content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from typing import Tuple
from typing import Optional
import io
import textwrap
from re import I
def _define_property_shape(
prop: intermediate.Property,
cls: intermediate.ClassUnion,
url_prefix: Stripped,
class_to_rdfs_range: rdf_shacl_common.ClassToRdfsRange,
constraints_by_property: infer_for_sc... | 29483d27548a7fbd208f820e8e0821e0b121132f | 3,632,314 |
def row2string(row, sep=', '):
"""Converts a one-dimensional numpy.ndarray, list or tuple to string
Args:
row: one-dimensional list, tuple, numpy.ndarray or similar
sep: string separator between elements
Returns:
string representation of a row
"""
return sep.join("{0}".form... | f81a2ec54b8c37285715cadca4458918962440b9 | 3,632,315 |
def apply_kNNO(Xs, Xt, ys=None, yt=None, scaling=True, k=10, contamination=0.1):
""" Apply kNNO.
k-distance is the distance of its k-th nearest neighbour in the dataset
KNNO ranks all instances in a dataset by their k-distance, with higher distances signifying
more anomalous instances
Parameter... | 6a90757063ff20dba11075508bce7038295920a1 | 3,632,317 |
def build_aggregation(facet_name, facet_options, min_doc_count=0):
"""Specify an elasticsearch aggregation from schema facet configuration.
"""
exclude = []
if facet_name == 'type':
field = 'embedded.@type'
exclude = ['Item']
elif facet_name.startswith('audit'):
field = facet... | b8c3f337143a229401b9a41a8fde8903027cf67e | 3,632,320 |
def route_wrap_01_version(request_mapping: str):
"""
flask 路由映射包裹器
增加API_VERSION
:param request_mapping:
:return:
"""
return '{}/{}'.format(API_VERSION, request_mapping) | 0a3db2ed132c1f2233817a8154c5c1c87872d6dc | 3,632,322 |
def spawn(pool):
"""spawn a greenlet
it will be automatically killed after the test run
"""
return pool.spawn | fadea4b814e77f7fb26af27f0cc7bce1189a7dcf | 3,632,323 |
from typing import Any
import json
def from_json_util(json_str: str) -> Any:
"""Load an arbitrary datatype from its JSON representation.
The Out-of-proc SDK has a special JSON encoding strategy
to enable arbitrary datatypes to be serialized. This utility
loads a JSON with the assumption that it follo... | 5da695fb260b1df35dc91dfb8ef9026b04472d6a | 3,632,324 |
def min_row_dist_sum_idx(dists):
"""Find the index of the row with the minimum row distance sum
This should return the index of the row index with the least distance overall
to all other rows.
Args:
dists (np.array): must be square distance matrix
Returns:
int: index of row wit... | 7bddc4e58344e519a2bd928187db3a6b65e17118 | 3,632,325 |
def inline(text):
"""
Convert all newline characters to HTML entities:
This can be used to prevent Hypertag from indenting lines of `text` when rendering parent nodes,
and to safely insert `text` inside <pre>, <textarea>, or similar elements.
"""
return text.replace('\n', ' ') | 658f7e5adbf5747ea069fad8a9599e9bd499a381 | 3,632,326 |
def align_pos(xyz, test_crd, ref_crd, ind=None):
"""Translates a set of atoms such that two positions are coincident.
Parameters
----------
xyz : (N, 3) array_like
The atomic cartesian coordinates.
test_crd : (3,) array_like
Cartesian coordinates of the original position.
test_c... | ffa6001e20a4e4a1379e6a95139946aa91a5bdd0 | 3,632,327 |
from typing import Optional
from typing import Sequence
def get_orderable_db_instance(availability_zone_group: Optional[str] = None,
engine: Optional[str] = None,
engine_version: Optional[str] = None,
instance_class: Optional[st... | 6557de19d6c14d903d9f3058f7428ffe700633d0 | 3,632,328 |
def publish_channel_url():
"""open_channel_url: returns url to publish channel
Args: None
Returns: string url to publish channel
"""
return PUBLISH_CHANNEL_URL.format(domain=DOMAIN) | 7ba59e32746b9ffa9c9a46fd073cfbb1c3905e9f | 3,632,329 |
def hist_counts(df_acts=None, lst_acts=None, df_ac=None, y_scale="linear", idle=False,
figsize=None, color=None, file_path=None):
"""
Plot a bar chart displaying how often activities are occurring.
