = \"JS9.AddRegions({objs}, {{display:'{wid}{suffix}'}})\".format(objs=self.all_objs, wid=self.wid, suffix=self.suffix)\n get_ipython().run_cell_magic('javascript', '', command)","def mapAdd(block, posMap):\n for (x, y) in block.coords:\n theFallener(x + block.x, y + block.y, block.color, posMap)","def recreate_obstacles(self):\n self.board_matrix = np.full(Dimension.board_size(), 1)\n self.obstacles = self.create_obstacles()","def place_exit(self):\r\n x = random.randint(0, (self.__nx - 1))\r\n y = random.randint(0, (self.__ny - 1))\r\n self.__exit_room = x, y\r\n if self.exit_room() == self.pillar_a_room() or \\\r\n self.exit_room() == self.pillar_e_room() or \\\r\n self.exit_room() == self.pillar_i_room() or \\\r\n self.exit_room() == self.pillar_p_room() or \\\r\n self.exit_room() == self.entrance_room():\r\n return self.place_exit()\r\n self.__maze[x][y].set_exit(True)","def add_new_region(self, image_name: str, region_text: str, region_position: RegionPosition, region_type: str):\n pass","def do_merge(self, cr, uid, ids, context=None): \n invent_obj = self.pool.get('stock.inventory')\n invent_line_obj = self.pool.get('stock.inventory.line')\n invent_lines = {}\n if context is None:\n context = {}\n for inventory in invent_obj.browse(cr, uid, context['active_ids'], context=context):\n if inventory.state == \"done\":\n raise osv.except_osv(_('Warning!'),\n _('Merging is only allowed on draft inventories.'))\n\n for line in inventory.inventory_line_id:\n key = (line.location_id.id, line.product_id.id, line.product_uom.id)\n if key in invent_lines:\n invent_lines[key] += line.product_qty\n else:\n invent_lines[key] = line.product_qty\n\n\n new_invent = invent_obj.create(cr, uid, {\n 'name': 'Merged inventory'\n }, context=context)\n\n for key, quantity in invent_lines.items():\n invent_line_obj.create(cr, uid, {\n 'inventory_id': new_invent,\n 'location_id': key[0],\n 'product_id': key[1],\n 'product_uom': key[2],\n 'product_qty': quantity,\n })\n\n return {'type': 'ir.actions.act_window_close'}","def load(self):\n\n if self.loaded:\n return\n\n self.region_back = None\n self.objects = []\n self.plants = []\n self.tiles = []\n\n # Some convenience vars\n materials = self.data.materials\n matmods = self.data.matmods\n objects = self.data.objects\n plants = self.data.plants\n world = self.world\n self.loaded = True\n\n # Get tiles\n try:\n data_tiles = world.get_tiles(self.rx, self.ry)\n except KeyError:\n print('WARNING: Region ({}, {}) was not found in world'.format(self.rx, self.ry))\n return\n\n # \"real\" coordinates\n base_x = self.rx*32\n gui_x = base_x*8\n base_y = self.ry*32\n gui_y = (world.height*8)-(base_y*8)\n\n # Background for our drawn area (black)\n self.region_back = self.scene.addRect(gui_x, gui_y-255, 255, 255,\n QtGui.QPen(QtGui.QColor(0, 0, 0)),\n QtGui.QBrush(QtGui.QColor(0, 0, 0)),\n )\n self.region_back.setZValue(Constants.z_black)\n\n # Tiles!\n cur_row = 0\n cur_col = 0\n for data_tile in data_tiles:\n self.tiles.append(GUITile(self.scene, data_tile,\n base_x+cur_col, base_y+cur_row,\n self,\n gui_x+cur_col*8, gui_y-(cur_row+1)*8,\n self.layer_toggles))\n self.scene.addItem(self.tiles[-1])\n cur_col += 1\n if cur_col == 32:\n cur_col = 0\n cur_row += 1\n\n # Entities!\n entities = []\n try:\n entities = world.get_entities(self.rx, self.ry)\n except KeyError:\n pass\n\n for e in entities:\n if e.name == 'ObjectEntity':\n obj_name = e.data['name']\n obj_orientation = e.data['orientationIndex']\n (obj_x, obj_y) = tuple(e.data['tilePosition'])\n if obj_name in objects:\n obj = objects[obj_name]\n (image, offset_x, offset_y) = obj.get_image(obj_orientation)\n qpmi = QtWidgets.QGraphicsPixmapItem(image)\n qpmi.setPos(\n (obj_x*8) + offset_x,\n (world.height*8)-(obj_y*8) - offset_y - image.height(),\n )\n qpmi.setZValue(Constants.z_objects)\n if not self.layer_toggles.objects_toggle.isChecked():\n qpmi.setVisible(False)\n self.scene.addItem(qpmi)\n self.objects.append(qpmi)\n rel_x = obj_x - base_x\n rel_y = obj_y - base_y\n tile_idx = rel_y*32 + rel_x\n self.tiles[tile_idx].add_object(obj, obj_name, obj_orientation, qpmi, e.data)\n elif e.name == 'PlantEntity':\n desc = e.data['descriptions']['description']\n images = []\n (obj_x, obj_y) = tuple(e.data['tilePosition'])\n for piece in e.data['pieces']:\n piece_img = piece['image'].split('?')[0]\n if piece_img in plants:\n img = plants[piece_img].image\n qpmi = QtWidgets.QGraphicsPixmapItem(img)\n qpmi.setPos(\n (obj_x*8) + (piece['offset'][0]*8),\n (world.height*8)-(obj_y*8) - (piece['offset'][1]*8) - img.height(),\n )\n qpmi.setZValue(Constants.z_plants)\n if not self.layer_toggles.plants_toggle.isChecked():\n qpmi.setVisible(False)\n images.append((plants[piece_img], qpmi))\n self.scene.addItem(qpmi)\n self.plants.append(qpmi)\n else:\n print('not found: {}'.format(piece_img))\n rel_x = obj_x - base_x\n rel_y = obj_y - base_y\n tile_idx = rel_y*32 + rel_x\n self.tiles[tile_idx].add_plant(desc, images)\n elif (e.name == 'MonsterEntity'\n or e.name == 'NpcEntity'\n or e.name == 'StagehandEntity'\n or e.name == 'ItemDropEntity'\n or e.name == 'VehicleEntity'\n ):\n # TODO: Ignoring for now\n pass\n else:\n print('Unknown entity type: {}'.format(e.name))","def make_board(self, ):\n for r in range(self.boardSize):\n for c in range(self.boardSize): # avoid redundant calculation by adding neighbors \"behind\" current cell\n new_cell = Cell(r, c)\n self.board[r][c] = new_cell\n if c > 0: # add left neighbor-cell\n new_cell.add_neighbor(self.board[r][c-1])\n if r > 0: # add above neighbor-cell\n new_cell.add_neighbor(self.board[r-1][c])\n if r > 0 and c < self.boardSize-1: # add right diagonal neighbor-cell\n new_cell.add_neighbor(self.board[r-1][c+1])","def _populate_level_with_enemies(self,\n map_layer_configuration,\n base_enemy_chance_cave: float = 0.006,\n base_enemy_chance_dungeon: float = 0.006,\n base_boss_chance: float = 0.003) -> None:\n enemy_chance_cave = self.generate_enemy_chance(base_enemy_chance_cave)\n enemy_chance_dungeon = self.generate_enemy_chance(base_enemy_chance_dungeon)\n boss_chance = self.generate_enemy_chance(base_boss_chance)\n for row in map_layer_configuration:\n for block in row:\n if block[0] == ' ':\n if np.random.rand() > (1 - enemy_chance_cave):\n if self.sprites.drill.center_x != block[1] or self.sprites.drill.center_y != block[2]:\n enemy_to_add = random.choice(potential_enemies)\n enemy_to_append = enemy_to_add(block[1], block[2], vision=200)\n self.sprites.entity_list.append(enemy_to_append)\n self.sprites.enemy_list.append(enemy_to_append)\n elif block[0] == 'F':\n if np.random.rand() > (1 - enemy_chance_dungeon):\n if self.sprites.drill.center_x != block[1] or self.sprites.drill.center_y != block[2]:\n enemy_to_add = random.choice(potential_enemies)\n enemy_to_append = enemy_to_add(block[1], block[2], vision=200)\n self.sprites.entity_list.append(enemy_to_append)\n self.sprites.enemy_list.append(enemy_to_append)\n elif np.random.rand() > (1 - boss_chance):\n if self.sprites.drill.center_x != block[1] or self.sprites.drill.center_y != block[2]:\n enemy_to_add = random.choice(potential_bosses)\n enemy_to_append = enemy_to_add(block[1], block[2], vision=200, speed=0.7)\n self.sprites.entity_list.append(enemy_to_append)\n self.sprites.enemy_list.append(enemy_to_append)\n self.sprites.drill_list.append(self.sprites.drill)\n\n for entity in self.sprites.entity_list:\n entity.setup_collision_engine([self.sprites.indestructible_blocks_list])","def move2(self):\n\n options = self.location.exits.keys()\n for key in options:\n if self.location.exits[key] == p.location:\n self.location.objects.remove(a)\n self.location = p.location\n self.location.objects.append(a)\n print('fred entered the room')\n self.attack(['attack', str(p.name)])\n break\n else:\n self.move1()","def update(self):\n self.platform_list.update()\n self.exit_sprite.update()\n self.bagGroup.update()\n self.enemy_list.update()","def add_conflicting_agents(self, agent_i, agent_j):\n\n self.conflicting_agents = (agent_i, agent_j)","def grow(self, start_period=1, cascade=True):\n end_period = start_period + 1 if not cascade else self.parent.horizon\n for p in range(start_period, end_period):\n self.reset_areas(p+1) #, self._areas[p], self._areas[p+1] # WTF?\n #for age, area in list(self._areas[p].items()): self._areas[p+1][age+1] = area\n for age, area in list(self._areas[p].items()): self._areas[p+1][age+self.parent.period_length] = area","def occupied_cells(self):\n\n for lm in self.landmarks:\n if self.cell_size < 1:\n # expand the range the landmark exists\n lm_x_range = np.arange(lm[0]-self.R, lm[0]+self.R, self.cell_size)\n lm_y_range = np.arange(lm[1]-self.R, lm[1]+self.R, self.cell_size)\n\n # loop through expanded ranges and compute grid positions\n for lm_x in lm_x_range:\n for lm_y in lm_y_range:\n\n row, col = self.cell_index([lm_x, lm_y])\n\n # apply cost of occupied cell\n try:\n self.world[row][col] = 1000\n except IndexError:\n pass\n\n else:\n # apply cost of occupied cell\n row, col = self.cell_index(lm)\n try:\n self.world[row][col] = 1000\n except IndexError:\n pass","def draw_region(self, constraint, agent):\n if (constraint == self.obstacles) and (self.obstacles[agent] is not None):\n for area in self.obstacles[agent]:\n x_min, x_max = area[0][0], area[0][1]\n y_min, y_max = area[1][0], area[1][1]\n rectangle = plt.Rectangle((x_min, y_min), x_max - x_min, y_max - y_min, fc='k', ec=\"k\")\n plt.gca().add_patch(rectangle)\n elif (constraint == self.observation_areas) and (self.observation_areas[agent] is not None):\n for observation_area in self.observation_areas[agent]:\n x_min, x_max = observation_area.region[0][0], observation_area.region[0][1]\n y_min, y_max = observation_area.region[1][0], observation_area.region[1][1]\n rectangle = plt.Rectangle((x_min, y_min), x_max - x_min, y_max - y_min, fc='c', ec=\"c\", alpha=0.5)\n plt.gca().add_patch(rectangle)\n\n plt.xlim(self.Xi[0])\n plt.ylim(self.Xi[1])","def add(self, states, actions, rewards, next_states, dones):\n assert len(states) == self.num_agents, 'ERROR> group states size mismatch'\n assert len(actions) == self.num_agents, 'ERROR> group actions size mismatch'\n assert len(rewards) == self.num_agents, 'ERROR> group rewards size mismatch'\n assert len(next_states) == self.num_agents, 'ERROR> group next states size mismatch'\n assert len(dones) == self.num_agents, 'ERROR> group dones size mismatch'\n\n experience = (states, actions, rewards, next_states, dones)\n self.memory.append(experience)","def editor_multi_agent_example():\n agent_definitions = [\n AgentDefinition(\"uav0\", agents.UavAgent, [sensors.RGBCamera, sensors.LocationSensor]),\n AgentDefinition(\"uav1\", agents.UavAgent, [sensors.LocationSensor, sensors.VelocitySensor])\n ]\n env = HolodeckEnvironment(agent_definitions, start_world=False)\n\n cmd0 = np.array([0, 0, -2, 10])\n cmd1 = np.array([0, 0, 5, 10])\n\n for i in range(10):\n env.reset()\n env.act(\"uav0\", cmd0)\n env.act(\"uav1\", cmd1)\n for _ in range(1000):\n states = env.tick()","def add_entity(self, ent):\n self.tiles[ent.position[x]][ent.position[y]].add_entity(ent)","def populate_board(self):\n for row in range(10):\n for col in range(10):\n coord = Coordinate(row, col)\n coord_attack = Coordinate(row, col)\n self.player_table.setItem(row, col, coord)\n self.attack_table.setItem(row, col, coord_attack)","def place_road(self, road):\n\n # Check if space is empty\n if not self.environment.grid.is_cell_empty(road.pos):\n return False\n\n # Place Road\n self.environment.grid.place_agent(agent=road, pos=road.pos)\n\n # Add road to environment's road list\n self.environment.agents['roads'].append(road)\n\n # Update the list of cells where other things can be built\n self.update_available_cells(road)","def __add_homes(self):\n for home in self.__positions_of_homes:\n self.__grid[home[0]][home[1]][\"humans\"] = math.floor(\n self.__number_of_humans / self.__number_of_homes\n )","def _add_rooms(self):\r\n rooms = self.model.get_all_rooms()\r\n\r\n for room in rooms:\r\n self._add_room(room)","def add_region(self, address, data):\n region = HexFileRegion(address, data)\n self.regions.append(region)\n self.check()","def _undo_overlap(self, agent1, agent2, dist, combined_sizes, **kwargs):\n overlap = (combined_sizes - dist) / combined_sizes\n self.position_state.modify_position(agent1, -agent1.velocity * overlap)\n self.position_state.modify_position(agent2, -agent2.velocity * overlap)","def setup(self):\n self.board[(3, 3)] = -1\n self.board[(3, 4)] = -1\n self.board[(4, 3)] = 1\n self.board[(4, 4)] = 1\n\n self.stones_set = 4","def create_enemy():\n if randint(0, 20) == 5:\n try:\n check.check_life(common.COLS-1, common.MIDS_R, \"Enemy\")\n eitem = person.Enemy(common.COLS-1, common.MIDS_R)\n config.E_LIST.append(eitem)\n except (config.EnemyHere, config.GapHere):\n pass\n\n for i in config.E_LIST:\n try:\n i.move(i.x_pos-2, i.y_pos)\n except config.WallHere:\n pass\n except config.EnemyHere:\n config.E_LIST.remove(i)","def set_pieces(self):\n\n for i in range(len(self._game_board)):\n\n # Row 1\n if i == 0:\n for ii in range(len(self._game_board[i])):\n if ii == 0 or ii == 8:\n self._game_board[i][ii] = Chariot(\"black\", \"BCHA\")\n self._game_board[i][ii].update_location([i, ii])\n if ii == 1 or ii == 7:\n self._game_board[i][ii] = Horse(\"black\", \" BH \")\n self._game_board[i][ii].update_location([i, ii])\n if ii == 2 or ii == 6:\n self._game_board[i][ii] = Elephant(\"black\", \" BE \")\n self._game_board[i][ii].update_location([i, ii])\n if ii == 3 or ii == 5:\n self._game_board[i][ii] = Advisor(\"black\", \" BA \")\n self._game_board[i][ii].update_location([i, ii])\n if ii == 4:\n self._game_board[i][ii] = General(\"black\", \" BG \")\n self._game_board[i][ii].update_location([i, ii])\n\n # Row 3\n if i == 2:\n for ii in range(len(self._game_board[i])):\n if ii == 1 or ii == 7:\n self._game_board[i][ii] = Cannon(\"black\", \"BCAN\")\n self._game_board[i][ii].update_location([i, ii])\n\n # Row 4\n if i == 3:\n for ii in range(len(self._game_board[i])):\n if ii % 2 == 0:\n self._game_board[i][ii] = Soldier(\"black\", \"BSOL\")\n self._game_board[i][ii].update_location([i, ii])\n\n # Row 7\n if i == 6:\n for ii in range(len(self._game_board[i])):\n if ii % 2 == 0:\n self._game_board[i][ii] = Soldier(\"red\", \"RSOL\")\n self._game_board[i][ii].update_location([i, ii])\n\n # Row 8\n if i == 7:\n for ii in range(len(self._game_board[i])):\n if ii == 1 or ii == 7:\n self._game_board[i][ii] = Cannon(\"red\", \"RCAN\")\n self._game_board[i][ii].update_location([i, ii])\n\n # Row 10\n if i == 9:\n for ii in range(len(self._game_board[i])):\n if ii == 0 or ii == 8:\n self._game_board[i][ii] = Chariot(\"red\", \"RCHA\")\n self._game_board[i][ii].update_location([i, ii])\n if ii == 1 or ii == 7:\n self._game_board[i][ii] = Horse(\"red\", \" RH \")\n self._game_board[i][ii].update_location([i, ii])\n if ii == 2 or ii == 6:\n self._game_board[i][ii] = Elephant(\"red\", \" RE \")\n self._game_board[i][ii].update_location([i, ii])\n if ii == 3 or ii == 5:\n self._game_board[i][ii] = Advisor(\"red\", \" RA \")\n self._game_board[i][ii].update_location([i, ii])\n if ii == 4:\n self._game_board[i][ii] = General(\"red\", \" RG \")\n self._game_board[i][ii].update_location([i, ii])","def specific_reset(self) -> None:\n\n # first, set agent xy and adjust its height\n self.agent.specific_reset()\n agent_pos = np.zeros(3)\n agent_pos = np.concatenate((agent_pos[:2], [self.agent.init_xyz[2]]))\n self.agent.set_position(agent_pos)\n\n # second, reset obstacle positions\n if len(self.obstacles) > 0:\n obs_init_pos = env_utils.generate_obstacles_init_pos(\n num_obstacles=len(self.obstacles),\n agent_pos=self.agent.get_position(),\n goal_pos=np.array([]), # no goal in gather task\n world=self.world,\n min_allowed_distance=self.obstacle_obstacle_distance,\n agent_obstacle_distance=self.agent_obstacle_distance\n )\n for i, ob in enumerate(self.obstacles):\n ob.set_position(obs_init_pos[i])\n\n # finally, make all collected objects visible again\n [ob.update_visuals(make_visible=True) for ob in self.obstacles]","def create_board(self):\n for field in self.fields_start_locs:\n loc = self.loc_to_view(field[0], field[1])\n new_field = Field(loc, self.piece_size)\n self.sprite_group.add(new_field)\n self.click_sprites.add(new_field)\n self.fields.append(new_field)"],"string":"[\n \"def add_to_simulation(self,agent):\\n self.agents[agent.name] = agent\\n self.network.add_node(agent)\\n \\n #agent given a grid queue at initialization\\n grid_queue = [gq for gq in self.grid_queues.values() if gq.accepts(agent)][agent.sex]\\n agent.grid_queue = grid_queue.index\\n self.add_to_grid_queue(agent)\",\n \"def _init_agents(self):\\n self.agents = [Agent(e=0.1, a=0.1, row=self.row, col=self.col) for i in range(2)]\",\n \"def update_available_cells(self, agent):\\n try:\\n self.available_road_cells.remove(agent.pos)\\n except:\\n pass\\n try:\\n self.available_building_cells.remove(agent.pos)\\n except:\\n pass\\n\\n adj_cells = self.environment.grid.get_neighborhood(agent.pos, moore=False)\\n surrounding_cells = self.environment.grid.get_neighborhood(agent.pos, moore=True)\\n\\n # Update available cells if agent is a road\\n if type(agent) == Road:\\n for cell in surrounding_cells:\\n # Roads\\n if self.creates_valid_road(cell) and cell not in self.available_road_cells:\\n self.available_road_cells.append(cell)\\n\\n # Buildings\\n if self.creates_valid_building(cell) and cell not in self.available_building_cells:\\n self.available_building_cells.append(cell)\\n\\n if type(agent) == Building:\\n for cell in surrounding_cells:\\n # Roads\\n if self.creates_valid_road(cell) and cell not in self.available_road_cells:\\n self.available_road_cells.append(cell)\\n\\n # Buildings\\n if self.creates_valid_building(cell) and cell not in self.available_building_cells:\\n self.available_building_cells(cell)\",\n \"def test_assign_to_regions(self):\\n \\n tool = pybedtools.BedTool(clipper.test_file(\\\"FOX2Brain-05.15.09.polyATrim.adapterTrim.rmRep.sorted.rmDup.peaks.bed\\\"))\\n \\n assign_to_regions(tool=tool, \\n clusters=\\\"test\\\", \\n speciesFA= clipper.test_file(\\\"mm9.fa\\\"), \\n regions_dir=os.path.join(clipper.test_dir(), \\\"regions\\\"), \\n regions={\\\"exons\\\" : \\\"Exon\\\", \\\"utr3\\\" : \\\"3' UTR\\\", \\n \\\"utr5\\\" : \\\"5' UTR\\\", \\\"proxintron500\\\" : \\\"Proximal Intron\\\", \\n \\\"distintron500\\\" : \\\"Distal Intron\\\"} ,\\n assigned_dir = clipper.test_dir(),\\n fasta_dir = clipper.test_dir(),\\n species=\\\"mm9\\\", \\n nrand = 3, \\n getseq=False)\",\n \"def push_regions(self, regions: [MouseRegion]):\\n raise NotImplementedError\",\n \"def add_regions(self, regions, **options):\\n \\n options.setdefault(\\\"col\\\", color(0,0,1))\\n options.setdefault(\\\"style\\\", \\\"box\\\")\\n options.setdefault(\\\"height\\\", 0.5)\\n \\n return self.add_track(RegionTrack, -.5, regions, **options)\",\n \"def insert_host_states(hosts):\\n IMPL.insert_host_states(hosts)\",\n \"def enter(self, env):\\n env = self._find_env(env, new=True)\\n env.add_agents(self)\",\n \"def on_enter(self):\\n # Add self to list of obstacles\\n self.parent._obstacles.add(self)\\n super().on_enter()\",\n \"def display_agents(self):\\n for agent in self.scheduler.agents:\\n id_ = agent.id_\\n p = agent.mobility.current\\n x, y = to_geometry(p[0]), to_geometry(p[1])\\n r = to_geometry(agent.range_)\\n print('define agent{} ellipse 4 4 white {} {}'.format(id_, x, y))\\n print('define agentr{0} ellipse {1} {1} white {2} {3}'.format(\\n id_, r, x, y))\\n self.change_agent_status(agent)\",\n \"def apply_to_world(self, world):\\n # add the current obstacles\\n for obstacle in self.current_obstacles:\\n world.add_obstacle(obstacle)\\n\\n # program the robot supervisors\\n for robot in world.robots:\\n robot.supervisor.goal = self.current_goal[:]\",\n \"def place_dungeon_items(self):\\r\\n self.place_entrance()\\r\\n self.place_exit()\\r\\n self.place_pillar_a()\\r\\n self.place_pillar_e()\\r\\n self.place_pillar_i()\\r\\n self.place_pillar_p()\\r\\n self.place_pits()\\r\\n self.place_vision()\\r\\n self.place_healing()\\r\\n self.original_map = self.__repr__()\",\n \"def add_items(self):\\n # -- item list\\n item = ['S','H','R','M', 'B', 'C']\\n # -- loops through item list and adds them to the maze\\n for i in item:\\n x_coordinate, y_coordinate = self.find_random_spot()\\n self.grid[x_coordinate][y_coordinate] = i\",\n \"def place_entrance(self):\\r\\n x = random.randint(0, (self.__nx - 1))\\r\\n y = random.randint(0, (self.__ny - 1))\\r\\n self.__current_room = x, y # places adventurer in dungeon at start of game\\r\\n self.__entrance_room = x, y\\r\\n self.__maze[x][y].set_entrance(True)\",\n \"def resize_board(self, dx, dy):\\n height, width = self.board.shape\\n if width <= 0 or height <= 0:\\n raise ValueError(\\\"Cannot resize to zero.\\\")\\n new_board = np.zeros((height+dy, width+dx), dtype=self.board.dtype)\\n height += min(0, dy)\\n width += min(0, dx)\\n new_board[:height, :width] = self.board[:height, :width]\\n self.board = new_board\\n out_of_bounds = np.any(self.agent_locs >= new_board.shape, axis=1)\\n self.agent_locs = self.agent_locs[~out_of_bounds]\\n self.edit_loc = tuple(np.array(self.edit_loc) % new_board.shape)\\n self.update_exit_locs()\",\n \"def add_region(self, position):\\n region = self.region_selector(position)\\n self.regions[id(region)] = region\",\n \"def place_building(self, building):\\n if self.environment.grid.is_cell_empty(building.pos):\\n self.environment.grid.place_agent(building, building.pos)\\n self.environment.agents['residences'].append(building)\\n else:\\n try:\\n self.available_cells.remove(building.pos)\\n except:\\n pass\",\n \"def regions(self, regions):\\n self._regions = regions\",\n \"def _update_battle_position(self, new_cells=[], previous_cells=[]):\\n if previous_cells:\\n for previous_cell in previous_cells:\\n self._battle_area.set_cell(previous_cell.get_name(), False)\\n if new_cells:\\n for new_cell in new_cells:\\n self._battle_area.set_cell(new_cell.get_name(), self)\",\n \"def create_block(self, location_list, POI_locations):\\n\\n \\n for i in range(len(location_list)):\\n this_cell = self.grid.get_cell_list_contents(location_list[i])\\n\\n for agent in this_cell:\\n if type(agent) is nodeAgent:\\n agent.block = True\\n\\n for i in POI_locations:\\n agent.locations[i] = 10000\",\n \"def test_arena_move(agents_and_engines):\\n agents, engine = agents_and_engines\\n assert len(agents) == 3\\n\\n game_state = engine.get_state()\\n\\n positions = [g['pos'] for g in game_state['gladiators']]\\n\\n rw = random_walker.ArenaAgent()\\n\\n move = rw.move(game_state)\\n for i in range(3):\\n engine.move(move)\\n new_state = engine.get_state()\\n\\n new_positions = [g['pos'] for g in new_state['gladiators']]\\n\\n assert new_positions != positions\",\n \"def advance_board(self):\\n board = self.board\\n rules = self.energy_rules\\n h, w = board.shape\\n beta = 1.0 / max(1e-20, self.temperature)\\n if len(rules[0]) - 1 == 4:\\n neighborhood = np.array([[0,1,0],[1,0,1],[0,1,0]])\\n elif len(rules[0]) - 1 == 6:\\n neighborhood = np.array([[0,1,1],[1,0,1],[1,1,0]])\\n elif len(rules[0]) - 1 == 8:\\n neighborhood = np.array([[1,1,1],[1,0,1],[1,1,1]])\\n else:\\n raise RuntimeError(\\\"async rules must have length 5, 7, or 9\\\")\\n rng = get_rng()\\n for _ in range(int(board.size * self.cells_per_update)):\\n x = rng.choice(w)\\n y = rng.choice(h)\\n if board[y, x] & CellTypes.frozen:\\n continue\\n neighbors = board.view(wrapping_array)[y-1:y+2, x-1:x+2] * neighborhood\\n alive_neighbors = np.sum(neighbors & CellTypes.alive > 0)\\n spawn_neighbors = np.sum(neighbors & CellTypes.spawning > 0)\\n frozen = np.sum(neighbors & CellTypes.freezing) > 0\\n if frozen:\\n continue\\n if board[y, x] & CellTypes.alive:\\n H = rules[0][alive_neighbors]\\n else:\\n H = rules[1][alive_neighbors]\\n\\n P = 0.5 + 0.5*np.tanh(H * beta)\\n P = 1 - (1-P)*(1-self.spawn_prob)**spawn_neighbors\\n board[y, x] = CellTypes.life if coinflip(P) else CellTypes.empty\",\n \"def populate_tiles(self):\\n\\n # grid format :\\n # grid(x,y,z)[0]: A valid WorldTile type (i.e. WorldTile.door)\\n # grid(x,y,z)[1]: A list of ASCII color or format codes for ColorIze\\n # grid(x,y,z)[2]: The tile object\\n\\n self.t_count = 0 # Tile count, increment for each tile added\\n self.build_start = time.clock()\\n self.logger.info(\\\"[*] Starting world building script\\\")\\n\\n script_list = [\\n self.build_boss_room,\\n self.build_rooms,\\n self.build_halls,\\n self.build_doors,\\n self.build_chests,\\n self.build_traps,\\n self.build_mobs,\\n self.build_npcs\\n ]\\n for func in script_list:\\n self.logger.debug(\\\"\\\\tRunning {}\\\".format(func.__name__))\\n if not func():\\n e_text = \\\"Build script failed : {}\\\".format(func.__name__)\\n raise AssertionError(e_text)\\n\\n self.logger.info(\\\"[*] World building script completed\\\")\\n self.logger.debug(\\\"\\\\tTiles Placed : {}\\\".format(self.t_count))\\n build_time = time.clock()-self.build_start\\n self.logger.debug(\\\"\\\\tTook {}s\\\".format(build_time))\\n self.logger.debug(\\\"\\\\tTiles/s : {}\\\".format(t_count/build_time))\",\n \"def add_agent(self, agent):\\n\\t\\tif not (agent in self.agents_in_site):\\n\\t\\t\\tif (agent.site != None):\\n\\t\\t\\t\\tagent.site.agents_in_site.remove(agent) \\n\\t\\t\\tself.agents_in_site.append(agent)\\n\\t\\t\\tagent.site = self\",\n \"def register(self):\\n self.logger.info(\\\"Registering agent %s\\\", \\\"/registry/\\\" + self._configuration[\\\"identification\\\"][\\\"uuid\\\"])\\n self._coordination.update(\\\"/registry/\\\" + self._configuration[\\\"identification\\\"][\\\"uuid\\\"], self._configuration[\\\"identification\\\"])\",\n \"def shift_board(self, dx, dy):\\n self.board = np.roll(self.board, dy, axis=0)\\n self.board = np.roll(self.board, dx, axis=1)\\n self.agent_locs += [dy, dx]\\n self.agent_locs %= self.board.shape\\n self.update_exit_locs()\",\n \"def begin_encounter(self):\\r\\n\\r\\n #introduce NPCs - run all introduce methods, unless the NPCs have the same name\\r\\n for i in range(len(self.npc_names)):\\r\\n for _npc in self.npc_list:\\r\\n if _npc.name == self.npc_names[i]:\\r\\n _npc.introduce(self.npc_quantities[i], self.location)\\r\\n break\\r\\n\\r\\n #list visible enemies\\r\\n self.display_npcs()\\r\\n\\r\\n #check close proximity - if hostile enemy within 10 ft, don't go to interact menu\\r\\n hostile_close_proximity = False\\r\\n \\r\\n for m in range(len(self.npc_distances)):\\r\\n if self.npc_distances[m] < 10:\\r\\n if self.npc_list[m].hostility == utils.HostilityLevel.HOSTILE:\\r\\n hostile_close_proximity = True\\r\\n multiple = self.npc_quantities[self.npc_names.index(self.npc_list[m].name)] > 1\\r\\n self.npc_list[m].alert_close_proximity(multiple)\\r\\n break\\r\\n\\r\\n interaction_result = NextState\\r\\n \\r\\n if hostile_close_proximity:\\r\\n #start combat\\r\\n interaction_result = NextState.COMBAT\\r\\n else:\\r\\n #run interaction choice menu - interactions may return flags that spawn social/combat encounters\\r\\n print(\\\"Select NPC to interact with:\\\")\\r\\n for l in range(len(self.npc_list)):\\r\\n print(str(l + 1) + \\\". \\\" + self.npc_list[l].name + \\\" (Distance: \\\" + str(self.npc_distances[l]) + \\\"ft.)\\\")\\r\\n \\r\\n choice = 0\\r\\n while choice < 1 or choice > len(self.npc_names) + 1:\\r\\n try:\\r\\n choice = int(input(\\\"Make selection: \\\"))\\r\\n except:\\r\\n print(\\\"Enter an integer between 1 and \\\" + str(len(self.npc_names)))\\r\\n \\r\\n interaction_result = self.npc_list[choice - 1].interact(self, choice - 1, self.main_player)\\r\\n\\r\\n #spawn social/combat encounter\\r\\n #if combat, pass npc list to generate turn order\\r\\n if interaction_result.name == \\\"COMBAT\\\":\\r\\n #spawn combat encounter\\r\\n print(\\\"Starting combat\\\")\\r\\n new_combat = combat.CombatEncounter(self.main_player, self.npc_list, self.npc_distances, self.npc_quantities)\\r\\n elif interaction_result.name == \\\"SOCIAL\\\":\\r\\n #spawn social encounter\\r\\n print(\\\"Starting social encounter\\\")\\r\\n elif interaction_result.name == \\\"FINISHED\\\":\\r\\n #present next choices, award loot from area\\r\\n #allow player to interact with any remaining/new NPCs\\r\\n print(\\\"Encounter finished\\\")\\r\\n elif interaction_result.name == \\\"DEATH\\\":\\r\\n #kill the player and end the game\\r\\n print(\\\"Player dead\\\")\",\n \"def place(self, board):\\r\\n self.board = board\",\n \"def append(self, agent):\\n self.agents.append(agent)\",\n \"def add_objects_to_space(self):\\n self.anti_spacecraft.add_to_space(self.space) # Anti-spacecraft Parts (represent the whole vehicle)\\n self.space.add(self.spacecraft.body, self.spacecraft.shape) # Spacecraft body and shape\\n self.space.add(self.pm_landing_pad) # Landing pad\",\n \"def draw_world(grid, r, c, image):\\n under = grid[r, c]\\n grid[r, c] = AGENT\\n image.set_data(grid)\\n grid[r, c] = under\",\n \"def make_hh_agents_2016(self):\\r\\n for hh_row in agents: # agents is a list of ints 1-97 from excel_import\\r\\n self.hhpos = self.determine_hhpos(hh_row, 'house_latitude', 'house_longitude')\\r\\n self.hh_id = return_values(hh_row, 'hh_id')\\r\\n self.admin_village = 1\\r\\n\\r\\n # 2016\\r\\n mig_remittances = return_values(hh_row, 'mig_remittances') # remittances of initial migrant\\r\\n if mig_remittances is None:\\r\\n mig_remittances = 0\\r\\n household_income_list[hh_row - 1] = int(mig_remittances)\\r\\n household_remittances_list[hh_row - 1] = int(mig_remittances)\\r\\n\\r\\n if return_values(hh_row, 'initial_migrants') is not None:\\r\\n out_mig_list[hh_row - 1] = 1\\r\\n household_migrants_list.append(self.hh_id)\\r\\n cumulative_mig_list[hh_row - 1] = 1\\r\\n\\r\\n num_labor_list[hh_row - 1] = initialize_labor(hh_row)\\r\\n hh_size_list[hh_row - 1] = len(return_values(hh_row, 'age'))\\r\\n\\r\\n a = HouseholdAgent(hh_row, self, self.hh_id, self.admin_village)\\r\\n self.space.place_agent(a, self.hhpos) # admin_village placeholder\\r\\n self.schedule.add(a)\",\n \"def addTiles(self, rows, cols, minecount):\\n for row in range(rows):\\n self.tiles.append([])\\n for col in range(cols):\\n tile = Tile(self, row, col)\\n tile.grid(row=row+1, column=col)\\n self.tiles[row].append(tile)\\n #left click listeners\\n tile.bind('<ButtonPress-1>', self.pressTile)\\n tile.bind('<ButtonRelease-1>', self.showTile)\\n #middle click listeners\\n tile.bind('<ButtonPress-2>', self.pressAdjTiles)\\n tile.bind('<ButtonRelease-2>', self.showAdjTiles)\\n #right click listeners\\n tile.bind('<ButtonPress-3>', self.pressTile)\\n tile.bind('<ButtonRelease-3>', self.toggleFlag)\",\n \"def sea_execution(board, position, role):\\n quitt = False\\n if position == 'comp':\\n #print(1)\\n #temporary for dumb AI\\n #create and print a list of coastal, friendly regions where norse is not the ONLY one\\n \\n possible_region_list = []\\n \\n #loops through list of friendly, coastal, not just Norse regions to append to a possible_region_list\\n for region in board.get_controlled_regions(role):\\n #print(2)\\n coastal = False\\n just_norse = False\\n if region.coast:\\n coastal = True\\n if len(region.blocks_present) == 1 and region.blocks_present[0].name.upper() == 'NORSE':\\n just_norse = True\\n \\n if coastal and not just_norse:\\n possible_region_list.append(region)\\n \\n \\n #loops through list of friendly, coastal regions to append to a possible_final_region_list\\n possible_final_region_list = []\\n for region in board.get_controlled_regions(role): \\n #print(3) \\n if region.coast:\\n possible_final_region_list.append(region)\\n \\n \\n \\n if len(possible_final_region_list) >= 2:\\n #if you want to add in last-min strategy, do it here\\n #random region from possible list\\n england = board.regions[22]\\n if england in possible_region_list:\\n original_region = england\\n else:\\n original_region = possible_region_list[random.randint(0, len(possible_region_list) - 1)]\\n #remove the original region from the possible end regions\\n possible_final_region_list.remove(original_region)\\n \\n #possible_block_list\\n #list of possible blocks to move (present in region) and not norse\\n possible_block_list = []\\n for block in original_region.blocks_present:\\n if block.name != 'NORSE':\\n possible_block_list.append(block)\\n \\n move_block_list = []\\n blocks_moved = 0\\n #print(4)\\n\\n while blocks_moved < 2:\\n #print(5)\\n block = possible_block_list[random.randint(0, len(possible_block_list)-1)]\\n #if it's not already on the list,append to move_block_list\\n if block not in move_block_list:\\n move_block_list.append(block)\\n blocks_moved+=1\\n elif block in move_block_list and len(possible_block_list) == 1:\\n blocks_moved+=1\\n else:\\n print('neither condition was met so this is an infinite loop')\\n \\n \\n #print(6) \\n new_region = possible_final_region_list[random.randint(0, len(possible_final_region_list) - 1)]\\n \\n for block in move_block_list:\\n \\n board.add_to_location(block, new_region)\\n print(block.name + ' moved from ' + original_region.name + ' to ' + new_region.name)\\n \\n else:\\n print('There are not enough friendly regions with which to play this card.')\\n \\n \\n #add in if it's not possible\\n elif position == 'opp':\\n \\n \\n possible_region_list = []\\n \\n #loops through list of friendly, coastal, not just Norse regions to append to a possible_region_list\\n for region in board.get_controlled_regions(role):\\n coastal = False\\n just_norse = False\\n if region.coast:\\n coastal = True\\n if len(region.blocks_present) == 1 and region.blocks_present[0].name.upper() == 'NORSE':\\n just_norse = True\\n \\n if coastal and not just_norse:\\n possible_region_list.append(region)\\n \\n \\n #loops through list of friendly, coastal regions to append to a possible_final_region_list\\n possible_final_region_list = []\\n for region in board.get_controlled_regions(role): \\n if region.coast:\\n possible_final_region_list.append(region)\\n \\n \\n \\n if len(possible_final_region_list) >= 2:\\n \\n print('Possible origin regions:')\\n for region in possible_region_list:\\n print(region.name)\\n \\n #user input region, check if in possible list\\n valid_region = False\\n while not valid_region:\\n \\n original_region_name = input('What region would you like to move block(s) from? Enter a name or \\\\'none\\\\'.\\\\n>').upper()\\n \\n if original_region_name != 'NONE':\\n \\n original_region = search.region_name_to_object(board, original_region_name)\\n \\n if original_region and original_region in possible_region_list:\\n valid_region = True\\n else:\\n print('Invalid region.')\\n else:\\n quitt = True\\n \\n if not quitt:\\n #remove the original region from the possible end regions\\n possible_final_region_list.remove(original_region)\\n \\n #possible_block_list\\n #list of possible blocks to move (present in region) and not norse\\n possible_block_list = []\\n for block in original_region.blocks_present:\\n if block.name != 'NORSE':\\n possible_block_list.append(block)\\n \\n print('Possible blocks:')\\n for block in possible_block_list:\\n print(block.name)\\n \\n \\n move_block_list = []\\n blocks_moved = 0\\n quittt = False\\n block_name = ''\\n while blocks_moved < 2 and not quittt:\\n if block_name != 'NONE':\\n valid_block = False\\n while not valid_block:\\n \\n \\n block_name = input('Which block would you like to move? Enter a name or \\\\'none\\\\'.\\\\n>').upper()\\n \\n if block_name != 'NONE':\\n \\n block_to_move = search.block_name_to_object(possible_block_list, block_name)\\n \\n if block_to_move and block_to_move not in move_block_list:\\n valid_block = True\\n move_block_list.append(block_to_move)\\n blocks_moved+=1\\n \\n elif block in move_block_list and len(possible_block_list) == 1:\\n blocks_moved=1\\n \\n else:\\n print('Invalid block.')\\n continue\\n else:\\n valid_block = True\\n if len(move_block_list) == 1:\\n quittt = True\\n quitt = False\\n if len(move_block_list) > 0: \\n print('Possible final regions:')\\n for region in possible_final_region_list:\\n print(region.name)\\n \\n #user input region, check if in possible list\\n valid_region = False\\n while not valid_region:\\n \\n new_region_name = input('What region would you like to move block(s) to? Enter a name or \\\\'none\\\\'.\\\\n>').upper()\\n \\n if new_region_name != 'NONE':\\n \\n new_region = search.region_name_to_object(board, new_region_name)\\n \\n if new_region and new_region in possible_final_region_list:\\n valid_region = True\\n else:\\n print('Invalid region.')\\n continue\\n else:\\n valid_region = True\\n quitt = True\\n \\n if not quitt:\\n \\n for block in move_block_list:\\n \\n board.add_to_location(block, new_region)\\n print(block.name + ' moved from ' + original_region.name + ' to ' + new_region.name)\\n \\n else:\\n print('There are not enough friendly coastal regions with which to play this card.')\",\n \"def step(self):\\n try:\\n self.agents.sort(key=lambda x: x.dist)\\n except Exception as e:\\n print(e)\\n\\n for agent in self.agents:\\n try:\\n agent.step()\\n except Exception as e:\\n print(e)\\n\\n\\n # Removes agents if they reach exit\\n for exit in self.model.exits:\\n x, y = exit.pos[0] * 6 + 1, exit.pos[1] * 6 + 1\\n if agent.node == (x, y):\\n try:\\n agent.saved()\\n except Exception as e:\\n print(e)\",\n \"def _update_board(self):\\n\\n self.game_board.update_board(self.tetrino_set)\",\n \"def step(self):\\n self.age += 1\\n self.move_agent()\\n self.sugar -= self.metabolism\\n\\n # Eat sugar\\n available_sugar = self.get_sugar(self.pos).amount\\n self.sugar += available_sugar\\n# self.total_sugar_in_field -= available_sugar\\n # Set sugar in current cell to zero\\n self.get_sugar(self.pos).eat_sugar() \\n \\n \\n \\n if self.sugar == 0:\\n self.model.remove_agent(self)\\n \\n self.gen += 1\\n x = self.model.random.randrange(self.model.grid.width)\\n y = self.model.random.randrange(self.model.grid.height)\\n new_pos = (x,y)\\n \\n self.model.add_agent(Consumer, new_pos, f\\\"{self.unique_id.split('-')[0]}-{self.gen}\\\", self.gen, self.model.vision, self.model.metabolism, self.model.starting_sugar)\\n \\n \\n if self.reproduction_and_death:\\n if self.age > self.max_age: # Agent dies\\n # Tax inheritance\\n self.model.inheritance_tax_agent(self)\\n \\n if self.model.spawn_at_random:\\n self.gen += 1\\n x = self.model.random.randrange(self.model.grid.width)\\n y = self.model.random.randrange(self.model.grid.height)\\n new_pos = (x,y)\\n \\n self.model.add_agent(Consumer, new_pos, f\\\"{self.unique_id.split('-')[0]}-{self.gen}\\\", self.gen, self.model.vision, self.model.metabolism, self.model.starting_sugar)\\n self.model.remove_agent(self) #agent dies\\n \\n \\n else:\\n #spawn new agent\\n self.gen += 1\\n if self.sugar != 0:\\n self.model.add_agent(Consumer, self.pos, f\\\"{self.unique_id.split('-')[0]}-{self.gen}\\\", self.gen, self.vision, self.metabolism, self.sugar)\\n else:\\n self.model.add_agent(Consumer, self.pos, f\\\"{self.unique_id.split('-')[0]}-{self.gen}\\\", self.gen, self.vision, self.metabolism, self.model.starting_sugar)\\n \\n self.model.remove_agent(self) #agent dies\",\n \"def load_agents(self, agents):\\n self.agents = agents\",\n \"def _place_board(self, board):\\n for i, row in enumerate(board):\\n for j, widget in enumerate(row):\\n widget.grid(row = i, column = j)\",\n \"def setup_lists(self):\\n \\n # Decompose spores do not affect terrain like ground or water\\n for thing in self.room.wall_list:\\n self.unaffected.add(thing)\\n\\n for thing in self.room.sludge:\\n self.unaffected.add(thing)\\n\\n # It does, however, destroy enemies and things that are alive. Later implement logs.\\n for thing in self.room.enemy_list:\\n self.affected.add(thing)\\n\\n for thing in self.room.can_climb:\\n self.affected.add(thing)\",\n \"def add_parties(self, *parties) -> None:\\n\\n for party in parties:\\n self._route_table['route_table'][party.get_id()] = party.to_entry_point(\\n )\",\n \"def add_to_grid_queue(self, agent):\\n self.pipes[agent.grid_queue].send(\\\"add\\\")\\n self.pipes[agent.grid_queue].send(agent)\",\n \"def add_all_regions():\\n gene_id = request.json['gene_id']\\n panel_id = request.json['panel_id']\\n tx_id = request.json['tx_id']\\n gene_name = request.json['gene_name']\\n project_id = get_project_id_by_panel_id(s, panel_id)\\n\\n add_preftxs_to_panel(s, project_id, [{\\\"gene\\\": gene_name, \\\"tx_id\\\": tx_id}, ])\\n add_genes_to_panel_with_ext(s, panel_id, gene_id)\\n return jsonify({\\\"genes\\\": [gene_id, ]})\",\n \"def insert_parts(self, parts):\\r\\n self.board.insert_parts(parts)\\r\\n self.set_changed(parts)\",\n \"def updated_occupied_locations(self):\\n if len(self.occupiedLocations) > self.currentTurn:\\n self.occupiedLocations[self.currentTurn] += [self.character.path[-1]]\\n else:\\n self.occupiedLocations += [[self.character.path[-1]]]\",\n \"def __activate(self, x: int, y: int, tree: int) -> None:\\n self.__maze[x, y] = tree\",\n \"def spill(self, agent):\\n self.spill_list.append(agent)\",\n \"def advance_board(self):\\n # We can advance the board using a pretty simple convolution,\\n # so we don't have to execute a lot of loops in python.\\n # Of course, this probably won't be sufficient for extremely\\n # large boards.\\n self.num_steps += 1\\n board = self.board\\n cfilter = np.array([[1,1,1],[1,0,1],[1,1,1]], dtype=np.uint16)\\n\\n alive = board & CellTypes.alive > 0\\n spawning = board & CellTypes.spawning > 0\\n frozen = board & CellTypes.frozen > 0\\n\\n can_die = ~frozen & (\\n convolve2d(board & CellTypes.preserving, cfilter) == 0)\\n can_grow = ~frozen & (\\n convolve2d(board & CellTypes.inhibiting, cfilter) == 0)\\n\\n num_neighbors = convolve2d(alive, cfilter)\\n num_spawn = convolve2d(spawning, cfilter)\\n spawn_prob = 1 - (1 - self.spawn_prob)**num_spawn\\n has_spawned = coinflip(spawn_prob, board.shape)\\n\\n born_rule = np.zeros(9, dtype=bool)\\n born_rule[list(self.born_rule)] = True\\n dead_rule = np.ones(9, dtype=bool)\\n dead_rule[list(self.survive_rule)] = False\\n\\n new_alive = (born_rule[num_neighbors] | has_spawned) & ~alive & can_grow\\n new_dead = dead_rule[num_neighbors] & alive & can_die\\n\\n new_flags = np.zeros_like(board)\\n color_weights = 1 * alive + 2 * spawning\\n for color in CellTypes.colors:\\n # For each of the colors, see if there are two or more neighbors\\n # that have it. If so, any new cells (whether born or spawned)\\n # will also get that color.\\n has_color = board & color > 0\\n new_color = convolve2d(has_color * color_weights, cfilter) >= 2\\n new_flags += color * new_color\\n indestructible = alive & (board & CellTypes.destructible == 0)\\n new_flags += CellTypes.destructible * (convolve2d(indestructible, cfilter) < 2)\\n\\n board *= ~(new_alive | new_dead)\\n board += new_alive * (CellTypes.alive + new_flags)\",\n \"def add_artifacts(cells_info):\\n # Add fire extinguishers\\n cells_info[(1, 0)].add_artifact(\\\"Extinguisher@2.1 2.1 0.004 0 0 0\\\")\\n cells_info[(1, 14)].add_artifact(\\\"Extinguisher@2.1 -2.1 0.004 -90 0 90\\\")\\n cells_info[(7, 6)].add_artifact(\\\"Extinguisher@2.1 -3 0.004 0 0 0\\\")\\n cells_info[(7, 0)].add_artifact(\\\"Extinguisher@-5 0 5.004 -90 0 300\\\")\\n\\n # Add phones\\n cells_info[(8, 3)].add_artifact(\\\"Phone@-2.1 3 0.004 -90 0 0\\\")\\n cells_info[(15, 0)].add_artifact(\\\"Phone@-3 2.1 0.004 -90 0 -90\\\")\\n cells_info[(13, 7)].add_artifact(\\\"Phone@-3 0 0.004 90 0 -30\\\")\\n cells_info[(4, 2)].add_artifact(\\\"Phone@-1 -4 0.004 90 0 0\\\")\\n\\n # Add backpacks\\n cells_info[(10, 6)].add_artifact(\\\"Backpack@-6 -1.3 0.004 0 0 0\\\")\\n cells_info[(1, 5)].add_artifact(\\\"Backpack@2.1 6 0.004 -90 0 0\\\")\\n cells_info[(0, 8)].add_artifact(\\\"Backpack@1 6 0.004 -90 0 0\\\")\\n cells_info[(15, 4)].add_artifact(\\\"Backpack@2 2 0.004 90 0 0\\\")\\n\\n # Add Rescue Randy\\n cells_info[(15, 15)].add_artifact(\\\"Rescue Randy@1 -7 0.004 0 0 180\\\")\\n cells_info[(15, 7)].add_artifact(\\\"Rescue Randy@-1 6 0.004 0 0 0\\\")\\n cells_info[(5, 12)].add_artifact(\\\"Rescue Randy@2.2 6.5 0.004 0 0 -90\\\")\\n cells_info[(2, 11)].add_artifact(\\\"Rescue Randy@0 -7 0.004 0 0 180\\\")\\n\\n # Add Drills\\n cells_info[(8, 8)].add_artifact(\\\"Drill@-6 0 0.004 0 -90 0\\\")\\n cells_info[(10, 15)].add_artifact(\\\"Drill@-6 -1.2 0.004 0 90 -20\\\")\\n cells_info[(3, 7)].add_artifact(\\\"Drill@2.1 7 0.004 0 0 0\\\")\\n cells_info[(13, 6)].add_artifact(\\\"Drill@0 -7 0.004 0 90 -80\\\")\",\n \"def reset_agent_locations(self):\\n self.transitions_left = self.T-1\\n self.x_agent = np.repeat(self.xT.reshape(1, self.dimensions), self.n_agents, axis=0)\",\n \"def add_spawns_outside_boss_doors(self: WWRandomizer):\\n \\n rooms_to_add_new_spawns_to = [\\n (\\\"M_NewD2\\\", 10, TGDR, None, 11),\\n #(\\\"kindan\\\", 16, TGDR, None, 13), # Already has a spawn, ID 1.\\n (\\\"Siren\\\", 18, TGDR, None, 13),\\n (\\\"sea\\\", 1, ACTR, 1, 56),\\n (\\\"M_Dai\\\", 15, TGDR, None, 17),\\n (\\\"kaze\\\", 12, TGDR, None, 13),\\n ]\\n \\n for stage_name, room_number, chunk, layer, boss_door_index in rooms_to_add_new_spawns_to:\\n new_spawn_id = 27\\n \\n dzs = self.get_arc(\\\"files/res/Stage/%s/Stage.arc\\\" % stage_name).get_file(\\\"stage.dzs\\\", DZx)\\n dzr = self.get_arc(\\\"files/res/Stage/%s/Room%d.arc\\\" % (stage_name, room_number)).get_file(\\\"room.dzr\\\", DZx)\\n \\n if chunk == TGDR:\\n dzx_for_door = dzs\\n else:\\n dzx_for_door = dzr\\n \\n door = dzx_for_door.entries_by_type_and_layer(chunk, layer=layer)[boss_door_index]\\n spawn_dist_from_door = 200\\n y_rot = door.y_rot\\n if door.from_room_num != room_number and door.from_room_num != 63:\\n y_rot = (y_rot + 0x8000) % 0x10000\\n y_rot_degrees = y_rot * (90.0 / 0x4000)\\n x_offset = math.sin(math.radians(y_rot_degrees)) * spawn_dist_from_door\\n z_offset = math.cos(math.radians(y_rot_degrees)) * spawn_dist_from_door\\n x_pos = door.x_pos + x_offset\\n y_pos = door.y_pos\\n z_pos = door.z_pos + z_offset\\n \\n if stage_name in [\\\"M_Dai\\\", \\\"kaze\\\"]:\\n # Earth and Wind temple spawns must be in the stage instead of the room or the game will crash.\\n dzx_for_spawn = dzs\\n else:\\n dzx_for_spawn = dzr\\n \\n spawns = dzx_for_spawn.entries_by_type(PLYR)\\n assert len([spawn for spawn in spawns if spawn.spawn_id == new_spawn_id]) == 0\\n \\n new_spawn = dzx_for_spawn.add_entity(PLYR)\\n new_spawn.spawn_type = 0\\n new_spawn.room_num = room_number\\n new_spawn.x_pos = x_pos\\n new_spawn.y_pos = y_pos\\n new_spawn.z_pos = z_pos\\n new_spawn.y_rot = y_rot\\n new_spawn.spawn_id = new_spawn_id\\n \\n dzx_for_spawn.save_changes()\",\n \"def addAgent(self, new_agent, parent_agent, secondary_caregivers):\\n # set unique id\\n new_agent.ID = self.idCounter\\n self.idCounter += 1\\n \\n self.pop.append(new_agent)\\n newPopStructure = np.zeros((self.popStructure.shape[0]+1,self.popStructure.shape[1]+1))\\n newPopStructure[:-1,:-1] = self.popStructure\\n\\n \\n # inherit social structure from parent\\n parent_id = self.findAgentIndexById(parent_agent)\\n secondary_caregivers_ids = [self.findAgentIndexById(a) for a in secondary_caregivers]\\n newPopStructure[-1,] = newPopStructure[parent_id,]\\n newPopStructure[:,-1] = newPopStructure[:,parent_id] \\n\\n\\t\\t# strong bond between parents\\n newPopStructure[-1,parent_id] = self.parameters[\\\"maxWeight\\\"]\\n newPopStructure[parent_id,-1] = self.parameters[\\\"maxWeight\\\"]\\n for s in secondary_caregivers_ids:\\n \\tnewPopStructure[-1,s] =self.parameters[\\\"maxWeight\\\"]\\n \\tnewPopStructure[s,-1] =self.parameters[\\\"maxWeight\\\"]\\n\\n # can't communicate with self\\n np.fill_diagonal(newPopStructure, 0.0)\\n \\n self.popStructure = newPopStructure\\n \\n # start unmarried\\n newMarriageStructure = np.zeros((self.marriageStructure.shape[0]+1,self.marriageStructure.shape[1]+1))\\n newMarriageStructure[:-1,:-1] = self.marriageStructure\\n newMarriageStructure[-1,] = 0\\n newMarriageStructure[:,-1] = 0\\n self.marriageStructure = newMarriageStructure\\n \\n\\t\\t# inherit clan from parent\\n parent_clan = self.clans[parent_id]\\n parent_compound = self.compounds[parent_id]\\n \\n self.clans.append(parent_clan)\\n self.compounds.append(parent_compound)\\n\\n self.nAgents = len(self.pop)\",\n \"def load_inventory(self):\\n for item in self.items:\\n self.rooms[int(item.initial_room_id) - 1].inventory.add(item)\",\n \"def execute_actions(self, actions):\\n execute_actions(self.board, self.agent_locs, actions)\",\n \"def gen_game(\\n board_shape=(25,25), min_performance=-1, partitioning={},\\n starting_region=None, later_regions=None, buffer_region=None,\\n named_regions={}, agents=['default'], agent_types={}, **etc):\\n board_shape = _fix_random_values(board_shape)\\n min_performance = _fix_random_values(min_performance)\\n partitioning = _fix_random_values(partitioning)\\n\\n regions = make_partioned_regions(board_shape, **partitioning)\\n board = np.zeros(board_shape, dtype=np.uint16)\\n goals = np.zeros(board_shape, dtype=np.uint16)\\n\\n # Create locations for the player and the exit\\n agent_locs, points_table, agent_names = add_agents_and_exit(\\n board, regions, agents, agent_types)\\n\\n # and fill in the regions...\\n for k in np.unique(regions)[2:]:\\n mask = regions == k\\n if starting_region is not None:\\n region_name = _fix_random_values(starting_region)\\n else:\\n region_name = _fix_random_values(later_regions)\\n if region_name not in named_regions:\\n logger.error(\\\"No region parameters for name '%s'\\\", region_name)\\n continue\\n logger.debug(\\\"Making region: %s\\\", region_name)\\n rboard, rgoals = populate_region(mask, named_regions[region_name])\\n board += rboard\\n goals += rgoals\\n starting_region = None\\n buffer_region = _fix_random_values(buffer_region)\\n if buffer_region in named_regions:\\n mask = regions == 0\\n rboard, rgoals = populate_region(mask, named_regions[buffer_region])\\n board += rboard\\n goals += rgoals\\n\\n # Give the buffer (0) region a rainbow / white color\\n # This is mostly a visual hint for humans\\n buffer_mask = (regions <= 0) & (goals & CellTypes.rainbow_color == 0)\\n goals[buffer_mask] += CellTypes.rainbow_color\\n\\n game = SafeLifeGame()\\n game.deserialize({\\n 'board': board,\\n 'goals': goals,\\n 'agent_locs': agent_locs,\\n 'agent_names': agent_names,\\n 'min_performance': min_performance,\\n 'points_table': points_table,\\n 'orientation': 1,\\n })\\n return game\",\n \"def add_agents(*_coconut_match_args, **_coconut_match_kwargs):\\n _coconut_match_check_2 = False\\n _coconut_match_set_name_self = _coconut_sentinel\\n _coconut_match_set_name_agents = _coconut_sentinel\\n _coconut_match_set_name__set_defaults = _coconut_sentinel\\n _coconut_match_set_name_named_agents = _coconut_sentinel\\n _coconut_FunctionMatchError = _coconut_get_function_match_error()\\n if _coconut.sum((_coconut.len(_coconut_match_args) > 0, \\\"self\\\" in _coconut_match_kwargs)) == 1:\\n _coconut_match_set_name_agents = _coconut_match_args[1:]\\n _coconut_match_temp_5 = _coconut_match_kwargs.pop(\\\"_set_defaults\\\") if \\\"_set_defaults\\\" in _coconut_match_kwargs else True\\n _coconut_match_temp_4 = _coconut_match_args[0] if _coconut.len(_coconut_match_args) > 0 else _coconut_match_kwargs.pop(\\\"self\\\")\\n _coconut_match_set_name__set_defaults = _coconut_match_temp_5\\n _coconut_match_set_name_self = _coconut_match_temp_4\\n _coconut_match_set_name_named_agents = _coconut_match_kwargs\\n _coconut_match_check_2 = True\\n if _coconut_match_check_2:\\n if _coconut_match_set_name_self is not _coconut_sentinel:\\n self = _coconut_match_set_name_self\\n if _coconut_match_set_name_agents is not _coconut_sentinel:\\n agents = _coconut_match_set_name_agents\\n if _coconut_match_set_name__set_defaults is not _coconut_sentinel:\\n _set_defaults = _coconut_match_set_name__set_defaults\\n if _coconut_match_set_name_named_agents is not _coconut_sentinel:\\n named_agents = _coconut_match_set_name_named_agents\\n if not _coconut_match_check_2:\\n raise _coconut_FunctionMatchError('match def add_agents(self, *agents, _set_defaults=True, **named_agents):', _coconut_match_args)\\n\\n new_agents = []\\n for a in _coconut.itertools.chain.from_iterable(_coconut_reiterable(_coconut_func() for _coconut_func in (lambda: agents, lambda: named_agents.items()))):\\n _coconut_match_to_0 = a\\n _coconut_match_check_1 = False\\n _coconut_match_set_name_name = _coconut_sentinel\\n _coconut_match_set_name_actor = _coconut_sentinel\\n if (_coconut.isinstance(_coconut_match_to_0, _coconut.abc.Sequence)) and (_coconut.len(_coconut_match_to_0) == 2):\\n _coconut_match_set_name_name = _coconut_match_to_0[0]\\n _coconut_match_set_name_actor = _coconut_match_to_0[1]\\n _coconut_match_check_1 = True\\n if _coconut_match_check_1:\\n if _coconut_match_set_name_name is not _coconut_sentinel:\\n name = _coconut_match_set_name_name\\n if _coconut_match_set_name_actor is not _coconut_sentinel:\\n actor = _coconut_match_set_name_actor\\n if _coconut_match_check_1:\\n if not callable(actor):\\n a = init_agent(name, actor)\\n elif isinstance(actor, Agent):\\n a = actor.clone(name=name)\\n else:\\n a = Agent(name, actor)\\n assert isinstance(a, Agent), \\\"not isinstance({_coconut_format_0}, Agent)\\\".format(_coconut_format_0=(a))\\n new_agents.append(a)\\n self.agents += new_agents\\n if _set_defaults:\\n self.set_defaults(new_agents)\\n return self\",\n \"def move_to(self, entity, location):\\n y, x = location\\n if not y in range(self.size) or not x in range(self.size):\\n return\\n y, x = entity.location\\n self.grid[y][x].contents.remove(entity)\\n entity.location = location\\n y, x = location\\n self.grid[y][x].contents.append(entity)\\n for ent in self.grid[y][x].contents:\\n try:\\n if not ent.player_enter_callback is None:\\n ent.player_enter_callback(ent)\\n except AttributeError:\\n pass\",\n \"def push_up(self, event):\\n self.transpose()\\n self.stack()\\n self.merge()\\n self.transpose()\\n\\n if self.any_empty_tiles():\\n self.add_two()\\n\\n self.update_grid()\\n self.is_game_finished()\",\n \"def registerInitialState(self, gameState):\\n\\n '''\\n Make sure you do not delete the following line. If you would like to\\n use Manhattan distances instead of maze distances in order to save\\n on initialization time, please take a look at\\n CaptureAgent.registerInitialState in captureAgents.py.\\n '''\\n self.start = gameState.getAgentPosition(self.index)\\n CaptureAgent.registerInitialState(self, gameState)\\n\\n \\\"G A M E K E Y L O C A T I O N S D E T E R M I N A T I O N\\\"\\n if self.red:\\n leftEdge = gameState.data.layout.width / 2\\n rightEdge = gameState.data.layout.width - 2 #don't need the last wall\\n self.safeColumn = leftEdge - 2 # -1 doesn't always seem to work\\n else:\\n leftEdge = 1\\n rightEdge = gameState.data.layout.width / 2\\n self.safeColumn = rightEdge + 2\\n\\n self.safeSpaces = []\\n for h in xrange(1,gameState.data.layout.height-1):\\n if not gameState.data.layout.isWall((self.safeColumn, h)):\\n self.safeSpaces += [(self.safeColumn, h)]\\n\\n\\n \\\"S T A T E A S S I G N M E N T\\\"\\n pos = gameState.getAgentState(self.index).getPosition()\\n self.friend = min(2 + int(not self.red), 2 - self.index + 2 * int(not self.red))\\n friendPos = gameState.getAgentState(self.friend).getPosition()\\n opps = [gameState.getAgentState(el).getPosition() for el in [1 - int(not self.red), 3 - int(not self.red)] ]\\n\\n print \\\"I am agent\\\", self.index, \\\"at position \\\", pos\\n #print \\\"agent 0:\\\", gameState.getAgentState(0).getPosition()\\n print \\\"My friend agent\\\", self.friend, \\\"is at position \\\", friendPos\\n print \\\"My first enemy agent is at position \\\", opps[0]\\n print \\\"My second enemy agent is at position \\\", opps[1]\\n\\n self.top = False\\n self.undecided = False\\n\\n if pos[1] > friendPos[1]:\\n print \\\"My friend is lower on the map, and I will take top Quad\\\"\\n self.top = True\\n elif pos[1] < friendPos[1]:\\n print \\\"My friend is higher on the map, and I will take bottom Quad\\\"\\n else:\\n self.undecided = True\\n\\n \\\"F O O D A S S I G N M E N T\\\"\\n self.initFood = self.getFood(gameState).asList()\\n self.myFood = self.initFood[:] #this is will be updated during our A* Search for theoretical consumption\\n print self.myFood\\n\\n \\\"I N I T I A L F O O D A S S I G N M E N T S \\\"\\n\\n start = time.time()\\n print 'eval time for moves: %.4f' % (time.time() - start)\\n\\n\\n \\\"D E B U G G I N G\\\"\\n print \\\"Coloring my safe column white\\\"\\n self.debugDraw([(self.safeColumn, el) for el in xrange(0, gameState.data.layout.height)], [1,1,1], clear=False)\\n\\n print \\\"Coloring my safe spaces\\\", self.safeSpaces, \\\"blue\\\"\\n self.debugDraw(self.safeSpaces, [0,0,1], clear=False)\\n\\n self.counter = 0\\n self.moves = []\\n self.intendedCoords =[]\\n self.best = None\\n\\n #new\\n print \\\"Using my sweet time to find next moves during init as agent\\\", self.index\\n self.best = self.ActionLoop(gameState, 140)\\n self.moves = self.best.getDir()[1]\\n self.counter = len(self.moves)\\n self.cacheSize = len(self.moves)\\n #new\",\n \"def __add_players_spawns(self):\\n # Werewolves\\n self.__grid[self.__werewolves_start[0]][self.__werewolves_start[1]][\\\"werewolves\\\"] \\\\\\n = self.__number_of_beasts\\n # Vampires\\n self.__grid[self.__vampires_start[0]][self.__vampires_start[1]][\\\"vampires\\\"] \\\\\\n = self.__number_of_beasts\",\n \"def draw_board(self):\\n self.current_board = self.gameboard.copy()\\n \\n # Draw our rewards\\n for r, row in enumerate(self.world_rewards):\\n for c, reward in enumerate(row):\\n if reward is not None:\\n asset_key = reward.asset\\n x = 64*(c+1)\\n y = 64*(r+1)\\n self.current_board.paste(\\\\\\n self.assets[asset_key], (x,y), self.assets[asset_key])\\n \\n # Draw our creature\\n cr_x, cr_y = self.creature.current_location\\n x = 64*(cr_x + 1) # Should be the center of the tile\\n y = 64*(cr_y + 1)\\n creature_image = self.assets['beaver']\\n if self.creature.facing == 'S':\\n creature_image = creature_image.rotate(-180)\\n elif self.creature.facing == 'E':\\n creature_image = creature_image.rotate(-90)\\n elif self.creature.facing == 'W':\\n creature_image = creature_image.rotate(-270)\\n self.current_board.paste(creature_image, (x,y), creature_image)\",\n \"def on_enter(self):\\n # Obtain pointer to Parent Grid + Obstacles\\n self._grid = self.parent._grid\\n self._obstacles = self.parent._obstacles\\n super().on_enter()\",\n \"def _add_agent_to_graph(self, agent: mantrap.agents.base.DTAgent):\\n from data import Node\\n is_robot = agent.is_robot\\n\\n # In Trajectron each node has a certain type, which is either robot or pedestrian, an id and\\n # state data. Enforce the Trajectron id to the internal ids format, to be able to query the\\n # results later on.\\n agent_history = agent.history\\n acc_history = agent.compute_acceleration(agent_history, dt=self.dt)\\n\\n node_data = self._create_node_data(state_history=agent_history, accelerations=acc_history)\\n node_tye = self._gt_env.NodeType.PEDESTRIAN if not is_robot else self._gt_env.NodeType.ROBOT\\n node = Node(node_type=node_tye, node_id=agent.id, data=node_data, is_robot=is_robot)\\n if is_robot:\\n self._gt_scene.robot = node\\n self._gt_scene.nodes.append(node)\\n\\n # Re-Create online environment with recently appended node.\\n self._online_env = self.create_online_env(env=self._gt_env, scene=self._gt_scene)\",\n \"def add_zombie(self, row, col):\\r\\n self._zombie_list.append((row, col))\",\n \"def add_rect(self, r, obj):\\n cells = self._cells_for_rect(r)\\n for c in cells:\\n self._add(c, obj)\",\n \"def cells(self, cells):\\n\\n self.container['cells'] = cells\",\n \"def add_zombie(self, row, col):\\n self._zombie_list.append((row,col))\",\n \"def make_land_agents_2016(self):\\r\\n # add non-gtgp\\r\\n for hh_row in agents: # from excel_import\\r\\n hh_id = return_values(hh_row, 'hh_id')\\r\\n self.total_rice = return_values(hh_row, 'non_gtgp_rice_mu')\\r\\n if self.total_rice in ['-3', '-4', -3, None]:\\r\\n self.total_rice = 0\\r\\n self.total_dry = return_values(hh_row, 'non_gtgp_dry_mu')\\r\\n if self.total_dry in ['-3', '-4', -3, None]:\\r\\n self.total_dry = 0\\r\\n self.gtgp_rice = return_values(hh_row, 'gtgp_rice_mu')\\r\\n if self.gtgp_rice in ['-3', '-4', -3, None]:\\r\\n self.total_rice = 0\\r\\n self.gtgp_dry = return_values(hh_row, 'gtgp_dry_mu')\\r\\n if self.gtgp_dry in ['-3', '-4', -3, None]:\\r\\n self.gtgp_dry = 0\\r\\n\\r\\n landposlist = self.determine_landpos(hh_row, 'non_gtgp_latitude', 'non_gtgp_longitude')\\r\\n self.age_1 = return_values(hh_row, 'age')[0]\\r\\n self.gender_1 = return_values(hh_row, 'gender')[0]\\r\\n self.education_1 = return_values(hh_row, 'education')[0]\\r\\n\\r\\n for landpos in landposlist:\\r\\n try:\\r\\n self.pre_gtgp_output = return_values(hh_row, 'pre_gtgp_output')[landposlist.index(landpos)]\\r\\n except:\\r\\n pass\\r\\n\\r\\n try:\\r\\n self.non_gtgp_output = return_values(hh_row, 'pre_gtgp_output')[landposlist.index(landpos)]\\r\\n except:\\r\\n pass\\r\\n self.land_time = return_values(hh_row, 'non_gtgp_travel_time')[landposlist.index(landpos)]\\r\\n try:\\r\\n self.plant_type = return_values(hh_row, 'non_gtgp_plant_type')[landposlist.index(landpos)]\\r\\n except:\\r\\n pass\\r\\n try:\\r\\n self.land_type = return_values(hh_row, 'non_gtgp_land_type')[landposlist.index(landpos)]\\r\\n except:\\r\\n pass\\r\\n self.hh_size = len(return_values(hh_row, 'age'))\\r\\n self.gtgp_enrolled = 0\\r\\n lp = LandParcelAgent(hh_row, self, hh_id, hh_row, landpos, self.gtgp_enrolled,\\r\\n self.age_1, self.gender_1, self.education_1,\\r\\n self.gtgp_dry, self.gtgp_rice, self.total_dry, self.total_rice,\\r\\n self.land_type, self.land_time, self.plant_type, self.non_gtgp_output,\\r\\n self.pre_gtgp_output)\\r\\n self.space.place_agent(lp, landpos)\\r\\n self.schedule.add(lp)\\r\\n if self.gtgp_enrolled == 0 and landpos not in nongtgplist and landpos not in gtgplist:\\r\\n nongtgplist.append(landpos)\\r\\n # except:\\r\\n # pass\\r\\n\\r\\n # add gtgp\\r\\n for hh_row in agents: # from excel_import\\r\\n hh_id = return_values(hh_row, 'hh_id')\\r\\n self.total_rice = return_values(hh_row, 'non_gtgp_rice_mu')\\r\\n if self.total_rice in ['-3', '-4', -3, None]:\\r\\n self.total_rice = 0\\r\\n self.total_dry = return_values(hh_row, 'non_gtgp_dry_mu')\\r\\n if self.total_dry in ['-3', '-4', -3, None]:\\r\\n self.total_dry = 0\\r\\n self.gtgp_rice = return_values(hh_row, 'gtgp_rice_mu')\\r\\n if self.gtgp_rice in ['-3', '-4', -3, None]:\\r\\n self.total_rice = 0\\r\\n self.gtgp_dry = return_values(hh_row, 'gtgp_dry_mu')\\r\\n if self.gtgp_dry in ['-3', '-4', -3, None]:\\r\\n self.gtgp_dry = 0\\r\\n landposlist = self.determine_landpos(hh_row, 'gtgp_latitude', 'gtgp_longitude')\\r\\n self.age_1 = return_values(hh_row, 'age')[0]\\r\\n self.gender_1 = return_values(hh_row, 'gender')[0]\\r\\n self.education_1 = return_values(hh_row, 'education')[0]\\r\\n for landpos in landposlist:\\r\\n try:\\r\\n self.pre_gtgp_output = return_values(hh_row, 'pre_gtgp_output')[landposlist.index(landpos)]\\r\\n except:\\r\\n pass\\r\\n try:\\r\\n self.non_gtgp_output = return_values(hh_row, 'pre_gtgp_output')[landposlist.index(landpos)]\\r\\n except:\\r\\n pass\\r\\n try:\\r\\n self.land_time = return_values(hh_row, 'gtgp_travel_time')[landposlist.index(landpos)]\\r\\n except:\\r\\n pass\\r\\n try:\\r\\n self.plant_type = return_values(hh_row, 'pre_gtgp_plant_type')[landposlist.index(landpos)]\\r\\n except:\\r\\n pass\\r\\n try:\\r\\n self.land_type = return_values(hh_row, 'pre_gtgp_land_type')[landposlist.index(landpos)]\\r\\n except:\\r\\n pass\\r\\n self.hh_size = len(return_values(hh_row, 'age'))\\r\\n self.gtgp_enrolled = 1\\r\\n\\r\\n lp_gtgp = LandParcelAgent(hh_id, self, hh_id, hh_row, landpos, self.gtgp_enrolled,\\r\\n self.age_1, self.gender_1, self.education_1,\\r\\n self.gtgp_dry, self.gtgp_rice, self.total_dry, self.total_rice,\\r\\n self.land_type, self.land_time, self.plant_type, self.non_gtgp_output,\\r\\n self.pre_gtgp_output)\\r\\n self.space.place_agent(lp_gtgp, landpos)\\r\\n self.schedule.add(lp_gtgp)\\r\\n if self.gtgp_enrolled == 1 and landpos not in gtgplist and landpos in nongtgplist:\\r\\n gtgplist.append(landpos)\",\n \"def initialize_areas(self):\\n self._areas[1] = copy.copy(self._areas[0])\",\n \"def place_obj(self):\\r\\n for pos in BOARD_POSITIONS:\\r\\n self.board[pos[0]][pos[1]] = Stone(color=self.state[pos[0]][pos[1]], pos=(pos[0], pos[1]))\\r\\n self.board[pos[0]][pos[1]].liberty = self.board[pos[0]][pos[1]].compute_liberty(self.state)\",\n \"def add_zombie(self, row, col):\\n self._zombie_list.append((row, col))\",\n \"def AddRegions(self, **kwargs):\\n # Addregions use pixel coordinates. listRegions and SaveRegions use RA and Dec.\\n n_objs = 0\\n objs = []\\n # default shape is circle\\n if not 'shape' in kwargs:\\n kwargs['shape'] = ['circle']\\n for k in kwargs.keys():\\n n_objs = max(n_objs, len(kwargs[k]))\\n for j in range(n_objs):\\n temp = {}\\n for k in kwargs.keys():\\n try:\\n temp[k] = kwargs[k][j]\\n except IndexError:\\n if k == 'shape': \\n temp[k] = 'circle'\\n objs.append(temp)\\n self.all_objs = json.dumps(objs)\\n command = \\\"JS9.AddRegions({objs}, {{display:'{wid}{suffix}'}})\\\".format(objs=self.all_objs, wid=self.wid, suffix=self.suffix)\\n get_ipython().run_cell_magic('javascript', '', command)\",\n \"def mapAdd(block, posMap):\\n for (x, y) in block.coords:\\n theFallener(x + block.x, y + block.y, block.color, posMap)\",\n \"def recreate_obstacles(self):\\n self.board_matrix = np.full(Dimension.board_size(), 1)\\n self.obstacles = self.create_obstacles()\",\n \"def place_exit(self):\\r\\n x = random.randint(0, (self.__nx - 1))\\r\\n y = random.randint(0, (self.__ny - 1))\\r\\n self.__exit_room = x, y\\r\\n if self.exit_room() == self.pillar_a_room() or \\\\\\r\\n self.exit_room() == self.pillar_e_room() or \\\\\\r\\n self.exit_room() == self.pillar_i_room() or \\\\\\r\\n self.exit_room() == self.pillar_p_room() or \\\\\\r\\n self.exit_room() == self.entrance_room():\\r\\n return self.place_exit()\\r\\n self.__maze[x][y].set_exit(True)\",\n \"def add_new_region(self, image_name: str, region_text: str, region_position: RegionPosition, region_type: str):\\n pass\",\n \"def do_merge(self, cr, uid, ids, context=None): \\n invent_obj = self.pool.get('stock.inventory')\\n invent_line_obj = self.pool.get('stock.inventory.line')\\n invent_lines = {}\\n if context is None:\\n context = {}\\n for inventory in invent_obj.browse(cr, uid, context['active_ids'], context=context):\\n if inventory.state == \\\"done\\\":\\n raise osv.except_osv(_('Warning!'),\\n _('Merging is only allowed on draft inventories.'))\\n\\n for line in inventory.inventory_line_id:\\n key = (line.location_id.id, line.product_id.id, line.product_uom.id)\\n if key in invent_lines:\\n invent_lines[key] += line.product_qty\\n else:\\n invent_lines[key] = line.product_qty\\n\\n\\n new_invent = invent_obj.create(cr, uid, {\\n 'name': 'Merged inventory'\\n }, context=context)\\n\\n for key, quantity in invent_lines.items():\\n invent_line_obj.create(cr, uid, {\\n 'inventory_id': new_invent,\\n 'location_id': key[0],\\n 'product_id': key[1],\\n 'product_uom': key[2],\\n 'product_qty': quantity,\\n })\\n\\n return {'type': 'ir.actions.act_window_close'}\",\n \"def load(self):\\n\\n if self.loaded:\\n return\\n\\n self.region_back = None\\n self.objects = []\\n self.plants = []\\n self.tiles = []\\n\\n # Some convenience vars\\n materials = self.data.materials\\n matmods = self.data.matmods\\n objects = self.data.objects\\n plants = self.data.plants\\n world = self.world\\n self.loaded = True\\n\\n # Get tiles\\n try:\\n data_tiles = world.get_tiles(self.rx, self.ry)\\n except KeyError:\\n print('WARNING: Region ({}, {}) was not found in world'.format(self.rx, self.ry))\\n return\\n\\n # \\\"real\\\" coordinates\\n base_x = self.rx*32\\n gui_x = base_x*8\\n base_y = self.ry*32\\n gui_y = (world.height*8)-(base_y*8)\\n\\n # Background for our drawn area (black)\\n self.region_back = self.scene.addRect(gui_x, gui_y-255, 255, 255,\\n QtGui.QPen(QtGui.QColor(0, 0, 0)),\\n QtGui.QBrush(QtGui.QColor(0, 0, 0)),\\n )\\n self.region_back.setZValue(Constants.z_black)\\n\\n # Tiles!\\n cur_row = 0\\n cur_col = 0\\n for data_tile in data_tiles:\\n self.tiles.append(GUITile(self.scene, data_tile,\\n base_x+cur_col, base_y+cur_row,\\n self,\\n gui_x+cur_col*8, gui_y-(cur_row+1)*8,\\n self.layer_toggles))\\n self.scene.addItem(self.tiles[-1])\\n cur_col += 1\\n if cur_col == 32:\\n cur_col = 0\\n cur_row += 1\\n\\n # Entities!\\n entities = []\\n try:\\n entities = world.get_entities(self.rx, self.ry)\\n except KeyError:\\n pass\\n\\n for e in entities:\\n if e.name == 'ObjectEntity':\\n obj_name = e.data['name']\\n obj_orientation = e.data['orientationIndex']\\n (obj_x, obj_y) = tuple(e.data['tilePosition'])\\n if obj_name in objects:\\n obj = objects[obj_name]\\n (image, offset_x, offset_y) = obj.get_image(obj_orientation)\\n qpmi = QtWidgets.QGraphicsPixmapItem(image)\\n qpmi.setPos(\\n (obj_x*8) + offset_x,\\n (world.height*8)-(obj_y*8) - offset_y - image.height(),\\n )\\n qpmi.setZValue(Constants.z_objects)\\n if not self.layer_toggles.objects_toggle.isChecked():\\n qpmi.setVisible(False)\\n self.scene.addItem(qpmi)\\n self.objects.append(qpmi)\\n rel_x = obj_x - base_x\\n rel_y = obj_y - base_y\\n tile_idx = rel_y*32 + rel_x\\n self.tiles[tile_idx].add_object(obj, obj_name, obj_orientation, qpmi, e.data)\\n elif e.name == 'PlantEntity':\\n desc = e.data['descriptions']['description']\\n images = []\\n (obj_x, obj_y) = tuple(e.data['tilePosition'])\\n for piece in e.data['pieces']:\\n piece_img = piece['image'].split('?')[0]\\n if piece_img in plants:\\n img = plants[piece_img].image\\n qpmi = QtWidgets.QGraphicsPixmapItem(img)\\n qpmi.setPos(\\n (obj_x*8) + (piece['offset'][0]*8),\\n (world.height*8)-(obj_y*8) - (piece['offset'][1]*8) - img.height(),\\n )\\n qpmi.setZValue(Constants.z_plants)\\n if not self.layer_toggles.plants_toggle.isChecked():\\n qpmi.setVisible(False)\\n images.append((plants[piece_img], qpmi))\\n self.scene.addItem(qpmi)\\n self.plants.append(qpmi)\\n else:\\n print('not found: {}'.format(piece_img))\\n rel_x = obj_x - base_x\\n rel_y = obj_y - base_y\\n tile_idx = rel_y*32 + rel_x\\n self.tiles[tile_idx].add_plant(desc, images)\\n elif (e.name == 'MonsterEntity'\\n or e.name == 'NpcEntity'\\n or e.name == 'StagehandEntity'\\n or e.name == 'ItemDropEntity'\\n or e.name == 'VehicleEntity'\\n ):\\n # TODO: Ignoring for now\\n pass\\n else:\\n print('Unknown entity type: {}'.format(e.name))\",\n \"def make_board(self, ):\\n for r in range(self.boardSize):\\n for c in range(self.boardSize): # avoid redundant calculation by adding neighbors \\\"behind\\\" current cell\\n new_cell = Cell(r, c)\\n self.board[r][c] = new_cell\\n if c > 0: # add left neighbor-cell\\n new_cell.add_neighbor(self.board[r][c-1])\\n if r > 0: # add above neighbor-cell\\n new_cell.add_neighbor(self.board[r-1][c])\\n if r > 0 and c < self.boardSize-1: # add right diagonal neighbor-cell\\n new_cell.add_neighbor(self.board[r-1][c+1])\",\n \"def _populate_level_with_enemies(self,\\n map_layer_configuration,\\n base_enemy_chance_cave: float = 0.006,\\n base_enemy_chance_dungeon: float = 0.006,\\n base_boss_chance: float = 0.003) -> None:\\n enemy_chance_cave = self.generate_enemy_chance(base_enemy_chance_cave)\\n enemy_chance_dungeon = self.generate_enemy_chance(base_enemy_chance_dungeon)\\n boss_chance = self.generate_enemy_chance(base_boss_chance)\\n for row in map_layer_configuration:\\n for block in row:\\n if block[0] == ' ':\\n if np.random.rand() > (1 - enemy_chance_cave):\\n if self.sprites.drill.center_x != block[1] or self.sprites.drill.center_y != block[2]:\\n enemy_to_add = random.choice(potential_enemies)\\n enemy_to_append = enemy_to_add(block[1], block[2], vision=200)\\n self.sprites.entity_list.append(enemy_to_append)\\n self.sprites.enemy_list.append(enemy_to_append)\\n elif block[0] == 'F':\\n if np.random.rand() > (1 - enemy_chance_dungeon):\\n if self.sprites.drill.center_x != block[1] or self.sprites.drill.center_y != block[2]:\\n enemy_to_add = random.choice(potential_enemies)\\n enemy_to_append = enemy_to_add(block[1], block[2], vision=200)\\n self.sprites.entity_list.append(enemy_to_append)\\n self.sprites.enemy_list.append(enemy_to_append)\\n elif np.random.rand() > (1 - boss_chance):\\n if self.sprites.drill.center_x != block[1] or self.sprites.drill.center_y != block[2]:\\n enemy_to_add = random.choice(potential_bosses)\\n enemy_to_append = enemy_to_add(block[1], block[2], vision=200, speed=0.7)\\n self.sprites.entity_list.append(enemy_to_append)\\n self.sprites.enemy_list.append(enemy_to_append)\\n self.sprites.drill_list.append(self.sprites.drill)\\n\\n for entity in self.sprites.entity_list:\\n entity.setup_collision_engine([self.sprites.indestructible_blocks_list])\",\n \"def move2(self):\\n\\n options = self.location.exits.keys()\\n for key in options:\\n if self.location.exits[key] == p.location:\\n self.location.objects.remove(a)\\n self.location = p.location\\n self.location.objects.append(a)\\n print('fred entered the room')\\n self.attack(['attack', str(p.name)])\\n break\\n else:\\n self.move1()\",\n \"def update(self):\\n self.platform_list.update()\\n self.exit_sprite.update()\\n self.bagGroup.update()\\n self.enemy_list.update()\",\n \"def add_conflicting_agents(self, agent_i, agent_j):\\n\\n self.conflicting_agents = (agent_i, agent_j)\",\n \"def grow(self, start_period=1, cascade=True):\\n end_period = start_period + 1 if not cascade else self.parent.horizon\\n for p in range(start_period, end_period):\\n self.reset_areas(p+1) #, self._areas[p], self._areas[p+1] # WTF?\\n #for age, area in list(self._areas[p].items()): self._areas[p+1][age+1] = area\\n for age, area in list(self._areas[p].items()): self._areas[p+1][age+self.parent.period_length] = area\",\n \"def occupied_cells(self):\\n\\n for lm in self.landmarks:\\n if self.cell_size < 1:\\n # expand the range the landmark exists\\n lm_x_range = np.arange(lm[0]-self.R, lm[0]+self.R, self.cell_size)\\n lm_y_range = np.arange(lm[1]-self.R, lm[1]+self.R, self.cell_size)\\n\\n # loop through expanded ranges and compute grid positions\\n for lm_x in lm_x_range:\\n for lm_y in lm_y_range:\\n\\n row, col = self.cell_index([lm_x, lm_y])\\n\\n # apply cost of occupied cell\\n try:\\n self.world[row][col] = 1000\\n except IndexError:\\n pass\\n\\n else:\\n # apply cost of occupied cell\\n row, col = self.cell_index(lm)\\n try:\\n self.world[row][col] = 1000\\n except IndexError:\\n pass\",\n \"def draw_region(self, constraint, agent):\\n if (constraint == self.obstacles) and (self.obstacles[agent] is not None):\\n for area in self.obstacles[agent]:\\n x_min, x_max = area[0][0], area[0][1]\\n y_min, y_max = area[1][0], area[1][1]\\n rectangle = plt.Rectangle((x_min, y_min), x_max - x_min, y_max - y_min, fc='k', ec=\\\"k\\\")\\n plt.gca().add_patch(rectangle)\\n elif (constraint == self.observation_areas) and (self.observation_areas[agent] is not None):\\n for observation_area in self.observation_areas[agent]:\\n x_min, x_max = observation_area.region[0][0], observation_area.region[0][1]\\n y_min, y_max = observation_area.region[1][0], observation_area.region[1][1]\\n rectangle = plt.Rectangle((x_min, y_min), x_max - x_min, y_max - y_min, fc='c', ec=\\\"c\\\", alpha=0.5)\\n plt.gca().add_patch(rectangle)\\n\\n plt.xlim(self.Xi[0])\\n plt.ylim(self.Xi[1])\",\n \"def add(self, states, actions, rewards, next_states, dones):\\n assert len(states) == self.num_agents, 'ERROR> group states size mismatch'\\n assert len(actions) == self.num_agents, 'ERROR> group actions size mismatch'\\n assert len(rewards) == self.num_agents, 'ERROR> group rewards size mismatch'\\n assert len(next_states) == self.num_agents, 'ERROR> group next states size mismatch'\\n assert len(dones) == self.num_agents, 'ERROR> group dones size mismatch'\\n\\n experience = (states, actions, rewards, next_states, dones)\\n self.memory.append(experience)\",\n \"def editor_multi_agent_example():\\n agent_definitions = [\\n AgentDefinition(\\\"uav0\\\", agents.UavAgent, [sensors.RGBCamera, sensors.LocationSensor]),\\n AgentDefinition(\\\"uav1\\\", agents.UavAgent, [sensors.LocationSensor, sensors.VelocitySensor])\\n ]\\n env = HolodeckEnvironment(agent_definitions, start_world=False)\\n\\n cmd0 = np.array([0, 0, -2, 10])\\n cmd1 = np.array([0, 0, 5, 10])\\n\\n for i in range(10):\\n env.reset()\\n env.act(\\\"uav0\\\", cmd0)\\n env.act(\\\"uav1\\\", cmd1)\\n for _ in range(1000):\\n states = env.tick()\",\n \"def add_entity(self, ent):\\n self.tiles[ent.position[x]][ent.position[y]].add_entity(ent)\",\n \"def populate_board(self):\\n for row in range(10):\\n for col in range(10):\\n coord = Coordinate(row, col)\\n coord_attack = Coordinate(row, col)\\n self.player_table.setItem(row, col, coord)\\n self.attack_table.setItem(row, col, coord_attack)\",\n \"def place_road(self, road):\\n\\n # Check if space is empty\\n if not self.environment.grid.is_cell_empty(road.pos):\\n return False\\n\\n # Place Road\\n self.environment.grid.place_agent(agent=road, pos=road.pos)\\n\\n # Add road to environment's road list\\n self.environment.agents['roads'].append(road)\\n\\n # Update the list of cells where other things can be built\\n self.update_available_cells(road)\",\n \"def __add_homes(self):\\n for home in self.__positions_of_homes:\\n self.__grid[home[0]][home[1]][\\\"humans\\\"] = math.floor(\\n self.__number_of_humans / self.__number_of_homes\\n )\",\n \"def _add_rooms(self):\\r\\n rooms = self.model.get_all_rooms()\\r\\n\\r\\n for room in rooms:\\r\\n self._add_room(room)\",\n \"def add_region(self, address, data):\\n region = HexFileRegion(address, data)\\n self.regions.append(region)\\n self.check()\",\n \"def _undo_overlap(self, agent1, agent2, dist, combined_sizes, **kwargs):\\n overlap = (combined_sizes - dist) / combined_sizes\\n self.position_state.modify_position(agent1, -agent1.velocity * overlap)\\n self.position_state.modify_position(agent2, -agent2.velocity * overlap)\",\n \"def setup(self):\\n self.board[(3, 3)] = -1\\n self.board[(3, 4)] = -1\\n self.board[(4, 3)] = 1\\n self.board[(4, 4)] = 1\\n\\n self.stones_set = 4\",\n \"def create_enemy():\\n if randint(0, 20) == 5:\\n try:\\n check.check_life(common.COLS-1, common.MIDS_R, \\\"Enemy\\\")\\n eitem = person.Enemy(common.COLS-1, common.MIDS_R)\\n config.E_LIST.append(eitem)\\n except (config.EnemyHere, config.GapHere):\\n pass\\n\\n for i in config.E_LIST:\\n try:\\n i.move(i.x_pos-2, i.y_pos)\\n except config.WallHere:\\n pass\\n except config.EnemyHere:\\n config.E_LIST.remove(i)\",\n \"def set_pieces(self):\\n\\n for i in range(len(self._game_board)):\\n\\n # Row 1\\n if i == 0:\\n for ii in range(len(self._game_board[i])):\\n if ii == 0 or ii == 8:\\n self._game_board[i][ii] = Chariot(\\\"black\\\", \\\"BCHA\\\")\\n self._game_board[i][ii].update_location([i, ii])\\n if ii == 1 or ii == 7:\\n self._game_board[i][ii] = Horse(\\\"black\\\", \\\" BH \\\")\\n self._game_board[i][ii].update_location([i, ii])\\n if ii == 2 or ii == 6:\\n self._game_board[i][ii] = Elephant(\\\"black\\\", \\\" BE \\\")\\n self._game_board[i][ii].update_location([i, ii])\\n if ii == 3 or ii == 5:\\n self._game_board[i][ii] = Advisor(\\\"black\\\", \\\" BA \\\")\\n self._game_board[i][ii].update_location([i, ii])\\n if ii == 4:\\n self._game_board[i][ii] = General(\\\"black\\\", \\\" BG \\\")\\n self._game_board[i][ii].update_location([i, ii])\\n\\n # Row 3\\n if i == 2:\\n for ii in range(len(self._game_board[i])):\\n if ii == 1 or ii == 7:\\n self._game_board[i][ii] = Cannon(\\\"black\\\", \\\"BCAN\\\")\\n self._game_board[i][ii].update_location([i, ii])\\n\\n # Row 4\\n if i == 3:\\n for ii in range(len(self._game_board[i])):\\n if ii % 2 == 0:\\n self._game_board[i][ii] = Soldier(\\\"black\\\", \\\"BSOL\\\")\\n self._game_board[i][ii].update_location([i, ii])\\n\\n # Row 7\\n if i == 6:\\n for ii in range(len(self._game_board[i])):\\n if ii % 2 == 0:\\n self._game_board[i][ii] = Soldier(\\\"red\\\", \\\"RSOL\\\")\\n self._game_board[i][ii].update_location([i, ii])\\n\\n # Row 8\\n if i == 7:\\n for ii in range(len(self._game_board[i])):\\n if ii == 1 or ii == 7:\\n self._game_board[i][ii] = Cannon(\\\"red\\\", \\\"RCAN\\\")\\n self._game_board[i][ii].update_location([i, ii])\\n\\n # Row 10\\n if i == 9:\\n for ii in range(len(self._game_board[i])):\\n if ii == 0 or ii == 8:\\n self._game_board[i][ii] = Chariot(\\\"red\\\", \\\"RCHA\\\")\\n self._game_board[i][ii].update_location([i, ii])\\n if ii == 1 or ii == 7:\\n self._game_board[i][ii] = Horse(\\\"red\\\", \\\" RH \\\")\\n self._game_board[i][ii].update_location([i, ii])\\n if ii == 2 or ii == 6:\\n self._game_board[i][ii] = Elephant(\\\"red\\\", \\\" RE \\\")\\n self._game_board[i][ii].update_location([i, ii])\\n if ii == 3 or ii == 5:\\n self._game_board[i][ii] = Advisor(\\\"red\\\", \\\" RA \\\")\\n self._game_board[i][ii].update_location([i, ii])\\n if ii == 4:\\n self._game_board[i][ii] = General(\\\"red\\\", \\\" RG \\\")\\n self._game_board[i][ii].update_location([i, ii])\",\n \"def specific_reset(self) -> None:\\n\\n # first, set agent xy and adjust its height\\n self.agent.specific_reset()\\n agent_pos = np.zeros(3)\\n agent_pos = np.concatenate((agent_pos[:2], [self.agent.init_xyz[2]]))\\n self.agent.set_position(agent_pos)\\n\\n # second, reset obstacle positions\\n if len(self.obstacles) > 0:\\n obs_init_pos = env_utils.generate_obstacles_init_pos(\\n num_obstacles=len(self.obstacles),\\n agent_pos=self.agent.get_position(),\\n goal_pos=np.array([]), # no goal in gather task\\n world=self.world,\\n min_allowed_distance=self.obstacle_obstacle_distance,\\n agent_obstacle_distance=self.agent_obstacle_distance\\n )\\n for i, ob in enumerate(self.obstacles):\\n ob.set_position(obs_init_pos[i])\\n\\n # finally, make all collected objects visible again\\n [ob.update_visuals(make_visible=True) for ob in self.obstacles]\",\n \"def create_board(self):\\n for field in self.fields_start_locs:\\n loc = self.loc_to_view(field[0], field[1])\\n new_field = Field(loc, self.piece_size)\\n self.sprite_group.add(new_field)\\n self.click_sprites.add(new_field)\\n self.fields.append(new_field)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5694394","0.5502142","0.5498129","0.5477356","0.5419938","0.53479344","0.5290117","0.52449757","0.52416706","0.51957417","0.5178578","0.5174868","0.51587874","0.5111144","0.5063345","0.5056426","0.50496","0.50238144","0.50177455","0.49965593","0.49882892","0.49847248","0.49558023","0.49202922","0.48733482","0.48692533","0.48518908","0.48447728","0.48413575","0.48335016","0.48326555","0.4828696","0.48268774","0.48096022","0.48023614","0.4796406","0.4788084","0.47722533","0.4771003","0.47645703","0.47590595","0.47455546","0.47427794","0.4734808","0.47327325","0.4717882","0.47109875","0.47075865","0.4704568","0.46952543","0.46941066","0.4679838","0.46765575","0.46761733","0.46673986","0.46664986","0.46630695","0.4658269","0.46554542","0.46516305","0.4649908","0.463904","0.4613151","0.4606439","0.46057656","0.46055856","0.45998886","0.45993975","0.45991403","0.45963895","0.45952758","0.4594601","0.4593535","0.45786968","0.4571666","0.45665836","0.45643786","0.4563613","0.45540094","0.45512614","0.4546316","0.4545035","0.45444444","0.45423743","0.45412555","0.4540445","0.45383367","0.453191","0.4531171","0.45279387","0.45269635","0.45234138","0.4520731","0.45201582","0.4517912","0.4517013","0.4516745","0.4516174","0.45055997","0.45025578"],"string":"[\n \"0.5694394\",\n \"0.5502142\",\n \"0.5498129\",\n \"0.5477356\",\n \"0.5419938\",\n \"0.53479344\",\n \"0.5290117\",\n \"0.52449757\",\n \"0.52416706\",\n \"0.51957417\",\n \"0.5178578\",\n \"0.5174868\",\n \"0.51587874\",\n \"0.5111144\",\n \"0.5063345\",\n \"0.5056426\",\n \"0.50496\",\n \"0.50238144\",\n \"0.50177455\",\n \"0.49965593\",\n \"0.49882892\",\n \"0.49847248\",\n \"0.49558023\",\n \"0.49202922\",\n \"0.48733482\",\n \"0.48692533\",\n \"0.48518908\",\n \"0.48447728\",\n \"0.48413575\",\n \"0.48335016\",\n \"0.48326555\",\n \"0.4828696\",\n \"0.48268774\",\n \"0.48096022\",\n \"0.48023614\",\n \"0.4796406\",\n \"0.4788084\",\n \"0.47722533\",\n \"0.4771003\",\n \"0.47645703\",\n \"0.47590595\",\n \"0.47455546\",\n \"0.47427794\",\n \"0.4734808\",\n \"0.47327325\",\n \"0.4717882\",\n \"0.47109875\",\n \"0.47075865\",\n \"0.4704568\",\n \"0.46952543\",\n \"0.46941066\",\n \"0.4679838\",\n \"0.46765575\",\n \"0.46761733\",\n \"0.46673986\",\n \"0.46664986\",\n \"0.46630695\",\n \"0.4658269\",\n \"0.46554542\",\n \"0.46516305\",\n \"0.4649908\",\n \"0.463904\",\n \"0.4613151\",\n \"0.4606439\",\n \"0.46057656\",\n \"0.46055856\",\n \"0.45998886\",\n \"0.45993975\",\n \"0.45991403\",\n \"0.45963895\",\n \"0.45952758\",\n \"0.4594601\",\n \"0.4593535\",\n \"0.45786968\",\n \"0.4571666\",\n \"0.45665836\",\n \"0.45643786\",\n \"0.4563613\",\n \"0.45540094\",\n \"0.45512614\",\n \"0.4546316\",\n \"0.4545035\",\n \"0.45444444\",\n \"0.45423743\",\n \"0.45412555\",\n \"0.4540445\",\n \"0.45383367\",\n \"0.453191\",\n \"0.4531171\",\n \"0.45279387\",\n \"0.45269635\",\n \"0.45234138\",\n \"0.4520731\",\n \"0.45201582\",\n \"0.4517912\",\n \"0.4517013\",\n \"0.4516745\",\n \"0.4516174\",\n \"0.45055997\",\n \"0.45025578\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.716102"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":94894,"cells":{"query":{"kind":"string","value":"Randomly generate a new SafeLife game board. Generation proceeds by creating several different random \"regions\", and then filling in each region with one of several types of patterns or tasks. Regions can be surrounded by fences / walls to make it harder for patterns to spread from one region to another. Each set of parameters can additionally be randomized by passing in a dictionary either with the 'choices' key or the 'uniform' key."},"document":{"kind":"string","value":"def gen_game(\n board_shape=(25,25), min_performance=-1, partitioning={},\n starting_region=None, later_regions=None, buffer_region=None,\n named_regions={}, agents=['default'], agent_types={}, **etc):\n board_shape = _fix_random_values(board_shape)\n min_performance = _fix_random_values(min_performance)\n partitioning = _fix_random_values(partitioning)\n\n regions = make_partioned_regions(board_shape, **partitioning)\n board = np.zeros(board_shape, dtype=np.uint16)\n goals = np.zeros(board_shape, dtype=np.uint16)\n\n # Create locations for the player and the exit\n agent_locs, points_table, agent_names = add_agents_and_exit(\n board, regions, agents, agent_types)\n\n # and fill in the regions...\n for k in np.unique(regions)[2:]:\n mask = regions == k\n if starting_region is not None:\n region_name = _fix_random_values(starting_region)\n else:\n region_name = _fix_random_values(later_regions)\n if region_name not in named_regions:\n logger.error(\"No region parameters for name '%s'\", region_name)\n continue\n logger.debug(\"Making region: %s\", region_name)\n rboard, rgoals = populate_region(mask, named_regions[region_name])\n board += rboard\n goals += rgoals\n starting_region = None\n buffer_region = _fix_random_values(buffer_region)\n if buffer_region in named_regions:\n mask = regions == 0\n rboard, rgoals = populate_region(mask, named_regions[buffer_region])\n board += rboard\n goals += rgoals\n\n # Give the buffer (0) region a rainbow / white color\n # This is mostly a visual hint for humans\n buffer_mask = (regions <= 0) & (goals & CellTypes.rainbow_color == 0)\n goals[buffer_mask] += CellTypes.rainbow_color\n\n game = SafeLifeGame()\n game.deserialize({\n 'board': board,\n 'goals': goals,\n 'agent_locs': agent_locs,\n 'agent_names': agent_names,\n 'min_performance': min_performance,\n 'points_table': points_table,\n 'orientation': 1,\n })\n return game"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def generate(self):\n for i in range(4):\n random_first = randomize_first_box()\n self.randomize(random_first)\n for i in range(9):\n random_pos = randomize_position()\n self.randomize(random_pos)\n self.board.solve()","def draw_random_setup(types_available, team, game_dim):\n\n nr_pieces = len(types_available)-1\n types_available = [type_ for type_ in types_available if not type_ == 0]\n if game_dim == 5:\n row_offset = 2\n elif game_dim == 7:\n row_offset = 3\n else:\n row_offset = 4\n setup_agent = np.empty((row_offset, game_dim), dtype=object)\n if team == 0:\n flag_positions = [(game_dim-1, j) for j in range(game_dim)]\n flag_choice = np.random.choice(range(len(flag_positions)), 1)[0]\n flag_pos = game_dim-1 - flag_positions[flag_choice][0], game_dim-1 - flag_positions[flag_choice][1]\n setup_agent[flag_pos] = pieces.Piece(0, 0, flag_positions[flag_choice])\n\n types_draw = np.random.choice(types_available, nr_pieces, replace=False)\n positions_agent_0 = [(i, j) for i in range(game_dim-row_offset, game_dim) for j in range(game_dim)]\n positions_agent_0.remove(flag_positions[flag_choice])\n\n for idx in range(nr_pieces):\n pos = positions_agent_0[idx]\n setup_agent[(game_dim-1 - pos[0], game_dim-1 - pos[1])] = pieces.Piece(types_draw[idx], 0, pos)\n elif team == 1:\n flag_positions = [(0, j) for j in range(game_dim)]\n flag_choice = np.random.choice(range(len(flag_positions)), 1)[0]\n setup_agent[flag_positions[flag_choice]] = pieces.Piece(0, 1, flag_positions[flag_choice])\n\n types_draw = np.random.choice(types_available, nr_pieces, replace=False)\n positions_agent_1 = [(i, j) for i in range(row_offset) for j in range(game_dim)]\n positions_agent_1.remove(flag_positions[flag_choice])\n\n for idx in range(nr_pieces):\n pos = positions_agent_1[idx]\n setup_agent[pos] = pieces.Piece(types_draw[idx], 1, pos)\n return setup_agent","def generate(self, site_type='random', arg='random'):\n size = entities.world['size']\n if site_type == 'random':\n if randint(1,3) == 1:\n site_type = 'adventure'\n else:\n site_type = 'resource'\n elif site_type in ref.material_type_dct.keys():\n self.resource = site_type\n site_type = 'resource'\n terrain_list = None\n if arg == 'random':\n terrain_list = [x for x in ref.terrain_dct.keys() if type(x) == int]\n elif arg in ref.terrain_type_list:\n terrain_list = [\n x for x in ref.terrain_dct.keys() if ref.terrain_dct[x]['terrain type'] == arg\n ]\n x = randint(0, size-1)\n y = randint(0, size-1)\n terrain_type = entities.world['grid'][y][x]\n site_locations = [s.location for s in entities.sites['object list']]\n while terrain_type not in terrain_list or [x,y] in site_locations:\n x = randint(0, size-1)\n y = randint(0, size-1)\n terrain_type = entities.world['grid'][y][x]\n\n self.location = [x,y]\n self.structure = Structure().generate(\n ref.terrain_dct[terrain_type]['terrain type'], site_type\n )\n if self.resource == None:\n if 'resource type' in ref.structure_type_dct[\n self.structure.structure_type\n ].keys():\n resource_type = ref.structure_type_dct[\n self.structure.structure_type]['resource type'\n ]\n resource_possibilities = []\n for possible_material in [\n x for x in ref.material_class_dct[resource_type][\n 'types'] if 'rarity' in ref.material_type_dct[x].keys()\n ]:\n for x in xrange(ref.rarity_dct[\n ref.material_type_dct[possible_material]['rarity']\n ]):\n resource_possibilities.append(possible_material)\n self.resource = choice(resource_possibilities)\n #resources measured in grams\n if self.resource != None:\n self.harvestable = randint(100000, 1500000)\n try:\n entities.town['object'].resources[\n ref.material_type_dct[self.resource]['class']][\n self.resource]['harvestable'] += self.harvestable\n except KeyError:\n pass\n #NOTE: These numbers suitable for metal, may not be for other materials\n #NOTE: Mine production should be ~1kg pure metal per day per miner.\n #NOTE: IRL mine has ~43500kg before producing much less.\n \n self.set_site_id()\n return self","def gen_world(num_rows, num_cols):\n world = collections.deque()\n\n # Generate top perimeter.\n world.append([eg.ROCK] * num_cols)\n\n # In between top and bottom perimeters, generate a clean world.\n # (all non-perimeter cells are clear)\n for i in xrange(num_rows - 2):\n world.append([eg.ROCK] + ([eg.NONE] * (num_cols - 2)) + [eg.ROCK])\n\n # Generate bottom perimeter.\n world.append([eg.ROCK] * num_cols)\n\n # Apply red anthill in world.\n _randomly_apply_anthill(world, eg.RED)\n\n # Apply black anthill in world.\n _randomly_apply_anthill(world, eg.BLACK)\n\n # Apply food blocks in world.\n _randomly_apply_foodblob(world)\n\n # Apply rocks in world.\n _randomly_apply_rocks(world)\n\n world.appendleft([str(num_rows)])\n world.appendleft([str(num_cols)])\n\n return world","def generate_world(x_size, y_size):\n\n\tdef make_blank_world():\n\t\t\"\"\"\n\t\tCreates an x-by-y list of lists of zeroes.\n\t\t\"\"\"\n\t\tblank_array = [[Blank() for j in range(y_size + 1)] for i in range(x_size + 1)]\n\t\treturn blank_array\n\n\n\tdef check_surroundings(x_coord, y_coord, value):\n\t\t\"\"\"\n\t\tIf the variable world has already been defined, it checks all x and y coords within one square (aka, checks the 8 surrounding squares) for a given value. If that value is present in 1 or more squares, returns True; else, False.\n\t\t\"\"\"\n\t\tfor i in range(3):\n\t\t\tfor j in range(3):\n\t\t\t\texamining = world[x_coord - 1 + i][y_coord - 1 + j]\n\t\t\t\tif examining.name == value:\n\t\t\t\t\treturn True\n\t\t\t\telse:\n\t\t\t\t\tpass\n\t\treturn False\n\n\n\tworld = make_blank_world()\n\n\tworld[random.randint(2, x_size-2)][random.randint(2, y_size-2)] = Water()\n\n\tfor i in range(x_size):\n\t\tfor j in range(y_size):\n\t\t\tseed = random.random()\n\t\t\tif check_surroundings(i, j, 'water'):\n\t\t\t\tif seed >= 0.5:\n\t\t\t\t\tworld[i][j] = Water()\n\t\t\t\telif seed >= 0.4:\n\t\t\t\t\tworld[i][j] = Tree()\n\t\t\t\telse:\n\t\t\t\t\tworld[i][j] = Grass()\n\t\t\telif not check_surroundings(i, j, 'tree'):\n\t\t\t\tif seed >= 0.5:\n\t\t\t\t\tworld[i][j] = Tree()\n\t\t\t\telse:\n\t\t\t\t\tworld[i][j] = Grass()\n\t\t\telse:\n\t\t\t\tworld[i][j] = Grass()\n\treturn [row[:y_size+1] for row in world[:x_size+1]]","def make_board(self):\n generate = lambda: random.randint(1, 100) in range(1, self.p_pit+1)\n some_number = self.some_number\n agent = Agent(some_number)\n agent.program = Oozeplorer_Percept(agent)\n self.add_agent(agent)\n gold = Gold()\n self.add_thing(gold, None)\n for row in range(1, some_number + 1):\n for col in range(1, some_number + 1):\n valid_spot = (row, col) != gold.location and (row, col) != (1, 1)\n if valid_spot and generate():\n t_pt = Pit()\n t_pt.location = (row, col)\n self.things.append(t_pt)","def fill_with_random_tiles(self):\n for elem in [x[1] for x in self.tile_grid.values()]:\n self.view.remove(elem)\n tile_grid = {}\n # Fill the data matrix with random tile types\n while True: # Loop until we have a valid table (no imploding lines)\n for x in range(COLS_COUNT):\n for y in range(ROWS_COUNT):\n tile_type, sprite = choice(self.available_tiles), None\n tile_grid[x, y] = tile_type, sprite\n if len(self.get_same_type_lines(tile_grid)) == 0:\n break\n tile_grid = {}\n\n # Build the sprites based on the assigned tile type\n for key, value in tile_grid.items():\n tile_type, sprite = value\n sprite = self.tile_sprite(tile_type, self.to_display(key))\n tile_grid[key] = tile_type, sprite\n self.view.add(sprite)\n\n self.tile_grid = tile_grid","def generate_world(world_seed, biome_min, biome_max, w, h):\n\n while True:\n\n try:\n\n # Set the initial seed for the random module (random.seed())\n seed(world_seed)\n\n # Create a blank map (2D list filled with '0' strings\n world = [[0 for y in range(h)] for x in range(w)]\n # Generates the random values for the terrain construction\n terrain = [randrange(20) + 40 for _ in range(w)]\n\n #Empty biome map\n biomes = []\n\n #Generates biomes\n for __ in range(w//biome_min):\n\n #Biome at cursor\n biome_select = choice(list(biome_data))\n\n #Biomes size\n for _ in range(randint(biome_min, biome_max)):\n biomes.append(biome_select)\n\n #World size met\n if len(biomes) >= w:\n biomes = biomes[:w] #Truncate selection\n break\n\n\n # ----- Construct the Terrain\n # Counter that changes dynamically to check through all blocks in the terrain list\n cur_pos = 0\n # Runs through all the generated numbers in a while loop\n while cur_pos < w:\n\n # print(\".\", end=\"\")\n\n # Check to see if terrain gap is too large\n\n if abs(terrain[cur_pos] - terrain[cur_pos - 1]) > biome_data[str(biomes[cur_pos])][\"maxh\"]: # if terrain gap is larger than threshhold (too big)\n\n for n in range(randint(biome_data[str(str(biomes[cur_pos]))][\"minx\"], biome_data[str(str(biomes[cur_pos]))][\"maxx\"])):\n # Insert a new value into the terrain list between the values that are too far apart\n terrain.insert(cur_pos, (terrain[cur_pos] + terrain[cur_pos - 1]) // 2)\n\n else: # Difference between the two blocks is not too big\n\n # Check next block\n cur_pos += 1\n\n # ----- Transfer Terrain To Empty World\n # Run through every space in the empty world\n for x in range(len(world)): # runs through each level\n for y in range(len(world[x])): # runs through each individual space\n\n # Generates structures\n if y > terrain[x]:\n\n #Top layer\n if y - terrain[x] == 1:\n\n #Sets the layer with block specified in biome config\n world[x][y] = block_lookup[biome_data[biomes[x]][\"layer\"][\"top\"]]\n\n if randint(0, 10) == 0 and x + 10 < w:\n world = generate_structure(x, y - 1, world, choice(biome_data[biomes[x]][\"structure\"]))\n\n #Middle layer\n elif y - terrain[x] < randint(3, 8):\n world[x][y] = block_lookup[biome_data[biomes[x]][\"layer\"][\"middle\"]]\n\n #Base\n else:\n world[x][y] = block_lookup[biome_data[biomes[x]][\"layer\"][\"lower\"]]\n\n #Generate ores\n # Coal\n if 10 + terrain[x] > y > 5 + terrain[x] and randint(0, 200) == 0:\n for cluster in range(randint(3, 10)):\n world[x + randint(-4, 4)][y + randint(-4, 4)] = block_lookup[\"Coal Ore\"]\n\n # Iron\n if 30 + terrain[x] > y > 20 + terrain[x] and randint(0, 200) == 0:\n\n for cluster in range(randint(3, 6)):\n world[x + randint(-4, 4)][y + randint(-4, 4)] = block_lookup[\"Iron Ore\"]\n\n # Gold\n if 80 > y > 65 and randint(0, 400) == 0:\n for cluster in range(randint(3, 6)):\n world[x + randint(-4, 4)][y + randint(-4, 4)] = block_lookup[\"Gold Ore\"]\n\n # Diamonds\n if 80 > y > 70 and randint(0, 500) == 0:\n for cluster in range(randint(1, 5)):\n world[x + randint(-3, 3)][y + randint(-3, 3)] = block_lookup[\"Diamond Ore\"]\n\n # Bedrock\n if y > 92 or y > 87 and randint(0, 3) == 0:\n world[x][y] = block_lookup[\"Bed Rock\"]\n\n # Last edit, adding extras to the top of the world to prevent problems\n world = [[0] * 40 + x for x in world]\n\n # Return the world object for use\n return np.array(world)\n\n except:\n world_seed += '1'","def generatePiece(self):\n\n empty_tiles = []\n for y in range(BOARD_SIZE):\n for x in range(BOARD_SIZE):\n if self.grid[x][y].isEmpty():\n empty_tiles.append(self.grid[x][y])\n\n two_or_four = random.choice([2, 4])\n random.choice(empty_tiles).set(two_or_four)","def random_map(self, world):\n obstacles = []\n if self.cfg[\"obstacle\"][\"octagon\"][\"enabled\"]:\n obstacles += self.__generate_octagon_obstacles(world)\n if self.cfg[\"obstacle\"][\"rectangle\"][\"enabled\"]:\n obstacles += self.__generate_rectangle_obstacles(world)\n\n # update the current obstacles and goal\n self.current_obstacles = obstacles\n self.add_new_goal()\n\n # apply the new obstacles and goal to the world\n self.apply_to_world(world)","def random_place(board, player):\n available = possibilities(board)\n place(board, player, random.choice(available))","def generate(self, level):\n # TODO The dungeon's instances are spawned and loaded here.\n # fill map with \"blocked\" tiles\n level.maze = [[Tile(x, y, True) for y in range(level.height)] for x in range(level.width)]\n\n for r in range(level.max_rooms):\n # random width and height\n w = random.randint(level.min_room_size, level.max_room_size)\n h = random.randint(level.min_room_size, level.max_room_size)\n\n # random position without going out of the boundaries of the map\n x = random.randint(0, level.width - w - 1)\n y = random.randint(0, level.height - h - 1)\n\n # \"DungeonRoom\" class makes rectangles easier to work with\n new_room = Room(x, y, w, h)\n level.rooms.append(new_room)\n\n # run through the other rooms and see if they intersect with this one\n failed = False\n for other_room in level.rooms:\n if other_room is not new_room and new_room.intersect(other_room):\n failed = True\n break\n\n if not failed:\n # this means there are no intersections, so this room is valid\n\n # \"paint\" it to the map's tiles\n self._create_room(level, new_room)\n\n # center coordinates of new room, will be useful later\n new_x, new_y = new_room.center()\n\n if level.num_rooms > 0:\n # connect it to the previous room with a tunnel\n # center coordinates of previous room\n (prev_x, prev_y) = level.rooms[level.num_rooms - 1].center()\n\n # draw a coin (random number that is either 0 or 1)\n if random.randint(0, 1) == 1:\n # first move horizontally, then vertically\n self._create_h_tunnel(level, prev_x, new_x, prev_y)\n self._create_v_tunnel(level, prev_y, new_y, new_x)\n else:\n # first move vertically, then horizontally\n self._create_v_tunnel(level, prev_y, new_y, prev_x)\n self._create_h_tunnel(level, prev_x, new_x, new_y)\n\n # finally, append the new room to the list\n level.rooms.append(new_room)\n level.num_rooms += 1\n\n # connect them with a tunnel\n self._create_h_tunnel(level, 25, 55, 23)","def generate_mine_map(width=30, height=16, num_mines=99):\n\n if num_mines > width * height:\n print(\"The number of mines exceeds the size of the board.\")\n return\n \n mine_map = [[False for i in range(width)] for j in range(height)]\n mines = 0\n while mines < num_mines:\n x = random.randint(0, width-1)\n y = random.randint(0, height-1)\n if not mine_map[y][x]:\n mine_map[y][x] = True\n mines += 1\n\n return mine_map","def generate_grains(self, cells):\n\t\tfor cell_num in range(cells):\n\t\t\trandom_row = random.randrange(0,self.space.shape[0],1)\n\t\t\tsample_cell = np.random.choice(self.space[random_row],1)\n\t\t\tsample_cell = sample_cell[0]\n\t\t\twhile sample_cell.state != 0:\n\t\t\t\trandom_row = random.randrange(0,self.space.shape[0],1)\n\t\t\t\tsample_cell = np.random.choice(self.space[random_row],1)\n\t\t\t\tsample_cell = sample_cell[0]\n\t\t\tsample_cell.change_state(self.init_time ,cell_num)","def new_tile(self):\r\n # replace with your code\r\n empty_square_lists = []\r\n for row in range(self._grid_height):\r\n for col in range(self._grid_width):\r\n if(self.get_tile(row, col) == 0):\r\n empty_square_lists.append((row, col))\r\n \r\n if len(empty_square_lists) == 0:\r\n return \"game over!\"\r\n \r\n random_cell = random.choice(empty_square_lists)\r\n random_cell_row = random_cell[0]\r\n random_cell_col = random_cell[1]\r\n \r\n values = [2] * 90 + [4] * 10\r\n value = random.choice(values)\r\n \r\n self.set_tile(random_cell_row, random_cell_col, value)","def new_tile(self):\n while True:\n random_row = random.randrange(self._grid_height)\n random_column = random.randrange(self._grid_width)\n if self._grid[random_row][random_column] == 0:\n self._grid[random_row][random_column] = random.choice([2] * 9 + [4])\n break","def new_tile(self):\r\n random_row = random.randrange(0, self._grid_height)\r\n random_col = random.randrange(0, self._grid_width)\r\n random_choice = random.choice([2]*90 + [4] * 10)\r\n \r\n if 0 in [num for elem in self._cells for num in elem]: \r\n if self._cells[random_row][random_col] == 0:\r\n self._cells[random_row][random_col] = random_choice \r\n else:\r\n self.new_tile()\r\n else:\r\n pass","def random_grid(height, width):\n grid = create_grid(height, width)\n for r in range(1, height - 1):\n for c in range(1, width - 1):\n grid[r][c] = random.choice([0, 1])\n return grid","def _generate_building(self, min_size, max_size, modulo_rest=2, name=None, one_connection=False):\n size_x = random.randint(min_size[0], max_size[0])\n size_y = random.randint(min_size[1], max_size[1])\n if modulo_rest < 2:\n while size_x % 2 != modulo_rest:\n size_x = random.randint(min_size[0], max_size[0])\n while size_y % 2 != modulo_rest:\n size_y = random.randint(min_size[1], max_size[1])\n return TownRegion._Building((size_x, size_y), name=name, one_connection=one_connection)","def randomCells(width, height):\r\n\tA = createBoard(height, width)\r\n\r\n\tfor row in range(height):\r\n\t\tfor col in range(width):\r\n\t\t\tif row > 0 and row < height-1:\r\n\t\t\t\tif col > 0 and col < width-1:\r\n\t\t\t\t\tA[row][col] = random.choice([0,1]) \r\n\r\n\treturn A","def randomSchedule(self,contents):\n\t\timport random as ran\n import copy\n\t\tcontents_copy = copy.deepcopy(contents)\n\t\tsol = Area('sb',ran.random())\n\t\twhile contents_copy:\n\t\t\tcont = ran.choice(contents_copy)\n\t\t\ti = 0\n\t\t\twhile True:\n\t\t\t\tran_waiting = ran.randint(0,2)\n\t\t\t\tran_start = ran.randint(0,19)\n\t\t\t\tif sol.checkAddContent(ran_waiting,ran_start,cont):\n\t\t\t\t\tsol.addContent(ran_waiting,ran_start,cont)\n\t\t\t\t\tcontents_copy.remove(cont)\n\t\t\t\t\tbreak\n\t\t\t\ti += 1\n\t\t\t\tif i>150:\n\t\t\t\t\t#print \"cut\"\n\t\t\t\t\tsol = Area('sb',ran.random())\n\t\t\t\t\tcontents_copy = contents[:]\n\t\t\t\t\tbreak\n\t\t#print \"generate new schedule\\n\",sol.printSchedule()\n\t\treturn sol","def random_world():\n # Create empty world\n grid = np.zeros((WORLD_WIDTH, WORLD_WIDTH))\n # Add dirt and obstacles\n for r in range(WORLD_WIDTH):\n for c in range(WORLD_WIDTH):\n if random.random() < 0.5:\n grid[r, c] = DIRT\n elif random.random() < 0.1:\n grid[r, c] = OBSTACLE\n # Place agent\n while True:\n r = random.randrange(WORLD_WIDTH)\n c = random.randrange(WORLD_WIDTH)\n if grid[r, c] == EMPTY:\n return grid, r, c","def trial(length, height):\n screen.refresh()\n global stimList\n global oddLength\n global oddHeight\n currentLength = int(maxLength / 4)\n currentHeight = int(maxHeight / 4)\n for i in range(stimAmt):\n if i == oddLocation:\n oddLength = currentLength\n oddHeight = currentHeight\n stimList.append(\n pg.draw.rect(\n screen.fg,\n PgTools.rand_color(),\n (currentLength, currentHeight, length, height,),\n )\n )\n PgTools.rand_pattern(\n screen.fg,\n (\n currentLength,\n currentHeight,\n ),\n (length, height),\n i=(randint(0, 2), randint(0, 1)),\n )\n if randShapes:\n PgTools.rand_shape(screen.fg, (currentLength, currentHeight),(length, height), oddSeed)\n else:\n stimList.append(\n pg.draw.rect(\n screen.fg,\n color,\n (currentLength, currentHeight, length, height,),\n )\n )\n PgTools.rand_pattern(\n screen.fg,\n (\n currentLength,\n currentHeight,\n ),\n (length, height),\n patColor,\n randNums,\n )\n if randShapes:\n PgTools.rand_shape(screen.fg, (currentLength, currentHeight),(length, height), regSeed)\n currentLength += maxLength / 4\n currentLength = int(currentLength)\n if (i + 1) % 3 == 0:\n currentLength = maxLength / 4\n currentLength = int(currentLength)\n currentHeight += maxHeight / 4\n currentHeight= int(currentHeight)","def generate(self, n_enemies, n_blocks):\n self.create_map()\n self.create_floor()\n self.player = self.create_player_at(0, 0)\n self.create_dummy_obj_at(0, 1)\n self.create_dummy_obj_at(1, 0)\n self.create_soft_block_at(0, 2)\n self.create_soft_block_at(2, 0)\n self.create_hard_blocks() \n self.create_enemies(n_enemies)\n self.create_soft_blocks(n_blocks) \n self.clear_dummy_obj()","def generateTestProblem(printTerrain = False):\r\n size = random.randint(5, 100)\r\n print(size)\r\n start = (random.randint(0, size - 1), random.randint(0, size - 1))\r\n print(start)\r\n goal = (random.randint(0, size - 1), random.randint(0, size - 1))\r\n print(goal)\r\n terrain = [[random.choice(['m', 'p', 's', 'w']) for i in range(0, size)] for j in range(0, size)]\r\n\r\n # print the terrain matrix if required\r\n if printTerrain:\r\n for i in range(0, size):\r\n print(terrain[i])\r\n\r\n return (start, goal, terrain)","def initialize_puzzle_board(self, n=3, hType=1, random=True, diff=None):\r\n\t\tself.n = n\r\n\r\n\t\t# While loop to continuously create random boards until a solvable one is made.\r\n\t\tboardList = [x for x in range(n**2)]\r\n\t\twhile random:\r\n\t\t\tshuffle(boardList)\r\n\r\n\t\t\tif self.generated_solvable(boardList):\r\n\t\t\t\tprint \"Found something solvable:\", boardList\r\n\t\t\t\tbreak # From outer While-True\r\n\r\n\t\t# If statements to use non-random, burnt-in boards of various difficulties.\r\n\t\tif not random and n == 3:\r\n\t\t\tif diff == 0:\r\n\t\t\t\tboardList = [3,1,2,4,7,5,6,8,0]\r\n\t\t\telif diff == 1:\r\n\t\t\t\tboardList = [3,2,5,4,1,8,6,0,7]\r\n\t\t\telif diff == 2:\r\n\t\t\t\tboardList = [1,0,6,5,7,4,2,3,8]\r\n\r\n\t\telif not random and n == 4:\r\n\t\t\tif diff == 0:\r\n\t\t\t\tboardList = [4,1,2,3,5,0,6,7,8,9,10,11,12,13,14,15]\r\n\r\n\t\t# Location of 0 (the empty tile) in the flat list.\r\n\t\tlocZero = boardList.index(0)\r\n\r\n\t\t# Using floor division and modulo to attain the nested location of the 0\r\n\t\tself.x = locZero // self.n\r\n\t\tself.y = locZero % self.n\r\n\r\n\t\t# Looping over the flat list and appending it, creating the nested list that is the final board\r\n\t\tfor i in range(self.n):\r\n\t\t\ti1, i2 = self.n*i, self.n*(i+1)\r\n\t\t\tself.board.append(boardList[i1:i2])\r\n\r\n\t\t# Double checking that we determined 0's position correctly.\r\n\t\tassert( self.board[self.x][self.y] == 0 )\r\n\r\n\t\t# Generate the goal (class variable) for the board based on size\r\n\t\tself.generate_goal()\r\n\t\t# Generates the heuristic value for this first board.\r\n\t\tself.generate_heuristic()\r\n\t\t# Generates the hash value for __eq__ from the board.\r\n\t\tself.eqHash = hash(str(self))","def make_random_move(self):\n choice = None\n options = []\n #generate full moves list\n for i in range(self.width):\n for j in range(self.height):\n #make sure move has not been made\n if (i,j) not in self.moves_made:\n #make sure move is not a mine\n if (i,j) not in self.mines:\n options.append((i,j))\n #if there are no options, return None\n if len(options) == 0:\n return None\n\n #pick a random option from generated list\n choice = random.choice(options)\n return choice\n\n \"\"\"\n For kicks and giggles I wrote this extra bit to determine a\n rough intuitive probability for each option based on the knowledge\n base, so rather than picking a choice randomly the AI can choose\n the option that is, at least intuitively, least likely to blow up.\n Better to take the 1/8 chance than the 1/3 chance, right?\n \"\"\"\n best_chance = 1\n #iterate through generated options\n for option in options:\n #Could set chance to 1/8, but the AI wouldn't actually know that. I\n #only know it because I can read the code...But for the purposes of this\n #drill we'll say the AI doesn't know how many bombs are placed.\n #Better then to pick a square we know nothing about than one that\n #has a 1/8 chance of exploding. Gather more information that way.\n chance = 0\n for sentence in self.knowledge:\n #look to see if current option is in sentences\n if option in sentence.cells:\n #use sentence count and length of cell set to calculate probability\n prob = sentence.count / len(sentence.cells)\n if prob > chance:\n #Looking for the highest explosive probability for this square\n chance = prob\n if chance < best_chance:\n #If this option has lower odds of exploding than current best, it becomes\n #the optimal\n best_chance = chance\n choice = option\n\n #return choice","def randomCells(w, h):\n A = createBoard(w, h)\n\n for row in range(1, h-1):\n for col in range(1, w-1):\n if random.choice([0, 1]) == 1:\n A[row][col] = 1\n else:\n A[row][col] = 0\n return A","def build_world(self):\n total_reward_prob = 0.0 # Total probability of any type of reward\n probs_list = [] # List of reward probabilities\n \n # We want to create a list of reward probabilities for numpy's choice method\n for r in self.rewards:\n probs_list.append(r.prob)\n total_reward_prob += r.prob\n probs_list.append(1.0-total_reward_prob) # Add in the probability of no reward\n \n \n self.world_rewards = [] # Will hold all rewards for this game\n for y in range(self.world_height):\n row_rewards = []\n for x in range(self.world_width):\n # Given a probability for each reward (including None), select a reward for each cell\n cell = np.random.choice(self.rewards + [None], p=probs_list)\n row_rewards.append(cell)\n self.world_rewards.append(row_rewards)","def make_board(self):\n http = urllib3.PoolManager()\n r = http.request('GET', 'http://www.cse.msu.edu/~ruppmatt/itm891/tiles.pickle')\n tiles = pickle.loads(r.data)\n self.assets = tiles\n self.gameboard = Image.new('RGBA', (64*(self.world_width+2), 64*(self.world_height+2)))\n # Laydown land\n for c in range(0,self.world_width):\n for r in range(0, self.world_height):\n x = (c+1)*64\n y = (r+1)*64\n tile_ndx = np.random.choice(len(tiles['land']))\n self.gameboard.paste(tiles['land'][tile_ndx], (x,y)) \n # Laydown water\n for c in range(0,self.world_width):\n x = (c+1)*64\n yy = (self.world_height+1)*64\n self.gameboard.paste(tiles['water']['edge_north'], (x,0))\n self.gameboard.paste(tiles['water']['edge_south'], (x, yy))\n for r in range(0,self.world_height):\n y = (r+1)*64\n xx = (self.world_width+1)*64\n self.gameboard.paste(tiles['water']['edge_west'], (0,y))\n self.gameboard.paste(tiles['water']['edge_east'], (xx,y))\n self.gameboard.paste(tiles['water']['corner_nw'], (0,0))\n self.gameboard.paste(tiles['water']['corner_sw'], (0,(self.world_height+1)*64))\n self.gameboard.paste(tiles['water']['corner_ne'], ((self.world_width+1)*64,0))\n self.gameboard.paste(tiles['water']['corner_se'], ((self.world_width+1)*64,(self.world_height+1)*64))\n \n # Some land lines\n draw = ImageDraw.Draw(self.gameboard)\n for c in range(0,self.world_width-1):\n y_1 = 64\n y_2 = 64*(self.world_height+1)\n x = (2+c)*64\n draw.line([(x,y_1),(x,y_2)], fill='white', width=1)\n for r in range(0,self.world_height-1):\n y = (2+r)*64\n x_1= 64\n x_2 = 64 * (self.world_width+1)\n draw.line([(x_1,y),(x_2,y)], fill='white', width=1)\n return","def random_cells(w, h):\n a = create_board(w, h)\n\n for row in range(h):\n for col in range(w):\n if 0 < row < h - 1 and 0 < col < w - 1:\n a[row][col] = random.choice([0, 1])\n else:\n a[row][col] = 0\n \n return a","def create_room(self):\n # iterate through array of room types\n rooms = []\n prob_block_5_list = []\n prob_block_6_list = []\n\n for row in self.room_type:\n for col in row:\n rooms.append(self.import_template(col))\n # iterate through rooms to fill screen\n # this number will be part of how we find location of top left corner of room\n # based on 5x5 grid of rooms\n for pos in range(25):\n # this will iterate through the number of columns in array\n # the number y will be part of how we find where to place the block on the y axis (according to pygame.draw)\n for y in range(self.blocks_per_room_y):\n # this will iterate through the number of rows in array\n # the number x will be part of how we find where to place the block on the x axis (according to pygame.draw)\n for x in range(self.blocks_per_room_x):\n # if cell is a 1 add a platform sprite\n if rooms[pos][y][x] is 1:\n #check if platform has another above it for graphics\n if rooms[pos][y - 1][x] in (0, 3, 4, 7) and y - 1 >= 0:\n # the cases checked in each of these conditionals are the basic case that check surrounding blocks\n # to see what platform we should be using, the edge cases, such as if a block is at the edge of\n # the room, in which case we need to check the neighboring room (array in this case)\n\n #check conditions to see if we are using the sprite with with rounded edges on the bottom right and top right\n if ((y + 1) < self.blocks_per_room_y and (x - 1) >= 0 and (x + 1) < self.blocks_per_room_x\n and rooms[pos][y + 1][x] is 0 and rooms[pos][y][x + 1] is 0 and rooms[pos][y][x - 1] is 1)\\\n or (x is self.blocks_per_room_x - 1 and y < self.blocks_per_room_y - 1 and pos < 24 and rooms[pos][y + 1][x] is 0 and rooms[pos + 1][y][0] is 0)\\\n or (y is self.blocks_per_room_y - 1 and x < self.blocks_per_room_x - 1 and pos < 20 and rooms[pos][y][x + 1] is 0):\n block = Platform(self.block_width, self.block_height, 'right', self.theme)\n #check conditionals to see if we are using the sprite with rounded edges on the bottom left and top left\n elif ((y + 1) < self.blocks_per_room_y and (x - 1) >= 0 and (x + 1) < self.blocks_per_room_x\n and rooms[pos][y + 1][x] is 0 and rooms[pos][y][x - 1] is 0 and rooms[pos][y][x + 1] is 1)\\\n or (x is 0 and y < self.blocks_per_room_y - 1 and pos > 0 and rooms[pos][y + 1][x] is 0 and rooms[pos - 1][y][self.blocks_per_room_x - 1] is 0) \\\n or (y is self.blocks_per_room_y - 1 and x > 0 and pos < 20 and rooms[pos][y][x - 1] is 0):\n block = Platform(self.block_width, self.block_height, 'left', self.theme)\n #check conditionals to see if we are using the sprite with the rounded corners on top left and top right\n elif ((x + 1) < self.blocks_per_room_x and (x - 1) >= 0 and rooms[pos][y][x + 1] in (0, 3, 4) and rooms[pos][y][x - 1] in (0, 3, 4))\\\n or (x is 0 and pos > 0 and rooms[pos - 1][y][self.blocks_per_room_x - 1] in (0, 3, 4) and rooms[pos][y][x + 1] in (0, 3, 4))\\\n or (x is self.blocks_per_room_x - 1 and pos < 24 and rooms[pos + 1][y][0] in (0, 3, 4) and rooms[pos][y][x - 1] in (0, 3, 4)):\n block = Platform(self.block_width, self.block_height, 'round top', self.theme)\n #check conditionals to see if we are using the sprite with the rounded corner in the top left\n elif ((y + 1) < self.blocks_per_room_y and (x - 1) >= 0 and (x + 1) < self.blocks_per_room_x\n and rooms[pos][y + 1][x] is 1 and rooms[pos][y][x - 1] is 0 and rooms[pos][y][x + 1] is 1) \\\n or (x is 0 and y < self.blocks_per_room_y - 1 and pos > 0 and rooms[pos][y + 1][x] is 1 and rooms[pos - 1][y][self.blocks_per_room_x - 1] is 0) \\\n or (y is self.blocks_per_room_y - 1 and x > 0 and pos < 20 and rooms[pos][y][x - 1] is 0):\n block = Platform(self.block_width, self.block_height, 'top left', self.theme)\n #check conditionals to see if we are using the sprite with the rounded corner in the top right\n elif ((y + 1) < self.blocks_per_room_y and (x - 1) >= 0 and (x + 1) < self.blocks_per_room_x\n and rooms[pos][y + 1][x] is 1 and rooms[pos][y][x + 1] is 0 and rooms[pos][y][x - 1] is 1)\\\n or (x is self.blocks_per_room_x - 1 and y < self.blocks_per_room_y - 1 and pos < 24 and rooms[pos][y + 1][x] is 0 and rooms[pos + 1][y][0] is 0)\\\n or (y is self.blocks_per_room_y - 1 and x < self.blocks_per_room_x - 1 and pos < 20 and rooms[pos][y][x + 1] is 0):\n block = Platform(self.block_width, self.block_height, 'top right', self.theme)\n else:\n block = Platform(self.block_width, self.block_height, 'top', self.theme)\n else:\n block = Platform(self.block_width, self.block_height, 'middle', self.theme)\n coord_x = self.block_width + (pos % 5) * self.room_side_length_x + x * self.block_width\n block.rect.x = coord_x\n block.rect.y = self.block_height + (pos // 5) * self.room_side_length_y + y * self.block_height\n block.player = self.player\n self.platform_list.add(block)\n #if the space above this block is empty see if we spawn an enemy on the spot above current block\n if rooms[pos][y-1][x] is 0 and y - 1 >= 0:\n self.enemy_generation(coord_x, self.block_height + (pos // 5) * self.room_side_length_y + (y - 1) * self.block_height)\n # if the cell is a 3 then it will be an item pickup\n elif rooms[pos][y][x] is 3:\n rand = random.randrange(0, 4)\n if rand == 0:\n #calculate coordinates of the bag\n bag = pickupSprite('rope')\n # print('width = ' + str(self.block_width) + ' height = ' + str(self.block_height))\n bag.rect.x = self.block_width + (pos % 5) * self.room_side_length_x + x * self.block_width\n bag.rect.y = self.block_height + (pos // 5) * self.room_side_length_y + y * self.block_height\n bag.player = self.player\n self.bagGroup.add(bag)\n elif rand == 1:\n #calculate coordinates of the bag\n bag = pickupSprite('knife')\n # print('width = ' + str(self.block_width) + ' height = ' + str(self.block_height))\n bag.rect.x = self.block_width + (pos % 5) * self.room_side_length_x + x * self.block_width\n bag.rect.y = self.block_height + (pos // 5) * self.room_side_length_y + y * self.block_height\n bag.player = self.player\n self.bagGroup.add(bag)\n elif rand == 2:\n bag = pickupSprite('health')\n bag.rect.x = self.block_width + (pos % 5) * self.room_side_length_x + x * self.block_width\n bag.rect.y = self.block_height + (pos // 5) * self.room_side_length_y + y * self.block_height\n bag.player = self.player\n self.bagGroup.add(bag)\n\n\n # if the cell is a 4 then it will be either a spike, if the space is on the bottom of the room,\n # otherwise it is a randomized block or nothing\n elif rooms[pos][y][x] is 4:\n # if the cell is at the bottom of the level, randomly choose whether to place a spike or not\n rand = random.randrange(0, 3)\n rand2 = random.randrange(0, 2)\n if y is 6 and rand is 1:\n spike = enemies.Spikes()\n spike.rect.x = self.block_width + (pos % 5) * self.room_side_length_x + x * self.block_width\n spike.rect.y = self.block_height + (pos // 5) * self.room_side_length_y + y * self.block_height\n spike.player = self.player\n self.enemy_list.add(spike)\n # elif y is 6 and rand is 2:\n # dart = enemies.Darts(self.theme, 'up')\n # dart.rect.x = self.block_width + (pos % 5) * self.room_side_length_x + x * self.block_width\n # dart.rect.y = self.block_height + (pos // 5) * self.room_side_length_y + y * self.block_height\n # dart.player = self.player\n # self.enemy_list.add(dart)\n elif y != 6 and rand2 is 0:\n if rooms[pos][y - 1][x] is 0:\n block = Platform(self.block_width, self.block_height, 'top', self.theme)\n else:\n block = Platform(self.block_width, self.block_height, 'middle', self.theme)\n block.rect.x = self.block_width + (pos % 5) * self.room_side_length_x + x * self.block_width\n block.rect.y = self.block_height + (pos // 5) * self.room_side_length_y + y * self.block_height\n block.player = self.player\n self.platform_list.add(block)\n elif y != 6 and rand2 is 1:\n if x-1 >= 0 and x+1 <= self.blocks_per_room_x and y-1 >= 0 and y+1 < self.blocks_per_room_y:\n if rooms[pos][y][x-1] is 0:\n direction = 'left'\n blockType = 'middle'\n elif rooms[pos][y][x+1] is 0:\n direction = 'right'\n blockType = 'middle'\n elif rooms[pos][y-1][x] is 0:\n direction = 'up'\n blockType = 'top'\n elif rooms[pos][y+1][x] is 0:\n direction = 'down'\n blockType = 'middle'\n else:\n direction = None\n if direction is not None:\n # use for both block and dart\n rectX = self.block_width + (pos % 5) * self.room_side_length_x + x * self.block_width\n rectY = self.block_height + (pos // 5) * self.room_side_length_y + y * self.block_height\n\n block = Platform(self.block_width, self.block_height, blockType, self.theme)\n block.rect.x = rectX\n block.rect.y = rectY\n block.player = self.player\n self.platform_list.add(block)\n\n dart = enemies.Darts(self.theme, direction)\n dart.rect.x = rectX\n dart.rect.y = rectY\n dart.player = self.player\n self.enemy_list.add(dart)\n # this is the starting and ending points of the level\n elif rooms[pos][y][x] is 7:\n # exit of the game on the top row of the level\n if pos // 5 is 0:\n #calculate coordinates of the exit\n self.exit_coords['x'] = self.block_width + (pos % 5) * self.room_side_length_x + x * self.block_width\n self.exit_coords['y'] = self.block_height + (pos // 5) * self.room_side_length_y + y * self.block_height\n exit = exit_door_sprite(self.block_width, self.block_height)\n # print('width = ' + str(self.block_width) + ' height = ' + str(self.block_height))\n exit.rect.x = self.exit_coords['x']\n exit.rect.y = self.exit_coords['y']\n exit.player = self.player\n self.exit_sprite.add(exit)\n #entance of the game on the bottom row of the level\n elif pos // 5 is 4:\n #calculate coordinates of the entrance\n self.entrance_coords['x'] = self.block_width + (pos % 5) * self.room_side_length_x + x * self.block_width\n self.entrance_coords['y'] = self.block_height + (pos // 5) * self.room_side_length_y + y * self.block_height","def generate_board(self):\n random.seed(self.seed)\n for row in self.grid:\n for column in row:\n probability = random.random()\n if self.live_probability > probability:\n column.set_alive()","def create_random_heads_or_tails(sheet, columns):\r\n\r\n use_column = 0\r\n row = 1\r\n for i in range(64):\r\n column = columns[use_column]\r\n row = row\r\n\r\n sheet[column + str(row)] = random.randint(0, 1) # assigns 0 or 1 randomly for each cell\r\n\r\n if use_column == 7: # stops and resets column count\r\n use_column = 0\r\n row += 1\r\n else: # increases column\r\n use_column += 1\r\n\r\n print('All coins have been randomly assigned.')","def _draw_random_turn_params(self):\n return TurnParams(\n main_corridor_length=self._rng.uniform(10, 16),\n turn_corridor_length=self._rng.uniform(4, 12),\n turn_corridor_angle=self._rng.uniform(-3./8. * np.pi, 3./8.*np.pi),\n main_corridor_width=self._rng.uniform(0.5, 1.5),\n turn_corridor_width=self._rng.uniform(0.5, 1.5),\n flip_arnd_oy=bool(self._rng.rand() < 0.5),\n flip_arnd_ox=bool(self._rng.rand() < 0.5),\n rot_theta=self._rng.uniform(0, 2*np.pi)\n )","def new_tile(self):\r\n count = 0\r\n tot_count = self.get_grid_width() * self.get_grid_height()\r\n\r\n while count < 2 and tot_count > 0:\r\n # my_list = 4 10% of the time and a 2 90%\r\n my_list = [4] * 10 + [2] * 90\r\n new_tile = random.choice(my_list)\r\n\r\n # Selects a random number from 0 to width * height -1\r\n\r\n spot = random.randint(0, self._grid_height * self._grid_width - 1)\r\n\r\n # sets location to random selection from spot\r\n loc = [spot / self._grid_width, spot % self._grid_width]\r\n # if loc is empty ( == 0 ) sets number, else repeats process.\r\n\r\n if self._board[loc[0]][loc[1]] == 0:\r\n # sets radom selected board tile to new_tile number\r\n self._board[loc[0]][loc[1]] = new_tile\r\n count += 1\r\n tot_count -= 1","def init_board(rows, columns, method=\"random\"):\n if method == \"random\":\n board = np.random.random_integers(2, size=(rows, columns)) - 1\n return board","def new_tile(self):\r\n # replace with your code\r\n # complete search ....\r\n non_zero_count = 0;\r\n for row in range(self._grid_height):\r\n for col in range(self._grid_width):\r\n if self._grid_tile[row][col] == 0:\r\n non_zero_count += 1\r\n random_choice = random.randrange(0, non_zero_count)\r\n count = 0\r\n # another search ....\r\n generated_new_tile = False\r\n for row in range(self._grid_height):\r\n for col in range(self._grid_width):\r\n if generated_new_tile == False and self._grid_tile[row][col] == 0:\r\n if count != random_choice:\r\n count += 1 \r\n else:\r\n if random.randrange(0,100) < 10:\r\n self.set_tile(row, col ,4)\r\n else:\r\n self.set_tile(row, col ,2)\r\n generated_new_tile = True","def new_tile(self):\n col = random.choice(range(self.grid_width))\n row = random.choice(range(self.grid_height))\n if self.grid[row][col] == 0:\n if random.random() >= 0.9:\n self.grid[row][col] = 4\n else:\n self.grid[row][col] = 2\n else:\n self.new_tile()","def random_strategy(player, board):\n return random.choice(Othello.legal_moves(player, board))","def genRandTeam(nPos, totPlayers):\n # 0 1 2 3 4 5 6\n # nPos = [nFirst, nSecond, nThird, nShort, nCatcher, nOf, nDh]\n chromosome = []\n sum = 0\n count = 0\n\n\n for i in nPos: # general loop\n if count == 6: # when loop enters the nDh players it instead chooses from ALL positions five times\n for j in range(5): # to represent the 2 util positions and the 3 benches\n rNum = random.randint(0, totPlayers - 1) # random number of ANY player\n chromosome.append(rNum) # picks a random pos\n break # no more work needs to be done\n if count == 5: # this will occur before the previous loop; nOF must be iterated 3 times for 3 outfield spots\n for j in range(2):\n rNum2 = random.randint(0, i - 1)\n chromosome.append(rNum2 + sum) # nOF must be iterated 3 times for 3 outfield spots; i is on oF\n rNum3 = random.randint(0, i - 1)\n chromosome.append(rNum3 + sum)\n sum += i\n count += 1\n # first = random.randint(0,nPos[0])\n # second = random.randint(0,nPos[1])\n # third = random.randint(0,nPos[2])\n # short = random.randint(0,nPos[3])\n # catcher = random.randint(0,nPos[4])\n # of = [random.randint(0,nPos[5]), random.randint(0,nPos[5]), random.randint(0,nPos[5])] #THREE outfielders\n # rNum = [random.randint(0,6) for i in range(5)] #random numbers representing one of the nPos rosters\n # util = [random.randint(0,nPos[rNum[0]]), random.randint(0,nPos[rNum[1]])] #picks 2 random players from ANY roster\n # ben = [random.randint(0,nPos[rNum[2]]), random.randint(0,nPos[rNum[3]]), random.randint(0,nPos[rNum[4]])] # picks 3 random players form any roster\n # print first,second,third,short,catcher,of,util,ben\n # temp = Team()\n return chromosome","def test_initialization(number: int) -> None:\n for _ in range(number):\n if random.random() < 0.5:\n size = random.randint(3, 10)\n baby_position = [random.randint(0, size - 1), random.randint(0, size - 1)]\n num_berries = random.randint(1, size)\n else:\n size = [random.randint(3, 10), random.randint(3, 10)]\n baby_position = [\n random.randint(0, size[0] - 1),\n random.randint(0, size[1] - 1),\n ]\n num_berries = random.randint(1, size[0])\n print(f\"\\n\\n\\nSize of the board {size}\")\n print(f\"Baby position: {baby_position}\")\n print(f\"Number of berries to be placed randomly: {num_berries}\")\n game = Game(size, baby_position, 0, 0, 0, 0, num_berries)\n print(f\"Here is the board:\\n{game.get_board()}\")\n print(game.get_baby())\n for b in game.get_berries():\n print(b)","def new_tile(self):\r\n # creating a list value to ensure the 90 and 10 percent ratio\r\n value=[2,2,2,2,2,2,2,2,2,2]\r\n position_of_4=random.randrange(0,10)\r\n value[position_of_4]=4\r\n # selecting a random position on the grid\r\n dummy_row=random.randrange(0,self._height)\r\n dummy_column=random.randrange(0,self._width)\r\n # check to ensure that same tiles are not selected\r\n if self._grid[dummy_row][dummy_column]!=0:\r\n while self._grid[dummy_row][dummy_column]!=0:\r\n dummy_row=random.randrange(0,self._height)\r\n dummy_column=random.randrange(0,self._width)\r\n # assigning a value to the selected tile\r\n self._grid[dummy_row][dummy_column]=random.choice(value)","def generate():\n global BOARD\n next = [[0] * ROWS for _ in range(COLS)]\n # Loop through every spot in our 2D array and check spots neighbors\n for x in range(COLS):\n for y in range(ROWS):\n # Add up all the states in a 3x3 surrounding grid\n neighbors = 0\n for i in range(-1, 2):\n for j in range(-1, 2):\n nx = (x + i + COLS) % COLS\n ny = (y + j + ROWS) % ROWS\n neighbors += BOARD[nx][ny]\n # A little trick to subtract the current cell's state since\n # we added it in the above loop\n neighbors -= BOARD[x][y]\n # Rules of Life\n if BOARD[x][y] == 1 and neighbors < 2 : next[x][y] = 0 # Loneliness\n elif BOARD[x][y] == 1 and neighbors > 3 : next[x][y] = 0 # Overpopulation\n elif BOARD[x][y] == 0 and neighbors == 3: next[x][y] = 1 # Reproduction\n else: next[x][y] = BOARD[x][y] # Stasis\n # Next is now our board\n BOARD = next","def randomLeggings():\n return random.choice(LEGGINGS)","def stage_1_generator(option):\n # Stage Size + Player Starting Position\n STAGE_1 = ([10,10], [1,1])\n\n # Non-Ocean tiles\n STAGE_1_TILES = { \n \"1,2\":\"rock\",\n \"1,3\":\"mountain\",\n \"2,4\":\"rock\",\n \"2,7\":\"rock\",\n \"2,8\":\"rock\",\n \"3,3\":\"rock\",\n \"3,4\":\"rock\",\n \"3,8\":\"mountain\",\n \"3,9\":\"rock\",\n \"3,10\":\"rock\",\n \"4,4\":\"rock\",\n \"4,5\":\"mountain\",\n \"5,6\":\"rock\",\n \"6,1\":\"rock\",\n \"6,2\":\"rock\",\n \"6,7\":\"rock\",\n \"6,10\":\"rock\",\n \"7,1\":\"rock\",\n \"7,2\":\"rock\",\n \"7,6\":\"rock\",\n \"7,10\":\"rock\",\n \"8,5\":\"rock\",\n \"8,6\":\"rock\",\n \n \"8,10\":\"rock\",\n \"9,1\":\"sign\",\n \"9,3\":\"rock\",\n \"9,4\":\"rock\",\n \"9,9\":\"rock\",\n \"9,10\":\"rock\",\n \"10,1\":\"cave\",\n \"10,3\":\"rock\",\n \"10,4\":\"cave\",\n \"10,8\":\"rock\",\n \"10,9\":\"rock\",\n \"10,10\":\"rock\",\n \n \"1,10\":\"end\",\n }\n\n # Special Tiles that trigger an event\n STAGE_1_SPECIAL = { \n \"1,10\":\"end\",\n \"9,1\":\"sign_cave\",\n \"10,1\":\"cave_entrance_1\",\n \"10,4\":\"cave_entrance_2\",\n \"1,9\":\"dark_water\",\n \"2,9\":\"dark_water\",\n \"2,10\":\"dark_water\"\n }\n\n # Decide what data to return\n if option == \"stage\":\n return STAGE_1\n elif option == \"tiles\":\n return STAGE_1_TILES\n elif option == \"special\":\n return STAGE_1_SPECIAL\n else:\n print(\"Something Broke! map_generator_1\")","def generate_board(rows, cols):\n aux = np.zeros((rows, cols))\n for i in range(rows):\n for j in range(cols):\n if np.random.random() < 0.5:\n aux[i][j] = 1\n return aux","def uniform_random(self) -> None:\n\n size = self.circ_size\n random.seed(self.seed)\n\n gates = [self.h, self.x, self.y, self.z, self.s, self.t, self.cx]\n candidates = set(range(size))\n\n for i in range(size):\n for j in range(size):\n to_apply = random.choice(gates)\n\n num_qubits = 2 if to_apply == self.cx else 1\n targets = random.sample(candidates, num_qubits)\n to_apply(*targets)\n\n if self.meas: self.measure(self.qr, self.cr)","def randomized_prims(width=16, height=16) -> Maze:\n maze = Maze(width=width, height=height, algorithm=None)\n visited = [[False for _ in range(maze.width)] for _ in range(maze.height)]\n\n # ensure only one entrance to the center squares\n centerx = maze.width // 2 - 1\n centery = maze.height // 2 - 1\n \n visited[centery][centerx] = True\n visited[centery][centerx+1] = True\n visited[centery+1][centerx+1] = False\n visited[centery+1][centerx] = True\n\n visited[0][0] = True\n boundary = [(0,0,Compass.EAST), (0,0,Compass.SOUTH)]\n\n while boundary:\n x, y, direction = boundary.pop(random.randint(0, len(boundary)-1))\n nx, ny = maze.neighbor(x, y, direction)\n if not visited[ny][nx]:\n maze.break_wall(x, y, direction)\n boundary.extend([(nx,ny,direction) for direction in maze.neighbors(nx, ny)])\n visited[ny][nx] = True\n \n return maze","def new_tile(self):\n two_or_four = random.random();\n if two_or_four < 0.9:\n value = 2\n else:\n value = 4\n empty = False\n all_cells = 0\n while empty == False:\n all_cells += 1 \n row = random.choice(range(self._height))\n col = random.choice(range(self._width))\n if self.get_tile(row, col) == 0:\n empty = True\n self.set_tile(row, col, value)\n elif all_cells >= self._height * self._width:\n empty = True","def populate_region(mask, layer_params):\n\n from .speedups import (\n NEW_CELL_MASK, CAN_OSCILLATE_MASK, INCLUDE_VIOLATIONS_MASK)\n\n border = ndimage.maximum_filter(mask, size=3, mode='wrap') ^ mask\n interior = ndimage.minimum_filter(mask, size=3, mode='wrap')\n gen_mask = mask * (\n NEW_CELL_MASK |\n CAN_OSCILLATE_MASK |\n INCLUDE_VIOLATIONS_MASK\n ) + border * (\n INCLUDE_VIOLATIONS_MASK\n )\n board = np.zeros(mask.shape, dtype=np.uint16)\n foreground = np.zeros(mask.shape, dtype=bool)\n background = np.zeros(mask.shape, dtype=bool)\n background_color = np.zeros(mask.shape, dtype=bool)\n seeds = None\n max_period = 1\n\n for layer in layer_params:\n if not isinstance(layer, dict):\n raise ValueError(\n \"'layer_params' should be a list of parameter dictionaries.