content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def spawn_dates_times(df, spawn_dates=True, spawn_times=False):
"""
Build date/times column from a timeseries dataframe
:param df: (pd.DataFrame) - dataframe with datetime index
:param spawn_dates: (boolean) - whether to spawn year, month, day cols
:param spawn_times: (boolean) - whether to spawn h... | ee58b5117d65fa3f217b16973dcdc06918c5474b | 54,738 |
def parse_date(string, format=None):
"""
:type string: str
:type format: NoneType or str
:rtype: NoneType or date
"""
if format is None:
formats = FORMATS
else:
formats = [format]
for f in formats:
try:
return dt.datetime.strptime(string, f).date()
except ValueError:
pass
return None | 7282d401ba0ab2e2243c7c4ad990136ad80d2ee3 | 54,739 |
from typing import List
def impurity_of_split_rec(points: List[DataPoint], split: float) -> float:
"""
Recursive method wrapper to split the data points into two arrays based on the split point provided and return the gini impurity measure for that split point.
"""
print("Printing split: {}".format(sp... | c3232595b4f1168472e3444939e57f5744a0b6da | 54,740 |
import ctypes
def GetConsoleOriginalTitle() -> str:
"""
GetConsoleOriginalTitle from Win32.
Return str.
Only available on Windows Vista or higher.
"""
if IsNT6orHigher:
arrayType = ctypes.c_wchar * MAX_PATH
values = arrayType()
ctypes.windll.kernel32.GetConsoleOriginalT... | 55900e0280253860b95a20acd2551f61a831d61d | 54,741 |
def connection():
"""
Function that provide the SQL connection to be uses by the ORM.
Returns
-------
(bool, SQL connection object)
The first element of the tuple indicates whether the connection is to be closed after every query. The second
element should provide an SQL connection ... | 65b0122a0cc7b57ab553ac85a6db576e3d242de6 | 54,744 |
def mergeinput_preprocess_duo(df1, df2):
""" Merge 2 data frames into one for full analysis.
Output will be two form: long form and wide form
long form: simply add 2 df on top of each other
wide form: each row represents a request coordinate with result from both run. -> calculate ED
relevant cols f... | 9967be2ec1ccae8d6462c5c01f63d8641b523759 | 54,745 |
def mbeans(query=None):
"""
Returns a list of all the available MBeans in the server. The optional
query parameter will filter the list by objectname
"""
return server.getQueryMBeans(ObjectName(query), None) | 3ad2ed5b36196b55deeefa51ab7968b009b523de | 54,746 |
def is_decimal_dtype(obj):
"""Check whether an array-like or dtype is of the decimal dtype.
Parameters
----------
obj : array-like or dtype
The array-like or dtype to check.
Returns
-------
bool
Whether or not the array-like or dtype is of the decimal dtype.
"""
ret... | c2151eb94ff9aebd6694aa679d1cfcc75f08133f | 54,747 |
def calculate_F1(max, compensate = 0, threshold = 0.5):
"""
Args:
max (M,N)
return:
AP,TP,FP,FN,precision,recall,F1
"""
if compensate < 0:
compensate = 0
TP = 0
FP = 0
FN = 0
for i in range(len(max)):
if max[i] > threshold:
TP = TP + 1
... | 6aab529bbf1837472f0d711997b31fca0fcc3eee | 54,748 |
import time
def runtime(X, y, model_generator, method_name):
""" Runtime (sec / 1k samples)
transform = "negate_log"
sort_order = 2
"""
old_seed = np.random.seed()
np.random.seed(3293)
# average the method scores over several train/test splits
method_reps = []
for i in range(3):
... | 6cbb4a7e773f3c5dafcaf43aa6106be59dc4b87f | 54,749 |
def get_mask(json_data, microplate_names):
"""Return wrapper for numpy array."""
