content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import yaml
import re
def yml_remove_releaseNote_record(file_path, current_server_version):
"""
locate and remove release notes from a yaml file.
:param file_path: path of the file
:param current_server_version: current server GA version
:return: True if file was changed, otherwise False.
"""
... | 48a6f68642a094dd07a0daa13a78d11991a2aa5c | 31,336 |
from typing import Union
def calculate_z_score(
data: Union[MultimodalData, UnimodalData, anndata.AnnData],
n_bins: int = 50,
) -> np.array:
"""Calculate the standardized z scores of the count matrix.
Parameters
-----------
data: ``MultimodalData``, ``UnimodalData``, or ``anndata.AnnData`` ob... | df510bea5d475690ee234c1f92c6a9cb5bfab308 | 31,337 |
def encode(*args, **kwargs):
"""
A helper function to encode an element.
@param args: The python data to be encoded.
@kwarg encoding: AMF encoding type. One of L{ENCODING_TYPES}.
@return: A L{util.BufferedByteStream} object that contains the data.
"""
encoding = kwargs.pop('encoding', DEFAU... | 41fd8c725643826a9e74dfdd59607f5bc6eda5c3 | 31,338 |
from typing import Tuple
def fenergy_symmetric_bar(
work_ab: ArrayLike,
work_bc: ArrayLike,
uncertainty_method: str = "BAR",
) -> Tuple[float, float]:
"""BAR for symmetric periodic protocols.
Args:
work_ab: Measurements of work from first half of protocol.
work_bc: Measurements of... | 569f694cd9a2ea58ef929230e5eb4fc399229e57 | 31,339 |
def mod_arr_fit(ktp_dct, mess_path,
fit_type='single', fit_method='dsarrfit',
t_ref=1.0, a_conv_factor=1.0, inp_param_dct=None):
"""
Routine for a single reaction:
(1) Grab high-pressure and pressure-dependent rate constants
from a MESS output file
(2)... | aacb366b2b826b8ffaaae620ee531ce7cb7e0339 | 31,341 |
from typing import Union
from typing import Sequence
from typing import List
def _choose_image_ids(selected: Union[None, int, Sequence[int]],
available: List[int]) -> List[int]:
"""Choose which image ids to load from disk."""
# Load all.
if selected is None:
return available
# Load... | 2f12c0f840ec4daede35ac3f65e745ad8681c19a | 31,342 |
import mite as m2
import M2kinter as m2
def _open_file(name, mode):
"""
Opens a file in the specified mode. If the mite or M2kinter module
is available the path given is not absolute, the writepath or
datapath (depending on the specified mode) is searched first.
"""
if not name:
raise ... | 4aee4a2a54e5f9bd1ba72810b72deb50d0f69d54 | 31,343 |
def canonical_message_builder(content, fmt):
"""Builds the canonical message to be verified.
Sorts the fields as a requirement from AWS
Args:
content (dict): Parsed body of the response
fmt (list): List of the fields that need to go into the message
Returns (str):
canonical mes... | 41a5e61cea00348c43675e373acb3cdcb311a762 | 31,344 |
import random
def get_random_image(shape):
"""
Expects something like shape=(480,640,3)
:param shape: tuple of shape for numpy array,
for example from my_array.shape
:type shape: tuple of ints
:return random_image:
:rtype: np.ndarray
"""
if random.random() < 0.5:
r... | 6ac0a627ce6f125b269584cb0694c6b26bb5e23d | 31,345 |
import torch
def evaluate(model, val_loader, device):
"""
model: CNN networks
val_loader: a Dataloader object with validation data
device: evaluate on cpu or gpu device
return classification accuracy of the model on val dataset
"""
# evaluate the model
model.eval()
# context-manage... | f5b738117a2c73d666718acaeff83f8856294db9 | 31,346 |
def estimateInharmonicity(inputFile = '../../sounds/piano.wav', t1=0.1, t2=0.5, window='hamming',
M=2048, N=2048, H=128, f0et=5.0, t=-90, minf0=130, maxf0=180, nH = 10):
"""
Function to estimate the extent of inharmonicity present in a sound
Input:
inputFile (string): wa... | f3d8d78b3e565b69e72f435b5afdef7a6f6a28fd | 31,347 |
import attr
def _get_default_secret(var, default):
"""
Get default or raise MissingSecretError.
