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def pull_df(self, md5): try: _packed_df = self.workbench.get_dataframe(md5) _df = pd.read_msgpack(lz4.loads(_packed_df)) return _df except zerorpc.exceptions.RemoteError as e: return repr_to_str_decorator.r_to_s(self._data_not_found)(e)
Wrapper for the Workbench get_dataframe method Args: md5: pull the dataframe identified by this md5 Returns: The uncompressed/unserialized dataframe
juraj-google-style
def get_configs(__pkg: str, __name: str = 'config') -> List[str]: dirs = [user_config(__pkg), ] dirs.extend(path.expanduser(path.sep.join([d, __pkg])) for d in getenv('XDG_CONFIG_DIRS', '/etc/xdg').split(':')) configs = [] for dname in reversed(dirs): test_path = path.join(d...
Return all configs for given package. Args: __pkg: Package name __name: Configuration file name
juraj-google-style
def update_config_data(msg, cfg): for attr in msg: if ((attr in cfg.data[msg.profile]) and (attr is not 'auth')): cfg.data[msg.profile][attr] = getattr(msg, attr)
Updates the profile's config entry with values set in each attr by the user. This will overwrite existing values. Args: :msg: (Message class) an instance of a message class. :cfg: (jsonconfig.Config) config instance.
codesearchnet
def increment(self, size: int): assert (size >= 0), size self.files += 1 self.size += size self.bandwidth_meter.feed(size)
Increment the number of files downloaded. Args: size: The size of the file
codesearchnet
def get_annotations_dict(members: dict[str, cfg.Variable]) -> '_instances.AnnotationsDict | None': if '__annotations__' not in members: return None annots_var = members['__annotations__'] try: annots = get_atomic_value(annots_var) except ConversionError: return None return an...
Get __annotations__ from a members map. Returns None rather than {} if the dict does not exist so that callers always have a reference to the actual dictionary, and can mutate it if needed. Args: members: A dict of member name to variable Returns: members['__annotations__'] unpacked as a python dict, or None
github-repos
def _run_command(argv): (command_name, argv) = _get_command_and_argv(argv) _LOGGER.info('Running command "%s %s" with args: %s', settings.command, command_name, argv) subcommand = _get_subcommand(command_name) func = call.get_callable(subcommand) doc = usage.format_usage(subcommand.__doc__) args...
Run the command with the given CLI options and exit. Command functions are expected to have a __doc__ string that is parseable by docopt. Args: argv: The list of command line arguments supplied for a command. The first argument is expected to be the name of the command to be run. Note that this is different than the ...
codesearchnet
def validate_sns_topic_subscription(self, region): sns = self.session.client('sns', region_name=region) arn = 'arn:aws:sns:{}:{}:{}'.format(region, self.account.account_number, self.topic_name) try: data = sns.list_subscriptions_by_topic(TopicArn=arn) except ClientEr...
Validates SQS subscription to the SNS topic. Returns `True` if subscribed or `False` if not subscribed or topic is missing Args: region (str): Name of AWS Region Returns: `bool`
juraj-google-style
def imresize(img, size, return_scale=False, interpolation='bilinear'): h, w = img.shape[:2] resized_img = cv2.resize( img, size, interpolation=interp_codes[interpolation]) if not return_scale: return resized_img else: w_scale = size[0] / w h_scale = size[1] / h ...
Resize image to a given size. Args: img (ndarray): The input image. size (tuple): Target (w, h). return_scale (bool): Whether to return `w_scale` and `h_scale`. interpolation (str): Interpolation method, accepted values are "nearest", "bilinear", "bicubic", "area", "lanczos". Returns: tuple or ndarray: (`resized_img`...
juraj-google-style
def recursive_print(name, val, spaces=0): if name is None: msg = None else: fmt = '.' * max(0, spaces - 2) + ' msg = fmt.format(name) if isinstance(val, dict): if msg is not None: print(msg) for k in val.keys(): recursive_print(k, val[k], space...
Recursively print the structure of a checkpoint. This function is taken from `convert_megatron_gpt2_checkpoint.py` Args: name (str): the name of the current tensor parameter val (Tuple(int)): the shape of the current tensor parameter spaces (int): the number of spaces to print before the output for a nested structure
github-repos
def writeInput(self, session, directory, name): self.project_directory = directory with tmp_chdir(directory): replaceParamFile = self.replaceParamFile self.write(session=session, directory=directory, name=name) self._writeXput(session=session, directory=directory, fileCards=self.INPUT_FI...
Write only input files for a GSSHA project from the database to file. Args: session (:mod:`sqlalchemy.orm.session.Session`): SQLAlchemy session object bound to PostGIS enabled database directory (str): Directory where the files will be written. name (str): Name that will be given to project when written (e.g.: 'exampl...
codesearchnet
def center_crop(self, image: 'torch.Tensor', size: dict[str, int], **kwargs) -> 'torch.Tensor': if size.height is None or size.width is None: raise ValueError(f"The size dictionary must have keys 'height' and 'width'. Got {size.keys()}") return F.center_crop(image, (size['height'], size['width']))
Center crop an image to `(size["height"], size["width"])`. If the input size is smaller than `crop_size` along any edge, the image is padded with 0's and then center cropped. Args: image (`"torch.Tensor"`): Image to center crop. size (`Dict[str, int]`): Size of the output image. Returns: `torch.Tensor`: The center cr...
github-repos
def define_simulation_graph(batch_env, algo_cls, config): step = tf.Variable(0, False, dtype=tf.int32, name='global_step') is_training = tf.placeholder(tf.bool, name='is_training') should_log = tf.placeholder(tf.bool, name='should_log') do_report = tf.placeholder(tf.bool, name='do_report') force_reset =...
