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def x10_command(self, house_code, unit_number, state): house_code = normalize_housecode(house_code) if unit_number is not None: unit_number = normalize_unitnumber(unit_number) return self._x10_command(house_code, unit_number, state)
Send X10 command to ??? unit. @param house_code (A-P) - example='A' @param unit_number (1-16)- example=1 (or None to impact entire house code) @param state - Mochad command/state, See https://sourceforge.net/p/mochad/code/ci/master/tree/README examples=OFF, 'OFF', 'ON', ALL_OFF, 'all_units_off', 'xdim 128', etc. Examples: x10_command('A', '1', ON) x10_command('A', '1', OFF) x10_command('A', '1', 'ON') x10_command('A', '1', 'OFF') x10_command('A', None, ON) x10_command('A', None, OFF) x10_command('A', None, 'all_lights_off') x10_command('A', None, 'all_units_off') x10_command('A', None, ALL_OFF) x10_command('A', None, 'all_lights_on') x10_command('A', 1, 'xdim 128')
def buildOverlappedSequences( numSequences = 2, seqLen = 5, sharedElements = [3,4], numOnBitsPerPattern = 3, patternOverlap = 0, seqOverlap = 0, **kwargs ): numSharedElements = len(sharedElements) numUniqueElements = seqLen - numSharedElements numPatterns = numSharedElements + numUniqueElements * numSequences patterns = getSimplePatterns(numOnBitsPerPattern, numPatterns, patternOverlap) numCols = len(patterns[0]) trainingSequences = [] uniquePatternIndices = range(numSharedElements, numPatterns) for _ in xrange(numSequences): sequence = [] sharedPatternIndices = range(numSharedElements) for j in xrange(seqLen): if j in sharedElements: patIdx = sharedPatternIndices.pop(0) else: patIdx = uniquePatternIndices.pop(0) sequence.append(patterns[patIdx]) trainingSequences.append(sequence) if VERBOSITY >= 3: print "\nTraining sequences" printAllTrainingSequences(trainingSequences) return (numCols, trainingSequences)
Create training sequences that share some elements in the middle. Parameters: ----------------------------------------------------- numSequences: Number of unique training sequences to generate seqLen: Overall length of each sequence sharedElements: Which element indices of each sequence are shared. These will be in the range between 0 and seqLen-1 numOnBitsPerPattern: Number of ON bits in each TM input pattern patternOverlap: Max number of bits of overlap between any 2 patterns retval: (numCols, trainingSequences) numCols - width of the patterns trainingSequences - a list of training sequences
def delayed_call(self, delay, function): main_loop = self handler = [] class DelayedCallHandler(TimeoutHandler): @timeout_handler(delay, False) def callback(self): try: function() finally: main_loop.remove_handler(handler[0]) handler.append(DelayedCallHandler()) self.add_handler(handler[0])
Schedule function to be called from the main loop after `delay` seconds. :Parameters: - `delay`: seconds to wait :Types: - `delay`: `float`
def flat_map(self, flatmap_function): from heronpy.streamlet.impl.flatmapbolt import FlatMapStreamlet fm_streamlet = FlatMapStreamlet(flatmap_function, self) self._add_child(fm_streamlet) return fm_streamlet
Return a new Streamlet by applying map_function to each element of this Streamlet and flattening the result
def get_raw_output(self, tile, _baselevel_readonly=False): if not isinstance(tile, (BufferedTile, tuple)): raise TypeError("'tile' must be a tuple or BufferedTile") if isinstance(tile, tuple): tile = self.config.output_pyramid.tile(*tile) if _baselevel_readonly: tile = self.config.baselevels["tile_pyramid"].tile(*tile.id) if tile.zoom not in self.config.zoom_levels: return self.config.output.empty(tile) if tile.crs != self.config.process_pyramid.crs: raise NotImplementedError( "reprojection between processes not yet implemented" ) if self.config.mode == "memory": process_tile = self.config.process_pyramid.intersecting(tile)[0] return self._extract( in_tile=process_tile, in_data=self._execute_using_cache(process_tile), out_tile=tile ) process_tile = self.config.process_pyramid.intersecting(tile)[0] if tile.pixelbuffer > self.config.output.pixelbuffer: output_tiles = list(self.config.output_pyramid.tiles_from_bounds( tile.bounds, tile.zoom )) else: output_tiles = self.config.output_pyramid.intersecting(tile) if self.config.mode == "readonly" or _baselevel_readonly: if self.config.output.tiles_exist(process_tile): return self._read_existing_output(tile, output_tiles) else: return self.config.output.empty(tile) elif self.config.mode == "continue" and not _baselevel_readonly: if self.config.output.tiles_exist(process_tile): return self._read_existing_output(tile, output_tiles) else: return self._process_and_overwrite_output(tile, process_tile) elif self.config.mode == "overwrite" and not _baselevel_readonly: return self._process_and_overwrite_output(tile, process_tile)
Get output raw data. This function won't work with multiprocessing, as it uses the ``threading.Lock()`` class. Parameters ---------- tile : tuple, Tile or BufferedTile If a tile index is given, a tile from the output pyramid will be assumed. Tile cannot be bigger than process tile! Returns ------- data : NumPy array or features process output
def getOutputElementCount(self, name): if name == "resetOut": print ("WARNING: getOutputElementCount should not have been called with " "resetOut") return 1 elif name == "sequenceIdOut": print ("WARNING: getOutputElementCount should not have been called with " "sequenceIdOut") return 1 elif name == "dataOut": if self.encoder is None: raise Exception("NuPIC requested output element count for 'dataOut' " "on a RecordSensor node, but the encoder has not " "been set") return self.encoder.getWidth() elif name == "sourceOut": if self.encoder is None: raise Exception("NuPIC requested output element count for 'sourceOut' " "on a RecordSensor node, " "but the encoder has not been set") return len(self.encoder.getDescription()) elif name == "bucketIdxOut": return 1 elif name == "actValueOut": return 1 elif name == "categoryOut": return self.numCategories elif name == 'spatialTopDownOut' or name == 'temporalTopDownOut': if self.encoder is None: raise Exception("NuPIC requested output element count for 'sourceOut' " "on a RecordSensor node, " "but the encoder has not been set") return len(self.encoder.getDescription()) else: raise Exception("Unknown output %s" % name)
Computes the width of dataOut. Overrides :meth:`nupic.bindings.regions.PyRegion.PyRegion.getOutputElementCount`.
def _setup_custom_grouping(self, topology): for i in range(len(topology.bolts)): for in_stream in topology.bolts[i].inputs: if in_stream.stream.component_name == self.my_component_name and \ in_stream.gtype == topology_pb2.Grouping.Value("CUSTOM"): if in_stream.type == topology_pb2.CustomGroupingObjectType.Value("PYTHON_OBJECT"): custom_grouping_obj = default_serializer.deserialize(in_stream.custom_grouping_object) if isinstance(custom_grouping_obj, str): pex_loader.load_pex(self.topology_pex_abs_path) grouping_cls = \ pex_loader.import_and_get_class(self.topology_pex_abs_path, custom_grouping_obj) custom_grouping_obj = grouping_cls() assert isinstance(custom_grouping_obj, ICustomGrouping) self.custom_grouper.add(in_stream.stream.id, self._get_taskids_for_component(topology.bolts[i].comp.name), custom_grouping_obj, self.my_component_name) elif in_stream.type == topology_pb2.CustomGroupingObjectType.Value("JAVA_OBJECT"): raise NotImplementedError("Java-serialized custom grouping is not yet supported " "for python topology") else: raise ValueError("Unrecognized custom grouping type found: %s" % str(in_stream.type))
Checks whether there are any bolts that consume any of my streams using custom grouping
def _store_helper(model: Action, session: Optional[Session] = None) -> None: if session is None: session = _make_session() session.add(model) session.commit() session.close()
Help store an action.
