content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def get_int(buffer: bytes, offset: int) -> int:
"""
Returns an int at the specified offset.
:param buffer: The buffer to get from.
:param offset: The offset to use.
:return: The int
"""
return _int_serialiser.deserialise_from_bytes(buffer[offset:offset + 4]) | 2f4830cf4693178e3992a861edc1bc234f3b85d4 | 66,678 |
def load_source_table():
""" Load table of arcline sources
Returns
-------
sources : Table
"""
src_file = arclines.__path__[0]+'/data/sources/arcline_sources.ascii'
# Load
sources = Table.read(src_file, format='ascii.fixed_width', comment='#')
# Return
return sources | ec1ccbeee783f3a47d76d1546d77772d38cc385f | 66,679 |
def clang_layer_packages():
"""Packages for the clang layer."""
clang_tools = [
tool_names.binutils,
tool_names.lib_cpp,
]
packages = []
for tool in clang_tools:
packages.extend(get_jessie_packages(jessie_tools()[tool]))
return depset(packages).to_list() | 4473a3038b52327d252cae4723c08d2b997b0b57 | 66,681 |
from typing import Generator
def read_until(
data: bytes, *, return_tail: bool = True
) -> Generator[tuple, bytes, bytes]:
"""
read until some bytes appear
"""
return (yield (Traps._read_until, data, return_tail)) | 277108459577218fd679b4ef44ae10ec9b009293 | 66,682 |
def clean_data(df):
"""Cleans the passed dataframe.
Actions done while cleaning:
- dropping all rows with missing location ids
- dropping all rows where dropoff time is before pickup time
- consider all location ids that map to the same zone as equivalent and replace them with a single value
... | f29a1d3784914c2dfcae1611c8860dbaa7f2a93c | 66,684 |
def sort_by_scores(scores, features_list, topn=None): #实际在输入的时候scores=labels,features_list=[labels,logits],所以是按照labels进行排序
"""Sorts example features according to per-example scores.
Args:
scores: A `Tensor` of shape [batch_size, list_size] representing the
per-example scores.
features_list: A list of... | 3483225e319f083b23262aead39c76e6f15103fd | 66,685 |
def _distance_sequence_from_scores(scores_1, scores_2):
"""
We want to compute the distance between two -local perturbation- models.
To do this, we simply take the usual distance between two hmm models; the pretrained predictive model
stays constant.
The desired distance is the limiting value of t... | 9a4488f157e8beaa9ad594467585063884800594 | 66,686 |
def polygon_clip(subjectPolygon, clipPolygon):
""" Clip a polygon with another polygon.
Args:
subjectPolygon: a list of (x,y) 2d points, any polygon.
clipPolygon: a list of (x,y) 2d points, has to be *convex*
Note:
**points have to be counter-clockwise ordered**
Return:
a list of (x,y) ... | 1064e3f20c4145ac42484c8b4fc772e396032be2 | 66,687 |
def is_openbabel_molecule(obj):
"""Check whether an object is an `oddt.toolkits.ob.Molecule` instance.
.. versionadded:: 0.6
"""
return (hasattr(oddt.toolkits, 'ob') and
isinstance(obj, oddt.toolkits.ob.Molecule)) | 1bf1cd6da46aab746f7d63d8f962c97cd5911ee0 | 66,689 |
def confirm(prompt=None, resp=False):
"""prompts for yes or no response from the user. Returns True for yes and
False for no.
'resp' should be set to the default value assumed by the caller when
user simply types ENTER.
>>> confirm(prompt='Create Directory?', resp=True)
Create Directory? [y]|n... | a5a6dcb89434aa7dbeac85ae1164b3912100bd4a | 66,690 |
def streamline(mesh, field, startCoord, dLengthSteps, dataMesh=None,
maxSteps=1000, verbose=False, coords=(0, 1)):
"""
Create a streamline from startCoord and following a vector field in up
and down direction.
"""
xd, yd, vd = streamlineDir(mesh, field, startCoord, dLengthStep... | d01339b965c2e99c5fecd3f8df93e6025904b769 | 66,691 |
def wall_filter(gray):
"""
Filter walls
Filter out walls from a grayscale image
@Param image
@Return image of walls
"""
ret, thresh = cv2.threshold(gray,0,255,cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)
# noise removal
kernel = np.ones((3,3),np.uint8)
opening = cv2.morphologyEx(thres... | 31d71c640aa229efc4384140b1bd6d502544827e | 66,692 |
from typing import Tuple
def FloatRangeTupleDataclassField(N=2, default: Tuple = (0.9, 0.999), min=0, max=1):
"""Returns a dataclass field with marshmallow metadata enforcing a `N`-dim. tuple with all values in given
range.
