content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def sourcecontrol_repos_repo_id_refs_get(repo_id): # noqa: E501
"""sourcecontrol_repos_repo_id_refs_get
# noqa: E501
:param repo_id: Source control repository identifier
:type repo_id: str
:rtype: None
"""
return 'do some magic!' | 880635586cca99cbd759f33ce5cfa6b8f56ee3eb | 3,621,851 |
from typing import Union
def duration_offpeak(
ts_left: Union[pd.Timestamp, pd.DatetimeIndex], freq: str = None
) -> Union[Q_, pd.Series]:
"""
Total duration of offpeak periods in a timestamp.
See also
--------
.tools.stamps.duration
"""
return duration_base(ts_left, freq) - duration_... | c0dfeb82477597d72c61a5d9073ad4827de749db | 3,621,852 |
def truncate_labels(labels):
"""
(1) replacing row[0] by 10, and move it to the last of row
(2) replace the second 10 by -1 row wise
"""
def do_one_row(row):
erase = False
for i, _ in enumerate(row):
if erase:
row[i] = -1
else:
... | 0cbf05f935ee12e123475ac58cfb47918ac9b4da | 3,621,853 |
import warnings
import math
def sample(problem, N, calc_second_order=True, seed=None, skip_values=1024):
"""Generates model inputs using Saltelli's extension of the Sobol' sequence.
Returns a NumPy matrix containing the model inputs using Saltelli's sampling
scheme. Saltelli's scheme extends the Sobol' s... | af179d538a9ab51a07332199fe37573c5f6a6535 | 3,621,854 |
def create_wall(obj_name, document):
"""Create a wall."""
obj = document.addObject('Part::FeaturePython', obj_name)
origin = document.addObject('App::Origin', 'WallOrigin')
Wall(obj, origin)
WallViewProvider(obj.ViewObject)
return obj | b2352fc4dff59f1854cdce3eec73cef83d1ba557 | 3,621,855 |
def prepare_roi(image5d, roi_size, roi_offset):
"""Extracts a region of interest (ROI).
Calls :meth:`prepare_subimage` but expects size and offset variables to
be in x,y,z order following this software's legacy convention.
Args:
image5d: Image array as a 5D array (t, z, y, x, c), or 4D if
... | 867c33140b9413434e442025599562369a489443 | 3,621,856 |
from arbiter.async import run_tasks
from arbiter.task import create_task
def test_no_dependencies():
"""
run dependency-less tasks (with threads)
"""
executed_tasks = set()
def make_task(name, dependencies=(), should_succeed=True):
"""
Make a task
"""
function = ... | 66ac6963eaee611dc1613fb4f4308d78f0ef937e | 3,621,858 |
import json
def decode(s):
"""
Deserialize a DMRS object from a DMRS-JSON string.
"""
return from_dict(json.loads(s)) | 340f5a184a565de06f7139158896127a9ddf91b8 | 3,621,859 |
import copy
def cross_multiply_array(array_1, array_2=None, axis=0):
"""Cross multiply the arrays along the given axis.
Cross multiplies along axis and computes array_1.conj() * array_2
if axis has length M then a new axis of size M will be inserted directly succeeding the original.
Parameters
-... | 0c27c8b27dd1d3cc4cc07bba4f9b211e725b2b95 | 3,621,860 |
from typing import Union
def Create(
allow_multiple=True,
) -> Union[ZeroOrMorePhraseItem, OptionalPhraseItem]:
"""\
('@' <name> <<Arguments>>? <newline>?)*
- or -
('@' <name> <<Arguments>>? <newline>?)? # If 'allow_multiple' is False
"""
phrase_item = PhraseItem.Create(
... | 0e783eceaf3f1f206a9ed3d72af82a85800c2b7e | 3,621,861 |
def return_largest_region(image_bin):
"""Returns the largest region in the input image.
Parameters
----------
image_bin : (M, N) ndarray
A binary image.
Returns
-------
image_bin : (M, N) ndarray
The input binary image containing only the largest region.
"""
props =... | 40f6745b0908c7ee08c1563f3991a5e7880c720e | 3,621,862 |
def stretchedAmplitude(TA_file, pol_time, peak_min, peak_max, time_zero=None):
"""Takes in TA data and picks out the peak for the polaron state and returns
the average value so it can be used for fitting function. Must make sure to
pick the right energy range, peak_min and max are in eV."""
TA = np.loa... | 8f734bf778f0a1e768ab35acd1fc7b8a39eb3183 | 3,621,863 |
def _write_rollup_config(
ctx,
root_dir,
filename = "_%s.rollup.conf.js",
downlevel_to_es2015 = False):
"""Generate a rollup config file.