def remove_handler(self, handler): with self.lock: if handler in self.handlers: self.handlers.remove(handler) self._update_handlers()
Remove a handler object. :Parameters: - `handler`: the object to remove
def in_op(self, other): if not is_object(other): raise MakeError( 'TypeError', "You can\'t use 'in' operator to search in non-objects") return other.has_property(to_string(self))
checks if self is in other
def register(self, what, obj): name = obj.name version = obj.version enable = obj.enable if enable == 'n': return key = Key(name, version) self.plugins[what][key] = obj
Registering a plugin Params ------ what: Nature of the plugin (backend, instrumentation, repo) obj: Instance of the plugin
def _build_google_client(service, api_version, http_auth): client = build(service, api_version, http=http_auth) return client
Google build client helper. :param service: service to build client for :type service: ``str`` :param api_version: API version to use. :type api_version: ``str`` :param http_auth: Initialized HTTP client to use. :type http_auth: ``object`` :return: google-python-api client initialized to use 'service' :rtype: ``object``
def limit(self, max=30): if abs(self.vx) > max: self.vx = self.vx/abs(self.vx)*max if abs(self.vy) > max: self.vy = self.vy/abs(self.vy)*max if abs(self.vz) > max: self.vz = self.vz/abs(self.vz)*max
The speed limit for a boid. Boids can momentarily go very fast, something that is impossible for real animals.
def save_file(self, obj): try: import StringIO as pystringIO except ImportError: import io as pystringIO if not hasattr(obj, 'name') or not hasattr(obj, 'mode'): raise pickle.PicklingError("Cannot pickle files that do not map to an actual file") if obj is sys.stdout: return self.save_reduce(getattr, (sys, 'stdout'), obj=obj) if obj is sys.stderr: return self.save_reduce(getattr, (sys, 'stderr'), obj=obj) if obj is sys.stdin: raise pickle.PicklingError("Cannot pickle standard input") if hasattr(obj, 'isatty') and obj.isatty(): raise pickle.PicklingError("Cannot pickle files that map to tty objects") if 'r' not in obj.mode: raise pickle.PicklingError("Cannot pickle files that are not opened for reading") name = obj.name try: fsize = os.stat(name).st_size except OSError: raise pickle.PicklingError("Cannot pickle file %s as it cannot be stat" % name) if obj.closed: retval = pystringIO.StringIO("") retval.close() elif not fsize: retval = pystringIO.StringIO("") try: tmpfile = file(name) tst = tmpfile.read(1) except IOError: raise pickle.PicklingError("Cannot pickle file %s as it cannot be read" % name) tmpfile.close() if tst != '': raise pickle.PicklingError( "Cannot pickle file %s as it does not appear to map to a physical, real file" % name) else: try: tmpfile = file(name) contents = tmpfile.read() tmpfile.close() except IOError: raise pickle.PicklingError("Cannot pickle file %s as it cannot be read" % name) retval = pystringIO.StringIO(contents) curloc = obj.tell() retval.seek(curloc) retval.name = name self.save(retval) self.memoize(obj)
Save a file
def load_all_methods(self): r methods = [] Tmins, Tmaxs = [], [] if self.CASRN in ['7732-18-5', '67-56-1', '64-17-5']: methods.append(TEST_METHOD_1) self.TEST_METHOD_1_Tmin = 200. self.TEST_METHOD_1_Tmax = 350 self.TEST_METHOD_1_coeffs = [1, .002] Tmins.append(self.TEST_METHOD_1_Tmin); Tmaxs.append(self.TEST_METHOD_1_Tmax) if self.CASRN in ['67-56-1']: methods.append(TEST_METHOD_2) self.TEST_METHOD_2_Tmin = 300. self.TEST_METHOD_2_Tmax = 400 self.TEST_METHOD_2_coeffs = [1, .003] Tmins.append(self.TEST_METHOD_2_Tmin); Tmaxs.append(self.TEST_METHOD_2_Tmax) self.all_methods = set(methods) if Tmins and Tmaxs: self.Tmin = min(Tmins) self.Tmax = max(Tmaxs)
r'''Method to load all data, and set all_methods based on the available data and properties. Demo function for testing only; must be implemented according to the methods available for each individual method.
def __intermediate_dns_servers(self, uci, address): if 'dns' in uci: return uci['dns'] if address['proto'] in ['dhcp', 'dhcpv6', 'none']: return None dns = self.netjson.get('dns_servers', None) if dns: return ' '.join(dns)
determines UCI interface "dns" option
def serialize_text(out, text): padding = len(out) add_padding = padding_adder(padding) text = add_padding(text, ignore_first_line=True) return out + text
This method is used to append content of the `text` argument to the `out` argument. Depending on how many lines in the text, a padding can be added to all lines except the first one. Concatenation result is appended to the `out` argument.
def mpsse_read_gpio(self): self._write('\x81\x83') data = self._poll_read(2) low_byte = ord(data[0]) high_byte = ord(data[1]) logger.debug('Read MPSSE GPIO low byte = {0:02X} and high byte = {1:02X}'.format(low_byte, high_byte)) return (high_byte << 8) | low_byte
Read both GPIO bus states and return a 16 bit value with their state. D0-D7 are the lower 8 bits and C0-C7 are the upper 8 bits.
def ip2long(ip): try: return int(binascii.hexlify(socket.inet_aton(ip)), 16) except socket.error: return int(binascii.hexlify(socket.inet_pton(socket.AF_INET6, ip)), 16)
Wrapper function for IPv4 and IPv6 converters. :arg ip: IPv4 or IPv6 address
def delete_key(key_name, stash, passphrase, backend): stash = _get_stash(backend, stash, passphrase) for key in key_name: try: click.echo('Deleting key {0}...'.format(key)) stash.delete(key_name=key) except GhostError as ex: sys.exit(ex) click.echo('Keys deleted successfully')
Delete a key from the stash `KEY_NAME` is the name of the key to delete You can provide that multiple times to delete multiple keys at once
def hsv2rgb_spectrum(hsv): h, s, v = hsv return hsv2rgb_raw(((h * 192) >> 8, s, v))
Generates RGB values from HSV values in line with a typical light spectrum.
def create_tree(endpoints): tree = {} for method, url, doc in endpoints: path = [p for p in url.strip('/').split('/')] here = tree version = path[0] here.setdefault(version, {}) here = here[version] for p in path[1:]: part = _camelcase_to_underscore(p) here.setdefault(part, {}) here = here[part] if not 'METHODS' in here: here['METHODS'] = [[method, doc]] else: if not method in here['METHODS']: here['METHODS'].append([method, doc]) return tree
Creates the Trello endpoint tree. >>> r = {'1': { \ 'actions': {'METHODS': {'GET'}}, \ 'boards': { \ 'members': {'METHODS': {'DELETE'}}}} \ } >>> r == create_tree([ \ 'GET /1/actions/[idAction]', \ 'DELETE /1/boards/[board_id]/members/[idMember]']) True
def schedule_play(self, call_params): path = '/' + self.api_version + '/SchedulePlay/' method = 'POST' return self.request(path, method, call_params)
REST Schedule playing something on a call Helper
def warn_if_not_float(X, estimator='This algorithm'): if not isinstance(estimator, str): estimator = estimator.__class__.__name__ if X.dtype.kind != 'f': warnings.warn("%s assumes floating point values as input, " "got %s" % (estimator, X.dtype)) return True return False
Warning utility function to check that data type is floating point. Returns True if a warning was raised (i.e. the input is not float) and False otherwise, for easier input validation.
