content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def where_op(condition, x, y):
"""Return a tensor of elements selected from either :attr:`x` or :attr:`y`, depending on :attr:`condition`.
If the element in condition is larger than 0,
it will take the `x` element, else it will take the `y` element
.. note::
The tensors :attr:`condition`, :at... | c4a34284c8105b8b0319f3e33db9d9ea0d74b0d2 | 3,626,800 |
def get_out_dir(key: str) -> str:
"""
Return the output directory
:param key: output product
"""
return OTD[key] | e510603d93cb72d916c3afab8aeb36756a563326 | 3,626,801 |
def jet_fire_api521(Tvessel):
"""
Incident heat flux of 100 kW/m2
"""
alpha = 0.75
e_flame = 0.33
e_surface = 0.75
h = 40
Tflame = 900 + 273.15
Tradiative = 1100 + 273.15
return stefan_boltzmann(alpha, e_flame, e_surface, h, Tflame, Tradiative, Tvessel) | e7d95073f9e899b8f48e5fc6fcd9505e622dea98 | 3,626,802 |
def ewma(values, window):
"""
Numpy-based implementation of EMA
"""
weights = np.exp(np.linspace(-1., 0., window))
weights /= weights.sum()
ema = np.convolve(weights, values)[window-1:-window+1]
return ema | a544b9a37bf227dcd12246d5ebd83d4788b217c9 | 3,626,803 |
import torch
def prepare_loss_weights(
labels,
pos_cls_weight=1.0,
neg_cls_weight=1.0,
loss_norm_type=LossNormType.NormByNumPositives,
dtype=torch.float32,
):
"""get cls_weights and reg_weights from labels.
"""
cared = labels >= 0
# cared: [N, num_anchors]
positives = labels > ... | 0f3a8bd3d9149c6264aa73f5a4daa0291f56d2e8 | 3,626,804 |
from typing import Optional
import subprocess
def capture_output(
command: str, ip: Optional[str] = None, **kwargs
) -> ADBCommandResult:
"""
Execute an adb command on the given device and return the result
:param command: command to execute
:param ip: device id
:param kwargs: if ... | 1f3077177c34a5fc6d1ac96638f34f4f88a51f4e | 3,626,805 |
def add_to_leftmost(branch, val):
"""adds value to the leftmost part of the branch and returns the modified branch and 0.
OR returns unchanged change and val if the val cannot be added"""
if val == 0:
return branch, val
if type(branch) is int:
return branch + val, 0
# add to children... | 1c2c3bdccfcb6f4966b9bf9228f092ee17ca49f9 | 3,626,806 |
def normalize_list_of_dict_into_dict(alist):
"""
Info is generated as a list of dict
objects with a single key.
@alist - the list in question.
@return - normalized dict with multiple keys
"""
result = {}
for element in alist:
for key in element.keys():
... | 8de00b0923d07b99085ca3b4d694960aae9fc7f5 | 3,626,807 |
import hashlib
def hashhex(s):
"""Returns a heximal formated SHA1 hash of the input string."""
h = hashlib.sha1()
h.update(s)
return h.hexdigest() | 0d2b0dd9c54b71f3668b971fb81f9d78223acbb2 | 3,626,808 |
import os
import errno
from typing import OrderedDict
import sys
def prerank(rnk, gene_sets, outdir='gseapy_out', pheno_pos='Pos', pheno_neg='Neg',
min_size=15, max_size=500, permutation_n=1000, weighted_score_type=1,
ascending=False, figsize=[6.5,6], format='pdf', graph_num=20, seed=None):
... | f9ccadecba9f3c7b656dd5ce72c62051f807f0fd | 3,626,809 |
import argparse
def get_args():
"""Get our arguments"""
parser = argparse.ArgumentParser()
parser.add_argument('filename', metavar='F', type=str, nargs=1,
help='File to load')
parser.add_argument('-a', '--annealing', action='store_true',
default=False,
... | 33e82867f37b1934f9622076459402beb2cb3214 | 3,626,810 |
import os
def read_results(folder, name):
"""
reads in cluster results
"""
tree_fname = os.path.join(folder, name + '.dg_01')
clu_fname = os.path.join(folder, name + '.dg_01.lab')
tree = np.loadtxt(tree_fname)
clu = np.loadtxt(clu_fname)
return clu, tree | 462fa9eae6b2616dde237e1fde86033b88c04b37 | 3,626,811 |
def planets(id='', name=''):
"""
Return a planet.
Like: Hoth, Naboo, etc.
