code stringlengths 20 4.93k | docstring stringlengths 33 1.27k | source stringclasses 3
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def __init__(self, cache_folder, genome_build):
self.api_version = ('1')
self.genome_build = genome_build
self.today = datetime.today()
if not os.path.exists(cache_folder):
os.mkdir(cache_folder)
path = os.path.join(cache_folder, "e... | initialise the class with the local cache folder
Args:
cache_folder: path to the cache | juraj-google-style |
def get_historical_data(nmr_problems):
observations = np.tile(np.array([[10, 256, 202, 97]]), (nmr_problems, 1))
nmr_tanks_ground_truth = (np.ones((nmr_problems,)) * 276)
return (observations, nmr_tanks_ground_truth) | Get the historical tank data.
Args:
nmr_problems (int): the number of problems
Returns:
tuple: (observations, nmr_tanks_ground_truth) | codesearchnet |
def force_rerun(flag, outfile):
if flag:
return True
elif ((not flag) and (not op.exists(outfile))):
return True
elif ((not flag) and (not is_non_zero_file(outfile))):
return True
else:
return False | Check if we should force rerunning of a command if an output file exists.
Args:
flag (bool): Flag to force rerun.
outfile (str): Path to output file which may already exist.
Returns:
bool: If we should force rerunning of a command
Examples:
>>> force_rerun(flag=True, outfile='/not/existing/file.txt')
True
>>> force... | codesearchnet |
def quantile_for_single_value(self, **kwargs):
if self._is_transposed:
kwargs['axis'] = (kwargs.get('axis', 0) ^ 1)
return self.transpose().quantile_for_single_value(**kwargs)
axis = kwargs.get('axis', 0)
q = kwargs.get('q', 0.5)
assert (type(q) is float)
def quantile_builder(df, **... | Returns quantile of each column or row.
Returns:
A new QueryCompiler object containing the quantile of each column or row. | codesearchnet |
def guaranteed_no_diff(modular_file_path, dependencies, models_in_diff):
model_name = modular_file_path.rsplit('modular_', 1)[1].replace('.py', '')
if model_name in models_in_diff:
return False
for dep in dependencies[modular_file_path]:
dependency_model_name = dep.split('.')[-2]
if ... | Returns whether it is guaranteed to have no differences between the modular file and the modeling file.
Model is in the diff -> not guaranteed to have no differences
Dependency is in the diff -> not guaranteed to have no differences
Otherwise -> guaranteed to have no differences
Args:
modular_file_path: The path to t... | github-repos |
def set_disk_usage(self, total_size, path=None):
if path is None:
path = self.root.name
mount_point = self._mount_point_for_path(path)
if (mount_point['total_size'] is not None and
mount_point['used_size'] > total_size):
self.raise_io_error(errno.... | Changes the total size of the file system, preserving the used space.
Example usage: set the size of an auto-mounted Windows drive.
Args:
total_size: The new total size of the filesystem in bytes.
path: The disk space is changed for the file system device where
`path` resides.
Defaults to the root path (e.g. '/' on U... | juraj-google-style |
def movies_box_office(self, **kwargs):
path = self._get_path('movies_box_office')
response = self._GET(path, kwargs)
self._set_attrs_to_values(response)
return response | Gets the top box office earning movies from the API.
Sorted by most recent weekend gross ticket sales.
Args:
limit (optional): limits the number of movies returned, default=10
country (optional): localized data for selected country, default="us"
Returns:
A dict respresentation of the JSON returned from the API. | codesearchnet |
def get_data(self, url, *args, **kwargs):
res = self._conn.get(url, headers=self._prepare_headers(**kwargs))
if res.status_code == 200:
return res.text
else:
return None | Gets data from url as text
Returns content under the provided url as text
Args:
**url**: address of the wanted data
.. versionadded:: 0.3.2
**additional_headers**: (optional) Additional headers
to be used with request
Returns:
string | juraj-google-style |
def base_multinode_parser():
base_parser = ArgumentParser(add_help=False)
base_parser.add_argument('urls', type=str, nargs='+', help="The URLs of the validator's REST APIs of interest, separated by commas or spaces. (no default)")
base_parser.add_argument('--users', type=str, action='append', metavar='USERN... | Creates a parser with arguments specific to sending HTTP requests
to multiple REST APIs.
Returns:
{ArgumentParser}: Base parser with default HTTP args | codesearchnet |
def _get_flags(osm_obj):
flags = []
if osm_obj.visible:
flags.append('visible')
if osm_obj.user:
flags.append('user: %s' % osm_obj.user)
if osm_obj.timestamp:
flags.append('timestamp: %s' % osm_obj.timestamp.isoformat())
if osm_obj.tags:
flags.append(', '.join('%... | Create element independent flags output.
Args:
osm_obj (Node): Object with OSM-style metadata
Returns:
list: Human readable flags output | juraj-google-style |
def _ConstructAndTestGradient(self, pool_func, input_sizes, output_sizes, window_rows, window_cols, row_stride, col_stride, padding, data_format, use_gpu, x_init_value=None):
assert input_sizes[0] == output_sizes[0]
assert input_sizes[3] == output_sizes[3]
total_size = 1
for s in input_sizes:
to... | Verifies the gradients of the max or avg pooling function.
Args:
pool_func: Function to be called, co.MaxPool, co.AvgPool,
or the Lua version.
input_sizes: Input tensor dimensions.
output_sizes: Output tensor dimensions.
window_rows: kernel size in row dim
window_cols: kernel size in col dim
row_stride: Row Stride.
co... | github-repos |
def Reference(uri, meaning=None):
attrib = {'uri': uri}
if meaning is not None:
attrib['meaning'] = meaning
return objectify.Element('Reference', attrib) | Represents external information, typically original obs data and metadata.
Args:
uri(str): Uniform resource identifier for external data, e.g. FITS file.
meaning(str): The nature of the document referenced, e.g. what
instrument and filter was used to create the data? | juraj-google-style |
def _parse_schema_resource(info):
if ('fields' not in info):
return ()
schema = []
for r_field in info['fields']:
name = r_field['name']
field_type = r_field['type']
mode = r_field.get('mode', 'NULLABLE')
description = r_field.get('description')
sub_fields = _... | Parse a resource fragment into a schema field.
