content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def compute_t_shift(metadata, i, t_p_interp, p_interp, p_file, date_ref,
time_ref, dpdt_thresh=10, plot_pressure=True):
"""
***OBSOLETE***: I determined that a multiplicative factor more accurately
adjusts the Belsorp time than a time shift. See compute_t_multiplier.
Computes number... | 2a7d5cfd9ba2026b4179cb4629ca5d2f7b8409d9 | 3,616,593 |
def quickHBar(ax, xticks, values, colors="b", lw=None):
"""
This function draws an horizontal bar graph
:Arguments:
:type ax: matplotlib Axis2D
:param ax: Axis on which bar graph will be drawn
:type xticks: list
:param xticks: Listo of labels for the bars
:type val... | 15bdcb7b7c78682419af6d53ef103527f434c553 | 3,616,594 |
from datetime import datetime
def exportFromNotebook(notebookPath, outFNames, outFPath=None, encoding='utf-8') :
"""
Routine to auto-generate a python script from Jupyter notebook cells.
Exports code cells that start with
# export name1 name2 ...
where one of the names is in the supplied list ... | 332597f76c692080ffc561775ee2b837dbc1720b | 3,616,595 |
from re import T
def enable_train_mode(mod: T) -> T:
"""Return a module in training mode."""
return mod.train() | f72448d7b4bc908b8f6fe58b52993d546698e8fd | 3,616,596 |
def train_step(real_image, label, noise):
"""
:param real_image:
:param fake_image:
:return:
"""
with tf.GradientTape() as gen_tape, tf.GradientTape() as disc_tape:
generated_image = generator(noise, label, training=True)
real_output = discriminator(real_image, label, training=... | 6323a5fa0e4982b004151844b84d41b3d557348b | 3,616,597 |
import torch
def compute_accuracy(logits, labels, mask):
"""Compute the accuracy"""
logits = logits[mask]
labels = labels[mask]
_, indices = torch.max(logits, dim=1)
correct = torch.sum(indices == labels)
return correct.item() * 1.0 / len(labels) | a7ee234837024598fc95fa9c54c55802ea411577 | 3,616,598 |
import random
import string
import traceback
def run(ceph_cluster, **kw):
"""
pre-requisites:
1. Create a volume with a name
2. Create a subvolume with a name
3. Create a subvolume group with a name
Test operation:
1. Try to create a volume with the same name
2. Try to create a subvol... | e11dad62bac4033954848050c5f8a1b9c3588e3e | 3,616,599 |
def consistent(a, b):
""" It is possible for an argument list to satisfy both A and B """
return (len(a) == len(b) and
all(issubclass(aa, bb) or issubclass(bb, aa)
for aa, bb in zip(a, b))) | e79ec485c667d9d85692eb43de3f8442a28e94ec | 3,616,600 |
from io import StringIO
def adjust_image(f, max_size=(800, 800), new_format=None, jpeg_quality=90, fill=False, stretch=False,
return_new_image=False, force_jpeg_save=True):
"""
Підганяє зображення під параметри.
max_size - максимальний розмір картинки. один з розмірів може бути None (авто... | 50b61e6f21639f7cca74b8dfcf5cb24ade4fff59 | 3,616,601 |
import urllib
def is_cloneable(owner, name):
"""Verify if a repository is clone-able.
Parameters
----------
owner : string
User name of the owner of the repository.
name : string
Name of the repository to clone.
Returns
-------
cloneablility : 2-tuple
A 2-tupl... | eb58a5ebc32f7253c58c220a34c70494d5e4f0bf | 3,616,602 |
import pandas
def limit_to_appropriate_columns(
*, res: pandas.DataFrame, transform: VariableTreatment
) -> pandas.DataFrame:
"""
Limit down to appropriate columns.