"""
response = Render.show(id, name, 'planets')
return response | 1e1944d58b50cf3fed7efc6fe23b888837689a57 | 3,626,812 |
def literal(string):
"""
If `string` is a valid literal in NTriples syntax, return its value, lang tag and type.
Use `None` if there is no language tag or no datatype.
If `string` is not a valid literal return `None`.
"""
match = literal.pattern.match(string)
if not match:
return Non... | a0d805d7b3365366b85c0ce576f75a69680251be | 3,626,813 |
import logging
def make_error_logger(name, level, filename):
"""
Création d'un Logger d'erreur
:param name: nom du logger
:param level: niveau de logging
:param filename: nom du fichier d'erreur
:return: logger
"""
formatter = logging.Formatter("%(asctime)s %(levelname)s - %(messa... | 0d78faa4657af348c06755298c2e1d3f717cd092 | 3,626,814 |
def correlate(a, b, shift, demean=True, normalize=True, domain='freq'):
"""
Cross-correlation of signals a and b with specified maximal shift.
:type a: :class:`~numpy.ndarray`, :class:`~obspy.core.trace.Trace`
:param a: first signal
:type b: :class:`~numpy.ndarray`, :class:`~obspy.core.trace.Trace`... | ff0a4adcde2f62f7de94c31702dd2605ae8f390c | 3,626,815 |
def get_user_idle_time():
"""
Return the amount of time (in seconds) that the user is said to be idle.
This is normally obtained from a lack of keyboard and/or mouse input.
"""
if system == 'Windows':
return get_user_idle_time_windows()
elif system == 'Darwin':
return get_user_idle_time_mac()
raise NotImplem... | bcdb1a9710721b94f2c6c490a8ac9d453cda412a | 3,626,816 |
from typing import Dict
from typing import Any
from typing import Iterable
from typing import Optional
from typing import Tuple
def kwargs_from_config(
config: Dict[str, Any],
required_keys: Iterable[str],
optional_keys: Iterable[str],
renames: Optional[Iterable[Tuple[str, str]]] = None,
) -> Dict[str... | b3acef60b87dc8bb4c00157c169d1968c8751100 | 3,626,817 |
def as_array(a, dtype=DEFAULT_FLOAT_DTYPE):
"""
Converts given :math:`a` variable to *ndarray* with given type.
Parameters
----------
a : object
Variable to convert.
dtype : object
Type to use for conversion.
Returns
-------
ndarray
:math:`a` variable conver... | 5efde6e83812dec9ad16283cf13b4d3d07ba5cd8 | 3,626,818 |
def round_filters(filters, global_params):
"""Round number of filters based on depth multiplier."""
multiplier = global_params.width_coefficient
divisor = global_params.depth_divisor
min_depth = global_params.min_depth
if not multiplier:
return filters
filters *= multiplier
min_dept... | 057d209906cde8287051ea48cf3d97af76e66cf2 | 3,626,819 |
from typing import List
def equal_opportunity(confusion_matrix_list: List[np.ndarray],
tolerance: float = 0.2,
label_index: int = 0) -> np.ndarray:
"""
Checks for equal opportunity between all of the sub-populations.
This function checks if **true positive rate... | f861293ece13ea5dc14c6397fbf99a991bf0f672 | 3,626,820 |
def determine_qc_protocol(project):
"""
Determine the QC protocol for a project
Arguments:
project (AnalysisProject): project instance
Return:
String: QC protocol for the project
"""
# Standard protocols
if project.info.paired_end:
protocol = "standardPE"
else:
... | 6862ab84450d4d4d0ca74ee178b90f5eacb303fb | 3,626,821 |
def entitydata_list_url_query(viewname, kwargs, query_params, more_params):
"""
Helper function for generatinglist URLs
"""
list_url=reverse(viewname, kwargs=kwargs)
return uri_with_params(list_url, query_params, more_params) | 5264a2f45befc9662f22a1febc5451d35881c984 | 3,626,822 |
def _adaptive_order_weno3_robust(q,
i,
j,
recons,
keep_positive,
eps=1.0e-17,
c1=1.0,
c2=... | dc772944d6eb13a02752d995f738b385a01fd7a0 | 3,626,823 |
import torch
def patch_and_fit_physio(time_series, replicates, patch=3, mask=None,
mode='gn', verbose=0):
"""Extract patches from an fMRI time + replicate series and fit parameters.
Parameters
----------
time_series : (replicates, *input_shape) tensor_like
fMRI time s... | f22083e42927d0661a315a0825b1b4344be75e53 | 3,626,824 |
def verify_file_exists(file_name, file_location):
"""
Function to verify if a file exists
:type file_name: String
:param file_name: The name of file to check
:type file_location: String
:param file_location: The location of the file, derive from the os module
:rtype: Boolean
:return: r... | 8ac4869f3f758d9342f9047a6212851f7f463f35 | 3,626,825 |
import math
def plot_cdfs(x, y, ccdf=False):
"""plot cumulative density functions for each column in x, based on
the classification specified in y.