In particular, inputs must be N-dimensional tuples of purely numeric values withi... | 2166b6aad243df5e9bc9d4b1ceb071cf00e7e5e0 | 66,693 |
import htmlentitydefs
import re
def xss_strip_all_tags(s):
"""
Strips out all HTML.
"""
return s
def fixup(m):
text = m.group(0)
if text[:1] == "<":
return "" # ignore tags
if text[:2] == "&#":
try:
if text[:3] == "&#x":
... | f78dc85368c63e4ed0484add6755bb9645186d02 | 66,694 |
def safe_divide(numerator, denominator, eps=1e-7):
"""Avoid dividing by zero by adding a small epsilon."""
safe_denominator = tf.where(denominator == 0.0, eps, denominator)
return numerator / safe_denominator | 551b74f9c9404882585831c316980d36e3bb3359 | 66,695 |
def sentinel2_sr_cloud_mask(input_img):
"""Extract cloud mask from the Sentinel 2 SR QA60 band
Parameters
----------
input_img : ee.Image
Image from the COPERNICUS/S2_SR collection with a QA60 band.
Returns
-------
ee.Image
Notes
-----
Output image is structured to be ... | 9b456f9b130d057cb7b2a811458e1cf426365037 | 66,696 |
def get_spacegroup(cell, positions, numbers, symprec=None):
"""Returns Pearson symbol and intl number corresponding to the given structure"""
cell = (cell, positions, numbers)
sg = spglib.get_spacegroup(cell, symprec=symprec or SYMPREC).split()
return sg[0], int(sg[1][1:-1]) | 19d6e98cfe9fe2119bbd053a81622971f018ba90 | 66,697 |
def preprocess_idl_type_and_value(idl_type, cpp_value, extended_attributes):
"""Returns IDL type and value, with preliminary type conversions applied."""
idl_type = idl_type.preprocessed_type
if idl_type.name == 'Promise':
idl_type = IdlType('ScriptValue')
if idl_type.base_type in ['long long', ... | cc270ba1b811fef6992c582cdd3e28ee04554434 | 66,698 |
def start_heterogeneous_tile(
tile_name,
pin_assignments,
sites,
equivalent_sites,
):
""" Returns a new tile xml definition.
Input parameters are:
- tile_name: name to assign to the tile
- pin_assignments: location of the pins to correctly build pin locations
... | f670e3deedd396b09a2f6a497f2f223e909413fb | 66,699 |
def midpoint(pair1, pair2):
"""find and return the midpoint between the two given points"""
x = (pair1[0] + pair2[0])/2
y = (pair1[1] + pair2[1])/2
return x, y | 760aca99b1dad002fb8b6f483515f222dee77160 | 66,701 |
from re import T
from typing import Tuple
def _to_tuple(x: T, n: int = 2) -> Tuple[T, T]:
"""Convert to n-tuple if not already an n-tuple."""
if isinstance(x, tuple):
if len(x) != n:
raise ValueError()
return x
return tuple([x] * n) | 5deb4f3e4fe9b8021b3bf35d834e5de9e9639282 | 66,702 |
def totalistic_ca(k, rule):
"""
The totalistic rule as described in NKS. The average color is mapped to a whole number in [0, k - 1].
The rule number is in base 10, but interpreted in base k. For a 1-dimensional cellular automaton, there are
3k - 2 possible average colors in the 3-cell neighbourhood. Th... | 470902207495fd54a05e1d31eac339382870e156 | 66,703 |
def _load_properties(filepath, sep='=', comment_char='#'):
"""
Read the file passed as parameter as a properties file.
@see https://stackoverflow.com/a/31852401
"""
props = {}
with open(filepath, "rt") as f:
for line in f:
line = line.strip()
if line and not line... | 4795ea5e7c30c8820e3035d09fef3a71452e3ce8 | 66,704 |
def vcat( *relations ):
""" Concatenate relations vertically.
All relations must have the same attribute set (names and types). The order
of columns is determined by the first relation in the input list.
The input relations are **not** consumed immediately.