Args:
ctx: Bazel rule execution context
root_dir: root directory for module resolution (defaults to None)
filename: output ... | f9b8cf2621e0cf68f0bad9a02802c2500dda9b53 | 3,621,864 |
def raw_images_to_array(images):
"""
Decode and normalize multiple images from tfrecord data
:param images: list of images encoded as a png in a string
:return: a numpy array of size (N, 56, 56, channels), normalized for training
"""
image_list = []
for image_str in images:
image = d... | adac8756926ba92536ae4fdd0a7b32620d37d028 | 3,621,865 |
from typing import Dict
def create_model(model: str, config: Dict) -> object:
"""
Creates a model with a given configuration
Args:
model (str): name of the model
config (dict): dictionary of parameters
Returns:
(object): created model (HHVAEM, HMCVAEM, ...)
"""
if mod... | 19bdb172fb8890bee08ac63de929c213dc85996d | 3,621,866 |
import torch
def make_positions(tensor, padding_idx, onnx_trace=False):
"""Replace non-padding symbols with their position numbers.
Position numbers begin at padding_idx+1. Padding symbols are ignored.
"""
mask = tensor.ne(padding_idx).long()
return torch.cumsum(mask, dim=1) * mask + padding_idx | f59fad86a23ff76f184c0dd6a21a92722f4817f5 | 3,621,867 |
import requests
def get_song_list(playlist_url):
"""
This function get the song list in the form of "name creator" from the spotify page
"""
# validating the data
if not playlist_url.startswith("https://open.spotify.com"):
print("this is not a spotify url")
return []
elif play... | 10bc3b6f14cd93c9a4f525883c7a2d56f66bf234 | 3,621,868 |
import unittest
def makeTestSuiteV201101():
"""Set up test suite using v201101.
Returns:
TestSuite test suite using v201101.
"""
suite = unittest.TestSuite()
suite.addTests(unittest.makeSuite(CustomTargetingServiceTestV201101))
return suite | 05b925b4bcdd38ab9a6e4b71374a6ff44fe8eb57 | 3,621,869 |
def add_bond_features(X_df):
"""
Using the information about standard C-H,N-H and O-H bond distances, we compute features
which aims to find a notion of deviation from the expected bond distances.
"""
assert len(set(['atom_1', 'atom_0', 'x_0', 'x_1', 'y_0', 'y_1', 'z_0', 'z_1']) - set(X_df.columns))... | 9798a97d9ebd308552334db64672ee23e8c6a666 | 3,621,870 |
def port_to_ip_mapping(index):
"""
A user defined mapping port_id (kni) to ipv4.
"""
return {"vEth0_{}".format(index): "192.167.10.{}".format(index + 1)} | 81d981bc8742e1295cb279d6b47d0e97f012b679 | 3,621,871 |
def quote():
"""Get stock quote."""
current_userid = session["user_id"]
userbalance = get_userbal(db, current_userid)
userstocks = get_userstock(db, current_userid)
stocklist = get_stocklist(db, stocksid=True, prices=True)
if request.method == "POST":
response = lookup(request.form.get("... | 506b0a2398269f73d6dc2e78f31ac5a9743cf01b | 3,621,872 |
from typing import OrderedDict
def cleanup_dataframe(df, logger=None):
"""Cleans the dataframe
- strips new lines, double, single quotes; None -> nan, etc
- formats the column names for Bigquery input
"""
if logger:
logger.log_text("Cleaning up the dataframe", severity='INFO')
... | 4fd7788bc5c99a220845d93a7c0549acbc67bdf6 | 3,621,873 |
import re
def organize_key(filename):
"""用于sorted的key参数"""
if filename[0:2].upper() == 'AD':
return 0
name = re.findall(r"-([0-9]+[A-Z]*).pdf", filename)[0]
num = get_group_index(filename)
alpha = name.replace(num, '')
if len(alpha) == 1:
return int(num)*100+ord(alpha)-64 # 使用... | eee3c3e9f0f967212e7f38ea8781291b4794ed38 | 3,621,874 |
def launch_svr(X, y, sample_weight=None, kernel='linear', C=1):
"""Fit the classification SVMs according to the given training data.