Define the algorithm and environment interaction. Args: batch_env: In-graph environments object. algo_cls: Constructor of a batch algorithm. config: Configuration object for the algorithm. Returns: Object providing graph elements via attributes.
juraj-google-style
def prune_volumes(self, filters=None): params = {} if filters: params['filters'] = utils.convert_filters(filters) url = self._url('/volumes/prune') return self._result(self._post(url, params=params), True)
Delete unused volumes Args: filters (dict): Filters to process on the prune list. Returns: (dict): A dict containing a list of deleted volume names and the amount of disk space reclaimed in bytes. Raises: :py:class:`docker.errors.APIError` If the server returns an error.
codesearchnet
def _is_padded_shape_compatible_with(padded_shape, input_component_shape): if padded_shape.dims is None or input_component_shape.dims is None: return True if len(padded_shape.dims) != len(input_component_shape.dims): return False for padded_dim, input_dim in zip(padded_shape.dims, input_comp...
Returns `True` if `input_component_shape` can be padded to `padded_shape`. Args: padded_shape: A `tf.TensorShape`. input_component_shape: A `tf.TensorShape`. Returns: `True` if `input_component_shape` can be padded to `padded_shape`, otherwise `False`.
github-repos
def compute_average_oxidation_state(site): try: avg_oxi = sum([(sp.oxi_state * occu) for (sp, occu) in site.species.items() if (sp is not None)]) return avg_oxi except AttributeError: pass try: return site.charge except AttributeError: raise ValueError('Ewald summ...
Calculates the average oxidation state of a site Args: site: Site to compute average oxidation state Returns: Average oxidation state of site.
codesearchnet
def kmer_count(seq_list, k): all_kmers = generate_all_kmers(k) kmer_count_list = [] for seq in seq_list: kmer_count_list.append([seq.count(kmer) for kmer in all_kmers]) return pd.DataFrame(kmer_count_list, columns=all_kmers)
Generate k-mer counts from a set of sequences Args: seq_list (iterable): List of DNA sequences (with letters from {A, C, G, T}) k (int): K in k-mer. Returns: pandas.DataFrame: Count matrix for seach sequence in seq_list Example: >>> kmer_count(["ACGTTAT", "GACGCGA"], 2) AA AC AG AT CA CC CG CT GA GC GG GT ...
codesearchnet
def load_entity(self, name, file_name, reload_cache=False): Entity.verify_name(name) self.entities.load(Entity.wrap_name(name), file_name, reload_cache) with open(file_name) as f: self.padaos.add_entity(name, f.read().split('\n')) self.must_train = True
Loads an entity, optionally checking the cache first Args: name (str): The associated name of the entity file_name (str): The location of the entity file reload_cache (bool): Whether to refresh all of cache
codesearchnet
def save_plot(self, filename, img_format="eps", **kwargs): plt = self.get_plot(**kwargs) plt.savefig(filename, format=img_format)
Save matplotlib plot to a file. Args: filename: Filename to write to. img_format: Image format to use. Defaults to EPS.
juraj-google-style
def _checksum(cls, line): tr_table = str.maketrans({c: None for c in (ascii_uppercase + '+ .')}) no_letters = line[:68].translate(tr_table).replace('-', '1') return (sum([int(l) for l in no_letters]) % 10)
Compute the checksum of a full line Args: line (str): Line to compute the checksum from Return: int: Checksum (modulo 10)
codesearchnet
def _RunOsLoginControl(self, params): try: return subprocess.call(([constants.OSLOGIN_CONTROL_SCRIPT] + params)) except OSError as e: if (e.errno == errno.ENOENT): return None else: raise
Run the OS Login control script. Args: params: list, the params to pass to the script Returns: int, the return code from the call, or None if the script is not found.
codesearchnet
def has_enough_gas_reserve(raiden, channels_to_open: int=0) -> Tuple[(bool, int)]: secure_reserve_estimate = get_reserve_estimate(raiden, channels_to_open) current_account_balance = raiden.chain.client.balance(raiden.chain.client.address) return ((secure_reserve_estimate <= current_account_balance), secure_...
Checks if the account has enough balance to handle the lifecycles of all open channels as well as the to be created channels. Note: This is just an estimation. Args: raiden: A raiden service instance channels_to_open: The number of new channels that should be opened Returns: Tuple of a boolean denoting if the accoun...
codesearchnet
def _supervised_signature_def(method_name, inputs, loss=None, predictions=None, metrics=None): if inputs is None or not inputs: raise ValueError('{} inputs cannot be None or empty.'.format(method_name)) signature_inputs = {key: utils.build_tensor_info(tensor) for key, tensor in inputs.items()} signa...
Creates a signature for training and eval data. This function produces signatures that describe the inputs and outputs of a supervised process, such as training or evaluation, that results in loss, metrics, and the like. Note that this function only requires inputs to be not None. Args: method_name: Method name of th...
github-repos
def comment_to_ast(self, comment, link_resolver): assert (comment is not None) text = comment.description if (self.remove_xml_tags or (comment.filename in self.gdbus_codegen_sources)): text = re.sub('<.*?>', '', text) if self.escape_html: text = cgi.escape(text) (ast, diagnostics) = ...
