content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def parse_oauth_callback(url: str):
"""Parse the URL to which an OAuth login redirected to obtain two
tokens: an access token for API credentials, and a refresh token for
getting updated access tokens.
"""
params = parse_qs(urlparse(url).query)
return {k: v[0] for k, v in params.items()} | 32c86c635440283538c40f6051dc57bfa61ddeb8 | 3,604,881 |
from operator import and_
def unfollow(id):
"""
Unfollow a user.
"""
user = session['user']
if user == None:
abort(404)
followed = User.query.get(id)
if followed == None:
abort(404)
if followed.id == user.id:
# don't follow self
return redirect(url_for... | 7fde25cee21b92388f575de3eca18b5429d33cc6 | 3,604,882 |
def giscube_search_get_app_modules():
"""Return the Python module for each installed app"""
return [i.module for i in apps.get_app_configs()] | c71b05590b0cda84a150e82a32ae5c88a23dd50c | 3,604,883 |
def parse_search_result_data(api_response):
"""
Parse the search result data from the given raw json by following the response style of tokopedia
Arg:
- api_response (list): list of products
Returns:
- product_list (list): list of compiled product properties
"""
product_list =... | ee1314589e1599f2d4a58523077abc8a7f270f88 | 3,604,884 |
def emc_status(hardware, emc, dgtype):
"""
Make a EMC diagnostic message
Fields:
- 'val': 0
"""
# Make EMC diagnostic status
d_emc = DiagnosticStatus(name='jetson_stats {type} emc'.format(type=dgtype),
message='{val}%'.format(val=emc['val']),
... | 9176e5bd2cce9f6da2954b3b770a281853ccda30 | 3,604,885 |
def check_bal_of_tree(node):
"""."""
if node is None:
return True
to_visit = [node]
while to_visit:
curr_node = to_visit.pop(0)
if check_bal_of_node(curr_node) > 1:
return False
if curr_node.left:
to_visit.append(curr_node.left)
if curr_n... | 081a352d7870a551e44f4404a929fc4bd961d250 | 3,604,886 |
from typing import Optional
def combine_masks(
mask1: Optional[np.ndarray], mask2: Optional[np.ndarray]
) -> Optional[np.ndarray]:
"""Combine two masks as mask1 AND mask2.
Ignore any missing mask argument.
"""
if mask1 is None:
if mask2 is None:
return None
else:
... | 15bf7898a5aff7428c11ac534a406a03cb168009 | 3,604,887 |
import io
from pathlib import Path
def _integrate(
poni_file: str,
img_file: str,
bg_img_file: str = None,
mask_file: str = None,
output_dir: str = ".",
bg_scale: float = None,
mask_setting: tp.Union[dict, str] = None,
integ_setting: dict = None, plot_setting: tp.Union[dict, str] = Non... | 73ee451f9c3b365c9773e79385692918797697c7 | 3,604,888 |
def magnify_heatmap(df,cm=sns.diverging_palette(5, 250, as_cmap=True)):
"""Color negative and positive vals for each column to display
overall trends per column and row and provide hover function
for inspecting individual values."""
cmap = cm
bigdf = df.style.background_gradient(cmap, axis=1)\
... | a55c2aeb8ba06230db878f750e014ad19122ccdb | 3,604,890 |
import torch
from datetime import datetime
import time
def trainning(model: GCN_Class or GCN_Reg,
criterion: torch.nn.modules.loss.NLLLoss or torch.nn.modules.loss.MSELoss,
train: torch.utils.data.dataloader.DataLoader,
test: torch.utils.data.dataloader.DataLoader,
... | 05b090f5a735ca4e16f35f94cdfbd1218f5792c5 | 3,604,891 |
def check_annulus(args):
"""
Checks and formats the annulus values.
:param args: The command-line arguments.
:type args: argparse.ArgumentParser Namespace
:returns: argparse.ArgumentParser Namespace -- The updated command-line
arguments.
"""
if not (args.annulus1 and args.annulus... | cd99b7200d226d9e36c644351d8e696a25a1a81d | 3,604,892 |
def computeSignalValueInFrame(startbit, ln, fmt, value):
"""
compute the signal value in the frame
"""
frame = 0
if fmt == 1: # Intel
# using "sawtooth bit counting policy" here
pos = ((7 - (startbit % 8)) + 8*(int(startbit/8)))
while ln > 0:
# How many bits can we ... | f35a63ea4811b248430ee457c64fda98ea17134d | 3,604,893 |
def submit():
"""
Process form's data or redirect if data is not correct.