Parameters
----------
x : DataFrame
the experiments to use in the cdfs
y : ndaray
the categorization for the data
ccdf : boo... | 3b98d7b3d474a374d17438b5263af53c20b24b83 | 3,626,826 |
def make_shell_context():
"""Pre-populate the shell environment when running run.py shell."""
return dict(app=keeper_app, db=db, models=models) | 9344b3d30f36c0c1a5b10847d93a92c10e58872c | 3,626,827 |
import contextlib
def _MaybeClosing(fileobj):
"""Returns closing context manager, if given fileobj is not None.
If the given fileobj is none, return nullcontext.
"""
return (contextlib.closing if fileobj else NullContext)(fileobj) | 05db3f9168d69c94513c95f0da396500319e079e | 3,626,828 |
def get_project_page(pid, cache_directory=settings.CACHE_DIRECTORY):
"""Get a project page rendered in HTML given a project ID.
Args:
pid (int): project ID.
cache_directory (str): the directory where cached projects are stored.
Returns:
A string containing the HTML for ... | bff55a1c6e51742cca264199b4ac669fe4b8b855 | 3,626,829 |
def is_slot_bound(module, device, slot):
"""Checks whether a specific slot in a given device is bound to clevis.
Return: <boolean> <error>"""
_unused, err = get_jwe(module, device, slot)
if err:
return False, err
return True, None | c103ae94ef86bad7eb3c3e33818faf20003e18b4 | 3,626,830 |
def to_matplotlib(img):
"""Returns a view of the image from Bob format to matplotlib format.
This function works with images, batches of images, videos, and higher
dimensional arrays that contain images.
Parameters
----------
img : numpy.ndarray
A N dimensional array containing an image... | f769af6d407d16543dc9ec98d8cc35338db47231 | 3,626,831 |
def energy_distance(x, y, **kwargs):
"""
energy_distance(x, y, *, exponent=1)
Computes the estimator for the energy distance of the
random vectors corresponding to :math:`x` and :math:`y`.
Both random vectors must have the same number of components.
Parameters
----------
x: array_like
... | a36d4277ed5cd9da049f129a2d8fa2b50a062ed3 | 3,626,832 |
import os
import os.path as op
from glob import glob
from warnings import warn
def bids_scan_file_walker(dataset=".", include_types=None, warn_no_files=False):
"""
Traverse a BIDS dataset and provide a generator interface
to the imaging files contained within.
:author: @chrisfilo
https://github.... | f3a4f3e1c96073e89fd69ff2768570c1f0667f9f | 3,626,833 |
def train_step(net, optim, batch):
"""
one training step
"""
(loss, net), grads = pax.value_and_grad(loss_fn, has_aux=True)(net, batch)
net, optim = opax.apply_gradients(net, optim, grads)
net = net.replace(rnn=net.gru_pruner(net.rnn))
net = net.replace(o1=net.o1_pruner(net.o1))
net = ne... | 3f3e9fa1f8487bafd0e0b70a673ef3af989e3dfc | 3,626,834 |
def insert_dim(arg, pos=-1):
"""insert 1 fake dimension inside the arg before pos'th dimension"""
shape = [i for i in arg.shape]
shape.insert(pos, 1)
return arg.reshape(shape) | 921cd27894df9910dbc12b31db6eb1f73d47f180 | 3,626,835 |
def encode_captions(captions):
"""
Convert all captions' words into indices.
Input:
- captions: dictionary containing image names and list of corresponding captions
Returns:
- word_to_idx: dictionary of indices for all words
- idx_to_word: list containing all words
- vocab_size... | 2ba216c844723b0925b46d0db7bc8afd6ce0f5b4 | 3,626,836 |
import logging
def post_dataset(conn, dataset_name, project_id=None, description=None,
across_groups=True):
"""Create a new dataset.
Parameters
----------
conn : ``omero.gateway.BlitzGateway`` object
OMERO connection.
dataset_name : str
Name of the Dataset being c... | cd0e57d8184683c403002de085fa5122c1e3458d | 3,626,837 |
def load_stop_words(stop_word_file):
"""
Utility function to load stop words from a file and return as a list of words
@param stop_word_file Path and file name of a file containing stop words.
@return list A list of stop words.