Given a gtk-doc comment string, returns an opaque PyCapsule containing the document root. This is an optimization allowing to parse the docstring only once, and to render it multiple times with `ast_to_html`, links discovery and most of the link resolution being lazily done in that second phase. If you don't care abo...
codesearchnet
def get_course_details(self, course_id): return self._load_data(self.COURSES_ENDPOINT, resource_id=course_id, many=False)
Return the details of a single course by id - not a course run id. Args: course_id (str): The unique id for the course in question. Returns: dict: Details of the course in question.
codesearchnet
def get_input_info_dict(self, signature=None): return self._spec.get_input_info_dict(signature=signature, tags=self._tags)
Describes the inputs required by a signature. Args: signature: A string with the signature to get inputs information for. If None, the default signature is used if defined. Returns: The result of ModuleSpec.get_input_info_dict() for the given signature, and the graph variant selected by `tags` when this Module was in...
codesearchnet
def get_message(self, message_id): for message in self.messages: if message.id == message_id: return message raise ArgumentError("Message ID not found", message_id=message_id)
Get a message by its persistent id. Args: message_id (int): The id of the message that we're looking for
juraj-google-style
def deprecated_argument_lookup(new_name, new_value, old_name, old_value): if old_value is not None: if new_value is not None: raise ValueError(f"Cannot specify both '{old_name}' and '{new_name}'.") return old_value return new_value
Looks up deprecated argument name and ensures both are not used. Args: new_name: new name of argument new_value: value of new argument (or None if not used) old_name: old name of argument old_value: value of old argument (or None if not used) Returns: The effective argument that should be used. Raises: ValueError: if...
github-repos
def _validator(code_or_name, validator_type): if validator_type == "error": from .errors import codes from .errors import EXT elif validator_type == "warning": from .warnings import codes from .warnings import EXT else: pass def decorator(func): def...
Internal shared implementation to handle both error and warning validation checks. Args: code code_or_name (int or str) : a defined error code or custom message validator_type (str) : either "error" or "warning" Returns: validation decorator
juraj-google-style
def parse(self, argument): if (not isinstance(argument, six.string_types)): raise TypeError('flag value must be a string, found "{}"'.format(type(argument))) return argument
Parses the string argument and returns the native value. By default it returns its argument unmodified. Args: argument: string argument passed in the commandline. Raises: ValueError: Raised when it fails to parse the argument. TypeError: Raised when the argument has the wrong type. Returns: The parsed value in nati...
codesearchnet
def is_commutable(expr1, expr2, eps=1e-08): return (sum(((x * x.conjugate()).real for x in commutator(expr1, expr2).coeffs())) < eps)
Test whether expr1 and expr2 are commutable. Args: expr1 (Expr, Term or Pauli operator): Pauli's expression. expr2 (Expr, Term or Pauli operator): Pauli's expression. eps (float, optional): Machine epsilon. If |[expr1, expr2]| < eps, consider it is commutable. Returns: bool: if expr1 and expr2 are commutable, returns...
codesearchnet
def relocate(source, destination, move=False): venv = api.VirtualEnvironment(source) if (not move): venv.relocate(destination) return None venv.move(destination) return None
Adjust the virtual environment settings and optional move it. Args: source (str): Path to the existing virtual environment. destination (str): Desired path of the virtual environment. move (bool): Whether or not to actually move the files. Default False.
codesearchnet
def callable_eq(x: Optional[Callable[..., Any]], y: Optional[Callable[..., Any]]) -> bool: if x is y: return True if x is None or y is None: return False if inspect.isfunction(x) and inspect.isfunction(y): return _code_eq(x.__code__, y.__code__) elif inspect.ismethod(x) and inspe...
Returns True if two (maybe) callables are equal. For functions: `x` and `y` are considered equal when they are the same instance or have the same code (e.g. lambda x: x). For methods: `x` and `y` are considered equal when: static method: The same method from the same class hierarchy. E.g. subclass inherits a base cla...
github-repos
def fastq_verifier(entries, ambiguous=False): if ambiguous: regex = '^@.+{0}[ACGTURYKMSWBDHVNX]+{0}\\+.*{0}[!" else: regex = '^@.+{0}[ACGTU]+{0}\\+.*{0}[!-~]+{0}$'.format(os.linesep) delimiter = '{0}'.format(os.linesep) for entry in entries: if (len(entry.sequence) != len(entry.q...
Raises error if invalid FASTQ format detected Args: entries (list): A list of FastqEntry instances ambiguous (bool): Permit ambiguous bases, i.e. permit non-ACGTU bases Raises: FormatError: Error when FASTQ format incorrect with descriptive message Example: >>> from bio_utils.iterators import fastq_iter >>> import ...
codesearchnet
def _should_pack(arg): return isinstance(arg, list)
Determines whether the caller needs to pack the argument in a tuple. If user-defined function returns a list of tensors, `nest.flatten()` and `ops.convert_to_tensor()` and would conspire to attempt to stack those tensors into a single tensor because the tf.data version of `nest.flatten()` does not recurse into lists. ...
github-repos
def ws050(self, value=None): if (value is not None): try: value = float(value) except ValueError: raise ValueError('value {} need to be of type float for field `ws050`'.format(value)) self._ws050 = value
Corresponds to IDD Field `ws050` Wind speed corresponding 5.0% annual cumulative frequency of occurrence Args: value (float): value for IDD Field `ws050` Unit: m/s if `value` is None it will not be checked against the specification and is assumed to be a missing value Raises: ValueError: if `value` is not a valid val...
codesearchnet
def from_json_file(cls, filename): with open(filename, 'r') as fp: return cls(json.load(fp))
Load a lexicon from a JSON file. Args: filename (str): The path to a JSON dump.