Also redirects if methods!=POST
"""
if request.method != 'POST':
return redirect('/form')
if request.form['name'] and request.form['address'] and request.form['postcode'] and request.form['city'] and request.form... | fa241589b7eb7e87e551b90a6d255763415f4dc5 | 3,604,894 |
def faceOrientation2Euler(r: np.ndarray, degrees:bool=True) -> np.ndarray:
"""Converts rodriguez representation of a rotation to euler angles
Args:
r (np.ndarray): The rodriguez representation vector (angle*u in form x,y,z)
degrees (bool): If True, the outputs will be in degrees otherwize in ra... | 1576114004127484f91fd7bc8138b9eb1dfc8754 | 3,604,895 |
def image_data(xr, x_range, y_range):
"""Create a tile"""
canvas = datashader.Canvas(plot_width=256,
plot_height=256,
x_range=x_range,
y_range=y_range)
xri = canvas.quadmesh(xr)
image = np.ma.masked_array(xri.va... | a2daa2b493b537e66058ba0eba74086e354431d4 | 3,604,896 |
import re
def parse_show_spanning_tree_mst_config(raw_result):
"""
Parse the 'show spanning-tree mst-config' command raw output.
:param str raw_result: vtysh raw result string.
:rtype: dict
:return: The parsed result of the show spanning-tree \
mst-config command in a dictionary of the for... | 2f07e13ff7f79e4c15e0fe5111cbc18fb638dae8 | 3,604,897 |
from numpy_sugar.linalg import economic_qs
from numpy import pi, var, diag
from glimix_core.glmm import GLMMExpFam
from glimix_core.lmm import LMM
def estimate(y, lik, K, M=None, verbose=True):
"""
Estimate the so-called narrow-sense heritability.
It supports Normal, Bernoulli, Probit, Binomial, and Pois... | 2c41e519fb9c5adefb01c8d38a62da1b87d1992d | 3,604,899 |
def do_logout(user):
"""
logout of Google
"""
return None | 2d8b719c2f22de87bc2bdc6f0f6a27eb57ff4982 | 3,604,900 |
import torch
def astensors(*xs, dtype=None, device=None, escape=None):
"""Convert input matrices to Tensor(s) or SparseTensor(s).
Parameters:
----------
xs: one or a list of python object(s)
dtype: The type of Tensor 'x', if not specified,
it will automatically use appropriate data type.
... | bccb2337dfa00d32582bd86f7a6732e435b3247d | 3,604,901 |
def system_action(name):
"""Make a decoractor to register a system action function
See `do_system_action` docs for expected function signature.
System actions should be submitted with `system_action.submit(...)`.
See `submit_system_action` docs for more details.
:param name: A unique name to be e... | 173d9f3b77da8453ee1f2dd18692b774764e850e | 3,604,902 |
def create_text_covid_symptom_annotations(text_covid_symptom_annotation_request=None): # noqa: E501
"""Annotate COVID symptoms in a clinical note
Return the COVID symptom annotations found in a clinical note # noqa: E501
:param text_covid_symptom_annotation_request:
:type text_covid_symptom_annotatio... | 0ad144a54e745a5f799e9fb639f571e35b42b977 | 3,604,903 |
def pixel_to_icrs_coords(x, y, wcs):
"""
Convert pixel coordinates to ICRS Right Ascension and Declination.
This is merely a convenience function to extract RA and Dec. from a
`~astropy.coordinates.SkyCoord` instance so they can be put in
separate columns in a `~astropy.table.Table`.
Parameter... | 3e9182ada63da17b48ab30683cad1e90eb61f367 | 3,604,904 |
def read_sql_file(filename, encoding='utf-8') -> str:
"""Read SQL file, remove comments, and return a list of sql statements as a string"""
with open(filename, encoding=encoding) as f:
file = f.read()
statements = file.split('\n')
return '\n'.join(filter(lambda line: not line.startswith('--'), s... | bd29c1080b2fd95d690b4696bf63c92932616964 | 3,604,905 |
def random_shear(x, intensity, row_axis=1, col_axis=2, channel_axis=0,
fill_mode='nearest', cval=0.):
"""Performs a random spatial shear of a Numpy image tensor.
# Arguments
x: Input tensor. Must be 3D.
intensity: Transformation intensity in degrees.
row_axis: Index of ... | b6521c6fd1e4a3c223a110704bdf56ed7cfa7e37 | 3,604,906 |
def scenegraphLocationString(dataPacket):
"""
Given a datapacket, return a string representing its location in the
scenegraph. (::UUID:OUTPUT)
"""
return "::"+str(dataPacket.sourceNode.uuid)+":"+dataPacket.sourceOutputName | 027a69984acac4454e27a149ad822864751a0983 | 3,604,908 |
def lastsample(df):
"""
Return the last sample in the data frame.