Args:
info: (Mapping[str->dict]): should contain a "fields" key to be parsed
Returns:
(Union[Sequence[:class:`google.cloud.bigquery.schema.SchemaField`],None])
a list of parsed fields, or ``None`` if no "fields" key found. | codesearchnet |
def SetValue(self, value, raise_on_error=True):
type_mappings = [(Text, "string"), (bytes, "data"), (bool, "boolean"),
(int, "integer"), (long, "integer"), (dict, "dict"),
(float, "float")]
if value is None:
self.none = "None"
elif isinstance(value, rdf... | Receives a value and fills it into a DataBlob.
Args:
value: value to set
raise_on_error: if True, raise if we can't serialize. If False, set the
key to an error string.
Returns:
self
Raises:
TypeError: if the value can't be serialized and raise_on_error is True | juraj-google-style |
def remove_profile(self, profile=None):
with self.db:
return self.db.remove(self.query.profile == profile) | Remove profile from credentials file.
Args:
profile (str): Credentials profile to remove.
Returns:
list: List of affected document IDs. | juraj-google-style |
def protect(self, developers_can_push=False, developers_can_merge=False, **kwargs):
id = self.get_id().replace('/', '%2F')
path = ('%s/%s/protect' % (self.manager.path, id))
post_data = {'developers_can_push': developers_can_push, 'developers_can_merge': developers_can_merge}
self.manager.gitlab.http_pu... | Protect the branch.
Args:
developers_can_push (bool): Set to True if developers are allowed
to push to the branch
developers_can_merge (bool): Set to True if developers are allowed
to merge to the branch
**kwargs: Extra options to send to the server (e.g. sudo)
Raises:
GitlabAuthenticationError: If authentication is ... | codesearchnet |
def get_paths(self):
paths = []
for (key, child) in six.iteritems(self):
if (isinstance(child, TreeMap) and child):
for path in child.get_paths():
path.insert(0, key)
paths.append(path)
else:
paths.append([key])
return paths | Get all paths from the root to the leaves.
For example, given a chain like `{'a':{'b':{'c':None}}}`,
this method would return `[['a', 'b', 'c']]`.
Returns:
A list of lists of paths. | codesearchnet |
def load_dot_env_file(dot_env_path):
if (not os.path.isfile(dot_env_path)):
return {}
logger.log_info('Loading environment variables from {}'.format(dot_env_path))
env_variables_mapping = {}
with io.open(dot_env_path, 'r', encoding='utf-8') as fp:
for line in fp:
if ('=' in l... | load .env file.
Args:
dot_env_path (str): .env file path
Returns:
dict: environment variables mapping
{
"UserName": "debugtalk",
"Password": "123456",
"PROJECT_KEY": "ABCDEFGH"
}
Raises:
exceptions.FileFormatError: If .env file format is invalid. | codesearchnet |
def get_meshes_vec(step, var):
if step.geom.twod_xz:
xmesh, ymesh = step.geom.x_mesh[:, 0, :], step.geom.z_mesh[:, 0, :]
vec1 = step.fields[var + '1'][:, 0, :, 0]
vec2 = step.fields[var + '3'][:, 0, :, 0]
elif step.geom.cartesian and step.geom.twod_yz:
xmesh, ymesh = step.ge... | Return vector field components along with coordinates meshes.
Only works properly in 2D geometry.
Args:
step (:class:`~stagpy.stagyydata._Step`): a step of a StagyyData
instance.
var (str): vector field name.
Returns:
tuple of :class:`numpy.array`: xmesh, ymesh, fldx, fldy
2D arrays containing respectively the x posi... | juraj-google-style |
def option(self, key, value=None, **kwargs):
if not isinstance(self._container, Section):
raise ValueError("Options can only be added inside a section!")
option = Option(key, value, container=self._container, **kwargs)
option.value = value
self._container.structure.i... | Creates a new option inside a section
Args:
key (str): key of the option
value (str or None): value of the option
**kwargs: are passed to the constructor of :class:`Option`
Returns:
self for chaining | juraj-google-style |
def truncated_normal_log_likelihood(params, low, high, data):
mu = params[0]
sigma = params[1]
if (sigma == 0):
return np.inf
ll = np.sum(norm.logpdf(data, mu, sigma))
ll -= (len(data) * np.log((norm.cdf(high, mu, sigma) - norm.cdf(low, mu, sigma))))
return (- ll) | Calculate the log likelihood of the truncated normal distribution.
Args:
params: tuple with (mean, std), the parameters under which we evaluate the model
low (float): the lower truncation bound
high (float): the upper truncation bound
data (ndarray): the one dimension list of data points for which we want to calculate... | codesearchnet |
def __init__(self, maxsize, out_deque=None, **kw):
super(DequeOutLRUCache, self).__init__(maxsize, **kw)
if out_deque is None:
out_deque = collections.deque()
elif not isinstance(out_deque, collections.deque):
raise ValueError(u'out_deque should be collections.de... | Constructor.
Args:
maxsize (int): the maximum number of entries in the queue
out_deque :class:`collections.deque`: a `deque` in which to add items
that expire from the cache
**kw: the other keyword args supported by constructor to
:class:`cachetools.LRUCache`
Raises:
ValueError: if out_deque is not a collections.dequ... | juraj-google-style |
def alternative_titles(self, **kwargs):
path = self._get_id_path('alternative_titles')
response = self._GET(path, kwargs)
self._set_attrs_to_values(response)
return response | Get the alternative titles for a specific movie id.
Args:
country: (optional) ISO 3166-1 code.
append_to_response: (optional) Comma separated, any movie method.
Returns:
A dict representation of the JSON returned from the API. | juraj-google-style |
def get_gene_info(ensembl_ids=None, hgnc_symbols=None):
uniq_ensembl_ids = set(ensembl_id for ensembl_id in (ensembl_ids or []))
uniq_hgnc_symbols = set(hgnc_symbol for hgnc_symbol in (hgnc_symbols or []))
genes = []
gene_data = []
if uniq_ensembl_ids:
for ensembl_id in uniq_ensemb... | Return the genes info based on the transcripts found
Args:
ensembl_ids (Optional[list]): list of Ensembl gene ids
hgnc_symbols (Optional[list]): list of HGNC gene symbols
Returns:
iterable: an iterable with `Gene` objects | juraj-google-style |
def _WriteRow(self, output_writer, values):
maximum_row_width = ((self._MAXIMUM_WIDTH - self._column_width) - 3)
primary_format_string = '{{0:>{0:d}s}} : {{1:s}}\n'.format(self._column_width)
secondary_format_string = '{{0:<{0:d}s}}{{1:s}}\n'.format((self._column_width + 3))
if isinstance(values[1], py2... | Writes a row of values aligned to the column width.