Parameters
----------
X : array-like, shape (n_samples, n_features)
Training vectors.
y : array-like, shape (n_samples,)
Target values.
sample_weig... | 02ae4f86a6cac32e0af862cb24f6565f932e6729 | 3,621,875 |
def cancel_candidacy(request, candidacy):
"""Cancel your own, yet-unapproved candidacy."""
user = request.user
cd = get_candidacy(candidacy)
if user != cd.user:
return HttpResponseForbidden(u"Vous ne pouvez annuler que vos propres candidatures.")
m.JournalEntry.log(user, "Cancelled own appli... | 0a8f93934ccf3b530e6d27a5be1bad76798c7607 | 3,621,876 |
import random
def generate_rsa_keys(prime_lenth=4):
"""Return tuple of (open, close, mod)"""
start = 10 ** (prime_lenth-1)
end = (10 ** (prime_lenth)) - 1
p, q = get_generate_prime_pair(start=start, end=end)
n = p * q
print("p: {} q: {}".format(p, q))
print("n: {}".format(n))
eul... | 8c2e5b6b6d4db6d2667ac6e935c8a9ae429b28ef | 3,621,877 |
def cache_by_hashed_args(obj):
""" Decorator for caching a function values
.. deprecated:: v0.9.8.3
:func:`cache_by_hashed_args` will be removed in pyGSTi
v0.9.9. Use :func:`functools.lru_cache` instead.
"""
return lru_cache(maxsize=128)(obj) | 2fc95b7a248febd206703e48bdd0494dd0bca04d | 3,621,878 |
import numpy
def setBadRegions(exposure, badStatistic="MEDIAN"):
"""Set all BAD areas of the chip to the average of the rest of the exposure
Parameters
----------
exposure : `lsst.afw.image.Exposure`
Exposure to mask. The exposure mask is modified.
badStatistic : `str`, optional
... | 90b987039b13264ac205f28a12c90bb341e04a80 | 3,621,879 |
def humanize_list(elements):
""""
splits a list and add punctuations to it elements
"""
humanize_string = ''
if len(elements) > 1:
for element in elements:
if element == elements[len(elements)-2]: # second to last item
humanize_string = humanize_string + element.... | 3172ac89f763d7faca4ce31c41611ca6b6731896 | 3,621,880 |
import typing
def ark(row: typing.Mapping[str, str]) -> str:
"""The item ARK (Archival Resource Key)
Args:
row: An input CSV record.
Returns:
The item ARK.
"""
ark_prefix = "ark:/"
if row["Item ARK"].startswith(ark_prefix, 0):
return row["Item ARK"]
return ark_pre... | ea428fcddf26a5bfdad3ec1c4906e765b72b1f47 | 3,621,881 |
def common_member(a, b, natural_sort=True):
"""
Checks if two lists (or sets) have a common member, and if so, returns
the common members.
:param a: First list (or set)
:param b: Second list (or set)
:param bool natural_sort: Sort the resulting items naturally
(default: True)
:return: Tr... | 160f1429f412a52513be60d331d7cb15d03e64e7 | 3,621,883 |
import copy
def transforms_description(f):
"""
Decorator which deepcopies the description and extracts ['rnn'][0] from it.
Desperately needs to be obsoleted.
"""
@wraps(f)
def wrapper(description, *args, **kwds):
description = copy.deepcopy(description)
try: desc = description[... | 04343be02ec049d98e548b378a5965adb929c61b | 3,621,885 |
async def close(ctx):
"""issueをcloseします。"""
try:
bot.close_issue(ctx.channel.id)
except ValueError:
return await ctx.send("issueがオープンされていません。", delete_after=5)
await ctx.message.add_reaction("\U0001f44d") | c6f6c9aac62855361d09f066f81344d13012ac3b | 3,621,886 |
import numpy as np
def read_data(fname, filter_params, time_windows, time_units, fps, is_manual_index):
"""
Reads the timeseries_data and the blob_features for a given file within every time window.
return:
timeseries_data_list: list of timeseries_data for each time window (length of lists = numbe... | aad55507d0bec581f072c173fb78f8fd1a470d8d | 3,621,887 |
def forecast(
precip,
velocity,
timesteps,
threshold,
extrap_method="semilagrangian",
extrap_kwargs=None,
slope=5,
):
"""
Generate a probability nowcast by a local lagrangian approach. The ouput is
the probability of exceeding a given intensity threshold, i.e.
P(precip>=thres... | 09bbeebdfe99277bdf8f77903d6d3e2fd812133e | 3,621,888 |
def train_svm(documents, ntesting=500):
"""
:param documents- politeness-annotated training data
:type documents- list of dicts
each document must be preprocessed and
'sentences' and 'parses' and 'score' fields.
:param ntesting- number of docs to reserve for testing
:type ntesting- ... | d756911708fd26116b990131cffaffc069cd6eb7 | 3,621,889 |
from typing import Union
from typing import Optional
from datetime import datetime
from typing import Sequence
def get_logs_for_action(
data: Union[LogData, pd.DataFrame],
log_action: str,
selected_day: Optional[datetime.date] = None,
rows: Optional[Union[str, int, Sequence[int]]] = None,
) -> Union[p... | 07d098ce6af982a1cc50a9d88121b84721bee181 | 3,621,890 |
import math
def is_mc_multiplier(multiplier, modulus):
"""
Checks if multiplier is a MC multiplier w.r.t. modulus.