:param res:
:param transform:
:return:
"""
assert transform.plan_ is not None # type hint
assert transform.score_fr... | 9dba8339b0a7d15964199e5ab2ebfc4d3b4d443c | 3,616,604 |
from typing import Union
def Optional(trait: TraitType) -> Union:
"""
Return Union of function argument and Instance(_Undefined)
Args:
trait (TraitType): optional trait
Returns:
union with undefined instance
"""
return Union(trait, Instance(_Undefined)) | 4fa6bf6017022e652f9af38f2db43d52ec1ed2f5 | 3,616,605 |
def mda_1D_Xindex(ScanNum,DetectorNum,coeff=1,bckg=0,filepath=None,prefix=None,scanIOC=None):
""" Return x=index and y=detector(DetectorNum)
for a given detector number DYY (as shown in dview). """
try:
(data_file,det)=mda_unpack(ScanNum,filepath,prefix,scanIOC)
index=det[DetectorNum][1]
... | 827f950b3d793a0f7c8c39ce9236aba1ff9ff893 | 3,616,606 |
def requires_admin(func):
"""Decorator requiring the requesting user be a website admin"""
@wraps(func)
def inner(*args, **kwargs):
if g.user is None:
return JsonResponse.create(StatusCode.LOGIN_REQUIRED, {'message': "Login Required"})
if not g.user.website_admin:
re... | f9793b3f1a9d8a7732842930784eab8578a4eb96 | 3,616,607 |
from cesiumpy.base import _CesiumObject, _CesiumEnum
import six
def to_jsscalar(x):
""" convert x to JavaScript representation """
if isinstance(x, (_CesiumObject, _CesiumEnum)):
return x.script
if isinstance(x, bool):
# convert to JavaScript repr
x = 'true' if x else 'false'
... | b4049e067a0bbec29da83ffecc7110212050ced2 | 3,616,608 |
def covid_API_request(location:str = data['location'],
location_type:str = data['location_type']) -> dict:
"""This function returns live data from the uk-covid19 API.
Args:
location (str, optional): Location of data needed from API.
Defaults to data["location"].
location_type (str, ... | e22247bd74c06ca2b77ad4aa6136b26c46bdc82f | 3,616,610 |
def pgloss(y_true, y_pred):
"""Policy Gradients loss. Maximizes log(output) · reward"""
return - K.mean(K.log(y_pred) * y_true) | 0f446fe4bc7bbf90bdea8a9557313e754b7f0dc5 | 3,616,611 |
from pathlib import Path
def remove_venv_config(name: str) -> Path:
"""Removes a vsh virtual environment configuration file
Args:
name: name of virtual environment
path: path to virtual environment
working: path of working dir when entering virtual environment
Returns:
co... | df62e7d9e6468360dfd17a3c7affdf877f57b97f | 3,616,612 |
def open(**kwargs):
"""
A factory function to open new ``Vim`` object.
``with`` statement can be used for this.
"""
return Vim(**kwargs) | 459bc8663f48a7dffb3e28a02455b3d935721d3d | 3,616,613 |
def difference(geometries,
spatial_ref,
geometry,
gis=None):
"""
The difference function is performed on a geometry service
resource. This function constructs the set-theoretic difference
between each element of an array of geometries and another geometry
... | 36142825006076adebee7260d1141e9a07e7a61a | 3,616,614 |
from .main import round_trip_load
def load_yaml_guess_indent(stream, **kw):
# type: (StreamTextType, Any) -> Any
"""guess the indent and block sequence indent of yaml stream/string
returns round_trip_loaded stream, indent level, block sequence indent
- block sequence indent is the number of spaces be... | f8b7c6df5bc45aafe3b0551ace1c3e3ce7fe058e | 3,616,615 |
def remove_duplicate_edges(G, max_ratio = 1.5):
"""
function for deleting duplicated edges - where there is more than one edge connecting a node pair. USE WITH CAUTION - will change both topological relationships and node maps
:param G: a graph object
:param max_ratio: most of the time we see duplicate ... | bc2a23081749e3dcb135ceea5aad004a7331e794 | 3,616,617 |
from typing import Sequence
from typing import Callable
def conv_classifier_deterministic_loss(
params: utils.Params,
batch: utils.Batch,
num_classes: int,
layer_channels: Sequence[int],
l2_reg: float = 0.0,
explicit_tagging: bool = False,
activation: Callable[[LayerInputs], LayerInputs] =... | 1432767d83c27826e06574ea825117c764708dfc | 3,616,618 |
def repo_changed(directory):
"""Determine if the Git repository in directory is dirty"""
ret = _call_git("status", "--porcelain", directory=directory)
return bool(ret.stdout) | 9956fb3211b7e9d689bc72f5a09ecb46f4f95b00 | 3,616,619 |
def color_bar(mode):
"""
Create different colormap for each mode
:param mode: 1 -- Rate, 2 -- Occupancy, 3 -- Recommanded
:type mode: int
:returns: color map
:rtype: branca.Colormap
"""
cm_name = {1: cm.linear.YlGnBu_07,
2: cm.linear.RdPu_06,
3: cm.linear.... | 28e0e7f91fa0edde6edc9325e5d1cbf7a9672bf7 | 3,616,620 |
def just_nucs(seqs):
"""eliminate sequences containing gaps/Ns,
along the 1st axis, match each base in seqs to <= 3 element-wise,
give the indices of those just_nucs seq idx.