return ControlMask(json_data, microplate_names) | d18fc86c9189b80f550d55646d8f2b94f924fe4d | 54,750 |
def utc2sec(*utc):
"""Convert list composed of year,month,day,hour,minute,second [,microsec]
:param utc: list of year,month,day,hour,minute,second
:returns: number of seconds since the epoch 0001-01-01
"""
utc2=list(utc)
if len(utc)<7:
utc2.append(0)
return int(utc2micro(*utc2)/10*... | 41b6469087414a8c210125b52060745f2cbaf380 | 54,751 |
def scale_sample(xy_sample,grid):
""" This function is used to apply the shifts and scaling to the sample. """
sample = xy_sample.copy()
if grid.dim == 2:
sample[:,2] = sample[:,2] + grid.shifts[0]*sample[:,0] + grid.shifts[1]*sample[:,1]
sample[:,0] = sample[:,0]/grid.b0
sample... | 3f0ae32f198ec75d112ff7d36ea2505dcd75dbea | 54,753 |
def radius_aperture(info_dict):
""" Compute the radius of the aperture
Parameters
----------
info_dict: dictionary
wavelength: float
wavelength in angstrom
Returns
--------
aperture: float
radius of the aperture in arcsec
"""
if info_dict["psf_type"] == "gaussi... | d5055e6bdb3b5fd519ac2b96941a0338bc547b0c | 54,754 |
from pathlib import Path
def find_file(filename):
"""
Finds a file in the directory that has the same name
as the parameter <filename>. If the file does not exist,
the directory is searched for <filename.*> instead, and if
only one match is found, that particular filename is returned.
"""
... | 4915739f11221f566a7fc6f381fc29bf30426908 | 54,755 |
def FermiDirac(Ef, EJ, T):
"""
Returns the Fermi-Dirac probability distribution, given the crystal's
Fermi energy, the temperature and the energy where the distribution values
is required.
Args:
| Ef: Fermi energy in J
| EJ: Energy in J
| T : Temperature in K
Returns:
... | 1e8fbfc0a9ef704340810f2b085afe3543f61356 | 54,756 |
def glXQueryVersion(dpy):
"""
dpy - Display*
return - bool, int, int: support, major, minor"""
major = Numeric.zeros(1, Numeric.Int32)
minor = Numeric.zeros(1, Numeric.Int32)
res = _glxlib.glXQueryVersion(dpy, major, minor)
return res, major[0], minor[0] | 28798bc9371bffd959025190af17b3d29cdd8a0b | 54,757 |
import random
def get_message_data():
"""Default valid message data."""
return {
'message': '''
-----BEGIN PGP MESSAGE-----
Version: Keybase OpenPGP v2.0.8
Comment: https://keybase.io/crypto
wcBMA6Uvn0xuUMOaAQf/bGf4y9ZfKChSOAJs4M5V7K3nDC2p/sUNcfy8FzoIl9VE
j2vT3bMZsaT3cJkQMfABqWgzq8VlQjRP1/m+bBX4jRUYV... | 1e715936bcdd133a981403e6b523bd623e806b1b | 54,759 |
def usgs_kyanite_parse(*, df_list, source, year, **_):
"""
Combine, parse, and format the provided dataframes
:param df_list: list of dataframes to concat and format
:param args: dictionary, used to run flowbyactivity.py
('year' and 'source')
:return: df, parsed and partially formatted to fl... | 25536570a06fffe43d36d4f62a0ff0a2ee98863d | 54,760 |
from typing import List
def prepare_element(sample_nist_component_def: component.ComponentDefinition):
"""Prepare a target element for remove tests."""
element = Element(sample_nist_component_def)
parties: List[common.Party] = []
parties.append(
common.Party(**{
'uuid': 'ff47836c-... | 08570b86e8eaf7c510c9b5cafa0071b3fe90edb9 | 54,761 |
import torch
def flow_warp_tensor(mask, flow, coord=None):
"""
:param mask: 1xCxHxW
:param flow: HxWx2
:return:
"""
if coord is None:
shape = mask.shape[-2:]
coord = torch.ones(shape).cuda().long()
coord = torch.nonzero(coord).float()
flow = flow2coord(flow, coord)
flow = flow.unsqueeze(0... | 0ff2ed886f5224708cdb8ee4f0129b952bb2de3e | 54,762 |
def neighborhood_ambulance_combinations(neighborhoods, total_ambulance):
"""
This function returns all possible combinatios for neighborhoods and
the number of ambulances they hold.
Inputs:
neighborhoods (Array of string) neighborhood names that contains ambulance stations
total_ambula... | 2e640ab8c089dc61e650978d7da1201f0032540b | 54,765 |
def get_number_of_desktops():
"""
Returns the number of virtual desktops.
:return: The number of desktops.
:rtype: util.PropertyCookieSingle (CARDINAL/32)
"""
cook = util.get_property(root, '_NET_NUMBER_OF_DESKTOPS')
return util.PropertyCookieSingle(cook) | 4899628116bac58fbeb23f5f9fddb248115e4cef | 54,766 |
def scalar_to_array(input_x):
"""
Converts a scalar to a `Tensor`.
Args:
input_x (Union[int, float]): The input is a scalar. Only constant value is allowed.
Returns:
Tensor. 0-D Tensor and the content is the input.
Raises:
TypeError: If `input_x` is neither int nor float.