"""
stop_words = []
for line in open(stop_word_file):
if... | 8127aeec8db8f7bc87130ea0d1e5faa4998ac86f | 3,626,838 |
def run_gcloud_command(cmd, project_id):
"""Execute a gcloud command and return the output.
Args:
cmd (list): a list of strings representing the gcloud command to run
project_id (string): append `--project {project_id}` to the command. Most
commands should specify the project ID, for those that don't... | 324345a3fdf687c3d36711c918060715fedfa79a | 3,626,839 |
def convert_gmx_flow_1_to_2(flow: GmxFlow, width: float) -> GmxFlow:
"""Convert flow data from 'GMX_FLOW_1' to 'GMX_FLOW_2'.
This changes the field 'M' to represent the mass density instead of
the total mass in the bin. Thus we also require the width of the system,
in order to calculate the bin volume.... | d1e005bf8adc73c27e4454730a744fb6b464100b | 3,626,840 |
def NullFlagHandler(feature):
""" This handler always returns False """
return False | 7d37ecc8518144b27b43580b7273adf5f68dfdfb | 3,626,841 |
def add_image(axes, path):
"""Add the image given by ``path`` to the plot ``axes``.
:param axes: represents an individual plot
:param path: path to the image
:type axes: matplotlib.pyplot.Axes
:type path: str
:return: mpimg.AxesImage
"""
try:
img = Image.open(path)
retur... | fa574ede75a5f2389380e906090e2d91c92944e9 | 3,626,842 |
from datetime import datetime
def abandonAffaire_reopenParentAffaire_view(request):
"""
Abandon child_affaire, reopen parent child_affaire and reattribute numbers to parent child_affaire.
"""
settings = request.registry.settings
etape_abandon_id = settings['affaire_etape_abandon_id']
etape_re... | c2993de78590f708fc4d7e8c0ed08008a21103b6 | 3,626,843 |
from typing import Optional
import logging
import functools
def get_dataset(
*,
batch_size,
eval_batch_size,
num_shards,
dtype_str='float32', # pylint: disable=unused-argument
shuffle_seed=0,
rng=None,
dataset_configs=None,
dataset_service_address: Optional[str] = None): # pylint... | 621ac7541489a08511e8e0e2ae4474a1591d3132 | 3,626,844 |
import copy
def find_paths(orbital_graph, starting_node, ending_node, visited_nodes=None):
"""Recursively find all the paths from starting_node to ending_node in the graph
Paths are returned as a list of paths, where paths are a list of nodes.
An empty list means that no valid path exists.
"""
pat... | 55a47542c3d70bbc1f5c722c1e87908e10b3d0e5 | 3,626,845 |
def rp_from_filename(filename, split_char=ELT_SPLIT,
rp_regex=REGEX_RP):
"""Gets the Rp (proton radius?) label from the file name, returns None if
not found.
:param filename: the name of the file to parse
:param split_char: the character which separates filename elements
:param ... | e5cae3428e6a7a30cceab779845b127df52c2ad1 | 3,626,846 |
def check_duplication(request):
"""API check_duplication"""
check_type = request.POST.get('check_type')
name = request.POST.get('username')
if check_type == 'id':
min_limit = settings.ID_MIN_LENGTH
max_limit = settings.ID_MAX_LENGTH
else:
min_limit = settings.NICKNAME_MIN_LE... | 2ef45506ada6b54cc86b1734a0301e6e48bb5ca6 | 3,626,847 |
def _merge_numeric_stats(
left, right,
feature_name):
"""Merge two partial numeric statistics and return the merged statistics."""
# Check if the types from the two partial statistics are not compatible.
# If so, raise an error.
if (left.type is not None and right.type is not None and
left.type !=... | 1eb4ea5a425ea70ae4e02da267d2553a8440376b | 3,626,848 |
import logging
def get_pod_names(client, namespace, name):
"""Get pod names from k8s.
"""
core_api = k8s_client.CoreV1Api(client)
resp = core_api.list_namespaced_pod(
namespace, label_selector=to_selector({TF_JOB_NAME_LABEL: name}))
logging.info("list_namespaced_pod: %s", str(resp))
pod_names = []
f... | 6228ed3a596093260c0b17a95201068b2d70c1d6 | 3,626,849 |
def calculate_drawdown(input_series: pd.Series, is_returns: bool = False) -> pd.Series:
"""Calculate the drawdown (MDD) of historical series. Note that the calculation is done
on cumulative returns (or prices). The definition of drawdown is
DD = (current value - rolling maximum) / rolling maximum
... | 95e128f00f3667e5a22bd114074525feb6063e1c | 3,626,850 |
def search_traversal(**kwargs):
"""Search Traversal in Database"""
db_inst = app.config['ARANGO_CONN']
db_inst.get_database()
graph = db_inst.get_graph(kwargs.get('graph_name'))
try:
traversal_results = graph.traverse(
start_vertex=kwargs.get('start_vertex'),
directi... | 971751adb1970a0bead9e632e00181a4bc3914a9 | 3,626,851 |
def find_matching_nodes(search_for, search_in, matches=[]):
"""
Search Vertex tree 'search_in' for the first isomorphic occurance of the
Vertex tree search_for
Return a list of [(x,y)...] for node in search_for (x) matched with
a pair (y) from search in, such as the two graphs preserve their ... | 9e6696533f7b5e313075fadade8b42fe6f09f0cf | 3,626,852 |
def getStrategicManagementBodies(project):
"""Returns the strategic management bodies for a given project."""