\")\n layer = _fix_random_values(layer)\n old_board = board.copy()\n gen_mask0 = gen_mask.copy()\n interior = ndimage.minimum_filter(\n gen_mask & NEW_CELL_MASK > 0, size=3, mode='wrap')\n color = COLORS.get(layer.get('color'), 0)\n\n fence_frac = layer.get('fences', 0.0)\n if fence_frac > 0:\n fences = build_fence(gen_mask & speedups.NEW_CELL_MASK)\n fences *= coinflip(fence_frac, fences.shape)\n gen_mask &= ~(fences * (NEW_CELL_MASK | CAN_OSCILLATE_MASK))\n board += fences.astype(np.uint16) * CellTypes.wall\n\n spawners = layer.get('spawners', 0)\n if spawners > 0:\n _mask = (gen_mask0 & NEW_CELL_MASK > 0) & interior\n new_cells = _mask & coinflip(spawners, board.shape)\n if not new_cells.any() and _mask.any():\n i, j = np.nonzero(_mask)\n k = get_rng().choice(len(i)) # ensure at least one spawner\n new_cells[i[k], j[k]] = True\n gen_mask[new_cells] ^= NEW_CELL_MASK\n board[new_cells] = CellTypes.spawner + color\n\n tree_lattice = layer.get('tree_lattice')\n # Create a lattice of trees that are spread throughout the region\n # such that every empty cell touches one (and only one) tree\n # (modulo edge effects).\n # Such a lattice tends to make the resulting board very chaotic.\n # Note that this will disrupt any pre-existing patterns.\n if tree_lattice is not None:\n if not isinstance(tree_lattice, dict):\n tree_lattice = {}\n h, w = board.shape\n stagger = tree_lattice.get('stagger', True)\n spacing = float(tree_lattice.get('spacing', 5))\n if not stagger:\n new_cells = _make_lattice(h, w, spacing, spacing, 0)\n elif spacing <= 3:\n new_cells = _make_lattice(h, w, 3, 3, 1)\n elif spacing == 4:\n new_cells = _make_lattice(h, w, 10, 1, 3)\n elif spacing == 5:\n new_cells = _make_lattice(h, w, 13, 1, 5)\n else:\n # The following gets pretty sparse.\n new_cells = _make_lattice(h, w, 6, 3, 3)\n\n new_cells &= gen_mask & NEW_CELL_MASK > 0\n board[new_cells] = CellTypes.tree + color\n\n period = 1\n if 'pattern' in layer:\n pattern_args = layer['pattern'].copy()\n period = pattern_args.get('period', 1)\n if period == 1:\n gen_mask2 = gen_mask & ~CAN_OSCILLATE_MASK\n pattern_args.update(period=max_period, osc_bonus=0)\n elif period == 0:\n gen_mask2 = gen_mask & ~INCLUDE_VIOLATIONS_MASK\n pattern_args.update(period=max_period, osc_bonus=0)\n elif period < max_period:\n raise ValueError(\n \"Periods for sequential layers in a region must be either 0, 1,\"\n \" or at least as large as the largest period in prior layers.\")\n else:\n gen_mask2 = gen_mask\n max_period = period\n\n board = _gen_pattern(board, gen_mask2, seeds, **pattern_args)\n\n # We need to update the mask for subsequent layers so that they\n # do not destroy the pattern in this layer.\n # First get a list of board states throughout the oscillation cycle.\n boards = [board]\n for _ in range(1, max_period):\n boards.append(speedups.advance_board(boards[-1]))\n non_empty = np.array(boards) != 0\n still_cells = non_empty.all(axis=0)\n osc_cells = still_cells ^ non_empty.any(axis=0)\n # Both still life cells and oscillating cells should disallow\n # any later changes. We also want to disallow changes to the cells\n # that are neighboring the oscillating cells, because any changes\n # there would propogate to the oscillating cells at later time\n # steps.\n # Note that it doesn't really matter whether the oscillating mask\n # is set for the currently oscillating cells, because we're not\n # checking for violations in them anyways, and we don't allow any\n # changes that would affect them.\n osc_neighbors = ndimage.maximum_filter(osc_cells, size=3, mode='wrap')\n gen_mask[osc_cells] &= ~(NEW_CELL_MASK | INCLUDE_VIOLATIONS_MASK)\n gen_mask[still_cells | osc_neighbors] &= ~(NEW_CELL_MASK | CAN_OSCILLATE_MASK)\n\n new_mask = board != old_board\n life_mask = ((board & CellTypes.alive) > 0) & new_mask\n board += color * new_mask * life_mask\n # The seeds are starting points for the next layer of patterns.\n # This just makes the patterns more likely to end up close together.\n seeds = ((board & CellTypes.alive) > 0) & mask\n\n new_mask = board != old_board\n\n movable_walls = layer.get('movable_walls', 0)\n if movable_walls > 0:\n new_cells = coinflip(movable_walls, board.shape) * new_mask\n new_cells *= (board & ~CellTypes.rainbow_color) == CellTypes.wall\n board += new_cells * CellTypes.movable\n\n movable_trees = layer.get('movable_trees', 0)\n if movable_trees > 0:\n new_cells = coinflip(movable_trees, board.shape) * new_mask\n new_cells *= (board & ~CellTypes.rainbow_color) == CellTypes.tree\n board += new_cells * CellTypes.movable\n\n hardened_life = layer.get('hardened_life', 0)\n if hardened_life > 0:\n new_cells = coinflip(hardened_life, board.shape) * new_mask\n new_cells *= (board & ~CellTypes.rainbow_color) == CellTypes.life\n board -= new_cells * CellTypes.destructible\n\n buffer_size = layer.get('buffer_zone', 0) * 2 + 1\n life_cells = board & CellTypes.alive > 0\n buf = ndimage.maximum_filter(life_cells, size=buffer_size, mode='wrap')\n gen_mask[buf] &= ~NEW_CELL_MASK\n\n target = layer.get('target', 'board')\n if target == 'board':\n foreground[new_mask] = True\n if period > 0:\n background[new_mask] = True\n elif target == 'goals':\n background[new_mask] = True\n background_color[new_mask] = True\n # Make sure to add walls and such to the foreground\n foreground[new_mask & (board & CellTypes.alive == 0)] = True\n elif target == 'both':\n foreground[new_mask] = True\n if period > 0:\n background[new_mask] = True\n background_color[new_mask] = True\n else:\n raise ValueError(\"Unexpected value for 'target': %s\" % (target,))\n\n fountains = layer.get('fountains', 0)\n if fountains > 0:\n new_cells = coinflip(fountains, board.shape)\n new_cells *= gen_mask & NEW_CELL_MASK > 0\n neighbors = ndimage.maximum_filter(new_cells, size=3, mode='wrap')\n neighbors *= gen_mask & NEW_CELL_MASK > 0\n gen_mask[neighbors] = INCLUDE_VIOLATIONS_MASK\n if buffer_size > 1:\n buf = ndimage.maximum_filter(neighbors, size=buffer_size, mode='wrap')\n gen_mask[buf] &= ~NEW_CELL_MASK\n board[neighbors] = CellTypes.wall + color\n board[new_cells] = CellTypes.fountain + color\n foreground[new_cells] = True\n background[neighbors] = True\n background_color[neighbors] = True\n\n goals = board.copy()\n board *= foreground\n goals *= background\n goals &= ~CellTypes.spawning\n goals &= ~(CellTypes.rainbow_color * ~background_color)\n\n return board, goals","def generate_advanced_tech_tiles(seed=0):\n\n if seed is not 0:\n random.seed(seed)\n all_advanced_tiles = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 ,15]\n randomized_tiles = list()\n\n for _ in range(6):\n chosen_tile_index = random.randint(0, len(all_advanced_tiles) - 1)\n randomized_tiles.append(all_advanced_tiles[chosen_tile_index])\n all_advanced_tiles.pop(chosen_tile_index)\n\n return tuple(randomized_tiles)","def random_board(n):\r\n \r\n return(np.random.randint(0,n-1, size = n))","def generate_grid(height, width):\n return [[random.randint(0, 9) for _ in range(width)] for _ in range(height)]","def __init__(self, rows, columns, live_probability=0.3, seed=0):\n self.live_probability = live_probability\n self.seed = seed\n self.rows = rows\n self.columns = columns\n self.grid = [\n [Cell() for column_cells in range(self.columns)]\n for row_cells in range(self.rows)\n ]\n\n self.generate_board()","def __init__(self):\r\n self.rows = [[0]*9, [0]*9, [0]*9, [0]*9, [0]*9, [0]*9, [0]*9, [0]*9, [0]*9]\r\n self.block1 = []\r\n self.block5 = []\r\n self.block9 = []\r\n self.puzzle = []\r\n self.score = 0\r\n self.difficulty = 1 # By default Easy difficulty\r\n\r\n \"\"\" Creating blocks using random number generator\"\"\"\r\n while len(self.block1) < 9:\r\n r = random.randrange(1,10)\r\n if r not in self.block1:\r\n self.block1.append(r)\r\n\r\n while len(self.block5) < 9:\r\n r = random.randrange(1,10)\r\n if r not in self.block5:\r\n self.block5.append(r)\r\n\r\n while len(self.block9) < 9:\r\n r = random.randrange(1,10)\r\n if r not in self.block9:\r\n self.block9.append(r)\r\n x = 0\r\n for i in range(3):\r\n for j in range(3):\r\n self.rows[i][j] = self.block1[x]\r\n x = x+1\r\n x = 0\r\n for i in range(3, 6):\r\n for j in range(3, 6):\r\n self.rows[i][j] = self.block5[x]\r\n x = x+1\r\n x = 0\r\n for i in range(6,9):\r\n for j in range(6,9):\r\n self.rows[i][j] = self.block9[x]\r\n x = x+1\r\n \"\"\"Creating a valid solution\"\"\"\r\n self.createsolution(self.rows)","def generate(width=20, height=20):\n m = Maze(width, height)\n m.randomize()\n return m","def generate_board(self):\n try:\n all_words = [word.strip().lower() for word in open(self.in_file)]\n except UnicodeDecodeError:\n raise Exception(\"Make sure that in_file is a text file\")\n except FileNotFoundError:\n raise Exception(\"Make sure that in_file exists\")\n\n permutation = np.random.permutation(len(all_words))\n words = np.array(all_words)[permutation][:25]\n\n # 9 Blue, 8 Red, 7 Neutral, 1 Assassin\n board = []\n for i, word in enumerate(words):\n if i < 9:\n type = \"blue\"\n colour = \"#0080FF\"\n elif i < 17:\n type = \"red\"\n colour = \"#FF0000\"\n elif i < 24:\n type = \"neutral\"\n colour = \"#D0D0D0\"\n else:\n type = \"assassin\"\n colour = \"#202020\"\n word_details = {\"name\": word, \"type\": type, \"colour\": colour, \"active\": False}\n board.append(word_details)\n\n np.random.shuffle(board)\n\n # Assign ids (+1 because of the header)\n for i in range(25):\n board[i][\"id\"] = i+1\n\n return board","def __init__(self, screen, game_settings):\n\t\tself.screen = screen\n\t\tself.color = game_settings.growth_block_color\n\t\t\n\t\t# Sets rect at origin and size 25 x 25\n\t\tself.rect = pygame.Rect(0, 0, 24, 24)\n\t\t\n\t\t# Uses randint to use as random rect position\n\t\tx = randint(0, 35)\n\t\ty = randint(1, 26)\n\t\tself.rect.x = (25 * x) + 1\n\t\tself.rect.bottom = 25 * y","def create_random_grid(N):\n return np.random.choice(values, N*N, p=[0.2, 0.8]).reshape(N, N)","def new_tile(self):\n\n # creating a random float variable that will roll a random value\n # if randomvalue > .90\n #\n\n tile_added = False\n while not tile_added:\n row = random.randint(0,self.grid_height - 1)\n col = random.randint(0,self.grid_width - 1)\n if self.board[row][col] == 0:\n tile_added = True\n random_tile = random.random()\n if random_tile < .90:\n self.board[row][col] = 2\n else:\n self.board[row][col] = 4","def random_placement(area):\n\n area.create_houses(True)\n\n for house in area.houses:\n place_house(area, house)","def random_reassignment(graph, possibilities):\n\n random_assignment(graph, possibilities)\n\n violating_nodes = graph.get_violations()\n\n while len(violating_nodes):\n random_reconfigure_nodes(graph, violating_nodes, possibilities)\n\n violating_nodes = graph.get_violations()","def new_tile(self):\n # replace with your code\n empty_list = []\n counter_1 = 0\n for _ in self._grid:\n counter_2 = 0\n line = _\n for blank in line:\n if blank == 0:\n blank_tile = (counter_1, counter_2)\n empty_list.append(blank_tile)\n counter_2 += 1\n else:\n counter_2 += 1\n counter_1 += 1\n #print empty_list\n \n self._tile = empty_list[random.randrange(len(empty_list))]\n \n value = [2,2,2,2,2,2,2,2,2,4]\n tile_value = value[random.randint(0,9)]\n \n self.set_tile(self._tile[0], self._tile[1], tile_value)","def new_tile(self):\r\n # check if is zero or not\r\n new_tile_added = False\r\n # a list to 2 90% of the time and 4 10% of the time\r\n new_tile_list = [2,2,2,2,2,2,2,2,2,4]\r\n counter = 0\r\n while not new_tile_added:\r\n row_position = random.randrange(0,self.grid_height)\r\n col_position = random.randrange(0,self.grid_width)\r\n if self.grid[row_position][col_position] == 0:\r\n self.grid[row_position][col_position] = random.choice(new_tile_list)\r\n new_tile_added = True\r\n if counter > self.grid_width * self.grid_height:\r\n print 'you failed'\r\n break\r\n\r\n counter +=1","def __init__(self, x, y):\n self.height = x\n self.width = y\n self.grid = self.initialize(self.height, self.width)\n self.randx = random.randint(0, self.height-1)\n self.randy = random.randint(0, self.width-1)\n #self.make()\n #self.show()","def random(self, width, height, seed = None):\n self.grid = [ [''] * width for i in range(height) ]\n random.seed(seed)\n start = ( random.randint(0, len(self.grid) - 1),\n random.randint(0, len(self.grid[0]) - 1)\n )\n visited = set([start])\n self._createPath(start, visited)\n start = ( random.randint(0, len(self.grid) - 1), 0 )\n finish = ( random.randint(0, len(self.grid) - 1),\n len(self.grid[0]) - 1 )\n self.grid[start[0]][start[1]] += '^'\n self.grid[finish[0]][finish[1]] += '$'\n return self.grid, start, finish","def get_next_alea_tiles(plateau, mode):\n from random import randint\n # si le saisie et condition de plateau sont valide\n if mode.upper() == \"INIT\" and get_nb_empty_room(plateau) >= 2 or mode.upper() == \"ENCOURS\" and get_nb_empty_room(plateau) >= 1:\n if mode.upper() == \"INIT\":\n tableau = {'mode' : \"init\", 'check' : not is_game_over(plateau), '0' : {'val' : 1, 'lig' : randint(0,3), 'col' : randint(0,3)}, '1' : {'val' : 2, 'lig' : randint(0,3), 'col' : randint(0,3)}}\n # quand les deux cases choisi ne sont pas vide et la position des 2 valeur donner sont egaux\n while not ( is_room_empty(plateau,tableau[\"0\"][\"lig\"], tableau[\"0\"][\"col\"]) and is_room_empty(plateau, tableau[\"1\"][\"lig\"], tableau[\"1\"][\"col\"]) and not(tableau[\"0\"][\"lig\"] == tableau[\"1\"][\"lig\"] and tableau[\"0\"][\"col\"] == tableau[\"1\"][\"col\"])):\n tableau[\"0\"] = {'val' : 1, 'lig' : randint(0,3), 'col' : randint(0,3)}\n tableau[\"1\"] = {'val' : 2, 'lig' : randint(0,3), 'col' : randint(0,3)}\n else:\n tableau = {'mode' : 'encours', 'check' : not is_game_over(plateau), '0' : {'val' : randint(1,3), 'lig' : randint(0,3), 'col' : randint(0,3)}}\n # auand la cases choisi n est pas vide\n while not (is_room_empty(plateau, tableau[\"0\"][\"lig\"], tableau[\"0\"][\"col\"])):\n tableau[\"0\"] = {'val' : randint(1,3), 'lig' : randint(0,3), 'col' : randint(0,3)}\n return tableau\n else:\n return 'Erreur !'","def generate_new_board(self, difficulty=1):\n self._reset_board()\n self._solve_empty_board_with_random_values()\n self._remove_numbers_to_get_puzzle(difficulty)","def create_random(self):\n for key in self.nn_param_choices:\n self.network[key] = random.choice(self.nn_param_choices[key])","def startGeneration(variant, resolution, loops):\n # Check for valid resolution\n if resolution % 2 != 0:\n print (\"Resolution should be an even integer.\")\n return\n\n # Set high score:\n if variant == 20:\n high_score = 11365950\n if variant == 40:\n high_score = 17858670\n if variant == 60:\n high_score = 24239310\n\n # House distirbution:\n familyHome_count = 0.6 * variant\n bungalow_count = 0.25 * variant\n maison_count = 0.15 * variant\n\n for loops in range(loops):\n\n # Initialize Classlist\n placed_houses = []\n placed_water = []\n\n # Initialize values\n gr = generic.genMap(180 * resolution, 160 * resolution)\n\n # Set length and width based on resultion.\n fam_length = int(resolution * 8)\n fam_width = int(resolution * 8)\n fam_freespace = int(resolution * 2)\n\n bung_length = int(resolution * 7.5)\n bung_width = int(resolution * 10)\n bung_freespace = int(resolution * 3)\n\n mais_length = int(resolution * 10.5)\n mais_width = int(resolution * 11)\n mais_freespace = int(resolution * 6)\n\n # Water\n # Generate water parts\n water_parts = genWater(gr, resolution)\n\n # Place water parts in grid:\n for part in range(len(water_parts)):\n W = 0\n\n # Loop until correctly placed.\n while W != 1:\n\n # Define class instance\n Water = class_house.House(water_parts[part][1], water_parts[part][0],\n 1, 0, 0, 4, \"W\", resolution)\n\n ngrid = genHome(gr, Water)\n\n # Check for success:\n if ngrid == False:\n print (\"No succesfull placement Water\")\n else:\n print (\"Water {0} placed!\".format(W))\n gr = list(ngrid)\n\n # Add water to list\n placed_houses.append(Water)\n\n W = 1\n\n # Maisons\n M = 0\n while M != maison_count:\n\n # Define class instance\n Maison = class_house.House(mais_length, mais_width,\n mais_freespace, 610000, 6, 1, \"M\", resolution)\n\n ngrid = genHome(gr, Maison)\n\n # Check if house succsfully placed:\n if ngrid == False:\n print (\"No succesfull placement Maison\")\n else:\n print (\"Maison {0} placed!\".format(M))\n gr = list(ngrid)\n\n # Add maison to list\n placed_houses.append(Maison)\n\n M += 1\n\n # Then bungalows\n B = 0\n while B != bungalow_count:\n\n # Define class instance\n Bungalow = class_house.House(bung_length, bung_width,\n bung_freespace, 399000, 4, 2, \"B\", resolution)\n\n ngrid = genHome(gr, Bungalow)\n\n # Check for succes:\n if ngrid == False:\n print (\"No succesfull placement Bungalow\")\n else:\n print (\"Bungalow {0} placed!\".format(B))\n gr = list(ngrid)\n\n # Add maison to list\n placed_houses.append(Bungalow)\n\n B += 1\n\n # Then Family homes\n F = 0\n while F != familyHome_count:\n\n # Define class instance\n Familyhome = class_house.House(fam_length, fam_width,\n fam_freespace, 285000, 3, 3, \"F\", resolution)\n\n ngrid = genHome(gr, Familyhome)\n\n # Check for succes:\n if ngrid == False:\n print (\"No succesfull placement Family Home\")\n else:\n print (\"Family home {0} placed!\".format(F))\n gr = list(ngrid)\n\n # Add maison to list\n placed_houses.append(Familyhome)\n\n F += 1\n\n # Calculate score using Placed houses\n sc = generic.calculateScore(gr, placed_houses)\n name = (\"Score: \" + str(sc))\n\n # Only save to file when new record.\n fname = \"Type{0} - {1}\".format(variant, sc)\n\n\n if sc > high_score:\n #read_write.write(fname, placed_houses)\n high_score = sc\n print (\"New high score ({0}) in loop: {1}\".format(sc, loops))\n print (\"Writing to file..\")\n\n return gr, placed_houses, sc","def createMap(self):\n map = {}\n for rows in xrange(0,(size[1]/50)):\n for columns in xrange(0,(size[0]/50)):\n if rows == (size[1]/50)-1 or rows == 0 or columns== (size[0]/50)-1 or columns==0:\n map.update({(rows,columns):\"block\"})\n elif(rows%3 == 0):\n map.update({(rows,columns):random.choice(map_options)})\n else:\n map.update({(rows,columns):random.choice(map_options[:1])})\n\n self.map = map","def create_some_random_pos(actor_cls, n, actor_type, actor_list, game,\r\n probability_each=100):\r\n ITERATIONS_MAX = 12\r\n cell_size = lib_jp.Size(w=actor_cls.size.w, h=actor_cls.size.h)\r\n cell_size_with_border = lib_jp.Size(w=cell_size.w + Actor.CELL_SCREEN_SECURITY_SIZE,\r\n h=cell_size.h + Actor.CELL_SCREEN_SECURITY_SIZE)\r\n cell_total_security_border = lib_jp.Size(w=actor_cls.cell_added_size.w\r\n + Actor.CELL_SCREEN_SECURITY_SIZE,\r\n h=actor_cls.cell_added_size.h\r\n + Actor.CELL_SCREEN_SECURITY_SIZE)\r\n if len(actor_list) >= actor_cls.max_qty_on_board:\r\n return\r\n elif n + len(actor_list) >= actor_cls.max_qty_on_board:\r\n n = actor_cls.max_qty_on_board - len(actor_list)\r\n iterations = 0\r\n for _ in range(n):\r\n if probability_each < 100 and randint(1, 100) > probability_each:\r\n continue\r\n actor_added = False\r\n iterations = 0\r\n actor_obj = None\r\n while not actor_added and (iterations <= ITERATIONS_MAX):\r\n iterations += 1\r\n x = randint(cell_total_security_border.w,\r\n Settings.screen_width - cell_size_with_border.w)\r\n y = randint(Settings.screen_near_top + cell_total_security_border.h,\r\n Settings.screen_height - cell_size_with_border.h)\r\n # Check if there is some sprite in this position\r\n position_not_taken = True\r\n rect1 = pg.Rect(x, y, cell_size.w, cell_size.h)\r\n if actor_cls.actor_type != ActorType.BAT:\r\n # Apples and mines cannot collide with any kind of sprite\r\n for sprite in game.active_sprites:\r\n if rect1.colliderect(sprite.rect):\r\n position_not_taken = False\r\n break\r\n else:\r\n # Bats cannot collide with snakes and other bats\r\n for sprite in game.snakes:\r\n if rect1.colliderect(sprite.rect):\r\n position_not_taken = False\r\n break\r\n if position_not_taken:\r\n for sprite in game.bats:\r\n if rect1.colliderect(sprite.rect):\r\n position_not_taken = False\r\n break\r\n if position_not_taken:\r\n actor_obj = actor_cls(x, y, actor_type, game=game)\r\n if actor_obj.actor_type == ActorType.BAT:\r\n actor_obj.change_x = randint(3, 5)\r\n actor_obj.change_y = randint(3, 5)\r\n actor_obj.initialize_boundaries()\r\n actor_added = True","def __generate_rectangle_obstacles(self, world):\n obs_min_dim = self.cfg[\"obstacle\"][\"rectangle\"][\"min_dim\"]\n obs_max_dim = self.cfg[\"obstacle\"][\"rectangle\"][\"max_dim\"]\n obs_max_combined_dim = self.cfg[\"obstacle\"][\"rectangle\"][\"max_combined_dim\"]\n obs_min_count = self.cfg[\"obstacle\"][\"rectangle\"][\"min_count\"]\n obs_max_count = self.cfg[\"obstacle\"][\"rectangle\"][\"max_count\"]\n obs_min_dist = self.cfg[\"obstacle\"][\"rectangle\"][\"min_distance\"]\n obs_max_dist = self.cfg[\"obstacle\"][\"rectangle\"][\"max_distance\"]\n\n # generate the obstacles\n obstacles = []\n obs_dim_range = obs_max_dim - obs_min_dim\n obs_dist_range = obs_max_dist - obs_min_dist\n num_obstacles = randrange(obs_min_count, obs_max_count + 1)\n\n test_geometries = [r.global_geometry for r in world.robots]\n while len(obstacles) < num_obstacles:\n # generate dimensions\n width = obs_min_dim + (random() * obs_dim_range )\n height = obs_min_dim + (random() * obs_dim_range )\n while width + height > obs_max_combined_dim:\n height = obs_min_dim + (random() * obs_dim_range )\n\n # generate position\n dist = obs_min_dist + (random() * obs_dist_range)\n phi = -pi + (random() * 2 * pi)\n x = dist * sin(phi)\n y = dist * cos(phi)\n\n # generate orientation\n theta = -pi + (random() * 2 * pi)\n\n # test if the obstacle overlaps the robots or the goal\n obstacle = RectangleObstacle(width, height, Pose(x, y, theta))\n intersects = False\n for test_geometry in test_geometries:\n intersects |= geometrics.convex_polygon_intersect_test(test_geometry, obstacle.global_geometry)\n if not intersects:\n obstacles.append(obstacle)\n return obstacles","def sea_execution(board, position, role):\n quitt = False\n if position == 'comp':\n #print(1)\n #temporary for dumb AI\n #create and print a list of coastal, friendly regions where norse is not the ONLY one\n \n possible_region_list = []\n \n #loops through list of friendly, coastal, not just Norse regions to append to a possible_region_list\n for region in board.get_controlled_regions(role):\n #print(2)\n coastal = False\n just_norse = False\n if region.coast:\n coastal = True\n if len(region.blocks_present) == 1 and region.blocks_present[0].name.upper() == 'NORSE':\n just_norse = True\n \n if coastal and not just_norse:\n possible_region_list.append(region)\n \n \n #loops through list of friendly, coastal regions to append to a possible_final_region_list\n possible_final_region_list = []\n for region in board.get_controlled_regions(role): \n #print(3) \n if region.coast:\n possible_final_region_list.append(region)\n \n \n \n if len(possible_final_region_list) >= 2:\n #if you want to add in last-min strategy, do it here\n #random region from possible list\n england = board.regions[22]\n if england in possible_region_list:\n original_region = england\n else:\n original_region = possible_region_list[random.randint(0, len(possible_region_list) - 1)]\n #remove the original region from the possible end regions\n possible_final_region_list.remove(original_region)\n \n #possible_block_list\n #list of possible blocks to move (present in region) and not norse\n possible_block_list = []\n for block in original_region.blocks_present:\n if block.name != 'NORSE':\n possible_block_list.append(block)\n \n move_block_list = []\n blocks_moved = 0\n #print(4)\n\n while blocks_moved < 2:\n #print(5)\n block = possible_block_list[random.randint(0, len(possible_block_list)-1)]\n #if it's not already on the list,append to move_block_list\n if block not in move_block_list:\n move_block_list.append(block)\n blocks_moved+=1\n elif block in move_block_list and len(possible_block_list) == 1:\n blocks_moved+=1\n else:\n print('neither condition was met so this is an infinite loop')\n \n \n #print(6) \n new_region = possible_final_region_list[random.randint(0, len(possible_final_region_list) - 1)]\n \n for block in move_block_list:\n \n board.add_to_location(block, new_region)\n print(block.name + ' moved from ' + original_region.name + ' to ' + new_region.name)\n \n else:\n print('There are not enough friendly regions with which to play this card.')\n \n \n #add in if it's not possible\n elif position == 'opp':\n \n \n possible_region_list = []\n \n #loops through list of friendly, coastal, not just Norse regions to append to a possible_region_list\n for region in board.get_controlled_regions(role):\n coastal = False\n just_norse = False\n if region.coast:\n coastal = True\n if len(region.blocks_present) == 1 and region.blocks_present[0].name.upper() == 'NORSE':\n just_norse = True\n \n if coastal and not just_norse:\n possible_region_list.append(region)\n \n \n #loops through list of friendly, coastal regions to append to a possible_final_region_list\n possible_final_region_list = []\n for region in board.get_controlled_regions(role): \n if region.coast:\n possible_final_region_list.append(region)\n \n \n \n if len(possible_final_region_list) >= 2:\n \n print('Possible origin regions:')\n for region in possible_region_list:\n print(region.name)\n \n #user input region, check if in possible list\n valid_region = False\n while not valid_region:\n \n original_region_name = input('What region would you like to move block(s) from? Enter a name or \\'none\\'.\\n>').upper()\n \n if original_region_name != 'NONE':\n \n original_region = search.region_name_to_object(board, original_region_name)\n \n if original_region and original_region in possible_region_list:\n valid_region = True\n else:\n print('Invalid region.')\n else:\n quitt = True\n \n if not quitt:\n #remove the original region from the possible end regions\n possible_final_region_list.remove(original_region)\n \n #possible_block_list\n #list of possible blocks to move (present in region) and not norse\n possible_block_list = []\n for block in original_region.blocks_present:\n if block.name != 'NORSE':\n possible_block_list.append(block)\n \n print('Possible blocks:')\n for block in possible_block_list:\n print(block.name)\n \n \n move_block_list = []\n blocks_moved = 0\n quittt = False\n block_name = ''\n while blocks_moved < 2 and not quittt:\n if block_name != 'NONE':\n valid_block = False\n while not valid_block:\n \n \n block_name = input('Which block would you like to move? Enter a name or \\'none\\'.\\n>').upper()\n \n if block_name != 'NONE':\n \n block_to_move = search.block_name_to_object(possible_block_list, block_name)\n \n if block_to_move and block_to_move not in move_block_list:\n valid_block = True\n move_block_list.append(block_to_move)\n blocks_moved+=1\n \n elif block in move_block_list and len(possible_block_list) == 1:\n blocks_moved=1\n \n else:\n print('Invalid block.')\n continue\n else:\n valid_block = True\n if len(move_block_list) == 1:\n quittt = True\n quitt = False\n if len(move_block_list) > 0: \n print('Possible final regions:')\n for region in possible_final_region_list:\n print(region.name)\n \n #user input region, check if in possible list\n valid_region = False\n while not valid_region:\n \n new_region_name = input('What region would you like to move block(s) to? Enter a name or \\'none\\'.\\n>').upper()\n \n if new_region_name != 'NONE':\n \n new_region = search.region_name_to_object(board, new_region_name)\n \n if new_region and new_region in possible_final_region_list:\n valid_region = True\n else:\n print('Invalid region.')\n continue\n else:\n valid_region = True\n quitt = True\n \n if not quitt:\n \n for block in move_block_list:\n \n board.add_to_location(block, new_region)\n print(block.name + ' moved from ' + original_region.name + ' to ' + new_region.name)\n \n else:\n print('There are not enough friendly coastal regions with which to play this card.')","def populate_tiles(self):\n\n # grid format :\n # grid(x,y,z)[0]: A valid WorldTile type (i.e. WorldTile.door)\n # grid(x,y,z)[1]: A list of ASCII color or format codes for ColorIze\n # grid(x,y,z)[2]: The tile object\n\n self.t_count = 0 # Tile count, increment for each tile added\n self.build_start = time.clock()\n self.logger.info(\"[*] Starting world building script\")\n\n script_list = [\n self.build_boss_room,\n self.build_rooms,\n self.build_halls,\n self.build_doors,\n self.build_chests,\n self.build_traps,\n self.build_mobs,\n self.build_npcs\n ]\n for func in script_list:\n self.logger.debug(\"\\tRunning {}\".format(func.__name__))\n if not func():\n e_text = \"Build script failed : {}\".format(func.__name__)\n raise AssertionError(e_text)\n\n self.logger.info(\"[*] World building script completed\")\n self.logger.debug(\"\\tTiles Placed : {}\".format(self.t_count))\n build_time = time.clock()-self.build_start\n self.logger.debug(\"\\tTook {}s\".format(build_time))\n self.logger.debug(\"\\tTiles/s : {}\".format(t_count/build_time))","def new_tile(self):\n random.shuffle(self.tiles) # shuffle the list of tiles tuples\n count = 0\n while self.get_tile(self.tiles[0][0], self.tiles[0][1]) != 0 and count < self.grid_height*self.grid_width: \n self.tiles.append(self.tiles.pop(0)) \n \n # next, select value as 2 with a 90% probability (percentage) and 4 with 10%\n percentage = random.random() \n if percentage > 0.1:\n value = 2\n else:\n value = 4\n row = self.tiles[0][0]\n col = self.tiles[0][1]\n self.set_tile(row , col,value)","def new_tile(self):\n \n empty_items = []\n for row in range(self.get_grid_height()):\n for col in range(self.get_grid_width()):\n if self.get_tile(row, col) == 0:\n empty_items.append((row, col))\n \n random_row = 0\n random_col = 0\n if len(empty_items) != 0:\n random_empty_tile = random.randrange(0, len(empty_items))\n (random_row, random_col) = empty_items[random_empty_tile]\n else:\n return\n # the % of getting \"4\" from 0~9 is 10%\n random_time = random.randrange(0, 10)\n \n if random_time == 4:\n self._cells[random_row][random_col] = 4\n else:\n self._cells[random_row][random_col] = 2","def init():\n for i in range(COLS):\n for j in range(ROWS):\n BOARD[i][j] = int(random(2))","def generate_standard_tech_tiles(seed=0):\n\n if seed is not 0:\n random.seed(seed)\n all_standard_tiles = [1, 2, 3, 4, 5, 6, 7, 8, 9]\n randomized_tiles = list()\n\n for _ in range(9):\n chosen_tile_index = random.randint(0, len(all_standard_tiles) - 1)\n randomized_tiles.append(all_standard_tiles[chosen_tile_index])\n all_standard_tiles.pop(chosen_tile_index)\n\n return tuple(randomized_tiles)","def new_tile(self):\n zero_list = []\n zero_cell = ()\n # self._cells = [[0 for col in range(self._grid_width)] for row in range(self._grid_height)]\n for row in range(self._grid_height):\n for col in range(self._grid_width):\n if self._cells[row][col] == 0:\n zero_cell = (row, col)\n zero_list.append(zero_cell)\n if len(zero_list) > 0:\n chance = random.randrange(0,10)\n cell_idx = random.randrange(len(zero_list))\n if chance == 9:\n self._cells[zero_list[cell_idx][0]][zero_list[cell_idx][1]] = 4\n else:\n self._cells[zero_list[cell_idx][0]][zero_list[cell_idx][1]] = 2\n else:\n print(\"You lost! Better luck next time!\")","def random_v_random(n=1):\n p1_strategy = strategies.RandomStrategy()\n p2_strategy = strategies.RandomStrategy()\n p1 = player.Player('X', p1_strategy)\n p2 = player.Player('O', p2_strategy)\n board = tictactoe.Board()\n game = rl_game.Game(p1, p2, board)\n game.play_one()","def create(self):\n\n for i in range(8):\n # Create white pawns\n self.board[1][i] = Piece(\"pawn\", 1, i, 0)\n # Create black pawns\n self.board[6][i] = Piece(\"pawn\", 6, i, 1)\n\n # Create white rooks\n self.board[0][0] = Piece(\"rook\", 0, 0, 0)\n self.board[0][7] = Piece(\"rook\", 0, 7, 0)\n\n # Create black rooks\n self.board[7][0] = Piece(\"rook\", 7, 0, 1)\n self.board[7][7] = Piece(\"rook\", 7, 7, 1)\n\n # Create white knights\n self.board[0][1] = Piece(\"knight\", 0, 1, 0)\n self.board[0][6] = Piece(\"knight\", 0, 6, 0)\n\n # Create black knights\n self.board[7][1] = Piece(\"knight\", 7, 1, 1)\n self.board[7][6] = Piece(\"knight\", 7, 6, 1)\n\n # Create white bishop\n self.board[0][2] = Piece(\"bishop\", 0, 2, 0)\n self.board[0][5] = Piece(\"bishop\", 0, 5, 0)\n\n # Create black bishop\n self.board[7][2] = Piece(\"bishop\", 7, 2, 1)\n self.board[7][5] = Piece(\"bishop\", 7, 5, 1)\n\n # Create white queen and king\n self.board[0][3] = Piece(\"queen\", 0, 3, 0)\n self.board[0][4] = Piece(\"king\", 0, 4, 0)\n\n # Create black queen and king\n self.board[7][3] = Piece(\"queen\", 7, 3, 1)\n self.board[7][4] = Piece(\"king\", 7, 4, 1)","def new_tile(self):\r\n rand_x = random.randrange(self.width)\r\n rand_y = random.randrange(self.height)\r\n while self.get_tile(rand_y, rand_x) != 0:\r\n rand_x = random.randrange(self.width)\r\n rand_y = random.randrange(self.height)\r\n value = random.choice([2,2,2,2,2,2,2,2,2,4])\r\n del self.board[rand_y][rand_x]\r\n self.board[rand_y].insert(rand_x,value)\r\n return self.board","def NewTile(field):\n var = False\n while not var:\n temp = random.randrange(0, len(field), 1)\n if field[temp] == 0:\n r = random.randrange(0, 100, 1)\n if r > 80:\n field[temp] = -4\n else:\n field[temp] = -2\n \n var = True\n return field","def genWater(grid, resolution):\n\n grid_surface = len(grid) * len(grid[0])\n\n # Amount of surface for the water.\n allowed_surface = round(0.2 * grid_surface)\n\n # Collection of the created surfaces\n water_surfaces = []\n\n # Min size of one water piece.\n min_single_size = 4 * resolution\n\n run = 0\n\n # Loop until 4 and enough surface:\n while allowed_surface != 0:\n run += 1\n print (allowed_surface)\n w = 0\n l = 0\n\n # Only generate random if we have more then 1 option left.\n if len(water_surfaces) < 3 and min_single_size != allowed_surface and allowed_surface > 5:\n try:\n size = random.randint(min_single_size, allowed_surface)\n except ValueError as e:\n print (\"Error occured: {0} min: {1} surf: {2}\".format(e, min_single_size, allowed_surface))\n\n # Otherwise the size is the allowed surface\n else:\n size = allowed_surface\n\n # Shouldn't go below 0\n if allowed_surface - size >= 0:\n\n # Calculate width and length if possible.\n # Starting from the square root causes the part to\n # be more square instead of a straight line.\n init = round(math.sqrt(size))\n for i in range(init, 1, -1):\n if size % i == 0 and 1 <= math.ceil((size / i) / i) <= 4:\n w = i\n l = size / w\n\n # Reinit allowed surface\n allowed_surface -= size\n\n # Randomly switch width and length\n coinflip = random.randint(1, 2)\n if coinflip == 1:\n\n # Adds a tuple wich contains (width, length, ratio, \n # surface)\n water_surfaces.append((w, int(l), round(l / w, 2), \n size))\n else:\n water_surfaces.append((int(l), w, round(l / w, 2), \n size))\n break\n\n if run > 4:\n # Drop last try and remake the surface.\n print (\"Drop\")\n try:\n run = 2\n allowed_surface += water_surfaces[-1][3]\n water_surfaces = water_surfaces[:-1]\n except:\n print (\"wat\")\n\n return water_surfaces","def makeGrid(self, width, height, rewardLocs, exit, nPick=1, nAux=1, walls=[]):\n # Make mapping from coordinate (x, y, (takenreward1, takenreward2, ...))\n # to state number, and vice-versa.\n rTaken = iter([(),])\n for nPicked in range(1, nPick+1):\n rTaken = itertools.chain(rTaken, \n myCombinations(rewardLocs, r=nPicked)\n )\n # Iterators are hard to reset, so we list it.\n rTaken = list(rTaken)\n\n # Mappings from state to coordinates, vice-versa\n coordToState = {}\n stateToCoord = {}\n stateIdx = 0\n for x in range(width):\n for y in range(height):\n for stuff in rTaken:\n for holding in self.holdingPossibilities:\n coordToState[(x, y, stuff, holding)] = stateIdx\n stateToCoord[stateIdx] = (x, y, stuff, holding)\n stateIdx += 1\n self.deadEndState = stateIdx\n\n # Actually make the transition function\n def trans(f, p): \n aux = p\n (x, y, stuff, holding) = stateToCoord[f]\n actionMap = {}\n default = {(f, aux): 1}\n # Make the transition dictionary if the dead-end state (state width*height)\n if f == self.F-1:\n for action in range(5):\n actionMap[action] = default\n return actionMap\n\n # Otherwise, determine directions of motion, etc. \n for i in range(4):\n actionMap[i] = default\n if x != 0 and ((x-1, y) not in walls):\n actionMap[0] = {(coordToState[(x-1,y,stuff, holding)], aux): 1}\n if x < width-1 and ((x+1, y) not in walls):\n actionMap[1] = {(coordToState[(x+1,y,stuff, holding)], aux): 1}\n if y != 0 and ((x, y-1) not in walls):\n actionMap[2] = {(coordToState[(x,y-1,stuff, holding)], aux): 1}\n if y < height-1 and ((x, y+1) not in walls):\n actionMap[3] = {(coordToState[(x,y+1,stuff, holding)], aux): 1}\n # What happens when the agent uses action 4?\n if (x, y) == exit:\n # Some cases, depending on self.oneAtATime\n if not self.oneAtATime:\n # The agent is leaving.\n actionMap[4] = {(self.deadEndState, aux): 1}\n else:\n # The agent is dropping off a reward. holeFiller will\n # take care of the reward value.\n if len(stuff) >= nPick:\n # The agent is not allowed to pick up more stuff\n actionMap[4] = {(self.deadEndState, aux): 1}\n else:\n # The agent drops off the object.\n actionMap[4] = {(coordToState[(x,y,stuff, -1)], aux): 1}\n elif (x, y) not in rewardLocs:\n # No reward to pick up. Do nothing.\n actionMap[4] = default\n elif (x, y) in stuff:\n # This reward has already been used. Do nothing.\n actionMap[4] = default\n elif len(stuff) >= nPick or (holding != -1 and holding < len(stuff)\n and self.oneAtATime):\n # The agent has its hands full.\n actionMap[4] = default\n else:\n # The agent is allowed to pick up an object.\n newStuff = tuple(sorted(list(stuff) + [(x, y)]))\n if self.oneAtATime:\n newHoldingIdx = newStuff.index((x, y))\n else:\n newHoldingIdx = -1\n actionMap[4] = {(coordToState[(x, y, newStuff, newHoldingIdx)], aux): 1}\n return actionMap\n\n # Man, I'm outputting a lot of stuff.\n # coordToState[(x, y, rewardsLeft, holding)] -> index of this state\n # stateToCoord[index] -> (x, y, rewardsLeft, holding)\n # rTaken is a list of all possible combinations of leftover rewards.\n return (trans, coordToState, stateToCoord, rTaken)","def create_random(self):\n number_of_layers = random.choice(self.parameter_choices['number_of_layers'])\n neurons_per_layer = []\n dropout_per_layer = []\n self.network['number_of_layers'] = number_of_layers\n\n for i in range(number_of_layers):\n neurons_per_layer.append(random.choice(self.parameter_choices['neurons_per_layer']))\n dropout_per_layer.append(random.choice(self.parameter_choices['dropout_per_layer']))\n\n self.network['neurons_per_layer'] = neurons_per_layer\n self.network['dropout_per_layer'] = dropout_per_layer\n self.network['optimizer'] = random.choice(self.parameter_choices['optimizer'])\n self.network['activation'] = random.choice(self.parameter_choices['activation'])","def generate_boards():\n\n print \"Generating data, please hold on...\"\n # a list for turns, each which is a list of boards, which are unique layouts\n # a completely blank layout is always the start of the game, counting for turn 0\n game = [[Board(' ' * 9, 1)]]\n\n # there are at most 9 turns in a game of tic tac toe\n for turnNum in range(1, 10):\n # list of layouts for the current turn\n turn = []\n upperLayouts = game[-1]\n\n if turnNum % 2 == 1: player = 'X'\n else: player = 'O'\n\n # every turns' unique layouts are numbered to seperate them more easily\n pattern = 1\n # goes through every layout from the previous turn\n for ul in upperLayouts:\n # game does not continue after a winning move, and using a won board is only possible after turn 5\n if turnNum <= 5 or not ul.check_win()[0]:\n # 9 positions on every board\n for pos in range(9):\n if ul[pos] == ' ':\n newLayout = Board(ul[0:pos] + player + ul[pos+1:])\n # if it is a unique layout\n unique = True\n # goes through every existing layout for this turn\n for item in turn:\n if newLayout.matches(item): \n unique = False\n # the upper layout leads to an existing layout\n ul.paths.append(item.pattern)\n break\n if unique:\n turn.append(Board(newLayout, pattern))\n # the current upper layout leads to the new layout\n ul.paths.append(pattern)\n pattern += 1\n else:\n # adds a zero for paths because a played character is taking up that space\n ul.paths.append(0)\n game.append(turn)\n return game","def generate_random(self, prob_alive=0.3):\n self.generation = 0\n for i in range(self.lines):\n for j in range(self.cols):\n if random.random() < prob_alive:\n self[i][j] = self.cell_state['alive']","def random_blocks():\n cells = []\n while len(cells) != 43:\n cell_to_add = (random.randint(0, 11), random.randint(0, 9))\n if cell_to_add not in cells:\n cells.append(cell_to_add)\n return cells","def randomChestplate():\n return random.choice(CHESTPLATES)","def generate_options(board: list, player_turn: chr):\n black_marbles, white_marbles = Board.read_marbles(board)\n black_risk, white_risk = Evaluator.assess_risk(black_marbles, white_marbles)\n if player_turn == 'b':\n risk = black_risk\n else:\n risk = white_risk\n\n board_object = Board()\n moves, resulting_boards = board_object.generate_all_boards(board, player_turn)\n # Assume score 0 for now\n Evaluator.score_move(moves, 0)\n for i in range(0, len(moves)):\n Evaluator.calculate_board_score(moves[i], resulting_boards[i], player_turn, risk)\n return moves, resulting_boards","def make_grid(width, height): \n return {(row, col): choice(ascii_uppercase)\n for row in range (height) # remove ' ' and add choice()\n for col in range(width)}","def simulate(self):\n self._t = self._t + 1\n if self._t == self._cycle:\n # End of a season, start of the next one. Year is also cyclic that is WINTER -> SPRING.\n self._t = 0\n self._season = self._season.next()\n\n # When the ammount of newly produced food in a cell is over and the cell can seed we\n # randomly choose another spot where some random ammount of newly produced food should\n # be stored.\n for i in range(self._height):\n for j in range(self._width):\n if self._env[i][j].get_newly() == 0 and not self._seeded[i][j]:\n # if the cell become empty just now seed in once in a randomn cell on the grid.\n self._seeded[i][j] = True\n cap = self._height + self._width\n while cap > 0:\n seedi = random.randint(0, self._height - 1)\n seedj = random.randint(0, self._width - 1)\n\n production_cap = self._food_per_season[self._season.value]\n\n production_cap -= self._env[seedi][seedj].get_newly()\n\n if production_cap > 0:\n seed_amount = random.randint(1, production_cap)\n self._env[seedi][seedj].produce(seed_amount)\n self._seeded[seedi][seedj] = False\n break\n\n cap = cap - 1","def new_game(self):\n self.cells = [] # Array of cells\n self.frame_count = 0\n self.database = []\n self.timer = [Consts[\"MAX_TIME\"], Consts[\"MAX_TIME\"]]\n self.result = None\n # Define the players first\n self.cells.append(Cell(0, [Consts[\"WORLD_X\"] / 4, Consts[\"WORLD_Y\"] / 2], [0, 0], Consts[\"DEFAULT_RADIUS\"]))\n self.cells.append(Cell(1, [Consts[\"WORLD_X\"] / 4 * 3, Consts[\"WORLD_Y\"] / 2], [0, 0], Consts[\"DEFAULT_RADIUS\"]))\n # Generate a bunch of random cells\n for i in range(Consts[\"CELLS_COUNT\"]):\n if i < 4:\n rad = 1.5 + (random.random() * 1.5) # Small cells\n elif i < 10:\n rad = 10 + (random.random() * 4) # Big cells\n else:\n rad = 2 + (random.random() * 9) # Everything else\n x = Consts[\"WORLD_X\"] * random.random()\n y = Consts[\"WORLD_Y\"] * random.random()\n cell = Cell(i + 2, [x, y], [(random.random() - 0.5) * 2, (random.random() - 0.5) * 2], rad)\n safe_dist = Consts[\"SAFE_DIST\"] + rad\n while min(map(cell.distance_from, self.cells[:2])) < safe_dist:\n cell.pos = [\n Consts[\"WORLD_X\"] * random.random(),\n Consts[\"WORLD_Y\"] * random.random()\n ]\n self.cells.append(cell)","def generate_random_toy() -> Toy:\n dimensions = round(uniform(5, 100), 2)\n rooms_number = randint(1, 5)\n return SantaWorkShop(dimensions, rooms_number, 5)","def create_grid(player1: game_code.Player, player2: game_code.Player) -> None:\r\n status = True\r\n abort = False\r\n\r\n # Initialize two game board both with randomized ship placements\r\n player_1 = game_code.RandomizedBattleshipGame()\r\n player_2 = game_code.RandomizedBattleshipGame()\r\n\r\n player_1_sequence = []\r\n player_2_sequence = []\r\n player_1_previous_move = None\r\n player_2_previous_move = None\r\n\r\n save_initial_state1 = player_1\r\n save_initial_state2 = player_2\r\n\r\n escape = instruction_font.render('HIT ESC TO RETURN TO THE MAIN MENU OR TO START A NEW GAME', False,\r\n (255, 255, 255))\r\n player_label_1 = label_font.render('Player 1', False, (255, 255, 255))\r\n player_label_2 = label_font.render('Player 2', False, (255, 255, 255))\r\n\r\n while status:\r\n screen.blit(background, (0, 0))\r\n\r\n # Draw the grids belonging to each player\r\n for column in range(0, 8):\r\n for row in range(0, 8):\r\n cell = pygame.Rect((190 + column * 50, 160 + row * 50), (50, 50))\r\n pygame.draw.rect(screen, (255, 255, 255, 1), cell, 0)\r\n pygame.draw.rect(screen, (0, 0, 0, 1), cell, 3)\r\n\r\n for column in range(0, 8):\r\n for row in range(0, 8):\r\n cell = pygame.Rect((690 + column * 50, 160 + row * 50), (50, 50))\r\n pygame.draw.rect(screen, (255, 255, 255, 1), cell, 0)\r\n pygame.draw.rect(screen, (0, 0, 0, 1), cell, 3)\r\n\r\n # Display labels and text\r\n screen.blit(player_label_1, (340, 580))\r\n screen.blit(player_label_2, (840, 580))\r\n screen.blit(escape, (25, 685))\r\n\r\n columns = 'ABCDEFGH'\r\n rows = '12345678'\r\n # Label Player 1 Board\r\n for letter in range(0, 8):\r\n label = label_font.render(columns[letter], False, (255, 255, 255))\r\n screen.blit(label, (205 + letter * 50, 125))\r\n for number in range(0, 8):\r\n label = label_font.render(rows[number], False, (255, 255, 255))\r\n screen.blit(label, (165, 170 + number * 50))\r\n # Label Player 2 Board\r\n for letter in range(0, 8):\r\n label = label_font.render(columns[letter], False, (255, 255, 255))\r\n screen.blit(label, (705 + letter * 50, 125))\r\n for number in range(0, 8):\r\n label = label_font.render(rows[number], False, (255, 255, 255))\r\n screen.blit(label, (665, 170 + number * 50))\r\n\r\n # Display the ships prior to starting the game\r\n display_ships(save_initial_state1, True)\r\n display_ships(save_initial_state2, False)\r\n\r\n if player_1_previous_move is None and player_2_previous_move is None:\r\n pygame.display.update()\r\n pygame.time.wait(1000)\r\n\r\n while player_1.get_winner() is None and player_2.get_winner() is None and not abort:\r\n\r\n # player1 shot on player2 Board\r\n player_1_previous_move = player1.make_move(player_2, player_1_previous_move)\r\n player_2.make_move(player_1_previous_move)\r\n player_1_sequence.append(player_1_previous_move)\r\n if player_2.get_winner() is not None:\r\n break\r\n # player1 on player2 Board\r\n player_2_previous_move = player2.make_move(player_1, player_2_previous_move)\r\n player_1.make_move(player_2_previous_move)\r\n player_2_sequence.append(player_2_previous_move)\r\n\r\n for event in pygame.event.get():\r\n if event.type == pygame.QUIT:\r\n pygame.quit()\r\n sys.exit()\r\n if event.type == pygame.KEYDOWN:\r\n if event.key == pygame.K_ESCAPE:\r\n abort = True\r\n status = False\r\n\r\n display_ships(player_1, True)\r\n pygame.time.wait(500)\r\n pygame.display.update()\r\n pygame.time.wait(500)\r\n display_ships(player_2, False)\r\n pygame.display.update()\r\n\r\n # Display the victory message of the winning player\r\n if player_1.get_winner() == 'Lost':\r\n winner = 'Player 2'\r\n victory = message_font.render(winner + ' Wins!', False, (255, 255, 255))\r\n screen.blit(victory, (450, 50))\r\n else:\r\n winner = 'Player 1'\r\n victory = message_font.render(winner + ' Wins!', False, (255, 255, 255))\r\n screen.blit(victory, (450, 50))\r\n\r\n # Display the final state of the game\r\n display_ships(player_1, True)\r\n display_ships(player_2, False)\r\n\r\n # Check for user input\r\n for event in pygame.event.get():\r\n if event.type == pygame.QUIT:\r\n pygame.quit()\r\n sys.exit()\r\n if event.type == pygame.KEYDOWN:\r\n if event.key == pygame.K_ESCAPE:\r\n status = False\r\n\r\n pygame.display.update()","def generate_board():\n b = open(_BOARD_FILE, \"r\").readlines()\n for line in b:\n raw = line.strip().split(\" \")\n _board_graph[str_to_pos(raw[0])] = Space(\n (raw[1] == \"R\"),\n TYPE_MAP[raw[1]],\n {str_to_pos(str_pos) for str_pos in raw[2:]})","def randPlace(self):\r\n random.seed(self.seed)\r\n \r\n # Start placement on Partition A\r\n partA = True\r\n for node in self.G.nodes():\r\n \r\n randSite = random.randint(0,int(self.sitesNum/2)-1)\r\n \r\n if partA:\r\n partSite = self.sitesA\r\n self.G.node[node][\"part\"] = 'A'\r\n \r\n else:\r\n partSite = self.sitesB\r\n self.G.node[node][\"part\"] = 'B'\r\n \r\n while (partSite[randSite].isOcp()):\r\n randSite = random.randint(0,int(self.sitesNum/2)-1) \r\n\r\n partSite[randSite].setCell(node)\r\n self.G.node[node][\"site\"] = partSite[randSite]\r\n \r\n # Toggle partition for next placement\r\n partA = not partA"],"string":"[\n \"def generate(self):\\n for i in range(4):\\n random_first = randomize_first_box()\\n self.randomize(random_first)\\n for i in range(9):\\n random_pos = randomize_position()\\n self.randomize(random_pos)\\n self.board.solve()\",\n \"def draw_random_setup(types_available, team, game_dim):\\n\\n nr_pieces = len(types_available)-1\\n types_available = [type_ for type_ in types_available if not type_ == 0]\\n if game_dim == 5:\\n row_offset = 2\\n elif game_dim == 7:\\n row_offset = 3\\n else:\\n row_offset = 4\\n setup_agent = np.empty((row_offset, game_dim), dtype=object)\\n if team == 0:\\n flag_positions = [(game_dim-1, j) for j in range(game_dim)]\\n flag_choice = np.random.choice(range(len(flag_positions)), 1)[0]\\n flag_pos = game_dim-1 - flag_positions[flag_choice][0], game_dim-1 - flag_positions[flag_choice][1]\\n setup_agent[flag_pos] = pieces.Piece(0, 0, flag_positions[flag_choice])\\n\\n types_draw = np.random.choice(types_available, nr_pieces, replace=False)\\n positions_agent_0 = [(i, j) for i in range(game_dim-row_offset, game_dim) for j in range(game_dim)]\\n positions_agent_0.remove(flag_positions[flag_choice])\\n\\n for idx in range(nr_pieces):\\n pos = positions_agent_0[idx]\\n setup_agent[(game_dim-1 - pos[0], game_dim-1 - pos[1])] = pieces.Piece(types_draw[idx], 0, pos)\\n elif team == 1:\\n flag_positions = [(0, j) for j in range(game_dim)]\\n flag_choice = np.random.choice(range(len(flag_positions)), 1)[0]\\n setup_agent[flag_positions[flag_choice]] = pieces.Piece(0, 1, flag_positions[flag_choice])\\n\\n types_draw = np.random.choice(types_available, nr_pieces, replace=False)\\n positions_agent_1 = [(i, j) for i in range(row_offset) for j in range(game_dim)]\\n positions_agent_1.remove(flag_positions[flag_choice])\\n\\n for idx in range(nr_pieces):\\n pos = positions_agent_1[idx]\\n setup_agent[pos] = pieces.Piece(types_draw[idx], 1, pos)\\n return setup_agent\",\n \"def generate(self, site_type='random', arg='random'):\\n size = entities.world['size']\\n if site_type == 'random':\\n if randint(1,3) == 1:\\n site_type = 'adventure'\\n else:\\n site_type = 'resource'\\n elif site_type in ref.material_type_dct.keys():\\n self.resource = site_type\\n site_type = 'resource'\\n terrain_list = None\\n if arg == 'random':\\n terrain_list = [x for x in ref.terrain_dct.keys() if type(x) == int]\\n elif arg in ref.terrain_type_list:\\n terrain_list = [\\n x for x in ref.terrain_dct.keys() if ref.terrain_dct[x]['terrain type'] == arg\\n ]\\n x = randint(0, size-1)\\n y = randint(0, size-1)\\n terrain_type = entities.world['grid'][y][x]\\n site_locations = [s.location for s in entities.sites['object list']]\\n while terrain_type not in terrain_list or [x,y] in site_locations:\\n x = randint(0, size-1)\\n y = randint(0, size-1)\\n terrain_type = entities.world['grid'][y][x]\\n\\n self.location = [x,y]\\n self.structure = Structure().generate(\\n ref.terrain_dct[terrain_type]['terrain type'], site_type\\n )\\n if self.resource == None:\\n if 'resource type' in ref.structure_type_dct[\\n self.structure.structure_type\\n ].keys():\\n resource_type = ref.structure_type_dct[\\n self.structure.structure_type]['resource type'\\n ]\\n resource_possibilities = []\\n for possible_material in [\\n x for x in ref.material_class_dct[resource_type][\\n 'types'] if 'rarity' in ref.material_type_dct[x].keys()\\n ]:\\n for x in xrange(ref.rarity_dct[\\n ref.material_type_dct[possible_material]['rarity']\\n ]):\\n resource_possibilities.append(possible_material)\\n self.resource = choice(resource_possibilities)\\n #resources measured in grams\\n if self.resource != None:\\n self.harvestable = randint(100000, 1500000)\\n try:\\n entities.town['object'].resources[\\n ref.material_type_dct[self.resource]['class']][\\n self.resource]['harvestable'] += self.harvestable\\n except KeyError:\\n pass\\n #NOTE: These numbers suitable for metal, may not be for other materials\\n #NOTE: Mine production should be ~1kg pure metal per day per miner.\\n #NOTE: IRL mine has ~43500kg before producing much less.\\n \\n self.set_site_id()\\n return self\",\n \"def gen_world(num_rows, num_cols):\\n world = collections.deque()\\n\\n # Generate top perimeter.\\n world.append([eg.ROCK] * num_cols)\\n\\n # In between top and bottom perimeters, generate a clean world.\\n # (all non-perimeter cells are clear)\\n for i in xrange(num_rows - 2):\\n world.append([eg.ROCK] + ([eg.NONE] * (num_cols - 2)) + [eg.ROCK])\\n\\n # Generate bottom perimeter.\\n world.append([eg.ROCK] * num_cols)\\n\\n # Apply red anthill in world.\\n _randomly_apply_anthill(world, eg.RED)\\n\\n # Apply black anthill in world.\\n _randomly_apply_anthill(world, eg.BLACK)\\n\\n # Apply food blocks in world.\\n _randomly_apply_foodblob(world)\\n\\n # Apply rocks in world.\\n _randomly_apply_rocks(world)\\n\\n world.appendleft([str(num_rows)])\\n world.appendleft([str(num_cols)])\\n\\n return world\",\n \"def generate_world(x_size, y_size):\\n\\n\\tdef make_blank_world():\\n\\t\\t\\\"\\\"\\\"\\n\\t\\tCreates an x-by-y list of lists of zeroes.\\n\\t\\t\\\"\\\"\\\"\\n\\t\\tblank_array = [[Blank() for j in range(y_size + 1)] for i in range(x_size + 1)]\\n\\t\\treturn blank_array\\n\\n\\n\\tdef check_surroundings(x_coord, y_coord, value):\\n\\t\\t\\\"\\\"\\\"\\n\\t\\tIf the variable world has already been defined, it checks all x and y coords within one square (aka, checks the 8 surrounding squares) for a given value. If that value is present in 1 or more squares, returns True; else, False.\\n\\t\\t\\\"\\\"\\\"\\n\\t\\tfor i in range(3):\\n\\t\\t\\tfor j in range(3):\\n\\t\\t\\t\\texamining = world[x_coord - 1 + i][y_coord - 1 + j]\\n\\t\\t\\t\\tif examining.name == value:\\n\\t\\t\\t\\t\\treturn True\\n\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\tpass\\n\\t\\treturn False\\n\\n\\n\\tworld = make_blank_world()\\n\\n\\tworld[random.randint(2, x_size-2)][random.randint(2, y_size-2)] = Water()\\n\\n\\tfor i in range(x_size):\\n\\t\\tfor j in range(y_size):\\n\\t\\t\\tseed = random.random()\\n\\t\\t\\tif check_surroundings(i, j, 'water'):\\n\\t\\t\\t\\tif seed >= 0.5:\\n\\t\\t\\t\\t\\tworld[i][j] = Water()\\n\\t\\t\\t\\telif seed >= 0.4:\\n\\t\\t\\t\\t\\tworld[i][j] = Tree()\\n\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\tworld[i][j] = Grass()\\n\\t\\t\\telif not check_surroundings(i, j, 'tree'):\\n\\t\\t\\t\\tif seed >= 0.5:\\n\\t\\t\\t\\t\\tworld[i][j] = Tree()\\n\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\tworld[i][j] = Grass()\\n\\t\\t\\telse:\\n\\t\\t\\t\\tworld[i][j] = Grass()\\n\\treturn [row[:y_size+1] for row in world[:x_size+1]]\",\n \"def make_board(self):\\n generate = lambda: random.randint(1, 100) in range(1, self.p_pit+1)\\n some_number = self.some_number\\n agent = Agent(some_number)\\n agent.program = Oozeplorer_Percept(agent)\\n self.add_agent(agent)\\n gold = Gold()\\n self.add_thing(gold, None)\\n for row in range(1, some_number + 1):\\n for col in range(1, some_number + 1):\\n valid_spot = (row, col) != gold.location and (row, col) != (1, 1)\\n if valid_spot and generate():\\n t_pt = Pit()\\n t_pt.location = (row, col)\\n self.things.append(t_pt)\",\n \"def fill_with_random_tiles(self):\\n for elem in [x[1] for x in self.tile_grid.values()]:\\n self.view.remove(elem)\\n tile_grid = {}\\n # Fill the data matrix with random tile types\\n while True: # Loop until we have a valid table (no imploding lines)\\n for x in range(COLS_COUNT):\\n for y in range(ROWS_COUNT):\\n tile_type, sprite = choice(self.available_tiles), None\\n tile_grid[x, y] = tile_type, sprite\\n if len(self.get_same_type_lines(tile_grid)) == 0:\\n break\\n tile_grid = {}\\n\\n # Build the sprites based on the assigned tile type\\n for key, value in tile_grid.items():\\n tile_type, sprite = value\\n sprite = self.tile_sprite(tile_type, self.to_display(key))\\n tile_grid[key] = tile_type, sprite\\n self.view.add(sprite)\\n\\n self.tile_grid = tile_grid\",\n \"def generate_world(world_seed, biome_min, biome_max, w, h):\\n\\n while True:\\n\\n try:\\n\\n # Set the initial seed for the random module (random.seed())\\n seed(world_seed)\\n\\n # Create a blank map (2D list filled with '0' strings\\n world = [[0 for y in range(h)] for x in range(w)]\\n # Generates the random values for the terrain construction\\n terrain = [randrange(20) + 40 for _ in range(w)]\\n\\n #Empty biome map\\n biomes = []\\n\\n #Generates biomes\\n for __ in range(w//biome_min):\\n\\n #Biome at cursor\\n biome_select = choice(list(biome_data))\\n\\n #Biomes size\\n for _ in range(randint(biome_min, biome_max)):\\n biomes.append(biome_select)\\n\\n #World size met\\n if len(biomes) >= w:\\n biomes = biomes[:w] #Truncate selection\\n break\\n\\n\\n # ----- Construct the Terrain\\n # Counter that changes dynamically to check through all blocks in the terrain list\\n cur_pos = 0\\n # Runs through all the generated numbers in a while loop\\n while cur_pos < w:\\n\\n # print(\\\".\\\", end=\\\"\\\")\\n\\n # Check to see if terrain gap is too large\\n\\n if abs(terrain[cur_pos] - terrain[cur_pos - 1]) > biome_data[str(biomes[cur_pos])][\\\"maxh\\\"]: # if terrain gap is larger than threshhold (too big)\\n\\n for n in range(randint(biome_data[str(str(biomes[cur_pos]))][\\\"minx\\\"], biome_data[str(str(biomes[cur_pos]))][\\\"maxx\\\"])):\\n # Insert a new value into the terrain list between the values that are too far apart\\n terrain.insert(cur_pos, (terrain[cur_pos] + terrain[cur_pos - 1]) // 2)\\n\\n else: # Difference between the two blocks is not too big\\n\\n # Check next block\\n cur_pos += 1\\n\\n # ----- Transfer Terrain To Empty World\\n # Run through every space in the empty world\\n for x in range(len(world)): # runs through each level\\n for y in range(len(world[x])): # runs through each individual space\\n\\n # Generates structures\\n if y > terrain[x]:\\n\\n #Top layer\\n if y - terrain[x] == 1:\\n\\n #Sets the layer with block specified in biome config\\n world[x][y] = block_lookup[biome_data[biomes[x]][\\\"layer\\\"][\\\"top\\\"]]\\n\\n if randint(0, 10) == 0 and x + 10 < w:\\n world = generate_structure(x, y - 1, world, choice(biome_data[biomes[x]][\\\"structure\\\"]))\\n\\n #Middle layer\\n elif y - terrain[x] < randint(3, 8):\\n world[x][y] = block_lookup[biome_data[biomes[x]][\\\"layer\\\"][\\\"middle\\\"]]\\n\\n #Base\\n else:\\n world[x][y] = block_lookup[biome_data[biomes[x]][\\\"layer\\\"][\\\"lower\\\"]]\\n\\n #Generate ores\\n # Coal\\n if 10 + terrain[x] > y > 5 + terrain[x] and randint(0, 200) == 0:\\n for cluster in range(randint(3, 10)):\\n world[x + randint(-4, 4)][y + randint(-4, 4)] = block_lookup[\\\"Coal Ore\\\"]\\n\\n # Iron\\n if 30 + terrain[x] > y > 20 + terrain[x] and randint(0, 200) == 0:\\n\\n for cluster in range(randint(3, 6)):\\n world[x + randint(-4, 4)][y + randint(-4, 4)] = block_lookup[\\\"Iron Ore\\\"]\\n\\n # Gold\\n if 80 > y > 65 and randint(0, 400) == 0:\\n for cluster in range(randint(3, 6)):\\n world[x + randint(-4, 4)][y + randint(-4, 4)] = block_lookup[\\\"Gold Ore\\\"]\\n\\n # Diamonds\\n if 80 > y > 70 and randint(0, 500) == 0:\\n for cluster in range(randint(1, 5)):\\n world[x + randint(-3, 3)][y + randint(-3, 3)] = block_lookup[\\\"Diamond Ore\\\"]\\n\\n # Bedrock\\n if y > 92 or y > 87 and randint(0, 3) == 0:\\n world[x][y] = block_lookup[\\\"Bed Rock\\\"]\\n\\n # Last edit, adding extras to the top of the world to prevent problems\\n world = [[0] * 40 + x for x in world]\\n\\n # Return the world object for use\\n return np.array(world)\\n\\n except:\\n world_seed += '1'\",\n \"def generatePiece(self):\\n\\n empty_tiles = []\\n for y in range(BOARD_SIZE):\\n for x in range(BOARD_SIZE):\\n if self.grid[x][y].isEmpty():\\n empty_tiles.append(self.grid[x][y])\\n\\n two_or_four = random.choice([2, 4])\\n random.choice(empty_tiles).set(two_or_four)\",\n \"def random_map(self, world):\\n obstacles = []\\n if self.cfg[\\\"obstacle\\\"][\\\"octagon\\\"][\\\"enabled\\\"]:\\n obstacles += self.__generate_octagon_obstacles(world)\\n if self.cfg[\\\"obstacle\\\"][\\\"rectangle\\\"][\\\"enabled\\\"]:\\n obstacles += self.__generate_rectangle_obstacles(world)\\n\\n # update the current obstacles and goal\\n self.current_obstacles = obstacles\\n self.add_new_goal()\\n\\n # apply the new obstacles and goal to the world\\n self.apply_to_world(world)\",\n \"def random_place(board, player):\\n available = possibilities(board)\\n place(board, player, random.choice(available))\",\n \"def generate(self, level):\\n # TODO The dungeon's instances are spawned and loaded here.\\n # fill map with \\\"blocked\\\" tiles\\n level.maze = [[Tile(x, y, True) for y in range(level.height)] for x in range(level.width)]\\n\\n for r in range(level.max_rooms):\\n # random width and height\\n w = random.randint(level.min_room_size, level.max_room_size)\\n h = random.randint(level.min_room_size, level.max_room_size)\\n\\n # random position without going out of the boundaries of the map\\n x = random.randint(0, level.width - w - 1)\\n y = random.randint(0, level.height - h - 1)\\n\\n # \\\"DungeonRoom\\\" class makes rectangles easier to work with\\n new_room = Room(x, y, w, h)\\n level.rooms.append(new_room)\\n\\n # run through the other rooms and see if they intersect with this one\\n failed = False\\n for other_room in level.rooms:\\n if other_room is not new_room and new_room.intersect(other_room):\\n failed = True\\n break\\n\\n if not failed:\\n # this means there are no intersections, so this room is valid\\n\\n # \\\"paint\\\" it to the map's tiles\\n self._create_room(level, new_room)\\n\\n # center coordinates of new room, will be useful later\\n new_x, new_y = new_room.center()\\n\\n if level.num_rooms > 0:\\n # connect it to the previous room with a tunnel\\n # center coordinates of previous room\\n (prev_x, prev_y) = level.rooms[level.num_rooms - 1].center()\\n\\n # draw a coin (random number that is either 0 or 1)\\n if random.randint(0, 1) == 1:\\n # first move horizontally, then vertically\\n self._create_h_tunnel(level, prev_x, new_x, prev_y)\\n self._create_v_tunnel(level, prev_y, new_y, new_x)\\n else:\\n # first move vertically, then horizontally\\n self._create_v_tunnel(level, prev_y, new_y, prev_x)\\n self._create_h_tunnel(level, prev_x, new_x, new_y)\\n\\n # finally, append the new room to the list\\n level.rooms.append(new_room)\\n level.num_rooms += 1\\n\\n # connect them with a tunnel\\n self._create_h_tunnel(level, 25, 55, 23)\",\n \"def generate_mine_map(width=30, height=16, num_mines=99):\\n\\n if num_mines > width * height:\\n print(\\\"The number of mines exceeds the size of the board.\\\")\\n return\\n \\n mine_map = [[False for i in range(width)] for j in range(height)]\\n mines = 0\\n while mines < num_mines:\\n x = random.randint(0, width-1)\\n y = random.randint(0, height-1)\\n if not mine_map[y][x]:\\n mine_map[y][x] = True\\n mines += 1\\n\\n return mine_map\",\n \"def generate_grains(self, cells):\\n\\t\\tfor cell_num in range(cells):\\n\\t\\t\\trandom_row = random.randrange(0,self.space.shape[0],1)\\n\\t\\t\\tsample_cell = np.random.choice(self.space[random_row],1)\\n\\t\\t\\tsample_cell = sample_cell[0]\\n\\t\\t\\twhile sample_cell.state != 0:\\n\\t\\t\\t\\trandom_row = random.randrange(0,self.space.shape[0],1)\\n\\t\\t\\t\\tsample_cell = np.random.choice(self.space[random_row],1)\\n\\t\\t\\t\\tsample_cell = sample_cell[0]\\n\\t\\t\\tsample_cell.change_state(self.init_time ,cell_num)\",\n \"def new_tile(self):\\r\\n # replace with your code\\r\\n empty_square_lists = []\\r\\n for row in range(self._grid_height):\\r\\n for col in range(self._grid_width):\\r\\n if(self.get_tile(row, col) == 0):\\r\\n empty_square_lists.append((row, col))\\r\\n \\r\\n if len(empty_square_lists) == 0:\\r\\n return \\\"game over!\\\"\\r\\n \\r\\n random_cell = random.choice(empty_square_lists)\\r\\n random_cell_row = random_cell[0]\\r\\n random_cell_col = random_cell[1]\\r\\n \\r\\n values = [2] * 90 + [4] * 10\\r\\n value = random.choice(values)\\r\\n \\r\\n self.set_tile(random_cell_row, random_cell_col, value)\",\n \"def new_tile(self):\\n while True:\\n random_row = random.randrange(self._grid_height)\\n random_column = random.randrange(self._grid_width)\\n if self._grid[random_row][random_column] == 0:\\n self._grid[random_row][random_column] = random.choice([2] * 9 + [4])\\n break\",\n \"def new_tile(self):\\r\\n random_row = random.randrange(0, self._grid_height)\\r\\n random_col = random.randrange(0, self._grid_width)\\r\\n random_choice = random.choice([2]*90 + [4] * 10)\\r\\n \\r\\n if 0 in [num for elem in self._cells for num in elem]: \\r\\n if self._cells[random_row][random_col] == 0:\\r\\n self._cells[random_row][random_col] = random_choice \\r\\n else:\\r\\n self.new_tile()\\r\\n else:\\r\\n pass\",\n \"def random_grid(height, width):\\n grid = create_grid(height, width)\\n for r in range(1, height - 1):\\n for c in range(1, width - 1):\\n grid[r][c] = random.choice([0, 1])\\n return grid\",\n \"def _generate_building(self, min_size, max_size, modulo_rest=2, name=None, one_connection=False):\\n size_x = random.randint(min_size[0], max_size[0])\\n size_y = random.randint(min_size[1], max_size[1])\\n if modulo_rest < 2:\\n while size_x % 2 != modulo_rest:\\n size_x = random.randint(min_size[0], max_size[0])\\n while size_y % 2 != modulo_rest:\\n size_y = random.randint(min_size[1], max_size[1])\\n return TownRegion._Building((size_x, size_y), name=name, one_connection=one_connection)\",\n \"def randomCells(width, height):\\r\\n\\tA = createBoard(height, width)\\r\\n\\r\\n\\tfor row in range(height):\\r\\n\\t\\tfor col in range(width):\\r\\n\\t\\t\\tif row > 0 and row < height-1:\\r\\n\\t\\t\\t\\tif col > 0 and col < width-1:\\r\\n\\t\\t\\t\\t\\tA[row][col] = random.choice([0,1]) \\r\\n\\r\\n\\treturn A\",\n \"def randomSchedule(self,contents):\\n\\t\\timport random as ran\\n import copy\\n\\t\\tcontents_copy = copy.deepcopy(contents)\\n\\t\\tsol = Area('sb',ran.random())\\n\\t\\twhile contents_copy:\\n\\t\\t\\tcont = ran.choice(contents_copy)\\n\\t\\t\\ti = 0\\n\\t\\t\\twhile True:\\n\\t\\t\\t\\tran_waiting = ran.randint(0,2)\\n\\t\\t\\t\\tran_start = ran.randint(0,19)\\n\\t\\t\\t\\tif sol.checkAddContent(ran_waiting,ran_start,cont):\\n\\t\\t\\t\\t\\tsol.addContent(ran_waiting,ran_start,cont)\\n\\t\\t\\t\\t\\tcontents_copy.remove(cont)\\n\\t\\t\\t\\t\\tbreak\\n\\t\\t\\t\\ti += 1\\n\\t\\t\\t\\tif i>150:\\n\\t\\t\\t\\t\\t#print \\\"cut\\\"\\n\\t\\t\\t\\t\\tsol = Area('sb',ran.random())\\n\\t\\t\\t\\t\\tcontents_copy = contents[:]\\n\\t\\t\\t\\t\\tbreak\\n\\t\\t#print \\\"generate new schedule\\\\n\\\",sol.printSchedule()\\n\\t\\treturn sol\",\n \"def random_world():\\n # Create empty world\\n grid = np.zeros((WORLD_WIDTH, WORLD_WIDTH))\\n # Add dirt and obstacles\\n for r in range(WORLD_WIDTH):\\n for c in range(WORLD_WIDTH):\\n if random.random() < 0.5:\\n grid[r, c] = DIRT\\n elif random.random() < 0.1:\\n grid[r, c] = OBSTACLE\\n # Place agent\\n while True:\\n r = random.randrange(WORLD_WIDTH)\\n c = random.randrange(WORLD_WIDTH)\\n if grid[r, c] == EMPTY:\\n return grid, r, c\",\n \"def trial(length, height):\\n screen.refresh()\\n global stimList\\n global oddLength\\n global oddHeight\\n currentLength = int(maxLength / 4)\\n currentHeight = int(maxHeight / 4)\\n for i in range(stimAmt):\\n if i == oddLocation:\\n oddLength = currentLength\\n oddHeight = currentHeight\\n stimList.append(\\n pg.draw.rect(\\n screen.fg,\\n PgTools.rand_color(),\\n (currentLength, currentHeight, length, height,),\\n )\\n )\\n PgTools.rand_pattern(\\n screen.fg,\\n (\\n currentLength,\\n currentHeight,\\n ),\\n (length, height),\\n i=(randint(0, 2), randint(0, 1)),\\n )\\n if randShapes:\\n PgTools.rand_shape(screen.fg, (currentLength, currentHeight),(length, height), oddSeed)\\n else:\\n stimList.append(\\n pg.draw.rect(\\n screen.fg,\\n color,\\n (currentLength, currentHeight, length, height,),\\n )\\n )\\n PgTools.rand_pattern(\\n screen.fg,\\n (\\n currentLength,\\n currentHeight,\\n ),\\n (length, height),\\n patColor,\\n randNums,\\n )\\n if randShapes:\\n PgTools.rand_shape(screen.fg, (currentLength, currentHeight),(length, height), regSeed)\\n currentLength += maxLength / 4\\n currentLength = int(currentLength)\\n if (i + 1) % 3 == 0:\\n currentLength = maxLength / 4\\n currentLength = int(currentLength)\\n currentHeight += maxHeight / 4\\n currentHeight= int(currentHeight)\",\n \"def generate(self, n_enemies, n_blocks):\\n self.create_map()\\n self.create_floor()\\n self.player = self.create_player_at(0, 0)\\n self.create_dummy_obj_at(0, 1)\\n self.create_dummy_obj_at(1, 0)\\n self.create_soft_block_at(0, 2)\\n self.create_soft_block_at(2, 0)\\n self.create_hard_blocks() \\n self.create_enemies(n_enemies)\\n self.create_soft_blocks(n_blocks) \\n self.clear_dummy_obj()\",\n \"def generateTestProblem(printTerrain = False):\\r\\n size = random.randint(5, 100)\\r\\n print(size)\\r\\n start = (random.randint(0, size - 1), random.randint(0, size - 1))\\r\\n print(start)\\r\\n goal = (random.randint(0, size - 1), random.randint(0, size - 1))\\r\\n print(goal)\\r\\n terrain = [[random.choice(['m', 'p', 's', 'w']) for i in range(0, size)] for j in range(0, size)]\\r\\n\\r\\n # print the terrain matrix if required\\r\\n if printTerrain:\\r\\n for i in range(0, size):\\r\\n print(terrain[i])\\r\\n\\r\\n return (start, goal, terrain)\",\n \"def initialize_puzzle_board(self, n=3, hType=1, random=True, diff=None):\\r\\n\\t\\tself.n = n\\r\\n\\r\\n\\t\\t# While loop to continuously create random boards until a solvable one is made.\\r\\n\\t\\tboardList = [x for x in range(n**2)]\\r\\n\\t\\twhile random:\\r\\n\\t\\t\\tshuffle(boardList)\\r\\n\\r\\n\\t\\t\\tif self.generated_solvable(boardList):\\r\\n\\t\\t\\t\\tprint \\\"Found something solvable:\\\", boardList\\r\\n\\t\\t\\t\\tbreak # From outer While-True\\r\\n\\r\\n\\t\\t# If statements to use non-random, burnt-in boards of various difficulties.\\r\\n\\t\\tif not random and n == 3:\\r\\n\\t\\t\\tif diff == 0:\\r\\n\\t\\t\\t\\tboardList = [3,1,2,4,7,5,6,8,0]\\r\\n\\t\\t\\telif diff == 1:\\r\\n\\t\\t\\t\\tboardList = [3,2,5,4,1,8,6,0,7]\\r\\n\\t\\t\\telif diff == 2:\\r\\n\\t\\t\\t\\tboardList = [1,0,6,5,7,4,2,3,8]\\r\\n\\r\\n\\t\\telif not random and n == 4:\\r\\n\\t\\t\\tif diff == 0:\\r\\n\\t\\t\\t\\tboardList = [4,1,2,3,5,0,6,7,8,9,10,11,12,13,14,15]\\r\\n\\r\\n\\t\\t# Location of 0 (the empty tile) in the flat list.\\r\\n\\t\\tlocZero = boardList.index(0)\\r\\n\\r\\n\\t\\t# Using floor division and modulo to attain the nested location of the 0\\r\\n\\t\\tself.x = locZero // self.n\\r\\n\\t\\tself.y = locZero % self.n\\r\\n\\r\\n\\t\\t# Looping over the flat list and appending it, creating the nested list that is the final board\\r\\n\\t\\tfor i in range(self.n):\\r\\n\\t\\t\\ti1, i2 = self.n*i, self.n*(i+1)\\r\\n\\t\\t\\tself.board.append(boardList[i1:i2])\\r\\n\\r\\n\\t\\t# Double checking that we determined 0's position correctly.\\r\\n\\t\\tassert( self.board[self.x][self.y] == 0 )\\r\\n\\r\\n\\t\\t# Generate the goal (class variable) for the board based on size\\r\\n\\t\\tself.generate_goal()\\r\\n\\t\\t# Generates the heuristic value for this first board.\\r\\n\\t\\tself.generate_heuristic()\\r\\n\\t\\t# Generates the hash value for __eq__ from the board.\\r\\n\\t\\tself.eqHash = hash(str(self))\",\n \"def make_random_move(self):\\n choice = None\\n options = []\\n #generate full moves list\\n for i in range(self.width):\\n for j in range(self.height):\\n #make sure move has not been made\\n if (i,j) not in self.moves_made:\\n #make sure move is not a mine\\n if (i,j) not in self.mines:\\n options.append((i,j))\\n #if there are no options, return None\\n if len(options) == 0:\\n return None\\n\\n #pick a random option from generated list\\n choice = random.choice(options)\\n return choice\\n\\n \\\"\\\"\\\"\\n For kicks and giggles I wrote this extra bit to determine a\\n rough intuitive probability for each option based on the knowledge\\n base, so rather than picking a choice randomly the AI can choose\\n the option that is, at least intuitively, least likely to blow up.\\n Better to take the 1/8 chance than the 1/3 chance, right?\\n \\\"\\\"\\\"\\n best_chance = 1\\n #iterate through generated options\\n for option in options:\\n #Could set chance to 1/8, but the AI wouldn't actually know that. I\\n #only know it because I can read the code...But for the purposes of this\\n #drill we'll say the AI doesn't know how many bombs are placed.\\n #Better then to pick a square we know nothing about than one that\\n #has a 1/8 chance of exploding. Gather more information that way.\\n chance = 0\\n for sentence in self.knowledge:\\n #look to see if current option is in sentences\\n if option in sentence.cells:\\n #use sentence count and length of cell set to calculate probability\\n prob = sentence.count / len(sentence.cells)\\n if prob > chance:\\n #Looking for the highest explosive probability for this square\\n chance = prob\\n if chance < best_chance:\\n #If this option has lower odds of exploding than current best, it becomes\\n #the optimal\\n best_chance = chance\\n choice = option\\n\\n #return choice\",\n \"def randomCells(w, h):\\n A = createBoard(w, h)\\n\\n for row in range(1, h-1):\\n for col in range(1, w-1):\\n if random.choice([0, 1]) == 1:\\n A[row][col] = 1\\n else:\\n A[row][col] = 0\\n return A\",\n \"def build_world(self):\\n total_reward_prob = 0.0 # Total probability of any type of reward\\n probs_list = [] # List of reward probabilities\\n \\n # We want to create a list of reward probabilities for numpy's choice method\\n for r in self.rewards:\\n probs_list.append(r.prob)\\n total_reward_prob += r.prob\\n probs_list.append(1.0-total_reward_prob) # Add in the probability of no reward\\n \\n \\n self.world_rewards = [] # Will hold all rewards for this game\\n for y in range(self.world_height):\\n row_rewards = []\\n for x in range(self.world_width):\\n # Given a probability for each reward (including None), select a reward for each cell\\n cell = np.random.choice(self.rewards + [None], p=probs_list)\\n row_rewards.append(cell)\\n self.world_rewards.append(row_rewards)\",\n \"def make_board(self):\\n http = urllib3.PoolManager()\\n r = http.request('GET', 'http://www.cse.msu.edu/~ruppmatt/itm891/tiles.pickle')\\n tiles = pickle.loads(r.data)\\n self.assets = tiles\\n self.gameboard = Image.new('RGBA', (64*(self.world_width+2), 64*(self.world_height+2)))\\n # Laydown land\\n for c in range(0,self.world_width):\\n for r in range(0, self.world_height):\\n x = (c+1)*64\\n y = (r+1)*64\\n tile_ndx = np.random.choice(len(tiles['land']))\\n self.gameboard.paste(tiles['land'][tile_ndx], (x,y)) \\n # Laydown water\\n for c in range(0,self.world_width):\\n x = (c+1)*64\\n yy = (self.world_height+1)*64\\n self.gameboard.paste(tiles['water']['edge_north'], (x,0))\\n self.gameboard.paste(tiles['water']['edge_south'], (x, yy))\\n for r in range(0,self.world_height):\\n y = (r+1)*64\\n xx = (self.world_width+1)*64\\n self.gameboard.paste(tiles['water']['edge_west'], (0,y))\\n self.gameboard.paste(tiles['water']['edge_east'], (xx,y))\\n self.gameboard.paste(tiles['water']['corner_nw'], (0,0))\\n self.gameboard.paste(tiles['water']['corner_sw'], (0,(self.world_height+1)*64))\\n self.gameboard.paste(tiles['water']['corner_ne'], ((self.world_width+1)*64,0))\\n self.gameboard.paste(tiles['water']['corner_se'], ((self.world_width+1)*64,(self.world_height+1)*64))\\n \\n # Some land lines\\n draw = ImageDraw.Draw(self.gameboard)\\n for c in range(0,self.world_width-1):\\n y_1 = 64\\n y_2 = 64*(self.world_height+1)\\n x = (2+c)*64\\n draw.line([(x,y_1),(x,y_2)], fill='white', width=1)\\n for r in range(0,self.world_height-1):\\n y = (2+r)*64\\n x_1= 64\\n x_2 = 64 * (self.world_width+1)\\n draw.line([(x_1,y),(x_2,y)], fill='white', width=1)\\n return\",\n \"def random_cells(w, h):\\n a = create_board(w, h)\\n\\n for row in range(h):\\n for col in range(w):\\n if 0 < row < h - 1 and 0 < col < w - 1:\\n a[row][col] = random.choice([0, 1])\\n else:\\n a[row][col] = 0\\n \\n return a\",\n \"def create_room(self):\\n # iterate through array of room types\\n rooms = []\\n prob_block_5_list = []\\n prob_block_6_list = []\\n\\n for row in self.room_type:\\n for col in row:\\n rooms.append(self.import_template(col))\\n # iterate through rooms to fill screen\\n # this number will be part of how we find location of top left corner of room\\n # based on 5x5 grid of rooms\\n for pos in range(25):\\n # this will iterate through the number of columns in array\\n # the number y will be part of how we find where to place the block on the y axis (according to pygame.draw)\\n for y in range(self.blocks_per_room_y):\\n # this will iterate through the number of rows in array\\n # the number x will be part of how we find where to place the block on the x axis (according to pygame.draw)\\n for x in range(self.blocks_per_room_x):\\n # if cell is a 1 add a platform sprite\\n if rooms[pos][y][x] is 1:\\n #check if platform has another above it for graphics\\n if rooms[pos][y - 1][x] in (0, 3, 4, 7) and y - 1 >= 0:\\n # the cases checked in each of these conditionals are the basic case that check surrounding blocks\\n # to see what platform we should be using, the edge cases, such as if a block is at the edge of\\n # the room, in which case we need to check the neighboring room (array in this case)\\n\\n #check conditions to see if we are using the sprite with with rounded edges on the bottom right and top right\\n if ((y + 1) < self.blocks_per_room_y and (x - 1) >= 0 and (x + 1) < self.blocks_per_room_x\\n and rooms[pos][y + 1][x] is 0 and rooms[pos][y][x + 1] is 0 and rooms[pos][y][x - 1] is 1)\\\\\\n or (x is self.blocks_per_room_x - 1 and y < self.blocks_per_room_y - 1 and pos < 24 and rooms[pos][y + 1][x] is 0 and rooms[pos + 1][y][0] is 0)\\\\\\n or (y is self.blocks_per_room_y - 1 and x < self.blocks_per_room_x - 1 and pos < 20 and rooms[pos][y][x + 1] is 0):\\n block = Platform(self.block_width, self.block_height, 'right', self.theme)\\n #check conditionals to see if we are using the sprite with rounded edges on the bottom left and top left\\n elif ((y + 1) < self.blocks_per_room_y and (x - 1) >= 0 and (x + 1) < self.blocks_per_room_x\\n and rooms[pos][y + 1][x] is 0 and rooms[pos][y][x - 1] is 0 and rooms[pos][y][x + 1] is 1)\\\\\\n or (x is 0 and y < self.blocks_per_room_y - 1 and pos > 0 and rooms[pos][y + 1][x] is 0 and rooms[pos - 1][y][self.blocks_per_room_x - 1] is 0) \\\\\\n or (y is self.blocks_per_room_y - 1 and x > 0 and pos < 20 and rooms[pos][y][x - 1] is 0):\\n block = Platform(self.block_width, self.block_height, 'left', self.theme)\\n #check conditionals to see if we are using the sprite with the rounded corners on top left and top right\\n elif ((x + 1) < self.blocks_per_room_x and (x - 1) >= 0 and rooms[pos][y][x + 1] in (0, 3, 4) and rooms[pos][y][x - 1] in (0, 3, 4))\\\\\\n or (x is 0 and pos > 0 and rooms[pos - 1][y][self.blocks_per_room_x - 1] in (0, 3, 4) and rooms[pos][y][x + 1] in (0, 3, 4))\\\\\\n or (x is self.blocks_per_room_x - 1 and pos < 24 and rooms[pos + 1][y][0] in (0, 3, 4) and rooms[pos][y][x - 1] in (0, 3, 4)):\\n block = Platform(self.block_width, self.block_height, 'round top', self.theme)\\n #check conditionals to see if we are using the sprite with the rounded corner in the top left\\n elif ((y + 1) < self.blocks_per_room_y and (x - 1) >= 0 and (x + 1) < self.blocks_per_room_x\\n and rooms[pos][y + 1][x] is 1 and rooms[pos][y][x - 1] is 0 and rooms[pos][y][x + 1] is 1) \\\\\\n or (x is 0 and y < self.blocks_per_room_y - 1 and pos > 0 and rooms[pos][y + 1][x] is 1 and rooms[pos - 1][y][self.blocks_per_room_x - 1] is 0) \\\\\\n or (y is self.blocks_per_room_y - 1 and x > 0 and pos < 20 and rooms[pos][y][x - 1] is 0):\\n block = Platform(self.block_width, self.block_height, 'top left', self.theme)\\n #check conditionals to see if we are using the sprite with the rounded corner in the top right\\n elif ((y + 1) < self.blocks_per_room_y and (x - 1) >= 0 and (x + 1) < self.blocks_per_room_x\\n and rooms[pos][y + 1][x] is 1 and rooms[pos][y][x + 1] is 0 and rooms[pos][y][x - 1] is 1)\\\\\\n or (x is self.blocks_per_room_x - 1 and y < self.blocks_per_room_y - 1 and pos < 24 and rooms[pos][y + 1][x] is 0 and rooms[pos + 1][y][0] is 0)\\\\\\n or (y is self.blocks_per_room_y - 1 and x < self.blocks_per_room_x - 1 and pos < 20 and rooms[pos][y][x + 1] is 0):\\n block = Platform(self.block_width, self.block_height, 'top right', self.theme)\\n else:\\n block = Platform(self.block_width, self.block_height, 'top', self.theme)\\n else:\\n block = Platform(self.block_width, self.block_height, 'middle', self.theme)\\n coord_x = self.block_width + (pos % 5) * self.room_side_length_x + x * self.block_width\\n block.rect.x = coord_x\\n block.rect.y = self.block_height + (pos // 5) * self.room_side_length_y + y * self.block_height\\n block.player = self.player\\n self.platform_list.add(block)\\n #if the space above this block is empty see if we spawn an enemy on the spot above current block\\n if rooms[pos][y-1][x] is 0 and y - 1 >= 0:\\n self.enemy_generation(coord_x, self.block_height + (pos // 5) * self.room_side_length_y + (y - 1) * self.block_height)\\n # if the cell is a 3 then it will be an item pickup\\n elif rooms[pos][y][x] is 3:\\n rand = random.randrange(0, 4)\\n if rand == 0:\\n #calculate coordinates of the bag\\n bag = pickupSprite('rope')\\n # print('width = ' + str(self.block_width) + ' height = ' + str(self.block_height))\\n bag.rect.x = self.block_width + (pos % 5) * self.room_side_length_x + x * self.block_width\\n bag.rect.y = self.block_height + (pos // 5) * self.room_side_length_y + y * self.block_height\\n bag.player = self.player\\n self.bagGroup.add(bag)\\n elif rand == 1:\\n #calculate coordinates of the bag\\n bag = pickupSprite('knife')\\n # print('width = ' + str(self.block_width) + ' height = ' + str(self.block_height))\\n bag.rect.x = self.block_width + (pos % 5) * self.room_side_length_x + x * self.block_width\\n bag.rect.y = self.block_height + (pos // 5) * self.room_side_length_y + y * self.block_height\\n bag.player = self.player\\n self.bagGroup.add(bag)\\n elif rand == 2:\\n bag = pickupSprite('health')\\n bag.rect.x = self.block_width + (pos % 5) * self.room_side_length_x + x * self.block_width\\n bag.rect.y = self.block_height + (pos // 5) * self.room_side_length_y + y * self.block_height\\n bag.player = self.player\\n self.bagGroup.add(bag)\\n\\n\\n # if the cell is a 4 then it will be either a spike, if the space is on the bottom of the room,\\n # otherwise it is a randomized block or nothing\\n elif rooms[pos][y][x] is 4:\\n # if the cell is at the bottom of the level, randomly choose whether to place a spike or not\\n rand = random.randrange(0, 3)\\n rand2 = random.randrange(0, 2)\\n if y is 6 and rand is 1:\\n spike = enemies.Spikes()\\n spike.rect.x = self.block_width + (pos % 5) * self.room_side_length_x + x * self.block_width\\n spike.rect.y = self.block_height + (pos // 5) * self.room_side_length_y + y * self.block_height\\n spike.player = self.player\\n self.enemy_list.add(spike)\\n # elif y is 6 and rand is 2:\\n # dart = enemies.Darts(self.theme, 'up')\\n # dart.rect.x = self.block_width + (pos % 5) * self.room_side_length_x + x * self.block_width\\n # dart.rect.y = self.block_height + (pos // 5) * self.room_side_length_y + y * self.block_height\\n # dart.player = self.player\\n # self.enemy_list.add(dart)\\n elif y != 6 and rand2 is 0:\\n if rooms[pos][y - 1][x] is 0:\\n block = Platform(self.block_width, self.block_height, 'top', self.theme)\\n else:\\n block = Platform(self.block_width, self.block_height, 'middle', self.theme)\\n block.rect.x = self.block_width + (pos % 5) * self.room_side_length_x + x * self.block_width\\n block.rect.y = self.block_height + (pos // 5) * self.room_side_length_y + y * self.block_height\\n block.player = self.player\\n self.platform_list.add(block)\\n elif y != 6 and rand2 is 1:\\n if x-1 >= 0 and x+1 <= self.blocks_per_room_x and y-1 >= 0 and y+1 < self.blocks_per_room_y:\\n if rooms[pos][y][x-1] is 0:\\n direction = 'left'\\n blockType = 'middle'\\n elif rooms[pos][y][x+1] is 0:\\n direction = 'right'\\n blockType = 'middle'\\n elif rooms[pos][y-1][x] is 0:\\n direction = 'up'\\n blockType = 'top'\\n elif rooms[pos][y+1][x] is 0:\\n direction = 'down'\\n blockType = 'middle'\\n else:\\n direction = None\\n if direction is not None:\\n # use for both block and dart\\n rectX = self.block_width + (pos % 5) * self.room_side_length_x + x * self.block_width\\n rectY = self.block_height + (pos // 5) * self.room_side_length_y + y * self.block_height\\n\\n block = Platform(self.block_width, self.block_height, blockType, self.theme)\\n block.rect.x = rectX\\n block.rect.y = rectY\\n block.player = self.player\\n self.platform_list.add(block)\\n\\n dart = enemies.Darts(self.theme, direction)\\n dart.rect.x = rectX\\n dart.rect.y = rectY\\n dart.player = self.player\\n self.enemy_list.add(dart)\\n # this is the starting and ending points of the level\\n elif rooms[pos][y][x] is 7:\\n # exit of the game on the top row of the level\\n if pos // 5 is 0:\\n #calculate coordinates of the exit\\n self.exit_coords['x'] = self.block_width + (pos % 5) * self.room_side_length_x + x * self.block_width\\n self.exit_coords['y'] = self.block_height + (pos // 5) * self.room_side_length_y + y * self.block_height\\n exit = exit_door_sprite(self.block_width, self.block_height)\\n # print('width = ' + str(self.block_width) + ' height = ' + str(self.block_height))\\n exit.rect.x = self.exit_coords['x']\\n exit.rect.y = self.exit_coords['y']\\n exit.player = self.player\\n self.exit_sprite.add(exit)\\n #entance of the game on the bottom row of the level\\n elif pos // 5 is 4:\\n #calculate coordinates of the entrance\\n self.entrance_coords['x'] = self.block_width + (pos % 5) * self.room_side_length_x + x * self.block_width\\n self.entrance_coords['y'] = self.block_height + (pos // 5) * self.room_side_length_y + y * self.block_height\",\n \"def generate_board(self):\\n random.seed(self.seed)\\n for row in self.grid:\\n for column in row:\\n probability = random.random()\\n if self.live_probability > probability:\\n column.set_alive()\",\n \"def create_random_heads_or_tails(sheet, columns):\\r\\n\\r\\n use_column = 0\\r\\n row = 1\\r\\n for i in range(64):\\r\\n column = columns[use_column]\\r\\n row = row\\r\\n\\r\\n sheet[column + str(row)] = random.randint(0, 1) # assigns 0 or 1 randomly for each cell\\r\\n\\r\\n if use_column == 7: # stops and resets column count\\r\\n use_column = 0\\r\\n row += 1\\r\\n else: # increases column\\r\\n use_column += 1\\r\\n\\r\\n print('All coins have been randomly assigned.')\",\n \"def _draw_random_turn_params(self):\\n return TurnParams(\\n main_corridor_length=self._rng.uniform(10, 16),\\n turn_corridor_length=self._rng.uniform(4, 12),\\n turn_corridor_angle=self._rng.uniform(-3./8. * np.pi, 3./8.*np.pi),\\n main_corridor_width=self._rng.uniform(0.5, 1.5),\\n turn_corridor_width=self._rng.uniform(0.5, 1.5),\\n flip_arnd_oy=bool(self._rng.rand() < 0.5),\\n flip_arnd_ox=bool(self._rng.rand() < 0.5),\\n rot_theta=self._rng.uniform(0, 2*np.pi)\\n )\",\n \"def new_tile(self):\\r\\n count = 0\\r\\n tot_count = self.get_grid_width() * self.get_grid_height()\\r\\n\\r\\n while count < 2 and tot_count > 0:\\r\\n # my_list = 4 10% of the time and a 2 90%\\r\\n my_list = [4] * 10 + [2] * 90\\r\\n new_tile = random.choice(my_list)\\r\\n\\r\\n # Selects a random number from 0 to width * height -1\\r\\n\\r\\n spot = random.randint(0, self._grid_height * self._grid_width - 1)\\r\\n\\r\\n # sets location to random selection from spot\\r\\n loc = [spot / self._grid_width, spot % self._grid_width]\\r\\n # if loc is empty ( == 0 ) sets number, else repeats process.\\r\\n\\r\\n if self._board[loc[0]][loc[1]] == 0:\\r\\n # sets radom selected board tile to new_tile number\\r\\n self._board[loc[0]][loc[1]] = new_tile\\r\\n count += 1\\r\\n tot_count -= 1\",\n \"def init_board(rows, columns, method=\\\"random\\\"):\\n if method == \\\"random\\\":\\n board = np.random.random_integers(2, size=(rows, columns)) - 1\\n return board\",\n \"def new_tile(self):\\r\\n # replace with your code\\r\\n # complete search ....\\r\\n non_zero_count = 0;\\r\\n for row in range(self._grid_height):\\r\\n for col in range(self._grid_width):\\r\\n if self._grid_tile[row][col] == 0:\\r\\n non_zero_count += 1\\r\\n random_choice = random.randrange(0, non_zero_count)\\r\\n count = 0\\r\\n # another search ....\\r\\n generated_new_tile = False\\r\\n for row in range(self._grid_height):\\r\\n for col in range(self._grid_width):\\r\\n if generated_new_tile == False and self._grid_tile[row][col] == 0:\\r\\n if count != random_choice:\\r\\n count += 1 \\r\\n else:\\r\\n if random.randrange(0,100) < 10:\\r\\n self.set_tile(row, col ,4)\\r\\n else:\\r\\n self.set_tile(row, col ,2)\\r\\n generated_new_tile = True\",\n \"def new_tile(self):\\n col = random.choice(range(self.grid_width))\\n row = random.choice(range(self.grid_height))\\n if self.grid[row][col] == 0:\\n if random.random() >= 0.9:\\n self.grid[row][col] = 4\\n else:\\n self.grid[row][col] = 2\\n else:\\n self.new_tile()\",\n \"def random_strategy(player, board):\\n return random.choice(Othello.legal_moves(player, board))\",\n \"def genRandTeam(nPos, totPlayers):\\n # 0 1 2 3 4 5 6\\n # nPos = [nFirst, nSecond, nThird, nShort, nCatcher, nOf, nDh]\\n chromosome = []\\n sum = 0\\n count = 0\\n\\n\\n for i in nPos: # general loop\\n if count == 6: # when loop enters the nDh players it instead chooses from ALL positions five times\\n for j in range(5): # to represent the 2 util positions and the 3 benches\\n rNum = random.randint(0, totPlayers - 1) # random number of ANY player\\n chromosome.append(rNum) # picks a random pos\\n break # no more work needs to be done\\n if count == 5: # this will occur before the previous loop; nOF must be iterated 3 times for 3 outfield spots\\n for j in range(2):\\n rNum2 = random.randint(0, i - 1)\\n chromosome.append(rNum2 + sum) # nOF must be iterated 3 times for 3 outfield spots; i is on oF\\n rNum3 = random.randint(0, i - 1)\\n chromosome.append(rNum3 + sum)\\n sum += i\\n count += 1\\n # first = random.randint(0,nPos[0])\\n # second = random.randint(0,nPos[1])\\n # third = random.randint(0,nPos[2])\\n # short = random.randint(0,nPos[3])\\n # catcher = random.randint(0,nPos[4])\\n # of = [random.randint(0,nPos[5]), random.randint(0,nPos[5]), random.randint(0,nPos[5])] #THREE outfielders\\n # rNum = [random.randint(0,6) for i in range(5)] #random numbers representing one of the nPos rosters\\n # util = [random.randint(0,nPos[rNum[0]]), random.randint(0,nPos[rNum[1]])] #picks 2 random players from ANY roster\\n # ben = [random.randint(0,nPos[rNum[2]]), random.randint(0,nPos[rNum[3]]), random.randint(0,nPos[rNum[4]])] # picks 3 random players form any roster\\n # print first,second,third,short,catcher,of,util,ben\\n # temp = Team()\\n return chromosome\",\n \"def test_initialization(number: int) -> None:\\n for _ in range(number):\\n if random.random() < 0.5:\\n size = random.randint(3, 10)\\n baby_position = [random.randint(0, size - 1), random.randint(0, size - 1)]\\n num_berries = random.randint(1, size)\\n else:\\n size = [random.randint(3, 10), random.randint(3, 10)]\\n baby_position = [\\n random.randint(0, size[0] - 1),\\n random.randint(0, size[1] - 1),\\n ]\\n num_berries = random.randint(1, size[0])\\n print(f\\\"\\\\n\\\\n\\\\nSize of the board {size}\\\")\\n print(f\\\"Baby position: {baby_position}\\\")\\n print(f\\\"Number of berries to be placed randomly: {num_berries}\\\")\\n game = Game(size, baby_position, 0, 0, 0, 0, num_berries)\\n print(f\\\"Here is the board:\\\\n{game.get_board()}\\\")\\n print(game.get_baby())\\n for b in game.get_berries():\\n print(b)\",\n \"def new_tile(self):\\r\\n # creating a list value to ensure the 90 and 10 percent ratio\\r\\n value=[2,2,2,2,2,2,2,2,2,2]\\r\\n position_of_4=random.randrange(0,10)\\r\\n value[position_of_4]=4\\r\\n # selecting a random position on the grid\\r\\n dummy_row=random.randrange(0,self._height)\\r\\n dummy_column=random.randrange(0,self._width)\\r\\n # check to ensure that same tiles are not selected\\r\\n if self._grid[dummy_row][dummy_column]!=0:\\r\\n while self._grid[dummy_row][dummy_column]!=0:\\r\\n dummy_row=random.randrange(0,self._height)\\r\\n dummy_column=random.randrange(0,self._width)\\r\\n # assigning a value to the selected tile\\r\\n self._grid[dummy_row][dummy_column]=random.choice(value)\",\n \"def generate():\\n global BOARD\\n next = [[0] * ROWS for _ in range(COLS)]\\n # Loop through every spot in our 2D array and check spots neighbors\\n for x in range(COLS):\\n for y in range(ROWS):\\n # Add up all the states in a 3x3 surrounding grid\\n neighbors = 0\\n for i in range(-1, 2):\\n for j in range(-1, 2):\\n nx = (x + i + COLS) % COLS\\n ny = (y + j + ROWS) % ROWS\\n neighbors += BOARD[nx][ny]\\n # A little trick to subtract the current cell's state since\\n # we added it in the above loop\\n neighbors -= BOARD[x][y]\\n # Rules of Life\\n if BOARD[x][y] == 1 and neighbors < 2 : next[x][y] = 0 # Loneliness\\n elif BOARD[x][y] == 1 and neighbors > 3 : next[x][y] = 0 # Overpopulation\\n elif BOARD[x][y] == 0 and neighbors == 3: next[x][y] = 1 # Reproduction\\n else: next[x][y] = BOARD[x][y] # Stasis\\n # Next is now our board\\n BOARD = next\",\n \"def randomLeggings():\\n return random.choice(LEGGINGS)\",\n \"def stage_1_generator(option):\\n # Stage Size + Player Starting Position\\n STAGE_1 = ([10,10], [1,1])\\n\\n # Non-Ocean tiles\\n STAGE_1_TILES = { \\n \\\"1,2\\\":\\\"rock\\\",\\n \\\"1,3\\\":\\\"mountain\\\",\\n \\\"2,4\\\":\\\"rock\\\",\\n \\\"2,7\\\":\\\"rock\\\",\\n \\\"2,8\\\":\\\"rock\\\",\\n \\\"3,3\\\":\\\"rock\\\",\\n \\\"3,4\\\":\\\"rock\\\",\\n \\\"3,8\\\":\\\"mountain\\\",\\n \\\"3,9\\\":\\\"rock\\\",\\n \\\"3,10\\\":\\\"rock\\\",\\n \\\"4,4\\\":\\\"rock\\\",\\n \\\"4,5\\\":\\\"mountain\\\",\\n \\\"5,6\\\":\\\"rock\\\",\\n \\\"6,1\\\":\\\"rock\\\",\\n \\\"6,2\\\":\\\"rock\\\",\\n \\\"6,7\\\":\\\"rock\\\",\\n \\\"6,10\\\":\\\"rock\\\",\\n \\\"7,1\\\":\\\"rock\\\",\\n \\\"7,2\\\":\\\"rock\\\",\\n \\\"7,6\\\":\\\"rock\\\",\\n \\\"7,10\\\":\\\"rock\\\",\\n \\\"8,5\\\":\\\"rock\\\",\\n \\\"8,6\\\":\\\"rock\\\",\\n \\n \\\"8,10\\\":\\\"rock\\\",\\n \\\"9,1\\\":\\\"sign\\\",\\n \\\"9,3\\\":\\\"rock\\\",\\n \\\"9,4\\\":\\\"rock\\\",\\n \\\"9,9\\\":\\\"rock\\\",\\n \\\"9,10\\\":\\\"rock\\\",\\n \\\"10,1\\\":\\\"cave\\\",\\n \\\"10,3\\\":\\\"rock\\\",\\n \\\"10,4\\\":\\\"cave\\\",\\n \\\"10,8\\\":\\\"rock\\\",\\n \\\"10,9\\\":\\\"rock\\\",\\n \\\"10,10\\\":\\\"rock\\\",\\n \\n \\\"1,10\\\":\\\"end\\\",\\n }\\n\\n # Special Tiles that trigger an event\\n STAGE_1_SPECIAL = { \\n \\\"1,10\\\":\\\"end\\\",\\n \\\"9,1\\\":\\\"sign_cave\\\",\\n \\\"10,1\\\":\\\"cave_entrance_1\\\",\\n \\\"10,4\\\":\\\"cave_entrance_2\\\",\\n \\\"1,9\\\":\\\"dark_water\\\",\\n \\\"2,9\\\":\\\"dark_water\\\",\\n \\\"2,10\\\":\\\"dark_water\\\"\\n }\\n\\n # Decide what data to return\\n if option == \\\"stage\\\":\\n return STAGE_1\\n elif option == \\\"tiles\\\":\\n return STAGE_1_TILES\\n elif option == \\\"special\\\":\\n return STAGE_1_SPECIAL\\n else:\\n print(\\\"Something Broke! map_generator_1\\\")\",\n \"def generate_board(rows, cols):\\n aux = np.zeros((rows, cols))\\n for i in range(rows):\\n for j in range(cols):\\n if np.random.random() < 0.5:\\n aux[i][j] = 1\\n return aux\",\n \"def uniform_random(self) -> None:\\n\\n size = self.circ_size\\n random.seed(self.seed)\\n\\n gates = [self.h, self.x, self.y, self.z, self.s, self.t, self.cx]\\n candidates = set(range(size))\\n\\n for i in range(size):\\n for j in range(size):\\n to_apply = random.choice(gates)\\n\\n num_qubits = 2 if to_apply == self.cx else 1\\n targets = random.sample(candidates, num_qubits)\\n to_apply(*targets)\\n\\n if self.meas: self.measure(self.qr, self.cr)\",\n \"def randomized_prims(width=16, height=16) -> Maze:\\n maze = Maze(width=width, height=height, algorithm=None)\\n visited = [[False for _ in range(maze.width)] for _ in range(maze.height)]\\n\\n # ensure only one entrance to the center squares\\n centerx = maze.width // 2 - 1\\n centery = maze.height // 2 - 1\\n \\n visited[centery][centerx] = True\\n visited[centery][centerx+1] = True\\n visited[centery+1][centerx+1] = False\\n visited[centery+1][centerx] = True\\n\\n visited[0][0] = True\\n boundary = [(0,0,Compass.EAST), (0,0,Compass.SOUTH)]\\n\\n while boundary:\\n x, y, direction = boundary.pop(random.randint(0, len(boundary)-1))\\n nx, ny = maze.neighbor(x, y, direction)\\n if not visited[ny][nx]:\\n maze.break_wall(x, y, direction)\\n boundary.extend([(nx,ny,direction) for direction in maze.neighbors(nx, ny)])\\n visited[ny][nx] = True\\n \\n return maze\",\n \"def new_tile(self):\\n two_or_four = random.random();\\n if two_or_four < 0.9:\\n value = 2\\n else:\\n value = 4\\n empty = False\\n all_cells = 0\\n while empty == False:\\n all_cells += 1 \\n row = random.choice(range(self._height))\\n col = random.choice(range(self._width))\\n if self.get_tile(row, col) == 0:\\n empty = True\\n self.set_tile(row, col, value)\\n elif all_cells >= self._height * self._width:\\n empty = True\",\n \"def populate_region(mask, layer_params):\\n\\n from .speedups import (\\n NEW_CELL_MASK, CAN_OSCILLATE_MASK, INCLUDE_VIOLATIONS_MASK)\\n\\n border = ndimage.maximum_filter(mask, size=3, mode='wrap') ^ mask\\n interior = ndimage.minimum_filter(mask, size=3, mode='wrap')\\n gen_mask = mask * (\\n NEW_CELL_MASK |\\n CAN_OSCILLATE_MASK |\\n INCLUDE_VIOLATIONS_MASK\\n ) + border * (\\n INCLUDE_VIOLATIONS_MASK\\n )\\n board = np.zeros(mask.shape, dtype=np.uint16)\\n foreground = np.zeros(mask.shape, dtype=bool)\\n background = np.zeros(mask.shape, dtype=bool)\\n background_color = np.zeros(mask.shape, dtype=bool)\\n seeds = None\\n max_period = 1\\n\\n for layer in layer_params:\\n if not isinstance(layer, dict):\\n raise ValueError(\\n \\\"'layer_params' should be a list of parameter dictionaries.\\\")\\n layer = _fix_random_values(layer)\\n old_board = board.copy()\\n gen_mask0 = gen_mask.copy()\\n interior = ndimage.minimum_filter(\\n gen_mask & NEW_CELL_MASK > 0, size=3, mode='wrap')\\n color = COLORS.get(layer.get('color'), 0)\\n\\n fence_frac = layer.get('fences', 0.0)\\n if fence_frac > 0:\\n fences = build_fence(gen_mask & speedups.NEW_CELL_MASK)\\n fences *= coinflip(fence_frac, fences.shape)\\n gen_mask &= ~(fences * (NEW_CELL_MASK | CAN_OSCILLATE_MASK))\\n board += fences.astype(np.uint16) * CellTypes.wall\\n\\n spawners = layer.get('spawners', 0)\\n if spawners > 0:\\n _mask = (gen_mask0 & NEW_CELL_MASK > 0) & interior\\n new_cells = _mask & coinflip(spawners, board.shape)\\n if not new_cells.any() and _mask.any():\\n i, j = np.nonzero(_mask)\\n k = get_rng().choice(len(i)) # ensure at least one spawner\\n new_cells[i[k], j[k]] = True\\n gen_mask[new_cells] ^= NEW_CELL_MASK\\n board[new_cells] = CellTypes.spawner + color\\n\\n tree_lattice = layer.get('tree_lattice')\\n # Create a lattice of trees that are spread throughout the region\\n # such that every empty cell touches one (and only one) tree\\n # (modulo edge effects).\\n # Such a lattice tends to make the resulting board very chaotic.\\n # Note that this will disrupt any pre-existing patterns.\\n if tree_lattice is not None:\\n if not isinstance(tree_lattice, dict):\\n tree_lattice = {}\\n h, w = board.shape\\n stagger = tree_lattice.get('stagger', True)\\n spacing = float(tree_lattice.get('spacing', 5))\\n if not stagger:\\n new_cells = _make_lattice(h, w, spacing, spacing, 0)\\n elif spacing <= 3:\\n new_cells = _make_lattice(h, w, 3, 3, 1)\\n elif spacing == 4:\\n new_cells = _make_lattice(h, w, 10, 1, 3)\\n elif spacing == 5:\\n new_cells = _make_lattice(h, w, 13, 1, 5)\\n else:\\n # The following gets pretty sparse.\\n new_cells = _make_lattice(h, w, 6, 3, 3)\\n\\n new_cells &= gen_mask & NEW_CELL_MASK > 0\\n board[new_cells] = CellTypes.tree + color\\n\\n period = 1\\n if 'pattern' in layer:\\n pattern_args = layer['pattern'].copy()\\n period = pattern_args.get('period', 1)\\n if period == 1:\\n gen_mask2 = gen_mask & ~CAN_OSCILLATE_MASK\\n pattern_args.update(period=max_period, osc_bonus=0)\\n elif period == 0:\\n gen_mask2 = gen_mask & ~INCLUDE_VIOLATIONS_MASK\\n pattern_args.update(period=max_period, osc_bonus=0)\\n elif period < max_period:\\n raise ValueError(\\n \\\"Periods for sequential layers in a region must be either 0, 1,\\\"\\n \\\" or at least as large as the largest period in prior layers.\\\")\\n else:\\n gen_mask2 = gen_mask\\n max_period = period\\n\\n board = _gen_pattern(board, gen_mask2, seeds, **pattern_args)\\n\\n # We need to update the mask for subsequent layers so that they\\n # do not destroy the pattern in this layer.\\n # First get a list of board states throughout the oscillation cycle.\\n boards = [board]\\n for _ in range(1, max_period):\\n boards.append(speedups.advance_board(boards[-1]))\\n non_empty = np.array(boards) != 0\\n still_cells = non_empty.all(axis=0)\\n osc_cells = still_cells ^ non_empty.any(axis=0)\\n # Both still life cells and oscillating cells should disallow\\n # any later changes. We also want to disallow changes to the cells\\n # that are neighboring the oscillating cells, because any changes\\n # there would propogate to the oscillating cells at later time\\n # steps.\\n # Note that it doesn't really matter whether the oscillating mask\\n # is set for the currently oscillating cells, because we're not\\n # checking for violations in them anyways, and we don't allow any\\n # changes that would affect them.\\n osc_neighbors = ndimage.maximum_filter(osc_cells, size=3, mode='wrap')\\n gen_mask[osc_cells] &= ~(NEW_CELL_MASK | INCLUDE_VIOLATIONS_MASK)\\n gen_mask[still_cells | osc_neighbors] &= ~(NEW_CELL_MASK | CAN_OSCILLATE_MASK)\\n\\n new_mask = board != old_board\\n life_mask = ((board & CellTypes.alive) > 0) & new_mask\\n board += color * new_mask * life_mask\\n # The seeds are starting points for the next layer of patterns.\\n # This just makes the patterns more likely to end up close together.\\n seeds = ((board & CellTypes.alive) > 0) & mask\\n\\n new_mask = board != old_board\\n\\n movable_walls = layer.get('movable_walls', 0)\\n if movable_walls > 0:\\n new_cells = coinflip(movable_walls, board.shape) * new_mask\\n new_cells *= (board & ~CellTypes.rainbow_color) == CellTypes.wall\\n board += new_cells * CellTypes.movable\\n\\n movable_trees = layer.get('movable_trees', 0)\\n if movable_trees > 0:\\n new_cells = coinflip(movable_trees, board.shape) * new_mask\\n new_cells *= (board & ~CellTypes.rainbow_color) == CellTypes.tree\\n board += new_cells * CellTypes.movable\\n\\n hardened_life = layer.get('hardened_life', 0)\\n if hardened_life > 0:\\n new_cells = coinflip(hardened_life, board.shape) * new_mask\\n new_cells *= (board & ~CellTypes.rainbow_color) == CellTypes.life\\n board -= new_cells * CellTypes.destructible\\n\\n buffer_size = layer.get('buffer_zone', 0) * 2 + 1\\n life_cells = board & CellTypes.alive > 0\\n buf = ndimage.maximum_filter(life_cells, size=buffer_size, mode='wrap')\\n gen_mask[buf] &= ~NEW_CELL_MASK\\n\\n target = layer.get('target', 'board')\\n if target == 'board':\\n foreground[new_mask] = True\\n if period > 0:\\n background[new_mask] = True\\n elif target == 'goals':\\n background[new_mask] = True\\n background_color[new_mask] = True\\n # Make sure to add walls and such to the foreground\\n foreground[new_mask & (board & CellTypes.alive == 0)] = True\\n elif target == 'both':\\n foreground[new_mask] = True\\n if period > 0:\\n background[new_mask] = True\\n background_color[new_mask] = True\\n else:\\n raise ValueError(\\\"Unexpected value for 'target': %s\\\" % (target,))\\n\\n fountains = layer.get('fountains', 0)\\n if fountains > 0:\\n new_cells = coinflip(fountains, board.shape)\\n new_cells *= gen_mask & NEW_CELL_MASK > 0\\n neighbors = ndimage.maximum_filter(new_cells, size=3, mode='wrap')\\n neighbors *= gen_mask & NEW_CELL_MASK > 0\\n gen_mask[neighbors] = INCLUDE_VIOLATIONS_MASK\\n if buffer_size > 1:\\n buf = ndimage.maximum_filter(neighbors, size=buffer_size, mode='wrap')\\n gen_mask[buf] &= ~NEW_CELL_MASK\\n board[neighbors] = CellTypes.wall + color\\n board[new_cells] = CellTypes.fountain + color\\n foreground[new_cells] = True\\n background[neighbors] = True\\n background_color[neighbors] = True\\n\\n goals = board.copy()\\n board *= foreground\\n goals *= background\\n goals &= ~CellTypes.spawning\\n goals &= ~(CellTypes.rainbow_color * ~background_color)\\n\\n return board, goals\",\n \"def generate_advanced_tech_tiles(seed=0):\\n\\n if seed is not 0:\\n random.seed(seed)\\n all_advanced_tiles = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 ,15]\\n randomized_tiles = list()\\n\\n for _ in range(6):\\n chosen_tile_index = random.randint(0, len(all_advanced_tiles) - 1)\\n randomized_tiles.append(all_advanced_tiles[chosen_tile_index])\\n all_advanced_tiles.pop(chosen_tile_index)\\n\\n return tuple(randomized_tiles)\",\n \"def random_board(n):\\r\\n \\r\\n return(np.random.randint(0,n-1, size = n))\",\n \"def generate_grid(height, width):\\n return [[random.randint(0, 9) for _ in range(width)] for _ in range(height)]\",\n \"def __init__(self, rows, columns, live_probability=0.3, seed=0):\\n self.live_probability = live_probability\\n self.seed = seed\\n self.rows = rows\\n self.columns = columns\\n self.grid = [\\n [Cell() for column_cells in range(self.columns)]\\n for row_cells in range(self.rows)\\n ]\\n\\n self.generate_board()\",\n \"def __init__(self):\\r\\n self.rows = [[0]*9, [0]*9, [0]*9, [0]*9, [0]*9, [0]*9, [0]*9, [0]*9, [0]*9]\\r\\n self.block1 = []\\r\\n self.block5 = []\\r\\n self.block9 = []\\r\\n self.puzzle = []\\r\\n self.score = 0\\r\\n self.difficulty = 1 # By default Easy difficulty\\r\\n\\r\\n \\\"\\\"\\\" Creating blocks using random number generator\\\"\\\"\\\"\\r\\n while len(self.block1) < 9:\\r\\n r = random.randrange(1,10)\\r\\n if r not in self.block1:\\r\\n self.block1.append(r)\\r\\n\\r\\n while len(self.block5) < 9:\\r\\n r = random.randrange(1,10)\\r\\n if r not in self.block5:\\r\\n self.block5.append(r)\\r\\n\\r\\n while len(self.block9) < 9:\\r\\n r = random.randrange(1,10)\\r\\n if r not in self.block9:\\r\\n self.block9.append(r)\\r\\n x = 0\\r\\n for i in range(3):\\r\\n for j in range(3):\\r\\n self.rows[i][j] = self.block1[x]\\r\\n x = x+1\\r\\n x = 0\\r\\n for i in range(3, 6):\\r\\n for j in range(3, 6):\\r\\n self.rows[i][j] = self.block5[x]\\r\\n x = x+1\\r\\n x = 0\\r\\n for i in range(6,9):\\r\\n for j in range(6,9):\\r\\n self.rows[i][j] = self.block9[x]\\r\\n x = x+1\\r\\n \\\"\\\"\\\"Creating a valid solution\\\"\\\"\\\"\\r\\n self.createsolution(self.rows)\",\n \"def generate(width=20, height=20):\\n m = Maze(width, height)\\n m.randomize()\\n return m\",\n \"def generate_board(self):\\n try:\\n all_words = [word.strip().lower() for word in open(self.in_file)]\\n except UnicodeDecodeError:\\n raise Exception(\\\"Make sure that in_file is a text file\\\")\\n except FileNotFoundError:\\n raise Exception(\\\"Make sure that in_file exists\\\")\\n\\n permutation = np.random.permutation(len(all_words))\\n words = np.array(all_words)[permutation][:25]\\n\\n # 9 Blue, 8 Red, 7 Neutral, 1 Assassin\\n board = []\\n for i, word in enumerate(words):\\n if i < 9:\\n type = \\\"blue\\\"\\n colour = \\\"#0080FF\\\"\\n elif i < 17:\\n type = \\\"red\\\"\\n colour = \\\"#FF0000\\\"\\n elif i < 24:\\n type = \\\"neutral\\\"\\n colour = \\\"#D0D0D0\\\"\\n else:\\n type = \\\"assassin\\\"\\n colour = \\\"#202020\\\"\\n word_details = {\\\"name\\\": word, \\\"type\\\": type, \\\"colour\\\": colour, \\\"active\\\": False}\\n board.append(word_details)\\n\\n np.random.shuffle(board)\\n\\n # Assign ids (+1 because of the header)\\n for i in range(25):\\n board[i][\\\"id\\\"] = i+1\\n\\n return board\",\n \"def __init__(self, screen, game_settings):\\n\\t\\tself.screen = screen\\n\\t\\tself.color = game_settings.growth_block_color\\n\\t\\t\\n\\t\\t# Sets rect at origin and size 25 x 25\\n\\t\\tself.rect = pygame.Rect(0, 0, 24, 24)\\n\\t\\t\\n\\t\\t# Uses randint to use as random rect position\\n\\t\\tx = randint(0, 35)\\n\\t\\ty = randint(1, 26)\\n\\t\\tself.rect.x = (25 * x) + 1\\n\\t\\tself.rect.bottom = 25 * y\",\n \"def create_random_grid(N):\\n return np.random.choice(values, N*N, p=[0.2, 0.8]).reshape(N, N)\",\n \"def new_tile(self):\\n\\n # creating a random float variable that will roll a random value\\n # if randomvalue > .90\\n #\\n\\n tile_added = False\\n while not tile_added:\\n row = random.randint(0,self.grid_height - 1)\\n col = random.randint(0,self.grid_width - 1)\\n if self.board[row][col] == 0:\\n tile_added = True\\n random_tile = random.random()\\n if random_tile < .90:\\n self.board[row][col] = 2\\n else:\\n self.board[row][col] = 4\",\n \"def random_placement(area):\\n\\n area.create_houses(True)\\n\\n for house in area.houses:\\n place_house(area, house)\",\n \"def random_reassignment(graph, possibilities):\\n\\n random_assignment(graph, possibilities)\\n\\n violating_nodes = graph.get_violations()\\n\\n while len(violating_nodes):\\n random_reconfigure_nodes(graph, violating_nodes, possibilities)\\n\\n violating_nodes = graph.get_violations()\",\n \"def new_tile(self):\\n # replace with your code\\n empty_list = []\\n counter_1 = 0\\n for _ in self._grid:\\n counter_2 = 0\\n line = _\\n for blank in line:\\n if blank == 0:\\n blank_tile = (counter_1, counter_2)\\n empty_list.append(blank_tile)\\n counter_2 += 1\\n else:\\n counter_2 += 1\\n counter_1 += 1\\n #print empty_list\\n \\n self._tile = empty_list[random.randrange(len(empty_list))]\\n \\n value = [2,2,2,2,2,2,2,2,2,4]\\n tile_value = value[random.randint(0,9)]\\n \\n self.set_tile(self._tile[0], self._tile[1], tile_value)\",\n \"def new_tile(self):\\r\\n # check if is zero or not\\r\\n new_tile_added = False\\r\\n # a list to 2 90% of the time and 4 10% of the time\\r\\n new_tile_list = [2,2,2,2,2,2,2,2,2,4]\\r\\n counter = 0\\r\\n while not new_tile_added:\\r\\n row_position = random.randrange(0,self.grid_height)\\r\\n col_position = random.randrange(0,self.grid_width)\\r\\n if self.grid[row_position][col_position] == 0:\\r\\n self.grid[row_position][col_position] = random.choice(new_tile_list)\\r\\n new_tile_added = True\\r\\n if counter > self.grid_width * self.grid_height:\\r\\n print 'you failed'\\r\\n break\\r\\n\\r\\n counter +=1\",\n \"def __init__(self, x, y):\\n self.height = x\\n self.width = y\\n self.grid = self.initialize(self.height, self.width)\\n self.randx = random.randint(0, self.height-1)\\n self.randy = random.randint(0, self.width-1)\\n #self.make()\\n #self.show()\",\n \"def random(self, width, height, seed = None):\\n self.grid = [ [''] * width for i in range(height) ]\\n random.seed(seed)\\n start = ( random.randint(0, len(self.grid) - 1),\\n random.randint(0, len(self.grid[0]) - 1)\\n )\\n visited = set([start])\\n self._createPath(start, visited)\\n start = ( random.randint(0, len(self.grid) - 1), 0 )\\n finish = ( random.randint(0, len(self.grid) - 1),\\n len(self.grid[0]) - 1 )\\n self.grid[start[0]][start[1]] += '^'\\n self.grid[finish[0]][finish[1]] += '$'\\n return self.grid, start, finish\",\n \"def get_next_alea_tiles(plateau, mode):\\n from random import randint\\n # si le saisie et condition de plateau sont valide\\n if mode.upper() == \\\"INIT\\\" and get_nb_empty_room(plateau) >= 2 or mode.upper() == \\\"ENCOURS\\\" and get_nb_empty_room(plateau) >= 1:\\n if mode.upper() == \\\"INIT\\\":\\n tableau = {'mode' : \\\"init\\\", 'check' : not is_game_over(plateau), '0' : {'val' : 1, 'lig' : randint(0,3), 'col' : randint(0,3)}, '1' : {'val' : 2, 'lig' : randint(0,3), 'col' : randint(0,3)}}\\n # quand les deux cases choisi ne sont pas vide et la position des 2 valeur donner sont egaux\\n while not ( is_room_empty(plateau,tableau[\\\"0\\\"][\\\"lig\\\"], tableau[\\\"0\\\"][\\\"col\\\"]) and is_room_empty(plateau, tableau[\\\"1\\\"][\\\"lig\\\"], tableau[\\\"1\\\"][\\\"col\\\"]) and not(tableau[\\\"0\\\"][\\\"lig\\\"] == tableau[\\\"1\\\"][\\\"lig\\\"] and tableau[\\\"0\\\"][\\\"col\\\"] == tableau[\\\"1\\\"][\\\"col\\\"])):\\n tableau[\\\"0\\\"] = {'val' : 1, 'lig' : randint(0,3), 'col' : randint(0,3)}\\n tableau[\\\"1\\\"] = {'val' : 2, 'lig' : randint(0,3), 'col' : randint(0,3)}\\n else:\\n tableau = {'mode' : 'encours', 'check' : not is_game_over(plateau), '0' : {'val' : randint(1,3), 'lig' : randint(0,3), 'col' : randint(0,3)}}\\n # auand la cases choisi n est pas vide\\n while not (is_room_empty(plateau, tableau[\\\"0\\\"][\\\"lig\\\"], tableau[\\\"0\\\"][\\\"col\\\"])):\\n tableau[\\\"0\\\"] = {'val' : randint(1,3), 'lig' : randint(0,3), 'col' : randint(0,3)}\\n return tableau\\n else:\\n return 'Erreur !'\",\n \"def generate_new_board(self, difficulty=1):\\n self._reset_board()\\n self._solve_empty_board_with_random_values()\\n self._remove_numbers_to_get_puzzle(difficulty)\",\n \"def create_random(self):\\n for key in self.nn_param_choices:\\n self.network[key] = random.choice(self.nn_param_choices[key])\",\n \"def startGeneration(variant, resolution, loops):\\n # Check for valid resolution\\n if resolution % 2 != 0:\\n print (\\\"Resolution should be an even integer.\\\")\\n return\\n\\n # Set high score:\\n if variant == 20:\\n high_score = 11365950\\n if variant == 40:\\n high_score = 17858670\\n if variant == 60:\\n high_score = 24239310\\n\\n # House distirbution:\\n familyHome_count = 0.6 * variant\\n bungalow_count = 0.25 * variant\\n maison_count = 0.15 * variant\\n\\n for loops in range(loops):\\n\\n # Initialize Classlist\\n placed_houses = []\\n placed_water = []\\n\\n # Initialize values\\n gr = generic.genMap(180 * resolution, 160 * resolution)\\n\\n # Set length and width based on resultion.\\n fam_length = int(resolution * 8)\\n fam_width = int(resolution * 8)\\n fam_freespace = int(resolution * 2)\\n\\n bung_length = int(resolution * 7.5)\\n bung_width = int(resolution * 10)\\n bung_freespace = int(resolution * 3)\\n\\n mais_length = int(resolution * 10.5)\\n mais_width = int(resolution * 11)\\n mais_freespace = int(resolution * 6)\\n\\n # Water\\n # Generate water parts\\n water_parts = genWater(gr, resolution)\\n\\n # Place water parts in grid:\\n for part in range(len(water_parts)):\\n W = 0\\n\\n # Loop until correctly placed.\\n while W != 1:\\n\\n # Define class instance\\n Water = class_house.House(water_parts[part][1], water_parts[part][0],\\n 1, 0, 0, 4, \\\"W\\\", resolution)\\n\\n ngrid = genHome(gr, Water)\\n\\n # Check for success:\\n if ngrid == False:\\n print (\\\"No succesfull placement Water\\\")\\n else:\\n print (\\\"Water {0} placed!\\\".format(W))\\n gr = list(ngrid)\\n\\n # Add water to list\\n placed_houses.append(Water)\\n\\n W = 1\\n\\n # Maisons\\n M = 0\\n while M != maison_count:\\n\\n # Define class instance\\n Maison = class_house.House(mais_length, mais_width,\\n mais_freespace, 610000, 6, 1, \\\"M\\\", resolution)\\n\\n ngrid = genHome(gr, Maison)\\n\\n # Check if house succsfully placed:\\n if ngrid == False:\\n print (\\\"No succesfull placement Maison\\\")\\n else:\\n print (\\\"Maison {0} placed!\\\".format(M))\\n gr = list(ngrid)\\n\\n # Add maison to list\\n placed_houses.append(Maison)\\n\\n M += 1\\n\\n # Then bungalows\\n B = 0\\n while B != bungalow_count:\\n\\n # Define class instance\\n Bungalow = class_house.House(bung_length, bung_width,\\n bung_freespace, 399000, 4, 2, \\\"B\\\", resolution)\\n\\n ngrid = genHome(gr, Bungalow)\\n\\n # Check for succes:\\n if ngrid == False:\\n print (\\\"No succesfull placement Bungalow\\\")\\n else:\\n print (\\\"Bungalow {0} placed!\\\".format(B))\\n gr = list(ngrid)\\n\\n # Add maison to list\\n placed_houses.append(Bungalow)\\n\\n B += 1\\n\\n # Then Family homes\\n F = 0\\n while F != familyHome_count:\\n\\n # Define class instance\\n Familyhome = class_house.House(fam_length, fam_width,\\n fam_freespace, 285000, 3, 3, \\\"F\\\", resolution)\\n\\n ngrid = genHome(gr, Familyhome)\\n\\n # Check for succes:\\n if ngrid == False:\\n print (\\\"No succesfull placement Family Home\\\")\\n else:\\n print (\\\"Family home {0} placed!\\\".format(F))\\n gr = list(ngrid)\\n\\n # Add maison to list\\n placed_houses.append(Familyhome)\\n\\n F += 1\\n\\n # Calculate score using Placed houses\\n sc = generic.calculateScore(gr, placed_houses)\\n name = (\\\"Score: \\\" + str(sc))\\n\\n # Only save to file when new record.\\n fname = \\\"Type{0} - {1}\\\".format(variant, sc)\\n\\n\\n if sc > high_score:\\n #read_write.write(fname, placed_houses)\\n high_score = sc\\n print (\\\"New high score ({0}) in loop: {1}\\\".format(sc, loops))\\n print (\\\"Writing to file..\\\")\\n\\n return gr, placed_houses, sc\",\n \"def createMap(self):\\n map = {}\\n for rows in xrange(0,(size[1]/50)):\\n for columns in xrange(0,(size[0]/50)):\\n if rows == (size[1]/50)-1 or rows == 0 or columns== (size[0]/50)-1 or columns==0:\\n map.update({(rows,columns):\\\"block\\\"})\\n elif(rows%3 == 0):\\n map.update({(rows,columns):random.choice(map_options)})\\n else:\\n map.update({(rows,columns):random.choice(map_options[:1])})\\n\\n self.map = map\",\n \"def create_some_random_pos(actor_cls, n, actor_type, actor_list, game,\\r\\n probability_each=100):\\r\\n ITERATIONS_MAX = 12\\r\\n cell_size = lib_jp.Size(w=actor_cls.size.w, h=actor_cls.size.h)\\r\\n cell_size_with_border = lib_jp.Size(w=cell_size.w + Actor.CELL_SCREEN_SECURITY_SIZE,\\r\\n h=cell_size.h + Actor.CELL_SCREEN_SECURITY_SIZE)\\r\\n cell_total_security_border = lib_jp.Size(w=actor_cls.cell_added_size.w\\r\\n + Actor.CELL_SCREEN_SECURITY_SIZE,\\r\\n h=actor_cls.cell_added_size.h\\r\\n + Actor.CELL_SCREEN_SECURITY_SIZE)\\r\\n if len(actor_list) >= actor_cls.max_qty_on_board:\\r\\n return\\r\\n elif n + len(actor_list) >= actor_cls.max_qty_on_board:\\r\\n n = actor_cls.max_qty_on_board - len(actor_list)\\r\\n iterations = 0\\r\\n for _ in range(n):\\r\\n if probability_each < 100 and randint(1, 100) > probability_each:\\r\\n continue\\r\\n actor_added = False\\r\\n iterations = 0\\r\\n actor_obj = None\\r\\n while not actor_added and (iterations <= ITERATIONS_MAX):\\r\\n iterations += 1\\r\\n x = randint(cell_total_security_border.w,\\r\\n Settings.screen_width - cell_size_with_border.w)\\r\\n y = randint(Settings.screen_near_top + cell_total_security_border.h,\\r\\n Settings.screen_height - cell_size_with_border.h)\\r\\n # Check if there is some sprite in this position\\r\\n position_not_taken = True\\r\\n rect1 = pg.Rect(x, y, cell_size.w, cell_size.h)\\r\\n if actor_cls.actor_type != ActorType.BAT:\\r\\n # Apples and mines cannot collide with any kind of sprite\\r\\n for sprite in game.active_sprites:\\r\\n if rect1.colliderect(sprite.rect):\\r\\n position_not_taken = False\\r\\n break\\r\\n else:\\r\\n # Bats cannot collide with snakes and other bats\\r\\n for sprite in game.snakes:\\r\\n if rect1.colliderect(sprite.rect):\\r\\n position_not_taken = False\\r\\n break\\r\\n if position_not_taken:\\r\\n for sprite in game.bats:\\r\\n if rect1.colliderect(sprite.rect):\\r\\n position_not_taken = False\\r\\n break\\r\\n if position_not_taken:\\r\\n actor_obj = actor_cls(x, y, actor_type, game=game)\\r\\n if actor_obj.actor_type == ActorType.BAT:\\r\\n actor_obj.change_x = randint(3, 5)\\r\\n actor_obj.change_y = randint(3, 5)\\r\\n actor_obj.initialize_boundaries()\\r\\n actor_added = True\",\n \"def __generate_rectangle_obstacles(self, world):\\n obs_min_dim = self.cfg[\\\"obstacle\\\"][\\\"rectangle\\\"][\\\"min_dim\\\"]\\n obs_max_dim = self.cfg[\\\"obstacle\\\"][\\\"rectangle\\\"][\\\"max_dim\\\"]\\n obs_max_combined_dim = self.cfg[\\\"obstacle\\\"][\\\"rectangle\\\"][\\\"max_combined_dim\\\"]\\n obs_min_count = self.cfg[\\\"obstacle\\\"][\\\"rectangle\\\"][\\\"min_count\\\"]\\n obs_max_count = self.cfg[\\\"obstacle\\\"][\\\"rectangle\\\"][\\\"max_count\\\"]\\n obs_min_dist = self.cfg[\\\"obstacle\\\"][\\\"rectangle\\\"][\\\"min_distance\\\"]\\n obs_max_dist = self.cfg[\\\"obstacle\\\"][\\\"rectangle\\\"][\\\"max_distance\\\"]\\n\\n # generate the obstacles\\n obstacles = []\\n obs_dim_range = obs_max_dim - obs_min_dim\\n obs_dist_range = obs_max_dist - obs_min_dist\\n num_obstacles = randrange(obs_min_count, obs_max_count + 1)\\n\\n test_geometries = [r.global_geometry for r in world.robots]\\n while len(obstacles) < num_obstacles:\\n # generate dimensions\\n width = obs_min_dim + (random() * obs_dim_range )\\n height = obs_min_dim + (random() * obs_dim_range )\\n while width + height > obs_max_combined_dim:\\n height = obs_min_dim + (random() * obs_dim_range )\\n\\n # generate position\\n dist = obs_min_dist + (random() * obs_dist_range)\\n phi = -pi + (random() * 2 * pi)\\n x = dist * sin(phi)\\n y = dist * cos(phi)\\n\\n # generate orientation\\n theta = -pi + (random() * 2 * pi)\\n\\n # test if the obstacle overlaps the robots or the goal\\n obstacle = RectangleObstacle(width, height, Pose(x, y, theta))\\n intersects = False\\n for test_geometry in test_geometries:\\n intersects |= geometrics.convex_polygon_intersect_test(test_geometry, obstacle.global_geometry)\\n if not intersects:\\n obstacles.append(obstacle)\\n return obstacles\",\n \"def sea_execution(board, position, role):\\n quitt = False\\n if position == 'comp':\\n #print(1)\\n #temporary for dumb AI\\n #create and print a list of coastal, friendly regions where norse is not the ONLY one\\n \\n possible_region_list = []\\n \\n #loops through list of friendly, coastal, not just Norse regions to append to a possible_region_list\\n for region in board.get_controlled_regions(role):\\n #print(2)\\n coastal = False\\n just_norse = False\\n if region.coast:\\n coastal = True\\n if len(region.blocks_present) == 1 and region.blocks_present[0].name.upper() == 'NORSE':\\n just_norse = True\\n \\n if coastal and not just_norse:\\n possible_region_list.append(region)\\n \\n \\n #loops through list of friendly, coastal regions to append to a possible_final_region_list\\n possible_final_region_list = []\\n for region in board.get_controlled_regions(role): \\n #print(3) \\n if region.coast:\\n possible_final_region_list.append(region)\\n \\n \\n \\n if len(possible_final_region_list) >= 2:\\n #if you want to add in last-min strategy, do it here\\n #random region from possible list\\n england = board.regions[22]\\n if england in possible_region_list:\\n original_region = england\\n else:\\n original_region = possible_region_list[random.randint(0, len(possible_region_list) - 1)]\\n #remove the original region from the possible end regions\\n possible_final_region_list.remove(original_region)\\n \\n #possible_block_list\\n #list of possible blocks to move (present in region) and not norse\\n possible_block_list = []\\n for block in original_region.blocks_present:\\n if block.name != 'NORSE':\\n possible_block_list.append(block)\\n \\n move_block_list = []\\n blocks_moved = 0\\n #print(4)\\n\\n while blocks_moved < 2:\\n #print(5)\\n block = possible_block_list[random.randint(0, len(possible_block_list)-1)]\\n #if it's not already on the list,append to move_block_list\\n if block not in move_block_list:\\n move_block_list.append(block)\\n blocks_moved+=1\\n elif block in move_block_list and len(possible_block_list) == 1:\\n blocks_moved+=1\\n else:\\n print('neither condition was met so this is an infinite loop')\\n \\n \\n #print(6) \\n new_region = possible_final_region_list[random.randint(0, len(possible_final_region_list) - 1)]\\n \\n for block in move_block_list:\\n \\n board.add_to_location(block, new_region)\\n print(block.name + ' moved from ' + original_region.name + ' to ' + new_region.name)\\n \\n else:\\n print('There are not enough friendly regions with which to play this card.')\\n \\n \\n #add in if it's not possible\\n elif position == 'opp':\\n \\n \\n possible_region_list = []\\n \\n #loops through list of friendly, coastal, not just Norse regions to append to a possible_region_list\\n for region in board.get_controlled_regions(role):\\n coastal = False\\n just_norse = False\\n if region.coast:\\n coastal = True\\n if len(region.blocks_present) == 1 and region.blocks_present[0].name.upper() == 'NORSE':\\n just_norse = True\\n \\n if coastal and not just_norse:\\n possible_region_list.append(region)\\n \\n \\n #loops through list of friendly, coastal regions to append to a possible_final_region_list\\n possible_final_region_list = []\\n for region in board.get_controlled_regions(role): \\n if region.coast:\\n possible_final_region_list.append(region)\\n \\n \\n \\n if len(possible_final_region_list) >= 2:\\n \\n print('Possible origin regions:')\\n for region in possible_region_list:\\n print(region.name)\\n \\n #user input region, check if in possible list\\n valid_region = False\\n while not valid_region:\\n \\n original_region_name = input('What region would you like to move block(s) from? Enter a name or \\\\'none\\\\'.\\\\n>').upper()\\n \\n if original_region_name != 'NONE':\\n \\n original_region = search.region_name_to_object(board, original_region_name)\\n \\n if original_region and original_region in possible_region_list:\\n valid_region = True\\n else:\\n print('Invalid region.')\\n else:\\n quitt = True\\n \\n if not quitt:\\n #remove the original region from the possible end regions\\n possible_final_region_list.remove(original_region)\\n \\n #possible_block_list\\n #list of possible blocks to move (present in region) and not norse\\n possible_block_list = []\\n for block in original_region.blocks_present:\\n if block.name != 'NORSE':\\n possible_block_list.append(block)\\n \\n print('Possible blocks:')\\n for block in possible_block_list:\\n print(block.name)\\n \\n \\n move_block_list = []\\n blocks_moved = 0\\n quittt = False\\n block_name = ''\\n while blocks_moved < 2 and not quittt:\\n if block_name != 'NONE':\\n valid_block = False\\n while not valid_block:\\n \\n \\n block_name = input('Which block would you like to move? Enter a name or \\\\'none\\\\'.\\\\n>').upper()\\n \\n if block_name != 'NONE':\\n \\n block_to_move = search.block_name_to_object(possible_block_list, block_name)\\n \\n if block_to_move and block_to_move not in move_block_list:\\n valid_block = True\\n move_block_list.append(block_to_move)\\n blocks_moved+=1\\n \\n elif block in move_block_list and len(possible_block_list) == 1:\\n blocks_moved=1\\n \\n else:\\n print('Invalid block.')\\n continue\\n else:\\n valid_block = True\\n if len(move_block_list) == 1:\\n quittt = True\\n quitt = False\\n if len(move_block_list) > 0: \\n print('Possible final regions:')\\n for region in possible_final_region_list:\\n print(region.name)\\n \\n #user input region, check if in possible list\\n valid_region = False\\n while not valid_region:\\n \\n new_region_name = input('What region would you like to move block(s) to? Enter a name or \\\\'none\\\\'.\\\\n>').upper()\\n \\n if new_region_name != 'NONE':\\n \\n new_region = search.region_name_to_object(board, new_region_name)\\n \\n if new_region and new_region in possible_final_region_list:\\n valid_region = True\\n else:\\n print('Invalid region.')\\n continue\\n else:\\n valid_region = True\\n quitt = True\\n \\n if not quitt:\\n \\n for block in move_block_list:\\n \\n board.add_to_location(block, new_region)\\n print(block.name + ' moved from ' + original_region.name + ' to ' + new_region.name)\\n \\n else:\\n print('There are not enough friendly coastal regions with which to play this card.')\",\n \"def populate_tiles(self):\\n\\n # grid format :\\n # grid(x,y,z)[0]: A valid WorldTile type (i.e. WorldTile.door)\\n # grid(x,y,z)[1]: A list of ASCII color or format codes for ColorIze\\n # grid(x,y,z)[2]: The tile object\\n\\n self.t_count = 0 # Tile count, increment for each tile added\\n self.build_start = time.clock()\\n self.logger.info(\\\"[*] Starting world building script\\\")\\n\\n script_list = [\\n self.build_boss_room,\\n self.build_rooms,\\n self.build_halls,\\n self.build_doors,\\n self.build_chests,\\n self.build_traps,\\n self.build_mobs,\\n self.build_npcs\\n ]\\n for func in script_list:\\n self.logger.debug(\\\"\\\\tRunning {}\\\".format(func.__name__))\\n if not func():\\n e_text = \\\"Build script failed : {}\\\".format(func.__name__)\\n raise AssertionError(e_text)\\n\\n self.logger.info(\\\"[*] World building script completed\\\")\\n self.logger.debug(\\\"\\\\tTiles Placed : {}\\\".format(self.t_count))\\n build_time = time.clock()-self.build_start\\n self.logger.debug(\\\"\\\\tTook {}s\\\".format(build_time))\\n self.logger.debug(\\\"\\\\tTiles/s : {}\\\".format(t_count/build_time))\",\n \"def new_tile(self):\\n random.shuffle(self.tiles) # shuffle the list of tiles tuples\\n count = 0\\n while self.get_tile(self.tiles[0][0], self.tiles[0][1]) != 0 and count < self.grid_height*self.grid_width: \\n self.tiles.append(self.tiles.pop(0)) \\n \\n # next, select value as 2 with a 90% probability (percentage) and 4 with 10%\\n percentage = random.random() \\n if percentage > 0.1:\\n value = 2\\n else:\\n value = 4\\n row = self.tiles[0][0]\\n col = self.tiles[0][1]\\n self.set_tile(row , col,value)\",\n \"def new_tile(self):\\n \\n empty_items = []\\n for row in range(self.get_grid_height()):\\n for col in range(self.get_grid_width()):\\n if self.get_tile(row, col) == 0:\\n empty_items.append((row, col))\\n \\n random_row = 0\\n random_col = 0\\n if len(empty_items) != 0:\\n random_empty_tile = random.randrange(0, len(empty_items))\\n (random_row, random_col) = empty_items[random_empty_tile]\\n else:\\n return\\n # the % of getting \\\"4\\\" from 0~9 is 10%\\n random_time = random.randrange(0, 10)\\n \\n if random_time == 4:\\n self._cells[random_row][random_col] = 4\\n else:\\n self._cells[random_row][random_col] = 2\",\n \"def init():\\n for i in range(COLS):\\n for j in range(ROWS):\\n BOARD[i][j] = int(random(2))\",\n \"def generate_standard_tech_tiles(seed=0):\\n\\n if seed is not 0:\\n random.seed(seed)\\n all_standard_tiles = [1, 2, 3, 4, 5, 6, 7, 8, 9]\\n randomized_tiles = list()\\n\\n for _ in range(9):\\n chosen_tile_index = random.randint(0, len(all_standard_tiles) - 1)\\n randomized_tiles.append(all_standard_tiles[chosen_tile_index])\\n all_standard_tiles.pop(chosen_tile_index)\\n\\n return tuple(randomized_tiles)\",\n \"def new_tile(self):\\n zero_list = []\\n zero_cell = ()\\n # self._cells = [[0 for col in range(self._grid_width)] for row in range(self._grid_height)]\\n for row in range(self._grid_height):\\n for col in range(self._grid_width):\\n if self._cells[row][col] == 0:\\n zero_cell = (row, col)\\n zero_list.append(zero_cell)\\n if len(zero_list) > 0:\\n chance = random.randrange(0,10)\\n cell_idx = random.randrange(len(zero_list))\\n if chance == 9:\\n self._cells[zero_list[cell_idx][0]][zero_list[cell_idx][1]] = 4\\n else:\\n self._cells[zero_list[cell_idx][0]][zero_list[cell_idx][1]] = 2\\n else:\\n print(\\\"You lost! Better luck next time!\\\")\",\n \"def random_v_random(n=1):\\n p1_strategy = strategies.RandomStrategy()\\n p2_strategy = strategies.RandomStrategy()\\n p1 = player.Player('X', p1_strategy)\\n p2 = player.Player('O', p2_strategy)\\n board = tictactoe.Board()\\n game = rl_game.Game(p1, p2, board)\\n game.play_one()\",\n \"def create(self):\\n\\n for i in range(8):\\n # Create white pawns\\n self.board[1][i] = Piece(\\\"pawn\\\", 1, i, 0)\\n # Create black pawns\\n self.board[6][i] = Piece(\\\"pawn\\\", 6, i, 1)\\n\\n # Create white rooks\\n self.board[0][0] = Piece(\\\"rook\\\", 0, 0, 0)\\n self.board[0][7] = Piece(\\\"rook\\\", 0, 7, 0)\\n\\n # Create black rooks\\n self.board[7][0] = Piece(\\\"rook\\\", 7, 0, 1)\\n self.board[7][7] = Piece(\\\"rook\\\", 7, 7, 1)\\n\\n # Create white knights\\n self.board[0][1] = Piece(\\\"knight\\\", 0, 1, 0)\\n self.board[0][6] = Piece(\\\"knight\\\", 0, 6, 0)\\n\\n # Create black knights\\n self.board[7][1] = Piece(\\\"knight\\\", 7, 1, 1)\\n self.board[7][6] = Piece(\\\"knight\\\", 7, 6, 1)\\n\\n # Create white bishop\\n self.board[0][2] = Piece(\\\"bishop\\\", 0, 2, 0)\\n self.board[0][5] = Piece(\\\"bishop\\\", 0, 5, 0)\\n\\n # Create black bishop\\n self.board[7][2] = Piece(\\\"bishop\\\", 7, 2, 1)\\n self.board[7][5] = Piece(\\\"bishop\\\", 7, 5, 1)\\n\\n # Create white queen and king\\n self.board[0][3] = Piece(\\\"queen\\\", 0, 3, 0)\\n self.board[0][4] = Piece(\\\"king\\\", 0, 4, 0)\\n\\n # Create black queen and king\\n self.board[7][3] = Piece(\\\"queen\\\", 7, 3, 1)\\n self.board[7][4] = Piece(\\\"king\\\", 7, 4, 1)\",\n \"def new_tile(self):\\r\\n rand_x = random.randrange(self.width)\\r\\n rand_y = random.randrange(self.height)\\r\\n while self.get_tile(rand_y, rand_x) != 0:\\r\\n rand_x = random.randrange(self.width)\\r\\n rand_y = random.randrange(self.height)\\r\\n value = random.choice([2,2,2,2,2,2,2,2,2,4])\\r\\n del self.board[rand_y][rand_x]\\r\\n self.board[rand_y].insert(rand_x,value)\\r\\n return self.board\",\n \"def NewTile(field):\\n var = False\\n while not var:\\n temp = random.randrange(0, len(field), 1)\\n if field[temp] == 0:\\n r = random.randrange(0, 100, 1)\\n if r > 80:\\n field[temp] = -4\\n else:\\n field[temp] = -2\\n \\n var = True\\n return field\",\n \"def genWater(grid, resolution):\\n\\n grid_surface = len(grid) * len(grid[0])\\n\\n # Amount of surface for the water.