"""
return csvq.structure.VCat( *relations ) | 6b646f7ac1a5b1710203eddaaf103e01e345eb36 | 66,705 |
import numpy
def power2(f1, f2=None, boxsize=1.0, k = None):
"""
Calculate power spectrum given density field in real space & boxsize
Do not divide by mean, but the field should have 0 mean
"""
# f1 = f1[::2, ::2, ::2]
c1 = numpy... | da7fa71e20071e85ea195c28b7fa4932782179d0 | 66,706 |
def send_email(email_message):
"""
Send email using Mandrill API
:param email_message: Mandrill API message dict to send
:return: result from Mandrill API
"""
result = None
try:
api_key = _get_mandrill_api_key()
mandrill_client = mandrill.Mandrill(api_key)
result = m... | 35238add778dc519dda8edab759de6a974e9e6a3 | 66,707 |
def separate_answers(albert_text, cls='[CLS]', sep='[SEP]'):
"""
Separates the sentences of sequence classification used for bert
:param bert_text: list of bert word tokens
:param cls: string of cls token
:param sep: string of sep token
:return: separated strings
"""
# Fix SPIECE_underli... | 66a9b1e5bcd2c096187db12f31b6e66336552f22 | 66,708 |
def today_datetime():
"""Today is two months after default timestamp"""
return dtvals.format_date(pd.Timestamp(2019, 3, 1, 1)) | 3f809a5d71341ecdef255444d816374d9baa9b35 | 66,709 |
def get_partition_vec(rank,n,cluster,closeRange=False):
""" get the partition vector from clusters returned by partition algorithms
rank: If the bins are sorted, give the rank of each item in the input list.
Used by AHP partition. Set rank = None if not used.
n: Length of vector in origi... | 69c4e7bcbc3cad1442f65693cfa574f3619567fd | 66,710 |
def concat_map_upstream_databases(*arg):
"""
Concatenates all of the upstream databases given as args. Then all of the
emissions in the combined database are mapped to the federal elementary
flows list in preparation for being turned into openLCA processes and
combined with the generation emissions.... | 5804e6a87ae7ddd550c09d62797d653b14429d02 | 66,711 |
def mail_addr_test(str):
"""Tests for a bracketed mailing address"""
testcase = str
start = str.find('<')
end = str.find('>')
if start==-1 or end==-1:
return False
else:
testcase2 = testcase[start+1:end]
if testcase2.find('<') != -1 or testcase2.find('>') != -1:
return False
elif testcase2.find(' ') !... | 2a814da46f7596ba6931d109270327a36cb56aed | 66,712 |
def get_doc_title(request, doc, value = None):
""" проверяем что есть поле title или name или value и что оно не равно 32 и в нем нет цыфр
это для того чтоб не попадало _id в выпадающий список
"""
title = ''
if 'title' in doc['doc']:
title = ct(request, doc['doc']['title'])
elif 'name' in doc['doc']:
tit... | ba760b2e9539a39eb641d4459a3c6e0efb842c36 | 66,713 |
import random
def random_with_bias(messages: list, word: str):
""" Go through all the messages and try to choose the ones where the given word is
not at the end of the string. """
last_word_messages = []
non_last_word_messages = []
for m in messages:
words = m.split()
if words[-1].... | 74579e4216af2a2c1023aa9a2130301c4ec04e6b | 66,714 |
def group_table(df, valuefield):
"""Group the table by -valuefield-
Args:
df (dataframe): dataframe
valuefield ([type]): [description]
Returns:
[type]: [description]
"""
df = df[df["Agegroup"] != "0-19"]
df_grouped = df.groupby([df[valuefield]], sort=True).sum().reset... | a55f601cda65d032dce90828d2a293c0976ef3a7 | 66,715 |
def find_allowed_size(nx_size):
"""
Finds the next largest "allowed size" for the Fried Phase Screen method
Parameters:
nx_size (int): Requested size
Returns:
int: Next allowed size
"""
n = 0
while (2 ** n + 1) < nx_size:
n += 1
nx_size = 2 ** n + 1
... | b7d53ba805ed3c4f543bbb3ff0a94056b76f9738 | 66,717 |
def remove_field(meta, field_id):
"""Delete field and any descendants."""
field_ids = []
if meta.has_field(field_id):
field_ids = meta.remove_field(field_id)
meta.plot = {
key: value for key, value in meta.plot.items() if value not in field_ids
}
return field_ids | c8bdc810448bf5d722587776377228391a820e60 | 66,718 |
def plot_binned_stat(x, y, statistic='mean', bins=20, errorbar=False, percentile=68.27, line=True,
ax=None, **kwargs):
"""
Plot statistics on the quantity y binned following the quantity x.