def get_zones(input_list): if not input_list: return [] output_list = [] for zone in input_list: if zone.endswith('*'): prefix = zone[:-1] output_list.extend([z for z in _ZONES if z.startswith(prefix)]) else: output_list.append(zone) return output_list
Returns a list of zones based on any wildcard input. This function is intended to provide an easy method for producing a list of desired zones for a pipeline to run in. The Pipelines API default zone list is "any zone". The problem with "any zone" is that it can lead to incurring Cloud Storage egress charges if the GCE zone selected is in a different region than the GCS bucket. See https://cloud.google.com/storage/pricing#network-egress. A user with a multi-region US bucket would want to pipelines to run in a "us-*" zone. A user with a regional bucket in US would want to restrict pipelines to run in a zone in that region. Rarely does the specific zone matter for a pipeline. This function allows for a simple short-hand such as: [ "us-*" ] [ "us-central1-*" ] These examples will expand out to the full list of US and us-central1 zones respectively. Args: input_list: list of zone names/patterns Returns: A list of zones, with any wildcard zone specifications expanded.
def total_memory(): with file('/proc/meminfo', 'r') as f: for line in f: words = line.split() if words[0].upper() == 'MEMTOTAL:': return int(words[1]) * 1024 raise IOError('MemTotal unknown')
Returns the the amount of memory available for use. The memory is obtained from MemTotal entry in /proc/meminfo. Notes ===== This function is not very useful and not very portable.
def play(self): if not self.is_playing(): self.play_pause() self._is_playing = True self.playEvent(self)
Play the video asynchronously returning control immediately to the calling code
def from_json(cls, fh): if isinstance(fh, str): return cls(json.loads(fh)) else: return cls(json.load(fh))
Load json from file handle. Args: fh (file): File handle to load from. Examlple: >>> with open('data.json', 'r') as json: >>> data = composite.load(json)
def html(tag): return (HTML_START.format(tag=tag), HTML_END.format(tag=tag))
Return sequence of start and end regex patterns for simple HTML tag
def get_queue_data(self, queues=None, edge=None, edge_type=None, return_header=False): queues = _get_queues(self.g, queues, edge, edge_type) data = np.zeros((0, 6)) for q in queues: dat = self.edge2queue[q].fetch_data() if len(dat) > 0: data = np.vstack((data, dat)) if return_header: return data, 'arrival,service,departure,num_queued,num_total,q_id' return data
Gets data from all the queues. If none of the parameters are given then data from every :class:`.QueueServer` is retrieved. Parameters ---------- queues : int or an *array_like* of int, (optional) The edge index (or an iterable of edge indices) identifying the :class:`QueueServer(s)<.QueueServer>` whose data will be retrieved. edge : 2-tuple of int or *array_like* (optional) Explicitly specify which queues to retrieve data from. Must be either: * A 2-tuple of the edge's source and target vertex indices, or * An iterable of 2-tuples of the edge's source and target vertex indices. edge_type : int or an iterable of int (optional) A integer, or a collection of integers identifying which edge types to retrieve data from. return_header : bool (optonal, default: False) Determines whether the column headers are returned. Returns ------- out : :class:`~numpy.ndarray` * 1st: The arrival time of an agent. * 2nd: The service start time of an agent. * 3rd: The departure time of an agent. * 4th: The length of the queue upon the agents arrival. * 5th: The total number of :class:`Agents<.Agent>` in the :class:`.QueueServer`. * 6th: The :class:`QueueServer's<.QueueServer>` edge index. out : str (optional) A comma seperated string of the column headers. Returns ``'arrival,service,departure,num_queued,num_total,q_id'``` Examples -------- Data is not collected by default. Before simulating, by sure to turn it on (as well as initialize the network). The following returns data from queues with ``edge_type`` 1 or 3: >>> import queueing_tool as qt >>> g = qt.generate_pagerank_graph(100, seed=13) >>> net = qt.QueueNetwork(g, seed=13) >>> net.start_collecting_data() >>> net.initialize(10) >>> net.simulate(2000) >>> data = net.get_queue_data(edge_type=(1, 3)) To get data from an edge connecting two vertices do the following: >>> data = net.get_queue_data(edge=(1, 50)) To get data from several edges do the following: >>> data = net.get_queue_data(edge=[(1, 50), (10, 91), (99, 99)]) You can specify the edge indices as well: >>> data = net.get_queue_data(queues=(20, 14, 0, 4))
def IIR_sos_header(fname_out, SOS_mat): Ns, Mcol = SOS_mat.shape f = open(fname_out, 'wt') f.write('//define a IIR SOS CMSIS-DSP coefficient array\n\n') f.write(' f.write(' f.write(' f.write(' f.write('/*********************************************************/\n'); f.write('/* IIR SOS Filter Coefficients */\n'); f.write('float32_t ba_coeff[%d] = { //b0,b1,b2,a1,a2,... by stage\n' % (5 * Ns)) for k in range(Ns): if (k < Ns - 1): f.write(' %+-13e, %+-13e, %+-13e,\n' % \ (SOS_mat[k, 0], SOS_mat[k, 1], SOS_mat[k, 2])) f.write(' %+-13e, %+-13e,\n' % \ (-SOS_mat[k, 4], -SOS_mat[k, 5])) else: f.write(' %+-13e, %+-13e, %+-13e,\n' % \ (SOS_mat[k, 0], SOS_mat[k, 1], SOS_mat[k, 2])) f.write(' %+-13e, %+-13e\n' % \ (-SOS_mat[k, 4], -SOS_mat[k, 5])) f.write('};\n') f.write('/*********************************************************/\n') f.close()
Write IIR SOS Header Files File format is compatible with CMSIS-DSP IIR Directform II Filter Functions Mark Wickert March 2015-October 2016
def requirements_for_changes(self, changes): requirements = [] reqs_set = set() if isinstance(changes, str): changes = changes.split('\n') if not changes or changes[0].startswith('-'): return requirements for line in changes: line = line.strip(' -+*') if not line: continue match = IS_REQUIREMENTS_RE2.search(line) if match: for match in REQUIREMENTS_RE.findall(match.group(1)): if match[1]: version = '==' + match[2] if match[1].startswith(' to ') else match[1] req_str = match[0] + version else: req_str = match[0] if req_str not in reqs_set: reqs_set.add(req_str) try: requirements.append(pkg_resources.Requirement.parse(req_str)) except Exception as e: log.warn('Could not parse requirement "%s" from changes: %s', req_str, e) return requirements
Parse changes for requirements :param list changes:
def credentials_from_code(client_id, client_secret, scope, code, redirect_uri='postmessage', http=None, user_agent=None, token_uri=oauth2client.GOOGLE_TOKEN_URI, auth_uri=oauth2client.GOOGLE_AUTH_URI, revoke_uri=oauth2client.GOOGLE_REVOKE_URI, device_uri=oauth2client.GOOGLE_DEVICE_URI, token_info_uri=oauth2client.GOOGLE_TOKEN_INFO_URI, pkce=False, code_verifier=None): flow = OAuth2WebServerFlow(client_id, client_secret, scope, redirect_uri=redirect_uri, user_agent=user_agent, auth_uri=auth_uri, token_uri=token_uri, revoke_uri=revoke_uri, device_uri=device_uri, token_info_uri=token_info_uri, pkce=pkce, code_verifier=code_verifier) credentials = flow.step2_exchange(code, http=http) return credentials
Exchanges an authorization code for an OAuth2Credentials object. Args: client_id: string, client identifier. client_secret: string, client secret. scope: string or iterable of strings, scope(s) to request. code: string, An authorization code, most likely passed down from the client redirect_uri: string, this is generally set to 'postmessage' to match the redirect_uri that the client specified http: httplib2.Http, optional http instance to use to do the fetch token_uri: string, URI for token endpoint. For convenience defaults to Google's endpoints but any OAuth 2.0 provider can be used. auth_uri: string, URI for authorization endpoint. For convenience defaults to Google's endpoints but any OAuth 2.0 provider can be used. revoke_uri: string, URI for revoke endpoint. For convenience defaults to Google's endpoints but any OAuth 2.0 provider can be used. device_uri: string, URI for device authorization endpoint. For convenience defaults to Google's endpoints but any OAuth 2.0 provider can be used. pkce: boolean, default: False, Generate and include a "Proof Key for Code Exchange" (PKCE) with your authorization and token requests. This adds security for installed applications that cannot protect a client_secret. See RFC 7636 for details. code_verifier: bytestring or None, default: None, parameter passed as part of the code exchange when pkce=True. If None, a code_verifier will automatically be generated as part of step1_get_authorize_url(). See RFC 7636 for details. Returns: An OAuth2Credentials object. Raises: FlowExchangeError if the authorization code cannot be exchanged for an access token
def parse_file_provider(uri): providers = {'gs': job_model.P_GCS, 'file': job_model.P_LOCAL} provider_found = re.match(r'^([A-Za-z][A-Za-z0-9+.-]{0,29})://', uri) if provider_found: prefix = provider_found.group(1).lower() else: prefix = 'file' if prefix in providers: return providers[prefix] else: raise ValueError('File prefix not supported: %s://' % prefix)
Find the file provider for a URI.