"""
(indices,) = (seqs <= 3).all(axis=1).nonzero()
just_bases = seqs.take(indices, axis=0)
return just_bases | 142bb7aa905e34d5e12fcfe3233bc3f80d440916 | 3,616,621 |
def plot_image_as_3d_histogram(image, save_path=None, image_title='Image', histogram_title='Histogram'):
"""
plot an image as a 3d histogram beside itself.
:param image: a 2D numpy array that is the image to plot
:param save_path: the path to save the plot to. if None the figure is displayed.
:param... | 620a7cf9351ef845dc82be5eb86fb1f6f5e44158 | 3,616,622 |
def read_clip(path, undersample=4):
"""Read a GIF a return an array of shape (C, W, H, T)."""
gif = Image.open(path)
frames = []
for i in range(gif.n_frames):
gif.seek(i)
frames.append(np.array(gif.convert('RGB')))
frames = frames[::undersample]
array = np.stack(frames).transpose... | 322e54057454822068e0cc6eb048cf899e1f49f6 | 3,616,623 |
import copy
def fir(nb, nk, u, y):
"""
Estimates a FIR model based on input (u(t)) and output (y(t)) vectors.
Returns the polynomial B(q) relative to the MIMO FIR model with nu inputs
and ny outputs, also affected by white gaussian noise e(t), as follows:
y(t) = B(q)*u(t) + e(t)
Parame... | c156d98f824e825a1a82e00f94a0113d4309d936 | 3,616,624 |
import warnings
def random_forest_error(forest, X_train, y_train, X_test,
alpha_level=0.05,
n_fixed_points=50, n_mc_samples=500,
n_trees_var=500,
use_built_trees=True,
random_state=None, n_jobs=None... | 8d110d90aab17514c253d42cff80d0c24dabe081 | 3,616,625 |
def descriptive_stats(x, feature_prefix=''):
"""Create a pandas dataframe containing the features calculated on x.
x is an input array for which the features below are calculated.
feature_prefix is prepended to each of the feature names to create unique columns."""
feature_names = [
'minimum'... | f97843f0bdff307ca40a16bf5c3b970f43ca0f4d | 3,616,626 |
from typing import Callable
def bind(
function: Callable[
[_FirstType],
KindN[_BindableKind, _UpdatedType, _SecondType, _ThirdType],
],
) -> Kinded[Callable[
[KindN[_BindableKind, _FirstType, _SecondType, _ThirdType]],
KindN[_BindableKind, _UpdatedType, _SecondType, _ThirdType],
]]:
... | 3dcd70a5f72ffd41df89e92b89a3761faf75576f | 3,616,628 |
import numbers
def transforms_rowskipfilter(
data,
output_data=None,
model=None,
count=0,
**params):
"""
**Description**
Allows limiting input to a subset of rows by skipping a number of
rows.
:param count: Number of items to skip (inputs).
:par... | 9fa574924c1c130acd6efaa1a4231175fc8d206d | 3,616,629 |
def startofday(expr, offset=None):
"""Get the start of day for a timestamp (round to preceding midnight).
Parameters
----------
expr: str, Column or expression.
The datetime column/expression to round to the start of the day.
offset: int, default None
The number of days to shift the... | c5a6439880bc2e64771fc760e7bdd1159d6773ad | 3,616,631 |
def polar2cart(angle, magnitude, retField=False):
""" Returns the field from the input phase angle and magnitude.
Args:
- angle, phase angle of the field (2 dims);
- magnitude, magnitude of the field (2 dims);
- retField, if True returns a field, otherwise returns (x,y).
"""
if retField:
if np.isscalar(m... | 1fe837256e89b9dafdbbf5148a85ccbf88100d3a | 3,616,632 |
def grant_role(role, user, tenant=None):
"""Grants `role` to `user` (and optionally, on `tenant`)"""
role = db_api.ROLE.get_by_name(name=role).id
user = db_api.USER.get_by_name(name=user).id
if tenant:
tenant = db_api.TENANT.get_by_name(name=tenant).id
obj = db_models.UserRoleAssociation()... | 62e6344d64085b0cedb34ff02145a550566c99ff | 3,616,633 |
def get_domain_server_version(domain):
"""
Get the Server version based on the Server header for the web server.
"""
if domain.canonical.server_version is not None:
return domain.canonical.server_version
if domain.https.server_version is not None:
return domain.https.server_version
... | 56966c986a5390c8a9aaa0fb71b19bfe2ca7361a | 3,616,634 |
from pathlib import Path
from typing import Union
def load_gan(path: Path, cuda: Union[bool, str] = False) -> ctgan.CTGANSynthesizer :
"""
Loads a ctgan model. Caches the models so that repeated models are
only loaded once
Parameters
----------
path : Path
Path to the file to load the ... | 09c481b3b0c3ecf9651ec555c01fd6022e269710 | 3,616,635 |
def convert_celsius_to_fahrenheit(temperature):
"""
Converts the temperature from degrees Celsius to degrees Fahrenheit.