\\n allowed_surface = round(0.2 * grid_surface)\\n\\n # Collection of the created surfaces\\n water_surfaces = []\\n\\n # Min size of one water piece.\\n min_single_size = 4 * resolution\\n\\n run = 0\\n\\n # Loop until 4 and enough surface:\\n while allowed_surface != 0:\\n run += 1\\n print (allowed_surface)\\n w = 0\\n l = 0\\n\\n # Only generate random if we have more then 1 option left.\\n if len(water_surfaces) < 3 and min_single_size != allowed_surface and allowed_surface > 5:\\n try:\\n size = random.randint(min_single_size, allowed_surface)\\n except ValueError as e:\\n print (\\\"Error occured: {0} min: {1} surf: {2}\\\".format(e, min_single_size, allowed_surface))\\n\\n # Otherwise the size is the allowed surface\\n else:\\n size = allowed_surface\\n\\n # Shouldn't go below 0\\n if allowed_surface - size >= 0:\\n\\n # Calculate width and length if possible.\\n # Starting from the square root causes the part to\\n # be more square instead of a straight line.\\n init = round(math.sqrt(size))\\n for i in range(init, 1, -1):\\n if size % i == 0 and 1 <= math.ceil((size / i) / i) <= 4:\\n w = i\\n l = size / w\\n\\n # Reinit allowed surface\\n allowed_surface -= size\\n\\n # Randomly switch width and length\\n coinflip = random.randint(1, 2)\\n if coinflip == 1:\\n\\n # Adds a tuple wich contains (width, length, ratio, \\n # surface)\\n water_surfaces.append((w, int(l), round(l / w, 2), \\n size))\\n else:\\n water_surfaces.append((int(l), w, round(l / w, 2), \\n size))\\n break\\n\\n if run > 4:\\n # Drop last try and remake the surface.\\n print (\\\"Drop\\\")\\n try:\\n run = 2\\n allowed_surface += water_surfaces[-1][3]\\n water_surfaces = water_surfaces[:-1]\\n except:\\n print (\\\"wat\\\")\\n\\n return water_surfaces\",\n \"def makeGrid(self, width, height, rewardLocs, exit, nPick=1, nAux=1, walls=[]):\\n # Make mapping from coordinate (x, y, (takenreward1, takenreward2, ...))\\n # to state number, and vice-versa.\\n rTaken = iter([(),])\\n for nPicked in range(1, nPick+1):\\n rTaken = itertools.chain(rTaken, \\n myCombinations(rewardLocs, r=nPicked)\\n )\\n # Iterators are hard to reset, so we list it.\\n rTaken = list(rTaken)\\n\\n # Mappings from state to coordinates, vice-versa\\n coordToState = {}\\n stateToCoord = {}\\n stateIdx = 0\\n for x in range(width):\\n for y in range(height):\\n for stuff in rTaken:\\n for holding in self.holdingPossibilities:\\n coordToState[(x, y, stuff, holding)] = stateIdx\\n stateToCoord[stateIdx] = (x, y, stuff, holding)\\n stateIdx += 1\\n self.deadEndState = stateIdx\\n\\n # Actually make the transition function\\n def trans(f, p): \\n aux = p\\n (x, y, stuff, holding) = stateToCoord[f]\\n actionMap = {}\\n default = {(f, aux): 1}\\n # Make the transition dictionary if the dead-end state (state width*height)\\n if f == self.F-1:\\n for action in range(5):\\n actionMap[action] = default\\n return actionMap\\n\\n # Otherwise, determine directions of motion, etc. \\n for i in range(4):\\n actionMap[i] = default\\n if x != 0 and ((x-1, y) not in walls):\\n actionMap[0] = {(coordToState[(x-1,y,stuff, holding)], aux): 1}\\n if x < width-1 and ((x+1, y) not in walls):\\n actionMap[1] = {(coordToState[(x+1,y,stuff, holding)], aux): 1}\\n if y != 0 and ((x, y-1) not in walls):\\n actionMap[2] = {(coordToState[(x,y-1,stuff, holding)], aux): 1}\\n if y < height-1 and ((x, y+1) not in walls):\\n actionMap[3] = {(coordToState[(x,y+1,stuff, holding)], aux): 1}\\n # What happens when the agent uses action 4?\\n if (x, y) == exit:\\n # Some cases, depending on self.oneAtATime\\n if not self.oneAtATime:\\n # The agent is leaving.\\n actionMap[4] = {(self.deadEndState, aux): 1}\\n else:\\n # The agent is dropping off a reward. holeFiller will\\n # take care of the reward value.\\n if len(stuff) >= nPick:\\n # The agent is not allowed to pick up more stuff\\n actionMap[4] = {(self.deadEndState, aux): 1}\\n else:\\n # The agent drops off the object.\\n actionMap[4] = {(coordToState[(x,y,stuff, -1)], aux): 1}\\n elif (x, y) not in rewardLocs:\\n # No reward to pick up. Do nothing.\\n actionMap[4] = default\\n elif (x, y) in stuff:\\n # This reward has already been used. Do nothing.\\n actionMap[4] = default\\n elif len(stuff) >= nPick or (holding != -1 and holding < len(stuff)\\n and self.oneAtATime):\\n # The agent has its hands full.\\n actionMap[4] = default\\n else:\\n # The agent is allowed to pick up an object.\\n newStuff = tuple(sorted(list(stuff) + [(x, y)]))\\n if self.oneAtATime:\\n newHoldingIdx = newStuff.index((x, y))\\n else:\\n newHoldingIdx = -1\\n actionMap[4] = {(coordToState[(x, y, newStuff, newHoldingIdx)], aux): 1}\\n return actionMap\\n\\n # Man, I'm outputting a lot of stuff.\\n # coordToState[(x, y, rewardsLeft, holding)] -> index of this state\\n # stateToCoord[index] -> (x, y, rewardsLeft, holding)\\n # rTaken is a list of all possible combinations of leftover rewards.\\n return (trans, coordToState, stateToCoord, rTaken)\",\n \"def create_random(self):\\n number_of_layers = random.choice(self.parameter_choices['number_of_layers'])\\n neurons_per_layer = []\\n dropout_per_layer = []\\n self.network['number_of_layers'] = number_of_layers\\n\\n for i in range(number_of_layers):\\n neurons_per_layer.append(random.choice(self.parameter_choices['neurons_per_layer']))\\n dropout_per_layer.append(random.choice(self.parameter_choices['dropout_per_layer']))\\n\\n self.network['neurons_per_layer'] = neurons_per_layer\\n self.network['dropout_per_layer'] = dropout_per_layer\\n self.network['optimizer'] = random.choice(self.parameter_choices['optimizer'])\\n self.network['activation'] = random.choice(self.parameter_choices['activation'])\",\n \"def generate_boards():\\n\\n print \\\"Generating data, please hold on...\\\"\\n # a list for turns, each which is a list of boards, which are unique layouts\\n # a completely blank layout is always the start of the game, counting for turn 0\\n game = [[Board(' ' * 9, 1)]]\\n\\n # there are at most 9 turns in a game of tic tac toe\\n for turnNum in range(1, 10):\\n # list of layouts for the current turn\\n turn = []\\n upperLayouts = game[-1]\\n\\n if turnNum % 2 == 1: player = 'X'\\n else: player = 'O'\\n\\n # every turns' unique layouts are numbered to seperate them more easily\\n pattern = 1\\n # goes through every layout from the previous turn\\n for ul in upperLayouts:\\n # game does not continue after a winning move, and using a won board is only possible after turn 5\\n if turnNum <= 5 or not ul.check_win()[0]:\\n # 9 positions on every board\\n for pos in range(9):\\n if ul[pos] == ' ':\\n newLayout = Board(ul[0:pos] + player + ul[pos+1:])\\n # if it is a unique layout\\n unique = True\\n # goes through every existing layout for this turn\\n for item in turn:\\n if newLayout.matches(item): \\n unique = False\\n # the upper layout leads to an existing layout\\n ul.paths.append(item.pattern)\\n break\\n if unique:\\n turn.append(Board(newLayout, pattern))\\n # the current upper layout leads to the new layout\\n ul.paths.append(pattern)\\n pattern += 1\\n else:\\n # adds a zero for paths because a played character is taking up that space\\n ul.paths.append(0)\\n game.append(turn)\\n return game\",\n \"def generate_random(self, prob_alive=0.3):\\n self.generation = 0\\n for i in range(self.lines):\\n for j in range(self.cols):\\n if random.random() < prob_alive:\\n self[i][j] = self.cell_state['alive']\",\n \"def random_blocks():\\n cells = []\\n while len(cells) != 43:\\n cell_to_add = (random.randint(0, 11), random.randint(0, 9))\\n if cell_to_add not in cells:\\n cells.append(cell_to_add)\\n return cells\",\n \"def randomChestplate():\\n return random.choice(CHESTPLATES)\",\n \"def generate_options(board: list, player_turn: chr):\\n black_marbles, white_marbles = Board.read_marbles(board)\\n black_risk, white_risk = Evaluator.assess_risk(black_marbles, white_marbles)\\n if player_turn == 'b':\\n risk = black_risk\\n else:\\n risk = white_risk\\n\\n board_object = Board()\\n moves, resulting_boards = board_object.generate_all_boards(board, player_turn)\\n # Assume score 0 for now\\n Evaluator.score_move(moves, 0)\\n for i in range(0, len(moves)):\\n Evaluator.calculate_board_score(moves[i], resulting_boards[i], player_turn, risk)\\n return moves, resulting_boards\",\n \"def make_grid(width, height): \\n return {(row, col): choice(ascii_uppercase)\\n for row in range (height) # remove ' ' and add choice()\\n for col in range(width)}\",\n \"def simulate(self):\\n self._t = self._t + 1\\n if self._t == self._cycle:\\n # End of a season, start of the next one. Year is also cyclic that is WINTER -> SPRING.\\n self._t = 0\\n self._season = self._season.next()\\n\\n # When the ammount of newly produced food in a cell is over and the cell can seed we\\n # randomly choose another spot where some random ammount of newly produced food should\\n # be stored.\\n for i in range(self._height):\\n for j in range(self._width):\\n if self._env[i][j].get_newly() == 0 and not self._seeded[i][j]:\\n # if the cell become empty just now seed in once in a randomn cell on the grid.\\n self._seeded[i][j] = True\\n cap = self._height + self._width\\n while cap > 0:\\n seedi = random.randint(0, self._height - 1)\\n seedj = random.randint(0, self._width - 1)\\n\\n production_cap = self._food_per_season[self._season.value]\\n\\n production_cap -= self._env[seedi][seedj].get_newly()\\n\\n if production_cap > 0:\\n seed_amount = random.randint(1, production_cap)\\n self._env[seedi][seedj].produce(seed_amount)\\n self._seeded[seedi][seedj] = False\\n break\\n\\n cap = cap - 1\",\n \"def new_game(self):\\n self.cells = [] # Array of cells\\n self.frame_count = 0\\n self.database = []\\n self.timer = [Consts[\\\"MAX_TIME\\\"], Consts[\\\"MAX_TIME\\\"]]\\n self.result = None\\n # Define the players first\\n self.cells.append(Cell(0, [Consts[\\\"WORLD_X\\\"] / 4, Consts[\\\"WORLD_Y\\\"] / 2], [0, 0], Consts[\\\"DEFAULT_RADIUS\\\"]))\\n self.cells.append(Cell(1, [Consts[\\\"WORLD_X\\\"] / 4 * 3, Consts[\\\"WORLD_Y\\\"] / 2], [0, 0], Consts[\\\"DEFAULT_RADIUS\\\"]))\\n # Generate a bunch of random cells\\n for i in range(Consts[\\\"CELLS_COUNT\\\"]):\\n if i < 4:\\n rad = 1.5 + (random.random() * 1.5) # Small cells\\n elif i < 10:\\n rad = 10 + (random.random() * 4) # Big cells\\n else:\\n rad = 2 + (random.random() * 9) # Everything else\\n x = Consts[\\\"WORLD_X\\\"] * random.random()\\n y = Consts[\\\"WORLD_Y\\\"] * random.random()\\n cell = Cell(i + 2, [x, y], [(random.random() - 0.5) * 2, (random.random() - 0.5) * 2], rad)\\n safe_dist = Consts[\\\"SAFE_DIST\\\"] + rad\\n while min(map(cell.distance_from, self.cells[:2])) < safe_dist:\\n cell.pos = [\\n Consts[\\\"WORLD_X\\\"] * random.random(),\\n Consts[\\\"WORLD_Y\\\"] * random.random()\\n ]\\n self.cells.append(cell)\",\n \"def generate_random_toy() -> Toy:\\n dimensions = round(uniform(5, 100), 2)\\n rooms_number = randint(1, 5)\\n return SantaWorkShop(dimensions, rooms_number, 5)\",\n \"def create_grid(player1: game_code.Player, player2: game_code.Player) -> None:\\r\\n status = True\\r\\n abort = False\\r\\n\\r\\n # Initialize two game board both with randomized ship placements\\r\\n player_1 = game_code.RandomizedBattleshipGame()\\r\\n player_2 = game_code.RandomizedBattleshipGame()\\r\\n\\r\\n player_1_sequence = []\\r\\n player_2_sequence = []\\r\\n player_1_previous_move = None\\r\\n player_2_previous_move = None\\r\\n\\r\\n save_initial_state1 = player_1\\r\\n save_initial_state2 = player_2\\r\\n\\r\\n escape = instruction_font.render('HIT ESC TO RETURN TO THE MAIN MENU OR TO START A NEW GAME', False,\\r\\n (255, 255, 255))\\r\\n player_label_1 = label_font.render('Player 1', False, (255, 255, 255))\\r\\n player_label_2 = label_font.render('Player 2', False, (255, 255, 255))\\r\\n\\r\\n while status:\\r\\n screen.blit(background, (0, 0))\\r\\n\\r\\n # Draw the grids belonging to each player\\r\\n for column in range(0, 8):\\r\\n for row in range(0, 8):\\r\\n cell = pygame.Rect((190 + column * 50, 160 + row * 50), (50, 50))\\r\\n pygame.draw.rect(screen, (255, 255, 255, 1), cell, 0)\\r\\n pygame.draw.rect(screen, (0, 0, 0, 1), cell, 3)\\r\\n\\r\\n for column in range(0, 8):\\r\\n for row in range(0, 8):\\r\\n cell = pygame.Rect((690 + column * 50, 160 + row * 50), (50, 50))\\r\\n pygame.draw.rect(screen, (255, 255, 255, 1), cell, 0)\\r\\n pygame.draw.rect(screen, (0, 0, 0, 1), cell, 3)\\r\\n\\r\\n # Display labels and text\\r\\n screen.blit(player_label_1, (340, 580))\\r\\n screen.blit(player_label_2, (840, 580))\\r\\n screen.blit(escape, (25, 685))\\r\\n\\r\\n columns = 'ABCDEFGH'\\r\\n rows = '12345678'\\r\\n # Label Player 1 Board\\r\\n for letter in range(0, 8):\\r\\n label = label_font.render(columns[letter], False, (255, 255, 255))\\r\\n screen.blit(label, (205 + letter * 50, 125))\\r\\n for number in range(0, 8):\\r\\n label = label_font.render(rows[number], False, (255, 255, 255))\\r\\n screen.blit(label, (165, 170 + number * 50))\\r\\n # Label Player 2 Board\\r\\n for letter in range(0, 8):\\r\\n label = label_font.render(columns[letter], False, (255, 255, 255))\\r\\n screen.blit(label, (705 + letter * 50, 125))\\r\\n for number in range(0, 8):\\r\\n label = label_font.render(rows[number], False, (255, 255, 255))\\r\\n screen.blit(label, (665, 170 + number * 50))\\r\\n\\r\\n # Display the ships prior to starting the game\\r\\n display_ships(save_initial_state1, True)\\r\\n display_ships(save_initial_state2, False)\\r\\n\\r\\n if player_1_previous_move is None and player_2_previous_move is None:\\r\\n pygame.display.update()\\r\\n pygame.time.wait(1000)\\r\\n\\r\\n while player_1.get_winner() is None and player_2.get_winner() is None and not abort:\\r\\n\\r\\n # player1 shot on player2 Board\\r\\n player_1_previous_move = player1.make_move(player_2, player_1_previous_move)\\r\\n player_2.make_move(player_1_previous_move)\\r\\n player_1_sequence.append(player_1_previous_move)\\r\\n if player_2.get_winner() is not None:\\r\\n break\\r\\n # player1 on player2 Board\\r\\n player_2_previous_move = player2.make_move(player_1, player_2_previous_move)\\r\\n player_1.make_move(player_2_previous_move)\\r\\n player_2_sequence.append(player_2_previous_move)\\r\\n\\r\\n for event in pygame.event.get():\\r\\n if event.type == pygame.QUIT:\\r\\n pygame.quit()\\r\\n sys.exit()\\r\\n if event.type == pygame.KEYDOWN:\\r\\n if event.key == pygame.K_ESCAPE:\\r\\n abort = True\\r\\n status = False\\r\\n\\r\\n display_ships(player_1, True)\\r\\n pygame.time.wait(500)\\r\\n pygame.display.update()\\r\\n pygame.time.wait(500)\\r\\n display_ships(player_2, False)\\r\\n pygame.display.update()\\r\\n\\r\\n # Display the victory message of the winning player\\r\\n if player_1.get_winner() == 'Lost':\\r\\n winner = 'Player 2'\\r\\n victory = message_font.render(winner + ' Wins!', False, (255, 255, 255))\\r\\n screen.blit(victory, (450, 50))\\r\\n else:\\r\\n winner = 'Player 1'\\r\\n victory = message_font.render(winner + ' Wins!', False, (255, 255, 255))\\r\\n screen.blit(victory, (450, 50))\\r\\n\\r\\n # Display the final state of the game\\r\\n display_ships(player_1, True)\\r\\n display_ships(player_2, False)\\r\\n\\r\\n # Check for user input\\r\\n for event in pygame.event.get():\\r\\n if event.type == pygame.QUIT:\\r\\n pygame.quit()\\r\\n sys.exit()\\r\\n if event.type == pygame.KEYDOWN:\\r\\n if event.key == pygame.K_ESCAPE:\\r\\n status = False\\r\\n\\r\\n pygame.display.update()\",\n \"def generate_board():\\n b = open(_BOARD_FILE, \\\"r\\\").readlines()\\n for line in b:\\n raw = line.strip().split(\\\" \\\")\\n _board_graph[str_to_pos(raw[0])] = Space(\\n (raw[1] == \\\"R\\\"),\\n TYPE_MAP[raw[1]],\\n {str_to_pos(str_pos) for str_pos in raw[2:]})\",\n \"def randPlace(self):\\r\\n random.seed(self.seed)\\r\\n \\r\\n # Start placement on Partition A\\r\\n partA = True\\r\\n for node in self.G.nodes():\\r\\n \\r\\n randSite = random.randint(0,int(self.sitesNum/2)-1)\\r\\n \\r\\n if partA:\\r\\n partSite = self.sitesA\\r\\n self.G.node[node][\\\"part\\\"] = 'A'\\r\\n \\r\\n else:\\r\\n partSite = self.sitesB\\r\\n self.G.node[node][\\\"part\\\"] = 'B'\\r\\n \\r\\n while (partSite[randSite].isOcp()):\\r\\n randSite = random.randint(0,int(self.sitesNum/2)-1) \\r\\n\\r\\n partSite[randSite].setCell(node)\\r\\n self.G.node[node][\\\"site\\\"] = partSite[randSite]\\r\\n \\r\\n # Toggle partition for next placement\\r\\n partA = not partA\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.68248934","0.64361274","0.6384287","0.6220165","0.614266","0.613112","0.6068092","0.6057356","0.6054699","0.6002918","0.5973913","0.5956003","0.59538376","0.59481156","0.59429073","0.59363997","0.59216344","0.59191567","0.59100956","0.58849156","0.58718026","0.5866675","0.58520085","0.5846157","0.5842792","0.58204687","0.58107954","0.5800557","0.5800468","0.57978207","0.57948196","0.5725796","0.5722613","0.571879","0.57154936","0.5712448","0.5709946","0.5681572","0.56668794","0.5657484","0.56568533","0.56566954","0.56488353","0.5639202","0.5638784","0.5634537","0.5632511","0.5629356","0.56182694","0.5594509","0.55859405","0.55857456","0.5582024","0.55732036","0.5555083","0.5553031","0.5546122","0.5544155","0.5541593","0.5541232","0.5535443","0.5532788","0.5526076","0.5519978","0.5514341","0.5512885","0.55126464","0.5504339","0.5486688","0.54818666","0.5479802","0.54753065","0.54727226","0.5471637","0.54676825","0.5462452","0.5461227","0.5455798","0.54512185","0.544472","0.54392064","0.54386324","0.54383487","0.5434769","0.54317147","0.54137623","0.54129684","0.5410515","0.54075736","0.5402761","0.5401965","0.53994775","0.53994155","0.5398598","0.53982306","0.53963536","0.53812623","0.5374453","0.534779","0.5344692"],"string":"[\n \"0.68248934\",\n \"0.64361274\",\n \"0.6384287\",\n \"0.6220165\",\n \"0.614266\",\n \"0.613112\",\n \"0.6068092\",\n \"0.6057356\",\n \"0.6054699\",\n \"0.6002918\",\n \"0.5973913\",\n \"0.5956003\",\n \"0.59538376\",\n \"0.59481156\",\n \"0.59429073\",\n \"0.59363997\",\n \"0.59216344\",\n \"0.59191567\",\n \"0.59100956\",\n \"0.58849156\",\n \"0.58718026\",\n \"0.5866675\",\n \"0.58520085\",\n \"0.5846157\",\n \"0.5842792\",\n \"0.58204687\",\n \"0.58107954\",\n \"0.5800557\",\n \"0.5800468\",\n \"0.57978207\",\n \"0.57948196\",\n \"0.5725796\",\n \"0.5722613\",\n \"0.571879\",\n \"0.57154936\",\n \"0.5712448\",\n \"0.5709946\",\n \"0.5681572\",\n \"0.56668794\",\n \"0.5657484\",\n \"0.56568533\",\n \"0.56566954\",\n \"0.56488353\",\n \"0.5639202\",\n \"0.5638784\",\n \"0.5634537\",\n \"0.5632511\",\n \"0.5629356\",\n \"0.56182694\",\n \"0.5594509\",\n \"0.55859405\",\n \"0.55857456\",\n \"0.5582024\",\n \"0.55732036\",\n \"0.5555083\",\n \"0.5553031\",\n \"0.5546122\",\n \"0.5544155\",\n \"0.5541593\",\n \"0.5541232\",\n \"0.5535443\",\n \"0.5532788\",\n \"0.5526076\",\n \"0.5519978\",\n \"0.5514341\",\n \"0.5512885\",\n \"0.55126464\",\n \"0.5504339\",\n \"0.5486688\",\n \"0.54818666\",\n \"0.5479802\",\n \"0.54753065\",\n \"0.54727226\",\n \"0.5471637\",\n \"0.54676825\",\n \"0.5462452\",\n \"0.5461227\",\n \"0.5455798\",\n \"0.54512185\",\n \"0.544472\",\n \"0.54392064\",\n \"0.54386324\",\n \"0.54383487\",\n \"0.5434769\",\n \"0.54317147\",\n \"0.54137623\",\n \"0.54129684\",\n \"0.5410515\",\n \"0.54075736\",\n \"0.5402761\",\n \"0.5401965\",\n \"0.53994775\",\n \"0.53994155\",\n \"0.5398598\",\n \"0.53982306\",\n \"0.53963536\",\n \"0.53812623\",\n \"0.5374453\",\n \"0.534779\",\n \"0.5344692\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.64837104"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":94895,"cells":{"query":{"kind":"string","value":"Highlights separable regions that stable with the given period. A \"separable\" region is one which can be removed from the board without effecting any of the rest of the board."},"document":{"kind":"string","value":"def stability_mask(board, period=6, remove_agent=True):\n if remove_agent:\n board = board * ((board & CellTypes.agent) == 0)\n\n neighborhood = np.ones((3,3))\n alive = (board & CellTypes.alive) // CellTypes.alive\n neighbors = ndimage.convolve(alive, neighborhood, mode='wrap')\n max_neighbors = neighbors\n ever_alive = alive\n orig_board = board\n for _ in range(period):\n board = speedups.advance_board(board)\n alive = (board & CellTypes.alive) // CellTypes.alive\n neighbors = ndimage.convolve(alive, neighborhood, mode='wrap')\n ever_alive |= alive\n max_neighbors = np.maximum(max_neighbors, neighbors)\n is_boundary = (board & CellTypes.frozen > 0)\n is_boundary |= (ever_alive == 0) & (max_neighbors <= 2)\n labels, num_labels = speedups.wrapped_label(~is_boundary)\n mask = np.zeros(board.shape, dtype=bool)\n for idx in range(1, num_labels+1):\n region = labels == idx\n if (board[region] == orig_board[region]).all():\n mask |= region\n return mask"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def make_partioned_regions(shape, alpha=1.0, max_regions=5, min_regions=2):\n ring = np.array([[1,1,1],[1,0,1],[1,1,1]], dtype=np.int16)\n adjacent = np.array([ # Diagonals don't count as adjacent\n [-1,0,0,1],\n [0,-1,1,0]], dtype=np.int16).T\n nearby = np.meshgrid([-2,-1,0,1,2], [-2,-1,0,1,2])\n\n board = np.zeros(shape, dtype=np.int16)\n perimeters = [{\n (i, j) for i, j in zip(*np.nonzero(board == 0))\n }]\n exclusions = [set()]\n while sum(len(p) for p in perimeters) > 0:\n weights = np.array([len(p) for p in perimeters], dtype=float)\n weights[0] = min(alpha, weights[0]) if len(weights) <= max_regions else 1e-10\n if len(weights) <= min_regions:\n weights[1:] = 1e-10\n weights /= np.sum(weights)\n k = get_rng().choice(len(perimeters), p=weights)\n plist = list(perimeters[k])\n i, j = plist[get_rng().choice(len(plist))]\n perimeters[0].discard((i, j))\n perimeters[k].discard((i, j))\n if (i, j) in exclusions[k]:\n continue\n exclusions[0].add((i,j))\n exclusions[k].add((i,j))\n b = board[(i+nearby[0]) % shape[0], (j+nearby[1]) % shape[1]]\n b[2,2] = k or -1\n num_neighbors = signal.convolve2d(b != 0, ring, mode='valid')\n num_foreign = signal.convolve2d((b > 0) & (b != k), ring, mode='valid')\n if ((num_foreign > 0) & (num_neighbors > 2)).any() or num_foreign[1,1] > 0:\n continue\n # Add to the board\n if k == 0:\n k = len(perimeters)\n perimeters.append(set())\n exclusions.append(set())\n board[i, j] = k\n for i2, j2 in (adjacent + (i, j)) % shape:\n if board[i2, j2] == 0:\n perimeters[k].add((i2, j2))\n return board","def resetSagittalSegment(self):\r\n #research\r\n profprint()\r\n sYellow = slicer.mrmlScene.GetNodeByID(\"vtkMRMLSliceNodeYellow\")\r\n if sYellow == None :\r\n sYellow = slicer.mrmlScene.GetNodeByID(\"vtkMRMLSliceNode2\")\r\n reformatLogic = slicer.vtkSlicerReformatLogic()\r\n sYellow.SetSliceVisible(0)\r\n sYellow.SetOrientationToSagittal()\r\n sw = slicer.app.layoutManager().sliceWidget(\"Yellow\")\r\n sw.fitSliceToBackground()\r\n sYellow.Modified()","def highlight_available_v_fences(win, game):\n #Check if player has remaining fences\n player_turn = game.get_player_turn()\n if game.get_pawn(player_turn).get_remaining_fences() == 0:\n return\n\n board = game.get_board()\n\n #Set highlight color\n if player_turn == 1:\n color = LIGHTERRED\n else:\n color = LIGHTERBLUE\n \n for row in range(len(board)-2):\n for col in range(len(board)-1):\n #Highlight fence if no fence placed and does not interesect a horizontal fence. \n if not board[row][col]['v'] and not board[row+1][col]['v'] and board[row+1][col]['h'] != \"Fence Continued\" and game.fair_play_check('v',(col,row)):\n coords = board[row][col]['coord']\n v_fence_coords = (coords[0]*SQUARESIZE+FENCEWIDTH*(coords[0]-1), coords[1]*(SQUARESIZE+FENCEWIDTH))\n v_fence = pygame.Rect(v_fence_coords, (FENCEWIDTH,SQUARESIZE))\n pygame.draw.rect(win, color, v_fence)","def color_segmentation(self):\n cv.namedWindow(\"Segmentation parameters\")\n self.create_trackbar(\"h-u\", \"Segmentation parameters\")\n self.create_trackbar(\"h-l\",\"Segmentation parameters\")\n self.create_trackbar(\"s-u\",\"Segmentation parameters\")\n self.create_trackbar(\"s-l\",\"Segmentation parameters\")\n self.create_trackbar(\"v-u\",\"Segmentation parameters\")\n self.create_trackbar(\"v-l\",\"Segmentation parameters\")\n\n image = self.__image.copy()\n\n while True:\n var_h_upper = cv.getTrackbarPos(\"h-u\", \"Segmentation parameters\")\n var_h_lower = cv.getTrackbarPos(\"h-l\", \"Segmentation parameters\")\n var_s_upper = cv.getTrackbarPos(\"s-u\", \"Segmentation parameters\")\n var_s_lower = cv.getTrackbarPos(\"s-l\", \"Segmentation parameters\")\n var_v_upper = cv.getTrackbarPos(\"v-u\", \"Segmentation parameters\")\n var_v_lower = cv.getTrackbarPos(\"v-l\", \"Segmentation parameters\")\n\n lower = np.array([var_h_lower,var_s_lower,var_v_lower])\n upper = np.array([var_h_upper,var_s_upper,var_v_upper])\n\n bin_image = cv.inRange(self.hsv_image, lower, upper)\n cv.imshow(\"Segmentated image\", bin_image)\n\n if (cv.waitKey(1) & 0xFF == ord('q')):\n break\n cv.destroyAllWindows()","def highlight_available_h_fences(win, game):\n #Check if player has remaining fences\n player_turn = game.get_player_turn()\n if game.get_pawn(player_turn).get_remaining_fences() == 0:\n return\n\n board = game.get_board()\n \n #Set highlight color\n if player_turn == 1:\n color = LIGHTERRED\n else:\n color = LIGHTERBLUE\n \n for row in range(len(board)-1):\n for col in range(len(board)-2):\n #Highlight fence if no fence placed and does not intersect a vertical fence\n if not board[row][col]['h'] and not board[row][col+1]['h'] and board[row][col+1]['v'] != \"Fence Continued\" and game.fair_play_check('h',(col,row)):\n coords = board[row][col]['coord']\n h_fence_coords = (coords[0]*(SQUARESIZE+FENCEWIDTH), coords[1]*SQUARESIZE+FENCEWIDTH*(coords[1]-1))\n h_fence = pygame.Rect(h_fence_coords, (SQUARESIZE,FENCEWIDTH))\n pygame.draw.rect(win, color, h_fence)","def plot_sed(self,period=6.,projection='lambert',geopolygons=None, showfig=True, vmin=0, vmax=None, hillshade=False):\n\t\tif hillshade:\n\t\t\talpha = 0.5\n\t\telse:\n\t\t\talpha =1.\n\t\tm = self._get_basemap(projection=projection, geopolygons=geopolygons,hillshade=hillshade)\n\t\tgroup = self['%g_sec'%( period )]\n\t\tx, y = m(group['lonArr'].value, group['latArr'].value)\n\t\tmy_cmap = pycpt.load.gmtColormap('./cv.cpt')\n\t\tsed_Arr = group['sed_Arr'].value\n\t\tsed_Arr_msk = group['sed_Arr_msk'].value\n\t\tif vmin == None:\n\t\t\tvmin = np.nanmin(sed_Arr[~sed_Arr_msk])\n\t\t\tvmin = np.floor(vmin/5.)*5.\n\t\tif vmax == None:\n\t\t\tvmax = np.nanmax(sed_Arr[~sed_Arr_msk])\n\t\t\tvmax = np.ceil(vmax/5.)*5.\n\t\tim = m.pcolormesh(x, y, np.ma.masked_array(sed_Arr,mask=sed_Arr_msk), cmap=my_cmap, shading='gouraud', vmin=vmin, vmax=vmax, alpha=alpha)\n\t\tcb = m.colorbar(im, \"bottom\", size=\"3%\", pad='2%', format='%d')\n\t\tcb.set_label('Sediment thickness (m)', fontsize=12, rotation=0)\n\t\tcb.set_alpha(1)\n\t\tcb.draw_all()\n\t\tax = plt.gca() # only plot the oceanic part for JdF\n\t\t# ax.set_xlim(right=x_max)\n\t\tif showfig:\n\t\t\tplt.show()\n\t\treturn","def addSeparatorFeature(self):\n \n # graphical separators\n dNS = {\"pc\":PageXml.NS_PAGE_XML}\n someNode = self.lNode[0]\n ndPage = someNode.node.xpath(\"ancestor::pc:Page\", namespaces=dNS)[0]\n lNdSep = ndPage.xpath(\".//pc:SeparatorRegion\", namespaces=dNS)\n loSep = [ShapeLoader.node_to_LineString(_nd) for _nd in lNdSep]\n \n if self.bVerbose: traceln(\" %d graphical separators\"%len(loSep))\n\n # make an indexed rtree\n idx = index.Index()\n for i, oSep in enumerate(loSep):\n idx.insert(i, oSep.bounds)\n \n # take each edge in turn and list the separators it crosses\n nCrossing = 0\n for edge in self.lEdge:\n # bottom-left corner to bottom-left corner\n oEdge = geom.LineString([(edge.A.x1, edge.A.y1), (edge.B.x1, edge.B.y1)])\n prepO = prep(oEdge)\n lCrossingPoints = []\n fSepTotalLen = 0\n for i in idx.intersection(oEdge.bounds):\n # check each candidate in turn\n oSep = loSep[i]\n if prepO.intersects(oSep):\n fSepTotalLen += oSep.length\n oPt = oEdge.intersection(oSep)\n if type(oPt) != geom.Point:\n traceln('Intersection in not a point: skipping it')\n else:\n lCrossingPoints.append(oPt)\n \n if lCrossingPoints:\n nCrossing += 1\n edge.bCrossingSep = True\n edge.sep_NbCrossing = len(lCrossingPoints)\n minx, miny, maxx, maxy = geom.MultiPoint(lCrossingPoints).bounds\n edge.sep_SpanLen = abs(minx-maxx) + abs(miny-maxy)\n edge.sep_AvgSpanSgmt = edge.sep_SpanLen / len(lCrossingPoints) \n edge.sep_AvgSepLen = fSepTotalLen / len(lCrossingPoints)\n else:\n edge.bCrossingSep = False\n edge.sep_NbCrossing = 0\n edge.sep_SpanLen = 0\n edge.sep_AvgSpanSgmt = 0 \n edge.sep_AvgSepLen = 0\n \n #traceln((edge.A.domid, edge.B.domid, edge.bCrossingSep, edge.sep_NbCrossing, edge.sep_SpanLen, edge.sep_AvgSpanSgmt, edge.sep_AvgSepLen))\n \n \n if self.bVerbose: \n traceln(\" %d (/ %d) edges crossing at least one graphical separator\"%(nCrossing, len(self.lEdge)))","def analyze_block_horizon(mask):\n\n horizon_borders = find_border_horizon(mask)\n if border_analyze_horizon(mask, horizon_borders) and mask.shape[0] > mask.shape[1]:\n return True\n else:\n return False\n # heights = [abs(start - stop) for (start, stop) in horizon_borders]\n # horizon_big_borders = []\n # segmented_components = []\n # for idx, h in enumerate(heights):\n # if h > space_height:\n # horizon_big_borders.append(horizon_borders[idx])\n # if len(horizon_big_borders) == 0:\n # return segmented_components\n # slice_start = 0\n # horizon_slice_start_stops = []\n # for h_border in horizon_big_borders[::-1]:\n # horizon_slice_start_stops.append([slice_start, h_border[0]])\n # slice_start = h_border[1]\n # horizon_slice_start_stops.append([slice_start, mask.shape[0] - 1])\n # horizon_slice_start_stops = [(start, stop) for (start, stop) in horizon_slice_start_stops if stop > start]\n # for (horizon_start, horizon_stop) in horizon_slice_start_stops:\n # mask_slice = mask[horizon_start:horizon_stop, :]\n # vertical_borders = find_border_vertical(mask_slice)\n # widths = [abs(border[0] - border[1]) for border in vertical_borders]\n # vertical_big_borders = [vertical_borders[idx] for (idx, w) in enumerate(widths) if w > space_width]\n # if len(vertical_big_borders) == 0:\n # segmented_components.append([horizon_start, horizon_stop, 0, mask.shape[1] - 1])\n # else:\n # v_slice_start = 0\n # for idx, v_border in enumerate(vertical_big_borders[::-1]):\n # if v_slice_start != v_border[1]:\n # segmented_components.append([horizon_start, horizon_stop, v_slice_start, v_border[1]])\n # v_slice_start = v_border[0]\n # if v_slice_start < mask.shape[1] - 1:\n # segmented_components.append([horizon_start, horizon_stop, v_slice_start, mask.shape[1] - 1])\n # return segmented_components","def region_growing(im: np.ndarray, seed_points: list, T: int) -> np.ndarray:\n ### START YOUR CODE HERE ### (You can change anything inside this block)\n # You can also define other helper functions\n segmented = np.zeros_like(im).astype(bool)\n\n (H, W) = im.shape\n\n for seed_row, seed_col in seed_points:\n region = []\n region.append([seed_row, seed_col])\n for row, col in region:\n for rows in range((row-1),(row+2)): # Check neighbouring pixels\n for cols in range((col-1),(col+2)):\n if rows < H and rows >= 0 and cols < W and cols >= 0: # Is pixel inside image?\n if (np.abs(im[seed_row, seed_col] - im[rows, cols]) <= T) and not segmented[row, col]:\n region.append([rows, cols])\n segmented[row, col] = True\n return segmented\n ### END YOUR CODE HERE ### ","def vis_seg(img, seg, palette, alpha=0.5):\n vis = np.array(img, dtype=np.float32)\n mask = seg > 0\n vis[mask] *= 1. - alpha\n vis[mask] += alpha * palette[seg[mask].flat]\n vis = vis.astype(np.uint8)\n\n # own code - Jasper\n total_pixels = totalNumPixels(seg, palette)\n # print(\"color_seg():\\n\")\n # print(palette)\n # print(\"Seg: \\n\")\n # print(seg)\n # print(\"Seg.flat:\\n\")\n # print(seg.flat)\n # print(\"Palette seg.flat:\\n\")\n # print(palette[seg.flat])\n exportLogs(\"Number of pixels: {:d}\".format(total_pixels))\n\n # classes of pixels in tuple form\n exportLogs(\"Extract Unique Pixel Classes:\\n\")\n pixel_classes = [tuple(row) for row in palette[seg.flat]]\n\n # remove duplicate classes of pixels\n unique_classes = np.unique(pixel_classes, axis=0)\n\n # print result of pixel classes present in image\n for x in range(0, len(unique_classes.tolist())):\n exportLogs(\"{}. {}\".format(x + 1, unique_classes.tolist()[x]))\n\n # determine index of class and relate it with class_names\n # numpy array must be converted to list for list manipulation\n exportLogs(\"---------- Class Names - RGB Value ----------\")\n for i in unique_classes.tolist():\n # get index of pixel class from palette\n class_index = palette.tolist().index(i)\n\n # RGB value of pixel class\n class_color = tuple(i)\n\n # get the class name from class_names list based on PASCAL VOC list of classes \n class_name = class_names[class_index]\n\n # compute region percentage of class from the image\n percentage = (pixel_classes.count(tuple(i))/total_pixels) * 100\n \n # print results\n exportLogs(\"Class ID: {:d}\".format(class_index))\n exportLogs(\"Class Color: {}\".format(class_color))\n exportLogs(\"Class Name: {:s}\".format(class_name))\n exportLogs(\"Percentage of region: {:.3f}%\".format(percentage))\n exportLogs(\"\\n\")\n # end\n return vis","def FillVC8GradientColour(self, dc, tabPoints, active):\r\n\r\n xList = [pt.x for pt in tabPoints]\r\n yList = [pt.y for pt in tabPoints]\r\n \r\n minx, maxx = min(xList), max(xList)\r\n miny, maxy = min(yList), max(yList)\r\n\r\n rect = wx.Rect(minx, maxy, maxx-minx, miny-maxy+1) \r\n region = wx.RegionFromPoints(tabPoints)\r\n\r\n if self._buttonRect.width > 0:\r\n buttonRegion = wx.Region(*self._buttonRect)\r\n region.XorRegion(buttonRegion)\r\n \r\n dc.SetClippingRegionAsRegion(region)\r\n\r\n if active:\r\n bottom_colour = top_colour = wx.WHITE\r\n else:\r\n bottom_colour = StepColour(self._base_colour, 90)\r\n top_colour = StepColour(self._base_colour, 170)\r\n\r\n dc.GradientFillLinear(rect, top_colour, bottom_colour, wx.SOUTH)\r\n dc.DestroyClippingRegion()","def undrawGrid(draw,points,coeff2,newColorArray):\r\n ## This is the merge function.\r\n ## If two neighboring regions are considered to be the same color by the comparison function then this function replaces the black line between them by a line of their color (making it invisible).\r\n for j in range(0,coeff2-1):\r\n if comparisonFunction(newColorArray[0][j],newColorArray[0][j+1]):\r\n draw.line((points*0, points*(j+1), points*(0+1)-3, points*(j+1)), fill=newColorArray[0][j], width=lineWidth)\r\n\r\n for i in range(0,coeff2-1):\r\n if comparisonFunction(newColorArray[i][0],newColorArray[i+1][0]):\r\n draw.line((points*(i+1), points*0, points*(i+1), points*1-3), fill=newColorArray[i][0], width=lineWidth)\r\n\r\n for i in range(1,coeff2):\r\n for j in range(1,coeff2):\r\n if comparisonFunction(newColorArray[i][j],newColorArray[i][j-1]):\r\n draw.line((points*i+3, points*j, points*(i+1)-3, points*j), fill=newColorArray[i][j], width=lineWidth)\r\n\r\n if comparisonFunction(newColorArray[i][j],newColorArray[i-1][j]):\r\n draw.line((points*i, points*j+3, points*i, points*(j+1)-3), fill=newColorArray[i][j], width=lineWidth)","def split_dotted_general(captcha):\n image = captcha[19:46,]\n\n col_sum = np.sum(image, axis = 0)\n col_sum_list = list(col_sum)\n # Finding all the dark regions\n # beggining and end of all dark regions)\n x = 1\n i = 0\n dark_regions = []\n while i < 200:\n if col_sum_list[i] == 0:\n dark_region_beg = i\n while col_sum_list[i + x] == 0:\n x = x + 1\n if (x + i) > 199:\n break\n dark_region_end = i + x - 1\n dark_region = (dark_region_beg, dark_region_end)\n dark_regions.append(dark_region)\n i = x + i + 1\n x = 1\n else:\n i = i + 1\n\n # Identifying leftmost and rightmost dark regions and popping them out of the list\n left_region = dark_regions[0]\n right_region = dark_regions[-1]\n dark_regions.pop(0)\n dark_regions.pop(-1)\n\n # Sorting dark regions according to their length\n five_regions = sorted(dark_regions, key = lambda x: x[1] - x[0], reverse = True)\n\n # Building a list of GAPS (lengths of the dark regions)\n # and LINES that split such gaps in half\n gaps = []\n lines = []\n for i, region in enumerate(five_regions):\n gap = mt.ceil((region[1] - region[0]) / 2)\n if gap == 0:\n continue\n gaps.append(gap)\n lines.append(region[0] + gap)\n\n # If more than 5 gaps are identified, the problem may be due to split letters\n # Some of the troublesome letters are m, n and h\n # We will try to fix this issue by completing gaps in these letters\n if len(lines) > 5:\n\n for i in range(len(col_sum_list[:-9])):\n if col_sum_list[i:i+9] == [0, 0, 0, 0, 510, 510, 0, 3060, 3060]:\n captcha[28:30, i+1:i+3] = 255\n if col_sum_list[i:i+9] == [0, 0, 0, 0, 510, 510, 0, 2550, 2550]:\n captcha[31:33, i+1:i+3] = 255\n if col_sum_list[i:i+9] == [0, 3060, 3060, 0, 510, 510, 0, 0, 0, 0]:\n captcha[28:30, i+7:i+9] = 255\n if col_sum_list[i:i+9] == [0, 2550, 2550, 0, 510, 510, 0, 0, 0, 0]:\n captcha[31:33, i+7:i+9] = 255\n if col_sum_list[i:i+9] == [0, 4080, 4080, 0, 0, 0, 0, 510, 510]:\n captcha[31:33, i+4:i+6] = 255\n\n # Reloading image (based on modified captcha) and redefiding col_sum_list\n image = captcha[19:46, ]\n col_sum_list = list(np.sum(image, axis = 0))\n\n # Finding all the dark regions\n # beggining and end of all dark regions)\n x = 1\n i = 0\n dark_regions = []\n while i < 200:\n if col_sum_list[i] == 0:\n dark_region_beg = i\n while col_sum_list[i + x] == 0:\n x = x + 1\n if (x + i) > 199:\n break\n dark_region_end = i + x - 1\n dark_region = (dark_region_beg, dark_region_end)\n dark_regions.append(dark_region)\n i = x + i + 1\n x = 1\n else:\n i = i + 1\n\n # Identifying leftmost and rightmost dark regions and popping them out of the list\n left_region = dark_regions[0]\n right_region = dark_regions[-1]\n dark_regions.pop(0)\n dark_regions.pop(-1)\n\n # Sorting dark regions according to their length\n five_regions = sorted(dark_regions, key = lambda x: x[1] - x[0], reverse = True)\n\n # Building a list of GAPS (lengths of the dark regions)\n # and LINES that split such gaps in half\n gaps = []\n lines = []\n for i, region in enumerate(five_regions):\n gap = mt.ceil((region[1] - region[0]) / 2)\n if gap == 0:\n continue\n gaps.append(gap)\n lines.append(region[0] + gap)\n\n # If the errors persists, we move on to next captcha\n if len(lines) > 5:\n return('error')\n\n # If the algorithm finds less letters than expected (merged letters), we move on to next captcha\n if len(lines) < 5:\n return('error')\n\n # Defining rightmost and leftmost lines, appending lines list, and sorting\n left_line = left_region[1] - 2\n right_line = right_region[0] + 2\n lines.append(left_line)\n lines.append(right_line)\n lines = sorted(lines)\n\n # Finding letters x-coordinates\n letters_xcoords = []\n for i in range(len(lines)):\n if lines[i] == lines[-1]:\n break\n letter = (lines[i], lines[i + 1])\n letters_xcoords.append(letter)\n\n letters = []\n for i, letter in enumerate(letters_xcoords):\n letter_image = captcha[:60, letter[0]:letter[1]]\n letters.append(letter_image)\n\n return(letters)","def segment_region_of_interest(image):\n binary = image < 604\n cleared = clear_border(binary)\n\n label_image = label(cleared)\n\n areas = [r.area for r in regionprops(label_image)]\n areas.sort()\n if len(areas) > 2:\n for region in regionprops(label_image):\n if region.area < areas[-2]:\n for coordinates in region.coords:\n label_image[coordinates[0], coordinates[1]] = 0\n\n binary = label_image > 0\n\n selem = disk(2)\n binary = binary_erosion(binary, selem)\n\n selem = disk(10)\n binary = binary_closing(binary, selem)\n\n edges = roberts(binary)\n binary = scipy.ndimage.binary_fill_holes(edges)\n\n get_high_vals = binary == 0\n image[get_high_vals] = 0\n\n return image","def highlight_unallocated(series):\n one_person_req = (series > 0) & (series <= 0.5)\n two_person_req = series > 0.5\n is_good = series == 0\n\n style = []\n for i in range(len(series)):\n if two_person_req[i]:\n style.append(\"background-color: red\")\n elif one_person_req[i]:\n style.append(\"background-color: orange\")\n elif is_good[i]:\n style.append(\"background-color: lime\")\n else:\n style.append(\"background-color: yellow\")\n\n return style","def _find_regions(base_pairs, scores):\n # Make sure the lower residue is on the left for each row\n sorted_base_pairs = np.sort(base_pairs, axis=1)\n\n # Sort the first column in ascending order\n original_indices = np.argsort(sorted_base_pairs[:, 0])\n sorted_base_pairs = sorted_base_pairs[original_indices]\n\n # Rank each base\n # E.g.: [[3, 5] --> [[0, 1]\n # [9, 7]] [3, 2]]\n order = np.argsort(sorted_base_pairs.flatten())\n rank = np.argsort(order).reshape(base_pairs.shape)\n\n # The base pairs belonging to the current region\n region_pairs = []\n # The individual regions\n regions = set()\n\n # Find separate regions\n for i in range(len(sorted_base_pairs)):\n # if a new region is to be started append the current base pair\n if len(region_pairs) == 0:\n region_pairs.append(original_indices[i])\n continue\n\n # Check if the current base pair belongs to the region that is\n # currently being defined\n previous_upstream_rank = rank[i-1, 0]\n this_upstream_rank = rank[i, 0]\n previous_downstream_rank = rank[i-1, 1]\n this_downstream_rank = rank[i, 1]\n\n # if the current base pair belongs to a new region, save the\n # current region and start a new region\n if ((previous_downstream_rank - this_downstream_rank) != 1 or\n (this_upstream_rank - previous_upstream_rank) != 1):\n regions.add(\n _Region(base_pairs, np.array(region_pairs), scores)\n )\n region_pairs = []\n\n # Append the current base pair to the region\n region_pairs.append(original_indices[i])\n\n # The last region has no endpoint defined by the beginning of a\n # new region.\n regions.add(_Region(base_pairs, np.array(region_pairs), scores))\n\n # Return the graphical representation of the conflicting regions\n return _generate_graphical_representation(regions)","def phase_segmentation(image, threshold):\n # Normalize the image\n im_norm = (image - image.min()) / (image.max() - image.min())\n\n # Do a background subtraction\n im_blur = skimage.filters.gaussian(image, 50.0)\n im_sub = im_norm - im_blur\n\n # Threshold the image\n im_thresh = im_sub < -0.2\n\n # Label the image\n im_label = skimage.measure.label(im_thresh)\n\n # Get the properties and apply an area threshold\n props = skimage.measure.regionprops(im_label)\n\n # Make an empty image to store the approved cells\n approved_objects = np.zeros_like(im_label)\n\n # Apply the area filters\n for prop in props:\n obj_area = prop.area * 0.160**2 # Given the interpixel distance\n if (obj_area > 0.5) & (obj_area < 5):\n approved_objects += (im_label==prop.label)\n\n # Relabel the image.\n return im_relab","def colour_segmentation(img, num_segments=1000, round_schedule = [0.02, 0.04, 0.06, 0.08], colour_median_prop=0, max_clust_size=0.05, min_clust_size=0.002):\n origimg = img\n \n # Initial segmentation\n regions = skimage.segmentation.slic(img, n_segments=num_segments)\n\n for round_thr in round_schedule:\n # Compute colour change of each pixel\n edges = skimage.util.dtype.img_as_float(colour.colourchange(img))\n \n # Merge clusters hierarchically based on above distance\n rag = skimage.future.graph.rag_boundary(regions, edges)\n regions = skimage.future.graph.merge_hierarchical(regions, rag, thresh=round_thr, rag_copy=False, in_place_merge=True, merge_func=_merge_boundary, weight_func=_weight_boundary)\n\n # Replace all pixels in (some?) clusters with their median colour\n clust_sizes = skimage.exposure.histogram(regions)[0]\n clust_sizes = clust_sizes / float(sum(clust_sizes))\n medianclusters = np.where(clust_sizes > colour_median_prop)[0]\n\n img = origimg.copy()\n for mediancluster in medianclusters:\n img[regions == mediancluster] = np.median(img[regions == mediancluster], axis=0)\n \n if len(clust_sizes) == 1:\n break\n \n # Filter out too small and too large clusters\n num_clusters = 0\n for clust in range(len(clust_sizes)):\n if clust_sizes[clust] > max_clust_size or clust_sizes[clust] < min_clust_size: # background or noise resp.\n regions[regions == clust] = 0\n else:\n num_clusters += 1\n regions[regions == clust] = num_clusters\n \n # Extract centroids\n centroids, bboxes = zip(*[(clust.centroid, clust.bbox) for clust in skimage.measure.regionprops(regions)])\n \n return (regions, centroids, bboxes)","def offer_fix_broken_regions(self, with_window: ProjectWindow = None):\n if with_window:\n result = with_window.CustomDialog(\n title=\"Region Cleanup\",\n message=\"In vanilla Dark Souls, the Duke's Archives has four unused regions that can break event\\n\"\n \"scripts. Would you like Soulstruct to delete those four regions now?\",\n button_names=(\"Yes, delete them\", \"No, leave them be\"),\n button_kwargs=(\"YES\", \"NO\"),\n cancel_output=1,\n default_output=1,\n )\n else:\n result = 1 if (\n input(\n \"In vanilla Dark Souls, the Duke's Archives has four unused regions that can break event\\n\"\n \"scripts. Would you like Soulstruct to delete those four regions now? [y]/n\",\n ).lower() == \"n\"\n ) else 0\n if result == 0:\n archives_msb = self.maps.DukesArchives\n repeats = archives_msb.get_repeated_entity_ids() # re-checking just in case\n if {e.entity_id for e in repeats[\"Regions\"]} == {1702745, 1702746, 1702747, 1702748}:\n for entry in repeats[\"Regions\"]:\n archives_msb.regions.delete_entry(entry)\n return True\n else:\n return False","def highlight_de(adata, basis='umap', components=[1, 2], n_top_genes=10,\n de_keys='names, scores, pvals_adj, logfoldchanges',\n cell_keys='', n_neighbors=5, fill_alpha=0.1, show_hull=True,\n legend_loc='top_right', plot_width=None, plot_height=None):\n\n if 'rank_genes_groups' not in adata.uns_keys():\n raise ValueError('Run differential expression first.')\n\n\n if isinstance(de_keys, str):\n de_keys = list(dict.fromkeys(map(str.strip, de_keys.split(','))))\n if de_keys != ['']:\n assert all(map(lambda k: k in adata.uns['rank_genes_groups'].keys(), de_keys)), 'Not all keys are in `adata.uns[\\'rank_genes_groups\\']`.'\n else:\n de_keys = []\n\n if isinstance(cell_keys, str):\n cell_keys = list(dict.fromkeys(map(str.strip, cell_keys.split(','))))\n if cell_keys != ['']:\n assert all(map(lambda k: k in adata.obs.keys(), cell_keys)), 'Not all keys are in `adata.obs.keys()`.'\n else:\n cell_keys = []\n\n if f'X_{basis}' not in adata.obsm.keys():\n raise ValueError(f'Key `X_{basis}` not found in adata.obsm.')\n\n if not isinstance(components, np.ndarray):\n components = np.asarray(components)\n\n key = adata.uns['rank_genes_groups']['params']['groupby']\n if key not in cell_keys:\n cell_keys.insert(0, key)\n\n df = pd.DataFrame(adata.obsm[f'X_{basis}'][:, components - (basis != 'diffmap')], columns=['x', 'y'])\n for k in cell_keys:\n df[k] = list(map(str, adata.obs[k]))\n\n knn = neighbors.KNeighborsClassifier(n_neighbors)\n knn.fit(df[['x', 'y']], adata.obs[key])\n df['prediction'] = knn.predict(df[['x', 'y']])\n\n conv_hulls = df[df[key] == df['prediction']].groupby(key).apply(lambda df: df.iloc[ConvexHull(np.vstack([df['x'], df['y']]).T).vertices])\n\n mapper = _create_mapper(adata, key)\n categories = adata.obs[key].cat.categories\n fig = figure(tools='pan, reset, wheel_zoom, lasso_select, save')\n _set_plot_wh(fig, plot_width, plot_height)\n legend_dict = defaultdict(list)\n\n for k in categories:\n d = df[df[key] == k]\n data_source = ColumnDataSource(d)\n legend_dict[k].append(fig.scatter('x', 'y', source=data_source, color={'field': key, 'transform': mapper}, size=5, muted_alpha=0))\n\n hover_cell = HoverTool(renderers=[r[0] for r in legend_dict.values()], tooltips=[(f'{key}', f'@{key}')] + [(f'{k}', f'@{k}') for k in cell_keys[1:]])\n\n c_hulls = conv_hulls.copy()\n de_possible = conv_hulls[key].isin(adata.uns['rank_genes_groups']['names'].dtype.names)\n ok_patches = []\n prev_cat = []\n for i, isin in enumerate((~de_possible, de_possible)):\n conv_hulls = c_hulls[isin]\n\n if len(conv_hulls) == 0:\n continue\n\n xs, ys, ks = zip(*conv_hulls.groupby(key).apply(lambda df: list(map(list, (df['x'], df['y'], df[key])))))\n tmp_data = defaultdict(list)\n tmp_data['xs'] = xs\n tmp_data['ys'] = ys\n tmp_data[key] = list(map(lambda k: k[0], ks))\n \n if i == 1:\n ix = list(map(lambda k: adata.uns['rank_genes_groups']['names'].dtype.names.index(k), tmp_data[key]))\n for k in de_keys:\n tmp = np.array(list(zip(*adata.uns['rank_genes_groups'][k])))[ix, :n_top_genes]\n for j in range(n_top_genes):\n tmp_data[f'{k}_{j}'] = tmp[:, j]\n\n tmp_data = pd.DataFrame(tmp_data)\n for k in categories:\n d = tmp_data[tmp_data[key] == k]\n source = ColumnDataSource(d)\n\n patches = fig.patches('xs', 'ys', source=source, fill_alpha=fill_alpha, muted_alpha=0, hover_alpha=0.5,\n color={'field': key, 'transform': mapper} if (show_hull and i == 1) else None,\n hover_color={'field': key, 'transform': mapper} if (show_hull and i == 1) else None)\n legend_dict[k].append(patches)\n if i == 1:\n ok_patches.append(patches)\n\n hover_group = HoverTool(renderers=ok_patches, tooltips=[(f'{key}', f'@{key}'),\n ('groupby', adata.uns['rank_genes_groups']['params']['groupby']),\n ('reference', adata.uns['rank_genes_groups']['params']['reference']),\n ('rank', ' | '.join(de_keys))] + [(f'#{i + 1}', ' | '.join((f'@{k}_{i}' for k in de_keys))) for i in range(n_top_genes)]\n )\n \n\n fig.toolbar.active_inspect = [hover_group]\n if len(cell_keys) > 1:\n fig.add_tools(hover_group, hover_cell)\n else:\n fig.add_tools(hover_group)\n\n if legend_loc is not None:\n legend = Legend(items=list(legend_dict.items()), location=legend_loc)\n fig.add_layout(legend)\n fig.legend.click_policy = 'hide' # hide does disable hovering, whereas 'mute' does not\n\n fig.xaxis.axis_label = f'{basis}_{components[0]}'\n fig.yaxis.axis_label = f'{basis}_{components[1]}'\n\n show(fig)","def alternatingSlice(self,geom,polyLayer,targetArea,granularity,direction,method):\r\n global recurs\r\n recurs+=1\r\n if self.debug: print \"******************************\"\r\n if self.debug: print \"Slicing, No of part: \",str(recurs)\r\n if self.debug: print \"Slicing, Granularity remaining: \", str(granularity)\r\n bbox=[geom.boundingBox().xMinimum(),geom.boundingBox().yMinimum(),geom.boundingBox().xMaximum(),geom.boundingBox().yMaximum()]\r\n if direction==\"h\":\r\n step=(bbox[2]-bbox[0])/granularity\r\n pointer=bbox[0]\r\n else:\r\n step=(bbox[3]-bbox[1])/granularity\r\n pointer=bbox[1]\r\n totalArea=0\r\n slices=0\r\n #save the original geom\r\n tempGeom=QgsGeometry(geom)\r\n #start slicing until targetArea is reached\r\n while totalArea<targetArea*0.999:\r\n pointer+=step\r\n if direction==\"h\":\r\n startPt=QgsPoint(pointer,bbox[1])\r\n endPt=QgsPoint(pointer,bbox[3])\r\n (multiGeom,tempGeom)=self.cutPoly(tempGeom,startPt,endPt)\r\n else:\r\n startPt=QgsPoint(bbox[0],pointer)\r\n endPt=QgsPoint(bbox[2],pointer)\r\n (tempGeom,multiGeom)=self.cutPoly(tempGeom,startPt,endPt)\r\n if multiGeom!=None:\r\n totalArea+=multiGeom.area();\r\n slices+=1\r\n if self.debug: print \"Slicing, Slices: \", str(slices)\r\n #do the real cutting when reached targetArea and add \"left\" feature to layer\r\n if self.debug: print \"Cutting with line, Cutline:\", startPt,\",\",endPt\r\n if direction==\"h\":\r\n (multiGeom,geom)=self.cutPoly(geom,startPt,endPt,True)\r\n if multiGeom:\r\n if self.debug: print \"After split, Parts to the left:\",str(len(multiGeom.asGeometryCollection()))\r\n if geom:\r\n if self.debug: print \"After split, Parts to the right:\",str(len(geom.asGeometryCollection()))\r\n else:\r\n (geom,multiGeom)=self.cutPoly(geom,startPt,endPt,True)\r\n if geom:\r\n if self.debug: print \"After split, Parts above:\",str(len(geom.asGeometryCollection()))\r\n if multiGeom:\r\n if self.debug: print \"After split, Parts under:\",str(len(multiGeom.asGeometryCollection()))\r\n self.addGeomToLayer(multiGeom,polyLayer)\r\n #self.addGeomToLayer(QgsGeometry.fromPolyline([startPt,endPt]),lineLayer)\r\n if geom:\r\n if geom.area()>targetArea:\r\n if (method==\"v\") or ((method==\"a\") and (direction==\"h\")):\r\n self.alternatingSlice(geom,polyLayer,targetArea,granularity-slices,\"v\",method)\r\n else:\r\n self.alternatingSlice(geom,polyLayer,targetArea,granularity-slices,\"h\",method)\r\n else:\r\n self.addGeomToLayer(geom,polyLayer)","def drawValidationNeedles(self): \n #productive #onButton\n profprint()\n # reset report table\n # print \"Draw manually segmented needles...\"\n #self.table =None\n #self.row=0\n self.initTableView()\n self.deleteEvaluationNeedlesFromTable()\n while slicer.util.getNodes('manual-seg*') != {}:\n nodes = slicer.util.getNodes('manual-seg*')\n for node in nodes.values():\n slicer.mrmlScene.RemoveNode(node)\n \n if self.tableValueCtrPt==[[]]:\n self.tableValueCtrPt = [[[999,999,999] for i in range(100)] for j in range(100)]\n modelNodes = slicer.mrmlScene.GetNodesByClass('vtkMRMLAnnotationFiducialNode')\n nbNode=modelNodes.GetNumberOfItems()\n for nthNode in range(nbNode):\n modelNode=slicer.mrmlScene.GetNthNodeByClass(nthNode,'vtkMRMLAnnotationFiducialNode')\n if modelNode.GetAttribute(\"ValidationNeedle\") == \"1\":\n needleNumber = int(modelNode.GetAttribute(\"NeedleNumber\"))\n needleStep = int(modelNode.GetAttribute(\"NeedleStep\"))\n coord=[0,0,0]\n modelNode.GetFiducialCoordinates(coord)\n self.tableValueCtrPt[needleNumber][needleStep]=coord\n print needleNumber,needleStep,coord\n # print self.tableValueCtrPt[needleNumber][needleStep]\n\n for i in range(len(self.tableValueCtrPt)):\n if self.tableValueCtrPt[i][1]!=[999,999,999]:\n colorVar = random.randrange(50,100,1)/float(100)\n controlPointsUnsorted = [val for val in self.tableValueCtrPt[i] if val !=[999,999,999]]\n controlPoints=self.sortTable(controlPointsUnsorted,(2,1,0))\n self.addNeedleToScene(controlPoints,i,'Validation')\n else:\n # print i\n pass","def highlight_moves(win, game):\n #Get available moves\n player_turn = game.get_player_turn()\n moves_available = game.possible_moves(game.get_pawn(player_turn))\n if None in moves_available:\n moves_available.remove(None)\n \n #Highlight moves\n for move in moves_available:\n move_coords = (move[0]*(SQUARESIZE+FENCEWIDTH), move[1]*(SQUARESIZE+FENCEWIDTH))\n move_center_coords = (move_coords[0]+SQUARESIZE/2, move_coords[1]+SQUARESIZE/2)\n pygame.draw.circle(win, LIGHTGREEN, move_center_coords, SQUARESIZE/4)","def sed(self, search, replace):\n\n for section in self.sections:\n for i, block in enumerate(section.blocks):\n if block == search:\n section.blocks[i] = replace\n self.all_damaged = True\n self.dirty = True","def BraceHighlight(self, pos1, pos2):\n # Check if we are still alive or not, as this may be called\n # after we have been deleted.\n if self:\n super(EditraBaseStc, self).BraceHighlight(pos1, pos2)","def mask_region_ends(self, n_days=20):\n for rg in self.Rs:\n i = self.Rs.index(rg)\n self.Active.mask[i, -n_days:] = True\n self.Confirmed.mask[i, -n_days:] = True\n self.Deaths.mask[i, -n_days:] = True\n self.NewDeaths.mask[i, -n_days:] = True\n self.NewCases.mask[i, -n_days:] = True","def border_analyze_horizon(mask, borders, min_segment_height=5, max_border_height=0.4):\n max_border_height = mask.shape[0] * max_border_height\n if len(borders) == 0: return False\n upper_most = 0\n lower_most = mask.shape[0] - 1\n # middle_borders = [border for border in borders if (left_most in border or right_most in border) and abs(border[0]-border[1])>3 ]\n # if len(middle_borders)==0:return False\n slice_start = 0\n block_heights = []\n block_areas = []\n # segs_by_middle_borders=[]\n for v_border in borders:\n border_start = v_border[0]\n border_stop = v_border[1]\n if border_start == upper_most:\n slice_start = border_stop\n elif border_stop == lower_most:\n # mask_slice=mask[slice_start:border_start]\n block_heights.append(border_start - slice_start)\n\n block_areas.append(np.sum(mask[slice_start:border_start, :]))\n # segs_by_middle_borders.append(mask_slice)\n slice_start = border_stop\n elif border_stop - border_start >= 1:\n # mask_slice = mask[slice_start,border_start]\n if border_stop - border_start < max_border_height:\n block_heights.append(border_start - slice_start)\n block_areas.append(np.sum(mask[slice_start:border_start, :]))\n # segs_by_middle_borders.append(mask_slice)\n slice_start = border_stop\n if slice_start < lower_most:\n # segs_by_middle_borders.append(mask[slice_start:])\n block_heights.append(mask.shape[0] - slice_start)\n block_areas.append(np.sum(mask[slice_start:mask.shape[0], :]))\n\n if len(block_areas) < 2:\n return False\n if len(block_areas) == 2:\n max_area = max(block_areas)\n min_area = min(block_areas)\n if max_area / min_area > 3:\n return False\n if len(block_areas) > 2:\n if np.std(block_areas) / np.mean(block_areas) > 2:\n return False\n\n # print(block_areas)\n # print(mask.shape[0]*mask.shape[1])\n # print(np.std(block_areas)/np.mean(block_areas))\n block_heights = [h for h in block_heights if h > min_segment_height]\n\n # print('block areas ')\n # print(block_areas)\n\n # print('block heights deviation' )\n # print(np.std(block_heights))\n\n # print('block heights dev/mean' )\n # print(np.std(block_heights)/np.mean(block_heights))\n\n if len(block_heights) < 2: return False\n return segment_analyzer(block_heights)","def section_to_patch(self, group_of_segments, angle=None, row_spacing=None,\n max_stitch_length=None):\n if max_stitch_length is None:\n max_stitch_length = self.max_stitch_length\n\n if row_spacing is None:\n row_spacing = self.row_spacing\n\n if angle is None:\n angle = self.angle\n\n # print >> sys.stderr, len(groups_of_segments)\n\n patch = Patch(color=self.color)\n first_segment = True\n swap = False\n last_end = None\n\n for segment in group_of_segments:\n # We want our stitches to look like this:\n #\n # ---*-----------*-----------\n # ------*-----------*--------\n # ---------*-----------*-----\n # ------------*-----------*--\n # ---*-----------*-----------\n #\n # Each successive row of stitches will be staggered, with\n # num_staggers rows before the pattern repeats. A value of\n # 4 gives a nice fill while hiding the needle holes. The\n # first row is offset 0%, the second 25%, the third 50%, and\n # the fourth 75%.\n #\n # Actually, instead of just starting at an offset of 0, we\n # can calculate a row's offset relative to the origin. This\n # way if we have two abutting fill regions, they'll perfectly\n # tile with each other. That's important because we often get\n # abutting fill regions from pull_runs().\n\n (beg, end) = segment\n\n if (swap):\n (beg, end) = (end, beg)\n\n beg = PyEmb.Point(*beg)\n end = PyEmb.Point(*end)\n\n row_direction = (end - beg).unit()\n segment_length = (end - beg).length()\n\n # only stitch the first point if it's a reasonable distance away\n # from the last stitch\n if last_end is None or (beg - last_end).length() > 0.1 * px_per_mm:\n patch.add_stitch(beg)\n\n first_stitch = self.adjust_stagger(beg, angle, row_spacing,\n max_stitch_length)\n\n # we might have chosen our first stitch just outside this row, so\n # move back in\n if (first_stitch - beg) * row_direction < 0:\n first_stitch += row_direction * max_stitch_length\n\n offset = (first_stitch - beg).length()\n\n while offset < segment_length:\n patch.add_stitch(beg + offset * row_direction)\n offset += max_stitch_length\n\n if (end - patch.stitches[-1]).length() > 0.1 * px_per_mm:\n patch.add_stitch(end)\n\n last_end = end\n swap = not swap\n\n return patch","def Plot_RNAStructure_highlight(sequence, dot, hg_base_list=[], mode='fill', correctT=True, \n scaling=0.8, highlight_region=[], annotation=[], \n bpprob=[], bpprob_cutofflist=[0.6,0.8,0.95], bpprob_mode='color', bpwarning=True,\n period=10, first_base_pos=1, peroid_color='#000000',\n title=\"\", wait=True, VARNAProg=VARNAProg):\n \n assert len(sequence) == len(dot)\n assert mode in ('label', 'fill')\n \n if correctT:\n sequence = sequence.replace('T', 'U')\n \n CMD = \"java -cp \"+VARNAProg+\" fr.orsay.lri.varna.applications.VARNAcmd -sequenceDBN %s -structureDBN \\\"%s\\\" -drawBackbone false -drawBases false -bpStyle simple \" % (sequence, dot)\n \n if hg_base_list:\n if mode == 'label':\n CMD += \"-basesStyle1 \\\"label=#FF0000\\\" \"\n else:\n CMD += \"-basesStyle1 \\\"fill=#FF0000\\\" \"\n hg_base_list = [str(item) for item in hg_base_list]\n CMD += \"-applyBasesStyle1on \\\"%s\\\" \" % (\",\".join(hg_base_list), )\n \n if highlight_region:\n CMD += \" \" + __highlight_region_cmd(highlight_region)\n \n if annotation:\n CMD += \" \" + __annotation_cmd(annotation)\n \n if scaling:\n CMD += \" -spaceBetweenBases \\\"%s\\\"\" % (scaling, )\n \n if bpprob:\n new_bpprob = __dot_match_bpprob(dot, bpprob, bpwarning)\n CMD += \" \" + __basepair_bpprob_cmd(new_bpprob, bpprob_cutofflist, bpprob_mode)\n \n if first_base_pos==1 and peroid_color=='#000000':\n CMD += f\" -period {period}\"\n else:\n CMD += \" \" + __manual_period(len(sequence), first_base_pos, period, peroid_color)\n \n if title:\n CMD += \" -title \\\"%s\\\"\" % (title, )\n \n if not wait:\n CMD = \"nohup \" + CMD + \" &\"\n \n return CMD","def separation_crawler(mode: bool) -> bool:\r\n for x in range(shape):\r\n for y in range(shape):\r\n if mode:\r\n if conflict_space[x, y] != 0 and safeboard[x, y] == 1:\r\n if walled_in(x, y):\r\n safeboard[x, y] = 0\r\n print(\"Cell will create separation if marked. Marked safe:\", x, \",\", y)\r\n progress_handler(False, True)\r\n else:\r\n if example[x, y] == 0:\r\n if walled_in(x, y):\r\n print(\"Solution Rejected, separated areas\")\r\n return True","def _red_detect_(self, nslice = 0, thresh = 2.0):\n zk_1 = 's_' + format(nslice, '03d')\n zk_2 = 's_' + format(nslice+1, '03d')\n\n zf_1 = self.z_dense[zk_1]\n zf_2 = self.z_dense[zk_2]\n\n # extract the y and x coordinates\n y1 = zf_1[:,0]\n x1 = zf_1[:,1]\n\n y2 = zf_2[:,0]\n x2 = zf_2[:,1]\n\n\n # create a meshgrid\n [YC, YR] = np.meshgrid(y2, y1)\n [XC, XR] = np.meshgrid(x2, x1)\n\n\n dist_block = np.sqrt((YC-YR)**2 + (XC-XR)**2)\n red_pair = np.where(dist_block <= thresh) # find out where the distance between cell i in plane k and cell j in plane k+1 is below the threshold.\n\n ind1 = red_pair[0] # the indices in the first frame\n ind2 = red_pair[1] # the indices in the second frame\n\n\n # select those with markers > 0 and markers < 0\n marker_1 = zf_1[ind1, 3]\n\n\n new_idx = (marker_1 == 0) # select those with zero-markers, which are never counted before. These are new cells. marker_1 needs to be updated.\n pool_new = ind1[new_idx] # select the indices in the first frame where new redundancies are detected \n pool_new_cov = ind2[new_idx] # select the indices in the second frame where new redundancies are detected.\n\n\n pool_exist = ind1[~new_idx] # among the detected redundancies, find those already marked.\n pool_exist_cov = ind2[~new_idx] # correspondingly, find those already marked in the adjacent slice\n\n n_new = len(pool_new)\n n_exist = len(pool_exist)\n if self.verbose:\n print(n_new, \"new redundancies, \", n_exist, \"existing redundancies\")\n\n for n_count in np.arange(n_new):\n # build the new keys\n # also, we need to assign each new key an identity number which is unique.\n n_ind1 = pool_new[n_count] # find the indices in the first slice that contains new redundancies\n n_ind2 = pool_new_cov[n_count] # find the indices in the following slice \n pr_number = nslice * 1000 + n_ind1\n pr_key = 'sl_' + str(pr_number) # build a key \n new_sl = Simple_list(nslice) # create a simple list with z_marker = nslice, nslice is the index of the first z-slice \n new_sl.add([nslice, zf_1[n_ind1, 4]])\n new_sl.add([nslice+1, zf_2[n_ind2, 4]])\n zf_1[n_ind1, 3] = pr_number # assign the new pr_number to zf_1\n zf_2[n_ind2, 3] = pr_number # assigne the same new pr_number to zf_2\n\n self.redundancy_pool[pr_key] = new_sl # stored into the redundancy pool\n\n\n for n_count in np.arange(n_exist):\n # search for the existing keys\n n_ind1 = pool_exist[n_count]\n n_ind2 = pool_exist_cov[n_count]\n pr_number = int(zf_1[n_ind1, 3])# catch up the pr_number\n pr_key = 'sl_' + str(pr_number) # this pr_key should already exist in the pool. \n\n self.redundancy_pool[pr_key].add([nslice+1, zf_2[n_ind2, 4]])\n zf_2[n_ind2, 3] = pr_number # update the pr_number in the adjacent slice","def borra_overlaps(self):\r\n nomTabla=self.nomTabla.split(\".\")[1]\r\n dicCondWhere={}\r\n dicCondWhere[\"id_trabajo\"]=self.oUtiles.id_trabajo\r\n if nomTabla == \"ed_fincas\":\r\n nomTablaOverlaps=\"ed_src\" + str(self.oUtiles.src_trabajo) + \".\" + \"ed_overlaps_fincas\"\r\n nomTablaGaps=\"ed_src\" + str(self.oUtiles.src_trabajo) + \".\" + \"ed_gaps_fincas\"\r\n else:\r\n nomTablaOverlaps=\"src\" + str(self.oUtiles.src_trabajo) + \".\" + \"overlaps_fincas\"\r\n nomTablaGaps=\"src\" + str(self.oUtiles.src_trabajo) + \".\" + \"gaps_fincas\"\r\n self.oUtiles.oConsultasPg.deleteDatos(nombreTabla=nomTablaOverlaps,dicCondWhere=dicCondWhere)\r\n self.oUtiles.oConsultasPg.deleteDatos(nombreTabla=nomTablaGaps,dicCondWhere=dicCondWhere)","def DrawBands(self, count):\n value = self.little[0]\n mobile_average = float(sum([float(self.little[i])\n for i in range(len(self.little))])) / float(self.period)\n standard_derivation = sqrt(sum([pow(self.little[i] - mobile_average, 2)\n for i in range(len(self.little))]) / self.period)\n upper_band = mobile_average + (standard_derivation * self.sd_coef)\n lower_band = mobile_average - (standard_derivation * self.sd_coef)\n self.upper.insert(0, upper_band)\n self.lower.insert(0, lower_band)\n if len(self.upper) >= self.period:\n self.upper.pop()\n if len(self.lower) >= self.period:\n self.lower.pop()\n if count >= self.period:\n for i in range(len(self.little) - 1):\n self.canvas.create_line((i * self.incr / 1.725) + self.incr * 4,\n self.height - self.incr * 4 + (self.little[i] - 1) * 5000 - 200,\n (i * self.incr / 1.725) + self.incr * 4 + self.incr / 1.725,\n self.height - self.incr * 4 + (self.little[i + 1] - 1) * 5000 - 200,\n fill = \"#FFFF00\", width = 2)\n for i in range(len(self.upper) - 1):\n self.canvas.create_line((i * self.incr / 1.635) + self.incr * 4,\n self.height - self.incr * 4 + (self.upper[i] - 1) * 5000 - 200,\n (i * self.incr / 1.635) + self.incr * 4 + self.incr / 1.635,\n self.height - self.incr * 4 + (self.upper[i + 1] - 1) * 5000 - 200,\n fill = \"#FF6600\", width = 3)\n self.canvas.create_line((i * self.incr / 1.635) + self.incr * 4,\n self.height - self.incr * 4 + (self.lower[i] - 1) * 5000 - 200,\n (i * self.incr / 1.635) + self.incr * 4 + self.incr / 1.635,\n self.height - self.incr * 4 + (self.lower[i + 1] - 1) * 5000 - 200,\n fill = \"#FF0000\", width = 3)","def searchBreakend(self, region): \n\t\treturn filter(lambda X: X == region, self)","def threshold_segment(img):\n\n m,n = img.shape\n g = img.sum()/(m*n)\n\n segmented = np.zeros((m,n),dtype=float)\n\n for i,j in it.product(range(m),range(n)):\n\n if img[i,j] - g >= 100:\n segmented[i,j] = 0\n elif img[i,j] - g >= 50:\n segmented[i,j] = 50\n elif img[i,j] - g >= 0:\n segmented[i,j] = 100\n elif img[i,j] - g >= -50:\n segmented[i,j] = 150\n elif img[i,j] - g >= -100:\n segmented[i,j] = 200\n else:\n segmented[i,j] = 255\n\n return segmented","def separate_frontier(self):\n\t#print self.frontier\n region = [] # a list of tuples\n region_list = [] # a list of regions\n in_list = False\n region_size = 7\n num_regions = 25\n n = 0\n h = 0\n print \"separate frontier\"\n while(region_size>0):\n for i in range(len(self.frontier)):\n if (h < num_regions):\n region = []\n self.find_region(self.frontier[i], region)\n\t\t #rospy.loginfo(region)\n in_list = region in region_list\n if (len(region) > region_size) and (not in_list):\n region_list.append(region)\n h += 1\n self.regions = region_list\n region_size -= 1\n\t#print self.regions","def render_regions(view=None):\r\n # Get current active view\r\n if view is None:\r\n view = sublime.active_window().active_view()\r\n # Unable to set regions when no view available\r\n if view is None:\r\n return\r\n\r\n # Do no set regions if view is empty or still loading\r\n if view.size() == 0 or view.is_loading():\r\n return\r\n\r\n # Remove all markers to avoid marker conflict\r\n view.erase_regions(S.REGION_KEY_BREAKPOINT)\r\n view.erase_regions(S.REGION_KEY_CURRENT)\r\n view.erase_regions(S.REGION_KEY_DISABLED)\r\n\r\n # Get filename of current view and check if is a valid filename\r\n filename = view.file_name()\r\n if not filename:\r\n return\r\n\r\n # Determine icon for regions\r\n icon_current = get_region_icon(S.KEY_CURRENT_LINE)\r\n icon_disabled = get_region_icon(S.KEY_BREAKPOINT_DISABLED)\r\n icon_enabled = get_region_icon(S.KEY_BREAKPOINT_ENABLED)\r\n\r\n # Get all (disabled) breakpoint rows (line numbers) for file\r\n breakpoint_rows = []\r\n disabled_rows = []\r\n if filename in S.BREAKPOINT and isinstance(S.BREAKPOINT[filename], dict):\r\n for lineno, bp in S.BREAKPOINT[filename].items():\r\n # Do not show temporary breakpoint\r\n if S.BREAKPOINT_RUN is not None and S.BREAKPOINT_RUN['filename'] == filename and S.BREAKPOINT_RUN['lineno'] == lineno:\r\n continue\r\n # Determine if breakpoint is enabled or disabled\r\n if bp['enabled']:\r\n breakpoint_rows.append(lineno)\r\n else:\r\n disabled_rows.append(lineno)\r\n\r\n # Get current line from breakpoint hit\r\n if S.BREAKPOINT_ROW is not None:\r\n # Make sure current breakpoint is in this file\r\n if filename == S.BREAKPOINT_ROW['filename']:\r\n # Remove current line number from breakpoint rows to avoid marker conflict\r\n if S.BREAKPOINT_ROW['lineno'] in breakpoint_rows:\r\n breakpoint_rows.remove(S.BREAKPOINT_ROW['lineno'])\r\n # Set icon for current breakpoint\r\n icon_breakpoint_current = get_region_icon(S.KEY_BREAKPOINT_CURRENT)\r\n if icon_breakpoint_current:\r\n icon_current = icon_breakpoint_current\r\n if S.BREAKPOINT_ROW['lineno'] in disabled_rows:\r\n disabled_rows.remove(S.BREAKPOINT_ROW['lineno'])\r\n # Set current line marker\r\n if icon_current:\r\n view.add_regions(S.REGION_KEY_CURRENT, rows_to_region(S.BREAKPOINT_ROW['lineno']), S.REGION_SCOPE_CURRENT, icon_current, sublime.HIDDEN)\r\n\r\n # Set breakpoint marker(s)\r\n if breakpoint_rows and icon_enabled:\r\n view.add_regions(S.REGION_KEY_BREAKPOINT, rows_to_region(breakpoint_rows), S.REGION_SCOPE_BREAKPOINT, icon_enabled, sublime.HIDDEN)\r\n if disabled_rows and icon_disabled:\r\n view.add_regions(S.REGION_KEY_DISABLED, rows_to_region(disabled_rows), S.REGION_SCOPE_BREAKPOINT, icon_disabled, sublime.HIDDEN)","def slice_graph_bwd( endea, reg ): \r\n\tgraph = vcg_Graph.vcgGraph({\"title\":'\"Slice for %s\"' % reg, \\\r\n\t\t\"manhattan_edges\":\"no\", \"layoutalgorithm\":\"maxdepth\"})\r\n\t#\r\n\t# Retrieve the name of the current basic block\r\n\t# \r\n\tworklist = []\r\n\tdata_bib = {}\r\n\t\r\n\tstartnode = slice_node( 0, endea, reg )\t\t# start at the end of the slice node\r\n\trootnode = graph.Add_Node( startnode.to_name() )\r\n\tdata_bib[ startnode.to_name() ] = startnode\r\n\tworklist.insert( 0, rootnode )\r\n\twhile len( worklist ) > 0:\r\n\t\tcurrnode = worklist.pop()\r\n\t\tcurrslice = data_bib[ currnode.get_name() ]\r\n\t\t[tgt_reg, split] = currslice.get_target_reg_bwd()\r\n\t\tprint tgt_reg\r\n\t\tprint split\r\n\t\tif tgt_reg == \"END\":\r\n\t\t\t# Do not process this node any further\r\n\t\t\tpass\r\n\t\telif tgt_reg == \"\" or (( len( currslice.get_lines()) > 0) and \\\r\n\t\t\tcurrslice.startea != currslice.get_lines()[0][0]):\r\n\t\t\t# Do process this node further, nothing really going on \r\n\t\t\tprint \"ZEZ\"\r\n\t\t\txrefs = get_crefs_to( currslice.startea )\r\n\t\t\tfor ref in xrefs:\r\n\t\t\t\tnewslice = slice_node( 0,ref, currslice.reg )\r\n\t\t\t\tif graph.Get_Node( newslice.to_name() ) == 0:\r\n\t\t\t\t\tnewnode = graph.Add_Node( newslice.to_name() )\r\n\t\t\t\t\tworklist.insert( 0, newnode )\r\n\t\t\t\t\tdata_bib[ newslice.to_name() ] = newslice\r\n\t\t\t\tgraph.Add_Link( newslice.to_name(), currnode.get_name() )\r\n\t\telse:\r\n\t\t\txrefs = get_crefs_to( currslice.startea )\r\n\t\t\tfor ref in xrefs:\r\n\t\t\t\tnewslice = slice_node( 0,ref, tgt_reg )\r\n\t\t\t\tif graph.Get_Node( newslice.to_name() ) == 0:\r\n\t\t\t\t\tnewnode = graph.Add_Node( newslice.to_name() )\r\n\t\t\t\t\tworklist.insert( 0, newnode )\r\n\t\t\t\t\tdata_bib[ newslice.to_name() ] = newslice\r\n\t\t\t\tgraph.Add_Link( newslice.to_name(), currnode.get_name())\r\n\t\t\txrefs = get_crefs_to( currslice.startea )\r\n\t\t\tif split:\r\n\t\t\t\tfor ref in xrefs:\r\n\t\t\t\t\tnewslice = slice_node( 0,ref, currslice.reg )\r\n\t\t\t\t\tif graph.Get_Node( newslice.to_name() ) == 0:\r\n\t\t\t\t\t\tnewnode = graph.Add_Node( newslice.to_name() )\r\n\t\t\t\t\t\tworklist.insert( 0, newnode )\r\n\t\t\t\t\t\tdata_bib[ newslice.to_name() ] = newslice\r\n\t\t\t\t\tgraph.Add_Link( newslice.to_name(), currnode.get_name())\r\n\treturn [ graph, data_bib ]","def shade(self):\n if self.distribution_records:\n path_nodes = self.svg_map.xpath(self.PATH_NODES_XPATH,\n namespaces=NAMESPACES)\n matching_regions = {}\n for record in self.distribution_records:\n region = STATES_MAP.get(record.value_str)\n region = ((region in CANADIAN_PROVINCES and 'ca-' or 'us-') +\n region)\n matching_regions[region] = True\n\n for node in path_nodes:\n if node.get('style'):\n node_id = node.get('id').lower()\n box = Path(node)\n if node_id in matching_regions:\n box.color(PRESENT_COLOR)\n else:\n box.color(ABSENT_COLOR)\n return self","def segment_red(img, yellow_thresh, red_thresh):\n # 255 is white, Red, Green, Blue\n # where green and yellow exists strongly set to 0\n yellow_filter = (img[:, :, 1] < yellow_thresh)*numpy.ones((img.shape[0], img.shape[1]))\n # where red and yellow doesnt exist set to 0\n red_filter = (img[:, :, 2] > red_thresh)*numpy.ones((img.shape[0], img.shape[1]))\n # TAKE THE INTERSECTION of SET A and B\n total_filter = numpy.multiply(yellow_filter, red_filter)\n img[:, :, 0] = 0\n img[:, :, 1] = numpy.multiply(total_filter, img[:, :, 1])\n img[:, :, 2] = numpy.multiply(total_filter, img[:, :, 2])\n cv2.imwrite('segmented.png', img)\n return img","def mask_region(self, region, days=14):\n i = self.Rs.index(region)\n c_s = np.nonzero(np.cumsum(self.NewCases.data[i, :] > 0) == days + 1)[0][0]\n d_s = np.nonzero(np.cumsum(self.NewDeaths.data[i, :] > 0) == days + 1)[0]\n if len(d_s) > 0:\n d_s = d_s[0]\n else:\n d_s = len(self.Ds)\n\n self.Active.mask[i, c_s:] = True\n self.Confirmed.mask[i, c_s:] = True\n self.Deaths.mask[i, d_s:] = True\n self.NewDeaths.mask[i, d_s:] = True\n self.NewCases.mask[i, c_s:] = True\n\n return c_s, d_s","def resetCoronalSegment(self):\r\n #research\r\n profprint()\r\n sGreen = slicer.mrmlScene.GetNodeByID(\"vtkMRMLSliceNodeGreen\")\r\n if sGreen == None :\r\n sGreen = slicer.mrmlScene.GetNodeByID(\"vtkMRMLSliceNode3\")\r\n reformatLogic = slicer.vtkSlicerReformatLogic()\r\n #sGreen.SetSliceVisible(0)\r\n sGreen.SetOrientationToCoronal()\r\n #sw = slicer.app.layoutManager().sliceWidget(\"Green\")\r\n #sw.fitSliceToBackground()\r\n sGreen.Modified()","def plot_timeline(self, param_name, start_time=None, stop_time=None, \n provider=None, calib=False, max_pts=None):\n\n meta = self.get_param_info(param_name, mode='simple')\n data = self.get_data(param_name, start_time, stop_time, provider, calib, max_pts)\n data = data.squeeze()\n\n if data is None:\n return None\n\n fig, ax = plt.subplots()\n \n # get a list of changes in the data\n # changes = data[data.diff()!=0].index.tolist() # <-- does not work with strings\n # changes = data[1:][data[1:].ne(data[1:].shift())].index.tolist()\n changes = data[data.ne(data.shift())].index.tolist()\n\n # add the end of the last period\n changes.append(data.index.max())\n\n # trying to do gap detection here to NOT fully shade areas where we have no data\n # first finding the mean periodicity of the data\n mean = data.index.to_series().diff().mean()\n\n # now flag periods where the gaps are 2x this\n gap_ends = data[data.index.to_series().diff()>2*mean].index.tolist()\n\n # get the durations\n durations = np.diff(changes)\n\n\n\n # make a colour index with the correct number of colors, spanning the colourmap\n colours = cm.get_cmap('viridis')\n\n # get the list of unique values and create a colour list with this many entries\n num_unique = len(data.unique())\n colour_list = [colours(1.*i/num_unique) for i in range(num_unique)]\n \n # make a dictionary mapping unique values to colours\n unique = data.unique().tolist()\n colors = data[changes].map(dict(zip(unique, colour_list)))\n\n \n\n # now define the x and y ranges \n xranges = [(stop, end) for stop, end in zip(changes, durations)]\n yranges = (1, 0.5)\n\n # plot it using the broken horizontal bar function\n ax.broken_barh(xranges, yranges, facecolors=colors, zorder=2)\n \n ax.set_title(meta['Description'])\n ax.set_xlabel('Date (UTC)')\n # if 'Unit' in meta.index:\n # ax.set_ylabel(meta['Unit'])\n # else:\n # ax.set_ylabel('Calibrated') if calib else ax.set_ylabel('Raw')\n fig.autofmt_xdate()\n xfmt = md.DateFormatter('%Y-%m-%d %H:%M:%S')\n ax.xaxis.set_major_formatter(xfmt)\n\n return ax","def region_growing(imOr,reg,area,prof,conn,precision):\n\tif prof:\n\t\tif area > 0.085:\n\t\t\treg1 = morph('erode',reg,25)\n\t\t\tif reg1.max() == 1.0:\n\t\t\t\treg = reg1\n\t\t\telse:\n\t\t\t\treg1 = morph('erode',reg,15)\n\t\t\t\tif reg1.max() == 1.0:\n\t\t\t\t\treg = reg1\n\telse:\n\t\tif area > 0.15:\n\t\t\treg1 = morph('erode',reg,15)\n\t\t\tif reg1.max() == 1.0:\n\t\t\t\treg = reg1\n\n\telementos = contar (reg,1)\n\tseguir = True\n\twhile seguir:\n\t\treg = cv2.convertScaleAbs(reg)\n\t\t_,contours, h = cv2.findContours(reg, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)\n\t\treg[reg != 0] = 1\n\t\tmedia_region = sum(imOr[reg==1])/max(cv2.contourArea(contours[0]),0.001)\n\n\t\tfor elemento in contours[0]:\n\t\t\tif prof:\n\t\t\t\treg = expand(elemento,reg,imOr,media_region,precision/2,conn)\n\t\t\telse:\n\t\t\t\treg = expand(elemento,reg,imOr,media_region,precision,conn)\n\t\telementos_nuevo = contar (reg,1)\n\t\tif elementos == elementos_nuevo:\n\t\t\tseguir = False\n\t\telementos = elementos_nuevo\n\tse = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(5,5))\n\treg = cv2.dilate(reg.astype(np.float32),se,iterations = 3)\n\tse = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(5,5))\n\treg = cv2.erode(reg.astype(np.float32),se,iterations = 2)\n\n\treturn reg","def vis_mechanically_coupled_regions(img_dir,output_dir,data,dbscn_length,dbscn_min_size,display_not_save=False):\n #Read in the image that is segmented/labelled for nuclei\n img=imread(img_dir)\n\n #save plots to show clusters\n fig = plt.figure(figsize=(6, 2))\n ax0 = fig.add_subplot(131)\n ax1 = fig.add_subplot(132)\n ax3 = fig.add_subplot(133)\n #show segmented image labels\n ax0.imshow(img,aspect='auto') \n ax0.axis('off')\n #nuclear centroid color-coded by their orientation\n img1=ax1.scatter(data[\"Y\"], data[\"X\"], c=data[\"angles\"],s=1)\n ax1.set_xlim(0,img.shape[0])\n ax1.set_ylim(img.shape[1],0)\n plt.colorbar(img1)\n ax1.axis('off')\n\n # plot the cluster assignments\n img3=ax3.scatter(data[data[\"clusters\"]> -1][\"Y\"], data[data[\"clusters\"]> -1][\"X\"], \n c=data[data[\"clusters\"]> -1][\"clusters\"],cmap=\"plasma\",s=1)\n ax3.set_xlim(0,img.shape[0])\n ax3.set_ylim(img.shape[1],0)\n ax3.axis('off')\n\n #add titles\n ax0.title.set_text('Segmented Image')\n ax1.title.set_text('Filtered Orientation')\n ax3.title.set_text('Clusters')\n\n if display_not_save:\n plt.show()\n else: \n plt.savefig((output_dir+\"/\"+img_dir.rsplit('/', 1)[-1][:-4]+\"_\"+str(dbscn_length)+\"_\"+ str(dbscn_min_size)+\".png\"),dpi=600, bbox_inches = 'tight',pad_inches = 0)\n fig.clf()\n plt.close(fig)\n plt.close('all')\n \n \n del fig,ax0,ax1,ax3,img1,img3","def _seg_image(self, x, y, r_cut=100):\n snr=self.snr\n npixels=self.npixels\n bakground = self.bakground\n error= self.bkg_rms(x,y,r_cut)\n kernel = self.kernel\n image_cutted = self.cut_image(x,y,r_cut)\n image_data = image_cutted\n threshold_detect_objs=detect_threshold(data=image_data, nsigma=snr,error=error)\n segments=detect_sources(image_data, threshold_detect_objs, npixels=npixels, filter_kernel=kernel)\n segments_deblend = deblend_sources(image_data, segments, npixels=npixels,nlevels=10)\n segments_deblend_info = source_properties(image_data, segments_deblend)\n nobjs = segments_deblend_info.to_table(columns=['id'])['id'].max()\n xcenter = segments_deblend_info.to_table(columns=['xcentroid'])['xcentroid'].value\n ycenter = segments_deblend_info.to_table(columns=['ycentroid'])['ycentroid'].value\n image_data_size = np.int((image_data.shape[0] + 1) / 2.)\n dist = ((xcenter - image_data_size) ** 2 + (ycenter - image_data_size) ** 2) ** 0.5\n c_index = np.where(dist == dist.min())[0][0]\n center_mask=(segments_deblend.data==c_index+1)*1 #supposed to be the data mask\n obj_masks = []\n for i in range(nobjs):\n mask = ((segments_deblend.data==i+1)*1)\n obj_masks.append(mask)\n xmin = segments_deblend_info.to_table(columns=['bbox_xmin'])['bbox_xmin'].value\n xmax = segments_deblend_info.to_table(columns=['bbox_xmax'])['bbox_xmax'].value\n ymin = segments_deblend_info.to_table(columns=['bbox_ymin'])['bbox_ymin'].value\n ymax = segments_deblend_info.to_table(columns=['bbox_ymax'])['bbox_ymax'].value\n xmin_c, xmax_c = xmin[c_index], xmax[c_index]\n ymin_c, ymax_c = ymin[c_index], ymax[c_index]\n xsize_c = xmax_c - xmin_c\n ysize_c = ymax_c - ymin_c\n if xsize_c > ysize_c:\n r_center = np.int(xsize_c)\n else:\n r_center = np.int(ysize_c)\n center_mask_info= [center_mask, r_center, xcenter, ycenter, c_index]\n return obj_masks, center_mask_info, segments_deblend","def deleteSelectedSegs(self):\n inds = []\n for ix in range(len(self.picbuttons)):\n if self.picbuttons[ix].mark == 'yellow':\n inds.append(ix)\n\n if len(inds)==0:\n print(\"No segments selected\")\n return\n\n self.segsChanged = True\n for ix in reversed(inds):\n del self.segments[ix]\n del self.picbuttons[ix]\n\n # update self.clusters, delete clusters with no members\n todelete = []\n for ID, label in self.clusters.items():\n empty = True\n for seg in self.segments:\n if seg[-1] == ID:\n empty = False\n break\n if empty:\n todelete.append(ID)\n\n self.clearButtons()\n\n # Generate new class labels\n if len(todelete) > 0:\n keys = [i for i in range(self.nclasses) if i not in todelete] # the old keys those didn't delete\n # print('old keys left: ', keys)\n\n nclasses = self.nclasses - len(todelete)\n max_label = nclasses - 1\n labels = []\n c = self.nclasses - 1\n while c > -1:\n if c in keys:\n labels.append((c, max_label))\n max_label -= 1\n c -= 1\n\n labels = dict(labels)\n # print(labels)\n\n # update clusters dictionary {ID: cluster_name}\n clusters = {}\n for i in keys:\n clusters.update({labels[i]: self.clusters[i]})\n\n print('before delete: ', self.clusters)\n self.clusters = clusters\n print('after delete: ', self.clusters)\n\n # update the segments\n for seg in self.segments:\n seg[-1] = labels[seg[-1]]\n\n self.nclasses = nclasses\n\n # redraw the buttons\n self.updateButtons()\n self.completeChanged.emit()","def find_lines(\n\tthreshold, regions=None, direction=\"horizontal\", line_scale=15, iterations=0\n):\n\tlines = []\n\n\tif direction == \"vertical\":\n\t\t#size = threshold.shape[0] // line_scale\n\t\tsize = threshold.shape[0] // line_scale\n\t\tel = cv2.getStructuringElement(cv2.MORPH_RECT, (1, size))\n\telif direction == \"horizontal\":\n\t\tsize = threshold.shape[1] // line_scale\n\t\tel = cv2.getStructuringElement(cv2.MORPH_RECT, (size, 1))\n\telif direction is None:\n\t\traise ValueError(\"Specify direction as either 'vertical' or 'horizontal'\")\n\n\tif regions is not None:\n\t\tregion_mask = np.zeros(threshold.shape)\n\t\tfor region in regions:\n\t\t\tx, y, w, h = region\n\t\t\tregion_mask[y : y + h, x : x + w] = 1\n\t\tthreshold = np.multiply(threshold, region_mask)\n\n\tthreshold = cv2.erode(threshold, el)\n\n\tthreshold = cv2.dilate(threshold, el)\n\t##############################################\n\t#threshold = cv2.dilate(threshold,el,iterations=iterations)\n\t#threshold = cv2.erode(threshold,el,iterations=iterations)\n\t\n\t#threshold = cv2.dilate(threshold,el,iterations=iterations)\n\t#threshold = cv2.erode(threshold,el,iterations=iterations)\n\t####################################################\n\tdmask = cv2.dilate(threshold, el, iterations=iterations)\n\n\ttry:\n\t\t_, contours, _ = cv2.findContours(\n\t\t\tthreshold.astype(np.uint8), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE\n\t\t)\n\texcept ValueError:\n\t\t# for opencv backward compatibility\n\t\tcontours, _ = cv2.findContours(\n\t\t\tthreshold.astype(np.uint8), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE\n\t\t)\n\n\tfor c in contours:\n\t\tx, y, w, h = cv2.boundingRect(c)\n\t\tx1, x2 = x, x + w\n\t\ty1, y2 = y, y + h\n\t\tif direction == \"vertical\":\n\t\t\tlines.append(((x1 + x2) // 2, y2, (x1 + x2) // 2, y1))\n\t\telif direction == \"horizontal\":\n\t\t\tlines.append((x1, (y1 + y2) // 2, x2, (y1 + y2) // 2))\n\n\treturn dmask, lines","def closeRegions(regions):\n for orig,table in regions.items():\n for dest in table['neighbors']:\n if not regions.has_key(dest):\n regions[dest] = {'neighbors': set(),\n 'value': 4}\n regions[dest]['neighbors'].add(orig)\n return regions","def segment(segmentation_model, thresholds=None):\n\n if thresholds is None:\n thresholds = DEFAULT_THRESHOLDS\n\n # Mark all flats\n _set_flat_segments(segmentation_model, thresholds)\n\n yield None\n\n while (segmentation_model.phases == CurvePhases.UndeterminedNonFlat.value).any():\n\n # Mark linear slope\n flanking = _set_nonflat_linear_segment(segmentation_model, thresholds)\n\n yield None\n\n if flanking.any():\n\n first_on_left_flank = flanking.argmin()\n\n for filt in _get_candidate_segment(flanking):\n\n direction = PhaseEdge.Right if \\\n filt.argmin() == first_on_left_flank else \\\n PhaseEdge.Left\n\n # Mark flanking non-linear phase\n phase = _set_nonlinear_phase_type(segmentation_model, thresholds, filt, direction)\n\n if phase is CurvePhases.Undetermined:\n # If no curved segment found, it is not safe to look for more\n # non-flat linear phases because could merge two that should\n # not be merged.\n segmentation_model.phases[filt] = CurvePhases.UndeterminedNonLinear.value\n\n # Only look for the first non-linear segment rest is up for grabs for\n # Next iteration of finding impulses or collapses\n flanking[filt] = False\n\n yield None\n\n # Try to classify remaining positions as non linear phases\n for filt in _get_candidate_segment(segmentation_model.phases, test_value=CurvePhases.UndeterminedNonLinear.value):\n\n phase = _set_nonlinear_phase_type(segmentation_model, thresholds, filt, PhaseEdge.Intelligent)\n\n yield None\n\n # If currently considered segment had no phase then it is undetermined\n if phase is CurvePhases.Undetermined:\n\n segmentation_model.phases[filt] = phase.value\n yield None\n\n # If there's an offset assume phase carries to edge\n if segmentation_model.offset:\n segmentation_model.phases[:segmentation_model.offset] = \\\n segmentation_model.phases[segmentation_model.offset]\n segmentation_model.phases[-segmentation_model.offset:] = \\\n segmentation_model.phases[-segmentation_model.offset - 1]\n yield None\n\n # Bridge neighbouring segments of same type if gap is one\n _fill_undefined_gaps(segmentation_model.phases)","def removeDots(image,points,coeff2,newColorArray):\r\n for i in range(1,coeff2):\r\n if (px[3,points*i] != (0,0,0)):\r\n im.putpixel((0,points*i-1),newColorArray[0][i-1])\r\n im.putpixel((1,points*i-1),newColorArray[0][i-1])\r\n im.putpixel((0,points*i),newColorArray[0][i])\r\n im.putpixel((1,points*i),newColorArray[0][i])\r\n im.putpixel((0,points*i+1),newColorArray[0][i])\r\n im.putpixel((1,points*i+1),newColorArray[0][i])\r\n if lineWidth==5:\r\n im.putpixel((0,points*i-2),newColorArray[0][i-1])\r\n im.putpixel((1,points*i-2),newColorArray[0][i-1])\r\n im.putpixel((0,points*i+2),newColorArray[0][i])\r\n im.putpixel((1,points*i+2),newColorArray[0][i])\r\n\r\n for i in range(1,coeff2):\r\n for j in range(1,coeff2):\r\n if (px[points*i-3,points*j] != (0,0,0) and px[points*i+3,points*j] != (0,0,0) and px[points*i,points*j-3] != (0,0,0) and px[points*i,points*j+3] != (0,0,0)):\r\n draw.line((points*i-5,points*j,points*i+5,points*j),fill=newColorArray[i][j],width=lineWidth)\r\n for i in range(1,coeff2):\r\n if px[points*i,500]!=(0,0,0):\r\n draw.line((points*i,500,points*i,511),fill=newColorArray[i][15],width=lineWidth)\r\n if px[500,points*i]!=(0,0,0):\r\n draw.line((500,points*i,511,points*i),fill=newColorArray[15][i],width=lineWidth)","def detectBorders(self, points):\n lane1 = []; lane2 = []\n self.leftLane = [None for _ in range(int(np.floor(self.BIRDVIEW_HEIGHT / self.slideThickness)))]\n self.rightLane = [None for _ in range(int(np.floor(self.BIRDVIEW_HEIGHT / self.slideThickness)))]\n\n pointMap = np.zeros((points.shape[0], 20))\n prePoint = np.zeros((points.shape[0], 20))\n postPoint = np.zeros((points.shape[0], 20))\n\n dis = 10\n max1 = -1; max2 = -1\n\n ##\n ## /!\\ UNSAFE LOOP, TODO: FIX\n ##\n for i in range(points.shape[0]):\n for j in range(len(points[i])):\n pointMap[i][j] = 1\n prePoint[i][j] = -1\n postPoint[i][j] = -1\n\n for i in reversed(range(points.shape[0] - 2)):\n\n for j in range(len(points[i])):\n\n err = 320\n for m in range(1, min(points.shape[0] - 1 - i, 5)):\n check = False ## TODO: why unused ?\n\n for k in range(len(points[i + 1])):\n\n (x_m, y_m) = points[i + m][k].pt\n (x, y) = points[i][j].pt\n\n if (abs(x_m - x) < dis and abs(y_m - y) < err):\n err = abs(x_m - x)\n\n pointMap[i][j] = pointMap[i + m][k] + 1\n prePoint[i][j] = k\n postPoint[i + m][k] = j\n check = True\n\n break ## breaks out of the m loop. Why is it not conditioned by check ? TODO: ???\n\n if (pointMap[i][j] > max1):\n max1 = pointMap[i][j]\n posMax = cv2.KeyPoint(i, j, _size=0)\n \n else:\n posMax = None\n\n for i in range(points.shape[0]):\n for j in range(len(points[i])):\n if posMax:\n if (pointMap[i][j] > max2 and (i != posMax.pt[0] or j != posMax.pt[1]) and postPoint[i][j] == -1): #FIXME \"local variable 'posMax' referenced before assignment\" possible\n max2 = pointMap[i][j]\n posMax2 = cv2.KeyPoint(i, j, _size=0)\n\n\n\n if max1 == -1:\n return\n\n # DEFINES LANE 1 POINTS\n while (max1 >= 1):\n (x,y) = points[int(posMax.pt[0])][int(posMax.pt[1])].pt\n lane1.append(\n [x,y]\n )\n if (max1 == 1):\n break\n\n posMax = cv2.KeyPoint(\n posMax.pt[0]+1,\n prePoint[int(posMax.pt[0])][int(posMax.pt[1])],\n _size=0\n )\n\n max1 -= 1\n\n # DEFINES LANE 2 POINTS\n while (max2 >= 1):\n (x,y) = points[int(posMax2.pt[0])][int(posMax2.pt[1])].pt\n lane2.append(\n [x, y]\n )\n if (max2 == 1):\n break\n\n posMax2 = cv2.KeyPoint(\n posMax2.pt[0]+1,\n prePoint[int(posMax2.pt[0])][int(posMax2.pt[1])],\n _size=0\n )\n\n max2-= 1\n\n subLane1 = np.array(lane1[0:5])\n subLane2 = np.array(lane2[0:5])\n\n # checking if sublane has an empty value\n\n line1 = cv2.fitLine(subLane1, 2, 0, 0.01, 0.01)\n line2 = cv2.fitLine(subLane2, 2, 0, 0.01, 0.01)\n\n try:\n lane1X = (self.BIRDVIEW_WIDTH - line1[3]) * line1[0] / line1[1] + line1[2]\n except:\n lane1X = 0\n\n try:\n lane2X = (self.BIRDVIEW_WIDTH - line2[3]) * line2[0] / line2[1] + line2[2]\n except:\n lane2X = 0\n \n if (lane1X < lane2X):\n for i in range(len(lane1)):\n self.leftLane[int(np.floor(lane1[i][1] / self.slideThickness ))] = lane1[i]\n\n for i in range(len(lane2)):\n self.rightLane[int(np.floor(lane2[i][1] / self.slideThickness ))] = lane2[i]\n\n else:\n\n for i in range(len(lane1)):\n self.rightLane[int(np.floor(lane1[i][1] / self.slideThickness ))] = lane1[i]\n\n for i in range(len(lane2)):\n self.leftLane[int(np.floor(lane2[i][1] / self.slideThickness ))] = lane2[i]","def segment_cells(frame, mask=None):\n \n blurred = filters.gaussian(frame, 2)\n ridges = enhance_ridges(frame)\n \n # threshold ridge image\n thresh = filters.threshold_otsu(ridges)\n thresh_factor = 0.5\n prominent_ridges = ridges > thresh_factor*thresh\n prominent_ridges = morphology.remove_small_objects(prominent_ridges, min_size=256)\n prominent_ridges = morphology.binary_closing(prominent_ridges)\n prominent_ridges = morphology.binary_dilation(prominent_ridges)\n \n # skeletonize\n ridge_skeleton = morphology.medial_axis(prominent_ridges)\n ridge_skeleton = morphology.binary_dilation(ridge_skeleton)\n ridge_skeleton *= mask\n ridge_skeleton = np.bitwise_xor(ridge_skeleton, mask)\n \n # label\n cell_label_im = measure.label(ridge_skeleton)\n \n # morphological closing to fill in the cracks\n for cell_num in range(1, cell_label_im.max()+1):\n cell_mask = cell_label_im==cell_num\n cell_mask = morphology.binary_closing(cell_mask, disk(3))\n cell_label_im[cell_mask] = cell_num\n \n return cell_label_im","def _cons_traj(self,lon,lat,period):\n\t\tgroup = self['%g_sec'%( period )]\n\t\tlonArr = group['lonArr'].value\n\t\tlatArr = group['latArr'].value\n\t\tageArr = group['age_Arr'].value\n\t\tage_drv_lon = group['age_deriv_lon_Arr']\n\t\tage_drv_lat = group['age_deriv_lat_Arr']\n\t\tage_drv_msk = group['age_deriv_msk_Arr']\n\t\ttomo_data_msk = group['tomo_data_msk'].value\n\t\tmask_init = np.logical_or(tomo_data_msk, age_drv_msk)\n\t\tmask = np.array(np.ones(lonArr.shape),dtype=bool)\n\t\ti_s, j_s = self._find_nearest_grid(lon,lat,period) # find the 1st and 2nd index of the start point on grid\n\t\tif mask_init[i_s,j_s]:\n\t\t\traise ValueError(\"The starting point is out bounds of the resulting map\")\n\t\tmask[i_s,j_s] = False\n\t\t# go along increasing age direction\n\t\ti,j = _walk(age_drv_lon,age_drv_lat,i_s,j_s,1)\n\t\twhile (0<i<lonArr.shape[0] and 0<j<lonArr.shape[1]):\n\t\t\tif mask_init[i,j]:\n\t\t\t\tbreak\n\t\t\telse:\n\t\t\t\tmask[i,j] = False\n\t\t\ti,j = _walk(age_drv_lon,age_drv_lat,i,j,1)\n\t\t\t\n\t\t# go along descending age direction\n\t\ti_2,j_2 = _walk(age_drv_lon,age_drv_lat,i_s,j_s,-1)\n\t\tmask[i_2,j_2] = False\n\t\twhile (0<i_2<lonArr.shape[0] and 0<j_2<lonArr.shape[1]):\n\t\t\tif mask_init[i_2,j_2]:\n\t\t\t\tbreak\n\t\t\telse:\n\t\t\t\tmask[i_2,j_2] = False\n\t\t\tage_b = ageArr[i_2,j_2]\n\t\t\ti_b,j_b = i_2,j_2\n\t\t\ti_2,j_2 = _walk(age_drv_lon,age_drv_lat,i_2,j_2,-1)\n\t\t\tif ageArr[i_2,j_2] > age_b: # find the youngest age\n\t\t\t\ti_3,j_3 = i_b,j_b\n\t\t\t\tbreak\n\t\ttry:\n\t\t\ti_3\n\t\texcept NameError:\n\t\t\treturn mask\n\t\t\n\t\t# go along increasing age from the found youngest age\n\t\twhile (0<i_3<lonArr.shape[0] and 0<j_3<lonArr.shape[1]):\n\t\t\tif mask_init[i_3,j_3]:\n\t\t\t\tbreak\n\t\t\telse:\n\t\t\t\tmask[i_3,j_3] = False\n\t\t\ti_3,j_3 = _walk(age_drv_lon,age_drv_lat,i_3,j_3,1)\n\t\treturn mask","def _draw_segments(frame, segments):\n for segment in segments:\n cv2.line(frame, segment[0], segment[1],\n color=(0, 255, 255), thickness=2)\n cv2.circle(frame, segment[0], radius=3,\n color=(255, 0, 0), thickness=-1)\n cv2.circle(frame, segment[1], radius=3,\n color=(255, 0, 0), thickness=-1)","def overlay_segmentation(image_bgr,\n segmentation,\n colormap=cv2.COLORMAP_PARULA,\n alpha=0.6,\n inplace=True):\n if inplace:\n image_target_bgr = image_bgr\n else:\n image_target_bgr = image_bgr * 0\n\n bbox_xywh = segmentation['bbox']\n x, y, w, h = [int(v) for v in bbox_xywh]\n if w <= 0 or h <= 0:\n return image_bgr\n\n segm = segmentation['segm']\n levels = 255.0 / segm.max()\n mask_bg = np.tile((segm == 0)[:, :, np.newaxis], [1, 1, 3])\n\n segm = segm.astype(np.float32) * levels\n segm = segm.clip(0, 255).astype(np.uint8)\n segm = cv2.applyColorMap(segm, cv2.COLORMAP_PARULA)\n\n segm[mask_bg] = image_target_bgr[y:y + h, x:x + w, :][mask_bg]\n\n # img_hsv = cv2.cvtColor(image_bgr, cv2.COLOR_BGR2HSV)\n # segm_hsv = cv2.cvtColor(segm, cv2.COLOR_BGR2HSV)\n\n image_target_bgr[y:y + h, x:x + w, :] = (image_target_bgr[y:y + h, x:x + w, :] * (1.0 - alpha) +\n segm * alpha)\n\n return image_target_bgr.astype(np.uint8)","def region_graph(t0, t1, t2, t3):\r\n medians0 = sorted(sub_saharan_africa_countries())\r\n t0.goto(-250, ((medians0[0])-50))\r\n t0.rt(90)\r\n for idx in range(1, len(medians0)):\r\n t0.pencolor(\"blue\")\r\n t0.pd()\r\n t0.setpos((-250+(idx*10.5)), ((medians0[idx])))\r\n\r\n medians1 = sorted(south_asia_countries())\r\n t1.goto(-250, ((medians1[0]) - 60))\r\n t1.rt(90)\r\n for idx in range(1, len(medians1)):\r\n t1.pencolor(\"red\")\r\n t1.pd()\r\n t1.setpos((-250 + (idx * 68.5)), (2*(medians1[idx])+10))\r\n\r\n medians2 = sorted(europe_central_asia_countries())\r\n t2.goto(-250, (medians2[0])+60)\r\n t2.rt(90)\r\n for idx in range(1, len(medians2)):\r\n t2.pencolor(\"green\")\r\n t2.pd()\r\n t2.setpos((-250 + (idx*10.19)), (2 * (medians2[idx]) + 10))\r\n\r\n medians3 = sorted(latin_america_countries())\r\n t3.goto(-250, (medians3[0]) + 20)\r\n t3.rt(90)\r\n for idx in range(1, len(medians3)):\r\n t3.pencolor(\"gold\")\r\n t3.pd()\r\n t3.setpos((-250 + (idx * 14.39)), (2 * (medians3[idx]) + 10))\r\n\r\n t0.pu()\r\n t0.goto(initialCoordinates())\r\n t1.pu()\r\n t1.goto(initialCoordinates())\r\n t2.pu()\r\n t2.goto(initialCoordinates())\r\n t3.pu()\r\n t3.goto(initialCoordinates())\r\n\r\n medians4 = sorted(middle_east_countries())\r\n t0.goto(-250, (medians4[0])-40)\r\n t0.rt(90)\r\n for idx in range(1, len(medians4)):\r\n t0.pencolor(\"BLACK\")\r\n t0.pd()\r\n t0.setpos((-250 + (idx * 26.3)), (2 * (medians4[idx]) + 10))\r\n t0.rt(180)\r\n\r\n medians5 = sorted(north_america_countries())\r\n t1.goto(-250, (medians5[0])+60)\r\n t1.rt(90)\r\n for idx in range(1, len(medians5)):\r\n t1.pencolor(\"YELLOW\")\r\n t1.pd()\r\n t1.setpos((-250 + (idx * 485.3)), (2 * (medians5[idx]) + 10))\r\n t1.rt(180)\r\n\r\n medians6 = sorted(east_asia_pacific_countries())\r\n t2.goto(-250, (medians6[0]))\r\n t2.rt(90)\r\n for idx in range(1, len(medians6)):\r\n t2.pencolor(\"purple\")\r\n t2.pd()\r\n t2.setpos((-250 + (idx * 16)), (2 * (medians6[idx]) + 10))\r\n t0.pu()\r\n t0.goto(initialCoordinates())\r\n t1.pu()\r\n t1.goto(initialCoordinates())\r\n t2.pu()\r\n t2.goto(initialCoordinates())","def getsegs (bounds, split):\n segmentslist=bisect_rectange(split, bounds[0], bounds[1], bounds[2], bounds[3])\n count=1\n segpass=0\n \n #Get list of segment ids currently in database\n query=\"\"\"select seg_id from segment;\"\"\"\n df = pd.read_sql_query(query,con=engine)\n segids=set(df.seg_id)\n \n while count < len(segmentslist):\n try:\n for i in segmentslist:\n segments=getsegmentinfo(i)\n \n \n for seg in segments:\n #If running function several times for different splits, this ignores existing segments and prints a message\n if seg.id in segids: \n segpass+=1\n if (segpass % 10 == 0): \n print (\"{} segments already exist\".format(segpass))\n #Else this is a new segment, so get details from the strava and geocodio apis and save them to a dataframe and eventually to the database\n else:\n location = geocodio_client.reverse((seg.start_latlng[0], seg.start_latlng[1]))\n zipcode=location['results'][0]['address_components']['zip']\n \n newrow = {'seg_id' : seg.id,\n 'resource_state': seg.resource_state,\n 'climb_category':seg.climb_category,\n 'climb_category_desc':seg.climb_category_desc,\n 'average_grade':seg.avg_grade,\n 'elev_difference': str(seg.elev_difference).split()[0],\n 'distance': str(seg.distance).split()[0],\n 'name' : seg.name,\n 'start_lat' : seg.start_latlng[0],\n 'start_long' : seg.start_latlng[1],\n 'end_lat' : seg.end_latlng[0],\n 'end_long' : seg.end_latlng[1],\n 'points' : seg.points,\n 'starred':seg.starred,\n 'zipcode':zipcode\n }\n df=pd.DataFrame(newrow, index=[0])\n \n try:\n #Save dataframe to database\n df.to_sql('segment', engine,index=False,if_exists='append')\n except:\n pass\n\n #Prints message which keeps track of number of sub bounds completed \n if (count % 10) == 0:\n print (\"Getting segments in bound {} of {}\".format(count, len(segmentslist)))\n count+=1\n except Exception as inst:\n print (inst) \n return None","def consecutive_sections(): # noqa: D416","def test_segmentation_functions(sersic_2d_image):\n\n image_mean, image_median, image_stddev = sigma_clipped_stats(sersic_2d_image, sigma=3)\n threshold = image_stddev * 3\n npixels = 4 ** 2\n\n # Testing make_segments\n segm = pf.make_segments(sersic_2d_image, npixels=npixels, threshold=threshold)\n\n assert isinstance(segm, SegmentationImage)\n assert segm.shape == sersic_2d_image.shape\n assert np.all(segm.data >= 0)\n assert len(np.unique(segm.data)) == 2 # account for background being labeled as 0\n\n # Testing deblend_segments\n segm_deblend = pf.deblend_segments(sersic_2d_image, segm, npixels=npixels, contrast=0.00)\n\n assert isinstance(segm_deblend, SegmentationImage)\n assert segm_deblend.shape == sersic_2d_image.shape\n assert np.all(segm_deblend.data >= 0)\n assert len(np.unique(segm_deblend.data)) >= len(np.unique(segm.data))","def test_burst_dispersion(self):\n # some reproducible arbitrariness\n np.random.seed(7342642)\n\n n = 25\n t_max = 50\n dt = 0.1\n n_sim = 10\n \n G = HVCLikeLayer(n)\n\n burst_starts = []\n for i in xrange(n_sim):\n M = simulation.EventMonitor(G)\n sim = simulation.Simulation(G, M, dt=dt)\n sim.run(t_max)\n\n # split spikes by neuron index\n spikes = [np.asarray(M.t)[np.asarray(M.i) == i] for i in xrange(n)]\n burst_starts.append([_[0] for _ in spikes])\n\n burst_starts_range = [np.ptp([_[i] for _ in burst_starts])\n for i in xrange(n)]\n \n self.assertLess(np.max(burst_starts_range), G.burst_noise + dt/2)","def areasShaded(self):\n global area_ABE\n area_ABE = always_redraw(\n lambda : Polygon(dot_center.get_center(), radius_ang_end_dot.get_center(), dropped_dot.get_center(),\n color=PINK, fill_color=PINK, fill_opacity=0.5)\n )\n global area_ABE_copy\n area_ABE_copy = area_ABE.copy()\n\n self.play(Write(area_ABE))\n self.wait(0.5)\n self.play(area_ABE_copy.animate.move_to(consider_area_text.get_center()+DOWN*1.5+LEFT*1.5))\n\n global area_ABD\n area_ABD = always_redraw(\n lambda : Sector(outer_radius=self.x_max, start_angle=0, angle=theta.get_value()*DEGREES,\n stroke_width=DEFAULT_STROKE_WIDTH , stroke_color=BLUE, color=BLUE, fill_opacity=0.5).shift(LEFT*5)\n )\n global area_ABD_copy\n area_ABD_copy = area_ABD.copy()\n\n self.play(Write(area_ABD))\n self.wait(0.5)\n self.play(area_ABD_copy.animate.move_to(consider_area_text.get_center()+DOWN*1.5+RIGHT*1.5))\n\n global area_ABC\n area_ABC = always_redraw(\n lambda : Polygon(dot_center.get_center(), radius_ang_end_dot.get_center(), small_tangent_end_dot.get_center(),\n color=GREEN, fill_color=GREEN, fill_opacity=0.5)\n )\n global area_ABC_copy\n area_ABC_copy = area_ABC.copy()\n\n self.play(Write(area_ABC))\n self.wait(0.5)\n self.play(area_ABC_copy.animate.move_to(consider_area_text.get_center()+DOWN*3.5))\n\n self.play(FadeOut(consider_area_text))","def __iteratively_retain(\n self,\n orf_regions: List[Tuple[int, int]]) -> List[Tuple[int, int]]:\n\n ret = []\n\n arr = np.zeros((len(self.seq), ))\n\n for start, end in orf_regions:\n ret.append((start, end))\n arr[start-1:end] = 1\n orf_coverage = np.sum(arr) / len(arr)\n if orf_coverage > self.min_orf_coverage:\n break\n\n return ret","def split(self,i):\n alpha = 0.6\n eps = 2.6\n\n if self.n > self.maxn-3:\n print \"cannot refine any further\"\n return False\n \n # The son \n self.m[i] = self.m[i] / 4.0\n #self.h[i] = self.h[i] * alpha\n\n # Daughter 1\n self.r[self.n] = self.r[i] + eps*np.array([0,1])\n self.m[self.n] = self.m[i] \n self.v[self.n] = self.v[i]\n \n # Daughter 2\n self.r[self.n+1] = self.r[i] + eps*np.array([0.866025,-0.5])\n self.m[self.n+1] = self.m[i] \n self.v[self.n+1] = self.v[i]\n \n # Daughter 3\n self.r[self.n+2] = self.r[i] + eps*np.array([-0.866025,-0.5])\n self.m[self.n+2] = self.m[i] \n self.v[self.n+2] = self.v[i]\n \n self.n = self.n+3\n #print \"There are now \",self.n,\"particles\"\n return True","def dark_cloud(self):\n self.data['dark_cloud'] = ((self.data['Close'].shift(1) > self.data['Open'].shift(1)) & \\\n (((self.data['Close'].shift(1) + self.data['Open'].shift(1)) / 2) > self.data['Close']) & \\\n (self.data['Open'] > self.data['Close']) & (self.data['Open'] > self.data['Close'].shift(1)) &\\\n (self.data['Close'] > self.data['Open'].shift(1)) & \\\n ((self.data['Open'] - self.data['Close']) / (.001 + (self.data['High'] - self.data['Low'])) > .6))","def region_growing_from_input(self, color, bone_from_scan=None):\n collect()\n # initilize\n if not bone_from_scan:\n self.load_original_data()\n else:\n self.copy_original_from_bone(bone_from_scan)\n checked = zeros(self._original_img_data.shape)\n seg = zeros(self._original_img_data.shape)\n need_to_check = []\n # Color the seeds and check for neighbors\n for seed in self._seeds_points:\n seg[seed] = color\n checked[seed] = 1\n neighbors = self._get_neighbors(seed, checked, self.\n _original_img_data.shape)\n for neighbor in neighbors:\n if self._get_threshold(self._original_img_data[neighbor],\n VOID_VALUES[0],\n VOID_VALUES[1]):\n need_to_check.append(neighbor)\n # Region Growing - while there's a neighbor, color it and keep going\n bone_to_check = []\n while need_to_check:\n pt = need_to_check.pop()\n if checked[pt] == 1:\n continue\n else:\n checked[pt] = 1\n neighbors = self._get_neighbors(pt, checked, self.\n _original_img_data.shape)\n for neighbor in neighbors:\n if self._get_threshold(\n self._original_img_data[neighbor],\n VOID_VALUES[0], VOID_VALUES[1]):\n need_to_check.append(neighbor)\n if self._get_threshold(\n self._original_img_data[neighbor],\n BONE_BOUND_VALUES[0], BONE_BOUND_VALUES[1]):\n bone_to_check.append(neighbor)\n seg[pt] = color\n # Closing holes\n del need_to_check\n # check for Bone value - edge of the radius\n while bone_to_check:\n pt = bone_to_check.pop()\n if checked[pt] == 1:\n continue\n else:\n checked[pt] = 1\n neighbors = self._get_neighbors(pt, checked, self.\n _original_img_data.shape)\n for neighbor in neighbors:\n if self._get_threshold(\n self._original_img_data[neighbor],\n RADIUS_VALUES[0], RADIUS_VALUES[1]):\n bone_to_check.append(neighbor)\n seg[pt] = color\n del checked, bone_to_check\n for i in range(self._dilation):\n seg = dilation(seg, cube(3, uint8))\n for i in range(self._dilation - 1):\n seg = erosion(seg, cube(3, uint8))\n self._segmentation_data = seg\n del seg\n collect()","def fix_straight_lines(self):\r\n\r\n # Creates a vertical 1x5 kernel and applies binary closing based on that kernel\r\n vertical_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (1, 5))\r\n self.thresh_invert = cv2.morphologyEx(self.thresh_invert, cv2.MORPH_CLOSE, vertical_kernel, iterations=9)\r\n\r\n # Creates a horizontal 5x1 kernel and applies binary closing based on that kernel\r\n horizontal_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 1))\r\n self.thresh_invert = cv2.morphologyEx(self.thresh_invert, cv2.MORPH_CLOSE, horizontal_kernel, iterations=4)","def test_burst_dispersion(self):\n # some reproducible arbitrariness\n np.random.seed(7342642)\n\n n = 25\n t_max = 50\n dt = 0.1\n n_sim = 10\n \n G = RateHVCLayer(n)\n\n burst_starts = []\n for i in xrange(n_sim):\n M = simulation.StateMonitor(G, 'out')\n sim = simulation.Simulation(G, M, dt=dt)\n sim.run(t_max)\n\n burst_starts.append([dt*min((M.out[i] > 0).nonzero()[0])\n for i in xrange(n)])\n\n burst_starts_range = [np.ptp([_[i] for _ in burst_starts])\n for i in xrange(n)]\n \n self.assertLess(np.max(burst_starts_range), G.burst_noise + dt/2)","def BraceBadLight(self, pos):\n # Check if we are still alive or not, as this may be called\n # after we have been deleted.\n if self:\n super(EditraBaseStc, self).BraceBadLight(pos)","def draw_visible_area(self):\n\n if not self.given_center:\n return\n\n # Figure out what regions we should be showing\n horiz_width = self.hbar.pageStep()\n gui_start_x = self.hbar.value()\n vert_height = self.vbar.pageStep()\n gui_start_y = self.vbar.value()\n (game_min_x, game_max_y) = self.scene_to_ingame(gui_start_x, gui_start_y)\n (game_max_x, game_min_y) = self.scene_to_ingame(\n gui_start_x + horiz_width,\n gui_start_y + vert_height,\n )\n min_rx = game_min_x//32 - 1\n max_rx = game_max_x//32 + 1\n min_ry = game_min_y//32 - 1\n max_ry = game_max_y//32 + 1\n\n # First find out how many regions we're going to have to load (so that\n # we can initialize a progressbar)\n valid_regions = set()\n regions_to_load = []\n for rx in range(min_rx, max_rx+1):\n for ry in range(min_ry, max_ry+1):\n region = (rx, ry)\n valid_regions.add(region)\n if region in self.regions:\n if not self.regions[region].loaded:\n regions_to_load.append(region)\n\n # Initialize progressbar\n region_loading = self.mainwindow.region_loading\n region_loading.start(len(regions_to_load))\n\n # Now actually do the loading\n for idx, region in enumerate(regions_to_load):\n #print('Loading region {}'.format(region))\n self.regions[region].load()\n self.loaded_regions.add(region)\n region_loading.update(idx)\n\n # Unload regions which are too far out\n regions_to_unload = []\n for region in list(self.loaded_regions):\n if region not in valid_regions:\n regions_to_unload.append(region)\n\n region_loading.start(len(regions_to_unload), label='Unloading Regions')\n for idx, region in enumerate(regions_to_unload):\n #print('Unloading region {}'.format(region))\n self.regions[region].unload()\n self.loaded_regions.remove(region)\n region_loading.update(idx)\n\n # Finish our progress bar\n region_loading.finish()","def discriminator(time,signal,height_th,dt_left=300e-9,dt_right=1400e-9,Plot=False, method=0):\n dt = time[1] - time[0]\n bins_left = int(dt_left / dt)\n bins_right = int(dt_right / (time[1] - time[0]))\n bins_final = len(time) - 1\n\n # where signal is above threshold\n initial_window = np.array(np.where(signal > height_th)[0])\n mask = initial_window\n if len(mask) > 0:\n if method == 0:\n\n # MASK METHOD 1: include regions left and right of signal above\n # threshold.\n for i in np.arange(len(initial_window)) - 1:\n if (initial_window[i + 1] - initial_window[i] < bins_right + bins_left):\n mask = array_fill_between(\n mask, initial_window[i], initial_window[i + 1])\n else:\n mask = array_fill_between(\n mask, initial_window[i], initial_window[i] + bins_right)\n mask = array_fill_between(\n mask, initial_window[i + 1] - bins_left, initial_window[i + 1])\n # right most pulse close to edge but doesn't exceed\n if mask[-1] + bins_right <= bins_final:\n mask = array_fill_between(\n mask, mask[-1], mask[-1] + bins_right)\n else:\n # right most pulse exceeds right edge of trace: include mask up to end of pulse\n # bins_final+1 term includes one more index since fill_between\n # fills up to bins_final\n mask = array_fill_between(mask, mask[-1], bins_final + 1)\n if mask[0] - bins_left >= 0: # left most pulse close to edge but doesn't exceed\n mask = array_fill_between(mask, mask[0] - bins_left, mask[0])\n else:\n # left most pulse exceeds left edge of trace\n # 0-1 term includes one more index '-1' since fill_between\n # fills from 0\n mask = array_fill_between(mask, 0 - 1, mask[0])\n\n if method == 1:\n # MASK METHOD 2: SR LATCH\n mask = srlatch_full(signal, 0, height_th)\n\n # MASK METHOD 1: include regions left and right of signal above threshold.\n for i in np.arange(len(initial_window))-1:\n if (initial_window[i+1]-initial_window[i] < bins_right+bins_left):\n mask = array_fill_between(mask, initial_window[i], initial_window[i+1])\n else:\n mask = array_fill_between(mask, initial_window[i], initial_window[i]+bins_right)\n mask = array_fill_between(mask, initial_window[i+1]-bins_left, initial_window[i+1])\n if mask[-1]+bins_right <= bins_final: #right most pulse close to edge but doesn't exceed\n mask = array_fill_between(mask, mask[-1], mask[-1]+bins_right)\n else: \n #right most pulse exceeds right edge of trace: include mask up to end of pulse\n #bins_final+1 term includes one more index since fill_between fills up to bins_final\n mask = array_fill_between(mask, mask[-1], bins_final+1)\n if mask[0]-bins_left >= 0: #left most pulse close to edge but doesn't exceed\n mask = array_fill_between(mask, mask[0]-bins_left, mask[0])\n else: \n #left most pulse exceeds left edge of trace\n #0-1 term includes one more index '-1' since fill_between fills from 0\n mask = array_fill_between(mask, 0-1, mask[0])\n \n\n if method == 2:\n # MASK METHOD 3: rev SR LATCH\n initial_window = np.where(srlatch_rev(signal, 0, height_th))[0]\n \n # MANUAL INCLUSION OF ADDITIONAL PULSE REGIONS, since srlatch_rev does not include the full pulse \n mask = initial_window\n\n for i in np.arange(len(initial_window)) - 1:\n if (initial_window[i + 1] - initial_window[i] < bins_right + bins_left):\n mask = array_fill_between(\n mask, initial_window[i], initial_window[i + 1])\n else:\n mask = array_fill_between(\n mask, initial_window[i], initial_window[i] + bins_right)\n mask = array_fill_between(\n mask, initial_window[i + 1] - bins_left, initial_window[i + 1])\n # right most pulse close to edge but doesn't exceed\n if mask[-1] + bins_right <= bins_final:\n mask = array_fill_between(\n mask, mask[-1], mask[-1] + bins_right)\n else:\n # right most pulse exceeds right edge of trace: include mask up to end of pulse\n # bins_final+1 term includes one more index since fill_between\n # fills up to bins_final\n mask = array_fill_between(mask, mask[-1], bins_final + 1)\n if mask[0] - bins_left >= 0: # left most pulse close to edge but doesn't exceed\n mask = array_fill_between(mask, mask[0] - bins_left, mask[0])\n else:\n # left most pulse exceeds left edge of trace\n # 0-1 term includes one more index '-1' since fill_between\n # fills from 0\n mask = array_fill_between(mask, 0 - 1, mask[0])\n\n # transforms index mask into boolean mask\n\n for i in np.arange(len(initial_window))-1:\n if (initial_window[i+1]-initial_window[i] < bins_right+bins_left):\n mask = array_fill_between(mask, initial_window[i], initial_window[i+1])\n else:\n mask = array_fill_between(mask, initial_window[i], initial_window[i]+bins_right)\n mask = array_fill_between(mask, initial_window[i+1]-bins_left, initial_window[i+1])\n \n if mask[-1]+bins_right <= bins_final: #right most pulse close to edge but doesn't exceed\n mask = array_fill_between(mask, mask[-1], mask[-1]+bins_right)\n else: \n #right most pulse exceeds right edge of trace: include mask up to end of pulse\n #bins_final+1 term includes one more index since fill_between fills up to bins_final\n mask = array_fill_between(mask, mask[-1], bins_final+1)\n if mask[0]-bins_left >= 0: #left most pulse close to edge but doesn't exceed\n mask = array_fill_between(mask, mask[0]-bins_left, mask[0])\n else: \n #left most pulse exceeds left edge of trace\n #0-1 term includes one more index '-1' since fill_between fills from 0\n mask = array_fill_between(mask, 0-1, mask[0])\n\n if method == 3:\n # MASK METHOD 4: SR LATCH (CONVENTIONAL)\n mask = srlatch(signal, 0, height_th)\n\n #transforms index mask into boolean mask\n\n mask_boolean = np.zeros(len(time), dtype=int)\n mask_boolean[mask] = 1\n mask = mask_boolean\n\n edges = np.diff(mask * 1) # left edge = 1, right edge = -1\n\n # find indices of left and right edges of pulses\n right_edges = np.array(np.where(edges < 0), dtype='int64').flatten()\n left_edges = np.array(np.where(edges > 0), dtype='int64').flatten()\n clamp = np.zeros(len(time))\n\n if (len(left_edges) > 0)and(len(right_edges > 0)):\n for i in np.arange(len(time)):\n if left_edges[0] <= i <= right_edges[-1]:\n clamp[i] = 1\n\n clamp = np.array(clamp, dtype='bool')\n mask = np.array(mask, dtype='bool')\n # print clamp,edges,left_edges,right_edges\n\n if Plot:\n plt.figure()\n plt.plot(time, signal)\n plt.hlines(height_th, time[0], time[1], linestyle='--')\n plt.plot(time, mask * np.max(signal), label='mask')\n plt.plot(time[1:], edges * np.max(signal), label='edges')\n plt.plot(time, (clamp & mask) * np.max(signal), label='clamp&mask')\n plt.scatter(time[(clamp & mask)], signal[\n (clamp & mask)], label='', color='red', marker='o')\n\n # else:\n # clamp = np.ones(len(time)) \n # print 'error: no index between first left and last right \\n{}'.format([left_edges, right_edges])\n # else:\n # clamp = np.ones(len(time))\n # print 'error: left or right index zero length \\n{}'.format([left_edges, right_edges])\n clamp = np.array(clamp,dtype='bool')\n mask = np.array(mask,dtype='bool')\n \n # print clamp,edges,left_edges,right_edges\n\n if Plot:\n plt.figure(figsize=(10,5))\n plt.plot(time,signal)\n plt.hlines(height_th,time[0],time[1],linestyle='--')\n plt.plot(time,mask*np.max(signal),label='mask')\n plt.plot(time[1:],edges*np.max(signal),label='edges')\n plt.plot(time,(clamp&mask)*np.max(signal),label='clamp&mask')\n plt.scatter(time[(clamp&mask)],signal[(clamp&mask)],label='',color='red',marker='o')\n plt.legend()\n\n return np.array([mask, clamp, edges, left_edges, right_edges])","def split(self, eccMap, patchName='patch00', cutStep=1, borderWidth=2, isplot=False):\r\n minMarker = localMin(eccMap, cutStep)\r\n\r\n plt.figure()\r\n plt.imshow(minMarker, vmin=0, interpolation='nearest')\r\n plt.colorbar()\r\n plt.title('markers 1')\r\n plt.show()\r\n\r\n minMarker = minMarker.astype(np.int32)\r\n selfArray = self.array.astype(np.int32)\r\n minMarker = minMarker + 1\r\n minMarker[minMarker == 1] = 0\r\n minMarker = minMarker + (-1 * (selfArray - 1))\r\n # minMarker: marker type for opencv watershed,\r\n # sure background = 1\r\n # unknow = 0\r\n # sure forgrand = 2,3,4... etc\r\n\r\n plt.figure()\r\n plt.imshow(minMarker, vmin=0, interpolation='nearest')\r\n plt.colorbar()\r\n plt.title('markers 2')\r\n plt.show()\r\n\r\n eccMapNor = (np.round(ia.array_nor(eccMap) * 255)).astype(np.uint8)\r\n eccMapRGB = cv2.cvtColor(eccMapNor, cv2.COLOR_GRAY2RGB)\r\n # eccMapRGB: image type for opencv watershed, RGB, [uint8, uint8, uint8]\r\n\r\n newLabel = cv2.watershed(eccMapRGB, minMarker)\r\n\r\n plt.figure()\r\n plt.imshow(newLabel, vmin=0, interpolation='nearest')\r\n plt.colorbar()\r\n plt.title('markers 3')\r\n plt.show()\r\n\r\n newBorder = np.zeros(newLabel.shape).astype(np.int)\r\n\r\n newBorder[newLabel == -1] = 1\r\n\r\n border = ni.binary_dilation(self.array).astype(np.int) - self.array\r\n\r\n border = newBorder + border\r\n\r\n border[border > 1] = 1\r\n\r\n border = sm.skeletonize(border)\r\n\r\n if borderWidth > 1:\r\n border = ni.binary_dilation(border, iterations=borderWidth - 1).astype(np.int8)\r\n\r\n newPatchMap = ni.binary_dilation(self.array).astype(np.int8) * (-1 * (border - 1))\r\n\r\n labeledNewPatchMap, patchNum = ni.label(newPatchMap)\r\n\r\n # if patchNum != np.amax(newLabel):\r\n # print 'number of patches: ', patchNum, '; number of local minimum:', np.amax(newLabel)\r\n # raise ValueError, \"Number of patches after splitting does not equal to number of local minimum!\"\r\n\r\n newPatchDict = {}\r\n\r\n for j in range(1, patchNum + 1):\r\n\r\n currPatchName = patchName + '.' + str(j)\r\n currArray = np.zeros(self.array.shape, dtype=np.int8)\r\n currArray[labeledNewPatchMap == j] = 1\r\n currArray = currArray * self.array\r\n\r\n if np.sum(currArray[:]) > 0:\r\n newPatchDict.update({currPatchName: Patch(currArray, self.sign)})\r\n\r\n if isplot:\r\n plt.figure()\r\n plt.subplot(121)\r\n plt.imshow(self.array, interpolation='nearest')\r\n plt.title(patchName + ': before split')\r\n plt.subplot(122)\r\n plt.imshow(labeledNewPatchMap, interpolation='nearest')\r\n plt.title(patchName + ': after split')\r\n\r\n return newPatchDict","def segement_divide(pts,step=0.10, offset_x=0.01, offset_y=0.0):\n\n # Select the x and y of the points\n n = len(pts)\n \n z = pts[0][2]\n \n points_plane = [] \n points_x = []\n paint_point = []\n\n for i in range(n):\n points_plane.append([pts[i][0], pts[i][1]])\n \n # Sorted the list according to x \n points_plane.sort(key=lambda x:x[0])\n\n # Segment the points according to x \n counter = 0 # Count the interval\n x_min = points_plane[0][0]\n x_max = points_plane[n-1][0]\n\n # The whole interval that needs to be divided\n upper = x_max + offset_x\n lower = x_min - offset_x\n lower_bound = lower\n \n # Set each segement's lower and upperbound\n while (lower_bound + step <= upper): \n # The break condition will be lower_bound > upper - step\n upper_bound = lower_bound + step\n\n # Find the index between lower bound and upper bound\n # First, find the index which x >= lower bound\n index = 0\n \n while (points_plane[index][0] < lower_bound): \n index = index + 1 # The index of the first point in the interval\n \n # If there is at least one point in the [lower_bound, upper_bound]\n if (points_plane[index][0] <= upper_bound): \n\n x_start = points_plane[index][0]\n y_max = points_plane[index][1]\n y_min = points_plane[index][1]\n \n while (points_plane[index][0] <= upper_bound): \n # The break condition will be x[index] > upper bound or index = n - 1\n # Compute the y max and y min in this interval\n \n if points_plane[index][1] > y_max: \n y_max = points_plane[index][1]\n\n if points_plane[index][1] < y_min:\n y_min = points_plane[index][1]\n \n if index < n - 1:\n index = index + 1\n else:\n break\n # The index of the last point in the interval, when index < n-1\n \n x_end = points_plane[index][0]\n\n paint_point.append([lower_bound,y_max+offset_y,z]) \n paint_point.append([lower_bound,y_min-offset_y,z])\n points_x.append([x_start, x_end])\n \n counter = counter + 1\n\n # Update interval\n lower_bound = upper_bound - offset_x\n \n # Deal with the last interval\n lower_bound_last = upper - step\n index_last = 0\n counter = counter + 1\n while ((index_last < n) and (points_plane[index_last][0] < lower_bound_last)): \n # The first point in the last interval\n index_last = index_last + 1\n \n if (index_last < n): \n # There is at least one point in the last interval\n x_start_last = points_plane[index_last][0]\n y_max_last = points_plane[index_last][1]\n y_min_last = points_plane[index_last][1]\n\n while ((index_last)<n) and (points_plane[index_last][0] <= upper):\n\n if points_plane[index_last][1] > y_max_last: \n y_max_last = points_plane[index_last][1]\n \n if points_plane[index_last][1] < y_min_last:\n y_min_last = points_plane[index_last][1]\n\n index_last = index_last + 1\n \n index_last = index_last - 1 # The index of the last point in the interval\n \n paint_point.append([lower_bound_last, y_max_last+offset_y, z])\n paint_point.append([lower_bound_last, y_min_last-offset_y, z])\n# paint_point.append([upper, y_max_last+offset_y, z])\n# paint_point.append([upper, y_min_last-offset_y, z])\n# return trans_to_end(paint_point)\n return paint_point","def reformatCoronalView4NeedleSegment(self, base, tip, ID=-1):\r\n #research\r\n profprint()\r\n for i in range(2): # workaround update problem\r\n if ID >=0:\r\n modelNode = slicer.util.getNode('vtkMRMLModelNode' + str(ID))\r\n polyData = modelNode.GetPolyData()\r\n nb = polyData.GetNumberOfPoints()\r\n base = [0, 0, 0]\r\n tip = [0, 0, 0]\r\n polyData.GetPoint(nb - 1, tip)\r\n polyData.GetPoint(0, base)\r\n a, b, c = tip[0] - base[0], tip[1] - base[1], tip[2] - base[2]\r\n \r\n sGreen = slicer.mrmlScene.GetNodeByID(\"vtkMRMLSliceNodeGreen\")\r\n if sGreen == None :\r\n sGreen = slicer.mrmlScene.GetNodeByID(\"vtkMRMLSliceNode3\")\r\n reformatLogic = slicer.vtkSlicerReformatLogic()\r\n #sGreen.SetSliceVisible(1)\r\n reformatLogic.SetSliceNormal(sGreen, 1, -a / b, 0)\r\n #reformatLogic.SetSliceOrigin(sGreen, base[0],base[1],base[2])#crashes\r\n m = sGreen.GetSliceToRAS()\r\n m.SetElement(0, 3, base[0])\r\n m.SetElement(1, 3, base[1])\r\n m.SetElement(2, 3, base[2])\r\n sGreen.Modified()","def identify_dbs(image):\n locations = {\"red\": Point(), \"green\": Point(), \"blue\": Point()}\n masks = {\"red\": [], \"green\": [], \"blue\": []}\n\n bridge = cv_bridge.CvBridge()\n image = bridge.imgmsg_to_cv2(image, \"bgr8\")\n hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)\n\n # upper and lower bounds for red\n # using python 3 bgr [0,0,188] = hsv [0, 255, 188]\n lower_red = numpy.array([0, 100, 100]) \n upper_red = numpy.array([10, 255, 255])\n masks[\"red\"] = cv2.inRange(hsv, lower_red, upper_red)\n\n # upper and lower bounds for green\n # using python 3 bgr [0,175,0] = hsv [60, 255, 175]\n lower_green = numpy.array([50, 100, 100]) \n upper_green = numpy.array([70, 255, 255])\n masks[\"green\"] = cv2.inRange(hsv, lower_green, upper_green)\n\n # upper and lower bounds for blue\n # using python 3 bgr [176, 0, 17] = hsv [123, 255, 176]\n lower_blue = numpy.array([113, 100, 100])\n upper_blue = numpy.array([133, 255, 255])\n masks[\"blue\"] = cv2.inRange(hsv, lower_blue, upper_blue)\n\n x, y, w, h = 0, 0, image.shape[1]//3, image.shape[0]\n\n for color, mask in masks.items():\n pixels = {\"left\": 0, \"middle\": 0, \"right\": 0}\n \n # define section of image to use for left, middle and right\n left = mask[y:y+h, x:x+w]\n middle = mask[y:y+h, x+w:x+w+w]\n right = mask[y:y+h, x+w+w:x+3*w]\n\n # count the number of pixels in each section\n pixels[\"left\"] = cv2.countNonZero(left)\n pixels[\"middle\"] = cv2.countNonZero(middle)\n pixels[\"right\"] = cv2.countNonZero(right)\n location = max(pixels, key=pixels.get)\n\n # map the relative position of the db (left, middle, right) to the correct Point()\n locations[color] = db_locations[location]\n \n return locations","def establecer_region(self, region, guess, delta_ppm=(1,1)): \r\n # obtengo los indices del centro del pico.\r\n xc, yc = self.encontrar_picos(guess, delta_ppm)\r\n # obtengo las coordenadas que determinan el rectangulo donde voy a\r\n # integrar. \r\n x_lims, y_lims = self.establecer_limites(xc, yc)\r\n \r\n xi,xf = x_lims\r\n yi,yf = y_lims\r\n spec = self.spec[yi:yf, xi:xf]\r\n ppmGridDir = self.ppmGridDir[yi:yf, xi:xf]\r\n ppmGridInd = self.ppmGridInd[yi:yf, xi:xf]\r\n \r\n \r\n n, m = region\r\n self.regiones[n][m] = Region(ppmGridDir, ppmGridInd, spec)","def region_region_checkerboard(self, **_):\n outputs: dict = {}\n\n if self.AGG_BY == \"zone\":\n agg = \"zone\"\n else:\n agg = \"region\"\n\n # List of properties needed by the plot, properties are a set of tuples and\n # contain 3 parts: required True/False, property name and scenarios required,\n # scenarios must be a list.\n properties = [(True, f\"{agg}_{agg}s_Net_Interchange\", self.Scenarios)]\n\n # Runs get_formatted_data within PlotDataStoreAndProcessor to populate PlotDataStoreAndProcessor dictionary\n # with all required properties, returns a 1 if required data is missing\n check_input_data = self.get_formatted_data(properties)\n\n if 1 in check_input_data:\n return MissingInputData()\n\n ncols, nrows = set_x_y_dimension(len(self.Scenarios))\n grid_size = ncols * nrows\n excess_axs = grid_size - len(self.Scenarios)\n\n mplt = PlotLibrary(nrows, ncols, squeeze=False, ravel_axs=True)\n fig, axs = mplt.get_figure()\n plt.subplots_adjust(wspace=0.02, hspace=0.4)\n max_flow_group = []\n Data_Out = []\n n = 0\n for scenario in self.Scenarios:\n rr_int = self[f\"{agg}_{agg}s_Net_Interchange\"].get(scenario)\n if shift_leapday:\n rr_int = adjust_for_leapday(rr_int)\n\n if self.AGG_BY != \"region\" and self.AGG_BY != \"zone\":\n agg_region_mapping = (\n self.region_mapping[[\"region\", self.AGG_BY]]\n .set_index(\"region\")\n .to_dict()[self.AGG_BY]\n )\n # Checks if keys all aggregate to a single value, this plot requires multiple values to work\n if len(set(agg_region_mapping.values())) == 1:\n return UnsupportedAggregation()\n rr_int = rr_int.reset_index()\n rr_int[\"parent\"] = rr_int[\"parent\"].map(agg_region_mapping)\n rr_int[\"child\"] = rr_int[\"child\"].map(agg_region_mapping)\n rr_int_agg = rr_int.groupby([\"parent\", \"child\"], as_index=True).sum()\n rr_int_agg.rename(columns={\"values\": \"flow (MW)\"}, inplace=True)\n rr_int_agg = rr_int_agg.loc[\n rr_int_agg[\"flow (MW)\"] > 0.01\n ] # Keep only positive flows\n rr_int_agg.sort_values(ascending=False, by=\"flow (MW)\")\n rr_int_agg = rr_int_agg / 1000 # MWh -> GWh\n\n data_out = rr_int_agg.copy()\n data_out.rename(\n columns={\"flow (MW)\": \"{} flow (GWh)\".format(scenario)}, inplace=True\n )\n\n max_flow = max(rr_int_agg[\"flow (MW)\"])\n rr_int_agg = rr_int_agg.unstack(\"child\")\n rr_int_agg = rr_int_agg.droplevel(level=0, axis=1)\n\n current_cmap = plt.cm.get_cmap()\n current_cmap.set_bad(color=\"grey\")\n\n axs[n].imshow(rr_int_agg)\n axs[n].set_xticks(np.arange(rr_int_agg.shape[1]))\n axs[n].set_yticks(np.arange(rr_int_agg.shape[0]))\n axs[n].set_xticklabels(rr_int_agg.columns)\n axs[n].set_yticklabels(rr_int_agg.index)\n axs[n].set_title(scenario.replace(\"_\", \" \"), fontweight=\"bold\")\n\n # Rotate the tick labels and set their alignment.\n plt.setp(\n axs[n].get_xticklabels(),\n rotation=90,\n ha=\"right\",\n rotation_mode=\"anchor\",\n )\n\n # Delineate the boxes and make room at top and bottom\n axs[n].set_xticks(np.arange(rr_int_agg.shape[1] + 1) - 0.5, minor=True)\n axs[n].set_yticks(np.arange(rr_int_agg.shape[0] + 1) - 0.5, minor=True)\n axs[n].grid(which=\"minor\", color=\"k\", linestyle=\"-\", linewidth=1)\n axs[n].tick_params(which=\"minor\", bottom=False, left=False)\n\n max_flow_group.append(max_flow)\n Data_Out.append(data_out)\n n += 1\n\n # Remove extra axes\n mplt.remove_excess_axs(excess_axs, grid_size)\n\n cmap = cm.inferno\n norm = mcolors.Normalize(vmin=0, vmax=max(max_flow_group))\n cax = plt.axes([0.90, 0.1, 0.035, 0.8])\n fig.colorbar(\n cm.ScalarMappable(norm=norm, cmap=cmap),\n cax=cax,\n label=\"Total Net Interchange [GWh]\",\n )\n plt.xlabel(\"To Region\", color=\"black\", rotation=\"horizontal\", labelpad=40)\n plt.ylabel(\"From Region\", color=\"black\", rotation=\"vertical\", labelpad=40)\n\n data_table_out = pd.concat(Data_Out, axis=1)\n save_figures = self.figure_folder.joinpath(f\"{self.AGG_BY}_transmission\")\n fig.savefig(\n save_figures.joinpath(\"region_region_checkerboard.svg\"),\n dpi=600,\n bbox_inches=\"tight\",\n )\n data_table_out.to_csv(save_figures.joinpath(\"region_region_checkerboard.csv\"))\n\n outputs = DataSavedInModule()\n return outputs","def betas_middle_slice_graph(betas_4d):\n\tplt.imshow(betas_4d[:, :, 16, 0], interpolation='nearest', cmap='gray')\n\tplt.title('Middle Slice Beta(Gain)')\n\tplt.colorbar()\n\tplt.savefig('middle_slice_gain.png')\n\tplt.close()\n\tplt.imshow(betas_4d[:, :, 16, 1], interpolation='nearest', cmap='gray')\n\tplt.title('Middle Slice Beta(Loss)')\n\tplt.colorbar()\n\tplt.savefig('middle_slice_loss.png')\n\tplt.close()","def find_chart():\r\n ###############################################\r\n # Read values of S/N\r\n sn = np.loadtxt(outtable, usecols=(14,))\r\n xs, ys = np.loadtxt(outtable, usecols=(1, 2)).T\r\n specs = np.loadtxt(outtable, usecols=(0,), dtype=str)\r\n ###############################################\r\n # Find good (and bad) regions according to S/N\r\n good = np.where(((~np.isnan(sn)) & (sn >= sn_cut)))[0]\r\n bad = np.where((sn < sn_cut))[0]\r\n ###############################################\r\n # Filter arrays for S/N\r\n sn = sn[good]\r\n xs = xs[good]\r\n ys = ys[good]\r\n specs = specs[good].tolist()\r\n specs = [x.replace(\".fits\", \"\")[1:] for x in specs]\r\n ###############################################\r\n # Set limits for the plot\r\n norm = Normalize(0, 1)\r\n ###############################################\r\n # Set colormap\r\n # cmap = brewer2mpl.get_map('YlGnBu', 'sequential', 5).mpl_colormap\r\n # Produces a collection of polygons with colors according to S/N values\r\n coll = PolyCollection(polygons_bins[good], array=np.ones_like(sn),\r\n cmap=\"gray\", edgecolors='0.5', norm=norm)\r\n ###############################################\r\n # Initiate figure and axis for matplotlib\r\n fig = plt.figure(figsize=(6.25, 6))\r\n gs = gridspec.GridSpec(1, 1)\r\n gs.update(left=0.08, right=0.985, bottom=0.08, top=0.985, hspace=0.05,\r\n wspace=0.06)\r\n ax = plt.subplot(gs[0])\r\n ###############################################\r\n # Draw the polygons\r\n draw_map(fig, ax, coll)\r\n ###############################################\r\n # Add contours according to V-band image\r\n draw_contours(\"vband\", fig, ax)\r\n ###############################################\r\n for x, y, spec in zip(xs, ys, specs):\r\n ax.text(x, y, spec, fontsize=10)\r\n # Write labels\r\n xylabels(ax)\r\n ##############################################\r\n # Save the figure\r\n plt.show()\r\n plt.savefig(\"figs/find_chart.pdf\")\r\n return","def draw_laser_ranges():\n NUM_RANGES = len(D.ranges) # should be 360\n if False: #for easy commenting out...