juraj-google-style
def update_qos_aggregated_configuration(self, qos_configuration, timeout=(- 1)): uri = '{}{}'.format(self.data['uri'], self.QOS_AGGREGATED_CONFIGURATION) return self._helper.update(qos_configuration, uri=uri, timeout=timeout)
Updates the QoS aggregated configuration for the logical interconnect. Args: qos_configuration: QOS configuration. timeout: Timeout in seconds. Wait for task completion by default. The timeout does not abort the operation in OneView, just stops waiting for its completion. Returns: dict: Logical Interconnect.
codesearchnet
def stepBy(self, steps): self.setValue(self.value() + steps*self.singleStep())
steps value up/down by a single step. Single step is defined in singleStep(). Args: steps (int): positiv int steps up, negativ steps down
juraj-google-style
def _BuildFindSpecsFromArtifact(self, definition, environment_variables): find_specs = [] for source in definition.sources: if source.type_indicator == artifact_types.TYPE_INDICATOR_FILE: for path_entry in set(source.paths): specifications = self._BuildFindSpecsFromFileSourcePath( ...
Builds find specifications from an artifact definition. Args: definition (artifacts.ArtifactDefinition): artifact definition. environment_variables (list[EnvironmentVariableArtifact]): environment variables. Returns: list[dfvfs.FindSpec|dfwinreg.FindSpec]: dfVFS or dfWinReg find specifications.
juraj-google-style
def _mouseDown(x, y, button): if button == 'left': try: _sendMouseEvent(MOUSEEVENTF_LEFTDOWN, x, y) except (PermissionError, OSError): pass elif button == 'middle': try: _sendMouseEvent(MOUSEEVENTF_MIDDLEDOWN, x, y) except (PermissionErro...
Send the mouse down event to Windows by calling the mouse_event() win32 function. Args: x (int): The x position of the mouse event. y (int): The y position of the mouse event. button (str): The mouse button, either 'left', 'middle', or 'right' Returns: None
juraj-google-style
def _path_formatter(self, suffix): if suffix.lower() == "mirror": path_items = [self.bucket, self.s3path] else: path_items = [self.bucket, self.s3path, suffix] path = '/'.join(path_items) s3_format = "s3: formatted_path = path.replace(' f...
Format the s3 path properly. Args: suffix (str): suffix to add on to an s3 path Returns: str: formatted path
juraj-google-style
def date_to_epoch(year, month, day): return int(date_to_delorean(year, month, day).epoch)
Converts a date to epoch in UTC Args: year: int between 1 and 9999. month: int between 1 and 12. day: int between 1 and 31. Returns: Int epoch in UTC from date.
juraj-google-style
def Parse(self, rdf_data): if self._filter: return list(self._filter.Parse(rdf_data, self.expression)) return rdf_data
Process rdf data through the filter. Filters sift data according to filter rules. Data that passes the filter rule is kept, other data is dropped. If no filter method is provided, the data is returned as a list. Otherwise, a items that meet filter conditions are returned in a list. Args: rdf_data: Host data that has...
codesearchnet
def pymmh3_hash128_x64(key: Union[bytes, bytearray], seed: int) -> int: def fmix(k): k ^= k >> 33 k = (k * 0xff51afd7ed558ccd) & 0xFFFFFFFFFFFFFFFF k ^= k >> 33 k = (k * 0xc4ceb9fe1a85ec53) & 0xFFFFFFFFFFFFFFFF k ^= k >> 33 return k length = len(key) nb...
Implements 128-bit murmur3 hash for x64, as per ``pymmh3``, with some bugfixes. Args: key: data to hash seed: seed Returns: integer hash
juraj-google-style
def GetFile(self, map_name, dst_file, current_file, location=None): if map_name == config.MAP_PASSWORD: return self.GetPasswdFile(dst_file, current_file) elif map_name == config.MAP_GROUP: return self.GetGroupFile(dst_file, current_file) elif map_name == config.MAP_SHADOW: return sel...
Retrieve a file from this source. Args: map_name: A string representation of the map whose file you want dst_file: Temporary filename to write to. current_file: Path to the current cache. location: optional field used by automounts to indicate a specific map Returns: path to new file Raises: UnsupportedMap: for unkn...
github-repos
def execute_edit(args, root_dir=None): EDITOR = os.environ.get('EDITOR', 'vim') key = args['key'] status = command_factory('status')({}, root_dir=root_dir) if ((not isinstance(status['data'], str)) and (key in status['data'])): if (status['data'][key]['status'] in ['queued', 'stashed']): ...
Edit a existing queue command in the daemon. Args: args['key'] int: The key of the queue entry to be edited root_dir (string): The path to the root directory the daemon is running in.
codesearchnet
def add_outbound_connection(self, uri): LOGGER.debug('Adding connection to %s', uri) conn = OutboundConnection(connections=self._connections, endpoint=uri, dispatcher=self._dispatcher, zmq_identity=self._zmq_identity, secured=self._secured, server_public_key=self._server_public_key, server_private_key=self._ser...
Adds an outbound connection to the network. Args: uri (str): The zmq-style (e.g. tcp://hostname:port) uri to attempt to connect to.
codesearchnet
def component_mget(self, zip_data, components): if not isinstance(components, list): print("Components param must be a list") return query_params = {"components": ",".join(components)} return self.fetch_identifier_component( "zip/component_mget", zi...