def _make_user_class(session, name): attrs = session.eval('fieldnames(%s);' % name, nout=1).ravel().tolist() methods = session.eval('methods(%s);' % name, nout=1).ravel().tolist() ref = weakref.ref(session) doc = _DocDescriptor(ref, name) values = dict(__doc__=doc, _name=name, _ref=ref, _attrs=attrs, __module__='oct2py.dynamic') for method in methods: doc = _MethodDocDescriptor(ref, name, method) cls_name = '%s_%s' % (name, method) method_values = dict(__doc__=doc) method_cls = type(str(cls_name), (OctaveUserClassMethod,), method_values) values[method] = method_cls(ref, method, name) for attr in attrs: values[attr] = OctaveUserClassAttr(ref, attr, attr) return type(str(name), (OctaveUserClass,), values)
Make an Octave class for a given class name
def put(self, credentials): self.acquire_lock() try: self.locked_put(credentials) finally: self.release_lock()
Write a credential. The Storage lock must be held when this is called. Args: credentials: Credentials, the credentials to store.
def getobjectsize(self, window_name, object_name=None): if not object_name: handle, name, app = self._get_window_handle(window_name) else: handle = self._get_object_handle(window_name, object_name) return self._getobjectsize(handle)
Get object size @param window_name: Window name to look for, either full name, LDTP's name convention, or a Unix glob. @type window_name: string @param object_name: Object name to look for, either full name, LDTP's name convention, or a Unix glob. Or menu heirarchy @type object_name: string @return: x, y, width, height on success. @rtype: list
def reload_programs(self): print("Reloading programs:") for name, program in self._programs.items(): if getattr(program, 'program', None): print(" - {}".format(program.meta.label)) program.program = resources.programs.load(program.meta)
Reload all shader programs with the reloadable flag set
def crown(self, depth=2): nodes = [] for node in self.leaves: nodes += node.flatten(depth-1) return cluster.unique(nodes)
Returns a list of leaves, nodes connected to leaves, etc.
def run_metrics(command, parser, cl_args, unknown_args): cluster, role, env = cl_args['cluster'], cl_args['role'], cl_args['environ'] topology = cl_args['topology-name'] try: result = tracker_access.get_topology_info(cluster, env, topology, role) spouts = result['physical_plan']['spouts'].keys() bolts = result['physical_plan']['bolts'].keys() components = spouts + bolts cname = cl_args['component'] if cname: if cname in components: components = [cname] else: Log.error('Unknown component: \'%s\'' % cname) raise except Exception: Log.error("Fail to connect to tracker: \'%s\'", cl_args["tracker_url"]) return False cresult = [] for comp in components: try: metrics = tracker_access.get_component_metrics(comp, cluster, env, topology, role) except: Log.error("Fail to connect to tracker: \'%s\'", cl_args["tracker_url"]) return False stat, header = to_table(metrics) cresult.append((comp, stat, header)) for i, (comp, stat, header) in enumerate(cresult): if i != 0: print('') print('\'%s\' metrics:' % comp) print(tabulate(stat, headers=header)) return True
run metrics subcommand
def guid(self, guid): return self._json(self._get(self._build_url('guids', guid)), 200)['data']['type']
Determines JSONAPI type for provided GUID
def update(self, dicomset): if not isinstance(dicomset, DicomFileSet): raise ValueError('Given dicomset is not a DicomFileSet.') self.items = list(set(self.items).update(dicomset))
Update this set with the union of itself and dicomset. Parameters ---------- dicomset: DicomFileSet
def condense_ranges(cls, ranges): result = [] if ranges: ranges.sort(key=lambda tup: tup[0]) result.append(ranges[0]) for i in range(1, len(ranges)): if result[-1][1] + 1 >= ranges[i][0]: result[-1] = (result[-1][0], max(result[-1][1], ranges[i][1])) else: result.append(ranges[i]) return result
Sorts and removes overlaps
def _get_password_url(self): password_url = None if self._settings["user"] or self._settings["authorization"]: if self._settings["url"]: password_url = self._settings["url"] elif self._settings["base_url"]: password_url = self._settings["base_url"] return password_url
Get URL used for authentication Returns: string: URL
def handle(self, *args, **options): LOGGER.info('Starting assigning enterprise roles to users!') role = options['role'] if role == ENTERPRISE_ADMIN_ROLE: self._assign_enterprise_role_to_users(self._get_enterprise_admin_users_batch, options) elif role == ENTERPRISE_OPERATOR_ROLE: self._assign_enterprise_role_to_users(self._get_enterprise_operator_users_batch, options) elif role == ENTERPRISE_LEARNER_ROLE: self._assign_enterprise_role_to_users(self._get_enterprise_customer_users_batch, options) elif role == ENTERPRISE_ENROLLMENT_API_ADMIN_ROLE: self._assign_enterprise_role_to_users(self._get_enterprise_enrollment_api_admin_users_batch, options, True) elif role == ENTERPRISE_CATALOG_ADMIN_ROLE: self._assign_enterprise_role_to_users(self._get_enterprise_catalog_admin_users_batch, options, True) else: raise CommandError('Please provide a valid role name. Supported roles are {admin} and {learner}'.format( admin=ENTERPRISE_ADMIN_ROLE, learner=ENTERPRISE_LEARNER_ROLE )) LOGGER.info('Successfully finished assigning enterprise roles to users!')