Parameters
----------
df_acts : pd.DataFrame, optional
recorded activities fr... | 4e9820d25bd2f33de8269f413fbce0b1898fd7fa | 3,632,330 |
def random_dense(shape, fortran):
"""Generate a random qutip Dense matrix of the given shape."""
return qutip.core.data.Dense(random_numpy_dense(shape, fortran)) | 869c8cd2972b40f82d73403ed5c54d170fe3dcb5 | 3,632,331 |
import torch
def bo_step(X, y, objective, bounds, GP=None, acquisition=None, q=1, state_dict=None, *GP_args,
**GP_kwargs):
"""
One iteration of Bayesian optimization:
1. Fit GP model using (X, y)
2. Create acquisition function
3. Optimize acquisition function to obtain cand... | e752091e5aaf3b42e3e8f21a21f0368485f60c25 | 3,632,332 |
def validate_inputs(input_data):
"""Check prediction inputs against schema."""
# set many=True to allow passing in a list
schema = InsuranceDataRequestSchema(strict=True, many=True)
errors = None
try:
schema.load(input_data)
except ValidationError as exc:
errors = exc.messages ... | e0faacabb729d191308bdf1d5710525b529d4793 | 3,632,333 |
def published_stats_list(request):
"""
List cumulative stats about projects published.
The request may specify the desired resource type
"""
resource_type = None
# Get the desired resource type if specified
if 'resource_type' in request.GET and request.GET['resource_type'] in ['0', '1']:
... | 308ef79fb6f51d192adb31849dd6bb75a46fe469 | 3,632,334 |
def get_entity(name):
"""Get an entity by the given name.
Args:
name (str): namespace.entity_name
Returns:
OntologyEntity: The entity with the given name.
"""
ns, n = name.split(".")
return _namespace_registry._get(ns)._get(n) | bd00058f8d3af4d29b35bcf0cc336f4c567baf8a | 3,632,335 |
def tst():
"""members page."""
return render_template('users/testing2.html') | 042463af7cc3742e78f744bc66ad09c3060ca877 | 3,632,336 |
def get_bq_col_type(col_type):
"""
Return correct SQL column type representation.
:param col_type: The type of column as defined in json schema files.
:return: A SQL column type compatible with BigQuery
"""
lower_col_type = col_type.lower()
if lower_col_type == 'integer':
return 'I... | 86cac08a04d804cc6addbeee86014f1aa6d35735 | 3,632,337 |
def _do_boundary_search(search_term):
"""
Execute full text search against all searchable boundary layers.
"""
result = []
query = _get_boundary_search_query(search_term)
with connection.cursor() as cursor:
wildcard_term = '%{}%'.format(search_term)
cursor.execute(query, {'term'... | b2cc74b7ba436c0c57bbb7505d964d79354a36f5 | 3,632,338 |
def prices(identifier, start_date=None, end_date=None, frequency='daily',
sort_order='desc'):
"""
Get historical stock market prices or indices.
Args:
identifier: Stock market symbol or index
start_date: Start date of prices (default no filter)
end_date: Last date (defaul... | 145d8ea607a1e374e205ef337345f7b9d6064479 | 3,632,339 |
def x1y1x2y2_to_xywh(x1y1x2y2):
"""Convert [x1 y1 x2 y2] box format to [x y w h] format."""
if isinstance(x1y1x2y2, (list, tuple)):
# Single box given as a list of coordinates
assert len(x1y1x2y2) == 4
ct_x, ct_y = (x1y1x2y2[3] + x1y1x2y2[1]) / 2, (x1y1x2y2[2] + x1y1x2y2[0]) / 2
... | b5535ace312ca2f790f4dcb66ed9e53223b90649 | 3,632,341 |
def col(loc, strg):
"""
Returns current column within a string, counting newlines as line separators.
The first column is number 1.
Note: the default parsing behavior is to expand tabs in the input string
before starting the parsing process. See
:class:`ParserElement.parseString` for more
... | 0dfc4387e391c4823939350ad19c60d106211a58 | 3,632,342 |
def create_model_fn(model_class, hparams, use_tpu=False):
"""Wraps model_class as an Estimator or TPUEstimator model_fn.
Args:
model_class: AstroModel or a subclass.
hparams: ConfigDict of configuration parameters for building the model.
use_tpu: If True, a TPUEstimator model_fn is returned. Otherwise ... | 83be600771b8e64c610db0d3d16fe10ba668fbd0 | 3,632,343 |
from typing import Any
def boolean(value: Any) -> bool:
"""Validate and coerce a boolean value."""
if isinstance(value, str):
value = value.lower()
if value in ("1", "true", "yes", "on", "enable"):
return True
if value in ("0", "false", "no", "off", "disable"):
... | 781dbb2e30448065d8dc65b42ab02914a3338b43 | 3,632,344 |
def unmap(data, count, inds, fill=0):
"""
Unmap a subset of item (data) back to the original set of items (of size count)
:param data: input data
:param count: the total count of data
:param inds: the selected indices of input data
:param fill: filled value
:return: unmaped data
"""
... | 3cc361650644275673e6340f8d6a216071b0c3c9 | 3,632,345 |
def recursive_feature(G, f, n):
"""
G: iGraph graph with annotations
func: string containing function name
n: int, recursion level
Computes the given function recursively on each vertex
Current precondition: already have run the computation for G, func, n-1.