return getManagementBodies(project, MANAGEMENT_BODY_CATEGORY_STRATEGIC) | 526c60342f348f327436f4e1bdcb5c90c7820cbe | 3,626,853 |
def clip(x, min_value, max_value):
"""Element-wise value clipping."""
if max_value is not None and max_value < min_value:
max_value = min_value
if max_value is None:
max_value = np.inf
min_value = _to_tensor(min_value, x.dtype.base_dtype)
max_value = _to_tensor(max_value, x.dtype.bas... | 58ba70a6212b2ab3b37f37aa8a4611bab262be81 | 3,626,854 |
import cmd
import subprocess
def dotnet_restore(path=""):
"""Restore the dotnet solution from the root of the project via dotnet restore """
if path:
cmd.append(path)
info("Restoring nuget packages (via %s" % " ".join(cmd))
result = subprocess.run(cmd)
status = result.returncode
if ... | 7cf78f998c1d9c2bb79a1e28c984fc20f6a8ac28 | 3,626,855 |
def SendMessage(service, user_id, message):
"""Send an email message.
Args:
service: Authorized Gmail API service instance.
user_id: User's email address. The special value "me"
can be used to indicate the authenticated user.
message: Message to be sent.
Returns:
Se... | 9c8c9985fe80b22a94678c354774ebe0453fe860 | 3,626,856 |
def getPolicy(lunaToken, policyName, network, account_key=''):
""" Gets a specific policy on a given network in JSON format """
session.headers.update({'Luna-Token': lunaToken})
if network == 'staging':
get_policy_endpoint = "/imaging/v2/network/staging/policies/" + policyName
else:
get... | 52a9c7496813b55e74c19a084a367a5f242a379a | 3,626,857 |
import re
def clean_str(string):
# Remove punctuation
"""
Tokenization/string cleaning for all datasets except for SST.
Original taken from https://github.com/yoonkim/CNN_sentence/blob/master/process_data.py
"""
string = re.sub(r"[^\u4e00-\u9fff]", " ", string)
string = re.sub(r"\s{2,}", "... | 025a17cfc81217b6115f049694ff205c5a5e93ab | 3,626,858 |
from typing import List
from typing import Tuple
def extract_ops(page: PageObject) -> List[Tuple]:
"""extract all operators"""
content = page.getContents()
if not isinstance(content, ContentStream):
content = ContentStream(content, page.pdf)
return list(content.operations) | 402ec35f7de36dce93ae56b13d535ea8cebc1916 | 3,626,859 |
import requests
def get_project_info(project_name, dnac_jwt_token):
"""
This function will retrieve all templates associated with the project with the name {project_name}
:param project_name: project name
:param dnac_jwt_token: DNA C token
:return: list of all templates, including names and ids
... | 61ff47100853175c76ecf05117d7016842a6745d | 3,626,860 |
import google
import os
def main(args):
"""This functions annotates a PDF document using the Document AI API"""
if not args.project_id:
_, project_id = google.auth.default()
args.project_id = project_id
parent = f"projects/{args.project_id}/locations/{args.multi_region_location}"
clien... | 34c6937f59758519bcb7b22e6dd59ff912e49116 | 3,626,861 |
import textwrap
import six
def generate(tag_cls):
"""
generate generates documentation for given wrapper tag class
:param tag_cls: wrapper_tag class
:return:
"""
doc = textwrap.dedent(tag_cls.__doc__ or '').strip()
arguments_doc = ""
for ag, arguments in six.iteritems(ArgumentsGroup... | 3b2fb93caa37552f4b4eaff1fc4a1c1d1d1412dd | 3,626,862 |
def load_data(database_filepath):
"""Load data from SQLite into memory.