Entry point for managment command execution.
def _ignore_path(cls, path, ignore_list=None, white_list=None): ignore_list = ignore_list or [] white_list = white_list or [] return (cls._matches_patterns(path, ignore_list) and not cls._matches_patterns(path, white_list))
Returns a whether a path should be ignored or not.
def _get(self, *args, **kwargs): messages, all_retrieved = super(StorageMixin, self)._get(*args, **kwargs) if self.user.is_authenticated(): inbox_messages = self.backend.inbox_list(self.user) else: inbox_messages = [] return messages + inbox_messages, all_retrieved
Retrieve unread messages for current user, both from the inbox and from other storages
def _dump_field(self, fd): v = {} v['label'] = Pbd.LABELS[fd.label] v['type'] = fd.type_name if len(fd.type_name) > 0 else Pbd.TYPES[fd.type] v['name'] = fd.name v['number'] = fd.number v['default'] = '[default = {}]'.format(fd.default_value) if len(fd.default_value) > 0 else '' f = '{label} {type} {name} = {number} {default};'.format(**v) f = ' '.join(f.split()) self._print(f) if len(fd.type_name) > 0: self.uses.append(fd.type_name)
Dump single field.
def set_pkg_license_declared(self, doc, lic): self.assert_package_exists() if not self.package_license_declared_set: self.package_license_declared_set = True if validations.validate_lics_conc(lic): doc.package.license_declared = lic return True else: raise SPDXValueError('Package::LicenseDeclared') else: raise CardinalityError('Package::LicenseDeclared')
Sets the package's declared license. Raises SPDXValueError if data malformed. Raises OrderError if no package previously defined. Raises CardinalityError if already set.
def get_top_long_short_abs(positions, top=10): positions = positions.drop('cash', axis='columns') df_max = positions.max() df_min = positions.min() df_abs_max = positions.abs().max() df_top_long = df_max[df_max > 0].nlargest(top) df_top_short = df_min[df_min < 0].nsmallest(top) df_top_abs = df_abs_max.nlargest(top) return df_top_long, df_top_short, df_top_abs
Finds the top long, short, and absolute positions. Parameters ---------- positions : pd.DataFrame The positions that the strategy takes over time. top : int, optional How many of each to find (default 10). Returns ------- df_top_long : pd.DataFrame Top long positions. df_top_short : pd.DataFrame Top short positions. df_top_abs : pd.DataFrame Top absolute positions.
def calculate_subgraph_edge_overlap( graph: BELGraph, annotation: str = 'Subgraph' ) -> Tuple[ Mapping[str, EdgeSet], Mapping[str, Mapping[str, EdgeSet]], Mapping[str, Mapping[str, EdgeSet]], Mapping[str, Mapping[str, float]], ]: sg2edge = defaultdict(set) for u, v, d in graph.edges(data=True): if not edge_has_annotation(d, annotation): continue sg2edge[d[ANNOTATIONS][annotation]].add((u, v)) subgraph_intersection = defaultdict(dict) subgraph_union = defaultdict(dict) result = defaultdict(dict) for sg1, sg2 in itt.product(sg2edge, repeat=2): subgraph_intersection[sg1][sg2] = sg2edge[sg1] & sg2edge[sg2] subgraph_union[sg1][sg2] = sg2edge[sg1] | sg2edge[sg2] result[sg1][sg2] = len(subgraph_intersection[sg1][sg2]) / len(subgraph_union[sg1][sg2]) return sg2edge, subgraph_intersection, subgraph_union, result
Build a DatafFame to show the overlap between different sub-graphs. Options: 1. Total number of edges overlap (intersection) 2. Percentage overlap (tanimoto similarity) :param graph: A BEL graph :param annotation: The annotation to group by and compare. Defaults to 'Subgraph' :return: {subgraph: set of edges}, {(subgraph 1, subgraph2): set of intersecting edges}, {(subgraph 1, subgraph2): set of unioned edges}, {(subgraph 1, subgraph2): tanimoto similarity},
def _findAll(self, name, attrs, text, limit, generator, **kwargs): "Iterates over a generator looking for things that match." if isinstance(name, SoupStrainer): strainer = name else: strainer = SoupStrainer(name, attrs, text, **kwargs) results = ResultSet(strainer) g = generator() while True: try: i = g.next() except StopIteration: break if i: found = strainer.search(i) if found: results.append(found) if limit and len(results) >= limit: break return results
Iterates over a generator looking for things that match.
def centerdc_2_twosided(data): N = len(data) newpsd = np.concatenate((data[N//2:], (cshift(data[0:N//2], -1)))) return newpsd
Convert a center-dc PSD to a twosided PSD
def course_key_is_valid(course_key): if course_key is None: return False try: CourseKey.from_string(text_type(course_key)) except (InvalidKeyError, UnicodeDecodeError): return False return True
Course key object validation
def create(self, data): self.app_id = None if 'client_id' not in data: raise KeyError('The authorized app must have a client_id') if 'client_secret' not in data: raise KeyError('The authorized app must have a client_secret') return self._mc_client._post(url=self._build_path(), data=data)
Retrieve OAuth2-based credentials to associate API calls with your application. :param data: The request body parameters :type data: :py:class:`dict` data = { "client_id": string*, "client_secret": string* }
def can(obj): import_needed = False for cls, canner in iteritems(can_map): if isinstance(cls, string_types): import_needed = True break elif istype(obj, cls): return canner(obj) if import_needed: _import_mapping(can_map, _original_can_map) return can(obj) return obj
Prepare an object for pickling.
def _create_folder(local_folder, parent_folder_id): new_folder = session.communicator.create_folder( session.token, os.path.basename(local_folder), parent_folder_id) return new_folder['folder_id']
Function for creating a remote folder and returning the id. This should be a building block for user-level functions. :param local_folder: full path to a local folder :type local_folder: string :param parent_folder_id: id of parent folder on the Midas Server instance, where the new folder will be added :type parent_folder_id: int | long :returns: id of the remote folder that was created :rtype: int | long
def joint_torques(self): return as_flat_array(getattr(j, 'amotor', j).feedback[-1][:j.ADOF] for j in self.joints)
Get a list of all current joint torques in the skeleton.
def get_heron_dir(): go_above_dirs = 9 path = "/".join(os.path.realpath(__file__).split('/')[:-go_above_dirs]) return normalized_class_path(path)
This will extract heron directory from .pex file. For example, when __file__ is '/Users/heron-user/bin/heron/heron/tools/common/src/python/utils/config.pyc', and its real path is '/Users/heron-user/.heron/bin/heron/tools/common/src/python/utils/config.pyc', the internal variable ``path`` would be '/Users/heron-user/.heron', which is the heron directory This means the variable `go_above_dirs` below is 9. :return: root location of the .pex file
def queue(users, label, extra_context=None, sender=None): if extra_context is None: extra_context = {} if isinstance(users, QuerySet): users = [row["pk"] for row in users.values("pk")] else: users = [user.pk for user in users] notices = [] for user in users: notices.append((user, label, extra_context, sender)) NoticeQueueBatch(pickled_data=base64.b64encode(pickle.dumps(notices))).save()
Queue the notification in NoticeQueueBatch. This allows for large amounts of user notifications to be deferred to a seperate process running outside the webserver.
def get_doc(doc_id, db_name, server_url='http://127.0.0.1:5984/', rev=None): db = get_server(server_url)[db_name] if rev: headers, response = db.resource.get(doc_id, rev=rev) return couchdb.client.Document(response) return db[doc_id]
Return a CouchDB document, given its ID, revision and database name.