:param multiplier: an integer in (0, modulus).
:param modulus: a prime number.
:return: True if multiplier is a MC multiplier w.r.t. modulus.
"""
return (modulus % multiplier)... | 6d210f8de081ae0a468692b2f93e5145170917e9 | 3,621,891 |
from typing import List
from typing import Container
async def buckets_get(buckets: Buckets = Depends(Provide[Container.buckets])) -> List[Bucket]:
""" returns all buckets configured """
return buckets.get_all() | 3f8d4a9db3a3648b00f79ba4a9108aef554415c2 | 3,621,892 |
def group_without_decoys(peptides, target_column, proteins):
"""Retrieve the protein group with a target-only FASTA.
Build a dictionary mapping the decoy peptides to a plausible unique
target peptide. Then proceed to map as with the targets.
Parameters
----------
peptides : pandas.DataFrame
... | 57c528aef970855a3cdce029d1c101485d5e401f | 3,621,893 |
from typing import Any
def get_endpoint_stats(netid: str, client: ShrunkClient) -> Any:
"""``GET /api/stats/endpoint``
Returns visit statistics for each Flask endpoint. Response format:
.. code-block:: json
{ "stats": [ { "endpoint": "string", "total_visits": "number", "unique_visits": "number" ... | b4d0d22ad0014da66fd1b99448d6fcf863071eeb | 3,621,894 |
import requests
import jsonschema
def create_project(project, notify_user=True):
"""
Create an OpenLDAP project.
Args:
project (Project): Project instance - required
notify_user (bool): Issue a notification email to the project technical lead? - optional
"""
url = ''.join([setting... | 022ab097e9df0be19def36fc9a418a1bf8d976ac | 3,621,895 |
def readToTuple(f_path):
"""Reads in a two-col file (tab-delim) and returns a list of tuples"""
f = open(f_path)
ls = []
for l in f:
if l.startswith("#"):
continue
ls.append(tuple(l.strip().split("\t")))
return ls | 726d1b4a4682c4e11afbf59e342340e0cf5ccc63 | 3,621,896 |
from typing import List
from typing import Tuple
import tqdm
def _preprocess_file(input_file: str, lang: str) -> List[Tuple[List[str]]]:
"""
Performs initial preprocessing, i.e., urls formatting, removal of "_trans" from Ru set
Args:
input_file: path to a file in google TN format
lang: da... | 8dfdba600ed2efe419983e90f2a7b7e7355bd534 | 3,621,897 |
from .methods import FaceNet
from .methods import GoogleNet
from .methods import AlexNet
from .methods import SqueezeNet
from .methods import VGGFace
from .methods import OpenFace
from .methods import FaceRecognition
def predict(image, method_name, **kwargs):
"""
Get descriptor of image with an specific metho... | ea6de2b4bdfd70a079ea911f78239cf26641e4cd | 3,621,899 |
import csv
def buildUsageAndRatingByCityJs():
"""Builds several strings defining variables used for visualization.
Reads a CSV file containing the usage-by-city data and uses it
to build a JavaScript string defining a DataTable containing the data.
Returns:
{string} of the form <var_name>=<json>, where ... | 4869a64c8ef91fd2ce3940ce5d4ab28ed8278092 | 3,621,900 |
def _get_Abc(c, c0=0, A_ub=None, b_ub=None, A_eq=None, b_eq=None, bounds=None,
x0=None, undo=[]):
"""
Given a linear programming problem of the form:
Minimize::
c @ x
Subject to::
A_ub @ x <= b_ub
A_eq @ x == b_eq
lb <= x <= ub
where ``lb = 0`` and ... | c177b919626f13d2d0b5cddeecb2c7678af23d6d | 3,621,902 |
def obj2np(obj):
"""Wraps an object into an np.array."""
ar = np.zeros((1,), dtype=np.object_)
ar[0] = obj
return ar | e35be1f05a0bb62a573592802c86ba823f727530 | 3,621,903 |
def masking(tokens, p = 0.1, mask='[MASK]'):
"""
Returns a new list by replacing elements in `tokens` by `mask` with probability `p`.
Args:
tokens (list): list of tokens or token ids.
p (float): probability to mask each element in `tokens`.