"""
retur... | 4516e85cddea50dc9a1f14448a7b950a0620e3f0 | 3,632,347 |
import unicodedata
def remove_accents(string):
"""
Removes unicode accents from a string, downgrading to the base character
"""
nfkd = unicodedata.normalize('NFKD', string)
return u"".join([c for c in nfkd if not unicodedata.combining(c)]) | 41c8e05aa8982c85cf5cf2135276cdb5e26fefec | 3,632,348 |
from typing import Optional
def __get_a0( # pylint: disable=invalid-name
n: int, a0: Optional[np.ndarray] = None
) -> np.ndarray:
"""
Returns initial parameters for fitting algorithm.
:param n: Number of parameters
:param a0: Initial parameters value. Optional
:return: nd.array
"""
i... | 80b5d974dd6187746215191cc1f4de1ae135b93e | 3,632,349 |
def convert_yaw_to_old_viewpoint(yaw):
""" we initially had viewpoint coordinates inverted
Example:
>>> import math
>>> TAU = 2 * math.pi
>>> old_viewpoint_labels = [
>>> ('left' , 0, 0.000 * TAU,),
>>> ('frontleft' , 45, 0.125 * TAU,),
>>> ... | 7659e15bf7f4693ac7c6223b8f4600450bc7f2fe | 3,632,350 |
def extract_lexical_features_test(nlp, tweet_list):
"""Provides tokenization, POS and dependency parsing
Args:
nlp (spaCy model): Language processing pipeline
"""
result = []
texts = (tweet for tweet in tweet_list)
for doc in nlp.pipe(texts, batch_size=10000, n_threads=3):
setti... | b0f87996558c4b2e1d77b59068e8ad259524a455 | 3,632,352 |
def get_hostname():
""" Return hostname. """
return tg.config.get('workbox.hostname') | 367dda60f71d169c6490913a3ee3f8befc83b738 | 3,632,353 |
import http
def geocode_location(api_key, loc):
"""Get a geocoded location from gooogle's geocoding api."""
try:
parsed_json = http.get_json(GEOCODING_URL, address=loc, key=api_key)
except IOError:
return None
return parsed_json | 95c820abc58a13cd57e662e78bfab8fceac5eadf | 3,632,354 |
def degree(f, *gens, **args):
"""
Return the degree of ``f`` in the given variable.
The degree of 0 is negative infinity.
Examples
========
>>> degree(x**2 + y*x + 1, gen=x)
2
>>> degree(x**2 + y*x + 1, gen=y)
1
>>> degree(0, x)
-inf
"""
allowed_flags(args, ['gen'... | a6b5e2ba9228ea1477234c0e16477dd603fb9598 | 3,632,355 |
from typing import Dict
def fit_model_sector(sector_corpus: Dict[DocId, Token]) -> sbmtm:
"""Fits the model taking the sector corpus data structure as an input
Args:
sector_corpus: a dict where keys are doc ids and
values are the tokenised descriptions
Returns:
The model
... | d025a0f4faac53b4b21486e159a0310c78dc72b8 | 3,632,356 |
def get_simulated_matches(path, met, sample_to_match, pop_var):
"""Selects initial conditions from cosmic data to match to star sample
Parameters
----------
path : `str`
path to cosmic data
met : `float`
metallicity of cosmic data file
sample_to_match : `DataFrame`
A d... | ecbb46f284f7b6748031b0907813deaad8967eba | 3,632,357 |
def _get_url_ext(url: str):
"""
>>> _get_url_ext('http://example.com/blog/feed')
'feed'
>>> _get_url_ext('http://example.com/blog/feed.xml')
'xml'
>>> no_error = _get_url_ext('http：//example.com')
"""
try:
url_path = urlparse(url).path.strip('/')
except ValueError:
re... | 61b94bd2c98686192a47ade9bb240bc4c58904c2 | 3,632,358 |
def connect_server():
"""Connect to azure cosmos DB.
Connet to azure cosmos DB.
Need to insert ID, DB name, table name, and key.