def enroll_users_in_course(cls, enterprise_customer, course_id, course_mode, emails): existing_users, unregistered_emails = cls.get_users_by_email(emails) successes = [] pending = [] failures = [] for user in existing_users: succeeded = cls.enroll_user(enterprise_customer, user, course_mode, course_id) if succeeded: successes.append(user) else: failures.append(user) for email in unregistered_emails: pending_user = enterprise_customer.enroll_user_pending_registration( email, course_mode, course_id ) pending.append(pending_user) return successes, pending, failures
Enroll existing users in a course, and create a pending enrollment for nonexisting users. Args: enterprise_customer: The EnterpriseCustomer which is sponsoring the enrollment course_id (str): The unique identifier of the course in which we're enrolling course_mode (str): The mode with which we're enrolling in the course emails: An iterable of email addresses which need to be enrolled Returns: successes: A list of users who were successfully enrolled in the course pending: A list of PendingEnterpriseCustomerUsers who were successfully linked and had pending enrollments created for them in the database failures: A list of users who could not be enrolled in the course
def _get_const_info(const_index, const_list): argval = const_index if const_list is not None: try: argval = const_list[const_index] except IndexError: raise ValidationError("Consts value out of range: {}".format(const_index)) from None return argval, repr(argval)
Helper to get optional details about const references Returns the dereferenced constant and its repr if the constant list is defined. Otherwise returns the constant index and its repr().
def isodate(datestamp=None, microseconds=False): datestamp = datestamp or datetime.datetime.now() if not microseconds: usecs = datetime.timedelta(microseconds=datestamp.microsecond) datestamp = datestamp - usecs return datestamp.isoformat(b' ' if PY2 else u' ')
Return current or given time formatted according to ISO-8601.
def dist_baystat(src, tar, min_ss_len=None, left_ext=None, right_ext=None): return Baystat().dist(src, tar, min_ss_len, left_ext, right_ext)
Return the Baystat distance. This is a wrapper for :py:meth:`Baystat.dist`. Parameters ---------- src : str Source string for comparison tar : str Target string for comparison min_ss_len : int Minimum substring length to be considered left_ext : int Left-side extension length right_ext : int Right-side extension length Returns ------- float The Baystat distance Examples -------- >>> round(dist_baystat('cat', 'hat'), 12) 0.333333333333 >>> dist_baystat('Niall', 'Neil') 0.6 >>> round(dist_baystat('Colin', 'Cuilen'), 12) 0.833333333333 >>> dist_baystat('ATCG', 'TAGC') 1.0
def dropbox_submission(dropbox, request): try: data = dropbox_schema.deserialize(request.POST) except Exception: return HTTPFound(location=request.route_url('dropbox_form')) dropbox.message = data.get('message') if 'testing_secret' in dropbox.settings: dropbox.from_watchdog = is_equal( unicode(dropbox.settings['test_submission_secret']), data.pop('testing_secret', u'')) if data.get('upload') is not None: dropbox.add_attachment(data['upload']) dropbox.submit() drop_url = request.route_url('dropbox_view', drop_id=dropbox.drop_id) print("Created dropbox %s" % drop_url) return HTTPFound(location=drop_url)
handles the form submission, redirects to the dropbox's status page.
def encode_body(req): if isinstance(req.body, text_type): split = req.headers.get('content-type', 'text/plain').split(';') if len(split) == 2: ct, cs = split cs = cs.split('=')[1] req.body = req.body.encode(cs) else: ct = split[0] if (ct == 'application/x-www-form-urlencoded' or 'x-amz-' in ct): req.body = req.body.encode() else: req.body = req.body.encode('utf-8') req.headers['content-type'] = ct + '; charset=utf-8'
Encode body of request to bytes and update content-type if required. If the body of req is Unicode then encode to the charset found in content-type header if present, otherwise UTF-8, or ASCII if content-type is application/x-www-form-urlencoded. If encoding to UTF-8 then add charset to content-type. Modifies req directly, does not return a modified copy. req -- Requests PreparedRequest object
def rows_after(self): rows_after = [] for mesh in self.produced_meshes: if mesh.is_consumed(): row = mesh.consuming_row if rows_after not in rows_after: rows_after.append(row) return rows_after
The rows that consume meshes from this row. :rtype: list :return: a list of rows that consume meshes from this row. Each row occurs only once. They are sorted by the first occurrence in the instructions.
def get_suggested_filename(metadata): if metadata.get('title') and metadata.get('track_number'): suggested_filename = '{track_number:0>2} {title}'.format(**metadata) elif metadata.get('title') and metadata.get('trackNumber'): suggested_filename = '{trackNumber:0>2} {title}'.format(**metadata) elif metadata.get('title') and metadata.get('tracknumber'): suggested_filename = '{tracknumber:0>2} {title}'.format(**metadata) else: suggested_filename = '00 {}'.format(metadata.get('title', '')) return suggested_filename
Generate a filename for a song based on metadata. Parameters: metadata (dict): A metadata dict. Returns: A filename.
def merge_images(images, axis='t'): if not images: return None axis_dim = {'x': 0, 'y': 1, 'z': 2, 't': 3, } if axis not in axis_dim: raise ValueError('Expected `axis` to be one of ({}), got {}.'.format(set(axis_dim.keys()), axis)) img1 = images[0] for img in images: check_img_compatibility(img1, img) image_data = [] for img in images: image_data.append(check_img(img).get_data()) work_axis = axis_dim[axis] ndim = image_data[0].ndim if ndim - 1 < work_axis: image_data = [np.expand_dims(img, axis=work_axis) for img in image_data] return np.concatenate(image_data, axis=work_axis)
Concatenate `images` in the direction determined in `axis`. Parameters ---------- images: list of str or img-like object. See NeuroImage constructor docstring. axis: str 't' : concatenate images in time 'x' : concatenate images in the x direction 'y' : concatenate images in the y direction 'z' : concatenate images in the z direction Returns ------- merged: img-like object
def connect(self): if not self.connected(): self._ws = create_connection(self.WS_URI) message = { 'type':self.WS_TYPE, 'product_id':self.WS_PRODUCT_ID } self._ws.send(dumps(message)) with self._lock: if not self._thread: thread = Thread(target=self._keep_alive_thread, args=[]) thread.start()
Connects and subscribes to the WebSocket Feed.
def finalizeOp(self, ops, account, permission, **kwargs): if "append_to" in kwargs and kwargs["append_to"]: if self.proposer: log.warning( "You may not use append_to and self.proposer at " "the same time. Append new_proposal(..) instead" ) append_to = kwargs["append_to"] parent = append_to.get_parent() assert isinstance( append_to, (self.transactionbuilder_class, self.proposalbuilder_class) ) append_to.appendOps(ops) if isinstance(append_to, self.proposalbuilder_class): parent.appendSigner(append_to.proposer, permission) else: parent.appendSigner(account, permission) return append_to.get_parent() elif self.proposer: proposal = self.proposal() proposal.set_proposer(self.proposer) proposal.set_expiration(self.proposal_expiration) proposal.set_review(self.proposal_review) proposal.appendOps(ops) else: self.txbuffer.appendOps(ops) if "fee_asset" in kwargs and kwargs["fee_asset"]: self.txbuffer.set_fee_asset(kwargs["fee_asset"]) if self.unsigned: self.txbuffer.addSigningInformation(account, permission) return self.txbuffer elif self.bundle: self.txbuffer.appendSigner(account, permission) return self.txbuffer.json() else: self.txbuffer.appendSigner(account, permission) self.txbuffer.sign() return self.txbuffer.broadcast()
This method obtains the required private keys if present in the wallet, finalizes the transaction, signs it and broadacasts it :param operation ops: The operation (or list of operaions) to broadcast :param operation account: The account that authorizes the operation :param string permission: The required permission for signing (active, owner, posting) :param object append_to: This allows to provide an instance of ProposalsBuilder (see :func:`new_proposal`) or TransactionBuilder (see :func:`new_tx()`) to specify where to put a specific operation. ... note:: ``append_to`` is exposed to every method used in the this class ... note:: If ``ops`` is a list of operation, they all need to be signable by the same key! Thus, you cannot combine ops that require active permission with ops that require posting permission. Neither can you use different accounts for different operations! ... note:: This uses ``txbuffer`` as instance of :class:`transactionbuilder.TransactionBuilder`. You may want to use your own txbuffer
def org_by_name(self, hostname): addr = self._gethostbyname(hostname) return self.org_by_addr(addr)
Returns Organization, ISP, or ASNum name for given hostname. :arg hostname: Hostname (e.g. example.com)
def human_transactions(self): txs = [] for tx in self.transactions: if tx.depth == 0: txs.append(tx) return tuple(txs)
Completed human transaction
def issue_line_with_user(self, line, issue): if not issue.get("pull_request") or not self.options.author: return line if not issue.get("user"): line += u" (Null user)" elif self.options.username_as_tag: line += u" (@{0})".format( issue["user"]["login"] ) else: line += u" ([{0}]({1}))".format( issue["user"]["login"], issue["user"]["html_url"] ) return line
If option author is enabled, a link to the profile of the author of the pull reqest will be added to the issue line. :param str line: String containing a markdown-formatted single issue. :param dict issue: Fetched issue from GitHub. :rtype: str :return: Issue line with added author link.