Call the zip component_mget endpoint Args: - zip_data - As described in the class docstring. - components - A list of strings for each component to include in the request. Example: ["zip/details", "zip/volatility"]
juraj-google-style
def _run_async(self, urls): loop = asyncio.get_event_loop() results = loop.run_until_complete(self._async_loop(urls)) return results
Asynchronous event loop execution Args: urls (list): URLs to fetch Returns: results (obj): All URL requests' responses
juraj-google-style
def log_softmax(logits, axis=None, name=None, dim=None): axis = deprecation.deprecated_argument_lookup('axis', axis, 'dim', dim) if axis is None: axis = -1 return _wrap_2d_function(logits, gen_nn_ops.log_softmax, axis, name)
Computes log softmax activations. For each batch `i` and class `j` we have logsoftmax = logits - log(reduce_sum(exp(logits), axis)) Args: logits: A non-empty `Tensor`. Must be one of the following types: `half`, `float32`, `float64`. axis: The dimension softmax would be performed on. The default is -1 which indicate...
github-repos
def write(self, message, cur_time=None): if cur_time is None: cur_time = time.time() lines = self._line_buffer.add_string(message) for line in lines: timestamp = '' if self._prepend_timestamp: timestamp = datetime.datetime...
Write some text to the pusher. Args: message: a string to push for this file. cur_time: used for unit testing. override line timestamp.
juraj-google-style
def unzip(self, overwrite: bool = False): if self.zip_content and not overwrite: raise FileExistsError(str(self.temp_dir)) LOGGER.debug('unzipping miz to temp dir') try: with ZipFile(str(self.miz_path)) as zip_file: LOGGER.debug('reading info...
Flattens a MIZ file into the temp dir Args: overwrite: allow overwriting exiting files
juraj-google-style
def get_full_psd_matrix(self): if (self.matrix_m is not None): return (self.matrix_h, self.matrix_m) h_columns = [] for i in range((self.nn_params.num_hidden_layers + 1)): current_col_elems = [] for j in range(i): current_col_elems.append(tf.zeros([self.nn_params.sizes[j]...
Function that returns the tf graph corresponding to the entire matrix M. Returns: matrix_h: unrolled version of tf matrix corresponding to H matrix_m: unrolled tf matrix corresponding to M
codesearchnet
async def get(self, uid: int, cached_msg: CachedMessage=None, requirement: FetchRequirement=FetchRequirement.METADATA) -> Optional[MessageT]: ...
Return the message with the given UID. Args: uid: The message UID. cached_msg: The last known cached message. requirement: The data required from each message. Raises: IndexError: The UID is not valid in the mailbox.
codesearchnet
def monitor(service_addr, duration_ms, level=1): return _pywrap_profiler_plugin.monitor(_strip_prefix(service_addr, _GRPC_PREFIX), duration_ms, level, True)
Sends grpc requests to profiler server to perform on-demand monitoring. The monitoring result is a light weight performance summary of your model execution. This method will block the caller thread until it receives the monitoring result. This method currently supports Cloud TPU only. Args: service_addr: gRPC address...
github-repos
def upload_benchmark_files(opts): client = datastore.Client() for fname in list_files_by_mtime(opts.datadir): fpath = os.path.join(opts.datadir, fname) try: with open(fpath, 'r') as fd: if trylock(fd): upload_benchmark_data(client, fd.read()) ...
Find benchmark files, process them, and upload their data to the datastore. Locate benchmark files in the data directory, process them, and upload their data to the datastore. After processing each file, move it to the archive directory for safe-keeping. Each file is locked for processing, which allows multiple uplo...
github-repos
def prepare_context(pipeline, context_in_string, context): logger.debug('starting') parsed_context = get_parsed_context(pipeline=pipeline, context_in_string=context_in_string) context.update(parsed_context) logger.debug('done')
Prepare context for pipeline run. Args: pipeline: dict. Dictionary representing the pipeline. context_in_string: string. Argument string used to initialize context. context: pypyr.context.Context. Merge any new context generated from context_in_string into this context instance. Returns: None. The context instance to...
codesearchnet
def AddEvent(self, event): self._RaiseIfNotWritable() event_data_identifier = event.GetEventDataIdentifier() if event_data_identifier: if not isinstance(event_data_identifier, identifiers.FakeIdentifier): raise IOError('Unsupported event data identifier type: {0:s}'.format( ...
Adds an event. Args: event (EventObject): event. Raises: IOError: when the storage writer is closed or if the event data identifier type is not supported. OSError: when the storage writer is closed or if the event data identifier type is not supported.
juraj-google-style
def from_int(i): point = ECPointAffine.from_int(bitcoin_curve, i) return PublicKey.from_point(point)
Generates a public key object from an integer. Note: This assumes that the upper 32 bytes of the integer are the x component of the public key point and the lower 32 bytes are the y component. Args: i (Bignum): A 512-bit integer representing the public key point on the secp256k1 curve. Returns: PublicKey: A PublicKe...
codesearchnet
def _get_device_dict_and_cores(devices): device_map = collections.defaultdict(list) num_cores = 0 for device in devices: match = _TPU_DEVICE_REGEX.match(device.name) if match: host_id = match.group('host_id') core_id = match.group('core_id') device_map[hos...
Returns a dict of hosts to cores and total cores given devices names. Returns a namedtuple with two attributes: device_map: A map of host_ids to a list of core_ids. total_cores: The total number of cores within the TPU system. Args: devices: A list of devices returned by session.list_devices()
github-repos
def get_markdown_files(self, dir_): md_files = OrderedSet() for (root, _, files) in os.walk(dir_): for name in files: split = os.path.splitext(name) if (len(split) == 1): continue if (split[1] in ('.markdown', '.md', '.yaml')): md_files...
Get all the markdown files in a folder, recursively Args: dir_: str, a toplevel folder to walk.
codesearchnet
def annotate(self, framedata): for artist in self.annotation_artists: artist.remove() self.annotation_artists = [] for annotation in self.annotations: if (annotation[2] > framedata): return if (annotation[2] == framedata): pos = annotation[0:2] sha...