Returns:
A new list by replacing eleme... | da19ca09fb76557c58c96a77986276a98feaac86 | 3,621,904 |
import string
from typing import Counter
def singlebyte_xor_cipher(hex):
"""
Takes a hex string and finds the best xor key
and returns (ResultString, Confidence)
"""
common = ['n', 'i', 'o', 't', 'e', ' ']
ret = None
score = 0
key=0
if not isinstance(hex, bytearray):
hex = hex.decode('hex')
hex = bytearr... | 1611372d05bfa7753d77cc389e58420a2efb0c99 | 3,621,905 |
def absolute_url(context, route, *args, **kwargs):
"""The absolute url for a request and a route"""
return context.request.build_absolute_uri(reverse(route, args=args, kwargs=kwargs)) | cfaff5366b115bdc318168669efb753c4164ca53 | 3,621,906 |
def get_Kernels(test_vectors,img_width):
"""
Creates 3x3 kernel which is operated by the conv2d
Parameters
----------
test_vectors : numpy array
Generated test vectors 3x1.
img_width : integer
with of test matrix.
Returns
-------
Kernel : numpy array
Kernel t... | f9da65a87fd497ec3f4ef851fa7acb1ad8101405 | 3,621,907 |
def get_solc_version() -> Version:
"""
Get the version of the active `solc` binary.
Returns
-------
Version
solc version
"""
solc_binary = get_executable()
return wrapper._get_solc_version(solc_binary) | 680d72cbeb2ceef5453722afde0dc238dbba3376 | 3,621,908 |
def epoch2dt64(ep_time):
"""
Convert from epoch time (seconds since 1/1/1970 00:00:00) to
numpy.datetime64 array
Parameters
----------
ep_time : xarray.DataArray
Time coordinate data-array or single time element
Returns
-------
time : numpy.datetime64
The converted... | 9fe7734d36a44cf4c4d63823190e7bab83b8a2f5 | 3,621,909 |
import requests
import tarfile
def get_file_from_recipe_url(url):
"""Downloads file at url and returns tarball"""
r = requests.get(url, timeout=MULLED_SOCKET_TIMEOUT)
return tarfile.open(mode="r:bz2", fileobj=BytesIO(r.content)) | 1bda8c89560c1af0da8ff0a6d8eb3a70281ae66a | 3,621,910 |
def df_to_dict_single(df, curation_id=None):
"""
Purpose:
Convert a single entry pandas DataFrame into a dictionary and strip out
indexing information
:param df: pandas DataFrame with single entry (e.g., use df.loc[] to filter)
:param curation_id: integer providing the curation_id. Default: ... | 5a63e4cb56f8492adfae48cfd0c54f0fa6f6e104 | 3,621,911 |
def check_lines_valid(left_line, right_line, last_left_line=None, last_right_line=None):
"""
Checks validity of two given lines based on there geometry and optionally based on the deviation to the previous
detected lines. Also calculates the Mean Absolute error and the Mean Squared Error of the x values bet... | 5b9bb2369d6eccb4c2c1ba4288b5939f6c290574 | 3,621,912 |
import requests
def get_the_manifest(filter_string, api_url, manifest_file, max_files=None):
"""
This function takes a JSON filter string and uses it to download a manifest from GDC
"""
#
# 1) When putting the size and "return_type" : "manifest" args inside a POST document, the result comes
#... | 04fd2006b42bf5478c7c5b6ee6a87da128ce7131 | 3,621,913 |
def imageseg(Cont_Image):
"""imageseg('Image Name')
This program takes an image that has been pre-proccessed by an edge finding script as its sole input, segments it, and spits out a segmented image file and a pandas dataframe of individual particle positions.
This function works by creating a binary of a... | 7d786863cb668c7ba1d7cc643180fe33bcb1d318 | 3,621,914 |
import re
def getSisters(tree, t="g"):
"""Some nasty regex to get pairs of sister taxa
(only at terminal branches)"""
if t == "s":
l = re.findall("\(([1-9][0-9]|\d),([1-9][0-9]|\d)\)", tree)
else:
l = re.findall(
"\(([1-9][0-9]|\d):\d\.\d\d\d,([1-9][0-9]|\d):\d\.\d\d\d\)", ... | b5c3d26b406847bfd0858181bd3becb90fccb878 | 3,621,915 |
from typing import Optional
import warnings
def cluster_ensembles(
labels: np.ndarray,
nclass: Optional[int] = None,
solver: str = 'hbgf',
random_state: Optional[int] = None,
verbose: bool = False) -> np.ndarray:
"""Generate a single consensus clustering label by using base... | 2d996860fd05418f676b22d2fd795a1478266dc6 | 3,621,916 |
def ReadFromXMLStream (istream,
options = XML_STRICT_HDR | XML_LOAD_DROP_TOP_LEVEL | XML_LOAD_EVAL_CONTENT, # best option for invertibility
array_disposition = ARRAYDISPOSITION_AS_NUMERIC_WRAPPER,
prepend_char=XML_PREPEND_CHAR) :
"""Read XML from... | 757caaf44bb50a0391e8561b9c08209469f40aa0 | 3,621,917 |
def AngleRA (angle,unit=units.hourangle,raise_errors=False):
"""
An object which represents a right ascension angle
see `astropy.coordinates.RA` for more extensive documentation
The primary difference with astropy is that if the call to coordinates.RA
errors you have the option to ignore it an... | 01d2d5d7aedfb73f2189fba2bb7ef0d5076d49a2 | 3,621,918 |
def k_euclidean_neighbors(k, x1, x2, exclude_identity=False, identities=None):
""" For each row vector in x1 the k-nearest neighbors in x2.