>>> lastsample(empty)
nan
>>> lastsample(sample)
8.0
"""
if len(df) == 0:
return nan
else:
return df.iloc[-1, 0] | 2ab385dbc89f5520da1827265a6c65a6ab94dcce | 3,604,909 |
def selu(x):
"""Scaled Exponential Linear Unit. (Klambauer et al., 2017)
# Arguments
x: A tensor or variable to compute the activation function for.
# References
- [Self-Normalizing Neural Networks](https://arxiv.org/abs/1706.02515)
- Taken from keras.activations (selu got included o... | cd09b405fe19515f3a66dd10e51e136d9b577217 | 3,604,910 |
def eeg():
"""
EEG information
"""
# If they clicked on the submit button
if request.method == "POST":
return render_template("transportation.html", transportation_csv=transportation_csv[session["language"]], layout=layout[session["language"]])
else:
language_set()
return... | c11d0d9a50c0655d9a246e9a53252fb2d5294cb2 | 3,604,911 |
def lightness_Fairchild2010(Y, epsilon=1.836):
"""
Computes *Lightness* :math:`L_{hdr}` of given *luminance* :math:`Y` using
*Fairchild and Wyble (2010)* method according to *Michealis-Menten*
kinetics.
Parameters
----------
Y : array_like
*luminance* :math:`Y`.
epsilon : numeri... | aa68d927087edd3ba8930fabd020ee2a21424e0c | 3,604,913 |
def resolve(data, ind, pos, sig, geo, comp, shift=0):
"""Resolves depth information."""
# Pack arguments as list and run
pos = partition(pos, comp['workers'])
sig = partition(sig, comp['workers'])
data = partition(data, comp['workers'])
ind = partition(ind, comp['workers'])
shift = [shift] ... | 8db7a5264af473a6665a12dad04e1bd706df3c0f | 3,604,914 |
def fitness_f(x):
"""the fitness function compares the position of each gene
with the optimal"""
n = 0
for i in range(len(x.genes)):
if word[i] == x.genes[i]:
n += 1
return n | 106fd2c709fe25d0e192ba87d375b4ae6c5761bb | 3,604,915 |
def quaternion2euler(quaternion, degrees=False):
"""Converts scipy quaternion into euler angle representation.
Euler angles have degeneracies, so the output might different
from the Euler angles that might have been used to generate
the input quaternion.
Euler angles representation also has a sing... | 4342a4e8e316334b1f95ac9674a76f58c5f3e2b7 | 3,604,916 |
def get_data_to_update_from_broker(file_type, database_columns, broker_table, fiscal_year,
fy_start, fy_end, unique_identifier):
"""
Generates SQL script to pull data from broker and compare it with website table
Creates Temporary table of the rows that differ ... | 675ccbce6e58e62568479c905a36b046e74e2399 | 3,604,917 |
def toggle_monitor(self, user=None):
"""Toggles monitor and returns the newly created monitor, or None if an
existing monitor was deleted."""
if not user:
user = get_current_user()
if self.has_direct_monitor():
self.has_direct_monitor().delete()
if hasattr(self, '__monitor'): del... | 499f320d10bbbd4172cbd24caef82dd570c58ec6 | 3,604,918 |
import copy
def get(
key,
default="",
delimiter=":",
merge=None,
omit_opts=False,
omit_pillar=False,
omit_master=False,
omit_grains=False,
):
"""
.. versionadded:: 0.14.0
Attempt to retrieve the named value from the minion config file, pillar,
grains or the master conf... | 794a7bbb1fe3129ff4bc81322c4c3449cc8a509e | 3,604,919 |
from bs4 import BeautifulSoup
def extract_paragraphs(txt: str) -> list:
"""
Extracts the paragraphs from HTML code as defined by the <p> anchor.
:param txt: String of the content to derive an embedding for.
:return: List of all the paragraphs.