"""
engine = create_engine(f'sqlite:///{database_filepath}')
df = pd.read_sql_table("Messages", engine)
X = df["message"]
Y = df.drop(["message", "id", "original", "genre"], axis=1)
return X, Y, Y.columns | e8e338d7c08113cd11f1e1efcb16f4687de354c7 | 3,626,863 |
def column_thresh(C, eps):
"""
cleans out C, removes all values below eps.
otherwise
"""
n1 = C.shape[1]
for i in range(n1):
if la.norm(C[:,i], 2) < eps: # norm here defaults to 2 norm for vector
C[:,i]=0
else:
C[:,i]=C[:,i]-eps*C[:,i]/la.norm(C[:,i],2)
... | ba53b3a728ff363a684c0974676430c3850d2c43 | 3,626,864 |
def distance_between_points(p1, p2):
""" Function that computes the euclidean distance between to points.
Returns:
float: distance value
"""
return ((p1['x']-p2['x']) * (p1['x'] - p2['x']) + (p1['y']-p2['y']) * (p1['y']-p2['y'])) ** 0.5 | b8cb563f13f64f0511525e5428d47d9228220915 | 3,626,865 |
def sigmoid(z):
"""
Compute the sigmoid of z
Arguments:
z -- A scalar or numpy array of any size.
Return:
s -- sigmoid(z)
"""
#(≈ 1 line of code)
# s = ...
# YOUR CODE STARTS HERE
s = 1/(1+np.exp(-z))
# YOUR CODE ENDS HERE
return s | 868599c3550a0e575d9a39632e0990f3dfc2f782 | 3,626,866 |
from typing import Tuple
from typing import Dict
import copy
def _decompose_expressions(circ: Circuit) -> Tuple[Circuit, bool]:
"""Rewrite a circuit command-wise, decomposing ClassicalExpBox."""
bit_heap = BitHeap()
reg_heap = RegHeap()
# add already used heap variables to heaps
for b in circ.bits... | 8dad1b0e438930541e0604a48114b8d5628db97d | 3,626,867 |
def get_trailing_app_metrics(args):
"""
Returns trailing app_name metrics for a given time period.
Args:
args: dict The parsed args from the request
args.limit: number The max number of apps to return
args.time_range: one of "week", "month", "all_time"
Returns:
[{ name: ... | e0b6f89a83af7250baa16926fcf644ca7b5b0e51 | 3,626,868 |
def get_all_related_objects(opts):
"""
Django 1.8 changed meta api, see
https://docs.djangoproject.com/en/1.8/ref/models/meta/#migrating-old-meta-api
https://code.djangoproject.com/ticket/12663
https://github.com/django/django/pull/3848
:param opts: Options instance
:return: list of relatio... | bc3cc8ec4b83a26ff5c409eb840733ca7bdfaaea | 3,626,869 |
import fastapi
async def fetch_dialog(
customer_id: str,
dialog_id: str,
db: motor_asyncio.AsyncIOMotorClient = fastapi.Depends(mongodb.get_database),
) -> utils.OrjsonResponse:
"""
Fetch a dialog.
- **customer_id**: customer id of the dialog to return
- **dialog_id**: dialog id of the di... | 4fd8f66df8375b5620c400c88446206e5acf337b | 3,626,870 |
def _get(pseudodict, key, single=True):
"""Helper method for getting values from "multi-dict"s"""
matches = [item[1] for item in pseudodict if item[0] == key]
if single:
return matches[0]
else:
return matches | f68156535d897dd719b05d675e66cadc284ce1a3 | 3,626,871 |
from typing import Counter
def guess_domain(tree, blacklist=_DOMAIN_BLACKLIST, get_domain=get_domain):
""" Return most common domain not in a black list. """
domains = [get_domain(href) for href in tree.xpath('//*/@href')]
domains = [d for d in domains if d and d not in blacklist]
if not domains:
... | 0d0c0ab8876092e8e06783cd9b4adaf50d9996cf | 3,626,872 |
from xmodule.modulestore.django import modulestore
from openedx.core.djangoapps.content.block_structure.models import BlockStructureModel
from openedx.core.djangoapps.content.block_structure.exceptions import BlockStructureNotFound
def get_course_last_published(course_key):
"""
We use the CourseStructure tabl... | c7a8e503553790ed05ca84a8bfa7ac6decf3bc0d | 3,626,873 |
def rgb_to_hex(rgb_triplet):
"""
Convert a 3-tuple of integers, suitable for use in an ``rgb()``
color triplet, to a normalized hexadecimal value for that color.
Examples:
>>> rgb_to_hex((255, 255, 255))
'#ffffff'
>>> rgb_to_hex((0, 0, 128))
'#000080'
"""
return '#%02x%02x%02x... | 53a21a387e19c8cf989cec868f8862bfcb2dbaed | 3,626,874 |
def dec2stringTime(decim, precision=5):
""" Convert a decimale time or coordinate to a formatted string.