Args:
output_writer (OutputWriter): output writer.
values (list[object]): values. | codesearchnet |
def DeregisterMountPoint(cls, mount_point):
if (mount_point not in cls._mount_points):
raise KeyError('Mount point: {0:s} not set.'.format(mount_point))
del cls._mount_points[mount_point] | Deregisters a path specification mount point.
Args:
mount_point (str): mount point identifier.
Raises:
KeyError: if the corresponding mount point is not set. | codesearchnet |
def run_multiple_processes(args_list: List[List[str]], die_on_failure: bool=True) -> None:
for procargs in args_list:
start_process(procargs)
wait_for_processes(die_on_failure=die_on_failure) | Fire up multiple processes, and wait for them to finihs.
Args:
args_list: command arguments for each process
die_on_failure: see :func:`wait_for_processes` | codesearchnet |
def ask_when_work_is_populated(self, work):
work.read_all_from_datastore()
if work.work:
print('Work is already written to datastore.\nIf you continue these data will be overwritten and possible corrupted.')
inp = input_str('Do you want to continue? (type "yes" without quotes to confirm): ')
... | When work is already populated asks whether we should continue.
This method prints warning message that work is populated and asks
whether user wants to continue or not.
Args:
work: instance of WorkPiecesBase
Returns:
True if we should continue and populate datastore, False if we should stop | codesearchnet |
def stats(path, hash_type='sha256', follow_symlinks=True):
if (not os.path.exists(path)):
raise CommandExecutionError('Path not found: {0}'.format(path))
if (follow_symlinks and (sys.getwindowsversion().major >= 6)):
path = _resolve_symlink(path)
pstat = os.stat(path)
ret = {}
ret['i... | Return a dict containing the stats about a given file
Under Windows, `gid` will equal `uid` and `group` will equal `user`.
While a file in Windows does have a 'primary group', this rarely used
attribute generally has no bearing on permissions unless intentionally
configured and is only used to support Unix compatibil... | codesearchnet |
def json_compat_obj_encode(data_type, obj, caller_permissions=None, alias_validators=None, old_style=False, for_msgpack=False, should_redact=False):
serializer = StoneToPythonPrimitiveSerializer(caller_permissions, alias_validators, for_msgpack, old_style, should_redact)
return serializer.encode(data_type, obj) | Encodes an object into a JSON-compatible dict based on its type.
Args:
data_type (Validator): Validator for obj.
obj (object): Object to be serialized.
caller_permissions (list): The list of raw-string caller permissions
with which to serialize.
Returns:
An object that when passed to json.dumps() will produce a strin... | codesearchnet |
def like_shared_file(self, sharekey=None):
if not sharekey:
raise Exception(
"You must specify a sharekey of the file you"
"want to 'like'.")
endpoint = '/api/sharedfile/{sharekey}/like'.format(sharekey=sharekey)
data = self._make_request("P... | 'Like' a SharedFile. mlkshk doesn't allow you to unlike a
sharedfile, so this is ~~permanent~~.
Args:
sharekey (str): Sharekey for the file you want to 'like'.
Returns:
Either a SharedFile on success, or an exception on error. | juraj-google-style |
def delete_resource_group(access_token, subscription_id, rgname):
endpoint = ''.join([get_rm_endpoint(), '/subscriptions/', subscription_id, '/resourcegroups/', rgname, '?api-version=', RESOURCE_API])
return do_delete(endpoint, access_token) | Delete the named resource group.
Args:
access_token (str): A valid Azure authentication token.
subscription_id (str): Azure subscription id.
rgname (str): Azure resource group name.
Returns:
HTTP response. | codesearchnet |
def generate_private_key(self):
random_string = base64.b64encode(os.urandom(4096)).decode('utf-8')
binary_data = bytes(random_string, 'utf-8')
hash_object = hashlib.sha256(binary_data)
message_digest_bin = hash_object.digest()
message_digest_hex = binascii.hexlify(message_digest_bin)
return mess... | Generates a private key based on the password.
SHA-256 is a member of the SHA-2 cryptographic hash functions designed by
the NSA. SHA stands for Secure Hash Algorithm. The password is converted
to bytes and hashed with SHA-256. The binary output is converted to a hex
representation.
Args:
data (str): The data to be h... | codesearchnet |
def __init__(self, unexpected_method, expected):
Error.__init__(self)
self._unexpected_method = unexpected_method
self._expected = expected | Init exception.
Args:
# unexpected_method: MockMethod that was called but was not at the head of
# the expected_method queue.
# expected: MockMethod or UnorderedGroup the method should have
# been in.
unexpected_method: MockMethod
expected: MockMethod or UnorderedGroup | juraj-google-style |
def RetrievePluginAsset(self, plugin_name, asset_name):
return plugin_asset_util.RetrieveAsset(self.path, plugin_name, asset_name) | Return the contents of a given plugin asset.
Args:
plugin_name: The string name of a plugin.
asset_name: The string name of an asset.
Returns:
The string contents of the plugin asset.
Raises:
KeyError: If the asset is not available. | juraj-google-style |
def watch(self, key, pipeline=False):
if pipeline:
self._pipeline.watch(key)
else:
self._db.watch(key) | Watch the given key.
Marks the given key to be watch for conditional execution
of a transaction.
Args:
key (str): Key that needs to be watched
pipeline (bool): True, start a transaction block. Default false. | codesearchnet |
def _prepare_lambada_data(tmp_dir, data_dir, vocab_size, vocab_filename):
if not tf.gfile.Exists(data_dir):
tf.gfile.MakeDirs(data_dir)
file_path = generator_utils.maybe_download(tmp_dir, _TAR, _URL)
tar_all = tarfile.open(file_path)
tar_all.extractall(tmp_dir)
tar_all.close()
tar_train = tarfile.o... | Downloading and preparing the dataset.