"""
soup = BeautifulSoup(txt, features='html5lib'... | 9f8e1cd43420c27a65ececaba2efb8d16ceb357d | 3,604,921 |
import time
def get_epoch(year, month='01'):
"""
calculate the epoch of first day of a year-month
"""
pattern = '%Y.%m.%d %H:%M:%S'
return int(time.mktime(time.strptime(str(year) + '.' + str(month) + '.01 00:00:00', pattern))) | 4126b720dedb0c91ec18f5198740896035da07e7 | 3,604,922 |
def get_directive_type(directive):
"""Given a dict containing a directive, return the directive type
Directives have the form {'<directive type>' : <dict of stuff>}
Example: {'#requirement': {...}} --> '#requirement'
"""
keys = list(directive.keys())
if len(keys) != 1:
raise ValueError(... | 584c1f22fc120815e79c781fc7ace69940c0f651 | 3,604,923 |
def process_articles_results(source_articles_list):
"""
Function that processes source articles result and transfroms them into a list of Objects
Args:
source_articles_list : A list of dictionaries that contain source articles details
Returns:
source_articles_results : A list of source ... | 644f3da03f61639ce3312d45014a4a69b55f41c3 | 3,604,924 |
import torch
def MaskedNLL(target, probs, balance_weights=None):
# adapted from https://gist.github.com/jihunchoi/f1434a77df9db1bb337417854b398df1
"""
Args:
target: A Variable containing a LongTensor of size
(batch, ) which contains the index of the true
class for each corr... | 17132ad088b00ae096f16946f5026ed2133c8eeb | 3,604,926 |
def set_log_level(level):
"""set_log_level(std::string level)"""
return _RMF.set_log_level(level) | a3cd680429fbda53fb9e7238d02a0cfd5c80aaf8 | 3,604,927 |
import json
def get_notebook_cells(path):
"""获取ipynb文档的cells"""
with open(path, "r", encoding="utf-8") as f:
data = json.load(f)
return data["cells"] | a7f4c9b45b1c58bdcf049c0834199f1a36402fa0 | 3,604,928 |
def jacobi(n, alpha, beta, monic=0):
"""Returns the nth order Jacobi polynomial, P^(alpha,beta)_n(x)
orthogonal over [-1,1] with weighting function
(1-x)**alpha (1+x)**beta with alpha,beta > -1.
"""
if n < 0:
raise ValueError("n must be nonnegative.")
wfunc = lambda x: (1-x)**alpha * (1... | 8dbbe468c0322d23c7605595305becccc55e10b6 | 3,604,929 |
async def async_setup_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
"""Async setup hass config entry."""
hass.data[DOMAIN] = {entry.entry_id: {TUYA_HA_TUYA_MAP: {}, TUYA_HA_DEVICES: set()}}
success = await _init_tuya_sdk(hass, entry)
if not success:
return False
return True | 9cb3b8b09f879fc8b1466c7bc083e15a138ead1b | 3,604,930 |
def _get_vasprun(args):
"""
Internal method to support multiprocessing.
"""
return Vasprun(args[0], ionic_step_skip=args[1],
parse_dos=False, parse_eigen=False) | 3626be15c816e4987f910fa187b17d7a7dcf03c2 | 3,604,931 |
def get_state_dependencies(state):
"""
Returns all of the states that this state depends on
"""
return states[:states.index(state)] | e67e40fb78b90f306d1a22b15872203d3253fbc9 | 3,604,932 |
def grover_circuit():
"""
Builds a QuantumCircuit of the qiskit aqua implementation of
grover's algorithm with set parameters.
Args:
Returns:
Resuling circuit of the qiskit aqua implementation of Grover's
algorithm after adding measures on every qubit.
"""
sat_cnf = """
c E... | f35bb3c553696801bb2be4c160db6c1ad5969390 | 3,604,933 |
def u8(x: int) -> bytes:
"""
Encode an 8-bit unsigned integer.
"""
assert 0 <= x < 256
return x.to_bytes(1, byteorder='little') | c23bb4b6ea6bb610da5c3ecd281129e0bcc40bb7 | 3,604,934 |
def state() -> str:
"""Return the state of the sensor."""
for item in FEED.entries:
last_updated = str(item.guid).replace("Country ", "")
last_updated = str(dt.strptime(last_updated, "%a, %d %b %Y %H:%M:%S GMT"))
return last_updated | 021cc6ad4b2c2407f80cbabd6b295917c5500203 | 3,604,935 |
def ultimate_answer(question):
"""Provides an answer to the ultimate question.
Returns '42' if the question is 'What is the meaning of Life, The Universe,
Everything?' otherwise returns 'That is not much of a question'
args:
question (str): The question to be answered.
returns... | 5fc1c51c3901d3005adc78468668317f86e54d5c | 3,604,936 |
def find_class_args(klass):
"""
Find all class arguments (parameters) which can be passed in ``__init__``.