The statistic can be given by a string ('mean', 'sum', 'max'...) or a function. See `scipy.stats.... | 90c6f7667ca10cd4314037783cb7394177212efa | 66,719 |
def compute_likelihood(da_logical, dim='ensemble'):
"""
Returns array of likelihoods computed along dim from logical event data
Notes
-----
See http://www.cawcr.gov.au/projects/verification/
"""
if dim == None:
likelihood = da_logical
else:
... | 7387b7720aa4619c5bee27fedcd4e0e8401eb4ce | 66,720 |
from .wlts_qgis import WltsQgis
def classFactory(iface): # pylint: disable=invalid-name
"""Load WltsQgis class from file WltsQgis.
:param iface: A QGIS interface instance.
:type iface: QgsInterface
"""
#
return WltsQgis(iface) | 8ecfc8f9f413a8a3c027b1fcec6dadc105a0f513 | 66,721 |
from typing import Optional
def process_snapshot(
serialized_snapshot: bytes,
detokenizer: Optional[pw_tokenizer.Detokenizer] = None,
elf_matcher: Optional[ElfMatcher] = None,
symbolizer_matcher: Optional[SymbolizerMatcher] = None) -> str:
"""Processes a single snapshot."""
ou... | 8ba45a916c4e37f800b2ced2210f5e52e39dcd65 | 66,722 |
import re
import urllib
def parse_ssid_value(ssid_value):
"""
Parse ssid value to a list.
"""
val_re = r"'([^']*)'"
ssid = []
ssid_items = re.findall(val_re, ssid_value)
for ssid_item in ssid_items:
ssid.append(urllib.parse.unquote(ssid_item))
return ssid | 67fa10d42c255ac8f93e4f9dfbea65e73d288cdd | 66,723 |
def traverse_list_rev(tail):
"""Prints all elements from tail to head in reverse direction"""
if tail is None:
return -1
curr = tail
arr = []
while curr.prev != tail:
arr.append(curr.data)
curr = curr.prev
arr.append(curr.data)
return " ".join(map(str, arr)) | ae337027eef66ba81447db8b9ced404b9606f25d | 66,724 |
def bioes_to_bio(tags):
"""
BIOES->BIO
:param tags:
:return:
"""
new_tags = []
for i, tag in enumerate(tags):
if tag.split('-')[0] == "B":
new_tags.append(tag)
elif tag.split('-')[0] == "I":
new_tags.append(tag)
elif tag.split('-')[0] == "S":
... | 10632bbadf9cacd96d2253ed1ac9eaf4d927c532 | 66,725 |
import numpy
def normalize_slices(shape,index):
""" returns index with slice expressions normalized, i.e.
simplified using actual length, replace ellipsis, extend where necessary
"""
if isinstance(index,EllipsisType):
index=(Ellipsis,)
if isinstance(index, tuple):
if is_all_int(ind... | 6a690e4275a5ce44cbc0c934836bc81ced4d6adf | 66,726 |
def get_iocs(sample_id, all_artifacts):
"""
Args:
sample_id (str):
Returns:
dict: response
"""
suffix = 'sample/{}/iocs'.format(sample_id)
if all_artifacts:
suffix += '?all_artifacts=true'
response = http_request('GET', suffix)
return response | 52156cfbbc30e787fef889ec7e66b93ebc29df0a | 66,727 |
def euler_step(u, delta_t, t, du):
"""
Implementation of Euler's method for coupled pair of ODEs for a single step
Parameters:
-----------
u: array-like
vector of initial conditions
delta_t: float
time step size
t: float
current time
d... | d78940e87ed472f772c73555e38d5950bc5367e1 | 66,728 |
from typing import Any
def update(
*,
user_id: int,
user_in: UserUpdate,
current_user: UsersTable = Depends(deps.get_current_active_superuser),
) -> Any:
"""
Update a user.
"""
user = user_crud.get(id=user_id)
if not user:
raise HTTPException(
status_code=404,
... | da3bb335bbf08f0ecc0b3f10913a91d65cf6775d | 66,729 |
def exception(msg, *args, **kwargs):
""" Logs a message with level ERROR inside exception handler """
return get_outer_logger().exception(msg, *args, **kwargs) | 86bcce59e8bd374f9643fad6f6abac76c9cbd7da | 66,730 |
def get_taxonomy_columns(rank: str) -> list:
"""
Gets a list of columns for a specific rank along with all the
inferior taxonomic ranks.
Parameters
----------
rank : str
Taxonomic rank.
Returns
-------
list
List with columns names for the taxonomic ranks.