Args:
tmp_dir: tem directory
data_dir: data directory
vocab_size: size of vocabulary
vocab_filename: name of vocab file | juraj-google-style |
def _replace_tensors_for_gradient(x, grad):
if not isinstance(x, composite_tensor.CompositeTensor):
return grad
if not isinstance(x, CompositeTensorGradientProtocol):
raise ValueError(f'Type {type(x).__name__} is not supported as a gradient source.')
composite_gradient = x.__composite_gradie... | Replaces the tensors in `x` that should be differentiated with `grad`.
Args:
x: A `Tensor` or `CompositeTensor`.
grad: A nested structure of `Tensor`, with the same structure as the value
returned by `_get_tensors_for_gradient(x)`.
Returns:
A `Tensor` or `CompositeTensor`. | github-repos |
def get_organization(self):
return hdx.data.organization.Organization.read_from_hdx(self.data['owner_org'], configuration=self.configuration) | Get the dataset's organization.
Returns:
Organization: Dataset's organization | codesearchnet |
def _run_static_range_ptq(src_saved_model_path: str, dst_saved_model_path: str, quant_opts: _QuantizationOptions, representative_dataset: Mapping[str, _RepresentativeDatasetFile], signature_def_map: _SignatureDefMap) -> None:
logging.info('Running static-range post-training quantization.')
signature_def_map_ser... | Runs static-range Post-Training Quantization.
Runs static-range PTQ for the model. Runs the calibration step with
`representative_dataset` to collect statistics required for quantization. This
produces the quantized GraphDef along with the SignatureDefs which might have
been modified according to the changes in the gr... | github-repos |
def psd(data, dt, ndivide=1, window=hanning, overlap_half=False):
logger = getLogger('decode.utils.ndarray.psd')
if overlap_half:
step = int((len(data) / (ndivide + 1)))
size = (step * 2)
else:
step = int((len(data) / ndivide))
size = step
if (bin(len(data)).count('1') !=... | Calculate power spectrum density of data.
Args:
data (np.ndarray): Input data.
dt (float): Time between each data.
ndivide (int): Do averaging (split data into ndivide, get psd of each, and average them).
ax (matplotlib.axes): Axis you want to plot on.
doplot (bool): Plot how averaging works.
overlap_half (bool): Spli... | codesearchnet |
def observe_reward_value(self, state_key, action_key):
x, y = state_key
if self.__map_arr[y][x] == self.__end_point_label:
return 100.0
elif self.__map_arr[y][x] == self.__start_point_label:
return 0.0
elif self.__map_arr[y][x] == self.__wall_label:
... | Compute the reward value.
Args:
state_key: The key of state.
action_key: The key of action.
Returns:
Reward value. | juraj-google-style |
def edgelist_to_adjacency(edgelist):
adjacency = dict()
for u, v in edgelist:
if u in adjacency:
adjacency[u].add(v)
else:
adjacency[u] = {v}
if v in adjacency:
adjacency[v].add(u)
else:
adjacency[v] = {u}
return adjacency | Converts an iterator of edges to an adjacency dict.
Args:
edgelist (iterable):
An iterator over 2-tuples where each 2-tuple is an edge.
Returns:
dict: The adjacency dict. A dict of the form {v: Nv, ...} where v is a node in a graph and
Nv is the neighbors of v as an set. | juraj-google-style |
def get_available_transcript_languages(video_id):
available_languages = VideoTranscript.objects.filter(video__edx_video_id=video_id).values_list('language_code', flat=True)
return list(available_languages) | Get available transcript languages
Arguments:
video_id(unicode): An id identifying the Video.
Returns:
A list containing transcript language codes for the Video. | codesearchnet |
def __discovery_doc_descriptor(self, services, hostname=None):
merged_api_info = self.__get_merged_api_info(services)
descriptor = self.get_descriptor_defaults(merged_api_info, hostname=hostname)
description = merged_api_info.description
if ((not description) and (len(services) == 1)):
descripti... | Builds a discovery doc for an API.
Args:
services: List of protorpc.remote.Service instances implementing an
api/version.
hostname: string, Hostname of the API, to override the value set on the
current service. Defaults to None.
Returns:
A dictionary that can be deserialized into JSON in discovery doc format.
Raises... | codesearchnet |
def include_revision(revision_num, skip_factor=1.1):
if skip_factor <= 1.0:
return True
return (int(math.log1p(revision_num) / math.log(skip_factor)) != int(
math.log(revision_num + 2.0) / math.log(skip_factor))) | Decide whether to include a revision.
If the number of revisions is large, we exclude some revisions to avoid
a quadratic blowup in runtime, since the article is likely also large.
We make the ratio between consecutive included revision numbers
appproximately equal to "factor".
Args:
revision_num: an integer
skip_fa... | juraj-google-style |
def _get_tables(self, base_dir):
table_dict = {}
for table in self.metadata['tables']:
if table['use']:
relative_path = os.path.join(base_dir, self.metadata['path'], table['path'])
data_table = pd.read_csv(relative_path)
pii_fields = ... | Load the contents of meta_file and the corresponding data.
If fields containing Personally Identifiable Information are detected in the metadata
they are anonymized before asign them into `table_dict`.
Args:
base_dir(str): Root folder of the dataset files.
Returns:
dict: Mapping str -> tuple(pandas.DataFrame, dict) | juraj-google-style |
def fn(x: tuple[int]):
return x | Test function
Args:
x: The input
Returns:
The output | github-repos |
def find(self, _id, instance = None):
if instance is None:
return self.service_instance.find(_id)
else:
return self.service_binding.find(_id, instance) | Find
Args:
_id (str): instance id or binding Id
Keyword Arguments:
instance (AtlasServiceInstance.Instance): Existing instance
Returns:
AtlasServiceInstance.Instance or AtlasServiceBinding.Binding: An instance or binding. | juraj-google-style |
def hide_tool(self, context_name, tool_name):
data = self._context(context_name)
hidden_tools = data['hidden_tools']
if (tool_name not in hidden_tools):
self._validate_tool(context_name, tool_name)
hidden_tools.add(tool_name)
self._flush_tools() | Hide a tool so that it is not exposed in the suite.
Args:
context_name (str): Context containing the tool.
tool_name (str): Name of tool to hide. | codesearchnet |
def __init__(self, context_type=ContextType.PATH, debug=False):
self._selector = DefaultSelector()
self._interface = Interface()
if context_type == ContextType.UDEV:
self._udev = self._libudev.udev_new()
self._li = self._libinput.libinput_udev_create_context(
byref(self._interface), None, self._udev... | Initialize context.