:param temperature: The value to convert, which must be in degrees Celsius
:type temperature: int | long | decimal.Decimal
:return: The temperature in degrees Fahrenheit to three decimal places... | df6b20631a548ea28a07ece7b0649761329b2fed | 3,616,636 |
def torify(x, size):
"""shift points to canonical torus domain
# Arguments
x: points to be shifted
size: torus size
# Result
points shifted to canonical torus domain
"""
rep_size = np.repeat(np.expand_dims(size,-1), x.shape[-1], -1)
return x - rep_size * np.floor( (x/rep_... | 41278b7907f2d316c11a3578e37a3b8a8c5f9d55 | 3,616,637 |
def build_lst(a, b):
""" function to be folded over a list (with initial value `None`)
produces one of:
1. `None`
2. A single value
3. A list of all values
"""
if type(a) is list:
return a + [b]
elif a:
return [a, b]
else:
return b | 1e47b7bf2987a52b77266d6949af40f1c7df0109 | 3,616,638 |
from typing import List
def get_mean_at_row(dfs: List[pd.DataFrame], row: int, column: str) -> np.double:
"""
Return the mean value of a certain column among the given list of benchmark dataframes in a certain row
:param dfs: list of benchmark dataframes
:param row: index of the row to be selected
... | 872975a8848ec160a8581e3a6505952ab6fe08ee | 3,616,639 |
def foo_1(x):
""" test
>>> foo_1(4)
2.0
"""
return x ** .5 | e8f7d3e9486e8c794a8c5761cea156b770851971 | 3,616,640 |
def add_extra_information(record=None, log_record={}):
"""
Adds extra useful information to logging
"""
if 'request' in log_record:
request = log_record['request']
del log_record['request']
for key, value in META_KEYS.items():
log_record[value] = request.META.get(key... | c0cbb92b154a1ae29cc23aa377d7dee7e03bc337 | 3,616,641 |
def sentence_perplexity(model, sentence):
"""Compute sentence perplexity for trigrams"""
words = sentence.split()
num_words = len(words)
trigrams = ngrams(
words, 3,
pad_left=True,
pad_right=True,
left_pad_symbol=PADDING.left_pad_symbol,
right_pad_symbol=PADDING.r... | 1dcecb7b49e0f5c01e07e4f40b199fb92448322f | 3,616,642 |
def VectorEnv(
env_id: str, n_envs: int = 2, parallel: int = False, env_type: str = "gym",
) -> VecEnv:
"""
Chooses the kind of Vector Environment that is required
:param env_id: Gym environment to be vectorised
:param n_envs: Number of environments
:param parallel: True if we want environments... | 61ddf820e61391e742ec485a5a80070a4c302cfc | 3,616,643 |
def requires_atoms():
"""A function requiring atoms to run"""
def func_decorator(func):
@wraps(func)
def wrapped_function(*args, **kwargs):
molecule = args[0]
assert hasattr(args[0], 'n_atoms')
assert hasattr(args[0], 'atoms')
if molecule.atoms ... | 7358c3dc05b6607582cf68f9306bcfed36c5dbe2 | 3,616,644 |
def acceptsArguments(method, numberOfArguments):
"""
Returns True if the given method will accept the given number of arguments:
method - the method to perform introspection on
numberOfArguments - the numberOfArguments
"""
if 'method' in method.__class__.__name__:
num... | 9cdf528d50fa4c7f99cf8c2674751148d499ae19 | 3,616,645 |
from typing import List
from typing import Union
from typing import Dict
def string_match_classifier_from_yaml(f) -> StringMatchClassifier:
"""Build StringMatchClassifier from a yaml file. Yaml is much easier to edit
in real-world classifiers that often include 50+ lines
Example
-------
The YAML ... | 8bdb1fa2a660749e52b194d27ef28b4e517e909b | 3,616,646 |
def kl_multi_div(params_1, params_2):
"""Kullback-Leibler divergence for multivariate diagonal-covariance gaussians.