Args:
None
Returns:
clt(str): an instance for connecting to azure cosmos DB server
"""
clt = client.Client(
'wss://<YOURID>... | 1826b4676af381882710a8802392f7f1d4f2253e | 3,632,359 |
def checkCpuTime(sleeptime=0.2):
"""Check if cpu time works correctly"""
if checkCpuTime.passed:
return True
# First test that sleeping does not consume cputime
start1 = process_time()
sleep(sleeptime)
t1 = process_time() - start1
# secondly check by comparing to cpusleep (where we ... | 5b7db840f56b5eafdbfa857c470c316c257c9bac | 3,632,360 |
def load_ply(path):
"""
Loads a 3D mesh model from a PLY file.
:param path: A path to a PLY file.
:return: The loaded model given by a dictionary with items:
'pts' (nx3 ndarray), 'normals' (nx3 ndarray), 'colors' (nx3 ndarray),
'faces' (mx3 ndarray) - the latter three are optional.
"""
... | 289c0854bc3270dafab5689bc53d2507ff27c67c | 3,632,362 |
def parse_range(rng, dictvars={}):
"""Parse a string with an integer range and return a list of numbers, replacing special variables in dictvars."""
parts = rng.split('-')
if len(parts) not in [1, 2]:
raise ValueError("Bad range: '%s'" % (rng,))
parts = [int(i) if i not in dictvars else dictva... | 214109a71c84d06241e29cacaa052d9ce00302c5 | 3,632,363 |
from typing import Union
from typing import Iterable
from typing import List
from pathlib import Path
def relpaths(basepath: _path_t, pattern: Union[str, Iterable[_path_t]]) -> List[str]:
"""Convert a list of paths to relative paths
Parameters
----------
basepath : Union[str, Path]
Path to us... | 80c9febd541d8fd1ab190b2ef36e8929ee387b08 | 3,632,364 |
def binary_backtests_returns(
backtests: pd.DataFrame,
) -> pd.DataFrame:
"""
Converts a Horizon backtest data frame into a binary backtests of directions
"""
return backtests.diff().apply(np.sign).dropna() | 0355cd48620cbdbe54eb4ee48e82f7315f069263 | 3,632,365 |
def calculate_students_features_csv(entry_id, xmodule_instance_args):
"""
Compute student profile information for a course and upload the
CSV to an S3 bucket for download.
"""
# Translators: This is a past-tense verb that is inserted into task progress messages as {action}.
action_name = ugettex... | ccf8eae3b9732535c94381ba1909f36bce52556d | 3,632,366 |
def save_genre(row: dict):
"""Genre's control and save in data base."""
try:
result: Genres = session.query(Genres) \
.filter(Genres.name == row.get('genre_name')) \
.one()
return result
except MultipleResultsFound:
pri... | 0c7e26082816a2639cc4561a1e9ee5f2697a4175 | 3,632,368 |
def specializations(examples_so_far, h):
"""Specialize the hypothesis by adding AND operations to the disjunctions"""
hypotheses = []
for i, disj in enumerate(h):
for e in examples_so_far:
for k, v in e.items():
if k in disj or k == 'GOAL':
continue
... | 5f21edd18477c09d37a03026073c0120b6be41b9 | 3,632,369 |
def formulate_contingency(problem: LpProblem, numerical_circuit: OpfTimeCircuit, flow_f, ratings, LODF, monitor,
lodf_tolerance):
"""
:param problem:
:param numerical_circuit:
:param flow_f:
:param LODF:
:param monitor:
:return:
"""
nbr, nt = ratings.shape
... | ecc5deb3b689a5802341d48e81382d2d602f1ebc | 3,632,370 |
def max_pooling3d(inputs,
pool_size, strides,
padding='valid', data_format='channels_last',
name=None):
"""Max pooling layer for 3D inputs (e.g. volumes).
Arguments:
inputs: The tensor over which to pool. Must have rank 5.
pool_size: An integer or tuple... | 49756ea26e58549115408fbcb4ce179442a09942 | 3,632,371 |
def parareal_engine(x_0, U, num_iter, coarse_model="learned"):
"""Rolls out a trajectory using Parareal
Args:
x_0: Initial state
U: Control sequence
num_iter: Number of Parareal iterations to use for prediction
coarse_model: Learned/Analytical coarse model
Returns:
X: The corresponding state seq... | bd589650711d510fcffb2033dd5f7a501dc4e041 | 3,632,372 |
def plot_posterior_op(trace_values, ax, kde_plot, point_estimate, round_to,
alpha_level, ref_val, rope, text_size=16, **kwargs):
"""Artist to draw posterior."""