Args:
context_type (~libinput.constant.ContextType): If
:attr:`~libinput.constant.ContextType.UDEV` devices are
added/removed from udev seat. If
:attr:`~libinput.constant.ContextType.PATH` devices have to be
added/removed manually.
debug (bool): If false, only errors are printed. | juraj-google-style |
def _get_predictions(self, data, break_ties='random', return_probs=False, **kwargs):
data_loader = self._create_data_loader(data)
Y_p = []
Y = []
Y_s = []
for (batch_num, data) in enumerate(data_loader):
(Xb, Yb) = data
Y.append(self._to_numpy(Yb))
if (self.config['device'] !... | Computes predictions in batch, given a labeled dataset
Args:
data: a Pytorch DataLoader, Dataset, or tuple with Tensors (X,Y):
X: The input for the predict method
Y: An [n] or [n, 1] torch.Tensor or np.ndarray of target labels
in {1,...,k}
break_ties: How to break ties when making predictions
return_probs: Return the ... | codesearchnet |
def write_to_file(src, dst):
n = 0
for block in src:
dst.write(block)
n += len(block)
return n | Write data from `src` into `dst`.
Args:
src (iterable): iterable that yields blocks of data to write
dst (file-like object): file-like object that must support
.write(block)
Returns:
number of bytes written to `dst` | codesearchnet |
def _Open(self, path_spec, mode='rb'):
if not path_spec.HasParent():
raise errors.PathSpecError(
'Unsupported path specification without parent.')
compression_method = getattr(path_spec, 'compression_method', None)
if not compression_method:
raise errors.PathSpecError(
... | Opens the file system defined by path specification.
Args:
path_spec (PathSpec): a path specification.
mode (Optional[str]): file access mode. The default is 'rb' which
represents read-only binary.
Raises:
AccessError: if the access to open the file was denied.
IOError: if the file system could not be opened.
PathSpe... | juraj-google-style |
def make_block_creator(yaml_path, filename=None):
(sections, yamlname, docstring) = Section.from_yaml(yaml_path, filename)
yamldir = os.path.dirname(yaml_path)
controller_sections = [s for s in sections if (s.section == 'controllers')]
assert (len(controller_sections) == 1), ('Expected exactly 1 control... | Make a collection function that will create a list of blocks
Args:
yaml_path (str): File path to YAML file, or a file in the same dir
filename (str): If give, use this filename as the last element in
the yaml_path (so yaml_path can be __file__)
Returns:
function: A collection function decorated with @takes. This can ... | codesearchnet |
def __init__(self, name, collections=None, capture_by_value=None, structured_input_signature=None, structured_outputs=None):
super().__init__()
self.name = name
self.inputs = []
self.outputs = []
self.control_outputs = []
self.structured_input_signature = structured_input_signature
self.stru... | Construct a new FuncGraph.
The graph will inherit its graph key, collections, seed, and distribution
strategy stack from the current context or graph.
Args:
name: the name of the function.
collections: a dictionary of collections this FuncGraph should start with.
If not specified (None), the FuncGraph will read (but ... | github-repos |
def join_pretty_tensors(tensors, output, join_function=None, name='join'):
if not tensors:
raise ValueError('pretty_tensors must be a non-empty sequence.')
with output.g.name_scope(name):
if join_function is None:
last_dim = len(tensors[0].shape) - 1
return output.with_tensor(tf.concat... | Joins the list of pretty_tensors and sets head of output_pretty_tensor.
Args:
tensors: A sequence of Layers or SequentialLayerBuilders to join.
output: A pretty_tensor to set the head with the result.
join_function: A function to join the tensors, defaults to concat on the
last dimension.
name: A name that is used for... | juraj-google-style |
def decode_terminated(data, encoding, strict=True):
codec_info = codecs.lookup(encoding)
encoding = codec_info.name
if (encoding in ('utf-8', 'iso8859-1')):
index = data.find(b'\x00')
if (index == (- 1)):
res = (data.decode(encoding), b'')
if strict:
r... | Returns the decoded data until the first NULL terminator
and all data after it.
Args:
data (bytes): data to decode
encoding (str): The codec to use
strict (bool): If True will raise ValueError in case no NULL is found
but the available data decoded successfully.
Returns:
Tuple[`text`, `bytes`]: A tuple containing the ... | codesearchnet |
def convert(self, graph_def, input_tensors, output_tensors):
self._validate_inputs(graph_def, input_tensors)
converter_kwargs = self._get_base_converter_args()
converter_kwargs.update(self._quant_mode.converter_flags())
if not self.experimental_new_converter:
logging.warning('Please consider swi... | Converts a TensorFlow GraphDef based on instance variables.
Args:
graph_def: Frozen TensorFlow GraphDef.
input_tensors: List of input tensors.
output_tensors: List of output tensors.
Returns:
The converted data in serialized format.
Raises:
ValueError:
No concrete function is specified.
Multiple concrete functions a... | github-repos |
def get_space_group_info(self, symprec=0.01, angle_tolerance=5.0):
from pymatgen.symmetry.analyzer import SpacegroupAnalyzer
a = SpacegroupAnalyzer(self, symprec=symprec, angle_tolerance=angle_tolerance)
return (a.get_space_group_symbol(), a.get_space_group_number()) | Convenience method to quickly get the spacegroup of a structure.
Args:
symprec (float): Same definition as in SpacegroupAnalyzer.
Defaults to 1e-2.
angle_tolerance (float): Same definition as in SpacegroupAnalyzer.
Defaults to 5 degrees.
Returns:
spacegroup_symbol, international_number | codesearchnet |
def random_density_matrix(length, rank=None, method='Hilbert-Schmidt', seed=None):
if (method == 'Hilbert-Schmidt'):
return __random_density_hs(length, rank, seed)
elif (method == 'Bures'):
return __random_density_bures(length, rank, seed)
else:
raise QiskitError('Error: unrecognized... | Generate a random density matrix rho.
Args:
length (int): the length of the density matrix.
rank (int or None): the rank of the density matrix. The default
value is full-rank.
method (string): the method to use.
'Hilbert-Schmidt': sample rho from the Hilbert-Schmidt metric.