... | d7923256a1908df9f1633ebe946a871ad7a6bcbe | 54,767 |
import json
import requests
def handle_action():
"""Handle a response when a user clicks a button from Wizzy in Slack"""
event_data = json.loads(request.form["payload"])
user = event_data['user']['id']
# if channel empty, it's a shortcut
if event_data.get('channel') is None:
# shortcut - g... | cb54f430e4e3317af658ef1068d893f4798a7c0e | 54,768 |
from typing import List
import copy
def calc_permutation_matrix(
system_order: List[int], size_list: List[int]
) -> np.ndarray:
"""calculate permutation matrix.
permutation matrix can reorder the system order to [0, 1,..., n].
Parameters
----------
system_order : List[int]
system_ord... | 6544e03cb1febde14c15ad5fa6ac2c425dabec0a | 54,769 |
import random
def cvt_horizontal_flip(
sample_input: Dataset, sample_output: Dataset, probability: float = 0.5
) -> Dataset:
"""Converts the sample_input dataset to horizontal flips in sample_output dataset.
Args:
sample_input: input dataset passed to generate output dataset.
sample_outpu... | 2f15e5ed3aae75bda360f17f95e7722b70bb0bbc | 54,771 |
def search():
"""Display search options"""
return render_template("search.html") | 97193ebb2820b33f038a5f027caa5bde6889a788 | 54,772 |
def get_client_setting(setting: str, cid: str) -> ClientSetting:
"""Return client setting based on setting name and cid."""
for client_setting in get_setting(setting).clients:
if client_setting.cid == cid:
return client_setting
raise ClientSettingNotFound() | e6292699c4a741541dede631fc1f5b42cbb744ec | 54,773 |
def between(x, min, max, exclude_max=UNSET) -> ProcessBuilder:
"""
Between comparison
:param x: The value to check.
:param min: Lower boundary (inclusive) to check against.
:param max: Upper boundary (inclusive) to check against.
:param exclude_max: Exclude the upper boundary `max` if set to `t... | 72417a83c8196b32a4c3838ec6e0b9b21c94d050 | 54,774 |
def parse_description(issue):
"""
:param issue: Issue object.
:return: ROGA type: (a string that should be listeria/salmonella/vtec - otherwise they'll get others later.
seq_ids: List of seqIDs which will later be written to file and used in ROGA report generation.
"""
# Take whatever i... | 13ea063546a327dd94eff1fca8f03d9ea7ea1476 | 54,775 |
def feedback(data: FeedbackData) -> str:
"""
Pass the request data as FeedbackData object,
as this can be customised in the model.py file to adapt based
on deployed model to make predictions
Parameters:
data: Parse the request body data based on your model schema and
pass this to pred... | cdfbe44e46c82282488f4d57d818b27c0279f488 | 54,776 |
def get_dataset(id_):
"""특정 dataset에 대한 정보 반환
Args:
id_ (int): dataset ID
Returns:
_type_: _description_
"""
result_json = {"datasetName": "", "image_metadata": []}
query = Dataset.query.filter_by(id=id_).first()
result_json["datasetName"] = query.name
query = ImageM... | 135b45947ebe604ee71d579c5aa9b373f9d8048f | 54,777 |
def test_metathesis(word, anagram):
""" Tests if a word and an anagram are a metathesis pair
This is only true if the words are I. Anagrams II. Differ in two places
"""
count = 0
for para in zip(word, anagram):
if para[0] != para[1]:
count += 1
return count == 2 | c26090d92b526ce7d2a84138e4248c884a19f5bc | 54,778 |
from aac.plugins import (
gen_json,
gen_plugin,
gen_protobuf,
gen_design_doc,
gen_gherkin_behaviors,
gen_plant_uml,
specifications,
)
def get_plugin_manager() -> PluginManager:
"""
Gets the plugin manager and automatically registers internal plugins.
... | 8a8bc92205bf2334c41332e2f6a337fc0709a634 | 54,779 |
def get_token(username, password):
"""Returns a new token for login credentials."""
payload = {'username': username, 'password': password}
key = username + password # simple key
token = jwt.encode(payload, key, algorithm='HS256')
# Convert bytes to string
token = token.decode('utf-8')
# Sto... | 2abef9d55fb96fcc9567b934d1dccd55e29e3c96 | 54,780 |
def standardize(ds, dim="time"):
"""Standardize Dataset/DataArray
.. math::
\\frac{x - \\mu_{x}}{\\sigma_{x}}
Args:
ds (xarray object): Dataset or DataArray with variable(s) to standardize.
dim (optional str): Which dimension to standardize over (default 'time').