def format_as_percent(x, round_to=0):
return '{0:.{1:d}f}%'.format(100 * x, round_to)
def display_ref_val(ref_val):
... | 13d7d12dfac13f803fb08b49970471e4f97c7bff | 3,632,373 |
from operator import sub
from re import M
def change_theme(file: str, theme_name: str, logfile: str) -> bool:
"""
Change Oh My ZSH Theme
"""
if get_zsh_theme(file, logfile):
current_file = read_file_log(file, logfile)
current_theme = get_zsh_theme(file, logfile)[1]
new_theme = ... | 55438f7d93779417aff4dfa4170997269b200dca | 3,632,374 |
def check_tensor(data):
"""Ensure that data is a numpy 4D array."""
assert isinstance(data, np.ndarray)
if data.ndim == 2:
data = data[np.newaxis,np.newaxis,...]
elif data.ndim == 3:
data = data[np.newaxis,...]
elif data.ndim == 4:
pass
else:
raise RuntimeError('... | d641645e9a2c780d52c5e635859bdfcce61f86ab | 3,632,375 |
from typing import Type
from typing import Optional
def _find_first_ref(ref: Ref, message_type: Type[B]) -> Optional[B]:
""" Finds and returns (if exists) the first instance of the specified message type
within the specified Ref.
"""
# Get the body message, if it exists
body = _get_ref_body(ref)
... | 474ad2a2c874c6ae226475fc1e4b144fdd4f72a1 | 3,632,376 |
def verify_activation_token(*, uidb64, token):
"""
:param uidb64: (str) Base 64 of user PK.
:param token: (str) Hash.
:return: (bool) True if user verified, False otherwise.
"""
user_id = force_text(urlsafe_base64_decode(uidb64))
try:
user = User.objects.get(pk=user_id)
except ... | f184a85852906526434dc54b2e26491ad3dafc51 | 3,632,377 |
def read_protein_from_file(file_pointer):
"""The algorithm Defining Secondary Structure of Proteins (DSSP) uses information on e.g. the
position of atoms and the hydrogen bonds of the molecule to determine the secondary structure
(helices, sheets...).
"""
dict_ = {}
_dssp_dict = {'L': 0, 'H': 1,... | 071a7b04b652261f83311e250e92884e95a4e818 | 3,632,379 |
def match(string, rule='IRI_reference'):
"""Convenience function for checking if `string` matches a specific rule.
Returns a match object or None::
>>> assert match('%C7X', 'pct_encoded') is None
>>> assert match('%C7', 'pct_encoded')
>>> assert match('%c7', 'pct_encoded')
"""
... | c6c2079786651bfaa1ba819251e1d51a276bf8cd | 3,632,380 |
from typing import List
def verify_td3(mrz: List[str]) -> bool:
"""Verify TD3 MRZ"""
if mrz[0][0] != "P":
return False
# if mrz[0][1]: # At the discretion of the issuing State or organization or "<"
# if mrz[0][2:5]: # ISSUING STATE OR ORGANIZATION
# if mrz[0][5:44]: # NAME
if calculat... | 13dca85d0f91cac9bbf759f8a5171e73ddfb4836 | 3,632,381 |
def compute_pwcca(acts1, acts2, epsilon=0.):
""" Computes projection weighting for weighting CCA coefficients
Args:
acts1: 2d numpy array, shaped (neurons, num_datapoints)
acts2: 2d numpy array, shaped (neurons, num_datapoints)
Returns:
Original cca coefficient mean and weighted mean
... | 17f0b6674cd1c45435eb73bc4e754543640543d6 | 3,632,382 |
def read_table(srm_file):
"""
Reads SRM compositional data from file.
For file format information, see:
http://latools.readthedocs.io/en/latest/users/configuration/srm-file.html
Parameters
----------
file : str
Path to SRM file.
Returns
-------
SRM compositions : panda... | 6ec87cab30162af55e3cce659b3ef7a205857595 | 3,632,383 |
def walker_method(for_class=object, methods_list=None):
"""A decorator to add something to the default walker methods,
selecting on class
"""
if methods_list is None: # handle early binding of defaults
methods_list = fallback_walker_method_list
def wrap(walker):
# wrap a walker wi... | b500f04510695e5cfd88590feaa75b27aee3b5b8 | 3,632,384 |
import pandas as pd
from IPython.display import display
def get_data(name_dataset='index',
verbose=True,
address="../datasets/",):
"""
This function is to load dataset from the git repository
:param name_dataset: name of dataset (str)
:param verbose:
:param address: url o... | fa518e744d43950ebcf65d00a5aa474d4fb36443 | 3,632,385 |
import torch
def copy_valid_indices(
acts, # type: torch.Tensor
target, # type: List[List[int]]
act_lens, # type: List[int]
valid_indices, # type: List[int]
):
# type: (...) -> (torch.Tensor, List[List[int]], List[int])
"""Copy the CTC inputs without the erroneous samples"""
if len(val... | 9eac2b7304ff5157ca13fae9d790af6c2b67d9c7 | 3,632,386 |
def is_odd(num: int) -> bool:
"""Is num odd?