The divergence is defined as:
D( (mu_1, sig_1) || (mu_2, sig_2) )
= .5 * ( Spur(sig_2**(-1) * sig_1) + (mu_2 - mu_1).T * sig_2**(-1)
* (mu_2 - mu_1) - k + ln(det(sig_2) ... | 006f4a98d8d084eed74eb359cf4ff07bce8bfbec | 3,616,647 |
from typing import Dict
from typing import List
import copy
def _make_coco_images(df: pd.DataFrame, image_map: Dict) -> List:
"""makes images list for coco"""
df = copy.deepcopy(df)
df.drop_duplicates(subset=["image_id"], keep="first", inplace=True)
df = (
df[["image_id", "image_height", "imag... | c4d78b638df2a15cc2637349301bc82fd4446b4c | 3,616,648 |
from cbflib_adaptbx import uncompress
import binascii
def get_raw_data_from_file(imageset, i):
"""Use cbflib_adaptbx directly to access the raw data array rather than
through the imageset, in order to work for multi-panel detectors and other
situations where the format class modifies the raw array"""
... | 19cbb82d5470f8f473f673cff5ed95cdf7afd6c7 | 3,616,649 |
import copy
def _get_intpol(root, gridfile, freqpath=None):
"""
Extract interpolation settings.
Parameters
----------
root : Element
Element object of the whole xml inputfile
gridfile : str
Name of the inputted gridfile
freqpath : str or None
If fitting frequencies... | 11b879f177e034a9d50a1d17eadc95e680133534 | 3,616,650 |
def is_trusted_idb(*args):
"""
is_trusted_idb() -> bool
Is the database considered as trusted?
"""
return _ida_loader.is_trusted_idb(*args) | eddc1fc63e5634a8b3cfe331487fd9e9c86f9c22 | 3,616,651 |
def _restore_namedtuple_gt_255_fields(typename, fields, values):
"""Creates an namedtuple_gt_255_fields objects along based its __reduce__ description.
The __reduce__ protocol to support pickling requires:
- a callable method that returns the pickled object on restore
- a tuple of its arguments.
T... | 0bb5e0e1d995e7bf9eb77a29c877e085fe1b9eaf | 3,616,652 |
def range_(x: pd.Series, w: int = 0) -> pd.Series:
"""
Range of series over given window
:param x: series: timeseries
:param w: window: number of observations to use (defaults to length of series)
:return: timeseries of range
**Usage**
Returns the range of the series (max - min) over roll... | 311535c9f5d07a64a66bdc118dd2e93bb8f3b3e1 | 3,616,653 |
def normal_ordered_ladder_term(term, coefficient, parity=-1):
"""Return a normal ordered FermionOperator or BosonOperator corresponding
to single term.
Args:
term (list or tuple): A sequence of tuples. The first element of each
tuple is an integer indicating the mode on which a fermion ... | 744ebaa139c514271a2b6788d4333f2eaf7d39eb | 3,616,654 |
def findPams (seq, pam, strand, startDict, endSet):
""" return two values: dict with pos -> strand of PAM and set of end positions of PAMs
Makes sure to return only values with at least GUIDELEN bp left (if strand "+") or to the
right of the match (if strand "-")
If the PAM is cpf1, then this is inverse... | 07330d13acfcabed543bb1dff0759dd960e784a4 | 3,616,655 |
def decode_depthimg(depthimg):
"""
depthimg.shape should be (H,W,C) where H is height, W is width, C is RGB channel i.e. C=3
In each depth png file the top 8 bits of depth are packed into the green channel and the lower 8 bits into blue.
"""
r = depthimg[:, :, 0]
g = depthimg[:, :, 1].astype(np.... | 7cf9431b50e696c652c77698db5b1ccfb1a18ace | 3,616,657 |
def self_att(tensor,
tensor_val=None,
mask=None,
mask_is_length=True,
logit_fn=None,
scale_dot=False,
normalizer=tf.nn.softmax,
tensors=None,
scope=None,
reuse=False):
"""Performs self attention.
Pe... | 13d41ba2b04306de52b6f4d24ff7c08a28c1fd19 | 3,616,658 |
def ogda_train(X, Y, priors=None):
"""Train a omoscedastic GDA classifier.
Parameters
----------
X : ndarray, shape (m, n)
training features.
Y : ndarray, shape (m,)
training labels with values in {0, ..., k - 1}.
priors : ndarray, shape (k,)
Prior probabilities for the ... | e7ab4a73646770272d7105ec32ec5059bfa821ba | 3,616,659 |
def local_align(x, y, score=ScoreParam(10, -5, -7)):
"""Do a local alignment between x and y with the given scoring parameters.
We assume we are MAXIMIZING.
example:
>>>local_align("acgt", "cg", ScoreParam(gap=-5, match=10, mismatch=-5))
"""
# create a zero-filled matrix
A = make_matrix(l... | 0aa837f9e2c0b797ad182fb9f495f64be9bd74ba | 3,616,660 |
def sigma_ss_to_xx(self, e_cm):
"""
Cross section for mediator annihilations into DM.