"""
... | 960ca36f7a978de042c43466f5744dcd71d5bb49 | 66,731 |
def write_n_line_file_to_gcs(project, temp_location, n):
"""Write an n-line file to the temp_location in Google Cloud Storage.
Args:
temp_location: A string specifying a GCS location to write to.
n: An integer specifying the number of lines to write to a file.
"""
# Prepare to write gcs ... | ea57065ac013b9939ed183e200b0d4ac83964c17 | 66,732 |
def format_module_group_selection(form_data):
"""
"""
if not key_in_dict_not_empty('group_selection', form_data):
return None
return form_data['group_selection'] | 7ec360a953b73863c1c3e92add531136f56dac40 | 66,733 |
def mask_to_shapely_polygon(mask: np.ndarray) -> MultiPolygon:
"""Generates shapely polygon from a single instance binary mask
Parameters
----------
mask : binary masks representing single object
Returns
-------
mp : shapely.geometry.MultiPolygon
Geo polygon as shapely object
"... | 70557f9f6d8ef6b1aadd18818493c4fcfea0b99a | 66,735 |
def get_data_peaks(list_dataset):
"""Returned Dataset with peaks data from 'hitfinder/peakinfo'.
Parameters
----------
list_dataset : list
List with dataset from h5py.
Returns
-------
dataset : The class 'h5py._hl.dataset.Dataset'
Dataset with peaks data.
"""
# we... | af5174fd5a9b5bbb3113f1e6481bbe1102732b15 | 66,736 |
def _dress_up_yvals(y):
"""Reshape temperature array to be per hex side
Parameters
----------
y : numpy.ndarray
Y-values to be interpolated
"""
ym = y.copy().reshape(6, -1)
tmp = np.zeros((6, ym.shape[1] + 1))
tmp[:, 1:] = ym
tmp[0, 0] = ym[-1, -1]
tmp[1:, 0] = ym[:-1, ... | ae264d05f2144f3c56d692b3e7d2d5592b01e0ac | 66,737 |
import types
def pd_range_index_getiter(context, builder, sig, args):
""" Returns a new iterator object for RangeIndexType by delegating to range.__iter__ """
(value,) = args
range_index = cgutils.create_struct_proxy(sig.args[0])(context, builder, value)
res = call_getiter(context, builder, types.rang... | 10b2529aa3b030b566511b46b836d52cb24adf27 | 66,738 |
from pathlib import Path
from typing import Set
def expand_globbed_path(path: Path, config_directory: Path) -> Set[Path]:
"""
Expand globs, i.e. * and **, of path object.
This function is actually not used at the moment, but I have left it here
in case we would want to support globbed paths in the fu... | 70f132e18f72084336a4a15f1bc367c3b6c5f518 | 66,739 |
def msg_obs_st(myjson, privacy = False, raw = False):
""" Process JSON Packet from WeatherFlow Hub - obs_st """
text = {}
wf_type = False
if 'type' in myjson:
if myjson['type'] == 'obs_st':
if 'obs' in myjson:
try:
obs_list = myjson['obs'][0]
... | 1429cded22a7adae238625e604bfbd203464b6be | 66,740 |
from typing import Generator
from unittest.mock import patch
import time
def client_fixture() -> Generator[None, MagicMock, None]:
"""Mock balboa."""
with patch(
"homeassistant.components.balboa.BalboaSpaWifi", autospec=True
) as mock_balboa:
# common attributes
client = mock_balbo... | 26f3614df512f1f3f06b254b7456cb5de13b828d | 66,741 |
def iou_ddd_distance(atracks, btracks, frame_id=0, use_prediction=True):
"""
Compute cost based on IoU
:type atracks: list[STrack]
:type btracks: list[STrack]
:rtype cost_matrix np.ndarray
"""
if (len(atracks) > 0 and isinstance(atracks[0], np.ndarray)) or (
len(btracks) > 0 and isi... | 27a5cebdbb3efb4114a08574939a18834a8c606e | 66,742 |
def normalize_column(tag):
"""Delete extra spaces from data"""
if type(tag) == list:
return list(set(
[' '.join(item.split()) for item in tag]
))
elif type(tag) == str:
return [tag, ]
else:
return [] | 1267a62933974cd688fe8945a2cc3b407ba7f0a6 | 66,743 |
import re
def number_of_rsp(ctx):
"""
Determine the number of RSP's in the chassis
:param ctx:
:return: the number of RSP's
"""
platforms = ['ASR-902', 'ASR-920']
count = 0
valid_count = ['1', '2']
if ctx._connection.platform in platforms:
count = 1
return count
... | 47a068c790e487b7259b1aef4e48a932d2a4f9d5 | 66,744 |
def isCompliant(quote):
"""Checks a few compliant parameters
to filter bad quotes."""
if quote == '':
return False
elif len(quote) < 30:
return False
else:
return True | db7bf215b28b8add0c01118c2ad7e043d5b34048 | 66,745 |
def unpad_tensors(sequence, other):
"""Unpad both sequence and other tensor based on the batch padding in sequence.