Returns:
... | 99de2a60e340a7ad451daec27aad028485d4aa59 | 54,781 |
import warnings
def predict(model, image_files, resize=False, show_image=True, cloud=None):
"""Predict using an model in a local or GCS directory (offline), or a deployed model (online).
Args:
model: if cloud is None, a local or GCS directory of a trained model. Otherwise, it specifies
a deployed mod... | 5cc4e7667032243448ab5b871c7728967698702b | 54,782 |
import six
def topics_offset_distance(
kafka_client,
group,
topics,
offset_storage='zookeeper',
):
"""Get the distance a group_id is from the current latest offset
for topics.
If the group is unkown to kafka it's assumed to be an offset 0. All other
errors will not be caught.
Thi... | d6f1ded7f609d86726b88eba494fec5fdc264e7d | 54,784 |
def get_first_meeting_day_num(days: str):
""" Returns the number representing the day of first meeting of the week
:param days:str: Days field of WebReg list, example: "MWF"
"""
day_nums = get_day_nums(days)
first_day_num = day_nums[0]
return first_day_num | f86f2832ea7cec4356b1aae60a7a1ac17573fc35 | 54,785 |
from typing import Any
from datetime import datetime
def post_search(netid: str, client: ShrunkClient, req: Any) -> Any:
"""``POST /api/search``
Execute a search query. Request format:
.. code-block:: json
{
"query?": "string",
"set": {
"set": "'user' | 'shared' | 'a... | a4d59bed2aee578d14fee1ecdb84d4e036c0d0b9 | 54,786 |
import smtplib
def os_error():
"""Operating system error. AKA EnvironmentError / IOError."""
try:
smtplib.SMTP('localhost:a_port')
except OSError:
return "bad port number" | 2b99d466f04369ab98bdb40c7a3417dd8c089744 | 54,787 |
def multivariate_potential(ptset2, meanvec, covmat):
"""
Vectorised evaluation of multivariate Gaussian pdf.
Args:
ptset: shape (N, d)
mean: shape (d,)
covar: shape (d,)
Raises:
AssertionError: if ptset, mean and covar have not consistent shape
Returns:
resul... | 226c0958c9fd835c93ce33a3f42cd1abea62eba0 | 54,789 |
def restart(backend):
"""Restart the running server from an async test function.
This fixture deals with possible differences between the environment of the
test function and that of the server.
"""
async def restart(server):
await backend.run_in_threadpool(AsyncioBackend().run, server.res... | 518af91d3ebf1bd88f2faae1a06215dd6d67d9cf | 54,791 |
def colinterp(a,x) :
"""Interpolates colors"""
l = len(a)-1
i = min(l, max(0, int (x * l)))
(u,v) = a[i:i+2,:]
return u - (u-v) * ((x * l) % 1.0) | 278eb403e220fee139a73ed6f764df93b6366bc9 | 54,792 |
def accepted_content_type(f):
"""
Check if the requested content type is application/json.
"""
def decorator(*args, **kwargs):
if request.content_type != 'application/json':
raise ServiceException('Content type must be application/json', 400)
return f(*args, **kwargs)
r... | 5b0bcde03e4dc204ca95dd685b0715680f502633 | 54,793 |
import requests
def get_articles_html(url_articles: str) -> str:
"""Wraps HTTP requests.get for testibility
Parameters
----------
url_articles : str
Articles URL
Returns
-------
str
HTML page of articles
"""
articles_html = requests.get(
url_articles, head... | 4fcbf397d4986eed19a3528dde99cb5a81581a10 | 54,794 |
def ei_merit(X, surrogate, fX, XX=None, dtol=0):
"""Compute the expected improvement merit function.
:param X: Points where to compute EI, of size n x dim
:type X: numpy.array
:param surrogate: Surrogate model object, must implement predict_std
:type surrogate: object
:param fX: Values at previ... | e53d35f93b7aeb5fca6c34e70ababb7812b78fc5 | 54,795 |
import soundfile as sf
from pathlib import Path
from typing import Optional
from typing import List
import logging
def load_audio(
path: Path,
channel: Optional[int] = None,
mmap: bool = False,
channel_names: List[str] = ["left", "right"],
) -> MultiTrack:
"""load waveform from file"""
multiTr... | bd853eb4fef33aad63a0267c5bb63ba91d457d3b | 54,796 |
def render_robots_meta_tag(context):
"""
Returns the robots meta tag.