:param num: number to check.
:type num: int
:returns: True if num is odd.
:rtype: bool
:raises: ``TypeError`` if num is not an int.
"""
if not isinstance(num, int):
raise TypeError("{} is not an int".format(num))
return num % 2 ==... | 0e5781596a99909e58583859948332c3afb06fb0 | 3,632,387 |
def cross_entropy_loss(y_hat, y):
"""
Cross entropy loss
y_hat: predict y after softmax, shape:(M,d), M is the #of samples
y: shape(M,d)
"""
loss = np.mean(np.sum(- y * np.log(y_hat), axis=-1))
dy = y_hat - y
return loss, dy | 81f6dc61d0ed9d9e5eac4a41042679b3ea01167d | 3,632,388 |
import string
def string_list(resource_name, encoding='utf-8'):
"""Package resource wrapper for obtaining resource contents as list of
strings.
The function uses the 'string' method and splits the resulting string
in lines.
Params:
resource_name: Relative path to the resource in the pack... | 88e7103056e38020670a74a19bfeee90326e7d38 | 3,632,389 |
from typing import Optional
def rpc_get_name() -> Optional[str]:
"""Retrieve the JsonRpc id name."""
global _RpcName
return _RpcName | 2b7d7e9b37b00281b0791e446e5ad4bacee78c4b | 3,632,391 |
def _epd_platform_from_raw_spec(raw_spec):
""" Create an EPDPlatform instance from the metadata info returned by
parse_rawspec.
if no platform is defined ('platform' and 'osdist' set to None), then
None is returned.
"""
platform = raw_spec[_TAG_PLATFORM]
osdist = raw_spec[_TAG_OSDIST]
i... | b6757206e6753441478629519531b0ec5adfc83a | 3,632,392 |
def index(request):
"""The home page for Distance Tracker."""
if request.user.is_authenticated:
today = date.today()
cur_week = today.isocalendar()[1]
cur_month = today.month
cur_year = today.year
exercises_week = Exercise.objects.filter(owner=request.user,
... | 279f6e7c1cb9f2821ebee7b138c7b8b22e60768e | 3,632,393 |
import runpy
import imp
def mod_from_file(mod_name, path):
"""Runs the Python code at path, returns a new module with the resulting globals"""
attrs = runpy.run_path(path, run_name=mod_name)
mod = imp.new_module(mod_name)
mod.__dict__.update(attrs)
return mod | 3ea8109d912582555b76816f55fbb632ba82f189 | 3,632,394 |
def interpolation(x0: float, y0: float, x1: float, y1: float, x: float) -> float:
"""
Performs interpolation.
Parameters
----------
x0 : float.
The coordinate of the first point on the x axis.
y0 : float.
The coordinate of the first point on the y axis.
x1 : float.
T... | f8fc96c6dc6c2eeeeceb22f92b32023f3873fe3e | 3,632,395 |
import collections
def product_counter_v3(products):
"""Get count of products in descending order."""
return collections.Counter(products) | 22c57d50dc36d3235e6b8b642a4add95c9266687 | 3,632,397 |
def remove_noise(line,minsize=8):
"""Remove small pixels from an image."""
if minsize==0: return line
bin = (line>0.5*np.amax(line))
labels,n = ndimage.label(bin)
sums = ndimage.sum(bin,labels,range(n+1))
sums = sums[labels]
good = np.minimum(bin,1-(sums>0)*(sums<minsize))
return good | 1e19fad38a081db35ac31e3e19d224f4cb8e7d59 | 3,632,398 |
import textwrap
def _ParseFormatDocString(printer):
"""Parses the doc string for printer.
Args:
printer: The doc string will be parsed from this resource format printer.
Returns:
A (description, attributes) tuple:
description - The format description.
attributes - A list of (name, descript... | f5aaffb91cbedbc1b6e0da64cdfb3ff4adfa684e | 3,632,399 |
def build_answers_xml(selector, args):
""" builds an answers xml string for a selector class using
default answers for the selector's questions. If any other attributes
were included in the call, they are appended to as part of the
work-info. """
# build an answers xml tree
answers = ET.Ele... | 9290190fef3396990a3a4199d81c50f413ee3bc1 | 3,632,400 |
import time
def give_me_the_answer(question, clever=False):
"""This gives you the answer.
Parameters
----------
question: str
the question you are asking.
clever: bool, optional
whether or not the answer should be clever or not
Returns
-------
The answer
"""
... | a2b8f7fd9cd131caa6d2d99c694d76cef34ead82 | 3,632,401 |
def round_down(x: float, decimal_places: int) -> float:
"""
Round a float down to decimal_places.