Annotates the processed axis with given annotations for the provided framedata. Args: framedata: The current frame number.
codesearchnet
def outgoing_edges(self, node): edges = self.edges() out_edges = [] for out_node, in_node in edges: if node is out_node: out_edges.append((out_node, in_node)) return tuple(out_edges)
Returns a ``tuple`` of outgoing edges for a **node object**. Arguments: - node(``object``) **node object** present in the graph to be queried for outgoing edges.
juraj-google-style
def is_artifact_optional(chain, task_id, path): upstream_artifacts = chain.task['payload'].get('upstreamArtifacts', []) optional_artifacts_per_task_id = get_optional_artifacts_per_task_id(upstream_artifacts) return (path in optional_artifacts_per_task_id.get(task_id, []))
Tells whether an artifact is flagged as optional or not. Args: chain (ChainOfTrust): the chain of trust object task_id (str): the id of the aforementioned task Returns: bool: True if artifact is optional
codesearchnet
def remove(self, force=False): return self.client.api.remove_volume(self.id, force=force)
Remove this volume. Args: force (bool): Force removal of volumes that were already removed out of band by the volume driver plugin. Raises: :py:class:`docker.errors.APIError` If volume failed to remove.
codesearchnet
def cv_squared(x): epsilon = 1e-10 float_size = tf.to_float(tf.size(x)) + epsilon mean = tf.reduce_sum(x) / float_size variance = tf.reduce_sum(tf.squared_difference(x, mean)) / float_size return variance / (tf.square(mean) + epsilon)
The squared coefficient of variation of a sample. Useful as a loss to encourage a positive distribution to be more uniform. Epsilons added for numerical stability. Returns 0 for an empty Tensor. Args: x: a `Tensor`. Returns: a `Scalar`.
juraj-google-style
def create_transformation(self, rotation=None, translation=None): mat = None if rotation is not None: mat = Matrix44.from_eulers(Vector3(rotation)) if translation is not None: trans = matrix44.create_from_translation(Vector3(translation)) if mat is N...
Creates a transformation matrix woth rotations and translation. Args: rotation: 3 component vector as a list, tuple, or :py:class:`pyrr.Vector3` translation: 3 component vector as a list, tuple, or :py:class:`pyrr.Vector3` Returns: A 4x4 matrix as a :py:class:`numpy.array`
juraj-google-style
def zero(duration: int, name: str = None) -> SamplePulse: return _sampled_zero_pulse(duration, name=name)
Generates zero-sampled `SamplePulse`. Args: duration: Duration of pulse. Must be greater than zero. name: Name of pulse.
juraj-google-style
def _validate_bn_layer(self, layer): if (not isinstance(layer, tf.keras.layers.BatchNormalization) and not isinstance(layer, tf.compat.v1.layers.BatchNormalization)): raise ValueError( "batchnorm_layer must be an instance of BatchNormalization layer.") if layer.renorm: raise V...
Check for valid BatchNormalization layer. Args: layer: Instance of `tf.layers.BatchNormalization`. Raises: ValueError: If batchnorm_layer argument is not an instance of `tf.layers.BatchNormalization`, or if `batchnorm_layer.renorm=True` or if `batchnorm_layer.virtual_batch_size` is specified.
juraj-google-style
def quarter_ellipsis_functions(xx, yy): npxx = np.array(xx) npyy = np.array(yy) if np.any(npxx == npyy): raise RuntimeError('Invalid points for quarter_ellipsis_functions') if np.all(npxx < npyy) or np.all(npxx > npyy): if npxx[0] < npyy[0]: p1 = npxx p2 = np...
Method that creates two quarter-ellipse functions based on points xx and yy. The ellipsis is supposed to be aligned with the axes. The two ellipsis pass through the two points xx and yy. Args: xx: First point yy: Second point Returns: A dictionary with the lower and upper quarter ellipsis functions.
juraj-google-style
def get_registration_id_info(self, registration_id): response = self.registration_info_request(registration_id) if response.status_code == 200: return response.json() return None
Returns details related to a registration id if it exists otherwise return None Args: registration_id: id to be checked Returns: dict: info about registration id None: if id doesn't exist
juraj-google-style
def deploy(target): if (not os.getenv(CIRCLECI_ENV_VAR)): raise EnvironmentError('Must be on CircleCI to run this script') current_branch = os.getenv('CIRCLE_BRANCH') if ((target == 'PROD') and (current_branch != 'master')): raise EnvironmentError(f'Refusing to deploy to production from bran...
Deploys the package and documentation. Proceeds in the following steps: 1. Ensures proper environment variables are set and checks that we are on Circle CI 2. Tags the repository with the new version 3. Creates a standard distribution and a wheel 4. Updates version.py to have the proper version 5. Commits the ChangeL...
codesearchnet
def recalculate_concepts(self, concepts, lang=None): if (len(concepts) == 0): return if (lang is None): items = Concept.objects.get_concept_item_mapping(concepts=Concept.objects.filter(pk__in=set(flatten(concepts.values())))) else: items = Concept.objects.get_concept_item_mapping(lan...
Recalculated given concepts for given users Args: concepts (dict): user id (int -> set of concepts to recalculate) lang(Optional[str]): language used to get items in all concepts (cached). Defaults to None, in that case are get items only in used concepts
codesearchnet
def filter(self, nodes): filtered_dag = DAG() for node in nodes: filtered_dag.add_node_if_not_exists(node) for edge in self.all_downstreams(node): filtered_dag.add_node_if_not_exists(edge) for (node, edges) in self.graph.items(): if (node in filtered_dag.graph): ...