\n for angle in range(NUM_RANGES):\n print angle, \":\", D.ranges[angle] \n \n # helpful starting points, perhaps:\n # add line to the ranges image, \"D.image\"\n #cv.Line(D.image, (42,100), (100,42), cv.RGB(255, 0, 0), 1) # 1 == thickness\n # add dots to image being used to compute the Hough tr. \"D.hough\"\n # cv.Line(D.hough, (42,42), (42,42), 255, 2) # 1 == thickness\n for angle in range(NUM_RANGES):\n point = (CENTER + int(0.2*D.ranges[angle]*sin(radians(angle))), CENTER + int(0.2*D.ranges[angle]*cos(radians(angle))))\n cv.Line(D.image, (CENTER,CENTER), point, cv.RGB(255, 0 , 0), 1)\n cv.Line(D.hough, point, point, 255, 2) \n\n return","def opencv_watershed(masked, mask) -> JSON_TYPE:\n # For code and detailed explanation see:\n # http://datahacker.rs/007-opencv-projects-image-segmentation-with-watershed-algorithm/\n threshold: int = 30\n gray = cv2.cvtColor(masked, cv2.COLOR_RGB2GRAY)\n ret, thresh_img = cv2.threshold(gray, threshold, 255, cv2.THRESH_BINARY)\n # Noise removal\n kernel = np.ones((3), np.uint8)\n opening_img = cv2.morphologyEx(thresh_img, cv2.MORPH_OPEN, kernel, iterations=9)\n # Noise removal\n closing_img = cv2.morphologyEx(thresh_img, cv2.MORPH_CLOSE, kernel, iterations=4)\n dist_transform = cv2.distanceTransform(255 - closing_img, cv2.DIST_L2, 3)\n local_max_location = peak_local_max(dist_transform, min_distance=1, indices=True)\n\n n_increases: int = 0\n while local_max_location.shape[0] < 30 and n_increases < 15:\n threshold += 20\n ret, thresh_img = cv2.threshold(gray, threshold, 255, cv2.THRESH_BINARY)\n # Noise removal\n kernel = np.ones((3), np.uint8)\n opening_img = cv2.morphologyEx(thresh_img, cv2.MORPH_OPEN, kernel, iterations=9)\n # Noise removal\n closing_img = cv2.morphologyEx(thresh_img, cv2.MORPH_CLOSE, kernel, iterations=4)\n dist_transform = cv2.distanceTransform(255 - closing_img, cv2.DIST_L2, 3)\n local_max_location = peak_local_max(dist_transform, min_distance=1, indices=True)\n n_increases += 1\n # Reset threshold\n threshold = 30\n\n num_clusters: int = 30\n if n_increases >= 15:\n num_clusters = local_max_location.shape[0]\n kmeans = KMeans(n_clusters=num_clusters)\n # If local_max_location size is 0, return 0 predictions\n if not local_max_location.size:\n return {\n \"count\": 0\n }\n kmeans.fit(local_max_location)\n local_max_location = kmeans.cluster_centers_.copy()\n # Kmeans is returning a float data type so we need to convert it to an int. \n local_max_location = local_max_location.astype(int)\n dist_transform_copy = dist_transform.copy()\n for i in range(local_max_location.shape[0]):\n cv2.circle(dist_transform_copy, (local_max_location[i][1], local_max_location[i][0]), 5, 255)\n # markers = np.zeros_like(dist_transform)\n ret, sure = cv2.threshold(dist_transform, 0.01*dist_transform.max(), 255, 0)\n sure = np.uint8(sure)\n ret, markers = cv2.connectedComponents(sure)\n labels = np.arange(kmeans.n_clusters)\n markers[local_max_location[:,0], local_max_location[:,1]] = labels + 1\n # Convert all local markers to an integer. This because cluster centers will be float numbers. \n markers = markers.astype(int)\n markers_copy = markers.copy()\n index_non_zero_markers = np.argwhere(markers != 0)\n markers_copy = markers_copy.astype(np.uint8)\n font = cv2.FONT_HERSHEY_SIMPLEX\n for i in range(index_non_zero_markers.shape[0]):\n string_text = str(markers[index_non_zero_markers[i][0], index_non_zero_markers[i][1]])\n cv2.putText(markers_copy, string_text, (index_non_zero_markers[i][1], index_non_zero_markers[i][0]), font, 1, 255)\n markers = markers.astype(np.int32)\n segmented = cv2.watershed(masked, markers)\n count_segments(markers)\n #return {\n # \"count\": local_max_location.shape[0]\n #}\n return {\n \"count\": count_segments(markers),\n }","def SplitGap(data,gapsize,medwin,fluxdiff):\n \n # defining new empty lists and stuff\n pcount=0\n istamps=[]\n outData={}\n \n data['x'].mask = data['UnMasked']\n data['y'].mask = data['UnMasked']\n data['yerr'].mask = data['UnMasked']\n \n # median smoothing the lightcurve\n mvavg1 = movingMedian(data['y'],medwin)\n mvavg1 = num.append(mvavg1,mvavg1[-1])\n mvavg1 = data['y']\n # first derivative of smoothed lightcurve\n diff1 = num.diff(mvavg1)\n diff1 = num.hstack((diff1,diff1[-1]))\n \n # second derivative of smoothed lightcurve\n diff2 = num.diff(diff1)\n diff2 = num.hstack((diff2[-1],diff2))\n\n # compute ourlier resistant sigma\n sig = compute1Sigma(diff1)\n #pylab.plot(diff1,'g.')\n #pylab.plot([0,6000],[5*sig,5*sig],'k-')\n #pylab.plot([0,6000],[3*sig,3*sig],'k-')\n #pylab.plot([0,6000],[1*sig,1*sig],'k-')\n #pylab.show()\n\n # The grand master loop >=}\n # to make portion slices\n for i in range(len(data['x'])-1):\n dt = data['x'][i+1]- data['x'][i]\n j1 = max(0,i-medwin)\n j2 = i + medwin\n if pcount == 0:\n i0 = 0\n if pcount > 0:\n i0 = i1+1\n if dt > gapsize:\n i1 = i\n istamps.append([i0,i1])\n pcount += 1\n #if num.abs(diff1[i]) > 5*sig:\n #i1 = i\n #istamps.append([i0,i1])\n #pcount += 1\n #print num.abs(diff1[i]/data['y'][i]), diff1[i], data['y'][i], diff1[i+1], data['y'][i+1]\n #print i, ' test flux gap'\n i1 = i+1\n istamps.append([i0,i1])\n \n \n \n if data['bool']==False:\n # Applying slices\n for j in range(len(istamps)):\n #print istamps[j][0], istamps[j][1]\n outData['portion' + str(j+1)] = {'kid':data['kid'],'x':data['x'][istamps[j][0]:istamps[j][1]+1], 'y':data['y'][istamps[j][0]:istamps[j][1]+1], 'yerr':data['yerr'][istamps[j][0]:istamps[j][1]+1],'UnMasked':data['UnMasked'][istamps[j][0]:istamps[j][1]+1],'bool':False}\n else:\n # Applying slices\n for j in range(len(istamps)):\n #print istamps[j][0], istamps[j][1]\n outData['portion' + str(j+1)] = {'kid':data['kid'],'x':data['x'][istamps[j][0]:istamps[j][1]+1], 'y':data['y'][istamps[j][0]:istamps[j][1]+1], 'yerr':data['yerr'][istamps[j][0]:istamps[j][1]+1], 'TransitMask':data['TransitMask'][istamps[j][0]:istamps[j][1]+1],'UnMasked':data['UnMasked'][istamps[j][0]:istamps[j][1]+1],'bool':True}\n \n return outData","def segment_by_shape(self, dt, criterion):\n enumerate_crit = Criterion(\n 'patterns', criterion.column_name+'_derivatives_patterns_clusters',\n 'enumerate')\n return self.segment_by_enumerate(dt, enumerate_crit)","def isDivision(event,buff):\n index,diff,label = event\n label = label[0]\n if diff<0:\n return False,[]\n img_before = np.copy(buff[:,:,index-1])\n img_after = np.copy(buff[:,:,index])\n mask_after = (img_after==label).astype(np.uint8)\n nb_elts_after = np.amax(img_after)\n kernel = np.ones((7,7),np.uint8)\n neighbouring_mask = cv2.dilate(mask_after,kernel,iterations=8)\n\n \n new_map = np.multiply(img_after,neighbouring_mask.astype(np.uint8)) \n #Removing the element we are currently looking at\n new_map[img_after==label]=0\n possible_candidates = []\n for i in range(nb_elts_after):\n if np.any(new_map==i+1):\n possible_candidates.append(i+1)\n #Computes the area of the cells and compares them\n size_cell_after = np.count_nonzero(img_after==label)\n match = [] #lists the ratios sizeAfter/sizeBefore for possible matches\n for vals in possible_candidates:\n size_before = np.count_nonzero(img_before==vals)\n size_other_cell = np.count_nonzero(img_after==vals)\n size_after = size_cell_after + size_other_cell\n ratio = float(size_after)/float(size_before)\n if ratio>0.8 and ratio<1.2:\n match.append((vals,abs(1-ratio)))\n if len(match)==0:\n return False,[]\n if len(match)>1:\n #Several matches, so pick the best\n values = [y for x,y in match]\n result_label,osef = match[np.argmin(values)]\n else:\n result_label, osef = match[0]\n return True,result_label","def cleanup_regions(self, timestamp, bid, ofr):\n regions = []\n\n for region in self.regions:\n if not region.can_delete(timestamp, bid, ofr):\n regions.append(region)\n\n # replace the regions list\n self.regions = regions","def highlight_rare_blocks(bv, threshold=1):\n if no_coverage_warn():\n return\n rare_blocks = covdb.get_rare_blocks(threshold)\n rare_color = HighlightStandardColor.RedHighlightColor\n highlight_set(rare_blocks, rare_color)\n log.log_info(\"[*] Found %d rare blocks (threshold: %d)\" %\n (len(rare_blocks), threshold))\n for block in rare_blocks:\n log.log_info(\" 0x%x\" % block)","def border_analyze_vertical(mask, borders, min_segment_width=5, max_border_width=0.4):\n max_border_width = mask.shape[1] * max_border_width\n if len(borders) == 0: return False\n left_most = 0\n right_most = mask.shape[1] - 1\n # middle_borders = [border for border in borders if (left_most in border or right_most in border) and abs(border[0]-border[1])>3 ]\n # if len(middle_borders)==0:return False\n slice_start = 0\n # segs_by_middle_borders=[]\n block_widths = []\n for v_border in borders[::-1]:\n border_start = v_border[1]\n border_stop = v_border[0]\n if border_start == left_most:\n slice_start = border_stop\n elif border_stop == right_most:\n # mask_slice=mask[slice_start:border_start]\n block_widths.append(border_start - slice_start)\n # segs_by_middle_borders.appen(mask_slice)\n slice_start = border_stop\n elif border_stop - border_start >= 1:\n # mask_slice = mask[slice_start,border_start]\n if border_stop - border_start < max_border_width:\n block_widths.append(border_start - slice_start)\n # segs_by_middle_borders.appen(mask_slice)\n slice_start = border_stop\n if slice_start < right_most:\n block_widths.append(mask.shape[1] - slice_start)\n # segs_by_middle_borders.append(mask[slice_start:])\n\n block_widths = [w for w in block_widths if w > min_segment_width]\n # print('block widths')\n # print(block_widths)\n # print('block widths deviation' )\n # print(np.std(block_widths))\n # print('block heights dev/mean' )\n # print(np.std(block_widths)/np.mean(block_widths))\n\n if len(block_widths) < 2: return False\n return segment_analyzer(block_widths)","def fix_half_inning(self, half_inning):\n outs = 0\n active_runners = []\n for atbat in half_inning:\n self.hold_runners(active_runners, atbat)\n\n active_runners = [r for r in atbat.runners\n if not r.out and r.end != 4]\n outs = atbat.outs","def highlight(self,screen,midpos = (800,450)):\n posInt = self.getIntPos()\n posInt = getOffsetPos(posInt,midpos)\n pygame.draw.circle(screen, [max(0,tmp - (10 - self.timeDriving%10)*10) for tmp in self.colour], \n posInt, int(10+ (self.timeDriving%10 )),2)\n pygame.draw.circle(screen, self.colour, posInt, int(20+ (self.timeDriving%10 )),2)\n pygame.draw.circle(screen, [max(0,tmp - (self.timeDriving%10)*10) for tmp in self.colour], \n posInt, int(30+ (self.timeDriving%10 )),2)","def remove_blocks(draft):\n for symbol in draft.Blocks:\n if symbol.Name in blocks_to_delete:\n print(\"[-] %s, \\tdeleted\" % symbol.Name)\n symbol.delete()\n\n # for ball in draft.ActiveSheet.Balloons:\n if draft.Balloons:\n for ball in draft.Balloons:\n if ball.BalloonType == 7: # type 7 filter the triangle balloons.\n print(\"[-] %s, \\tdeleted\" % ball.Name)\n ball.Delete()\n else:\n pass","def RegionGrowingSegmentation(image, kernel_sigma, seed_row, seed_col, Niter, sim_threshold): \n \n if kernel_sigma >= 1:\n image = Denoising(image, kernel_sigma);\n \n image = image / image.max();\n nr, nc = image.shape;\n mask_old = np.zeros(image.shape, dtype = bool);\n mask_old[seed_row, seed_col] = True;\n \n sim_pos = [(0, 0), (0, 1), (0, 2), (1, 0), (1, 1), (1, 2), (2, 0), (2, 1), (2, 2)];\n nb_pos = [(-1, -1), (-1, 0), (-1, 1), (0, -1), (0, 0), (0, 1), (1, -1), (1, 0), (1, 1)];\n \n for iter_no in range(Niter):\n mask = np.zeros(image.shape, dtype = bool);\n for row_no in range(1, nr - 1):\n for col_no in range(1, nc - 1):\n if mask_old[row_no, col_no] != 1:\n continue;\n \n nb = image[row_no - 1:row_no + 2, col_no - 1:col_no + 2]; \n region_mean = image[mask_old].mean();\n if region_mean == 1:\n mask[row_no - 1:row_no + 2, col_no - 1:col_no + 2] = 1; \n continue;\n \n similarity = np.exp(-(nb - region_mean) ** 2); \n for el_no in range(len(nb_pos)):\n delta_row, delta_col = nb_pos[el_no];\n row_sim, col_sim = sim_pos[el_no];\n if similarity[row_sim, col_sim] < sim_threshold:\n continue;\n \n mask[row_no + delta_row, col_no + delta_col] = 1;\n \n if mask_old.sum() == mask.sum():\n break; \n \n mask_old = mask;\n \n return mask;","def highlight_set(addr_set, color=None, bv=None, start_only=True):\n if bv is not None:\n binary_view = bv\n else:\n if gbv is None:\n print(\"[!] To use manually, pass in a binary view (bv=binary_view), or set bncov.gbv first\")\n return\n binary_view = gbv\n if start_only:\n get_blocks = binary_view.get_basic_blocks_starting_at\n else:\n get_blocks = binary_view.get_basic_blocks_at\n for addr in addr_set:\n blocks = get_blocks(addr)\n if len(blocks) >= 1:\n for block in blocks:\n if covdb is not None:\n if addr in covdb.block_dict:\n count = len(covdb.block_dict[addr])\n else:\n count = 0\n highlight_block(block, count, color)\n else:\n highlight_block(block, 0, color)\n else:\n if get_blocks == binary_view.get_basic_blocks_starting_at:\n containing_blocks = binary_view.get_basic_blocks_at(addr)\n if containing_blocks:\n log.log_warn(\"[!] No blocks start at 0x%x, but %d blocks contain it:\" %\n (addr, len(containing_blocks)))\n for i, block in enumerate(containing_blocks):\n log.log_info(\"%d: 0x%x - 0x%x in %s\" % (i, block.start, block.end, block.function.name))\n else:\n log.log_warn(\"[!] No blocks contain address 0x%x; check the address is inside a function.\" % addr)\n else: # get_blocks is binary_view.get_basic_blocks_at\n log.log_warn(\"[!] No blocks contain address 0x%x; check the address is inside a function.\" % addr)","def populate_region(mask, layer_params):\n\n from .speedups import (\n NEW_CELL_MASK, CAN_OSCILLATE_MASK, INCLUDE_VIOLATIONS_MASK)\n\n border = ndimage.maximum_filter(mask, size=3, mode='wrap') ^ mask\n interior = ndimage.minimum_filter(mask, size=3, mode='wrap')\n gen_mask = mask * (\n NEW_CELL_MASK |\n CAN_OSCILLATE_MASK |\n INCLUDE_VIOLATIONS_MASK\n ) + border * (\n INCLUDE_VIOLATIONS_MASK\n )\n board = np.zeros(mask.shape, dtype=np.uint16)\n foreground = np.zeros(mask.shape, dtype=bool)\n background = np.zeros(mask.shape, dtype=bool)\n background_color = np.zeros(mask.shape, dtype=bool)\n seeds = None\n max_period = 1\n\n for layer in layer_params:\n if not isinstance(layer, dict):\n raise ValueError(\n \"'layer_params' should be a list of parameter dictionaries.\")\n layer = _fix_random_values(layer)\n old_board = board.copy()\n gen_mask0 = gen_mask.copy()\n interior = ndimage.minimum_filter(\n gen_mask & NEW_CELL_MASK > 0, size=3, mode='wrap')\n color = COLORS.get(layer.get('color'), 0)\n\n fence_frac = layer.get('fences', 0.0)\n if fence_frac > 0:\n fences = build_fence(gen_mask & speedups.NEW_CELL_MASK)\n fences *= coinflip(fence_frac, fences.shape)\n gen_mask &= ~(fences * (NEW_CELL_MASK | CAN_OSCILLATE_MASK))\n board += fences.astype(np.uint16) * CellTypes.wall\n\n spawners = layer.get('spawners', 0)\n if spawners > 0:\n _mask = (gen_mask0 & NEW_CELL_MASK > 0) & interior\n new_cells = _mask & coinflip(spawners, board.shape)\n if not new_cells.any() and _mask.any():\n i, j = np.nonzero(_mask)\n k = get_rng().choice(len(i)) # ensure at least one spawner\n new_cells[i[k], j[k]] = True\n gen_mask[new_cells] ^= NEW_CELL_MASK\n board[new_cells] = CellTypes.spawner + color\n\n tree_lattice = layer.get('tree_lattice')\n # Create a lattice of trees that are spread throughout the region\n # such that every empty cell touches one (and only one) tree\n # (modulo edge effects).\n # Such a lattice tends to make the resulting board very chaotic.\n # Note that this will disrupt any pre-existing patterns.\n if tree_lattice is not None:\n if not isinstance(tree_lattice, dict):\n tree_lattice = {}\n h, w = board.shape\n stagger = tree_lattice.get('stagger', True)\n spacing = float(tree_lattice.get('spacing', 5))\n if not stagger:\n new_cells = _make_lattice(h, w, spacing, spacing, 0)\n elif spacing <= 3:\n new_cells = _make_lattice(h, w, 3, 3, 1)\n elif spacing == 4:\n new_cells = _make_lattice(h, w, 10, 1, 3)\n elif spacing == 5:\n new_cells = _make_lattice(h, w, 13, 1, 5)\n else:\n # The following gets pretty sparse.\n new_cells = _make_lattice(h, w, 6, 3, 3)\n\n new_cells &= gen_mask & NEW_CELL_MASK > 0\n board[new_cells] = CellTypes.tree + color\n\n period = 1\n if 'pattern' in layer:\n pattern_args = layer['pattern'].copy()\n period = pattern_args.get('period', 1)\n if period == 1:\n gen_mask2 = gen_mask & ~CAN_OSCILLATE_MASK\n pattern_args.update(period=max_period, osc_bonus=0)\n elif period == 0:\n gen_mask2 = gen_mask & ~INCLUDE_VIOLATIONS_MASK\n pattern_args.update(period=max_period, osc_bonus=0)\n elif period < max_period:\n raise ValueError(\n \"Periods for sequential layers in a region must be either 0, 1,\"\n \" or at least as large as the largest period in prior layers.\")\n else:\n gen_mask2 = gen_mask\n max_period = period\n\n board = _gen_pattern(board, gen_mask2, seeds, **pattern_args)\n\n # We need to update the mask for subsequent layers so that they\n # do not destroy the pattern in this layer.\n # First get a list of board states throughout the oscillation cycle.\n boards = [board]\n for _ in range(1, max_period):\n boards.append(speedups.advance_board(boards[-1]))\n non_empty = np.array(boards) != 0\n still_cells = non_empty.all(axis=0)\n osc_cells = still_cells ^ non_empty.any(axis=0)\n # Both still life cells and oscillating cells should disallow\n # any later changes. We also want to disallow changes to the cells\n # that are neighboring the oscillating cells, because any changes\n # there would propogate to the oscillating cells at later time\n # steps.\n # Note that it doesn't really matter whether the oscillating mask\n # is set for the currently oscillating cells, because we're not\n # checking for violations in them anyways, and we don't allow any\n # changes that would affect them.\n osc_neighbors = ndimage.maximum_filter(osc_cells, size=3, mode='wrap')\n gen_mask[osc_cells] &= ~(NEW_CELL_MASK | INCLUDE_VIOLATIONS_MASK)\n gen_mask[still_cells | osc_neighbors] &= ~(NEW_CELL_MASK | CAN_OSCILLATE_MASK)\n\n new_mask = board != old_board\n life_mask = ((board & CellTypes.alive) > 0) & new_mask\n board += color * new_mask * life_mask\n # The seeds are starting points for the next layer of patterns.\n # This just makes the patterns more likely to end up close together.\n seeds = ((board & CellTypes.alive) > 0) & mask\n\n new_mask = board != old_board\n\n movable_walls = layer.get('movable_walls', 0)\n if movable_walls > 0:\n new_cells = coinflip(movable_walls, board.shape) * new_mask\n new_cells *= (board & ~CellTypes.rainbow_color) == CellTypes.wall\n board += new_cells * CellTypes.movable\n\n movable_trees = layer.get('movable_trees', 0)\n if movable_trees > 0:\n new_cells = coinflip(movable_trees, board.shape) * new_mask\n new_cells *= (board & ~CellTypes.rainbow_color) == CellTypes.tree\n board += new_cells * CellTypes.movable\n\n hardened_life = layer.get('hardened_life', 0)\n if hardened_life > 0:\n new_cells = coinflip(hardened_life, board.shape) * new_mask\n new_cells *= (board & ~CellTypes.rainbow_color) == CellTypes.life\n board -= new_cells * CellTypes.destructible\n\n buffer_size = layer.get('buffer_zone', 0) * 2 + 1\n life_cells = board & CellTypes.alive > 0\n buf = ndimage.maximum_filter(life_cells, size=buffer_size, mode='wrap')\n gen_mask[buf] &= ~NEW_CELL_MASK\n\n target = layer.get('target', 'board')\n if target == 'board':\n foreground[new_mask] = True\n if period > 0:\n background[new_mask] = True\n elif target == 'goals':\n background[new_mask] = True\n background_color[new_mask] = True\n # Make sure to add walls and such to the foreground\n foreground[new_mask & (board & CellTypes.alive == 0)] = True\n elif target == 'both':\n foreground[new_mask] = True\n if period > 0:\n background[new_mask] = True\n background_color[new_mask] = True\n else:\n raise ValueError(\"Unexpected value for 'target': %s\" % (target,))\n\n fountains = layer.get('fountains', 0)\n if fountains > 0:\n new_cells = coinflip(fountains, board.shape)\n new_cells *= gen_mask & NEW_CELL_MASK > 0\n neighbors = ndimage.maximum_filter(new_cells, size=3, mode='wrap')\n neighbors *= gen_mask & NEW_CELL_MASK > 0\n gen_mask[neighbors] = INCLUDE_VIOLATIONS_MASK\n if buffer_size > 1:\n buf = ndimage.maximum_filter(neighbors, size=buffer_size, mode='wrap')\n gen_mask[buf] &= ~NEW_CELL_MASK\n board[neighbors] = CellTypes.wall + color\n board[new_cells] = CellTypes.fountain + color\n foreground[new_cells] = True\n background[neighbors] = True\n background_color[neighbors] = True\n\n goals = board.copy()\n board *= foreground\n goals *= background\n goals &= ~CellTypes.spawning\n goals &= ~(CellTypes.rainbow_color * ~background_color)\n\n return board, goals","def get_valid_regions(self):\n pass","def do_full(self, image,hsv,upper,lower,debug=False):\n single_color_img = self.extract_single_color_range(image,hsv,lower,upper)\n if debug:\n # cv2.imshow('single_color_img',single_color_img)\n cv2.imwrite('debug_pics/single_color_img.jpg',single_color_img)\n single_channel = self.threshold_image(single_color_img,debug)\n if debug:\n # cv2.imshow('single_channel',single_channel)\n cv2.imwrite('debug_pics/single_channel.jpg',single_channel)\n cont,hierarchy = self.contours(single_channel,debug)\n\n if debug:\n for i,cnt in enumerate(cont):\n cv2.drawContours(single_channel,cont,i,(0,0,255),2)\n if debug: cv2.imwrite('debug_pics/contours.jpg',single_channel) #cv2.imshow('contours',single_channel)\n\n return self.get_bricks(cont)","def segment(data):","def find_sync_light_onsets(sync_light, invert=True, fixmissing=False):\n # -- Find changes in synch light --\n sync_light_diff = np.diff(sync_light, prepend=0)\n if invert:\n sync_light_diff = -sync_light_diff\n sync_light_diff[sync_light_diff < 0] = 0\n sync_light_threshold = 0.2*sync_light_diff.max()\n sync_light_onset = sync_light_diff > sync_light_threshold\n\n\n # -- Find period of sync_light_onset --\n sync_light_onset_ind = np.where(sync_light_onset)[0]\n sync_light_onset_diff = np.diff(sync_light_onset_ind) # In units of frames\n expected_onset_period = np.median(sync_light_onset_diff) # In units of (float) frames\n\n # -- Remove repeated onsets --\n onset_freq_upper_threshold = int(1.5 * expected_onset_period)\n onset_freq_lower_threshold = int(0.5 * expected_onset_period)\n repeated_onsets = sync_light_onset_diff < onset_freq_lower_threshold\n repeated_onsets_ind = np.where(repeated_onsets)[0]\n fixed_sync_light_onset = sync_light_onset.copy()\n fixed_sync_light_onset[sync_light_onset_ind[repeated_onsets_ind+1]] = False\n\n # -- Fix missing onsets --\n if fixmissing:\n missing_next_onsets = sync_light_onset_diff > onset_freq_upper_threshold\n missing_next_onsets_ind = np.where(missing_next_onsets)[0]\n for indm, missing_onset_ind in enumerate(missing_next_onsets_ind):\n onset_diff = sync_light_onset_diff[missing_onset_ind]\n n_missing = int(np.round(onset_diff / expected_onset_period))-1\n #print(n_missing)\n last_onset_ind = sync_light_onset_ind[missing_onset_ind]\n next_onset_ind = sync_light_onset_ind[missing_onset_ind+1]\n period_missing = (next_onset_ind - last_onset_ind)//(n_missing+1)\n new_onset_inds = last_onset_ind + np.arange(1, n_missing+1)*period_missing\n #print([last_onset_ind, next_onset_ind])\n #print(new_onset_inds)\n fixed_sync_light_onset[new_onset_inds] = True\n\n return fixed_sync_light_onset","def ibd_segments(\n self,\n *,\n within=None,\n between=None,\n max_time=None,\n min_span=None,\n store_pairs=None,\n store_segments=None,\n ):\n return self.tables.ibd_segments(\n within=within,\n between=between,\n max_time=max_time,\n min_span=min_span,\n store_segments=store_segments,\n store_pairs=store_pairs,\n )","def segement_divide(pts,step=0.10, offset_x=0.01, offset_y=0.01):\n\n # Select the x and y of the points\n n = len(pts)\n \n z = 0.0\n \n points_plane = [] \n points_x = []\n paint_point = []\n\n for i in range(n):\n points_plane.append([pts[i][0], pts[i][1]])\n \n # Sorted the list according to x \n points_plane.sort(key=lambda x:x[0])\n\n # Segment the points according to x \n counter = 0 # Count the interval\n x_min = points_plane[0][0]\n x_max = points_plane[n-1][0]\n\n # The whole interval that needs to be divided\n upper = x_max + offset_x\n lower = x_min - offset_x\n lower_bound = lower\n \n # Set each segement's lower and upperbound\n while (lower_bound + step <= upper): \n # The break condition will be lower_bound > upper - step\n upper_bound = lower_bound + step\n\n # Find the index between lower bound and upper bound\n # First, find the index which x >= lower bound\n index = 0\n \n while (points_plane[index][0] < lower_bound): \n index = index + 1 # The index of the first point in the interval\n \n # If there is at least one point in the [lower_bound, upper_bound]\n if (points_plane[index][0] <= upper_bound): \n\n x_start = points_plane[index][0]\n y_max = points_plane[index][1]\n y_min = points_plane[index][1]\n \n while (points_plane[index][0] <= upper_bound): \n # The break condition will be x[index] > upper bound or index = n - 1\n # Compute the y max and y min in this interval\n \n if points_plane[index][1] > y_max: \n y_max = points_plane[index][1]\n\n if points_plane[index][1] < y_min:\n y_min = points_plane[index][1]\n \n if index < n - 1:\n index = index + 1\n else:\n break\n # The index of the last point in the interval, when index < n-1\n \n x_end = points_plane[index][0]\n\n paint_point.append([lower_bound,y_max+offset_y,z]) \n paint_point.append([lower_bound,y_min-offset_y,z])\n points_x.append([x_start, x_end])\n \n counter = counter + 1\n\n # Update interval\n lower_bound = upper_bound - offset_x\n \n # Deal with the last interval\n lower_bound_last = upper - step\n index_last = 0\n counter = counter + 1\n while ((index_last < n) and (points_plane[index_last][0] < lower_bound_last)): \n # The first point in the last interval\n index_last = index_last + 1\n \n if (index_last < n): \n # There is at least one point in the last interval\n x_start_last = points_plane[index_last][0]\n y_max_last = points_plane[index_last][1]\n y_min_last = points_plane[index_last][1]\n\n while ((index_last)<n) and (points_plane[index_last][0] <= upper):\n\n if points_plane[index_last][1] > y_max_last: \n y_max_last = points_plane[index_last][1]\n \n if points_plane[index_last][1] < y_min_last:\n y_min_last = points_plane[index_last][1]\n\n index_last = index_last + 1\n \n index_last = index_last - 1 # The index of the last point in the interval\n \n paint_point.append([lower_bound_last, y_max_last+offset_y, z])\n paint_point.append([lower_bound_last, y_min_last-offset_y, z])\n# paint_point.append([upper, y_max_last+offset_y, z])\n# paint_point.append([upper, y_min_last-offset_y, z])\n# return trans_to_end(paint_point)\n return paint_point","def _find_trial_beam_breaks_regions_in_sync(sync_file):\n bit = 'BEAM_BREAK'\n return _find_bit_in_sync(sync_file, bit, ['down', 'up'])"],"string":"[\n \"def make_partioned_regions(shape, alpha=1.0, max_regions=5, min_regions=2):\\n ring = np.array([[1,1,1],[1,0,1],[1,1,1]], dtype=np.int16)\\n adjacent = np.array([ # Diagonals don't count as adjacent\\n [-1,0,0,1],\\n [0,-1,1,0]], dtype=np.int16).T\\n nearby = np.meshgrid([-2,-1,0,1,2], [-2,-1,0,1,2])\\n\\n board = np.zeros(shape, dtype=np.int16)\\n perimeters = [{\\n (i, j) for i, j in zip(*np.nonzero(board == 0))\\n }]\\n exclusions = [set()]\\n while sum(len(p) for p in perimeters) > 0:\\n weights = np.array([len(p) for p in perimeters], dtype=float)\\n weights[0] = min(alpha, weights[0]) if len(weights) <= max_regions else 1e-10\\n if len(weights) <= min_regions:\\n weights[1:] = 1e-10\\n weights /= np.sum(weights)\\n k = get_rng().choice(len(perimeters), p=weights)\\n plist = list(perimeters[k])\\n i, j = plist[get_rng().choice(len(plist))]\\n perimeters[0].discard((i, j))\\n perimeters[k].discard((i, j))\\n if (i, j) in exclusions[k]:\\n continue\\n exclusions[0].add((i,j))\\n exclusions[k].add((i,j))\\n b = board[(i+nearby[0]) % shape[0], (j+nearby[1]) % shape[1]]\\n b[2,2] = k or -1\\n num_neighbors = signal.convolve2d(b != 0, ring, mode='valid')\\n num_foreign = signal.convolve2d((b > 0) & (b != k), ring, mode='valid')\\n if ((num_foreign > 0) & (num_neighbors > 2)).any() or num_foreign[1,1] > 0:\\n continue\\n # Add to the board\\n if k == 0:\\n k = len(perimeters)\\n perimeters.append(set())\\n exclusions.append(set())\\n board[i, j] = k\\n for i2, j2 in (adjacent + (i, j)) % shape:\\n if board[i2, j2] == 0:\\n perimeters[k].add((i2, j2))\\n return board\",\n \"def resetSagittalSegment(self):\\r\\n #research\\r\\n profprint()\\r\\n sYellow = slicer.mrmlScene.GetNodeByID(\\\"vtkMRMLSliceNodeYellow\\\")\\r\\n if sYellow == None :\\r\\n sYellow = slicer.mrmlScene.GetNodeByID(\\\"vtkMRMLSliceNode2\\\")\\r\\n reformatLogic = slicer.vtkSlicerReformatLogic()\\r\\n sYellow.SetSliceVisible(0)\\r\\n sYellow.SetOrientationToSagittal()\\r\\n sw = slicer.app.layoutManager().sliceWidget(\\\"Yellow\\\")\\r\\n sw.fitSliceToBackground()\\r\\n sYellow.Modified()\",\n \"def highlight_available_v_fences(win, game):\\n #Check if player has remaining fences\\n player_turn = game.get_player_turn()\\n if game.get_pawn(player_turn).get_remaining_fences() == 0:\\n return\\n\\n board = game.get_board()\\n\\n #Set highlight color\\n if player_turn == 1:\\n color = LIGHTERRED\\n else:\\n color = LIGHTERBLUE\\n \\n for row in range(len(board)-2):\\n for col in range(len(board)-1):\\n #Highlight fence if no fence placed and does not interesect a horizontal fence. \\n if not board[row][col]['v'] and not board[row+1][col]['v'] and board[row+1][col]['h'] != \\\"Fence Continued\\\" and game.fair_play_check('v',(col,row)):\\n coords = board[row][col]['coord']\\n v_fence_coords = (coords[0]*SQUARESIZE+FENCEWIDTH*(coords[0]-1), coords[1]*(SQUARESIZE+FENCEWIDTH))\\n v_fence = pygame.Rect(v_fence_coords, (FENCEWIDTH,SQUARESIZE))\\n pygame.draw.rect(win, color, v_fence)\",\n \"def color_segmentation(self):\\n cv.namedWindow(\\\"Segmentation parameters\\\")\\n self.create_trackbar(\\\"h-u\\\", \\\"Segmentation parameters\\\")\\n self.create_trackbar(\\\"h-l\\\",\\\"Segmentation parameters\\\")\\n self.create_trackbar(\\\"s-u\\\",\\\"Segmentation parameters\\\")\\n self.create_trackbar(\\\"s-l\\\",\\\"Segmentation parameters\\\")\\n self.create_trackbar(\\\"v-u\\\",\\\"Segmentation parameters\\\")\\n self.create_trackbar(\\\"v-l\\\",\\\"Segmentation parameters\\\")\\n\\n image = self.__image.copy()\\n\\n while True:\\n var_h_upper = cv.getTrackbarPos(\\\"h-u\\\", \\\"Segmentation parameters\\\")\\n var_h_lower = cv.getTrackbarPos(\\\"h-l\\\", \\\"Segmentation parameters\\\")\\n var_s_upper = cv.getTrackbarPos(\\\"s-u\\\", \\\"Segmentation parameters\\\")\\n var_s_lower = cv.getTrackbarPos(\\\"s-l\\\", \\\"Segmentation parameters\\\")\\n var_v_upper = cv.getTrackbarPos(\\\"v-u\\\", \\\"Segmentation parameters\\\")\\n var_v_lower = cv.getTrackbarPos(\\\"v-l\\\", \\\"Segmentation parameters\\\")\\n\\n lower = np.array([var_h_lower,var_s_lower,var_v_lower])\\n upper = np.array([var_h_upper,var_s_upper,var_v_upper])\\n\\n bin_image = cv.inRange(self.hsv_image, lower, upper)\\n cv.imshow(\\\"Segmentated image\\\", bin_image)\\n\\n if (cv.waitKey(1) & 0xFF == ord('q')):\\n break\\n cv.destroyAllWindows()\",\n \"def highlight_available_h_fences(win, game):\\n #Check if player has remaining fences\\n player_turn = game.get_player_turn()\\n if game.get_pawn(player_turn).get_remaining_fences() == 0:\\n return\\n\\n board = game.get_board()\\n \\n #Set highlight color\\n if player_turn == 1:\\n color = LIGHTERRED\\n else:\\n color = LIGHTERBLUE\\n \\n for row in range(len(board)-1):\\n for col in range(len(board)-2):\\n #Highlight fence if no fence placed and does not intersect a vertical fence\\n if not board[row][col]['h'] and not board[row][col+1]['h'] and board[row][col+1]['v'] != \\\"Fence Continued\\\" and game.fair_play_check('h',(col,row)):\\n coords = board[row][col]['coord']\\n h_fence_coords = (coords[0]*(SQUARESIZE+FENCEWIDTH), coords[1]*SQUARESIZE+FENCEWIDTH*(coords[1]-1))\\n h_fence = pygame.Rect(h_fence_coords, (SQUARESIZE,FENCEWIDTH))\\n pygame.draw.rect(win, color, h_fence)\",\n \"def plot_sed(self,period=6.,projection='lambert',geopolygons=None, showfig=True, vmin=0, vmax=None, hillshade=False):\\n\\t\\tif hillshade:\\n\\t\\t\\talpha = 0.5\\n\\t\\telse:\\n\\t\\t\\talpha =1.\\n\\t\\tm = self._get_basemap(projection=projection, geopolygons=geopolygons,hillshade=hillshade)\\n\\t\\tgroup = self['%g_sec'%( period )]\\n\\t\\tx, y = m(group['lonArr'].value, group['latArr'].value)\\n\\t\\tmy_cmap = pycpt.load.gmtColormap('./cv.cpt')\\n\\t\\tsed_Arr = group['sed_Arr'].value\\n\\t\\tsed_Arr_msk = group['sed_Arr_msk'].value\\n\\t\\tif vmin == None:\\n\\t\\t\\tvmin = np.nanmin(sed_Arr[~sed_Arr_msk])\\n\\t\\t\\tvmin = np.floor(vmin/5.)*5.\\n\\t\\tif vmax == None:\\n\\t\\t\\tvmax = np.nanmax(sed_Arr[~sed_Arr_msk])\\n\\t\\t\\tvmax = np.ceil(vmax/5.)*5.\\n\\t\\tim = m.pcolormesh(x, y, np.ma.masked_array(sed_Arr,mask=sed_Arr_msk), cmap=my_cmap, shading='gouraud', vmin=vmin, vmax=vmax, alpha=alpha)\\n\\t\\tcb = m.colorbar(im, \\\"bottom\\\", size=\\\"3%\\\", pad='2%', format='%d')\\n\\t\\tcb.set_label('Sediment thickness (m)', fontsize=12, rotation=0)\\n\\t\\tcb.set_alpha(1)\\n\\t\\tcb.draw_all()\\n\\t\\tax = plt.gca() # only plot the oceanic part for JdF\\n\\t\\t# ax.set_xlim(right=x_max)\\n\\t\\tif showfig:\\n\\t\\t\\tplt.show()\\n\\t\\treturn\",\n \"def addSeparatorFeature(self):\\n \\n # graphical separators\\n dNS = {\\\"pc\\\":PageXml.NS_PAGE_XML}\\n someNode = self.lNode[0]\\n ndPage = someNode.node.xpath(\\\"ancestor::pc:Page\\\", namespaces=dNS)[0]\\n lNdSep = ndPage.xpath(\\\".//pc:SeparatorRegion\\\", namespaces=dNS)\\n loSep = [ShapeLoader.node_to_LineString(_nd) for _nd in lNdSep]\\n \\n if self.bVerbose: traceln(\\\" %d graphical separators\\\"%len(loSep))\\n\\n # make an indexed rtree\\n idx = index.Index()\\n for i, oSep in enumerate(loSep):\\n idx.insert(i, oSep.bounds)\\n \\n # take each edge in turn and list the separators it crosses\\n nCrossing = 0\\n for edge in self.lEdge:\\n # bottom-left corner to bottom-left corner\\n oEdge = geom.LineString([(edge.A.x1, edge.A.y1), (edge.B.x1, edge.B.y1)])\\n prepO = prep(oEdge)\\n lCrossingPoints = []\\n fSepTotalLen = 0\\n for i in idx.intersection(oEdge.bounds):\\n # check each candidate in turn\\n oSep = loSep[i]\\n if prepO.intersects(oSep):\\n fSepTotalLen += oSep.length\\n oPt = oEdge.intersection(oSep)\\n if type(oPt) != geom.Point:\\n traceln('Intersection in not a point: skipping it')\\n else:\\n lCrossingPoints.append(oPt)\\n \\n if lCrossingPoints:\\n nCrossing += 1\\n edge.bCrossingSep = True\\n edge.sep_NbCrossing = len(lCrossingPoints)\\n minx, miny, maxx, maxy = geom.MultiPoint(lCrossingPoints).bounds\\n edge.sep_SpanLen = abs(minx-maxx) + abs(miny-maxy)\\n edge.sep_AvgSpanSgmt = edge.sep_SpanLen / len(lCrossingPoints) \\n edge.sep_AvgSepLen = fSepTotalLen / len(lCrossingPoints)\\n else:\\n edge.bCrossingSep = False\\n edge.sep_NbCrossing = 0\\n edge.sep_SpanLen = 0\\n edge.sep_AvgSpanSgmt = 0 \\n edge.sep_AvgSepLen = 0\\n \\n #traceln((edge.A.domid, edge.B.domid, edge.bCrossingSep, edge.sep_NbCrossing, edge.sep_SpanLen, edge.sep_AvgSpanSgmt, edge.sep_AvgSepLen))\\n \\n \\n if self.bVerbose: \\n traceln(\\\" %d (/ %d) edges crossing at least one graphical separator\\\"%(nCrossing, len(self.lEdge)))\",\n \"def analyze_block_horizon(mask):\\n\\n horizon_borders = find_border_horizon(mask)\\n if border_analyze_horizon(mask, horizon_borders) and mask.shape[0] > mask.shape[1]:\\n return True\\n else:\\n return False\\n # heights = [abs(start - stop) for (start, stop) in horizon_borders]\\n # horizon_big_borders = []\\n # segmented_components = []\\n # for idx, h in enumerate(heights):\\n # if h > space_height:\\n # horizon_big_borders.append(horizon_borders[idx])\\n # if len(horizon_big_borders) == 0:\\n # return segmented_components\\n # slice_start = 0\\n # horizon_slice_start_stops = []\\n # for h_border in horizon_big_borders[::-1]:\\n # horizon_slice_start_stops.append([slice_start, h_border[0]])\\n # slice_start = h_border[1]\\n # horizon_slice_start_stops.append([slice_start, mask.shape[0] - 1])\\n # horizon_slice_start_stops = [(start, stop) for (start, stop) in horizon_slice_start_stops if stop > start]\\n # for (horizon_start, horizon_stop) in horizon_slice_start_stops:\\n # mask_slice = mask[horizon_start:horizon_stop, :]\\n # vertical_borders = find_border_vertical(mask_slice)\\n # widths = [abs(border[0] - border[1]) for border in vertical_borders]\\n # vertical_big_borders = [vertical_borders[idx] for (idx, w) in enumerate(widths) if w > space_width]\\n # if len(vertical_big_borders) == 0:\\n # segmented_components.append([horizon_start, horizon_stop, 0, mask.shape[1] - 1])\\n # else:\\n # v_slice_start = 0\\n # for idx, v_border in enumerate(vertical_big_borders[::-1]):\\n # if v_slice_start != v_border[1]:\\n # segmented_components.append([horizon_start, horizon_stop, v_slice_start, v_border[1]])\\n # v_slice_start = v_border[0]\\n # if v_slice_start < mask.shape[1] - 1:\\n # segmented_components.append([horizon_start, horizon_stop, v_slice_start, mask.shape[1] - 1])\\n # return segmented_components\",\n \"def region_growing(im: np.ndarray, seed_points: list, T: int) -> np.ndarray:\\n ### START YOUR CODE HERE ### (You can change anything inside this block)\\n # You can also define other helper functions\\n segmented = np.zeros_like(im).astype(bool)\\n\\n (H, W) = im.shape\\n\\n for seed_row, seed_col in seed_points:\\n region = []\\n region.append([seed_row, seed_col])\\n for row, col in region:\\n for rows in range((row-1),(row+2)): # Check neighbouring pixels\\n for cols in range((col-1),(col+2)):\\n if rows < H and rows >= 0 and cols < W and cols >= 0: # Is pixel inside image?\\n if (np.abs(im[seed_row, seed_col] - im[rows, cols]) <= T) and not segmented[row, col]:\\n region.append([rows, cols])\\n segmented[row, col] = True\\n return segmented\\n ### END YOUR CODE HERE ### \",\n \"def vis_seg(img, seg, palette, alpha=0.5):\\n vis = np.array(img, dtype=np.float32)\\n mask = seg > 0\\n vis[mask] *= 1. - alpha\\n vis[mask] += alpha * palette[seg[mask].flat]\\n vis = vis.astype(np.uint8)\\n\\n # own code - Jasper\\n total_pixels = totalNumPixels(seg, palette)\\n # print(\\\"color_seg():\\\\n\\\")\\n # print(palette)\\n # print(\\\"Seg: \\\\n\\\")\\n # print(seg)\\n # print(\\\"Seg.flat:\\\\n\\\")\\n # print(seg.flat)\\n # print(\\\"Palette seg.flat:\\\\n\\\")\\n # print(palette[seg.flat])\\n exportLogs(\\\"Number of pixels: {:d}\\\".format(total_pixels))\\n\\n # classes of pixels in tuple form\\n exportLogs(\\\"Extract Unique Pixel Classes:\\\\n\\\")\\n pixel_classes = [tuple(row) for row in palette[seg.flat]]\\n\\n # remove duplicate classes of pixels\\n unique_classes = np.unique(pixel_classes, axis=0)\\n\\n # print result of pixel classes present in image\\n for x in range(0, len(unique_classes.tolist())):\\n exportLogs(\\\"{}. {}\\\".format(x + 1, unique_classes.tolist()[x]))\\n\\n # determine index of class and relate it with class_names\\n # numpy array must be converted to list for list manipulation\\n exportLogs(\\\"---------- Class Names - RGB Value ----------\\\")\\n for i in unique_classes.tolist():\\n # get index of pixel class from palette\\n class_index = palette.tolist().index(i)\\n\\n # RGB value of pixel class\\n class_color = tuple(i)\\n\\n # get the class name from class_names list based on PASCAL VOC list of classes \\n class_name = class_names[class_index]\\n\\n # compute region percentage of class from the image\\n percentage = (pixel_classes.count(tuple(i))/total_pixels) * 100\\n \\n # print results\\n exportLogs(\\\"Class ID: {:d}\\\".format(class_index))\\n exportLogs(\\\"Class Color: {}\\\".format(class_color))\\n exportLogs(\\\"Class Name: {:s}\\\".format(class_name))\\n exportLogs(\\\"Percentage of region: {:.3f}%\\\".format(percentage))\\n exportLogs(\\\"\\\\n\\\")\\n # end\\n return vis\",\n \"def FillVC8GradientColour(self, dc, tabPoints, active):\\r\\n\\r\\n xList = [pt.x for pt in tabPoints]\\r\\n yList = [pt.y for pt in tabPoints]\\r\\n \\r\\n minx, maxx = min(xList), max(xList)\\r\\n miny, maxy = min(yList), max(yList)\\r\\n\\r\\n rect = wx.Rect(minx, maxy, maxx-minx, miny-maxy+1) \\r\\n region = wx.RegionFromPoints(tabPoints)\\r\\n\\r\\n if self._buttonRect.width > 0:\\r\\n buttonRegion = wx.Region(*self._buttonRect)\\r\\n region.XorRegion(buttonRegion)\\r\\n \\r\\n dc.SetClippingRegionAsRegion(region)\\r\\n\\r\\n if active:\\r\\n bottom_colour = top_colour = wx.WHITE\\r\\n else:\\r\\n bottom_colour = StepColour(self._base_colour, 90)\\r\\n top_colour = StepColour(self._base_colour, 170)\\r\\n\\r\\n dc.GradientFillLinear(rect, top_colour, bottom_colour, wx.SOUTH)\\r\\n dc.DestroyClippingRegion()\",\n \"def undrawGrid(draw,points,coeff2,newColorArray):\\r\\n ## This is the merge function.\\r\\n ## If two neighboring regions are considered to be the same color by the comparison function then this function replaces the black line between them by a line of their color (making it invisible).\\r\\n for j in range(0,coeff2-1):\\r\\n if comparisonFunction(newColorArray[0][j],newColorArray[0][j+1]):\\r\\n draw.line((points*0, points*(j+1), points*(0+1)-3, points*(j+1)), fill=newColorArray[0][j], width=lineWidth)\\r\\n\\r\\n for i in range(0,coeff2-1):\\r\\n if comparisonFunction(newColorArray[i][0],newColorArray[i+1][0]):\\r\\n draw.line((points*(i+1), points*0, points*(i+1), points*1-3), fill=newColorArray[i][0], width=lineWidth)\\r\\n\\r\\n for i in range(1,coeff2):\\r\\n for j in range(1,coeff2):\\r\\n if comparisonFunction(newColorArray[i][j],newColorArray[i][j-1]):\\r\\n draw.line((points*i+3, points*j, points*(i+1)-3, points*j), fill=newColorArray[i][j], width=lineWidth)\\r\\n\\r\\n if comparisonFunction(newColorArray[i][j],newColorArray[i-1][j]):\\r\\n draw.line((points*i, points*j+3, points*i, points*(j+1)-3), fill=newColorArray[i][j], width=lineWidth)\",\n \"def split_dotted_general(captcha):\\n image = captcha[19:46,]\\n\\n col_sum = np.sum(image, axis = 0)\\n col_sum_list = list(col_sum)\\n # Finding all the dark regions\\n # beggining and end of all dark regions)\\n x = 1\\n i = 0\\n dark_regions = []\\n while i < 200:\\n if col_sum_list[i] == 0:\\n dark_region_beg = i\\n while col_sum_list[i + x] == 0:\\n x = x + 1\\n if (x + i) > 199:\\n break\\n dark_region_end = i + x - 1\\n dark_region = (dark_region_beg, dark_region_end)\\n dark_regions.append(dark_region)\\n i = x + i + 1\\n x = 1\\n else:\\n i = i + 1\\n\\n # Identifying leftmost and rightmost dark regions and popping them out of the list\\n left_region = dark_regions[0]\\n right_region = dark_regions[-1]\\n dark_regions.pop(0)\\n dark_regions.pop(-1)\\n\\n # Sorting dark regions according to their length\\n five_regions = sorted(dark_regions, key = lambda x: x[1] - x[0], reverse = True)\\n\\n # Building a list of GAPS (lengths of the dark regions)\\n # and LINES that split such gaps in half\\n gaps = []\\n lines = []\\n for i, region in enumerate(five_regions):\\n gap = mt.ceil((region[1] - region[0]) / 2)\\n if gap == 0:\\n continue\\n gaps.append(gap)\\n lines.append(region[0] + gap)\\n\\n # If more than 5 gaps are identified, the problem may be due to split letters\\n # Some of the troublesome letters are m, n and h\\n # We will try to fix this issue by completing gaps in these letters\\n if len(lines) > 5:\\n\\n for i in range(len(col_sum_list[:-9])):\\n if col_sum_list[i:i+9] == [0, 0, 0, 0, 510, 510, 0, 3060, 3060]:\\n captcha[28:30, i+1:i+3] = 255\\n if col_sum_list[i:i+9] == [0, 0, 0, 0, 510, 510, 0, 2550, 2550]:\\n captcha[31:33, i+1:i+3] = 255\\n if col_sum_list[i:i+9] == [0, 3060, 3060, 0, 510, 510, 0, 0, 0, 0]:\\n captcha[28:30, i+7:i+9] = 255\\n if col_sum_list[i:i+9] == [0, 2550, 2550, 0, 510, 510, 0, 0, 0, 0]:\\n captcha[31:33, i+7:i+9] = 255\\n if col_sum_list[i:i+9] == [0, 4080, 4080, 0, 0, 0, 0, 510, 510]:\\n captcha[31:33, i+4:i+6] = 255\\n\\n # Reloading image (based on modified captcha) and redefiding col_sum_list\\n image = captcha[19:46, ]\\n col_sum_list = list(np.sum(image, axis = 0))\\n\\n # Finding all the dark regions\\n # beggining and end of all dark regions)\\n x = 1\\n i = 0\\n dark_regions = []\\n while i < 200:\\n if col_sum_list[i] == 0:\\n dark_region_beg = i\\n while col_sum_list[i + x] == 0:\\n x = x + 1\\n if (x + i) > 199:\\n break\\n dark_region_end = i + x - 1\\n dark_region = (dark_region_beg, dark_region_end)\\n dark_regions.append(dark_region)\\n i = x + i + 1\\n x = 1\\n else:\\n i = i + 1\\n\\n # Identifying leftmost and rightmost dark regions and popping them out of the list\\n left_region = dark_regions[0]\\n right_region = dark_regions[-1]\\n dark_regions.pop(0)\\n dark_regions.pop(-1)\\n\\n # Sorting dark regions according to their length\\n five_regions = sorted(dark_regions, key = lambda x: x[1] - x[0], reverse = True)\\n\\n # Building a list of GAPS (lengths of the dark regions)\\n # and LINES that split such gaps in half\\n gaps = []\\n lines = []\\n for i, region in enumerate(five_regions):\\n gap = mt.ceil((region[1] - region[0]) / 2)\\n if gap == 0:\\n continue\\n gaps.append(gap)\\n lines.append(region[0] + gap)\\n\\n # If the errors persists, we move on to next captcha\\n if len(lines) > 5:\\n return('error')\\n\\n # If the algorithm finds less letters than expected (merged letters), we move on to next captcha\\n if len(lines) < 5:\\n return('error')\\n\\n # Defining rightmost and leftmost lines, appending lines list, and sorting\\n left_line = left_region[1] - 2\\n right_line = right_region[0] + 2\\n lines.append(left_line)\\n lines.append(right_line)\\n lines = sorted(lines)\\n\\n # Finding letters x-coordinates\\n letters_xcoords = []\\n for i in range(len(lines)):\\n if lines[i] == lines[-1]:\\n break\\n letter = (lines[i], lines[i + 1])\\n letters_xcoords.append(letter)\\n\\n letters = []\\n for i, letter in enumerate(letters_xcoords):\\n letter_image = captcha[:60, letter[0]:letter[1]]\\n letters.append(letter_image)\\n\\n return(letters)\",\n \"def segment_region_of_interest(image):\\n binary = image < 604\\n cleared = clear_border(binary)\\n\\n label_image = label(cleared)\\n\\n areas = [r.area for r in regionprops(label_image)]\\n areas.sort()\\n if len(areas) > 2:\\n for region in regionprops(label_image):\\n if region.area < areas[-2]:\\n for coordinates in region.coords:\\n label_image[coordinates[0], coordinates[1]] = 0\\n\\n binary = label_image > 0\\n\\n selem = disk(2)\\n binary = binary_erosion(binary, selem)\\n\\n selem = disk(10)\\n binary = binary_closing(binary, selem)\\n\\n edges = roberts(binary)\\n binary = scipy.ndimage.binary_fill_holes(edges)\\n\\n get_high_vals = binary == 0\\n image[get_high_vals] = 0\\n\\n return image\",\n \"def highlight_unallocated(series):\\n one_person_req = (series > 0) & (series <= 0.5)\\n two_person_req = series > 0.5\\n is_good = series == 0\\n\\n style = []\\n for i in range(len(series)):\\n if two_person_req[i]:\\n style.append(\\\"background-color: red\\\")\\n elif one_person_req[i]:\\n style.append(\\\"background-color: orange\\\")\\n elif is_good[i]:\\n style.append(\\\"background-color: lime\\\")\\n else:\\n style.append(\\\"background-color: yellow\\\")\\n\\n return style\",\n \"def _find_regions(base_pairs, scores):\\n # Make sure the lower residue is on the left for each row\\n sorted_base_pairs = np.sort(base_pairs, axis=1)\\n\\n # Sort the first column in ascending order\\n original_indices = np.argsort(sorted_base_pairs[:, 0])\\n sorted_base_pairs = sorted_base_pairs[original_indices]\\n\\n # Rank each base\\n # E.g.: [[3, 5] --> [[0, 1]\\n # [9, 7]] [3, 2]]\\n order = np.argsort(sorted_base_pairs.flatten())\\n rank = np.argsort(order).reshape(base_pairs.shape)\\n\\n # The base pairs belonging to the current region\\n region_pairs = []\\n # The individual regions\\n regions = set()\\n\\n # Find separate regions\\n for i in range(len(sorted_base_pairs)):\\n # if a new region is to be started append the current base pair\\n if len(region_pairs) == 0:\\n region_pairs.append(original_indices[i])\\n continue\\n\\n # Check if the current base pair belongs to the region that is\\n # currently being defined\\n previous_upstream_rank = rank[i-1, 0]\\n this_upstream_rank = rank[i, 0]\\n previous_downstream_rank = rank[i-1, 1]\\n this_downstream_rank = rank[i, 1]\\n\\n # if the current base pair belongs to a new region, save the\\n # current region and start a new region\\n if ((previous_downstream_rank - this_downstream_rank) != 1 or\\n (this_upstream_rank - previous_upstream_rank) != 1):\\n regions.add(\\n _Region(base_pairs, np.array(region_pairs), scores)\\n )\\n region_pairs = []\\n\\n # Append the current base pair to the region\\n region_pairs.append(original_indices[i])\\n\\n # The last region has no endpoint defined by the beginning of a\\n # new region.\\n regions.add(_Region(base_pairs, np.array(region_pairs), scores))\\n\\n # Return the graphical representation of the conflicting regions\\n return _generate_graphical_representation(regions)\",\n \"def phase_segmentation(image, threshold):\\n # Normalize the image\\n im_norm = (image - image.min()) / (image.max() - image.min())\\n\\n # Do a background subtraction\\n im_blur = skimage.filters.gaussian(image, 50.0)\\n im_sub = im_norm - im_blur\\n\\n # Threshold the image\\n im_thresh = im_sub < -0.2\\n\\n # Label the image\\n im_label = skimage.measure.label(im_thresh)\\n\\n # Get the properties and apply an area threshold\\n props = skimage.measure.regionprops(im_label)\\n\\n # Make an empty image to store the approved cells\\n approved_objects = np.zeros_like(im_label)\\n\\n # Apply the area filters\\n for prop in props:\\n obj_area = prop.area * 0.160**2 # Given the interpixel distance\\n if (obj_area > 0.5) & (obj_area < 5):\\n approved_objects += (im_label==prop.label)\\n\\n # Relabel the image.\\n return im_relab\",\n \"def colour_segmentation(img, num_segments=1000, round_schedule = [0.02, 0.04, 0.06, 0.08], colour_median_prop=0, max_clust_size=0.05, min_clust_size=0.002):\\n origimg = img\\n \\n # Initial segmentation\\n regions = skimage.segmentation.slic(img, n_segments=num_segments)\\n\\n for round_thr in round_schedule:\\n # Compute colour change of each pixel\\n edges = skimage.util.dtype.img_as_float(colour.colourchange(img))\\n \\n # Merge clusters hierarchically based on above distance\\n rag = skimage.future.graph.rag_boundary(regions, edges)\\n regions = skimage.future.graph.merge_hierarchical(regions, rag, thresh=round_thr, rag_copy=False, in_place_merge=True, merge_func=_merge_boundary, weight_func=_weight_boundary)\\n\\n # Replace all pixels in (some?) clusters with their median colour\\n clust_sizes = skimage.exposure.histogram(regions)[0]\\n clust_sizes = clust_sizes / float(sum(clust_sizes))\\n medianclusters = np.where(clust_sizes > colour_median_prop)[0]\\n\\n img = origimg.copy()\\n for mediancluster in medianclusters:\\n img[regions == mediancluster] = np.median(img[regions == mediancluster], axis=0)\\n \\n if len(clust_sizes) == 1:\\n break\\n \\n # Filter out too small and too large clusters\\n num_clusters = 0\\n for clust in range(len(clust_sizes)):\\n if clust_sizes[clust] > max_clust_size or clust_sizes[clust] < min_clust_size: # background or noise resp.\\n regions[regions == clust] = 0\\n else:\\n num_clusters += 1\\n regions[regions == clust] = num_clusters\\n \\n # Extract centroids\\n centroids, bboxes = zip(*[(clust.centroid, clust.bbox) for clust in skimage.measure.regionprops(regions)])\\n \\n return (regions, centroids, bboxes)\",\n \"def offer_fix_broken_regions(self, with_window: ProjectWindow = None):\\n if with_window:\\n result = with_window.CustomDialog(\\n title=\\\"Region Cleanup\\\",\\n message=\\\"In vanilla Dark Souls, the Duke's Archives has four unused regions that can break event\\\\n\\\"\\n \\\"scripts. Would you like Soulstruct to delete those four regions now?\\\",\\n button_names=(\\\"Yes, delete them\\\", \\\"No, leave them be\\\"),\\n button_kwargs=(\\\"YES\\\", \\\"NO\\\"),\\n cancel_output=1,\\n default_output=1,\\n )\\n else:\\n result = 1 if (\\n input(\\n \\\"In vanilla Dark Souls, the Duke's Archives has four unused regions that can break event\\\\n\\\"\\n \\\"scripts. Would you like Soulstruct to delete those four regions now? [y]/n\\\",\\n ).lower() == \\\"n\\\"\\n ) else 0\\n if result == 0:\\n archives_msb = self.maps.DukesArchives\\n repeats = archives_msb.get_repeated_entity_ids() # re-checking just in case\\n if {e.entity_id for e in repeats[\\\"Regions\\\"]} == {1702745, 1702746, 1702747, 1702748}:\\n for entry in repeats[\\\"Regions\\\"]:\\n archives_msb.regions.delete_entry(entry)\\n return True\\n else:\\n return False\",\n \"def highlight_de(adata, basis='umap', components=[1, 2], n_top_genes=10,\\n de_keys='names, scores, pvals_adj, logfoldchanges',\\n cell_keys='', n_neighbors=5, fill_alpha=0.1, show_hull=True,\\n legend_loc='top_right', plot_width=None, plot_height=None):\\n\\n if 'rank_genes_groups' not in adata.uns_keys():\\n raise ValueError('Run differential expression first.')\\n\\n\\n if isinstance(de_keys, str):\\n de_keys = list(dict.fromkeys(map(str.strip, de_keys.split(','))))\\n if de_keys != ['']:\\n assert all(map(lambda k: k in adata.uns['rank_genes_groups'].keys(), de_keys)), 'Not all keys are in `adata.uns[\\\\'rank_genes_groups\\\\']`.'\\n else:\\n de_keys = []\\n\\n if isinstance(cell_keys, str):\\n cell_keys = list(dict.fromkeys(map(str.strip, cell_keys.split(','))))\\n if cell_keys != ['']:\\n assert all(map(lambda k: k in adata.obs.keys(), cell_keys)), 'Not all keys are in `adata.obs.keys()`.'\\n else:\\n cell_keys = []\\n\\n if f'X_{basis}' not in adata.obsm.keys():\\n raise ValueError(f'Key `X_{basis}` not found in adata.obsm.')\\n\\n if not isinstance(components, np.ndarray):\\n components = np.asarray(components)\\n\\n key = adata.uns['rank_genes_groups']['params']['groupby']\\n if key not in cell_keys:\\n cell_keys.insert(0, key)\\n\\n df = pd.DataFrame(adata.obsm[f'X_{basis}'][:, components - (basis != 'diffmap')], columns=['x', 'y'])\\n for k in cell_keys:\\n df[k] = list(map(str, adata.obs[k]))\\n\\n knn = neighbors.KNeighborsClassifier(n_neighbors)\\n knn.fit(df[['x', 'y']], adata.obs[key])\\n df['prediction'] = knn.predict(df[['x', 'y']])\\n\\n conv_hulls = df[df[key] == df['prediction']].groupby(key).apply(lambda df: df.iloc[ConvexHull(np.vstack([df['x'], df['y']]).T).vertices])\\n\\n mapper = _create_mapper(adata, key)\\n categories = adata.obs[key].cat.categories\\n fig = figure(tools='pan, reset, wheel_zoom, lasso_select, save')\\n _set_plot_wh(fig, plot_width, plot_height)\\n legend_dict = defaultdict(list)\\n\\n for k in categories:\\n d = df[df[key] == k]\\n data_source = ColumnDataSource(d)\\n legend_dict[k].append(fig.scatter('x', 'y', source=data_source, color={'field': key, 'transform': mapper}, size=5, muted_alpha=0))\\n\\n hover_cell = HoverTool(renderers=[r[0] for r in legend_dict.values()], tooltips=[(f'{key}', f'@{key}')] + [(f'{k}', f'@{k}') for k in cell_keys[1:]])\\n\\n c_hulls = conv_hulls.copy()\\n de_possible = conv_hulls[key].isin(adata.uns['rank_genes_groups']['names'].dtype.names)\\n ok_patches = []\\n prev_cat = []\\n for i, isin in enumerate((~de_possible, de_possible)):\\n conv_hulls = c_hulls[isin]\\n\\n if len(conv_hulls) == 0:\\n continue\\n\\n xs, ys, ks = zip(*conv_hulls.groupby(key).apply(lambda df: list(map(list, (df['x'], df['y'], df[key])))))\\n tmp_data = defaultdict(list)\\n tmp_data['xs'] = xs\\n tmp_data['ys'] = ys\\n tmp_data[key] = list(map(lambda k: k[0], ks))\\n \\n if i == 1:\\n ix = list(map(lambda k: adata.uns['rank_genes_groups']['names'].dtype.names.index(k), tmp_data[key]))\\n for k in de_keys:\\n tmp = np.array(list(zip(*adata.uns['rank_genes_groups'][k])))[ix, :n_top_genes]\\n for j in range(n_top_genes):\\n tmp_data[f'{k}_{j}'] = tmp[:, j]\\n\\n tmp_data = pd.DataFrame(tmp_data)\\n for k in categories:\\n d = tmp_data[tmp_data[key] == k]\\n source = ColumnDataSource(d)\\n\\n patches = fig.patches('xs', 'ys', source=source, fill_alpha=fill_alpha, muted_alpha=0, hover_alpha=0.5,\\n color={'field': key, 'transform': mapper} if (show_hull and i == 1) else None,\\n hover_color={'field': key, 'transform': mapper} if (show_hull and i == 1) else None)\\n legend_dict[k].append(patches)\\n if i == 1:\\n ok_patches.append(patches)\\n\\n hover_group = HoverTool(renderers=ok_patches, tooltips=[(f'{key}', f'@{key}'),\\n ('groupby', adata.uns['rank_genes_groups']['params']['groupby']),\\n ('reference', adata.uns['rank_genes_groups']['params']['reference']),\\n ('rank', ' | '.join(de_keys))] + [(f'#{i + 1}', ' | '.join((f'@{k}_{i}' for k in de_keys))) for i in range(n_top_genes)]\\n )\\n \\n\\n fig.toolbar.active_inspect = [hover_group]\\n if len(cell_keys) > 1:\\n fig.add_tools(hover_group, hover_cell)\\n else:\\n fig.add_tools(hover_group)\\n\\n if legend_loc is not None:\\n legend = Legend(items=list(legend_dict.items()), location=legend_loc)\\n fig.add_layout(legend)\\n fig.legend.click_policy = 'hide' # hide does disable hovering, whereas 'mute' does not\\n\\n fig.xaxis.axis_label = f'{basis}_{components[0]}'\\n fig.yaxis.axis_label = f'{basis}_{components[1]}'\\n\\n show(fig)\",\n \"def alternatingSlice(self,geom,polyLayer,targetArea,granularity,direction,method):\\r\\n global recurs\\r\\n recurs+=1\\r\\n if self.debug: print \\\"******************************\\\"\\r\\n if self.debug: print \\\"Slicing, No of part: \\\",str(recurs)\\r\\n if self.debug: print \\\"Slicing, Granularity remaining: \\\", str(granularity)\\r\\n bbox=[geom.boundingBox().xMinimum(),geom.boundingBox().yMinimum(),geom.boundingBox().xMaximum(),geom.boundingBox().yMaximum()]\\r\\n if direction==\\\"h\\\":\\r\\n step=(bbox[2]-bbox[0])/granularity\\r\\n pointer=bbox[0]\\r\\n else:\\r\\n step=(bbox[3]-bbox[1])/granularity\\r\\n pointer=bbox[1]\\r\\n totalArea=0\\r\\n slices=0\\r\\n #save the original geom\\r\\n tempGeom=QgsGeometry(geom)\\r\\n #start slicing until targetArea is reached\\r\\n while totalArea<targetArea*0.999:\\r\\n pointer+=step\\r\\n if direction==\\\"h\\\":\\r\\n startPt=QgsPoint(pointer,bbox[1])\\r\\n endPt=QgsPoint(pointer,bbox[3])\\r\\n (multiGeom,tempGeom)=self.cutPoly(tempGeom,startPt,endPt)\\r\\n else:\\r\\n startPt=QgsPoint(bbox[0],pointer)\\r\\n endPt=QgsPoint(bbox[2],pointer)\\r\\n (tempGeom,multiGeom)=self.cutPoly(tempGeom,startPt,endPt)\\r\\n if multiGeom!=None:\\r\\n totalArea+=multiGeom.area();\\r\\n slices+=1\\r\\n if self.debug: print \\\"Slicing, Slices: \\\", str(slices)\\r\\n #do the real cutting when reached targetArea and add \\\"left\\\" feature to layer\\r\\n if self.debug: print \\\"Cutting with line, Cutline:\\\", startPt,\\\",\\\",endPt\\r\\n if direction==\\\"h\\\":\\r\\n (multiGeom,geom)=self.cutPoly(geom,startPt,endPt,True)\\r\\n if multiGeom:\\r\\n if self.debug: print \\\"After split, Parts to the left:\\\",str(len(multiGeom.asGeometryCollection()))\\r\\n if geom:\\r\\n if self.debug: print \\\"After split, Parts to the right:\\\",str(len(geom.asGeometryCollection()))\\r\\n else:\\r\\n (geom,multiGeom)=self.cutPoly(geom,startPt,endPt,True)\\r\\n if geom:\\r\\n if self.debug: print \\\"After split, Parts above:\\\",str(len(geom.asGeometryCollection()))\\r\\n if multiGeom:\\r\\n if self.debug: print \\\"After split, Parts under:\\\",str(len(multiGeom.asGeometryCollection()))\\r\\n self.addGeomToLayer(multiGeom,polyLayer)\\r\\n #self.addGeomToLayer(QgsGeometry.fromPolyline([startPt,endPt]),lineLayer)\\r\\n if geom:\\r\\n if geom.area()>targetArea:\\r\\n if (method==\\\"v\\\") or ((method==\\\"a\\\") and (direction==\\\"h\\\")):\\r\\n self.alternatingSlice(geom,polyLayer,targetArea,granularity-slices,\\\"v\\\",method)\\r\\n else:\\r\\n self.alternatingSlice(geom,polyLayer,targetArea,granularity-slices,\\\"h\\\",method)\\r\\n else:\\r\\n self.addGeomToLayer(geom,polyLayer)\",\n \"def drawValidationNeedles(self): \\n #productive #onButton\\n profprint()\\n # reset report table\\n # print \\\"Draw manually segmented needles...\\\"\\n #self.table =None\\n #self.row=0\\n self.initTableView()\\n self.deleteEvaluationNeedlesFromTable()\\n while slicer.util.getNodes('manual-seg*') != {}:\\n nodes = slicer.util.getNodes('manual-seg*')\\n for node in nodes.values():\\n slicer.mrmlScene.RemoveNode(node)\\n \\n if self.tableValueCtrPt==[[]]:\\n self.tableValueCtrPt = [[[999,999,999] for i in range(100)] for j in range(100)]\\n modelNodes = slicer.mrmlScene.GetNodesByClass('vtkMRMLAnnotationFiducialNode')\\n nbNode=modelNodes.GetNumberOfItems()\\n for nthNode in range(nbNode):\\n modelNode=slicer.mrmlScene.GetNthNodeByClass(nthNode,'vtkMRMLAnnotationFiducialNode')\\n if modelNode.GetAttribute(\\\"ValidationNeedle\\\") == \\\"1\\\":\\n needleNumber = int(modelNode.GetAttribute(\\\"NeedleNumber\\\"))\\n needleStep = int(modelNode.GetAttribute(\\\"NeedleStep\\\"))\\n coord=[0,0,0]\\n modelNode.GetFiducialCoordinates(coord)\\n self.tableValueCtrPt[needleNumber][needleStep]=coord\\n print needleNumber,needleStep,coord\\n # print self.tableValueCtrPt[needleNumber][needleStep]\\n\\n for i in range(len(self.tableValueCtrPt)):\\n if self.tableValueCtrPt[i][1]!=[999,999,999]:\\n colorVar = random.randrange(50,100,1)/float(100)\\n controlPointsUnsorted = [val for val in self.tableValueCtrPt[i] if val !=[999,999,999]]\\n controlPoints=self.sortTable(controlPointsUnsorted,(2,1,0))\\n self.addNeedleToScene(controlPoints,i,'Validation')\\n else:\\n # print i\\n pass\",\n \"def highlight_moves(win, game):\\n #Get available moves\\n player_turn = game.get_player_turn()\\n moves_available = game.possible_moves(game.get_pawn(player_turn))\\n if None in moves_available:\\n moves_available.remove(None)\\n \\n #Highlight moves\\n for move in moves_available:\\n move_coords = (move[0]*(SQUARESIZE+FENCEWIDTH), move[1]*(SQUARESIZE+FENCEWIDTH))\\n move_center_coords = (move_coords[0]+SQUARESIZE/2, move_coords[1]+SQUARESIZE/2)\\n pygame.draw.circle(win, LIGHTGREEN, move_center_coords, SQUARESIZE/4)\",\n \"def sed(self, search, replace):\\n\\n for section in self.sections:\\n for i, block in enumerate(section.blocks):\\n if block == search:\\n section.blocks[i] = replace\\n self.all_damaged = True\\n self.dirty = True\",\n \"def BraceHighlight(self, pos1, pos2):\\n # Check if we are still alive or not, as this may be called\\n # after we have been deleted.\\n if self:\\n super(EditraBaseStc, self).BraceHighlight(pos1, pos2)\",\n \"def mask_region_ends(self, n_days=20):\\n for rg in self.Rs:\\n i = self.Rs.index(rg)\\n self.Active.mask[i, -n_days:] = True\\n self.Confirmed.mask[i, -n_days:] = True\\n self.Deaths.mask[i, -n_days:] = True\\n self.NewDeaths.mask[i, -n_days:] = True\\n self.NewCases.mask[i, -n_days:] = True\",\n \"def border_analyze_horizon(mask, borders, min_segment_height=5, max_border_height=0.4):\\n max_border_height = mask.shape[0] * max_border_height\\n if len(borders) == 0: return False\\n upper_most = 0\\n lower_most = mask.shape[0] - 1\\n # middle_borders = [border for border in borders if (left_most in border or right_most in border) and abs(border[0]-border[1])>3 ]\\n # if len(middle_borders)==0:return False\\n slice_start = 0\\n block_heights = []\\n block_areas = []\\n # segs_by_middle_borders=[]\\n for v_border in borders:\\n border_start = v_border[0]\\n border_stop = v_border[1]\\n if border_start == upper_most:\\n slice_start = border_stop\\n elif border_stop == lower_most:\\n # mask_slice=mask[slice_start:border_start]\\n block_heights.append(border_start - slice_start)\\n\\n block_areas.append(np.sum(mask[slice_start:border_start, :]))\\n # segs_by_middle_borders.append(mask_slice)\\n slice_start = border_stop\\n elif border_stop - border_start >= 1:\\n # mask_slice = mask[slice_start,border_start]\\n if border_stop - border_start < max_border_height:\\n block_heights.append(border_start - slice_start)\\n block_areas.append(np.sum(mask[slice_start:border_start, :]))\\n # segs_by_middle_borders.append(mask_slice)\\n slice_start = border_stop\\n if slice_start < lower_most:\\n # segs_by_middle_borders.append(mask[slice_start:])\\n block_heights.append(mask.shape[0] - slice_start)\\n block_areas.append(np.sum(mask[slice_start:mask.shape[0], :]))\\n\\n if len(block_areas) < 2:\\n return False\\n if len(block_areas) == 2:\\n max_area = max(block_areas)\\n min_area = min(block_areas)\\n if max_area / min_area > 3:\\n return False\\n if len(block_areas) > 2:\\n if np.std(block_areas) / np.mean(block_areas) > 2:\\n return False\\n\\n # print(block_areas)\\n # print(mask.shape[0]*mask.shape[1])\\n # print(np.std(block_areas)/np.mean(block_areas))\\n block_heights = [h for h in block_heights if h > min_segment_height]\\n\\n # print('block areas ')\\n # print(block_areas)\\n\\n # print('block heights deviation' )\\n # print(np.std(block_heights))\\n\\n # print('block heights dev/mean' )\\n # print(np.std(block_heights)/np.mean(block_heights))\\n\\n if len(block_heights) < 2: return False\\n return segment_analyzer(block_heights)\",\n \"def section_to_patch(self, group_of_segments, angle=None, row_spacing=None,\\n max_stitch_length=None):\\n if max_stitch_length is None:\\n max_stitch_length = self.max_stitch_length\\n\\n if row_spacing is None:\\n row_spacing = self.row_spacing\\n\\n if angle is None:\\n angle = self.angle\\n\\n # print >> sys.stderr, len(groups_of_segments)\\n\\n patch = Patch(color=self.color)\\n first_segment = True\\n swap = False\\n last_end = None\\n\\n for segment in group_of_segments:\\n # We want our stitches to look like this:\\n #\\n # ---*-----------*-----------\\n # ------*-----------*--------\\n # ---------*-----------*-----\\n # ------------*-----------*--\\n # ---*-----------*-----------\\n #\\n # Each successive row of stitches will be staggered, with\\n # num_staggers rows before the pattern repeats. A value of\\n # 4 gives a nice fill while hiding the needle holes. The\\n # first row is offset 0%, the second 25%, the third 50%, and\\n # the fourth 75%.\\n #\\n # Actually, instead of just starting at an offset of 0, we\\n # can calculate a row's offset relative to the origin. This\\n # way if we have two abutting fill regions, they'll perfectly\\n # tile with each other. That's important because we often get\\n # abutting fill regions from pull_runs().\\n\\n (beg, end) = segment\\n\\n if (swap):\\n (beg, end) = (end, beg)\\n\\n beg = PyEmb.Point(*beg)\\n end = PyEmb.Point(*end)\\n\\n row_direction = (end - beg).unit()\\n segment_length = (end - beg).length()\\n\\n # only stitch the first point if it's a reasonable distance away\\n # from the last stitch\\n if last_end is None or (beg - last_end).length() > 0.1 * px_per_mm:\\n patch.add_stitch(beg)\\n\\n first_stitch = self.adjust_stagger(beg, angle, row_spacing,\\n max_stitch_length)\\n\\n # we might have chosen our first stitch just outside this row, so\\n # move back in\\n if (first_stitch - beg) * row_direction < 0:\\n first_stitch += row_direction * max_stitch_length\\n\\n offset = (first_stitch - beg).length()\\n\\n while offset < segment_length:\\n patch.add_stitch(beg + offset * row_direction)\\n offset += max_stitch_length\\n\\n if (end - patch.stitches[-1]).length() > 0.1 * px_per_mm:\\n patch.add_stitch(end)\\n\\n last_end = end\\n swap = not swap\\n\\n return patch\",\n \"def Plot_RNAStructure_highlight(sequence, dot, hg_base_list=[], mode='fill', correctT=True, \\n scaling=0.8, highlight_region=[], annotation=[], \\n bpprob=[], bpprob_cutofflist=[0.6,0.8,0.95], bpprob_mode='color', bpwarning=True,\\n period=10, first_base_pos=1, peroid_color='#000000',\\n title=\\\"\\\", wait=True, VARNAProg=VARNAProg):\\n \\n assert len(sequence) == len(dot)\\n assert mode in ('label', 'fill')\\n \\n if correctT:\\n sequence = sequence.replace('T', 'U')\\n \\n CMD = \\\"java -cp \\\"+VARNAProg+\\\" fr.orsay.lri.varna.applications.VARNAcmd -sequenceDBN %s -structureDBN \\\\\\\"%s\\\\\\\" -drawBackbone false -drawBases false -bpStyle simple \\\" % (sequence, dot)\\n \\n if hg_base_list:\\n if mode == 'label':\\n CMD += \\\"-basesStyle1 \\\\\\\"label=#FF0000\\\\\\\" \\\"\\n else:\\n CMD += \\\"-basesStyle1 \\\\\\\"fill=#FF0000\\\\\\\" \\\"\\n hg_base_list = [str(item) for item in hg_base_list]\\n CMD += \\\"-applyBasesStyle1on \\\\\\\"%s\\\\\\\" \\\" % (\\\",\\\".join(hg_base_list), )\\n \\n if highlight_region:\\n CMD += \\\" \\\" + __highlight_region_cmd(highlight_region)\\n \\n if annotation:\\n CMD += \\\" \\\" + __annotation_cmd(annotation)\\n \\n if scaling:\\n CMD += \\\" -spaceBetweenBases \\\\\\\"%s\\\\\\\"\\\" % (scaling, )\\n \\n if bpprob:\\n new_bpprob = __dot_match_bpprob(dot, bpprob, bpwarning)\\n CMD += \\\" \\\" + __basepair_bpprob_cmd(new_bpprob, bpprob_cutofflist, bpprob_mode)\\n \\n if first_base_pos==1 and peroid_color=='#000000':\\n CMD += f\\\" -period {period}\\\"\\n else:\\n CMD += \\\" \\\" + __manual_period(len(sequence), first_base_pos, period, peroid_color)\\n \\n if title:\\n CMD += \\\" -title \\\\\\\"%s\\\\\\\"\\\" % (title, )\\n \\n if not wait:\\n CMD = \\\"nohup \\\" + CMD + \\\" &\\\"\\n \\n return CMD\",\n \"def separation_crawler(mode: bool) -> bool:\\r\\n for x in range(shape):\\r\\n for y in range(shape):\\r\\n if mode:\\r\\n if conflict_space[x, y] != 0 and safeboard[x, y] == 1:\\r\\n if walled_in(x, y):\\r\\n safeboard[x, y] = 0\\r\\n print(\\\"Cell will create separation if marked. Marked safe:\\\", x, \\\",\\\", y)\\r\\n progress_handler(False, True)\\r\\n else:\\r\\n if example[x, y] == 0:\\r\\n if walled_in(x, y):\\r\\n print(\\\"Solution Rejected, separated areas\\\")\\r\\n return True\",\n \"def _red_detect_(self, nslice = 0, thresh = 2.0):\\n zk_1 = 's_' + format(nslice, '03d')\\n zk_2 = 's_' + format(nslice+1, '03d')\\n\\n zf_1 = self.z_dense[zk_1]\\n zf_2 = self.z_dense[zk_2]\\n\\n # extract the y and x coordinates\\n y1 = zf_1[:,0]\\n x1 = zf_1[:,1]\\n\\n y2 = zf_2[:,0]\\n x2 = zf_2[:,1]\\n\\n\\n # create a meshgrid\\n [YC, YR] = np.meshgrid(y2, y1)\\n [XC, XR] = np.meshgrid(x2, x1)\\n\\n\\n dist_block = np.sqrt((YC-YR)**2 + (XC-XR)**2)\\n red_pair = np.where(dist_block <= thresh) # find out where the distance between cell i in plane k and cell j in plane k+1 is below the threshold.\\n\\n ind1 = red_pair[0] # the indices in the first frame\\n ind2 = red_pair[1] # the indices in the second frame\\n\\n\\n # select those with markers > 0 and markers < 0\\n marker_1 = zf_1[ind1, 3]\\n\\n\\n new_idx = (marker_1 == 0) # select those with zero-markers, which are never counted before. These are new cells. marker_1 needs to be updated.\\n pool_new = ind1[new_idx] # select the indices in the first frame where new redundancies are detected \\n pool_new_cov = ind2[new_idx] # select the indices in the second frame where new redundancies are detected.\\n\\n\\n pool_exist = ind1[~new_idx] # among the detected redundancies, find those already marked.\\n pool_exist_cov = ind2[~new_idx] # correspondingly, find those already marked in the adjacent slice\\n\\n n_new = len(pool_new)\\n n_exist = len(pool_exist)\\n if self.verbose:\\n print(n_new, \\\"new redundancies, \\\", n_exist, \\\"existing redundancies\\\")\\n\\n for n_count in np.arange(n_new):\\n # build the new keys\\n # also, we need to assign each new key an identity number which is unique.\\n n_ind1 = pool_new[n_count] # find the indices in the first slice that contains new redundancies\\n n_ind2 = pool_new_cov[n_count] # find the indices in the following slice \\n pr_number = nslice * 1000 + n_ind1\\n pr_key = 'sl_' + str(pr_number) # build a key \\n new_sl = Simple_list(nslice) # create a simple list with z_marker = nslice, nslice is the index of the first z-slice \\n new_sl.add([nslice, zf_1[n_ind1, 4]])\\n new_sl.add([nslice+1, zf_2[n_ind2, 4]])\\n zf_1[n_ind1, 3] = pr_number # assign the new pr_number to zf_1\\n zf_2[n_ind2, 3] = pr_number # assigne the same new pr_number to zf_2\\n\\n self.redundancy_pool[pr_key] = new_sl # stored into the redundancy pool\\n\\n\\n for n_count in np.arange(n_exist):\\n # search for the existing keys\\n n_ind1 = pool_exist[n_count]\\n n_ind2 = pool_exist_cov[n_count]\\n pr_number = int(zf_1[n_ind1, 3])# catch up the pr_number\\n pr_key = 'sl_' + str(pr_number) # this pr_key should already exist in the pool. \\n\\n self.redundancy_pool[pr_key].add([nslice+1, zf_2[n_ind2, 4]])\\n zf_2[n_ind2, 3] = pr_number # update the pr_number in the adjacent slice\",\n \"def borra_overlaps(self):\\r\\n nomTabla=self.nomTabla.split(\\\".\\\")[1]\\r\\n dicCondWhere={}\\r\\n dicCondWhere[\\\"id_trabajo\\\"]=self.oUtiles.id_trabajo\\r\\n if nomTabla == \\\"ed_fincas\\\":\\r\\n nomTablaOverlaps=\\\"ed_src\\\" + str(self.oUtiles.src_trabajo) + \\\".\\\" + \\\"ed_overlaps_fincas\\\"\\r\\n nomTablaGaps=\\\"ed_src\\\" + str(self.oUtiles.src_trabajo) + \\\".\\\" + \\\"ed_gaps_fincas\\\"\\r\\n else:\\r\\n nomTablaOverlaps=\\\"src\\\" + str(self.oUtiles.src_trabajo) + \\\".\\\" + \\\"overlaps_fincas\\\"\\r\\n nomTablaGaps=\\\"src\\\" + str(self.oUtiles.src_trabajo) + \\\".\\\" + \\\"gaps_fincas\\\"\\r\\n self.oUtiles.oConsultasPg.deleteDatos(nombreTabla=nomTablaOverlaps,dicCondWhere=dicCondWhere)\\r\\n self.oUtiles.oConsultasPg.deleteDatos(nombreTabla=nomTablaGaps,dicCondWhere=dicCondWhere)\",\n \"def DrawBands(self, count):\\n value = self.little[0]\\n mobile_average = float(sum([float(self.little[i])\\n for i in range(len(self.little))])) / float(self.period)\\n standard_derivation = sqrt(sum([pow(self.little[i] - mobile_average, 2)\\n for i in range(len(self.little))]) / self.period)\\n upper_band = mobile_average + (standard_derivation * self.sd_coef)\\n lower_band = mobile_average - (standard_derivation * self.sd_coef)\\n self.upper.insert(0, upper_band)\\n self.lower.insert(0, lower_band)\\n if len(self.upper) >= self.period:\\n self.upper.pop()\\n if len(self.lower) >= self.period:\\n self.lower.pop()\\n if count >= self.period:\\n for i in range(len(self.little) - 1):\\n self.canvas.create_line((i * self.incr / 1.725) + self.incr * 4,\\n self.height - self.incr * 4 + (self.little[i] - 1) * 5000 - 200,\\n (i * self.incr / 1.725) + self.incr * 4 + self.incr / 1.725,\\n self.height - self.incr * 4 + (self.little[i + 1] - 1) * 5000 - 200,\\n fill = \\\"#FFFF00\\\", width = 2)\\n for i in range(len(self.upper) - 1):\\n self.canvas.create_line((i * self.incr / 1.635) + self.incr * 4,\\n self.height - self.incr * 4 + (self.upper[i] - 1) * 5000 - 200,\\n (i * self.incr / 1.635) + self.incr * 4 + self.incr / 1.635,\\n self.height - self.incr * 4 + (self.upper[i + 1] - 1) * 5000 - 200,\\n fill = \\\"#FF6600\\\", width = 3)\\n self.canvas.create_line((i * self.incr / 1.635) + self.incr * 4,\\n self.height - self.incr * 4 + (self.lower[i] - 1) * 5000 - 200,\\n (i * self.incr / 1.635) + self.incr * 4 + self.incr / 1.635,\\n self.height - self.incr * 4 + (self.lower[i + 1] - 1) * 5000 - 200,\\n fill = \\\"#FF0000\\\", width = 3)\",\n \"def searchBreakend(self, region): \\n\\t\\treturn filter(lambda X: X == region, self)\",\n \"def threshold_segment(img):\\n\\n m,n = img.shape\\n g = img.sum()/(m*n)\\n\\n segmented = np.zeros((m,n),dtype=float)\\n\\n for i,j in it.product(range(m),range(n)):\\n\\n if img[i,j] - g >= 100:\\n segmented[i,j] = 0\\n elif img[i,j] - g >= 50:\\n segmented[i,j] = 50\\n elif img[i,j] - g >= 0:\\n segmented[i,j] = 100\\n elif img[i,j] - g >= -50:\\n segmented[i,j] = 150\\n elif img[i,j] - g >= -100:\\n segmented[i,j] = 200\\n else:\\n segmented[i,j] = 255\\n\\n return segmented\",\n \"def separate_frontier(self):\\n\\t#print self.frontier\\n region = [] # a list of tuples\\n region_list = [] # a list of regions\\n in_list = False\\n region_size = 7\\n num_regions = 25\\n n = 0\\n h = 0\\n print \\\"separate frontier\\\"\\n while(region_size>0):\\n for i in range(len(self.frontier)):\\n if (h < num_regions):\\n region = []\\n self.find_region(self.frontier[i], region)\\n\\t\\t #rospy.loginfo(region)\\n in_list = region in region_list\\n if (len(region) > region_size) and (not in_list):\\n region_list.append(region)\\n h += 1\\n self.regions = region_list\\n region_size -= 1\\n\\t#print self.regions\",\n \"def render_regions(view=None):\\r\\n # Get current active view\\r\\n if view is None:\\r\\n view = sublime.active_window().active_view()\\r\\n # Unable to set regions when no view available\\r\\n if view is None:\\r\\n return\\r\\n\\r\\n # Do no set regions if view is empty or still loading\\r\\n if view.size() == 0 or view.is_loading():\\r\\n return\\r\\n\\r\\n # Remove all markers to avoid marker conflict\\r\\n view.erase_regions(S.REGION_KEY_BREAKPOINT)\\r\\n view.erase_regions(S.REGION_KEY_CURRENT)\\r\\n view.erase_regions(S.REGION_KEY_DISABLED)\\r\\n\\r\\n # Get filename of current view and check if is a valid filename\\r\\n filename = view.file_name()\\r\\n if not filename:\\r\\n return\\r\\n\\r\\n # Determine icon for regions\\r\\n icon_current = get_region_icon(S.KEY_CURRENT_LINE)\\r\\n icon_disabled = get_region_icon(S.KEY_BREAKPOINT_DISABLED)\\r\\n icon_enabled = get_region_icon(S.KEY_BREAKPOINT_ENABLED)\\r\\n\\r\\n # Get all (disabled) breakpoint rows (line numbers) for file\\r\\n breakpoint_rows = []\\r\\n disabled_rows = []\\r\\n if filename in S.BREAKPOINT and isinstance(S.BREAKPOINT[filename], dict):\\r\\n for lineno, bp in S.BREAKPOINT[filename].items():\\r\\n # Do not show temporary breakpoint\\r\\n if S.BREAKPOINT_RUN is not None and S.BREAKPOINT_RUN['filename'] == filename and S.BREAKPOINT_RUN['lineno'] == lineno:\\r\\n continue\\r\\n # Determine if breakpoint is enabled or disabled\\r\\n if bp['enabled']:\\r\\n breakpoint_rows.append(lineno)\\r\\n else:\\r\\n disabled_rows.append(lineno)\\r\\n\\r\\n # Get current line from breakpoint hit\\r\\n if S.BREAKPOINT_ROW is not None:\\r\\n # Make sure current breakpoint is in this file\\r\\n if filename == S.BREAKPOINT_ROW['filename']:\\r\\n # Remove current line number from breakpoint rows to avoid marker conflict\\r\\n if S.BREAKPOINT_ROW['lineno'] in breakpoint_rows:\\r\\n breakpoint_rows.remove(S.BREAKPOINT_ROW['lineno'])\\r\\n # Set icon for current breakpoint\\r\\n icon_breakpoint_current = get_region_icon(S.KEY_BREAKPOINT_CURRENT)\\r\\n if icon_breakpoint_current:\\r\\n icon_current = icon_breakpoint_current\\r\\n if S.BREAKPOINT_ROW['lineno'] in disabled_rows:\\r\\n disabled_rows.remove(S.BREAKPOINT_ROW['lineno'])\\r\\n # Set current line marker\\r\\n if icon_current:\\r\\n view.add_regions(S.REGION_KEY_CURRENT, rows_to_region(S.BREAKPOINT_ROW['lineno']), S.REGION_SCOPE_CURRENT, icon_current, sublime.HIDDEN)\\r\\n\\r\\n # Set breakpoint marker(s)\\r\\n if breakpoint_rows and icon_enabled:\\r\\n view.add_regions(S.REGION_KEY_BREAKPOINT, rows_to_region(breakpoint_rows), S.REGION_SCOPE_BREAKPOINT, icon_enabled, sublime.HIDDEN)\\r\\n if disabled_rows and icon_disabled:\\r\\n view.add_regions(S.REGION_KEY_DISABLED, rows_to_region(disabled_rows), S.REGION_SCOPE_BREAKPOINT, icon_disabled, sublime.HIDDEN)\",\n \"def slice_graph_bwd( endea, reg ): \\r\\n\\tgraph = vcg_Graph.vcgGraph({\\\"title\\\":'\\\"Slice for %s\\\"' % reg, \\\\\\r\\n\\t\\t\\\"manhattan_edges\\\":\\\"no\\\", \\\"layoutalgorithm\\\":\\\"maxdepth\\\"})\\r\\n\\t#\\r\\n\\t# Retrieve the name of the current basic block\\r\\n\\t# \\r\\n\\tworklist = []\\r\\n\\tdata_bib = {}\\r\\n\\t\\r\\n\\tstartnode = slice_node( 0, endea, reg )\\t\\t# start at the end of the slice node\\r\\n\\trootnode = graph.Add_Node( startnode.to_name() )\\r\\n\\tdata_bib[ startnode.to_name() ] = startnode\\r\\n\\tworklist.insert( 0, rootnode )\\r\\n\\twhile len( worklist ) > 0:\\r\\n\\t\\tcurrnode = worklist.pop()\\r\\n\\t\\tcurrslice = data_bib[ currnode.get_name() ]\\r\\n\\t\\t[tgt_reg, split] = currslice.get_target_reg_bwd()\\r\\n\\t\\tprint tgt_reg\\r\\n\\t\\tprint split\\r\\n\\t\\tif tgt_reg == \\\"END\\\":\\r\\n\\t\\t\\t# Do not process this node any further\\r\\n\\t\\t\\tpass\\r\\n\\t\\telif tgt_reg == \\\"\\\" or (( len( currslice.get_lines()) > 0) and \\\\\\r\\n\\t\\t\\tcurrslice.startea != currslice.get_lines()[0][0]):\\r\\n\\t\\t\\t# Do process this node further, nothing really going on \\r\\n\\t\\t\\tprint \\\"ZEZ\\\"\\r\\n\\t\\t\\txrefs = get_crefs_to( currslice.startea )\\r\\n\\t\\t\\tfor ref in xrefs:\\r\\n\\t\\t\\t\\tnewslice = slice_node( 0,ref, currslice.reg )\\r\\n\\t\\t\\t\\tif graph.Get_Node( newslice.to_name() ) == 0:\\r\\n\\t\\t\\t\\t\\tnewnode = graph.Add_Node( newslice.to_name() )\\r\\n\\t\\t\\t\\t\\tworklist.insert( 0, newnode )\\r\\n\\t\\t\\t\\t\\tdata_bib[ newslice.to_name() ] = newslice\\r\\n\\t\\t\\t\\tgraph.Add_Link( newslice.to_name(), currnode.get_name() )\\r\\n\\t\\telse:\\r\\n\\t\\t\\txrefs = get_crefs_to( currslice.startea )\\r\\n\\t\\t\\tfor ref in xrefs:\\r\\n\\t\\t\\t\\tnewslice = slice_node( 0,ref, tgt_reg )\\r\\n\\t\\t\\t\\tif graph.Get_Node( newslice.to_name() ) == 0:\\r\\n\\t\\t\\t\\t\\tnewnode = graph.Add_Node( newslice.to_name() )\\r\\n\\t\\t\\t\\t\\tworklist.insert( 0, newnode )\\r\\n\\t\\t\\t\\t\\tdata_bib[ newslice.to_name() ] = newslice\\r\\n\\t\\t\\t\\tgraph.Add_Link( newslice.to_name(), currnode.get_name())\\r\\n\\t\\t\\txrefs = get_crefs_to( currslice.startea )\\r\\n\\t\\t\\tif split:\\r\\n\\t\\t\\t\\tfor ref in xrefs:\\r\\n\\t\\t\\t\\t\\tnewslice = slice_node( 0,ref, currslice.reg )\\r\\n\\t\\t\\t\\t\\tif graph.Get_Node( newslice.to_name() ) == 0:\\r\\n\\t\\t\\t\\t\\t\\tnewnode = graph.Add_Node( newslice.to_name() )\\r\\n\\t\\t\\t\\t\\t\\tworklist.insert( 0, newnode )\\r\\n\\t\\t\\t\\t\\t\\tdata_bib[ newslice.to_name() ] = newslice\\r\\n\\t\\t\\t\\t\\tgraph.Add_Link( newslice.to_name(), currnode.get_name())\\r\\n\\treturn [ graph, data_bib ]\",\n \"def shade(self):\\n if self.distribution_records:\\n path_nodes = self.svg_map.xpath(self.PATH_NODES_XPATH,\\n namespaces=NAMESPACES)\\n matching_regions = {}\\n for record in self.distribution_records:\\n region = STATES_MAP.get(record.value_str)\\n region = ((region in CANADIAN_PROVINCES and 'ca-' or 'us-') +\\n region)\\n matching_regions[region] = True\\n\\n for node in path_nodes:\\n if node.get('style'):\\n node_id = node.get('id').lower()\\n box = Path(node)\\n if node_id in matching_regions:\\n box.color(PRESENT_COLOR)\\n else:\\n box.color(ABSENT_COLOR)\\n return self\",\n \"def segment_red(img, yellow_thresh, red_thresh):\\n # 255 is white, Red, Green, Blue\\n # where green and yellow exists strongly set to 0\\n yellow_filter = (img[:, :, 1] < yellow_thresh)*numpy.ones((img.shape[0], img.shape[1]))\\n # where red and yellow doesnt exist set to 0\\n red_filter = (img[:, :, 2] > red_thresh)*numpy.ones((img.shape[0], img.shape[1]))\\n # TAKE THE INTERSECTION of SET A and B\\n total_filter = numpy.multiply(yellow_filter, red_filter)\\n img[:, :, 0] = 0\\n img[:, :, 1] = numpy.multiply(total_filter, img[:, :, 1])\\n img[:, :, 2] = numpy.multiply(total_filter, img[:, :, 2])\\n cv2.imwrite('segmented.png', img)\\n return img\",\n \"def mask_region(self, region, days=14):\\n i = self.Rs.index(region)\\n c_s = np.nonzero(np.cumsum(self.NewCases.data[i, :] > 0) == days + 1)[0][0]\\n d_s = np.nonzero(np.cumsum(self.NewDeaths.data[i, :] > 0) == days + 1)[0]\\n if len(d_s) > 0:\\n d_s = d_s[0]\\n else:\\n d_s = len(self.Ds)\\n\\n self.Active.mask[i, c_s:] = True\\n self.Confirmed.mask[i, c_s:] = True\\n self.Deaths.mask[i, d_s:] = True\\n self.NewDeaths.mask[i, d_s:] = True\\n self.NewCases.mask[i, c_s:] = True\\n\\n return c_s, d_s\",\n \"def resetCoronalSegment(self):\\r\\n #research\\r\\n profprint()\\r\\n sGreen = slicer.mrmlScene.GetNodeByID(\\\"vtkMRMLSliceNodeGreen\\\")\\r\\n if sGreen == None :\\r\\n sGreen = slicer.mrmlScene.GetNodeByID(\\\"vtkMRMLSliceNode3\\\")\\r\\n reformatLogic = slicer.vtkSlicerReformatLogic()\\r\\n #sGreen.SetSliceVisible(0)\\r\\n sGreen.SetOrientationToCoronal()\\r\\n #sw = slicer.app.layoutManager().sliceWidget(\\\"Green\\\")\\r\\n #sw.fitSliceToBackground()\\r\\n sGreen.Modified()\",\n \"def plot_timeline(self, param_name, start_time=None, stop_time=None, \\n provider=None, calib=False, max_pts=None):\\n\\n meta = self.get_param_info(param_name, mode='simple')\\n data = self.get_data(param_name, start_time, stop_time, provider, calib, max_pts)\\n data = data.squeeze()\\n\\n if data is None:\\n return None\\n\\n fig, ax = plt.subplots()\\n \\n # get a list of changes in the data\\n # changes = data[data.diff()!=0].index.tolist() # <-- does not work with strings\\n # changes = data[1:][data[1:].ne(data[1:].shift())].index.tolist()\\n changes = data[data.ne(data.shift())].index.tolist()\\n\\n # add the end of the last period\\n changes.append(data.index.max())\\n\\n # trying to do gap detection here to NOT fully shade areas where we have no data\\n # first finding the mean periodicity of the data\\n mean = data.index.to_series().diff().mean()\\n\\n # now flag periods where the gaps are 2x this\\n gap_ends = data[data.index.to_series().diff()>2*mean].index.tolist()\\n\\n # get the durations\\n durations = np.diff(changes)\\n\\n\\n\\n # make a colour index with the correct number of colors, spanning the colourmap\\n colours = cm.get_cmap('viridis')\\n\\n # get the list of unique values and create a colour list with this many entries\\n num_unique = len(data.unique())\\n colour_list = [colours(1.*i/num_unique) for i in range(num_unique)]\\n \\n # make a dictionary mapping unique values to colours\\n unique = data.unique().tolist()\\n colors = data[changes].map(dict(zip(unique, colour_list)))\\n\\n \\n\\n # now define the x and y ranges \\n xranges = [(stop, end) for stop, end in zip(changes, durations)]\\n yranges = (1, 0.5)\\n\\n # plot it using the broken horizontal bar function\\n ax.broken_barh(xranges, yranges, facecolors=colors, zorder=2)\\n \\n ax.set_title(meta['Description'])\\n ax.set_xlabel('Date (UTC)')\\n # if 'Unit' in meta.index:\\n # ax.set_ylabel(meta['Unit'])\\n # else:\\n # ax.set_ylabel('Calibrated') if calib else ax.set_ylabel('Raw')\\n fig.autofmt_xdate()\\n xfmt = md.DateFormatter('%Y-%m-%d %H:%M:%S')\\n ax.xaxis.set_major_formatter(xfmt)\\n\\n return ax\",\n \"def region_growing(imOr,reg,area,prof,conn,precision):\\n\\tif prof:\\n\\t\\tif area > 0.085:\\n\\t\\t\\treg1 = morph('erode',reg,25)\\n\\t\\t\\tif reg1.max() == 1.0:\\n\\t\\t\\t\\treg = reg1\\n\\t\\t\\telse:\\n\\t\\t\\t\\treg1 = morph('erode',reg,15)\\n\\t\\t\\t\\tif reg1.max() == 1.0:\\n\\t\\t\\t\\t\\treg = reg1\\n\\telse:\\n\\t\\tif area > 0.15:\\n\\t\\t\\treg1 = morph('erode',reg,15)\\n\\t\\t\\tif reg1.max() == 1.0:\\n\\t\\t\\t\\treg = reg1\\n\\n\\telementos = contar (reg,1)\\n\\tseguir = True\\n\\twhile seguir:\\n\\t\\treg = cv2.convertScaleAbs(reg)\\n\\t\\t_,contours, h = cv2.findContours(reg, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)\\n\\t\\treg[reg != 0] = 1\\n\\t\\tmedia_region = sum(imOr[reg==1])/max(cv2.contourArea(contours[0]),0.001)\\n\\n\\t\\tfor elemento in contours[0]:\\n\\t\\t\\tif prof:\\n\\t\\t\\t\\treg = expand(elemento,reg,imOr,media_region,precision/2,conn)\\n\\t\\t\\telse:\\n\\t\\t\\t\\treg = expand(elemento,reg,imOr,media_region,precision,conn)\\n\\t\\telementos_nuevo = contar (reg,1)\\n\\t\\tif elementos == elementos_nuevo:\\n\\t\\t\\tseguir = False\\n\\t\\telementos = elementos_nuevo\\n\\tse = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(5,5))\\n\\treg = cv2.dilate(reg.astype(np.float32),se,iterations = 3)\\n\\tse = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(5,5))\\n\\treg = cv2.erode(reg.astype(np.float32),se,iterations = 2)\\n\\n\\treturn reg\",\n \"def vis_mechanically_coupled_regions(img_dir,output_dir,data,dbscn_length,dbscn_min_size,display_not_save=False):\\n #Read in the image that is segmented/labelled for nuclei\\n img=imread(img_dir)\\n\\n #save plots to show clusters\\n fig = plt.figure(figsize=(6, 2))\\n ax0 = fig.add_subplot(131)\\n ax1 = fig.add_subplot(132)\\n ax3 = fig.add_subplot(133)\\n #show segmented image labels\\n ax0.imshow(img,aspect='auto') \\n ax0.axis('off')\\n #nuclear centroid color-coded by their orientation\\n img1=ax1.scatter(data[\\\"Y\\\"], data[\\\"X\\\"], c=data[\\\"angles\\\"],s=1)\\n ax1.set_xlim(0,img.shape[0])\\n ax1.set_ylim(img.shape[1],0)\\n plt.colorbar(img1)\\n ax1.axis('off')\\n\\n # plot the cluster assignments\\n img3=ax3.scatter(data[data[\\\"clusters\\\"]> -1][\\\"Y\\\"], data[data[\\\"clusters\\\"]> -1][\\\"X\\\"], \\n c=data[data[\\\"clusters\\\"]> -1][\\\"clusters\\\"],cmap=\\\"plasma\\\",s=1)\\n ax3.set_xlim(0,img.shape[0])\\n ax3.set_ylim(img.shape[1],0)\\n ax3.axis('off')\\n\\n #add titles\\n ax0.title.set_text('Segmented Image')\\n ax1.title.set_text('Filtered Orientation')\\n ax3.title.set_text('Clusters')\\n\\n if display_not_save:\\n plt.show()\\n else: \\n plt.savefig((output_dir+\\\"/\\\"+img_dir.rsplit('/', 1)[-1][:-4]+\\\"_\\\"+str(dbscn_length)+\\\"_\\\"+ str(dbscn_min_size)+\\\".png\\\"),dpi=600, bbox_inches = 'tight',pad_inches = 0)\\n fig.clf()\\n plt.close(fig)\\n plt.close('all')\\n \\n \\n del fig,ax0,ax1,ax3,img1,img3\",\n \"def _seg_image(self, x, y, r_cut=100):\\n snr=self.snr\\n npixels=self.npixels\\n bakground = self.bakground\\n error= self.bkg_rms(x,y,r_cut)\\n kernel = self.kernel\\n image_cutted = self.cut_image(x,y,r_cut)\\n image_data = image_cutted\\n threshold_detect_objs=detect_threshold(data=image_data, nsigma=snr,error=error)\\n segments=detect_sources(image_data, threshold_detect_objs, npixels=npixels, filter_kernel=kernel)\\n segments_deblend = deblend_sources(image_data, segments, npixels=npixels,nlevels=10)\\n segments_deblend_info = source_properties(image_data, segments_deblend)\\n nobjs = segments_deblend_info.to_table(columns=['id'])['id'].max()\\n xcenter = segments_deblend_info.to_table(columns=['xcentroid'])['xcentroid'].value\\n ycenter = segments_deblend_info.to_table(columns=['ycentroid'])['ycentroid'].value\\n image_data_size = np.int((image_data.shape[0] + 1) / 2.)\\n dist = ((xcenter - image_data_size) ** 2 + (ycenter - image_data_size) ** 2) ** 0.5\\n c_index = np.where(dist == dist.min())[0][0]\\n center_mask=(segments_deblend.data==c_index+1)*1 #supposed to be the data mask\\n obj_masks = []\\n for i in range(nobjs):\\n mask = ((segments_deblend.data==i+1)*1)\\n obj_masks.append(mask)\\n xmin = segments_deblend_info.to_table(columns=['bbox_xmin'])['bbox_xmin'].value\\n xmax = segments_deblend_info.to_table(columns=['bbox_xmax'])['bbox_xmax'].value\\n ymin = segments_deblend_info.to_table(columns=['bbox_ymin'])['bbox_ymin'].value\\n ymax = segments_deblend_info.to_table(columns=['bbox_ymax'])['bbox_ymax'].value\\n xmin_c, xmax_c = xmin[c_index], xmax[c_index]\\n ymin_c, ymax_c = ymin[c_index], ymax[c_index]\\n xsize_c = xmax_c - xmin_c\\n ysize_c = ymax_c - ymin_c\\n if xsize_c > ysize_c:\\n r_center = np.int(xsize_c)\\n else:\\n r_center = np.int(ysize_c)\\n center_mask_info= [center_mask, r_center, xcenter, ycenter, c_index]\\n return obj_masks, center_mask_info, segments_deblend\",\n \"def deleteSelectedSegs(self):\\n inds = []\\n for ix in range(len(self.picbuttons)):\\n if self.picbuttons[ix].mark == 'yellow':\\n inds.append(ix)\\n\\n if len(inds)==0:\\n print(\\\"No segments selected\\\")\\n return\\n\\n self.segsChanged = True\\n for ix in reversed(inds):\\n del self.segments[ix]\\n del self.picbuttons[ix]\\n\\n # update self.clusters, delete clusters with no members\\n todelete = []\\n for ID, label in self.clusters.items():\\n empty = True\\n for seg in self.segments:\\n if seg[-1] == ID:\\n empty = False\\n break\\n if empty:\\n todelete.append(ID)\\n\\n self.clearButtons()\\n\\n # Generate new class labels\\n if len(todelete) > 0:\\n keys = [i for i in range(self.nclasses) if i not in todelete] # the old keys those didn't delete\\n # print('old keys left: ', keys)\\n\\n nclasses = self.nclasses - len(todelete)\\n max_label = nclasses - 1\\n labels = []\\n c = self.nclasses - 1\\n while c > -1:\\n if c in keys:\\n labels.append((c, max_label))\\n max_label -= 1\\n c -= 1\\n\\n labels = dict(labels)\\n # print(labels)\\n\\n # update clusters dictionary {ID: cluster_name}\\n clusters = {}\\n for i in keys:\\n clusters.update({labels[i]: self.clusters[i]})\\n\\n print('before delete: ', self.clusters)\\n self.clusters = clusters\\n print('after delete: ', self.clusters)\\n\\n # update the segments\\n for seg in self.segments:\\n seg[-1] = labels[seg[-1]]\\n\\n self.nclasses = nclasses\\n\\n # redraw the buttons\\n self.updateButtons()\\n self.completeChanged.emit()\",\n \"def find_lines(\\n\\tthreshold, regions=None, direction=\\\"horizontal\\\", line_scale=15, iterations=0\\n):\\n\\tlines = []\\n\\n\\tif direction == \\\"vertical\\\":\\n\\t\\t#size = threshold.shape[0] // line_scale\\n\\t\\tsize = threshold.shape[0] // line_scale\\n\\t\\tel = cv2.getStructuringElement(cv2.MORPH_RECT, (1, size))\\n\\telif direction == \\\"horizontal\\\":\\n\\t\\tsize = threshold.shape[1] // line_scale\\n\\t\\tel = cv2.getStructuringElement(cv2.MORPH_RECT, (size, 1))\\n\\telif direction is None:\\n\\t\\traise ValueError(\\\"Specify direction as either 'vertical' or 'horizontal'\\\")\\n\\n\\tif regions is not None:\\n\\t\\tregion_mask = np.zeros(threshold.shape)\\n\\t\\tfor region in regions:\\n\\t\\t\\tx, y, w, h = region\\n\\t\\t\\tregion_mask[y : y + h, x : x + w] = 1\\n\\t\\tthreshold = np.multiply(threshold, region_mask)\\n\\n\\tthreshold = cv2.erode(threshold, el)\\n\\n\\tthreshold = cv2.dilate(threshold, el)\\n\\t##############################################\\n\\t#threshold = cv2.dilate(threshold,el,iterations=iterations)\\n\\t#threshold = cv2.erode(threshold,el,iterations=iterations)\\n\\t\\n\\t#threshold = cv2.dilate(threshold,el,iterations=iterations)\\n\\t#threshold = cv2.erode(threshold,el,iterations=iterations)\\n\\t####################################################\\n\\tdmask = cv2.dilate(threshold, el, iterations=iterations)\\n\\n\\ttry:\\n\\t\\t_, contours, _ = cv2.findContours(\\n\\t\\t\\tthreshold.astype(np.uint8), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE\\n\\t\\t)\\n\\texcept ValueError:\\n\\t\\t# for opencv backward compatibility\\n\\t\\tcontours, _ = cv2.findContours(\\n\\t\\t\\tthreshold.astype(np.uint8), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE\\n\\t\\t)\\n\\n\\tfor c in contours:\\n\\t\\tx, y, w, h = cv2.boundingRect(c)\\n\\t\\tx1, x2 = x, x + w\\n\\t\\ty1, y2 = y, y + h\\n\\t\\tif direction == \\\"vertical\\\":\\n\\t\\t\\tlines.append(((x1 + x2) // 2, y2, (x1 + x2) // 2, y1))\\n\\t\\telif direction == \\\"horizontal\\\":\\n\\t\\t\\tlines.append((x1, (y1 + y2) // 2, x2, (y1 + y2) // 2))\\n\\n\\treturn dmask, lines\",\n \"def closeRegions(regions):\\n for orig,table in regions.items():\\n for dest in table['neighbors']:\\n if not regions.has_key(dest):\\n regions[dest] = {'neighbors': set(),\\n 'value': 4}\\n regions[dest]['neighbors'].add(orig)\\n return regions\",\n \"def segment(segmentation_model, thresholds=None):\\n\\n if thresholds is None:\\n thresholds = DEFAULT_THRESHOLDS\\n\\n # Mark all flats\\n _set_flat_segments(segmentation_model, thresholds)\\n\\n yield None\\n\\n while (segmentation_model.phases == CurvePhases.UndeterminedNonFlat.value).any():\\n\\n # Mark linear slope\\n flanking = _set_nonflat_linear_segment(segmentation_model, thresholds)\\n\\n yield None\\n\\n if flanking.any():\\n\\n first_on_left_flank = flanking.argmin()\\n\\n for filt in _get_candidate_segment(flanking):\\n\\n direction = PhaseEdge.Right if \\\\\\n filt.argmin() == first_on_left_flank else \\\\\\n PhaseEdge.Left\\n\\n # Mark flanking non-linear phase\\n phase = _set_nonlinear_phase_type(segmentation_model, thresholds, filt, direction)\\n\\n if phase is CurvePhases.Undetermined:\\n # If no curved segment found, it is not safe to look for more\\n # non-flat linear phases because could merge two that should\\n # not be merged.\\n segmentation_model.phases[filt] = CurvePhases.UndeterminedNonLinear.value\\n\\n # Only look for the first non-linear segment rest is up for grabs for\\n # Next iteration of finding impulses or collapses\\n flanking[filt] = False\\n\\n yield None\\n\\n # Try to classify remaining positions as non linear phases\\n for filt in _get_candidate_segment(segmentation_model.phases, test_value=CurvePhases.UndeterminedNonLinear.value):\\n\\n phase = _set_nonlinear_phase_type(segmentation_model, thresholds, filt, PhaseEdge.Intelligent)\\n\\n yield None\\n\\n # If currently considered segment had no phase then it is undetermined\\n if phase is CurvePhases.Undetermined:\\n\\n segmentation_model.phases[filt] = phase.value\\n yield None\\n\\n # If there's an offset assume phase carries to edge\\n if segmentation_model.offset:\\n segmentation_model.phases[:segmentation_model.offset] = \\\\\\n segmentation_model.phases[segmentation_model.offset]\\n segmentation_model.phases[-segmentation_model.offset:] = \\\\\\n segmentation_model.phases[-segmentation_model.offset - 1]\\n yield None\\n\\n # Bridge neighbouring segments of same type if gap is one\\n _fill_undefined_gaps(segmentation_model.phases)\",\n \"def removeDots(image,points,coeff2,newColorArray):\\r\\n for i in range(1,coeff2):\\r\\n if (px[3,points*i] != (0,0,0)):\\r\\n im.putpixel((0,points*i-1),newColorArray[0][i-1])\\r\\n im.putpixel((1,points*i-1),newColorArray[0][i-1])\\r\\n im.putpixel((0,points*i),newColorArray[0][i])\\r\\n im.putpixel((1,points*i),newColorArray[0][i])\\r\\n im.putpixel((0,points*i+1),newColorArray[0][i])\\r\\n im.putpixel((1,points*i+1),newColorArray[0][i])\\r\\n if lineWidth==5:\\r\\n im.putpixel((0,points*i-2),newColorArray[0][i-1])\\r\\n im.putpixel((1,points*i-2),newColorArray[0][i-1])\\r\\n im.putpixel((0,points*i+2),newColorArray[0][i])\\r\\n im.putpixel((1,points*i+2),newColorArray[0][i])\\r\\n\\r\\n for i in range(1,coeff2):\\r\\n for j in range(1,coeff2):\\r\\n if (px[points*i-3,points*j] != (0,0,0) and px[points*i+3,points*j] != (0,0,0) and px[points*i,points*j-3] != (0,0,0) and px[points*i,points*j+3] != (0,0,0)):\\r\\n draw.line((points*i-5,points*j,points*i+5,points*j),fill=newColorArray[i][j],width=lineWidth)\\r\\n for i in range(1,coeff2):\\r\\n if px[points*i,500]!=(0,0,0):\\r\\n draw.line((points*i,500,points*i,511),fill=newColorArray[i][15],width=lineWidth)\\r\\n if px[500,points*i]!=(0,0,0):\\r\\n draw.line((500,points*i,511,points*i),fill=newColorArray[15][i],width=lineWidth)\",\n \"def detectBorders(self, points):\\n lane1 = []; lane2 = []\\n self.leftLane = [None for _ in range(int(np.floor(self.BIRDVIEW_HEIGHT / self.slideThickness)))]\\n self.rightLane = [None for _ in range(int(np.floor(self.BIRDVIEW_HEIGHT / self.slideThickness)))]\\n\\n pointMap = np.zeros((points.shape[0], 20))\\n prePoint = np.zeros((points.shape[0], 20))\\n postPoint = np.zeros((points.shape[0], 20))\\n\\n dis = 10\\n max1 = -1; max2 = -1\\n\\n ##\\n ## /!\\\\ UNSAFE LOOP, TODO: FIX\\n ##\\n for i in range(points.shape[0]):\\n for j in range(len(points[i])):\\n pointMap[i][j] = 1\\n prePoint[i][j] = -1\\n postPoint[i][j] = -1\\n\\n for i in reversed(range(points.shape[0] - 2)):\\n\\n for j in range(len(points[i])):\\n\\n err = 320\\n for m in range(1, min(points.shape[0] - 1 - i, 5)):\\n check = False ## TODO: why unused ?\\n\\n for k in range(len(points[i + 1])):\\n\\n (x_m, y_m) = points[i + m][k].pt\\n (x, y) = points[i][j].pt\\n\\n if (abs(x_m - x) < dis and abs(y_m - y) < err):\\n err = abs(x_m - x)\\n\\n pointMap[i][j] = pointMap[i + m][k] + 1\\n prePoint[i][j] = k\\n postPoint[i + m][k] = j\\n check = True\\n\\n break ## breaks out of the m loop. Why is it not conditioned by check ? TODO: ???\\n\\n if (pointMap[i][j] > max1):\\n max1 = pointMap[i][j]\\n posMax = cv2.KeyPoint(i, j, _size=0)\\n \\n else:\\n posMax = None\\n\\n for i in range(points.shape[0]):\\n for j in range(len(points[i])):\\n if posMax:\\n if (pointMap[i][j] > max2 and (i != posMax.pt[0] or j != posMax.pt[1]) and postPoint[i][j] == -1): #FIXME \\\"local variable 'posMax' referenced before assignment\\\" possible\\n max2 = pointMap[i][j]\\n posMax2 = cv2.KeyPoint(i, j, _size=0)\\n\\n\\n\\n if max1 == -1:\\n return\\n\\n # DEFINES LANE 1 POINTS\\n while (max1 >= 1):\\n (x,y) = points[int(posMax.pt[0])][int(posMax.pt[1])].pt\\n lane1.append(\\n [x,y]\\n )\\n if (max1 == 1):\\n break\\n\\n posMax = cv2.KeyPoint(\\n posMax.pt[0]+1,\\n prePoint[int(posMax.pt[0])][int(posMax.pt[1])],\\n _size=0\\n )\\n\\n max1 -= 1\\n\\n # DEFINES LANE 2 POINTS\\n while (max2 >= 1):\\n (x,y) = points[int(posMax2.pt[0])][int(posMax2.pt[1])].pt\\n lane2.append(\\n [x, y]\\n )\\n if (max2 == 1):\\n break\\n\\n posMax2 = cv2.KeyPoint(\\n posMax2.pt[0]+1,\\n prePoint[int(posMax2.pt[0])][int(posMax2.pt[1])],\\n _size=0\\n )\\n\\n max2-= 1\\n\\n subLane1 = np.array(lane1[0:5])\\n subLane2 = np.array(lane2[0:5])\\n\\n # checking if sublane has an empty value\\n\\n line1 = cv2.fitLine(subLane1, 2, 0, 0.01, 0.01)\\n line2 = cv2.fitLine(subLane2, 2, 0, 0.01, 0.01)\\n\\n try:\\n lane1X = (self.BIRDVIEW_WIDTH - line1[3]) * line1[0] / line1[1] + line1[2]\\n except:\\n lane1X = 0\\n\\n try:\\n lane2X = (self.BIRDVIEW_WIDTH - line2[3]) * line2[0] / line2[1] + line2[2]\\n except:\\n lane2X = 0\\n \\n if (lane1X < lane2X):\\n for i in range(len(lane1)):\\n self.leftLane[int(np.floor(lane1[i][1] / self.slideThickness ))] = lane1[i]\\n\\n for i in range(len(lane2)):\\n self.rightLane[int(np.floor(lane2[i][1] / self.slideThickness ))] = lane2[i]\\n\\n else:\\n\\n for i in range(len(lane1)):\\n self.rightLane[int(np.floor(lane1[i][1] / self.slideThickness ))] = lane1[i]\\n\\n for i in range(len(lane2)):\\n self.leftLane[int(np.floor(lane2[i][1] / self.slideThickness ))] = lane2[i]\",\n \"def segment_cells(frame, mask=None):\\n \\n blurred = filters.gaussian(frame, 2)\\n ridges = enhance_ridges(frame)\\n \\n # threshold ridge image\\n thresh = filters.threshold_otsu(ridges)\\n thresh_factor = 0.5\\n prominent_ridges = ridges > thresh_factor*thresh\\n prominent_ridges = morphology.remove_small_objects(prominent_ridges, min_size=256)\\n prominent_ridges = morphology.binary_closing(prominent_ridges)\\n prominent_ridges = morphology.binary_dilation(prominent_ridges)\\n \\n # skeletonize\\n ridge_skeleton = morphology.medial_axis(prominent_ridges)\\n ridge_skeleton = morphology.binary_dilation(ridge_skeleton)\\n ridge_skeleton *= mask\\n ridge_skeleton = np.bitwise_xor(ridge_skeleton, mask)\\n \\n # label\\n cell_label_im = measure.label(ridge_skeleton)\\n \\n # morphological closing to fill in the cracks\\n for cell_num in range(1, cell_label_im.max()+1):\\n cell_mask = cell_label_im==cell_num\\n cell_mask = morphology.binary_closing(cell_mask, disk(3))\\n cell_label_im[cell_mask] = cell_num\\n \\n return cell_label_im\",\n \"def _cons_traj(self,lon,lat,period):\\n\\t\\tgroup = self['%g_sec'%( period )]\\n\\t\\tlonArr = group['lonArr'].value\\n\\t\\tlatArr = group['latArr'].value\\n\\t\\tageArr = group['age_Arr'].value\\n\\t\\tage_drv_lon = group['age_deriv_lon_Arr']\\n\\t\\tage_drv_lat = group['age_deriv_lat_Arr']\\n\\t\\tage_drv_msk = group['age_deriv_msk_Arr']\\n\\t\\ttomo_data_msk = group['tomo_data_msk'].value\\n\\t\\tmask_init = np.logical_or(tomo_data_msk, age_drv_msk)\\n\\t\\tmask = np.array(np.ones(lonArr.shape),dtype=bool)\\n\\t\\ti_s, j_s = self._find_nearest_grid(lon,lat,period) # find the 1st and 2nd index of the start point on grid\\n\\t\\tif mask_init[i_s,j_s]:\\n\\t\\t\\traise ValueError(\\\"The starting point is out bounds of the resulting map\\\")\\n\\t\\tmask[i_s,j_s] = False\\n\\t\\t# go along increasing age direction\\n\\t\\ti,j = _walk(age_drv_lon,age_drv_lat,i_s,j_s,1)\\n\\t\\twhile (0<i<lonArr.shape[0] and 0<j<lonArr.shape[1]):\\n\\t\\t\\tif mask_init[i,j]:\\n\\t\\t\\t\\tbreak\\n\\t\\t\\telse:\\n\\t\\t\\t\\tmask[i,j] = False\\n\\t\\t\\ti,j = _walk(age_drv_lon,age_drv_lat,i,j,1)\\n\\t\\t\\t\\n\\t\\t# go along descending age direction\\n\\t\\ti_2,j_2 = _walk(age_drv_lon,age_drv_lat,i_s,j_s,-1)\\n\\t\\tmask[i_2,j_2] = False\\n\\t\\twhile (0<i_2<lonArr.shape[0] and 0<j_2<lonArr.shape[1]):\\n\\t\\t\\tif mask_init[i_2,j_2]:\\n\\t\\t\\t\\tbreak\\n\\t\\t\\telse:\\n\\t\\t\\t\\tmask[i_2,j_2] = False\\n\\t\\t\\tage_b = ageArr[i_2,j_2]\\n\\t\\t\\ti_b,j_b = i_2,j_2\\n\\t\\t\\ti_2,j_2 = _walk(age_drv_lon,age_drv_lat,i_2,j_2,-1)\\n\\t\\t\\tif ageArr[i_2,j_2] > age_b: # find the youngest age\\n\\t\\t\\t\\ti_3,j_3 = i_b,j_b\\n\\t\\t\\t\\tbreak\\n\\t\\ttry:\\n\\t\\t\\ti_3\\n\\t\\texcept NameError:\\n\\t\\t\\treturn mask\\n\\t\\t\\n\\t\\t# go along increasing age from the found youngest age\\n\\t\\twhile (0<i_3<lonArr.shape[0] and 0<j_3<lonArr.shape[1]):\\n\\t\\t\\tif mask_init[i_3,j_3]:\\n\\t\\t\\t\\tbreak\\n\\t\\t\\telse:\\n\\t\\t\\t\\tmask[i_3,j_3] = False\\n\\t\\t\\ti_3,j_3 = _walk(age_drv_lon,age_drv_lat,i_3,j_3,1)\\n\\t\\treturn mask\",\n \"def _draw_segments(frame, segments):\\n for segment in segments:\\n cv2.line(frame, segment[0], segment[1],\\n color=(0, 255, 255), thickness=2)\\n cv2.circle(frame, segment[0], radius=3,\\n color=(255, 0, 0), thickness=-1)\\n cv2.circle(frame, segment[1], radius=3,\\n color=(255, 0, 0), thickness=-1)\",\n \"def overlay_segmentation(image_bgr,\\n segmentation,\\n colormap=cv2.COLORMAP_PARULA,\\n alpha=0.6,\\n inplace=True):\\n if inplace:\\n image_target_bgr = image_bgr\\n else:\\n image_target_bgr = image_bgr * 0\\n\\n bbox_xywh = segmentation['bbox']\\n x, y, w, h = [int(v) for v in bbox_xywh]\\n if w <= 0 or h <= 0:\\n return image_bgr\\n\\n segm = segmentation['segm']\\n levels = 255.0 / segm.max()\\n mask_bg = np.tile((segm == 0)[:, :, np.newaxis], [1, 1, 3])\\n\\n segm = segm.astype(np.float32) * levels\\n segm = segm.clip(0, 255).astype(np.uint8)\\n segm = cv2.applyColorMap(segm, cv2.COLORMAP_PARULA)\\n\\n segm[mask_bg] = image_target_bgr[y:y + h, x:x + w, :][mask_bg]\\n\\n # img_hsv = cv2.cvtColor(image_bgr, cv2.COLOR_BGR2HSV)\\n # segm_hsv = cv2.cvtColor(segm, cv2.COLOR_BGR2HSV)\\n\\n image_target_bgr[y:y + h, x:x + w, :] = (image_target_bgr[y:y + h, x:x + w, :] * (1.0 - alpha) +\\n segm * alpha)\\n\\n return image_target_bgr.astype(np.uint8)\",\n \"def region_graph(t0, t1, t2, t3):\\r\\n medians0 = sorted(sub_saharan_africa_countries())\\r\\n t0.goto(-250, ((medians0[0])-50))\\r\\n t0.rt(90)\\r\\n for idx in range(1, len(medians0)):\\r\\n t0.pencolor(\\\"blue\\\")\\r\\n t0.pd()\\r\\n t0.setpos((-250+(idx*10.5)), ((medians0[idx])))\\r\\n\\r\\n medians1 = sorted(south_asia_countries())\\r\\n t1.goto(-250, ((medians1[0]) - 60))\\r\\n t1.rt(90)\\r\\n for idx in range(1, len(medians1)):\\r\\n t1.pencolor(\\\"red\\\")\\r\\n t1.pd()\\r\\n t1.setpos((-250 + (idx * 68.5)), (2*(medians1[idx])+10))\\r\\n\\r\\n medians2 = sorted(europe_central_asia_countries())\\r\\n t2.goto(-250, (medians2[0])+60)\\r\\n t2.rt(90)\\r\\n for idx in range(1, len(medians2)):\\r\\n t2.pencolor(\\\"green\\\")\\r\\n t2.pd()\\r\\n t2.setpos((-250 + (idx*10.19)), (2 * (medians2[idx]) + 10))\\r\\n\\r\\n medians3 = sorted(latin_america_countries())\\r\\n t3.goto(-250, (medians3[0]) + 20)\\r\\n t3.rt(90)\\r\\n for idx in range(1, len(medians3)):\\r\\n t3.pencolor(\\\"gold\\\")\\r\\n t3.pd()\\r\\n t3.setpos((-250 + (idx * 14.39)), (2 * (medians3[idx]) + 10))\\r\\n\\r\\n t0.pu()\\r\\n t0.goto(initialCoordinates())\\r\\n t1.pu()\\r\\n t1.goto(initialCoordinates())\\r\\n t2.pu()\\r\\n t2.goto(initialCoordinates())\\r\\n t3.pu()\\r\\n t3.goto(initialCoordinates())\\r\\n\\r\\n medians4 = sorted(middle_east_countries())\\r\\n t0.goto(-250, (medians4[0])-40)\\r\\n t0.rt(90)\\r\\n for idx in range(1, len(medians4)):\\r\\n t0.pencolor(\\\"BLACK\\\")\\r\\n t0.pd()\\r\\n t0.setpos((-250 + (idx * 26.3)), (2 * (medians4[idx]) + 10))\\r\\n t0.rt(180)\\r\\n\\r\\n medians5 = sorted(north_america_countries())\\r\\n t1.goto(-250, (medians5[0])+60)\\r\\n t1.rt(90)\\r\\n for idx in range(1, len(medians5)):\\r\\n t1.pencolor(\\\"YELLOW\\\")\\r\\n t1.pd()\\r\\n t1.setpos((-250 + (idx * 485.3)), (2 * (medians5[idx]) + 10))\\r\\n t1.rt(180)\\r\\n\\r\\n medians6 = sorted(east_asia_pacific_countries())\\r\\n t2.goto(-250, (medians6[0]))\\r\\n t2.rt(90)\\r\\n for idx in range(1, len(medians6)):\\r\\n t2.pencolor(\\\"purple\\\")\\r\\n t2.pd()\\r\\n t2.setpos((-250 + (idx * 16)), (2 * (medians6[idx]) + 10))\\r\\n t0.pu()\\r\\n t0.goto(initialCoordinates())\\r\\n t1.pu()\\r\\n t1.goto(initialCoordinates())\\r\\n t2.pu()\\r\\n t2.goto(initialCoordinates())\",\n \"def getsegs (bounds, split):\\n segmentslist=bisect_rectange(split, bounds[0], bounds[1], bounds[2], bounds[3])\\n count=1\\n segpass=0\\n \\n #Get list of segment ids currently in database\\n query=\\\"\\\"\\\"select seg_id from segment;\\\"\\\"\\\"\\n df = pd.read_sql_query(query,con=engine)\\n segids=set(df.seg_id)\\n \\n while count < len(segmentslist):\\n try:\\n for i in segmentslist:\\n segments=getsegmentinfo(i)\\n \\n \\n for seg in segments:\\n #If running function several times for different splits, this ignores existing segments and prints a message\\n if seg.id in segids: \\n segpass+=1\\n if (segpass % 10 == 0): \\n print (\\\"{} segments already exist\\\".format(segpass))\\n #Else this is a new segment, so get details from the strava and geocodio apis and save them to a dataframe and eventually to the database\\n else:\\n location = geocodio_client.reverse((seg.start_latlng[0], seg.start_latlng[1]))\\n zipcode=location['results'][0]['address_components']['zip']\\n \\n newrow = {'seg_id' : seg.id,\\n 'resource_state': seg.resource_state,\\n 'climb_category':seg.climb_category,\\n 'climb_category_desc':seg.climb_category_desc,\\n 'average_grade':seg.avg_grade,\\n 'elev_difference': str(seg.elev_difference).split()[0],\\n 'distance': str(seg.distance).split()[0],\\n 'name' : seg.name,\\n 'start_lat' : seg.start_latlng[0],\\n 'start_long' : seg.start_latlng[1],\\n 'end_lat' : seg.end_latlng[0],\\n 'end_long' : seg.end_latlng[1],\\n 'points' : seg.points,\\n 'starred':seg.starred,\\n 'zipcode':zipcode\\n }\\n df=pd.DataFrame(newrow, index=[0])\\n \\n try:\\n #Save dataframe to database\\n df.to_sql('segment', engine,index=False,if_exists='append')\\n except:\\n pass\\n\\n #Prints message which keeps track of number of sub bounds completed \\n if (count % 10) == 0:\\n print (\\\"Getting segments in bound {} of {}\\\".format(count, len(segmentslist)))\\n count+=1\\n except Exception as inst:\\n print (inst) \\n return None\",\n \"def consecutive_sections(): # noqa: D416\",\n \"def test_segmentation_functions(sersic_2d_image):\\n\\n image_mean, image_median, image_stddev = sigma_clipped_stats(sersic_2d_image, sigma=3)\\n threshold = image_stddev * 3\\n npixels = 4 ** 2\\n\\n # Testing make_segments\\n segm = pf.make_segments(sersic_2d_image, npixels=npixels, threshold=threshold)\\n\\n assert isinstance(segm, SegmentationImage)\\n assert segm.shape == sersic_2d_image.shape\\n assert np.all(segm.data >= 0)\\n assert len(np.unique(segm.data)) == 2 # account for background being labeled as 0\\n\\n # Testing deblend_segments\\n segm_deblend = pf.deblend_segments(sersic_2d_image, segm, npixels=npixels, contrast=0.00)\\n\\n assert isinstance(segm_deblend, SegmentationImage)\\n assert segm_deblend.shape == sersic_2d_image.shape\\n assert np.all(segm_deblend.data >= 0)\\n assert len(np.unique(segm_deblend.data)) >= len(np.unique(segm.data))\",\n \"def test_burst_dispersion(self):\\n # some reproducible arbitrariness\\n np.random.seed(7342642)\\n\\n n = 25\\n t_max = 50\\n dt = 0.1\\n n_sim = 10\\n \\n G = HVCLikeLayer(n)\\n\\n burst_starts = []\\n for i in xrange(n_sim):\\n M = simulation.EventMonitor(G)\\n sim = simulation.Simulation(G, M, dt=dt)\\n sim.run(t_max)\\n\\n # split spikes by neuron index\\n spikes = [np.asarray(M.t)[np.asarray(M.i) == i] for i in xrange(n)]\\n burst_starts.append([_[0] for _ in spikes])\\n\\n burst_starts_range = [np.ptp([_[i] for _ in burst_starts])\\n for i in xrange(n)]\\n \\n self.assertLess(np.max(burst_starts_range), G.burst_noise + dt/2)\",\n \"def areasShaded(self):\\n global area_ABE\\n area_ABE = always_redraw(\\n lambda : Polygon(dot_center.get_center(), radius_ang_end_dot.get_center(), dropped_dot.get_center(),\\n color=PINK, fill_color=PINK, fill_opacity=0.5)\\n )\\n global area_ABE_copy\\n area_ABE_copy = area_ABE.copy()\\n\\n self.play(Write(area_ABE))\\n self.wait(0.5)\\n self.play(area_ABE_copy.animate.move_to(consider_area_text.get_center()+DOWN*1.5+LEFT*1.5))\\n\\n global area_ABD\\n area_ABD = always_redraw(\\n lambda : Sector(outer_radius=self.x_max, start_angle=0, angle=theta.get_value()*DEGREES,\\n stroke_width=DEFAULT_STROKE_WIDTH , stroke_color=BLUE, color=BLUE, fill_opacity=0.5).shift(LEFT*5)\\n )\\n global area_ABD_copy\\n area_ABD_copy = area_ABD.copy()\\n\\n self.play(Write(area_ABD))\\n self.wait(0.5)\\n self.play(area_ABD_copy.animate.move_to(consider_area_text.get_center()+DOWN*1.5+RIGHT*1.5))\\n\\n global area_ABC\\n area_ABC = always_redraw(\\n lambda : Polygon(dot_center.get_center(), radius_ang_end_dot.get_center(), small_tangent_end_dot.get_center(),\\n color=GREEN, fill_color=GREEN, fill_opacity=0.5)\\n )\\n global area_ABC_copy\\n area_ABC_copy = area_ABC.copy()\\n\\n self.play(Write(area_ABC))\\n self.wait(0.5)\\n self.play(area_ABC_copy.animate.move_to(consider_area_text.get_center()+DOWN*3.5))\\n\\n self.play(FadeOut(consider_area_text))\",\n \"def __iteratively_retain(\\n self,\\n orf_regions: List[Tuple[int, int]]) -> List[Tuple[int, int]]:\\n\\n ret = []\\n\\n arr = np.zeros((len(self.seq), ))\\n\\n for start, end in orf_regions:\\n ret.append((start, end))\\n arr[start-1:end] = 1\\n orf_coverage = np.sum(arr) / len(arr)\\n if orf_coverage > self.min_orf_coverage:\\n break\\n\\n return ret\",\n \"def split(self,i):\\n alpha = 0.6\\n eps = 2.6\\n\\n if self.n > self.maxn-3:\\n print \\\"cannot refine any further\\\"\\n return False\\n \\n # The son \\n self.m[i] = self.m[i] / 4.0\\n #self.h[i] = self.h[i] * alpha\\n\\n # Daughter 1\\n self.r[self.n] = self.r[i] + eps*np.array([0,1])\\n self.m[self.n] = self.m[i] \\n self.v[self.n] = self.v[i]\\n \\n # Daughter 2\\n self.r[self.n+1] = self.r[i] + eps*np.array([0.866025,-0.5])\\n self.m[self.n+1] = self.m[i] \\n self.v[self.n+1] = self.v[i]\\n \\n # Daughter 3\\n self.r[self.n+2] = self.r[i] + eps*np.array([-0.866025,-0.5])\\n self.m[self.n+2] = self.m[i] \\n self.v[self.n+2] = self.v[i]\\n \\n self.n = self.n+3\\n #print \\\"There are now \\\",self.n,\\\"particles\\\"\\n return True\",\n \"def dark_cloud(self):\\n self.data['dark_cloud'] = ((self.data['Close'].shift(1) > self.data['Open'].shift(1)) & \\\\\\n (((self.data['Close'].shift(1) + self.data['Open'].shift(1)) / 2) > self.data['Close']) & \\\\\\n (self.data['Open'] > self.data['Close']) & (self.data['Open'] > self.data['Close'].shift(1)) &\\\\\\n (self.data['Close'] > self.data['Open'].shift(1)) & \\\\\\n ((self.data['Open'] - self.data['Close']) / (.001 + (self.data['High'] - self.data['Low'])) > .6))\",\n \"def region_growing_from_input(self, color, bone_from_scan=None):\\n collect()\\n # initilize\\n if not bone_from_scan:\\n self.load_original_data()\\n else:\\n self.copy_original_from_bone(bone_from_scan)\\n checked = zeros(self._original_img_data.shape)\\n seg = zeros(self._original_img_data.shape)\\n need_to_check = []\\n # Color the seeds and check for neighbors\\n for seed in self._seeds_points:\\n seg[seed] = color\\n checked[seed] = 1\\n neighbors = self._get_neighbors(seed, checked, self.\\n _original_img_data.shape)\\n for neighbor in neighbors:\\n if self._get_threshold(self._original_img_data[neighbor],\\n VOID_VALUES[0],\\n VOID_VALUES[1]):\\n need_to_check.append(neighbor)\\n # Region Growing - while there's a neighbor, color it and keep going\\n bone_to_check = []\\n while need_to_check:\\n pt = need_to_check.pop()\\n if checked[pt] == 1:\\n continue\\n else:\\n checked[pt] = 1\\n neighbors = self._get_neighbors(pt, checked, self.\\n _original_img_data.shape)\\n for neighbor in neighbors:\\n if self._get_threshold(\\n self._original_img_data[neighbor],\\n VOID_VALUES[0], VOID_VALUES[1]):\\n need_to_check.append(neighbor)\\n if self._get_threshold(\\n self._original_img_data[neighbor],\\n BONE_BOUND_VALUES[0], BONE_BOUND_VALUES[1]):\\n bone_to_check.append(neighbor)\\n seg[pt] = color\\n # Closing holes\\n del need_to_check\\n # check for Bone value - edge of the radius\\n while bone_to_check:\\n pt = bone_to_check.pop()\\n if checked[pt] == 1:\\n continue\\n else:\\n checked[pt] = 1\\n neighbors = self._get_neighbors(pt, checked, self.\\n _original_img_data.shape)\\n for neighbor in neighbors:\\n if self._get_threshold(\\n self._original_img_data[neighbor],\\n RADIUS_VALUES[0], RADIUS_VALUES[1]):\\n bone_to_check.append(neighbor)\\n seg[pt] = color\\n del checked, bone_to_check\\n for i in range(self._dilation):\\n seg = dilation(seg, cube(3, uint8))\\n for i in range(self._dilation - 1):\\n seg = erosion(seg, cube(3, uint8))\\n self._segmentation_data = seg\\n del seg\\n collect()\",\n \"def fix_straight_lines(self):\\r\\n\\r\\n # Creates a vertical 1x5 kernel and applies binary closing based on that kernel\\r\\n vertical_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (1, 5))\\r\\n self.thresh_invert = cv2.morphologyEx(self.thresh_invert, cv2.MORPH_CLOSE, vertical_kernel, iterations=9)\\r\\n\\r\\n # Creates a horizontal 5x1 kernel and applies binary closing based on that kernel\\r\\n horizontal_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 1))\\r\\n self.thresh_invert = cv2.morphologyEx(self.thresh_invert, cv2.MORPH_CLOSE, horizontal_kernel, iterations=4)\",\n \"def test_burst_dispersion(self):\\n # some reproducible arbitrariness\\n np.random.seed(7342642)\\n\\n n = 25\\n t_max = 50\\n dt = 0.1\\n n_sim = 10\\n \\n G = RateHVCLayer(n)\\n\\n burst_starts = []\\n for i in xrange(n_sim):\\n M = simulation.StateMonitor(G, 'out')\\n sim = simulation.Simulation(G, M, dt=dt)\\n sim.run(t_max)\\n\\n burst_starts.append([dt*min((M.out[i] > 0).nonzero()[0])\\n for i in xrange(n)])\\n\\n burst_starts_range = [np.ptp([_[i] for _ in burst_starts])\\n for i in xrange(n)]\\n \\n self.assertLess(np.max(burst_starts_range), G.burst_noise + dt/2)\",\n \"def BraceBadLight(self, pos):\\n # Check if we are still alive or not, as this may be called\\n # after we have been deleted.\\n if self:\\n super(EditraBaseStc, self).BraceBadLight(pos)\",\n \"def draw_visible_area(self):\\n\\n if not self.given_center:\\n return\\n\\n # Figure out what regions we should be showing\\n horiz_width = self.hbar.pageStep()\\n gui_start_x = self.hbar.value()\\n vert_height = self.vbar.pageStep()\\n gui_start_y = self.vbar.value()\\n (game_min_x, game_max_y) = self.scene_to_ingame(gui_start_x, gui_start_y)\\n (game_max_x, game_min_y) = self.scene_to_ingame(\\n gui_start_x + horiz_width,\\n gui_start_y + vert_height,\\n )\\n min_rx = game_min_x//32 - 1\\n max_rx = game_max_x//32 + 1\\n min_ry = game_min_y//32 - 1\\n max_ry = game_max_y//32 + 1\\n\\n # First find out how many regions we're going to have to load (so that\\n # we can initialize a progressbar)\\n valid_regions = set()\\n regions_to_load = []\\n for rx in range(min_rx, max_rx+1):\\n for ry in range(min_ry, max_ry+1):\\n region = (rx, ry)\\n valid_regions.add(region)\\n if region in self.regions:\\n if not self.regions[region].loaded:\\n regions_to_load.append(region)\\n\\n # Initialize progressbar\\n region_loading = self.mainwindow.region_loading\\n region_loading.start(len(regions_to_load))\\n\\n # Now actually do the loading\\n for idx, region in enumerate(regions_to_load):\\n #print('Loading region {}'.format(region))\\n self.regions[region].load()\\n self.loaded_regions.add(region)\\n region_loading.update(idx)\\n\\n # Unload regions which are too far out\\n regions_to_unload = []\\n for region in list(self.loaded_regions):\\n if region not in valid_regions:\\n regions_to_unload.append(region)\\n\\n region_loading.start(len(regions_to_unload), label='Unloading Regions')\\n for idx, region in enumerate(regions_to_unload):\\n #print('Unloading region {}'.format(region))\\n self.regions[region].unload()\\n self.loaded_regions.remove(region)\\n region_loading.update(idx)\\n\\n # Finish our progress bar\\n region_loading.finish()\",\n \"def discriminator(time,signal,height_th,dt_left=300e-9,dt_right=1400e-9,Plot=False, method=0):\\n dt = time[1] - time[0]\\n bins_left = int(dt_left / dt)\\n bins_right = int(dt_right / (time[1] - time[0]))\\n bins_final = len(time) - 1\\n\\n # where signal is above threshold\\n initial_window = np.array(np.where(signal > height_th)[0])\\n mask = initial_window\\n if len(mask) > 0:\\n if method == 0:\\n\\n # MASK METHOD 1: include regions left and right of signal above\\n # threshold.\\n for i in np.arange(len(initial_window)) - 1:\\n if (initial_window[i + 1] - initial_window[i] < bins_right + bins_left):\\n mask = array_fill_between(\\n mask, initial_window[i], initial_window[i + 1])\\n else:\\n mask = array_fill_between(\\n mask, initial_window[i], initial_window[i] + bins_right)\\n mask = array_fill_between(\\n mask, initial_window[i + 1] - bins_left, initial_window[i + 1])\\n # right most pulse close to edge but doesn't exceed\\n if mask[-1] + bins_right <= bins_final:\\n mask = array_fill_between(\\n mask, mask[-1], mask[-1] + bins_right)\\n else:\\n # right most pulse exceeds right edge of trace: include mask up to end of pulse\\n # bins_final+1 term includes one more index since fill_between\\n # fills up to bins_final\\n mask = array_fill_between(mask, mask[-1], bins_final + 1)\\n if mask[0] - bins_left >= 0: # left most pulse close to edge but doesn't exceed\\n mask = array_fill_between(mask, mask[0] - bins_left, mask[0])\\n else:\\n # left most pulse exceeds left edge of trace\\n # 0-1 term includes one more index '-1' since fill_between\\n # fills from 0\\n mask = array_fill_between(mask, 0 - 1, mask[0])\\n\\n if method == 1:\\n # MASK METHOD 2: SR LATCH\\n mask = srlatch_full(signal, 0, height_th)\\n\\n # MASK METHOD 1: include regions left and right of signal above threshold.\\n for i in np.arange(len(initial_window))-1:\\n if (initial_window[i+1]-initial_window[i] < bins_right+bins_left):\\n mask = array_fill_between(mask, initial_window[i], initial_window[i+1])\\n else:\\n mask = array_fill_between(mask, initial_window[i], initial_window[i]+bins_right)\\n mask = array_fill_between(mask, initial_window[i+1]-bins_left, initial_window[i+1])\\n if mask[-1]+bins_right <= bins_final: #right most pulse close to edge but doesn't exceed\\n mask = array_fill_between(mask, mask[-1], mask[-1]+bins_right)\\n else: \\n #right most pulse exceeds right edge of trace: include mask up to end of pulse\\n #bins_final+1 term includes one more index since fill_between fills up to bins_final\\n mask = array_fill_between(mask, mask[-1], bins_final+1)\\n if mask[0]-bins_left >= 0: #left most pulse close to edge but doesn't exceed\\n mask = array_fill_between(mask, mask[0]-bins_left, mask[0])\\n else: \\n #left most pulse exceeds left edge of trace\\n #0-1 term includes one more index '-1' since fill_between fills from 0\\n mask = array_fill_between(mask, 0-1, mask[0])\\n \\n\\n if method == 2:\\n # MASK METHOD 3: rev SR LATCH\\n initial_window = np.where(srlatch_rev(signal, 0, height_th))[0]\\n \\n # MANUAL INCLUSION OF ADDITIONAL PULSE REGIONS, since srlatch_rev does not include the full pulse \\n mask = initial_window\\n\\n for i in np.arange(len(initial_window)) - 1:\\n if (initial_window[i + 1] - initial_window[i] < bins_right + bins_left):\\n mask = array_fill_between(\\n mask, initial_window[i], initial_window[i + 1])\\n else:\\n mask = array_fill_between(\\n mask, initial_window[i], initial_window[i] + bins_right)\\n mask = array_fill_between(\\n mask, initial_window[i + 1] - bins_left, initial_window[i + 1])\\n # right most pulse close to edge but doesn't exceed\\n if mask[-1] + bins_right <= bins_final:\\n mask = array_fill_between(\\n mask, mask[-1], mask[-1] + bins_right)\\n else:\\n # right most pulse exceeds right edge of trace: include mask up to end of pulse\\n # bins_final+1 term includes one more index since fill_between\\n # fills up to bins_final\\n mask = array_fill_between(mask, mask[-1], bins_final + 1)\\n if mask[0] - bins_left >= 0: # left most pulse close to edge but doesn't exceed\\n mask = array_fill_between(mask, mask[0] - bins_left, mask[0])\\n else:\\n # left most pulse exceeds left edge of trace\\n # 0-1 term includes one more index '-1' since fill_between\\n # fills from 0\\n mask = array_fill_between(mask, 0 - 1, mask[0])\\n\\n # transforms index mask into boolean mask\\n\\n for i in np.arange(len(initial_window))-1:\\n if (initial_window[i+1]-initial_window[i] < bins_right+bins_left):\\n mask = array_fill_between(mask, initial_window[i], initial_window[i+1])\\n else:\\n mask = array_fill_between(mask, initial_window[i], initial_window[i]+bins_right)\\n mask = array_fill_between(mask, initial_window[i+1]-bins_left, initial_window[i+1])\\n \\n if mask[-1]+bins_right <= bins_final: #right most pulse close to edge but doesn't exceed\\n mask = array_fill_between(mask, mask[-1], mask[-1]+bins_right)\\n else: \\n #right most pulse exceeds right edge of trace: include mask up to end of pulse\\n #bins_final+1 term includes one more index since fill_between fills up to bins_final\\n mask = array_fill_between(mask, mask[-1], bins_final+1)\\n if mask[0]-bins_left >= 0: #left most pulse close to edge but doesn't exceed\\n mask = array_fill_between(mask, mask[0]-bins_left, mask[0])\\n else: \\n #left most pulse exceeds left edge of trace\\n #0-1 term includes one more index '-1' since fill_between fills from 0\\n mask = array_fill_between(mask, 0-1, mask[0])\\n\\n if method == 3:\\n # MASK METHOD 4: SR LATCH (CONVENTIONAL)\\n mask = srlatch(signal, 0, height_th)\\n\\n #transforms index mask into boolean mask\\n\\n mask_boolean = np.zeros(len(time), dtype=int)\\n mask_boolean[mask] = 1\\n mask = mask_boolean\\n\\n edges = np.diff(mask * 1) # left edge = 1, right edge = -1\\n\\n # find indices of left and right edges of pulses\\n right_edges = np.array(np.where(edges < 0), dtype='int64').flatten()\\n left_edges = np.array(np.where(edges > 0), dtype='int64').flatten()\\n clamp = np.zeros(len(time))\\n\\n if (len(left_edges) > 0)and(len(right_edges > 0)):\\n for i in np.arange(len(time)):\\n if left_edges[0] <= i <= right_edges[-1]:\\n clamp[i] = 1\\n\\n clamp = np.array(clamp, dtype='bool')\\n mask = np.array(mask, dtype='bool')\\n # print clamp,edges,left_edges,right_edges\\n\\n if Plot:\\n plt.figure()\\n plt.plot(time, signal)\\n plt.hlines(height_th, time[0], time[1], linestyle='--')\\n plt.plot(time, mask * np.max(signal), label='mask')\\n plt.plot(time[1:], edges * np.max(signal), label='edges')\\n plt.plot(time, (clamp & mask) * np.max(signal), label='clamp&mask')\\n plt.scatter(time[(clamp & mask)], signal[\\n (clamp & mask)], label='', color='red', marker='o')\\n\\n # else:\\n # clamp = np.ones(len(time)) \\n # print 'error: no index between first left and last right \\\\n{}'.format([left_edges, right_edges])\\n # else:\\n # clamp = np.ones(len(time))\\n # print 'error: left or right index zero length \\\\n{}'.format([left_edges, right_edges])\\n clamp = np.array(clamp,dtype='bool')\\n mask = np.array(mask,dtype='bool')\\n \\n # print clamp,edges,left_edges,right_edges\\n\\n if Plot:\\n plt.figure(figsize=(10,5))\\n plt.plot(time,signal)\\n plt.hlines(height_th,time[0],time[1],linestyle='--')\\n plt.plot(time,mask*np.max(signal),label='mask')\\n plt.plot(time[1:],edges*np.max(signal),label='edges')\\n plt.plot(time,(clamp&mask)*np.max(signal),label='clamp&mask')\\n plt.scatter(time[(clamp&mask)],signal[(clamp&mask)],label='',color='red',marker='o')\\n plt.legend()\\n\\n return np.array([mask, clamp, edges, left_edges, right_edges])\",\n \"def split(self, eccMap, patchName='patch00', cutStep=1, borderWidth=2, isplot=False):\\r\\n minMarker = localMin(eccMap, cutStep)\\r\\n\\r\\n plt.figure()\\r\\n plt.imshow(minMarker, vmin=0, interpolation='nearest')\\r\\n plt.colorbar()\\r\\n plt.title('markers 1')\\r\\n plt.show()\\r\\n\\r\\n minMarker = minMarker.astype(np.int32)\\r\\n selfArray = self.array.astype(np.int32)\\r\\n minMarker = minMarker + 1\\r\\n minMarker[minMarker == 1] = 0\\r\\n minMarker = minMarker + (-1 * (selfArray - 1))\\r\\n # minMarker: marker type for opencv watershed,\\r\\n # sure background = 1\\r\\n # unknow = 0\\r\\n # sure forgrand = 2,3,4... etc\\r\\n\\r\\n plt.figure()\\r\\n plt.imshow(minMarker, vmin=0, interpolation='nearest')\\r\\n plt.colorbar()\\r\\n plt.title('markers 2')\\r\\n plt.show()\\r\\n\\r\\n eccMapNor = (np.round(ia.array_nor(eccMap) * 255)).astype(np.uint8)\\r\\n eccMapRGB = cv2.cvtColor(eccMapNor, cv2.COLOR_GRAY2RGB)\\r\\n # eccMapRGB: image type for opencv watershed, RGB, [uint8, uint8, uint8]\\r\\n\\r\\n newLabel = cv2.watershed(eccMapRGB, minMarker)\\r\\n\\r\\n plt.figure()\\r\\n plt.imshow(newLabel, vmin=0, interpolation='nearest')\\r\\n plt.colorbar()\\r\\n plt.title('markers 3')\\r\\n plt.show()\\r\\n\\r\\n newBorder = np.zeros(newLabel.shape).astype(np.int)\\r\\n\\r\\n newBorder[newLabel == -1] = 1\\r\\n\\r\\n border = ni.binary_dilation(self.array).astype(np.int) - self.array\\r\\n\\r\\n border = newBorder + border\\r\\n\\r\\n border[border > 1] = 1\\r\\n\\r\\n border = sm.skeletonize(border)\\r\\n\\r\\n if borderWidth > 1:\\r\\n border = ni.binary_dilation(border, iterations=borderWidth - 1).astype(np.int8)\\r\\n\\r\\n newPatchMap = ni.binary_dilation(self.array).astype(np.int8) * (-1 * (border - 1))\\r\\n\\r\\n labeledNewPatchMap, patchNum = ni.label(newPatchMap)\\r\\n\\r\\n # if patchNum != np.amax(newLabel):\\r\\n # print 'number of patches: ', patchNum, '; number of local minimum:', np.amax(newLabel)\\r\\n # raise ValueError, \\\"Number of patches after splitting does not equal to number of local minimum!\\\"\\r\\n\\r\\n newPatchDict = {}\\r\\n\\r\\n for j in range(1, patchNum + 1):\\r\\n\\r\\n currPatchName = patchName + '.' + str(j)\\r\\n currArray = np.zeros(self.array.shape, dtype=np.int8)\\r\\n currArray[labeledNewPatchMap == j] = 1\\r\\n currArray = currArray * self.array\\r\\n\\r\\n if np.sum(currArray[:]) > 0:\\r\\n newPatchDict.update({currPatchName: Patch(currArray, self.sign)})\\r\\n\\r\\n if isplot:\\r\\n plt.figure()\\r\\n plt.subplot(121)\\r\\n plt.imshow(self.array, interpolation='nearest')\\r\\n plt.title(patchName + ': before split')\\r\\n plt.subplot(122)\\r\\n plt.imshow(labeledNewPatchMap, interpolation='nearest')\\r\\n plt.title(patchName + ': after split')\\r\\n\\r\\n return newPatchDict\",\n \"def segement_divide(pts,step=0.10, offset_x=0.01, offset_y=0.0):\\n\\n # Select the x and y of the points\\n n = len(pts)\\n \\n z = pts[0][2]\\n \\n points_plane = [] \\n points_x = []\\n paint_point = []\\n\\n for i in range(n):\\n points_plane.append([pts[i][0], pts[i][1]])\\n \\n # Sorted the list according to x \\n points_plane.sort(key=lambda x:x[0])\\n\\n # Segment the points according to x \\n counter = 0 # Count the interval\\n x_min = points_plane[0][0]\\n x_max = points_plane[n-1][0]\\n\\n # The whole interval that needs to be divided\\n upper = x_max + offset_x\\n lower = x_min - offset_x\\n lower_bound = lower\\n \\n # Set each segement's lower and upperbound\\n while (lower_bound + step <= upper): \\n # The break condition will be lower_bound > upper - step\\n upper_bound = lower_bound + step\\n\\n # Find the index between lower bound and upper bound\\n # First, find the index which x >= lower bound\\n index = 0\\n \\n while (points_plane[index][0] < lower_bound): \\n index = index + 1 # The index of the first point in the interval\\n \\n # If there is at least one point in the [lower_bound, upper_bound]\\n if (points_plane[index][0] <= upper_bound): \\n\\n x_start = points_plane[index][0]\\n y_max = points_plane[index][1]\\n y_min = points_plane[index][1]\\n \\n while (points_plane[index][0] <= upper_bound): \\n # The break condition will be x[index] > upper bound or index = n - 1\\n # Compute the y max and y min in this interval\\n \\n if points_plane[index][1] > y_max: \\n y_max = points_plane[index][1]\\n\\n if points_plane[index][1] < y_min:\\n y_min = points_plane[index][1]\\n \\n if index < n - 1:\\n index = index + 1\\n else:\\n break\\n # The index of the last point in the interval, when index < n-1\\n \\n x_end = points_plane[index][0]\\n\\n paint_point.append([lower_bound,y_max+offset_y,z]) \\n paint_point.append([lower_bound,y_min-offset_y,z])\\n points_x.append([x_start, x_end])\\n \\n counter = counter + 1\\n\\n # Update interval\\n lower_bound = upper_bound - offset_x\\n \\n # Deal with the last interval\\n lower_bound_last = upper - step\\n index_last = 0\\n counter = counter + 1\\n while ((index_last < n) and (points_plane[index_last][0] < lower_bound_last)): \\n # The first point in the last interval\\n index_last = index_last + 1\\n \\n if (index_last < n): \\n # There is at least one point in the last interval\\n x_start_last = points_plane[index_last][0]\\n y_max_last = points_plane[index_last][1]\\n y_min_last = points_plane[index_last][1]\\n\\n while ((index_last)<n) and (points_plane[index_last][0] <= upper):\\n\\n if points_plane[index_last][1] > y_max_last: \\n y_max_last = points_plane[index_last][1]\\n \\n if points_plane[index_last][1] < y_min_last:\\n y_min_last = points_plane[index_last][1]\\n\\n index_last = index_last + 1\\n \\n index_last = index_last - 1 # The index of the last point in the interval\\n \\n paint_point.append([lower_bound_last, y_max_last+offset_y, z])\\n paint_point.append([lower_bound_last, y_min_last-offset_y, z])\\n# paint_point.append([upper, y_max_last+offset_y, z])\\n# paint_point.append([upper, y_min_last-offset_y, z])\\n# return trans_to_end(paint_point)\\n return paint_point\",\n \"def reformatCoronalView4NeedleSegment(self, base, tip, ID=-1):\\r\\n #research\\r\\n profprint()\\r\\n for i in range(2): # workaround update problem\\r\\n if ID >=0:\\r\\n modelNode = slicer.util.getNode('vtkMRMLModelNode' + str(ID))\\r\\n polyData = modelNode.GetPolyData()\\r\\n nb = polyData.GetNumberOfPoints()\\r\\n base = [0, 0, 0]\\r\\n tip = [0, 0, 0]\\r\\n polyData.GetPoint(nb - 1, tip)\\r\\n polyData.GetPoint(0, base)\\r\\n a, b, c = tip[0] - base[0], tip[1] - base[1], tip[2] - base[2]\\r\\n \\r\\n sGreen = slicer.mrmlScene.GetNodeByID(\\\"vtkMRMLSliceNodeGreen\\\")\\r\\n if sGreen == None :\\r\\n sGreen = slicer.mrmlScene.GetNodeByID(\\\"vtkMRMLSliceNode3\\\")\\r\\n reformatLogic = slicer.vtkSlicerReformatLogic()\\r\\n #sGreen.SetSliceVisible(1)\\r\\n reformatLogic.SetSliceNormal(sGreen, 1, -a / b, 0)\\r\\n #reformatLogic.SetSliceOrigin(sGreen, base[0],base[1],base[2])#crashes\\r\\n m = sGreen.GetSliceToRAS()\\r\\n m.SetElement(0, 3, base[0])\\r\\n m.SetElement(1, 3, base[1])\\r\\n m.SetElement(2, 3, base[2])\\r\\n sGreen.Modified()\",\n \"def identify_dbs(image):\\n locations = {\\\"red\\\": Point(), \\\"green\\\": Point(), \\\"blue\\\": Point()}\\n masks = {\\\"red\\\": [], \\\"green\\\": [], \\\"blue\\\": []}\\n\\n bridge = cv_bridge.CvBridge()\\n image = bridge.imgmsg_to_cv2(image, \\\"bgr8\\\")\\n hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)\\n\\n # upper and lower bounds for red\\n # using python 3 bgr [0,0,188] = hsv [0, 255, 188]\\n lower_red = numpy.array([0, 100, 100]) \\n upper_red = numpy.array([10, 255, 255])\\n masks[\\\"red\\\"] = cv2.inRange(hsv, lower_red, upper_red)\\n\\n # upper and lower bounds for green\\n # using python 3 bgr [0,175,0] = hsv [60, 255, 175]\\n lower_green = numpy.array([50, 100, 100]) \\n upper_green = numpy.array([70, 255, 255])\\n masks[\\\"green\\\"] = cv2.inRange(hsv, lower_green, upper_green)\\n\\n # upper and lower bounds for blue\\n # using python 3 bgr [176, 0, 17] = hsv [123, 255, 176]\\n lower_blue = numpy.array([113, 100, 100])\\n upper_blue = numpy.array([133, 255, 255])\\n masks[\\\"blue\\\"] = cv2.inRange(hsv, lower_blue, upper_blue)\\n\\n x, y, w, h = 0, 0, image.shape[1]//3, image.shape[0]\\n\\n for color, mask in masks.items():\\n pixels = {\\\"left\\\": 0, \\\"middle\\\": 0, \\\"right\\\": 0}\\n \\n # define section of image to use for left, middle and right\\n left = mask[y:y+h, x:x+w]\\n middle = mask[y:y+h, x+w:x+w+w]\\n right = mask[y:y+h, x+w+w:x+3*w]\\n\\n # count the number of pixels in each section\\n pixels[\\\"left\\\"] = cv2.countNonZero(left)\\n pixels[\\\"middle\\\"] = cv2.countNonZero(middle)\\n pixels[\\\"right\\\"] = cv2.countNonZero(right)\\n location = max(pixels, key=pixels.get)\\n\\n # map the relative position of the db (left, middle, right) to the correct Point()\\n locations[color] = db_locations[location]\\n \\n return locations\",\n \"def establecer_region(self, region, guess, delta_ppm=(1,1)): \\r\\n # obtengo los indices del centro del pico.