"""
args = set()
for i in klass.mro():
if i is object or not hasattr(i, '__init__'):
continue
args |= set(find_function_args(i.__init__))
return list(args) | 37e6c8f75ed2f04ed6dd9301b2944a8cdf4bab0f | 3,604,937 |
from .internal.domain import gt_domain
def transliterate(text, source_language="auto"):
"""
Returns the transliteration provided by Google Translate (if available)\n
i.e Ohayou --> おはよう / おはよう --> Ohayou
"""
if driver is None:
raise BrowserError("Browser is not set yet.\n Please set it wit... | d4d85f80e25f22ceb118d16ee367c7c5b4306ef7 | 3,604,938 |
def last(s):
"""Return a word string sorted alpha-ly by last char in each word.
input = string, words
output = string, sorted words alphabetically by last char
ex: "man i need a taxi up to ubud") ==>["a", "need", "ubud", "i", "taxi", "man", "to", "up"]
"""
alpha = list(map(chr, range(97, 123))... | ed1fc01420d1b89e6b52a54e7413e54fbc8ed691 | 3,604,940 |
from pathlib import Path
from typing import Dict
def git_find_remotes(p: Path) -> Dict[str, str]:
"""从git项目中找到远端仓库url.
Args:
p (Path): 目标地址
Raises:
AttributeError: 如果路径不是git项目则会抛出
Returns:
Dict[str, str]: 远程仓库的本地命名和对应地址
"""
d = make_repod(p)
if not is_git_dir(d)... | 2fdc884bc2bdd5943f6fd753563d3e3ed6efb152 | 3,604,941 |
def _vectorize_intersection(f):
"""Vectorize a function f(DAG, node) for one or more nodes, return set intersection."""
def wrapper(DAG, nodes):
return set.intersection(*(set(f(DAG, node)) for node in _set(nodes)))
return wrapper | 0aa1bdaebd97429f09f8a09aa9b57f68bfa3680a | 3,604,942 |
from datetime import datetime
def register(email,
password,
confirmed=True,
next_action_uri=None,
_invoke_handler=True):
"""
Register new user in traditional way
Args:
email: user email
password: user password
confirmed: if no, e... | b829f0032e0fea2dfbef98cd77df451ed9a0dd3c | 3,604,943 |
def get_u_for_capture(searchers: dict, V: list, v: int):
"""Return a list with the all searchers vertex u that could capture the target placed at v"""
my_list = []
for s_id in searchers.keys():
s = searchers[s_id]
for u in V:
# get capture matrix
C = s.get_capture_mat... | c3265082d9db032f343118e29dc3d4a844298932 | 3,604,944 |
def get_name_color(*args):
"""
get_name_color(_from, ea) -> color_t
Calculate flags for 'get_ea_name()' function.
Get name color.
@param _from: linear address where the name is used. if not
applicable, then should be BADADDR . The kernel returns
a local name color if t... | c3a431eae9c3ca05cd584eafc24874d76efa95ff | 3,604,945 |
def spectral_moment(k, matrix):
""" Return k-th spectral moment of a matrix
parameters: matrix
"""
return np.sum(np.power(spectrum(matrix), k)) | 821634a2b02017d3a8c027fec5718e7f2001820a | 3,604,946 |
from typing import Dict
async def authentication_token_from_email(
*, client: AsyncClient, email: str, db_session: AsyncSession
) -> Dict[str, str]:
"""
Return a valid token for the user with the provided email.
If the user doesn't exist, it is created first.
"""
password = random_lower_stri... | 5f68a9dc4d74152382e972e076fae24fdeaa959a | 3,604,948 |
def fit_O2_Ar(df, length):
"""
fit O2 and Ar signal to a linear line for O2 correction
Parameters
----------
df : DataFrame
DESCRIPTION.
length : int
The index of DataFrame of how far the dataset is fitting.
Returns
-------
slope, intercept and r_square.
"""
... | 372f911fc83f216d17a4044d5b43b35b508a1f1f | 3,604,949 |
def compare_score(path_region, path_full, score_str, conf_interval=True, return_stat=False):
"""This function is used to compare the region-based calibration score
and full-image based calibration score
"""
score_region, percent_pixel_region = load_score(path_region, score_str, "region")
score_full,... | 8a37b3e6738312d65ea0268d019a7e7415245c97 | 3,604,950 |
import requests
def post_through_spectre(path, data=None, extra_headers=None):
"""This simulates a client POSTing to a service proxied
through Spectre.
"""
headers = HAPROXY_ADDED_HEADERS.copy()
if extra_headers is not None:
headers.update(extra_headers)
return requests.post(SPECTRE_BA... | a941c85070ed1d6c75b2e38f70ebb483d7e626e8 | 3,604,952 |
def rule_confidence(rule: IndexRule, binary_data: np.ndarray) -> float:
"""
Confidence of a rule (x -> y) in the transactions represented by binary_data
:param rule: a tuple where the first element is the set of indexes for the left side of the rule (x) and the
second element is the set of indexes for t... | 572c4425a98b875593b0b2a2fa73a0db94524ac2 | 3,604,953 |
def evaluate_poly(poly, x):
"""
Computes the polynomial function for a given value x. Returns that value.