"""
return sig_ss_to_xx(
e_cm,
self.mx,
self.ms,
self.gsxx,
self.gsff,
self.gsGG,
self.gsFF,
self.lam,
self.width_s,
self.vs,
) | 5f60a26dc7a57821a5a8f3f713a7217f94e8a8a8 | 3,616,661 |
import re
import json
import time
import requests
import traceback
def track(headers, body):
"""
数据追踪，解决1金币问题
:param headers:
:param body:
:return:
"""
try:
url = 'https://mqqapi.reader.qq.com/log/v4/mqq/track'
timestamp = re.compile(r'"dis": (.*?),')
body = json.du... | 71ce3ca86a49877abde9d598114c0b9899a1bea4 | 3,616,662 |
def global_handle_allocate(flags, size):
"""Allocate a specified number of bytes via a global handle.
Parameters:
:param size: The number of bytes to be allocated
.. note::
Can only be used with twain 1.x sources
"""
return _GlobalAlloc(flags, size) | 8642ad1db71d22eae74c3a052f31d8d928856a98 | 3,616,663 |
from typing import Optional
from typing import List
def match_difficulty(our_doc_filter: DocumentFilter, other_doc_filter: DocumentFilter,
mu_lst: Optional[List[str]] = None, sum_lst: Optional[List[str]] = None,
test: Optional[bool] = False) -> pd.DataFrame:
"""
Calc... | d6c1ef3a1dea63dd7011cab06147eade74f64cf6 | 3,616,664 |
def delete_feedback(user_feedback_id):
""" Allows Admin to delete user feedback comments from the db """
# Checks if user is in session
if "user" in session:
# Checks if user is admin
if session["user"] == "admin".lower():
# Removes a specific feedback entry from the db
... | f538c863e30c00f7a3c4b67035ef1eb01c12ca7b | 3,616,665 |
def FormDis(dfr, num=5):
"""
Format and display num number of rows of dataframe dfr,
with float-type values in 2 decimals and yellow color.
"""
ftn = {"z":"{0:,.2f}"}
ftc = {"z":"green"}
for com in dfr.columns:
try:
one = dfr.loc[0,com]
if float(one):
... | 1b1bfdf58a0acdaff0611210a68000e862354ca6 | 3,616,666 |
def hash_transaction(transaction: Transaction) -> str:
"""
Generate a hash for the transaction to make them identifiable.
"""
data = transaction.data
payload = "%s:%s:%s:%s:%s" % (
data["date"],
data["applicant_name"],
data["purpose"],
data["amount"],
data.get... | e64a1f2a2ea1935fe2fd02c4bbdd1a27aa851b07 | 3,616,667 |
import pandas
import numpy
def try_to_datetime(x, frmt=''):
"""Try to convert a string to a date. In case of failure, return nan"""
try:
if frmt == '':
return pandas.to_datetime(x)
else:
return pandas.to_datetime(x, format=frmt)
except:
return numpy.nan | f639a5fdc4170531b3bf660ee0979041a8aab123 | 3,616,668 |
def crs_from_layers(source_layers: t.List[t.SourceLayer]) -> t.List[t.Crs]:
"""Return an intersection of crs supported by each source layer."""
cs = set()
for sl in source_layers:
if not sl.supported_crs:
continue
if not cs:
cs.update(sl.supported_crs)
else:... | c4bd62a84941e04bb7f51724c73229f96b8d18d5 | 3,616,669 |
def test_app():
"""Return a test Application."""
return Application('testing') | 0dd417db575116c7ef2841a68a9ec9e8ad2f6904 | 3,616,671 |
def determine_torsion_symmetry(label, top1, mol_list, torsion_scan):
"""
Check whether a torsion is symmetric.
If a torsion well is "well defined" and not smeared, it could be symmetric.
Check the groups attached to the rotor pivots to determine whether it is indeed symmetric
We don't care about th... | 11026d207cd20d0e79e456a00823fb74e0cbdb82 | 3,616,673 |
def check_holdings(asset_id, address):
"""
Checks the asset balance for the specific address and asset id.