'Bures': sample rho from the Bures metric.
s... | codesearchnet |
def get_coding_intervals(self, build='37', genes=None):
intervals = {}
if not genes:
genes = self.all_genes(build=build)
LOG.info("Building interval trees...")
for i,hgnc_obj in enumerate(genes):
chrom = hgnc_obj['chromosome']
start = max((hgn... | Return a dictionary with chromosomes as keys and interval trees as values
Each interval represents a coding region of overlapping genes.
Args:
build(str): The genome build
genes(iterable(scout.models.HgncGene)):
Returns:
intervals(dict): A dictionary with chromosomes as keys and overlapping genomic intervals as valu... | juraj-google-style |
def query_dns(domain, record_type, cache=None, nameservers=None, timeout=2.0):
domain = str(domain).lower()
record_type = record_type.upper()
cache_key = "{0}_{1}".format(domain, record_type)
if cache:
records = cache.get(cache_key, None)
if records:
return records
... | Queries DNS
Args:
domain (str): The domain or subdomain to query about
record_type (str): The record type to query for
cache (ExpiringDict): Cache storage
nameservers (list): A list of one or more nameservers to use
(Cloudflare's public DNS resolvers by default)
timeout (float): Sets the DNS timeout in seconds
Return... | juraj-google-style |
def hwvtep_add_rbridgeid(self, **kwargs):
name = kwargs.pop('name')
id = kwargs.pop('rb_range')
ip_args = dict(name=name, rb_add=id)
method_name = 'overlay_gateway_attach_rbridge_id_rb_add'
method_class = self._brocade_tunnels
gw_attr = getattr(method_class, meth... | Add a range of rbridge-ids
Args:
name (str): gateway-name
vlan (str): rbridge-ids range
callback (function): A function executed upon completion of the
method.
Returns:
Return value of `callback`.
Raises:
None | juraj-google-style |
def get_connection_id(self, conn_or_int_id):
key = conn_or_int_id
if isinstance(key, str):
table = self._int_connections
elif isinstance(key, int):
table = self._connections
else:
raise ArgumentError('You must supply either an int connection id or a string internal id to _get_con... | Get the connection id.
Args:
conn_or_int_id (int, string): The external integer connection id or
and internal string connection id
Returns:
dict: The context data associated with that connection or None if it cannot
be found.
Raises:
ArgumentError: When the key is not found in the list of active connections
or is in... | codesearchnet |
def allsame(list_, strict=True):
if (len(list_) == 0):
return True
first_item = list_[0]
return list_all_eq_to(list_, first_item, strict) | checks to see if list is equal everywhere
Args:
list_ (list):
Returns:
True if all items in the list are equal | codesearchnet |
def _secant_step(x1, x2, y1, y2):
x_difference = x1 - x2
y_difference = y1 - y2
return -y1 * x_difference / y_difference | Returns the step size at the current position if using the secant method.
This function is meant for exclusive use by the `_brent_loop_body` function:
- It does not guard against divisions by zero, and instead assumes that `y1`
is distinct from `y2`. The `_brent_loop_body` function guarantees this
property.
- It does ... | github-repos |
def __format__(self, format_spec='dms'):
location = [super(Trigpoint, self).__format__(format_spec), ]
if self.altitude:
location.append('alt %im' % self.altitude)
if self.name:
return '%s (%s)' % (self.name, ' '.join(location))
else:
return ... | Extended pretty printing for location strings.
Args:
format_spec (str): Coordinate formatting system to use
Returns:
str: Human readable string representation of ``Trigpoint`` object
Raises:
ValueError: Unknown value for ``format_spec`` | juraj-google-style |
def find_interface_by_mac(self, **kwargs):
mac = kwargs.pop('mac_address')
results = [x for x in self.mac_table if (x['mac_address'] == mac)]
return results | Find the interface through which a MAC can be reached.
Args:
mac_address (str): A MAC address in 'xx:xx:xx:xx:xx:xx' format.
Returns:
list[dict]: a list of mac table data.
Raises:
KeyError: if `mac_address` is not specified.
Examples:
>>> from pprint import pprint
>>> import pynos.device
>>> conn = ('10.24.39.211',... | codesearchnet |
def sum(self, selector=identity):
if self.closed():
raise ValueError('Attempt to call sum() on a closed Queryable.')
if (not is_callable(selector)):
raise TypeError('sum() parameter selector={0} is not callable'.format(repr(selector)))
return sum(self.select(selector)) | Return the arithmetic sum of the values in the sequence..
All of the source sequence will be consumed.
Note: This method uses immediate execution.
Args:
selector: An optional single argument function which will be used
to project the elements of the sequence. If omitted, the
identity function is used.
Returns:
The ... | codesearchnet |
def get_config_dict(self, services, hostname=None):
if not isinstance(services, (tuple, list)):
services = [services]
endpoints_util.check_list_type(services, remote._ServiceClass, 'services',
allow_none=False)
return self.__api_descriptor(servic... | JSON dict description of a protorpc.remote.Service in API format.
Args:
services: Either a single protorpc.remote.Service or a list of them
that implements an api/version.
hostname: string, Hostname of the API, to override the value set on the
current service. Defaults to None.
Returns:
dict, The API descriptor docum... | juraj-google-style |
def list(self, **kwargs):
return [
self.prepare_model(s)
for s in self.client.api.services(**kwargs)
] | List services.
Args:
filters (dict): Filters to process on the nodes list. Valid
filters: ``id``, ``name`` , ``label`` and ``mode``.
Default: ``None``.
Returns:
list of :py:class:`Service`: The services.
Raises:
:py:class:`docker.errors.APIError`
If the server returns an error. | juraj-google-style |
def make_repr(inst, attrs):
arg_str = ', '.join((('%s=%r' % (a, getattr(inst, a))) for a in attrs if hasattr(inst, a)))
repr_str = ('%s(%s)' % (inst.__class__.__name__, arg_str))
return repr_str | Create a repr from an instance of a class
Args:
inst: The class instance we are generating a repr of
attrs: The attributes that should appear in the repr | codesearchnet |
def assign_methods(self, resource_class):
assert all([(x.upper() in VALID_METHODS) for x in resource_class.Meta.methods])
for method in resource_class.Meta.methods:
self._assign_method(resource_class, method.upper()) | Given a resource_class and it's Meta.methods tuple,
assign methods for communicating with that resource.