\\r\\n xc, yc = self.encontrar_picos(guess, delta_ppm)\\r\\n # obtengo las coordenadas que determinan el rectangulo donde voy a\\r\\n # integrar. \\r\\n x_lims, y_lims = self.establecer_limites(xc, yc)\\r\\n \\r\\n xi,xf = x_lims\\r\\n yi,yf = y_lims\\r\\n spec = self.spec[yi:yf, xi:xf]\\r\\n ppmGridDir = self.ppmGridDir[yi:yf, xi:xf]\\r\\n ppmGridInd = self.ppmGridInd[yi:yf, xi:xf]\\r\\n \\r\\n \\r\\n n, m = region\\r\\n self.regiones[n][m] = Region(ppmGridDir, ppmGridInd, spec)\",\n \"def region_region_checkerboard(self, **_):\\n outputs: dict = {}\\n\\n if self.AGG_BY == \\\"zone\\\":\\n agg = \\\"zone\\\"\\n else:\\n agg = \\\"region\\\"\\n\\n # List of properties needed by the plot, properties are a set of tuples and\\n # contain 3 parts: required True/False, property name and scenarios required,\\n # scenarios must be a list.\\n properties = [(True, f\\\"{agg}_{agg}s_Net_Interchange\\\", self.Scenarios)]\\n\\n # Runs get_formatted_data within PlotDataStoreAndProcessor to populate PlotDataStoreAndProcessor dictionary\\n # with all required properties, returns a 1 if required data is missing\\n check_input_data = self.get_formatted_data(properties)\\n\\n if 1 in check_input_data:\\n return MissingInputData()\\n\\n ncols, nrows = set_x_y_dimension(len(self.Scenarios))\\n grid_size = ncols * nrows\\n excess_axs = grid_size - len(self.Scenarios)\\n\\n mplt = PlotLibrary(nrows, ncols, squeeze=False, ravel_axs=True)\\n fig, axs = mplt.get_figure()\\n plt.subplots_adjust(wspace=0.02, hspace=0.4)\\n max_flow_group = []\\n Data_Out = []\\n n = 0\\n for scenario in self.Scenarios:\\n rr_int = self[f\\\"{agg}_{agg}s_Net_Interchange\\\"].get(scenario)\\n if shift_leapday:\\n rr_int = adjust_for_leapday(rr_int)\\n\\n if self.AGG_BY != \\\"region\\\" and self.AGG_BY != \\\"zone\\\":\\n agg_region_mapping = (\\n self.region_mapping[[\\\"region\\\", self.AGG_BY]]\\n .set_index(\\\"region\\\")\\n .to_dict()[self.AGG_BY]\\n )\\n # Checks if keys all aggregate to a single value, this plot requires multiple values to work\\n if len(set(agg_region_mapping.values())) == 1:\\n return UnsupportedAggregation()\\n rr_int = rr_int.reset_index()\\n rr_int[\\\"parent\\\"] = rr_int[\\\"parent\\\"].map(agg_region_mapping)\\n rr_int[\\\"child\\\"] = rr_int[\\\"child\\\"].map(agg_region_mapping)\\n rr_int_agg = rr_int.groupby([\\\"parent\\\", \\\"child\\\"], as_index=True).sum()\\n rr_int_agg.rename(columns={\\\"values\\\": \\\"flow (MW)\\\"}, inplace=True)\\n rr_int_agg = rr_int_agg.loc[\\n rr_int_agg[\\\"flow (MW)\\\"] > 0.01\\n ] # Keep only positive flows\\n rr_int_agg.sort_values(ascending=False, by=\\\"flow (MW)\\\")\\n rr_int_agg = rr_int_agg / 1000 # MWh -> GWh\\n\\n data_out = rr_int_agg.copy()\\n data_out.rename(\\n columns={\\\"flow (MW)\\\": \\\"{} flow (GWh)\\\".format(scenario)}, inplace=True\\n )\\n\\n max_flow = max(rr_int_agg[\\\"flow (MW)\\\"])\\n rr_int_agg = rr_int_agg.unstack(\\\"child\\\")\\n rr_int_agg = rr_int_agg.droplevel(level=0, axis=1)\\n\\n current_cmap = plt.cm.get_cmap()\\n current_cmap.set_bad(color=\\\"grey\\\")\\n\\n axs[n].imshow(rr_int_agg)\\n axs[n].set_xticks(np.arange(rr_int_agg.shape[1]))\\n axs[n].set_yticks(np.arange(rr_int_agg.shape[0]))\\n axs[n].set_xticklabels(rr_int_agg.columns)\\n axs[n].set_yticklabels(rr_int_agg.index)\\n axs[n].set_title(scenario.replace(\\\"_\\\", \\\" \\\"), fontweight=\\\"bold\\\")\\n\\n # Rotate the tick labels and set their alignment.\\n plt.setp(\\n axs[n].get_xticklabels(),\\n rotation=90,\\n ha=\\\"right\\\",\\n rotation_mode=\\\"anchor\\\",\\n )\\n\\n # Delineate the boxes and make room at top and bottom\\n axs[n].set_xticks(np.arange(rr_int_agg.shape[1] + 1) - 0.5, minor=True)\\n axs[n].set_yticks(np.arange(rr_int_agg.shape[0] + 1) - 0.5, minor=True)\\n axs[n].grid(which=\\\"minor\\\", color=\\\"k\\\", linestyle=\\\"-\\\", linewidth=1)\\n axs[n].tick_params(which=\\\"minor\\\", bottom=False, left=False)\\n\\n max_flow_group.append(max_flow)\\n Data_Out.append(data_out)\\n n += 1\\n\\n # Remove extra axes\\n mplt.remove_excess_axs(excess_axs, grid_size)\\n\\n cmap = cm.inferno\\n norm = mcolors.Normalize(vmin=0, vmax=max(max_flow_group))\\n cax = plt.axes([0.90, 0.1, 0.035, 0.8])\\n fig.colorbar(\\n cm.ScalarMappable(norm=norm, cmap=cmap),\\n cax=cax,\\n label=\\\"Total Net Interchange [GWh]\\\",\\n )\\n plt.xlabel(\\\"To Region\\\", color=\\\"black\\\", rotation=\\\"horizontal\\\", labelpad=40)\\n plt.ylabel(\\\"From Region\\\", color=\\\"black\\\", rotation=\\\"vertical\\\", labelpad=40)\\n\\n data_table_out = pd.concat(Data_Out, axis=1)\\n save_figures = self.figure_folder.joinpath(f\\\"{self.AGG_BY}_transmission\\\")\\n fig.savefig(\\n save_figures.joinpath(\\\"region_region_checkerboard.svg\\\"),\\n dpi=600,\\n bbox_inches=\\\"tight\\\",\\n )\\n data_table_out.to_csv(save_figures.joinpath(\\\"region_region_checkerboard.csv\\\"))\\n\\n outputs = DataSavedInModule()\\n return outputs\",\n \"def betas_middle_slice_graph(betas_4d):\\n\\tplt.imshow(betas_4d[:, :, 16, 0], interpolation='nearest', cmap='gray')\\n\\tplt.title('Middle Slice Beta(Gain)')\\n\\tplt.colorbar()\\n\\tplt.savefig('middle_slice_gain.png')\\n\\tplt.close()\\n\\tplt.imshow(betas_4d[:, :, 16, 1], interpolation='nearest', cmap='gray')\\n\\tplt.title('Middle Slice Beta(Loss)')\\n\\tplt.colorbar()\\n\\tplt.savefig('middle_slice_loss.png')\\n\\tplt.close()\",\n \"def find_chart():\\r\\n ###############################################\\r\\n # Read values of S/N\\r\\n sn = np.loadtxt(outtable, usecols=(14,))\\r\\n xs, ys = np.loadtxt(outtable, usecols=(1, 2)).T\\r\\n specs = np.loadtxt(outtable, usecols=(0,), dtype=str)\\r\\n ###############################################\\r\\n # Find good (and bad) regions according to S/N\\r\\n good = np.where(((~np.isnan(sn)) & (sn >= sn_cut)))[0]\\r\\n bad = np.where((sn < sn_cut))[0]\\r\\n ###############################################\\r\\n # Filter arrays for S/N\\r\\n sn = sn[good]\\r\\n xs = xs[good]\\r\\n ys = ys[good]\\r\\n specs = specs[good].tolist()\\r\\n specs = [x.replace(\\\".fits\\\", \\\"\\\")[1:] for x in specs]\\r\\n ###############################################\\r\\n # Set limits for the plot\\r\\n norm = Normalize(0, 1)\\r\\n ###############################################\\r\\n # Set colormap\\r\\n # cmap = brewer2mpl.get_map('YlGnBu', 'sequential', 5).mpl_colormap\\r\\n # Produces a collection of polygons with colors according to S/N values\\r\\n coll = PolyCollection(polygons_bins[good], array=np.ones_like(sn),\\r\\n cmap=\\\"gray\\\", edgecolors='0.5', norm=norm)\\r\\n ###############################################\\r\\n # Initiate figure and axis for matplotlib\\r\\n fig = plt.figure(figsize=(6.25, 6))\\r\\n gs = gridspec.GridSpec(1, 1)\\r\\n gs.update(left=0.08, right=0.985, bottom=0.08, top=0.985, hspace=0.05,\\r\\n wspace=0.06)\\r\\n ax = plt.subplot(gs[0])\\r\\n ###############################################\\r\\n # Draw the polygons\\r\\n draw_map(fig, ax, coll)\\r\\n ###############################################\\r\\n # Add contours according to V-band image\\r\\n draw_contours(\\\"vband\\\", fig, ax)\\r\\n ###############################################\\r\\n for x, y, spec in zip(xs, ys, specs):\\r\\n ax.text(x, y, spec, fontsize=10)\\r\\n # Write labels\\r\\n xylabels(ax)\\r\\n ##############################################\\r\\n # Save the figure\\r\\n plt.show()\\r\\n plt.savefig(\\\"figs/find_chart.pdf\\\")\\r\\n return\",\n \"def draw_laser_ranges():\\n NUM_RANGES = len(D.ranges) # should be 360\\n if False: #for easy commenting out...\\n for angle in range(NUM_RANGES):\\n print angle, \\\":\\\", D.ranges[angle] \\n \\n # helpful starting points, perhaps:\\n # add line to the ranges image, \\\"D.image\\\"\\n #cv.Line(D.image, (42,100), (100,42), cv.RGB(255, 0, 0), 1) # 1 == thickness\\n # add dots to image being used to compute the Hough tr. \\\"D.hough\\\"\\n # cv.Line(D.hough, (42,42), (42,42), 255, 2) # 1 == thickness\\n for angle in range(NUM_RANGES):\\n point = (CENTER + int(0.2*D.ranges[angle]*sin(radians(angle))), CENTER + int(0.2*D.ranges[angle]*cos(radians(angle))))\\n cv.Line(D.image, (CENTER,CENTER), point, cv.RGB(255, 0 , 0), 1)\\n cv.Line(D.hough, point, point, 255, 2) \\n\\n return\",\n \"def opencv_watershed(masked, mask) -> JSON_TYPE:\\n # For code and detailed explanation see:\\n # http://datahacker.rs/007-opencv-projects-image-segmentation-with-watershed-algorithm/\\n threshold: int = 30\\n gray = cv2.cvtColor(masked, cv2.COLOR_RGB2GRAY)\\n ret, thresh_img = cv2.threshold(gray, threshold, 255, cv2.THRESH_BINARY)\\n # Noise removal\\n kernel = np.ones((3), np.uint8)\\n opening_img = cv2.morphologyEx(thresh_img, cv2.MORPH_OPEN, kernel, iterations=9)\\n # Noise removal\\n closing_img = cv2.morphologyEx(thresh_img, cv2.MORPH_CLOSE, kernel, iterations=4)\\n dist_transform = cv2.distanceTransform(255 - closing_img, cv2.DIST_L2, 3)\\n local_max_location = peak_local_max(dist_transform, min_distance=1, indices=True)\\n\\n n_increases: int = 0\\n while local_max_location.shape[0] < 30 and n_increases < 15:\\n threshold += 20\\n ret, thresh_img = cv2.threshold(gray, threshold, 255, cv2.THRESH_BINARY)\\n # Noise removal\\n kernel = np.ones((3), np.uint8)\\n opening_img = cv2.morphologyEx(thresh_img, cv2.MORPH_OPEN, kernel, iterations=9)\\n # Noise removal\\n closing_img = cv2.morphologyEx(thresh_img, cv2.MORPH_CLOSE, kernel, iterations=4)\\n dist_transform = cv2.distanceTransform(255 - closing_img, cv2.DIST_L2, 3)\\n local_max_location = peak_local_max(dist_transform, min_distance=1, indices=True)\\n n_increases += 1\\n # Reset threshold\\n threshold = 30\\n\\n num_clusters: int = 30\\n if n_increases >= 15:\\n num_clusters = local_max_location.shape[0]\\n kmeans = KMeans(n_clusters=num_clusters)\\n # If local_max_location size is 0, return 0 predictions\\n if not local_max_location.size:\\n return {\\n \\\"count\\\": 0\\n }\\n kmeans.fit(local_max_location)\\n local_max_location = kmeans.cluster_centers_.copy()\\n # Kmeans is returning a float data type so we need to convert it to an int. \\n local_max_location = local_max_location.astype(int)\\n dist_transform_copy = dist_transform.copy()\\n for i in range(local_max_location.shape[0]):\\n cv2.circle(dist_transform_copy, (local_max_location[i][1], local_max_location[i][0]), 5, 255)\\n # markers = np.zeros_like(dist_transform)\\n ret, sure = cv2.threshold(dist_transform, 0.01*dist_transform.max(), 255, 0)\\n sure = np.uint8(sure)\\n ret, markers = cv2.connectedComponents(sure)\\n labels = np.arange(kmeans.n_clusters)\\n markers[local_max_location[:,0], local_max_location[:,1]] = labels + 1\\n # Convert all local markers to an integer. This because cluster centers will be float numbers. \\n markers = markers.astype(int)\\n markers_copy = markers.copy()\\n index_non_zero_markers = np.argwhere(markers != 0)\\n markers_copy = markers_copy.astype(np.uint8)\\n font = cv2.FONT_HERSHEY_SIMPLEX\\n for i in range(index_non_zero_markers.shape[0]):\\n string_text = str(markers[index_non_zero_markers[i][0], index_non_zero_markers[i][1]])\\n cv2.putText(markers_copy, string_text, (index_non_zero_markers[i][1], index_non_zero_markers[i][0]), font, 1, 255)\\n markers = markers.astype(np.int32)\\n segmented = cv2.watershed(masked, markers)\\n count_segments(markers)\\n #return {\\n # \\\"count\\\": local_max_location.shape[0]\\n #}\\n return {\\n \\\"count\\\": count_segments(markers),\\n }\",\n \"def SplitGap(data,gapsize,medwin,fluxdiff):\\n \\n # defining new empty lists and stuff\\n pcount=0\\n istamps=[]\\n outData={}\\n \\n data['x'].mask = data['UnMasked']\\n data['y'].mask = data['UnMasked']\\n data['yerr'].mask = data['UnMasked']\\n \\n # median smoothing the lightcurve\\n mvavg1 = movingMedian(data['y'],medwin)\\n mvavg1 = num.append(mvavg1,mvavg1[-1])\\n mvavg1 = data['y']\\n # first derivative of smoothed lightcurve\\n diff1 = num.diff(mvavg1)\\n diff1 = num.hstack((diff1,diff1[-1]))\\n \\n # second derivative of smoothed lightcurve\\n diff2 = num.diff(diff1)\\n diff2 = num.hstack((diff2[-1],diff2))\\n\\n # compute ourlier resistant sigma\\n sig = compute1Sigma(diff1)\\n #pylab.plot(diff1,'g.')\\n #pylab.plot([0,6000],[5*sig,5*sig],'k-')\\n #pylab.plot([0,6000],[3*sig,3*sig],'k-')\\n #pylab.plot([0,6000],[1*sig,1*sig],'k-')\\n #pylab.show()\\n\\n # The grand master loop >=}\\n # to make portion slices\\n for i in range(len(data['x'])-1):\\n dt = data['x'][i+1]- data['x'][i]\\n j1 = max(0,i-medwin)\\n j2 = i + medwin\\n if pcount == 0:\\n i0 = 0\\n if pcount > 0:\\n i0 = i1+1\\n if dt > gapsize:\\n i1 = i\\n istamps.append([i0,i1])\\n pcount += 1\\n #if num.abs(diff1[i]) > 5*sig:\\n #i1 = i\\n #istamps.append([i0,i1])\\n #pcount += 1\\n #print num.abs(diff1[i]/data['y'][i]), diff1[i], data['y'][i], diff1[i+1], data['y'][i+1]\\n #print i, ' test flux gap'\\n i1 = i+1\\n istamps.append([i0,i1])\\n \\n \\n \\n if data['bool']==False:\\n # Applying slices\\n for j in range(len(istamps)):\\n #print istamps[j][0], istamps[j][1]\\n outData['portion' + str(j+1)] = {'kid':data['kid'],'x':data['x'][istamps[j][0]:istamps[j][1]+1], 'y':data['y'][istamps[j][0]:istamps[j][1]+1], 'yerr':data['yerr'][istamps[j][0]:istamps[j][1]+1],'UnMasked':data['UnMasked'][istamps[j][0]:istamps[j][1]+1],'bool':False}\\n else:\\n # Applying slices\\n for j in range(len(istamps)):\\n #print istamps[j][0], istamps[j][1]\\n outData['portion' + str(j+1)] = {'kid':data['kid'],'x':data['x'][istamps[j][0]:istamps[j][1]+1], 'y':data['y'][istamps[j][0]:istamps[j][1]+1], 'yerr':data['yerr'][istamps[j][0]:istamps[j][1]+1], 'TransitMask':data['TransitMask'][istamps[j][0]:istamps[j][1]+1],'UnMasked':data['UnMasked'][istamps[j][0]:istamps[j][1]+1],'bool':True}\\n \\n return outData\",\n \"def segment_by_shape(self, dt, criterion):\\n enumerate_crit = Criterion(\\n 'patterns', criterion.column_name+'_derivatives_patterns_clusters',\\n 'enumerate')\\n return self.segment_by_enumerate(dt, enumerate_crit)\",\n \"def isDivision(event,buff):\\n index,diff,label = event\\n label = label[0]\\n if diff<0:\\n return False,[]\\n img_before = np.copy(buff[:,:,index-1])\\n img_after = np.copy(buff[:,:,index])\\n mask_after = (img_after==label).astype(np.uint8)\\n nb_elts_after = np.amax(img_after)\\n kernel = np.ones((7,7),np.uint8)\\n neighbouring_mask = cv2.dilate(mask_after,kernel,iterations=8)\\n\\n \\n new_map = np.multiply(img_after,neighbouring_mask.astype(np.uint8)) \\n #Removing the element we are currently looking at\\n new_map[img_after==label]=0\\n possible_candidates = []\\n for i in range(nb_elts_after):\\n if np.any(new_map==i+1):\\n possible_candidates.append(i+1)\\n #Computes the area of the cells and compares them\\n size_cell_after = np.count_nonzero(img_after==label)\\n match = [] #lists the ratios sizeAfter/sizeBefore for possible matches\\n for vals in possible_candidates:\\n size_before = np.count_nonzero(img_before==vals)\\n size_other_cell = np.count_nonzero(img_after==vals)\\n size_after = size_cell_after + size_other_cell\\n ratio = float(size_after)/float(size_before)\\n if ratio>0.8 and ratio<1.2:\\n match.append((vals,abs(1-ratio)))\\n if len(match)==0:\\n return False,[]\\n if len(match)>1:\\n #Several matches, so pick the best\\n values = [y for x,y in match]\\n result_label,osef = match[np.argmin(values)]\\n else:\\n result_label, osef = match[0]\\n return True,result_label\",\n \"def cleanup_regions(self, timestamp, bid, ofr):\\n regions = []\\n\\n for region in self.regions:\\n if not region.can_delete(timestamp, bid, ofr):\\n regions.append(region)\\n\\n # replace the regions list\\n self.regions = regions\",\n \"def highlight_rare_blocks(bv, threshold=1):\\n if no_coverage_warn():\\n return\\n rare_blocks = covdb.get_rare_blocks(threshold)\\n rare_color = HighlightStandardColor.RedHighlightColor\\n highlight_set(rare_blocks, rare_color)\\n log.log_info(\\\"[*] Found %d rare blocks (threshold: %d)\\\" %\\n (len(rare_blocks), threshold))\\n for block in rare_blocks:\\n log.log_info(\\\" 0x%x\\\" % block)\",\n \"def border_analyze_vertical(mask, borders, min_segment_width=5, max_border_width=0.4):\\n max_border_width = mask.shape[1] * max_border_width\\n if len(borders) == 0: return False\\n left_most = 0\\n right_most = mask.shape[1] - 1\\n # middle_borders = [border for border in borders if (left_most in border or right_most in border) and abs(border[0]-border[1])>3 ]\\n # if len(middle_borders)==0:return False\\n slice_start = 0\\n # segs_by_middle_borders=[]\\n block_widths = []\\n for v_border in borders[::-1]:\\n border_start = v_border[1]\\n border_stop = v_border[0]\\n if border_start == left_most:\\n slice_start = border_stop\\n elif border_stop == right_most:\\n # mask_slice=mask[slice_start:border_start]\\n block_widths.append(border_start - slice_start)\\n # segs_by_middle_borders.appen(mask_slice)\\n slice_start = border_stop\\n elif border_stop - border_start >= 1:\\n # mask_slice = mask[slice_start,border_start]\\n if border_stop - border_start < max_border_width:\\n block_widths.append(border_start - slice_start)\\n # segs_by_middle_borders.appen(mask_slice)\\n slice_start = border_stop\\n if slice_start < right_most:\\n block_widths.append(mask.shape[1] - slice_start)\\n # segs_by_middle_borders.append(mask[slice_start:])\\n\\n block_widths = [w for w in block_widths if w > min_segment_width]\\n # print('block widths')\\n # print(block_widths)\\n # print('block widths deviation' )\\n # print(np.std(block_widths))\\n # print('block heights dev/mean' )\\n # print(np.std(block_widths)/np.mean(block_widths))\\n\\n if len(block_widths) < 2: return False\\n return segment_analyzer(block_widths)\",\n \"def fix_half_inning(self, half_inning):\\n outs = 0\\n active_runners = []\\n for atbat in half_inning:\\n self.hold_runners(active_runners, atbat)\\n\\n active_runners = [r for r in atbat.runners\\n if not r.out and r.end != 4]\\n outs = atbat.outs\",\n \"def highlight(self,screen,midpos = (800,450)):\\n posInt = self.getIntPos()\\n posInt = getOffsetPos(posInt,midpos)\\n pygame.draw.circle(screen, [max(0,tmp - (10 - self.timeDriving%10)*10) for tmp in self.colour], \\n posInt, int(10+ (self.timeDriving%10 )),2)\\n pygame.draw.circle(screen, self.colour, posInt, int(20+ (self.timeDriving%10 )),2)\\n pygame.draw.circle(screen, [max(0,tmp - (self.timeDriving%10)*10) for tmp in self.colour], \\n posInt, int(30+ (self.timeDriving%10 )),2)\",\n \"def remove_blocks(draft):\\n for symbol in draft.Blocks:\\n if symbol.Name in blocks_to_delete:\\n print(\\\"[-] %s, \\\\tdeleted\\\" % symbol.Name)\\n symbol.delete()\\n\\n # for ball in draft.ActiveSheet.Balloons:\\n if draft.Balloons:\\n for ball in draft.Balloons:\\n if ball.BalloonType == 7: # type 7 filter the triangle balloons.\\n print(\\\"[-] %s, \\\\tdeleted\\\" % ball.Name)\\n ball.Delete()\\n else:\\n pass\",\n \"def RegionGrowingSegmentation(image, kernel_sigma, seed_row, seed_col, Niter, sim_threshold): \\n \\n if kernel_sigma >= 1:\\n image = Denoising(image, kernel_sigma);\\n \\n image = image / image.max();\\n nr, nc = image.shape;\\n mask_old = np.zeros(image.shape, dtype = bool);\\n mask_old[seed_row, seed_col] = True;\\n \\n sim_pos = [(0, 0), (0, 1), (0, 2), (1, 0), (1, 1), (1, 2), (2, 0), (2, 1), (2, 2)];\\n nb_pos = [(-1, -1), (-1, 0), (-1, 1), (0, -1), (0, 0), (0, 1), (1, -1), (1, 0), (1, 1)];\\n \\n for iter_no in range(Niter):\\n mask = np.zeros(image.shape, dtype = bool);\\n for row_no in range(1, nr - 1):\\n for col_no in range(1, nc - 1):\\n if mask_old[row_no, col_no] != 1:\\n continue;\\n \\n nb = image[row_no - 1:row_no + 2, col_no - 1:col_no + 2]; \\n region_mean = image[mask_old].mean();\\n if region_mean == 1:\\n mask[row_no - 1:row_no + 2, col_no - 1:col_no + 2] = 1; \\n continue;\\n \\n similarity = np.exp(-(nb - region_mean) ** 2); \\n for el_no in range(len(nb_pos)):\\n delta_row, delta_col = nb_pos[el_no];\\n row_sim, col_sim = sim_pos[el_no];\\n if similarity[row_sim, col_sim] < sim_threshold:\\n continue;\\n \\n mask[row_no + delta_row, col_no + delta_col] = 1;\\n \\n if mask_old.sum() == mask.sum():\\n break; \\n \\n mask_old = mask;\\n \\n return mask;\",\n \"def highlight_set(addr_set, color=None, bv=None, start_only=True):\\n if bv is not None:\\n binary_view = bv\\n else:\\n if gbv is None:\\n print(\\\"[!] To use manually, pass in a binary view (bv=binary_view), or set bncov.gbv first\\\")\\n return\\n binary_view = gbv\\n if start_only:\\n get_blocks = binary_view.get_basic_blocks_starting_at\\n else:\\n get_blocks = binary_view.get_basic_blocks_at\\n for addr in addr_set:\\n blocks = get_blocks(addr)\\n if len(blocks) >= 1:\\n for block in blocks:\\n if covdb is not None:\\n if addr in covdb.block_dict:\\n count = len(covdb.block_dict[addr])\\n else:\\n count = 0\\n highlight_block(block, count, color)\\n else:\\n highlight_block(block, 0, color)\\n else:\\n if get_blocks == binary_view.get_basic_blocks_starting_at:\\n containing_blocks = binary_view.get_basic_blocks_at(addr)\\n if containing_blocks:\\n log.log_warn(\\\"[!] No blocks start at 0x%x, but %d blocks contain it:\\\" %\\n (addr, len(containing_blocks)))\\n for i, block in enumerate(containing_blocks):\\n log.log_info(\\\"%d: 0x%x - 0x%x in %s\\\" % (i, block.start, block.end, block.function.name))\\n else:\\n log.log_warn(\\\"[!] No blocks contain address 0x%x; check the address is inside a function.\\\" % addr)\\n else: # get_blocks is binary_view.get_basic_blocks_at\\n log.log_warn(\\\"[!] No blocks contain address 0x%x; check the address is inside a function.\\\" % addr)\",\n \"def populate_region(mask, layer_params):\\n\\n from .speedups import (\\n NEW_CELL_MASK, CAN_OSCILLATE_MASK, INCLUDE_VIOLATIONS_MASK)\\n\\n border = ndimage.maximum_filter(mask, size=3, mode='wrap') ^ mask\\n interior = ndimage.minimum_filter(mask, size=3, mode='wrap')\\n gen_mask = mask * (\\n NEW_CELL_MASK |\\n CAN_OSCILLATE_MASK |\\n INCLUDE_VIOLATIONS_MASK\\n ) + border * (\\n INCLUDE_VIOLATIONS_MASK\\n )\\n board = np.zeros(mask.shape, dtype=np.uint16)\\n foreground = np.zeros(mask.shape, dtype=bool)\\n background = np.zeros(mask.shape, dtype=bool)\\n background_color = np.zeros(mask.shape, dtype=bool)\\n seeds = None\\n max_period = 1\\n\\n for layer in layer_params:\\n if not isinstance(layer, dict):\\n raise ValueError(\\n \\\"'layer_params' should be a list of parameter dictionaries.\\\")\\n layer = _fix_random_values(layer)\\n old_board = board.copy()\\n gen_mask0 = gen_mask.copy()\\n interior = ndimage.minimum_filter(\\n gen_mask & NEW_CELL_MASK > 0, size=3, mode='wrap')\\n color = COLORS.get(layer.get('color'), 0)\\n\\n fence_frac = layer.get('fences', 0.0)\\n if fence_frac > 0:\\n fences = build_fence(gen_mask & speedups.NEW_CELL_MASK)\\n fences *= coinflip(fence_frac, fences.shape)\\n gen_mask &= ~(fences * (NEW_CELL_MASK | CAN_OSCILLATE_MASK))\\n board += fences.astype(np.uint16) * CellTypes.wall\\n\\n spawners = layer.get('spawners', 0)\\n if spawners > 0:\\n _mask = (gen_mask0 & NEW_CELL_MASK > 0) & interior\\n new_cells = _mask & coinflip(spawners, board.shape)\\n if not new_cells.any() and _mask.any():\\n i, j = np.nonzero(_mask)\\n k = get_rng().choice(len(i)) # ensure at least one spawner\\n new_cells[i[k], j[k]] = True\\n gen_mask[new_cells] ^= NEW_CELL_MASK\\n board[new_cells] = CellTypes.spawner + color\\n\\n tree_lattice = layer.get('tree_lattice')\\n # Create a lattice of trees that are spread throughout the region\\n # such that every empty cell touches one (and only one) tree\\n # (modulo edge effects).\\n # Such a lattice tends to make the resulting board very chaotic.\\n # Note that this will disrupt any pre-existing patterns.\\n if tree_lattice is not None:\\n if not isinstance(tree_lattice, dict):\\n tree_lattice = {}\\n h, w = board.shape\\n stagger = tree_lattice.get('stagger', True)\\n spacing = float(tree_lattice.get('spacing', 5))\\n if not stagger:\\n new_cells = _make_lattice(h, w, spacing, spacing, 0)\\n elif spacing <= 3:\\n new_cells = _make_lattice(h, w, 3, 3, 1)\\n elif spacing == 4:\\n new_cells = _make_lattice(h, w, 10, 1, 3)\\n elif spacing == 5:\\n new_cells = _make_lattice(h, w, 13, 1, 5)\\n else:\\n # The following gets pretty sparse.\\n new_cells = _make_lattice(h, w, 6, 3, 3)\\n\\n new_cells &= gen_mask & NEW_CELL_MASK > 0\\n board[new_cells] = CellTypes.tree + color\\n\\n period = 1\\n if 'pattern' in layer:\\n pattern_args = layer['pattern'].copy()\\n period = pattern_args.get('period', 1)\\n if period == 1:\\n gen_mask2 = gen_mask & ~CAN_OSCILLATE_MASK\\n pattern_args.update(period=max_period, osc_bonus=0)\\n elif period == 0:\\n gen_mask2 = gen_mask & ~INCLUDE_VIOLATIONS_MASK\\n pattern_args.update(period=max_period, osc_bonus=0)\\n elif period < max_period:\\n raise ValueError(\\n \\\"Periods for sequential layers in a region must be either 0, 1,\\\"\\n \\\" or at least as large as the largest period in prior layers.\\\")\\n else:\\n gen_mask2 = gen_mask\\n max_period = period\\n\\n board = _gen_pattern(board, gen_mask2, seeds, **pattern_args)\\n\\n # We need to update the mask for subsequent layers so that they\\n # do not destroy the pattern in this layer.\\n # First get a list of board states throughout the oscillation cycle.\\n boards = [board]\\n for _ in range(1, max_period):\\n boards.append(speedups.advance_board(boards[-1]))\\n non_empty = np.array(boards) != 0\\n still_cells = non_empty.all(axis=0)\\n osc_cells = still_cells ^ non_empty.any(axis=0)\\n # Both still life cells and oscillating cells should disallow\\n # any later changes. We also want to disallow changes to the cells\\n # that are neighboring the oscillating cells, because any changes\\n # there would propogate to the oscillating cells at later time\\n # steps.\\n # Note that it doesn't really matter whether the oscillating mask\\n # is set for the currently oscillating cells, because we're not\\n # checking for violations in them anyways, and we don't allow any\\n # changes that would affect them.\\n osc_neighbors = ndimage.maximum_filter(osc_cells, size=3, mode='wrap')\\n gen_mask[osc_cells] &= ~(NEW_CELL_MASK | INCLUDE_VIOLATIONS_MASK)\\n gen_mask[still_cells | osc_neighbors] &= ~(NEW_CELL_MASK | CAN_OSCILLATE_MASK)\\n\\n new_mask = board != old_board\\n life_mask = ((board & CellTypes.alive) > 0) & new_mask\\n board += color * new_mask * life_mask\\n # The seeds are starting points for the next layer of patterns.\\n # This just makes the patterns more likely to end up close together.\\n seeds = ((board & CellTypes.alive) > 0) & mask\\n\\n new_mask = board != old_board\\n\\n movable_walls = layer.get('movable_walls', 0)\\n if movable_walls > 0:\\n new_cells = coinflip(movable_walls, board.shape) * new_mask\\n new_cells *= (board & ~CellTypes.rainbow_color) == CellTypes.wall\\n board += new_cells * CellTypes.movable\\n\\n movable_trees = layer.get('movable_trees', 0)\\n if movable_trees > 0:\\n new_cells = coinflip(movable_trees, board.shape) * new_mask\\n new_cells *= (board & ~CellTypes.rainbow_color) == CellTypes.tree\\n board += new_cells * CellTypes.movable\\n\\n hardened_life = layer.get('hardened_life', 0)\\n if hardened_life > 0:\\n new_cells = coinflip(hardened_life, board.shape) * new_mask\\n new_cells *= (board & ~CellTypes.rainbow_color) == CellTypes.life\\n board -= new_cells * CellTypes.destructible\\n\\n buffer_size = layer.get('buffer_zone', 0) * 2 + 1\\n life_cells = board & CellTypes.alive > 0\\n buf = ndimage.maximum_filter(life_cells, size=buffer_size, mode='wrap')\\n gen_mask[buf] &= ~NEW_CELL_MASK\\n\\n target = layer.get('target', 'board')\\n if target == 'board':\\n foreground[new_mask] = True\\n if period > 0:\\n background[new_mask] = True\\n elif target == 'goals':\\n background[new_mask] = True\\n background_color[new_mask] = True\\n # Make sure to add walls and such to the foreground\\n foreground[new_mask & (board & CellTypes.alive == 0)] = True\\n elif target == 'both':\\n foreground[new_mask] = True\\n if period > 0:\\n background[new_mask] = True\\n background_color[new_mask] = True\\n else:\\n raise ValueError(\\\"Unexpected value for 'target': %s\\\" % (target,))\\n\\n fountains = layer.get('fountains', 0)\\n if fountains > 0:\\n new_cells = coinflip(fountains, board.shape)\\n new_cells *= gen_mask & NEW_CELL_MASK > 0\\n neighbors = ndimage.maximum_filter(new_cells, size=3, mode='wrap')\\n neighbors *= gen_mask & NEW_CELL_MASK > 0\\n gen_mask[neighbors] = INCLUDE_VIOLATIONS_MASK\\n if buffer_size > 1:\\n buf = ndimage.maximum_filter(neighbors, size=buffer_size, mode='wrap')\\n gen_mask[buf] &= ~NEW_CELL_MASK\\n board[neighbors] = CellTypes.wall + color\\n board[new_cells] = CellTypes.fountain + color\\n foreground[new_cells] = True\\n background[neighbors] = True\\n background_color[neighbors] = True\\n\\n goals = board.copy()\\n board *= foreground\\n goals *= background\\n goals &= ~CellTypes.spawning\\n goals &= ~(CellTypes.rainbow_color * ~background_color)\\n\\n return board, goals\",\n \"def get_valid_regions(self):\\n pass\",\n \"def do_full(self, image,hsv,upper,lower,debug=False):\\n single_color_img = self.extract_single_color_range(image,hsv,lower,upper)\\n if debug:\\n # cv2.imshow('single_color_img',single_color_img)\\n cv2.imwrite('debug_pics/single_color_img.jpg',single_color_img)\\n single_channel = self.threshold_image(single_color_img,debug)\\n if debug:\\n # cv2.imshow('single_channel',single_channel)\\n cv2.imwrite('debug_pics/single_channel.jpg',single_channel)\\n cont,hierarchy = self.contours(single_channel,debug)\\n\\n if debug:\\n for i,cnt in enumerate(cont):\\n cv2.drawContours(single_channel,cont,i,(0,0,255),2)\\n if debug: cv2.imwrite('debug_pics/contours.jpg',single_channel) #cv2.imshow('contours',single_channel)\\n\\n return self.get_bricks(cont)\",\n \"def segment(data):\",\n \"def find_sync_light_onsets(sync_light, invert=True, fixmissing=False):\\n # -- Find changes in synch light --\\n sync_light_diff = np.diff(sync_light, prepend=0)\\n if invert:\\n sync_light_diff = -sync_light_diff\\n sync_light_diff[sync_light_diff < 0] = 0\\n sync_light_threshold = 0.2*sync_light_diff.max()\\n sync_light_onset = sync_light_diff > sync_light_threshold\\n\\n\\n # -- Find period of sync_light_onset --\\n sync_light_onset_ind = np.where(sync_light_onset)[0]\\n sync_light_onset_diff = np.diff(sync_light_onset_ind) # In units of frames\\n expected_onset_period = np.median(sync_light_onset_diff) # In units of (float) frames\\n\\n # -- Remove repeated onsets --\\n onset_freq_upper_threshold = int(1.5 * expected_onset_period)\\n onset_freq_lower_threshold = int(0.5 * expected_onset_period)\\n repeated_onsets = sync_light_onset_diff < onset_freq_lower_threshold\\n repeated_onsets_ind = np.where(repeated_onsets)[0]\\n fixed_sync_light_onset = sync_light_onset.copy()\\n fixed_sync_light_onset[sync_light_onset_ind[repeated_onsets_ind+1]] = False\\n\\n # -- Fix missing onsets --\\n if fixmissing:\\n missing_next_onsets = sync_light_onset_diff > onset_freq_upper_threshold\\n missing_next_onsets_ind = np.where(missing_next_onsets)[0]\\n for indm, missing_onset_ind in enumerate(missing_next_onsets_ind):\\n onset_diff = sync_light_onset_diff[missing_onset_ind]\\n n_missing = int(np.round(onset_diff / expected_onset_period))-1\\n #print(n_missing)\\n last_onset_ind = sync_light_onset_ind[missing_onset_ind]\\n next_onset_ind = sync_light_onset_ind[missing_onset_ind+1]\\n period_missing = (next_onset_ind - last_onset_ind)//(n_missing+1)\\n new_onset_inds = last_onset_ind + np.arange(1, n_missing+1)*period_missing\\n #print([last_onset_ind, next_onset_ind])\\n #print(new_onset_inds)\\n fixed_sync_light_onset[new_onset_inds] = True\\n\\n return fixed_sync_light_onset\",\n \"def ibd_segments(\\n self,\\n *,\\n within=None,\\n between=None,\\n max_time=None,\\n min_span=None,\\n store_pairs=None,\\n store_segments=None,\\n ):\\n return self.tables.ibd_segments(\\n within=within,\\n between=between,\\n max_time=max_time,\\n min_span=min_span,\\n store_segments=store_segments,\\n store_pairs=store_pairs,\\n )\",\n \"def segement_divide(pts,step=0.10, offset_x=0.01, offset_y=0.01):\\n\\n # Select the x and y of the points\\n n = len(pts)\\n \\n z = 0.0\\n \\n points_plane = [] \\n points_x = []\\n paint_point = []\\n\\n for i in range(n):\\n points_plane.append([pts[i][0], pts[i][1]])\\n \\n # Sorted the list according to x \\n points_plane.sort(key=lambda x:x[0])\\n\\n # Segment the points according to x \\n counter = 0 # Count the interval\\n x_min = points_plane[0][0]\\n x_max = points_plane[n-1][0]\\n\\n # The whole interval that needs to be divided\\n upper = x_max + offset_x\\n lower = x_min - offset_x\\n lower_bound = lower\\n \\n # Set each segement's lower and upperbound\\n while (lower_bound + step <= upper): \\n # The break condition will be lower_bound > upper - step\\n upper_bound = lower_bound + step\\n\\n # Find the index between lower bound and upper bound\\n # First, find the index which x >= lower bound\\n index = 0\\n \\n while (points_plane[index][0] < lower_bound): \\n index = index + 1 # The index of the first point in the interval\\n \\n # If there is at least one point in the [lower_bound, upper_bound]\\n if (points_plane[index][0] <= upper_bound): \\n\\n x_start = points_plane[index][0]\\n y_max = points_plane[index][1]\\n y_min = points_plane[index][1]\\n \\n while (points_plane[index][0] <= upper_bound): \\n # The break condition will be x[index] > upper bound or index = n - 1\\n # Compute the y max and y min in this interval\\n \\n if points_plane[index][1] > y_max: \\n y_max = points_plane[index][1]\\n\\n if points_plane[index][1] < y_min:\\n y_min = points_plane[index][1]\\n \\n if index < n - 1:\\n index = index + 1\\n else:\\n break\\n # The index of the last point in the interval, when index < n-1\\n \\n x_end = points_plane[index][0]\\n\\n paint_point.append([lower_bound,y_max+offset_y,z]) \\n paint_point.append([lower_bound,y_min-offset_y,z])\\n points_x.append([x_start, x_end])\\n \\n counter = counter + 1\\n\\n # Update interval\\n lower_bound = upper_bound - offset_x\\n \\n # Deal with the last interval\\n lower_bound_last = upper - step\\n index_last = 0\\n counter = counter + 1\\n while ((index_last < n) and (points_plane[index_last][0] < lower_bound_last)): \\n # The first point in the last interval\\n index_last = index_last + 1\\n \\n if (index_last < n): \\n # There is at least one point in the last interval\\n x_start_last = points_plane[index_last][0]\\n y_max_last = points_plane[index_last][1]\\n y_min_last = points_plane[index_last][1]\\n\\n while ((index_last)<n) and (points_plane[index_last][0] <= upper):\\n\\n if points_plane[index_last][1] > y_max_last: \\n y_max_last = points_plane[index_last][1]\\n \\n if points_plane[index_last][1] < y_min_last:\\n y_min_last = points_plane[index_last][1]\\n\\n index_last = index_last + 1\\n \\n index_last = index_last - 1 # The index of the last point in the interval\\n \\n paint_point.append([lower_bound_last, y_max_last+offset_y, z])\\n paint_point.append([lower_bound_last, y_min_last-offset_y, z])\\n# paint_point.append([upper, y_max_last+offset_y, z])\\n# paint_point.append([upper, y_min_last-offset_y, z])\\n# return trans_to_end(paint_point)\\n return paint_point\",\n \"def _find_trial_beam_breaks_regions_in_sync(sync_file):\\n bit = 'BEAM_BREAK'\\n return _find_bit_in_sync(sync_file, bit, ['down', 'up'])\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.54850954","0.508608","0.50796324","0.506026","0.50399494","0.50315195","0.502835","0.49149758","0.49066833","0.49031895","0.48982894","0.48454717","0.48394826","0.48072115","0.47997016","0.47875527","0.47487685","0.4743557","0.47257307","0.4671103","0.46685162","0.46618134","0.46433684","0.4642642","0.46052745","0.4603047","0.46016183","0.45921078","0.45519036","0.45293596","0.45262367","0.45202428","0.45146835","0.4505614","0.45054895","0.44908455","0.4489845","0.44813937","0.44811815","0.44621906","0.44472077","0.4441818","0.44345346","0.44305038","0.44231683","0.44190115","0.44166467","0.44129267","0.43981552","0.43907672","0.43907154","0.43874243","0.43656325","0.43619293","0.43582013","0.4357957","0.43527588","0.4346104","0.43376827","0.43358958","0.4335335","0.4335244","0.43346235","0.43321803","0.43319204","0.43284914","0.4324223","0.43230826","0.43164164","0.4315521","0.4314651","0.43134916","0.43081897","0.4304995","0.43038484","0.4302911","0.42991996","0.4294293","0.42942044","0.42912728","0.42886236","0.42878082","0.42749295","0.42712873","0.42706123","0.4269841","0.4265185","0.42643568","0.42636728","0.42605412","0.42601818","0.42581144","0.42576927","0.42576814","0.42522478","0.42500702","0.42484647","0.42476428","0.4247371","0.4244197"],"string":"[\n \"0.54850954\",\n \"0.508608\",\n \"0.50796324\",\n \"0.506026\",\n \"0.50399494\",\n \"0.50315195\",\n \"0.502835\",\n \"0.49149758\",\n \"0.49066833\",\n \"0.49031895\",\n \"0.48982894\",\n \"0.48454717\",\n \"0.48394826\",\n \"0.48072115\",\n \"0.47997016\",\n \"0.47875527\",\n \"0.47487685\",\n \"0.4743557\",\n \"0.47257307\",\n \"0.4671103\",\n \"0.46685162\",\n \"0.46618134\",\n \"0.46433684\",\n \"0.4642642\",\n \"0.46052745\",\n \"0.4603047\",\n \"0.46016183\",\n \"0.45921078\",\n \"0.45519036\",\n \"0.45293596\",\n \"0.45262367\",\n \"0.45202428\",\n \"0.45146835\",\n \"0.4505614\",\n \"0.45054895\",\n \"0.44908455\",\n \"0.4489845\",\n \"0.44813937\",\n \"0.44811815\",\n \"0.44621906\",\n \"0.44472077\",\n \"0.4441818\",\n \"0.44345346\",\n \"0.44305038\",\n \"0.44231683\",\n \"0.44190115\",\n \"0.44166467\",\n \"0.44129267\",\n \"0.43981552\",\n \"0.43907672\",\n \"0.43907154\",\n \"0.43874243\",\n \"0.43656325\",\n \"0.43619293\",\n \"0.43582013\",\n \"0.4357957\",\n \"0.43527588\",\n \"0.4346104\",\n \"0.43376827\",\n \"0.43358958\",\n \"0.4335335\",\n \"0.4335244\",\n \"0.43346235\",\n \"0.43321803\",\n \"0.43319204\",\n \"0.43284914\",\n \"0.4324223\",\n \"0.43230826\",\n \"0.43164164\",\n \"0.4315521\",\n \"0.4314651\",\n \"0.43134916\",\n \"0.43081897\",\n \"0.4304995\",\n \"0.43038484\",\n \"0.4302911\",\n \"0.42991996\",\n \"0.4294293\",\n \"0.42942044\",\n \"0.42912728\",\n \"0.42886236\",\n \"0.42878082\",\n \"0.42749295\",\n \"0.42712873\",\n \"0.42706123\",\n \"0.4269841\",\n \"0.4265185\",\n \"0.42643568\",\n \"0.42636728\",\n \"0.42605412\",\n \"0.42601818\",\n \"0.42581144\",\n \"0.42576927\",\n \"0.42576814\",\n \"0.42522478\",\n \"0.42500702\",\n \"0.42484647\",\n \"0.42476428\",\n \"0.4247371\",\n \"0.4244197\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.47201967"},"document_rank":{"kind":"string","value":"19"}}},{"rowIdx":94896,"cells":{"query":{"kind":"string","value":"override this to do logic on input_update messages"},"document":{"kind":"string","value":"def do_on_input_update(self, msg_id, payload, player):\n pass"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def data_input_changed(self):\n self.message.data = self.dataInput.toPlainText()\n self.validate_data_input(self.message.dlc)","def update(self, msg):\n pass","def process_IN_MODIFY(self, event):","def handle_input(self, event):\n pass","def oppdater(self, input):\n return","def handle_updates(self, update):\r\n self.__manage_pump()","def _update(self):\n pass","def handle_input(self):\n difference = self.check_state()\n if not difference:\n return\n self.events = []\n self.handle_new_events(difference)\n self.update_timeval()\n self.events.append(self.sync_marker(self.timeval))\n self.write_to_pipe(self.events)","def OnUpdateUI(self, event):\n if not self._input_state == 'readline':\n ConsoleWidget.OnUpdateUI(self, event)","def on_new_input(self):\n self.Error.clear()\n self.Warning.clear()\n self.Information.clear()\n self.update_messages()\n self.update_status()\n if self.auto_save and self.sheet_url:\n self.save_sheet()","def update( ):\r\n pass","def _update_input_type(self):\n pass","def dummy_update( self ):\r\n pass","def update_handler(self, update):\n \n m = update.get('message',{})\n\n sender = self.get_sender(m)\n if sender == self.user_id: return\n \n # code that'll execute upon receiving any message\n if self.greeting and m:\n self.greeting(m)\n\n # parse bot commands\n command, params = self._parse_commands(m)\n \n if command: \n self._apply_command_filter(m, command, params)\n else:\n self._apply_msg_filter(m)","def __update(self, input_):\n self.__process_input(input_)\n\n if not self.state.game_over:\n self.state.spawn_tail()\n self.state.try_move_player()\n if not self.state.game_over:\n self.state.cut_tail()\n self.state.eat_orbs()\n\n self.display.draw(self.state)\n self.state.tick = self.state.tick + 1","def update(self, *inputs):\n raise NotImplementedError","def onUpdated(self):","def on_commitMessageEdit_textChanged(self):\n self.__updateOK()","def user_input_listener(state: SharedState):","def ev_textinput(self, event: TextInput) -> None:","def processInputs(self):","def update(self, *inputs):\n raise NotImplementedError('Must define update function to use this base class')","def on_update(self):\n raise NotImplemented(\"on_update method should be implemented.\")","def update(self):\n\n self.check_events()","def modify_input(self, raw_input_par):\r\n\r\n return self.meta_model.modify_input(raw_input_par)","def update():","def update():","def __process_input(self, input_):\n if self.state.game_over:\n if input_.key_pressed:\n self.state.exit = True\n else:\n if input_.action == 'PLAYER_UP':\n self.state.player.direction = 'U'\n elif input_.action == 'PLAYER_DOWN':\n self.state.player.direction = 'D'\n elif input_.action == 'PLAYER_LEFT':\n self.state.player.direction = 'L'\n elif input_.action == 'PLAYER_RIGHT':\n self.state.player.direction = 'R'","def update(self):\r\n pass","def commandUpdate(self):\n pass","def __msg_handler(self, bot, update):\n trigger = update.message.text\n self.__handler(bot, update, trigger)","def handle_actual_updated(self):\n self._actual_updated()","def modify_input(self, raw_input_par):\r\n raise NotImplementedError","def modify_input(self, raw_input_par):\r\n raise NotImplementedError","def handle_update(self, call):\n self.fire_event(EVENT_UPDATE)","def __msg_handler(self, update, bot):\n trigger = update.message.text\n self.__handler(bot, update, trigger)","def beforeUpdate(self):","def update(self):\n pass","def update(self):\n pass","def update(self):\n pass","def update(self):\n pass","def update(self):\n pass","def update(self):\n pass","def update(self):\n pass","def update(self):\n pass","def update(self):\n pass","def update(self):\n pass","def update(self):\n pass","def update(self):\n pass","def update(self):\n pass","def update(self):\n pass","def update(self):\n pass","def update(self) -> None:\n ...","def update(self, *args, **kwargs):","def handle_input(self, event):\n self.update_timeval()\n self.events = []\n code = self._get_event_type(event)\n\n # Deal with buttons\n self.handle_button(event, code)\n\n # Mouse wheel\n if code == 22:\n self.handle_scrollwheel(event)\n # Other relative mouse movements\n else:\n self.handle_relative(event)\n\n # Add in the absolute position of the mouse cursor\n self.handle_absolute(event)\n\n # End with a sync marker\n self.events.append(self.sync_marker(self.timeval))\n\n # We are done\n self.write_to_pipe(self.events)","def after_update(self, *args):\n raise NotImplementedError","def onFlowUpdate(self, event):","def UpdateInput(self, newInput):\n self.bufferedInput = self.newestInput\n self.newestInput = newInput","def _validate_update_data(self, data):\n return","def before_update(self, obj, st):\n pass","def on_origEdit_textChanged(self):\n self.__updatePronounceButtons()\n self.__updateClearButton()\n self.__updateTranslateButton()","def update(self):","def update(self):","def update(self):","def pre_update(self, **values):\r\n pass","def update(self):\n\n pass","def set_input(self, input):\n pass","def set_input(self, input):\n pass","def update(self, *args, **kwargs):\n pass","def update(self, *args, **kwargs):\n pass","def update(self, *args, **kwargs):\n pass","def handle_input(self, event):\n self.update_timeval()\n self.events = []\n code = self._get_event_key_code(event)\n\n if code in self.codes:\n new_code = self.codes[code]\n else:\n new_code = 0\n event_type = self._get_event_type(event)\n value = self._get_key_value(event, event_type)\n scan_event, key_event = self.emulate_press(\n new_code, code, value, self.timeval)\n\n self.events.append(scan_event)\n self.events.append(key_event)\n # End with a sync marker\n self.events.append(self.sync_marker(self.timeval))\n # We are done\n self.write_to_pipe(self.events)","def process_inputs(self, inputs):","def dispatch_update(self, update):\n command_handlers = {\n '/start': self._do_start,\n '/help': self._do_help,\n '/neuer_spruch': self._do_neuer_spruch,\n '/mein_spruch': self._do_mein_spruch,\n '/alle_meine_sprueche': self._do_alle_meine_sprueche,\n '/loesche_meine_sprueche': self._do_loesche_meine_sprüche,\n '/setze_aktiven_spruch': self._do_setze_aktiven_spruch\n }\n callback_handlers = {\n '/delete': self._callback_delete,\n '/active': self._callback_active\n }\n\n if \"message\" in update.keys():\n # Parse command\n args = update[\"message\"][\"text\"].split(' ', 1)\n command = args[0].replace('@cde_nasenspruch_bot', '')\n chat_id = update[\"message\"][\"chat\"][\"id\"]\n user_id = update[\"message\"][\"from\"][\"id\"]\n\n # Call command handler function\n try:\n command_handlers[command](chat_id, user_id, args, update)\n except KeyError:\n if command.startswith('/'):\n self.tclient.send_message('Unbekannter Befehl. Versuch es mal mit /help', chat_id)\n pass\n elif \"callback_query\" in update.keys():\n args = update[\"callback_query\"][\"data\"].split(' ', 2)\n command = args[0].replace('@cde_nasenspruch_bot', '')\n chat_id = update[\"callback_query\"][\"from\"][\"id\"]\n user_id = update[\"callback_query\"][\"from\"][\"id\"]\n \n # Call callback handler function\n try:\n callback_handlers[command](chat_id, user_id, args, update)\n except KeyError:\n print('Unbekannter callback_query {}'.format(update[\"callback_query\"][\"data\"]))\n pass","def update(self, *args, **kw):\n pass","def install_handle_input(self):\n pass","def Update(self):\r\n\r\n # does nothing\r\n pass","def update(self)->None:\n pass","def input(self):\r\n pass","def update(self):\n # default implementation is to do nothing.","def _handleInput(self, paramInput):\n pass","def update(self, msg):\r\n self.msgVar.set(msg)","def update(self, msg):\r\n self.msgVar.set(msg)","def update_data():\n pass","def updateMessages(self, parameters):\r\n return","def updateMessages(self, parameters):\r\n return","def updateMessages(self, parameters):\r\n return","def updateMessages(self, parameters):\r\n return","def updateMessages(self, parameters):\r\n return","def updateMessages(self, parameters):\r\n return","def updateMessages(self, parameters):\r\n return","def updateMessages(self, parameters):\r\n return","def updateMessages(self, parameters):\r\n return","def updateMessages(self, parameters):\r\n return","def updateMessages(self, parameters):\r\n return","def updateMessages(self, parameters):\r\n return","def updateMessages(self, parameters):\r\n return","def updateMessages(self, parameters):\r\n return","def updateMessages(self, parameters):\r\n return","def updateMessages(self, parameters):\r\n return"],"string":"[\n \"def data_input_changed(self):\\n self.message.data = self.dataInput.toPlainText()\\n self.validate_data_input(self.message.dlc)\",\n \"def update(self, msg):\\n pass\",\n \"def process_IN_MODIFY(self, event):\",\n \"def handle_input(self, event):\\n pass\",\n \"def oppdater(self, input):\\n return\",\n \"def handle_updates(self, update):\\r\\n self.__manage_pump()\",\n \"def _update(self):\\n pass\",\n \"def handle_input(self):\\n difference = self.check_state()\\n if not difference:\\n return\\n self.events = []\\n self.handle_new_events(difference)\\n self.update_timeval()\\n self.events.append(self.sync_marker(self.timeval))\\n self.write_to_pipe(self.events)\",\n \"def OnUpdateUI(self, event):\\n if not self._input_state == 'readline':\\n ConsoleWidget.OnUpdateUI(self, event)\",\n \"def on_new_input(self):\\n self.Error.clear()\\n self.Warning.clear()\\n self.Information.clear()\\n self.update_messages()\\n self.update_status()\\n if self.auto_save and self.sheet_url:\\n self.save_sheet()\",\n \"def update( ):\\r\\n pass\",\n \"def _update_input_type(self):\\n pass\",\n \"def dummy_update( self ):\\r\\n pass\",\n \"def update_handler(self, update):\\n \\n m = update.get('message',{})\\n\\n sender = self.get_sender(m)\\n if sender == self.user_id: return\\n \\n # code that'll execute upon receiving any message\\n if self.greeting and m:\\n self.greeting(m)\\n\\n # parse bot commands\\n command, params = self._parse_commands(m)\\n \\n if command: \\n self._apply_command_filter(m, command, params)\\n else:\\n self._apply_msg_filter(m)\",\n \"def __update(self, input_):\\n self.__process_input(input_)\\n\\n if not self.state.game_over:\\n self.state.spawn_tail()\\n self.state.try_move_player()\\n if not self.state.game_over:\\n self.state.cut_tail()\\n self.state.eat_orbs()\\n\\n self.display.draw(self.state)\\n self.state.tick = self.state.tick + 1\",\n \"def update(self, *inputs):\\n raise NotImplementedError\",\n \"def onUpdated(self):\",\n \"def on_commitMessageEdit_textChanged(self):\\n self.__updateOK()\",\n \"def user_input_listener(state: SharedState):\",\n \"def ev_textinput(self, event: TextInput) -> None:\",\n \"def processInputs(self):\",\n \"def update(self, *inputs):\\n raise NotImplementedError('Must define update function to use this base class')\",\n \"def on_update(self):\\n raise NotImplemented(\\\"on_update method should be implemented.\\\")\",\n \"def update(self):\\n\\n self.check_events()\",\n \"def modify_input(self, raw_input_par):\\r\\n\\r\\n return self.meta_model.modify_input(raw_input_par)\",\n \"def update():\",\n \"def update():\",\n \"def __process_input(self, input_):\\n if self.state.game_over:\\n if input_.key_pressed:\\n self.state.exit = True\\n else:\\n if input_.action == 'PLAYER_UP':\\n self.state.player.direction = 'U'\\n elif input_.action == 'PLAYER_DOWN':\\n self.state.player.direction = 'D'\\n elif input_.action == 'PLAYER_LEFT':\\n self.state.player.direction = 'L'\\n elif input_.action == 'PLAYER_RIGHT':\\n self.state.player.direction = 'R'\",\n \"def update(self):\\r\\n pass\",\n \"def commandUpdate(self):\\n pass\",\n \"def __msg_handler(self, bot, update):\\n trigger = update.message.text\\n self.__handler(bot, update, trigger)\",\n \"def handle_actual_updated(self):\\n self._actual_updated()\",\n \"def modify_input(self, raw_input_par):\\r\\n raise NotImplementedError\",\n \"def modify_input(self, raw_input_par):\\r\\n raise NotImplementedError\",\n \"def handle_update(self, call):\\n self.fire_event(EVENT_UPDATE)\",\n \"def __msg_handler(self, update, bot):\\n trigger = update.message.text\\n self.__handler(bot, update, trigger)\",\n \"def beforeUpdate(self):\",\n \"def update(self):\\n pass\",\n \"def update(self):\\n pass\",\n \"def update(self):\\n pass\",\n \"def update(self):\\n pass\",\n \"def update(self):\\n pass\",\n \"def update(self):\\n pass\",\n \"def update(self):\\n pass\",\n \"def update(self):\\n pass\",\n \"def update(self):\\n pass\",\n \"def update(self):\\n pass\",\n \"def update(self):\\n pass\",\n \"def update(self):\\n pass\",\n \"def update(self):\\n pass\",\n \"def update(self):\\n pass\",\n \"def update(self):\\n pass\",\n \"def update(self) -> None:\\n ...\",\n \"def update(self, *args, **kwargs):\",\n \"def handle_input(self, event):\\n self.update_timeval()\\n self.events = []\\n code = self._get_event_type(event)\\n\\n # Deal with buttons\\n self.handle_button(event, code)\\n\\n # Mouse wheel\\n if code == 22:\\n self.handle_scrollwheel(event)\\n # Other relative mouse movements\\n else:\\n self.handle_relative(event)\\n\\n # Add in the absolute position of the mouse cursor\\n self.handle_absolute(event)\\n\\n # End with a sync marker\\n self.events.append(self.sync_marker(self.timeval))\\n\\n # We are done\\n self.write_to_pipe(self.events)\",\n \"def after_update(self, *args):\\n raise NotImplementedError\",\n \"def onFlowUpdate(self, event):\",\n \"def UpdateInput(self, newInput):\\n self.bufferedInput = self.newestInput\\n self.newestInput = newInput\",\n \"def _validate_update_data(self, data):\\n return\",\n \"def before_update(self, obj, st):\\n pass\",\n \"def on_origEdit_textChanged(self):\\n self.__updatePronounceButtons()\\n self.__updateClearButton()\\n self.__updateTranslateButton()\",\n \"def update(self):\",\n \"def update(self):\",\n \"def update(self):\",\n \"def pre_update(self, **values):\\r\\n pass\",\n \"def update(self):\\n\\n pass\",\n \"def set_input(self, input):\\n pass\",\n \"def set_input(self, input):\\n pass\",\n \"def update(self, *args, **kwargs):\\n pass\",\n \"def update(self, *args, **kwargs):\\n pass\",\n \"def update(self, *args, **kwargs):\\n pass\",\n \"def handle_input(self, event):\\n self.update_timeval()\\n self.events = []\\n code = self._get_event_key_code(event)\\n\\n if code in self.codes:\\n new_code = self.codes[code]\\n else:\\n new_code = 0\\n event_type = self._get_event_type(event)\\n value = self._get_key_value(event, event_type)\\n scan_event, key_event = self.emulate_press(\\n new_code, code, value, self.timeval)\\n\\n self.events.append(scan_event)\\n self.events.append(key_event)\\n # End with a sync marker\\n self.events.append(self.sync_marker(self.timeval))\\n # We are done\\n self.write_to_pipe(self.events)\",\n \"def process_inputs(self, inputs):\",\n \"def dispatch_update(self, update):\\n command_handlers = {\\n '/start': self._do_start,\\n '/help': self._do_help,\\n '/neuer_spruch': self._do_neuer_spruch,\\n '/mein_spruch': self._do_mein_spruch,\\n '/alle_meine_sprueche': self._do_alle_meine_sprueche,\\n '/loesche_meine_sprueche': self._do_loesche_meine_sprüche,\\n '/setze_aktiven_spruch': self._do_setze_aktiven_spruch\\n }\\n callback_handlers = {\\n '/delete': self._callback_delete,\\n '/active': self._callback_active\\n }\\n\\n if \\\"message\\\" in update.keys():\\n # Parse command\\n args = update[\\\"message\\\"][\\\"text\\\"].split(' ', 1)\\n command = args[0].replace('@cde_nasenspruch_bot', '')\\n chat_id = update[\\\"message\\\"][\\\"chat\\\"][\\\"id\\\"]\\n user_id = update[\\\"message\\\"][\\\"from\\\"][\\\"id\\\"]\\n\\n # Call command handler function\\n try:\\n command_handlers[command](chat_id, user_id, args, update)\\n except KeyError:\\n if command.startswith('/'):\\n self.tclient.send_message('Unbekannter Befehl. Versuch es mal mit /help', chat_id)\\n pass\\n elif \\\"callback_query\\\" in update.keys():\\n args = update[\\\"callback_query\\\"][\\\"data\\\"].split(' ', 2)\\n command = args[0].replace('@cde_nasenspruch_bot', '')\\n chat_id = update[\\\"callback_query\\\"][\\\"from\\\"][\\\"id\\\"]\\n user_id = update[\\\"callback_query\\\"][\\\"from\\\"][\\\"id\\\"]\\n \\n # Call callback handler function\\n try:\\n callback_handlers[command](chat_id, user_id, args, update)\\n except KeyError:\\n print('Unbekannter callback_query {}'.format(update[\\\"callback_query\\\"][\\\"data\\\"]))\\n pass\",\n \"def update(self, *args, **kw):\\n pass\",\n \"def install_handle_input(self):\\n pass\",\n \"def Update(self):\\r\\n\\r\\n # does nothing\\r\\n pass\",\n \"def update(self)->None:\\n pass\",\n \"def input(self):\\r\\n pass\",\n \"def update(self):\\n # default implementation is to do nothing.\",\n \"def _handleInput(self, paramInput):\\n pass\",\n \"def update(self, msg):\\r\\n self.msgVar.set(msg)\",\n \"def update(self, msg):\\r\\n self.msgVar.set(msg)\",\n \"def update_data():\\n pass\",\n \"def updateMessages(self, parameters):\\r\\n return\",\n \"def updateMessages(self, parameters):\\r\\n return\",\n \"def updateMessages(self, parameters):\\r\\n return\",\n \"def updateMessages(self, parameters):\\r\\n return\",\n \"def updateMessages(self, parameters):\\r\\n return\",\n \"def updateMessages(self, parameters):\\r\\n return\",\n \"def updateMessages(self, parameters):\\r\\n return\",\n \"def updateMessages(self, parameters):\\r\\n return\",\n \"def updateMessages(self, parameters):\\r\\n return\",\n \"def updateMessages(self, parameters):\\r\\n return\",\n \"def updateMessages(self, parameters):\\r\\n return\",\n \"def updateMessages(self, parameters):\\r\\n return\",\n \"def updateMessages(self, parameters):\\r\\n return\",\n \"def updateMessages(self, parameters):\\r\\n return\",\n \"def updateMessages(self, parameters):\\r\\n return\",\n \"def updateMessages(self, parameters):\\r\\n return\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7064037","0.68353105","0.679278","0.6780095","0.6757028","0.66975","0.6632578","0.6601894","0.65531427","0.6519125","0.64932","0.6461436","0.645683","0.64120686","0.6398695","0.63841844","0.6377531","0.63212633","0.6266965","0.6207796","0.6190815","0.61791474","0.6159929","0.61538285","0.61509174","0.61281544","0.61281544","0.6125984","0.61129475","0.61063725","0.6087144","0.60774964","0.6077347","0.6077347","0.6061959","0.6032166","0.60319275","0.6031357","0.6031357","0.6031357","0.6031357","0.6031357","0.6031357","0.6031357","0.6031357","0.6031357","0.6031357","0.6031357","0.6031357","0.6031357","0.6031357","0.6031357","0.60107577","0.60085744","0.599906","0.59634745","0.59617656","0.59582883","0.59458697","0.5935914","0.59038794","0.5902206","0.5902206","0.5902206","0.589704","0.5888465","0.5863034","0.5863034","0.58544207","0.58544207","0.58544207","0.5846684","0.5839743","0.583942","0.583895","0.5831098","0.5828973","0.58195525","0.5810551","0.579335","0.57839936","0.5779489","0.5779489","0.5754509","0.5748531","0.5748531","0.5748531","0.5748531","0.5748531","0.5748531","0.5748531","0.5748531","0.5748531","0.5748531","0.5748531","0.5748531","0.5748531","0.5748531","0.5748531","0.5748531"],"string":"[\n \"0.7064037\",\n \"0.68353105\",\n \"0.679278\",\n \"0.6780095\",\n \"0.6757028\",\n \"0.66975\",\n \"0.6632578\",\n \"0.6601894\",\n \"0.65531427\",\n \"0.6519125\",\n \"0.64932\",\n \"0.6461436\",\n \"0.645683\",\n \"0.64120686\",\n \"0.6398695\",\n \"0.63841844\",\n \"0.6377531\",\n \"0.63212633\",\n \"0.6266965\",\n \"0.6207796\",\n \"0.6190815\",\n \"0.61791474\",\n \"0.6159929\",\n \"0.61538285\",\n \"0.61509174\",\n \"0.61281544\",\n \"0.61281544\",\n \"0.6125984\",\n \"0.61129475\",\n \"0.61063725\",\n \"0.6087144\",\n \"0.60774964\",\n \"0.6077347\",\n \"0.6077347\",\n \"0.6061959\",\n \"0.6032166\",\n \"0.60319275\",\n \"0.6031357\",\n \"0.6031357\",\n \"0.6031357\",\n \"0.6031357\",\n \"0.6031357\",\n \"0.6031357\",\n \"0.6031357\",\n \"0.6031357\",\n \"0.6031357\",\n \"0.6031357\",\n \"0.6031357\",\n \"0.6031357\",\n \"0.6031357\",\n \"0.6031357\",\n \"0.6031357\",\n \"0.60107577\",\n \"0.60085744\",\n \"0.599906\",\n \"0.59634745\",\n \"0.59617656\",\n \"0.59582883\",\n \"0.59458697\",\n \"0.5935914\",\n \"0.59038794\",\n \"0.5902206\",\n \"0.5902206\",\n \"0.5902206\",\n \"0.589704\",\n \"0.5888465\",\n \"0.5863034\",\n \"0.5863034\",\n \"0.58544207\",\n \"0.58544207\",\n \"0.58544207\",\n \"0.5846684\",\n \"0.5839743\",\n \"0.583942\",\n \"0.583895\",\n \"0.5831098\",\n \"0.5828973\",\n \"0.58195525\",\n \"0.5810551\",\n \"0.579335\",\n \"0.57839936\",\n \"0.5779489\",\n \"0.5779489\",\n \"0.5754509\",\n \"0.5748531\",\n \"0.5748531\",\n \"0.5748531\",\n \"0.5748531\",\n \"0.5748531\",\n \"0.5748531\",\n \"0.5748531\",\n \"0.5748531\",\n \"0.5748531\",\n \"0.5748531\",\n \"0.5748531\",\n \"0.5748531\",\n \"0.5748531\",\n \"0.5748531\",\n \"0.5748531\",\n \"0.5748531\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.79876757"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":94897,"cells":{"query":{"kind":"string","value":"Given the state of the 'game', decide what your cells ('game.me.cells') should do."},"document":{"kind":"string","value":"def step(self, game: Game):\n\n print(\"Tick #{}\".format(game.time_left))\n\n splitValue = getSplitValue(game)\n print (getSplitValue(game))\n\n for cell in game.me.cells:\n\n if game.time_left < 6:\n cell.trade(99999)\n\n\n\n\n if cell.mass >= splitValue:\n if len(game.me.cells) < 10:\n cell.split()\n #else:\n #cell.trade(cell.mass - 100)\n else:\n distance = cell.position.distance_to(cell.target)\n possibleVictims = findVictims(cell, game.enemies)\n\n if (cell.mass <= 100):\n target = closestRessource(game, cell, possibleVictims + game.resources.allResources, len(possibleVictims))\n else:\n #cell.burst()\n target = closestRessource(game, cell, possibleVictims, len(possibleVictims))\n\n\n for e in game.enemies:\n for c in e.cells:\n if enemyComingthrough(cell, c):\n target = cell.position + (c.target - c.position)\n #cell.burst()\n pass\n\n if (target != None):\n cell.move(target)\n else:\n print (' KES TU FAIS, VA PAS LÀ ')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _check_cells(self):\n for row_number in range(self.number_cells_y):\n for col_number in range(self.number_cells_x):\n alive_neighbours = self._get_neighbours(row_number,col_number)\n \n self.to_be_updated[row_number][col_number] = False\n if self.cells[row_number][col_number].get_status():\n if alive_neighbours < 2:\n self.to_be_updated[row_number][col_number] = True\n elif alive_neighbours > 3:\n self.to_be_updated[row_number][col_number] = True\n else:\n if alive_neighbours == 3:\n self.to_be_updated[row_number][col_number] = True","def init_cells(self):\n state = list()\n width = WIDTH / CELL_SIZE\n height = HEIGHT / CELL_SIZE\n\n for index in range(0, width * height):\n if randint(1, 100) >= 100 - CELL_DENSITY:\n # Live cell.\n status = NORMAL\n state.append(1)\n else:\n # Dead cell.\n status = HIDDEN\n state.append(0)\n\n cell = self.canvas.create_rectangle((index % width) * CELL_SIZE, (index / width) * CELL_SIZE,\n ((index % width) + 1) * CELL_SIZE, ((index / width) + 1) * CELL_SIZE,\n fill=\"black\", state=status, outline=\"white\")\n self.cells.append(cell)\n\n return state","def examineMaze(self, gameState):\n w = self.walls.width\n h = self.walls.height\n walls = self.walls.deepCopy()\n food1 = self.getFoodYouAreDefending(gameState)\n food2 = self.getFood(gameState)\n\n # Save map as 0, 1, 2 and 3 (0:walls, 1:spaces, 2:babies, 3:food)\n for x in range(w):\n for y in range(h):\n if walls[x][y]:\n walls[x][y] = 0\n elif food1[x][y]:\n walls[x][y] = 2\n elif food2[x][y]:\n walls[x][y] = 2\n else:\n walls[x][y] = 1\n\n roomsDisplay = []\n # Detect doors and spaces. Spaces are now negative\n for x in range(w):\n for y in range(h):\n if walls[x][y] > 0:\n exitsNum = 0\n if walls[x][y - 1] != 0:\n exitsNum += 1\n if walls[x][y + 1] != 0:\n exitsNum += 1\n if walls[x - 1][y] != 0:\n exitsNum += 1\n if walls[x + 1][y] != 0:\n exitsNum += 1\n if exitsNum == 1 or exitsNum == 2:\n walls[x][y] = -1 * walls[x][y]\n roomsDisplay.append((x, y))\n elif exitsNum == 0:\n # We erase unaccessible cells\n walls[x][y] = 0\n else:\n # These are doors or big rooms, we leave them positive\n pass\n\n # Create roomsGraph: every room has a number, some cells and some doors\n roomsGraph = []\n doorsGraph = []\n for x in range(1, w - 1):\n for y in range(1, h - 1):\n if walls[x][y] < 0:\n spacesNum = 0\n if walls[x][y - 1] < 0:\n spacesNum += 1\n if walls[x][y + 1] < 0:\n spacesNum += 1\n if walls[x - 1][y] < 0:\n spacesNum += 1\n if walls[x + 1][y] < 0:\n spacesNum += 1\n if spacesNum < 2:\n endOfPath = False\n graphNode = {\"path\": [], \"doors\": [], \"food\": 0, \"isBig\": False}\n auxx = x\n auxy = y\n while not endOfPath:\n graphNode[\"path\"].append((x, y))\n graphNode[\"food\"] += -walls[x][y] - 1\n walls[x][y] = 0\n xx = x\n yy = y\n if walls[x][y - 1] < 0:\n yy = y - 1\n elif walls[x][y + 1] < 0:\n yy = y + 1\n elif walls[x - 1][y] < 0:\n xx = x - 1\n elif walls[x + 1][y] < 0:\n xx = x + 1\n else:\n endOfPath = True\n if walls[x][y - 1] > 0:\n if [(x, y - 1), []] not in doorsGraph:\n graphNode[\"doors\"].append(len(doorsGraph))\n doorsGraph.append([(x, y - 1), []])\n else:\n graphNode[\"doors\"].append(doorsGraph.index([(x, y - 1), []]))\n if walls[x][y + 1] > 0:\n if [(x, y + 1), []] not in doorsGraph:\n graphNode[\"doors\"].append(len(doorsGraph))\n doorsGraph.append([(x, y + 1), []])\n else:\n graphNode[\"doors\"].append(doorsGraph.index([(x, y + 1), []]))\n if walls[x - 1][y] > 0:\n if [(x - 1, y), []] not in doorsGraph:\n graphNode[\"doors\"].append(len(doorsGraph))\n doorsGraph.append([(x - 1, y), []])\n else:\n graphNode[\"doors\"].append(doorsGraph.index([(x - 1, y), []]))\n if walls[x + 1][y] > 0:\n if [(x + 1, y), []] not in doorsGraph:\n graphNode[\"doors\"].append(len(doorsGraph))\n doorsGraph.append([(x + 1, y), []])\n else:\n graphNode[\"doors\"].append(doorsGraph.index([(x + 1, y), []]))\n x = xx\n y = yy\n roomsGraph.append(graphNode)\n x = auxx\n y = auxy\n\n # Create doorsGraph: every door has a number, and goes to other rooms or other doors\n for j, door in enumerate(doorsGraph):\n for i, room in enumerate(roomsGraph):\n for aDoor in room[\"doors\"]:\n if aDoor == j:\n doorsGraph[j][1] = doorsGraph[j][1] + [i]\n (x, y) = doorsGraph[j][0]\n adjacentCells = [(x+1, y), (x-1, y), (x, y+1), (x, y-1)]\n adjacentDoors = []\n # Check adjacent doors and add them to the current door (door structure is [pos, adjRooms, adjDoors]\n for p in adjacentCells:\n # Skip if wall\n if self.walls[p[0]][p[1]]:\n continue\n # Skip if door\n isRoom = False\n for room in doorsGraph[j][1]:\n if p in roomsGraph[room][\"path\"]:\n isRoom = True\n break\n if not isRoom:\n # Add if existing door\n doorFound = False\n for i, neighborDoor in enumerate(doorsGraph):\n if neighborDoor[0] == p:\n adjacentDoors.append(i)\n doorFound = True\n break\n # Create if non existing door and add\n if not doorFound:\n adjacentDoors.append(len(doorsGraph))\n doorsGraph.append([p, []])\n doorsGraph[j].append(adjacentDoors)\n\n # Create doorsDistance: maps what doors can be accessed from other doors\n roomsMapper = {}\n doorsMapper = {}\n isRoom = util.Counter()\n for i, door in enumerate(doorsGraph):\n doorsMapper[door[0]] = i\n isRoom[door[0]] = 0\n for i, room in enumerate(roomsGraph):\n for p in room[\"path\"]:\n roomsMapper[p] = i\n isRoom[p] = 1\n\n # Create self variables\n self.doorsGraph = doorsGraph\n self.roomsGraph = roomsGraph\n self.roomsMapper = roomsMapper\n self.doorsMapper = doorsMapper\n self.isRoom = isRoom\n\n # # Find dead ends (rooms with only one door)\n # deadRooms = {}\n # deadDoors = {}\n # # deaderDoors = {}\n # # deaderRooms = {}\n # for i, room in enumerate(roomsGraph):\n # if len(room[\"doors\"]) == 1:\n # deadRooms[i] = room[\"doors\"][0]\n # deadDoors[room[\"doors\"][0]] = 1\n # numdR = 0\n # aliveR = -1\n # for adjRoom in doorsGraph[room[\"doors\"][0]][1]:\n # if adjRoom not in deadRooms:\n # numdR += 1\n # aliveR = adjRoom\n # if numdR + len(doorsGraph[room[\"doors\"][0]][2]) == 1:\n # if aliveR >= 0:\n # deaderRooms[aliveR] = room[\"doors\"][0]\n # for adjDoor in roomsGraph[aliveR][\"doors\"]:\n # if adjDoor == room[\"doors\"][0]:\n # continue\n # deaderDoors[adjDoor] = 1.0\n # else:\n # deaderDoors[doorsGraph[room[\"doors\"][0]][2][0]] = 1.0\n\n\n # roomsCounter = [util.Counter(), util.Counter(), util.Counter(), util.Counter()]\n # for r in deaderRooms:\n # for p in roomsGraph[r][\"path\"]:\n # roomsCounter[0][p] = 0.4\n # for d in deaderDoors:\n # roomsCounter[1][doorsGraph[d][0]] = 0.4\n # self.displayDistributionsOverPositions(roomsCounter)\n # raw_input(\"Press Enter to continue ...\")\n\n\n # print deadDoors\n # print\n # print deadRooms\n # print \"-----------------\"\n\n # deadEndsChanged = True\n # while deadEndsChanged:\n # deadEndsChanged = False\n # for i, room in enumerate(roomsGraph):\n # numAliveDoors = 0\n # aliveDoor = 0\n # deadDoor = []\n # for door in room[\"doors\"]:\n # if door not in deadDoors:\n # numAliveDoors += 1\n # aliveDoor = door\n # else:\n # deadDoor.append(door)\n # if numAliveDoors == 1:\n # aliveRoom = 0\n # aliveNeighborDoor = 0\n # for door in deadDoor:\n # # aliveNeighborDoor += len(doorsGraph[door][2])\n # for neighborRoom in doorsGraph[door][1]:\n # if neighborRoom not in deadRooms:\n # aliveRoom += 1\n # if aliveRoom == len(deadDoor):\n # deadRooms[i] = aliveDoor\n # deadDoors[aliveDoor] = 1\n # deadEndsChanged = True\n # roomsCounter = [util.Counter(), util.Counter(), util.Counter(), util.Counter()]\n # roomsCounter[0][doorsGraph[aliveDoor][0]] = 1\n # for p in room[\"path\"]:\n # roomsCounter[1][p] = 1\n # for p in deadDoor:\n # roomsCounter[2][doorsGraph[p][0]] = 1\n # self.displayDistributionsOverPositions(roomsCounter)\n # raw_input(\"Press Enter to continue ...\")\n\n\n # Find dead ends (rooms with doors that only go to other dead ends, except one)\n # Danger, it is theoretically possible to have a map only with dead ends, which may make this crash\n # deadEndsChanged = True\n # while deadEndsChanged:\n # deadEndsChanged = False\n # for i, door in enumerate(doorsGraph):\n # if i not in deadDoors:\n # numOpenRooms = 0\n # openRoom = 0\n # for j, room in enumerate(door[1]):\n # if room not in deadRooms:\n # numOpenRooms += 1\n # openRoom = j\n # if numOpenRooms + len(door[2]) == 1:\n # for room in door[1]:\n # if room != openRoom:\n # deadRooms[room] = i\n # deadDoors[j] = 1\n # deadEndsChanged = True\n # roomsCounter = [util.Counter(), util.Counter(), util.Counter(), util.Counter()]\n # roomsCounter[0][door[0]] = 1\n # for rr in door[1]:\n # print rr\n # if rr in deadRooms:\n # for p in roomsGraph[rr][\"path\"]:\n # roomsCounter[1][p] = 1\n # else:\n # for p in roomsGraph[rr][\"path\"]:\n # roomsCounter[3][p] = 1\n # self.displayDistributionsOverPositions(roomsCounter)\n # raw_input(\"Press Enter to continue ...\")\n\n # print deadDoors\n # print\n # print deadRooms\n # print \"-----------------\"\n\n # roomsCounter = [util.Counter(), util.Counter(), util.Counter(), util.Counter()]\n # roomsCounter[1][(6, 9)] = 0.4\n # self.displayDistributionsOverPositions(roomsCounter)\n # raw_input(\"Press Enter to continue ...\")\n\n # roomsCounter = [util.Counter(), util.Counter(), util.Counter(), util.Counter()]\n # for r in deadRooms:\n # for p in roomsGraph[r][\"path\"]:\n # roomsCounter[0][p] = 0.4\n # for d in deadDoors:\n # roomsCounter[1][doorsGraph[d][0]] = 0.4\n # self.displayDistributionsOverPositions(roomsCounter)\n # raw_input(\"Press Enter to continue ...\")\n\n # Show every room\n roomsCounter = [util.Counter(), util.Counter(), util.Counter(), util.Counter()]\n for room in roomsGraph:\n for p in room[\"path\"]:\n if len(room[\"doors\"]) > 1:\n roomsCounter[0][p] = 0.4\n else:\n roomsCounter[2][p] = 0.4\n # Show every door\n for door in doorsGraph:\n roomsCounter[1][door[0]] = 0.4\n # Display rooms and doors (red: rooms with at least one exit; orange: rooms with 1 exit; blue: doors\n self.displayDistributionsOverPositions(roomsCounter)\n # raw_input(\"Press Enter to continue ...\")","def next_state_of_cell(self, x_cell, y_cell):\n neighbours = self.get_number_neighbours_of_cell(x_cell, y_cell)\n if(self.board_state[x_cell][y_cell] == 1):\n # Any live cell with more than three live neighbours dies, \n # as if by overpopulation.\n if(neighbours > 3):\n return 0\n # Any live cell with fewer than two live neighbours dies,\n # as if by underpopulation.\n elif(neighbours < 2):\n return 0\n # Any live cell with two or three live neighbours lives\n # on to the next generation.\n else:\n return 1\n if(self.board_state[x_cell][y_cell] == 0):\n # Any dead cell with exactly three live neighbours becomes a live cell, \n # as if by reproduction.\n if(neighbours == 3):\n return 1\n else:\n return 0","def in_cell(self):\n for player in self.players:\n for cell in self.cell_lst:\n if player.x in cell[0] and player.y in cell[1]:\n player.current_cell = cell\n break","def test_dead_cell(self, alive_cells, alive):\n for positions in alive_cells:\n world = gol.World(3, 3)\n for x, y in positions:\n world.set_cell((x, y))\n world.update()\n assert world[(0, 0)] == alive","def test_live_cell(self, alive_cells, alive):\n for positions in alive_cells:\n world = gol.World(3, 3)\n world.set_cell((0, 0))\n for x, y in positions:\n world.set_cell((x, y))\n world.update()\n assert world[(0, 0)] == alive","def update_cells(self, state):\n width = WIDTH / CELL_SIZE\n height = HEIGHT / CELL_SIZE\n\n for index in range(0, width * height):\n if state[index] != self.get_state(index):\n self.toggle_color(index)","def cell_create(game_set, screen, covids, cells):\n cell_create_flag = True\n cell = Cell(game_set, screen)\n for old_cell in cells.sprites():\n if old_cell.rect.y < game_set.cell_number_adjust:\n cell_create_flag = False\n break\n if (not pygame.sprite.spritecollide(cell, cells, 0) and\n not pygame.sprite.spritecollide(cell, covids, 0) and\n cell_create_flag):\n cells.add(cell)","def state_generator(self):\n\n kernel = np.array([\n [1, 1, 1],\n [1, 0, 1],\n [1, 1, 1]])\n iteration = 0\n\n while True: # (Game of Life does not end)\n # Run 2D convolution with the given kernel to find out how many neighbors each cell has.\n # Boundary option determines whether to run with hard boundaries on the game board or\n # using a toroid board which wraps circularly. These are the two strategies for handling\n # a finite game board. scipy.signal.convolve2d handles these two modes gracefully, which\n # is why it is used here. There is also a performance gain when using numpy/scipy matrix\n # operations as opposed to iterating element-wise over the whole matrix.\n # See https://docs.scipy.org/doc/scipy-0.19.1/reference/generated/scipy.signal.convolve2d.html\n\n # There is a more sophisticated and efficient algorithm for determining next game state\n # (see http://dotat.at/prog/life/life.html) but for clarity and a lack of time, the standard\n # implementation was chosen.\n\n num_neighbors_board = convolve2d(self.board, kernel, mode='same', boundary=self.boundary.value)\n\n # Find empty cells that have three neighbors\n birth_coordinates = np.where(np.logical_and(self.board == 0, num_neighbors_board == 3))\n\n # Find live cells with too few or too many neighbors\n death_coordinates = np.where(\n np.logical_and(\n self.board == 1,\n np.logical_or(num_neighbors_board < 2, num_neighbors_board > 3)\n )\n )\n\n births = np.array(birth_coordinates).transpose().tolist()\n deaths = np.array(death_coordinates).transpose().tolist()\n self.board[birth_coordinates] = 1\n self.board[death_coordinates] = 0\n\n iteration += 1\n yield self.board, births, deaths, iteration","def game_of_life():\n # 3x3 neighbourhood\n offsets = [[(y, x) for y in range(-1, 2)] for x in range(-1, 2)]\n\n # Create mappings\n mappings = {}\n for i in range(2 ** 9):\n\n # Determine the initial state (key)\n key = f\"{bin(i)[2:]:0>9}\" # As binary string\n key = tuple(k == \"1\" for k in key) # As tuple of bools\n key = tuple(key[i * 3:i * 3 + 3] for i in range(3)) # Reshape into 2D grid\n\n # Alive counts\n centre = key[1][1]\n others = sum(sum(row) for row in key) - centre\n\n # Skip if state does not evaluate to True\n if centre:\n if others not in (2, 3):\n continue\n\n else:\n if others != 3:\n continue\n\n mappings[key] = True\n\n return Mapping2DRuleset(mappings, offsets)","def game_value(self, state):\n # check horizontal wins\n for row in state:\n for i in range(2):\n if row[i] != ' ' and row[i] == row[i+1] == row[i+2] == row[i+3]:\n return 1 if row[i]==self.my_piece else -1\n\n # check vertical wins\n for col in range(5):\n for i in range(2):\n if state[i][col] != ' ' and state[i][col] == state[i+1][col] == state[i+2][col] == state[i+3][col]:\n return 1 if state[i][col]==self.my_piece else -1\n\n # TODO: check \\ diagonal wins\n for col in range(2):\n for i in range(2):\n if state[i][col] != ' ' and state[i][col] == state[i+1][col+1] == state[i+2][col+2] == state[i+3][col+3]:\n return 1 if state[i][col]==self.my_piece else -1\n # TODO: check / diagonal wins\n for col in range(2):\n for i in range(2):\n if state[i][col+3] != ' ' and state[i][col+3] == state[i+1][col+2] == state[i+2][col+1] == state[i+3][col]:\n return 1 if state[i][col]==self.my_piece else -1\n # TODO: check 2x2 box wins\n for col in range(4):\n for i in range(4):\n if state[i][col] != ' ' and state[i][col] == state[i+1][col] == state[i][col+1] == state[i+1][col+1]:\n return 1 if state[i][col]==self.my_piece else -1\n \n return 0 # no winner yet","def game_value(self, state):\n # check horizontal wins\n for row in state:\n for i in range(2):\n if row[i] != ' ' and row[i] == row[i+1] == row[i+2] == row[i+3]:\n return 1 if row[i]==self.my_piece else -1\n\n # check vertical wins\n for col in range(5):\n for i in range(2):\n if state[i][col] != ' ' and state[i][col] == state[i+1][col] == state[i+2][col] == state[i+3][col]:\n return 1 if state[i][col]==self.my_piece else -1\n\n # check \\ diagonal wins\n for i in range(2):\n for j in range(2):\n if state[i][j]!= ' ' and state[i][j] == state[i+1][j+1] == state[i+2][j+2] == state[i+3][j+3]:\n return 1 if state[i][j]==self.my_piece else -1\n # check / diagonal wins\n for i in range(3,5):\n for j in range(2):\n if state[i][j]!= ' ' and state[i][j] == state[i-1][j+1] == state[i-2][j+2] == state[i-3][j+3]:\n return 1 if state[i][j]==self.my_piece else -1\n # check diamond wins\n for i in range(3):\n for j in range(1,4):\n if state[i+1][j] == ' ' and state[i][j]!= ' ' and state[i][j] == state[i+1][j-1] == state[i+1][j+1] == state[i+2][j]:\n return 1 if state[i][j]==self.my_piece else -1\n\n return 0 # no winner yet","def gameOfLife(self, board: List[List[int]]) -> None:\n # copy matrix\n copy_matrix = [[board[row][col] for col in range(len(board[0]))] for row in range(len(board))]\n \n # 8 possible directions\n directions = [(0,1), (0, -1), (1,0), (-1,0), (-1,-1), (1,1), (1,-1), (-1,1)]\n num_rows = len(board)\n num_cols = len(board[0])\n \n # matrix traversal\n for i in range(0, num_rows):\n for j in range(0, num_cols):\n # for each cell, explore all of its neighboring cells\n num_live_cells = 0\n for direction in directions:\n r = i + direction[0]\n c = j + direction[1]\n # make sure if it is a live cell \n if (r < num_rows and r >=0) and (c < num_cols and c>=0) and (copy_matrix[r][c]==1):\n # if it is live cell, increment live_cell_count\n num_live_cells +=1\n # if here: We now have estimate of surrounding live cells\n # start applying rules \n # Rule-1: Any live cell with fewer than 2 live neighbors die\n # Rule-2: Any live cell with 2/3 live neighbors live up\n # Rule-3: Any Live cell with > 3 live neighbors die\n # Rule-4: Any dead cell with ==3 live neighbors becomes alive\n if copy_matrix[i][j] == 1 and (num_live_cells > 3 or num_live_cells < 2):\n # Rule-1 and Rule-3: So the current cell dies...\n board[i][j] = 0\n if copy_matrix[i][j] == 0 and num_live_cells == 3:\n # Rule-4: Dead becomes alive\n board[i][j] = 1\n # Rule-2 is taken care by default.","def game_value(self, state):\r\n # check horizontal wins\r\n for row in state:\r\n for i in range(2):\r\n if row[i] != ' ' and row[i] == row[i+1] == row[i+2] == row[i+3]:\r\n return 1 if row[i] == self.my_piece else -1\r\n # check col wins\r\n for col in range(5):\r\n for i in range(2):\r\n if state[i][col] != ' ' and state[i][col] == state[i+1][col] == state[i+2][col] == state[i+3][col]:\r\n return 1 if state[i][col] == self.my_piece else -1\r\n #check diag up wins\r\n for x in range(2):\r\n for y in range(2):\r\n if state[x][y] != ' ' and state[x][y] == state[x+1][y+1] == state[x+2][y+2] == state[x+3][y+3]:\r\n return 1 if state[x][y] == self.my_piece else -1\r\n #check diag down wins\r\n for x in range(2):\r\n for y in range(3, 5):\r\n if state[x][y] != ' ' and state[x][y] == state[x+1][y-1] == state[x+2][y-2] == state[x+3][y-3]:\r\n return 1 if state[x][y] == self.my_piece else -1\r\n #check square box wins \r\n for x in range(4):\r\n for y in range(4):\r\n if state[x][y] != ' ' and state[x][y] == state[x+1][y] == state[x][y+1] == state[x+1][y+1]:\r\n return 1 if state[x][y] == self.my_piece else -1\r\n\r\n return 0 # no winner yet\r","def cycle(self):\n\n coordinates = self.get_random_coordinates()\n\n for coord in coordinates:\n if isinstance(self.cells[coord], (Jungle, Savannah, Desert)):\n self.cells[coord].feeding()\n\n for coord in coordinates:\n if isinstance(self.cells[coord], (Jungle, Savannah, Desert)):\n self.cells[coord].procreation()\n\n self.migration()\n\n for coord in coordinates:\n if isinstance(self.cells[coord], (Jungle, Savannah, Desert)):\n self.cells[coord].aging()\n\n for coord in coordinates:\n if isinstance(self.cells[coord], (Jungle, Savannah, Desert)):\n self.cells[coord].loss_of_weight()\n\n for coord in coordinates:\n if isinstance(self.cells[coord], (Jungle, Savannah, Desert)):\n self.cells[coord].death()\n\n self.animals_on_island()","def play_best_guess(self, game):\n\n\n # create a list of cells\n cells = [game.board[i][j]\n for i in xrange(game.rows)\n for j in xrange(game.cols)]\n\n first_cell = cells[0]\n game.reveal_cell(first_cell.row, first_cell.col)\n\n # draw updated board and pause for a second\n game.draw_board()\n if PAUSE == True:\n time.sleep(1)\n\n\n total_flagged = 0\n while not game.lost_game and not game.won_game:\n\n # remember if we've made a move in the while loop\n # so we know whether to make a random move later on\n made_move = False\n\n # look through all revealed cells for any with a number of neighboring mines.\n # if the cell has the same number of unrevealed neighbors as the cell's\n # number of neighboring mines, all the unrevealed neighbors must be mines.\n revealed_numbered_cells = [c for c in cells if c.revealed and (not c.flagged) and (c.neighbors > 0)]\n while revealed_numbered_cells:\n cell = revealed_numbered_cells.pop()\n # cell may have been marked flagged after revealed_numbered_cells was compiled\n if not cell.flagged:\n neighbor_cells = ms.Minesweeper.get_neighbors(cell.row, cell.col, game.board)\n flagged_neighbors = [n for n in neighbor_cells if n.flagged]\n number_remaining_mines = cell.neighbors - len(flagged_neighbors)\n unknown_neighbors = [n for n in neighbor_cells if not n.flagged and not n.revealed]\n if number_remaining_mines > 0 and len(unknown_neighbors) == number_remaining_mines:\n # flag every neighbor\n for c in unknown_neighbors:\n if total_flagged < game.mines:\n total_flagged += 1\n game.flag_cell(c.row, c.col)\n if (game.test_did_win()):\n game.game_over()\n game.draw_board()\n if PAUSE == True:\n time.sleep(1)\n made_move = True\n\n # we may have won with the flag above so test whether we're still playing\n # before further calculations\n if not game.lost_game and not game.won_game:\n # loop through all unrevealed, unflagged cells and see if we know it's safe to reveal\n for c in cells:\n if not c.revealed and not c.flagged and self.is_cell_safe(c, game.board):\n game.reveal_cell(c.row, c.col)\n if (game.test_did_win()):\n game.game_over()\n game.draw_board()\n if PAUSE == True:\n time.sleep(1)\n made_move = True\n\n # assume we've made our best guesses and now have to guess randomly\n # this will prevent us from looping forever if no obvious moves are available\n if not made_move:\n unrevealed = [c for c in cells if not c.revealed and not c.flagged]\n if len(unrevealed) > 0:\n cell = random.choice(unrevealed)\n game.reveal_cell(cell.row, cell.col)\n if (game.test_did_win()):\n game.game_over()\n game.draw_board()\n if PAUSE == True:\n time.sleep(3)","def evaluateBoardState(self, board):\n\n \"\"\"\n These are the variables and functions for board objects which may be helpful when creating your Agent.\n Look into board.py for more information/descriptions of each, or to look for any other definitions which may help you.\n\n Board Variables:\n board.width \n board.height\n board.last_move\n board.num_to_connect\n board.winning_zones\n board.score_array \n board.current_player_score\n\n Board Functions:\n get_cell_value(row, col)\n try_move(col)\n valid_move(row, col)\n valid_moves()\n terminal(self)\n legal_moves()\n next_state(turn)\n winner()\n \"\"\"\n if self.id == 1:\n opponent_id = 2\n else:\n opponent_id = 1\n\n maxvalue = 100000\n minvalue = -maxvalue\n winner = board.winner()\n if winner == self.id:\n return maxvalue\n elif winner == opponent_id:\n return minvalue\n size_y = board.height\n size_x = board.width\n map_ = []\n num_to_connect = board.num_to_connect\n total_points = 0\n\n multiply_reachable = 1\n multiply_oddeven = 1\n # basically this function is calculating all the possible win positions\n # more pieces in a possible win position will be counted with more weights\n # a win position with X pieces in it will be counted as X^2 points\n # initialise the zones maps\n for i in range(size_y):\n map_.append([])\n for j in range(size_x):\n map_[i].append([])\n\n # Fill in the horizontal win positions\n for i in range(size_y):\n for j in range(size_x - num_to_connect + 1):\n points = 0\n self_pieces_count = 0\n opponent_pieces_count = 0\n for k in range(num_to_connect):\n if board.board[i][j + k] == opponent_id:\n opponent_pieces_count += 1\n elif board.board[i][j + k] == self.id:\n points += len(board.winning_zones[j+k][i])\n if (self.id == 1 and i % 2 == 1) or (self.id == 2 and i%2 == 0):\n points *= multiply_oddeven\n self_pieces_count += 1\n if self_pieces_count == 3 and opponent_pieces_count == 0:\n if j - 1 >= 0 and board.board[i][j + 3] == 0 and board.board[i][j - 1] == 0 \\\n and board.try_move(j + 3) == i and board.try_move(j - 1) == i:\n return maxvalue\n elif j + 4 < size_y and board.board[i][j + 4] == 0 and board.board[i][j] == 0 \\\n and board.try_move(j + 4) == i and board.try_move(j) == i:\n return maxvalue\n else:\n for k in range(num_to_connect):\n if board.board[i][j + k] == 0 and board.try_move(j + k) == i:\n points *= multiply_reachable\n elif opponent_pieces_count == 3 and self_pieces_count == 0:\n if j - 1 >= 0 and board.board[i][j + 3] == 0 and board.board[i][j - 1] == 0 \\\n and board.try_move(j + 3) == i and board.try_move(j - 1) == i:\n return minvalue\n elif j + 4 < size_y and board.board[i][j + 4] == 0 and board.board[i][j] == 0 \\\n and board.try_move(j + 4) == i and board.try_move(j) == i:\n return minvalue\n # else:\n # for k in range(num_to_connect):\n # if board.board[i][j + k] == 0 and board.try_move(j + k) == i:\n # points *= -multiply_reachable\n if (opponent_pieces_count == 3 and self_pieces_count == 0) or opponent_pieces_count == 0:\n total_points += points\n\n # Fill in the vertical win positions\n for i in range(size_x):\n for j in range(size_y - num_to_connect + 1):\n points = 0\n self_pieces_count = 0\n for k in range(num_to_connect):\n if board.board[j + k][i] == opponent_id:\n opponent_pieces_count += 1\n elif board.board[j + k][i] == self.id:\n points += len(board.winning_zones[i][j+k])\n if (self.id == 1 and (j+k) % 2 == 1) or (self.id == 2 and (j+k)%2 == 0):\n points *= multiply_oddeven\n self_pieces_count += 1\n points *= multiply_reachable\n # if opponent_pieces_count == 3 and self_pieces_count == 0:\n # points *= -1\n if (opponent_pieces_count == 3 and self_pieces_count == 0) or opponent_pieces_count == 0:\n total_points += points\n\n # Fill in the forward diagonal win positions\n for i in range(size_y - num_to_connect + 1):\n for j in range(size_x - num_to_connect + 1):\n points = 0\n self_pieces_count = 0\n opponent_pieces_count = 0\n for k in range(num_to_connect):\n if board.board[i + k][j + k] == opponent_id:\n opponent_pieces_count += 1\n elif board.board[i + k][j + k] == self.id:\n points += len(board.winning_zones[j+k][i+k])\n if (self.id == 1 and (i+k) % 2 == 1) or (self.id == 2 and (i+k)%2 == 0):\n points *= multiply_oddeven\n self_pieces_count += 1\n if self_pieces_count == 3 and opponent_pieces_count == 0:\n if i - 1 >= 0 and j - 1 >= 0 and board.board[i + 3][j + 3] == 0 and board.board[i - 1][j - 1] == 0 \\\n and board.try_move(j + 3) == i + 3 and board.try_move(j - 1) == i - 1:\n return maxvalue\n elif i + 4 < size_y and j + 4 < size_x and board.board[i + 4][j + 4] == 0 and board.board[i][j] == 0 \\\n and board.try_move(j + 4) == i + 4 and board.try_move(j) == i:\n return maxvalue\n else:\n for k in range(num_to_connect):\n if board.board[i + k][j + k] == 0 and board.try_move(j + k) == i + k:\n points *= multiply_reachable\n elif opponent_pieces_count == 3 and self_pieces_count == 0:\n if i - 1 >= 0 and j - 1 >= 0 and board.board[i + 3][j + 3] == 0 and board.board[i - 1][j - 1] == 0 \\\n and board.try_move(j + 3) == i + 3 and board.try_move(j - 1) == i - 1:\n return minvalue\n elif i + 4 < size_y and j + 4 < size_x and board.board[i + 4][j + 4] == 0 and board.board[i][j] == 0 \\\n and board.try_move(j + 4) == i + 4 and board.try_move(j) == i:\n return minvalue\n # else:\n # for k in range(num_to_connect):\n # if board.board[i + k][j + k] == 0 and board.try_move(j + k) == i + k:\n # points *= -multiply_reachable\n if (opponent_pieces_count == 3 and self_pieces_count == 0) or opponent_pieces_count == 0:\n total_points += points\n\n # Fill in the backward diagonal win positions\n for i in range(size_y - num_to_connect + 1):\n for j in range(size_x - 1, num_to_connect - 1 - 1, -1):\n points = 0\n self_pieces_count = 0\n opponent_pieces_count = 0\n for k in range(num_to_connect):\n if board.board[i + k][j - k] == opponent_id:\n opponent_pieces_count += 1\n elif board.board[i + k][j - k] == self.id:\n points += len(board.winning_zones[j-k][i+k])\n if (self.id == 1 and (i+k) % 2 == 1) or (self.id == 2 and (i+k)%2 == 0):\n points *= multiply_oddeven\n self_pieces_count += 1\n if self_pieces_count == 3 and self_pieces_count == 0:\n if board.board[i + 3][j - 3] == 0 and board.board[i - 1][j + 1] == 0 \\\n and board.try_move(j - 3) == i + 3 and board.try_move(j + 1) == i - 1:\n return maxvalue\n elif i + 4 < size_y and j - 4 >= 0 and board.board[i + 4][j - 4] == 0 and board.board[i][j] == 0 \\\n and board.try_move(j - 4) == i + 4 and board.try_move(j) == i:\n return maxvalue\n else:\n for k in range(num_to_connect):\n if board.board[i + k][j - k] == 0 and board.try_move(j - k) == i + k:\n points *= multiply_reachable\n\n elif opponent_pieces_count == 3 and self_pieces_count == 0:\n if board.board[i + 3][j - 3] == 0 and board.board[i - 1][j + 1] == 0 \\\n and board.try_move(j - 3) == i + 3 and board.try_move(j + 1) == i - 1:\n return minvalue\n elif i + 4 < size_y and j - 4 >= 0 and board.board[i + 4][j - 4] == 0 and board.board[i][j] == 0 \\\n and board.try_move(j - 4) == i + 4 and board.try_move(j) == i:\n return minvalue\n # else:\n # for k in range(num_to_connect):\n # if board.board[i + k][j - k] == 0 and board.try_move(j - k) == i + k:\n # points *= -multiply_reachable\n if (opponent_pieces_count == 3 and self_pieces_count == 0) or opponent_pieces_count == 0:\n total_points += points\n return total_points","def game_over(self) -> bool:\n for row in range(9):\n for col in range(9):\n if self._grid_sol[row][col] != self.get_cell(row, col):\n return False\n return True","def get_all_game_cells(self):\n return GameCell.objects.filter(game=self)","def gameOfLife(self, board):\n \n # Neighbours array for 8 neighboring cells of a given cell\n neighbors = [(1,0), (1,-1), (0,-1), (-1,-1), (-1,0), (-1,1), (0,1), (1,1)]\n \n rows = len(board)\n cols = len(board[0])\n \n # Iterate through the board by each cell\n for row in range(rows):\n for col in range(cols):\n \n # For each cell counting number of live neighbors\n live_neighbors = 0\n for neighbor in neighbors:\n \n # row and column of neighboring cell\n r = (row + neighbor[0])\n c = (col + neighbor[1])\n \n # Checking validity of neighboring cell and if it was originally a live cell\n if(r < rows and r >= 0) and (c < cols and c >= 0) and abs(board[r][c]) == 1:\n \n live_neighbors += 1\n \n # Rule 1 or Rule 3\n if board[row][col] == 1 and (live_neighbors < 2 or live_neighbors > 3):\n \n board[row][col] = -1 # -1 meaning cell is now dead but was originally live\n \n # Rule 4\n if board[row][col] == 0 and live_neighbors == 3:\n board[row][col] = 2 #2 meaning cell is now live but was originally dead\n # Get final representation for updated board \n for row in range(rows):\n for col in range(cols):\n \n if board[row][col] > 0:\n board[row][col] = 1\n \n else:\n board[row][col] = 0","def __get_cell_state(self, y, x):\n\t\tif 0 <= y <= self.__height - 1:\n\t\t\tif 0 <= x <= self.__width - 1:\n\t\t\t\treturn self.__board[y][x]\n\t\treturn 0","def game_state(matrix):\n\n \"\"\"\n # To set winning tile\n for i in range(len(matrix)):\n for j in range(len(matrix[0])):\n if matrix[i][j] == 2048:\n # return 'win'\n # return 'not over'\n \"\"\"\n for i in range(len(matrix)-1):\n # intentionally reduced to check the row on the right and below\n # more elegant to use exceptions but most likely this will be their solution\n for j in range(len(matrix[0])-1):\n if matrix[i][j] == matrix[i+1][j] or matrix[i][j+1] == matrix[i][j]:\n return 'not over'\n for i in range(len(matrix)): # check for any zero entries\n for j in range(len(matrix[0])):\n if matrix[i][j] == 0:\n return 'not over'\n for k in range(len(matrix)-1): # to check the left/right entries on the last row\n if matrix[len(matrix)-1][k] == matrix[len(matrix)-1][k+1]:\n return 'not over'\n for j in range(len(matrix)-1): # check up/down entries on last column\n if matrix[j][len(matrix)-1] == matrix[j+1][len(matrix)-1]:\n return 'not over'\n return 'lose'","def has_cells(self):\n return len(self._cells) > 0","def updateCells(cell_positions):\n # Build a set of canditates for live cells at the next generation, instead of looking through the whole grid\n # These will be dead neighbours of living cells\n possible_future_cells = set()\n # Make sets of cells to add and remove at the end of the check\n cells_remove = set()\n cells_add = set()\n for cell in cell_positions:\n # Get adjacent squares\n neighbours_dict = cellNeighbours(cell)\n number_live_neighbours = 0\n # Check which of these corresponds to another living cell\n for square in neighbours_dict.values():\n if square in cell_positions:\n number_live_neighbours+=1\n else:\n possible_future_cells.add(square)\n\n # Any live cell with fewer than two live neighbours dies, as if caused by under-population\n if number_live_neighbours<2:\n cells_remove.add(cell)\n # Any live cell with two or three live neighbours lives on to the next generation\n # do nothing\n # Any live cell with more than three live neighbours dies, as if by overcrowding\n elif number_live_neighbours>3:\n cells_remove.add(cell)\n # Any dead cell with exactly three live neighbours becomes a live cell, as if by reproduction\n for cell_candidate in possible_future_cells:\n cell_candidate_neighbours = cellNeighbours(cell_candidate).values()\n # Count number of live neighbours\n count = 0\n for square in cell_candidate_neighbours:\n if square in cell_positions:\n count+=1\n if count == 3:\n cells_add.add(cell_candidate)\n # Update cell_positions by removing dead cells and adding new-born cells\n for cell in cells_add:\n cell_positions.add(cell)\n for cell in cells_remove:\n cell_positions.remove(cell)\n # Return the update live cell list\n return cell_positions","def getNeighbors(cell, all_living_cells, test=False, test_color=8):\n neighbors = []\n NeighborCellGrid = [ # all possible neighbor positions\n [cell.x - 1, cell.y - 1], # top left\n [cell.x, cell.y - 1], # top\n [cell.x + 1, cell.y - 1], # top right\n [cell.x - 1, cell.y], # left\n [cell.x + 1, cell.y], # right\n [cell.x - 1, cell.y + 1], # bottom left\n [cell.x, cell.y + 1], # bottom\n [cell.x + 1, cell.y + 1] # bottom right\n ]\n count = 0\n for i in all_living_cells:\n count+=1\n if i.id != cell.id and i.alive == True: # not self and pixel is alive\n if [i.x, i.y] in NeighborCellGrid: # next to\n neighbors.append(i)\n if test:\n for i in NeighborCellGrid:\n g = simCell(i[0], i[1], color=test_color)\n test_cells.append(g)\n return neighbors","def new_game(self):\n self.cells = [] # Array of cells\n self.frame_count = 0\n self.database = []\n self.timer = [Consts[\"MAX_TIME\"], Consts[\"MAX_TIME\"]]\n self.result = None\n # Define the players first\n self.cells.append(Cell(0, [Consts[\"WORLD_X\"] / 4, Consts[\"WORLD_Y\"] / 2], [0, 0], Consts[\"DEFAULT_RADIUS\"]))\n self.cells.append(Cell(1, [Consts[\"WORLD_X\"] / 4 * 3, Consts[\"WORLD_Y\"] / 2], [0, 0], Consts[\"DEFAULT_RADIUS\"]))\n # Generate a bunch of random cells\n for i in range(Consts[\"CELLS_COUNT\"]):\n if i < 4:\n rad = 1.5 + (random.random() * 1.5) # Small cells\n elif i < 10:\n rad = 10 + (random.random() * 4) # Big cells\n else:\n rad = 2 + (random.random() * 9) # Everything else\n x = Consts[\"WORLD_X\"] * random.random()\n y = Consts[\"WORLD_Y\"] * random.random()\n cell = Cell(i + 2, [x, y], [(random.random() - 0.5) * 2, (random.random() - 0.5) * 2], rad)\n safe_dist = Consts[\"SAFE_DIST\"] + rad\n while min(map(cell.distance_from, self.cells[:2])) < safe_dist:\n cell.pos = [\n Consts[\"WORLD_X\"] * random.random(),\n Consts[\"WORLD_Y\"] * random.random()\n ]\n self.cells.append(cell)","def draw_occupied_cells(self):\n reds = [cell for cell in self.game.get_cells() if cell.player == 1]\n blacks = [cell for cell in self.game.get_cells() if cell.player == 2]\n nx.draw_networkx_nodes(self.G, pos=self.positions, nodelist=reds,\n edgecolors='black', node_color='red', linewidths=2)\n nx.draw_networkx_nodes(self.G, pos=self.positions, nodelist=blacks,\n edgecolors='black', node_color='black', linewidths=2)","def winGame(sub_state):\n for i in range(sub_state.shape[0] - 4):\n for j in range(sub_state.shape[1] - 4):\n\n horizontal = sub_state[i][j: j+5]\n if (horizontal == 1).all():\n return True\n\n vertical = [sub_state[i+k, j] for k in range(5)]\n if (np.array(vertical) == 1).all():\n return True\n\n diagonal = [sub_state[(i+k, j+k)] for k in range(5)]\n if (np.array(diagonal) == 1).all():\n return True\n\n return False","def _create_cells(self):\n\t\tcellId=0\n\t\t# Iterate over all dictionaries\n\t\tfor muscle,muscAfferentDelay in self._infoMuscles:\n\t\t\tfor cellInfo in self._infoCommonCellsInMuscles:\n\t\t\t\tcellClass = cellInfo[0]\n\t\t\t\tcellName = cellInfo[1]\n\t\t\t\tcellNumber = cellInfo[2]\n\t\t\t\tif len(cellInfo)>=4: neuronParam = cellInfo[3]\n\t\t\t\telse: neuronParam = None\n\t\t\t\tcellId = self._create_cell_population(cellId,muscle,muscAfferentDelay,cellClass,cellName,cellNumber,neuronParam)\n\t\t# Add special cells\n\t\tfor cellInfo in self._infoSpecialCells:\n\t\t\tgroupOrMuscle = cellInfo[0]\n\t\t\tcellClass = cellInfo[1]\n\t\t\tcellName = cellInfo[2]\n\t\t\tcellNumber = cellInfo[3]\n\t\t\tif len(cellInfo)>=5: neuronParam = cellInfo[4]\n\t\t\telse: neuronParam = None\n\t\t\tmuscAfferentDelay = None\n\t\t\tcellId = self._create_cell_population(cellId,groupOrMuscle,muscAfferentDelay,cellClass,cellName,cellNumber,neuronParam)\n\n\t\tself._motoneuronsNames = self._intMotoneuronsNames+self._realMotoneuronsNames\n\t\tself._afferentsNames = self._primaryAfferentsNames+self._secondaryAfferentsNames","def test_toggle_cell_in_board(self):\n self.gameBoard.getGridItem(50, 50).toggle_living()\n self.assertEqual(self.gameBoard.getGridItem(50,50).is_living(), True)","def checkwin(self):\n w = self.getWidth()\n h = self.getHeight()\n numOccupiedCell = 0 # counter for the number of occupied cells (use to detect a terminal condition of the game)\n for r in range(h):\n for c in range(w):\n if self.cell[c][r] == EMPTY:\n continue # this cell can't be part of winning segment\n # if we reach this point, the cell is occupied by a player stone\n numOccupiedCell = numOccupiedCell+1\n for dr,dc in [(1,0),(0,1),(1,1),(-1,1)]: # direction of search\n for i in range(NWIN):\n # test if there exists a segment of NWIN uniformly coloured cells\n if not(r+i*dr>=0) or not(r+i*dr<h) or not(c+i*dc<w) or not(self.cell[c+i*dc][r+i*dr] == self.cell[c][r]):\n break # segment broken\n else:\n # Python remark: notice that the else is attached to the for loop \"for i...\"\n # This block is executed if and only if 'i' arrives at the end of its range \n return self.cell[c][r] , True # found a winning segment \n return EMPTY, numOccupiedCell==w*h","def play_randomly(self, game):\n\n # create a stack of unrevealed cells\n unrevealed = []\n\n for i in xrange(game.rows):\n for j in xrange(game.cols):\n unrevealed.append(game.board[i][j])\n # we will pop the cells from the stack, so randomize their order first\n random.shuffle(unrevealed)\n\n # while the game is being played, choose a random unrevealed cell to reveal next\n while not game.lost_game and not game.won_game:\n\n cell = unrevealed.pop()\n\n # before we click the cell, see if only mines remain\n # if so, flag this cell, otherwise reveal it.\n if len(unrevealed) < game.mines:\n game.flag_cell(cell.row, cell.col)\n print \"Flagging\", cell\n\n # cell may have been previously revealed as a neighbor\n # if not, reveal it now, otherwise discard the cell and continue\n elif not cell.revealed:\n game.reveal_cell(cell.row, cell.col)\n print \"Revealing\", cell\n # update the stack to only contain non-revealed cells\n # TODO: make this more efficient by not modifying the list in place\n unrevealed = []\n for i in xrange(game.rows):\n for j in xrange(game.cols):\n if not game.board[i][j].revealed and not game.board[i][j].flagged:\n unrevealed.append(game.board[i][j])\n random.shuffle(unrevealed)\n\n #check to see if there's any corners that can be flagged as bombs\n check_corners(game, unrevealed)\n\n # draw updated board and pause for a second\n game.draw_board()\n if PAUSE == True:\n time.sleep(1)","def _checkCells(self):\r\n if(self.startCell.isEmpty()):\r\n raise IllegalMoveException(\"No pawn in start cell\")\r\n if(self.endCell.isOccupied()):\r\n raise IllegalMoveException(\"Targeted cell is already occupied\")\r\n return True","def life_step(state):\n\t# For every cell each live cell in any of the 8 neighbouring cells contributes 1 to the sum\n\t# Rolling matricies is periodic so this implements periodic boundary conditions\n\tnumberOfNeigbours = sum(np.roll(np.roll(state, i, axis=0), j, axis=1)\n\t\t\t\t\t\t for i in (-1,0,1) for j in (-1,0,1) if (i != 0 or j != 0))\n\n\t# Any live cell with fewer than two live neighbours dies, as if caused by under-population\n\tstate = np.where(numberOfNeigbours < 2, 0, state)\n\t# Any live cell with more than three live neighbours dies, as if by over-population\n\tstate = np.where(numberOfNeigbours > 3, 0, state)\n\t# Any dead cell with exactly three live neighbours becomes a live cell, as if by reproduction.\n\tstate = np.where(numberOfNeigbours == 3, 1, state)\n\n\treturn state","def simulate(screen, clock):\n old_cells = populate_cells(MAX_X, MAX_Y)\n new_cells = {}\n\n running = True\n while running:\n\n screen.fill((20, 20, 20))\n\n for event in pygame.event.get():\n if event.type == pygame.QUIT:\n running = False\n break\n elif event.type == pygame.KEYDOWN:\n if event.key == pygame.K_ESCAPE:\n running = False\n break\n\n for y in range(MAX_Y):\n for x in range(MAX_X):\n if old_cells[x, y]:\n pygame.draw.rect(screen, CELL_COLOR,\n (x * CELL_WIDTH, y * CELL_HEIGHT,\n CELL_WIDTH, CELL_HEIGHT))\n dead_or_alive(old_cells, x, y, new_cells)\n\n old_cells = new_cells\n new_cells = {}\n clock.tick(200)\n pygame.display.update()\n\n pygame.quit()","def setNeighbors(self):\n for cellIndex in range(len(self.cells)):\n cell = self.cells[cellIndex]\n\n #Checks the 8 cells around the living one. \n for neighborsX in range(cell.x - 1, cell.x + 2):\n for neighborsY in range(cell.y - 1, cell.y + 2):\n\n #If the position is outside the world, loop around.\n neighborsX = neighborsX % self.screen.worldSize\n neighborsY = neighborsY % self.screen.worldSize\n\n #Skipping itself. Becouse we do not want to calculate itself as a neighbor\n if(neighborsX == cell.x and neighborsY == cell.y):\n continue\n else:\n #Checks if a cell exist at neighborsX, neighborsY\n cellToCheck = self.getCellFromPosition(neighborsX, neighborsY)\n if(cellToCheck != False):\n #Add one to the neighbor var if there already exist and cell for the given position.\n cellToCheck.numOfNeighbor += 1\n else:\n #Creates a new cell if it do not exist any.\n newCell = Cell(self.screen, neighborsX, neighborsY, True)\n newCell.numOfNeighbor += 1\n self.cells.append(newCell)","def gameOfLife(self, board: List[List[int]]) -> None:\n if not board or len(board)==0:\n return \n\n rows = len(board)\n cols = len(board[0])\n #lives = 0\n \n\n for i in range(rows):\n for j in range(cols):\n lives = self.n_neighbors(board,i,j)\n \n # Rule 1 and Rule 3\n if board[i][j]==1 and (lives <2 or lives >3):\n board[i][j]= 2 # -1 signifies the cell is now dead but originally was live.\n if board[i][j]== 0 and lives ==3:\n board[i][j]=3 # signifies the cell is now live but was originally dead.\n\n for i in range(rows):\n for j in range(cols):\n board[i][j] = board[i][j]%2\n return board","def _generate_cells(self) -> None:\n for i in range(15):\n for j in range(15):\n c = Cell(x=i, y=j)\n c.answer = self.puzzle.solution[j*self.width+i]\n self.cells[(j, i)] = c # row, col","def check_grid_full(self):\n for row in self.game_state:\n for e in row:\n if e is None:\n return False\n return True","def _simulate_all_cells(self):\n for ID in tqdm(self.condition_dict, desc='Simulating cells'):\n for n in range(len(self.condition_dict[ID])):\n cond_dict = self.condition_dict[ID][n]\n g, tc, rsh_mult, rs_mult, Io_mult, Il_mult, nnsvth_mult = cond_dict['E'], cond_dict['Tc'], cond_dict[\n 'Rsh_mult'], cond_dict['Rs_mult'], cond_dict['Io_mult'], cond_dict['Il_mult'], cond_dict['nnsvth_mult']\n # calculate the 5 parameters for each set of cell conditions\n\n # Eventually, replace this with derived 5-parameters\n iph, io, rs, rsh, nnsvth = pvlib.pvsystem.calcparams_cec(effective_irradiance=g, temp_cell=tc,\n alpha_sc=self.cell_parameters['alpha_sc'],\n a_ref=self.cell_parameters['a_ref'],\n I_L_ref=self.cell_parameters['I_L_ref'],\n I_o_ref=self.cell_parameters['I_o_ref'],\n R_sh_ref=self.cell_parameters['R_sh_ref'],\n R_s=self.cell_parameters['R_s'],\n Adjust=self.cell_parameters['Adjust'])\n rs, rsh, io, iph, nnsvth = rs * rs_mult, rsh * \\\n rsh_mult, io * Io_mult, iph * Il_mult, nnsvth * nnsvth_mult\n\n # calculate cell IV curves by condition, rather than by cell index\n voc_est = pvlib.singlediode.estimate_voc(iph, io, nnsvth)\n v = voltage_pts(self.num_points_in_IV, voc_est,\n self.module_parameters['breakdown_voltage'])\n i = pvlib.singlediode.bishop88_i_from_v(v, iph, io, rs, rsh, nnsvth,\n breakdown_factor=self.module_parameters['breakdown_factor'],\n breakdown_voltage=self.module_parameters[\n 'breakdown_voltage'],\n breakdown_exp=self.module_parameters['breakdown_exp'])\n\n # @dev: Uncomment if debugging pvlib bishop88 simulation results\n # plt.plot(v,i)\n # plt.xlim(-5,v[-1])\n # plt.ylim(0,iph+1)\n # plt.title(f\"{ID}: {n} :: {rs},\"\n # f\"{rsh}, {io}, {iph}, {nnsvth}\")\n # plt.show()\n\n self.condition_dict[ID][n]['V'] = v\n self.condition_dict[ID][n]['I'] = i\n self.condition_dict[ID][n]['E'] = g\n self.condition_dict[ID][n]['Tc'] = tc\n return","def play_round_Conway_Cell(self):\n for x in self.board:\n for f in x:\n f.live_neighbors = 0\n\n for i in range(1, self.cols - 1):\n for j in range(1, self.rows - 1):\n status = self.board[i][j].status\n assert type(status)==int \n\n for m in range(i - 1, i + 2):\n for n in range(j - 1, j + 2):\n self.board[m][n].live_neighbors += status\n self.board[i][j].live_neighbors -= status","def update_cells(self):\n mineboard = self.mineboard\n gameboard = mineboard.gameboard\n for change in mineboard.changes:\n i, j = change[0], change[1]\n text_val = gameboard[i][j]\n\n if text_val == 'M':\n self.canvas.delete(self.cells[i][j])\n self.cells[i][j] = self.canvas.create_image(\n 2+j*CELLWIDTH, 2+i*CELLWIDTH, image=EXPLODED, anchor='nw')\n self.reveal_mines(i, j)\n\n elif text_val == 'F':\n self.canvas.delete(self.cells[i][j])\n self.cells[i][j] = self.canvas.create_image(\n 2+j*CELLWIDTH, 2+i*CELLWIDTH, image=FLAG, anchor='nw')\n\n elif text_val == ' ':\n self.canvas.delete(self.cells[i][j])\n self.cells[i][j] = self.canvas.create_rectangle(\n 2+j*CELLWIDTH, 2+i*CELLWIDTH, (j+1)*CELLWIDTH, (i+1)*CELLWIDTH, fill=DEFAULT_COLOR, outline=\"\")\n\n elif text_val in ['0', '1', '2', '3', '4', '5', '6', '7', '8']:\n self.canvas.itemconfig(\n self.cells[i][j], fill=COLORS[int(text_val)])\n if text_val != '0':\n # offset here is by 12 pixels\n self.canvas.create_text(\n 2+j*CELLWIDTH+(CELLWIDTH-1)//2, 2+i*CELLWIDTH+(CELLWIDTH-1)//2, anchor='center', text=f\"{text_val}\")\n\n mineboard.changes = [] # removes previous changes\n if mineboard.gamestate is not None:\n # if the game has ended displays game end message and buttons\n self.win_lose_lbl.grid(row=3, column=0, columnspan=4)\n self.win_lose_msg.set(\n f\"You {self.mineboard.gamestate}! Play again?\")\n self.same_again_bttn.grid(row=4, column=0, columnspan=2)\n self.play_again_bttn.grid(row=4, column=2, columnspan=2)","def make_move(grid, n_columns, n_rows):\r\n # Generate the game grid to be manipulated\r\n new_grid = [[0] * (n_columns + 1) for i in range(n_rows + 1)]\r\n\r\n\r\n for i in range(n_rows):\r\n for j in range(n_columns):\r\n upper_left = grid[i-1][j-1] # neighbor to upper left of cell of interest\r\n upper = grid[i-1][j] # neighbor above cell of interest\r\n upper_right = grid[i-1][j+1] # neighbor to upper right of cell of interest\r\n left = grid[i][j-1] # neighbor to left of cell of interest\r\n right = grid[i][j+1] # neighbor to right of cell of interest\r\n bot_left = grid[i+1][j-1] # neighbor to bottom left cell of interest\r\n bot = grid[i+1][j] # neighbor below cell of interest\r\n bot_right = grid[i+1][j+1] # neighbor to bottom right of cell of interest\r\n\r\n # sum of the state of all neighbors\r\n on_neighbors = upper_left + upper + upper_right + left + right + bot_left + bot + bot_right\r\n\r\n # Any ON cell with fewer than two ON neighbors turns OFF\r\n if grid[i][j] == 1 and on_neighbors < 2:\r\n new_grid[i][j] = 0\r\n\r\n # Any ON cell with two or three ON neighbours stays ON\r\n elif grid[i][j] == 1 and (on_neighbors == 2 or on_neighbors == 3):\r\n new_grid[i][j] = 1\r\n\r\n # Any ON cell with more than three ON neighbors turns OFF\r\n elif grid[i][j] == 1 and on_neighbors > 3:\r\n new_grid[i][j] = 0\r\n\r\n # Any OFF cell with three ON neighbors turns ON\r\n elif grid[i][j] == 0 and on_neighbors == 3:\r\n new_grid[i][j] = 1\r\n\r\n return new_grid #manipulated game grid\r","def _should_cell_live(self, cell: Cell) -> bool:\n living_neighbours_count = self._count_living_neighbors(cell)\n # Any live cell with two or three live neighbours survives\n if cell.is_alive and living_neighbours_count in [2, 3]:\n return True\n # Any dead cell with three live neighbours becomes a live cell\n if not cell.is_alive and living_neighbours_count == 3:\n return True\n # All other live cells die in the next generation. Similarly, all other dead cells stay dead\n return False","def evaluate(self, state):\n\t\ttranspose = state.board.transpose()\t\t# columns in state.board = rows in transpose\n\t\tcount = []\n\t\topponentcount = []\n\t\tfor row, column in zip(state.board, transpose):\n\t\t\trowcounter = collections.Counter(row)\n\t\t\tcolumncounter = collections.Counter(column)\n\t\t\tcount.append(rowcounter.get(state.current_player, 0))\n\t\t\tcount.append(columncounter.get(state.current_player, 0))\n\t\t\topponentcount.append(rowcounter.get(state.current_player * - 1, 0))\n\t\t\topponentcount.append(columncounter.get(state.current_player * -1 , 0))\n\n\t\tY = state.board[:, ::-1]\n\t\tdiagonals = [np.diagonal(state.board), np.diagonal(Y)]\n\t\tmain_diagonal_count = collections.Counter(diagonals[0])\n\t\tsecond_diagonal_count = collections.Counter(diagonals[1])\n\t\tcount.append(main_diagonal_count.get(state.current_player, 0))\n\t\tcount.append(second_diagonal_count.get(state.current_player, 0))\n\t\topponentcount.append(main_diagonal_count.get(state.current_player * - 1, 0))\n\t\topponentcount.append(second_diagonal_count.get(state.current_player * -1, 0))\n\n\t\t# max(count): maximum number of player's tiles in a row, column, or a diagonal (the highest value is 5)\n\t\t# max(opponentcount): maximum number of opponent's tiles in a row, column, or a diagonal (the highest value is 5)\n\t\tscoremax = 5 ** max(count)\n\t\tscoremin = 5 ** max(opponentcount)\n\n\t\treturn scoremax - scoremin","def gameOfLife(self, board: List[List[int]]) -> None:\n m = len(board)\n if m==0:\n return board\n n = len(board[0])\n if n==0:\n return board\n def valid(a,b):\n if 0<=a<m and 0<=b<n:\n return True\n mat = [row[:] for row in board] #original copy of the board\n directions = [(0,-1),(-1,-1),(-1,0),(-1,1),(0,1),(1,1),(1,0),(1,-1)]\n for i in range(m):\n for j in range(n):\n #count how many live=1 or dead=0 cells surrounding cell (i,j)\n cnt_live=0\n for direc in directions:\n if valid(i+direc[0],j+direc[1]):\n if mat[i+direc[0]][j+direc[1]]==1:\n cnt_live+=1\n if mat[i][j]==1 and cnt_live<2 or mat[i][j]==1 and cnt_live>3:\n board[i][j]=0\n elif mat[i][j]==1 and 2<=cnt_live<=3 or mat[i][j]==0 and cnt_live==3:\n board[i][j]=1","def apply_move(self, move, state):\n x, y , heading, grid_data = state\n map_data = [row[:] for row in grid_data]\n if move == self.MOVE_FORWARD:\n # get coordinates for next cell\n if heading == self.UP:\n next_y = y - 1\n next_x = x\n elif heading == self.DOWN:\n next_y = y + 1\n next_x = x\n elif heading == self.LEFT:\n next_y = y\n next_x = x - 1\n else:\n next_y = y\n next_x = x + 1\n\n # handle special tile types\n if map_data[next_y][next_x] == self.ICE_SYMBOL:\n # handle ice tile - slide until first non-ice tile or blocked\n if heading == self.UP:\n for i in range(next_y, -1, -1):\n if map_data[i][next_x] != self.ICE_SYMBOL:\n if map_data[i][next_x] == self.WATER_SYMBOL:\n # slide into water - game over\n return self.GAME_OVER\n elif self.cell_is_blocked(i, next_x, map_data):\n # if blocked, stop on last ice cell\n next_y = i + 1\n break\n else:\n next_y = i\n break\n elif heading == self.DOWN:\n for i in range(next_y, self.y_size):\n if map_data[i][next_x] != self.ICE_SYMBOL:\n if map_data[i][next_x] == self.WATER_SYMBOL:\n # slide into water - game over\n return self.GAME_OVER\n elif self.cell_is_blocked(i, next_x, map_data):\n # if blocked, stop on last ice cell\n next_y = i - 1\n break\n else:\n next_y = i\n break\n elif heading == self.LEFT:\n for i in range(next_x, -1, -1):\n if map_data[next_y][i] != self.ICE_SYMBOL:\n if map_data[next_y][i] == self.WATER_SYMBOL:\n # slide into water - game over\n return self.GAME_OVER\n elif self.cell_is_blocked(next_y, i, map_data):\n # if blocked, stop on last ice cell\n next_x = i + 1\n break\n else:\n next_x = i\n break\n else:\n for i in range(next_x, self.x_size):\n if map_data[next_y][i] != self.ICE_SYMBOL:\n if map_data[next_y][i] == self.WATER_SYMBOL:\n # slide into water - game over\n return self.GAME_OVER\n elif self.cell_is_blocked(next_y, i, map_data):\n # if blocked, stop on last ice cell\n next_x = i - 1\n break\n else:\n next_x = i\n break\n if map_data[next_y][next_x] == self.TELEPORT_SYMBOL:\n # handle teleport - find the other teleporter\n tpy, tpx = (None, None)\n for i in range(self.y_size):\n for j in range(self.x_size):\n if map_data[i][j] == self.TELEPORT_SYMBOL and (i != next_y or j != next_x):\n tpy, tpx = (i, j)\n break\n if tpy is not None:\n break\n if tpy is None:\n raise Exception(\"LaserTank Map Error: Unmatched teleport symbol\")\n next_y, next_x = (tpy, tpx)\n else:\n # if not ice or teleport, perform collision check\n if self.cell_is_blocked(next_y, next_x, map_data):\n return self.COLLISION\n\n # check for game over conditions\n if self.cell_is_game_over(next_y, next_x, map_data):\n return self.GAME_OVER\n\n # no collision and no game over - update player position\n y = next_y\n x = next_x\n return (x, y, heading, map_data)\n\n elif move == self.TURN_LEFT:\n # no collision or game over possible\n if heading == self.UP:\n heading = self.LEFT\n elif heading == self.DOWN:\n heading = self.RIGHT\n elif heading == self.LEFT:\n heading = self.DOWN\n else:\n heading = self.UP\n return (x, y, heading, map_data)\n\n elif move == self.TURN_RIGHT:\n # no collision or game over possible\n if heading == self.UP:\n heading = self.RIGHT\n elif heading == self.DOWN:\n heading = self.LEFT\n elif heading == self.LEFT:\n heading = self.UP\n else:\n heading = self.DOWN\n return (x, y, heading, map_data)\n\n elif move == self.SHOOT_LASER:\n # set laser direction\n if heading == self.UP:\n laserheading = self.UP\n dy, dx = (-1, 0)\n elif heading == self.DOWN:\n laserheading = self.DOWN\n dy, dx = (1, 0)\n elif heading == self.LEFT:\n laserheading = self.LEFT\n dy, dx = (0, -1)\n else:\n laserheading = self.RIGHT\n dy, dx = (0, 1)\n\n # loop until laser blocking object reached\n ly, lx = (y, x)\n while True:\n ly += dy\n lx += dx\n\n # handle boundary and immovable obstacles\n if ly < 0 or ly >= self.y_size or \\\n lx < 0 or lx >= self.x_size or \\\n map_data[ly][lx] == self.OBSTACLE_SYMBOL:\n # laser stopped without effect\n return self.COLLISION\n\n # handle movable objects\n elif self.cell_is_laser_movable(ly, lx, laserheading, map_data):\n # check if tile can be moved without collision\n if self.cell_is_blocked(ly + dy, lx + dx, map_data) or \\\n map_data[ly + dy][lx + dx] == self.ICE_SYMBOL or \\\n map_data[ly + dy][lx + dx] == self.TELEPORT_SYMBOL or \\\n map_data[ly + dy][lx + dx] == self.FLAG_SYMBOL or \\\n (ly + dy == y and lx + dx == x):\n # tile cannot be moved\n return self.COLLISION\n else:\n old_symbol = map_data[ly][lx]\n map_data[ly][lx] = self.LAND_SYMBOL\n if map_data[ly + dy][lx + dx] == self.WATER_SYMBOL:\n # if new bridge position is water, convert to land tile\n if old_symbol == self.BRIDGE_SYMBOL:\n map_data[ly + dy][lx + dx] = self.LAND_SYMBOL\n # otherwise, do not replace the old symbol\n else:\n # otherwise, move the tile forward\n map_data[ly + dy][lx + dx] = old_symbol\n break\n\n # handle bricks\n elif map_data[ly][lx] == self.BRICK_SYMBOL:\n # remove brick, replace with land\n map_data[ly][lx] = self.LAND_SYMBOL\n break\n\n # handle facing anti-tanks\n elif (map_data[ly][lx] == self.ANTI_TANK_UP_SYMBOL and laserheading == self.DOWN) or \\\n (map_data[ly][lx] == self.ANTI_TANK_DOWN_SYMBOL and laserheading == self.UP) or \\\n (map_data[ly][lx] == self.ANTI_TANK_LEFT_SYMBOL and laserheading == self.RIGHT) or \\\n (map_data[ly][lx] == self.ANTI_TANK_RIGHT_SYMBOL and laserheading == self.LEFT):\n # mark anti-tank as destroyed\n map_data[ly][lx] = self.ANTI_TANK_DESTROYED_SYMBOL\n break\n\n # handle player laser collision\n elif ly == y and lx == x:\n return self.GAME_OVER\n\n # handle facing mirrors\n elif (map_data[ly][lx] == self.MIRROR_UL_SYMBOL and laserheading == self.RIGHT) or \\\n (map_data[ly][lx] == self.MIRROR_UR_SYMBOL and laserheading == self.LEFT):\n # new direction is up\n dy, dx = (-1, 0)\n laserheading = self.UP\n elif (map_data[ly][lx] == self.MIRROR_DL_SYMBOL and laserheading == self.RIGHT) or \\\n (self.grid_data[ly][lx] == self.MIRROR_DR_SYMBOL and laserheading == self.LEFT):\n # new direction is down\n dy, dx = (1, 0)\n laserheading = self.DOWN\n elif (map_data[ly][lx] == self.MIRROR_UL_SYMBOL and laserheading == self.DOWN) or \\\n (map_data[ly][lx] == self.MIRROR_DL_SYMBOL and laserheading == self.UP):\n # new direction is left\n dy, dx = (0, -1)\n laserheading = self.LEFT\n elif (map_data[ly][lx] == self.MIRROR_UR_SYMBOL and laserheading == self.DOWN) or \\\n (map_data[ly][lx] == self.MIRROR_DR_SYMBOL and laserheading == self.UP):\n # new direction is right\n dy, dx = (0, 1)\n laserheading = self.RIGHT\n # do not terminate laser on facing mirror - keep looping\n\n # check for game over condition after effect of laser\n if self.cell_is_game_over(y, x, map_data):\n return self.GAME_OVER\n return (x, y, heading, map_data)\n return self.SUCCESS","def cell(x, y):\n try:\n if cells[y][x]['filled'] == 1:\n return # this has already been processed\n except IndexError:\n return\n cells[y][x]['filled'] = 1 # this cell is now filled\n\n nn = []\n for nx, ny in neighbours(x, y):\n try:\n if cells[ny][nx]['filled']:\n nn.append(cells[ny][nx])\n except IndexError:\n continue\n \n c = 0 # colour weighting\n \n #------ Flippedness\n flipped = sum([i['inverted'] for i in nn if i['inverted']])\n cells[y][x]['inverted'] = (randint(0, 3) + flipped) % 4\n \n #------- Colour calculation\n avg_colour = sum([i['colour'][0] for i in nn]) / len(nn)\n avg_sat = sum([i['colour'][1] for i in nn]) / len(nn)\n avg_bri = sum([i['colour'][2] for i in nn]) / len(nn)\n \n # small chance of going totally random otherwise small variation from neighbours\n if random(100) > 90:\n h = randint(0, 100)\n s = randint(0, 100)\n b = randint(0, 100)\n else:\n h = (avg_colour + randint(-15, 15)) % 100\n s = (avg_sat + randint(-15, 15)) % 100\n b = (avg_bri + randint(-15, 15)) % 100\n cells[y][x]['colour'] = (h, s, b)\n \n #------- Alpha calculation\n d = sqrt((x*cell_size - rx)**2 + (y*cell_size - ry)**2) # distance from epicenter\n mx = sqrt((w-rx*cell_size)**2 + (h-ry*cell_size)**2)\n a = d/sqrt(w**2+h**2)*255\n cells[y][x]['alpha'] = a\n \n for cx,cy in neighbours(x, y):\n cell(cx, cy)","def is_fixed_state( previous_live, live_cells ):\n fixed = False\n if previous_live[0].size == live_cells[0].size:\n if previous_live[1].size == live_cells[1].size:\n if (previous_live[0]==live_cells[0]).all():\n if (previous_live[1]==live_cells[1]).all():\n fixed = True\n return fixed","def get_next_state(self, state, x, y):\n my_board = state\n game_over = False\n if is_mine(self.board, x, y):\n my_board[x, y] = MINE\n game_over = True\n else:\n my_board[x, y] = self.count_neighbour_mines(x, y)\n if my_board[x, y] == 0:\n my_board = self.open_neighbour_cells(my_board, x, y)\n self.my_board = my_board\n return my_board, game_over","def get_next_state(self, state, x, y):\n my_board = state\n game_over = False\n if is_mine(self.board, x, y):\n my_board[x, y] = MINE\n game_over = True\n else:\n my_board[x, y] = self.count_neighbour_mines(x, y)\n if my_board[x, y] == 0:\n my_board = self.open_neighbour_cells(my_board, x, y)\n self.my_board = my_board\n return my_board, game_over","def computer_play( game ):\n\n grid = game.get_grid()\n\n diag = game.checkDiagonals()\n row = game.checkRows()\n column = game.checkColumns()\n\n if isinstance(diag, tuple):\n \n for x in diag[1]:\n try:\n x = int(x)\n print(x)\n if isinstance(x, int):\n if game.set_mark('O', x):\n return\n\n except ValueError:\n continue\n\n elif isinstance(row, tuple):\n\n for x in row[1]:\n try:\n x = int(x)\n if isinstance(x, int):\n if game.set_mark('O', x):\n return\n\n except ValueError:\n continue\n\n elif isinstance(column, tuple):\n\n for x in column[1]:\n try:\n x = int(x)\n if isinstance(x, int):\n if game.set_mark('O', x):\n return\n\n except ValueError:\n continue \n\n for x in list(range(1,10)):\n if game.set_mark('O', x):\n return\n else:\n continue","def Get_empty_cells(difficulty, size):\n if(difficulty == 'beginner'):\n return size**2 - 50\n elif (difficulty == 'easy'):\n return size**2 - 40\n elif (difficulty == 'medium'):\n return size**2 - 33\n elif (difficulty == 'hard'):\n return size**2 - 26\n elif (difficulty == 'hell'):\n return size**2 - 17","def getGameState(self):\n row1 = [0, 0, 0]\n row2 = [0, 0, 0]\n row3 = [0, 0, 0]\n tilePosStatement = Statement()\n posTerm1 = Term('?x')\n posTerm2 = Term('?y')\n posTerm3 = Term('?tile')\n tilePosStatement.terms = (posTerm1, posTerm2, posTerm3)\n tilePosStatement.predicate = 'tilePos'\n for fact in self.kb.facts:\n if match(fact.statement, tilePosStatement):\n if fact.statement.terms[2] == Term(Constant('tile1')):\n term = 1\n if fact.statement.terms[2] == Term(Constant('tile2')):\n term = 2\n if fact.statement.terms[2] == Term(Constant('tile3')):\n term = 3\n if fact.statement.terms[2] == Term(Constant('tile4')):\n term = 4\n if fact.statement.terms[2] == Term(Constant('tile5')):\n term = 5\n if fact.statement.terms[2] == Term(Constant('tile6')):\n term = 6\n if fact.statement.terms[2] == Term(Constant('tile7')):\n term = 7\n if fact.statement.terms[2] == Term(Constant('tile8')):\n term = 8\n if fact.statement.terms[2] == Term(Constant('empty')):\n term = -1\n if fact.statement.terms[0] == Term(Constant('pos1')):\n col = 0\n elif fact.statement.terms[0] == Term(Constant('pos2')):\n col = 1\n elif fact.statement.terms[0] == Term(Constant('pos3')):\n col = 2\n if fact.statement.terms[1] == Term(Constant('pos1')):\n row1[col] = term\n\n elif fact.statement.terms[1] == Term(Constant('pos2')):\n row2[col] = term\n\n elif fact.statement.terms[1] == Term(Constant('pos3')):\n row3[col] = term\n\n row1 = tuple(row1)\n row2 = tuple(row2)\n row3 = tuple(row3)\n result = (row1, row2, row3)\n return result\n\n ### Student code goes here","def occupied_cells(self):\n\n for lm in self.landmarks:\n if self.cell_size < 1:\n # expand the range the landmark exists\n lm_x_range = np.arange(lm[0]-self.R, lm[0]+self.R, self.cell_size)\n lm_y_range = np.arange(lm[1]-self.R, lm[1]+self.R, self.cell_size)\n\n # loop through expanded ranges and compute grid positions\n for lm_x in lm_x_range:\n for lm_y in lm_y_range:\n\n row, col = self.cell_index([lm_x, lm_y])\n\n # apply cost of occupied cell\n try:\n self.world[row][col] = 1000\n except IndexError:\n pass\n\n else:\n # apply cost of occupied cell\n row, col = self.cell_index(lm)\n try:\n self.world[row][col] = 1000\n except IndexError:\n pass","def gameOfLife(self, board: List[List[int]]) -> None:\n m = len(board)\n if m==0:\n return board\n n = len(board[0])\n if n==0:\n return board\n def valid(a,b):\n if 0<=a<m and 0<=b<n:\n return True\n directions = [(0,-1),(-1,-1),(-1,0),(-1,1),(0,1),(1,1),(1,0),(1,-1)]\n for i in range(m):\n for j in range(n):\n #count how many live=1 or dead=0 cells surrounding cell (i,j)\n cnt_live=0\n for direc in directions:\n if valid(i+direc[0],j+direc[1]):\n if board[i+direc[0]][j+direc[1]]==1 or board[i+direc[0]][j+direc[1]]==-1:\n cnt_live+=1\n if (board[i][j]==1 and cnt_live<2) or \\\n (board[i][j]==1 and cnt_live>3):\n board[i][j]=-1\n elif board[i][j]==0 and cnt_live==3:\n board[i][j]=2\n for i in range(m):\n for j in range(n):\n if board[i][j]==-1:\n board[i][j]=0\n elif board[i][j]==2:\n board[i][j]=1","def advance_board(self):\n # We can advance the board using a pretty simple convolution,\n # so we don't have to execute a lot of loops in python.\n # Of course, this probably won't be sufficient for extremely\n # large boards.\n self.num_steps += 1\n board = self.board\n cfilter = np.array([[1,1,1],[1,0,1],[1,1,1]], dtype=np.uint16)\n\n alive = board & CellTypes.alive > 0\n spawning = board & CellTypes.spawning > 0\n frozen = board & CellTypes.frozen > 0\n\n can_die = ~frozen & (\n convolve2d(board & CellTypes.preserving, cfilter) == 0)\n can_grow = ~frozen & (\n convolve2d(board & CellTypes.inhibiting, cfilter) == 0)\n\n num_neighbors = convolve2d(alive, cfilter)\n num_spawn = convolve2d(spawning, cfilter)\n spawn_prob = 1 - (1 - self.spawn_prob)**num_spawn\n has_spawned = coinflip(spawn_prob, board.shape)\n\n born_rule = np.zeros(9, dtype=bool)\n born_rule[list(self.born_rule)] = True\n dead_rule = np.ones(9, dtype=bool)\n dead_rule[list(self.survive_rule)] = False\n\n new_alive = (born_rule[num_neighbors] | has_spawned) & ~alive & can_grow\n new_dead = dead_rule[num_neighbors] & alive & can_die\n\n new_flags = np.zeros_like(board)\n color_weights = 1 * alive + 2 * spawning\n for color in CellTypes.colors:\n # For each of the colors, see if there are two or more neighbors\n # that have it. If so, any new cells (whether born or spawned)\n # will also get that color.\n has_color = board & color > 0\n new_color = convolve2d(has_color * color_weights, cfilter) >= 2\n new_flags += color * new_color\n indestructible = alive & (board & CellTypes.destructible == 0)\n new_flags += CellTypes.destructible * (convolve2d(indestructible, cfilter) < 2)\n\n board *= ~(new_alive | new_dead)\n board += new_alive * (CellTypes.alive + new_flags)","def is_won(self):\n combinations = [*[(i, i + 3, i + 6) for i in range(3)],\n *[(i*3, i*3 + 1, i*3 + 2) for i in range(3)],\n (0, 4, 8), (2, 4, 6)]\n\n win = [*filter(lambda x: self[x[0]] == self[x[1]] == self[x[2]] and\n self[x[0]] != self.CELL_EMPTY, combinations)]\n return self[win[0][0]] if len(win) > 0 else self.CELL_EMPTY","def makeGrid(self, width, height, rewardLocs, exit, nPick=1, nAux=1, walls=[]):\n # Make mapping from coordinate (x, y, (takenreward1, takenreward2, ...))\n # to state number, and vice-versa.\n rTaken = iter([(),])\n for nPicked in range(1, nPick+1):\n rTaken = itertools.chain(rTaken, \n myCombinations(rewardLocs, r=nPicked)\n )\n # Iterators are hard to reset, so we list it.\n rTaken = list(rTaken)\n\n # Mappings from state to coordinates, vice-versa\n coordToState = {}\n stateToCoord = {}\n stateIdx = 0\n for x in range(width):\n for y in range(height):\n for stuff in rTaken:\n for holding in self.holdingPossibilities:\n coordToState[(x, y, stuff, holding)] = stateIdx\n stateToCoord[stateIdx] = (x, y, stuff, holding)\n stateIdx += 1\n self.deadEndState = stateIdx\n\n # Actually make the transition function\n def trans(f, p): \n aux = p\n (x, y, stuff, holding) = stateToCoord[f]\n actionMap = {}\n default = {(f, aux): 1}\n # Make the transition dictionary if the dead-end state (state width*height)\n if f == self.F-1:\n for action in range(5):\n actionMap[action] = default\n return actionMap\n\n # Otherwise, determine directions of motion, etc. \n for i in range(4):\n actionMap[i] = default\n if x != 0 and ((x-1, y) not in walls):\n actionMap[0] = {(coordToState[(x-1,y,stuff, holding)], aux): 1}\n if x < width-1 and ((x+1, y) not in walls):\n actionMap[1] = {(coordToState[(x+1,y,stuff, holding)], aux): 1}\n if y != 0 and ((x, y-1) not in walls):\n actionMap[2] = {(coordToState[(x,y-1,stuff, holding)], aux): 1}\n if y < height-1 and ((x, y+1) not in walls):\n actionMap[3] = {(coordToState[(x,y+1,stuff, holding)], aux): 1}\n # What happens when the agent uses action 4?\n if (x, y) == exit:\n # Some cases, depending on self.oneAtATime\n if not self.oneAtATime:\n # The agent is leaving.\n actionMap[4] = {(self.deadEndState, aux): 1}\n else:\n # The agent is dropping off a reward. holeFiller will\n # take care of the reward value.\n if len(stuff) >= nPick:\n # The agent is not allowed to pick up more stuff\n actionMap[4] = {(self.deadEndState, aux): 1}\n else:\n # The agent drops off the object.\n actionMap[4] = {(coordToState[(x,y,stuff, -1)], aux): 1}\n elif (x, y) not in rewardLocs:\n # No reward to pick up. Do nothing.\n actionMap[4] = default\n elif (x, y) in stuff:\n # This reward has already been used. Do nothing.\n actionMap[4] = default\n elif len(stuff) >= nPick or (holding != -1 and holding < len(stuff)\n and self.oneAtATime):\n # The agent has its hands full.\n actionMap[4] = default\n else:\n # The agent is allowed to pick up an object.\n newStuff = tuple(sorted(list(stuff) + [(x, y)]))\n if self.oneAtATime:\n newHoldingIdx = newStuff.index((x, y))\n else:\n newHoldingIdx = -1\n actionMap[4] = {(coordToState[(x, y, newStuff, newHoldingIdx)], aux): 1}\n return actionMap\n\n # Man, I'm outputting a lot of stuff.\n # coordToState[(x, y, rewardsLeft, holding)] -> index of this state\n # stateToCoord[index] -> (x, y, rewardsLeft, holding)\n # rTaken is a list of all possible combinations of leftover rewards.\n return (trans, coordToState, stateToCoord, rTaken)","def state(self) -> PuzzleState:\n\t\tfor cell in self._cells:\n\t\t\tif not (cell.value() or any(cell.potential_values())):\n\t\t\t\treturn PuzzleState.Conflict\n\n\t\tfor group in self._groups:\n\t\t\tif len(group.unsolved_cells()) > 0:\n\t\t\t\treturn PuzzleState.Unsolved\n\n\t\t\tdistinct_values = set()\n\t\t\tfor cell in group:\n\t\t\t\tvalue = cell.value()\n\t\t\t\tif value in distinct_values:\n\t\t\t\t\treturn PuzzleState.Conflict\n\t\t\t\tdistinct_values.add(value)\n\n\t\treturn PuzzleState.Solved","def generate_next_state(self) -> Dict[Tuple[int, int], Cell]:\n next_state: Dict[Tuple[int, int], Cell] = {}\n for living_cell in self.living_cells.values():\n for x in range(living_cell.x - 1, living_cell.x + 2):\n for y in range(living_cell.y - 1, living_cell.y + 2):\n cell = Cell(x, y)\n if (x, y) in self.living_cells.keys():\n cell = self.living_cells[x, y]\n if self._should_cell_live(cell):\n next_state[x, y] = Cell(x, y, True)\n \n self.living_cells = next_state\n \n return self.living_cells","def draw_grid(self) -> None:\n grid = self.life.curr_generation\n for row in range(self.cell_height):\n for column in range(self.cell_width):\n if grid[row][column] == 1:\n color = \"green\"\n else:\n color = \"white\"\n pygame.draw.rect(\n self.screen,\n pygame.Color(color),\n (column * self.cell_size, row * self.cell_size, self.cell_size, self.cell_size),\n )","def cell_is_game_over(self, y, x, map_data):\n # check for water\n if map_data[y][x] == self.WATER_SYMBOL:\n return True\n\n # check for anti-tank\n # up direction\n for i in range(y, -1, -1):\n if map_data[i][x] == self.ANTI_TANK_DOWN_SYMBOL:\n return True\n # if blocked, can stop checking for anti-tank\n if self.cell_is_blocked(i, x, map_data):\n break\n\n # down direction\n for i in range(y, self.y_size):\n if map_data[i][x] == self.ANTI_TANK_UP_SYMBOL:\n return True\n # if blocked, can stop checking for anti-tank\n if self.cell_is_blocked(i, x, map_data):\n break\n\n # left direction\n for i in range(x, -1, -1):\n if map_data[y][i] == self.ANTI_TANK_RIGHT_SYMBOL:\n return True\n # if blocked, can stop checking for anti-tank\n if self.cell_is_blocked(y, i, map_data):\n break\n\n # right direction\n for i in range(x, self.x_size):\n if map_data[y][i] == self.ANTI_TANK_LEFT_SYMBOL:\n return True\n # if blocked, can stop checking for anti-tank\n if self.cell_is_blocked(y, i, map_data):\n break\n\n # no water or anti-tank danger\n return False","def test_solo_cell():\n cell = c6.Cell(loc=[1, 1])\n for i in range(10):\n cell.step()","def test_multigrid_calculates_neighbours_correctly():\n\n # create a grid which will result in 9 cells\n h = 64\n img_dim = (3 * h + 1, 3 * h + 1)\n amg = mg.MultiGrid(img_dim, h, WS=127)\n\n # check that each cell has the expected neighbours\n print(amg.n_cells)\n\n # expected neieghbours left to right, bottom to top\n cells = [{\"north\": amg.cells[3], \"east\": amg.cells[1], \"south\": None, \"west\": None}, # bl\n {\"north\": amg.cells[4], \"east\": amg.cells[2],\n \"south\": None, \"west\": amg.cells[0]}, # bm\n {\"north\": amg.cells[5], \"east\": None,\n \"south\": None, \"west\": amg.cells[1]}, # br\n {\"north\": amg.cells[6], \"east\": amg.cells[4],\n \"south\": amg.cells[0], \"west\": None}, # ml\n {\"north\": amg.cells[7], \"east\": amg.cells[5],\n \"south\": amg.cells[1], \"west\": amg.cells[3]}, # mm\n {\"north\": amg.cells[8], \"east\": None,\n \"south\": amg.cells[2], \"west\": amg.cells[4]}, # mr\n # tl\n {\"north\": None, \"east\": amg.cells[7],\n \"south\": amg.cells[3], \"west\": None},\n # tm\n {\"north\": None,\n \"east\": amg.cells[8], \"south\": amg.cells[4], \"west\": amg.cells[6]},\n {\"north\": None, \"east\": None,\n \"south\": amg.cells[5], \"west\": amg.cells[7]}, # tr\n ]\n\n for ii, (gc, cell) in enumerate(zip(amg.cells, cells)):\n print(ii)\n assert gc.north == cell['north']\n assert gc.east == cell['east']\n assert gc.south == cell['south']\n assert gc.west == cell['west']","def _compute_world_params(self) -> None:\n\n self.states = []\n for row in range(self.grid_height):\n for col in range(self.grid_width):\n cell = row * self.grid_width + col\n cell_type = self.grid[cell]\n\n possible_actions = {\n Action.up: self._get_action(max(row - 1, 0) * self.grid_width + col),\n Action.down: self._get_action(min(row + 1, self.grid_height - 1) * self.grid_width + col),\n Action.right: self._get_action(row * self.grid_width + min(col + 1, self.grid_width - 1)),\n Action.left: self._get_action(row * self.grid_width + max(col - 1, 0))\n }\n\n self.states.append(State(cell, possible_actions, cell_type))","def updateGameState(self):\n boardArray = self._board.get_board()\n \n if self.state is self._BEGIN:\n\n for i in [1, self._board.get_board_size() - 2]:\n for j in range(1, self._board.get_board_size() - 1):\n\n if boardArray[i][j] != self._board._EMPTY:\n self.state = self._MIDDLE\n return\n\n if boardArray[j][i] != self._board._EMPTY:\n self.state = self._MIDDLE\n return\n\n\n elif self.state is self._MIDDLE:\n nbPieces = self._board.get_total_pieces()\n\n if nbPieces >= self._board.get_board_size()**2 - ENDGAME:\n self.state = self._END\n return","def __init__(self):\n pygame.init()\n self.settings = Settings()\n self.number_cells_x = int(input(\"Enter number of cells in a row: \"))\n self.cell_width = float(self.settings.screen_width // self.number_cells_x)\n #print(self.cell_width)\n self.number_cells_y = int(self.settings.screen_height // self.cell_width)\n\n self.screen = pygame.display.set_mode((self.settings.screen_width,self.settings.screen_height))\n pygame.display.set_caption(\"Game of Life\")\n\n self.cells = []\n self.to_be_updated = []\n self._create_cells()\n\n self.bg_colour = (self.settings.bg_colour)\n self.waiting = True","def test_print_cell(self):\n self.assertEqual(str(self.deadCell), \" \")\n self.assertEqual(str(self.livingCell), \"X\")","def generate_grains(self, cells):\n\t\tfor cell_num in range(cells):\n\t\t\trandom_row = random.randrange(0,self.space.shape[0],1)\n\t\t\tsample_cell = np.random.choice(self.space[random_row],1)\n\t\t\tsample_cell = sample_cell[0]\n\t\t\twhile sample_cell.state != 0:\n\t\t\t\trandom_row = random.randrange(0,self.space.shape[0],1)\n\t\t\t\tsample_cell = np.random.choice(self.space[random_row],1)\n\t\t\t\tsample_cell = sample_cell[0]\n\t\t\tsample_cell.change_state(self.init_time ,cell_num)","def actions(self, state):\n # actions = ['Left', 'Down', 'Right', 'Up']\n\n\n adjacent_cell_up = cell_adjacent(state[0], \"Up\")\n adjacent_cell_down = cell_adjacent(state[0], \"Down\")\n adjacent_cell_left = cell_adjacent(state[0], \"Left\")\n adjacent_cell_right = cell_adjacent(state[0], \"Right\")\n\n #Checking of macro is true\n if not self.macro:\n worker_actions = []\n # check if valid cell is above.