def _get_children_as_string(node): out = [] if node: for child in node: if child.nodeType == child.TEXT_NODE: out.append(child.data) else: out.append(_get_children_as_string(child.childNodes)) return ''.join(out)
Iterate through all the children of a node. Returns one string containing the values from all the text-nodes recursively.
def _import_mapping(mapping, original=None): for key, value in list(mapping.items()): if isinstance(key, string_types): try: cls = import_item(key) except Exception: if original and key not in original: print("ERROR: canning class not importable: %r", key, exc_info=True) mapping.pop(key) else: mapping[cls] = mapping.pop(key)
Import any string-keys in a type mapping.
def init_raspbian_vm(self): r = self.local_renderer r.comment('Installing system packages.') r.sudo('add-apt-repository ppa:linaro-maintainers/tools') r.sudo('apt-get update') r.sudo('apt-get install libsdl-dev qemu-system') r.comment('Download image.') r.local('wget https://downloads.raspberrypi.org/raspbian_lite_latest') r.local('unzip raspbian_lite_latest.zip') r.comment('Find start of the Linux ext4 partition.') r.local( "parted -s 2016-03-18-raspbian-jessie-lite.img unit B print | " "awk '/^Number/{{p=1;next}}; p{{gsub(/[^[:digit:]]/, "", $2); print $2}}' | sed -n 2p", assign_to='START') r.local('mkdir -p {raspbian_mount_point}') r.sudo('mount -v -o offset=$START -t ext4 {raspbian_image} $MNT') r.comment('Comment out everything in ld.so.preload') r.local("sed -i 's/^/ r.comment('Comment out entries containing /dev/mmcblk in fstab.') r.local("sed -i '/mmcblk/ s?^? r.sudo('umount {raspbian_mount_point}') r.comment('Download kernel.') r.local('wget https://github.com/dhruvvyas90/qemu-rpi-kernel/blob/master/{raspbian_kernel}?raw=true') r.local('mv {raspbian_kernel} {libvirt_images_dir}') r.comment('Creating libvirt machine.') r.local('virsh define libvirt-raspbian.xml') r.comment('You should now be able to boot the VM by running:') r.comment('') r.comment(' qemu-system-arm -kernel {libvirt_boot_dir}/{raspbian_kernel} ' '-cpu arm1176 -m 256 -M versatilepb -serial stdio -append "root=/dev/sda2 rootfstype=ext4 rw" ' '-hda {libvirt_images_dir}/{raspbian_image}') r.comment('') r.comment('Or by running virt-manager.')
Creates an image for running Raspbian in a QEMU virtual machine. Based on the guide at: https://github.com/dhruvvyas90/qemu-rpi-kernel/wiki/Emulating-Jessie-image-with-4.1.x-kernel
def read_chunk(filename, offset=-1, length=-1, escape_data=False): try: length = int(length) offset = int(offset) except ValueError: return {} if not os.path.isfile(filename): return {} try: fstat = os.stat(filename) except Exception: return {} if offset == -1: offset = fstat.st_size if length == -1: length = fstat.st_size - offset with open(filename, "r") as fp: fp.seek(offset) try: data = fp.read(length) except IOError: return {} if data: data = _escape_data(data) if escape_data else data return dict(offset=offset, length=len(data), data=data) return dict(offset=offset, length=0)
Read a chunk of a file from an offset upto the length.
def find_matching(cls, path, patterns): for pattern in patterns: if pattern.match(path): yield pattern
Yield all matching patterns for path.
def export(self): graph = nx.MultiDiGraph() regions = self.network.getRegions() for idx in xrange(regions.getCount()): regionPair = regions.getByIndex(idx) regionName = regionPair[0] graph.add_node(regionName, label=regionName) for linkName, link in self.network.getLinks(): graph.add_edge(link.getSrcRegionName(), link.getDestRegionName(), src=link.getSrcOutputName(), dest=link.getDestInputName()) return graph
Exports a network as a networkx MultiDiGraph intermediate representation suitable for visualization. :return: networkx MultiDiGraph
def mapCellsToColumns(self, cells): cellsForColumns = defaultdict(set) for cell in cells: column = self.columnForCell(cell) cellsForColumns[column].add(cell) return cellsForColumns
Maps cells to the columns they belong to. :param cells: (set) Cells :returns: (dict) Mapping from columns to their cells in `cells`
def get_notification_subject_line(course_name, template_configuration=None): stock_subject_template = _('You\'ve been enrolled in {course_name}!') default_subject_template = getattr( settings, 'ENTERPRISE_ENROLLMENT_EMAIL_DEFAULT_SUBJECT_LINE', stock_subject_template, ) if template_configuration is not None and template_configuration.subject_line: final_subject_template = template_configuration.subject_line else: final_subject_template = default_subject_template try: return final_subject_template.format(course_name=course_name) except KeyError: pass try: return default_subject_template.format(course_name=course_name) except KeyError: return stock_subject_template.format(course_name=course_name)
Get a subject line for a notification email. The method is designed to fail in a "smart" way; if we can't render a database-backed subject line template, then we'll fall back to a template saved in the Django settings; if we can't render _that_ one, then we'll fall through to a friendly string written into the code. One example of a failure case in which we want to fall back to a stock template would be if a site admin entered a subject line string that contained a template tag that wasn't available, causing a KeyError to be raised. Arguments: course_name (str): Course name to be rendered into the string template_configuration: A database-backed object with a stored subject line template
def wheel_helper(pos, length, cycle_step): return wheel_color((pos * len(_WHEEL) / length) + cycle_step)
Helper for wheel_color that distributes colors over length and allows shifting position.
def findAll(self, name=None, attrs={}, recursive=True, text=None, limit=None, **kwargs): generator = self.recursiveChildGenerator if not recursive: generator = self.childGenerator return self._findAll(name, attrs, text, limit, generator, **kwargs)
Extracts a list of Tag objects that match the given criteria. You can specify the name of the Tag and any attributes you want the Tag to have. The value of a key-value pair in the 'attrs' map can be a string, a list of strings, a regular expression object, or a callable that takes a string and returns whether or not the string matches for some custom definition of 'matches'. The same is true of the tag name.
def is_empty(self): if len(self.val) != 0: if isinstance(self.val, str_types): self._err('Expected <%s> to be empty string, but was not.' % self.val) else: self._err('Expected <%s> to be empty, but was not.' % self.val) return self
Asserts that val is empty.