:param k:
:param x1: M x Feat-dim
:param x2: N x Feat-dim
:param exclude_identity:
:param identities:
:return: M x k
"""
all_cross_pairwise_dist... | 746b6100eb0e6724178633093b02725a30022ec9 | 3,621,919 |
def get_train_feed_dict(model, reviews, win_reviews, batch_length, ote_labels, ts_labels, opn_labels, stm_lm_labels, lr, dropout_rate=1.0, train_flag=True):
"""Construct feed dictionary."""
feed_dict = dict()
feed_dict.update({model.reviews: reviews})
feed_dict.update({model.win_reviews: win_reviews})
... | d1abf917a6fc0db66102aebda61ce431a508988f | 3,621,920 |
def pass_through_third_point(marking_points, i, j, thresh):
"""See whether the line between two points pass through a third point."""
x_1 = marking_points[i][1][0]
y_1 = marking_points[i][1][1]
x_2 = marking_points[j][1][0]
y_2 = marking_points[j][1][1]
for point_idx, point in enumerate(marking_... | fbd38906e1266e8e4690e3c1eae99825009a6fab | 3,621,921 |
def increment_ctr(ctr):
"""
Increments one the counter.
Parameters
----------
ctr : string
Counter
Returns
-------
incremented_counter : string
Incremented Counter
"""
ctr_inc_int = int.from_bytes(bytes.fromhex(ctr), byteorder="big") + 1
return bytes.hex(c... | 0ef04e10283f02b6b7df46cf196493a3ad4a95c8 | 3,621,922 |
from typing import Any
def _instantiate(config: Any, *args: Any, **kwargs: Any) -> Any:
"""
:param config: An config object describing what to call and what params to use.
In addition to the parameters, the config must contain:
_target_ : target class or callable name (st... | 82527dbf49f5af837435ef0498a2c74785806594 | 3,621,923 |
import json
import torch
from re import T
import time
import math
def test_emb(
opt,
batch_size=16,
img_size=(1088, 608),
print_interval=40, ):
"""
:param opt:
:param batch_size:
:param img_size:
:param print_interval:
:return:
"""
data_cfg = opt.data_cf... | a2931c824ca69701611ab078770a46ca3167196a | 3,621,924 |
def is_supported(value, check_all=False, filters=None, iterate=True):
"""Return True if the value is supported, False otherwise"""
assert filters is not None
if not is_editable_type(value):
return False
elif not isinstance(value, filters):
return False
elif iterate:
if isinst... | b9f557b779121fa36f88e79318357d36849a3186 | 3,621,925 |
def box_net(images,
level,
num_anchors,
num_filters,
is_training,
act_type,
repeats=4,
separable_conv=True,
survival_prob=None):
"""Box regression network."""
for i in range(repeats):
orig_images = images
... | 4541b6498fe821fc113b22b7b5d7142a2c24e4b1 | 3,621,927 |
def process_folder(repo_path, folder):
"""Find files and send for processing."""
folder_path = repo_path + folder + "\\"
vars()[folder] = dict()
json_queries = enum_json(folder_path)
vars()[folder].update(json_queries)
yaml_queries = enum_yaml(folder_path)
vars()[folder].update(yaml_queries... | d84434ed931c61ac94f1a53467c86da5e4d85ebc | 3,621,928 |
def img_to_array(img, data_format=None, dtype=None):
"""Converts a PIL Image instance to a Numpy array.
# Arguments
img: PIL Image instance.
data_format: Image data format, either "channels_first" or "channels_last".
If omitted (`None`), then `backend.image_data_format()` is used.
... | 0e297731b9f069995bf7faa350ea556e343274d8 | 3,621,929 |
import array
def C3(theta):
"""
Parameters
----------
theta : float
Angle 'theta' to be rotated around the X axis in rad.
Returns
-------
array
Cossine matix (3X3) of a 'theta' rotation around the Z axis.
"""
return array([[cos(theta), sin(theta), 0],
... | 6a0249a4e4ee3517809a22b7587a12ebc3522a56 | 3,621,930 |
def open_url(filename, basepath=None):
"""Opens and reads a certain file from a web or remote location.