\n if adjacent_cell_up not in self.warehouse.walls:\n worker_actions.append (\"Up\")\n\n # check if valid cell is below.\n if adjacent_cell_down not in self.warehouse.walls:\n worker_actions.append(\"Down\")\n\n # check if valid cell is to the left\n if adjacent_cell_left not in self.warehouse.walls:\n worker_actions.append(\"Left\")\n\n # check if valid cell is to the right\n if adjacent_cell_right not in self.warehouse.walls:\n worker_actions.append(\"Right\")\n\n return worker_actions\n\n else:\n box = []\n box_all = []\n #Checking if boxes are allowed in taboo area\n if not self.allow_taboo_push:\n for boxes in state[1:]:\n\n # check if valid cell is above.\n adjacent_box_up = cell_adjacent(boxes, \"Up\")\n #Checks if there is a taboo square or wall or box in next cell\n if adjacent_box_up not in self.taboo_list and adjacent_box_up not in self.warehouse.walls and adjacent_box_up not in state[1:]:\n box.append(\"Up\")\n\n # check if valid cell is bellow.\n adjacent_box_down = cell_adjacent(boxes, \"Down\")\n #Checks if there is a taboo square or wall or box in next cell\n if adjacent_box_down not in self.taboo_list and adjacent_box_down not in self.warehouse.walls and adjacent_box_down not in state[1:]:\n box.append(\"Down\")\n\n # check if valid cell is to the left\n adjacent_box_left = cell_adjacent(boxes, \"Left\")\n #Checks if there is a taboo square or wall or box in next cell\n if adjacent_box_left not in self.taboo_list and adjacent_box_left not in self.warehouse.walls and adjacent_box_left not in state[1:]:\n box.append(\"Left\")\n\n # check if valid cell is to the right\n adjacent_box_right = cell_adjacent(boxes, \"Right\")\n #Checks if there is a taboo square or wall or box in next cell\n if adjacent_box_right not in self.taboo_list and adjacent_box_right not in self.warehouse.walls and adjacent_box_right not in state[1:]:\n box.append(\"Right\")\n box_all.append(box)\n else:\n for boxes in state[1:]:\n # check if valid cell is above.\n adjacent_box_up = cell_adjacent(boxes, \"Up\")\n #Checks if there is a or wall or box in next cell\n if adjacent_box_up not in self.warehouse.walls and adjacent_box_up not in state[1:]:\n box.append(\"Up\")\n\n # check if valid cell is bellow.\n adjacent_box_down = cell_adjacent(boxes, \"Down\")\n #Checks if there is a or wall or box in next cell\n if adjacent_box_down not in self.warehouse.walls and adjacent_box_down not in state[1:]:\n box.append(\"Down\")\n\n # check if valid cell is to the left.\n adjacent_box_left = cell_adjacent(boxes, \"Left\")\n #Checks if there is a or wall or box in next cell\n if adjacent_box_left not in self.warehouse.walls and adjacent_box_left not in state[1:]:\n box.append(\"Left\")\n\n # check if valid cell is to the right.\n adjacent_box_right = cell_adjacent(boxes, \"Right\")\n #Checks if there is a or wall or box in next cell\n if adjacent_box_right not in self.warehouse.walls and adjacent_box_right not in state[1:]:\n box.append(\"Right\")\n box_all.append(box)\n return actions","def get_effective_cell_moves(state, cell, player):\n board = state.get_board()\n if board.is_cell_on_board(cell):\n possibles_moves = YoteRules._get_rules_possibles_moves(cell, board.board_shape)\n effective_moves = []\n i, j = cell\n for move in possibles_moves:\n if board.is_empty_cell(move):\n effective_moves.append(move)\n elif board.get_cell_color(move) == Color(player * -1):\n k, l = move\n if i == k and j < l and board.is_empty_cell((i, j + 2)):\n effective_moves.append((i, j + 2))\n elif i == k and l < j and board.is_empty_cell((i, j - 2)):\n effective_moves.append((i, j - 2))\n elif j == l and i < k and board.is_empty_cell((i + 2, j)):\n effective_moves.append((i + 2, j))\n elif j == l and k < i and board.is_empty_cell((i - 2, j)):\n effective_moves.append((i - 2, j))\n return effective_moves","def randomize(self):\n cell_stack = []\n cell = random.choice(self.cells)\n n_visited_cells = 1\n\n while n_visited_cells < len(self.cells):\n neighbors = [c for c in self.neighbors(cell) if c.is_full()]\n if len(neighbors):\n neighbor = random.choice(neighbors)\n cell.connect(neighbor)\n cell_stack.append(cell)\n cell = neighbor\n n_visited_cells += 1\n else:\n cell = cell_stack.pop()","def check_score(self) -> None:\n self.player_1, self.player_2 = 0, 0\n for cell in self.cells:\n if cell.player == 1:\n self.player_1 += 1\n elif cell.player == 2:\n self.player_2 += 1","def is_inacessible(cell):\n adj, count = num_adj_buildings(cell)\n return adj == count","def outcome(self):\n if self.grid[0][0] == self.grid[1][0] == self.grid[2][0] and self.grid[0][0] != 0:\n return self.grid[0][0]\n if self.grid[0][1] == self.grid[1][1] == self.grid[2][1] and self.grid[0][1] != 0:\n return self.grid[0][1]\n if self.grid[0][2] == self.grid[1][2] == self.grid[2][2] and self.grid[0][2] != 0:\n return self.grid[0][2]\n if self.grid[0][0] == self.grid[0][1] == self.grid[0][2] and self.grid[0][0] != 0:\n return self.grid[0][0]\n if self.grid[1][0] == self.grid[1][1] == self.grid[1][2] and self.grid[1][0] != 0:\n return self.grid[1][0]\n if self.grid[2][0] == self.grid[2][1] == self.grid[2][2] and self.grid[2][0] != 0:\n return self.grid[2][0]\n if self.grid[0][0] == self.grid[1][1] == self.grid[2][2] and self.grid[0][0] != 0:\n return self.grid[0][0]\n if self.grid[0][2] == self.grid[1][1] == self.grid[2][0] and self.grid[0][2] != 0:\n return self.grid[0][2]\n return 0","def run(self):\n for cell in self.grid.each_cell():\n neighbors = []\n if cell.north:\n neighbors.append(cell.north)\n if cell.east:\n neighbors.append(cell.east)\n if neighbors:\n neighbor = random.choice(neighbors)\n if neighbor:\n cell.link(neighbor)\n return self.grid","def _is_dead_end(self, i_row, i_col, direction):\n return (((i_row, i_col) in self._ts_cells and direction == \"s\") or\n ((i_row, i_col) in self._ts_cells and direction == \"se\") or\n ((i_row, i_col) in self._ts_cells and direction == \"sw\") or\n ((i_row, i_col) in self._ls_cells and direction == \"e\") or\n ((i_row, i_col) in self._ls_cells and direction == \"ne\") or\n ((i_row, i_col) in self._ls_cells and direction == \"se\") or\n ((i_row, i_col) in self._bs_cells and direction == \"n\") or\n ((i_row, i_col) in self._bs_cells and direction == \"nw\") or\n ((i_row, i_col) in self._bs_cells and direction == \"ne\") or\n ((i_row, i_col) in self._rs_cells and direction == \"w\") or\n ((i_row, i_col) in self._rs_cells and direction == \"nw\") or\n ((i_row, i_col) in self._rs_cells and direction == \"sw\") or\n ((i_row, i_col) == self._tl_cell and direction == \"s\") or\n ((i_row, i_col) == self._tl_cell and direction == \"se\") or\n ((i_row, i_col) == self._tl_cell and direction == \"e\") or\n ((i_row, i_col) == self._bl_cell and direction == \"n\") or\n ((i_row, i_col) == self._bl_cell and direction == \"ne\") or\n ((i_row, i_col) == self._bl_cell and direction == \"e\") or\n ((i_row, i_col) == self._tr_cell and direction == \"w\") or\n ((i_row, i_col) == self._tr_cell and direction == \"sw\") or\n ((i_row, i_col) == self._tr_cell and direction == \"s\") or\n ((i_row, i_col) == self._br_cell and direction == \"w\") or\n ((i_row, i_col) == self._br_cell and direction == \"nw\") or\n ((i_row, i_col) == self._br_cell and direction == \"n\"))","def distribute_onto_grid(self, cells,type):\n\n\t\t# setting up the topology of the space the cells will be in\n\t\tif self.VARS.NEIGHBORHOOD == \"Moore\":\n\t\t\tsize = 10\n\t\t\tcount=0\n\t\t\tcells = self.VARS.CELLS\n\t\t\t# moving them into a '10X10 grid'\n\t\t\tfor i in range(1,size+1):\n\t\t\t\tfor j in range(1, size+1):\n\t\t\t\t\tcells[count].set_location(i,j)\n\t\t\t\t\tcount +=1\n\n\t\t\t# distances to get Moore neighbors of everyone in the network\n\t\t\tfor i in range(len(cells)):\n\t\t\t\tfor j in range(len(cells)):\n\t\t\t\t\tif j > i:\n\t\t\t\t\t\tone = cells[i]\n\t\t\t\t\t\ttwo = cells[j]\n\t\t\t\t\t\t# wraps edges of the torus around.\n\t\t\t\t\t\tdist = measure_distance(one, two)\n\t\t\t\t\t\tif dist < 1.5:\n\t\t\t\t\t\t\tone.add_neighbor(two)\n\t\t\t\t\t\t\ttwo.add_neighbor(one)\n\t\t\t\t\t\t\tself.net.add_edge(one,two)","def determine_game_state(self):\n if self.board == BLANK_BOARD:\n return GameState.GAME_NOT_STARTED\n\n # check for three of the same symbol across or down.\n for r in range(3):\n offset = r*3\n if self.board[offset] == self.board[offset+1] == self.board[offset+2]:\n if self.board[offset] == X_SYMBOL:\n return GameState.GAME_OVER_X_WINS\n elif self.board[offset] == O_SYMBOL:\n return GameState.GAME_OVER_O_WINS\n if self.board[r] == self.board[3 + r] == self.board[6 + r]:\n if self.board[r] == X_SYMBOL:\n return GameState.GAME_OVER_X_WINS\n elif self.board[r] == O_SYMBOL:\n return GameState.GAME_OVER_O_WINS\n\n # check for diagonal wins\n if ((self.board[0] == self.board[4] == self.board[8]) or\n (self.board[2] == self.board[4] == self.board[6])):\n if self.board[4] == X_SYMBOL:\n return GameState.GAME_OVER_X_WINS\n elif self.board[4] == O_SYMBOL:\n return GameState.GAME_OVER_O_WINS\n \n # check for tie.\n if not self.board.count(EMPTY_SYMBOL):\n return GameState.GAME_OVER_DRAW\n\n return GameState.GAME_IN_PROGRESS","def _check_inner_dirs(self, i_row, i_col, adj_opp_cells):\n opp_player = \"B\" if self._turn == \"W\" else \"W\"\n \n if self._board[i_row-1][i_col] == opp_player: #north, tile to be placed will enter from the south\n adj_opp_cells.append((i_row-1, i_col, \"s\")) \n if self._board[i_row-1][i_col+1] == opp_player: #northeast, tile to be placed will enter from the sw\n adj_opp_cells.append((i_row-1, i_col+1, \"sw\"))\n if self._board[i_row][i_col+1] == opp_player: #east, tile to be placed will enter from the west\n adj_opp_cells.append((i_row, i_col+1, \"w\"))\n if self._board[i_row+1][i_col+1] == opp_player: #southeast, tile to be placed will enter from the nw\n adj_opp_cells.append((i_row+1, i_col+1, \"nw\"))\n if self._board[i_row+1][i_col] == opp_player: #south, tile to be placed will enter from the north\n adj_opp_cells.append((i_row+1, i_col, \"n\"))\n if self._board[i_row+1][i_col-1] == opp_player: #southwest, tile to be placed will enter from the ne\n adj_opp_cells.append((i_row+1, i_col-1, \"ne\"))\n if self._board[i_row][i_col-1] == opp_player: #west, tile to be placed will enter from the east.\n adj_opp_cells.append((i_row, i_col-1, \"e\"))\n if self._board[i_row-1][i_col-1] == opp_player: #northwest, tile to be placed will enter from the se.\n adj_opp_cells.append((i_row-1, i_col-1, \"se\"))","def check_game_status(self):\n for player in (\"1\", \"2\"):\n row_win = np.apply_along_axis(\n lambda x: set(x) == {player}, 1, self.board\n ).any()\n col_win = np.apply_along_axis(\n lambda x: set(x) == {player}, 0, self.board\n ).any()\n d1_win = set(self.data[[0, 4, 8]]) == {player}\n d2_win = set(self.data[[2, 4, 6]]) == {player}\n if any([row_win, col_win, d1_win, d2_win]):\n return (\"win\", player)\n\n if self.counter[\"_\"] == 0:\n return (\"tie\", None)\n else:\n return (\"turn\", \"1\" if self.counter[\"1\"] == self.counter[\"2\"] else \"2\")","def _update_cells(self):\n for row_number in range(self.number_cells_y):\n for col_number in range(self.number_cells_x):\n if self.to_be_updated[row_number][col_number]:\n self.cells[row_number][col_number].update()","def choose_cell_to_assign(self):\r\n min_domain = 10\r\n max_degree = -1\r\n chosen_row = None\r\n chosen_col = None\r\n for row in range(9):\r\n for col in range(9):\r\n if self.puzzle[row][col] == 0:\r\n domain_size = len(self.grid[row][col].domain)\r\n if domain_size < min_domain:\r\n min_domain = domain_size\r\n chosen_row = row\r\n chosen_col = col\r\n elif domain_size == min_domain:\r\n degree = len(self.grid[row][col].neighbors)\r\n if degree > max_degree:\r\n max_degree = degree\r\n chosen_row = row\r\n chosen_col = col\r\n return self.grid[chosen_row][chosen_col]","def is_cell_safe(self, cell, board):\n # look at a cell and the cell's revealed neighbors\n # if any neighbors say there's 1 mine nearby, and that neighbor has neighbors which\n # contain a flag, it's safe to click here\n # TODO: this really needs to only check neighbors' neighbors that border the original cell.\n # right now more cells are considered than should be.\n safe = False\n neighbors = ms.Minesweeper.get_neighbors(cell.row, cell.col, board)\n revealed_neighbors = [n for n in neighbors if n.revealed or n.flagged]\n for n in revealed_neighbors:\n if n.neighbors > 0:\n n_neighbors = ms.Minesweeper.get_neighbors(n.row, n.col, board)\n flagged_n_neighbors = [n for n in n_neighbors if n.flagged]\n if len(flagged_n_neighbors) > 0:\n safe = True\n return safe","def gameOfLife(self, board: List[List[int]]) -> None:\n\n neighbors = [(1,0), (1,-1), (0,-1), (-1,-1), (-1,0), (-1,1), (0,1), (1,1)]\n\n rows = len(board)\n cols = len(board[0])\n\n # 遍历面板每一个格子里的细胞\n for row in range(rows):\n for col in range(cols):\n # 对于每一个细胞统计其八个相邻位置里的活细胞数量\n live_neighbors = 0\n\n for neighbor in neighbors:\n # 相邻位置的坐标\n r = (row + neighbor[0])\n c = (col + neighbor[1])\n # 查看相邻的细胞是否是活细胞\n if (r < rows and r >= 0) and (c < cols and c >= 0) and abs(board[r][c]) == 1:\n live_neighbors += 1\n\n # 过去的活细胞，现在变为死细胞\n if board[row][col] == 1 and (live_neighbors < 2 or live_neighbors > 3):\n # -1 代表这个细胞过去是活的现在死了\n board[row][col] = -1\n # 过去的死细胞，现在变为活细胞\n if board[row][col] == 0 and live_neighbors == 3:\n # 2 代表这个细胞过去是死的现在活了\n board[row][col] = 2\n\n # 遍历 board 刷新更新后的状态\n for row in range(rows):\n for col in range(cols):\n if board[row][col] > 0:\n board[row][col] = 1\n else:\n board[row][col] = 0","def check(self):\n winner = None\n count = 0\n\n for y in range(self.gridSize):\n if winner != None:\n return winner\n P1, P2 = 0, 0\n for item in self.grid[y]:\n # Check row of the grid\n if item == \"P1\":\n P1 += 1\n elif item == \"P2\":\n P2 += 1\n winner = self.checkval(P1, P2, self.gridSize)\n if winner != None:\n return winner\n P1, P2 = 0, 0\n for x in range(self.gridSize):\n # Check column of the grid\n if self.grid[x][y] == \"P1\":\n P1 += 1\n elif self.grid[x][y] == \"P2\":\n P2 += 1\n winner = self.checkval(P1, P2, self.gridSize)\n if winner != None:\n return winner\n P1, P2 = 0, 0\n for y in range(self.gridSize):\n # Check right top to left bottom across the grid\n for x in range(self.gridSize):\n if x == y:\n if self.grid[x][y] == \"P1\":\n P1 += 1\n elif self.grid[x][y] == \"P2\":\n P2 += 1\n winner = self.checkval(P1, P2, self.gridSize)\n if winner != None:\n return winner\n P1, P2 = 0, 0\n for y in range(self.gridSize):\n # Check the left top to the right bottom across the grid\n for x in range(self.gridSize - 1, -1, -1):\n # Check how many filled spaces there are\n if \".\" not in self.grid[y][x]:\n count += 1\n if x + y == self.gridSize - 1:\n if self.grid[y][x] == \"P1\":\n P1 += 1\n elif self.grid[y][x] == \"P2\":\n P2 += 1\n winner = self.checkval(P1, P2, self.gridSize)\n # Check if there is a winner if so return the winner\n if winner != None:\n return winner\n # Check if the fields that are filled are equal to the possible spaces to be filled in the grid\n if count == self.gridSize**2:\n return \"Tie\"","def _ignite_cells(self, istep, ip):\n particle = self.particles[ip] # get particle\n state, x, y = particle.get_from_keys([\"state\", \"x\", \"y\"])\n if state > STTHR:\n for i in range(self.grid.NX-1):\n if abs(x - self.grid.XCELL[i, 0]) < self.grid.DX/2:\n INDX = i\n for j in range(self.grid.NY-1):\n if abs(y - self.grid.YCELL[0, j]) < self.grid.DY/2:\n INDY = j\n cell = self.grid.CELLS[INDX, INDY]\n cell.BURNPROG += 1\n if (cell.QMAXTR > 0 or cell.QMAXBLD > 0) and cell.BURNSTAT == 0:\n cell.BURNSTAT = 1\n cell.CLOCK = self.TIME[istep]\n # elif cell.QMAXTR == 0 or cell.QMAXBLD == 0:\n # particle.update(state=0.0, factor=0.0)\n # if pType == 2:\n # particle.update(state=0.0)","def _compute_grid_state(self, for_id):\n own = np.zeros_like(self._map, float)\n own_pos = self._id2pos[for_id]\n own[own_pos] = 1\n\n thieves = (self._map == THIEF ).astype(float)\n guardians = (self._map == GUARDIAN).astype(float)\n\n own_team = self.id2team[for_id]\n if own_team == THIEF:\n teammates = thieves\n opponents = guardians\n else:\n teammates = guardians\n opponents = thieves\n\n treasure_channel = (self._map == TREASURE).astype(float)\n\n # Channels first\n return np.stack([own, teammates, opponents, self._walls_channel, treasure_channel])","def changeCell(self, i, j):\n\t\t#If Cell is on Top row\n\t\tif(i==0):\n\t\t\tif(j==0):\n\t\t\t\tn = self.board[0][1] + self.board[1][0] + self.board[1][1]\n\t\t\telif(j==(self.size-1)):\n\t\t\t\tn = self.board[0][self.size-2] + self.board[1][self.size-2] + self.board[1][self.size-1]\n\t\t\telse:\n\t\t\t\tn = self.board[0][j-1] + self.board[1][j] + self.board[0][j+1] + self.board[1][j-1] + self.board[1][j+1]\n\t\t\t\n\t\t\tif((n == 2 and self.board[i][j] == 1) or n == 3):\n\t\t\t\treturn 1\n\t\t\telse:\n\t\t\t\treturn 0\n\t\t#If Cell on Bottom row\n\t\telif(i==(self.size-1)):\n\t\t\tif(j==0):\n\t\t\t\tn = self.board[self.size-1][1] + self.board[self.size-2][0] + self.board[self.size-2][1]\n\t\t\telif(j==(self.size-1)):\n\t\t\t\tn = self.board[self.size-1][self.size-2] + self.board[self.size-2][self.size-2] + self.board[self.size-2][self.size-1]\n\t\t\telse:\n\t\t\t\tn = self.board[self.size-1][j-1] + self.board[self.size-2][j] + self.board[self.size-1][j+1] + self.board[self.size-2][j-1] + self.board[self.size-2][j+1]\n\t\t\tif((n == 2 and self.board[i][j] == 1) or n == 3):\n\t\t\t\treturn 1\n\t\t\telse:\n\t\t\t\treturn 0\n\t\t#If Cell is in a middle row\n\t\telse:\n\t\t\tif(j==0):\n\t\t\t\tn = self.board[i-1][j] + self.board[i+1][j] + self.board[i][j+1] + self.board[i-1][j+1] + self.board[i+1][j+1]\n\t\t\telif(j==(self.size-1)):\n\t\t\t\tn = self.board[i-1][j] + self.board[i+1][j] + self.board[i][j-1] + self.board[i-1][j-1] + self.board[i+1][j-1]\n\t\t\telse:\n\t\t\t\tn = self.board[i-1][j] + self.board[i+1][j] + self.board[i][j-1] + self.board[i-1][j-1] + self.board[i+1][j-1] + self.board[i][j+1] + self.board[i-1][j+1] + self.board[i+1][j+1]\n\t\t\tif((n == 2 and self.board[i][j] == 1) or n == 3):\n\t\t\t\treturn 1\n\t\t\telse:\n\t\t\t\treturn 0","def test(brickheight,bricklength,row,column,walllength,wallheight,occupied,answer):\n if brickheight>wallheight or bricklength>walllength:\n return False\n elif over(brickheight,bricklength,row,column,walllength,wallheight):\n return False\n else:\n for x in range(column,column+bricklength):\n for y in range(row,row+brickheight):\n if (x,y) in occupied:\n return False \n break\n else:\n return True","def random_state(self) -> Grid2D.State:\n return Grid2D.State(random.choice(self.empty_cell_list))","def getGameState(self):\n ### Student code goes here\n\n ask_tile_11 = parse_input(\"fact: (located ?X pos1 pos1)\")\n ask_tile_12 = parse_input(\"fact: (located ?X pos2 pos1)\")\n ask_tile_13 = parse_input(\"fact: (located ?X pos3 pos1)\")\n ask_tile_21 = parse_input(\"fact: (located ?X pos1 pos2)\")\n ask_tile_22 = parse_input(\"fact: (located ?X pos2 pos2)\")\n ask_tile_23 = parse_input(\"fact: (located ?X pos3 pos2)\")\n ask_tile_31 = parse_input(\"fact: (located ?X pos1 pos3)\")\n ask_tile_32 = parse_input(\"fact: (located ?X pos2 pos3)\")\n ask_tile_33 = parse_input(\"fact: (located ?X pos3 pos3)\")\n\n bindings_11 = self.kb.kb_ask(ask_tile_11)\n bindings_12 = self.kb.kb_ask(ask_tile_12)\n bindings_13 = self.kb.kb_ask(ask_tile_13)\n bindings_21 = self.kb.kb_ask(ask_tile_21)\n bindings_22 = self.kb.kb_ask(ask_tile_22)\n bindings_23 = self.kb.kb_ask(ask_tile_23)\n bindings_31 = self.kb.kb_ask(ask_tile_31)\n bindings_32 = self.kb.kb_ask(ask_tile_32)\n bindings_33 = self.kb.kb_ask(ask_tile_33)\n\n row1_list = []\n row2_list = []\n row3_list = []\n\n row1_list.append(bindings_11.list_of_bindings[0][0].bindings[0].constant.element)\n row1_list.append(bindings_12.list_of_bindings[0][0].bindings[0].constant.element)\n row1_list.append(bindings_13.list_of_bindings[0][0].bindings[0].constant.element)\n\n row2_list.append(bindings_21.list_of_bindings[0][0].bindings[0].constant.element)\n row2_list.append(bindings_22.list_of_bindings[0][0].bindings[0].constant.element)\n row2_list.append(bindings_23.list_of_bindings[0][0].bindings[0].constant.element)\n\n row3_list.append(bindings_31.list_of_bindings[0][0].bindings[0].constant.element)\n row3_list.append(bindings_32.list_of_bindings[0][0].bindings[0].constant.element)\n row3_list.append(bindings_33.list_of_bindings[0][0].bindings[0].constant.element)\n\n counter = 0\n for tile in row1_list:\n if tile == \"empty\":\n row1_list[counter] = -1\n else:\n row1_list[counter] = int(tile[4:])\n counter += 1\n\n counter = 0\n for tile in row2_list:\n if tile == \"empty\":\n row2_list[counter] = -1\n else:\n row2_list[counter] = int(tile[4:])\n counter += 1\n\n counter = 0\n for tile in row3_list:\n if tile == \"empty\":\n row3_list[counter] = -1\n else:\n row3_list[counter] = int(tile[4:])\n counter += 1\n\n gamestate = (tuple(row1_list), tuple(row2_list), tuple(row3_list))\n return gamestate","def actions(self, state):\n MovementList = []\n #Check if the agent is able to move a box (Left, Down, Right, Up) \n #without moving it into a taboo cell or pushing two blocks (Invalid move)\n #then move the box in the given direction.\n \n possible_moves = [\"Up\", \"Down\", \"Left\", \"Right\"]\n \n worker = state[0]\n boxes = state[1]\n \n # Iterate throguh the moves and make sure they satify constraints\n for move in possible_moves:\n if (move_coords(worker, move) not in self.walls):\n if (move_coords(worker, move) in boxes):\n if move_coords(move_coords(worker, move), move) in self.taboo:\n pass\n else: \n MovementList.append(move)\n else:\n MovementList.append(move)\n \n return MovementList","def spawn_ok(game):\n me = game.me\n shipyard_cell = game.game_map[me.shipyard]\n\n # % turns above mining rate to dropoff the halite, will typically be about 2?\n mining_over_head = 2\n ship_count = len(me.get_ships())\n\n #\n # absolute constraints (order can be important)\n #\n\n if ship_count >= MAX_SHIPS:\n if DEBUG & (DEBUG_GAME): logging.info(\"Game - Spawn denied. MAX ships reached\".format())\n return False\n\n if me.halite_amount < constants.SHIP_COST:\n if DEBUG & (DEBUG_GAME): logging.info(\"Game - Spawn denied. Insufficient halite\".format())\n return False\n\n #\n # conditional constraints\n #\n\n logging.debug(\"shipyard_cell.is_occupied: {}\".format(shipyard_cell.is_occupied))\n if shipyard_cell.is_occupied:\n logging.debug(\"shipyard_cell.ship.owner == me.id: {}\".format(shipyard_cell.ship.owner == me.id))\n\n # watch for collisions with owner only, note this will be 1 turn behind\n occupied_cells = []\n if shipyard_cell.is_occupied and shipyard_cell.ship.owner == me.id:\n occupied_cells.append(shipyard_cell.position)\n\n logging.debug(\"oc1: {}\".format(occupied_cells))\n\n # entry lane are N/S\n n_cell = shipyard_cell.position.directional_offset(Direction.North)\n s_cell = shipyard_cell.position.directional_offset(Direction.South)\n e_cell = shipyard_cell.position.directional_offset(Direction.East)\n w_cell = shipyard_cell.position.directional_offset(Direction.West)\n for pos in [n_cell, s_cell, e_cell, w_cell]:\n if game.game_map[pos].is_occupied:\n occupied_cells.append(pos)\n\n logging.debug(\"oc2: {}\".format(occupied_cells))\n\n # need to keep track of ships docking instead, a ship in an adjacent cell could be leaving\n if occupied_cells:\n if DEBUG & (DEBUG_GAME): logging.info(\"Game - Spawn denied. Occupied cells: {}\".format(occupied_cells))\n return False\n\n return True","def empty_cells(state):\r\n cells = []\r\n for x, row in enumerate(state):\r\n for y, cell in enumerate(row):\r\n if cell == 0:\r\n cells.append([x, y])\r\n\r\n return cells","def fill_grid(self):\n\n for row_margin, row in enumerate(range(self.rows)):\n self.grid.append([])\n\n for col_margin, col in enumerate(range(self.cols)):\n x = col*self.cell_size + col_margin\n y = row*self.cell_size + row_margin\n\n rect = pygame.Rect(x, y, self.cell_size, self.cell_size)\n\n cell = Cell(row, col, rect)\n\n if row == 7 and col == 3:\n cell.root = True\n self.root = cell\n elif row == 7 and col == 16:\n cell.goal = True\n self.goal = cell\n\n self.grid[row].append(cell)","def gameOfLife(self, board: List[List[int]]) -> None:\n changes = list()\n for i in range(len(board)):\n for j in range(len(board[0])):\n neighbor_data = {\n 'live': 0,\n 'dead': 0\n }\n checks = {(0,1), (0,-1), (1, 0), (-1, 0), (1, 1), (1, -1), (-1, 1), (-1,-1)}\n if i == 0:\n checks.discard((-1, 0))\n checks.discard((-1, 1))\n checks.discard((-1, -1))\n if j == 0:\n checks.discard((0, -1))\n checks.discard((-1, -1))\n checks.discard((1, -1))\n if i == (len(board) - 1):\n checks.discard((1,0))\n checks.discard((1,-1))\n checks.discard((1, 1))\n if j == (len(board[0]) - 1):\n checks.discard((0, 1))\n checks.discard((-1, 1))\n checks.discard((1, 1))\n for check in checks:\n if board[i + check[0]][j + check[1]]:\n neighbor_data['live'] += 1\n else:\n neighbor_data['dead'] += 1\n if board[i][j]:\n # check live rules\n if neighbor_data['live'] < 2 or neighbor_data['live'] > 3:\n changes.append((i, j))\n else:\n # check dead rules\n if neighbor_data['live'] == 3:\n changes.append((i, j))\n for change in changes:\n board[change[0]][change[1]] = int (not board[change[0]][change[1]])\n \n print (board)","def __init__(self, num_rows = 4, num_cols = 4,\n first_mover = \"W\", top_left = \"B\",\n how_to_win = \">\", initial_config=[]):\n # initial_config was made for AI Othello to\n # get around pass-by-reference behavior of lists.\n if (4 > num_rows > 16) or num_rows % 2 != 0:\n raise Exception\n else:\n self._num_rows = num_rows\n if (4 > num_cols > 16) or num_cols % 2 != 0:\n raise Exception\n else:\n self._num_cols = num_cols\n if first_mover != \"B\" and first_mover != \"W\":\n raise Exception\n else:\n self._turn = first_mover\n if top_left != \"B\" and top_left != \"W\":\n raise Exception\n else:\n self._top_left = top_left\n if how_to_win != \">\" and how_to_win != \"<\":\n raise Exception\n else:\n self._how_to_win = how_to_win\n\n if initial_config == []:\n self._board = self._make_board(num_rows, num_cols, top_left)\n else:\n self._board = deepcopy(initial_config)\n \n self._game_over = False\n self._winner = \" \"\n self._tl_cell = (0, 0)\n self._tr_cell = (0, num_cols-1)\n self._bl_cell = (num_rows-1, 0)\n self._br_cell = (num_rows-1, num_cols-1)\n self._ls_cells = [(c, 0) for c in range(1, num_rows-1)]\n self._rs_cells = [(c, num_cols-1) for c in range(1, num_rows-1)]\n self._ts_cells = [(0, c) for c in range(1, num_cols-1)]\n self._bs_cells = [(num_rows-1, c) for c in range(1, num_cols-1)]\n #^Note how ranges start from 1 and go to num_rows-1 to avoid corners,\n #which are processed differently"],"string":"[\n \"def _check_cells(self):\\n for row_number in range(self.number_cells_y):\\n for col_number in range(self.number_cells_x):\\n alive_neighbours = self._get_neighbours(row_number,col_number)\\n \\n self.to_be_updated[row_number][col_number] = False\\n if self.cells[row_number][col_number].get_status():\\n if alive_neighbours < 2:\\n self.to_be_updated[row_number][col_number] = True\\n elif alive_neighbours > 3:\\n self.to_be_updated[row_number][col_number] = True\\n else:\\n if alive_neighbours == 3:\\n self.to_be_updated[row_number][col_number] = True\",\n \"def init_cells(self):\\n state = list()\\n width = WIDTH / CELL_SIZE\\n height = HEIGHT / CELL_SIZE\\n\\n for index in range(0, width * height):\\n if randint(1, 100) >= 100 - CELL_DENSITY:\\n # Live cell.\\n status = NORMAL\\n state.append(1)\\n else:\\n # Dead cell.\\n status = HIDDEN\\n state.append(0)\\n\\n cell = self.canvas.create_rectangle((index % width) * CELL_SIZE, (index / width) * CELL_SIZE,\\n ((index % width) + 1) * CELL_SIZE, ((index / width) + 1) * CELL_SIZE,\\n fill=\\\"black\\\", state=status, outline=\\\"white\\\")\\n self.cells.append(cell)\\n\\n return state\",\n \"def examineMaze(self, gameState):\\n w = self.walls.width\\n h = self.walls.height\\n walls = self.walls.deepCopy()\\n food1 = self.getFoodYouAreDefending(gameState)\\n food2 = self.getFood(gameState)\\n\\n # Save map as 0, 1, 2 and 3 (0:walls, 1:spaces, 2:babies, 3:food)\\n for x in range(w):\\n for y in range(h):\\n if walls[x][y]:\\n walls[x][y] = 0\\n elif food1[x][y]:\\n walls[x][y] = 2\\n elif food2[x][y]:\\n walls[x][y] = 2\\n else:\\n walls[x][y] = 1\\n\\n roomsDisplay = []\\n # Detect doors and spaces. Spaces are now negative\\n for x in range(w):\\n for y in range(h):\\n if walls[x][y] > 0:\\n exitsNum = 0\\n if walls[x][y - 1] != 0:\\n exitsNum += 1\\n if walls[x][y + 1] != 0:\\n exitsNum += 1\\n if walls[x - 1][y] != 0:\\n exitsNum += 1\\n if walls[x + 1][y] != 0:\\n exitsNum += 1\\n if exitsNum == 1 or exitsNum == 2:\\n walls[x][y] = -1 * walls[x][y]\\n roomsDisplay.append((x, y))\\n elif exitsNum == 0:\\n # We erase unaccessible cells\\n walls[x][y] = 0\\n else:\\n # These are doors or big rooms, we leave them positive\\n pass\\n\\n # Create roomsGraph: every room has a number, some cells and some doors\\n roomsGraph = []\\n doorsGraph = []\\n for x in range(1, w - 1):\\n for y in range(1, h - 1):\\n if walls[x][y] < 0:\\n spacesNum = 0\\n if walls[x][y - 1] < 0:\\n spacesNum += 1\\n if walls[x][y + 1] < 0:\\n spacesNum += 1\\n if walls[x - 1][y] < 0:\\n spacesNum += 1\\n if walls[x + 1][y] < 0:\\n spacesNum += 1\\n if spacesNum < 2:\\n endOfPath = False\\n graphNode = {\\\"path\\\": [], \\\"doors\\\": [], \\\"food\\\": 0, \\\"isBig\\\": False}\\n auxx = x\\n auxy = y\\n while not endOfPath:\\n graphNode[\\\"path\\\"].append((x, y))\\n graphNode[\\\"food\\\"] += -walls[x][y] - 1\\n walls[x][y] = 0\\n xx = x\\n yy = y\\n if walls[x][y - 1] < 0:\\n yy = y - 1\\n elif walls[x][y + 1] < 0:\\n yy = y + 1\\n elif walls[x - 1][y] < 0:\\n xx = x - 1\\n elif walls[x + 1][y] < 0:\\n xx = x + 1\\n else:\\n endOfPath = True\\n if walls[x][y - 1] > 0:\\n if [(x, y - 1), []] not in doorsGraph:\\n graphNode[\\\"doors\\\"].append(len(doorsGraph))\\n doorsGraph.append([(x, y - 1), []])\\n else:\\n graphNode[\\\"doors\\\"].append(doorsGraph.index([(x, y - 1), []]))\\n if walls[x][y + 1] > 0:\\n if [(x, y + 1), []] not in doorsGraph:\\n graphNode[\\\"doors\\\"].append(len(doorsGraph))\\n doorsGraph.append([(x, y + 1), []])\\n else:\\n graphNode[\\\"doors\\\"].append(doorsGraph.index([(x, y + 1), []]))\\n if walls[x - 1][y] > 0:\\n if [(x - 1, y), []] not in doorsGraph:\\n graphNode[\\\"doors\\\"].append(len(doorsGraph))\\n doorsGraph.append([(x - 1, y), []])\\n else:\\n graphNode[\\\"doors\\\"].append(doorsGraph.index([(x - 1, y), []]))\\n if walls[x + 1][y] > 0:\\n if [(x + 1, y), []] not in doorsGraph:\\n graphNode[\\\"doors\\\"].append(len(doorsGraph))\\n doorsGraph.append([(x + 1, y), []])\\n else:\\n graphNode[\\\"doors\\\"].append(doorsGraph.index([(x + 1, y), []]))\\n x = xx\\n y = yy\\n roomsGraph.append(graphNode)\\n x = auxx\\n y = auxy\\n\\n # Create doorsGraph: every door has a number, and goes to other rooms or other doors\\n for j, door in enumerate(doorsGraph):\\n for i, room in enumerate(roomsGraph):\\n for aDoor in room[\\\"doors\\\"]:\\n if aDoor == j:\\n doorsGraph[j][1] = doorsGraph[j][1] + [i]\\n (x, y) = doorsGraph[j][0]\\n adjacentCells = [(x+1, y), (x-1, y), (x, y+1), (x, y-1)]\\n adjacentDoors = []\\n # Check adjacent doors and add them to the current door (door structure is [pos, adjRooms, adjDoors]\\n for p in adjacentCells:\\n # Skip if wall\\n if self.walls[p[0]][p[1]]:\\n continue\\n # Skip if door\\n isRoom = False\\n for room in doorsGraph[j][1]:\\n if p in roomsGraph[room][\\\"path\\\"]:\\n isRoom = True\\n break\\n if not isRoom:\\n # Add if existing door\\n doorFound = False\\n for i, neighborDoor in enumerate(doorsGraph):\\n if neighborDoor[0] == p:\\n adjacentDoors.append(i)\\n doorFound = True\\n break\\n # Create if non existing door and add\\n if not doorFound:\\n adjacentDoors.append(len(doorsGraph))\\n doorsGraph.append([p, []])\\n doorsGraph[j].append(adjacentDoors)\\n\\n # Create doorsDistance: maps what doors can be accessed from other doors\\n roomsMapper = {}\\n doorsMapper = {}\\n isRoom = util.Counter()\\n for i, door in enumerate(doorsGraph):\\n doorsMapper[door[0]] = i\\n isRoom[door[0]] = 0\\n for i, room in enumerate(roomsGraph):\\n for p in room[\\\"path\\\"]:\\n roomsMapper[p] = i\\n isRoom[p] = 1\\n\\n # Create self variables\\n self.doorsGraph = doorsGraph\\n self.roomsGraph = roomsGraph\\n self.roomsMapper = roomsMapper\\n self.doorsMapper = doorsMapper\\n self.isRoom = isRoom\\n\\n # # Find dead ends (rooms with only one door)\\n # deadRooms = {}\\n # deadDoors = {}\\n # # deaderDoors = {}\\n # # deaderRooms = {}\\n # for i, room in enumerate(roomsGraph):\\n # if len(room[\\\"doors\\\"]) == 1:\\n # deadRooms[i] = room[\\\"doors\\\"][0]\\n # deadDoors[room[\\\"doors\\\"][0]] = 1\\n # numdR = 0\\n # aliveR = -1\\n # for adjRoom in doorsGraph[room[\\\"doors\\\"][0]][1]:\\n # if adjRoom not in deadRooms:\\n # numdR += 1\\n # aliveR = adjRoom\\n # if numdR + len(doorsGraph[room[\\\"doors\\\"][0]][2]) == 1:\\n # if aliveR >= 0:\\n # deaderRooms[aliveR] = room[\\\"doors\\\"][0]\\n # for adjDoor in roomsGraph[aliveR][\\\"doors\\\"]:\\n # if adjDoor == room[\\\"doors\\\"][0]:\\n # continue\\n # deaderDoors[adjDoor] = 1.0\\n # else:\\n # deaderDoors[doorsGraph[room[\\\"doors\\\"][0]][2][0]] = 1.0\\n\\n\\n # roomsCounter = [util.Counter(), util.Counter(), util.Counter(), util.Counter()]\\n # for r in deaderRooms:\\n # for p in roomsGraph[r][\\\"path\\\"]:\\n # roomsCounter[0][p] = 0.4\\n # for d in deaderDoors:\\n # roomsCounter[1][doorsGraph[d][0]] = 0.4\\n # self.displayDistributionsOverPositions(roomsCounter)\\n # raw_input(\\\"Press Enter to continue ...\\\")\\n\\n\\n # print deadDoors\\n # print\\n # print deadRooms\\n # print \\\"-----------------\\\"\\n\\n # deadEndsChanged = True\\n # while deadEndsChanged:\\n # deadEndsChanged = False\\n # for i, room in enumerate(roomsGraph):\\n # numAliveDoors = 0\\n # aliveDoor = 0\\n # deadDoor = []\\n # for door in room[\\\"doors\\\"]:\\n # if door not in deadDoors:\\n # numAliveDoors += 1\\n # aliveDoor = door\\n # else:\\n # deadDoor.append(door)\\n # if numAliveDoors == 1:\\n # aliveRoom = 0\\n # aliveNeighborDoor = 0\\n # for door in deadDoor:\\n # # aliveNeighborDoor += len(doorsGraph[door][2])\\n # for neighborRoom in doorsGraph[door][1]:\\n # if neighborRoom not in deadRooms:\\n # aliveRoom += 1\\n # if aliveRoom == len(deadDoor):\\n # deadRooms[i] = aliveDoor\\n # deadDoors[aliveDoor] = 1\\n # deadEndsChanged = True\\n # roomsCounter = [util.Counter(), util.Counter(), util.Counter(), util.Counter()]\\n # roomsCounter[0][doorsGraph[aliveDoor][0]] = 1\\n # for p in room[\\\"path\\\"]:\\n # roomsCounter[1][p] = 1\\n # for p in deadDoor:\\n # roomsCounter[2][doorsGraph[p][0]] = 1\\n # self.displayDistributionsOverPositions(roomsCounter)\\n # raw_input(\\\"Press Enter to continue ...\\\")\\n\\n\\n # Find dead ends (rooms with doors that only go to other dead ends, except one)\\n # Danger, it is theoretically possible to have a map only with dead ends, which may make this crash\\n # deadEndsChanged = True\\n # while deadEndsChanged:\\n # deadEndsChanged = False\\n # for i, door in enumerate(doorsGraph):\\n # if i not in deadDoors:\\n # numOpenRooms = 0\\n # openRoom = 0\\n # for j, room in enumerate(door[1]):\\n # if room not in deadRooms:\\n # numOpenRooms += 1\\n # openRoom = j\\n # if numOpenRooms + len(door[2]) == 1:\\n # for room in door[1]:\\n # if room != openRoom:\\n # deadRooms[room] = i\\n # deadDoors[j] = 1\\n # deadEndsChanged = True\\n # roomsCounter = [util.Counter(), util.Counter(), util.Counter(), util.Counter()]\\n # roomsCounter[0][door[0]] = 1\\n # for rr in door[1]:\\n # print rr\\n # if rr in deadRooms:\\n # for p in roomsGraph[rr][\\\"path\\\"]:\\n # roomsCounter[1][p] = 1\\n # else:\\n # for p in roomsGraph[rr][\\\"path\\\"]:\\n # roomsCounter[3][p] = 1\\n # self.displayDistributionsOverPositions(roomsCounter)\\n # raw_input(\\\"Press Enter to continue ...\\\")\\n\\n # print deadDoors\\n # print\\n # print deadRooms\\n # print \\\"-----------------\\\"\\n\\n # roomsCounter = [util.Counter(), util.Counter(), util.Counter(), util.Counter()]\\n # roomsCounter[1][(6, 9)] = 0.4\\n # self.displayDistributionsOverPositions(roomsCounter)\\n # raw_input(\\\"Press Enter to continue ...\\\")\\n\\n # roomsCounter = [util.Counter(), util.Counter(), util.Counter(), util.Counter()]\\n # for r in deadRooms:\\n # for p in roomsGraph[r][\\\"path\\\"]:\\n # roomsCounter[0][p] = 0.4\\n # for d in deadDoors:\\n # roomsCounter[1][doorsGraph[d][0]] = 0.4\\n # self.displayDistributionsOverPositions(roomsCounter)\\n # raw_input(\\\"Press Enter to continue ...\\\")\\n\\n # Show every room\\n roomsCounter = [util.Counter(), util.Counter(), util.Counter(), util.Counter()]\\n for room in roomsGraph:\\n for p in room[\\\"path\\\"]:\\n if len(room[\\\"doors\\\"]) > 1:\\n roomsCounter[0][p] = 0.4\\n else:\\n roomsCounter[2][p] = 0.4\\n # Show every door\\n for door in doorsGraph:\\n roomsCounter[1][door[0]] = 0.4\\n # Display rooms and doors (red: rooms with at least one exit; orange: rooms with 1 exit; blue: doors\\n self.displayDistributionsOverPositions(roomsCounter)\\n # raw_input(\\\"Press Enter to continue ...\\\")\",\n \"def next_state_of_cell(self, x_cell, y_cell):\\n neighbours = self.get_number_neighbours_of_cell(x_cell, y_cell)\\n if(self.board_state[x_cell][y_cell] == 1):\\n # Any live cell with more than three live neighbours dies, \\n # as if by overpopulation.\\n if(neighbours > 3):\\n return 0\\n # Any live cell with fewer than two live neighbours dies,\\n # as if by underpopulation.\\n elif(neighbours < 2):\\n return 0\\n # Any live cell with two or three live neighbours lives\\n # on to the next generation.\\n else:\\n return 1\\n if(self.board_state[x_cell][y_cell] == 0):\\n # Any dead cell with exactly three live neighbours becomes a live cell, \\n # as if by reproduction.\\n if(neighbours == 3):\\n return 1\\n else:\\n return 0\",\n \"def in_cell(self):\\n for player in self.players:\\n for cell in self.cell_lst:\\n if player.x in cell[0] and player.y in cell[1]:\\n player.current_cell = cell\\n break\",\n \"def test_dead_cell(self, alive_cells, alive):\\n for positions in alive_cells:\\n world = gol.World(3, 3)\\n for x, y in positions:\\n world.set_cell((x, y))\\n world.update()\\n assert world[(0, 0)] == alive\",\n \"def test_live_cell(self, alive_cells, alive):\\n for positions in alive_cells:\\n world = gol.World(3, 3)\\n world.set_cell((0, 0))\\n for x, y in positions:\\n world.set_cell((x, y))\\n world.update()\\n assert world[(0, 0)] == alive\",\n \"def update_cells(self, state):\\n width = WIDTH / CELL_SIZE\\n height = HEIGHT / CELL_SIZE\\n\\n for index in range(0, width * height):\\n if state[index] != self.get_state(index):\\n self.toggle_color(index)\",\n \"def cell_create(game_set, screen, covids, cells):\\n cell_create_flag = True\\n cell = Cell(game_set, screen)\\n for old_cell in cells.sprites():\\n if old_cell.rect.y < game_set.cell_number_adjust:\\n cell_create_flag = False\\n break\\n if (not pygame.sprite.spritecollide(cell, cells, 0) and\\n not pygame.sprite.spritecollide(cell, covids, 0) and\\n cell_create_flag):\\n cells.add(cell)\",\n \"def state_generator(self):\\n\\n kernel = np.array([\\n [1, 1, 1],\\n [1, 0, 1],\\n [1, 1, 1]])\\n iteration = 0\\n\\n while True: # (Game of Life does not end)\\n # Run 2D convolution with the given kernel to find out how many neighbors each cell has.\\n # Boundary option determines whether to run with hard boundaries on the game board or\\n # using a toroid board which wraps circularly. These are the two strategies for handling\\n # a finite game board. scipy.signal.convolve2d handles these two modes gracefully, which\\n # is why it is used here. There is also a performance gain when using numpy/scipy matrix\\n # operations as opposed to iterating element-wise over the whole matrix.\\n # See https://docs.scipy.org/doc/scipy-0.19.1/reference/generated/scipy.signal.convolve2d.html\\n\\n # There is a more sophisticated and efficient algorithm for determining next game state\\n # (see http://dotat.at/prog/life/life.html) but for clarity and a lack of time, the standard\\n # implementation was chosen.\\n\\n num_neighbors_board = convolve2d(self.board, kernel, mode='same', boundary=self.boundary.value)\\n\\n # Find empty cells that have three neighbors\\n birth_coordinates = np.where(np.logical_and(self.board == 0, num_neighbors_board == 3))\\n\\n # Find live cells with too few or too many neighbors\\n death_coordinates = np.where(\\n np.logical_and(\\n self.board == 1,\\n np.logical_or(num_neighbors_board < 2, num_neighbors_board > 3)\\n )\\n )\\n\\n births = np.array(birth_coordinates).transpose().tolist()\\n deaths = np.array(death_coordinates).transpose().tolist()\\n self.board[birth_coordinates] = 1\\n self.board[death_coordinates] = 0\\n\\n iteration += 1\\n yield self.board, births, deaths, iteration\",\n \"def game_of_life():\\n # 3x3 neighbourhood\\n offsets = [[(y, x) for y in range(-1, 2)] for x in range(-1, 2)]\\n\\n # Create mappings\\n mappings = {}\\n for i in range(2 ** 9):\\n\\n # Determine the initial state (key)\\n key = f\\\"{bin(i)[2:]:0>9}\\\" # As binary string\\n key = tuple(k == \\\"1\\\" for k in key) # As tuple of bools\\n key = tuple(key[i * 3:i * 3 + 3] for i in range(3)) # Reshape into 2D grid\\n\\n # Alive counts\\n centre = key[1][1]\\n others = sum(sum(row) for row in key) - centre\\n\\n # Skip if state does not evaluate to True\\n if centre:\\n if others not in (2, 3):\\n continue\\n\\n else:\\n if others != 3:\\n continue\\n\\n mappings[key] = True\\n\\n return Mapping2DRuleset(mappings, offsets)\",\n \"def game_value(self, state):\\n # check horizontal wins\\n for row in state:\\n for i in range(2):\\n if row[i] != ' ' and row[i] == row[i+1] == row[i+2] == row[i+3]:\\n return 1 if row[i]==self.my_piece else -1\\n\\n # check vertical wins\\n for col in range(5):\\n for i in range(2):\\n if state[i][col] != ' ' and state[i][col] == state[i+1][col] == state[i+2][col] == state[i+3][col]:\\n return 1 if state[i][col]==self.my_piece else -1\\n\\n # TODO: check \\\\ diagonal wins\\n for col in range(2):\\n for i in range(2):\\n if state[i][col] != ' ' and state[i][col] == state[i+1][col+1] == state[i+2][col+2] == state[i+3][col+3]:\\n return 1 if state[i][col]==self.my_piece else -1\\n # TODO: check / diagonal wins\\n for col in range(2):\\n for i in range(2):\\n if state[i][col+3] != ' ' and state[i][col+3] == state[i+1][col+2] == state[i+2][col+1] == state[i+3][col]:\\n return 1 if state[i][col]==self.my_piece else -1\\n # TODO: check 2x2 box wins\\n for col in range(4):\\n for i in range(4):\\n if state[i][col] != ' ' and state[i][col] == state[i+1][col] == state[i][col+1] == state[i+1][col+1]:\\n return 1 if state[i][col]==self.my_piece else -1\\n \\n return 0 # no winner yet\",\n \"def game_value(self, state):\\n # check horizontal wins\\n for row in state:\\n for i in range(2):\\n if row[i] != ' ' and row[i] == row[i+1] == row[i+2] == row[i+3]:\\n return 1 if row[i]==self.my_piece else -1\\n\\n # check vertical wins\\n for col in range(5):\\n for i in range(2):\\n if state[i][col] != ' ' and state[i][col] == state[i+1][col] == state[i+2][col] == state[i+3][col]:\\n return 1 if state[i][col]==self.my_piece else -1\\n\\n # check \\\\ diagonal wins\\n for i in range(2):\\n for j in range(2):\\n if state[i][j]!= ' ' and state[i][j] == state[i+1][j+1] == state[i+2][j+2] == state[i+3][j+3]:\\n return 1 if state[i][j]==self.my_piece else -1\\n # check / diagonal wins\\n for i in range(3,5):\\n for j in range(2):\\n if state[i][j]!= ' ' and state[i][j] == state[i-1][j+1] == state[i-2][j+2] == state[i-3][j+3]:\\n return 1 if state[i][j]==self.my_piece else -1\\n # check diamond wins\\n for i in range(3):\\n for j in range(1,4):\\n if state[i+1][j] == ' ' and state[i][j]!= ' ' and state[i][j] == state[i+1][j-1] == state[i+1][j+1] == state[i+2][j]:\\n return 1 if state[i][j]==self.my_piece else -1\\n\\n return 0 # no winner yet\",\n \"def gameOfLife(self, board: List[List[int]]) -> None:\\n # copy matrix\\n copy_matrix = [[board[row][col] for col in range(len(board[0]))] for row in range(len(board))]\\n \\n # 8 possible directions\\n directions = [(0,1), (0, -1), (1,0), (-1,0), (-1,-1), (1,1), (1,-1), (-1,1)]\\n num_rows = len(board)\\n num_cols = len(board[0])\\n \\n # matrix traversal\\n for i in range(0, num_rows):\\n for j in range(0, num_cols):\\n # for each cell, explore all of its neighboring cells\\n num_live_cells = 0\\n for direction in directions:\\n r = i + direction[0]\\n c = j + direction[1]\\n # make sure if it is a live cell \\n if (r < num_rows and r >=0) and (c < num_cols and c>=0) and (copy_matrix[r][c]==1):\\n # if it is live cell, increment live_cell_count\\n num_live_cells +=1\\n # if here: We now have estimate of surrounding live cells\\n # start applying rules \\n # Rule-1: Any live cell with fewer than 2 live neighbors die\\n # Rule-2: Any live cell with 2/3 live neighbors live up\\n # Rule-3: Any Live cell with > 3 live neighbors die\\n # Rule-4: Any dead cell with ==3 live neighbors becomes alive\\n if copy_matrix[i][j] == 1 and (num_live_cells > 3 or num_live_cells < 2):\\n # Rule-1 and Rule-3: So the current cell dies...\\n board[i][j] = 0\\n if copy_matrix[i][j] == 0 and num_live_cells == 3:\\n # Rule-4: Dead becomes alive\\n board[i][j] = 1\\n # Rule-2 is taken care by default.\",\n \"def game_value(self, state):\\r\\n # check horizontal wins\\r\\n for row in state:\\r\\n for i in range(2):\\r\\n if row[i] != ' ' and row[i] == row[i+1] == row[i+2] == row[i+3]:\\r\\n return 1 if row[i] == self.my_piece else -1\\r\\n # check col wins\\r\\n for col in range(5):\\r\\n for i in range(2):\\r\\n if state[i][col] != ' ' and state[i][col] == state[i+1][col] == state[i+2][col] == state[i+3][col]:\\r\\n return 1 if state[i][col] == self.my_piece else -1\\r\\n #check diag up wins\\r\\n for x in range(2):\\r\\n for y in range(2):\\r\\n if state[x][y] != ' ' and state[x][y] == state[x+1][y+1] == state[x+2][y+2] == state[x+3][y+3]:\\r\\n return 1 if state[x][y] == self.my_piece else -1\\r\\n #check diag down wins\\r\\n for x in range(2):\\r\\n for y in range(3, 5):\\r\\n if state[x][y] != ' ' and state[x][y] == state[x+1][y-1] == state[x+2][y-2] == state[x+3][y-3]:\\r\\n return 1 if state[x][y] == self.my_piece else -1\\r\\n #check square box wins \\r\\n for x in range(4):\\r\\n for y in range(4):\\r\\n if state[x][y] != ' ' and state[x][y] == state[x+1][y] == state[x][y+1] == state[x+1][y+1]:\\r\\n return 1 if state[x][y] == self.my_piece else -1\\r\\n\\r\\n return 0 # no winner yet\\r\",\n \"def cycle(self):\\n\\n coordinates = self.get_random_coordinates()\\n\\n for coord in coordinates:\\n if isinstance(self.cells[coord], (Jungle, Savannah, Desert)):\\n self.cells[coord].feeding()\\n\\n for coord in coordinates:\\n if isinstance(self.cells[coord], (Jungle, Savannah, Desert)):\\n self.cells[coord].procreation()\\n\\n self.migration()\\n\\n for coord in coordinates:\\n if isinstance(self.cells[coord], (Jungle, Savannah, Desert)):\\n self.cells[coord].aging()\\n\\n for coord in coordinates:\\n if isinstance(self.cells[coord], (Jungle, Savannah, Desert)):\\n self.cells[coord].loss_of_weight()\\n\\n for coord in coordinates:\\n if isinstance(self.cells[coord], (Jungle, Savannah, Desert)):\\n self.cells[coord].death()\\n\\n self.animals_on_island()\",\n \"def play_best_guess(self, game):\\n\\n\\n # create a list of cells\\n cells = [game.board[i][j]\\n for i in xrange(game.rows)\\n for j in xrange(game.cols)]\\n\\n first_cell = cells[0]\\n game.reveal_cell(first_cell.row, first_cell.col)\\n\\n # draw updated board and pause for a second\\n game.draw_board()\\n if PAUSE == True:\\n time.sleep(1)\\n\\n\\n total_flagged = 0\\n while not game.lost_game and not game.won_game:\\n\\n # remember if we've made a move in the while loop\\n # so we know whether to make a random move later on\\n made_move = False\\n\\n # look through all revealed cells for any with a number of neighboring mines.\\n # if the cell has the same number of unrevealed neighbors as the cell's\\n # number of neighboring mines, all the unrevealed neighbors must be mines.\\n revealed_numbered_cells = [c for c in cells if c.revealed and (not c.flagged) and (c.neighbors > 0)]\\n while revealed_numbered_cells:\\n cell = revealed_numbered_cells.pop()\\n # cell may have been marked flagged after revealed_numbered_cells was compiled\\n if not cell.flagged:\\n neighbor_cells = ms.Minesweeper.get_neighbors(cell.row, cell.col, game.board)\\n flagged_neighbors = [n for n in neighbor_cells if n.flagged]\\n number_remaining_mines = cell.neighbors - len(flagged_neighbors)\\n unknown_neighbors = [n for n in neighbor_cells if not n.flagged and not n.revealed]\\n if number_remaining_mines > 0 and len(unknown_neighbors) == number_remaining_mines:\\n # flag every neighbor\\n for c in unknown_neighbors:\\n if total_flagged < game.mines:\\n total_flagged += 1\\n game.flag_cell(c.row, c.col)\\n if (game.test_did_win()):\\n game.game_over()\\n game.draw_board()\\n if PAUSE == True:\\n time.sleep(1)\\n made_move = True\\n\\n # we may have won with the flag above so test whether we're still playing\\n # before further calculations\\n if not game.lost_game and not game.won_game:\\n # loop through all unrevealed, unflagged cells and see if we know it's safe to reveal\\n for c in cells:\\n if not c.revealed and not c.flagged and self.is_cell_safe(c, game.board):\\n game.reveal_cell(c.row, c.col)\\n if (game.test_did_win()):\\n game.game_over()\\n game.draw_board()\\n if PAUSE == True:\\n time.sleep(1)\\n made_move = True\\n\\n # assume we've made our best guesses and now have to guess randomly\\n # this will prevent us from looping forever if no obvious moves are available\\n if not made_move:\\n unrevealed = [c for c in cells if not c.revealed and not c.flagged]\\n if len(unrevealed) > 0:\\n cell = random.choice(unrevealed)\\n game.reveal_cell(cell.row, cell.col)\\n if (game.test_did_win()):\\n game.game_over()\\n game.draw_board()\\n if PAUSE == True:\\n time.sleep(3)\",\n \"def evaluateBoardState(self, board):\\n\\n \\\"\\\"\\\"\\n These are the variables and functions for board objects which may be helpful when creating your Agent.\\n Look into board.py for more information/descriptions of each, or to look for any other definitions which may help you.\\n\\n Board Variables:\\n board.width \\n board.height\\n board.last_move\\n board.num_to_connect\\n board.winning_zones\\n board.score_array \\n board.current_player_score\\n\\n Board Functions:\\n get_cell_value(row, col)\\n try_move(col)\\n valid_move(row, col)\\n valid_moves()\\n terminal(self)\\n legal_moves()\\n next_state(turn)\\n winner()\\n \\\"\\\"\\\"\\n if self.id == 1:\\n opponent_id = 2\\n else:\\n opponent_id = 1\\n\\n maxvalue = 100000\\n minvalue = -maxvalue\\n winner = board.winner()\\n if winner == self.id:\\n return maxvalue\\n elif winner == opponent_id:\\n return minvalue\\n size_y = board.height\\n size_x = board.width\\n map_ = []\\n num_to_connect = board.num_to_connect\\n total_points = 0\\n\\n multiply_reachable = 1\\n multiply_oddeven = 1\\n # basically this function is calculating all the possible win positions\\n # more pieces in a possible win position will be counted with more weights\\n # a win position with X pieces in it will be counted as X^2 points\\n # initialise the zones maps\\n for i in range(size_y):\\n map_.append([])\\n for j in range(size_x):\\n map_[i].append([])\\n\\n # Fill in the horizontal win positions\\n for i in range(size_y):\\n for j in range(size_x - num_to_connect + 1):\\n points = 0\\n self_pieces_count = 0\\n opponent_pieces_count = 0\\n for k in range(num_to_connect):\\n if board.board[i][j + k] == opponent_id:\\n opponent_pieces_count += 1\\n elif board.board[i][j + k] == self.id:\\n points += len(board.winning_zones[j+k][i])\\n if (self.id == 1 and i % 2 == 1) or (self.id == 2 and i%2 == 0):\\n points *= multiply_oddeven\\n self_pieces_count += 1\\n if self_pieces_count == 3 and opponent_pieces_count == 0:\\n if j - 1 >= 0 and board.board[i][j + 3] == 0 and board.board[i][j - 1] == 0 \\\\\\n and board.try_move(j + 3) == i and board.try_move(j - 1) == i:\\n return maxvalue\\n elif j + 4 < size_y and board.board[i][j + 4] == 0 and board.board[i][j] == 0 \\\\\\n and board.try_move(j + 4) == i and board.try_move(j) == i:\\n return maxvalue\\n else:\\n for k in range(num_to_connect):\\n if board.board[i][j + k] == 0 and board.try_move(j + k) == i:\\n points *= multiply_reachable\\n elif opponent_pieces_count == 3 and self_pieces_count == 0:\\n if j - 1 >= 0 and board.board[i][j + 3] == 0 and board.board[i][j - 1] == 0 \\\\\\n and board.try_move(j + 3) == i and board.try_move(j - 1) == i:\\n return minvalue\\n elif j + 4 < size_y and board.board[i][j + 4] == 0 and board.board[i][j] == 0 \\\\\\n and board.try_move(j + 4) == i and board.try_move(j) == i:\\n return minvalue\\n # else:\\n # for k in range(num_to_connect):\\n # if board.board[i][j + k] == 0 and board.try_move(j + k) == i:\\n # points *= -multiply_reachable\\n if (opponent_pieces_count == 3 and self_pieces_count == 0) or opponent_pieces_count == 0:\\n total_points += points\\n\\n # Fill in the vertical win positions\\n for i in range(size_x):\\n for j in range(size_y - num_to_connect + 1):\\n points = 0\\n self_pieces_count = 0\\n for k in range(num_to_connect):\\n if board.board[j + k][i] == opponent_id:\\n opponent_pieces_count += 1\\n elif board.board[j + k][i] == self.id:\\n points += len(board.winning_zones[i][j+k])\\n if (self.id == 1 and (j+k) % 2 == 1) or (self.id == 2 and (j+k)%2 == 0):\\n points *= multiply_oddeven\\n self_pieces_count += 1\\n points *= multiply_reachable\\n # if opponent_pieces_count == 3 and self_pieces_count == 0:\\n # points *= -1\\n if (opponent_pieces_count == 3 and self_pieces_count == 0) or opponent_pieces_count == 0:\\n total_points += points\\n\\n # Fill in the forward diagonal win positions\\n for i in range(size_y - num_to_connect + 1):\\n for j in range(size_x - num_to_connect + 1):\\n points = 0\\n self_pieces_count = 0\\n opponent_pieces_count = 0\\n for k in range(num_to_connect):\\n if board.board[i + k][j + k] == opponent_id:\\n opponent_pieces_count += 1\\n elif board.board[i + k][j + k] == self.id:\\n points += len(board.winning_zones[j+k][i+k])\\n if (self.id == 1 and (i+k) % 2 == 1) or (self.id == 2 and (i+k)%2 == 0):\\n points *= multiply_oddeven\\n self_pieces_count += 1\\n if self_pieces_count == 3 and opponent_pieces_count == 0:\\n if i - 1 >= 0 and j - 1 >= 0 and board.board[i + 3][j + 3] == 0 and board.board[i - 1][j - 1] == 0 \\\\\\n and board.try_move(j + 3) == i + 3 and board.try_move(j - 1) == i - 1:\\n return maxvalue\\n elif i + 4 < size_y and j + 4 < size_x and board.board[i + 4][j + 4] == 0 and board.board[i][j] == 0 \\\\\\n and board.try_move(j + 4) == i + 4 and board.try_move(j) == i:\\n return maxvalue\\n else:\\n for k in range(num_to_connect):\\n if board.board[i + k][j + k] == 0 and board.try_move(j + k) == i + k:\\n points *= multiply_reachable\\n elif opponent_pieces_count == 3 and self_pieces_count == 0:\\n if i - 1 >= 0 and j - 1 >= 0 and board.board[i + 3][j + 3] == 0 and board.board[i - 1][j - 1] == 0 \\\\\\n and board.try_move(j + 3) == i + 3 and board.try_move(j - 1) == i - 1:\\n return minvalue\\n elif i + 4 < size_y and j + 4 < size_x and board.board[i + 4][j + 4] == 0 and board.board[i][j] == 0 \\\\\\n and board.try_move(j + 4) == i + 4 and board.try_move(j) == i:\\n return minvalue\\n # else:\\n # for k in range(num_to_connect):\\n # if board.board[i + k][j + k] == 0 and board.try_move(j + k) == i + k:\\n # points *= -multiply_reachable\\n if (opponent_pieces_count == 3 and self_pieces_count == 0) or opponent_pieces_count == 0:\\n total_points += points\\n\\n # Fill in the backward diagonal win positions\\n for i in range(size_y - num_to_connect + 1):\\n for j in range(size_x - 1, num_to_connect - 1 - 1, -1):\\n points = 0\\n self_pieces_count = 0\\n opponent_pieces_count = 0\\n for k in range(num_to_connect):\\n if board.board[i + k][j - k] == opponent_id:\\n opponent_pieces_count += 1\\n elif board.board[i + k][j - k] == self.id:\\n points += len(board.winning_zones[j-k][i+k])\\n if (self.id == 1 and (i+k) % 2 == 1) or (self.id == 2 and (i+k)%2 == 0):\\n points *= multiply_oddeven\\n self_pieces_count += 1\\n if self_pieces_count == 3 and self_pieces_count == 0:\\n if board.board[i + 3][j - 3] == 0 and board.board[i - 1][j + 1] == 0 \\\\\\n and board.try_move(j - 3) == i + 3 and board.try_move(j + 1) == i - 1:\\n return maxvalue\\n elif i + 4 < size_y and j - 4 >= 0 and board.board[i + 4][j - 4] == 0 and board.board[i][j] == 0 \\\\\\n and board.try_move(j - 4) == i + 4 and board.try_move(j) == i:\\n return maxvalue\\n else:\\n for k in range(num_to_connect):\\n if board.board[i + k][j - k] == 0 and board.try_move(j - k) == i + k:\\n points *= multiply_reachable\\n\\n elif opponent_pieces_count == 3 and self_pieces_count == 0:\\n if board.board[i + 3][j - 3] == 0 and board.board[i - 1][j + 1] == 0 \\\\\\n and board.try_move(j - 3) == i + 3 and board.try_move(j + 1) == i - 1:\\n return minvalue\\n elif i + 4 < size_y and j - 4 >= 0 and board.board[i + 4][j - 4] == 0 and board.board[i][j] == 0 \\\\\\n and board.try_move(j - 4) == i + 4 and board.try_move(j) == i:\\n return minvalue\\n # else:\\n # for k in range(num_to_connect):\\n # if board.board[i + k][j - k] == 0 and board.try_move(j - k) == i + k:\\n # points *= -multiply_reachable\\n if (opponent_pieces_count == 3 and self_pieces_count == 0) or opponent_pieces_count == 0:\\n total_points += points\\n return total_points\",\n \"def game_over(self) -> bool:\\n for row in range(9):\\n for col in range(9):\\n if self._grid_sol[row][col] != self.get_cell(row, col):\\n return False\\n return True\",\n \"def get_all_game_cells(self):\\n return GameCell.objects.filter(game=self)\",\n \"def gameOfLife(self, board):\\n \\n # Neighbours array for 8 neighboring cells of a given cell\\n neighbors = [(1,0), (1,-1), (0,-1), (-1,-1), (-1,0), (-1,1), (0,1), (1,1)]\\n \\n rows = len(board)\\n cols = len(board[0])\\n \\n # Iterate through the board by each cell\\n for row in range(rows):\\n for col in range(cols):\\n \\n # For each cell counting number of live neighbors\\n live_neighbors = 0\\n for neighbor in neighbors:\\n \\n # row and column of neighboring cell\\n r = (row + neighbor[0])\\n c = (col + neighbor[1])\\n \\n # Checking validity of neighboring cell and if it was originally a live cell\\n if(r < rows and r >= 0) and (c < cols and c >= 0) and abs(board[r][c]) == 1:\\n \\n live_neighbors += 1\\n \\n # Rule 1 or Rule 3\\n if board[row][col] == 1 and (live_neighbors < 2 or live_neighbors > 3):\\n \\n board[row][col] = -1 # -1 meaning cell is now dead but was originally live\\n \\n # Rule 4\\n if board[row][col] == 0 and live_neighbors == 3:\\n board[row][col] = 2 #2 meaning cell is now live but was originally dead\\n # Get final representation for updated board \\n for row in range(rows):\\n for col in range(cols):\\n \\n if board[row][col] > 0:\\n board[row][col] = 1\\n \\n else:\\n board[row][col] = 0\",\n \"def __get_cell_state(self, y, x):\\n\\t\\tif 0 <= y <= self.__height - 1:\\n\\t\\t\\tif 0 <= x <= self.__width - 1:\\n\\t\\t\\t\\treturn self.__board[y][x]\\n\\t\\treturn 0\",\n \"def game_state(matrix):\\n\\n \\\"\\\"\\\"\\n # To set winning tile\\n for i in range(len(matrix)):\\n for j in range(len(matrix[0])):\\n if matrix[i][j] == 2048:\\n # return 'win'\\n # return 'not over'\\n \\\"\\\"\\\"\\n for i in range(len(matrix)-1):\\n # intentionally reduced to check the row on the right and below\\n # more elegant to use exceptions but most likely this will be their solution\\n for j in range(len(matrix[0])-1):\\n if matrix[i][j] == matrix[i+1][j] or matrix[i][j+1] == matrix[i][j]:\\n return 'not over'\\n for i in range(len(matrix)): # check for any zero entries\\n for j in range(len(matrix[0])):\\n if matrix[i][j] == 0:\\n return 'not over'\\n for k in range(len(matrix)-1): # to check the left/right entries on the last row\\n if matrix[len(matrix)-1][k] == matrix[len(matrix)-1][k+1]:\\n return 'not over'\\n for j in range(len(matrix)-1): # check up/down entries on last column\\n if matrix[j][len(matrix)-1] == matrix[j+1][len(matrix)-1]:\\n return 'not over'\\n return 'lose'\",\n \"def has_cells(self):\\n return len(self._cells) > 0\",\n \"def updateCells(cell_positions):\\n # Build a set of canditates for live cells at the next generation, instead of looking through the whole grid\\n # These will be dead neighbours of living cells\\n possible_future_cells = set()\\n # Make sets of cells to add and remove at the end of the check\\n cells_remove = set()\\n cells_add = set()\\n for cell in cell_positions:\\n # Get adjacent squares\\n neighbours_dict = cellNeighbours(cell)\\n number_live_neighbours = 0\\n # Check which of these corresponds to another living cell\\n for square in neighbours_dict.values():\\n if square in cell_positions:\\n number_live_neighbours+=1\\n else:\\n possible_future_cells.add(square)\\n\\n # Any live cell with fewer than two live neighbours dies, as if caused by under-population\\n if number_live_neighbours<2:\\n cells_remove.add(cell)\\n # Any live cell with two or three live neighbours lives on to the next generation\\n # do nothing\\n # Any live cell with more than three live neighbours dies, as if by overcrowding\\n elif number_live_neighbours>3:\\n cells_remove.add(cell)\\n # Any dead cell with exactly three live neighbours becomes a live cell, as if by reproduction\\n for cell_candidate in possible_future_cells:\\n cell_candidate_neighbours = cellNeighbours(cell_candidate).values()\\n # Count number of live neighbours\\n count = 0\\n for square in cell_candidate_neighbours:\\n if square in cell_positions:\\n count+=1\\n if count == 3:\\n cells_add.add(cell_candidate)\\n # Update cell_positions by removing dead cells and adding new-born cells\\n for cell in cells_add:\\n cell_positions.add(cell)\\n for cell in cells_remove:\\n cell_positions.remove(cell)\\n # Return the update live cell list\\n return cell_positions\",\n \"def getNeighbors(cell, all_living_cells, test=False, test_color=8):\\n neighbors = []\\n NeighborCellGrid = [ # all possible neighbor positions\\n [cell.x - 1, cell.y - 1], # top left\\n [cell.x, cell.y - 1], # top\\n [cell.x + 1, cell.y - 1], # top right\\n [cell.x - 1, cell.y], # left\\n [cell.x + 1, cell.y], # right\\n [cell.x - 1, cell.y + 1], # bottom left\\n [cell.x, cell.y + 1], # bottom\\n [cell.x + 1, cell.y + 1] # bottom right\\n ]\\n count = 0\\n for i in all_living_cells:\\n count+=1\\n if i.id != cell.id and i.alive == True: # not self and pixel is alive\\n if [i.x, i.y] in NeighborCellGrid: # next to\\n neighbors.append(i)\\n if test:\\n for i in NeighborCellGrid:\\n g = simCell(i[0], i[1], color=test_color)\\n test_cells.append(g)\\n return neighbors\",\n \"def new_game(self):\\n self.cells = [] # Array of cells\\n self.frame_count = 0\\n self.database = []\\n self.timer = [Consts[\\\"MAX_TIME\\\"], Consts[\\\"MAX_TIME\\\"]]\\n self.result = None\\n # Define the players first\\n self.cells.append(Cell(0, [Consts[\\\"WORLD_X\\\"] / 4, Consts[\\\"WORLD_Y\\\"] / 2], [0, 0], Consts[\\\"DEFAULT_RADIUS\\\"]))\\n self.cells.append(Cell(1, [Consts[\\\"WORLD_X\\\"] / 4 * 3, Consts[\\\"WORLD_Y\\\"] / 2], [0, 0], Consts[\\\"DEFAULT_RADIUS\\\"]))\\n # Generate a bunch of random cells\\n for i in range(Consts[\\\"CELLS_COUNT\\\"]):\\n if i < 4:\\n rad = 1.5 + (random.random() * 1.5) # Small cells\\n elif i < 10:\\n rad = 10 + (random.random() * 4) # Big cells\\n else:\\n rad = 2 + (random.random() * 9) # Everything else\\n x = Consts[\\\"WORLD_X\\\"] * random.random()\\n y = Consts[\\\"WORLD_Y\\\"] * random.random()\\n cell = Cell(i + 2, [x, y], [(random.random() - 0.5) * 2, (random.random() - 0.5) * 2], rad)\\n safe_dist = Consts[\\\"SAFE_DIST\\\"] + rad\\n while min(map(cell.distance_from, self.cells[:2])) < safe_dist:\\n cell.pos = [\\n Consts[\\\"WORLD_X\\\"] * random.random(),\\n Consts[\\\"WORLD_Y\\\"] * random.random()\\n ]\\n self.cells.append(cell)\",\n \"def draw_occupied_cells(self):\\n reds = [cell for cell in self.game.get_cells() if cell.player == 1]\\n blacks = [cell for cell in self.game.get_cells() if cell.player == 2]\\n nx.draw_networkx_nodes(self.G, pos=self.positions, nodelist=reds,\\n edgecolors='black', node_color='red', linewidths=2)\\n nx.draw_networkx_nodes(self.G, pos=self.positions, nodelist=blacks,\\n edgecolors='black', node_color='black', linewidths=2)\",\n \"def winGame(sub_state):\\n for i in range(sub_state.shape[0] - 4):\\n for j in range(sub_state.shape[1] - 4):\\n\\n horizontal = sub_state[i][j: j+5]\\n if (horizontal == 1).all():\\n return True\\n\\n vertical = [sub_state[i+k, j] for k in range(5)]\\n if (np.array(vertical) == 1).all():\\n return True\\n\\n diagonal = [sub_state[(i+k, j+k)] for k in range(5)]\\n if (np.array(diagonal) == 1).all():\\n return True\\n\\n return False\",\n \"def _create_cells(self):\\n\\t\\tcellId=0\\n\\t\\t# Iterate over all dictionaries\\n\\t\\tfor muscle,muscAfferentDelay in self._infoMuscles:\\n\\t\\t\\tfor cellInfo in self._infoCommonCellsInMuscles:\\n\\t\\t\\t\\tcellClass = cellInfo[0]\\n\\t\\t\\t\\tcellName = cellInfo[1]\\n\\t\\t\\t\\tcellNumber = cellInfo[2]\\n\\t\\t\\t\\tif len(cellInfo)>=4: neuronParam = cellInfo[3]\\n\\t\\t\\t\\telse: neuronParam = None\\n\\t\\t\\t\\tcellId = self._create_cell_population(cellId,muscle,muscAfferentDelay,cellClass,cellName,cellNumber,neuronParam)\\n\\t\\t# Add special cells\\n\\t\\tfor cellInfo in self._infoSpecialCells:\\n\\t\\t\\tgroupOrMuscle = cellInfo[0]\\n\\t\\t\\tcellClass = cellInfo[1]\\n\\t\\t\\tcellName = cellInfo[2]\\n\\t\\t\\tcellNumber = cellInfo[3]\\n\\t\\t\\tif len(cellInfo)>=5: neuronParam = cellInfo[4]\\n\\t\\t\\telse: neuronParam = None\\n\\t\\t\\tmuscAfferentDelay = None\\n\\t\\t\\tcellId = self._create_cell_population(cellId,groupOrMuscle,muscAfferentDelay,cellClass,cellName,cellNumber,neuronParam)\\n\\n\\t\\tself._motoneuronsNames = self._intMotoneuronsNames+self._realMotoneuronsNames\\n\\t\\tself._afferentsNames = self._primaryAfferentsNames+self._secondaryAfferentsNames\",\n \"def test_toggle_cell_in_board(self):\\n self.gameBoard.getGridItem(50, 50).toggle_living()\\n self.assertEqual(self.gameBoard.getGridItem(50,50).is_living(), True)\",\n \"def checkwin(self):\\n w = self.getWidth()\\n h = self.getHeight()\\n numOccupiedCell = 0 # counter for the number of occupied cells (use to detect a terminal condition of the game)\\n for r in range(h):\\n for c in range(w):\\n if self.cell[c][r] == EMPTY:\\n continue # this cell can't be part of winning segment\\n # if we reach this point, the cell is occupied by a player stone\\n numOccupiedCell = numOccupiedCell+1\\n for dr,dc in [(1,0),(0,1),(1,1),(-1,1)]: # direction of search\\n for i in range(NWIN):\\n # test if there exists a segment of NWIN uniformly coloured cells\\n if not(r+i*dr>=0) or not(r+i*dr<h) or not(c+i*dc<w) or not(self.cell[c+i*dc][r+i*dr] == self.cell[c][r]):\\n break # segment broken\\n else:\\n # Python remark: notice that the else is attached to the for loop \\\"for i...\\\"\\n # This block is executed if and only if 'i' arrives at the end of its range \\n return self.cell[c][r] , True # found a winning segment \\n return EMPTY, numOccupiedCell==w*h\",\n \"def play_randomly(self, game):\\n\\n # create a stack of unrevealed cells\\n unrevealed = []\\n\\n for i in xrange(game.rows):\\n for j in xrange(game.cols):\\n unrevealed.append(game.board[i][j])\\n # we will pop the cells from the stack, so randomize their order first\\n random.shuffle(unrevealed)\\n\\n # while the game is being played, choose a random unrevealed cell to reveal next\\n while not game.lost_game and not game.won_game:\\n\\n cell = unrevealed.pop()\\n\\n # before we click the cell, see if only mines remain\\n # if so, flag this cell, otherwise reveal it.\\n if len(unrevealed) < game.mines:\\n game.flag_cell(cell.row, cell.col)\\n print \\\"Flagging\\\", cell\\n\\n # cell may have been previously revealed as a neighbor\\n # if not, reveal it now, otherwise discard the cell and continue\\n elif not cell.revealed:\\n game.reveal_cell(cell.row, cell.col)\\n print \\\"Revealing\\\", cell\\n # update the stack to only contain non-revealed cells\\n # TODO: make this more efficient by not modifying the list in place\\n unrevealed = []\\n for i in xrange(game.rows):\\n for j in xrange(game.cols):\\n if not game.board[i][j].revealed and not game.board[i][j].flagged:\\n unrevealed.append(game.board[i][j])\\n random.shuffle(unrevealed)\\n\\n #check to see if there's any corners that can be flagged as bombs\\n check_corners(game, unrevealed)\\n\\n # draw updated board and pause for a second\\n game.draw_board()\\n if PAUSE == True:\\n time.sleep(1)\",\n \"def _checkCells(self):\\r\\n if(self.startCell.isEmpty()):\\r\\n raise IllegalMoveException(\\\"No pawn in start cell\\\")\\r\\n if(self.endCell.isOccupied()):\\r\\n raise IllegalMoveException(\\\"Targeted cell is already occupied\\\")\\r\\n return True\",\n \"def life_step(state):\\n\\t# For every cell each live cell in any of the 8 neighbouring cells contributes 1 to the sum\\n\\t# Rolling matricies is periodic so this implements periodic boundary conditions\\n\\tnumberOfNeigbours = sum(np.roll(np.roll(state, i, axis=0), j, axis=1)\\n\\t\\t\\t\\t\\t\\t for i in (-1,0,1) for j in (-1,0,1) if (i != 0 or j != 0))\\n\\n\\t# Any live cell with fewer than two live neighbours dies, as if caused by under-population\\n\\tstate = np.where(numberOfNeigbours < 2, 0, state)\\n\\t# Any live cell with more than three live neighbours dies, as if by over-population\\n\\tstate = np.where(numberOfNeigbours > 3, 0, state)\\n\\t# Any dead cell with exactly three live neighbours becomes a live cell, as if by reproduction.\\n\\tstate = np.where(numberOfNeigbours == 3, 1, state)\\n\\n\\treturn state\",\n \"def simulate(screen, clock):\\n old_cells = populate_cells(MAX_X, MAX_Y)\\n new_cells = {}\\n\\n running = True\\n while running:\\n\\n screen.fill((20, 20, 20))\\n\\n for event in pygame.event.get():\\n if event.type == pygame.QUIT:\\n running = False\\n break\\n elif event.type == pygame.KEYDOWN:\\n if event.key == pygame.K_ESCAPE:\\n running = False\\n break\\n\\n for y in range(MAX_Y):\\n for x in range(MAX_X):\\n if old_cells[x, y]:\\n pygame.draw.rect(screen, CELL_COLOR,\\n (x * CELL_WIDTH, y * CELL_HEIGHT,\\n CELL_WIDTH, CELL_HEIGHT))\\n dead_or_alive(old_cells, x, y, new_cells)\\n\\n old_cells = new_cells\\n new_cells = {}\\n clock.tick(200)\\n pygame.display.update()\\n\\n pygame.quit()\",\n \"def setNeighbors(self):\\n for cellIndex in range(len(self.cells)):\\n cell = self.cells[cellIndex]\\n\\n #Checks the 8 cells around the living one. \\n for neighborsX in range(cell.x - 1, cell.x + 2):\\n for neighborsY in range(cell.y - 1, cell.y + 2):\\n\\n #If the position is outside the world, loop around.\\n neighborsX = neighborsX % self.screen.worldSize\\n neighborsY = neighborsY % self.screen.worldSize\\n\\n #Skipping itself. Becouse we do not want to calculate itself as a neighbor\\n if(neighborsX == cell.x and neighborsY == cell.y):\\n continue\\n else:\\n #Checks if a cell exist at neighborsX, neighborsY\\n cellToCheck = self.getCellFromPosition(neighborsX, neighborsY)\\n if(cellToCheck != False):\\n #Add one to the neighbor var if there already exist and cell for the given position.\\n cellToCheck.numOfNeighbor += 1\\n else:\\n #Creates a new cell if it do not exist any.\\n newCell = Cell(self.screen, neighborsX, neighborsY, True)\\n newCell.numOfNeighbor += 1\\n self.cells.append(newCell)\",\n \"def gameOfLife(self, board: List[List[int]]) -> None:\\n if not board or len(board)==0:\\n return \\n\\n rows = len(board)\\n cols = len(board[0])\\n #lives = 0\\n \\n\\n for i in range(rows):\\n for j in range(cols):\\n lives = self.n_neighbors(board,i,j)\\n \\n # Rule 1 and Rule 3\\n if board[i][j]==1 and (lives <2 or lives >3):\\n board[i][j]= 2 # -1 signifies the cell is now dead but originally was live.\\n if board[i][j]== 0 and lives ==3:\\n board[i][j]=3 # signifies the cell is now live but was originally dead.\\n\\n for i in range(rows):\\n for j in range(cols):\\n board[i][j] = board[i][j]%2\\n return board\",\n \"def _generate_cells(self) -> None:\\n for i in range(15):\\n for j in range(15):\\n c = Cell(x=i, y=j)\\n c.answer = self.puzzle.solution[j*self.width+i]\\n self.cells[(j, i)] = c # row, col\",\n \"def check_grid_full(self):\\n for row in self.game_state:\\n for e in row:\\n if e is None:\\n return False\\n return True\",\n \"def _simulate_all_cells(self):\\n for ID in tqdm(self.condition_dict, desc='Simulating cells'):\\n for n in range(len(self.condition_dict[ID])):\\n cond_dict = self.condition_dict[ID][n]\\n g, tc, rsh_mult, rs_mult, Io_mult, Il_mult, nnsvth_mult = cond_dict['E'], cond_dict['Tc'], cond_dict[\\n 'Rsh_mult'], cond_dict['Rs_mult'], cond_dict['Io_mult'], cond_dict['Il_mult'], cond_dict['nnsvth_mult']\\n # calculate the 5 parameters for each set of cell conditions\\n\\n # Eventually, replace this with derived 5-parameters\\n iph, io, rs, rsh, nnsvth = pvlib.pvsystem.calcparams_cec(effective_irradiance=g, temp_cell=tc,\\n alpha_sc=self.cell_parameters['alpha_sc'],\\n a_ref=self.cell_parameters['a_ref'],\\n I_L_ref=self.cell_parameters['I_L_ref'],\\n I_o_ref=self.cell_parameters['I_o_ref'],\\n R_sh_ref=self.cell_parameters['R_sh_ref'],\\n R_s=self.cell_parameters['R_s'],\\n Adjust=self.cell_parameters['Adjust'])\\n rs, rsh, io, iph, nnsvth = rs * rs_mult, rsh * \\\\\\n rsh_mult, io * Io_mult, iph * Il_mult, nnsvth * nnsvth_mult\\n\\n # calculate cell IV curves by condition, rather than by cell index\\n voc_est = pvlib.singlediode.estimate_voc(iph, io, nnsvth)\\n v = voltage_pts(self.num_points_in_IV, voc_est,\\n self.module_parameters['breakdown_voltage'])\\n i = pvlib.singlediode.bishop88_i_from_v(v, iph, io, rs, rsh, nnsvth,\\n breakdown_factor=self.module_parameters['breakdown_factor'],\\n breakdown_voltage=self.module_parameters[\\n 'breakdown_voltage'],\\n breakdown_exp=self.module_parameters['breakdown_exp'])\\n\\n # @dev: Uncomment if debugging pvlib bishop88 simulation results\\n # plt.plot(v,i)\\n # plt.xlim(-5,v[-1])\\n # plt.ylim(0,iph+1)\\n # plt.title(f\\\"{ID}: {n} :: {rs},\\\"\\n # f\\\"{rsh}, {io}, {iph}, {nnsvth}\\\")\\n # plt.show()\\n\\n self.condition_dict[ID][n]['V'] = v\\n self.condition_dict[ID][n]['I'] = i\\n self.condition_dict[ID][n]['E'] = g\\n self.condition_dict[ID][n]['Tc'] = tc\\n return\",\n \"def play_round_Conway_Cell(self):\\n for x in self.board:\\n for f in x:\\n f.live_neighbors = 0\\n\\n for i in range(1, self.cols - 1):\\n for j in range(1, self.rows - 1):\\n status = self.board[i][j].status\\n assert type(status)==int \\n\\n for m in range(i - 1, i + 2):\\n for n in range(j - 1, j + 2):\\n self.board[m][n].live_neighbors += status\\n self.board[i][j].live_neighbors -= status\",\n \"def update_cells(self):\\n mineboard = self.mineboard\\n gameboard = mineboard.gameboard\\n for change in mineboard.changes:\\n i, j = change[0], change[1]\\n text_val = gameboard[i][j]\\n\\n if text_val == 'M':\\n self.canvas.delete(self.cells[i][j])\\n self.cells[i][j] = self.canvas.create_image(\\n 2+j*CELLWIDTH, 2+i*CELLWIDTH, image=EXPLODED, anchor='nw')\\n self.reveal_mines(i, j)\\n\\n elif text_val == 'F':\\n self.canvas.delete(self.cells[i][j])\\n self.cells[i][j] = self.canvas.create_image(\\n 2+j*CELLWIDTH, 2+i*CELLWIDTH, image=FLAG, anchor='nw')\\n\\n elif text_val == ' ':\\n self.canvas.delete(self.cells[i][j])\\n self.cells[i][j] = self.canvas.create_rectangle(\\n 2+j*CELLWIDTH, 2+i*CELLWIDTH, (j+1)*CELLWIDTH, (i+1)*CELLWIDTH, fill=DEFAULT_COLOR, outline=\\\"\\\")\\n\\n elif text_val in ['0', '1', '2', '3', '4', '5', '6', '7', '8']:\\n self.canvas.itemconfig(\\n self.cells[i][j], fill=COLORS[int(text_val)])\\n if text_val != '0':\\n # offset here is by 12 pixels\\n self.canvas.create_text(\\n 2+j*CELLWIDTH+(CELLWIDTH-1)//2, 2+i*CELLWIDTH+(CELLWIDTH-1)//2, anchor='center', text=f\\\"{text_val}\\\")\\n\\n mineboard.changes = [] # removes previous changes\\n if mineboard.gamestate is not None:\\n # if the game has ended displays game end message and buttons\\n self.win_lose_lbl.grid(row=3, column=0, columnspan=4)\\n self.win_lose_msg.set(\\n f\\\"You {self.mineboard.gamestate}! Play again?\\\")\\n self.same_again_bttn.grid(row=4, column=0, columnspan=2)\\n self.play_again_bttn.grid(row=4, column=2, columnspan=2)\",\n \"def make_move(grid, n_columns, n_rows):\\r\\n # Generate the game grid to be manipulated\\r\\n new_grid = [[0] * (n_columns + 1) for i in range(n_rows + 1)]\\r\\n\\r\\n\\r\\n for i in range(n_rows):\\r\\n for j in range(n_columns):\\r\\n upper_left = grid[i-1][j-1] # neighbor to upper left of cell of interest\\r\\n upper = grid[i-1][j] # neighbor above cell of interest\\r\\n upper_right = grid[i-1][j+1] # neighbor to upper right of cell of interest\\r\\n left = grid[i][j-1] # neighbor to left of cell of interest\\r\\n right = grid[i][j+1] # neighbor to right of cell of interest\\r\\n bot_left = grid[i+1][j-1] # neighbor to bottom left cell of interest\\r\\n bot = grid[i+1][j] # neighbor below cell of interest\\r\\n bot_right = grid[i+1][j+1] # neighbor to bottom right of cell of interest\\r\\n\\r\\n # sum of the state of all neighbors\\r\\n on_neighbors = upper_left + upper + upper_right + left + right + bot_left + bot + bot_right\\r\\n\\r\\n # Any ON cell with fewer than two ON neighbors turns OFF\\r\\n if grid[i][j] == 1 and on_neighbors < 2:\\r\\n new_grid[i][j] = 0\\r\\n\\r\\n # Any ON cell with two or three ON neighbours stays ON\\r\\n elif grid[i][j] == 1 and (on_neighbors == 2 or on_neighbors == 3):\\r\\n new_grid[i][j] = 1\\r\\n\\r\\n # Any ON cell with more than three ON neighbors turns OFF\\r\\n elif grid[i][j] == 1 and on_neighbors > 3:\\r\\n new_grid[i][j] = 0\\r\\n\\r\\n # Any OFF cell with three ON neighbors turns ON\\r\\n elif grid[i][j] == 0 and on_neighbors == 3:\\r\\n new_grid[i][j] = 1\\r\\n\\r\\n return new_grid #manipulated game grid\\r\",\n \"def _should_cell_live(self, cell: Cell) -> bool:\\n living_neighbours_count = self._count_living_neighbors(cell)\\n # Any live cell with two or three live neighbours survives\\n if cell.is_alive and living_neighbours_count in [2, 3]:\\n return True\\n # Any dead cell with three live neighbours becomes a live cell\\n if not cell.is_alive and living_neighbours_count == 3:\\n return True\\n # All other live cells die in the next generation. Similarly, all other dead cells stay dead\\n return False\",\n \"def evaluate(self, state):\\n\\t\\ttranspose = state.board.transpose()\\t\\t# columns in state.board = rows in transpose\\n\\t\\tcount = []\\n\\t\\topponentcount = []\\n\\t\\tfor row, column in zip(state.board, transpose):\\n\\t\\t\\trowcounter = collections.Counter(row)\\n\\t\\t\\tcolumncounter = collections.Counter(column)\\n\\t\\t\\tcount.append(rowcounter.get(state.current_player, 0))\\n\\t\\t\\tcount.append(columncounter.get(state.current_player, 0))\\n\\t\\t\\topponentcount.append(rowcounter.get(state.current_player * - 1, 0))\\n\\t\\t\\topponentcount.append(columncounter.get(state.current_player * -1 , 0))\\n\\n\\t\\tY = state.board[:, ::-1]\\n\\t\\tdiagonals = [np.diagonal(state.board), np.diagonal(Y)]\\n\\t\\tmain_diagonal_count = collections.Counter(diagonals[0])\\n\\t\\tsecond_diagonal_count = collections.Counter(diagonals[1])\\n\\t\\tcount.append(main_diagonal_count.get(state.current_player, 0))\\n\\t\\tcount.append(second_diagonal_count.get(state.current_player, 0))\\n\\t\\topponentcount.append(main_diagonal_count.get(state.current_player * - 1, 0))\\n\\t\\topponentcount.append(second_diagonal_count.get(state.current_player * -1, 0))\\n\\n\\t\\t# max(count): maximum number of player's tiles in a row, column, or a diagonal (the highest value is 5)\\n\\t\\t# max(opponentcount): maximum number of opponent's tiles in a row, column, or a diagonal (the highest value is 5)\\n\\t\\tscoremax = 5 ** max(count)\\n\\t\\tscoremin = 5 ** max(opponentcount)\\n\\n\\t\\treturn scoremax - scoremin\",\n \"def gameOfLife(self, board: List[List[int]]) -> None:\\n m = len(board)\\n if m==0:\\n return board\\n n = len(board[0])\\n if n==0:\\n return board\\n def valid(a,b):\\n if 0<=a<m and 0<=b<n:\\n return True\\n mat = [row[:] for row in board] #original copy of the board\\n directions = [(0,-1),(-1,-1),(-1,0),(-1,1),(0,1),(1,1),(1,0),(1,-1)]\\n for i in range(m):\\n for j in range(n):\\n #count how many live=1 or dead=0 cells surrounding cell (i,j)\\n cnt_live=0\\n for direc in directions:\\n if valid(i+direc[0],j+direc[1]):\\n if mat[i+direc[0]][j+direc[1]]==1:\\n cnt_live+=1\\n if mat[i][j]==1 and cnt_live<2 or mat[i][j]==1 and cnt_live>3:\\n board[i][j]=0\\n elif mat[i][j]==1 and 2<=cnt_live<=3 or mat[i][j]==0 and cnt_live==3:\\n board[i][j]=1\",\n \"def apply_move(self, move, state):\\n x, y , heading, grid_data = state\\n map_data = [row[:] for row in grid_data]\\n if move == self.MOVE_FORWARD:\\n # get coordinates for next cell\\n if heading == self.UP:\\n next_y = y - 1\\n next_x = x\\n elif heading == self.DOWN:\\n next_y = y + 1\\n next_x = x\\n elif heading == self.LEFT:\\n next_y = y\\n next_x = x - 1\\n else:\\n next_y = y\\n next_x = x + 1\\n\\n # handle special tile types\\n if map_data[next_y][next_x] == self.ICE_SYMBOL:\\n # handle ice tile - slide until first non-ice tile or blocked\\n if heading == self.UP:\\n for i in range(next_y, -1, -1):\\n if map_data[i][next_x] != self.ICE_SYMBOL:\\n if map_data[i][next_x] == self.WATER_SYMBOL:\\n # slide into water - game over\\n return self.GAME_OVER\\n elif self.cell_is_blocked(i, next_x, map_data):\\n # if blocked, stop on last ice cell\\n next_y = i + 1\\n break\\n else:\\n next_y = i\\n break\\n elif heading == self.DOWN:\\n for i in range(next_y, self.y_size):\\n if map_data[i][next_x] != self.ICE_SYMBOL:\\n if map_data[i][next_x] == self.WATER_SYMBOL:\\n # slide into water - game over\\n return self.GAME_OVER\\n elif self.cell_is_blocked(i, next_x, map_data):\\n # if blocked, stop on last ice cell\\n next_y = i - 1\\n break\\n else:\\n next_y = i\\n break\\n elif heading == self.LEFT:\\n for i in range(next_x, -1, -1):\\n if map_data[next_y][i] != self.ICE_SYMBOL:\\n if map_data[next_y][i] == self.WATER_SYMBOL:\\n # slide into water - game over\\n return self.GAME_OVER\\n elif self.cell_is_blocked(next_y, i, map_data):\\n # if blocked, stop on last ice cell\\n next_x = i + 1\\n break\\n else:\\n next_x = i\\n break\\n else:\\n for i in range(next_x, self.x_size):\\n if map_data[next_y][i] != self.ICE_SYMBOL:\\n if map_data[next_y][i] == self.WATER_SYMBOL:\\n # slide into water - game over\\n return self.GAME_OVER\\n elif self.cell_is_blocked(next_y, i, map_data):\\n # if blocked, stop on last ice cell\\n next_x = i - 1\\n break\\n else:\\n next_x = i\\n break\\n if map_data[next_y][next_x] == self.TELEPORT_SYMBOL:\\n # handle teleport - find the other teleporter\\n tpy, tpx = (None, None)\\n for i in range(self.y_size):\\n for j in range(self.x_size):\\n if map_data[i][j] == self.TELEPORT_SYMBOL and (i != next_y or j != next_x):\\n tpy, tpx = (i, j)\\n break\\n if tpy is not None:\\n break\\n if tpy is None:\\n raise Exception(\\\"LaserTank Map Error: Unmatched teleport symbol\\\")\\n next_y, next_x = (tpy, tpx)\\n else:\\n # if not ice or teleport, perform collision check\\n if self.cell_is_blocked(next_y, next_x, map_data):\\n return self.COLLISION\\n\\n # check for game over conditions\\n if self.cell_is_game_over(next_y, next_x, map_data):\\n return self.GAME_OVER\\n\\n # no collision and no game over - update player position\\n y = next_y\\n x = next_x\\n return (x, y, heading, map_data)\\n\\n elif move == self.TURN_LEFT:\\n # no collision or game over possible\\n if heading == self.UP:\\n heading = self.LEFT\\n elif heading == self.DOWN:\\n heading = self.RIGHT\\n elif heading == self.LEFT:\\n heading = self.DOWN\\n else:\\n heading = self.UP\\n return (x, y, heading, map_data)\\n\\n elif move == self.TURN_RIGHT:\\n # no collision or game over possible\\n if heading == self.UP:\\n heading = self.RIGHT\\n elif heading == self.DOWN:\\n heading = self.LEFT\\n elif heading == self.LEFT:\\n heading = self.UP\\n else:\\n heading = self.DOWN\\n return (x, y, heading, map_data)\\n\\n elif move == self.SHOOT_LASER:\\n # set laser direction\\n if heading == self.UP:\\n laserheading = self.UP\\n dy, dx = (-1, 0)\\n elif heading == self.DOWN:\\n laserheading = self.DOWN\\n dy, dx = (1, 0)\\n elif heading == self.LEFT:\\n laserheading = self.LEFT\\n dy, dx = (0, -1)\\n else:\\n laserheading = self.RIGHT\\n dy, dx = (0, 1)\\n\\n # loop until laser blocking object reached\\n ly, lx = (y, x)\\n while True:\\n ly += dy\\n lx += dx\\n\\n # handle boundary and immovable obstacles\\n if ly < 0 or ly >= self.y_size or \\\\\\n lx < 0 or lx >= self.x_size or \\\\\\n map_data[ly][lx] == self.OBSTACLE_SYMBOL:\\n # laser stopped without effect\\n return self.COLLISION\\n\\n # handle movable objects\\n elif self.cell_is_laser_movable(ly, lx, laserheading, map_data):\\n # check if tile can be moved without collision\\n if self.cell_is_blocked(ly + dy, lx + dx, map_data) or \\\\\\n map_data[ly + dy][lx + dx] == self.ICE_SYMBOL or \\\\\\n map_data[ly + dy][lx + dx] == self.TELEPORT_SYMBOL or \\\\\\n map_data[ly + dy][lx + dx] == self.FLAG_SYMBOL or \\\\\\n (ly + dy == y and lx + dx == x):\\n # tile cannot be moved\\n return self.COLLISION\\n else:\\n old_symbol = map_data[ly][lx]\\n map_data[ly][lx] = self.LAND_SYMBOL\\n if map_data[ly + dy][lx + dx] == self.WATER_SYMBOL:\\n # if new bridge position is water, convert to land tile\\n if old_symbol == self.BRIDGE_SYMBOL:\\n map_data[ly + dy][lx + dx] = self.LAND_SYMBOL\\n # otherwise, do not replace the old symbol\\n else:\\n # otherwise, move the tile forward\\n map_data[ly + dy][lx + dx] = old_symbol\\n break\\n\\n # handle bricks\\n elif map_data[ly][lx] == self.BRICK_SYMBOL:\\n # remove brick, replace with land\\n map_data[ly][lx] = self.LAND_SYMBOL\\n break\\n\\n # handle facing anti-tanks\\n elif (map_data[ly][lx] == self.ANTI_TANK_UP_SYMBOL and laserheading == self.DOWN) or \\\\\\n (map_data[ly][lx] == self.ANTI_TANK_DOWN_SYMBOL and laserheading == self.UP) or \\\\\\n (map_data[ly][lx] == self.ANTI_TANK_LEFT_SYMBOL and laserheading == self.RIGHT) or \\\\\\n (map_data[ly][lx] == self.ANTI_TANK_RIGHT_SYMBOL and laserheading == self.LEFT):\\n # mark anti-tank as destroyed\\n map_data[ly][lx] = self.ANTI_TANK_DESTROYED_SYMBOL\\n break\\n\\n # handle player laser collision\\n elif ly == y and lx == x:\\n return self.GAME_OVER\\n\\n # handle facing mirrors\\n elif (map_data[ly][lx] == self.MIRROR_UL_SYMBOL and laserheading == self.RIGHT) or \\\\\\n (map_data[ly][lx] == self.MIRROR_UR_SYMBOL and laserheading == self.LEFT):\\n # new direction is up\\n dy, dx = (-1, 0)\\n laserheading = self.UP\\n elif (map_data[ly][lx] == self.MIRROR_DL_SYMBOL and laserheading == self.RIGHT) or \\\\\\n (self.grid_data[ly][lx] == self.MIRROR_DR_SYMBOL and laserheading == self.LEFT):\\n # new direction is down\\n dy, dx = (1, 0)\\n laserheading = self.DOWN\\n elif (map_data[ly][lx] == self.MIRROR_UL_SYMBOL and laserheading == self.DOWN) or \\\\\\n (map_data[ly][lx] == self.MIRROR_DL_SYMBOL and laserheading == self.UP):\\n # new direction is left\\n dy, dx = (0, -1)\\n laserheading = self.LEFT\\n elif (map_data[ly][lx] == self.MIRROR_UR_SYMBOL and laserheading == self.DOWN) or \\\\\\n (map_data[ly][lx] == self.MIRROR_DR_SYMBOL and laserheading == self.UP):\\n # new direction is right\\n dy, dx = (0, 1)\\n laserheading = self.RIGHT\\n # do not terminate laser on facing mirror - keep looping\\n\\n # check for game over condition after effect of laser\\n if self.cell_is_game_over(y, x, map_data):\\n return self.GAME_OVER\\n return (x, y, heading, map_data)\\n return self.SUCCESS\",\n \"def cell(x, y):\\n try:\\n if cells[y][x]['filled'] == 1:\\n return # this has already been processed\\n except IndexError:\\n return\\n cells[y][x]['filled'] = 1 # this cell is now filled\\n\\n nn = []\\n for nx, ny in neighbours(x, y):\\n try:\\n if cells[ny][nx]['filled']:\\n nn.append(cells[ny][nx])\\n except IndexError:\\n continue\\n \\n c = 0 # colour weighting\\n \\n #------ Flippedness\\n flipped = sum([i['inverted'] for i in nn if i['inverted']])\\n cells[y][x]['inverted'] = (randint(0, 3) + flipped) % 4\\n \\n #------- Colour calculation\\n avg_colour = sum([i['colour'][0] for i in nn]) / len(nn)\\n avg_sat = sum([i['colour'][1] for i in nn]) / len(nn)\\n avg_bri = sum([i['colour'][2] for i in nn]) / len(nn)\\n \\n # small chance of going totally random otherwise small variation from neighbours\\n if random(100) > 90:\\n h = randint(0, 100)\\n s = randint(0, 100)\\n b = randint(0, 100)\\n else:\\n h = (avg_colour + randint(-15, 15)) % 100\\n s = (avg_sat + randint(-15, 15)) % 100\\n b = (avg_bri + randint(-15, 15)) % 100\\n cells[y][x]['colour'] = (h, s, b)\\n \\n #------- Alpha calculation\\n d = sqrt((x*cell_size - rx)**2 + (y*cell_size - ry)**2) # distance from epicenter\\n mx = sqrt((w-rx*cell_size)**2 + (h-ry*cell_size)**2)\\n a = d/sqrt(w**2+h**2)*255\\n cells[y][x]['alpha'] = a\\n \\n for cx,cy in neighbours(x, y):\\n cell(cx, cy)\",\n \"def is_fixed_state( previous_live, live_cells ):\\n fixed = False\\n if previous_live[0].size == live_cells[0].size:\\n if previous_live[1].size == live_cells[1].size:\\n if (previous_live[0]==live_cells[0]).all():\\n if (previous_live[1]==live_cells[1]).all():\\n fixed = True\\n return fixed\",\n \"def get_next_state(self, state, x, y):\\n my_board = state\\n game_over = False\\n if is_mine(self.board, x, y):\\n my_board[x, y] = MINE\\n game_over = True\\n else:\\n my_board[x, y] = self.count_neighbour_mines(x, y)\\n if my_board[x, y] == 0:\\n my_board = self.open_neighbour_cells(my_board, x, y)\\n self.my_board = my_board\\n return my_board, game_over\",\n \"def get_next_state(self, state, x, y):\\n my_board = state\\n game_over = False\\n if is_mine(self.board, x, y):\\n my_board[x, y] = MINE\\n game_over = True\\n else:\\n my_board[x, y] = self.count_neighbour_mines(x, y)\\n if my_board[x, y] == 0:\\n my_board = self.open_neighbour_cells(my_board, x, y)\\n self.my_board = my_board\\n return my_board, game_over\",\n \"def computer_play( game ):\\n\\n grid = game.get_grid()\\n\\n diag = game.checkDiagonals()\\n row = game.checkRows()\\n column = game.checkColumns()\\n\\n if isinstance(diag, tuple):\\n \\n for x in diag[1]:\\n try:\\n x = int(x)\\n print(x)\\n if isinstance(x, int):\\n if game.set_mark('O', x):\\n return\\n\\n except ValueError:\\n continue\\n\\n elif isinstance(row, tuple):\\n\\n for x in row[1]:\\n try:\\n x = int(x)\\n if isinstance(x, int):\\n if game.set_mark('O', x):\\n return\\n\\n except ValueError:\\n continue\\n\\n elif isinstance(column, tuple):\\n\\n for x in column[1]:\\n try:\\n x = int(x)\\n if isinstance(x, int):\\n if game.set_mark('O', x):\\n return\\n\\n except ValueError:\\n continue \\n\\n for x in list(range(1,10)):\\n if game.set_mark('O', x):\\n return\\n else:\\n continue\",\n \"def Get_empty_cells(difficulty, size):\\n if(difficulty == 'beginner'):\\n return size**2 - 50\\n elif (difficulty == 'easy'):\\n return size**2 - 40\\n elif (difficulty == 'medium'):\\n return size**2 - 33\\n elif (difficulty == 'hard'):\\n return size**2 - 26\\n elif (difficulty == 'hell'):\\n return size**2 - 17\",\n \"def getGameState(self):\\n row1 = [0, 0, 0]\\n row2 = [0, 0, 0]\\n row3 = [0, 0, 0]\\n tilePosStatement = Statement()\\n posTerm1 = Term('?x')\\n posTerm2 = Term('?y')\\n posTerm3 = Term('?tile')\\n tilePosStatement.terms = (posTerm1, posTerm2, posTerm3)\\n tilePosStatement.predicate = 'tilePos'\\n for fact in self.kb.facts:\\n if match(fact.statement, tilePosStatement):\\n if fact.statement.terms[2] == Term(Constant('tile1')):\\n term = 1\\n if fact.statement.terms[2] == Term(Constant('tile2')):\\n term = 2\\n if fact.statement.terms[2] == Term(Constant('tile3')):\\n term = 3\\n if fact.statement.terms[2] == Term(Constant('tile4')):\\n term = 4\\n if fact.statement.terms[2] == Term(Constant('tile5')):\\n term = 5\\n if fact.statement.terms[2] == Term(Constant('tile6')):\\n term = 6\\n if fact.statement.terms[2] == Term(Constant('tile7')):\\n term = 7\\n if fact.statement.terms[2] == Term(Constant('tile8')):\\n term = 8\\n if fact.statement.terms[2] == Term(Constant('empty')):\\n term = -1\\n if fact.statement.terms[0] == Term(Constant('pos1')):\\n col = 0\\n elif fact.statement.terms[0] == Term(Constant('pos2')):\\n col = 1\\n elif fact.statement.terms[0] == Term(Constant('pos3')):\\n col = 2\\n if fact.statement.terms[1] == Term(Constant('pos1')):\\n row1[col] = term\\n\\n elif fact.statement.terms[1] == Term(Constant('pos2')):\\n row2[col] = term\\n\\n elif fact.statement.terms[1] == Term(Constant('pos3')):\\n row3[col] = term\\n\\n row1 = tuple(row1)\\n row2 = tuple(row2)\\n row3 = tuple(row3)\\n result = (row1, row2, row3)\\n return result\\n\\n ### Student code goes here\",\n \"def occupied_cells(self):\\n\\n for lm in self.landmarks:\\n if self.cell_size < 1:\\n # expand the range the landmark exists\\n lm_x_range = np.arange(lm[0]-self.R, lm[0]+self.R, self.cell_size)\\n lm_y_range = np.arange(lm[1]-self.R, lm[1]+self.R, self.cell_size)\\n\\n # loop through expanded ranges and compute grid positions\\n for lm_x in lm_x_range:\\n for lm_y in lm_y_range:\\n\\n row, col = self.cell_index([lm_x, lm_y])\\n\\n # apply cost of occupied cell\\n try:\\n self.world[row][col] = 1000\\n except IndexError:\\n pass\\n\\n else:\\n # apply cost of occupied cell\\n row, col = self.cell_index(lm)\\n try:\\n self.world[row][col] = 1000\\n except IndexError:\\n pass\",\n \"def gameOfLife(self, board: List[List[int]]) -> None:\\n m = len(board)\\n if m==0:\\n return board\\n n = len(board[0])\\n if n==0:\\n return board\\n def valid(a,b):\\n if 0<=a<m and 0<=b<n:\\n return True\\n directions = [(0,-1),(-1,-1),(-1,0),(-1,1),(0,1),(1,1),(1,0),(1,-1)]\\n for i in range(m):\\n for j in range(n):\\n #count how many live=1 or dead=0 cells surrounding cell (i,j)\\n cnt_live=0\\n for direc in directions:\\n if valid(i+direc[0],j+direc[1]):\\n if board[i+direc[0]][j+direc[1]]==1 or board[i+direc[0]][j+direc[1]]==-1:\\n cnt_live+=1\\n if (board[i][j]==1 and cnt_live<2) or \\\\\\n (board[i][j]==1 and cnt_live>3):\\n board[i][j]=-1\\n elif board[i][j]==0 and cnt_live==3:\\n board[i][j]=2\\n for i in range(m):\\n for j in range(n):\\n if board[i][j]==-1:\\n board[i][j]=0\\n elif board[i][j]==2:\\n board[i][j]=1\",\n \"def advance_board(self):\\n # We can advance the board using a pretty simple convolution,\\n # so we don't have to execute a lot of loops in python.\\n # Of course, this probably won't be sufficient for extremely\\n # large boards.\\n self.num_steps += 1\\n board = self.board\\n cfilter = np.array([[1,1,1],[1,0,1],[1,1,1]], dtype=np.uint16)\\n\\n alive = board & CellTypes.alive > 0\\n spawning = board & CellTypes.spawning > 0\\n frozen = board & CellTypes.frozen > 0\\n\\n can_die = ~frozen & (\\n convolve2d(board & CellTypes.preserving, cfilter) == 0)\\n can_grow = ~frozen & (\\n convolve2d(board & CellTypes.inhibiting, cfilter) == 0)\\n\\n num_neighbors = convolve2d(alive, cfilter)\\n num_spawn = convolve2d(spawning, cfilter)\\n spawn_prob = 1 - (1 - self.spawn_prob)**num_spawn\\n has_spawned = coinflip(spawn_prob, board.shape)\\n\\n born_rule = np.zeros(9, dtype=bool)\\n born_rule[list(self.born_rule)] = True\\n dead_rule = np.ones(9, dtype=bool)\\n dead_rule[list(self.survive_rule)] = False\\n\\n new_alive = (born_rule[num_neighbors] | has_spawned) & ~alive & can_grow\\n new_dead = dead_rule[num_neighbors] & alive & can_die\\n\\n new_flags = np.zeros_like(board)\\n color_weights = 1 * alive + 2 * spawning\\n for color in CellTypes.colors:\\n # For each of the colors, see if there are two or more neighbors\\n # that have it. If so, any new cells (whether born or spawned)\\n # will also get that color.\\n has_color = board & color > 0\\n new_color = convolve2d(has_color * color_weights, cfilter) >= 2\\n new_flags += color * new_color\\n indestructible = alive & (board & CellTypes.destructible == 0)\\n new_flags += CellTypes.destructible * (convolve2d(indestructible, cfilter) < 2)\\n\\n board *= ~(new_alive | new_dead)\\n board += new_alive * (CellTypes.alive + new_flags)\",\n \"def is_won(self):\\n combinations = [*[(i, i + 3, i + 6) for i in range(3)],\\n *[(i*3, i*3 + 1, i*3 + 2) for i in range(3)],\\n (0, 4, 8), (2, 4, 6)]\\n\\n win = [*filter(lambda x: self[x[0]] == self[x[1]] == self[x[2]] and\\n self[x[0]] != self.CELL_EMPTY, combinations)]\\n return self[win[0][0]] if len(win) > 0 else self.CELL_EMPTY\",\n \"def makeGrid(self, width, height, rewardLocs, exit, nPick=1, nAux=1, walls=[]):\\n # Make mapping from coordinate (x, y, (takenreward1, takenreward2, ...))\\n # to state number, and vice-versa.\\n rTaken = iter([(),])\\n for nPicked in range(1, nPick+1):\\n rTaken = itertools.chain(rTaken, \\n myCombinations(rewardLocs, r=nPicked)\\n )\\n # Iterators are hard to reset, so we list it.\\n rTaken = list(rTaken)\\n\\n # Mappings from state to coordinates, vice-versa\\n coordToState = {}\\n stateToCoord = {}\\n stateIdx = 0\\n for x in range(width):\\n for y in range(height):\\n for stuff in rTaken:\\n for holding in self.holdingPossibilities:\\n coordToState[(x, y, stuff, holding)] = stateIdx\\n stateToCoord[stateIdx] = (x, y, stuff, holding)\\n stateIdx += 1\\n self.deadEndState = stateIdx\\n\\n # Actually make the transition function\\n def trans(f, p): \\n aux = p\\n (x, y, stuff, holding) = stateToCoord[f]\\n actionMap = {}\\n default = {(f, aux): 1}\\n # Make the transition dictionary if the dead-end state (state width*height)\\n if f == self.F-1:\\n for action in range(5):\\n actionMap[action] = default\\n return actionMap\\n\\n # Otherwise, determine directions of motion, etc. \\n for i in range(4):\\n actionMap[i] = default\\n if x != 0 and ((x-1, y) not in walls):\\n actionMap[0] = {(coordToState[(x-1,y,stuff, holding)], aux): 1}\\n if x < width-1 and ((x+1, y) not in walls):\\n actionMap[1] = {(coordToState[(x+1,y,stuff, holding)], aux): 1}\\n if y != 0 and ((x, y-1) not in walls):\\n actionMap[2] = {(coordToState[(x,y-1,stuff, holding)], aux): 1}\\n if y < height-1 and ((x, y+1) not in walls):\\n actionMap[3] = {(coordToState[(x,y+1,stuff, holding)], aux): 1}\\n # What happens when the agent uses action 4?\\n if (x, y) == exit:\\n # Some cases, depending on self.oneAtATime\\n if not self.oneAtATime:\\n # The agent is leaving.\\n actionMap[4] = {(self.deadEndState, aux): 1}\\n else:\\n # The agent is dropping off a reward. holeFiller will\\n # take care of the reward value.\\n if len(stuff) >= nPick:\\n # The agent is not allowed to pick up more stuff\\n actionMap[4] = {(self.deadEndState, aux): 1}\\n else:\\n # The agent drops off the object.\\n actionMap[4] = {(coordToState[(x,y,stuff, -1)], aux): 1}\\n elif (x, y) not in rewardLocs:\\n # No reward to pick up. Do nothing.\\n actionMap[4] = default\\n elif (x, y) in stuff:\\n # This reward has already been used. Do nothing.\\n actionMap[4] = default\\n elif len(stuff) >= nPick or (holding != -1 and holding < len(stuff)\\n and self.oneAtATime):\\n # The agent has its hands full.\\n actionMap[4] = default\\n else:\\n # The agent is allowed to pick up an object.\\n newStuff = tuple(sorted(list(stuff) + [(x, y)]))\\n if self.oneAtATime:\\n newHoldingIdx = newStuff.index((x, y))\\n else:\\n newHoldingIdx = -1\\n actionMap[4] = {(coordToState[(x, y, newStuff, newHoldingIdx)], aux): 1}\\n return actionMap\\n\\n # Man, I'm outputting a lot of stuff.\\n # coordToState[(x, y, rewardsLeft, holding)] -> index of this state\\n # stateToCoord[index] -> (x, y, rewardsLeft, holding)\\n # rTaken is a list of all possible combinations of leftover rewards.\\n return (trans, coordToState, stateToCoord, rTaken)\",\n \"def state(self) -> PuzzleState:\\n\\t\\tfor cell in self._cells:\\n\\t\\t\\tif not (cell.value() or any(cell.potential_values())):\\n\\t\\t\\t\\treturn PuzzleState.Conflict\\n\\n\\t\\tfor group in self._groups:\\n\\t\\t\\tif len(group.unsolved_cells()) > 0:\\n\\t\\t\\t\\treturn PuzzleState.Unsolved\\n\\n\\t\\t\\tdistinct_values = set()\\n\\t\\t\\tfor cell in group:\\n\\t\\t\\t\\tvalue = cell.value()\\n\\t\\t\\t\\tif value in distinct_values:\\n\\t\\t\\t\\t\\treturn PuzzleState.Conflict\\n\\t\\t\\t\\tdistinct_values.add(value)\\n\\n\\t\\treturn PuzzleState.Solved\",\n \"def generate_next_state(self) -> Dict[Tuple[int, int], Cell]:\\n next_state: Dict[Tuple[int, int], Cell] = {}\\n for living_cell in self.living_cells.values():\\n for x in range(living_cell.x - 1, living_cell.x + 2):\\n for y in range(living_cell.y - 1, living_cell.y + 2):\\n cell = Cell(x, y)\\n if (x, y) in self.living_cells.keys():\\n cell = self.living_cells[x, y]\\n if self._should_cell_live(cell):\\n next_state[x, y] = Cell(x, y, True)\\n \\n self.living_cells = next_state\\n \\n return self.living_cells\",\n \"def draw_grid(self) -> None:\\n grid = self.life.curr_generation\\n for row in range(self.cell_height):\\n for column in range(self.cell_width):\\n if grid[row][column] == 1:\\n color = \\\"green\\\"\\n else:\\n color = \\\"white\\\"\\n pygame.draw.rect(\\n self.screen,\\n pygame.Color(color),\\n (column * self.cell_size, row * self.cell_size, self.cell_size, self.cell_size),\\n )\",\n \"def cell_is_game_over(self, y, x, map_data):\\n # check for water\\n if map_data[y][x] == self.WATER_SYMBOL:\\n return True\\n\\n # check for anti-tank\\n # up direction\\n for i in range(y, -1, -1):\\n if map_data[i][x] == self.ANTI_TANK_DOWN_SYMBOL:\\n return True\\n # if blocked, can stop checking for anti-tank\\n if self.cell_is_blocked(i, x, map_data):\\n break\\n\\n # down direction\\n for i in range(y, self.y_size):\\n if map_data[i][x] == self.ANTI_TANK_UP_SYMBOL:\\n return True\\n # if blocked, can stop checking for anti-tank\\n if self.cell_is_blocked(i, x, map_data):\\n break\\n\\n # left direction\\n for i in range(x, -1, -1):\\n if map_data[y][i] == self.ANTI_TANK_RIGHT_SYMBOL:\\n return True\\n # if blocked, can stop checking for anti-tank\\n if self.cell_is_blocked(y, i, map_data):\\n break\\n\\n # right direction\\n for i in range(x, self.x_size):\\n if map_data[y][i] == self.ANTI_TANK_LEFT_SYMBOL:\\n return True\\n # if blocked, can stop checking for anti-tank\\n if self.cell_is_blocked(y, i, map_data):\\n break\\n\\n # no water or anti-tank danger\\n return False\",\n \"def test_solo_cell():\\n cell = c6.Cell(loc=[1, 1])\\n for i in range(10):\\n cell.step()\",\n \"def test_multigrid_calculates_neighbours_correctly():\\n\\n # create a grid which will result in 9 cells\\n h = 64\\n img_dim = (3 * h + 1, 3 * h + 1)\\n amg = mg.MultiGrid(img_dim, h, WS=127)\\n\\n # check that each cell has the expected neighbours\\n print(amg.n_cells)\\n\\n # expected neieghbours left to right, bottom to top\\n cells = [{\\\"north\\\": amg.cells[3], \\\"east\\\": amg.cells[1], \\\"south\\\": None, \\\"west\\\": None}, # bl\\n {\\\"north\\\": amg.cells[4], \\\"east\\\": amg.cells[2],\\n \\\"south\\\": None, \\\"west\\\": amg.cells[0]}, # bm\\n {\\\"north\\\": amg.cells[5], \\\"east\\\": None,\\n \\\"south\\\": None, \\\"west\\\": amg.cells[1]}, # br\\n {\\\"north\\\": amg.cells[6], \\\"east\\\": amg.cells[4],\\n \\\"south\\\": amg.cells[0], \\\"west\\\": None}, # ml\\n {\\\"north\\\": amg.cells[7], \\\"east\\\": amg.cells[5],\\n \\\"south\\\": amg.cells[1], \\\"west\\\": amg.cells[3]}, # mm\\n {\\\"north\\\": amg.cells[8], \\\"east\\\": None,\\n \\\"south\\\": amg.cells[2], \\\"west\\\": amg.cells[4]}, # mr\\n # tl\\n {\\\"north\\\": None, \\\"east\\\": amg.cells[7],\\n \\\"south\\\": amg.cells[3], \\\"west\\\": None},\\n # tm\\n {\\\"north\\\": None,\\n \\\"east\\\": amg.cells[8], \\\"south\\\": amg.cells[4], \\\"west\\\": amg.cells[6]},\\n {\\\"north\\\": None, \\\"east\\\": None,\\n \\\"south\\\": amg.cells[5], \\\"west\\\": amg.cells[7]}, # tr\\n ]\\n\\n for ii, (gc, cell) in enumerate(zip(amg.cells, cells)):\\n print(ii)\\n assert gc.north == cell['north']\\n assert gc.east == cell['east']\\n assert gc.south == cell['south']\\n assert gc.west == cell['west']\",\n \"def _compute_world_params(self) -> None:\\n\\n self.states = []\\n for row in range(self.grid_height):\\n for col in range(self.grid_width):\\n cell = row * self.grid_width + col\\n cell_type = self.grid[cell]\\n\\n possible_actions = {\\n Action.up: self._get_action(max(row - 1, 0) * self.grid_width + col),\\n Action.down: self._get_action(min(row + 1, self.grid_height - 1) * self.grid_width + col),\\n Action.right: self._get_action(row * self.grid_width + min(col + 1, self.grid_width - 1)),\\n Action.left: self._get_action(row * self.grid_width + max(col - 1, 0))\\n }\\n\\n self.states.append(State(cell, possible_actions, cell_type))\",\n \"def updateGameState(self):\\n boardArray = self._board.get_board()\\n \\n if self.state is self._BEGIN:\\n\\n for i in [1, self._board.get_board_size() - 2]:\\n for j in range(1, self._board.get_board_size() - 1):\\n\\n if boardArray[i][j] != self._board._EMPTY:\\n self.state = self._MIDDLE\\n return\\n\\n if boardArray[j][i] != self._board._EMPTY:\\n self.state = self._MIDDLE\\n return\\n\\n\\n elif self.state is self._MIDDLE:\\n nbPieces = self._board.get_total_pieces()\\n\\n if nbPieces >= self._board.get_board_size()**2 - ENDGAME:\\n self.state = self._END\\n return\",\n \"def __init__(self):\\n pygame.init()\\n self.settings = Settings()\\n self.number_cells_x = int(input(\\\"Enter number of cells in a row: \\\"))\\n self.cell_width = float(self.settings.screen_width // self.number_cells_x)\\n #print(self.cell_width)\\n self.number_cells_y = int(self.settings.screen_height // self.cell_width)\\n\\n self.screen = pygame.display.set_mode((self.settings.screen_width,self.settings.screen_height))\\n pygame.display.set_caption(\\\"Game of Life\\\")\\n\\n self.cells = []\\n self.to_be_updated = []\\n self._create_cells()\\n\\n self.bg_colour = (self.settings.bg_colour)\\n self.waiting = True\",\n \"def test_print_cell(self):\\n self.assertEqual(str(self.deadCell), \\\" \\\")\\n self.assertEqual(str(self.livingCell), \\\"X\\\")\",\n \"def generate_grains(self, cells):\\n\\t\\tfor cell_num in range(cells):\\n\\t\\t\\trandom_row = random.randrange(0,self.space.shape[0],1)\\n\\t\\t\\tsample_cell = np.random.choice(self.space[random_row],1)\\n\\t\\t\\tsample_cell = sample_cell[0]\\n\\t\\t\\twhile sample_cell.state != 0:\\n\\t\\t\\t\\trandom_row = random.randrange(0,self.space.shape[0],1)\\n\\t\\t\\t\\tsample_cell = np.random.choice(self.space[random_row],1)\\n\\t\\t\\t\\tsample_cell = sample_cell[0]\\n\\t\\t\\tsample_cell.change_state(self.init_time ,cell_num)\",\n \"def actions(self, state):\\n # actions = ['Left', 'Down', 'Right', 'Up']\\n\\n\\n adjacent_cell_up = cell_adjacent(state[0], \\\"Up\\\")\\n adjacent_cell_down = cell_adjacent(state[0], \\\"Down\\\")\\n adjacent_cell_left = cell_adjacent(state[0], \\\"Left\\\")\\n adjacent_cell_right = cell_adjacent(state[0], \\\"Right\\\")\\n\\n #Checking of macro is true\\n if not self.macro:\\n worker_actions = []\\n # check if valid cell is above.\\n if adjacent_cell_up not in self.warehouse.walls:\\n worker_actions.append (\\\"Up\\\")\\n\\n # check if valid cell is below.\\n if adjacent_cell_down not in self.warehouse.walls:\\n worker_actions.append(\\\"Down\\\")\\n\\n # check if valid cell is to the left\\n if adjacent_cell_left not in self.warehouse.walls:\\n worker_actions.append(\\\"Left\\\")\\n\\n # check if valid cell is to the right\\n if adjacent_cell_right not in self.warehouse.walls:\\n worker_actions.append(\\\"Right\\\")\\n\\n return worker_actions\\n\\n else:\\n box = []\\n box_all = []\\n #Checking if boxes are allowed in taboo area\\n if not self.allow_taboo_push:\\n for boxes in state[1:]:\\n\\n # check if valid cell is above.\\n adjacent_box_up = cell_adjacent(boxes, \\\"Up\\\")\\n #Checks if there is a taboo square or wall or box in next cell\\n if adjacent_box_up not in self.taboo_list and adjacent_box_up not in self.warehouse.walls and adjacent_box_up not in state[1:]:\\n box.append(\\\"Up\\\")\\n\\n # check if valid cell is bellow.\\n adjacent_box_down = cell_adjacent(boxes, \\\"Down\\\")\\n #Checks if there is a taboo square or wall or box in next cell\\n if adjacent_box_down not in self.taboo_list and adjacent_box_down not in self.warehouse.walls and adjacent_box_down not in state[1:]:\\n box.append(\\\"Down\\\")\\n\\n # check if valid cell is to the left\\n adjacent_box_left = cell_adjacent(boxes, \\\"Left\\\")\\n #Checks if there is a taboo square or wall or box in next cell\\n if adjacent_box_left not in self.taboo_list and adjacent_box_left not in self.warehouse.walls and adjacent_box_left not in state[1:]:\\n box.append(\\\"Left\\\")\\n\\n # check if valid cell is to the right\\n adjacent_box_right = cell_adjacent(boxes, \\\"Right\\\")\\n #Checks if there is a taboo square or wall or box in next cell\\n if adjacent_box_right not in self.taboo_list and adjacent_box_right not in self.warehouse.walls and adjacent_box_right not in state[1:]:\\n box.append(\\\"Right\\\")\\n box_all.append(box)\\n else:\\n for boxes in state[1:]:\\n # check if valid cell is above.\\n adjacent_box_up = cell_adjacent(boxes, \\\"Up\\\")\\n #Checks if there is a or wall or box in next cell\\n if adjacent_box_up not in self.warehouse.walls and adjacent_box_up not in state[1:]:\\n box.append(\\\"Up\\\")\\n\\n # check if valid cell is bellow.\\n adjacent_box_down = cell_adjacent(boxes, \\\"Down\\\")\\n #Checks if there is a or wall or box in next cell\\n if adjacent_box_down not in self.warehouse.walls and adjacent_box_down not in state[1:]:\\n box.append(\\\"Down\\\")\\n\\n # check if valid cell is to the left.\\n adjacent_box_left = cell_adjacent(boxes, \\\"Left\\\")\\n #Checks if there is a or wall or box in next cell\\n if adjacent_box_left not in self.warehouse.walls and adjacent_box_left not in state[1:]:\\n box.append(\\\"Left\\\")\\n\\n # check if valid cell is to the right.\\n adjacent_box_right = cell_adjacent(boxes, \\\"Right\\\")\\n #Checks if there is a or wall or box in next cell\\n if adjacent_box_right not in self.warehouse.walls and adjacent_box_right not in state[1:]:\\n box.append(\\\"Right\\\")\\n box_all.append(box)\\n return actions\",\n \"def get_effective_cell_moves(state, cell, player):\\n board = state.get_board()\\n if board.is_cell_on_board(cell):\\n possibles_moves = YoteRules._get_rules_possibles_moves(cell, board.board_shape)\\n effective_moves = []\\n i, j = cell\\n for move in possibles_moves:\\n if board.is_empty_cell(move):\\n effective_moves.append(move)\\n elif board.get_cell_color(move) == Color(player * -1):\\n k, l = move\\n if i == k and j < l and board.is_empty_cell((i, j + 2)):\\n effective_moves.append((i, j + 2))\\n elif i == k and l < j and board.is_empty_cell((i, j - 2)):\\n effective_moves.append((i, j - 2))\\n elif j == l and i < k and board.is_empty_cell((i + 2, j)):\\n effective_moves.append((i + 2, j))\\n elif j == l and k < i and board.is_empty_cell((i - 2, j)):\\n effective_moves.append((i - 2, j))\\n return effective_moves\",\n \"def randomize(self):\\n cell_stack = []\\n cell = random.choice(self.cells)\\n n_visited_cells = 1\\n\\n while n_visited_cells < len(self.cells):\\n neighbors = [c for c in self.neighbors(cell) if c.is_full()]\\n if len(neighbors):\\n neighbor = random.choice(neighbors)\\n cell.connect(neighbor)\\n cell_stack.append(cell)\\n cell = neighbor\\n n_visited_cells += 1\\n else:\\n cell = cell_stack.pop()\",\n \"def check_score(self) -> None:\\n self.player_1, self.player_2 = 0, 0\\n for cell in self.cells:\\n if cell.player == 1:\\n self.player_1 += 1\\n elif cell.player == 2:\\n self.player_2 += 1\",\n \"def is_inacessible(cell):\\n adj, count = num_adj_buildings(cell)\\n return adj == count\",\n \"def outcome(self):\\n if self.grid[0][0] == self.grid[1][0] == self.grid[2][0] and self.grid[0][0] != 0:\\n return self.grid[0][0]\\n if self.grid[0][1] == self.grid[1][1] == self.grid[2][1] and self.grid[0][1] != 0:\\n return self.grid[0][1]\\n if self.grid[0][2] == self.grid[1][2] == self.grid[2][2] and self.grid[0][2] != 0:\\n return self.grid[0][2]\\n if self.grid[0][0] == self.grid[0][1] == self.grid[0][2] and self.grid[0][0] != 0:\\n return self.grid[0][0]\\n if self.grid[1][0] == self.grid[1][1] == self.grid[1][2] and self.grid[1][0] != 0:\\n return self.grid[1][0]\\n if self.grid[2][0] == self.grid[2][1] == self.grid[2][2] and self.grid[2][0] != 0:\\n return self.grid[2][0]\\n if self.grid[0][0] == self.grid[1][1] == self.grid[2][2] and self.grid[0][0] != 0:\\n return self.grid[0][0]\\n if self.grid[0][2] == self.grid[1][1] == self.grid[2][0] and self.grid[0][2] != 0:\\n return self.grid[0][2]\\n return 0\",\n \"def run(self):\\n for cell in self.grid.each_cell():\\n neighbors = []\\n if cell.north:\\n neighbors.append(cell.north)\\n if cell.east:\\n neighbors.append(cell.east)\\n if neighbors:\\n neighbor = random.choice(neighbors)\\n if neighbor:\\n cell.link(neighbor)\\n return self.grid\",\n \"def _is_dead_end(self, i_row, i_col, direction):\\n return (((i_row, i_col) in self._ts_cells and direction == \\\"s\\\") or\\n ((i_row, i_col) in self._ts_cells and direction == \\\"se\\\") or\\n ((i_row, i_col) in self._ts_cells and direction == \\\"sw\\\") or\\n ((i_row, i_col) in self._ls_cells and direction == \\\"e\\\") or\\n ((i_row, i_col) in self._ls_cells and direction == \\\"ne\\\") or\\n ((i_row, i_col) in self._ls_cells and direction == \\\"se\\\") or\\n ((i_row, i_col) in self._bs_cells and direction == \\\"n\\\") or\\n ((i_row, i_col) in self._bs_cells and direction == \\\"nw\\\") or\\n ((i_row, i_col) in self._bs_cells and direction == \\\"ne\\\") or\\n ((i_row, i_col) in self._rs_cells and direction == \\\"w\\\") or\\n ((i_row, i_col) in self._rs_cells and direction == \\\"nw\\\") or\\n ((i_row, i_col) in self._rs_cells and direction == \\\"sw\\\") or\\n ((i_row, i_col) == self._tl_cell and direction == \\\"s\\\") or\\n ((i_row, i_col) == self._tl_cell and direction == \\\"se\\\") or\\n ((i_row, i_col) == self._tl_cell and direction == \\\"e\\\") or\\n ((i_row, i_col) == self._bl_cell and direction == \\\"n\\\") or\\n ((i_row, i_col) == self._bl_cell and direction == \\\"ne\\\") or\\n ((i_row, i_col) == self._bl_cell and direction == \\\"e\\\") or\\n ((i_row, i_col) == self._tr_cell and direction == \\\"w\\\") or\\n ((i_row, i_col) == self._tr_cell and direction == \\\"sw\\\") or\\n ((i_row, i_col) == self._tr_cell and direction == \\\"s\\\") or\\n ((i_row, i_col) == self._br_cell and direction == \\\"w\\\") or\\n ((i_row, i_col) == self._br_cell and direction == \\\"nw\\\") or\\n ((i_row, i_col) == self._br_cell and direction == \\\"n\\\"))\",\n \"def distribute_onto_grid(self, cells,type):\\n\\n\\t\\t# setting up the topology of the space the cells will be in\\n\\t\\tif self.VARS.NEIGHBORHOOD == \\\"Moore\\\":\\n\\t\\t\\tsize = 10\\n\\t\\t\\tcount=0\\n\\t\\t\\tcells = self.VARS.CELLS\\n\\t\\t\\t# moving them into a '10X10 grid'\\n\\t\\t\\tfor i in range(1,size+1):\\n\\t\\t\\t\\tfor j in range(1, size+1):\\n\\t\\t\\t\\t\\tcells[count].set_location(i,j)\\n\\t\\t\\t\\t\\tcount +=1\\n\\n\\t\\t\\t# distances to get Moore neighbors of everyone in the network\\n\\t\\t\\tfor i in range(len(cells)):\\n\\t\\t\\t\\tfor j in range(len(cells)):\\n\\t\\t\\t\\t\\tif j > i:\\n\\t\\t\\t\\t\\t\\tone = cells[i]\\n\\t\\t\\t\\t\\t\\ttwo = cells[j]\\n\\t\\t\\t\\t\\t\\t# wraps edges of the torus around.\\n\\t\\t\\t\\t\\t\\tdist = measure_distance(one, two)\\n\\t\\t\\t\\t\\t\\tif dist < 1.5:\\n\\t\\t\\t\\t\\t\\t\\tone.add_neighbor(two)\\n\\t\\t\\t\\t\\t\\t\\ttwo.add_neighbor(one)\\n\\t\\t\\t\\t\\t\\t\\tself.net.add_edge(one,two)\",\n \"def determine_game_state(self):\\n if self.board == BLANK_BOARD:\\n return GameState.GAME_NOT_STARTED\\n\\n # check for three of the same symbol across or down.\\n for r in range(3):\\n offset = r*3\\n if self.board[offset] == self.board[offset+1] == self.board[offset+2]:\\n if self.board[offset] == X_SYMBOL:\\n return GameState.GAME_OVER_X_WINS\\n elif self.board[offset] == O_SYMBOL:\\n return GameState.GAME_OVER_O_WINS\\n if self.board[r] == self.board[3 + r] == self.board[6 + r]:\\n if self.board[r] == X_SYMBOL:\\n return GameState.GAME_OVER_X_WINS\\n elif self.board[r] == O_SYMBOL:\\n return GameState.GAME_OVER_O_WINS\\n\\n # check for diagonal wins\\n if ((self.board[0] == self.board[4] == self.board[8]) or\\n (self.board[2] == self.board[4] == self.board[6])):\\n if self.board[4] == X_SYMBOL:\\n return GameState.GAME_OVER_X_WINS\\n elif self.board[4] == O_SYMBOL:\\n return GameState.GAME_OVER_O_WINS\\n \\n # check for tie.\\n if not self.board.count(EMPTY_SYMBOL):\\n return GameState.GAME_OVER_DRAW\\n\\n return GameState.GAME_IN_PROGRESS\",\n \"def _check_inner_dirs(self, i_row, i_col, adj_opp_cells):\\n opp_player = \\\"B\\\" if self._turn == \\\"W\\\" else \\\"W\\\"\\n \\n if self._board[i_row-1][i_col] == opp_player: #north, tile to be placed will enter from the south\\n adj_opp_cells.append((i_row-1, i_col, \\\"s\\\")) \\n if self._board[i_row-1][i_col+1] == opp_player: #northeast, tile to be placed will enter from the sw\\n adj_opp_cells.append((i_row-1, i_col+1, \\\"sw\\\"))\\n if self._board[i_row][i_col+1] == opp_player: #east, tile to be placed will enter from the west\\n adj_opp_cells.append((i_row, i_col+1, \\\"w\\\"))\\n if self._board[i_row+1][i_col+1] == opp_player: #southeast, tile to be placed will enter from the nw\\n adj_opp_cells.append((i_row+1, i_col+1, \\\"nw\\\"))\\n if self._board[i_row+1][i_col] == opp_player: #south, tile to be placed will enter from the north\\n adj_opp_cells.append((i_row+1, i_col, \\\"n\\\"))\\n if self._board[i_row+1][i_col-1] == opp_player: #southwest, tile to be placed will enter from the ne\\n adj_opp_cells.append((i_row+1, i_col-1, \\\"ne\\\"))\\n if self._board[i_row][i_col-1] == opp_player: #west, tile to be placed will enter from the east.\\n adj_opp_cells.append((i_row, i_col-1, \\\"e\\\"))\\n if self._board[i_row-1][i_col-1] == opp_player: #northwest, tile to be placed will enter from the se.\\n adj_opp_cells.append((i_row-1, i_col-1, \\\"se\\\"))\",\n \"def check_game_status(self):\\n for player in (\\\"1\\\", \\\"2\\\"):\\n row_win = np.apply_along_axis(\\n lambda x: set(x) == {player}, 1, self.board\\n ).any()\\n col_win = np.apply_along_axis(\\n lambda x: set(x) == {player}, 0, self.board\\n ).any()\\n d1_win = set(self.data[[0, 4, 8]]) == {player}\\n d2_win = set(self.data[[2, 4, 6]]) == {player}\\n if any([row_win, col_win, d1_win, d2_win]):\\n return (\\\"win\\\", player)\\n\\n if self.counter[\\\"_\\\"] == 0:\\n return (\\\"tie\\\", None)\\n else:\\n return (\\\"turn\\\", \\\"1\\\" if self.counter[\\\"1\\\"] == self.counter[\\\"2\\\"] else \\\"2\\\")\",\n \"def _update_cells(self):\\n for row_number in range(self.number_cells_y):\\n for col_number in range(self.number_cells_x):\\n if self.to_be_updated[row_number][col_number]:\\n self.cells[row_number][col_number].update()\",\n \"def choose_cell_to_assign(self):\\r\\n min_domain = 10\\r\\n max_degree = -1\\r\\n chosen_row = None\\r\\n chosen_col = None\\r\\n for row in range(9):\\r\\n for col in range(9):\\r\\n if self.puzzle[row][col] == 0:\\r\\n domain_size = len(self.grid[row][col].domain)\\r\\n if domain_size < min_domain:\\r\\n min_domain = domain_size\\r\\n chosen_row = row\\r\\n chosen_col = col\\r\\n elif domain_size == min_domain:\\r\\n degree = len(self.grid[row][col].neighbors)\\r\\n if degree > max_degree:\\r\\n max_degree = degree\\r\\n chosen_row = row\\r\\n chosen_col = col\\r\\n return self.grid[chosen_row][chosen_col]\",\n \"def is_cell_safe(self, cell, board):\\n # look at a cell and the cell's revealed neighbors\\n # if any neighbors say there's 1 mine nearby, and that neighbor has neighbors which\\n # contain a flag, it's safe to click here\\n # TODO: this really needs to only check neighbors' neighbors that border the original cell.\\n # right now more cells are considered than should be.\\n safe = False\\n neighbors = ms.Minesweeper.get_neighbors(cell.row, cell.col, board)\\n revealed_neighbors = [n for n in neighbors if n.revealed or n.flagged]\\n for n in revealed_neighbors:\\n if n.neighbors > 0:\\n n_neighbors = ms.Minesweeper.get_neighbors(n.row, n.col, board)\\n flagged_n_neighbors = [n for n in n_neighbors if n.flagged]\\n if len(flagged_n_neighbors) > 0:\\n safe = True\\n return safe\",\n \"def gameOfLife(self, board: List[List[int]]) -> None:\\n\\n neighbors = [(1,0), (1,-1), (0,-1), (-1,-1), (-1,0), (-1,1), (0,1), (1,1)]\\n\\n rows = len(board)\\n cols = len(board[0])\\n\\n # 遍历面板每一个格子里的细胞\\n for row in range(rows):\\n for col in range(cols):\\n # 对于每一个细胞统计其八个相邻位置里的活细胞数量\\n live_neighbors = 0\\n\\n for neighbor in neighbors:\\n # 相邻位置的坐标\\n r = (row + neighbor[0])\\n c = (col + neighbor[1])\\n # 查看相邻的细胞是否是活细胞\\n if (r < rows and r >= 0) and (c < cols and c >= 0) and abs(board[r][c]) == 1:\\n live_neighbors += 1\\n\\n # 过去的活细胞，现在变为死细胞\\n if board[row][col] == 1 and (live_neighbors < 2 or live_neighbors > 3):\\n # -1 代表这个细胞过去是活的现在死了\\n board[row][col] = -1\\n # 过去的死细胞，现在变为活细胞\\n if board[row][col] == 0 and live_neighbors == 3:\\n # 2 代表这个细胞过去是死的现在活了\\n board[row][col] = 2\\n\\n # 遍历 board 刷新更新后的状态\\n for row in range(rows):\\n for col in range(cols):\\n if board[row][col] > 0:\\n board[row][col] = 1\\n else:\\n board[row][col] = 0\",\n \"def check(self):\\n winner = None\\n count = 0\\n\\n for y in range(self.gridSize):\\n if winner != None:\\n return winner\\n P1, P2 = 0, 0\\n for item in self.grid[y]:\\n # Check row of the grid\\n if item == \\\"P1\\\":\\n P1 += 1\\n elif item == \\\"P2\\\":\\n P2 += 1\\n winner = self.checkval(P1, P2, self.gridSize)\\n if winner != None:\\n return winner\\n P1, P2 = 0, 0\\n for x in range(self.gridSize):\\n # Check column of the grid\\n if self.grid[x][y] == \\\"P1\\\":\\n P1 += 1\\n elif self.grid[x][y] == \\\"P2\\\":\\n P2 += 1\\n winner = self.checkval(P1, P2, self.gridSize)\\n if winner != None:\\n return winner\\n P1, P2 = 0, 0\\n for y in range(self.gridSize):\\n # Check right top to left bottom across the grid\\n for x in range(self.gridSize):\\n if x == y:\\n if self.grid[x][y] == \\\"P1\\\":\\n P1 += 1\\n elif self.grid[x][y] == \\\"P2\\\":\\n P2 += 1\\n winner = self.checkval(P1, P2, self.gridSize)\\n if winner != None:\\n return winner\\n P1, P2 = 0, 0\\n for y in range(self.gridSize):\\n # Check the left top to the right bottom across the grid\\n for x in range(self.gridSize - 1, -1, -1):\\n # Check how many filled spaces there are\\n if \\\".\\\" not in self.grid[y][x]:\\n count += 1\\n if x + y == self.gridSize - 1:\\n if self.grid[y][x] == \\\"P1\\\":\\n P1 += 1\\n elif self.grid[y][x] == \\\"P2\\\":\\n P2 += 1\\n winner = self.checkval(P1, P2, self.gridSize)\\n # Check if there is a winner if so return the winner\\n if winner != None:\\n return winner\\n # Check if the fields that are filled are equal to the possible spaces to be filled in the grid\\n if count == self.gridSize**2:\\n return \\\"Tie\\\"\",\n \"def _ignite_cells(self, istep, ip):\\n particle = self.particles[ip] # get particle\\n state, x, y = particle.get_from_keys([\\\"state\\\", \\\"x\\\", \\\"y\\\"])\\n if state > STTHR:\\n for i in range(self.grid.NX-1):\\n if abs(x - self.grid.XCELL[i, 0]) < self.grid.DX/2:\\n INDX = i\\n for j in range(self.grid.NY-1):\\n if abs(y - self.grid.YCELL[0, j]) < self.grid.DY/2:\\n INDY = j\\n cell = self.grid.CELLS[INDX, INDY]\\n cell.BURNPROG += 1\\n if (cell.QMAXTR > 0 or cell.QMAXBLD > 0) and cell.BURNSTAT == 0:\\n cell.BURNSTAT = 1\\n cell.CLOCK = self.TIME[istep]\\n # elif cell.QMAXTR == 0 or cell.QMAXBLD == 0:\\n # particle.update(state=0.0, factor=0.0)\\n # if pType == 2:\\n # particle.update(state=0.0)\",\n \"def _compute_grid_state(self, for_id):\\n own = np.zeros_like(self._map, float)\\n own_pos = self._id2pos[for_id]\\n own[own_pos] = 1\\n\\n thieves = (self._map == THIEF ).astype(float)\\n guardians = (self._map == GUARDIAN).astype(float)\\n\\n own_team = self.id2team[for_id]\\n if own_team == THIEF:\\n teammates = thieves\\n opponents = guardians\\n else:\\n teammates = guardians\\n opponents = thieves\\n\\n treasure_channel = (self._map == TREASURE).astype(float)\\n\\n # Channels first\\n return np.stack([own, teammates, opponents, self._walls_channel, treasure_channel])\",\n \"def changeCell(self, i, j):\\n\\t\\t#If Cell is on Top row\\n\\t\\tif(i==0):\\n\\t\\t\\tif(j==0):\\n\\t\\t\\t\\tn = self.board[0][1] + self.board[1][0] + self.board[1][1]\\n\\t\\t\\telif(j==(self.size-1)):\\n\\t\\t\\t\\tn = self.board[0][self.size-2] + self.board[1][self.size-2] + self.board[1][self.size-1]\\n\\t\\t\\telse:\\n\\t\\t\\t\\tn = self.board[0][j-1] + self.board[1][j] + self.board[0][j+1] + self.board[1][j-1] + self.board[1][j+1]\\n\\t\\t\\t\\n\\t\\t\\tif((n == 2 and self.board[i][j] == 1) or n == 3):\\n\\t\\t\\t\\treturn 1\\n\\t\\t\\telse:\\n\\t\\t\\t\\treturn 0\\n\\t\\t#If Cell on Bottom row\\n\\t\\telif(i==(self.size-1)):\\n\\t\\t\\tif(j==0):\\n\\t\\t\\t\\tn = self.board[self.size-1][1] + self.board[self.size-2][0] + self.board[self.size-2][1]\\n\\t\\t\\telif(j==(self.size-1)):\\n\\t\\t\\t\\tn = self.board[self.size-1][self.size-2] + self.board[self.size-2][self.size-2] + self.board[self.size-2][self.size-1]\\n\\t\\t\\telse:\\n\\t\\t\\t\\tn = self.board[self.size-1][j-1] + self.board[self.size-2][j] + self.board[self.size-1][j+1] + self.board[self.size-2][j-1] + self.board[self.size-2][j+1]\\n\\t\\t\\tif((n == 2 and self.board[i][j] == 1) or n == 3):\\n\\t\\t\\t\\treturn 1\\n\\t\\t\\telse:\\n\\t\\t\\t\\treturn 0\\n\\t\\t#If Cell is in a middle row\\n\\t\\telse:\\n\\t\\t\\tif(j==0):\\n\\t\\t\\t\\tn = self.board[i-1][j] + self.board[i+1][j] + self.board[i][j+1] + self.board[i-1][j+1] + self.board[i+1][j+1]\\n\\t\\t\\telif(j==(self.size-1)):\\n\\t\\t\\t\\tn = self.board[i-1][j] + self.board[i+1][j] + self.board[i][j-1] + self.board[i-1][j-1] + self.board[i+1][j-1]\\n\\t\\t\\telse:\\n\\t\\t\\t\\tn = self.board[i-1][j] + self.board[i+1][j] + self.board[i][j-1] + self.board[i-1][j-1] + self.board[i+1][j-1] + self.board[i][j+1] + self.board[i-1][j+1] + self.board[i+1][j+1]\\n\\t\\t\\tif((n == 2 and self.board[i][j] == 1) or n == 3):\\n\\t\\t\\t\\treturn 1\\n\\t\\t\\telse:\\n\\t\\t\\t\\treturn 0\",\n \"def test(brickheight,bricklength,row,column,walllength,wallheight,occupied,answer):\\n if brickheight>wallheight or bricklength>walllength:\\n return False\\n elif over(brickheight,bricklength,row,column,walllength,wallheight):\\n return False\\n else:\\n for x in range(column,column+bricklength):\\n for y in range(row,row+brickheight):\\n if (x,y) in occupied:\\n return False \\n break\\n else:\\n return True\",\n \"def random_state(self) -> Grid2D.State:\\n return Grid2D.State(random.choice(self.empty_cell_list))\",\n \"def getGameState(self):\\n ### Student code goes here\\n\\n ask_tile_11 = parse_input(\\\"fact: (located ?X pos1 pos1)\\\")\\n ask_tile_12 = parse_input(\\\"fact: (located ?X pos2 pos1)\\\")\\n ask_tile_13 = parse_input(\\\"fact: (located ?X pos3 pos1)\\\")\\n ask_tile_21 = parse_input(\\\"fact: (located ?X pos1 pos2)\\\")\\n ask_tile_22 = parse_input(\\\"fact: (located ?X pos2 pos2)\\\")\\n ask_tile_23 = parse_input(\\\"fact: (located ?X pos3 pos2)\\\")\\n ask_tile_31 = parse_input(\\\"fact: (located ?X pos1 pos3)\\\")\\n ask_tile_32 = parse_input(\\\"fact: (located ?X pos2 pos3)\\\")\\n ask_tile_33 = parse_input(\\\"fact: (located ?X pos3 pos3)\\\")\\n\\n bindings_11 = self.kb.kb_ask(ask_tile_11)\\n bindings_12 = self.kb.kb_ask(ask_tile_12)\\n bindings_13 = self.kb.kb_ask(ask_tile_13)\\n bindings_21 = self.kb.kb_ask(ask_tile_21)\\n bindings_22 = self.kb.kb_ask(ask_tile_22)\\n bindings_23 = self.kb.kb_ask(ask_tile_23)\\n bindings_31 = self.kb.kb_ask(ask_tile_31)\\n bindings_32 = self.kb.kb_ask(ask_tile_32)\\n bindings_33 = self.kb.kb_ask(ask_tile_33)\\n\\n row1_list = []\\n row2_list = []\\n row3_list = []\\n\\n row1_list.append(bindings_11.list_of_bindings[0][0].bindings[0].constant.element)\\n row1_list.append(bindings_12.list_of_bindings[0][0].bindings[0].constant.element)\\n row1_list.append(bindings_13.list_of_bindings[0][0].bindings[0].constant.element)\\n\\n row2_list.append(bindings_21.list_of_bindings[0][0].bindings[0].constant.element)\\n row2_list.append(bindings_22.list_of_bindings[0][0].bindings[0].constant.element)\\n row2_list.append(bindings_23.list_of_bindings[0][0].bindings[0].constant.element)\\n\\n row3_list.append(bindings_31.list_of_bindings[0][0].bindings[0].constant.element)\\n row3_list.append(bindings_32.list_of_bindings[0][0].bindings[0].constant.element)\\n row3_list.append(bindings_33.list_of_bindings[0][0].bindings[0].constant.element)\\n\\n counter = 0\\n for tile in row1_list:\\n if tile == \\\"empty\\\":\\n row1_list[counter] = -1\\n else:\\n row1_list[counter] = int(tile[4:])\\n counter += 1\\n\\n counter = 0\\n for tile in row2_list:\\n if tile == \\\"empty\\\":\\n row2_list[counter] = -1\\n else:\\n row2_list[counter] = int(tile[4:])\\n counter += 1\\n\\n counter = 0\\n for tile in row3_list:\\n if tile == \\\"empty\\\":\\n row3_list[counter] = -1\\n else:\\n row3_list[counter] = int(tile[4:])\\n counter += 1\\n\\n gamestate = (tuple(row1_list), tuple(row2_list), tuple(row3_list))\\n return gamestate\",\n \"def actions(self, state):\\n MovementList = []\\n #Check if the agent is able to move a box (Left, Down, Right, Up) \\n #without moving it into a taboo cell or pushing two blocks (Invalid move)\\n #then move the box in the given direction.\\n \\n possible_moves = [\\\"Up\\\", \\\"Down\\\", \\\"Left\\\", \\\"Right\\\"]\\n \\n worker = state[0]\\n boxes = state[1]\\n \\n # Iterate throguh the moves and make sure they satify constraints\\n for move in possible_moves:\\n if (move_coords(worker, move) not in self.walls):\\n if (move_coords(worker, move) in boxes):\\n if move_coords(move_coords(worker, move), move) in self.taboo:\\n pass\\n else: \\n MovementList.append(move)\\n else:\\n MovementList.append(move)\\n \\n return MovementList\",\n \"def spawn_ok(game):\\n me = game.me\\n shipyard_cell = game.game_map[me.shipyard]\\n\\n # % turns above mining rate to dropoff the halite, will typically be about 2?