Example:
>>> poly = (0.0, 0.0, 5.0, 9.3, 7.0) # f(x) = 7x^4 + 9.3x^3 + 5x^2
>>> x = -13
>>> print evaluate_poly(poly, x) # f(-13) = 7(-13)^4 + 9.3(-13)^3 + 5(-13)^2
180339.9
po... | 2705dbdaa937c564454078dc2cbc8dd4a9bd56e8 | 3,604,954 |
def currency_format(currency="USD", suffix=""):
"""Currency formatter for matplotlib.
:param currency: Name of the currency, e.g. 'USD', 'GBP'.
:param suffix: Suffix to append, e.g. 'B'. Defaults to ''.
:returns: FuncFormatter.
"""
prefix = {
"USD": "$",
"GBP": "£"
}[curre... | 65d4e1739d92bf93736269579ee6369d46b3ab4a | 3,604,955 |
import base64
def json_to_numpy(obj):
"""Decodes a dict from json into a numpy array"""
dtype = obj['dtype']
if dtype == 'string':
dtype = 'str'
if 'data' in obj:
return np.array(obj['data'], dtype).reshape(obj['shape'])
data_bytes = base64.decodebytes(obj['dataEnc'].encode())
... | 313b2a9b4df7393cd3da10492b2b553482f7ef04 | 3,604,956 |
from ase import Atoms
from ase.calculators.lj import LennardJones
from pinn.io import load_numpy, sparse_batch
from pinn.models import potential_model
import tempfile
def test_potential_model():
"""A simple example to test training and using a potential"""
def three_body_sample(atoms, a, r):
x = a * n... | b57be7be108f41fd617f408f8835b735723369a0 | 3,604,957 |
def get_segm_by_name(*args):
"""
get_segm_by_name(name) -> segment_t
Get pointer to segment by its name. If there are several segments with
the same name, returns the first of them.
@param name: segment name. may be NULL. (C++: const char *)
@return: NULL or pointer to segment structure
"""
return ... | bce51941886f5ceaa22e9d75e2e4352193582666 | 3,604,959 |
def assign_pt_to_grid(XYs, grid, distance_metric='euclidean', random_state=None):
"""
Spatial join pts to grids. Reassign border points to nearest grid based on centroid distance.
"""
np.random.seed(random_state)
XYs = convert_geodataframe(XYs)
# Equate spatial reference systems if defined
... | ae893fb99a68158104c96ba2812e65e80dc256fa | 3,604,960 |
def svn_diff_contains_conflicts(*args):
"""svn_diff_contains_conflicts(svn_diff_t diff) -> svn_boolean_t"""
return _diff.svn_diff_contains_conflicts(*args) | b0eb8d8555700326d522a6eb370aa03b2a3e9d38 | 3,604,961 |
import re
def ask_for_droplet_name() -> str:
"""
Present a prompt for the user to enter a name for the droplet.
Valid droplet name characters: a-z, A-Z, 0-9, . and -
:return: str (the preferred name)
"""
pattern = re.compile("^[a-zA-Z0-9]+[-.a-zA-Z0-9]*$")
q = question(
message="E... | 014d3c1af4deef37f42b697b4c01a4978da9abb1 | 3,604,962 |
def applyIncidenceFilter(image, bandNames, classDictionary, numChangesCutoff = 8, connectedPixelCutoff=6):
"""
Function to apply an incidence filter. The incidence filter finds all pixels that changed more than numChangesCutoff times and is connected
to less than connectedPixelCutoff pixels, then replaces ... | fe481ba5342b4e40c8a75b9c59bfe393dd9ad3dc | 3,604,963 |
def loadJsonConfig(jsonobj_or_fn):
"""Loads the visualization options from a JSON object or file.
jsonobj_or_fn can either by a dict (previously obtained by saveJsonConfig
or a str indicating a filename (previously saved using saveJsonConfig.)