Parameters
----------
x : float
decimal_places : int
Returns
-------
rounded_float : float
Examples
--------
>>> round_down(1.23456, 3)
1.234
>>> round_down(1.2345... | f1accd23ffef4fbceb0aa75098862dfb75e03c61 | 3,632,402 |
import importlib
def import_from_string(val, setting_name):
"""
Attempt to import a class from a string representation.
"""
try:
parts = val.split(".")
module_path, class_name = ".".join(parts[:-1]), parts[-1]
module = importlib.import_module(module_path)
return getattr... | 45bd96b219c808a5cf928e1b7364aa3c3178160a | 3,632,403 |
def datatype_to_tracktype(datatype):
"""
Infer a default track type from a data type. There can
be other track types that can display a given data type.
Parameters
----------
datatype: str
A datatype identifier (e.g. 'matrix')
Returns
-------
str, str:
A track type ... | fb0679ade37478ee0b9a451ce667bfd23f86e1ae | 3,632,404 |
def rossler(x, y, z, a, b, c):
""" Rössler System of Ordinary Differential Equations """
dx = - y - z
dy = x + a*y
dz = b + z*(x - c)
return dx, dy, dz | bcf27c7ff8223681d6dc7d0c49497e975b826d80 | 3,632,405 |
import re
def get_extension(filename):
"""
Extract file extension from filename using regex.
Args:
filename (str): name of file
Returns:
str: the file extension
"""
match = re.search(r"\.(?P<ext>[^.]+)$", filename)
if match:
return match.group("ext")
raise Val... | 8f5195b339a153d5fa144182505dba986992d4df | 3,632,407 |
import asyncio
def run_async(func):
"""
Allows you to run a click command asynchronously.
"""
func = asyncio.coroutine(func)
def inner_handler(*args, **kwargs):
run(func(*args, **kwargs))
return update_wrapper(inner_handler, func) | 29b0d731d101159f7ec7311dc6beb6ab56523022 | 3,632,408 |
def Conv2D(input_tensor, input_shape, filter_size, num_filters, strides=1, name=None):
"""
Handy helper function for convnets.
Performs 2D convolution with a default stride of 1. The kernel has shape
filter_size x filter_size with num_filters output filters.
"""
shape = [filter_size, filter_size, input_shape, nu... | 91505ed82eaf1585023edba55848a33e4145bbc3 | 3,632,409 |
def scale_val(val, factor, direction):
"""Scale val by factor either 'up' or 'down'."""
if direction == 'up':
return val+(val*factor)
if direction == 'down':
return val-(val*factor)
raise ValueError('direction must be "up" or "down"') | 16c2efe16fc787fe4461fb0ae640e2cf22d556e0 | 3,632,410 |
def ttee(iterable, n=2):
"""
>>> ttee("ABC")
(('A', 'B', 'C'), ('A', 'B', 'C'))
"""
return tuple(map(tuple, tee(iterable, n))) | 7b5b6ff83492f4df5cbe845367d73bbadd0c6b10 | 3,632,411 |
def addattrs(field, css):
"""
在模板的form的field中，特别是input中添加各种attr
"""
attrs = {}
definition = css.split(',')
for d in definition:
if '=' not in d:
attrs['class'] = d
else:
t, v = d.split('=')
attrs[t] = v
return field.as_widget(attrs=attrs) | cdbb2b4b44b6e7facbe2af44d503c3118eb31ef7 | 3,632,412 |
def regular_periodic(freqs, amplitudes, phase, size=501):
"""Generate periodic test data sampled at regular intervals: superposition
of multiple sine waves, each with multiple harmonics.
"""
times = np.linspace(0, 2, size)
values = np.zeros(size)
for (i,j), amplitude in np.ndenumerate(amplitudes... | bfe23122e8edd3a279caed27a758edd353f15bc7 | 3,632,413 |
from bread.contrib.reports.fields.queryfield import parsequeryexpression
def generate_excel_view(queryset, fields, filterstr=None):
"""
Generates an excel file from the given queryset with the specified fields.
fields: list [<fieldname1>, <fieldname2>, ...] or dict with {<fieldname>: formatting_function(o... | ca03a09ee3a6a2e17df542ab4c124c4078677b4a | 3,632,414 |
def get_tag_by_name(repo: Repository, tag_name: str) -> Tag:
"""Fetches a tag by name from the given repository"""
ref = get_ref_for_tag(repo, tag_name)
try:
return repo.tag(ref.object.sha)
except github3.exceptions.NotFoundError:
raise DependencyLookupError(
f"Could not find... | d8191f819e7a2f1cdcaeabb52cda452fd3e555bf | 3,632,416 |
def get_geo_selected(results, datas, extras, filters=False):
"""Get specific Geography based on existing ids."""