This relies on the fact that the sequence tensor ONLY has pad characters to represent
batch-level padding, not missing residues. This pad character can be used to identify
the correct bat... | 546ce7cbb648c852c9dadf76b0d3150328f8e713 | 66,746 |
def expandRectangle(rect, xfactor=3, yfactor=3):
"""
Takes a (x,y,w,h) rectangle tuple and returns a new bounding
rectangle that is centered on the center of the origin rectangle,
but has a width/height that is larger by a given factor.
The returned coordinates are rounded to integers
"""
x... | dbc37c87f7fe69c846a3089ab0543e4810ee3c21 | 66,747 |
def wrap_init(f, params={}):
"""Wraps function `f` as a `WrappedFun`, suitable for transformation."""
return WrappedFun(f, (), (), tuple(sorted(params.items()))) | fe80752b0a97784e5831292b7bb714ea438dfa36 | 66,748 |
import re
def baby_names_table_rows_from_babyfile_string(babyfile_string):
"""
babyfile_string sample excerpt with lines of html
<tr align="right"><td>1</td><td>Michael</td><td>Jessica</td>
<tr align="right"><td>2</td><td>Christopher</td><td>Ashley</td>
<tr align="right"><td>3</td><td>Matthew</td>... | a0bb831ee908e9fae0c125b2452977afc23058ce | 66,749 |
def findColor(frame, DISPLAY, MOTOR, motor, cmdDict):
"""initial function, create HSV range+mask and passes to 'findPurpleDems'"""
#make array for final values
HSVLOW=np.array([hul,sal,val])
HSVHIGH=np.array([huh,sah,vah])
# it is common to apply a blur to the frame
frame=cv2.GaussianBlur(frame... | 833d0915ec69424739eb185183a49e5efb547118 | 66,751 |
import re
def strong_to_b(value):
"""
Replaces enclosing <strong> and </strong>s with <p><b>s
"""
value = re.sub(r'^<p><strong>(.+?)</strong></p>$', u'<p><b>\\1</b></p>', value)
return value | 06e0f531160e4e5bf23feba3723aaf85971e606b | 66,752 |
from typing import Dict
from typing import Union
import gc
def compute_site_source_distances(
stations: np.ndarray,
faults: Dict[str, Union[nhm.NHMFault, dict]],
calculate_directivity: bool = True,
n_procs: int = 1,
):
"""
Computes the site-source distances for the given stations and faults
... | 8d2003297e7c127800ece20b7146380e999b4f7c | 66,753 |
def LoadPemGeneric(s, header, footer, skip_info=True):
"""Load a generic pem format string.
Args:
s: str, item in pem format
header: str, header type to look for, e.g. "BEGIN CERTIFICATE"
footer: str, footer type to look for, e.g. "END CERTIFICATE"
skip_info: bool, default True, skip info lines lik... | fedda89f9d0aa023cfbc69c37f747077f390c39e | 66,755 |
def generate_notes_from_corpus(corpus_files,starting_note=None, ending_note=None, length:int=32, width:int=4, save_to_file=None):
"""
Generate note sequence of defined length from corpus text files
@param corpus_files: List of corpus file paths that contain sequence of notes
@param starting_note: Starti... | 0f0395cdfc0a6e95f75bb1c7f43d2a8fcda57f13 | 66,756 |
def net():
"""Generate proteingraph from 2VUI.pdb."""
return generate_network() | 8e14f72a4023255a69b62eef9664ab85364627c9 | 66,757 |
from typing import Dict
from typing import Any
def podcast_obj(podcast_data: Dict[str, Any]) -> Podcast:
"""Get a Podcast object."""