"""
account_info = client.account_info(address)
assets = account_info.get("assets")
if assets:
asset_holding = None
for i in account_info["assets"]:
if i['asset-... | 7cf31751cb63616a104c7222f34be6f59369e881 | 3,616,674 |
import re
def isValidGUID(guid):
""" Verify the GUID generated with uuidgen """
status = False
pattern = "[A-F0-9]{8}-[A-F0-9]{4}-[A-F0-9]{4}-[A-F0-9]{4}-[A-F0-9]{12}"
m = re.search(pattern, guid.upper())
if not m:
tolog("!!WARNING!!2333!! GUID=\'%s\' does not follow pattern \'%s\'" % (g... | 54dfc207945bcb3052da240b43160c5e95ce8efb | 3,616,675 |
from pathlib import Path
def read_probabilties(proba_folder, subset='valid',
model_names=model_names):
"""Reads saved .npy validation and test predicted probabilities from PsychicLearners/data/probabilities"""
proba_folder = Path(proba_folder)
all_probabilities = []
for folder in... | dc0f75eb50295f3bf023a942ee731f9fdae1006e | 3,616,676 |
from typing import Union
from typing import Callable
def filter_bad_ids(
data: DataFrame,
bad_ids: Union[Series, list[str], str],
filter_col: str,
filter_method: Union[str, Callable] = "odo",
):
"""
Filter observation IDs that are flagged as badded, either from an
online Google Sheet or fr... | 1e96e3cdc3ac69ab24c1d6f88ada13dc4bb3682d | 3,616,678 |
def normalized_abl1():
"""Return normalized Gene Descriptor for ABL1."""
params = {
"id": "normalize.gene:ABL1",
"type": "GeneDescriptor",
"gene_id": "hgnc:76",
"label": "ABL1",
"xrefs": {
"ensembl:ENSG00000097007",
"ncbigene:25"
},
... | 72c6393dc47f285be5f20a2dc7a3349b7bba0d65 | 3,616,679 |
def lookup_school_reverse(school_id):
"""
A function to lookup school name from school_id
Args:
school_id as int
Returns:
school (str): the name of the school
Examples:
lookup_school_id_reverse(167)
>>> "Cornell"
"""
school_row = _SCHOOL_ID_LU... | 4aacefbffe689056e91c9afc7c83b700ce2b883c | 3,616,681 |
def flip(x):
"""
flip image(翻轉影像)
"""
x = tf.image.random_flip_left_right(x) # 隨機左右翻轉影像
return x | e864e7277a5ded7717e279f43fddef72a73fb637 | 3,616,682 |
def three_to_one(s):
"""
Three letter code to one letter code.
For example: ALA to A.
"""
i=d3_to_index[s]
return dindex_to_1[i] | 14464de8f7cf04da379aad1492a9f4a0d746e449 | 3,616,683 |
def get_queue_index(name='default'):
"""
Returns the position of Queue for the named queue in QUEUES_LIST
"""
queue_index = None
connection = get_connection(name)
connection_kwargs = connection.connection_pool.connection_kwargs
for i in range(0, 100):
q = get_queue_by_index(i)
... | c8dcc822e67ef886ec45acb866afd60cdc8f4fa5 | 3,616,684 |
def to_hash_str(source, encoding="ascii"): # pragma: no cover -- deprecated & unused
"""deprecated, use to_native_str() instead"""
return to_native_str(source, encoding, param="hash") | df745e66337965501bbc42eef502f2710fd98c97 | 3,616,685 |
def k_pod(data, n_clusters,max_iter=300,tol=0,random_state=0):
""" Compute cluster centers and predict cluster index for sample containing missing data.
Parameters
----------
data: {array-like, sparse matrix} of shape (N, P)
Data to predict clusters for.
n_clusters: int
The number ... | 3962e9f6bf6c3d5eb4cd346fc171ae69a5041cdb | 3,616,686 |
def _get_datemapping(df, events):
"""
return the mapping of human_readable dates to
integer numbers for plotting. Mapping is a dict.
Furthermore return a sorted list of the dates.
"""
dates = sorted(df.human_readable.unique(), key=_date_key_function)
date_mapping = {}
for in... | 2e88a3d01aff568c75205e397e07fe32c65a35a2 | 3,616,687 |
import datasets
def load_rotated_mnist(data_dir, image_size=32, train=True, rotation=0):
"""
Load a MNIST dataset where each image has a rotation.
"""
rotate_image = rotate_transform(rotation)
image_transforms = [
transforms.Resize(image_size),
transforms.CenterCrop(image_size),
... | fb7b39267e7a7df2d5c265a33b5942832ffb1a40 | 3,616,688 |
def slave_delete(request):
"""
接令人删除为同意的召集令请求
"""
# body = json.loads(request.body)
body = request.GET
req = body.get('request_id', '')
try:
Request.objects.filter(
uid__exact=req, request_status__exact=0).delete()
except Request.DoesNotExist:
return HttpResp... | cfee53adfee8db9881fc3546778ce2c7efe60d3e | 3,616,690 |
import collections
def meetup(date):
"""
Displays the meetup taking place on the given date.