Opens and reads a certain file from a web or remote location. This
function utilizes the urllib2 module, which means that it is
restricted to the types of remote locations supported by urllib2.
... | 346bdbe1a508458dc216c95e582d2854bd9470e1 | 3,621,934 |
def build_login():
""" Construye la ventana del inicio de sesion del usuario"""
layout =[[sg.T("Usuario", size=(8,1)), sg.InputText(key='-USER-')],
[sg.T("Contraseña", size=(8,1)), sg.InputText(key='-PASS-')],
[sg.Submit("LogIn", size=(15,1), pad=(0,15))],
[sg.T("No estas r... | 7b8a6acc2891d82b745323f7605856e63653d8f5 | 3,621,936 |
def get_tif_image_layer_count(file_name):
"""
:param file_name:
:return:
"""
with tifffile.TiffFile(file_name) as tif:
return len(tif.pages) | 945118d8849dbe3af8f4d7b8db1cd59d08ded774 | 3,621,937 |
def sonify_chromagram_with_signal(chroma_data, x, frame_rate, Fs, fading_msec=5, stereo=True):
"""Sonify the chroma features from a chromagram together with a corresponding signal
Parameters
----------
chroma_data : NumPy Array
A chromagram (e.g. gathered from a list of note events by list_to_c... | e05151412a8f0e8f7a23bcaaad37a9c283234a27 | 3,621,938 |
def ensure_binary(s, encoding='utf-8', errors='strict'):
"""Coerce **s** to six.binary_type.
For Python 2:
- `unicode` -> encoded to `str`
- `str` -> `str`
For Python 3:
- `str` -> encoded to `bytes`
- `bytes` -> `bytes`
"""
if isinstance(s, text_type):
return s.encode(encoding, errors)
... | e4890c18b918bc0939a594eb0de19767a73e9898 | 3,621,939 |
import asyncio
def pytest_pyfunc_call(pyfuncitem):
"""Run coroutines in an event loop instead of a normal function call."""
if asyncio.iscoroutinefunction(pyfuncitem.function):
existing_loop = pyfuncitem.funcargs.get('loop', None)
with _passthrough_loop_context(existing_loop) as _loop:
... | a78518681acd2c9d3e8ed8f015573d4f42c135c2 | 3,621,940 |
import re
from datetime import datetime
def get_forecast_times(forecast_length, forecast_date=None,
forecast_time=None):
"""
Generate a list of python datetime objects specifying the desired forecast
times. This list will be created from input specifications if provided.
Otherwi... | 9fe3c8a58b4dabb1513419d9e082e3a6bbf023be | 3,621,941 |
import requests
def human_output():
"""Get request with human output params"""
response = requests.request("GET", BASE_URL, params=querystring)
return response | c15c07baaba60dc469aaf71443a3bad57b310180 | 3,621,943 |
def multiset(left, right, pairwise):
"""
Calculate the multiset distance between two vectors.
:arg array_like left, right: Vector.
:arg function pairwise: A pairwise distance function.
:return: The multiset distance between `left` and `right`.
:rtype: float
Note that `function` must be ve... | bbeb929963e92ebd371fcb52153763c1519b06d2 | 3,621,944 |
def json_response(func):
"""
A decorator thats takes a view response and turns it
into json. If a callback is added through GET or POST
the response is JSONP.
"""
def decorator(request, *args, **kwargs):
objects = func(request, *args, **kwargs)
if isinstance(objects, HttpResponse... | 1b49343e2f583bc9ba05092d4203177d7e23db3f | 3,621,945 |
def sample_CRP(N, alpha,d =0):
"""
sample from a Pitman-Yor process via the Chinese Restaraunt process, default
value of d=0 samples from a Dirichlet process
Parameters
-----------
N : scalar, integer
number of samples to return
alpha : scalar > -d
concentration parameter
... | be809c64c54b18c28554fadbfc351bc1d7f55d3f | 3,621,946 |
def iotest(fh, eof, blocksize=512, t=10):
"""io test"""
io_num = 0
start_ts = time.time()
while time.time() < start_ts+t:
io_num += 1
# freebsd8: need 512B sector alignment and at least one whole block left
pos = random.randint(0, eof - blocksize) & ~0x1ff
fh.seek(pos)
... | a205b9cf30d171df4b0c51c1a136c907b3db23af | 3,621,947 |
def calc_info_frames(site_results_filtered, remove_multiple=None):
"""Return the info frames for the input."""