return Podcast(**podcast_data) | 144cf8e315caa8b4c2b6f96eac2abab20f540600 | 66,758 |
import typing
def get_baggage(
name: str, context: typing.Optional[Context] = None
) -> typing.Optional[object]:
"""Provides access to the value for a name/value pair in the
Baggage
Args:
name: The name of the value to retrieve
context: The Context to use. If not set, uses current Con... | 500467a0955af37459762d8431b7f2a6c6139975 | 66,759 |
def safe_execution(func):
"""run a function in safe mode"""
def inner_func(*args, **kwargs):
try:
return func(*args, **kwargs)
except Exception as e:
print("An exception occcurred, details:{}".format(e))
return inner_func | 2423332a5a71e2858eb82496176c110a0be738cf | 66,760 |
def verify_password(plain_text_password, hashed_password) -> bool:
"""
:rtype: bool that is true if an appropriate password was passed
"""
return bcrypt.verify(plain_text_password, hashed_password) | f8faa6612eb95218ba9ceb1c61f6b1e2d89bd355 | 66,761 |
def product(var_x, var_y):
"""This is a test!"""
return var_x * var_y | bd71b40841a39f9df1b796975782c238c20ec3a3 | 66,762 |
def SingletonDecorator(cls):
"""
Decorator to setup any class as Singleton.
Args:
cls (class): decorated class
Returns:
cls instance
Warning:
Some subclass or decorated inside methods may lost docstring.
Not recommended use this decorator with documented class.
... | 37c330af4c12b12c338fe56c6882d0a9c937e105 | 66,763 |
def empty_list_production(service, create_cmd):
"""Fixture for empty list command for production"""
return toolbox.run_cmd(create_cmd(service, 'list', 'production'))['stdout'] | 70bc2ed800ffcb8043cb0c6e05435a843e534a56 | 66,764 |
def open_localhost_vnc_vterm(adapter, lpar_uuid, force=False):
"""Opens a VNC vTerm to a given LPAR. Always binds to localhost.
:param adapter: The adapter to drive the PowerVM API
:param lpar_uuid: Partition UUID.
:param force: (Optional, Default: False) If set to true will force the
... | ca463c9a39582c8d9e53950907e330a8d9e4d4b7 | 66,765 |
def obscure(item, start=3, end=3):
"""
Replaces middle of string with *
:param item: string - to be obscured string
:param start: int - how many letters to leave from start
:return: obscured string - how many letters to leave from end
"""
# ignore None
if item is None:
return Non... | c5f181e83806d4027bb3e8dd19e94701dda1f4f4 | 66,766 |
from typing import List
def MishWindowEncoder(
width: int, window_size: int, depth: int
) -> Model[List[Floats2d], List[Floats2d]]:
"""Encode context using convolutions with mish activation, layer
normalization and residual connections.
width (int): The input and output width. These are required to b... | a583b5bbfad61d068aa3f8669b9aeb85c1ac3db0 | 66,767 |
from onnx.helper import make_node
import logging
def convert_contrib_box_nms(node, **kwargs):
"""Map MXNet's _contrib_box_nms operator to ONNX
"""
name, input_nodes, attrs = get_inputs(node, kwargs)
input_dtypes = get_input_dtypes(node, kwargs)
dtype = input_dtypes[0]
#dtype_t = onnx.mapping.... | da4fe22efd731aa20af2fed5e12f8749c52e63e3 | 66,768 |
from datetime import datetime
def str2dt(timestr: str, /, *args, **kwargs) -> datetime:
"""Return datetime from string
Args:
timestr: string describing a datetime
*args, **kwargs : @see `dateutil.parser.parse`
"""
return parse(timestr, *args, **kwargs) | c9b965743986609237e3c2b4f5c4229f8b56139c | 66,769 |
def _check_stacking_layer(stacking_layer: dict, estimator_type: str) -> dict:
"""Chooses the the first and second stacking layer estimators.
Parameters
----------
stacking_layer : dict
Specify the estimator(s) in the first stacking layer, and the
final estimator in the second stacking l... | f23b1999f65d0e620f686db3197e1ee22d810a63 | 66,770 |
def english_to_french(english_text):
""" translate english to french"""
#write the code here
translation_response = language_translator.translate(text=english_text, model_id='en-fr')
translation=translation_response.get_result()
french_text =translation['translations'][0]['translation']
retur... | 18f5a386d46d5337ca8dd65e2ca2e913f5a80a94 | 66,772 |
import requests
def set_zip_info(zip_code=None):
"""given a zip code, it returns a json dictionary object with nested data"""
if zip_code is None:
print("Function takes zip_code as a string")
return None
if AUTH_ID is None or AUTH_TOKEN is None:
return -1
resp = requests.get(... | 188b10b2a64213489257c49787229b391b5220eb | 66,773 |
import inspect
def t_sne(
dimension="both",
text_corpus=None,
num_topics=10,
remove_3d_outliers=False,
fig_size=(20, 10),
save_file=False,
**kwargs,
):
"""
Returns the outputs of an LDA model plotted using t-SNE (t-distributed Stochastic Neighbor Embedding).