def _reproject(self, p): nulls = self.problem.nullspace equalities = self.problem.equalities if np.allclose(equalities.dot(p), self.problem.b, rtol=0, atol=self.feasibility_tol): new = p else: LOGGER.info("feasibility violated in sample" " %d, trying to reproject" % self.n_samples) new = nulls.dot(nulls.T.dot(p)) if any(new != p): LOGGER.info("reprojection failed in sample" " %d, using random point in space" % self.n_samples) new = self._random_point() return new
Reproject a point into the feasibility region. This function is guaranteed to return a new feasible point. However, no guarantees in terms of proximity to the original point can be made. Parameters ---------- p : numpy.array The current sample point. Returns ------- numpy.array A new feasible point. If `p` was feasible it wil return p.
def add_tags(self, tags): return self.get_data( "firewalls/%s/tags" % self.id, type=POST, params={"tags": tags} )
Add tags to this Firewall.
def get_md_status(self, line): ret = {} splitted = split('\W+', line) if len(splitted) < 7: ret['available'] = None ret['used'] = None ret['config'] = None else: ret['available'] = splitted[-4] ret['used'] = splitted[-3] ret['config'] = splitted[-2] return ret
Return a dict of md status define in the line.
def NormalizePath(path): if path.endswith('/') or path.endswith('\\'): slash = os.path.sep else: slash = '' return os.path.normpath(path) + slash
Normalizes a path maintaining the final slashes. Some environment variables need the final slash in order to work. Ex. The SOURCES_DIR set by subversion must end with a slash because of the way it is used in the Visual Studio projects. :param unicode path: The path to normalize. :rtype: unicode :returns: Normalized path
def numeric_task_id(task_id): if task_id is not None: if task_id.startswith('task-'): return int(task_id[len('task-'):]) else: return int(task_id)
Converts a task-id to the numeric task-id. Args: task_id: task-id in either task-n or n format Returns: n
def report_read_counts(self, filename, grp_wise=False, reorder='as-is', notes=None): expected_read_counts = self.probability.sum(axis=APM.Axis.READ) if grp_wise: lname = self.probability.gname expected_read_counts = expected_read_counts * self.grp_conv_mat else: lname = self.probability.lname total_read_counts = expected_read_counts.sum(axis=0) if reorder == 'decreasing': report_order = np.argsort(total_read_counts.flatten()) report_order = report_order[::-1] elif reorder == 'increasing': report_order = np.argsort(total_read_counts.flatten()) elif reorder == 'as-is': report_order = np.arange(len(lname)) cntdata = np.vstack((expected_read_counts, total_read_counts)) fhout = open(filename, 'w') fhout.write("locus\t" + "\t".join(self.probability.hname) + "\ttotal") if notes is not None: fhout.write("\tnotes") fhout.write("\n") for locus_id in report_order: lname_cur = lname[locus_id] fhout.write("\t".join([lname_cur] + map(str, cntdata[:, locus_id].ravel()))) if notes is not None: fhout.write("\t%s" % notes[lname_cur]) fhout.write("\n") fhout.close()
Exports expected read counts :param filename: File name for output :param grp_wise: whether the report is at isoform level or gene level :param reorder: whether the report should be either 'decreasing' or 'increasing' order or just 'as-is' :return: Nothing but the method writes a file
def get_repr(self, obj, referent=None): objtype = type(obj) typename = str(objtype.__module__) + "." + objtype.__name__ prettytype = typename.replace("__builtin__.", "") name = getattr(obj, "__name__", "") if name: prettytype = "%s %r" % (prettytype, name) key = "" if referent: key = self.get_refkey(obj, referent) url = reverse('dowser_trace_object', args=( typename, id(obj) )) return ('<a class="objectid" href="%s">%s</a> ' '<span class="typename">%s</span>%s<br />' '<span class="repr">%s</span>' % (url, id(obj), prettytype, key, get_repr(obj, 100)) )
Return an HTML tree block describing the given object.
def _adaptToResource(self, result): if result is None: return NotFound() spinneretResource = ISpinneretResource(result, None) if spinneretResource is not None: return SpinneretResource(spinneretResource) renderable = IRenderable(result, None) if renderable is not None: return _RenderableResource(renderable) resource = IResource(result, None) if resource is not None: return resource if isinstance(result, URLPath): return Redirect(str(result)) return result
Adapt a result to `IResource`. Several adaptions are tried they are, in order: ``None``, `IRenderable <twisted:twisted.web.iweb.IRenderable>`, `IResource <twisted:twisted.web.resource.IResource>`, and `URLPath <twisted:twisted.python.urlpath.URLPath>`. Anything else is returned as is. A `URLPath <twisted:twisted.python.urlpath.URLPath>` is treated as a redirect.
def textpath(self, txt, x, y, width=None, height=1000000, enableRendering=False, **kwargs): txt = self.Text(txt, x, y, width, height, **kwargs) path = txt.path if draw: path.draw() return path
Draws an outlined path of the input text
def anomalyRemoveLabels(self, start, end, labelFilter): self._getAnomalyClassifier().getSelf().removeLabels(start, end, labelFilter)
Remove labels from the anomaly classifier within this model. Removes all records if ``labelFilter==None``, otherwise only removes the labels equal to ``labelFilter``. :param start: (int) index to start removing labels :param end: (int) index to end removing labels :param labelFilter: (string) If specified, only removes records that match
def iterwindows(self, count=64, window_shape=(256, 256)): if count is None: while True: yield self.randwindow(window_shape) else: for i in xrange(count): yield self.randwindow(window_shape)
Iterate over random windows of an image Args: count (int): the number of the windows to generate. Defaults to 64, if `None` will continue to iterate over random windows until stopped. window_shape (tuple): The desired shape of each image as (height, width) in pixels. Yields: image: an image of the given shape and same type.
def proto_04_01_MTmon70s2(abf=exampleABF): standard_inspect(abf) swhlab.memtest.memtest(abf) swhlab.memtest.checkSweep(abf) swhlab.plot.save(abf,tag='check',resize=False) swhlab.memtest.plot_standard4(abf) swhlab.plot.save(abf,tag='memtests')
repeated membrane tests, likely with drug added. Maybe IPSCs.
def getTopologyByClusterRoleEnvironAndName(self, cluster, role, environ, topologyName): topologies = list(filter(lambda t: t.name == topologyName and t.cluster == cluster and (not role or t.execution_state.role == role) and t.environ == environ, self.topologies)) if not topologies or len(topologies) > 1: if role is not None: raise Exception("Topology not found for {0}, {1}, {2}, {3}".format( cluster, role, environ, topologyName)) else: raise Exception("Topology not found for {0}, {1}, {2}".format( cluster, environ, topologyName)) return topologies[0]
Find and return the topology given its cluster, environ, topology name, and an optional role. Raises exception if topology is not found, or more than one are found.
def hierarchy_flatten(annotation): intervals, values = annotation.to_interval_values() ordering = dict() for interval, value in zip(intervals, values): level = value['level'] if level not in ordering: ordering[level] = dict(intervals=list(), labels=list()) ordering[level]['intervals'].append(interval) ordering[level]['labels'].append(value['label']) levels = sorted(list(ordering.keys())) hier_intervals = [ordering[level]['intervals'] for level in levels] hier_labels = [ordering[level]['labels'] for level in levels] return hier_intervals, hier_labels
Flatten a multi_segment annotation into mir_eval style. Parameters ---------- annotation : jams.Annotation An annotation in the `multi_segment` namespace Returns ------- hier_intervalss : list A list of lists of intervals, ordered by increasing specificity. hier_labels : list A list of lists of labels, ordered by increasing specificity.