Parameters
----------
decim : int, float
precision : int
Returns
-------
String formatted HH:MM:SS.SSSSS
"""
return hms2stringTime(*dec2sex(decim), precision=precision) | d7ea8334f021dc302c1291556bd5d6a8bb921b46 | 3,626,875 |
def getCartShape(dimension, communicator=None):
"""
Returns :samp:`getCartShapeForSize(dimension, communicator.Get_size())`.
:type dimension: int
:param dimension: Spatial dimension for returned cartesian layout.
:type communicator: :obj:`mpi4py.MPI.Comm`
:param communicator: If :samp:`None... | fe26d0bef1f7e244b1bcbf78cc7754b04790f121 | 3,626,876 |
def gumbel_log_survival(x):
"""Returns log P(g > x) for a standard Gumbel g.
log P(g > x) = log(1 - P(g < x)) = log(1 - exp(-exp(-x))). The implementation
is more numerically robust than a naive implementation of that formula.
Args:
x: The cutoff Gumbel value.
"""
# Adapted from
# https://gist.githu... | 416069914e011f82db4d47dd667c95b8f2539a2d | 3,626,877 |
import platform
def platform_is(requested_platform: str) -> bool:
"""
Compare requested platform with current platform.
Common platforms:
- Win / Windows
- Mac / macOS / Darwin
- Linux
- Unix (Mac, SunOS, BSD unix's)
- *nix / posix (Not Windows)
:return: True if current platform m... | 8e9ca64fc9053369da100da46083685cb6dcd47a | 3,626,878 |
def prepare_bert(content, max_len, bow_vocab_size=1000, vectorizer=None, ctx=mx.cpu()):
"""
Utility function to take text content (e.g. list of document strings), a maximum sequence
length and vocabulary size, returning a data_train object that can be used
by a SeqBowEstimator object for the call to fit... | 76f6ebc3d874668507e8e7b9326a82dbd1b01997 | 3,626,879 |
import Qconfig
import functools
import unittest
import os
def requires_qe_access(func):
"""
Decorator that signals that the test uses the online API:
* determines if the test should be skipped by checking environment
variables.
* if the test is not skipped, it reads `QE_TOKEN` and ... | 8c29a089ef2098fe8e22c572b5d6f53fd16c702c | 3,626,880 |
def to_homogeneous(t, is_point):
"""Makes a homogeneous space tensor given a tensor with ultimate coordinates.
Args:
t: Tensor with shape [..., K], where t is a tensor of points in
K-dimensional space.
is_point: Boolean. True for points, false for directions
Returns:
Tensor with shape [..., K+... | 484668c34b6c61e7e2479ea44c7beb4a0111676b | 3,626,881 |
import zipfile
def name_from_archive(archive_path):
""" Name From Archive """
archive = zipfile.ZipFile(archive_path, allowZip64=True)
xml_data = archive.read("manifest.xml")
elem = etree.fromstring(xml_data)
return elem.get("uuid") | 34c4e89cb75d86cd0d703a79ac0ed70b223a91c0 | 3,626,882 |
import glob
def datedfile(filename,date):
""" select file based on observation date and latest version
Parameters
----------
filename: text file name pattern, including "yyyymmdd_vnn" place holder for date and version
date: yyyymmdd of observation
Returns: file name
"""
filelist = ... | 203cf848e351ef9b8b77bda62d5850b35485762a | 3,626,883 |
import random
import string
def random_user(n):
"""generate a random user id of size n"""
chars = []
for i in range(n):
chars.append(random.choice(string.ascii_lowercase))
return ''.join(chars) | 21d8ec2ef8b275ffca481e4553ec396ff4010653 | 3,626,884 |
def playerStandings():
"""Returns a list of the players and their win records, sorted by wins.
The first entry in the list should be the player in first place,
or a player tied for first place if there is currently a tie.
Returns:
A list of tuples, each of which contains (id, name, wins, matches... | 7b8d50b1b4dbc592e2792f248df6f848c9c3aac6 | 3,626,885 |
import logging
def load_statistics(
input_path: Text) -> statistics_pb2.DatasetFeatureStatisticsList:
"""Loads data statistics proto from file.
Args:
input_path: Data statistics file path. The file should be a one-record
TFRecord file or a plain file containing the statistics proto in Proto
T... | a86b6cfd25b6e77db78419afad41aa6b7e456b7e | 3,626,886 |
from typing import Counter
def get_counter(request):
"""
Get the Counter object associated with a request.