Returns a new DAG with only the given nodes and their dependencies. Args: nodes (list): The nodes you are interested in. Returns: :class:`stacker.dag.DAG`: The filtered graph.
codesearchnet
def configure_sbi(self, sbi_config: dict, schema_path: str = None): if not self.active: raise RuntimeError("Unable to add SBIs to inactive subarray!") sbi_config['subarray_id'] = self._id sbi = SchedulingBlockInstance.from_config(sbi_config, schema_path) self._add_sb...
Add a new SBI to the database associated with this subarray. Args: sbi_config (dict): SBI configuration. schema_path (str, optional): Path to the SBI config schema.
juraj-google-style
def load(self, file_name): new_rundata = self.loader(file_name) new_rundata = self.inspect(new_rundata) return new_rundata
Load a raw data-file Args: file_name (path) Returns: loaded test
juraj-google-style
def delete(filething): t = OggTheora(filething) filething.fileobj.seek(0) t.delete(filething)
delete(filething) Arguments: filething (filething) Raises: mutagen.MutagenError Remove tags from a file.
juraj-google-style
def Validate(self, value): if value is None: return None if not isinstance(value, self.rdfclass): try: r = self.rdfclass() r.FromDict(value) return r except (AttributeError, TypeError, rdfvalue.InitializeError): raise Type...
Validate the value. Args: value: Value is expected to be a dict-like object that a given RDFStruct can be initialized from. Raises: TypeValueError: If the value is not a valid dict-like object that a given RDFStruct can be initialized from. Returns: A valid instance of self.rdfclass or None.
juraj-google-style
def get_value(data, key): ref = data try: for subkey in key.split('.'): if isinstance(ref, dict): ref = ref[subkey] else: print('CRITICAL: Cannot use subkey %s on non-dictionary element' % subkey) return None return ref...
Follow the dot notation to get the proper field, then perform the action Args: data: the data as a dictionary (required to be a dictionary) key: the key (as dot notation) into the data that gives the field (IP.src) Returns: the value of the field(subfield) if it exist, otherwise None
juraj-google-style
def get(self, key, default=None): return self._fetch_cmd(b'get', [key], False).get(key, default)
The memcached "get" command, but only for one key, as a convenience. Args: key: str, see class docs for details. default: value that will be returned if the key was not found. Returns: The value for the key, or default if the key wasn't found.
codesearchnet
def structure_2_lmpdata(structure, ff_elements=None, atom_style='charge'): s = structure.get_sorted_structure() (a, b, c) = s.lattice.abc m = s.lattice.matrix xhi = a xy = np.dot(m[1], (m[0] / xhi)) yhi = np.sqrt(((b ** 2) - (xy ** 2))) xz = np.dot(m[2], (m[0] / xhi)) yz = ((np.dot(m[1],...
Converts a structure to a LammpsData object with no force field parameters and topologies. Args: structure (Structure): Input structure. ff_elements ([str]): List of strings of elements that must be present due to force field settings but not necessarily in the structure. Default to None. atom_style (str): Choose betw...
codesearchnet
def get_metric(name, constructor, *args, **kwargs): metric = _registered_metrics.get(name) if metric is not None: return metric else: return constructor(name, *args, **kwargs)
Return an existing metric or create a new one for the given name. Args: name: The name of the metric. constructor: A class to instantiate if a new metric is required. *args: Additional positional args to pass to the constructor. **kwargs: Keyword args for the constructor. Returns: The current metric registered to nam...
github-repos
def _translate_name(name): underscored = inflection.underscore(name) dasherized = inflection.dasherize(underscored) words = dasherized.split('-') last_word = words.pop() words.append(inflection.pluralize(last_word)) return '-'.join(words)
Translate the class name to the API endpoint. For example, Car would become cars, FastCar would become fast-cars. Args: name (string): Camel case name (singular) Returns: string: A pluraised, dasherized string.
codesearchnet
def resize(self, container, height, width): params = {'h': height, 'w': width} url = self._url("/containers/{0}/resize", container) res = self._post(url, params=params) self._raise_for_status(res)
Resize the tty session. Args: container (str or dict): The container to resize height (int): Height of tty session width (int): Width of tty session Raises: :py:class:`docker.errors.APIError` If the server returns an error.
juraj-google-style
def GetValueLength(rd, pos): rd = bytearray(rd) key = rd[pos] if (key == LONG_ITEM_ENCODING): if ((pos + 1) < len(rd)): return (3, rd[(pos + 1)]) else: raise errors.HidError('Malformed report descriptor') else: code = (key & 3) if (code <= 2): ...
Get value length for a key in rd. For a key at position pos in the Report Descriptor rd, return the length of the associated value. This supports both short and long format values. Args: rd: Report Descriptor pos: The position of the key in rd. Returns: (key_size, data_len) where key_size is the number of bytes occ...
codesearchnet
def on_message(self, message): try: self.log.debug("Got message %s", message) d = json_decode(message) response = deserialize_object(d, Response) if isinstance(response, (Return, Error)): request = self._request_lookup.pop(respons...
Pass response from server to process receive queue Args: message(str): Received message
juraj-google-style
def __init__(self, initializer=None, age=None, base="aff4:/flows", queue=DEFAULT_FLOW_QUEUE, flow_name=None): if initializer is None: if flow_name is None: flow_name = random.UInt32() if isinstance(flow_name,...