"""
request = context['request']
robots_indexing = None
robots_following = None
# Prevent indexing any unwanted domains (e.g. staging).
if context.request.get_host() in settings.META_TAGGER_ROBOTS_DOMAIN_WHITELIST:
... | 018084102031ca13a36f2563c6f05d810045432e | 54,797 |
from typing import Dict
def search(search_string)->Dict:
"""
API to search "search_string" in the stored documents
:param search_string: search string provided by the user
:type search_string: str
:return: returns results i.e. return list of documents that are closest match to the search string
... | 588960333a7140ad51ffc577741f9102e90d082f | 54,798 |
def convert_lang_code(code):
"""
Map a language code to the canonical one that ConceptNet 5 uses, using the
'langcodes' library.
"""
return str(langcodes.get(code)) | 0da05bd40e6758038c28c3d585744d2ed63fe6f7 | 54,799 |
def solution_math(
A: np.array, B: np.array, threshold: int = 1_000_000_000, scale: int = 1_000_000
) -> int:
"""Math based method. See tutorial/examples in docs for more details.add()
Parameters
----------
A : np.array
integer part of the decimal numbers
B : np.array
decimal pa... | d87c860846968e49705ac8390aa5caded1381f84 | 54,800 |
def tag_list(context, addon, tags=[]):
"""Display list of tags, with delete buttons."""
c = dict(context.items())
c.update({'addon': addon,
'tags': tags})
return c | 0b59aa158137eecd5210c631f053ae137762b690 | 54,801 |
def make_range_partition(min_val, max_val):
"""
Returns a new partitioning function that partitions keys in the range
*[min_val:max_val]* into equal sized partitions.
The number of partitions is defined by the *partitions* parameter
"""
r = max_val - min_val
f = ("lambda k_n_p: int(round(fl... | 6b9c15f93312a913dff432f0954e409b69f97572 | 54,802 |
import torch
def sparse_mx_to_torch_sparse_tensor(sparse_mx):
"""Convert a scipy sparse matrix to a torch sparse tensor."""
sparse_mx = sparse_mx.tocoo().astype(np.float32)
indices = torch.from_numpy(np.vstack((sparse_mx.row,sparse_mx.col)).astype(np.int64))
values = torch.from_numpy(sparse_mx.data)
... | cdf10274d87997fbe93085d48e738e3bad92edf9 | 54,803 |
def split_outside(a, sep, start="([{", end=")]}"):
"""Split string a at occurences of separator sep, except when
it occurs inside matching groups of start and end characters."""
segments = split_by_group(a, start, end)
res = [""]
for seg in segments:
if len(seg) == 0: continue
if seg[0] in start:
res[-1] +=... | efd84168831cac6af8ac1b88bdface450c0aea14 | 54,804 |
def gen_unique_image_path(standard_image_path, image_num):
"""
Generates a unique image path based on the standard_image_path
by adding the IMAGE_IDENTIFIER_SEQUENCE followed by a number
"""
# Index where extension sequence starts (.jpg, .jpeg, or .png)
extension_start = standard_image_path.lowe... | a42148e671d9d551099108b989cec0d9ec627c96 | 54,805 |
from typing import Optional
from typing import Any
def try_wrapper(
func: callable,
*args,
ret_: Optional[Any] = None,
msg_: str = "",
verbose_: bool = True,
**kwargs,
) -> Any:
"""Wrap ``func(*args, **kwargs)`` with ``try`` and ``except`` blocks.
Args:
func (callable) ... | 3514663751028e8bcb9979f952045c053a325ff1 | 54,806 |
from typing import Dict
from typing import Any
from typing import List
def _CreateSamples(results: Dict[str, Any], number_of_messages: int,
message_size: int, cloud: str) -> List[sample.Sample]:
"""Handles sample creation from benchmark_scenario results."""
samples = []
common_metadata = {
... | a60652e74bd041dc183837746202dd3d3ed24ae5 | 54,807 |
def merge(df_list,merge_param_list):
"""
method to merge the list of data frames based on list of column identifiers. This returns intersection of values
:param df_list:
:param merge_param_list:
:return merged data frame:
"""
merged = funs.reduce(lambda left, right: pd.merge(left, right,how... | b41a26f8c8b0ff69aa80e1d4d328b67a141d68ec | 54,808 |
def yices_check_context(ctx, params):
"""Checks whether all the assertions stored in the context ctx are satisfiable.
- params is an optional structure that stores heuristic parameters.
- if params is NULL, default parameter settings are used.