wards = []
all_list = get_all_geo_list(filters)
datas.remove('') if '' in datas else datas
extras.remove('') if '' in extras else extras
results['wards'] = datas
area_ids = list(m... | 755b8461f0decc320c54174541bef0672585bcc8 | 3,632,417 |
def notify(text, boxwidth=60):
"""Create a 'notification' styled textbox"""
return box(text, decor="*", boxwidth=boxwidth) | 1fe8d98b890bf7c2cd6aaee27b2c11dca6b8046c | 3,632,418 |
def returns_player(method):
"""
Decorator: Always returns a single result or None.
"""
def func(self, *args, **kwargs):
"decorator"
rfunc = returns_player_list(method)
match = rfunc(self, *args, **kwargs)
if match:
return match[0]
else:
ret... | 22549888600556804ae3446a6c7442e94841813f | 3,632,419 |
def tracks(date):
"""
Query the charts/beatport/tracks endpoint for the given date.
Data available on Fridays.
https://api.chartmetric.com/api/charts/beatport
**Parameters**
- `date`: string date in ISO format %Y-%m-%d
**Returns**
A list of dictionary of tracks on Beatport ch... | e117fe57e78eb4780f2ba8850b1fe80d7ab43c0c | 3,632,420 |
def cos_sim(A_mat, B_vec):
"""
item-vevtorの行列(またはベクトル)が与えられた際にitem-vevtor間のコサイン類似度行列を求める
"""
d = np.dot(A_mat, B_vec) # 各ベクトル同士の内積を要素とする行列
# 各ベクトルの大きさの平方根
A_norm = (A_mat ** 2).sum(axis=1, keepdims=True) ** .5
B_norm = (B_vec ** 2).sum(axis=0, keepdims=True) ** .5
# それぞれのベクトルの大きさの平方根で... | 823778eaaeb8bb85e93544c5b6d09001cba0e236 | 3,632,421 |
def parse_dtype(space):
"""Get a tensor dtype from a OpenAI Gym space.
Args:
space: Gym space.
Returns:
TensorFlow data type.
"""
if isinstance(space, gym.spaces.Discrete):
return tf.int32
if isinstance(space, gym.spaces.Box):
return tf.float32
raise NotImplementedError() | 903824c5c013c9081bd988ca437f123ebb322ef8 | 3,632,422 |
def tf_efficientnet_b2_ap(pretrained=True, **kwargs):
""" EfficientNet-B2. Tensorflow compatible variant """
kwargs['bn_eps'] = BN_EPS_TF_DEFAULT
kwargs['pad_type'] = 'same'
out_indices = [1, 2, 4, 6]
model = _gen_efficientnet(
'tf_efficientnet_b2_ap', channel_multiplier=1.1, depth_multipli... | 61ebd0953be7024d262ecd509bfd6d4886431afb | 3,632,423 |
def plot_ld_curves(ld_stats, stats_to_plot=[], rows=None, cols=None,
statistics=None, fig_size=(6,6), dpi=150, r_edges=None,
numfig=1, cM=False, output=None, show=False):
"""
Plot single set of LD curves
LD curves are named as given in statistics
ld_stats is th... | 5bf8128cce7a4b85347787e4552444f69f68873a | 3,632,424 |
def onehottify_2d_array(a):
"""
https://stackoverflow.com/questions/36960320/convert-a-2d-matrix-to-a-3d-one-hot-matrix-numpy
:param a: 2-dimensional array.
:return: 3-dim array where last dim corresponds to one-hot encoded vectors.
"""
# https://stackoverflow.com/a/46103129/ @Divakar
def a... | a612b6fa7ba2bc59f48aec85ee2e63e9d3cf86ac | 3,632,425 |
def getUserCompetencies(cnx, exceptUserIDs):
"""
Returns array of persons with their competences as values
"""
competencies = {}
cnx = establishDBConnection(dbconfig)
cursor = cnx.cursor()
placeholder = '%s'
placeholders = ', '.join(placeholder for unused in exceptUserIDs)
query = ("... | 4cd73c2e01fe76abad337cfd4929edcce297c92e | 3,632,426 |
def add_induct_def(name, T, eqs):
"""Add the given inductive definition.
The inductive definition is specified by the name and type of
the constant, and a list of equations.
For example, addition on natural numbers is specified by:
('plus', nat => nat => nat,
[(plus(0,n) = n, plus(Suc(m), n) ... | 7de7884e36cceba2a49377230a7932ff133f902f | 3,632,427 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.