Constructor. Args: initializer: A string or another RDFURN. age: The age of this entry. base: The base namespace this session id lives in. queue: The queue to use. flow_name: The name of this flow or its random id. Raises: InitializeError: The given URN cannot be converted to a SessionID.
juraj-google-style
def NewFromJSON(data): return Comment( body=data.get('body', None), posted_at=data.get('posted_at', None), user=User.NewFromJSON(data.get('user', None)) )
Create a new Comment instance from a JSON dict. Args: data (dict): JSON dictionary representing a Comment. Returns: A Comment instance.
juraj-google-style
def from_coffeescript(cls, func, v_func, args={}): compiled = nodejs_compile(func, lang='coffeescript', file='???') if ('error' in compiled): raise CompilationError(compiled.error) v_compiled = nodejs_compile(v_func, lang='coffeescript', file='???') if ('error' in v_compiled): raise Comp...
Create a ``CustomJSTransform`` instance from a pair of CoffeeScript snippets. The function bodies are translated to JavaScript functions using node and therefore require return statements. The ``func`` snippet namespace will contain the variable ``x`` (the untransformed value) at render time. The ``v_func`` snippet na...
codesearchnet
def GenerateDateTripsDeparturesList(self, date_start, date_end): service_id_to_trips = defaultdict(lambda: 0) service_id_to_departures = defaultdict(lambda: 0) for trip in self.GetTripList(): headway_start_times = trip.GetFrequencyStartTimes() if headway_start_times: trip_runs = le...
Return a list of (date object, number of trips, number of departures). The list is generated for dates in the range [date_start, date_end). Args: date_start: The first date in the list, a date object date_end: The first date after the list, a date object Returns: a list of (date object, number of trips, number of de...
juraj-google-style
def __init__(self, config=None): self.driver = get_database_instance(config) self.logger = logging.getLogger('Plugin') logging.basicConfig(level=logging.INFO)
Initialize a :class:`~.Plugin` instance and connect to MongoDB. Args: *nodes (str): One or more URLs of MongoDB nodes to connect to as the persistence layer
juraj-google-style
def state_range_type(self) -> Sequence[str]: fluents = self.domain.state_fluents ordering = self.domain.state_fluent_ordering return self._fluent_range_type(fluents, ordering)
The range type of each state fluent in canonical order. Returns: Sequence[str]: A tuple of range types representing the range of each fluent.
codesearchnet
def _percentile(self, values, percent, key=lambda x: x): vals = sorted(values) k = (len(vals) - 1) * (percent / 100) f = math.floor(k) c = math.ceil(k) if f == c: return key(vals[int(k)]) d0 = key(vals[int(f)]) * (c - k) d1 = key(vals[int(c)])...
Find the percentile of a list of values. Args: values: A list of values for which percentiles are desired percent: A float value from 0 to 100 representing the requested percentile. key: optional key function to compute value from each element of N. Return: The percentile of the values
juraj-google-style
def load_function_def_library(library, saved_object_graph=None, load_shared_name_suffix=None, wrapper_function=None): library_function_names = set((fdef.signature.name for fdef in library.function)) functions = {} renamed_functions = {} if ops.executing_eagerly_outside_functions(): graph = ops.G...
Load a set of functions as concrete functions without captured inputs. Functions names are manipulated during load such that they do not overlap with previously created ones. Gradients are re-registered under new names. Ops that reference the gradients are updated to reflect the new registered names. Args: library: ...
github-repos
def rename(self, source_file_names, destination_file_names): if not len(source_file_names) == len(destination_file_names): message = 'Unable to rename unequal number of sources and destinations.' raise BeamIOError(message) src_dest_pairs = list(zip(source_file_names, destination_file_names)) ...
Rename the files at the source list to the destination list. Source and destination lists should be of the same size. Args: source_file_names: List of file paths that need to be moved destination_file_names: List of destination_file_names for the files Raises: ``BeamIOError``: if any of the rename operations fail
github-repos
def get_by_uri(self, uri): self._helper.validate_resource_uri(uri) data = self._helper.do_get(uri) if data: new_resource = self.new(self._connection, data) else: new_resource = None return new_resource
Retrieves a resource by its URI Args: uri: URI of the resource Returns: Resource object
juraj-google-style
def get_provider_fn_decorations(provider_fn, default_arg_names): if hasattr(provider_fn, _IS_WRAPPER_ATTR): provider_decorations = getattr(provider_fn, _PROVIDER_DECORATIONS_ATTR) if provider_decorations: expanded_provider_decorations = [] for provider_decoration in prov...
Retrieves the provider method-relevant info set by decorators. If any info wasn't set by decorators, then defaults are returned. Args: provider_fn: a (possibly decorated) provider function default_arg_names: the (possibly empty) arg names to use if none were specified via @provides() Returns: a sequence of ProviderDe...
juraj-google-style
def shape(self): raise NotImplementedError
The `TensorShape` of this variable. Returns: A `TensorShape`.
github-repos
def expect_no_raises(message=None, extras=None): try: yield except Exception as e: e_record = records.ExceptionRecord(e) if extras: e_record.extras = extras msg = message or 'Got an unexpected exception' details = '%s: %s' % (msg, e_record.details) log...
Expects no exception is raised in a context. If the expectation is not met, the test is marked as fail after its execution finishes. A default message is added to the exception `details`. Args: message: string, custom message to add to exception's `details`. extras: An optional field for extra information to be incl...
github-repos
def owner_set(self): owners = set() if self.has_attr() or self.has_subscript(): owners.add(self.parent) owners.update(self.parent.owner_set) return owners
Returns all the symbols (simple or composite) that own this QN. In other words, if this symbol was modified, the symbols in the owner set may also be affected. Examples: 'a.b[c.d]' has two owners, 'a' and 'a.b'
github-repos