"""
return scene().loadJsonConfig(jsonobj_or_fn) | 3955ae668078a776eaf16ae209b777aa1e74babc | 3,604,964 |
def load_expected_whitelist(filename, logger):
"""
**Purpose**
Load the expected whitelist and output a set
"""
expected_whitelist = []
oh = open(filename, 'rt')
for line in oh:
expected_whitelist.append(line.strip())
oh.close()
expected_whitelist = set(expected_whiteli... | 097981e4d7e2c44931cdeebd935e6ba2b8f78e38 | 3,604,965 |
def split(string_to_split, separator):
"""Returns the list of strings divided by the separator."""
return string_to_split.split(separator) | c96d4ed6e3128617925c7d52c19d607cbfe1ece1 | 3,604,966 |
def create_user(
username: str,
password: str,
is_admin: bool = False,
is_manager: bool = False,
is_active: bool = True,
) -> str: # pragma: no cover
"""
Create User
Params:
* **username** String, required.
* **password** String, required, will be set through `set_password`.... | 10abff306b5243b87557d8369dc37a9c0059cd88 | 3,604,968 |
def _find_biggest_value(list):
"""
Get the intex of the largest value in list of values
:return: -1 if list empty, otherwise index of biggest value
"""
if len(list) < 1:
return -1
max = 0
for idx, val in enumerate(list):
if val > list[max]:
max = idx
return ... | e4c4267ac2bfe73ad3bdb11433935805f4859e95 | 3,604,970 |
def open_file(experiment_id='piControl', source_id='BCC-CSM2-MR', path='/glade/u/home/molina/CMIP6_pathnames.csv'):
"""
Parameters
----------
Input:
experiment_id = type of experiment (e.g., piControl, ssp585, historical)
"""
data_list = pd.read_csv(path)
if source_id... | db723fa2d1be274800cfeab698610e9f9aa27e3f | 3,604,971 |
def populate_index(dataset_loader, module_dea_index):
"""
Index populated with example datasets. Assumes our tests wont modify the data!
It's module-scoped as it's expensive to populate.
"""
loaded = dataset_loader(
"s2a_ard_granule", TEST_DATA_DIR / "s2a_ard_granule.yaml.gz"
)
asse... | 8a0e2570e019554b8da1557209b3bae4b14e6807 | 3,604,972 |
from typing import List
from typing import Union
def solve_sudoku_CSP(sudoku: List[List[int]], k: int) -> Union[List[List[int]], None]:
"""Solve a k-by-k block Sudoku puzzle by encoding the problem as a collection of constraints
and using a constraint satisfaction problem (CSP) solver
:param sudoku: A... | 0a15743a38a93b15f271f3c68a164ca4e3cc0267 | 3,604,973 |
def calculate_direct_distance(route):
"""calculate distance between start and end point of route.
input: route = list of paths, which are lists of points in route.
output: direct distance, in meters
"""
starting_pt = route[0][0]
destination_pt = route[-1][-1]
return haversine(*starting... | 83465f8e78a1a588717567f9a86e72da1847f03a | 3,604,974 |
def test_search_url_callbacks_not_found(tmpconfig):
"""Test search_url_callbacks when pattern does not match."""
sopel = bot.Sopel(tmpconfig, daemon=False)
results = sopel.search_url_callbacks('https://example.com')
assert not list(results), 'No handler registered; must return an empty list'
def ur... | 99230b8f331eedb8b110646eae66c2ae20428b8d | 3,604,975 |
def calculate_cohens_d(values_1: np.ndarray, values_2: np.ndarray) -> float:
"""Calculate Cohen's d using pooled standard deviation.
:param values_1: First array of values
:type values_1: np.ndarray
:param values_2: Second array of values
:type values_2: np.ndarray
:returns: Cohen's d effect ... | 9ccc07effa125c3b5026866f2e2c13373801eb00 | 3,604,976 |
def generate_image(session, pg_gan_model, tl_gan_model, features, feature_names):
"""
Converts a feature vector into an image.
"""
# Create rescaled feature vector
feature_values = np.array([features[name] for name in feature_names])
feature_values = (feature_values - 50) / 250
# Multiply by... | 0b422b999956e60f937d3e863eca8e169a5bc150 | 3,604,977 |
from datetime import datetime
def validate_date_input(requested_date):
""" date validation.
Args:
requested_date (date) - date requested for forecast.
Returns:
(bool) - validate ended in success or not.
(str) - error message.
"""
if isinstance(requested_date, datetime.date)... | 0f96f0c61407061180d18ae841065c57cda7bdbc | 3,604,978 |
import numpy
def haversine(coord1, coord2, to_radians=True, earth_radius=6371):
"""
slightly modified version: of http://stackoverflow.com/a/29546836/2901002
Calculate the great circle distance between two points
on the earth (specified in decimal degrees or in radians)
All (lat, lon) coordinate... | 46d073421bed55e0ccd11f995dbcbfdaf5124720 | 3,604,979 |
def inline(s, fmt):
"""Wrap string with inline escape"""
return "`\u200B{}\u200B`".format(fmt.format(s)) | 3f07a4f55e60c763a10956c9ac52314b6958eca8 | 3,604,980 |
def has_row_check(table, conn):
"""Check if there is any row in table.