Args:
resource_class: A single resource class | codesearchnet |
def is_allowed(self, filepath, excludes=[]):
if os.path.isabs(filepath):
raise FinderException("'Finder.is_allowed()' only accept relative filepath")
if excludes:
for pattern in excludes:
if fnmatch.fnmatch(filepath, pattern):
return False
return True | Check from exclude patterns if a relative filepath is allowed
Args:
filepath (str): A relative file path. (exclude patterns are
allways based from the source directory).
Keyword Arguments:
excludes (list): A list of excluding (glob) patterns. If filepath
matchs one of patterns, filepath is not allowed.
Raises:
bouss... | codesearchnet |
def mix_in_audio_sample(track_data, track_offset, sample_data, sample_offset, clip_duration, sample_volume, ramp_in, ramp_out):
ramp_out_index = clip_duration - ramp_out
track_end = min(track_offset + clip_duration, track_data.shape[0])
track_end = min(track_end, track_offset + (sample_data.shape[0] - sampl... | Mixes the sample data into the main track at the specified offset.
Args:
track_data: Numpy array holding main audio data. Modified in-place.
track_offset: Where to mix the sample into the main track.
sample_data: Numpy array of audio data to mix into the main track.
sample_offset: Where to start in the audio sample.
c... | github-repos |
def qhalf(options, halfspaces, interior_point):
points = [(list(h.normal) + [h.offset]) for h in halfspaces]
data = [[len(interior_point), 1]]
data.append(map(repr, interior_point))
data.append([len(points[0])])
data.append([len(points)])
data.extend([map(repr, row) for row in points])
prep_... | Similar to qvoronoi command in command-line qhull.
Args:
option:
An options string. Up to two options separated by spaces
are supported. See Qhull's qhalf help for info. Typically
used options are:
Fp
halfspaces:
List of Halfspaces as input.
interior_point:
An interior point (see qhalf documentation)
Returns:
Output ... | codesearchnet |
def call_rpc(self, address, rpc_id, payload=b""):
if rpc_id < 0 or rpc_id > 0xFFFF:
raise RPCInvalidIDError("Invalid RPC ID: {}".format(rpc_id))
if address not in self._rpc_overlays and address not in self._tiles:
raise TileNotFoundError("Unknown tile address, no regis... | Call an RPC by its address and ID.
Args:
address (int): The address of the mock tile this RPC is for
rpc_id (int): The number of the RPC
payload (bytes): A byte string of payload parameters up to 20 bytes
Returns:
bytes: The response payload from the RPC | juraj-google-style |
def __init__(self, filename=None):
assert isinstance(filename, str) or filename is None
self._parser = self._setup_parser(filename)
self._warn_on_old_config()
self._engine = self._parse_engine()
self._path = self._parse_path()
... | Create a Config instance.
Args:
filename (str): Optional filename of the config file. If empty,
defaults to MACKUP_CONFIG_FILE | juraj-google-style |
def create_event_model(event):
if event['type'].startswith('task'):
factory = {JobEventName.Started: JobStartedEvent, JobEventName.Succeeded: JobSucceededEvent, JobEventName.Stopped: JobStoppedEvent, JobEventName.Aborted: JobAbortedEvent}
if (event['type'] in factory):
return factory[eve... | Factory function that turns a celery event into an event object.
Args:
event (dict): A dictionary that represents a celery event.
Returns:
object: An event object representing the received event.
Raises:
JobEventTypeUnsupported: If an unsupported celery job event was received.
WorkerEventTypeUnsupported: If an unsup... | codesearchnet |
def load(self, filename, bs=512):
with open(filename, 'rb') as f:
f.seek(GPT_HEADER_OFFSET + 0x0C)
header_size = struct.unpack("<I", f.read(4))[0]
f.seek(GPT_HEADER_OFFSET)
header_data = f.read(header_size)
self.header = GPT_HEADER(header_dat... | Loads GPT partition table.
Args:
filename (str): path to file or device to open for reading
bs (uint): Block size of the volume, default: 512
Raises:
IOError: If file does not exist or not readable | juraj-google-style |
def _GetTypeFromScope(self, package, type_name, scope):
if type_name not in scope:
components = _PrefixWithDot(package).split('.')
while components:
possible_match = '.'.join(components + [type_name])
if possible_match in scope:
type_name = possible_match
break
... | Finds a given type name in the current scope.
Args:
package: The package the proto should be located in.
type_name: The name of the type to be found in the scope.
scope: Dict mapping short and full symbols to message and enum types.
Returns:
The descriptor for the requested type. | juraj-google-style |
def wulff_gform_and_r(self, wulffshape, bulk_entry, r, from_sphere_area=False, r_units='nanometers', e_units='keV', normalize=False, scale_per_atom=False):
miller_se_dict = wulffshape.miller_energy_dict
new_wulff = self.scaled_wulff(wulffshape, r)
new_wulff_area = new_wulff.miller_area_dict
if (not from... | Calculates the formation energy of the particle with arbitrary radius r.
Args:
wulffshape (WulffShape): Initial, unscaled WulffShape
bulk_entry (ComputedStructureEntry): Entry of the corresponding bulk.
r (float (Ang)): Arbitrary effective radius of the WulffShape
from_sphere_area (bool): There are two ways to calcula... | codesearchnet |
def lookup(self, keys, name=None):
if keys.dtype.base_dtype != self._key_dtype:
raise TypeError(f'Dtype of argument `keys` must be {self._key_dtype}, received: {keys.dtype}')
values = keys
if isinstance(keys, (sparse_tensor.SparseTensor, internal.RaggedTensor)):
values = keys.values
if s... | Looks up `keys` in the table, outputs the corresponding values.
It assigns out-of-vocabulary keys to buckets based in their hashes.
Args:
keys: Keys to look up. May be either a `SparseTensor` or dense `Tensor`.
name: Optional name for the op.
Returns:
A `SparseTensor` if keys are sparse, a `RaggedTensor` if keys are... | github-repos |
def resolve(self, strict=None):
if sys.version_info >= (3, 6) or pathlib2:
if strict is None:
strict = False
else:
if strict is not None:
raise TypeError(
"resolve() got an unexpected keyword argument 'strict'")
... | Make the path absolute, resolving all symlinks on the way and also
normalizing it (for example turning slashes into backslashes
under Windows).
Args:
strict: If False (default) no exception is raised if the path
does not exist.
New in Python 3.6.