"""
meetup = _get_meetup(date)
user_upvotes = []
user_downvotes = []
ideas = meetup.sessionideas
idea_ids = [idea.id for idea in ideas]
vote_results = collections.defaultdict(int)
for v... | 9a8d874f70b3b2249f8bcd8fc120060e2cf48f9e | 3,616,691 |
import math
def is_hilbert_squarefree_number(n):
"""
I define a "Hilbert squarefree" number as a positive integer not divisible
by the square of any Hilbert number, i.e. by a Hilbert square.
Note: the given n need not be a Hilbert number but could be any positive
integer.
"""
ubound = ma... | 28f2339aafd5ef7a319bfb7ff618f9ec9861ad39 | 3,616,692 |
def get_plotting_specs_somato(beamf_type, plot_type):
"""Get all parameters and settings for plotting."""
if plot_type not in ('corr', 'foc', 'ori'):
raise ValueError('Do not know plotting type "%s".' % plot_type)
if beamf_type == 'lcmv':
xmax = 130
if plot_type == 'foc':
... | 7da949136d3042c3fb99f779fc626e1247b98447 | 3,616,693 |
from typing import List
def create_streaming_params(client_params: List[ClientParam]) -> str:
"""Build the C++ parameter list for streaming functions."""
params = _to_parameter_list(client_params)
client_context_param = "::grpc::ClientContext& context"
params = [stub_param()] + [client_context_param] ... | 5d48c3a29c41327152768412a09dd61f6915e953 | 3,616,695 |
def app(request):
"""AioHTTP application with configurable endpoints.
Endpoint names should be passed as positional arguments to `pytest.mark.endpoints` decorator.
"""
marker = request.node.get_closest_marker("endpoints")
if marker:
endpoints = marker.args
else:
endpoints = ("su... | eeb90127e74c89403bd4efb21bbfa62c4ede4673 | 3,616,696 |
def scraperMode():
"""
The operating mode of the scraper.
It can either send notification if text is found on the page, or waiting and keep refreshing
until the text goes away from the page.
:return: the mode
"""
print("In which mode should the scraper behave?\nInsert the... | f60a2fdb73ed92c970c764d8327b11f40edfbd45 | 3,616,697 |
import numpy
def checkCoordinateList(coordinates, varname="coordinates"):
"""
Check that the given coordinates is a valid Nx3 sequence of numbers.
:param coordinates: The object to test. To pass the test this must be
an Nx3 array of floating point numbers.
:param varname: The ... | 7048c5a7fa4231ce8849d0a67ee07e10ea80e6ad | 3,616,698 |
import re
def validate_enum(temp_enum):
"""
Strips spaces & converts values that could be interpreted in yaml as
nonstring, to double quotation string
"""
enum = stripper(temp_enum)
# enum = enum.replace(':', '-')
if enum != 'open' and '/' not in enum:
if isinstance(enum, str) an... | a1ffbb3713a1e4ae025d01ab38e12beb28c8499f | 3,616,699 |
def encode_circuits(circuits, model):
"""
Encode a list of circuits generated from a given model. Each circuit will be encoded using 4 integers:
1. The index of the gate sequence before the germ, i.e. preparation fiducials
2. The index of the gate sequence after the germ, i.e. measurement fiduci... | 90e4c10a31968b93177e100a9f225833658b3544 | 3,616,700 |
def domain_match(A, B):
"""Return True if domain A domain-matches domain B, according to RFC 2965.
A and B may be host domain names or IP addresses.
RFC 2965, section 1:
Host names can be specified either as an IP address or a HDN string.
Sometimes we compare one host name with another. (Such co... | 4f930b92f3b869d8ac4f499ef817f4bb2ed44360 | 3,616,701 |
def _build_timetables(schedules, events=None, partner=None):
"""
Dati un elenco di schedule ids/eventi e partner program ritorna una lista
di TimeTable relative ai dati passati.
_build_timetables([1,2])
Restituisce due TimeTable relative agli schedule 1 e 2 (gli eventi
vengono recupera... | 31b431b224273649ce63e9f9419e2d28043bf24d | 3,616,702 |
from typing import Optional
from typing import Iterator
def get_tags(owner: str, repo: str, n: int = 100, filter: Optional[str] = None) -> Iterator[str]:
"""Get the tags on a repository in descending commit tag date order."""
ref_query = ""
if filter is not None:
ref_query = f', query: "{filter}"... | b5e5b79a03e5bf8dea13fade121a6b81bd762512 | 3,616,704 |
def Function(from_types, to_type):
"""A binary type constructor which builds function types"""
return TypeOperator('fun', list(from_types) + [to_type]) | 6f16c0f885c16186592ac1661adae29f13bfd77a | 3,616,705 |
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