Args:
table(str): Name of the table
conn: connection to the database
Returns:
True if row count > 0, else False
"""
row_count = pd.read_sql(sql=row_count_check.format(table=table), con=conn).loc[0, 'count... | ac99ab1c4c593d8c2015d5f285b3ec2b65c925f3 | 3,604,982 |
from typing import Optional
import cgi
def format_download_filename(content_disposition: Optional[str], download_url: str) -> str:
"""Uses RFC-6266 'Content-Disposition' header to get file name"""
value, params = cgi.parse_header(content_disposition or '')
download_filename = params.get('filename')
... | 0abd0d17db1b92afff1fc5163aadd6450dac7e1c | 3,604,983 |
def ct_vpeak(Zb,Ip,N):
"""
ct_vpeak Function
Simple formula to calculate the Peak Voltage of a CT.
Parameters
----------
Zb: float
The burden impedance magnitude (in ohms).
Ip: float
The peak current for the CT.
N: float
... | 56ce939e7e7507f27577d115f326027e9ea0253b | 3,604,984 |
from typing import Sequence
from typing import Optional
from typing import Dict
def calculate_prensors(
expressions: Sequence[expression.Expression],
options: Optional[calculate_options.Options] = None,
feed_dict: Optional[Dict[expression.Expression, prensor.Prensor]] = None
) -> Sequence[prensor.Prensor]... | 2dc8dc131c9d87947b40021264ab5a51c86fcee2 | 3,604,985 |
def network_matched_filter_snr(IFO_matched_filter_snrs, IFO_optimal_snrs):
"""Return the network matched filter SNR for a given detector network. Code
adapted from Christopher Berry's python notebook
Parameters
----------
IFO_matched_filter_snrs: list
list of matched filter SNRs for each IF... | d9ec28ab4f988e48f20ac29ec7d4fa74b2e754a7 | 3,604,986 |
def scale(df: pd.DataFrame, scale: dict):
""" apply a z-transformation (centering) to some dataframe"""
return (df - scale['mean']) / scale['sd'] | c832dc5535f1db597e83e8872d9d8fec3b11fec1 | 3,604,988 |
import types
def new_coverage(*args, **kwargs):
""" xml_report """
r = orig_coverage(*args, **kwargs)
r.orig_xml_report = r.xml_report
r.xml_report = types.MethodType(new_xml_report, r)
return r | e1a0f01191fdb9b10c29a3a69b4eb8755afac2d6 | 3,604,989 |
def delete_ticket(request):
"""
Delete a ticket
:param request: ticket.id the ticket id
:return:
"""
# Get actual user
actual_user = User.objects.filter(username__iexact=request.user.username)[0]
ticket_id = request.GET.get("ticket_id", None)
ticket_to_delete = Ticket.objects.filter... | 590f41b64ab1294b17bc1c90565d3da5a0c2f360 | 3,604,990 |
def cov(a, b):
"""
Computes covariance only between terms of a and terms of b, not within
a and b.
Parameters
----------
a, b: 2darray, features x samples
Returns
-------
Covariance between features in x and features in y
"""
demeaned_a = a - np.mean(a, axis=1, keepdims=Tru... | aba834a654df2415cadd3a7579247c0b333d1dcd | 3,604,991 |
def _compute_cultural_score_building(building_geometry, historical_elements_gdf, historical_elements_gdf_sindex, score = None):
"""
Compute pragmatic for a single building. It supports the function "pragmatic_meaning"
Parameters
----------
buildings_geometry: Polygon
building_land_use: s... | 743be39a3c100f53787df8195298c43affac8b4d | 3,604,994 |
def extract_footprint_location(footprint):
"""
Constructs a location from a building footprint.
:param footprint: pandas row representing a building footprint.
"""
type_ = extract_location_type(footprint)
if not type_:
return
polygon = footprint["geometry"]
point = polygon.cen... | 38da1ec0da9c51186d8540e55a3fab298300e115 | 3,604,995 |
def _rule_spec_from_path(path):
"""Turn a sequence of path components into a rule spec
Args:
path (sequence[unicode]): the URL path components.
Returns:
dict: rule spec dict, containing scope/template/rule_id entries,
and possibly attr.
Raises:
UnrecognizedRequestE... | b8f1bad2e4eb2df4b3343211c87b273f5944c537 | 3,604,996 |
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