It's better to keep params=NULL unless you encounter perfo... | 191f9776a2dd50ee5f56b515571c5a4cfe055b4c | 54,809 |
import torch
def collate_fn_v2_(data_batch):
"""
used for trained on the original complex dataset and tested on the ligand-only and protein-only datasets
:param data_batch:
:return:
"""
graphs, graphs3, Ys, Nodes = map(list, zip(*data_batch))
bg = dgl.batch(graphs)
bg3 = dg... | 18778a2da4986b8e4c42f5d902bc1be752fcca3f | 54,810 |
def standardvariables_get(username=None, label=None, page=None, per_page=None): # noqa: E501
"""List all instances of StandardVariable
Gets a list of all instances of StandardVariable (more information in https://w3id.org/okn/o/sd#StandardVariable) # noqa: E501
:param username: Name of the user graph to ... | b04df9f32330541c316a7e8d67217c6bcbb0ab71 | 54,811 |
from re import S
from re import T
def construct_scale(root_note, scale_signature, scale_length=None):
"""Construct a musical scale from a root note
Arguments:
root_note -- A root note object from class Note
scale_signature -- array of frequency ratios between consecutive notes on the scale
scale_... | 555099024c4e9fc8d2b487ddc7e57138084e494f | 54,812 |
def get_env_logname(name):
"""
get_env_logname
"""
modname = name.split('.')[0].upper()
envname = f"{modname}_LOGLEVEL"
# print(envname)
return envname | 6fa8032ee77d94695363d976ea06a4e58f69c7f7 | 54,813 |
def horizontal_flip(image_array: ndarray):
"""
horizontal flip doesn't need skimage, it's easy as flipping the image array of pixels !
"""
return image_array[:, ::-1] | a56b12889dad254e8618326d1a85d220827652d9 | 54,814 |
def lookup(a, idx, dim=0):
"""
Lookup the values of input array based on index.
Parameters
----------
a : af.Array.
Multi dimensional array.
idx : is lookup indices
dim : optional: int. default: 0.
Specifies the dimension for indexing
Returns
-------
out : af.... | 9084d196de4f84bfdf568ea67b3fc34f357cc88c | 54,815 |
from typing import VT
from typing import Optional
from typing import Callable
from typing import List
from typing import Set
def match_connected_hboxes(g: BaseGraph[VT,ET],
edgef: Optional[Callable[[ET],bool]] = None
) -> List[ET]:
"""Matches Hadamard-edges that are connected to H-boxes, as these ... | d26dd13ed41ff46d5d46a8df0e4704271570ea92 | 54,816 |
def n2N(n):
"""
Calculate the square matrix rank N
for a packed storage size n
Parameters
----------
n : int
The packed length.
Returns
-------
N : np.uint64
The matrix rank.
"""
N = np.uint64((np.sqrt(8*n+1)-1)/2)
return N | 93f73c36a52a1fb4200c07a678b0f5527439092c | 54,819 |
from typing import Union
from typing import List
from typing import Tuple
from typing import Dict
import requests
def scrape_url(url: str, python_objects: Union[bool, List, Tuple] = False,
nonstandard_attrs: bool = False,
migrate_old_schema: bool = True,
user_agent_str: st... | 7edb4a94361bd72999a546a4ae53233b31222140 | 54,821 |
import time
def ecs_container_instance(request, ecs_cluster, ec2_client, ecs_client, ecs_instance_type, ecs_ami):
"""
Fixture to handle spin up and tear down of ECS container instance
:param request: pytest request object
:param ecs_cluster: ecs cluster fixture
:param ec2_client: boto3 ec2 client... | 9bdf9bc4c16ab1a1c0219ce7c4910e1fa8472227 | 54,822 |
from typing import Dict
def sound_mode_rev_map_factory(instance: DenonAVRFoundation) -> Dict[str, str]:
"""
Construct the sound_mode_rev_map.
Reverse the key value structure. The sound_mode_rev_map is bigger,
but allows for direct matching using a dictionary key access.
The sound_mode_map is uses... | c93d33501d8c54c3e38fb7221f7515acdcc2f1c7 | 54,823 |
def get_objhash_from_object_desc(gitobjcontent):
"""returns object hash without control characters"""
return gitobjcontent.split(" ")[1][:40] | 662357569cb22bf77d6236e7c53a71f19f29823a | 54,824 |
def wgs84_to_lv03(latitude, longitude, altitude=None):
"""Convert WGS84 to LV03.
:param float latitude: latitude in degrees
:param float longitude: longitude in degrees
:param float altitude: altitude
:rtype: (float, float, float)
"""
lat_sex = dms_to_sex(*dd_to_dms(dd=latitude))
lon_se... | eb7d4c91ce0d8e0d3eeb4b40c556920457b38f14 | 54,825 |
def decrypt(signature: str, js: str):
"""
Main function for decrypting the signature cipher.