dat, conf_both, conf_any = get_pipeline_stats(site_results_filtered, log=False)
df_all = get_conf_dfs(conf_any)
if remove_multiple:
url_by_leak = df_all.groupby(["browser", "url"])[["me... | efcf4360febc44bb6d413b84bb2bb7f704eedb02 | 3,621,949 |
def _cleaner( vbo ):
"""Construct a mapped-array cleaner function to unmap vbo.target"""
def clean( ref ):
try:
_cleaners.pop( vbo )
except Exception as err:
pass
else:
vbo.implementation.glUnmapBuffer( vbo.target )
return clean | f478025165cc9ea1bfbc8f5980df8cf752b575ab | 3,621,950 |
def winrate_match(timebox, size, map_category):
""" Returns civs with winrate data based on matches. """
sql = QUERIES["win_rates_match"].format(*timebox, filters(map_category, size))
civs = CivDict(WinrateCivilization, size, map_category, "match")
bottom_civs = CivDict(BottomWinrateCivilization, size, ... | ef1924be54d462f362467cfb297220924d9f7dd6 | 3,621,951 |
def powerLaw(t, m, a, b):
"""
Model for the shower dominated part of a ratescan
"""
return m*np.power(t, a)+b | b0aaa838bc523d40322b621d4e4cae526cdaeb88 | 3,621,952 |
def update_unified_dataset(
session: Session, project: SchemaMappingProject
) -> Operation:
"""Apply changes to the unified dataset and wait for the operation to complete
Args:
project: Tamr Schema Mapping project
"""
unified_dataset = unified.from_project(session, project)
op = unified... | e9e628d9fb4e6da9331f7b0f2198db220123084c | 3,621,953 |
def make_v_spacer() -> QSpacerItem:
"""Make vertical QSpacerItem."""
widget = QSpacerItem(40, 20, QSizePolicy.Preferred, QSizePolicy.Expanding)
return widget | 11216ae878058593e05a6542f3b14be91ef7c1e2 | 3,621,954 |
def combine_measurements(values):
"""Combines a np.array of measurements into one ufloat"""
return ufloat(mean(values), stdDevOfMean(values)) | 1e6df9fa79dbcab5d7476cc7f4b59b6c82c37584 | 3,621,955 |
def rename_guided(expr, resolution_guide):
"""
resolution_guide is a dictionary whose keys are expressions
and values are tuples (previous_pred, new_pred) that guide
the renaming.
"""
replacements = resolution_guide.get(expr, [])
for prev_pred, new_pred in replacements:
expr = expr.r... | d12a8ab0968e07b47f429ce8fbf7d3a6f8e1c02b | 3,621,956 |
def get_base_required_fields_uframe():
""" Get required fields for base asset in uframe.
"""
base_required_fields = [
'assetId',
'assetType',
'@class',
'dataSource'
'de... | 233e9c8985b82335d32765daab3cc29ae5959354 | 3,621,957 |
def get_comparative_forms(tokens):
"""Identify, color and count comparatives and superlatives"""
# find comp. forms of adjectives
comparatives = [t for t in tokens if t.full_pos in ['ADJA', 'ADJD'] and t.mo.comp == 'Comp']
superlatives = [t for t in tokens if t.full_pos in ['ADJA', 'ADJD'] and t.mo... | 020ce0f3a4959a2525698bfac4c45ac497e5cc67 | 3,621,958 |
from typing import Optional
def fit_hypsometric_bins_poly(hypsometric_bins: pd.DataFrame, value_column: str = "value", degree: int = 3,
iterations: int = 1, count_threshold: Optional[int] = None) -> pd.Series:
"""
Fit a polynomial to the hypsometric bins.
:param hypsometric_... | d54d03cff1f65aa13a5b8678626e5a3000ad755a | 3,621,960 |
def get_nvidia_model(summary=True):
"""
Get the keras Model corresponding to the NVIDIA architecture described in:
Bojarski, Mariusz, et al. "End to end learning for self-driving cars."
The paper describes the network architecture but doesn't go into details for some aspects.
Input normalization, a... | 3195f7880f3deaa4f7b4f4919579252597feea84 | 3,621,961 |
def templateXcorr(datastream, template):
"""
Normalized cross correlation of short template trace against longer data stream
Based off matlab function coralTemplateXcorr.m by Justin Sweet
Args:
datastream: obspy trace of longer time period to search for template matches
template: obspy ... | bae76c7bd4cc7b40e533acb868a2a2c3215ce60a | 3,621,962 |
from datetime import datetime
def _load_dates():
"""Return a dict with the dates from the start_date to the current date.
Returns
-------
dates : dict
Dictionary containing dates and indicies.
"""
dates = {}
end_date = datetime.datetime.now()
curr_date = datetime.datetime(... | 8fe0bffefe46ef57d857ccd13caaec14db003fbf | 3,621,963 |
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