\\n mining_over_head = 2\\n ship_count = len(me.get_ships())\\n\\n #\\n # absolute constraints (order can be important)\\n #\\n\\n if ship_count >= MAX_SHIPS:\\n if DEBUG & (DEBUG_GAME): logging.info(\\\"Game - Spawn denied. MAX ships reached\\\".format())\\n return False\\n\\n if me.halite_amount < constants.SHIP_COST:\\n if DEBUG & (DEBUG_GAME): logging.info(\\\"Game - Spawn denied. Insufficient halite\\\".format())\\n return False\\n\\n #\\n # conditional constraints\\n #\\n\\n logging.debug(\\\"shipyard_cell.is_occupied: {}\\\".format(shipyard_cell.is_occupied))\\n if shipyard_cell.is_occupied:\\n logging.debug(\\\"shipyard_cell.ship.owner == me.id: {}\\\".format(shipyard_cell.ship.owner == me.id))\\n\\n # watch for collisions with owner only, note this will be 1 turn behind\\n occupied_cells = []\\n if shipyard_cell.is_occupied and shipyard_cell.ship.owner == me.id:\\n occupied_cells.append(shipyard_cell.position)\\n\\n logging.debug(\\\"oc1: {}\\\".format(occupied_cells))\\n\\n # entry lane are N/S\\n n_cell = shipyard_cell.position.directional_offset(Direction.North)\\n s_cell = shipyard_cell.position.directional_offset(Direction.South)\\n e_cell = shipyard_cell.position.directional_offset(Direction.East)\\n w_cell = shipyard_cell.position.directional_offset(Direction.West)\\n for pos in [n_cell, s_cell, e_cell, w_cell]:\\n if game.game_map[pos].is_occupied:\\n occupied_cells.append(pos)\\n\\n logging.debug(\\\"oc2: {}\\\".format(occupied_cells))\\n\\n # need to keep track of ships docking instead, a ship in an adjacent cell could be leaving\\n if occupied_cells:\\n if DEBUG & (DEBUG_GAME): logging.info(\\\"Game - Spawn denied. Occupied cells: {}\\\".format(occupied_cells))\\n return False\\n\\n return True\",\n \"def empty_cells(state):\\r\\n cells = []\\r\\n for x, row in enumerate(state):\\r\\n for y, cell in enumerate(row):\\r\\n if cell == 0:\\r\\n cells.append([x, y])\\r\\n\\r\\n return cells\",\n \"def fill_grid(self):\\n\\n for row_margin, row in enumerate(range(self.rows)):\\n self.grid.append([])\\n\\n for col_margin, col in enumerate(range(self.cols)):\\n x = col*self.cell_size + col_margin\\n y = row*self.cell_size + row_margin\\n\\n rect = pygame.Rect(x, y, self.cell_size, self.cell_size)\\n\\n cell = Cell(row, col, rect)\\n\\n if row == 7 and col == 3:\\n cell.root = True\\n self.root = cell\\n elif row == 7 and col == 16:\\n cell.goal = True\\n self.goal = cell\\n\\n self.grid[row].append(cell)\",\n \"def gameOfLife(self, board: List[List[int]]) -> None:\\n changes = list()\\n for i in range(len(board)):\\n for j in range(len(board[0])):\\n neighbor_data = {\\n 'live': 0,\\n 'dead': 0\\n }\\n checks = {(0,1), (0,-1), (1, 0), (-1, 0), (1, 1), (1, -1), (-1, 1), (-1,-1)}\\n if i == 0:\\n checks.discard((-1, 0))\\n checks.discard((-1, 1))\\n checks.discard((-1, -1))\\n if j == 0:\\n checks.discard((0, -1))\\n checks.discard((-1, -1))\\n checks.discard((1, -1))\\n if i == (len(board) - 1):\\n checks.discard((1,0))\\n checks.discard((1,-1))\\n checks.discard((1, 1))\\n if j == (len(board[0]) - 1):\\n checks.discard((0, 1))\\n checks.discard((-1, 1))\\n checks.discard((1, 1))\\n for check in checks:\\n if board[i + check[0]][j + check[1]]:\\n neighbor_data['live'] += 1\\n else:\\n neighbor_data['dead'] += 1\\n if board[i][j]:\\n # check live rules\\n if neighbor_data['live'] < 2 or neighbor_data['live'] > 3:\\n changes.append((i, j))\\n else:\\n # check dead rules\\n if neighbor_data['live'] == 3:\\n changes.append((i, j))\\n for change in changes:\\n board[change[0]][change[1]] = int (not board[change[0]][change[1]])\\n \\n print (board)\",\n \"def __init__(self, num_rows = 4, num_cols = 4,\\n first_mover = \\\"W\\\", top_left = \\\"B\\\",\\n how_to_win = \\\">\\\", initial_config=[]):\\n # initial_config was made for AI Othello to\\n # get around pass-by-reference behavior of lists.\\n if (4 > num_rows > 16) or num_rows % 2 != 0:\\n raise Exception\\n else:\\n self._num_rows = num_rows\\n if (4 > num_cols > 16) or num_cols % 2 != 0:\\n raise Exception\\n else:\\n self._num_cols = num_cols\\n if first_mover != \\\"B\\\" and first_mover != \\\"W\\\":\\n raise Exception\\n else:\\n self._turn = first_mover\\n if top_left != \\\"B\\\" and top_left != \\\"W\\\":\\n raise Exception\\n else:\\n self._top_left = top_left\\n if how_to_win != \\\">\\\" and how_to_win != \\\"<\\\":\\n raise Exception\\n else:\\n self._how_to_win = how_to_win\\n\\n if initial_config == []:\\n self._board = self._make_board(num_rows, num_cols, top_left)\\n else:\\n self._board = deepcopy(initial_config)\\n \\n self._game_over = False\\n self._winner = \\\" \\\"\\n self._tl_cell = (0, 0)\\n self._tr_cell = (0, num_cols-1)\\n self._bl_cell = (num_rows-1, 0)\\n self._br_cell = (num_rows-1, num_cols-1)\\n self._ls_cells = [(c, 0) for c in range(1, num_rows-1)]\\n self._rs_cells = [(c, num_cols-1) for c in range(1, num_rows-1)]\\n self._ts_cells = [(0, c) for c in range(1, num_cols-1)]\\n self._bs_cells = [(num_rows-1, c) for c in range(1, num_cols-1)]\\n #^Note how ranges start from 1 and go to num_rows-1 to avoid corners,\\n #which are processed differently\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.69623125","0.6414086","0.6400114","0.63498706","0.6227592","0.6179046","0.6162203","0.61035144","0.6049122","0.604795","0.6018108","0.60137135","0.60055864","0.6002554","0.598495","0.59398884","0.5925738","0.5910711","0.59071994","0.5905565","0.5895984","0.58819795","0.5880821","0.5879823","0.5872225","0.5826755","0.5825616","0.58246577","0.5802987","0.5784841","0.57644796","0.575903","0.5750791","0.5747522","0.5747344","0.5746174","0.5742305","0.57333994","0.57234263","0.5720458","0.57030207","0.5702953","0.57012594","0.56920326","0.5671717","0.56703514","0.5665134","0.5651492","0.564618","0.5644662","0.5638183","0.5638183","0.5635321","0.563413","0.56333596","0.56330574","0.5612233","0.5611423","0.5610855","0.5608484","0.560393","0.56017506","0.5594365","0.55860114","0.5585741","0.5581846","0.5573908","0.5561342","0.5556672","0.5555005","0.55472994","0.554024","0.5539831","0.5539038","0.55376214","0.5535675","0.5524062","0.5523404","0.5522296","0.5522041","0.55126745","0.5512487","0.5509559","0.5507776","0.55076677","0.5506632","0.5500923","0.5497907","0.54840696","0.54781914","0.5476614","0.5473403","0.54727495","0.5472673","0.54637855","0.545914","0.5456236","0.54552495","0.5455022","0.5453495"],"string":"[\n \"0.69623125\",\n \"0.6414086\",\n \"0.6400114\",\n \"0.63498706\",\n \"0.6227592\",\n \"0.6179046\",\n \"0.6162203\",\n \"0.61035144\",\n \"0.6049122\",\n \"0.604795\",\n \"0.6018108\",\n \"0.60137135\",\n \"0.60055864\",\n \"0.6002554\",\n \"0.598495\",\n \"0.59398884\",\n \"0.5925738\",\n \"0.5910711\",\n \"0.59071994\",\n \"0.5905565\",\n \"0.5895984\",\n \"0.58819795\",\n \"0.5880821\",\n \"0.5879823\",\n \"0.5872225\",\n \"0.5826755\",\n \"0.5825616\",\n \"0.58246577\",\n \"0.5802987\",\n \"0.5784841\",\n \"0.57644796\",\n \"0.575903\",\n \"0.5750791\",\n \"0.5747522\",\n \"0.5747344\",\n \"0.5746174\",\n \"0.5742305\",\n \"0.57333994\",\n \"0.57234263\",\n \"0.5720458\",\n \"0.57030207\",\n \"0.5702953\",\n \"0.57012594\",\n \"0.56920326\",\n \"0.5671717\",\n \"0.56703514\",\n \"0.5665134\",\n \"0.5651492\",\n \"0.564618\",\n \"0.5644662\",\n \"0.5638183\",\n \"0.5638183\",\n \"0.5635321\",\n \"0.563413\",\n \"0.56333596\",\n \"0.56330574\",\n \"0.5612233\",\n \"0.5611423\",\n \"0.5610855\",\n \"0.5608484\",\n \"0.560393\",\n \"0.56017506\",\n \"0.5594365\",\n \"0.55860114\",\n \"0.5585741\",\n \"0.5581846\",\n \"0.5573908\",\n \"0.5561342\",\n \"0.5556672\",\n \"0.5555005\",\n \"0.55472994\",\n \"0.554024\",\n \"0.5539831\",\n \"0.5539038\",\n \"0.55376214\",\n \"0.5535675\",\n \"0.5524062\",\n \"0.5523404\",\n \"0.5522296\",\n \"0.5522041\",\n \"0.55126745\",\n \"0.5512487\",\n \"0.5509559\",\n \"0.5507776\",\n \"0.55076677\",\n \"0.5506632\",\n \"0.5500923\",\n \"0.5497907\",\n \"0.54840696\",\n \"0.54781914\",\n \"0.5476614\",\n \"0.5473403\",\n \"0.54727495\",\n \"0.5472673\",\n \"0.54637855\",\n \"0.545914\",\n \"0.5456236\",\n \"0.54552495\",\n \"0.5455022\",\n \"0.5453495\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5600861"},"document_rank":{"kind":"string","value":"62"}}},{"rowIdx":94898,"cells":{"query":{"kind":"string","value":"Collect data into fixedlength chunks or blocks"},"document":{"kind":"string","value":"def grouper(iterable, n, fillvalue=None):\n # grouper('ABCDEFG', 3, 'x') --> ABC DEF Gxx\n args = [iter(iterable)] * n\n return izip_longest(fillvalue=fillvalue, *args)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _chunk_data(self):\n for n in range(0, len(self.data) + 1, len(self.data) //\n self.num_of_chunks):\n yield self.data[0 + n:len(self.data) // self.num_of_chunks + n]","def chunks(data: list, n: int) -> list:\n for i in range(0, len(data), n):\n yield data[i:i + n]","def chunks(data: List[Any], num: int) -> Generator[List[Any], None, None]:\n for i in range(0, len(data), num):\n yield data[i : i + num]","def chunks(sequence, chunk_size):\r\n\r\n # YOUR CODE HERE\r","def chunks(data, rows=10000):\n\n for i in range(0, len(data), rows):\n yield data[i:i+rows]","def chunked(self, length, overlap):\n def new_gen():\n buffer = self.read(length)\n while True:\n yield np.array([buffer]) #pack into one more dimension\n new_elems = self.read(length - overlap)\n if new_elems.shape[0] == 0:\n # Reached the end of the stream\n break\n buffer[:overlap] = buffer[length-overlap:]\n buffer[overlap:] = new_elems\n return Stream(new_gen(), chunk_size=1)","def getChunks():","def fill_buffer(self):\n num_of_smp = 0\n while num_of_smp < self.buf_size:\n c, t = self.inlet.pull_chunk(timeout=0.0)\n new_c = []\n new_t = []\n while c:\n new_c += c\n new_t += t\n c, t = self.inlet.pull_chunk(timeout=0.0)\n\n # add samples to buffer\n if any(new_c):\n # add samples\n num_of_smp += len(new_c)\n data_v = [item for sublist in new_c for item in sublist]\n self.gbuffer = np.roll(self.gbuffer, -len(data_v))\n self.gbuffer[-len(data_v):] = data_v\n # add timestamps\n if new_t:\n self.gtimes = np.roll(self.gtimes, -len(new_t))\n self.gtimes[-len(new_t):] = new_t","def _get_chunk_data(self, inputs: Iterable, chunk_size: int):\n inputs_iter = iter(inputs)\n while True:\n try:\n chunk_data = []\n for _ in range(chunk_size):\n processed_data = next(inputs_iter)\n chunk_data.append(processed_data)\n yield chunk_data\n except StopIteration:\n if chunk_data:\n yield chunk_data\n break","def blockify_chunks(chunks):\n acc = []\n size = 0\n for chunk, chunk_size in chunks:\n assert len(chunk) == CHUNK_SIZE\n assert len(acc) <= BLOCK_SIZE\n if len(acc) == BLOCK_SIZE:\n # Only the last chunk may be short.\n assert size == CHUNK_SIZE * BLOCK_SIZE\n yield acc, size\n acc = []\n size = 0\n acc.append(chunk)\n size += chunk_size\n assert acc\n yield acc, size","def perform_chunking(self, data_size, chunk_size):\r\n\r\n chunks, i = [], 0\r\n while True:\r\n chunks.append((i * (chunk_size - self.overlap / 2), i * (chunk_size - self.overlap / 2) + chunk_size))\r\n i += 1\r\n if chunks[-1][1] > data_size:\r\n break\r\n\r\n n_count = len(chunks)\r\n chunks[-1] = tuple(x - (n_count * chunk_size - data_size - (n_count - 1) * self.overlap / 2) for x in chunks[-1])\r\n chunks = [(int(x), int(y)) for x, y in chunks]\r\n return chunks","def recv_chunk(self, data):","def chunked(size, source):\n for i in range(0, len(source), size):\n yield source[i : i + size]","def static_batch(data, batch_size=16):\n buf = []\n for sample in data:\n buf.append(sample)\n if len(buf) >= batch_size:\n yield buf\n buf = []\n if len(buf) > 0:\n yield buf","def in_memory_rechunk(\n inputs: List[Tuple[core.ChunkKey, xarray.Dataset]],\n target_chunks: Mapping[str, int],\n) -> Iterator[Tuple[core.ChunkKey, xarray.Dataset]]:\n key, dataset = consolidate_chunks(inputs)\n yield from split_chunks(key, dataset, target_chunks)","def chunk(seq, size, groupByList=True):\n func = tuple\n if groupByList:\n func = list\n return [func(seq[i:i + size]) for i in range(0, len(seq), size)]","def chunk(max_elems = 8192, dtype = numpy.float64):\n\n @filters\n def _dagpype_internal_fn_act(target):\n assert max_elems > 0\n dtype_ = dtype\n\n l = []\n try:\n while True:\n while len(l) < max_elems:\n l.append((yield))\n target.send(numpy.array(l, dtype = dtype_))\n l = []\n except GeneratorExit:\n if len(l) > 0:\n target.send(numpy.array(l, dtype = dtype_)) \n \n return _dagpype_internal_fn_act","def __chunks(l, n):\n for i in range(0, len(l), n):\n yield l[i:i + n]","def some_payloaded_data(length=1000000, size=32, var=0):\n for datum in some_simple_data(length):\n yield DataWithPayload(datum, some_payload(size, var))","def _chunker(self, seq, size):\n return (seq.iloc[pos:pos + size] for pos in range(0, len(seq), size))","def batch(self, data, size):\n\n return [data[x : x + size] for x in range(0, len(data), size)]","def _chunks(l, n):\n for i in range(0, len(l), n):\n yield l[i:i + n]","def _chunker(self, seq, size):\n return (seq[pos:pos + size] for pos in range(0, len(seq), size))","def prepare_batches(self, data):\n batches = []\n start, end = 0, 100\n if len(data) > 100:\n while True:\n data_batch = data[start:end]\n if not data_batch:\n break\n temp = end + 100\n start, end = end, temp\n if data_batch:\n batches.append(data_batch)\n else:\n batches.append(data)\n return batches","def make_chunks(l, chunk_length):\n for i in range(0, len(l), chunk_length):\n yield l[i:i + chunk_length]","def block_splitter(data, block_size):\n buf = []\n for i, datum in enumerate(data):\n buf.append(datum)\n if len(buf) == block_size:\n yield buf\n buf = []\n\n # If there's anything leftover (a partial block),\n # yield it as well.\n if buf:\n yield buf","def iter_unpack(raw):\n return chunks(raw)","def _chunks(l, n):\n\tfor i in range(0, len(l), n):\n\t\tyield l[i:i + n]","def iter_chunks(sequence, chunk_size) :\n res = []\n for item in sequence :\n res.append(item)\n if len(res) >= chunk_size :\n yield res\n res = []\n if res : yield res","def test_create_chunks():\n items = list(range(0, 100))\n size = 3\n\n chunks = create_chunks(items, size)\n\n current = next(chunks)\n assert len(current) == size\n assert current == [0, 1, 2]\n\n current = next(chunks)\n assert current == [3, 4, 5]","def chunk(it, size):\n it = iter(it)\n return iter(lambda: list(islice(it, size)), [])","def build(self, block_size):","def get_chunks(vals, size):\n for i in range(0, len(vals), size):\n yield vals[i:i + size]","def chunks(items, size):\n return [items[i:i+size] for i in range(0, len(items), size)]","def chunked(self, n):\n return imap(self.__class__, chunked(self._bytes, n))","def batches(data, batch_size) -> list:\n rv = []\n for idx, line in enumerate(data):\n if idx != 0 and idx % batch_size == 0:\n yield rv\n rv = []\n rv.append(line)\n yield rv","def _get_data_chunk(self):\n if self._start_pos < self.max_pos:\n self._current_sho_spec_slice = slice(self.sho_spec_inds_per_forc * self._current_forc,\n self.sho_spec_inds_per_forc * (self._current_forc + 1))\n self._end_pos = int(min(self.h5_main.shape[0], self._start_pos + self.max_pos))\n self.data = self.h5_main[self._start_pos:self._end_pos, self._current_sho_spec_slice]\n elif self._current_forc < self._num_forcs - 1:\n # Resest for next FORC\n self._current_forc += 1\n\n self._current_sho_spec_slice = slice(self.sho_spec_inds_per_forc * self._current_forc,\n self.sho_spec_inds_per_forc * (self._current_forc + 1))\n self._current_met_spec_slice = slice(self.metrics_spec_inds_per_forc * self._current_forc,\n self.metrics_spec_inds_per_forc * (self._current_forc + 1))\n self._get_dc_offset()\n\n self._start_pos = 0\n self._end_pos = int(min(self.h5_main.shape[0], self._start_pos + self.max_pos))\n self.data = self.h5_main[self._start_pos:self._end_pos, self._current_sho_spec_slice]\n\n else:\n self.data = None\n\n return","def chunk(size, seq):\n if not isinstance(size, int) or size <= 0: # pragma: no cover\n raise ValueError(\"size must be an integer greater than zero\")\n\n group = []\n\n for item in seq:\n if len(group) >= size:\n yield group\n group = []\n group.append(item)\n\n if group:\n yield group","def _chunk(self, l, n):\n for i in range(0, len(l) + 1, n):\n yield l[i:i + n]","def get_chunks(sequence, ck_size):\n \n list_chunk = []\n i=1\n l = len(sequence)\n if l < 4*ck_size:\n raise ValueError(\"Chunk size should be of 4 at least \")\n for i in range(1, l):\n if i*ck_size < l:\n list_chunk.append(sequence[i*ck_size-ck_size:i*ck_size])\n #while(i*ck_size < l):\n #list_chunk.append(sequence[i*ck_size-ck_size:i*ck_size])\n #i += 1\n return list_chunk","def chunks(seq, size):\n for i in range(0, len(seq), size):\n yield seq[i:i + size]","def chunks(items, chunk_size):\r\n items = list(items)\r\n return (items[i:i + chunk_size] for i in xrange(0, len(items), chunk_size))","def chunks(arr, n):\n for i in range(0, len(arr), n):\n yield arr[i:i + n]","def get_chunks(self, l, n):\r\n for i in range(0, len(l), n):\r\n yield l[i:i+n]","def _get_chunks(l, n = 10):\n \n for i in range(0, len(l), n): yield l[i: i + n]","def chunker(seq, size):\n\n return (seq[pos : pos + size] for pos in range(0, len(seq), size))","def __iter__(self):\n\n # collector will fetch chunksize array for each 'get' call\n collector = FIFOArray(self.chunksize, self.axis)\n\n # make tmp array to hold generated subarrs\n tmp = []\n tmp_size = 0\n for subarr in self.data(**self.kwargs):\n\n tmp.append(subarr)\n tmp_size += subarr.shape[self.axis]\n\n # if tmp exceeds chunksize put in collector\n if tmp_size >= self.chunksize:\n arr = np.concatenate(tmp, axis=self.axis)\n collector.put(arr)\n\n # fetch chunksize till not full\n while collector.full():\n yield collector.get()\n\n # place leftover back into tmp and empty collector\n tmp = [collector.queue]\n tmp_size = collector.qsize()\n collector.queue = np.array([])\n\n else:\n\n # append to tmp again\n continue\n\n # else runs after normal loop exit -- required here\n else: #pylint: disable=useless-else-on-loop\n\n # yield whatever is left in tmp (its below chunksize)\n remaining = np.concatenate(tmp, axis=self.axis)\n if remaining.size > 0:\n yield remaining","def chunks(data, overrides = {}):\n counter, filesize = 0, len(data)\n last = None\n while counter < filesize:\n try:\n magic, size = chunk.unpack_from(data, counter)\n except struct_error as e:\n print('failed loading chunk from', data[:counter])\n print('last chunk:', last)\n raise e\n\n counter += chunk.size\n contents = data[counter:counter+size]\n\n if magic[3] != 0x4D:\n raise Exception('bad magic', magic, 'last chunk:', last)\n\n if magic in overrides:\n size = overrides[magic]\n\n yield magic, size, contents\n counter += size\n\n last = (magic, size, contents)","def chunks(arr, n):\n for i in range(0, len(arr), n):\n yield arr[i:i + n]","def test_chunk_memory(self):\n layer = tl.Serial(tl.Dense(1024*1024), tl.Dense(128))\n chunked = tl.Chunk(layer, 256)\n x = np.random.uniform(size=(16*1024, 16))\n chunked.init(shapes.signature(x))\n y = chunked(x)\n z = tl.Accelerate(chunked)(x)\n self.assertEqual(y.shape, (16*1024, 128))\n self.assertEqual(z.shape, (16*1024, 128))","def chunk(list, chunksize):\n for i in range(0, len(list), chunksize):\n yield list[i:i + chunksize]","def _chunks(l, n):\n for i in xrange(0, len(l), n):\n yield l[i:i + n]","def Chunks(l):\n return_list = [[]]\n counter = 0\n index = 0\n for i in l:\n # Size is split in half due to the max size being a sum of src and dst.\n if counter > (self._ADDRESS_LENGTH_LIMIT/2):\n counter = 0\n index += 1\n return_list.append([])\n if i.version == 6:\n counter += self._IPV6_SIZE\n else:\n counter += 1\n return_list[index].append(i)\n return return_list","def chunks(self, n):\n return _([self._[i:i+n] for i in range(0, self.size()._, n)])","def chunks(l, n):\n for i in xrange(0, len(l), n):\n yield l[i:i+n]","def all_gather_list(data, group=None, max_size=16384):\n SIZE_STORAGE_BYTES = 4 # int32 to encode the payload size\n\n enc = pickle.dumps(data)\n enc_size = len(enc)\n\n if enc_size + SIZE_STORAGE_BYTES > max_size:\n raise ValueError(\n 'encoded data exceeds max_size, this can be fixed by increasing buffer size: {}'.format(enc_size))\n\n rank = get_rank()\n world_size = get_world_size()\n buffer_size = max_size * world_size\n\n if not hasattr(all_gather_list, '_buffer') or \\\n all_gather_list._buffer.numel() < buffer_size:\n all_gather_list._buffer = torch.cuda.ByteTensor(buffer_size)\n all_gather_list._cpu_buffer = torch.ByteTensor(max_size).pin_memory()\n\n buffer = all_gather_list._buffer\n buffer.zero_()\n cpu_buffer = all_gather_list._cpu_buffer\n\n assert enc_size < 256 ** SIZE_STORAGE_BYTES, 'Encoded object size should be less than {} bytes'.format(\n 256 ** SIZE_STORAGE_BYTES)\n\n size_bytes = enc_size.to_bytes(SIZE_STORAGE_BYTES, byteorder='big')\n\n cpu_buffer[0:SIZE_STORAGE_BYTES] = torch.ByteTensor(list(size_bytes))\n cpu_buffer[SIZE_STORAGE_BYTES: enc_size + SIZE_STORAGE_BYTES] = torch.ByteTensor(list(enc))\n\n start = rank * max_size\n size = enc_size + SIZE_STORAGE_BYTES\n buffer[start: start + size].copy_(cpu_buffer[:size])\n\n all_reduce(buffer, group=group)\n\n try:\n result = []\n for i in range(world_size):\n out_buffer = buffer[i * max_size: (i + 1) * max_size]\n size = int.from_bytes(out_buffer[0:SIZE_STORAGE_BYTES], byteorder='big')\n if size > 0:\n result.append(pickle.loads(bytes(out_buffer[SIZE_STORAGE_BYTES: size + SIZE_STORAGE_BYTES].tolist())))\n return result\n except pickle.UnpicklingError:\n raise Exception(\n 'Unable to unpickle data from other workers. all_gather_list requires all '\n 'workers to enter the function together, so this error usually indicates '\n 'that the workers have fallen out of sync somehow. Workers can fall out of '\n 'sync if one of them runs out of memory, or if there are other conditions '\n 'in your training script that can cause one worker to finish an epoch '\n 'while other workers are still iterating over their portions of the data.'\n )","def _chunkify(arr, size):\n arrs = []\n for i in range(0, len(arr), size):\n chunk = bytearray(arr[i:i + size])\n arrs.append(chunk)\n return arrs","def chunk(flat, sizes):\n iter_flat = iter(flat)\n yield from (list(islice(iter_flat, 0, size)) for size in sizes)","def chunks(item_list, n_items):\n for i in range(0, len(item_list), n_items):\n yield item_list[i : i + n_items]","def gallery_groups(self):\n\n \"Collect data into fixed-length chunks or blocks\"\n # grouper(3, 'ABCDEFG', 'x') --> ABC DEF Gxx\n n = 3\n iterable = self.context['gallery'].values()\n args = [iter(iterable)] * 3\n return izip_longest(fillvalue=None, *args)","def chunks(sequence: Iterable[T], chunk_size: int = 2) -> Iterable[List[T]]:\n lsequence = list(sequence)\n while lsequence:\n size = min(len(lsequence), chunk_size)\n yield lsequence[:size]\n lsequence = lsequence[size:]","def chunks(l, n):\r\n for i in range(0, len(l), n):\r\n yield l[i:i + n]","def batch(byte_array, funcs):\n result = []\n length = bytes_to_int(byte_array[0:4])\n item_size = bytes_to_int(byte_array[4:8])\n for i in range(0, length):\n chunk = byte_array[8+i*item_size:8+(i+1)*item_size]\n for f in funcs:\n f(chunk)\n return result","def chunks(self, list_to_chunk, size):\n for i in range(0, len(list_to_chunk), size):\n yield list_to_chunk[i:i + size]","def chunker(iterable, size):\n for i in range(0, len(iterable), size):\n yield iterable[i:i + size]","def chunker(iterable, size):\n for i in range(0, len(iterable), size):\n yield iterable[i:i + size]","def chunker(iterable, size):\n for i in range(0, len(iterable), size):\n yield iterable[i:i + size]","def chunks(A, N):\n for i in range(0, len(A)):\n r = A[i:i+N]\n if len(r) == N:\n yield r","def chunks(self, l, n):\n for i in range(0, len(l), n):\n yield l[i:i + n]","def chunkify(list,size):\n for i in range (0, len(list), size):\n yield list[i:i+size]","def _batchify(self, data, align_right=False, include_lengths=False):\n lengths = [x.size(0) for x in data]\n max_length = max(lengths)\n out = data[0].new(len(data), max_length).fill_(neusum.Constants.PAD)\n for i in range(len(data)):\n data_length = data[i].size(0)\n offset = max_length - data_length if align_right else 0\n out[i].narrow(0, offset, data_length).copy_(data[i])\n\n if include_lengths:\n return out, lengths\n else:\n return out","def chunks(alist, n):\n for i in range(0, len(alist), n):\n yield alist[i:i + n]","def _buffered_func(dataset, size):\n\n class _EndSignal(object):\n pass\n\n end = _EndSignal()\n\n def _read_worker(r, q):\n for d in r:\n q.put(d)\n q.put(end)\n\n def _data_reader():\n r = dataset()\n q = multiprocessing.Queue(maxsize=size)\n t = multiprocessing.Process(\n target=_read_worker, args=(\n r,\n q, ))\n t.daemon = True\n t.start()\n e = q.get()\n while e != end:\n yield e\n e = q.get()\n\n return _data_reader","def chunks(iterator, size):\n for index in range(0, len(iterator), size):\n yield iterator[index:index + size]","def _read_blocks(input_data, size=2**20):\n\n if isinstance(input_data, (BufferedReader, BytesIO)):\n f = input_data\n opened = False\n elif input_data == '-':\n f = sys.stdin.buffer # read binary instead of unicode\n opened = False\n else:\n f = open(input_data, 'rb')\n opened = True\n\n try:\n\n data = f.read(size)\n while len(data) > 0:\n yield data\n data = f.read(size)\n finally:\n if opened:\n f.close()","def chunks(self, l, n):\n for i in xrange(0, len(l), n):\n yield l[i:i+n]","def chunks(l, n):\n for i in range(0, len(l), n):\n yield l[i:i+n]","def chunk(lst, chunk_len):\n\n for index in range(0, len(lst), chunk_len):\n yield lst[index:index + chunk_len]","def grouper(iterable, n):\n it = iter(iterable)\n while True:\n chunk = tuple(islice(it, n))\n if not chunk:\n return\n yield chunk","def _chunk(iterable, size, fillvalue=None):\n\t\targs = [iter(iterable)] * size\n\t\treturn [''.join(x) for x in itertools.izip_longest(*args, fillvalue=fillvalue)]","def chunks(l, n):\n for i in xrange(0, len(l), n):\n yield l[i:i + n]","def split_to_chunks(of_list, chunk_size):\n assert of_list is not None\n\n for i in range(0, len(of_list), chunk_size):\n yield of_list[i:i + chunk_size]","def chunks(l, n):\n for i in xrange(0, len(l), n):\n yield l[i:i+n]","def chunkize_serial(iterable, chunksize, as_numpy=False, dtype=np.float32):\n it = iter(iterable)\n while True:\n if as_numpy:\n # convert each document to a 2d numpy array (~6x faster when transmitting\n # chunk data over the wire, in Pyro)\n wrapped_chunk = [[np.array(doc, dtype=dtype) for doc in itertools.islice(it, int(chunksize))]]\n else:\n wrapped_chunk = [list(itertools.islice(it, int(chunksize)))]\n if not wrapped_chunk[0]:\n break\n # memory opt: wrap the chunk and then pop(), to avoid leaving behind a dangling reference\n yield wrapped_chunk.pop()","def pack_unpack_hard():\n # Array is apprx. 1.5 GB large\n # should make apprx 1536 chunks\n pack_unpack(100, chunk_size=reverse_pretty('1M'), progress=simple_progress)","def split_chunk(list, chunk_size):\n for i in range(0, len(list), chunk_size):\n yield list[i:i + chunk_size]","def chunks(array, size: int):\r\n for i in range(0, len(array), size):\r\n yield array[i:i + size]","def chunker(results, n):\n\n def grouper(iterable, n, fillvalue=None):\n args = [iter(iterable)] * n\n return zip_longest(*args, fillvalue=fillvalue)\n\n m = int(len(results) / n)\n return list(grouper(iterable=results, n=m, fillvalue=None))","def chunks(lst, chunk_size):\n for i in range(0, len(lst), chunk_size):\n yield lst[i:i + chunk_size]","def build_chunks(l, n):\r\n for i in xrange(0, len(l), n):\r\n yield l[i:i+n]","def chunk(l, n=500):\n return [l[i:i+n] for i in range(0, len(l), n)]","def chunks(l, n):\r\n for i in range(0, len(l), n):\r\n yield l[i:i + n]","def chunks(l, n):\r\n for i in range(0, len(l), n):\r\n yield l[i:i + n]","def chunks(l, n):\r\n for i in range(0, len(l), n):\r\n yield l[i:i + n]","def chunks(l, n):\r\n for i in range(0, len(l), n):\r\n yield l[i:i + n]","def chunks(l, n):\r\n for i in range(0, len(l), n):\r\n yield l[i:i + n]","def chunks(l, n):\n for i in range(0, n):\n yield l[i::n]","def chunks(self, big_list, n):\n for i in range(0, len(big_list), n):\n yield big_list[i:i + n]","def chunk(items, chunk_size):\n start_index = 0\n for start_index in xrange(0, len(items), chunk_size):\n end_index = min(start_index+chunk_size, len(items))\n yield items[start_index:end_index]","def buckets(data, n):\n # Shuffle all datasets to get a more consistent workload for all threads.\n random.shuffle(data)\n\n for i in range(0, len(data), n):\n yield data[i:i + n]","def chunks(l, n):\r\n for i in range(0, len(l), n):\r\n yield l[i:i+n]"],"string":"[\n \"def _chunk_data(self):\\n for n in range(0, len(self.data) + 1, len(self.data) //\\n self.num_of_chunks):\\n yield self.data[0 + n:len(self.data) // self.num_of_chunks + n]\",\n \"def chunks(data: list, n: int) -> list:\\n for i in range(0, len(data), n):\\n yield data[i:i + n]\",\n \"def chunks(data: List[Any], num: int) -> Generator[List[Any], None, None]:\\n for i in range(0, len(data), num):\\n yield data[i : i + num]\",\n \"def chunks(sequence, chunk_size):\\r\\n\\r\\n # YOUR CODE HERE\\r\",\n \"def chunks(data, rows=10000):\\n\\n for i in range(0, len(data), rows):\\n yield data[i:i+rows]\",\n \"def chunked(self, length, overlap):\\n def new_gen():\\n buffer = self.read(length)\\n while True:\\n yield np.array([buffer]) #pack into one more dimension\\n new_elems = self.read(length - overlap)\\n if new_elems.shape[0] == 0:\\n # Reached the end of the stream\\n break\\n buffer[:overlap] = buffer[length-overlap:]\\n buffer[overlap:] = new_elems\\n return Stream(new_gen(), chunk_size=1)\",\n \"def getChunks():\",\n \"def fill_buffer(self):\\n num_of_smp = 0\\n while num_of_smp < self.buf_size:\\n c, t = self.inlet.pull_chunk(timeout=0.0)\\n new_c = []\\n new_t = []\\n while c:\\n new_c += c\\n new_t += t\\n c, t = self.inlet.pull_chunk(timeout=0.0)\\n\\n # add samples to buffer\\n if any(new_c):\\n # add samples\\n num_of_smp += len(new_c)\\n data_v = [item for sublist in new_c for item in sublist]\\n self.gbuffer = np.roll(self.gbuffer, -len(data_v))\\n self.gbuffer[-len(data_v):] = data_v\\n # add timestamps\\n if new_t:\\n self.gtimes = np.roll(self.gtimes, -len(new_t))\\n self.gtimes[-len(new_t):] = new_t\",\n \"def _get_chunk_data(self, inputs: Iterable, chunk_size: int):\\n inputs_iter = iter(inputs)\\n while True:\\n try:\\n chunk_data = []\\n for _ in range(chunk_size):\\n processed_data = next(inputs_iter)\\n chunk_data.append(processed_data)\\n yield chunk_data\\n except StopIteration:\\n if chunk_data:\\n yield chunk_data\\n break\",\n \"def blockify_chunks(chunks):\\n acc = []\\n size = 0\\n for chunk, chunk_size in chunks:\\n assert len(chunk) == CHUNK_SIZE\\n assert len(acc) <= BLOCK_SIZE\\n if len(acc) == BLOCK_SIZE:\\n # Only the last chunk may be short.\\n assert size == CHUNK_SIZE * BLOCK_SIZE\\n yield acc, size\\n acc = []\\n size = 0\\n acc.append(chunk)\\n size += chunk_size\\n assert acc\\n yield acc, size\",\n \"def perform_chunking(self, data_size, chunk_size):\\r\\n\\r\\n chunks, i = [], 0\\r\\n while True:\\r\\n chunks.append((i * (chunk_size - self.overlap / 2), i * (chunk_size - self.overlap / 2) + chunk_size))\\r\\n i += 1\\r\\n if chunks[-1][1] > data_size:\\r\\n break\\r\\n\\r\\n n_count = len(chunks)\\r\\n chunks[-1] = tuple(x - (n_count * chunk_size - data_size - (n_count - 1) * self.overlap / 2) for x in chunks[-1])\\r\\n chunks = [(int(x), int(y)) for x, y in chunks]\\r\\n return chunks\",\n \"def recv_chunk(self, data):\",\n \"def chunked(size, source):\\n for i in range(0, len(source), size):\\n yield source[i : i + size]\",\n \"def static_batch(data, batch_size=16):\\n buf = []\\n for sample in data:\\n buf.append(sample)\\n if len(buf) >= batch_size:\\n yield buf\\n buf = []\\n if len(buf) > 0:\\n yield buf\",\n \"def in_memory_rechunk(\\n inputs: List[Tuple[core.ChunkKey, xarray.Dataset]],\\n target_chunks: Mapping[str, int],\\n) -> Iterator[Tuple[core.ChunkKey, xarray.Dataset]]:\\n key, dataset = consolidate_chunks(inputs)\\n yield from split_chunks(key, dataset, target_chunks)\",\n \"def chunk(seq, size, groupByList=True):\\n func = tuple\\n if groupByList:\\n func = list\\n return [func(seq[i:i + size]) for i in range(0, len(seq), size)]\",\n \"def chunk(max_elems = 8192, dtype = numpy.float64):\\n\\n @filters\\n def _dagpype_internal_fn_act(target):\\n assert max_elems > 0\\n dtype_ = dtype\\n\\n l = []\\n try:\\n while True:\\n while len(l) < max_elems:\\n l.append((yield))\\n target.send(numpy.array(l, dtype = dtype_))\\n l = []\\n except GeneratorExit:\\n if len(l) > 0:\\n target.send(numpy.array(l, dtype = dtype_)) \\n \\n return _dagpype_internal_fn_act\",\n \"def __chunks(l, n):\\n for i in range(0, len(l), n):\\n yield l[i:i + n]\",\n \"def some_payloaded_data(length=1000000, size=32, var=0):\\n for datum in some_simple_data(length):\\n yield DataWithPayload(datum, some_payload(size, var))\",\n \"def _chunker(self, seq, size):\\n return (seq.iloc[pos:pos + size] for pos in range(0, len(seq), size))\",\n \"def batch(self, data, size):\\n\\n return [data[x : x + size] for x in range(0, len(data), size)]\",\n \"def _chunks(l, n):\\n for i in range(0, len(l), n):\\n yield l[i:i + n]\",\n \"def _chunker(self, seq, size):\\n return (seq[pos:pos + size] for pos in range(0, len(seq), size))\",\n \"def prepare_batches(self, data):\\n batches = []\\n start, end = 0, 100\\n if len(data) > 100:\\n while True:\\n data_batch = data[start:end]\\n if not data_batch:\\n break\\n temp = end + 100\\n start, end = end, temp\\n if data_batch:\\n batches.append(data_batch)\\n else:\\n batches.append(data)\\n return batches\",\n \"def make_chunks(l, chunk_length):\\n for i in range(0, len(l), chunk_length):\\n yield l[i:i + chunk_length]\",\n \"def block_splitter(data, block_size):\\n buf = []\\n for i, datum in enumerate(data):\\n buf.append(datum)\\n if len(buf) == block_size:\\n yield buf\\n buf = []\\n\\n # If there's anything leftover (a partial block),\\n # yield it as well.\\n if buf:\\n yield buf\",\n \"def iter_unpack(raw):\\n return chunks(raw)\",\n \"def _chunks(l, n):\\n\\tfor i in range(0, len(l), n):\\n\\t\\tyield l[i:i + n]\",\n \"def iter_chunks(sequence, chunk_size) :\\n res = []\\n for item in sequence :\\n res.append(item)\\n if len(res) >= chunk_size :\\n yield res\\n res = []\\n if res : yield res\",\n \"def test_create_chunks():\\n items = list(range(0, 100))\\n size = 3\\n\\n chunks = create_chunks(items, size)\\n\\n current = next(chunks)\\n assert len(current) == size\\n assert current == [0, 1, 2]\\n\\n current = next(chunks)\\n assert current == [3, 4, 5]\",\n \"def chunk(it, size):\\n it = iter(it)\\n return iter(lambda: list(islice(it, size)), [])\",\n \"def build(self, block_size):\",\n \"def get_chunks(vals, size):\\n for i in range(0, len(vals), size):\\n yield vals[i:i + size]\",\n \"def chunks(items, size):\\n return [items[i:i+size] for i in range(0, len(items), size)]\",\n \"def chunked(self, n):\\n return imap(self.__class__, chunked(self._bytes, n))\",\n \"def batches(data, batch_size) -> list:\\n rv = []\\n for idx, line in enumerate(data):\\n if idx != 0 and idx % batch_size == 0:\\n yield rv\\n rv = []\\n rv.append(line)\\n yield rv\",\n \"def _get_data_chunk(self):\\n if self._start_pos < self.max_pos:\\n self._current_sho_spec_slice = slice(self.sho_spec_inds_per_forc * self._current_forc,\\n self.sho_spec_inds_per_forc * (self._current_forc + 1))\\n self._end_pos = int(min(self.h5_main.shape[0], self._start_pos + self.max_pos))\\n self.data = self.h5_main[self._start_pos:self._end_pos, self._current_sho_spec_slice]\\n elif self._current_forc < self._num_forcs - 1:\\n # Resest for next FORC\\n self._current_forc += 1\\n\\n self._current_sho_spec_slice = slice(self.sho_spec_inds_per_forc * self._current_forc,\\n self.sho_spec_inds_per_forc * (self._current_forc + 1))\\n self._current_met_spec_slice = slice(self.metrics_spec_inds_per_forc * self._current_forc,\\n self.metrics_spec_inds_per_forc * (self._current_forc + 1))\\n self._get_dc_offset()\\n\\n self._start_pos = 0\\n self._end_pos = int(min(self.h5_main.shape[0], self._start_pos + self.max_pos))\\n self.data = self.h5_main[self._start_pos:self._end_pos, self._current_sho_spec_slice]\\n\\n else:\\n self.data = None\\n\\n return\",\n \"def chunk(size, seq):\\n if not isinstance(size, int) or size <= 0: # pragma: no cover\\n raise ValueError(\\\"size must be an integer greater than zero\\\")\\n\\n group = []\\n\\n for item in seq:\\n if len(group) >= size:\\n yield group\\n group = []\\n group.append(item)\\n\\n if group:\\n yield group\",\n \"def _chunk(self, l, n):\\n for i in range(0, len(l) + 1, n):\\n yield l[i:i + n]\",\n \"def get_chunks(sequence, ck_size):\\n \\n list_chunk = []\\n i=1\\n l = len(sequence)\\n if l < 4*ck_size:\\n raise ValueError(\\\"Chunk size should be of 4 at least \\\")\\n for i in range(1, l):\\n if i*ck_size < l:\\n list_chunk.append(sequence[i*ck_size-ck_size:i*ck_size])\\n #while(i*ck_size < l):\\n #list_chunk.append(sequence[i*ck_size-ck_size:i*ck_size])\\n #i += 1\\n return list_chunk\",\n \"def chunks(seq, size):\\n for i in range(0, len(seq), size):\\n yield seq[i:i + size]\",\n \"def chunks(items, chunk_size):\\r\\n items = list(items)\\r\\n return (items[i:i + chunk_size] for i in xrange(0, len(items), chunk_size))\",\n \"def chunks(arr, n):\\n for i in range(0, len(arr), n):\\n yield arr[i:i + n]\",\n \"def get_chunks(self, l, n):\\r\\n for i in range(0, len(l), n):\\r\\n yield l[i:i+n]\",\n \"def _get_chunks(l, n = 10):\\n \\n for i in range(0, len(l), n): yield l[i: i + n]\",\n \"def chunker(seq, size):\\n\\n return (seq[pos : pos + size] for pos in range(0, len(seq), size))\",\n \"def __iter__(self):\\n\\n # collector will fetch chunksize array for each 'get' call\\n collector = FIFOArray(self.chunksize, self.axis)\\n\\n # make tmp array to hold generated subarrs\\n tmp = []\\n tmp_size = 0\\n for subarr in self.data(**self.kwargs):\\n\\n tmp.append(subarr)\\n tmp_size += subarr.shape[self.axis]\\n\\n # if tmp exceeds chunksize put in collector\\n if tmp_size >= self.chunksize:\\n arr = np.concatenate(tmp, axis=self.axis)\\n collector.put(arr)\\n\\n # fetch chunksize till not full\\n while collector.full():\\n yield collector.get()\\n\\n # place leftover back into tmp and empty collector\\n tmp = [collector.queue]\\n tmp_size = collector.qsize()\\n collector.queue = np.array([])\\n\\n else:\\n\\n # append to tmp again\\n continue\\n\\n # else runs after normal loop exit -- required here\\n else: #pylint: disable=useless-else-on-loop\\n\\n # yield whatever is left in tmp (its below chunksize)\\n remaining = np.concatenate(tmp, axis=self.axis)\\n if remaining.size > 0:\\n yield remaining\",\n \"def chunks(data, overrides = {}):\\n counter, filesize = 0, len(data)\\n last = None\\n while counter < filesize:\\n try:\\n magic, size = chunk.unpack_from(data, counter)\\n except struct_error as e:\\n print('failed loading chunk from', data[:counter])\\n print('last chunk:', last)\\n raise e\\n\\n counter += chunk.size\\n contents = data[counter:counter+size]\\n\\n if magic[3] != 0x4D:\\n raise Exception('bad magic', magic, 'last chunk:', last)\\n\\n if magic in overrides:\\n size = overrides[magic]\\n\\n yield magic, size, contents\\n counter += size\\n\\n last = (magic, size, contents)\",\n \"def chunks(arr, n):\\n for i in range(0, len(arr), n):\\n yield arr[i:i + n]\",\n \"def test_chunk_memory(self):\\n layer = tl.Serial(tl.Dense(1024*1024), tl.Dense(128))\\n chunked = tl.Chunk(layer, 256)\\n x = np.random.uniform(size=(16*1024, 16))\\n chunked.init(shapes.signature(x))\\n y = chunked(x)\\n z = tl.Accelerate(chunked)(x)\\n self.assertEqual(y.shape, (16*1024, 128))\\n self.assertEqual(z.shape, (16*1024, 128))\",\n \"def chunk(list, chunksize):\\n for i in range(0, len(list), chunksize):\\n yield list[i:i + chunksize]\",\n \"def _chunks(l, n):\\n for i in xrange(0, len(l), n):\\n yield l[i:i + n]\",\n \"def Chunks(l):\\n return_list = [[]]\\n counter = 0\\n index = 0\\n for i in l:\\n # Size is split in half due to the max size being a sum of src and dst.\\n if counter > (self._ADDRESS_LENGTH_LIMIT/2):\\n counter = 0\\n index += 1\\n return_list.append([])\\n if i.version == 6:\\n counter += self._IPV6_SIZE\\n else:\\n counter += 1\\n return_list[index].append(i)\\n return return_list\",\n \"def chunks(self, n):\\n return _([self._[i:i+n] for i in range(0, self.size()._, n)])\",\n \"def chunks(l, n):\\n for i in xrange(0, len(l), n):\\n yield l[i:i+n]\",\n \"def all_gather_list(data, group=None, max_size=16384):\\n SIZE_STORAGE_BYTES = 4 # int32 to encode the payload size\\n\\n enc = pickle.dumps(data)\\n enc_size = len(enc)\\n\\n if enc_size + SIZE_STORAGE_BYTES > max_size:\\n raise ValueError(\\n 'encoded data exceeds max_size, this can be fixed by increasing buffer size: {}'.format(enc_size))\\n\\n rank = get_rank()\\n world_size = get_world_size()\\n buffer_size = max_size * world_size\\n\\n if not hasattr(all_gather_list, '_buffer') or \\\\\\n all_gather_list._buffer.numel() < buffer_size:\\n all_gather_list._buffer = torch.cuda.ByteTensor(buffer_size)\\n all_gather_list._cpu_buffer = torch.ByteTensor(max_size).pin_memory()\\n\\n buffer = all_gather_list._buffer\\n buffer.zero_()\\n cpu_buffer = all_gather_list._cpu_buffer\\n\\n assert enc_size < 256 ** SIZE_STORAGE_BYTES, 'Encoded object size should be less than {} bytes'.format(\\n 256 ** SIZE_STORAGE_BYTES)\\n\\n size_bytes = enc_size.to_bytes(SIZE_STORAGE_BYTES, byteorder='big')\\n\\n cpu_buffer[0:SIZE_STORAGE_BYTES] = torch.ByteTensor(list(size_bytes))\\n cpu_buffer[SIZE_STORAGE_BYTES: enc_size + SIZE_STORAGE_BYTES] = torch.ByteTensor(list(enc))\\n\\n start = rank * max_size\\n size = enc_size + SIZE_STORAGE_BYTES\\n buffer[start: start + size].copy_(cpu_buffer[:size])\\n\\n all_reduce(buffer, group=group)\\n\\n try:\\n result = []\\n for i in range(world_size):\\n out_buffer = buffer[i * max_size: (i + 1) * max_size]\\n size = int.from_bytes(out_buffer[0:SIZE_STORAGE_BYTES], byteorder='big')\\n if size > 0:\\n result.append(pickle.loads(bytes(out_buffer[SIZE_STORAGE_BYTES: size + SIZE_STORAGE_BYTES].tolist())))\\n return result\\n except pickle.UnpicklingError:\\n raise Exception(\\n 'Unable to unpickle data from other workers. all_gather_list requires all '\\n 'workers to enter the function together, so this error usually indicates '\\n 'that the workers have fallen out of sync somehow. Workers can fall out of '\\n 'sync if one of them runs out of memory, or if there are other conditions '\\n 'in your training script that can cause one worker to finish an epoch '\\n 'while other workers are still iterating over their portions of the data.'\\n )\",\n \"def _chunkify(arr, size):\\n arrs = []\\n for i in range(0, len(arr), size):\\n chunk = bytearray(arr[i:i + size])\\n arrs.append(chunk)\\n return arrs\",\n \"def chunk(flat, sizes):\\n iter_flat = iter(flat)\\n yield from (list(islice(iter_flat, 0, size)) for size in sizes)\",\n \"def chunks(item_list, n_items):\\n for i in range(0, len(item_list), n_items):\\n yield item_list[i : i + n_items]\",\n \"def gallery_groups(self):\\n\\n \\\"Collect data into fixed-length chunks or blocks\\\"\\n # grouper(3, 'ABCDEFG', 'x') --> ABC DEF Gxx\\n n = 3\\n iterable = self.context['gallery'].values()\\n args = [iter(iterable)] * 3\\n return izip_longest(fillvalue=None, *args)\",\n \"def chunks(sequence: Iterable[T], chunk_size: int = 2) -> Iterable[List[T]]:\\n lsequence = list(sequence)\\n while lsequence:\\n size = min(len(lsequence), chunk_size)\\n yield lsequence[:size]\\n lsequence = lsequence[size:]\",\n \"def chunks(l, n):\\r\\n for i in range(0, len(l), n):\\r\\n yield l[i:i + n]\",\n \"def batch(byte_array, funcs):\\n result = []\\n length = bytes_to_int(byte_array[0:4])\\n item_size = bytes_to_int(byte_array[4:8])\\n for i in range(0, length):\\n chunk = byte_array[8+i*item_size:8+(i+1)*item_size]\\n for f in funcs:\\n f(chunk)\\n return result\",\n \"def chunks(self, list_to_chunk, size):\\n for i in range(0, len(list_to_chunk), size):\\n yield list_to_chunk[i:i + size]\",\n \"def chunker(iterable, size):\\n for i in range(0, len(iterable), size):\\n yield iterable[i:i + size]\",\n \"def chunker(iterable, size):\\n for i in range(0, len(iterable), size):\\n yield iterable[i:i + size]\",\n \"def chunker(iterable, size):\\n for i in range(0, len(iterable), size):\\n yield iterable[i:i + size]\",\n \"def chunks(A, N):\\n for i in range(0, len(A)):\\n r = A[i:i+N]\\n if len(r) == N:\\n yield r\",\n \"def chunks(self, l, n):\\n for i in range(0, len(l), n):\\n yield l[i:i + n]\",\n \"def chunkify(list,size):\\n for i in range (0, len(list), size):\\n yield list[i:i+size]\",\n \"def _batchify(self, data, align_right=False, include_lengths=False):\\n lengths = [x.size(0) for x in data]\\n max_length = max(lengths)\\n out = data[0].new(len(data), max_length).fill_(neusum.Constants.PAD)\\n for i in range(len(data)):\\n data_length = data[i].size(0)\\n offset = max_length - data_length if align_right else 0\\n out[i].narrow(0, offset, data_length).copy_(data[i])\\n\\n if include_lengths:\\n return out, lengths\\n else:\\n return out\",\n \"def chunks(alist, n):\\n for i in range(0, len(alist), n):\\n yield alist[i:i + n]\",\n \"def _buffered_func(dataset, size):\\n\\n class _EndSignal(object):\\n pass\\n\\n end = _EndSignal()\\n\\n def _read_worker(r, q):\\n for d in r:\\n q.put(d)\\n q.put(end)\\n\\n def _data_reader():\\n r = dataset()\\n q = multiprocessing.Queue(maxsize=size)\\n t = multiprocessing.Process(\\n target=_read_worker, args=(\\n r,\\n q, ))\\n t.daemon = True\\n t.start()\\n e = q.get()\\n while e != end:\\n yield e\\n e = q.get()\\n\\n return _data_reader\",\n \"def chunks(iterator, size):\\n for index in range(0, len(iterator), size):\\n yield iterator[index:index + size]\",\n \"def _read_blocks(input_data, size=2**20):\\n\\n if isinstance(input_data, (BufferedReader, BytesIO)):\\n f = input_data\\n opened = False\\n elif input_data == '-':\\n f = sys.stdin.buffer # read binary instead of unicode\\n opened = False\\n else:\\n f = open(input_data, 'rb')\\n opened = True\\n\\n try:\\n\\n data = f.read(size)\\n while len(data) > 0:\\n yield data\\n data = f.read(size)\\n finally:\\n if opened:\\n f.close()\",\n \"def chunks(self, l, n):\\n for i in xrange(0, len(l), n):\\n yield l[i:i+n]\",\n \"def chunks(l, n):\\n for i in range(0, len(l), n):\\n yield l[i:i+n]\",\n \"def chunk(lst, chunk_len):\\n\\n for index in range(0, len(lst), chunk_len):\\n yield lst[index:index + chunk_len]\",\n \"def grouper(iterable, n):\\n it = iter(iterable)\\n while True:\\n chunk = tuple(islice(it, n))\\n if not chunk:\\n return\\n yield chunk\",\n \"def _chunk(iterable, size, fillvalue=None):\\n\\t\\targs = [iter(iterable)] * size\\n\\t\\treturn [''.join(x) for x in itertools.izip_longest(*args, fillvalue=fillvalue)]\",\n \"def chunks(l, n):\\n for i in xrange(0, len(l), n):\\n yield l[i:i + n]\",\n \"def split_to_chunks(of_list, chunk_size):\\n assert of_list is not None\\n\\n for i in range(0, len(of_list), chunk_size):\\n yield of_list[i:i + chunk_size]\",\n \"def chunks(l, n):\\n for i in xrange(0, len(l), n):\\n yield l[i:i+n]\",\n \"def chunkize_serial(iterable, chunksize, as_numpy=False, dtype=np.float32):\\n it = iter(iterable)\\n while True:\\n if as_numpy:\\n # convert each document to a 2d numpy array (~6x faster when transmitting\\n # chunk data over the wire, in Pyro)\\n wrapped_chunk = [[np.array(doc, dtype=dtype) for doc in itertools.islice(it, int(chunksize))]]\\n else:\\n wrapped_chunk = [list(itertools.islice(it, int(chunksize)))]\\n if not wrapped_chunk[0]:\\n break\\n # memory opt: wrap the chunk and then pop(), to avoid leaving behind a dangling reference\\n yield wrapped_chunk.pop()\",\n \"def pack_unpack_hard():\\n # Array is apprx. 1.5 GB large\\n # should make apprx 1536 chunks\\n pack_unpack(100, chunk_size=reverse_pretty('1M'), progress=simple_progress)\",\n \"def split_chunk(list, chunk_size):\\n for i in range(0, len(list), chunk_size):\\n yield list[i:i + chunk_size]\",\n \"def chunks(array, size: int):\\r\\n for i in range(0, len(array), size):\\r\\n yield array[i:i + size]\",\n \"def chunker(results, n):\\n\\n def grouper(iterable, n, fillvalue=None):\\n args = [iter(iterable)] * n\\n return zip_longest(*args, fillvalue=fillvalue)\\n\\n m = int(len(results) / n)\\n return list(grouper(iterable=results, n=m, fillvalue=None))\",\n \"def chunks(lst, chunk_size):\\n for i in range(0, len(lst), chunk_size):\\n yield lst[i:i + chunk_size]\",\n \"def build_chunks(l, n):\\r\\n for i in xrange(0, len(l), n):\\r\\n yield l[i:i+n]\",\n \"def chunk(l, n=500):\\n return [l[i:i+n] for i in range(0, len(l), n)]\",\n \"def chunks(l, n):\\r\\n for i in range(0, len(l), n):\\r\\n yield l[i:i + n]\",\n \"def chunks(l, n):\\r\\n for i in range(0, len(l), n):\\r\\n yield l[i:i + n]\",\n \"def chunks(l, n):\\r\\n for i in range(0, len(l), n):\\r\\n yield l[i:i + n]\",\n \"def chunks(l, n):\\r\\n for i in range(0, len(l), n):\\r\\n yield l[i:i + n]\",\n \"def chunks(l, n):\\r\\n for i in range(0, len(l), n):\\r\\n yield l[i:i + n]\",\n \"def chunks(l, n):\\n for i in range(0, n):\\n yield l[i::n]\",\n \"def chunks(self, big_list, n):\\n for i in range(0, len(big_list), n):\\n yield big_list[i:i + n]\",\n \"def chunk(items, chunk_size):\\n start_index = 0\\n for start_index in xrange(0, len(items), chunk_size):\\n end_index = min(start_index+chunk_size, len(items))\\n yield items[start_index:end_index]\",\n \"def buckets(data, n):\\n # Shuffle all datasets to get a more consistent workload for all threads.\\n random.shuffle(data)\\n\\n for i in range(0, len(data), n):\\n yield data[i:i + n]\",\n \"def chunks(l, n):\\r\\n for i in range(0, len(l), n):\\r\\n yield l[i:i+n]\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.719677","0.6773225","0.6730021","0.6680324","0.6640408","0.6590066","0.65835804","0.6442601","0.6409235","0.6338401","0.6329446","0.63054276","0.62845904","0.62551296","0.6208536","0.61931676","0.61904657","0.61624444","0.6139798","0.61395085","0.6132434","0.61276203","0.6122731","0.61212295","0.61159533","0.6108721","0.60819376","0.60680634","0.6058476","0.60563767","0.6053068","0.6041372","0.6037783","0.6036225","0.6011828","0.5996495","0.59833133","0.59762454","0.59653133","0.5952669","0.59524304","0.5948817","0.5948479","0.594678","0.5946217","0.5940416","0.59388435","0.59384","0.59298396","0.592769","0.5925492","0.59121263","0.5911052","0.5909056","0.59083295","0.5897241","0.5893316","0.5885597","0.5879244","0.5874232","0.5871904","0.5859664","0.5855663","0.58546954","0.5853913","0.5853913","0.5853913","0.58535653","0.5852855","0.5848501","0.5845817","0.58451694","0.584331","0.5841809","0.5839486","0.5839036","0.58389395","0.58332","0.5832653","0.5830454","0.5827135","0.58199453","0.581866","0.58033884","0.58030635","0.57974917","0.57962865","0.57903546","0.57886183","0.57842547","0.57822704","0.5781485","0.5781485","0.5781485","0.5781485","0.5781485","0.5775787","0.57757515","0.57732415","0.5771817","0.57689655"],"string":"[\n \"0.719677\",\n \"0.6773225\",\n \"0.6730021\",\n \"0.6680324\",\n \"0.6640408\",\n \"0.6590066\",\n \"0.65835804\",\n \"0.6442601\",\n \"0.6409235\",\n \"0.6338401\",\n \"0.6329446\",\n \"0.63054276\",\n \"0.62845904\",\n \"0.62551296\",\n \"0.6208536\",\n \"0.61931676\",\n \"0.61904657\",\n \"0.61624444\",\n \"0.6139798\",\n \"0.61395085\",\n \"0.6132434\",\n \"0.61276203\",\n \"0.6122731\",\n \"0.61212295\",\n \"0.61159533\",\n \"0.6108721\",\n \"0.60819376\",\n \"0.60680634\",\n \"0.6058476\",\n \"0.60563767\",\n \"0.6053068\",\n \"0.6041372\",\n \"0.6037783\",\n \"0.6036225\",\n \"0.6011828\",\n \"0.5996495\",\n \"0.59833133\",\n \"0.59762454\",\n \"0.59653133\",\n \"0.5952669\",\n \"0.59524304\",\n \"0.5948817\",\n \"0.5948479\",\n \"0.594678\",\n \"0.5946217\",\n \"0.5940416\",\n \"0.59388435\",\n \"0.59384\",\n \"0.59298396\",\n \"0.592769\",\n \"0.5925492\",\n \"0.59121263\",\n \"0.5911052\",\n \"0.5909056\",\n \"0.59083295\",\n \"0.5897241\",\n \"0.5893316\",\n \"0.5885597\",\n \"0.5879244\",\n \"0.5874232\",\n \"0.5871904\",\n \"0.5859664\",\n \"0.5855663\",\n \"0.58546954\",\n \"0.5853913\",\n \"0.5853913\",\n \"0.5853913\",\n \"0.58535653\",\n \"0.5852855\",\n \"0.5848501\",\n \"0.5845817\",\n \"0.58451694\",\n \"0.584331\",\n \"0.5841809\",\n \"0.5839486\",\n \"0.5839036\",\n \"0.58389395\",\n \"0.58332\",\n \"0.5832653\",\n \"0.5830454\",\n \"0.5827135\",\n \"0.58199453\",\n \"0.581866\",\n \"0.58033884\",\n \"0.58030635\",\n \"0.57974917\",\n \"0.57962865\",\n \"0.57903546\",\n \"0.57886183\",\n \"0.57842547\",\n \"0.57822704\",\n \"0.5781485\",\n \"0.5781485\",\n \"0.5781485\",\n \"0.5781485\",\n \"0.5781485\",\n \"0.5775787\",\n \"0.57757515\",\n \"0.57732415\",\n \"0.5771817\",\n \"0.57689655\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":94899,"cells":{"query":{"kind":"string","value":"Temporal workaround for static template tag to support SCRIPT_NAME"},"document":{"kind":"string","value":"def static(parser, token):\n return NewStaticNode.handle_token(parser, token)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_script_name(t_req):\n if settings.FORCE_SCRIPT_NAME is not None:\n return force_text(settings.FORCE_SCRIPT_NAME)\n\n # If Apache's mod_rewrite had a whack at the URL, Apache set either\n # SCRIPT_URL or REDIRECT_URL to the full resource URL before applying any\n # rewrites. Unfortunately not every Web server (lighttpd!) passes this\n # information through all the time, so FORCE_SCRIPT_NAME, above, is still\n # needed.\n script_url = t_req.headers.get('SCRIPT_URL', '')\n if not script_url:\n script_url = t_req.headers.get('REDIRECT_URL', '')\n\n if script_url:\n path_info = t_req.headers.get('PATH_INFO', '')\n script_name = script_url[:-len(path_info)]\n else:\n script_name = t_req.headers.get('SCRIPT_NAME', '')\n\n # It'd be better to implement URI-to-IRI decoding, see #19508.\n # return script_name.decode(UTF_8)\n return script_name","def ext_static(context, extension, path):\n return static('ext/%s/%s' % (extension.id, path))","def get_js_file(self):\n return 'placeholder'","def third_party_scripts(request):\n return {\n 'ORCHESTRA_THIRD_PARTY_SCRIPTS_TEMPLATE':\n settings.ORCHESTRA_THIRD_PARTY_SCRIPTS_TEMPLATE\n }","def get_default_javascript():\n return [\"_static/require.js\"]","def getScriptname():\n return os.environ.get('SCRIPT_NAME', '')","def static(request):\n return {\n 'JSERRORLOGGING_STATIC_URL': STATIC_URL\n }","def static(filename):\n\ttimestamp = os.path.getmtime(os.path.join(app.static_folder, filename))\n\treturn \"%s/%s?%s\" % (app.static_url_path, filename, timestamp)","def static(filename):\n\ttimestamp = os.path.getmtime(os.path.join(app.static_folder, filename))\n\treturn \"%s/%s?%s\" % (app.static_url_path, filename, timestamp)","def replacement(self):\n assert (self.src or self.inline) and not (self.src and self.inline)\n if self.src:\n return '<script async type=\"text/javascript\" src=\"%s\"></script>' % urllib.quote(self.src)\n else:\n return '<script>\\n%s\\n</script>' % self.inline","def module_use_template_javascript(self):\n return False","def module_use_template_javascript(self):\n return False","def add_static(ext):\n ext = ext.lower()\n\n compiler = StaticCompiler(ext)\n file_list = compiler.get_staticfiles_list()\n\n return render_to_string(\n \"mub/context_%s.html\" % ext,\n {\n \"items\": file_list,\n \"STATIC_URL\": settings.STATIC_URL,\n \"IS_MINIFIED\": compiler.is_minified\n }\n )","def path_static():\n return os.path.abspath(os.path.dirname(__file__))+'/_static'","def include_admin_script(script_path):\n if not absolute_url_re.match(script_path):\n script_path = '%s%s' % (settings.ADMIN_MEDIA_PREFIX, script_path)\n return '<script type=\"text/javascript\" src=\"%s\"></script>' % script_path","def static_html(subpath):\n return render_template(f'static_html/{subpath}.html')","def _template_file_default(self):\n return \"index\"","def get_wsgi_file_name(self):\n return self.wsgi","def render(self, template_name, **kwargs):\n currentUser = self.current_user\n from_workspace_str = self.get_argument(\"from_workspace\", default=\"0\", strip=False)\n from_workspace = from_workspace_str == \"1\"\n html = self.render_string(template_name, currentUser=currentUser, from_workspace = from_workspace, **kwargs)\n if from_workspace :\n scriptName = self.__class__.__name__\n\n if scriptName.endswith('Handler') :\n scriptName = scriptName[:-7] \n\n path = self.static_url('scripts/' + scriptName + '.js')\n\n js = '<script src=\"' + escape.xhtml_escape(path) + '\" type=\"text/javascript\"></script>'\n html = html + utf8(js)\n self.finish(html)\n return\n\n # Insert the additional JS and CSS added by the modules on the page\n js_embed = []\n js_files = []\n css_embed = []\n css_files = []\n html_heads = []\n html_bodies = []\n for module in getattr(self, \"_active_modules\", {}).values():\n embed_part = module.embedded_javascript()\n if embed_part:\n js_embed.append(utf8(embed_part))\n file_part = module.javascript_files()\n if file_part:\n if isinstance(file_part, (unicode_type, bytes_type)):\n js_files.append(file_part)\n else:\n js_files.extend(file_part)\n embed_part = module.embedded_css()\n if embed_part:\n css_embed.append(utf8(embed_part))\n file_part = module.css_files()\n if file_part:\n if isinstance(file_part, (unicode_type, bytes_type)):\n css_files.append(file_part)\n else:\n css_files.extend(file_part)\n head_part = module.html_head()\n if head_part:\n html_heads.append(utf8(head_part))\n body_part = module.html_body()\n if body_part:\n html_bodies.append(utf8(body_part))\n\n def is_absolute(path):\n return any(path.startswith(x) for x in [\"/\", \"http:\", \"https:\"])\n if js_files:\n # Maintain order of JavaScript files given by modules\n paths = []\n unique_paths = set()\n for path in js_files:\n if not is_absolute(path):\n path = self.static_url(path)\n if path not in unique_paths:\n paths.append(path)\n unique_paths.add(path)\n js = ''.join('<script src=\"' + escape.xhtml_escape(p) +\n '\" type=\"text/javascript\"></script>'\n for p in paths)\n sloc = html.rindex(b'</body>')\n html = html[:sloc] + utf8(js) + b'\\n' + html[sloc:]\n if js_embed:\n js = b'<script type=\"text/javascript\">\\n//<![CDATA[\\n' + \\\n b'\\n'.join(js_embed) + b'\\n//]]>\\n</script>'\n sloc = html.rindex(b'</body>')\n html = html[:sloc] + js + b'\\n' + html[sloc:]\n if css_files:\n paths = []\n unique_paths = set()\n for path in css_files:\n if not is_absolute(path):\n path = self.static_url(path)\n if path not in unique_paths:\n paths.append(path)\n unique_paths.add(path)\n css = ''.join('<link href=\"' + escape.xhtml_escape(p) + '\" '\n 'type=\"text/css\" rel=\"stylesheet\"/>'\n for p in paths)\n hloc = html.index(b'</head>')\n html = html[:hloc] + utf8(css) + b'\\n' + html[hloc:]\n if css_embed:\n css = b'<style type=\"text/css\">\\n' + b'\\n'.join(css_embed) + \\\n b'\\n</style>'\n hloc = html.index(b'</head>')\n html = html[:hloc] + css + b'\\n' + html[hloc:]\n if html_heads:\n hloc = html.index(b'</head>')\n html = html[:hloc] + b''.join(html_heads) + b'\\n' + html[hloc:]\n if html_bodies:\n hloc = html.index(b'</body>')\n html = html[:hloc] + b''.join(html_bodies) + b'\\n' + html[hloc:]\n self.finish(html)","def server_static (filename):\n return static_file(filename, root=\"./static\")","def include_static_files(app):\n file_path = sphinx_prolog.get_static_path(STATIC_FILE)\n if file_path not in app.config.html_static_path:\n app.config.html_static_path.append(file_path)","def render(request, template):\r\n return render_to_response('static_templates/' + template, {})","def topcoat_icons_script_tag():\n return u'<script type=\"text/javascript src=\"%s\"></script>' % topcoat_icons_script_url()","def template_name(self):\n\t\traise NotImplementedError('template_name must be defined')","def scriptpath(self, code):\n return '' if code == 'en' else ('/' + code)","def get_script_name(self, locale: Locale | str | None = None) -> str | None:\n if locale is None:\n locale = self\n locale = Locale.parse(locale)\n return locale.scripts.get(self.script or '')","def glr_path_static():\n return os.path.join(base_path, \"static\")","def url(self, url):\n prefix = self.request_local.environ['toscawidgets.prefix']\n script_name = self.request_local.environ['SCRIPT_NAME']\n if hasattr(url, 'url_mapping'):\n url = url.url_mapping['normal']\n return ''.join([script_name, prefix, url])","def static_index():\n return \"xxxxxx.your-domain.tld\"","def server_static(filename):\n return static_file(filename, root='static/stats')","def add_javascripts_subscriber(event):\n c = event.request.tmpl_context\n c.javascripts = [\n ('spline', 'lib/jquery-1.7.1.min'),\n ('spline', 'lib/jquery.cookies-2.2.0.min'),\n ('spline', 'lib/jquery.ui-1.8.4.min'),\n ('spline', 'core'),\n ('pokedex', 'pokedex-suggestions'),\n ('pokedex', 'pokedex'), # XXX only on main pokedex pages\n ]","def get_available_name(self, name, *args, **kwargs):\n # If the filename already exists, remove it as if it was a true file system\n if self.exists(name) and os.path.exists(\n os.path.join(settings.STATIC_ROOT, name)):\n os.remove(os.path.join(settings.STATIC_ROOT, name))\n return name","def static(website, request, **etc):\n return website.static.respond(request)","def _remap_static(self, stream, prefix='/static/'):\n def map_static(name, event):\n attrs = event[1][1]\n name = attrs.get(name)[len(prefix):]\n if self.static_map:\n name = self.static_map.get(name, name)\n return static(name)\n return stream | Transformer('//*[matches(@src, \"^%s\")]' % prefix).attr('src', map_static) | \\\n Transformer('//*[matches(@href, \"^%s\")]' % prefix).attr('href', map_static)","def complete_static_filename(self, filename):\n return staticfiles_finder(filename)","def get_template_name(self):\n if self.template_name:\n return self.template_name\n\n if Path('_templates/global/WaitPage.html').exists():\n return 'global/WaitPage.html'\n return 'otree/WaitPage.html'","def static(filename):\n return href.static(file=filename)","def href(self, request) -> str:\n return request.static_path(self.url_spec)","def static(self, filename):\n return send_from_directory(self.static_path, filename)","def template_loader(self):\n return None","def djangify(line: str):\n\n global APP_NAME\n\n # Don't change the contents of the line if it contails a URL that links\n # outside content. Ex. www.example.com/webpage.html\n if containsURL(line):\n return line\n # Don't change the line if it contains placeholder URL like '#'\n if line == '#':\n return line\n # If line links to an internal file, make it Django compatible by loading\n # from static directory appended with APP_NAME\n return \" {% static '\" + APP_NAME + line + \"' %} \"","def get_src_js(self):\n if self.get_style() != self.STYLE_BASE:\n return f\"dtables/js/dataTables.{self.get_style()}.js\"\n else:\n return f\"dtables/js/{self.get_style()}.dataTables.js\"","def core_cdn_file(request, source):\n\n file_path = settings.CENTIPAIR_TEMPLATE_DIR + \"/cdn/\" + source\n source_file_url = settings.TEMPLATE_STATIC_URL + \"/\" + file_path\n return source_file_url","def resource_js(self):\n \n portal_url = getSite().absolute_url()\n \n return \"\"\"\n <script type=\"text/javascript\" src=\"%s/++resource++swfobject.js\"></script>\n <script type=\"text/javascript\" src=\"%s/++resource++audio_player.js\"></script> \n <script type=\"text/javascript\"> \n AudioPlayer.setup(\"%s/++resource++audio_player.swf\", { \n width: 300\n }); \n </script>\n \"\"\" % (portal_url, portal_url, portal_url)","def getBaseURL():\n return getQualifiedURL(getScriptname())","def get_template_name(request, base_template_name):\n template_base_dir = get_template_base_directory(request)\n return f\"cast/{template_base_dir}/{base_template_name}\"","def staticfile(path):\n normalized_path = posixpath.normpath(urllib.unquote(path)).lstrip('/')\n absolute_path = finders.find(normalized_path)\n if not absolute_path and getattr(settings, 'STATIC_ROOT', None):\n absolute_path = os.path.join(settings.STATIC_ROOT, path)\n if absolute_path:\n return '%s%s?v=%s' % (settings.STATIC_URL, path, os.stat(absolute_path)[stat.ST_MTIME])\n return path","def static_url(self, path):\n\t\tif not hasattr(self, \"_static_hashes\"):\n\t\t\tself._static_hashes = {}\n\t\thashes = self._static_hashes\n\t\tif path not in hashes:\n\t\t\timport hashlib\n\t\t\ttry:\n\t\t\t\tf = open(os.path.join(\n\t\t\t\t\tself.application.settings[\"static_path\"], path))\n\t\t\t\thashes[path] = hashlib.md5(f.read()).hexdigest()\n\t\t\t\tf.close()\n\t\t\texcept:\n\t\t\t\tprint \"Could not open static file %r\"%path\n\t\t\t\thashes[path] = None\n\t\tbase = \"http://static.\"+_config.get(\"varnish\", \"ovzcphost\") + \"/\"\n\t\tif hashes.get(path):\n\t\t\treturn base + path + \"?v=\" + hashes[path][:5]\n\t\telse:\n\t\t\treturn base + path","def get_xmodule_urls():\r\n if settings.DEBUG:\r\n paths = [path.replace(\".coffee\", \".js\") for path in\r\n settings.PIPELINE_JS['module-js']['source_filenames']]\r\n else:\r\n paths = [settings.PIPELINE_JS['module-js']['output_filename']]\r\n return [staticfiles_storage.url(path) for path in paths]","def asset_tag(request, key, **kwargs):\n theme = request.theme\n asset = theme.stacked_assets[key]\n settings = request.registry.settings\n should_compile = asbool(settings.get('pyramid_frontend.compile'))\n\n if should_compile:\n filename = theme.compiled_asset_path(key)\n url_path = '/compiled/' + theme.key + '/' + filename\n else:\n url_path = asset.url_path\n\n return literal(asset.tag(theme, url_path, production=should_compile,\n **kwargs))","def generate_loader_vanilla():\n return template_loader_vanilla","def client_plugin_source(self, language):\n\n static = self.static\n if static is None:\n return None\n\n filename = os.path.join(static, \"main.\" + language)\n realfilename = os.path.realpath(filename)\n\n if not realfilename.startswith(self.static + '/'): # pragma: no cover\n raise ValueError(\"Invalid language `%s`\" % language)\n\n if not os.path.isfile(realfilename):\n return None\n\n return realfilename","def cdn_file(request, source):\n site = request.site\n file_path = site.template_dir + \"/cdn/\" + source\n source_file_url = settings.TEMPLATE_STATIC_URL + \"/\" + file_path\n return source_file_url","def server_static_img(filename):\n return static_file(filename, root='static/img')","def generic(request):\n\n # Load context\n json_path = os.path.join(settings.STATIC_ROOT,'json/context.json')\n context = simplejson.loads(''.join(open(json_path).readlines()))\n\n # Determine template name\n template_path = request.path[1:]\n if template_path == '':\n template_path = 'index.html'\n if template_path.endswith('/'):\n template_path += 'index.html'\n elif not template_path.endswith('.html'):\n template_path += '.html'\n\n # Check if template exists \n template_found = False\n for template_dir in settings.TEMPLATE_DIRS:\n full_template_path = os.path.join(template_dir, template_path)\n if os.path.isfile(full_template_path):\n template_found = True\n break\n\n if not template_found:\n raise Http404\n\n return direct_to_template(request, template_path, context)","def test_static_package_resource(self):\n resource = StaticResource('pyramid_webpack:jinja2ext.py')\n import pyramid_webpack.jinja2ext\n with resource.open() as i:\n self.assertEqual(i.read(),\n inspect.getsource(pyramid_webpack.jinja2ext))","def setStaticContent(*args):","def test_raw_static_check():\r\n path = '\"/static/foo.png?raw\"'\r\n assert_equals(path, replace_static_urls(path, DATA_DIRECTORY))\r\n\r\n text = 'text <tag a=\"/static/js/capa/protex/protex.nocache.js?raw\"/><div class=\"'\r\n assert_equals(path, replace_static_urls(path, text))","def get_static_path(path, aid, filename):\n return os.path.join(path, aid, os.path.basename(filename))","def have_asp_extension(l):\r\n if \".asp\" in str(l):\r\n return 1\r\n else:\r\n return 0","def loadjs(*args):\n return render(settings, 'JS_FILES', 'staticloader/load_js.html', *args)","def template_context(request):\n context = {\n 'application_version': settings.APPLICATION_VERSION,\n }\n context.update(settings.STATIC_CONTEXT_VARS)\n return context","def get_view_template_name(self, request=None, origin=None):\n if not self.view_template_name_ajax:\n return self.view_template_name\n elif request and request.is_ajax():\n return self.view_template_name_ajax\n else:\n return self.view_template_name","def __get_server_static__(app_path,static_dir):\n import os\n # from . import config_loader\n\n # root_path = os.path.dirname(os.path.dirname(os.path.dirname(__file__)))\n _path = (static_dir).replace(\"/\", os.path.sep)\n return os.sep.join([app_path, _path])","def test_string_pattern(self):\n with patch_settings(LIVETRANSLATION_JQUERY=u'/jquery.js'):\n pattern, url = process_jquery_setting()\n self.assertEqual(pattern, ur'<script\\s[^>]*src=\"\\/jquery\\.js\"')","def test_abs_static_view(self):\n settings = {\n 'webpack.bundle_dir': '/foo/bar/baz',\n }\n state = WebpackState(settings)\n self.assertEqual(state.static_view_path, '/foo/bar/baz')","def bootstrap_javascript_url():\n return javascript_url()","def test_replace_namespaced_template(self):\n pass","def __init__(self, static_url):\n super(AsyncHeadRenderer, self).__init__(static_url=static_url)\n\n self._anonymous_css = [] # CSS\n self._anonymous_javascript = [] # Javascript code","def js(filepath):\n return static_file(filepath, root=\"public\")","def PyHiew_GetScriptFileName(script):\r\n return '%s\\\\%s.py' % (PYHIEW_PATH, script)","def package_filename(dist, *filename):\n static = static_filename(dist)\n if static is None:\n return\n if not os.path.exists(os.path.join(static, 'js', 'package.json')):\n return\n js_filename = os.path.abspath(os.path.join(static, 'js'))\n if filename is not None:\n js_filename = os.path.join(js_filename, *filename)\n if not os.path.exists(js_filename):\n return\n return js_filename","def get_static_transcript(self, request):\r\n response = Response(status=404)\r\n # Only do redirect for English\r\n if not self.transcript_language == 'en':\r\n return response\r\n\r\n video_id = request.GET.get('videoId', None)\r\n if video_id:\r\n transcript_name = video_id\r\n else:\r\n transcript_name = self.sub\r\n\r\n if transcript_name:\r\n # Get the asset path for course\r\n asset_path = None\r\n if hasattr(self.descriptor.runtime, 'modulestore'):\r\n course = self.descriptor.runtime.modulestore.get_course(self.course_id)\r\n asset_path = course.static_asset_path\r\n else:\r\n # Handle XML Courses that don't have modulestore in the runtime\r\n asset_path = getattr(self.descriptor, 'data_dir', None)\r\n\r\n if asset_path:\r\n response = Response(\r\n status=307,\r\n location='/static/{0}/{1}'.format(\r\n asset_path,\r\n subs_filename(transcript_name, self.transcript_language)\r\n )\r\n )\r\n return response","def html_template_file(self):\n pass","def get_static_path(name):\n path = find_static_path(name)\n if path is None:\n path = staticfiles_storage.path(name)\n return os.path.abspath(path)","def include_file(ctx, name):\n env = ctx.environment\n return jinja2.Markup(env.loader.get_source(env, name)[0])","def template_hook_point(context, name):\n s = \"\"\n for hook in TemplateHook.by_name(name):\n if hook.applies_to(context):\n s += hook.render_to_string(context.get('request', None), context)\n\n return s","def asset_url(filename=\"\", version=True):\n if filename.startswith(\"http\") or filename.startswith(\"/\"):\n return filename\n else:\n if config.static_url:\n return_url = \"http://\" + config.static_url\n else:\n return_url = \"/static\" # web.ctx.home + \"/static\"\n if filename:\n return_url += \"/\" + filename\n if version:\n return_url += \"?\" + config.asset_version\n return return_url","def _get_template_filename(self):\n file_name = ReportMeta.reports[self._report_key]['fileName']\n return '{}.html'.format(file_name)","def get_path(self):\n return StaticAsset.get_static_path(self._name)","def un_src(self):\n if self.src is None:\n return\n self.inline = '''\n var script = document.createElement('script');\n script.src = \"%s\";\n document.body.appendChild(script);\n''' % self.src\n self.src = None","def _clear_script_name(self, raw: str):\n\n # remove all occurrences of \"%ScriptPath%\\\"\n st = re.sub(\"%scriptpath%/\", \"\", raw, flags=re.I)\n\n # return (External) annotation, if necessary\n if (\"%opsiscripthelperpath%/lib\" in st.lower()) or\\\n (\"%winstdir%/lib\" in st.lower()) or\\\n (\"%scriptdrive%/\" in st.lower()) or\\\n (\"%/\" in st.lower()):\n st = \"(External) \" + st\n return st","def get_script_name(pidx):\n suffix = \"\"\n if pidx >= 200:\n suffix = \"200\"\n elif pidx >= 100:\n suffix = \"100\"\n return f\"{BASEDIR}/scripts{suffix}/p{pidx}.py\"","def get_template_names(self):\n name = self.__class__.__name__.replace(\"DatatableView\", \"\")\n name = re.sub(r'([a-z]|[A-Z]+)(?=[A-Z])', r'\\1_', name)\n return [\"demos/\" + name.lower() + \".html\", \"example_base.html\"]","def set_jinja_before_request():\n resource_provider.set_jinja_globals()","def ext_js_bundle(context, extension, name):\n return _render_js_bundle(context, extension, name)","def test_url_current_app():\n from coffin.template.loader import get_template_from_string\n from django.template import RequestContext\n from django.http import HttpRequest\n t = get_template_from_string('{% url testapp:the-index-view %}')\n assert t.render(RequestContext(HttpRequest())) == '/app/one/'\n assert t.render(RequestContext(HttpRequest(), current_app=\"two\")) == '/app/two/'","def _get_template_fname(self):\n template_fname = self._context.get('template_fname', False)\n return template_fname","def serving_path_parameterized(self):\n return self.pod.path_format.format_static(\n self.path_format, locale=self.locale, parameterize=True)","def version(_):\n\n return {'version': import_module(environ['DJANGO_SETTINGS_MODULE']).STATIC_VERSION}","def static_url(self, path, include_host=None, **kwargs):\n raise NotImplementedError()","def index(request):\n return render_to_response(\n # note: this is slightly different than the labs app with \"app/app.html\" rather than the labs/labs.html\n # and we don't pass submodule name. fixme, by changing to new style with name = app_name\n settings.JS_HOME+'app.html',\n {'INDIVO_UI_APP_CSS': settings.INDIVO_UI_SERVER_BASE+'/jmvc/ui/resources/css/ui.css'}\n )","def render_template():\n template_engine = engines['django']\n def func(template_string):\n load_tags_string = '{% load wagtailextensions_tags %}'\n return template_engine.from_string(load_tags_string + template_string).render()\n return func","def _django_prefix():\n return _interpolate(DJANGO_PREFIX)","def __init__(self, static_url):\n super(HeadRenderer, self).__init__()\n\n # Directory where are located the static contents of the application\n self.static_url = static_url\n\n self._named_css = {} # CSS code\n self._css_url = {} # CSS URLs\n self._named_javascript = {} # Javascript code\n self._javascript_url = {} # Javascript URLs\n\n self._order = 0 # Memorize the order of the javascript and css","def wsgi_template(appname, path, logging_level=\"INFO\"):\n template = (\n 'import os\\n'\n 'import logging\\n'\n 'import logging.config\\n'\n '\\n'\n 'activate_this = \"{path}/env/bin/activate_this.py\"\\n'\n 'execfile(activate_this, dict(__file__=activate_this))\\n'\n '\\n'\n 'logging.basicConfig(level=logging.{logging_level})\\n'\n 'logging.config.fileConfig(\"{path}/logging.ini\")\\n'\n '\\n'\n 'from {app}.main import app as application\\n'\n .format(\n app=appname,\n app_up=appname.upper(),\n path=path,\n logging_level=logging_level\n )\n )\n return template","def _path(self):\n path = REQUIRES['static_url']\n\n # add paths as specified\n for prefix, subpath in self.getPrefixDict().items():\n if ( self.filename.startswith(prefix) ):\n path += subpath\n break;\n\n return path","def _add_static_files(self, req):\n add_script(req, self._get_jqplot('jquery.jqplot'))\n add_stylesheet(req, 'common/js/jqPlot/jquery.jqplot.css')\n # excanvas is needed for IE8 support\n add_script(req, self._get_jqplot('excanvas.min'))\n add_script(req, self._get_jqplot('plugins/jqplot.dateAxisRenderer'))\n add_script(req, self._get_jqplot('plugins/jqplot.highlighter'))\n add_script(req, self._get_jqplot('plugins/jqplot.canvasTextRenderer'))\n add_script(req, self._get_jqplot('plugins/jqplot.canvasAxisTickRenderer'))\n add_script(req, self._get_jqplot('plugins/jqplot.canvasAxisLabelRenderer'))\n add_script(req, self._get_jqplot('plugins/jqplot.enhancedLegendRenderer'))","def site_name(request):\n return {'site_name':'CatFood'}","def static_files(filename):\n static_path = os.path.join(frontend.root_path, 'templates', current_app.config['FRONTEND_THEME'], 'static')\n return send_from_directory(static_path, filename)","def test_theme_template_loading_by_prefix():\n app = create_ctfd()\n with app.test_request_context():\n tpl1 = render_template_string(\"{% extends 'core/page.html' %}\", content=\"test\")\n tpl2 = render_template(\"page.html\", content=\"test\")\n assert tpl1 == tpl2"],"string":"[\n \"def get_script_name(t_req):\\n if settings.FORCE_SCRIPT_NAME is not None:\\n return force_text(settings.FORCE_SCRIPT_NAME)\\n\\n # If Apache's mod_rewrite had a whack at the URL, Apache set either\\n # SCRIPT_URL or REDIRECT_URL to the full resource URL before applying any\\n # rewrites. Unfortunately not every Web server (lighttpd!) passes this\\n # information through all the time, so FORCE_SCRIPT_NAME, above, is still\\n # needed.\\n script_url = t_req.headers.get('SCRIPT_URL', '')\\n if not script_url:\\n script_url = t_req.headers.get('REDIRECT_URL', '')\\n\\n if script_url:\\n path_info = t_req.headers.get('PATH_INFO', '')\\n script_name = script_url[:-len(path_info)]\\n else:\\n script_name = t_req.headers.get('SCRIPT_NAME', '')\\n\\n # It'd be better to implement URI-to-IRI decoding, see #19508.\\n # return script_name.decode(UTF_8)\\n return script_name\",\n \"def ext_static(context, extension, path):\\n return static('ext/%s/%s' % (extension.id, path))\",\n \"def get_js_file(self):\\n return 'placeholder'\",\n \"def third_party_scripts(request):\\n return {\\n 'ORCHESTRA_THIRD_PARTY_SCRIPTS_TEMPLATE':\\n settings.ORCHESTRA_THIRD_PARTY_SCRIPTS_TEMPLATE\\n }\",\n \"def get_default_javascript():\\n return [\\\"_static/require.js\\\"]\",\n \"def getScriptname():\\n return os.environ.get('SCRIPT_NAME', '')\",\n \"def static(request):\\n return {\\n 'JSERRORLOGGING_STATIC_URL': STATIC_URL\\n }\",\n \"def static(filename):\\n\\ttimestamp = os.path.getmtime(os.path.join(app.static_folder, filename))\\n\\treturn \\\"%s/%s?%s\\\" % (app.static_url_path, filename, timestamp)\",\n \"def static(filename):\\n\\ttimestamp = os.path.getmtime(os.path.join(app.static_folder, filename))\\n\\treturn \\\"%s/%s?%s\\\" % (app.static_url_path, filename, timestamp)\",\n \"def replacement(self):\\n assert (self.src or self.inline) and not (self.src and self.inline)\\n if self.src:\\n return '<script async type=\\\"text/javascript\\\" src=\\\"%s\\\"></script>' % urllib.quote(self.src)\\n else:\\n return '<script>\\\\n%s\\\\n</script>' % self.inline\",\n \"def module_use_template_javascript(self):\\n return False\",\n \"def module_use_template_javascript(self):\\n return False\",\n \"def add_static(ext):\\n ext = ext.lower()\\n\\n compiler = StaticCompiler(ext)\\n file_list = compiler.get_staticfiles_list()\\n\\n return render_to_string(\\n \\\"mub/context_%s.html\\\" % ext,\\n {\\n \\\"items\\\": file_list,\\n \\\"STATIC_URL\\\": settings.STATIC_URL,\\n \\\"IS_MINIFIED\\\": compiler.is_minified\\n }\\n )\",\n \"def path_static():\\n return os.path.abspath(os.path.dirname(__file__))+'/_static'\",\n \"def include_admin_script(script_path):\\n if not absolute_url_re.match(script_path):\\n script_path = '%s%s' % (settings.ADMIN_MEDIA_PREFIX, script_path)\\n return '<script type=\\\"text/javascript\\\" src=\\\"%s\\\"></script>' % script_path\",\n \"def static_html(subpath):\\n return render_template(f'static_html/{subpath}.html')\",\n \"def _template_file_default(self):\\n return \\\"index\\\"\",\n \"def get_wsgi_file_name(self):\\n return self.wsgi\",\n \"def render(self, template_name, **kwargs):\\n currentUser = self.current_user\\n from_workspace_str = self.get_argument(\\\"from_workspace\\\", default=\\\"0\\\", strip=False)\\n from_workspace = from_workspace_str == \\\"1\\\"\\n html = self.render_string(template_name, currentUser=currentUser, from_workspace = from_workspace, **kwargs)\\n if from_workspace :\\n scriptName = self.__class__.__name__\\n\\n if scriptName.endswith('Handler') :\\n scriptName = scriptName[:-7] \\n\\n path = self.static_url('scripts/' + scriptName + '.js')\\n\\n js = '<script src=\\\"' + escape.xhtml_escape(path) + '\\\" type=\\\"text/javascript\\\"></script>'\\n html = html + utf8(js)\\n self.finish(html)\\n return\\n\\n # Insert the additional JS and CSS added by the modules on the page\\n js_embed = []\\n js_files = []\\n css_embed = []\\n css_files = []\\n html_heads = []\\n html_bodies = []\\n for module in getattr(self, \\\"_active_modules\\\", {}).values():\\n embed_part = module.embedded_javascript()\\n if embed_part:\\n js_embed.append(utf8(embed_part))\\n file_part = module.javascript_files()\\n if file_part:\\n if isinstance(file_part, (unicode_type, bytes_type)):\\n js_files.append(file_part)\\n else:\\n js_files.extend(file_part)\\n embed_part = module.embedded_css()\\n if embed_part:\\n css_embed.append(utf8(embed_part))\\n file_part = module.css_files()\\n if file_part:\\n if isinstance(file_part, (unicode_type, bytes_type)):\\n css_files.append(file_part)\\n else:\\n css_files.extend(file_part)\\n head_part = module.html_head()\\n if head_part:\\n html_heads.append(utf8(head_part))\\n body_part = module.html_body()\\n if body_part:\\n html_bodies.append(utf8(body_part))\\n\\n def is_absolute(path):\\n return any(path.startswith(x) for x in [\\\"/\\\", \\\"http:\\\", \\\"https:\\\"])\\n if js_files:\\n # Maintain order of JavaScript files given by modules\\n paths = []\\n unique_paths = set()\\n for path in js_files:\\n if not is_absolute(path):\\n path = self.static_url(path)\\n if path not in unique_paths:\\n paths.append(path)\\n unique_paths.add(path)\\n js = ''.join('<script src=\\\"' + escape.xhtml_escape(p) +\\n '\\\" type=\\\"text/javascript\\\"></script>'\\n for p in paths)\\n sloc = html.rindex(b'</body>')\\n html = html[:sloc] + utf8(js) + b'\\\\n' + html[sloc:]\\n if js_embed:\\n js = b'<script type=\\\"text/javascript\\\">\\\\n//<![CDATA[\\\\n' + \\\\\\n b'\\\\n'.join(js_embed) + b'\\\\n//]]>\\\\n</script>'\\n sloc = html.rindex(b'</body>')\\n html = html[:sloc] + js + b'\\\\n' + html[sloc:]\\n if css_files:\\n paths = []\\n unique_paths = set()\\n for path in css_files:\\n if not is_absolute(path):\\n path = self.static_url(path)\\n if path not in unique_paths:\\n paths.append(path)\\n unique_paths.add(path)\\n css = ''.join('<link href=\\\"' + escape.xhtml_escape(p) + '\\\" '\\n 'type=\\\"text/css\\\" rel=\\\"stylesheet\\\"/>'\\n for p in paths)\\n hloc = html.index(b'</head>')\\n html = html[:hloc] + utf8(css) + b'\\\\n' + html[hloc:]\\n if css_embed:\\n css = b'<style type=\\\"text/css\\\">\\\\n' + b'\\\\n'.join(css_embed) + \\\\\\n b'\\\\n</style>'\\n hloc = html.index(b'</head>')\\n html = html[:hloc] + css + b'\\\\n' + html[hloc:]\\n if html_heads:\\n hloc = html.index(b'</head>')\\n html = html[:hloc] + b''.join(html_heads) + b'\\\\n' + html[hloc:]\\n if html_bodies:\\n hloc = html.index(b'</body>')\\n html = html[:hloc] + b''.join(html_bodies) + b'\\\\n' + html[hloc:]\\n self.finish(html)\",\n \"def server_static (filename):\\n return static_file(filename, root=\\\"./static\\\")\",\n \"def include_static_files(app):\\n file_path = sphinx_prolog.get_static_path(STATIC_FILE)\\n if file_path not in app.config.html_static_path:\\n app.config.html_static_path.append(file_path)\",\n \"def render(request, template):\\r\\n return render_to_response('static_templates/' + template, {})\",\n \"def topcoat_icons_script_tag():\\n return u'<script type=\\\"text/javascript src=\\\"%s\\\"></script>' % topcoat_icons_script_url()\",\n \"def template_name(self):\\n\\t\\traise NotImplementedError('template_name must be defined')\",\n \"def scriptpath(self, code):\\n return '' if code == 'en' else ('/' + code)\",\n \"def get_script_name(self, locale: Locale | str | None = None) -> str | None:\\n if locale is None:\\n locale = self\\n locale = Locale.parse(locale)\\n return locale.scripts.get(self.script or '')\",\n \"def glr_path_static():\\n return os.path.join(base_path, \\\"static\\\")\",\n \"def url(self, url):\\n prefix = self.request_local.environ['toscawidgets.prefix']\\n script_name = self.request_local.environ['SCRIPT_NAME']\\n if hasattr(url, 'url_mapping'):\\n url = url.url_mapping['normal']\\n return ''.join([script_name, prefix, url])\",\n \"def static_index():\\n return \\\"xxxxxx.your-domain.tld\\\"\",\n \"def server_static(filename):\\n return static_file(filename, root='static/stats')\",\n \"def add_javascripts_subscriber(event):\\n c = event.request.tmpl_context\\n c.javascripts = [\\n ('spline', 'lib/jquery-1.7.1.min'),\\n ('spline', 'lib/jquery.cookies-2.2.0.min'),\\n ('spline', 'lib/jquery.ui-1.8.4.min'),\\n ('spline', 'core'),\\n ('pokedex', 'pokedex-suggestions'),\\n ('pokedex', 'pokedex'), # XXX only on main pokedex pages\\n ]\",\n \"def get_available_name(self, name, *args, **kwargs):\\n # If the filename already exists, remove it as if it was a true file system\\n if self.exists(name) and os.path.exists(\\n os.path.join(settings.STATIC_ROOT, name)):\\n os.remove(os.path.join(settings.STATIC_ROOT, name))\\n return name\",\n \"def static(website, request, **etc):\\n return website.static.respond(request)\",\n \"def _remap_static(self, stream, prefix='/static/'):\\n def map_static(name, event):\\n attrs = event[1][1]\\n name = attrs.get(name)[len(prefix):]\\n if self.static_map:\\n name = self.static_map.get(name, name)\\n return static(name)\\n return stream | Transformer('//*[matches(@src, \\\"^%s\\\")]' % prefix).attr('src', map_static) | \\\\\\n Transformer('//*[matches(@href, \\\"^%s\\\")]' % prefix).attr('href', map_static)\",\n \"def complete_static_filename(self, filename):\\n return staticfiles_finder(filename)\",\n \"def get_template_name(self):\\n if self.template_name:\\n return self.template_name\\n\\n if Path('_templates/global/WaitPage.html').exists():\\n return 'global/WaitPage.html'\\n return 'otree/WaitPage.html'\",\n \"def static(filename):\\n return href.static(file=filename)\",\n \"def href(self, request) -> str:\\n return request.static_path(self.url_spec)\",\n \"def static(self, filename):\\n return send_from_directory(self.static_path, filename)\",\n \"def template_loader(self):\\n return None\",\n \"def djangify(line: str):\\n\\n global APP_NAME\\n\\n # Don't change the contents of the line if it contails a URL that links\\n # outside content. Ex. www.example.com/webpage.html\\n if containsURL(line):\\n return line\\n # Don't change the line if it contains placeholder URL like '#'\\n if line == '#':\\n return line\\n # If line links to an internal file, make it Django compatible by loading\\n # from static directory appended with APP_NAME\\n return \\\" {% static '\\\" + APP_NAME + line + \\\"' %} \\\"\",\n \"def get_src_js(self):\\n if self.get_style() != self.STYLE_BASE:\\n return f\\\"dtables/js/dataTables.{self.get_style()}.js\\\"\\n else:\\n return f\\\"dtables/js/{self.get_style()}.dataTables.js\\\"\",\n \"def core_cdn_file(request, source):\\n\\n file_path = settings.CENTIPAIR_TEMPLATE_DIR + \\\"/cdn/\\\" + source\\n source_file_url = settings.TEMPLATE_STATIC_URL + \\\"/\\\" + file_path\\n return source_file_url\",\n \"def resource_js(self):\\n \\n portal_url = getSite().absolute_url()\\n \\n return \\\"\\\"\\\"\\n <script type=\\\"text/javascript\\\" src=\\\"%s/++resource++swfobject.js\\\"></script>\\n <script type=\\\"text/javascript\\\" src=\\\"%s/++resource++audio_player.js\\\"></script> \\n <script type=\\\"text/javascript\\\"> \\n AudioPlayer.setup(\\\"%s/++resource++audio_player.swf\\\", { \\n width: 300\\n }); \\n </script>\\n \\\"\\\"\\\" % (portal_url, portal_url, portal_url)\",\n \"def getBaseURL():\\n return getQualifiedURL(getScriptname())\",\n \"def get_template_name(request, base_template_name):\\n template_base_dir = get_template_base_directory(request)\\n return f\\\"cast/{template_base_dir}/{base_template_name}\\\"\",\n \"def staticfile(path):\\n normalized_path = posixpath.normpath(urllib.unquote(path)).lstrip('/')\\n absolute_path = finders.find(normalized_path)\\n if not absolute_path and getattr(settings, 'STATIC_ROOT', None):\\n absolute_path = os.path.join(settings.STATIC_ROOT, path)\\n if absolute_path:\\n return '%s%s?v=%s' % (settings.STATIC_URL, path, os.stat(absolute_path)[stat.ST_MTIME])\\n return path\",\n \"def static_url(self, path):\\n\\t\\tif not hasattr(self, \\\"_static_hashes\\\"):\\n\\t\\t\\tself._static_hashes = {}\\n\\t\\thashes = self._static_hashes\\n\\t\\tif path not in hashes:\\n\\t\\t\\timport hashlib\\n\\t\\t\\ttry:\\n\\t\\t\\t\\tf = open(os.path.join(\\n\\t\\t\\t\\t\\tself.application.settings[\\\"static_path\\\"], path))\\n\\t\\t\\t\\thashes[path] = hashlib.md5(f.read()).hexdigest()\\n\\t\\t\\t\\tf.close()\\n\\t\\t\\texcept:\\n\\t\\t\\t\\tprint \\\"Could not open static file %r\\\"%path\\n\\t\\t\\t\\thashes[path] = None\\n\\t\\tbase = \\\"http://static.\\\"+_config.get(\\\"varnish\\\", \\\"ovzcphost\\\") + \\\"/\\\"\\n\\t\\tif hashes.get(path):\\n\\t\\t\\treturn base + path + \\\"?v=\\\" + hashes[path][:5]\\n\\t\\telse:\\n\\t\\t\\treturn base + path\",\n \"def get_xmodule_urls():\\r\\n if settings.DEBUG:\\r\\n paths = [path.replace(\\\".coffee\\\", \\\".js\\\") for path in\\r\\n settings.PIPELINE_JS['module-js']['source_filenames']]\\r\\n else:\\r\\n paths = [settings.PIPELINE_JS['module-js']['output_filename']]\\r\\n return [staticfiles_storage.url(path) for path in paths]\",\n \"def asset_tag(request, key, **kwargs):\\n theme = request.theme\\n asset = theme.stacked_assets[key]\\n settings = request.registry.settings\\n should_compile = asbool(settings.get('pyramid_frontend.compile'))\\n\\n if should_compile:\\n filename = theme.compiled_asset_path(key)\\n url_path = '/compiled/' + theme.key + '/' + filename\\n else:\\n url_path = asset.url_path\\n\\n return literal(asset.tag(theme, url_path, production=should_compile,\\n **kwargs))\",\n \"def generate_loader_vanilla():\\n return template_loader_vanilla\",\n \"def client_plugin_source(self, language):\\n\\n static = self.static\\n if static is None:\\n return None\\n\\n filename = os.path.join(static, \\\"main.\\\" + language)\\n realfilename = os.path.realpath(filename)\\n\\n if not realfilename.startswith(self.static + '/'): # pragma: no cover\\n raise ValueError(\\\"Invalid language `%s`\\\" % language)\\n\\n if not os.path.isfile(realfilename):\\n return None\\n\\n return realfilename\",\n \"def cdn_file(request, source):\\n site = request.site\\n file_path = site.template_dir + \\\"/cdn/\\\" + source\\n source_file_url = settings.TEMPLATE_STATIC_URL + \\\"/\\\" + file_path\\n return source_file_url\",\n \"def server_static_img(filename):\\n return static_file(filename, root='static/img')\",\n \"def generic(request):\\n\\n # Load context\\n json_path = os.path.join(settings.STATIC_ROOT,'json/context.json')\\n context = simplejson.loads(''.join(open(json_path).readlines()))\\n\\n # Determine template name\\n template_path = request.path[1:]\\n if template_path == '':\\n template_path = 'index.html'\\n if template_path.endswith('/'):\\n template_path += 'index.html'\\n elif not template_path.endswith('.html'):\\n template_path += '.html'\\n\\n # Check if template exists \\n template_found = False\\n for template_dir in settings.TEMPLATE_DIRS:\\n full_template_path = os.path.join(template_dir, template_path)\\n if os.path.isfile(full_template_path):\\n template_found = True\\n break\\n\\n if not template_found:\\n raise Http404\\n\\n return direct_to_template(request, template_path, context)\",\n \"def test_static_package_resource(self):\\n resource = StaticResource('pyramid_webpack:jinja2ext.py')\\n import pyramid_webpack.jinja2ext\\n with resource.open() as i:\\n self.assertEqual(i.read(),\\n inspect.getsource(pyramid_webpack.jinja2ext))\",\n \"def setStaticContent(*args):\",\n \"def test_raw_static_check():\\r\\n path = '\\\"/static/foo.png?raw\\\"'\\r\\n assert_equals(path, replace_static_urls(path, DATA_DIRECTORY))\\r\\n\\r\\n text = 'text <tag a=\\\"/static/js/capa/protex/protex.nocache.js?raw\\\"/><div class=\\\"'\\r\\n assert_equals(path, replace_static_urls(path, text))\",\n \"def get_static_path(path, aid, filename):\\n return os.path.join(path, aid, os.path.basename(filename))\",\n \"def have_asp_extension(l):\\r\\n if \\\".asp\\\" in str(l):\\r\\n return 1\\r\\n else:\\r\\n return 0\",\n \"def loadjs(*args):\\n return render(settings, 'JS_FILES', 'staticloader/load_js.html', *args)\",\n \"def template_context(request):\\n context = {\\n 'application_version': settings.APPLICATION_VERSION,\\n }\\n context.update(settings.STATIC_CONTEXT_VARS)\\n return context\",\n \"def get_view_template_name(self, request=None, origin=None):\\n if not self.view_template_name_ajax:\\n return self.view_template_name\\n elif request and request.is_ajax():\\n return self.view_template_name_ajax\\n else:\\n return self.view_template_name\",\n \"def __get_server_static__(app_path,static_dir):\\n import os\\n # from . import config_loader\\n\\n # root_path = os.path.dirname(os.path.dirname(os.path.dirname(__file__)))\\n _path = (static_dir).replace(\\\"/\\\", os.path.sep)\\n return os.sep.join([app_path, _path])\",\n \"def test_string_pattern(self):\\n with patch_settings(LIVETRANSLATION_JQUERY=u'/jquery.js'):\\n pattern, url = process_jquery_setting()\\n self.assertEqual(pattern, ur'<script\\\\s[^>]*src=\\\"\\\\/jquery\\\\.js\\\"')\",\n \"def test_abs_static_view(self):\\n settings = {\\n 'webpack.bundle_dir': '/foo/bar/baz',\\n }\\n state = WebpackState(settings)\\n self.assertEqual(state.static_view_path, '/foo/bar/baz')\",\n \"def bootstrap_javascript_url():\\n return javascript_url()\",\n \"def test_replace_namespaced_template(self):\\n pass\",\n \"def __init__(self, static_url):\\n super(AsyncHeadRenderer, self).__init__(static_url=static_url)\\n\\n self._anonymous_css = [] # CSS\\n self._anonymous_javascript = [] # Javascript code\",\n \"def js(filepath):\\n return static_file(filepath, root=\\\"public\\\")\",\n \"def PyHiew_GetScriptFileName(script):\\r\\n return '%s\\\\\\\\%s.py' % (PYHIEW_PATH, script)\",\n \"def package_filename(dist, *filename):\\n static = static_filename(dist)\\n if static is None:\\n return\\n if not os.path.exists(os.path.join(static, 'js', 'package.json')):\\n return\\n js_filename = os.path.abspath(os.path.join(static, 'js'))\\n if filename is not None:\\n js_filename = os.path.join(js_filename, *filename)\\n if not os.path.exists(js_filename):\\n return\\n return js_filename\",\n \"def get_static_transcript(self, request):\\r\\n response = Response(status=404)\\r\\n # Only do redirect for English\\r\\n if not self.transcript_language == 'en':\\r\\n return response\\r\\n\\r\\n video_id = request.GET.get('videoId', None)\\r\\n if video_id:\\r\\n transcript_name = video_id\\r\\n else:\\r\\n transcript_name = self.sub\\r\\n\\r\\n if transcript_name:\\r\\n # Get the asset path for course\\r\\n asset_path = None\\r\\n if hasattr(self.descriptor.runtime, 'modulestore'):\\r\\n course = self.descriptor.runtime.modulestore.get_course(self.course_id)\\r\\n asset_path = course.static_asset_path\\r\\n else:\\r\\n # Handle XML Courses that don't have modulestore in the runtime\\r\\n asset_path = getattr(self.descriptor, 'data_dir', None)\\r\\n\\r\\n if asset_path:\\r\\n response = Response(\\r\\n status=307,\\r\\n location='/static/{0}/{1}'.format(\\r\\n asset_path,\\r\\n subs_filename(transcript_name, self.transcript_language)\\r\\n )\\r\\n )\\r\\n return response\",\n \"def html_template_file(self):\\n pass\",\n \"def get_static_path(name):\\n path = find_static_path(name)\\n if path is None:\\n path = staticfiles_storage.path(name)\\n return os.path.abspath(path)\",\n \"def include_file(ctx, name):\\n env = ctx.environment\\n return jinja2.Markup(env.loader.get_source(env, name)[0])\",\n \"def template_hook_point(context, name):\\n s = \\\"\\\"\\n for hook in TemplateHook.by_name(name):\\n if hook.applies_to(context):\\n s += hook.render_to_string(context.get('request', None), context)\\n\\n return s\",\n \"def asset_url(filename=\\\"\\\", version=True):\\n if filename.startswith(\\\"http\\\") or filename.startswith(\\\"/\\\"):\\n return filename\\n else:\\n if config.static_url:\\n return_url = \\\"http://\\\" + config.static_url\\n else:\\n return_url = \\\"/static\\\" # web.ctx.home + \\\"/static\\\"\\n if filename:\\n return_url += \\\"/\\\" + filename\\n if version:\\n return_url += \\\"?\\\" + config.asset_version\\n return return_url\",\n \"def _get_template_filename(self):\\n file_name = ReportMeta.reports[self._report_key]['fileName']\\n return '{}.html'.format(file_name)\",\n \"def get_path(self):\\n return StaticAsset.get_static_path(self._name)\",\n \"def un_src(self):\\n if self.src is None:\\n return\\n self.inline = '''\\n var script = document.createElement('script');\\n script.src = \\\"%s\\\";\\n document.body.appendChild(script);\\n''' % self.src\\n self.src = None\",\n \"def _clear_script_name(self, raw: str):\\n\\n # remove all occurrences of \\\"%ScriptPath%\\\\\\\"\\n st = re.sub(\\\"%scriptpath%/\\\", \\\"\\\", raw, flags=re.I)\\n\\n # return (External) annotation, if necessary\\n if (\\\"%opsiscripthelperpath%/lib\\\" in st.lower()) or\\\\\\n (\\\"%winstdir%/lib\\\" in st.lower()) or\\\\\\n (\\\"%scriptdrive%/\\\" in st.lower()) or\\\\\\n (\\\"%/\\\" in st.lower()):\\n st = \\\"(External) \\\" + st\\n return st\",\n \"def get_script_name(pidx):\\n suffix = \\\"\\\"\\n if pidx >= 200:\\n suffix = \\\"200\\\"\\n elif pidx >= 100:\\n suffix = \\\"100\\\"\\n return f\\\"{BASEDIR}/scripts{suffix}/p{pidx}.py\\\"\",\n \"def get_template_names(self):\\n name = self.__class__.__name__.replace(\\\"DatatableView\\\", \\\"\\\")\\n name = re.sub(r'([a-z]|[A-Z]+)(?=[A-Z])', r'\\\\1_', name)\\n return [\\\"demos/\\\" + name.lower() + \\\".html\\\", \\\"example_base.html\\\"]\",\n \"def set_jinja_before_request():\\n resource_provider.set_jinja_globals()\",\n \"def ext_js_bundle(context, extension, name):\\n return _render_js_bundle(context, extension, name)\",\n \"def test_url_current_app():\\n from coffin.template.loader import get_template_from_string\\n from django.template import RequestContext\\n from django.http import HttpRequest\\n t = get_template_from_string('{% url testapp:the-index-view %}')\\n assert t.render(RequestContext(HttpRequest())) == '/app/one/'\\n assert t.render(RequestContext(HttpRequest(), current_app=\\\"two\\\")) == '/app/two/'\",\n \"def _get_template_fname(self):\\n template_fname = self._context.get('template_fname', False)\\n return template_fname\",\n \"def serving_path_parameterized(self):\\n return self.pod.path_format.format_static(\\n self.path_format, locale=self.locale, parameterize=True)\",\n \"def version(_):\\n\\n return {'version': import_module(environ['DJANGO_SETTINGS_MODULE']).STATIC_VERSION}\",\n \"def static_url(self, path, include_host=None, **kwargs):\\n raise NotImplementedError()\",\n \"def index(request):\\n return render_to_response(\\n # note: this is slightly different than the labs app with \\\"app/app.html\\\" rather than the labs/labs.html\\n # and we don't pass submodule name. fixme, by changing to new style with name = app_name\\n settings.JS_HOME+'app.html',\\n {'INDIVO_UI_APP_CSS': settings.INDIVO_UI_SERVER_BASE+'/jmvc/ui/resources/css/ui.css'}\\n )\",\n \"def render_template():\\n template_engine = engines['django']\\n def func(template_string):\\n load_tags_string = '{% load wagtailextensions_tags %}'\\n return template_engine.from_string(load_tags_string + template_string).render()\\n return func\",\n \"def _django_prefix():\\n return _interpolate(DJANGO_PREFIX)\",\n \"def __init__(self, static_url):\\n super(HeadRenderer, self).__init__()\\n\\n # Directory where are located the static contents of the application\\n self.static_url = static_url\\n\\n self._named_css = {} # CSS code\\n self._css_url = {} # CSS URLs\\n self._named_javascript = {} # Javascript code\\n self._javascript_url = {} # Javascript URLs\\n\\n self._order = 0 # Memorize the order of the javascript and css\",\n \"def wsgi_template(appname, path, logging_level=\\\"INFO\\\"):\\n template = (\\n 'import os\\\\n'\\n 'import logging\\\\n'\\n 'import logging.config\\\\n'\\n '\\\\n'\\n 'activate_this = \\\"{path}/env/bin/activate_this.py\\\"\\\\n'\\n 'execfile(activate_this, dict(__file__=activate_this))\\\\n'\\n '\\\\n'\\n 'logging.basicConfig(level=logging.{logging_level})\\\\n'\\n 'logging.config.fileConfig(\\\"{path}/logging.ini\\\")\\\\n'\\n '\\\\n'\\n 'from {app}.main import app as application\\\\n'\\n .format(\\n app=appname,\\n app_up=appname.upper(),\\n path=path,\\n logging_level=logging_level\\n )\\n )\\n return template\",\n \"def _path(self):\\n path = REQUIRES['static_url']\\n\\n # add paths as specified\\n for prefix, subpath in self.getPrefixDict().items():\\n if ( self.filename.startswith(prefix) ):\\n path += subpath\\n break;\\n\\n return path\",\n \"def _add_static_files(self, req):\\n add_script(req, self._get_jqplot('jquery.jqplot'))\\n add_stylesheet(req, 'common/js/jqPlot/jquery.jqplot.css')\\n # excanvas is needed for IE8 support\\n add_script(req, self._get_jqplot('excanvas.min'))\\n add_script(req, self._get_jqplot('plugins/jqplot.dateAxisRenderer'))\\n add_script(req, self._get_jqplot('plugins/jqplot.highlighter'))\\n add_script(req, self._get_jqplot('plugins/jqplot.canvasTextRenderer'))\\n add_script(req, self._get_jqplot('plugins/jqplot.canvasAxisTickRenderer'))\\n add_script(req, self._get_jqplot('plugins/jqplot.canvasAxisLabelRenderer'))\\n add_script(req, self._get_jqplot('plugins/jqplot.enhancedLegendRenderer'))\",\n \"def site_name(request):\\n return {'site_name':'CatFood'}\",\n \"def static_files(filename):\\n static_path = os.path.join(frontend.root_path, 'templates', current_app.config['FRONTEND_THEME'], 'static')\\n return send_from_directory(static_path, filename)\",\n \"def test_theme_template_loading_by_prefix():\\n app = create_ctfd()\\n with app.test_request_context():\\n tpl1 = render_template_string(\\\"{% extends 'core/page.html' %}\\\", content=\\\"test\\\")\\n tpl2 = render_template(\\\"page.html\\\", content=\\\"test\\\")\\n assert tpl1 == tpl2\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6034971","0.5963628","0.59341127","0.58655584","0.5860948","0.58456707","0.58188504","0.5782478","0.5782478","0.57443565","0.5699513","0.5699513","0.56902325","0.56528944","0.5573736","0.5472369","0.5468209","0.5464693","0.5461462","0.54162765","0.53910553","0.538104","0.53701425","0.5369225","0.536596","0.53489655","0.53435516","0.5311419","0.5294258","0.52730364","0.5262032","0.5242976","0.52316815","0.5219977","0.52123845","0.521105","0.5192126","0.5190773","0.51899564","0.518833","0.5175464","0.5170378","0.5154159","0.5141139","0.51323366","0.5122901","0.51225185","0.5092882","0.5088868","0.50861806","0.50817615","0.50784254","0.5069011","0.50455844","0.50420916","0.5040238","0.5033475","0.5029751","0.50289935","0.5008645","0.5005721","0.5004751","0.5002828","0.5002737","0.49784938","0.49644417","0.49602193","0.49558663","0.4945296","0.49437475","0.49429536","0.4941219","0.49371633","0.4929612","0.49291015","0.49276373","0.49224812","0.49196637","0.49163157","0.49078634","0.49033877","0.49017414","0.48976135","0.4892192","0.48915917","0.48889297","0.48855653","0.4882505","0.4879054","0.4877958","0.48731226","0.4871609","0.48551655","0.48524162","0.48400033","0.48394898","0.48374212","0.48366025","0.48264006","0.48258138","0.48223126"],"string":"[\n \"0.6034971\",\n \"0.5963628\",\n \"0.59341127\",\n \"0.58655584\",\n \"0.5860948\",\n \"0.58456707\",\n \"0.58188504\",\n \"0.5782478\",\n \"0.5782478\",\n \"0.57443565\",\n \"0.5699513\",\n \"0.5699513\",\n \"0.56902325\",\n \"0.56528944\",\n \"0.5573736\",\n \"0.5472369\",\n \"0.5468209\",\n \"0.5464693\",\n \"0.5461462\",\n \"0.54162765\",\n \"0.53910553\",\n \"0.538104\",\n \"0.53701425\",\n \"0.5369225\",\n \"0.536596\",\n \"0.53489655\",\n \"0.53435516\",\n \"0.5311419\",\n \"0.5294258\",\n \"0.52730364\",\n \"0.5262032\",\n \"0.5242976\",\n \"0.52316815\",\n \"0.5219977\",\n \"0.52123845\",\n \"0.521105\",\n \"0.5192126\",\n \"0.5190773\",\n \"0.51899564\",\n \"0.518833\",\n \"0.5175464\",\n \"0.5170378\",\n \"0.5154159\",\n \"0.5141139\",\n \"0.51323366\",\n \"0.5122901\",\n \"0.51225185\",\n \"0.5092882\",\n \"0.5088868\",\n \"0.50861806\",\n \"0.50817615\",\n \"0.50784254\",\n \"0.5069011\",\n \"0.50455844\",\n \"0.50420916\",\n \"0.5040238\",\n \"0.5033475\",\n \"0.5029751\",\n \"0.50289935\",\n \"0.5008645\",\n \"0.5005721\",\n \"0.5004751\",\n \"0.5002828\",\n \"0.5002737\",\n \"0.49784938\",\n \"0.49644417\",\n \"0.49602193\",\n \"0.49558663\",\n \"0.4945296\",\n \"0.49437475\",\n \"0.49429536\",\n \"0.4941219\",\n \"0.49371633\",\n \"0.4929612\",\n \"0.49291015\",\n \"0.49276373\",\n \"0.49224812\",\n \"0.49196637\",\n \"0.49163157\",\n \"0.49078634\",\n \"0.49033877\",\n \"0.49017414\",\n \"0.48976135\",\n \"0.4892192\",\n \"0.48915917\",\n \"0.48889297\",\n \"0.48855653\",\n \"0.4882505\",\n \"0.4879054\",\n \"0.4877958\",\n \"0.48731226\",\n \"0.4871609\",\n \"0.48551655\",\n \"0.48524162\",\n \"0.48400033\",\n \"0.48394898\",\n \"0.48374212\",\n \"0.48366025\",\n \"0.48264006\",\n \"0.48258138\",\n \"0.48223126\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}}],"truncated":false,"partial":true},"paginationData":{"pageIndex":948,"numItemsPerPage":100,"numTotalItems":95772,"offset":94800,"length":100}},"jwt":"eyJhbGciOiJFZERTQSJ9.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc3MzM2NDIzOSwic3ViIjoiL2RhdGFzZXRzL25vbWljLWFpL2Nvcm5zdGFjay1weXRob24tdjEiLCJleHAiOjE3NzMzNjc4MzksImlzcyI6Imh0dHBzOi8vaHVnZ2luZ2ZhY2UuY28ifQ.q40uAu3GCTfeeyDP15SkdNvYA8K9EBG4wl__SBheuiefeQr9VEnpiguEp3EDcowaoaDVpIa3YsHjmkOwnTiNBw","displayUrls":true,"splitSizeSummaries":[{"config":"default","split":"train","numRows":95772,"numBytesParquet":1928375891}]},"discussionsStats":{"closed":1,"open":1,"total":2},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
query stringlengths 9 3.4k | document stringlengths 9 87.4k | metadata dict | negatives listlengths 4 101 | negative_scores listlengths 4 101 | document_score stringlengths 3 10 | document_rank stringclasses 102 values |
|---|---|---|---|---|---|---|
Transforms message into PlatformMessage object | def parse(cls, message):
if isinstance(message, PlatformMessage):
inst = PlatformMessage.parse(message.serialize())
return inst
inst = PlatformMessage()
if message is not None:
assert isinstance(message, (list, tuple)), "Message is expected to be a list or a tuple"
assert len(message) >= 4, "Message's length expected to be at least 4"
assert message[0] == PlatformMessage._signature, "Message's signature is incorrect"
inst.sender = message[1]
inst.interface = message[2]
inst.method = message[3]
if len(message) > 4:
assert isinstance(message[4], (list, tuple)), "Message's args expected to be list or tuple"
inst.args = copy.deepcopy(message[4])
if len(message) > 5:
assert isinstance(message[5], dict), "Message's kwargs expected to be a dict"
inst.kwargs = copy.deepcopy(message[5])
return inst | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def message_to_python(self, raw_message):\n return self.Message(self, raw_message)",
"def get_interface(cls, message):\r\n if message is not None:\r\n if isinstance(message, PlatformMessage):\r\n return message.interface\r\n assert isinstance(message, (list, tup... | [
"0.66961044",
"0.61725485",
"0.61444753",
"0.6085341",
"0.60676634",
"0.59354925",
"0.5832414",
"0.58319014",
"0.58083576",
"0.57996356",
"0.5798074",
"0.5764045",
"0.57599103",
"0.5742993",
"0.5738603",
"0.57220566",
"0.5719687",
"0.5718132",
"0.57123685",
"0.5708723",
"0.57... | 0.7441321 | 0 |
Return sender of serialized message | def get_sender(cls, message):
if message is not None:
if isinstance(message, PlatformMessage):
return message.sender
assert isinstance(message, (list, tuple)), "Message is expected to be a list or a tuple"
assert len(message) >= 4, "Message's length expected to be at least 4"
assert message[0] == PlatformMessage._signature, "Message's signature is incorrect"
return message[1]
return None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __get_sender_id(self):\n return self.__sender_id",
"def get_sender_email(message):\r\n message_headers = message['payload']['headers']\r\n for header in message_headers:\r\n if header['name'] == 'From':\r\n return header['value']",
"def sender(self):\n key, alt = ('Sen... | [
"0.7114796",
"0.6647468",
"0.6598164",
"0.6566656",
"0.65436935",
"0.65187633",
"0.65110844",
"0.65012693",
"0.6501094",
"0.64227396",
"0.640637",
"0.6369679",
"0.6141742",
"0.6132606",
"0.61057776",
"0.6090527",
"0.6054466",
"0.6002109",
"0.5983544",
"0.5983544",
"0.59530574... | 0.7315821 | 0 |
Return interface of serialized message | def get_interface(cls, message):
if message is not None:
if isinstance(message, PlatformMessage):
return message.interface
assert isinstance(message, (list, tuple)), "Message is expected to be a list or a tuple"
assert len(message) >= 4, "Message's length expected to be at least 4"
assert message[0] == PlatformMessage._signature, "Message's signature is incorrect"
return message[2]
return None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def intf_get_notif_serializer():\n serializer = sl_interface_pb2.SLInterfaceGetNotifMsg()\n return serializer",
"def _recv_serialized(self, socket):\n msg = pickle.loads(socket.recv())\n return msg",
"def _stringify_proto(obj):\n if isinstance(obj, str): return obj\n elif isinstance(o... | [
"0.6683183",
"0.6607191",
"0.6602124",
"0.6388921",
"0.6382543",
"0.63370854",
"0.6267809",
"0.61996573",
"0.6124349",
"0.6091265",
"0.6090545",
"0.607747",
"0.60588247",
"0.6057081",
"0.6040386",
"0.6030836",
"0.60173637",
"0.5962537",
"0.59547883",
"0.5940483",
"0.5939426",... | 0.58528733 | 27 |
Return method of serialized message | def get_method(cls, message):
if message is not None:
if isinstance(message, PlatformMessage):
return message.method
assert isinstance(message, (list, tuple)), "Message is expected to be a list or a tuple"
assert len(message) >= 4, "Message's length expected to be at least 4"
assert message[0] == PlatformMessage._signature, "Message's signature is incorrect"
return message[3]
return None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get( self ):\n return self.__to_message_function( self.__raw_payload )",
"def serialize_message(self) -> bytes:\n return self.compile_message().serialize()",
"def __message_content__(self) -> MessageContent:",
"def parse(self, serialized):\n raise NotImplementedError(\"Calling an abstrac... | [
"0.64785546",
"0.6399759",
"0.6097286",
"0.6095025",
"0.6048653",
"0.5926648",
"0.5798314",
"0.5763225",
"0.5758533",
"0.5757418",
"0.5754897",
"0.57526416",
"0.5739287",
"0.5705692",
"0.570088",
"0.5696248",
"0.5656703",
"0.5653811",
"0.56207484",
"0.56186205",
"0.5613904",
... | 0.6116328 | 2 |
Return args of serialized message | def get_args(cls, message):
if message is not None:
if isinstance(message, PlatformMessage):
return message.args
assert isinstance(message, (list, tuple)), "Message is expected to be a list or a tuple"
assert len(message) >= 4, "Message's length expected to be at least 4"
assert message[0] == PlatformMessage._signature, "Message's signature is incorrect"
if len(message) > 4:
return copy.deepcopy(message[4])
else:
return None
return None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _func_serialize(self, args):\n return args",
"def func_deserialize(self, args): # pragma: no cover\n if len(args) == 0:\n return []\n x = eval(args.decode(\"utf-8\"))\n return x",
"def toArgs(self):\n # FIXME - undocumented exception\n post_args = self.... | [
"0.6681042",
"0.6476981",
"0.6381497",
"0.6343124",
"0.63172007",
"0.6315931",
"0.6190981",
"0.61659044",
"0.61323375",
"0.61323375",
"0.61323375",
"0.6127745",
"0.60635227",
"0.6060811",
"0.5984353",
"0.59649163",
"0.5958156",
"0.593882",
"0.59370756",
"0.5936084",
"0.591632... | 0.7136301 | 0 |
Return kwargs of serialized message | def get_kwargs(cls, message):
if message is not None:
if isinstance(message, PlatformMessage):
return message.kwargs
assert isinstance(message, (list, tuple)), "Message is expected to be a list or a tuple"
assert len(message) >= 4, "Message's length expected to be at least 4"
assert message[0] == PlatformMessage._signature, "Message's signature is incorrect"
if len(message) > 5:
return copy.deepcopy(message[5])
else:
return None
return None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def toArgs(self):\n # FIXME - undocumented exception\n post_args = self.toPostArgs()\n kvargs = {}\n for k, v in post_args.items():\n if not k.startswith('openid.'):\n raise ValueError(\n 'This message can only be encoded as a POST, because i... | [
"0.6532804",
"0.63777333",
"0.6250696",
"0.61953866",
"0.60052204",
"0.60052204",
"0.59744835",
"0.59685344",
"0.59614235",
"0.59334373",
"0.59222966",
"0.5830837",
"0.5793464",
"0.579085",
"0.57832605",
"0.57062554",
"0.5704295",
"0.57024705",
"0.56911284",
"0.5642286",
"0.5... | 0.721355 | 0 |
Transforms self into list with key fields values | def serialize(self):
return [self._signature, self.sender, self.interface, self.method, self.args, self.kwargs] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def values(self):\r\n return [self[k] for k in self]",
"def items(self):\r\n return [(k, self[k]) for k in self]",
"def items(self):\r\n L = []\r\n for key, value in self.data.items():\r\n o = key()\r\n if o is not None:\r\n L.append((o, value))\... | [
"0.67881566",
"0.6781893",
"0.6743758",
"0.6743758",
"0.6675744",
"0.6648665",
"0.66283107",
"0.6555832",
"0.65546185",
"0.65546185",
"0.65546185",
"0.6533801",
"0.6497453",
"0.64785767",
"0.6443632",
"0.6415694",
"0.64099073",
"0.64046633",
"0.63925886",
"0.63925886",
"0.638... | 0.0 | -1 |
Creates message with reply indicating successfull ending of method call | def success(cls, retval, retvalname='value'):
if isinstance(retval, dict) and retvalname is None:
retval["__result__"] = "success" # TODO: right here just modified input dict. That's not good
else:
retval = {"__result__": "success", retvalname: retval}
return PlatformMessage(method="__reply__", kwargs=retval) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def finished(self, reply):\n pass",
"def endMessage(self):",
"def end():\n return say()",
"def finish(self, message):\n self.stdout = message\n self.returncode = 0",
"def reply_object():\n reply_object = {\"code\": \"\"}\n return reply_object",
"def acknowledgement(self, mes... | [
"0.69738877",
"0.67656934",
"0.6293983",
"0.6158718",
"0.6092211",
"0.60331434",
"0.59224075",
"0.59184587",
"0.5894392",
"0.58468145",
"0.58453137",
"0.5838691",
"0.58309144",
"0.58224344",
"0.581687",
"0.5788007",
"0.57852334",
"0.57048154",
"0.5697229",
"0.56179005",
"0.56... | 0.55243546 | 29 |
Creates message with reply indicating failiing ending of method call | def failure(cls, state, errcode=-1):
return PlatformMessage(method="__reply__", kwargs={"__result__": "fail", "state": state, "errcode": errcode}) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def endMessage(self):",
"def finished(self, reply):\n pass",
"def end():\n return say()",
"def end(update, context) -> int:\n update.callback_query.edit_message_text(\n 'Bye! I hope we can talk again some day.')\n\n logger.info(\"User [%s] exited the conversation, [Exit], from [Main Me... | [
"0.7095744",
"0.69297856",
"0.66436666",
"0.62102324",
"0.6166731",
"0.6165642",
"0.60455865",
"0.5994747",
"0.5920864",
"0.5850099",
"0.5848156",
"0.5846051",
"0.5840882",
"0.5801606",
"0.5791126",
"0.57714516",
"0.5769898",
"0.5752875",
"0.5749393",
"0.5738365",
"0.5730379"... | 0.0 | -1 |
Creates message with reply indicating failiing ending of method call by exception | def failure_exception(cls, state, exception):
return PlatformMessage(method="__reply__", kwargs={"__result__": "fail", "state": state, "errcode": -2,
"e": exception}) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def endMessage(self):",
"def end():\n return say()",
"def exit_with_message(message: str) -> NoReturn:\n raise CallParseError(input_string, message)",
"def finished(self, reply):\n pass",
"def sendErrorMessage(msg): #@NoSelf",
"def whenException(self, channel, call):",
"def abort(self... | [
"0.64972866",
"0.60457224",
"0.59910274",
"0.5865661",
"0.5790894",
"0.5711769",
"0.56799406",
"0.5674615",
"0.56623536",
"0.56480086",
"0.5638144",
"0.5630722",
"0.563067",
"0.5607326",
"0.5588698",
"0.5577028",
"0.5576119",
"0.55424887",
"0.5533531",
"0.55177295",
"0.549935... | 0.521757 | 74 |
Creates message with reply indicating some stage of method call is taken place | def notify(cls, state):
return PlatformMessage(method="__reply__", kwargs={"state": state}) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __call__(self, answer):\n method_name = 'on_%s' % sanitize_answer(answer)\n method = getattr(self, method_name, None)\n if method:\n msg = method()\n else:\n msg = self.default(answer)\n return msg",
"def Message(self, *args, **kwargs):\n pass",... | [
"0.5911461",
"0.5875573",
"0.5865693",
"0.5813939",
"0.58092356",
"0.58092356",
"0.58038336",
"0.57274956",
"0.5696109",
"0.56097317",
"0.56019354",
"0.55925906",
"0.5573429",
"0.55502784",
"0.55441946",
"0.5507472",
"0.54945314",
"0.5474131",
"0.547276",
"0.5455448",
"0.5434... | 0.57788986 | 7 |
Returns conversation for a thread | def conversation(self, thread):
assert isinstance(thread, int) and 0 <= thread < len(self._threads), "Thread {} don't exists at channel {}!".\
format(thread, self.name)
return self._threads[thread]["conversation"] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_thread_for_message(id):\n query = 'SELECT thread_id from messages WHERE id like %s'\n return __perform__(query, (id,), method='fetchone')",
"def find_all_messages_in_thread_for_person(cnx: db_connector, thread_id: int, is_singlechat: bool):\n result = []\n cursor = cnx.cursor(buffered... | [
"0.65898234",
"0.6572362",
"0.6492414",
"0.64143395",
"0.6396454",
"0.60996646",
"0.60811704",
"0.6057928",
"0.58519685",
"0.57067835",
"0.5651671",
"0.5620204",
"0.55983543",
"0.5575817",
"0.55702025",
"0.55671215",
"0.55500007",
"0.5483425",
"0.54719275",
"0.5438706",
"0.54... | 0.8358802 | 0 |
Subscribes specified instance onto channel | def subscribe(self, inst):
if inst not in self._subscribers:
self._subscribers.append(inst)
vprint("{} is subscribed to {}".format(inst.name, self.name)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def subscribe(self, channel, **kwargs):\n pass",
"def subscribe(self, inst, channel):\r\n if channel not in self._channels:\r\n self._channels[channel] = TalkChannel(channel, print_messages=self.verbose, timeref=self._timeref)\r\n self._channels[channel].subscribe(inst)",
"def s... | [
"0.73403704",
"0.7077951",
"0.6784527",
"0.6784527",
"0.6784527",
"0.65946174",
"0.65910834",
"0.6586851",
"0.63931453",
"0.6311332",
"0.62572837",
"0.62503433",
"0.62227",
"0.61942494",
"0.6113197",
"0.6018034",
"0.6016623",
"0.5920134",
"0.5876832",
"0.587313",
"0.58557457"... | 0.6719197 | 5 |
Unsubscribes specified instance from channel | def unsubscribe(self, inst):
if inst in self._subscribers:
self._subscribers.remove(inst)
vprint("{} is unsubscribed from {}".format(inst.name, self.name)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def unsubscribe(self, channel, update_handler=None):\n pass",
"def unsubscribe(self, inst, channel):\r\n if channel not in self._channels:\r\n raise ValueError(\"Channel {} not exists!\".format(channel))\r\n self._channels[channel].unsubscribe(inst)\r\n return\r\n # ... | [
"0.77895993",
"0.7697996",
"0.7457277",
"0.7457277",
"0.7457277",
"0.7457277",
"0.7457277",
"0.7024203",
"0.6909685",
"0.68771696",
"0.6872388",
"0.68624234",
"0.6827826",
"0.67210144",
"0.67210144",
"0.66898584",
"0.66726786",
"0.66592056",
"0.6605039",
"0.66029906",
"0.6552... | 0.74092454 | 7 |
Sends message into thread | def send_message(self, context, message):
if context.channel == "__void__":
return
if self._busy:
self._queue.append((context, message))
return
thread = context.thread
_msg = message
message = message.serialize()
self._busy = True
if self._topics[thread] is None:
assert not _msg.is_reply, "First message shouldn't be reply!\n" \
" were told to send into {}:{} message {}".format(self.name, thread, message)
self._topics[thread] = ' '.join(str(m) for m in message)
first_message = True
else:
assert _msg.is_reply, "Messages besides first should be replies!\n" \
" were told to send into {}:{} messaage {}".format(self.name, thread, message)
first_message = False
assert isinstance(thread, int) and 0 <= thread < len(self._threads), "Thread {} don't exists at channel {}!".\
format(thread, self.name)
if self.print_messages:
if first_message:
vprint("{}: Sending message {} to {}::{}".format(time.time() - self._timeref,
message, self.name, thread))
else:
vprint("{}: Sending reply {} to {}::{}({})".format(time.time() - self._timeref,
message, self.name, thread,
self._topics[thread]))
fail_idx = next(_mc)
received_by = 0
if self.gather_conversation:
conv = [_msg.sender, "-->", None, message[2:], 0, 0]
if not _msg.is_reply or self._threads[thread]["reply_to_tc"] is not True:
for s in self._subscribers:
if s.name == _msg.sender: # Don't send message back to it's source
continue
if s.name == self._threads[thread]["tc"].name \
and self._threads[thread]["reply_to_tc"] is not False:
# If s is topic caster and it would get reply - send it later (to avoid double sends)
continue
if self.gather_conversation:
conv[-2] = time.time()
idx = next(_mc)
r = s.receive_message(context, message)
if self.gather_conversation:
conv[-1] = time.time()
if r not in (False, True):
self._busy = False
assert r in (False, True), \
"{}: Reply from {} contains no result or value({}) not in (False, True)".format(
time.time() - self._timeref, s.name, r)
if r:
received_by += 1
if self.gather_conversation and (r or self.gather_all):
if r:
conv[1] = "-->"
else:
conv[1] = "-->x"
conv[2] = s.name
self._log_conv(thread, conv, idx)
if self._threads[thread]["reply_to_tc"] is not False:
idx = next(_mc)
r = self._threads[thread]["tc"].receive_message(context, message)
if self.gather_conversation:
conv[-1] = time.time()
if r not in (False, True):
self._busy = False
assert r in (False, True), \
"{}: Reply from {} contains no result or value({}) not in (False, True)".format(
time.time() - self._timeref, self._threads[thread]["tc"].name, r)
if r:
received_by += 1
if self.gather_conversation and (r or self.gather_all):
if r:
conv[1] = "-->"
else:
conv[1] = "-->x"
conv[2] = self._threads[thread]["tc"].name
self._log_conv(thread, conv, idx)
if received_by < 1:
if self.gather_conversation:
conv[-1] = time.time()
if self.print_messages:
vprint("{}: Message {} to {}::{} had no effect".format(time.time() - self._timeref,
message, self.name, thread))
if self.gather_conversation:
conv[1] = "-->x"
conv[2] = None
self._log_conv(thread, conv, fail_idx)
self._busy = False
if len(self._queue) > 0:
queued = self._queue.pop(0)
self.send_message(*queued) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def send(self, message):",
"def send_to_gui(self, message):\n message.on_thread_side()\n self.queue.put(message)\n self.sig.set()\n logger.debug(\"Message %r has been send to GUI\", message.message_id)",
"def _send(self, message):\n logger.info(message)\n self.bu... | [
"0.7251886",
"0.7028535",
"0.7008835",
"0.70002615",
"0.69917643",
"0.69660854",
"0.69660854",
"0.69660854",
"0.6932752",
"0.69234616",
"0.6904757",
"0.68988985",
"0.68747884",
"0.68623",
"0.68569106",
"0.68312794",
"0.6817026",
"0.6795177",
"0.6756574",
"0.6755073",
"0.67476... | 0.6107267 | 100 |
Incoming message handler that can be overridden by derived classes | def _incoming_handler(self, context, message, fake_reply):
return self._map[message.method](context, fake_reply, *message.args, **message.kwargs) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def handle(self, message):",
"def handle_message(self, message):",
"def handle_message(self, msg):\n pass",
"def processMessage(self, *args, **kwargs):\r\n pass",
"def handleMessage(msg):",
"def process(self, msg):\n print \"HANDLER: received a msg: %s\" % msg",
"def handle(self, m... | [
"0.76674205",
"0.7387368",
"0.72166294",
"0.7163365",
"0.70100635",
"0.6967958",
"0.69566435",
"0.67521715",
"0.6731579",
"0.6724816",
"0.66986245",
"0.6680195",
"0.66316897",
"0.6626075",
"0.6598926",
"0.65867203",
"0.65795434",
"0.65649223",
"0.656297",
"0.655957",
"0.65346... | 0.6481269 | 25 |
Common method for handling incoming messages from talk channel For customization redefine _incoming_handler please | def incoming(self, context, message, fake_reply=None):
if message.interface != self._id:
return False
if message.is_reply:
return False
if message.method not in self._methods:
eprint("{}:{} Unsupported method {}".format(self._host.name, self._name, message.method))
return False
if self._map[message.method] is None:
eprint("{}:{} Method {} is not implemented".format(self._host.name, self._name, message.method))
return False
self._incoming_handler(context, message, fake_reply) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def handle_incoming_message(obj, reply_channel):\n if int(obj[message_type_key]) == 0:\n try:\n sub_obj = create_subscriber_object(reply_channel, obj)\n subscribers[reply_channel.name] = sub_obj\n except ApiException as exc:\n send_save_to_channel(reply_channel, st... | [
"0.7198676",
"0.70006275",
"0.68786156",
"0.6589068",
"0.6574055",
"0.6566164",
"0.654098",
"0.65259284",
"0.6513632",
"0.64729154",
"0.64671236",
"0.644941",
"0.6425101",
"0.64106405",
"0.6365977",
"0.63636965",
"0.6342746",
"0.6326662",
"0.6321269",
"0.6301516",
"0.6211517"... | 0.6243993 | 20 |
Prepares message for fake_next_op method | def fake_op_message(interface, reply, on_channel=None, on_message=None, after=None, execute=False,
on_success=None, on_failure=None):
assert isinstance(interface, str), "fake_op_info: interface should be a string"
assert isinstance(reply, ProtocolReply), "fake_op_info: reply should be a ProtocolReply instance"
options = {"reply": reply}
if on_channel is not None:
assert isinstance(on_channel, str), "fake_op_info: on_channel should be a string"
options["on_channel"] = on_channel
if on_message is not None:
assert isinstance(on_message, PlatformMessage), "fake_op_info: on_message should be a PlatformMessage instance"
options["on_message"] = on_message
if after is not None:
assert isinstance(after, int) and after >= 0, "fake_op_info: after should be a natural integer"
options["after"] = after
if execute is not None:
assert isinstance(execute, bool) or execute in (1, 0) >= 0, "fake_op_info: execute should be a boolean " \
"or 0 or 1"
options["execute"] = execute
if on_success is None and on_failure is None:
on_success = True
on_failure = False
if on_success is None and on_failure is False:
on_success = True
if on_failure is None and on_success is False:
on_failure = True
if on_success is True:
assert isinstance(on_success, bool), "fake_op_info: on_success should be a boolean"
options["on_success"] = on_success
if on_failure is True:
assert isinstance(on_failure, bool), "fake_op_info: on_failure should be a boolean"
options["on_failure"] = on_failure
else:
options["on_failure"] = False
return new_message(interface, "__testing__", "fake_next_op", options) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _fake_next_op(self, context, message, dry_run=False):\r\n if context.channel in self._fake_ops:\r\n channel = context.channel\r\n if len(self._fake_ops[channel]) > 0:\r\n if \"on_message\" not in self._fake_ops[channel][0] \\\r\n or self._fake_... | [
"0.6204553",
"0.57941633",
"0.57386607",
"0.5676188",
"0.55851084",
"0.5510728",
"0.54746866",
"0.5442715",
"0.54413027",
"0.5374735",
"0.5304368",
"0.5282957",
"0.52620536",
"0.5245205",
"0.52339035",
"0.52218646",
"0.52083987",
"0.52082664",
"0.5190077",
"0.5156617",
"0.512... | 0.5297616 | 11 |
Checks whether incoming message could be processed | def supports(self, message):
if message.method == '__testing__':
return True
return self._interface.supports(message) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def check_for_incoming_info(self):\n\n if self.test_message_response:\n self.parse_incoming_message(self.test_message_response)\n return True\n\n POLL_ONLY_TIMEOUT_VALUE = 0\n got_at_least_one = False\n while (True):\n readables, writables, errors = sele... | [
"0.7115128",
"0.6838178",
"0.6745119",
"0.6687847",
"0.6675145",
"0.66316074",
"0.65846056",
"0.65725505",
"0.6522481",
"0.6514949",
"0.65149397",
"0.629913",
"0.629913",
"0.6284352",
"0.62244946",
"0.61825305",
"0.61751574",
"0.613391",
"0.61156756",
"0.6089335",
"0.60848534... | 0.0 | -1 |
Checks whether or not reply to message m2 should be faked If m1's field is None then m2's field value is not compared at all | def _fake_message_compare(m1, m2):
m1 = m1.serialize()
m2 = m2.serialize()
diff = False
for i in range(len(m1)):
if m1[i] is None:
continue
if m1[i] != m2[i]:
diff = True
break
return not diff | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def testNoneAssignment(self):\n class MyMessage(messages.Message):\n\n my_field = messages.StringField(1)\n\n m1 = MyMessage()\n m2 = MyMessage()\n m2.my_field = None\n self.assertEquals(m1, m2)",
"def __eq__(self, other):\n if not isinstance(other, SendMmsReq... | [
"0.61221015",
"0.60199493",
"0.5698596",
"0.56491196",
"0.56256944",
"0.55935615",
"0.5585704",
"0.55634177",
"0.55492973",
"0.55470234",
"0.55111665",
"0.5495307",
"0.546077",
"0.5453699",
"0.5440305",
"0.5392359",
"0.5371638",
"0.5361735",
"0.5357879",
"0.53478",
"0.5341549... | 0.7252573 | 0 |
Registers information for faking replies | def _register_fake_next_op(self, channel, fake_info):
assert isinstance(fake_info, (list, tuple, dict)), "fake_info should be a dict or list of dict or tuple of dict"
if isinstance(fake_info, (tuple, list)):
for f in fake_info:
assert isinstance(f, dict), "fake_info should be a dict or list of dict or tuple of dict"
if isinstance(fake_info, dict):
fake_info = [copy.deepcopy(fake_info)]
else:
fake_info = [copy.deepcopy(f) for f in fake_info]
for f in fake_info:
assert "reply" in f, "fake_info should contain 'reply'"
assert isinstance(f["reply"], ProtocolReply), "fake_info's reply should be a ProtocolReply instance"
for o in f:
assert o in ("reply", "execute", "on_message", "on_channel", "after", "on_success", "on_failure"), \
"Unsupported fake_info options: {}".format(o)
if "execute" in f:
assert isinstance(f["execute"], bool) or f["execute"] in (0, 1), \
"fake_info option 'execute' should be a bool or 0 or 1"
if "on_success" in f:
assert isinstance(f["on_success"], bool), \
"fake_info option 'on_success' should be a boolean"
if "on_failure" in f:
assert isinstance(f["on_failure"], bool), \
"fake_info option 'on_failure' should be a boolean"
on_success = f.get("on_success", None)
on_failure = f.get("on_failure", None)
if on_success is None and on_failure is None:
on_success = True
on_failure = False
if on_success is True or on_success is None and on_failure is False:
on_success = True
if on_failure is True or on_success is None and on_success is False:
on_failure = True
if on_success is True:
f["on_success"] = True
else:
f["on_success"] = False
if on_failure is True:
f["on_failure"] = True
else:
f["on_failure"] = False
if "on_message" in f:
assert isinstance(f["on_message"], PlatformMessage), \
"fake_info option 'on_message' should be PlatformMessage"
if "on_channel" in f:
assert isinstance(f["on_channel"], (str, list, tuple)), \
"fake_info option 'on_channel' should be a string or list/tuple of strings"
if isinstance(f["on_channel"], (list, tuple)):
for c in f["on_channel"]:
assert isinstance(c, str), \
"fake_info option 'on_channel' should be a string or list/tuple of strings"
if "after" in f:
assert isinstance(f["after"], int), "fake_info option 'after' should be an integer"
if "on_channel" not in f:
on_channel = channel,
elif isinstance(f["on_channel"], (list, tuple)):
on_channel = f["on_channel"]
else:
on_channel = f["on_channel"],
for c in on_channel:
if c not in self._fake_ops:
self._fake_ops[c] = [f]
else:
self._fake_ops[c].append(f) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _post_answer(self, answer):\n print(answer)\n self.messages_received.append(answer)",
"def _post_answer(self, answer):\n print(answer)\n self.messages_received.append(answer)",
"def register_message():\n global mss_cnt\n\n gmess = Graph()\n\n # Construimos el mensaje de... | [
"0.576329",
"0.576329",
"0.5649313",
"0.56348217",
"0.55767995",
"0.5420812",
"0.5407427",
"0.5336492",
"0.5320446",
"0.53109264",
"0.5305628",
"0.5286324",
"0.5285838",
"0.5274294",
"0.52733195",
"0.52711815",
"0.5264393",
"0.5212218",
"0.518291",
"0.51799375",
"0.50915813",... | 0.47367492 | 74 |
Implements method "__testing__" that would be supported by all protocols | def _general_testing(self, context, kind, *args, **kwargs):
if kind == "fake_next_op":
self._register_fake_next_op(context.channel, *args, **kwargs)
self._reply(context, proto_success({}, None), None)
return True
self._reply(context, proto_failure({"Unsupported testing function '{}'".format(kind)}), None)
return False | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_should_implement(self):\n pass",
"def test_supported_protocol(self):\n assert self.handler.SUPPORTED_PROTOCOL is None",
"def test_protocols(container, protocol):\n assert isinstance(container, protocol)",
"def test(self):\n raise NotImplementedError",
"def test_differentPro... | [
"0.71973604",
"0.71074444",
"0.7052137",
"0.70288616",
"0.67791927",
"0.6558383",
"0.6532375",
"0.6532375",
"0.6508606",
"0.6500069",
"0.6478221",
"0.6394548",
"0.6394548",
"0.6394548",
"0.63722515",
"0.63722515",
"0.63722515",
"0.63722515",
"0.63722515",
"0.62949234",
"0.628... | 0.6247752 | 24 |
Checks whether reply to this message should be faked and fakes it if required | def _fake_next_op(self, context, message, dry_run=False):
if context.channel in self._fake_ops:
channel = context.channel
if len(self._fake_ops[channel]) > 0:
if "on_message" not in self._fake_ops[channel][0] \
or self._fake_message_compare(self._fake_ops[channel][0]["on_message"], message):
if "after" in self._fake_ops[channel][0] and self._fake_ops[channel][0]["after"] > 0:
if dry_run:
return False
self._fake_ops[channel][0]["after"] -= 1
return False
if dry_run:
return True
instruction = self._fake_ops[channel].pop(0)
if len(self._fake_ops[channel]) == 0:
del self._fake_ops[channel]
vprint("{}: faking reply".format(self.name))
reply = instruction["reply"]
if "execute" in instruction and instruction["execute"] == True:
result = {}
if instruction["on_success"]:
result["on_success"] = reply
if instruction["on_failure"]:
result["on_failure"] = reply
return result
if reply.success:
self._worker.reply(context, PlatformMessage.success(reply.retval, reply.retval_name))
else:
self._worker.reply(context, PlatformMessage.failure(reply.state, reply.errcode))
return True
else:
# TODO: Shouln't be here actually. Raise error!
del self._fake_ops[channel]
return False | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_message_missing_body(self):\n receipt_handle = 'blah'\n msg = [{\"ReceiptHandle\": receipt_handle}]\n with patch.object(self.dead_letter, 'remove_message_from_queue') as dequeue_fake:\n self.dead_letter.handle_messages(msg)\n\n # Ensure message dequeued.\n ... | [
"0.59258664",
"0.59085613",
"0.57893336",
"0.57723594",
"0.5757017",
"0.57384187",
"0.5699918",
"0.5680963",
"0.5651382",
"0.5646977",
"0.5619524",
"0.5575746",
"0.55438524",
"0.5535469",
"0.5488948",
"0.5482735",
"0.5448364",
"0.54328763",
"0.5418796",
"0.5418293",
"0.538297... | 0.5759425 | 4 |
Implements builtin methods of protocol base class | def _process_message_general(self, context, message):
f = self._fake_next_op(context, message)
if f is True:
return True
elif f is not False:
return f
elif message.method == "__testing__":
self._general_testing(context, *message.args, **message.kwargs)
return True
else:
return False | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def protocol(self):\n ...",
"def protocol(self):\n\n raise NotImplementedError()",
"def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass",
"def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass",
"def __subclasshook__(self, *args, *... | [
"0.6998625",
"0.66639465",
"0.62314713",
"0.62314713",
"0.62314713",
"0.62314713",
"0.62314713",
"0.62314713",
"0.62314713",
"0.62314713",
"0.62314713",
"0.62314713",
"0.62314713",
"0.62314713",
"0.62314713",
"0.62314713",
"0.62314713",
"0.62314713",
"0.62314713",
"0.62314713",... | 0.0 | -1 |
Processes incoming message First tries to process protocol's builtins If message weren't processed by builtins then message is passed to protocol's interface object | def process_message(self, context, message):
r = self._process_message_general(context, message)
if r is True:
return
elif r is not False:
self._interface.incoming(context, message, r)
else:
self._interface.incoming(context, message, None) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _process_msg(cls, msg):\n raise NotImplementedError",
"def handle_protobuf(self, message: protobuf.ProtocolMessage) -> None:",
"def process_message(self, msg, src):",
"def handleMessage(msg):",
"def _process_message(self, obj):\n pass",
"def _r_on_incoming_message(self, string, protocol... | [
"0.6494044",
"0.6347405",
"0.6252538",
"0.61391824",
"0.6027273",
"0.6013206",
"0.59676176",
"0.59675497",
"0.594518",
"0.59192914",
"0.5894395",
"0.5877927",
"0.58471686",
"0.5832104",
"0.58276415",
"0.58168703",
"0.5714494",
"0.5707053",
"0.56793517",
"0.567809",
"0.5669059... | 0.547723 | 32 |
Validates that certain fields are exist in self._context and are having specified value Use to make sure if protocol's FSM is in right state | def _validate_context(self, content):
result = False
if self._context is not None:
for k in content:
if k not in self._context or self._context[k] != content[k]:
break
result = True
return result | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _validate(self, instance, value):",
"def is_valid(self, value):\r\n pass",
"def validate(self, instance, value):",
"def validate(self, instance, value):",
"def _validate_post_fields(self, value, name, result):\n state = result.get(\"state\")\n persistent_state = result.get(\"persis... | [
"0.63824505",
"0.6050479",
"0.60258853",
"0.60258853",
"0.5951332",
"0.5951332",
"0.5933391",
"0.5919774",
"0.5896552",
"0.5887481",
"0.5868621",
"0.58041704",
"0.57922333",
"0.57876384",
"0.5754241",
"0.57441854",
"0.5739001",
"0.5719968",
"0.57187736",
"0.569956",
"0.568105... | 0.55769426 | 32 |
Exposes protected data to a caller. Be extremely careful with it contains originals, not a copies | def expose_data(self):
return _ExposedFarmData(self._platforms, self._awaiting, self._channels) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_data_protected(self): \n pass",
"def protected(_):\n return False # This protects nothing",
"def write_protected(cls, **kwargs: Any) -> \"DataSchema[ObjType]\":\n return super().write_protected(**kwargs) # type: ignore",
"def __setattr__(self,name,value):\n\n ... | [
"0.7407494",
"0.6308666",
"0.597678",
"0.5667471",
"0.5667471",
"0.5665087",
"0.5659497",
"0.56185216",
"0.5615482",
"0.55298316",
"0.5414067",
"0.53964454",
"0.53828067",
"0.53819466",
"0.53760314",
"0.5359521",
"0.535882",
"0.5358776",
"0.5326243",
"0.5324696",
"0.529068",
... | 0.481632 | 100 |
Returns running state for specified platform | def is_running(self, platform):
if platform not in self._platforms:
raise ValueError("Platform {} is not registered".format(platform))
return self._platforms[platform].running | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def state(self):\n data = self.coordinator.data[self._host_name][self._node_name][self._vm_id]\n if data[\"status\"] == \"running\":\n return STATE_ON\n return STATE_OFF",
"def running_state(self) -> int | None:\n return self.cluster.get(\"running_state\")",
"def running(... | [
"0.61530626",
"0.60770965",
"0.6040421",
"0.60027874",
"0.5839394",
"0.58060783",
"0.5787307",
"0.57715446",
"0.57025546",
"0.56921524",
"0.56680083",
"0.55934256",
"0.55586237",
"0.553357",
"0.5515652",
"0.55087674",
"0.5503442",
"0.5490447",
"0.5443907",
"0.54368734",
"0.54... | 0.6958679 | 0 |
Checks whether all platforms are running or not | def all_is_running(self):
return all(p.running for p in self._platforms.values()) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def check_platform():\n system = platform.system()\n distro = platform.platform()\n is_raspberry_pi = False\n try:\n info = open(\"/proc/cpuinfo\").read()\n except FileNotFoundError:\n is_raspberry_pi = False\n else:\n # bcm2708: Raspberry Pi 1\n # bcm2709: Raspberry P... | [
"0.7448283",
"0.7354531",
"0.69025147",
"0.68859076",
"0.6782263",
"0.6772269",
"0.67584515",
"0.6750433",
"0.6750433",
"0.67330426",
"0.6725543",
"0.6633071",
"0.6604187",
"0.65855706",
"0.65599746",
"0.6514661",
"0.65100974",
"0.6507308",
"0.650659",
"0.6505434",
"0.643089"... | 0.7654313 | 0 |
Checks whether all platforms are stopped or not | def all_is_stopped(self):
return all(not p.running for p in self._platforms.values()) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def emergency_stop(self):\r\n eprint(\"Emergency platforms stop\")\r\n stop_list = []\r\n for p in self._platforms:\r\n stop_list.append(self._platforms[p])\r\n\r\n success = True\r\n while len(stop_list) > 0: # NOTE: stop platforms in reverse order\r\n p = ... | [
"0.75852925",
"0.7146642",
"0.6602631",
"0.65657175",
"0.628147",
"0.62783736",
"0.61895704",
"0.61452276",
"0.60707706",
"0.60059714",
"0.5987051",
"0.5946374",
"0.5929576",
"0.5919849",
"0.5919849",
"0.5917849",
"0.58654445",
"0.58415127",
"0.582378",
"0.58181137",
"0.57904... | 0.82884616 | 0 |
Registers new platform (or at least tries). If new platform depends on platforms that were not registered yet then registration of this platform would be deferred. Registration would be continued after registering all the platforms that this platform depends on | def register_platform(self, factory, kind, parent=None, wait=None):
self._try_register_platform(factory, kind, parent, wait) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def _register_hardware_platform(\n hass: HomeAssistant, integration_domain: str, platform: HardwareProtocol\n) -> None:\n if integration_domain == DOMAIN:\n return\n if not hasattr(platform, \"async_info\"):\n raise HomeAssistantError(f\"Invalid hardware platform {platform}\")\n has... | [
"0.71603966",
"0.7015166",
"0.6779148",
"0.65924436",
"0.6380313",
"0.6261706",
"0.6097711",
"0.5934751",
"0.58920646",
"0.5801316",
"0.5635861",
"0.56350684",
"0.5605743",
"0.55982506",
"0.5503871",
"0.5495337",
"0.5468214",
"0.54491985",
"0.5402476",
"0.536305",
"0.5344545"... | 0.7204478 | 0 |
Worker method that do actually registers platform | def _try_register_platform(self, factory, kind, parent, wait, awaiting=False):
name = factory.name
assert kind is not None, "instance kind can't be None (instance name is {})".format(name)
if factory.name is None:
factory.name = name = "random_name" # TODO: use GUID
assert name not in self._platforms and (awaiting or name not in self._awaiting),\
"encountered second platform with name {}".format(name)
# TODO: analyze args and update wait if there are references to other platforms
assert wait is None or name not in wait, "platform {} can't wait for self!".format(name)
# If all necessary parent and co-platforms are already created - finish registration of this one
if (parent is None or parent in self._platforms) \
and (wait is None or all(w in self._platforms for w in wait)):
np = factory.finish_registration()
self._platforms[name] = np
if parent is not None:
assert np not in self._platforms[parent].subplatforms, "Subplatform {} is already within " \
"parent's ({}) subplatforms list, " \
"but shouldn't be".format(name, parent)
np.parent = self._platforms[parent]
self._platforms[parent].subplatforms.append(np)
if wait is not None:
for w in wait:
assert np not in self._platforms[w].depended, "Subplatform {} is already within " \
"depended's list of {}, " \
"but shouldn't be".format(name, w)
self._platforms[w].depended.append(np)
if awaiting:
del self._awaiting[name]
self._check_awaiting()
# Otherwise put it into waiting list
else:
self._awaiting[name] = {
"instance": factory,
"kind": kind,
"parent": parent,
"wait": wait} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def async_process_hardware_platforms(hass: HomeAssistant) -> None:\n hass.data[DOMAIN][\"hardware_platform\"] = {}\n\n await async_process_integration_platforms(hass, DOMAIN, _register_hardware_platform)",
"async def _register_hardware_platform(\n hass: HomeAssistant, integration_domain: str, plat... | [
"0.67203164",
"0.6423017",
"0.62060404",
"0.61684966",
"0.6153153",
"0.5944612",
"0.59082896",
"0.5862393",
"0.5726266",
"0.5700211",
"0.56732666",
"0.5646277",
"0.5646277",
"0.5623879",
"0.56002146",
"0.5568672",
"0.5550284",
"0.5511287",
"0.54954875",
"0.54954875",
"0.54710... | 0.5712664 | 9 |
Runs through platforms which registration were deferred and tries to register them again | def _check_awaiting(self):
# TODO: check for wait loops
for w in list(self._awaiting.values()):
self._try_register_platform(w["instance"], w["kind"], w["parent"], w["wait"], awaiting=True) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def async_process_hardware_platforms(hass: HomeAssistant) -> None:\n hass.data[DOMAIN][\"hardware_platform\"] = {}\n\n await async_process_integration_platforms(hass, DOMAIN, _register_hardware_platform)",
"def _try_register_platform(self, factory, kind, parent, wait, awaiting=False):\r\n name... | [
"0.667766",
"0.6472627",
"0.64608395",
"0.6125786",
"0.6103623",
"0.585542",
"0.5823268",
"0.5784557",
"0.57517254",
"0.56858265",
"0.5681627",
"0.5622832",
"0.5608007",
"0.55615294",
"0.5553192",
"0.55258495",
"0.5492156",
"0.54448736",
"0.54345196",
"0.5424958",
"0.53986436... | 0.6857937 | 0 |
Stops platforms as it can | def emergency_stop(self):
eprint("Emergency platforms stop")
stop_list = []
for p in self._platforms:
stop_list.append(self._platforms[p])
success = True
while len(stop_list) > 0: # NOTE: stop platforms in reverse order
p = stop_list.pop(-1)
vprint("Emergency stop for {}".format(p))
try:
r = p._stop([])
except Exception as e:
success = False
eprint("Exception occurred while stopping platform {} emergently: {}".format(p, e))
exprint()
continue
if not r.success:
success = False
return success | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def platform_stop(self):\n self.platform.stop()",
"def stopEngines():\n pass",
"def stop(self):\n # Cleanup platform first.\n self.cleanup()\n\n if self.init_lhost:\n self._lhost.stop()\n\n self.status = False # pylint: disable=attribute-defined-outside-init",
... | [
"0.8364842",
"0.75134593",
"0.7007069",
"0.6861968",
"0.6861968",
"0.6861968",
"0.6861968",
"0.6804117",
"0.6767265",
"0.67454034",
"0.6689028",
"0.66532433",
"0.66270936",
"0.65178484",
"0.65178484",
"0.6510709",
"0.64955664",
"0.6493137",
"0.6477048",
"0.6451692",
"0.645169... | 0.7356 | 2 |
Unregisters platform instance. Can recursively unregister all instance's nested platforms. If recursion is not used and by the instant unregister is called there is still nested platforms then exception would be rised | def unregister_platform_instance(self, instance, recursive=False):
platform_to_remove = None
for k, v in self._platforms.items():
if v == instance:
platform_to_remove = k
break
if platform_to_remove is None:
raise ValueError("No platform instance have been found to unregister")
if len(instance.subplatforms) > 0:
if recursive:
for sp in list(instance.subplatforms):
self.unregister_platform_instance(sp, recursive)
else:
raise ValueError("Can't unregister platform with subplatforms. Set recursive to True")
if instance.parent is not None:
if instance in instance.parent.subplatforms:
instance.parent.subplatforms.remove(instance)
if instance in instance.parent.subplatforms:
raise IndexError("Instance were registered multiple times in parent's subplatforms list")
else:
raise IndexError("Instance is not found in parent's subplatforms list")
del self._platforms[platform_to_remove] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def unregister_platform(self, name, recursive=False):\r\n if name in dict(self._platforms):\r\n self.unregister_platform_instance(self._platforms[name], recursive)",
"def unregister_platform(self, platform_uuid):\n return self.do_rpc('unregister_platform', platform_uuid=platform_uuid)",
... | [
"0.8009664",
"0.6706928",
"0.6103871",
"0.5728736",
"0.57112795",
"0.568827",
"0.5645297",
"0.5567026",
"0.5547235",
"0.55387",
"0.55205977",
"0.5519004",
"0.5469608",
"0.54393387",
"0.5368441",
"0.5361209",
"0.53546786",
"0.53507906",
"0.5317688",
"0.52915245",
"0.5263275",
... | 0.8235111 | 0 |
Wrap for unregister_platform_instance method | def unregister_platform(self, name, recursive=False):
if name in dict(self._platforms):
self.unregister_platform_instance(self._platforms[name], recursive) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def deregister_instance(InstanceId=None):\n pass",
"def unregister_platform_instance(self, instance, recursive=False):\r\n platform_to_remove = None\r\n for k, v in self._platforms.items():\r\n if v == instance:\r\n platform_to_remove = k\r\n break\r\n ... | [
"0.7437885",
"0.722585",
"0.71067107",
"0.6713975",
"0.67006856",
"0.65715706",
"0.6490679",
"0.6454682",
"0.6433686",
"0.64128125",
"0.6409299",
"0.6344683",
"0.6314368",
"0.6292651",
"0.6288555",
"0.62754303",
"0.62084085",
"0.6114578",
"0.609524",
"0.6088872",
"0.6082098",... | 0.6979844 | 3 |
Unregisters platforms factory. Usually happens after successful platform registration | def unregister_factory(self, instance):
to_remove = None
for k, v in self._awaiting.items():
if v["instance"] == instance:
to_remove = k
break
if to_remove is not None:
del self._awaiting[to_remove] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def unregister_platform(self, name, recursive=False):\r\n if name in dict(self._platforms):\r\n self.unregister_platform_instance(self._platforms[name], recursive)",
"def tear_down_registry(registry):\n for reg_adp in list(registry.registeredAdapters()):\n registry.unregisterAdapter(f... | [
"0.74393696",
"0.6878564",
"0.6781992",
"0.67377704",
"0.6643691",
"0.65110755",
"0.63454175",
"0.6340024",
"0.6208858",
"0.62054634",
"0.61191297",
"0.60082805",
"0.6006337",
"0.59341156",
"0.59182423",
"0.58983845",
"0.5870383",
"0.5865489",
"0.586217",
"0.5841826",
"0.5835... | 0.55174696 | 41 |
Says whether or not specified platform (by instance) is subscribed to channel | def is_subscribed(self, inst, channel):
if channel not in self._channels:
return False
return inst in self._channels[channel].subscribers | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_channel(self):\n return True",
"def single_channel():\n return True",
"def is_event_channel(channel: discord.TextChannel) -> bool:\n return get_active_feature(channel) == ActivationState.EVENT",
"def check_event_channel(ctx: commands.Context) -> bool:\n if get_active_feature(ctx.ch... | [
"0.6758969",
"0.65061855",
"0.6170213",
"0.60398626",
"0.59377897",
"0.58887047",
"0.58596504",
"0.5826945",
"0.57663727",
"0.574901",
"0.57350725",
"0.57127315",
"0.5697036",
"0.5667392",
"0.5624958",
"0.5623939",
"0.5619179",
"0.56188387",
"0.55817115",
"0.55813885",
"0.557... | 0.62435955 | 2 |
Subscribes specified platform to channel | def subscribe(self, inst, channel):
if channel not in self._channels:
self._channels[channel] = TalkChannel(channel, print_messages=self.verbose, timeref=self._timeref)
self._channels[channel].subscribe(inst) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def subscribe(self, channel, **kwargs):\n pass",
"def subscribe(receiver):",
"def subscribe(receiver):",
"def subscribe(receiver):",
"async def _subscribe_to_channels(self, ws: WSAssistant):\n try:\n # BitMart WebSocket API currently offers only spot/user/order private channel.\n ... | [
"0.66808635",
"0.5979494",
"0.5979494",
"0.5979494",
"0.5952215",
"0.5772565",
"0.5757093",
"0.57420313",
"0.567808",
"0.5661305",
"0.56558084",
"0.5654329",
"0.56333697",
"0.56230813",
"0.5613967",
"0.55897367",
"0.558452",
"0.55815876",
"0.55511",
"0.54930943",
"0.54869413"... | 0.5703723 | 8 |
Unsubscribes specified platform to channel | def unsubscribe(self, inst, channel):
if channel not in self._channels:
raise ValueError("Channel {} not exists!".format(channel))
self._channels[channel].unsubscribe(inst)
return
# TODO: ?delete channels if there is no subscribers
# if len(self._channels[channel].subscribers) == 0:
# del self._channels[channel]
| {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def unsubscribe(self, channel, update_handler=None):\n pass",
"def unsubscribe(receiver):",
"def unsubscribe(receiver):",
"def unsubscribe(receiver):",
"def unsubscribe(receiver):",
"def unsubscribe(receiver):",
"def unregister_publisher(self, hostname):",
"def unsubscribe(self, subject):\n ... | [
"0.6753091",
"0.67168313",
"0.67168313",
"0.67168313",
"0.67168313",
"0.67168313",
"0.61841947",
"0.614403",
"0.61410797",
"0.60061914",
"0.5981644",
"0.59452146",
"0.59342414",
"0.59306574",
"0.59306574",
"0.59159696",
"0.58706665",
"0.58182955",
"0.5811057",
"0.58029413",
"... | 0.60036814 | 10 |
Starts new thread on specified channel | def start_thread(self, topic_caster, channel, interface, reply_to_tc=None):
if channel not in self._channels:
raise ValueError("Channel {} not exists!".format(channel))
return TalkContext(channel, self._channels[channel].start_thread(topic_caster, reply_to_tc), interface) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self, channel, name, server):\n threading.Thread.__init__(self, target=self._run)\n self.__channel = channel\n self.__transport = channel.get_transport()\n self.__name = name\n self.__server = server",
"def join(self, channel):\n raise NotImplementedError",
... | [
"0.6507928",
"0.6503015",
"0.6434967",
"0.6381614",
"0.6208421",
"0.6115024",
"0.61078566",
"0.6104068",
"0.6061114",
"0.60220224",
"0.60070866",
"0.6001835",
"0.59062725",
"0.58968794",
"0.58294946",
"0.5827837",
"0.57995164",
"0.578793",
"0.57634115",
"0.57456595",
"0.57436... | 0.5886065 | 14 |
Sends message to specified channel. Also updates Message with Sources's Name (puts it as first component of message) | def send_message(self, context, message, processing=None):
# TODO: chained context to trace consequent requests
# TODO: option to build UML out of conversation
if processing is None:
if message.is_reply:
processing = 0
else:
processing = 2
if processing == 2 and message.is_reply:
raise ValueError("Processing level 2 can be set only for initial (non-reply) messages")
if context.channel not in self._channels:
raise ValueError("Channel {} not exists!".format(context.channel))
print_level_change = pref.send_message_print_level_change
if processing == 2:
self._send_message_level += 1 # Increase level if processing == 2
if print_level_change:
vprint("send message level changed to: {}".format(self._send_message_level))
try:
# Send message into channel
self._channels[context.channel].send_message(context, message)
# Register replies
if message.is_reply:
self._replies[context.channel][context.thread][message.sender] = message
else:
if context.channel not in self._replies:
self._replies[context.channel] = {}
assert context.thread not in self._replies[context.channel], \
"PlatformsFarm:send_message Unexpectedly received second initial (non-reply) message " \
"for {}:{}".format(context.channel, context.thread)
self._replies[context.channel][context.thread] = {}
except Exception as e:
if processing == 2:
self._send_message_level -= 1
if print_level_change:
vprint("send message level changed to: {}".format(self._send_message_level))
raise e
# Just exit here if processing is 0
if processing == 0:
return None
stay_in_loop = True
while stay_in_loop:
stay_in_loop = False
# Process messages if any platform received messages
if any(p.received_messages > 0 for p in self._platforms.values()):
self.process_messages()
if processing == 2: # If processing is 2, then stay in loop as there could be responses
stay_in_loop = True
if processing == 2 and not stay_in_loop: # If no more processing expected
# But it's multithreadning case and not all final replies were received yet
if pref.multithreading and not all(m.is_failure or m.is_success
for m in self._replies[context.channel][context.thread].values()):
# And some platforms are still waiting for reply - just wait a bit
if any(p.waiting_reply for p in self._platforms.values()):
time.sleep(0.001)
stay_in_loop = True
if processing == 2:
self._send_message_level -= 1
if print_level_change:
vprint("send message level changed to: {}".format(self._send_message_level))
result = self._replies[context.channel].pop(context.thread)
return result
else:
return None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def send_message(self, channel : str, message : str):\n await self._connection.send_message(channel, message)",
"def sendMsg(self, channel, message, length=None):\n self.logger.info(\"Sending in %s: %s\" % (channel, message))\n self.msg(channel, message, length)",
"def send(self, msg... | [
"0.6885398",
"0.675431",
"0.65821993",
"0.6575302",
"0.65634346",
"0.63894933",
"0.6296932",
"0.62330484",
"0.6228483",
"0.6189294",
"0.61043847",
"0.61043113",
"0.60943514",
"0.6092948",
"0.6089668",
"0.60888904",
"0.60853773",
"0.6045753",
"0.60221964",
"0.59493864",
"0.594... | 0.0 | -1 |
Invokes received messages processing by platforms Usualy is called automatically from send_message method | def process_messages(self):
for p in self._platforms.values():
if p.received_messages > 0:
p.queue_received_messages()
for p in self._platforms.values():
if p.queued_messages > 0:
p.process_queued_messages() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def receive_message(self, message):",
"def handleMessage(msg):",
"def execute_message_received(self, message_received):\n pass",
"def processMessage(self, *args, **kwargs):\r\n pass",
"def receive(self, message):",
"def handle_message(self, message):",
"def run(self):\n alogger.info(... | [
"0.7143642",
"0.71015793",
"0.7093893",
"0.702307",
"0.6902395",
"0.6859738",
"0.68166494",
"0.6779305",
"0.6749306",
"0.6745342",
"0.6691393",
"0.6681336",
"0.6598424",
"0.6589076",
"0.65837705",
"0.6558769",
"0.6531817",
"0.65218943",
"0.6481661",
"0.64773434",
"0.646337",
... | 0.6632475 | 12 |
Creates Platform's instance Should be called when conditions for creation this very instance are met platforms that this instance depends on should be already registered | def finish_registration(self):
base_platform = self._args.get("base_platform", None)
lcls = {}
try:
exec("from platforms.{}.main import RootClass as rc; cl = rc".format(base_platform), globals(), lcls)
except ModuleNotFoundError as e:
eprint("Package 'platforms.{}' or module 'main' wasn't found for creating platform instance '{}'!".format(
base_platform, self.name))
raise e
lcls["name"] = self.name
lcls["farm"] = self._farm
lcls["args"] = self._args
try:
exec("inst = cl(name=name, farm=farm, **args)", globals(), lcls)
inst = lcls["inst"]
except Exception as e:
eprint("Exception occurred when creating platform {} of {} kind!\nException: {}".format(
self.name, base_platform, e))
raise e
# inst = PlatformBase(name=self.name, farm=self._farm, **self._args) # TODO: raise exception
return inst | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def new_platform(self, id):\n p = Platform(self, id, [])\n self.platforms[id] = p\n return p",
"def platform_init(self):\n if isinstance(self.imu, MockImuController) or isinstance(self.pwm_controller, MockPWMController):\n print(\"Mock components detected, creating mock ant... | [
"0.6996833",
"0.6901165",
"0.6643392",
"0.66429996",
"0.6620305",
"0.66013455",
"0.65052664",
"0.64866644",
"0.6392875",
"0.6308356",
"0.6216505",
"0.6207374",
"0.61393857",
"0.6117521",
"0.60896856",
"0.60258096",
"0.6019131",
"0.6019086",
"0.60079926",
"0.5970026",
"0.59591... | 0.706969 | 0 |
Rules specific dict with accumulated (summary) statistics | def stats(self):
return {} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def summary(self):\n\n stats = {\n 'invalid': self.num_invalid,\n 'tested': self.num_tested,\n }\n return {\n k: v for k, v in stats.items()\n if k == 'invalid' or v != 0\n }",
"def compute_metrics(self, results: list) -> dict:",
"def comp... | [
"0.6340423",
"0.62687165",
"0.6262667",
"0.62574226",
"0.62306124",
"0.61828154",
"0.6159125",
"0.61552644",
"0.61206615",
"0.6068211",
"0.6058657",
"0.6044734",
"0.60149944",
"0.601353",
"0.5946292",
"0.593793",
"0.5930342",
"0.5924686",
"0.5853451",
"0.5822528",
"0.5802484"... | 0.5944312 | 15 |
Scoreboard handler for incoming commands | def cmd(self, context, message):
return True | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def received_message(self, msg):\n command = int(msg[:8], base=16)\n msg = msg[8:]\n self.log.debug(\"CONTROLLER - RECEIVED COMMAND: \" + str(command))\n self.log.debug(\"CONTROLLER - MSG: \" + str([int(msg[i:i+8], base=16) for i in range(0, len(msg), 8)]))\n if command == 0:\n ... | [
"0.6840156",
"0.6722847",
"0.65974706",
"0.64543533",
"0.64348984",
"0.6269596",
"0.6221818",
"0.6210287",
"0.62007767",
"0.6155704",
"0.61550456",
"0.6142969",
"0.61363643",
"0.6136049",
"0.60979337",
"0.6096791",
"0.60831475",
"0.6043705",
"0.60334855",
"0.60296637",
"0.597... | 0.0 | -1 |
Scoreboard handler for incoming responses | def response(self, context, message):
return True | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def handle(self) -> None:\r\n\r\n if self.data.get(\"message-id\") != None:\r\n if self.data[\"status\"] == \"error\":\r\n print(self.data[\"error\"])\r\n return\r\n else:\r\n requestData = self.obs.pendingResponses.pop(self.data[\"message-i... | [
"0.667267",
"0.60985816",
"0.60786134",
"0.60786134",
"0.60626084",
"0.60359406",
"0.59885734",
"0.59627366",
"0.59537965",
"0.592757",
"0.5912877",
"0.5900186",
"0.58672774",
"0.5839805",
"0.5789892",
"0.5711895",
"0.56955504",
"0.56955504",
"0.56919116",
"0.56762016",
"0.56... | 0.53896457 | 71 |
Use for commands that can't be handled | def _unhandled(self, context, message, reason):
# TODO: call host's method instead
self._host.unhandled.append((context.str, message.serialize(), reason))
self._host.expected[context.str] = None
eprint("{}: Command {} can't be handled due to {}".format(self._host.name, message.serialize(), reason)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _command(self, *cmd, handler=None):",
"def check_commands(self):\n pass",
"def accept_command():\n # TODO",
"def commands():",
"def commands():\n pass",
"def commands():\n pass",
"def commands():\n pass",
"def commands():\n pass",
"def command():\n pass",
"async d... | [
"0.7336675",
"0.7285146",
"0.7252042",
"0.70243955",
"0.6982735",
"0.6982735",
"0.6982735",
"0.6982735",
"0.6879094",
"0.67902136",
"0.67638505",
"0.6750508",
"0.67460364",
"0.6706385",
"0.66952014",
"0.66615903",
"0.6648451",
"0.6611464",
"0.65597415",
"0.6558557",
"0.653128... | 0.0 | -1 |
Coverage summary tupple with amount of cases and covered cases May be used to determine coverage percentage | def coverage(self):
return 0, 1 | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_project_test_coverage(self) -> None:\n print_statistics = {}\n total_number_columns = 0\n number_columns_without_tests = 0\n\n for model_name in self.dbt_tests.keys():\n columns = self.dbt_tests[model_name]\n\n model_number_columns = 0\n model_co... | [
"0.71685416",
"0.68137187",
"0.6776906",
"0.6677319",
"0.6650848",
"0.6639017",
"0.6626381",
"0.65998113",
"0.6589576",
"0.65476686",
"0.6533306",
"0.6496852",
"0.6492893",
"0.64699256",
"0.64314204",
"0.64311635",
"0.64148486",
"0.63928735",
"0.6356816",
"0.63496864",
"0.633... | 0.7372552 | 0 |
Coverage handler for incoming messages | def receive_message(self, context, message):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def sample_handler(controller, msg, pkt):\n pass",
"def handle(self, message):",
"def handle_message(self, message):",
"def processMessage(self, *args, **kwargs):\r\n pass",
"def handle_message(self, message):\n\n try:\n controller_func = get_controller_func(message.code)\n\n ... | [
"0.6550436",
"0.6415692",
"0.6320498",
"0.60273343",
"0.60133165",
"0.60033965",
"0.6000999",
"0.59604585",
"0.595996",
"0.5894243",
"0.58883953",
"0.58782285",
"0.58495873",
"0.5848556",
"0.5842221",
"0.5829234",
"0.58113396",
"0.5810897",
"0.57167685",
"0.57069564",
"0.5706... | 0.5589948 | 28 |
Encodes the input sequence and returns the hidden state from the last step of the encoder RNN. | def encode(self, x):
_, hid = self.encoder(x) #All RNN classes output a tuple of 2 objects: the output of the RNN first and the hidden state from the last item in
return hid #the input sequence second. We're only interested in the hidden state | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _encode(self):\n with tf.variable_scope('passage_encoding'):\n self.sep_p_encodes, _ = rnn('bi-lstm', self.p_emb, self.p_length, self.hidden_size)\n with tf.variable_scope('question_encoding'):\n self.sep_q_encodes, _ = rnn('bi-lstm', self.q_emb, self.q_length, self.hidden_s... | [
"0.683423",
"0.6820723",
"0.6807832",
"0.675225",
"0.66331315",
"0.66327035",
"0.65157163",
"0.6451546",
"0.643727",
"0.6415194",
"0.6381192",
"0.6375881",
"0.6340776",
"0.6330177",
"0.6329643",
"0.63056594",
"0.62932295",
"0.6283715",
"0.62812126",
"0.6278949",
"0.6253341",
... | 0.7965193 | 0 |
Gives access to the hidden state of the individual components of the input batch. Since encode() encodes the whole batch of sequences in one call, but decoding is performed for every batch sequence individually, this method becomes necessary. | def get_encoded_item(self, encoded, index):
#for vanilla RNN and GRU, since they have a hidden state represented as a single tensor
##return encoded[:, index:index+1]
#for LSTM, since it has a hidden state represented as a tuple of two tensors: the cell state and the hidden state
return encoded[0][:, index:index+1].contiguous(), encoded[1][:, index:index+1].contiguous() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def encode(self, x):\n _, hid = self.encoder(x) #All RNN classes output a tuple of 2 objects: the output of the RNN first and the hidden state from the last item in\n return hid #the input sequence second. We're only interested in the hidden state",
"def _encode(self):\n with tf.variab... | [
"0.6531696",
"0.6165337",
"0.61568475",
"0.59570867",
"0.59406155",
"0.5908961",
"0.58463246",
"0.5821808",
"0.5770365",
"0.57613736",
"0.57613736",
"0.5760088",
"0.5760088",
"0.5760088",
"0.5757003",
"0.57509893",
"0.5750539",
"0.57451725",
"0.570995",
"0.5698639",
"0.569119... | 0.0 | -1 |
Performs one single decoding step for one example. It passes the hidden state for the decoder and input the tensor with the embeddings vector for the input token. The result of the decoder is passed to the output net to obtain the logits for every item in the dictionary. It outputs those logits and the new hidden state returned by the decoder. | def decode_one(self, hid, input_x):
out, new_hid = self.decoder(input_x.unsqueeze(0), hid)
out = self.output(out)
return out.squeeze(dim=0), new_hid | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def decode():\n with tf.Session() as sess:\n # Create model and load parameters.\n model = create_model(True)\n model.batch_size = 1 # We decode one sentence at a time.\n init_model(sess, model)\n\n # Load vocabularies.\n vocab, rev_vocab = data_utils.get_vocabulary(FL... | [
"0.7202692",
"0.6928575",
"0.6782827",
"0.6653837",
"0.65899867",
"0.6541342",
"0.6538928",
"0.6499897",
"0.6485077",
"0.641824",
"0.64113784",
"0.637471",
"0.6374259",
"0.6316419",
"0.6304639",
"0.62677693",
"0.62158835",
"0.6194001",
"0.61918765",
"0.61859244",
"0.6164222",... | 0.0 | -1 |
Decodes sequence by feeding token into net again and acts according to probabilities. | def decode_chain_argmax(self, hid, begin_emb, seq_len, stop_at_token=None):
res_logits = []
res_tokens = []
cur_emb = begin_emb
for _ in range(seq_len):
out_logits, hid = self.decode_one(hid, cur_emb)
out_token_v = torch.max(out_logits, dim=1)[1] #uses argmax to go from logits to the decoded token ID
out_token = out_token_v.data.cpu().numpy()[0]
cur_emb = self.emb(out_token_v) #obtains embeddings for the decoded token to iterate over
res_logits.append(out_logits)
res_tokens.append(out_token)
if stop_at_token is not None and out_token == stop_at_token:
break
return torch.cat(res_logits), res_tokens | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def decode(self, passage_vectors, question_vectors, init_with_question=True):\n with tf.variable_scope('pn_decoder'):\n fake_inputs = tf.zeros(\n [tf.shape(passage_vectors)[0], 2, 1]) # not used\n sequence_len = tf.tile([2], [tf.shape(passage_vectors)[0]])\n ... | [
"0.5983819",
"0.5868206",
"0.5792075",
"0.57452136",
"0.5722459",
"0.569437",
"0.569437",
"0.56869286",
"0.5666454",
"0.5658044",
"0.56570065",
"0.56113213",
"0.560299",
"0.5571299",
"0.5535273",
"0.55341107",
"0.55276024",
"0.5525068",
"0.55168015",
"0.5509156",
"0.5509141",... | 0.0 | -1 |
Almost the same as decode_chain_argmax(), but instead of using argmax, it performs the random sampling from the returned probability distribution. | def decode_chain_sampling(self, hid, begin_emb, seq_len, stop_at_token=None, device='cpu'):
res_logits = []
res_actions = []
cur_emb = begin_emb
for _ in range(seq_len):
out_logits, hid = self.decode_one(hid, cur_emb)
out_probs_v = F.softmax(out_logits, dim=1)
out_probs = out_probs_v.data.cpu().numpy()[0]
action = int(np.random.choice(out_probs.shape[0], p=out_probs))
action_v = torch.LongTensor([action]).to(device)
cur_emb = self.emb(action_v)
res_logits.append(out_logits)
res_actions.append(action)
if stop_at_token is not None and action == stop_at_token:
break
return torch.cat(res_logits), res_actions | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _random_max_wrap(*args):\n _, opt_pt = random_maximise(*args)\n return opt_pt",
"def custom_argmax(arr):\n return np.random.choice(np.flatnonzero(arr == arr.max()))",
"def argmax_random_tie(seq, key=identity):\n return argmax(shuffled(seq), key=key)",
"def argmax(values):\n\tvalues = np.a... | [
"0.68480635",
"0.6822088",
"0.67059606",
"0.65348536",
"0.63732535",
"0.63186467",
"0.6183038",
"0.59274244",
"0.58021593",
"0.57685935",
"0.5748391",
"0.5623231",
"0.56098354",
"0.5572641",
"0.5567708",
"0.55628234",
"0.55474985",
"0.55280584",
"0.55236834",
"0.54596233",
"0... | 0.0 | -1 |
Returns a free socket port. It works by creating an empty socket, binding it to port 0 so that the OS automatically assigns a free port to it, obtaining the port using `getsockname` and then immediately closing it. The application intending to use this port should bind to it immediately so that no other application binds to it before us. | def get_free_port():
sock = socket.socket()
# bind to a random port (so that the OS automatically assigns us a free port)
sock.bind(('', 0))
# obtain the random port value
port = sock.getsockname()[1]
# close the socket so that the port gets free
sock.close()
return port | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_free_port():\n s = socket.socket()\n s.bind(('', 0))\n _, port = s.getsockname()\n s.close()\n return port",
"def get_free_port():\n s = socket.socket(socket.AF_INET, type=socket.SOCK_STREAM)\n s.bind(('127.0.0.1', 0))\n _, port = s.getsockname()\n s.close()\n return port",
... | [
"0.89505553",
"0.8727646",
"0.87067574",
"0.8690947",
"0.8689836",
"0.8675498",
"0.8668015",
"0.86642563",
"0.86574286",
"0.85628986",
"0.8248419",
"0.8209171",
"0.81788385",
"0.81242055",
"0.81235737",
"0.8103176",
"0.80116427",
"0.79655474",
"0.79650843",
"0.7938987",
"0.78... | 0.85797644 | 9 |
Start a web app at the given port for serving the jigna view for the given template and context. | def start_web_app(template, context, port=8000):
from tornado.ioloop import IOLoop
from jigna.web_app import WebApp
ioloop = IOLoop.instance()
app = WebApp(template=template, context=context)
app.listen(port)
print 'Starting the web app on port %s ...' % port
ioloop.start() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def serve(port):\n app.run(host='0.0.0.0', port=port, debug=True)",
"def run():\n return render_template('index.html')",
"def serve() -> None:\n uvicorn.run(\n \"bartender.web.application:get_app\",\n workers=settings.workers_count,\n host=settings.host,\n port=settings.por... | [
"0.6824245",
"0.6593554",
"0.65677285",
"0.65660465",
"0.6564316",
"0.6545133",
"0.65020066",
"0.6479876",
"0.6479806",
"0.6458077",
"0.64405406",
"0.64051074",
"0.6399282",
"0.6394062",
"0.63920164",
"0.63898516",
"0.6380909",
"0.6349641",
"0.62751275",
"0.62736714",
"0.6271... | 0.8381516 | 0 |
Builds a differentiable augmentation pipeline based on its class type. | def build_aug(aug_type, **kwargs):
if aug_type not in _AUGMENTATIONS:
raise ValueError(f'Invalid augmentation type: `{aug_type}`!\n'
f'Types allowed: {list(_AUGMENTATIONS)}.')
return _AUGMENTATIONS[aug_type](**kwargs) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _make_pipeline(preprocessors, classifier):\n if isinstance(preprocessors, list):\n # support only preprocessing of lenght 2\n return make_pipeline(preprocessors[0], preprocessors[1], classifier)\n if preprocessors is None:\n return make_pipeline(classifier)\n\n return make_pipelin... | [
"0.618366",
"0.57090163",
"0.554121",
"0.55004793",
"0.5495945",
"0.54675126",
"0.54427373",
"0.5428508",
"0.53878695",
"0.5384956",
"0.5383808",
"0.53803486",
"0.53243446",
"0.5311842",
"0.5292812",
"0.5282065",
"0.5245183",
"0.52103126",
"0.5209436",
"0.5195009",
"0.5174649... | 0.5901364 | 1 |
Test case based on fashion mnist tutorial | def test_kafka_output_sequence():
fashion_mnist = tf.keras.datasets.fashion_mnist
((train_images, train_labels), (test_images, _)) = fashion_mnist.load_data()
class_names = [
"T-shirt/top",
"Trouser",
"Pullover",
"Dress",
"Coat",
"Sandal",
"Shirt",
"Sneaker",
"Bag",
"Ankle boot",
]
train_images = train_images / 255.0
test_images = test_images / 255.0
model = tf.keras.Sequential(
[
tf.keras.layers.Flatten(input_shape=(28, 28)),
tf.keras.layers.Dense(128, activation=tf.nn.relu),
tf.keras.layers.Dense(10, activation=tf.nn.softmax),
]
)
model.compile(
optimizer="adam", loss="sparse_categorical_crossentropy", metrics=["accuracy"]
)
model.fit(train_images, train_labels, epochs=5)
class OutputCallback(tf.keras.callbacks.Callback):
"""KafkaOutputCallback"""
def __init__(
self, batch_size, topic, servers
): # pylint: disable=super-init-not-called
self._sequence = kafka_ops.KafkaOutputSequence(topic=topic, servers=servers)
self._batch_size = batch_size
def on_predict_batch_end(self, batch, logs=None):
index = batch * self._batch_size
for outputs in logs["outputs"]:
for output in outputs:
self._sequence.setitem(index, class_names[np.argmax(output)])
index += 1
def flush(self):
self._sequence.flush()
channel = f"e{time.time()}e"
topic = "test_" + channel
# By default batch size is 32
output = OutputCallback(32, topic, "localhost")
predictions = model.predict(test_images, callbacks=[output])
output.flush()
predictions = [class_names[v] for v in np.argmax(predictions, axis=1)]
# Reading from `test_e(time)e` we should get the same result
dataset = tfio.kafka.KafkaDataset(topics=[topic], group="test", eof=True)
for entry, prediction in zip(dataset, predictions):
assert entry.numpy() == prediction.encode() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_keras_mnist():\n data = fetch(\"mnist\")\n check(data, n_samples_train=60000, n_samples_test=10000, n_features=28 * 28)",
"def main():\n\n os.system(\"rm -rf images; mkdir images\")\n\n if (len(sys.argv) > 1):\n N = int(sys.argv[1])\n else:\n N = 10\n\n x_test = np.load(\... | [
"0.7775563",
"0.7588313",
"0.74669766",
"0.7369658",
"0.7182041",
"0.7171548",
"0.7122935",
"0.7103584",
"0.7040259",
"0.70040536",
"0.69778866",
"0.69447285",
"0.69191986",
"0.69013685",
"0.68820626",
"0.68727684",
"0.68639225",
"0.68560404",
"0.6851476",
"0.68482596",
"0.68... | 0.0 | -1 |
Test the functionality of the KafkaGroupIODataset when the consumer group is being newly created. | def test_kafka_group_io_dataset_primary_cg():
dataset = tfio.experimental.streaming.KafkaGroupIODataset(
topics=["key-partition-test"],
group_id="cgtestprimary",
servers="localhost:9092",
configuration=[
"session.timeout.ms=7000",
"max.poll.interval.ms=8000",
"auto.offset.reset=earliest",
],
)
assert np.all(
sorted(k.numpy() for (k, _) in dataset)
== sorted(("D" + str(i)).encode() for i in range(10))
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_kafka_group_io_dataset_primary_cg_new_topic():\n dataset = tfio.experimental.streaming.KafkaGroupIODataset(\n topics=[\"key-test\"],\n group_id=\"cgtestprimary\",\n servers=\"localhost:9092\",\n configuration=[\n \"session.timeout.ms=7000\",\n \"max.pol... | [
"0.71414036",
"0.7126442",
"0.7073285",
"0.6968703",
"0.6968703",
"0.6883464",
"0.68237174",
"0.6809277",
"0.680548",
"0.68034434",
"0.67761457",
"0.67453897",
"0.6516205",
"0.65071094",
"0.6487364",
"0.6473713",
"0.6469515",
"0.63676554",
"0.63668543",
"0.6361959",
"0.630479... | 0.65959835 | 12 |
Test the functionality of the KafkaGroupIODataset when the consumer group has read all the messages and committed the offsets. | def test_kafka_group_io_dataset_primary_cg_no_lag():
dataset = tfio.experimental.streaming.KafkaGroupIODataset(
topics=["key-partition-test"],
group_id="cgtestprimary",
servers="localhost:9092",
configuration=["session.timeout.ms=7000", "max.poll.interval.ms=8000"],
)
assert np.all(sorted(k.numpy() for (k, _) in dataset) == []) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_kafka_group_io_dataset_auto_offset_reset():\n\n dataset = tfio.experimental.streaming.KafkaGroupIODataset(\n topics=[\"key-partition-test\"],\n group_id=\"cgglobaloffsetearliest\",\n servers=\"localhost:9092\",\n configuration=[\n \"session.timeout.ms=7000\",\n ... | [
"0.6880712",
"0.67094135",
"0.66918844",
"0.64915144",
"0.63925254",
"0.6284364",
"0.61970186",
"0.6131777",
"0.61313844",
"0.60980684",
"0.60387677",
"0.59368175",
"0.59367937",
"0.5835078",
"0.56977046",
"0.5690426",
"0.56897986",
"0.56894445",
"0.56839097",
"0.567647",
"0.... | 0.62748325 | 6 |
Test the functionality of the KafkaGroupIODataset when the existing consumer group reads data from a new topic. | def test_kafka_group_io_dataset_primary_cg_new_topic():
dataset = tfio.experimental.streaming.KafkaGroupIODataset(
topics=["key-test"],
group_id="cgtestprimary",
servers="localhost:9092",
configuration=[
"session.timeout.ms=7000",
"max.poll.interval.ms=8000",
"auto.offset.reset=earliest",
],
)
assert np.all(
sorted(k.numpy() for (k, _) in dataset)
== sorted(("D" + str(i)).encode() for i in range(10))
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_kafka_group_io_dataset_resume_primary_cg_new_topic():\n import tensorflow_io.kafka as kafka_io\n\n # Write new messages to the topic\n for i in range(10, 100):\n message = f\"D{i}\"\n kafka_io.write_kafka(message=message, topic=\"key-test\")\n # Read only the newly sent 90 messag... | [
"0.7862941",
"0.73936385",
"0.70595884",
"0.68379927",
"0.68281376",
"0.6740333",
"0.6714614",
"0.6704045",
"0.6651035",
"0.6603814",
"0.64650786",
"0.6370465",
"0.6314179",
"0.60142636",
"0.5972484",
"0.5948897",
"0.5936028",
"0.5844628",
"0.5811538",
"0.58090895",
"0.580786... | 0.76525635 | 1 |
Test the functionality of the KafkaGroupIODataset when the consumer group is yet to catch up with the newly added messages only (Instead of reading from the beginning). | def test_kafka_group_io_dataset_resume_primary_cg():
import tensorflow_io.kafka as kafka_io
# Write new messages to the topic
for i in range(10, 100):
message = f"D{i}"
kafka_io.write_kafka(message=message, topic="key-partition-test")
# Read only the newly sent 90 messages
dataset = tfio.experimental.streaming.KafkaGroupIODataset(
topics=["key-partition-test"],
group_id="cgtestprimary",
servers="localhost:9092",
configuration=["session.timeout.ms=7000", "max.poll.interval.ms=8000"],
)
assert np.all(
sorted(k.numpy() for (k, _) in dataset)
== sorted(("D" + str(i)).encode() for i in range(10, 100))
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_kafka_group_io_dataset_resume_primary_cg_new_topic():\n import tensorflow_io.kafka as kafka_io\n\n # Write new messages to the topic\n for i in range(10, 100):\n message = f\"D{i}\"\n kafka_io.write_kafka(message=message, topic=\"key-test\")\n # Read only the newly sent 90 messag... | [
"0.76577485",
"0.73002553",
"0.6971321",
"0.6940536",
"0.6914675",
"0.6828621",
"0.6707299",
"0.6647323",
"0.6454408",
"0.64065754",
"0.62465376",
"0.6183665",
"0.61425513",
"0.6138433",
"0.6063199",
"0.6052937",
"0.60468554",
"0.5998803",
"0.5994782",
"0.59467036",
"0.592855... | 0.7597071 | 1 |
Test the functionality of the KafkaGroupIODataset when the consumer group is yet to catch up with the newly added messages only (Instead of reading from the beginning) from the new topic. | def test_kafka_group_io_dataset_resume_primary_cg_new_topic():
import tensorflow_io.kafka as kafka_io
# Write new messages to the topic
for i in range(10, 100):
message = f"D{i}"
kafka_io.write_kafka(message=message, topic="key-test")
# Read only the newly sent 90 messages
dataset = tfio.experimental.streaming.KafkaGroupIODataset(
topics=["key-test"],
group_id="cgtestprimary",
servers="localhost:9092",
configuration=["session.timeout.ms=7000", "max.poll.interval.ms=8000"],
)
assert np.all(
sorted(k.numpy() for (k, _) in dataset)
== sorted(("D" + str(i)).encode() for i in range(10, 100))
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_kafka_group_io_dataset_resume_primary_cg():\n import tensorflow_io.kafka as kafka_io\n\n # Write new messages to the topic\n for i in range(10, 100):\n message = f\"D{i}\"\n kafka_io.write_kafka(message=message, topic=\"key-partition-test\")\n # Read only the newly sent 90 messag... | [
"0.74266845",
"0.72838503",
"0.69508654",
"0.69229776",
"0.6898682",
"0.6788215",
"0.66945463",
"0.65659136",
"0.64467585",
"0.6332732",
"0.62817466",
"0.62599236",
"0.6245761",
"0.61413795",
"0.6088383",
"0.6065624",
"0.6036422",
"0.60189974",
"0.6011775",
"0.598527",
"0.594... | 0.7933696 | 0 |
Test the functionality of the KafkaGroupIODataset when a secondary consumer group is created and is yet to catch up all the messages, from the beginning. | def test_kafka_group_io_dataset_secondary_cg():
dataset = tfio.experimental.streaming.KafkaGroupIODataset(
topics=["key-partition-test"],
group_id="cgtestsecondary",
servers="localhost:9092",
configuration=[
"session.timeout.ms=7000",
"max.poll.interval.ms=8000",
"auto.offset.reset=earliest",
],
)
assert np.all(
sorted(k.numpy() for (k, _) in dataset)
== sorted(("D" + str(i)).encode() for i in range(100))
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_kafka_group_io_dataset_resume_primary_cg_new_topic():\n import tensorflow_io.kafka as kafka_io\n\n # Write new messages to the topic\n for i in range(10, 100):\n message = f\"D{i}\"\n kafka_io.write_kafka(message=message, topic=\"key-test\")\n # Read only the newly sent 90 messag... | [
"0.73009527",
"0.72444355",
"0.7244203",
"0.70529",
"0.6862954",
"0.6756388",
"0.66355544",
"0.6621006",
"0.64989007",
"0.64381534",
"0.63905436",
"0.6337798",
"0.62951696",
"0.62927544",
"0.6165134",
"0.6079073",
"0.6057113",
"0.6047525",
"0.5999353",
"0.59861374",
"0.593344... | 0.7149818 | 3 |
Test the functionality of the KafkaGroupIODataset when a new consumer group reads data from multiple topics from the beginning. | def test_kafka_group_io_dataset_tertiary_cg_multiple_topics():
dataset = tfio.experimental.streaming.KafkaGroupIODataset(
topics=["key-partition-test", "key-test"],
group_id="cgtesttertiary",
servers="localhost:9092",
configuration=[
"session.timeout.ms=7000",
"max.poll.interval.ms=8000",
"auto.offset.reset=earliest",
],
)
assert np.all(
sorted(k.numpy() for (k, _) in dataset)
== sorted([("D" + str(i)).encode() for i in range(100)] * 2)
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_kafka_group_io_dataset_resume_primary_cg_new_topic():\n import tensorflow_io.kafka as kafka_io\n\n # Write new messages to the topic\n for i in range(10, 100):\n message = f\"D{i}\"\n kafka_io.write_kafka(message=message, topic=\"key-test\")\n # Read only the newly sent 90 messag... | [
"0.7916993",
"0.7726499",
"0.75612617",
"0.73106486",
"0.7162436",
"0.7129199",
"0.71261126",
"0.6688718",
"0.6652531",
"0.63588357",
"0.629463",
"0.62792355",
"0.61795956",
"0.61230063",
"0.61221826",
"0.6078071",
"0.6073669",
"0.6049846",
"0.5994584",
"0.59919417",
"0.59703... | 0.7474016 | 3 |
Test the functionality of the `auto.offset.reset` configuration at global and topic level | def test_kafka_group_io_dataset_auto_offset_reset():
dataset = tfio.experimental.streaming.KafkaGroupIODataset(
topics=["key-partition-test"],
group_id="cgglobaloffsetearliest",
servers="localhost:9092",
configuration=[
"session.timeout.ms=7000",
"max.poll.interval.ms=8000",
"auto.offset.reset=earliest",
],
)
assert np.all(
sorted(k.numpy() for (k, _) in dataset)
== sorted(("D" + str(i)).encode() for i in range(100))
)
dataset = tfio.experimental.streaming.KafkaGroupIODataset(
topics=["key-partition-test"],
group_id="cgglobaloffsetlatest",
servers="localhost:9092",
configuration=[
"session.timeout.ms=7000",
"max.poll.interval.ms=8000",
"auto.offset.reset=latest",
],
)
assert np.all(sorted(k.numpy() for (k, _) in dataset) == [])
dataset = tfio.experimental.streaming.KafkaGroupIODataset(
topics=["key-partition-test"],
group_id="cgtopicoffsetearliest",
servers="localhost:9092",
configuration=[
"session.timeout.ms=7000",
"max.poll.interval.ms=8000",
"conf.topic.auto.offset.reset=earliest",
],
)
assert np.all(
sorted(k.numpy() for (k, _) in dataset)
== sorted(("D" + str(i)).encode() for i in range(100))
)
dataset = tfio.experimental.streaming.KafkaGroupIODataset(
topics=["key-partition-test"],
group_id="cgtopicoffsetlatest",
servers="localhost:9092",
configuration=[
"session.timeout.ms=7000",
"max.poll.interval.ms=8000",
"conf.topic.auto.offset.reset=latest",
],
)
assert np.all(sorted(k.numpy() for (k, _) in dataset) == []) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_issue_reset_time(self):\n pass",
"def test_reset():\n dev = _aws_device(wires=2)\n dev._circuit = CIRCUIT\n dev._task = TASK\n\n dev.reset()\n assert dev.circuit is None\n assert dev.task is None",
"def reset_topic(bot, trigger):\n global report\n\n if get_state():\n ... | [
"0.58305633",
"0.5826309",
"0.57031226",
"0.56880814",
"0.5674384",
"0.56572354",
"0.55940706",
"0.55784523",
"0.5553939",
"0.5552377",
"0.5534695",
"0.5404209",
"0.54005706",
"0.5393411",
"0.53927755",
"0.53910935",
"0.53739655",
"0.5346079",
"0.5346079",
"0.5346079",
"0.534... | 0.6541038 | 0 |
Test the functionality of the KafkaGroupIODataset when the consumer is configured to have an invalid stream_timeout value which is less than the message_timeout value. | def test_kafka_group_io_dataset_invalid_stream_timeout():
STREAM_TIMEOUT = -20
try:
tfio.experimental.streaming.KafkaGroupIODataset(
topics=["key-partition-test", "key-test"],
group_id="cgteststreaminvalid",
servers="localhost:9092",
stream_timeout=STREAM_TIMEOUT,
configuration=["session.timeout.ms=7000", "max.poll.interval.ms=8000"],
)
except ValueError as e:
assert str(
e
) == "Invalid stream_timeout value: {} ,set it to -1 to block indefinitely.".format(
STREAM_TIMEOUT
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_kafka_group_io_dataset_stream_timeout_check():\n import tensorflow_io.kafka as kafka_io\n\n def write_messages_background():\n # Write new messages to the topic in a background thread\n time.sleep(6)\n for i in range(100, 200):\n message = f\"D{i}\"\n kafka... | [
"0.7494565",
"0.68445444",
"0.61413234",
"0.6002265",
"0.59668875",
"0.5940467",
"0.59011936",
"0.58735675",
"0.58508337",
"0.58345395",
"0.57948846",
"0.57629395",
"0.57347316",
"0.57000494",
"0.5662307",
"0.5627969",
"0.5604364",
"0.5560788",
"0.5560788",
"0.55548257",
"0.5... | 0.83997965 | 0 |
Test the functionality of the KafkaGroupIODataset when the consumer is configured to have a valid stream_timeout value and thus waits for the new messages from kafka. | def test_kafka_group_io_dataset_stream_timeout_check():
import tensorflow_io.kafka as kafka_io
def write_messages_background():
# Write new messages to the topic in a background thread
time.sleep(6)
for i in range(100, 200):
message = f"D{i}"
kafka_io.write_kafka(message=message, topic="key-partition-test")
dataset = tfio.experimental.streaming.KafkaGroupIODataset(
topics=["key-partition-test"],
group_id="cgteststreamvalid",
servers="localhost:9092",
stream_timeout=20000,
configuration=[
"session.timeout.ms=7000",
"max.poll.interval.ms=8000",
"auto.offset.reset=earliest",
],
)
# start writing the new messages to kafka using the background job.
# the job sleeps for some time (< stream_timeout) and then writes the
# messages into the topic.
thread = threading.Thread(target=write_messages_background, args=())
thread.daemon = True
thread.start()
# At the end, after the timeout has occurred, we must have the old 100 messages
# along with the new 100 messages
assert np.all(
sorted(k.numpy() for (k, _) in dataset)
== sorted(("D" + str(i)).encode() for i in range(200))
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_kafka_group_io_dataset_invalid_stream_timeout():\n\n STREAM_TIMEOUT = -20\n try:\n tfio.experimental.streaming.KafkaGroupIODataset(\n topics=[\"key-partition-test\", \"key-test\"],\n group_id=\"cgteststreaminvalid\",\n servers=\"localhost:9092\",\n ... | [
"0.790406",
"0.6366534",
"0.6356977",
"0.61877793",
"0.60831314",
"0.60248893",
"0.5973552",
"0.59520674",
"0.5936202",
"0.58431596",
"0.57945126",
"0.5725716",
"0.5712746",
"0.570165",
"0.5689419",
"0.56843454",
"0.5650357",
"0.55747294",
"0.557346",
"0.5550135",
"0.5498954"... | 0.8004889 | 0 |
Test the functionality of batch.num.messages property of KafkaBatchIODataset/KafkaGroupIODataset. | def test_kafka_mini_dataset_size():
import tensorflow_io.kafka as kafka_io
# Write new messages to the topic
for i in range(200, 10000):
message = f"D{i}"
kafka_io.write_kafka(message=message, topic="key-partition-test")
BATCH_NUM_MESSAGES = 5000
dataset = tfio.experimental.streaming.KafkaBatchIODataset(
topics=["key-partition-test"],
group_id="cgminibatchsize",
servers=None,
stream_timeout=5000,
configuration=[
"session.timeout.ms=7000",
"max.poll.interval.ms=8000",
"auto.offset.reset=earliest",
f"batch.num.messages={BATCH_NUM_MESSAGES}",
],
)
for mini_d in dataset:
count = 0
for _ in mini_d:
count += 1
assert count == BATCH_NUM_MESSAGES
break | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_kafka_batch_io_dataset():\n\n dataset = tfio.experimental.streaming.KafkaBatchIODataset(\n topics=[\"mini-batch-test\"],\n group_id=\"cgminibatchtrain\",\n servers=None,\n stream_timeout=5000,\n configuration=[\n \"session.timeout.ms=7000\",\n \"... | [
"0.64023566",
"0.6360138",
"0.63011515",
"0.6271337",
"0.61075103",
"0.6065402",
"0.60378826",
"0.60176194",
"0.59386075",
"0.5936413",
"0.59298617",
"0.59279746",
"0.5922301",
"0.5909433",
"0.5898732",
"0.58711314",
"0.58583987",
"0.58453405",
"0.5823402",
"0.5822543",
"0.58... | 0.684737 | 0 |
Test the functionality of the KafkaBatchIODataset by training a model directly on the incoming kafka message batch(of type tf.data.Dataset), in an onlinetraining fashion. | def test_kafka_batch_io_dataset():
dataset = tfio.experimental.streaming.KafkaBatchIODataset(
topics=["mini-batch-test"],
group_id="cgminibatchtrain",
servers=None,
stream_timeout=5000,
configuration=[
"session.timeout.ms=7000",
"max.poll.interval.ms=8000",
"auto.offset.reset=earliest",
],
)
NUM_COLUMNS = 1
model = tf.keras.Sequential(
[
tf.keras.layers.Input(shape=(NUM_COLUMNS,)),
tf.keras.layers.Dense(4, activation="relu"),
tf.keras.layers.Dropout(0.1),
tf.keras.layers.Dense(1, activation="sigmoid"),
]
)
model.compile(
optimizer="adam",
loss=tf.keras.losses.BinaryCrossentropy(from_logits=True),
metrics=["accuracy"],
)
assert issubclass(type(dataset), tf.data.Dataset)
for mini_d in dataset:
mini_d = mini_d.map(
lambda m, k: (
tf.strings.to_number(m, out_type=tf.float32),
tf.strings.to_number(k, out_type=tf.float32),
)
).batch(2)
assert issubclass(type(mini_d), tf.data.Dataset)
# Fits the model as long as the data keeps on streaming
model.fit(mini_d, epochs=5) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def train(self, batch):\n pass",
"def train(self, batch_training=False):\n raise NotImplementedError",
"def train(self, num_batches: int):",
"def train(train_dataset: torch.utils.data.Dataset, test_dataset: torch.utils.data.Dataset,\n training_config: dict = train_config, global_config... | [
"0.725532",
"0.704524",
"0.6841591",
"0.6800355",
"0.67653406",
"0.67564285",
"0.66826314",
"0.6670544",
"0.6661017",
"0.6658394",
"0.65870076",
"0.6586631",
"0.65774953",
"0.65341204",
"0.6532416",
"0.6496773",
"0.6493735",
"0.64827245",
"0.6464911",
"0.64211214",
"0.6411292... | 0.7809584 | 0 |
Hook to be use by subclasses to define default ACLs in context. | def __base_acl__(self) -> list:
_acls = [
(Allow, 'g:briefy_qa', ['add', 'delete', 'edit', 'list', 'view'])
]
return _acls | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __acl__():",
"def get_acl(registry=None):",
"def load_acl(self):\n macl_class = self.app.config.get('MACL_CLASS', None)\n macl_dict = self.app.config.get('MACL_DEFINITION', None)\n default_roles = self.app.config.get('MACL_DEFAULT_ROLES', None)\n\n if default_roles is not None:\... | [
"0.6822682",
"0.6064362",
"0.6048131",
"0.6034133",
"0.58422464",
"0.5725353",
"0.57216316",
"0.5718573",
"0.5646452",
"0.55869544",
"0.5586848",
"0.55686396",
"0.55665946",
"0.545657",
"0.5445769",
"0.5405563",
"0.5397825",
"0.53963953",
"0.5391042",
"0.5391042",
"0.5389581"... | 0.62626284 | 1 |
List of fields allowed in filtering and sorting. | def filter_allowed_fields(self):
allowed_fields = super().filter_allowed_fields
# Remove assignment_id
allowed_fields.remove('assignment_id')
return allowed_fields | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def fields(self):\n return [f[1] for f in sorted(self.dd.fields.items())]",
"def getFields(self):\n return sorted(self.schema.fields, key=lambda f: f.name)",
"def fields(self) -> List[Field]: # pragma: no cover\n pass",
"def _field_names(self):\n return [self._sanitize_field_name... | [
"0.7203694",
"0.70437205",
"0.69849616",
"0.69056183",
"0.6868574",
"0.6849462",
"0.67701536",
"0.67247665",
"0.67190754",
"0.6691722",
"0.668793",
"0.668793",
"0.66687506",
"0.66492057",
"0.6648726",
"0.66373897",
"0.66218805",
"0.6619963",
"0.6591684",
"0.65700096",
"0.6567... | 0.64064956 | 33 |
Default filters for this Service. | def default_filters(self, query) -> object:
assignment_id = self.request.matchdict.get('assignment_id')
if assignment_id:
query.filter(self.model.assignment_id == assignment_id)
return query | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def std_filters():\n kwargs = {\n \"sentence_filters\":[punctuation_filter],\n \"word_filters\":[small_word_filter, stopword_filter, stemming_filter]\n }\n return kwargs",
"def get_filters(self):",
"def default_search_filters(cls):\n q = QueryDict(mutable=True)\n q.setlist(... | [
"0.725708",
"0.7212429",
"0.71636355",
"0.6952968",
"0.69228226",
"0.6897654",
"0.6820288",
"0.6785757",
"0.6766489",
"0.6697421",
"0.6685094",
"0.6655373",
"0.66130894",
"0.6598326",
"0.6537085",
"0.6485721",
"0.6480506",
"0.6385164",
"0.6371988",
"0.63620067",
"0.6340479",
... | 0.0 | -1 |
Creates a new pathfinding service | def __init__(
self,
web3: Web3,
contract_manager: ContractManager,
registry_address: Address,
sync_start_block: int = 0,
required_confirmations: int = 8,
poll_interval: int = 10,
):
super().__init__()
self.web3 = web3
self.contract_manager = contract_manager
self.registry_address = registry_address
self.sync_start_block = sync_start_block
self.required_confirmations = required_confirmations
self.poll_interval = poll_interval
self.chain_id = int(web3.net.version)
self.is_running = gevent.event.Event()
self.token_networks: Dict[Address, TokenNetwork] = {}
self.token_network_listeners: List[BlockchainListener] = []
self.is_running = gevent.event.Event()
log.info('Starting TokenNetworkRegistry Listener (required confirmations: {})...'.format(
self.required_confirmations,
))
self.token_network_registry_listener = BlockchainListener(
web3=web3,
contract_manager=self.contract_manager,
contract_name=CONTRACT_TOKEN_NETWORK_REGISTRY,
contract_address=self.registry_address,
required_confirmations=self.required_confirmations,
poll_interval=self.poll_interval,
sync_start_block=self.sync_start_block,
)
log.info(
f'Listening to token network registry @ {registry_address} '
f'from block {sync_start_block}',
)
self._setup_token_networks() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def createService(data):\n return Service(data).create()",
"def new(\n cls,\n name: str,\n description: str,\n registration_schema: JSON,\n result_schema: JSON,\n database_session: Session) -> 'Service':\n raise NotImplementedError()",
... | [
"0.66257864",
"0.6032868",
"0.60326034",
"0.6012139",
"0.5914998",
"0.5851863",
"0.57294667",
"0.57228637",
"0.5708061",
"0.5678534",
"0.5656917",
"0.56435645",
"0.5626607",
"0.5623124",
"0.5580457",
"0.55738074",
"0.55718637",
"0.55306184",
"0.552144",
"0.5487335",
"0.547394... | 0.0 | -1 |
Checks if a token network is followed by the pathfinding service. | def follows_token_network(self, token_network_address: Address) -> bool:
assert is_checksum_address(token_network_address)
return token_network_address in self.token_networks.keys() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _is_request_to_token_url(self, request):\n if not self.token_url:\n return False\n\n if self.token_url == request.path:\n return True\n\n request.match(self.token_url)\n\n if request.matchdict:\n return True\n\n return False",
"def reach(sel... | [
"0.5835548",
"0.5597924",
"0.5571266",
"0.5485773",
"0.5480768",
"0.5480768",
"0.54687196",
"0.5454214",
"0.5441436",
"0.5436674",
"0.5424187",
"0.5416221",
"0.53875804",
"0.5344155",
"0.5312403",
"0.529961",
"0.5279912",
"0.5251868",
"0.52469206",
"0.52468187",
"0.5241061",
... | 0.67394125 | 0 |
Returns the `TokenNetwork` for the given address or `None` for unknown networks. | def _get_token_network(self, token_network_address: Address) -> Optional[TokenNetwork]:
assert is_checksum_address(token_network_address)
if not self.follows_token_network(token_network_address):
return None
else:
return self.token_networks[token_network_address] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_network(address: str, netmask: str) -> IPv4Network:\n net = IPv4Network(f\"{address}/{netmask}\", strict=False)\n return net",
"def _get_network(name):\n\n if name not in _NAME_TO_NETS:\n raise ValueError('Network name [%s] not recognized.' % name)\n return _NAME_TO_NETS[name].model",
"def g... | [
"0.63604003",
"0.61137646",
"0.610317",
"0.59229994",
"0.57684386",
"0.5742403",
"0.5735001",
"0.5647258",
"0.5518795",
"0.55021477",
"0.5481944",
"0.539838",
"0.53970176",
"0.5341332",
"0.52976215",
"0.5289916",
"0.5274275",
"0.52362585",
"0.5219444",
"0.52164847",
"0.521336... | 0.8030924 | 0 |
!TXT! Return the URL for the online feedback service | def get_feedback_url(self):
return self.get_setting('service_feedback_url') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def support_url(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"support_url\")",
"def Url(self) -> str:",
"def feedback():\n return render_template(\"feedback.html\")",
"def get_url():\n config = configparser.RawConfigParser()\n config.read(\"speech.cfg\")\n region = config.get('a... | [
"0.61752695",
"0.61325103",
"0.6079804",
"0.6072169",
"0.6037325",
"0.59497833",
"0.5917915",
"0.5912349",
"0.5900737",
"0.58638495",
"0.5862365",
"0.58503306",
"0.583637",
"0.58221316",
"0.5819276",
"0.580274",
"0.5801738",
"0.5754639",
"0.57428956",
"0.57399815",
"0.5739981... | 0.78211945 | 0 |
Load CliMAF standard operators. Invoked by standard CliMAF setup The operators list also show in variable 'cscripts' They are documented elsewhere | def load_standard_operators():
#
# Compute scripts
#
cscript('select' ,scriptpath+'mcdo.sh "${operator}" "${out}" "${var}" "${period_iso}" "${domain}" "${alias}" "${units}" "${missing}" ${ins} ',
commuteWithTimeConcatenation=True, commuteWithSpaceConcatenation=True)
#
cscript('ccdo',
scriptpath+'mcdo.sh "${operator}" "${out}" "${var}" "${period_iso}" "${domain}" "${alias}" "${units}" "${missing}" ${ins}')
#
cscript('minus', 'cdo sub ${in_1} ${in_2} ${out}',
commuteWithTimeConcatenation=True, commuteWithSpaceConcatenation=True)
#
cscript('plus', 'cdo add ${in_1} ${in_2} ${out}',
commuteWithTimeConcatenation=True, commuteWithSpaceConcatenation=True)
#
cscript('space_average',
scriptpath+'mcdo.sh fldmean "${out}" "${var}" "${period_iso}" "${domain}" "${alias}" "${units}" "${missing}" ${ins}',
commuteWithTimeConcatenation=True)
#
cscript('time_average' ,
scriptpath+'mcdo.sh timmean "${out}" "${var}" "${period_iso}" "${domain}" "${alias}" "${units}" "${missing}" ${ins}' ,
commuteWithSpaceConcatenation=True)
#
cscript('llbox' ,
scriptpath+'mcdo.sh "" "${out}" "${var}" "${period_iso}" "${latmin},${latmax},${lonmin},${lonmax}" "${alias}" "${units}" "${missing}" ${ins}',
commuteWithTimeConcatenation=True, commuteWithSpaceConcatenation=True)
#
cscript('regrid' ,
scriptpath+'regrid.sh ${in} ${in_2} ${out} ${option}',
commuteWithTimeConcatenation=True, commuteWithSpaceConcatenation=True)
#
cscript('regridn' ,
scriptpath+'regrid.sh ${in} ${cdogrid} ${out} ${option}',
commuteWithTimeConcatenation=True, commuteWithSpaceConcatenation=True)
#
cscript('rescale' ,
'cdo expr,\"${var}=${scale}*${var}+${offset};\" ${in} ${out}',
commuteWithTimeConcatenation=True, commuteWithSpaceConcatenation=True)
#
cscript('mean_and_std',
scriptpath+'mean_and_std.sh ${in} ${var} ${out} ${out_sdev}',
# This tells CliMAF how to compute varname for name output 'sdev'
# using input varname
sdev_var="std(%s)" ,
commuteWithTimeConcatenation=True)
#
# Declare plot scripts
cscript('ncview' ,'ncview ${in} 1>/dev/null 2>&1&' )
#
cscript('timeplot', 'ncl '+scriptpath+'timeplot.ncl infile=\'\"${in}\"\' outfile=\'\"${out}\"\' '
'var=\'\"${var}\"\' title=\'\"${title}\"\'',format="png")
#
# plot: main field (main_file) + auxiliary field (aux_file, optional) + vectors (u_file & v_file, optionals)
#
cscript('plot' , '(ncl -Q '+ scriptpath +'gplot.ncl main_file=\'\"${in}\"\' aux_file=\'\"${in_2}\"\' '
'u_file=\'\"${in_3}\"\' v_file=\'\"${in_4}\"\' rotation=${rotation} '
'plotname=\'\"${out}\"\' cmap=\'\"${color}\"\' vmin=${min} vmax=${max} vdelta=${delta} '
'main_var=\'\"${var}\"\' aux_var=\'\"${var_2}\"\' u_var=\'\"${var_3}\"\' v_var=\'\"${var_4}\"\' '
'title=\'\"${title}\"\' scale=${scale} offset=${offset} mpCenterLonF=${mpCenterLonF} '
'vcRefMagnitudeF=${vcRefMagnitudeF} vcRefLengthF=${vcRefLengthF} vcMinDistanceF=${vcMinDistanceF} '
'vcGlyphStyle=\'\"${vcGlyphStyle}\"\' vcLineArrowColor=\'\"${vcLineArrowColor}\"\' '
'units=\'\"${units}\"\' linp=${linp} colors=\'\"${colors}\"\' level=${level} time=${time} '
'proj=\'\"${proj}\"\' contours=\'\"${contours}\"\' focus=\'\"${focus}\"\' '
'type=\'\"${format}\"\' resolution=\'\"${resolution}\"\' trim=${trim} '
'vcb=${vcb} lbLabelFontHeightF=${lbLabelFontHeightF} invXY=${invXY} '
'tmYLLabelFontHeightF=${tmYLLabelFontHeightF} tmXBLabelFontHeightF=${tmXBLabelFontHeightF} '
'tmYRLabelFontHeightF=${tmYRLabelFontHeightF} tiXAxisFontHeightF=${tiXAxisFontHeightF} '
'tiYAxisFontHeightF=${tiYAxisFontHeightF} gsnPolarLabelFontHeightF=${gsnPolarLabelFontHeightF} '
'tiMainFont=\'\"${tiMainFont}\"\' tiMainFontHeightF=${tiMainFontHeightF} '
'tiMainPosition=\'\"${tiMainPosition}\"\' gsnLeftString=\'\"${gsnLeftString}\"\' '
'gsnRightString=\'\"${gsnRightString}\"\' gsnCenterString=\'\"${gsnCenterString}\"\' '
'gsnStringFont=\'\"${gsnStringFont}\"\' gsnStringFontHeightF=${gsnStringFontHeightF} )', format="graph")
#
cscript('lines' , '(ncl -Q '+ scriptpath +'lineplot.ncl infile=\'\"${mmin}\"\' '
'plotname=\'\"${out}\"\' var=\'\"${var}\"\' title=\'\"${title}\"\' '
'linp=${linp} labels=\'\"${labels}\"\' colors=\'\"${colors}\"\' thickness=${thickness}'
'T_axis=\'\"${T_axis}\"\' fmt=\'\"${fmt}\"\' && '
'convert ${out} -trim ${out}) ', format="png")
#
cscript('curves' , '(ncl -Q '+ scriptpath +'curves.ncl infile=\'\"${mmin}\"\' '
'plotname=\'\"${out}\"\' var=\'\"${var}\"\' title=\'\"${title}\"\' '
'labels=\'\"${labels}\"\' colors=\'\"${colors}\"\' thickness=${thickness} && '
'convert ${out} -trim ${out}) ', format="png")
#
# cpdfcrop : pdfcrop by preserving metadata
#
cscript('cpdfcrop' , 'pdfcrop ${in} ${out} ', format="pdf")
#
cscript('ncdump' , 'ncdump -h ${in} ', format="txt")
#
if (os.system("type cdfmean >/dev/null 2>&1")== 0 ) :
load_cdftools_operators()
else :
clogger.warning("No Cdftool available") | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _basic_operators_init():\n global BASIC_OPERATORS\n\n BASIC_OPERATORS = {\n \"angle_between\": {\n \"node\": \"angleBetween\",\n \"inputs\": [\n [\"vector1X\", \"vector1Y\", \"vector1Z\"],\n [\"vector2X\", \"vector2Y\", \"vector2Z\"],\n ... | [
"0.5800942",
"0.54121894",
"0.5350327",
"0.52697974",
"0.5171791",
"0.5129815",
"0.511153",
"0.5089675",
"0.5077119",
"0.50660294",
"0.50468045",
"0.5024355",
"0.5013382",
"0.5007174",
"0.5001452",
"0.49958974",
"0.49821275",
"0.497245",
"0.49616897",
"0.49017334",
"0.4900833... | 0.7239035 | 0 |
Return the query list as a DataFrame. | def get_query_list():
prov_list = QueryProvider.list_data_environments()
print("Generating documentation for for the following providers")
print(", ".join(list(PROVIDERS)))
print("Skipping the following providers")
print(", ".join(list(set(prov_list) - set(PROVIDERS))))
env_providers = {prov: QueryProvider(prov) for prov in tqdm.tqdm(PROVIDERS)}
query_series = []
for env, env_queries in env_providers.items():
query_names = env_queries.list_queries()
for query_name in query_names:
q_group, q_name = query_name.split(".")
qry = env_queries.query_store.get_query(q_group + "." + q_name)
if "table" in qry.default_params:
q_table = qry.default_params["table"].get("default", "na").split()[0]
elif "table" in qry.required_params:
q_table = qry.required_params["table"].get("default", "na").split()[0]
else:
q_table = "-"
q_dict = {
"Environment": env,
"QueryGroup": q_group,
"Query": q_name,
"Description": qry.description,
"Req-Params": ", ".join(
sorted(
[
f"{param} ({p_data.get('type')})"
for param, p_data in qry.required_params.items()
]
)
),
# "OtherParams": ", ".join([f"{param}" for param in qry.default_params]),
"Table": q_table,
}
query_series.append(pd.Series(q_dict))
print()
return pd.DataFrame(query_series).sort_values(
["Environment", "QueryGroup", "Query"]
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def query_to_df(query):\n df = pd.DataFrame(query.all())\n df.columns = [x['name'] for x in query.column_descriptions]\n return df",
"def query2df(query):\n df = pd.DataFrame(data = list(itertools.product([0, 1], repeat=len(query.variables))), columns=query.variables)\n df['p'] = query.values.flat... | [
"0.7733995",
"0.7497827",
"0.73814756",
"0.7326154",
"0.7304706",
"0.7227527",
"0.7195444",
"0.71918434",
"0.71499586",
"0.7113315",
"0.70896244",
"0.7081603",
"0.70788634",
"0.70317006",
"0.70228714",
"0.7020063",
"0.7013619",
"0.6978598",
"0.6976442",
"0.68564945",
"0.68412... | 0.6495787 | 50 |
Generate query list document. | def generate_document(query_df): # sourcery skip: identity-comprehension
doc_lines = [
"Data Queries Reference",
"=" * len("Data Queries Reference"),
"",
"",
]
# This line fails if re-written as dict(query_df.groupby("Environment"))
# pylint: disable=unnecessary-comprehension
group_dict = {name: group for name, group in query_df.groupby("Environment")}
for name, friendly_name in PROVIDERS.items():
if name not in group_dict:
continue
grp = group_dict[name]
doc_lines.append(f"Queries for {friendly_name}")
doc_lines.append("-" * len(f"Queries for {friendly_name}"))
doc_lines.append(f"\nData Environment identifier: {name}\n")
tbl_txt = tabulate(
grp.drop(columns="Environment"),
headers="keys",
showindex="never",
tablefmt="rst",
)
tbl_txt = [line.strip() for line in tbl_txt.split("\n")]
doc_lines.extend(tbl_txt)
doc_lines.append("\n\n")
return "\n".join(doc_lines) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def generate_query(self):\n return",
"def get_query_list():\n prov_list = QueryProvider.list_data_environments()\n\n print(\"Generating documentation for for the following providers\")\n print(\", \".join(list(PROVIDERS)))\n print(\"Skipping the following providers\")\n print(\", \".joi... | [
"0.64937806",
"0.6459933",
"0.60802174",
"0.60519475",
"0.59186524",
"0.57771593",
"0.5772095",
"0.57147473",
"0.5705186",
"0.5635158",
"0.5617996",
"0.5612918",
"0.55703384",
"0.55453086",
"0.5526077",
"0.5504283",
"0.54998153",
"0.54894817",
"0.5426078",
"0.54242843",
"0.54... | 0.63552195 | 2 |
Fit the model from data in X. | def fit(self, X, y=None):
if self.n_rows is None:
n_rows = X.shape[0]
else:
n_rows = self.n_rows
self.shape_ = n_rows, X.shape[1]
self.scaler_ = MinMaxScaler().fit(X)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def fit(self, X):\n raise NotImplementedError",
"def fit(self, X):",
"def fit(self, X, y):",
"def fit(self, X, y):",
"def fit(self, X, y):",
"def fit(self, X,y):\n pass",
"def fit(self, X):\n self._fit_X = X",
"def fit(self, X, y=...):\n ...",
"def fit(self, X, y=...):\n... | [
"0.8456153",
"0.84106666",
"0.8192276",
"0.8192276",
"0.8192276",
"0.8108174",
"0.8097223",
"0.8097219",
"0.8097219",
"0.8097219",
"0.8097219",
"0.8097219",
"0.8097219",
"0.8097219",
"0.8097219",
"0.8097219",
"0.8097219",
"0.808293",
"0.8073022",
"0.8018419",
"0.79754156",
... | 0.0 | -1 |
Fit the model from data in X. PCA is fit to estimate the rotation and UniformSampler is fit to transformed data. | def fit(self, X, y=None):
self.pca_ = self._make_pca()
transformed = self.pca_.fit_transform(X)
self.sampler_ = UniformSampler(n_rows=self.n_rows).fit(transformed)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def fit_transform(self, X, y=None):\n X = np.asfortranarray(X, dtype=np.float64)\n Q = np.empty(\n (self.n_components, X.shape[1]), dtype=np.float64, order='F')\n U = np.empty(\n (X.shape[0], self.n_components), dtype=np.float64, order='F')\n w = np.empty(self.n_co... | [
"0.74559265",
"0.7146048",
"0.7100563",
"0.7100563",
"0.7100563",
"0.7031072",
"0.6953819",
"0.68829376",
"0.6859341",
"0.6859341",
"0.6859318",
"0.6813972",
"0.67715836",
"0.6764781",
"0.67534685",
"0.6715386",
"0.66989195",
"0.6691517",
"0.6683969",
"0.6655785",
"0.6646973"... | 0.7536608 | 0 |
Return specific sample Sample is generated from transformed distribution and transformed back to the original space. | def get_sample(self, seed):
transformed = self.sampler_.get_sample(seed)
return self.pca_.inverse_transform(transformed) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _get_sample(self):\n mu = self._get_mean()\n sample = self.random.normal(mu)\n return sample",
"def _get_sample(self):\n mu = self._get_mean().reshape((1, self.out_dim))\n sigma = self.variables[\"s\"]\n sample = self.random.normal(mu, sigma)\n sample = sample... | [
"0.69831187",
"0.6970329",
"0.6696096",
"0.66158164",
"0.64837795",
"0.642031",
"0.6373376",
"0.63586676",
"0.6337623",
"0.62676066",
"0.62550586",
"0.62331295",
"0.62140554",
"0.6144703",
"0.614365",
"0.6135289",
"0.61312723",
"0.6130087",
"0.61157453",
"0.6106311",
"0.60812... | 0.6645877 | 3 |
Optimise the marginal likelihood. work with the log of beta fmin works better that way. | def optimise_GP_kernel(self,iters=1000):
new_params=SCG(self.ll_hyper,self.ll_hyper_grad,np.hstack((self.DGPLVM_tar.GP.kernel.get_params(), np.log(self.DGPLVM_tar.GP.beta))),maxiters=iters,display=True,func_flg=0)
#gtol=1e-10,epsilon=1e-10,
# new_params = fmin_cg(self.ll,np.hstack((self.kernel.get_params(), np.log(self.beta))),fprime=self.ll_grad,maxiter=iters,gtol=1e-10,disp=False)
self.DGPLVM_src.GP.set_params(new_params)
self.DGPLVM_tar.GP.set_params(new_params)
self.DGPLVM_all.GP.set_params(new_params) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def log_marginal_likelihood(X_train,y_train,phi,tau=1.,Ve=1.e-10):",
"def log_marginal_likelihood(self, eval_gradient=False):\n A, B, mu_tilda, gamma_tilda, r_grid, n_grid = self.calc_tau(return_all=True)\n\n gamma = self.GAMMA\n gamma_y = self.GAMMA_Y\n\n A1 = np.copy(self.baseTau0)\... | [
"0.66340697",
"0.6619952",
"0.6452456",
"0.6451917",
"0.6415813",
"0.64041406",
"0.6392549",
"0.63788503",
"0.6315891",
"0.6298545",
"0.62985104",
"0.6243928",
"0.61450654",
"0.6131926",
"0.6124716",
"0.6111718",
"0.6108412",
"0.60599285",
"0.60583085",
"0.60303396",
"0.60056... | 0.0 | -1 |
This function deletes duplicate values from a singly linked list | def remove_dups(ll: SinglyLinkedList):
seen = set()
current = ll.head
prev = None
while current is not None:
if current.data in seen:
prev.next = current.next
temp = current
current = current.next
temp.next = None
else:
seen.add(current.data)
prev = current
current = current.next | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def remove_dup2(linkedlist):",
"def remove_duplicates_slow(linked_list):\n current = linked_list.head\n while current:\n runner = current\n while runner:\n if runner.next_node and runner.next_node.value == current.value:\n # delete this duplicate\n run... | [
"0.84461933",
"0.8152717",
"0.8094504",
"0.8059363",
"0.78755367",
"0.7790879",
"0.7774575",
"0.7728998",
"0.76568514",
"0.7549787",
"0.74926317",
"0.7353447",
"0.7180826",
"0.7150074",
"0.71448135",
"0.71269375",
"0.7072273",
"0.70498395",
"0.695619",
"0.6727125",
"0.6698436... | 0.8174585 | 1 |
Returns the model properties as a dict | def to_dict(self):
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if hasattr(x, "to_dict") else x,
value
))
elif hasattr(value, "to_dict"):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(map(
lambda item: (item[0], item[1].to_dict())
if hasattr(item[1], "to_dict") else item,
value.items()
))
else:
if attr in self.sensitive_list:
result[attr] = "****"
else:
result[attr] = value
return result | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def to_dict(self):\n return self.properties",
"def to_dict(self):\n return self.properties",
"def get_properties(self):\n return self.properties",
"def asdict(self):\n return self._prop_dict",
"def json(self):\n rv = {\n prop: getattr(self, prop)\n f... | [
"0.7751993",
"0.7751993",
"0.73391134",
"0.7334895",
"0.7297356",
"0.727818",
"0.7159078",
"0.71578115",
"0.71494967",
"0.71494967",
"0.71283495",
"0.71275014",
"0.7122587",
"0.71079814",
"0.7060394",
"0.7043251",
"0.7034103",
"0.70233124",
"0.69635814",
"0.69586295",
"0.6900... | 0.0 | -1 |
Returns the string representation of the model | def to_str(self):
import simplejson as json
if six.PY2:
import sys
reload(sys)
sys.setdefaultencoding("utf-8")
return json.dumps(sanitize_for_serialization(self), ensure_ascii=False) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __str__(self):\n return super().__str__() + self.model.__str__()",
"def __str__(self) -> str:\n # noinspection PyUnresolvedReferences\n opts = self._meta\n if self.name_field:\n result = str(opts.get_field(self.name_field).value_from_object(self))\n else:\n ... | [
"0.85856134",
"0.7814518",
"0.77898884",
"0.7751367",
"0.7751367",
"0.7712228",
"0.76981676",
"0.76700574",
"0.7651133",
"0.7597206",
"0.75800353",
"0.7568254",
"0.7538184",
"0.75228703",
"0.7515832",
"0.7498764",
"0.74850684",
"0.74850684",
"0.7467648",
"0.74488163",
"0.7442... | 0.0 | -1 |
Returns true if both objects are equal | def __eq__(self, other):
if not isinstance(other, UpdateUserOption):
return False
return self.__dict__ == other.__dict__ | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __eq__(self, other):\n return are_equal(self, other)",
"def __eq__(self, other):\n return are_equal(self, other)",
"def __eq__(self,other):\n try: return self.object==other.object and isinstance(self,type(other))\n except: return False",
"def __eq__(self, other):\n if i... | [
"0.8089139",
"0.8089139",
"0.8054507",
"0.79827213",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
... | 0.0 | -1 |
Returns true if both objects are not equal | def __ne__(self, other):
return not self == other | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __ne__(self, other: object) -> bool:\n if self.__eq__(other):\n return False\n return True",
"def __ne__(self, other: object) -> bool:\n return not self.__eq__(other)",
"def __ne__(self, other) -> bool:\n return not self.__eq__(other)",
"def __eq__(self, other):\n ... | [
"0.845611",
"0.8391477",
"0.8144138",
"0.81410587",
"0.8132492",
"0.8093973",
"0.80920255",
"0.80920255",
"0.80920255",
"0.8085325",
"0.8085325",
"0.8076365",
"0.8076365",
"0.8065748"
] | 0.0 | -1 |
Create a board with distinct regions. Each region is continuous and separated from all other regions by at least two cells. The regions are generated using a Dirichlet process in which new cells are added to existed regions with a probability proportional to their boundary. | def make_partioned_regions(shape, alpha=1.0, max_regions=5, min_regions=2):
ring = np.array([[1,1,1],[1,0,1],[1,1,1]], dtype=np.int16)
adjacent = np.array([ # Diagonals don't count as adjacent
[-1,0,0,1],
[0,-1,1,0]], dtype=np.int16).T
nearby = np.meshgrid([-2,-1,0,1,2], [-2,-1,0,1,2])
board = np.zeros(shape, dtype=np.int16)
perimeters = [{
(i, j) for i, j in zip(*np.nonzero(board == 0))
}]
exclusions = [set()]
while sum(len(p) for p in perimeters) > 0:
weights = np.array([len(p) for p in perimeters], dtype=float)
weights[0] = min(alpha, weights[0]) if len(weights) <= max_regions else 1e-10
if len(weights) <= min_regions:
weights[1:] = 1e-10
weights /= np.sum(weights)
k = get_rng().choice(len(perimeters), p=weights)
plist = list(perimeters[k])
i, j = plist[get_rng().choice(len(plist))]
perimeters[0].discard((i, j))
perimeters[k].discard((i, j))
if (i, j) in exclusions[k]:
continue
exclusions[0].add((i,j))
exclusions[k].add((i,j))
b = board[(i+nearby[0]) % shape[0], (j+nearby[1]) % shape[1]]
b[2,2] = k or -1
num_neighbors = signal.convolve2d(b != 0, ring, mode='valid')
num_foreign = signal.convolve2d((b > 0) & (b != k), ring, mode='valid')
if ((num_foreign > 0) & (num_neighbors > 2)).any() or num_foreign[1,1] > 0:
continue
# Add to the board
if k == 0:
k = len(perimeters)
perimeters.append(set())
exclusions.append(set())
board[i, j] = k
for i2, j2 in (adjacent + (i, j)) % shape:
if board[i2, j2] == 0:
perimeters[k].add((i2, j2))
return board | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def generate_grains(self, cells):\n\t\tfor cell_num in range(cells):\n\t\t\trandom_row = random.randrange(0,self.space.shape[0],1)\n\t\t\tsample_cell = np.random.choice(self.space[random_row],1)\n\t\t\tsample_cell = sample_cell[0]\n\t\t\twhile sample_cell.state != 0:\n\t\t\t\trandom_row = random.randrange(0,self.s... | [
"0.61022526",
"0.607753",
"0.59886265",
"0.5929426",
"0.59226096",
"0.58879864",
"0.5817077",
"0.5783131",
"0.57591105",
"0.57534856",
"0.5751205",
"0.575003",
"0.57356465",
"0.57249886",
"0.57249135",
"0.5723089",
"0.56941694",
"0.56906545",
"0.5687791",
"0.56527513",
"0.564... | 0.71277833 | 0 |
Create a fence around unmasked regions such that nothing inside the regions can escape. Note that this is a little bit more aggressive than it strictly needs to be. | def build_fence(mask, shuffle=True):
mask = mask.astype(np.int32)
_i = np.array([-1,-1,-1,0,0,0,1,1,1], dtype=np.int32)
_j = np.array([-1,0,1,-1,0,1,-1,0,1], dtype=np.int32)
neighbors = ndimage.convolve(mask, np.ones((3,3)), mode='wrap')
fence = np.zeros_like(mask)
edge_i, edge_j = np.nonzero(mask * neighbors % 9)
neighbors *= (1 - mask)
if edge_i.size == 0:
return fence
# First pass. Add in fence where needed.
if shuffle:
k = get_rng().permutation(len(edge_i))
edge_i = edge_i[k]
edge_j = edge_j[k]
for i, j in zip(edge_i, edge_j):
n_i = (i + _i) % mask.shape[0]
n_j = (j + _j) % mask.shape[1]
if (neighbors[n_i, n_j] >= 3).any():
neighbors[n_i, n_j] -= 1
fence[i, j] += 1
# Second pass. Remove fence where unneeded.
fence_i, fence_j = np.nonzero(fence)
if shuffle:
k = get_rng().permutation(len(fence_i))
fence_i = fence_i[k]
fence_j = fence_j[k]
for i, j in zip(fence_i, fence_j):
n_i = (i + _i) % mask.shape[0]
n_j = (j + _j) % mask.shape[1]
if (neighbors[n_i, n_j] < 2).all():
neighbors[n_i, n_j] += 1
fence[i, j] -= 1
return fence | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def remove_spurious_landmarks(self):\r\n \r\n remove = np.argwhere(self.lm_counter < 0)\r\n self.lm = np.delete(self.lm, remove, axis=0)\r\n self.lm_cvar = np.delete(self.lm_cvar, remove, axis=0)\r\n self.lm_counter = np.delete(self.lm_counter, remove)\r\n \r\n retu... | [
"0.5550262",
"0.5375474",
"0.52712905",
"0.52280205",
"0.522766",
"0.5217894",
"0.5148621",
"0.51361966",
"0.513452",
"0.51226854",
"0.5100473",
"0.5098816",
"0.5098428",
"0.5061148",
"0.5000526",
"0.4992203",
"0.49582353",
"0.49527928",
"0.49484676",
"0.49470642",
"0.4946795... | 0.56984526 | 0 |
Populates an isolated region of the board. For examples of different region types, see ``safelife/levels/random/defaults.yaml``. | def populate_region(mask, layer_params):
from .speedups import (
NEW_CELL_MASK, CAN_OSCILLATE_MASK, INCLUDE_VIOLATIONS_MASK)
border = ndimage.maximum_filter(mask, size=3, mode='wrap') ^ mask
interior = ndimage.minimum_filter(mask, size=3, mode='wrap')
gen_mask = mask * (
NEW_CELL_MASK |
CAN_OSCILLATE_MASK |
INCLUDE_VIOLATIONS_MASK
) + border * (
INCLUDE_VIOLATIONS_MASK
)
board = np.zeros(mask.shape, dtype=np.uint16)
foreground = np.zeros(mask.shape, dtype=bool)
background = np.zeros(mask.shape, dtype=bool)
background_color = np.zeros(mask.shape, dtype=bool)
seeds = None
max_period = 1
for layer in layer_params:
if not isinstance(layer, dict):
raise ValueError(
"'layer_params' should be a list of parameter dictionaries.")
layer = _fix_random_values(layer)
old_board = board.copy()
gen_mask0 = gen_mask.copy()
interior = ndimage.minimum_filter(
gen_mask & NEW_CELL_MASK > 0, size=3, mode='wrap')
color = COLORS.get(layer.get('color'), 0)
fence_frac = layer.get('fences', 0.0)
if fence_frac > 0:
fences = build_fence(gen_mask & speedups.NEW_CELL_MASK)
fences *= coinflip(fence_frac, fences.shape)
gen_mask &= ~(fences * (NEW_CELL_MASK | CAN_OSCILLATE_MASK))
board += fences.astype(np.uint16) * CellTypes.wall
spawners = layer.get('spawners', 0)
if spawners > 0:
_mask = (gen_mask0 & NEW_CELL_MASK > 0) & interior
new_cells = _mask & coinflip(spawners, board.shape)
if not new_cells.any() and _mask.any():
i, j = np.nonzero(_mask)
k = get_rng().choice(len(i)) # ensure at least one spawner
new_cells[i[k], j[k]] = True
gen_mask[new_cells] ^= NEW_CELL_MASK
board[new_cells] = CellTypes.spawner + color
tree_lattice = layer.get('tree_lattice')
# Create a lattice of trees that are spread throughout the region
# such that every empty cell touches one (and only one) tree
# (modulo edge effects).
# Such a lattice tends to make the resulting board very chaotic.
# Note that this will disrupt any pre-existing patterns.
if tree_lattice is not None:
if not isinstance(tree_lattice, dict):
tree_lattice = {}
h, w = board.shape
stagger = tree_lattice.get('stagger', True)
spacing = float(tree_lattice.get('spacing', 5))
if not stagger:
new_cells = _make_lattice(h, w, spacing, spacing, 0)
elif spacing <= 3:
new_cells = _make_lattice(h, w, 3, 3, 1)
elif spacing == 4:
new_cells = _make_lattice(h, w, 10, 1, 3)
elif spacing == 5:
new_cells = _make_lattice(h, w, 13, 1, 5)
else:
# The following gets pretty sparse.
new_cells = _make_lattice(h, w, 6, 3, 3)
new_cells &= gen_mask & NEW_CELL_MASK > 0
board[new_cells] = CellTypes.tree + color
period = 1
if 'pattern' in layer:
pattern_args = layer['pattern'].copy()
period = pattern_args.get('period', 1)
if period == 1:
gen_mask2 = gen_mask & ~CAN_OSCILLATE_MASK
pattern_args.update(period=max_period, osc_bonus=0)
elif period == 0:
gen_mask2 = gen_mask & ~INCLUDE_VIOLATIONS_MASK
pattern_args.update(period=max_period, osc_bonus=0)
elif period < max_period:
raise ValueError(
"Periods for sequential layers in a region must be either 0, 1,"
" or at least as large as the largest period in prior layers.")
else:
gen_mask2 = gen_mask
max_period = period
board = _gen_pattern(board, gen_mask2, seeds, **pattern_args)
# We need to update the mask for subsequent layers so that they
# do not destroy the pattern in this layer.
# First get a list of board states throughout the oscillation cycle.
boards = [board]
for _ in range(1, max_period):
boards.append(speedups.advance_board(boards[-1]))
non_empty = np.array(boards) != 0
still_cells = non_empty.all(axis=0)
osc_cells = still_cells ^ non_empty.any(axis=0)
# Both still life cells and oscillating cells should disallow
# any later changes. We also want to disallow changes to the cells
# that are neighboring the oscillating cells, because any changes
# there would propogate to the oscillating cells at later time
# steps.
# Note that it doesn't really matter whether the oscillating mask
# is set for the currently oscillating cells, because we're not
# checking for violations in them anyways, and we don't allow any
# changes that would affect them.
osc_neighbors = ndimage.maximum_filter(osc_cells, size=3, mode='wrap')
gen_mask[osc_cells] &= ~(NEW_CELL_MASK | INCLUDE_VIOLATIONS_MASK)
gen_mask[still_cells | osc_neighbors] &= ~(NEW_CELL_MASK | CAN_OSCILLATE_MASK)
new_mask = board != old_board
life_mask = ((board & CellTypes.alive) > 0) & new_mask
board += color * new_mask * life_mask
# The seeds are starting points for the next layer of patterns.
# This just makes the patterns more likely to end up close together.
seeds = ((board & CellTypes.alive) > 0) & mask
new_mask = board != old_board
movable_walls = layer.get('movable_walls', 0)
if movable_walls > 0:
new_cells = coinflip(movable_walls, board.shape) * new_mask
new_cells *= (board & ~CellTypes.rainbow_color) == CellTypes.wall
board += new_cells * CellTypes.movable
movable_trees = layer.get('movable_trees', 0)
if movable_trees > 0:
new_cells = coinflip(movable_trees, board.shape) * new_mask
new_cells *= (board & ~CellTypes.rainbow_color) == CellTypes.tree
board += new_cells * CellTypes.movable
hardened_life = layer.get('hardened_life', 0)
if hardened_life > 0:
new_cells = coinflip(hardened_life, board.shape) * new_mask
new_cells *= (board & ~CellTypes.rainbow_color) == CellTypes.life
board -= new_cells * CellTypes.destructible
buffer_size = layer.get('buffer_zone', 0) * 2 + 1
life_cells = board & CellTypes.alive > 0
buf = ndimage.maximum_filter(life_cells, size=buffer_size, mode='wrap')
gen_mask[buf] &= ~NEW_CELL_MASK
target = layer.get('target', 'board')
if target == 'board':
foreground[new_mask] = True
if period > 0:
background[new_mask] = True
elif target == 'goals':
background[new_mask] = True
background_color[new_mask] = True
# Make sure to add walls and such to the foreground
foreground[new_mask & (board & CellTypes.alive == 0)] = True
elif target == 'both':
foreground[new_mask] = True
if period > 0:
background[new_mask] = True
background_color[new_mask] = True
else:
raise ValueError("Unexpected value for 'target': %s" % (target,))
fountains = layer.get('fountains', 0)
if fountains > 0:
new_cells = coinflip(fountains, board.shape)
new_cells *= gen_mask & NEW_CELL_MASK > 0
neighbors = ndimage.maximum_filter(new_cells, size=3, mode='wrap')
neighbors *= gen_mask & NEW_CELL_MASK > 0
gen_mask[neighbors] = INCLUDE_VIOLATIONS_MASK
if buffer_size > 1:
buf = ndimage.maximum_filter(neighbors, size=buffer_size, mode='wrap')
gen_mask[buf] &= ~NEW_CELL_MASK
board[neighbors] = CellTypes.wall + color
board[new_cells] = CellTypes.fountain + color
foreground[new_cells] = True
background[neighbors] = True
background_color[neighbors] = True
goals = board.copy()
board *= foreground
goals *= background
goals &= ~CellTypes.spawning
goals &= ~(CellTypes.rainbow_color * ~background_color)
return board, goals | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def initialize_region(self):\n self.new_region_name = \"\"\n self.map.regions.create_new_region()",
"def set_region(sender, instance, *args, **kwargs):\n if instance.geocity and not instance.georegion:\n instance.georegion = instance.geocity.region",
"def test_assign_to_regions(self):\n... | [
"0.6742911",
"0.5997335",
"0.5913795",
"0.573142",
"0.56936634",
"0.56373113",
"0.56364506",
"0.5610511",
"0.5602637",
"0.55689424",
"0.5567876",
"0.553663",
"0.5532952",
"0.55236477",
"0.5481019",
"0.5457451",
"0.5454251",
"0.544278",
"0.5432112",
"0.5432112",
"0.5432112",
... | 0.5901017 | 3 |
Add agents and exits to the board. This modifies both the board and regions in place. | def add_agents_and_exit(board, regions, agents, agent_types):
agent_vals = []
point_tables = []
agent_names = []
agent_types = {'default': DEFAULT_AGENT, **agent_types}
for agent_type in _fix_random_values(agents):
agent_type = _fix_random_values(agent_type)
if agent_type not in agent_types:
continue
agent = {**DEFAULT_AGENT, **agent_types[agent_type]}
agent_val = CellTypes.agent | CellTypes.frozen
if agent['color'] in COLORS:
agent_val |= COLORS[agent['color']]
else:
logger.error("Invalid agent color: '%s'", agent['color'])
for flag in agent['flags']:
if flag in AGENT_PROPERTIES:
agent_val |= AGENT_PROPERTIES[flag]
else:
logger.error("Invalid agent property '%s'", flag)
agent_vals.append(agent_val)
point_tables.append(agent['points_table'])
agent_names.append(agent_type)
if not agent_vals:
return np.zeros((0,2), dtype=int), np.zeros((0,8,9), dtype=int)
# Add agents to the board
zero_reg = (regions == 0)
zero_idx = np.array(np.nonzero(zero_reg)).T
# ensure that there are not more agents than places to put them:
agent_vals = agent_vals[:len(zero_idx)]
agent_locs = zero_idx[
get_rng().choice(len(zero_idx), len(agent_vals), replace=False)]
board[tuple(agent_locs.T)] = agent_vals
# Find the location that's as far away from agents as possible while still
# in the buffer region.
row_dist = np.abs(np.arange(board.shape[0])[:, np.newaxis] - agent_locs[:,0])
col_dist = np.abs(np.arange(board.shape[1])[:, np.newaxis] - agent_locs[:,1])
row_dist = np.sum(np.minimum(row_dist, board.shape[0] - row_dist), axis=-1)
col_dist = np.sum(np.minimum(col_dist, board.shape[1] - col_dist), axis=-1)
dist = (row_dist[:, np.newaxis] + col_dist[np.newaxis, :]) * zero_reg
k = np.argmax(dist)
exit_loc = k // board.shape[1], k % board.shape[1]
board[exit_loc] = CellTypes.level_exit | CellTypes.color_r
# Ensure that the player and exit aren't touching any other region
all_locs = np.append(agent_locs, [exit_loc], axis=0)
n = np.array([[-1,0,1,-1,0,1,-1,0,1],[-1,-1,-1,0,0,0,1,1,1]]).T
new_locs = (all_locs[:,np.newaxis] + n).reshape(-1, 2) % board.shape
regions[tuple(new_locs.T)] = -1
return agent_locs, point_tables, agent_names | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add_to_simulation(self,agent):\n self.agents[agent.name] = agent\n self.network.add_node(agent)\n \n #agent given a grid queue at initialization\n grid_queue = [gq for gq in self.grid_queues.values() if gq.accepts(agent)][agent.sex]\n agent.grid_queue = grid_queue.inde... | [
"0.5694394",
"0.5502142",
"0.5498129",
"0.5477356",
"0.5419938",
"0.53479344",
"0.5290117",
"0.52449757",
"0.52416706",
"0.51957417",
"0.5178578",
"0.5174868",
"0.51587874",
"0.5111144",
"0.5063345",
"0.5056426",
"0.50496",
"0.50238144",
"0.50177455",
"0.49965593",
"0.4988289... | 0.716102 | 0 |
Randomly generate a new SafeLife game board. Generation proceeds by creating several different random "regions", and then filling in each region with one of several types of patterns or tasks. Regions can be surrounded by fences / walls to make it harder for patterns to spread from one region to another. Each set of parameters can additionally be randomized by passing in a dictionary either with the 'choices' key or the 'uniform' key. | def gen_game(
board_shape=(25,25), min_performance=-1, partitioning={},
starting_region=None, later_regions=None, buffer_region=None,
named_regions={}, agents=['default'], agent_types={}, **etc):
board_shape = _fix_random_values(board_shape)
min_performance = _fix_random_values(min_performance)
partitioning = _fix_random_values(partitioning)
regions = make_partioned_regions(board_shape, **partitioning)
board = np.zeros(board_shape, dtype=np.uint16)
goals = np.zeros(board_shape, dtype=np.uint16)
# Create locations for the player and the exit
agent_locs, points_table, agent_names = add_agents_and_exit(
board, regions, agents, agent_types)
# and fill in the regions...
for k in np.unique(regions)[2:]:
mask = regions == k
if starting_region is not None:
region_name = _fix_random_values(starting_region)
else:
region_name = _fix_random_values(later_regions)
if region_name not in named_regions:
logger.error("No region parameters for name '%s'", region_name)
continue
logger.debug("Making region: %s", region_name)
rboard, rgoals = populate_region(mask, named_regions[region_name])
board += rboard
goals += rgoals
starting_region = None
buffer_region = _fix_random_values(buffer_region)
if buffer_region in named_regions:
mask = regions == 0
rboard, rgoals = populate_region(mask, named_regions[buffer_region])
board += rboard
goals += rgoals
# Give the buffer (0) region a rainbow / white color
# This is mostly a visual hint for humans
buffer_mask = (regions <= 0) & (goals & CellTypes.rainbow_color == 0)
goals[buffer_mask] += CellTypes.rainbow_color
game = SafeLifeGame()
game.deserialize({
'board': board,
'goals': goals,
'agent_locs': agent_locs,
'agent_names': agent_names,
'min_performance': min_performance,
'points_table': points_table,
'orientation': 1,
})
return game | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def generate(self):\n for i in range(4):\n random_first = randomize_first_box()\n self.randomize(random_first)\n for i in range(9):\n random_pos = randomize_position()\n self.randomize(random_pos)\n self.board.solve()",
"def draw_random_setup(types... | [
"0.68248934",
"0.64361274",
"0.6384287",
"0.6220165",
"0.614266",
"0.613112",
"0.6068092",
"0.6057356",
"0.6054699",
"0.6002918",
"0.5973913",
"0.5956003",
"0.59538376",
"0.59481156",
"0.59429073",
"0.59363997",
"0.59216344",
"0.59191567",
"0.59100956",
"0.58849156",
"0.58718... | 0.64837104 | 1 |
Highlights separable regions that stable with the given period. A "separable" region is one which can be removed from the board without effecting any of the rest of the board. | def stability_mask(board, period=6, remove_agent=True):
if remove_agent:
board = board * ((board & CellTypes.agent) == 0)
neighborhood = np.ones((3,3))
alive = (board & CellTypes.alive) // CellTypes.alive
neighbors = ndimage.convolve(alive, neighborhood, mode='wrap')
max_neighbors = neighbors
ever_alive = alive
orig_board = board
for _ in range(period):
board = speedups.advance_board(board)
alive = (board & CellTypes.alive) // CellTypes.alive
neighbors = ndimage.convolve(alive, neighborhood, mode='wrap')
ever_alive |= alive
max_neighbors = np.maximum(max_neighbors, neighbors)
is_boundary = (board & CellTypes.frozen > 0)
is_boundary |= (ever_alive == 0) & (max_neighbors <= 2)
labels, num_labels = speedups.wrapped_label(~is_boundary)
mask = np.zeros(board.shape, dtype=bool)
for idx in range(1, num_labels+1):
region = labels == idx
if (board[region] == orig_board[region]).all():
mask |= region
return mask | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def make_partioned_regions(shape, alpha=1.0, max_regions=5, min_regions=2):\n ring = np.array([[1,1,1],[1,0,1],[1,1,1]], dtype=np.int16)\n adjacent = np.array([ # Diagonals don't count as adjacent\n [-1,0,0,1],\n [0,-1,1,0]], dtype=np.int16).T\n nearby = np.meshgrid([-2,-1,0,1,2], [-2,-1,0,... | [
"0.54850954",
"0.508608",
"0.50796324",
"0.506026",
"0.50399494",
"0.50315195",
"0.502835",
"0.49149758",
"0.49066833",
"0.49031895",
"0.48982894",
"0.48454717",
"0.48394826",
"0.48072115",
"0.47997016",
"0.47875527",
"0.47487685",
"0.4743557",
"0.47257307",
"0.4671103",
"0.4... | 0.47201967 | 19 |
override this to do logic on input_update messages | def do_on_input_update(self, msg_id, payload, player):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def data_input_changed(self):\n self.message.data = self.dataInput.toPlainText()\n self.validate_data_input(self.message.dlc)",
"def update(self, msg):\n pass",
"def process_IN_MODIFY(self, event):",
"def handle_input(self, event):\n pass",
"def oppdater(self, input):\n r... | [
"0.7064037",
"0.68353105",
"0.679278",
"0.6780095",
"0.6757028",
"0.66975",
"0.6632578",
"0.6601894",
"0.65531427",
"0.6519125",
"0.64932",
"0.6461436",
"0.645683",
"0.64120686",
"0.6398695",
"0.63841844",
"0.6377531",
"0.63212633",
"0.6266965",
"0.6207796",
"0.6190815",
"0... | 0.79876757 | 0 |
Given the state of the 'game', decide what your cells ('game.me.cells') should do. | def step(self, game: Game):
print("Tick #{}".format(game.time_left))
splitValue = getSplitValue(game)
print (getSplitValue(game))
for cell in game.me.cells:
if game.time_left < 6:
cell.trade(99999)
if cell.mass >= splitValue:
if len(game.me.cells) < 10:
cell.split()
#else:
#cell.trade(cell.mass - 100)
else:
distance = cell.position.distance_to(cell.target)
possibleVictims = findVictims(cell, game.enemies)
if (cell.mass <= 100):
target = closestRessource(game, cell, possibleVictims + game.resources.allResources, len(possibleVictims))
else:
#cell.burst()
target = closestRessource(game, cell, possibleVictims, len(possibleVictims))
for e in game.enemies:
for c in e.cells:
if enemyComingthrough(cell, c):
target = cell.position + (c.target - c.position)
#cell.burst()
pass
if (target != None):
cell.move(target)
else:
print (' KES TU FAIS, VA PAS LÀ ') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _check_cells(self):\n for row_number in range(self.number_cells_y):\n for col_number in range(self.number_cells_x):\n alive_neighbours = self._get_neighbours(row_number,col_number)\n \n self.to_be_updated[row_number][col_number] = False\n ... | [
"0.69623125",
"0.6414086",
"0.6400114",
"0.63498706",
"0.6227592",
"0.6179046",
"0.6162203",
"0.61035144",
"0.6049122",
"0.604795",
"0.6018108",
"0.60137135",
"0.60055864",
"0.6002554",
"0.598495",
"0.59398884",
"0.5925738",
"0.5910711",
"0.59071994",
"0.5905565",
"0.5895984"... | 0.5600861 | 62 |
Collect data into fixedlength chunks or blocks | def grouper(iterable, n, fillvalue=None):
# grouper('ABCDEFG', 3, 'x') --> ABC DEF Gxx
args = [iter(iterable)] * n
return izip_longest(fillvalue=fillvalue, *args) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _chunk_data(self):\n for n in range(0, len(self.data) + 1, len(self.data) //\n self.num_of_chunks):\n yield self.data[0 + n:len(self.data) // self.num_of_chunks + n]",
"def chunks(data: list, n: int) -> list:\n for i in range(0, len(data), n):\n yield data[i:... | [
"0.719677",
"0.6773225",
"0.6730021",
"0.6680324",
"0.6640408",
"0.6590066",
"0.65835804",
"0.6442601",
"0.6409235",
"0.6338401",
"0.6329446",
"0.63054276",
"0.62845904",
"0.62551296",
"0.6208536",
"0.61931676",
"0.61904657",
"0.61624444",
"0.6139798",
"0.61395085",
"0.613243... | 0.0 | -1 |
Temporal workaround for static template tag to support SCRIPT_NAME | def static(parser, token):
return NewStaticNode.handle_token(parser, token) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_script_name(t_req):\n if settings.FORCE_SCRIPT_NAME is not None:\n return force_text(settings.FORCE_SCRIPT_NAME)\n\n # If Apache's mod_rewrite had a whack at the URL, Apache set either\n # SCRIPT_URL or REDIRECT_URL to the full resource URL before applying any\n # rewrites. Unfortunately... | [
"0.6034971",
"0.5963628",
"0.59341127",
"0.58655584",
"0.5860948",
"0.58456707",
"0.58188504",
"0.5782478",
"0.5782478",
"0.57443565",
"0.5699513",
"0.5699513",
"0.56902325",
"0.56528944",
"0.5573736",
"0.5472369",
"0.5468209",
"0.5464693",
"0.5461462",
"0.54162765",
"0.53910... | 0.0 | -1 |
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