Raises:
IOError: if the path doesn't exist (strict=True or Python < 3.6... | juraj-google-style |
def get_filename(self, **kwargs):
if (self.filename_parser is None):
raise RuntimeError('No filename pattern or specific filename provided')
output_filename = self.filename_parser.compose(kwargs)
dirname = os.path.dirname(output_filename)
if (dirname and (not os.path.isdir(dirname))):
LO... | Create a filename where output data will be saved.
Args:
kwargs (dict): Attributes and other metadata to use for formatting
the previously provided `filename`. | codesearchnet |
def create_summary_metadata(display_name, description, num_thresholds):
pr_curve_plugin_data = plugin_data_pb2.PrCurvePluginData(
version=PROTO_VERSION, num_thresholds=num_thresholds)
content = pr_curve_plugin_data.SerializeToString()
return summary_pb2.SummaryMetadata(
display_name=display_name,
... | Create a `summary_pb2.SummaryMetadata` proto for pr_curves plugin data.
Arguments:
display_name: The display name used in TensorBoard.
description: The description to show in TensorBoard.
num_thresholds: The number of thresholds to use for PR curves.
Returns:
A `summary_pb2.SummaryMetadata` protobuf object. | juraj-google-style |
def __strict(self):
def conc(a, b):
return (a + b)
b = np.array(reduce(conc, [[i.top.z, i.base.z] for i in self]))
return all((np.diff(b) >= 0)) | Private method. Checks if striplog is monotonically increasing in
depth.
Returns:
Bool. | codesearchnet |
def dict_values(src):
for v in src.values():
if isinstance(v, dict):
for v in dict_values(v):
(yield v)
else:
(yield v) | Recursively get values in dict.
Unlike the builtin dict.values() function, this method will descend into
nested dicts, returning all nested values.
Arguments:
src (dict): Source dict.
Returns:
list: List of values. | codesearchnet |
def __init__(self, message='Hello!'):
self.message = message | Constructor of the test class.
Constructs a new ClassWithDocstring object.
Args:
message: The default message to print. | github-repos |
def get_channel_id(turn_context: TurnContext) -> str:
if turn_context.activity.channel_id is None:
return ""
else:
return turn_context.activity.channel_id | Get the Channel Id from the current Activity on the Turn Context.
Args:
turn_context (TurnContext): The Turn Context to retrieve the Activity's Channel Id from.
Returns:
str: The Channel Id from the Turn Context's Activity. | juraj-google-style |
def get_function_descriptor_list(self):
descriptor_list = []
if self.is_for_driver_task:
return descriptor_list
else:
descriptor_list.append(self.module_name.encode('ascii'))
descriptor_list.append(self.class_name.encode('ascii'))
descriptor_list.append(self.function_name.enc... | Return a list of bytes representing the function descriptor.
This function is used to pass this function descriptor to backend.
Returns:
A list of bytes. | codesearchnet |
def __init__(self, root=None, **kwargs):
super().__init__()
global _END_TIME_OF_LAST_WRITE
with _END_TIME_OF_LAST_WRITE_LOCK:
if _END_TIME_OF_LAST_WRITE is None:
_END_TIME_OF_LAST_WRITE = time.time()
self._root = root
self._kwargs = kwargs
self._delete_tracking('_kwargs')
... | Creates a training checkpoint for a single or group of objects.
Args:
root: The root object to checkpoint. `root` may be a trackable object or
`WeakRef` of a trackable object.
**kwargs: Keyword arguments are set as attributes of this object, and are
saved with the checkpoint. All `kwargs` must be trackable objects, or... | github-repos |
def swf2png(swf_path, png_path, swfrender_path='swfrender'):
try:
cmd = [swfrender_path, swf_path, '-o', png_path]
subprocess.check_output(cmd, stderr=subprocess.STDOUT)
except subprocess.CalledProcessError as e:
raise ConversionError(('Failed to convert SWF file %s.\n\tCommand: %s\n\tEx... | Convert SWF slides into a PNG image
Raises:
OSError is raised if swfrender is not available.
ConversionError is raised if image cannot be created. | codesearchnet |
def __init__(self, _args):
super(TcExValidate, self).__init__(_args)
self._app_packages = []
self._install_json_schema = None
self._layout_json_schema = None
self.config = {}
if 'pkg_resources' in sys.modules:
self.install_json... | Init Class properties.
Args:
_args (namespace): The argparser args Namespace. | juraj-google-style |
def parse_raw_fact(raw_fact):
def at_split(string):
result = string.split('@', 1)
length = len(result)
if length == 1:
front, back = result[0].strip(), None
else:
front, back = result
front, back = front.strip(), back.strip()
... | Extract semantically meaningful sub-components from a ``raw fact`` text.
Args:
raw_fact (text_type): ``raw fact`` text to be parsed.
Returns:
dict: dict with sub-components as values. | juraj-google-style |
def _parse_ports(port_values: dict) -> dict:
endpoints = {}
for port_element in port_values:
target_port = port_element.split(':')
for port in target_port:
endpoints[int(port)] = int(port)
endpoint_spec = docker.types.EndpointS... | Parse ports key.
Args:
port_values (dict): ports configuration values
Returns:
dict, Ports specification which contains exposed ports | juraj-google-style |
def load_default(self):
path = ctypes_util.find_library(self._sdk)
if path is None:
if self._windows or self._cygwin:
path = next(self.find_library_windows(), None)
elif sys.platform.startswith('linux'):
... | Loads the default J-Link SDK DLL.
The default J-Link SDK is determined by first checking if ``ctypes``
can find the DLL, then by searching the platform-specific paths.
Args:
self (Library): the ``Library`` instance
Returns:
``True`` if the DLL was loaded, otherwise ``False``. | juraj-google-style |
def onkeydown(self, key, keycode, ctrl, shift, alt):
return (key, keycode, ctrl, shift, alt) | Called when user types and releases a key.
The widget should be able to receive the focus in order to emit the event.
Assign a 'tabindex' attribute to make it focusable.
Args:
key (str): the character value
keycode (str): the numeric char code | juraj-google-style |
def detect_deprecated_references_in_node(self, node):
results = []
if node.expression:
results += self.detect_deprecation_in_expression(node.expression)
for dep_node in self.DEPRECATED_NODE_TYPES:
if (node.type == dep_node[0]):
results.append(dep_node)
return results | Detects if a node makes use of any deprecated standards.
Returns:
list of tuple: (detecting_signature, original_text, recommended_text) | codesearchnet |
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