:param signature: original signature, encrypted
:param js: base.js contents
:return: the decrypted signature
"""
functions = get_dict_functions(js)
signature = [char for char in signature]
... | d630449ac6e3221a23e3a349026a06ea22558447 | 54,826 |
def get_path(origin, dest):
"""
MapBox APIを用いてルート探索を行う
Arguments:
origin {list} -- 出発地の緯度経度
dest {list} -- 到着地の緯度経度
Returns:
list -- ルート探索結果
"""
api = mapbox.Directions()
res = api.directions([{
'type': 'Feature',
'geometry': {
'type': 'P... | 76160f50c12f27ac8db92233cb2bd71863ae6991 | 54,828 |
import collections
def update_dict(to_update, updates):
""" Recursively updates a nested dict `to_update` from a nested dict `updates`
"""
for key, val in updates.items():
if isinstance(val, collections.Mapping):
to_update[key] = update_dict(to_update.get(key, {}), val)
else:
... | 7697d2beb42d45e60e8fdfb1386842c168bffbcc | 54,829 |
from typing import Optional
def sin(duration: int, amp: complex, freq: float = None,
phase: float = 0, name: Optional[str] = None) -> SamplePulse:
"""Generates sine wave `SamplePulse`.
Args:
duration: Duration of pulse. Must be greater than zero.
amp: Pulse amplitude.
freq: Pu... | 5f5e1f0c00991158a80d530669fc82d433fb11e4 | 54,830 |
from typing import List
def list_resources() -> List[str]:
"""
Lists all available resources by name.
:returns: A list of resources by name.
"""
return _get_resources(_get_resources_json()["resources"]).keys() | dad3e4920d353d9de7f7f354d5cc49ab8f5e1449 | 54,831 |
import torch
def computeMaskIntersection(gt, gtMask, pred, predMask):
"""
Compute intersection between GT instance and prediction.
Increase efficiency by computing elementwise product between masks
only inside the tight bounding box of the union of the prediction and
target masks.
"""
if g... | 69dbe02148f23f7f3925aebab0a1fc8afa6544fa | 54,834 |
from typing import Tuple
from typing import Union
from typing import Dict
def handle_merge_duplicate_facilities(
facilities: DataFrame,
) -> Tuple[DataFrame, Union[Dict[str, str], None]]:
"""Drops duplicate facilities by name and some other logic. Returns
facility DataFrame without duplicate facilities an... | e7e1cf96aa6bf541d55865361a52b476c897980e | 54,835 |
def get_applicant(form):
""" Gets applicant info, or adds if necessary
"""
applicant_result = Applicant.query.filter_by(email=form.get("email")).first()
if applicant_result:
applicant_id = applicant_result.applicant_id
else:
applicant_id = add_applicant(form)
return applicant_i... | 8072ee16e20939eeceacda7dc80729f108c9b3ec | 54,837 |
def graphing(dataframe_after_LDA, title, color_list, labels):
"""
Function that given a dataframe after the LDA, returns a graph where each point corresponds to a frame, and each
cluster correspond to a different location of the mouse during the experiment (HOME, CORRIDOR, FARCHAMBER)
:param dataframe... | 409f040951b2215a7ae7434d8d683827bfdc9bf1 | 54,839 |
def make_sentences(diff):
"""Create human-readable sentences out of the diff dict."""
info = []
for t in sorted(diff.keys()):
if "old" in diff[t]:
old_range = make_range(diff[t]["old"]["min"], diff[t]["old"]["max"])
new_range = make_range(diff[t]["new"]["min"], diff[t]["new"]... | a18865be04cab94c36278e70c048c1d3ec550447 | 54,840 |
def swsl_resnext101_32x16d(pretrained=True, **kwargs):
"""Constructs a semi-weakly supervised ResNeXt-101 32x16 model pre-trained on 1B weakly supervised
image dataset and finetuned on ImageNet.
`"Billion-scale Semi-Supervised Learning for Image Classification" <https://arxiv.org/abs/1905.00546>`_
... | 33c1a73fd00da4a64b77fc0408cb09ad66fbdbc1 | 54,842 |
def completeTreeNames(tree, useBS = False ) :
"""
Takes:
- tree (ete3.Tree)
- useBS (bool) [default = False] : uses bootstrap to name nodes
Returns:
(ete3.Tree) : the tree, but where the nodes without a name now have one that correspond
to their post-order OR the... | 07077fce3ea18ba40af578cd1b0768a71e7b16c8 | 54,843 |
from typing import Sequence
import string
def password(characters: Sequence[chr] = string.printable,
length: int = 8,
unique: bool = False) -> str:
"""
:param characters: The character pool that will be used when generating the password
:param length: The total length of the pass... | 949b6df79021cea6654c26bf4e3aeaacc80eab82 | 54,844 |
import json
def build(kernel_desc, attrs=None, poly=True, use_repo=True):
"""
build kernel with compute description in json format
Args:
kernel_desc : str or dict of compute description
attrs : dict of build attributes
Returns:
Module.