Notes
-----
... | a5206a47b7d97a16b484d35b43b9cc51c4d503ac | 66,774 |
from functools import reduce
def combination(n: int, r: int) -> int:
"""
Calculate combination
Args:
n (int): integer of number of elements
r (int): integer of size of combinations
Returns:
int: An integer of number of combinations
"""
r = min(r, n - r)
nu... | e95805032107f78f93687240c4eba0a9c666b977 | 66,775 |
def decode_as_text(encoded, encoding='utf-8'):
"""Decode a Base64 encoded string.
Decode the Base64 string and then decode the result from *encoding*
(UTF-8 by default).
:param encoded: bytes or text Base64 encoded string to be decoded
:returns: decoded text string (bytes)
Use decode_as_bytes... | 16037e4aeb4151dfdbb529f294c2c8112a2f3ac9 | 66,776 |
def test_token():
"""Retrieve a token used for testing."""
_ = dotdb.find_one_organization('it_doesnt_exist')
result = dotdb.login('test', 'test')
return result.token | e9bb34419158377a97e12949c2bfd12c1c93760a | 66,781 |
def scale_rows(A, v):
"""Scale each row of A by the corresponding entry of v and return the
result."""
return sparse.spdiags(v, 0, len(v), len(v)) @ A | 361afdb855de4f2dbd982951e8966ba213003687 | 66,782 |
from typing import Tuple
def biggest_labelizer_balance(metrics: dict, *args, **kwargs) -> Tuple[str, float]:
"""Given dict of metrics result, returns (key, metrics[key]) whose value is maximal."""
metric_values = list(metrics.values())
metric_keys = list(metrics.keys())
big = metric_values[0]
draw... | 6d17c971c8bcb0333a91bdc3add6a6883845a6ef | 66,783 |
def valid_snap_channel(channel):
""" Validate snap channel exists
:raises InvalidSnapChannel: When channel does not exist
:return: Boolean
"""
if channel.lower() in SNAP_CHANNELS:
return True
else:
raise InvalidSnapChannel("Invalid Snap Channel: {}".format(channel)) | 4d4e86614522e2585cddcd0463027a3d6f30f877 | 66,784 |
from typing import List
from re import A
def center_crop(height: int, width: int, **kwargs) -> List[BasicTransform]:
"""
Wrapper for albumentations center crop. For every patch
a crop a is extracted from the center, p=1.0.
Args:
----------
height (int): height of the output image
... | d00cb20f07de44788994169d38e487cb44bd3df9 | 66,785 |
import json
def error_response(title, status='500'):
"""Generates an error response to return to API Gateway
Parameters
----------
title: string
The title description of the error.
status: string
Thes http status code.
Returns
-------
dict:
An response bac... | 16a62ec46396bee5fe3b240febe4bd0ac2cf9de9 | 66,786 |
def make_spacy_tokenizer(model_name):
"""
Make a spacy tokenizer
"""
model = spacy.load(model_name)
def spacy_tokenizer(string):
"""spacy tokenbizer"""
return [t.text for t in model.tokenizer(string)]
return spacy_tokenizer | 33ba92db24fd5783426f1b9efe9b94a11f7c4e35 | 66,787 |
def get_srcpath():
"""
Get the sourcepath where the inspection is conducted
"""
try:
return jsonify({"SOURCEPATH": inspsettings.get_sourcepath()})
except (ComprehensionError, InvalidRequestError) as error:
return jsonify(error.to_dict()), error.status_code | 124af9183d02b5940ce7338b41fbf11828631395 | 66,788 |
def add_affinity_others(image, weight, weight_val, bbox_1, bbox_2):
"""
Add gaussian heatmap for affinity bbox to the image and also generate weighted map for weak-supervision
:param image: 2-d array containing affinity heatmap
:param weight: 2-d array containing weight heatmap
:param weight_val: weight to be... | 5219528bbe467ee2d3a02e2a150bfc3d63e96b66 | 66,789 |
def calculate_ssim(img1, img2):
"""calculate SSIM
the same outputs as MATLAB's
img1, img2: [0, 255]
"""
if not img1.shape == img2.shape:
raise ValueError('Input images must have the same dimensions.')
if img1.ndim == 2:
return ssim(img1, img2)
elif img1.ndim == 3:
if ... | 0cffee7069e887601b3e544eedc8bc9e34a27c6a | 66,790 |
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