Raise AjaxError if session is invalid or counter is not found.
"""
if "counter" not in request.session:
raise AjaxError(RET_UNAUTHORIZED, _(u"Not logged in."))
counter_id = requ... | 6d676880fccb47b05c1936e26c8be819136ad399 | 3,626,887 |
def _get_parse_input(parse_args, args_in, dict_in):
"""Return default for parse_input.
This is to decide if context_parser should run or not.
To make it easy on an API consumer, default behavior is ALWAYS to run
parser UNLESS dict_in initializes context and there is no args_in.
If dict_in specifi... | 64dcfd32a3d9f66749a27d4b26bd5fb3a66edf28 | 3,626,888 |
from typing import Dict
from typing import List
import logging
import re
def get_haiku(
text: str,
inflect_p,
pronounce_dict: Dict,
syllable_dict: Dict,
emoticons_list: List,
guess_syl_method: str,
) -> str:
"""Attempt to turn a string into a haiku.
Returns haiku if able, otherwise ret... | 0405dc44095945b7414940c61a5d15238661514b | 3,626,889 |
import argparse
def get_parser():
"""
Creates and returns the argument parser for jExam
Returns:
``argparse.ArgumentParser``: the argument parser for jExam
"""
parser = argparse.ArgumentParser()
parser.add_argument("master", type=str, help="Path to exam master notebook")
parse... | 03e433f3b3cdb371dff74489f619f0e65311f5dd | 3,626,890 |
def is_average_pooling(layer):
"""Checks if layer is an average-pooling layer."""
AVERAGEPOOLING_LAYERS = (
keras_layers.AveragePooling1D,
keras_layers.AveragePooling2D,
keras_layers.AveragePooling3D,
keras_layers.GlobalAveragePooling1D,
keras_layers.GlobalAveragePooling2... | 7a0d91d291b13006341a86bf3864b612bad247c2 | 3,626,891 |
import os
def find_source_filename(source_name, dir_path):
"""Find the filename matching the source/module name
in the specified path. For example searching for "queue"
might return "queue.py" or "queue.pyc"
"""
source_filenames = [
os.path.join(dir_path, source_name + ext) for
... | 0360e57d4071c389d28768946551ad041236e6e3 | 3,626,892 |
def MergeDictsRecursively(original_dict, merging_dict):
"""
Merges two dictionaries by iterating over both of their keys and returning the merge
of each dict contained within both dictionaries.
The outer dict is also merged.
ATTENTION: The :param(merging_dict) is modified in the process!
:para... | 43174a7f5163a36eb850bc2c4d0f557790920189 | 3,626,893 |
def eq_assoc(u, v, eq=core.eq, n=None):
""" Goal for associative equality
>>> from logpy import run, var, fact
>>> from logpy.assoccomm import eq_assoc as eq
>>> fact(commutative, 'add') # declare that 'add' is commutative
>>> fact(associative, 'add') # declare that 'add' is associative
... | b7ba81dbd73091dc6a2e01ec5136c80cf3c49c88 | 3,626,894 |
import six
def printer(func=None, **options):
""" Decorator used to print whatever text is returned in the caller
function.
When a list or a tuple are returned, then the contents are iterated
and printed.
Options:
dedent - whether or not to dedent the text (default: ... | 632cfb59fbc213b3c8f69f05d6f8ff686207a6e3 | 3,626,895 |
import logging
import sys
import time
def stdoutlogger(name, level=logging.INFO):
"""
Return a standard python logger with a stdout handler attached and using a prefix
format that will make logging consistent between scripts.
"""
logger = logging.getLogger(name)
logger.setLevel(level)
... | 865f00a0baebf5032b1820893b0a062ff61ac501 | 3,626,896 |
import argparse
def parse_args():
"""
Parse command line arguments for CLI
:return: namespace containing the arguments passed.
"""
parser = argparse.ArgumentParser()
parser.add_argument(
'--login',
type=str,
required=True,
help="Full path to file containing JSO... | 0982407f808c9af9996bae0a36e8ae252cae0df6 | 3,626,897 |
from StringIO import StringIO
from io import StringIO
def strio():
"""
This was difficult to get right in doctests when porting to Python 3.
"""
try:
except ImportError:
return StringIO() | 9900b0a15da617278e3a5a1de8ef45a417e4e813 | 3,626,898 |
def getJamLengthMeters(detID):
"""getJamLengthMeters(string) -> double
Returns the jam length in meters within the last simulation step.
"""
return _getUniversal(tc.JAM_LENGTH_METERS, detID) | 750d7579ffded917e18faa5ec2f991576606aaf8 | 3,626,899 |
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