"""
if isinstance(kernel_desc, str... | d2c0926f9a14e465449687bd3bdafc1387211627 | 54,845 |
def bitsize(a):
"""
Compute the bitsize of an element of Z (not counting the sign).
"""
val = abs(a)
res = 0
while val:
res += 1
val >>= 1
return res | 18755ee3bfe2a122702f3161135288f8fae2dc8b | 54,846 |
def InjectDll(proc, name, entry = None):
"""Inject a dll with CreateRemoteThread in the remote process"""
kernel32 = _GetModuleHandleA(b'kernel32')
if not kernel32:
raise Win32Exception()
LoadLibraryEx = _GetProcAddress(kernel32, b'LoadLibraryA')
if not LoadLibraryEx:
raise Win32Exce... | 28e635ecfba55bfb68585a233942ce8971698c4b | 54,847 |
def find_module_corner2(mask, mode=0):
"""
mode == 0: detect corners of the convex of module
mode == 1: detect corners of the approximated convex of module
mode == 2: detect corners of the approximated contour of the module
mode == 3: detect corners of the blurred mask of the module
"""
blur... | d69d76190c166be9ed6835ee7885463e166e37da | 54,848 |
import random
def gen_rand_lists():
"""
Generate two lists with random numbers in [0,5], output them and
compare their mean and tell who is greater
"""
def gen_list():
ll = []
for i in range(5):
ll.append(random.randint(0, 5))
return ll
def calc_avera... | 03195edb47f43ce17933188523235f87472667d1 | 54,849 |
import time
import zipfile
def get_image_zip(project_id, project_name, json_data, filters=None):
"""
Create a zip file in memory containing the project's images and a
descriptive JSON file.
"""
all_data = ProjectImageData.query.filter_by(project_id=project_id).all()
date_time = time.localtime(... | eea6da48a5f6922f3584b03e9f39d8aa092df56f | 54,850 |
def degre(poly):
"""Renvoie le degré du polynôme _poly_"""
poly = clear_poly(poly)
return len(poly)-1 | cb8413dbde586e0a8383978ae646bee8f36d6a05 | 54,851 |
def store_forecast_values(forecast_id, forecast_df):
"""Store Forecast data
Parameters
----------
forecast_id: string
UUID of the associated forecast.
forecast_df: DataFrame
Dataframe with DatetimeIndex and value column.
Returns
-------
string
The UUID of the as... | 7315d566a0cbd6e4ac94347c61d369cfcd37c5f4 | 54,852 |
def gather_link_defn_lines(file_lines):
"""Returns all link def lines occuring after main content.
Should be called with set of lines starting with first
non-main-content line."""
ld_lines = []
for mdfl in file_lines:
if is_ld_block_begin_line(mdfl):
continue # ignore the b... | bd5b6a3d3fdb7153b2bbaae14745ca705ca7606e | 54,853 |
def _hdf5_yt_attr(fh, attr, unit_registry=None):
"""
Read an hdf5 attribute. If there exists another attribute
named <attr>_units, use that to assign units and return
as either a unyt_array or unyt_quantity.
"""
val = fh.attrs[attr]
units = ""
ufield = "%s_units" % attr
if ufield in... | a751fe3997af75f4bc4539873c65d0a32580c13c | 54,854 |
import numpy
def raster_rpn_calculator_op(*args_list):
"""Calculate RPN expression.
Args:
args_list (list): a length list of N+4 long where:
- the first N elements are array followed by nodata
- the N+1th element is the target nodata
- the N+2nd element is an RPN ... | 8742cd6087d9c5aa283b33cc29c5847658a32f73 | 54,855 |
import random
def get_boundary_mutation_function(minimum, maximum):
"""
Returns a function that pushes a value to either the minimum or maximum allowed value for a gene; see :ref:`mutation-functions`
:Valid For:
``"int"``, ``"[int]"``, ``"float"``, and ``"[float]"`` gene types
:param minimum... | 0f3e2b6b4d69e758fb1d439d2785306da7f537e8 | 54,856 |
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