"""
if isinstance(default, attr.Factory):
return attr.NOTHING
elif isinstance(default, Raise):
raise MissingSecretError(var)
return default | debece74ea410589a0330dac9aaf2e57796c2001 | 31,348 |
import copy
def merge_similar_bounds(json_data: dict, file_names: list, bounds_list: list) -> dict:
"""Finds keys in a dictionary where there bounds are similar and merges them.
Parameters
----------
json_data : dict
Dictionary data from which the data informations were extracted from.
fi... | 314d6501e887d7a52d2aed054583188be992c1ed | 31,349 |
import base64
def is_base64(s):
"""Return True if input string is base64, false otherwise."""
s = s.strip("'\"")
try:
if isinstance(s, str):
sb_bytes = bytes(s, 'ascii')
elif isinstance(s, bytes):
sb_bytes = s
else:
raise ValueError("Argument mus... | 6ce7bc4ddc79d5d50acce35f7995033ffb7d364a | 31,350 |
def get_coco(opt, coco_path):
"""Get coco dataset."""
train_dataset = CenterMultiPoseDataset(opt, split = 'train') # custom dataset
val_dataset = CenterMultiPoseDataset(opt, split = 'val') # custom dataset
opt.val_interval = 10
return train_dataset, val_dataset | c78e07bff16053ce1c4c9a8246750f938159f3b6 | 31,351 |
def _get_output_columns(nodes, context):
"""Get the output columns for a list of SqlNodes.
Args:
nodes: List[SqlNode], the nodes to get output columns from.
context: CompilationContext, global compilation state and metadata.
Returns:
List[Column], list of SqlAlchemy Columns to outp... | 9c8c45311ca03892eaf4e82bbb592af6137eb0a6 | 31,352 |
from typing import final
def notif(message):
"""
docstring
"""
#message= mess.text
#print(message)
#print(type(message))
query= str(message).split(',')
#print(query)
if(len(query)==2):
#print(eval(query[1]))
list_str= final.ajio_care.find_stock(eval(query[0]),eval(q... | 5791165d8ac9fe582090de2f6a4831f2da3039ee | 31,353 |
def float32(x):
"""Returns a 32-bit floating point representation of the input.
Only defined for basic scalar types."""
return np.float32(x) | a63d595a1d9a1949183a8303b0258779082278c7 | 31,355 |
from pathlib import Path
def collect_test_names():
""" "
Finds all test names in `TEST_DATA_DIR` which have are valid, i.e.
which have both a C file and associated gcc AST json
"""
test_data_dir_path = Path(TEST_DATA_DIR)
c_files = test_data_dir_path.glob("*.c")
ast_files = test_data_dir_p... | c34609264f460c66d8ea85a456901e0f1daca84f | 31,356 |
def read_from_file(filename):
"""Read from a file located at `filename` and return the corresponding graph object."""
file = open(filename, "r")
lines = file.readlines()
file.close()
# Check if it is a graph or digraph
graph_or_digraph_str = lines[0].strip() if len(lines) > 0 else None
if ... | 86879facbef971541fabe95ef9430480931ef986 | 31,357 |
from quaternion.calculus import spline_definite_integral as sdi
def inner_product(t, abar, b, axis=None, apply_conjugate=False):
"""Perform a time-domain complex inner product between two waveforms <a, b>.
This is implemented using spline interpolation, calling
quaternion.calculus.spline_definite_integra... | c675ee377a73e0858ad078bce47b5e41120b8d0b | 31,358 |
from typing import List
def build_datamodel(good_pbks: List[str], is_supply: bool) -> DataModel:
"""
Build a data model for supply and demand (i.e. for offered or requested goods).
:param good_pbks: the list of good public keys
:param is_supply: Boolean indicating whether it is a supply or demand dat... | 35b450039e6401a80fc03c61e771eb433bfab693 | 31,359 |
def tryReduceOr(sig, val):
"""
Return sig and val reduced by | operator or None
if it is not possible to statically reduce expression
"""
m = sig._dtype.all_mask()
if not val.vldMask:
return val
if val._isFullVld():
v = val.val
if v == m:
return val
... | 4be6cb3ebf3792859745ed474151e0b748f4d479 | 31,360 |
def get_mod_from_id(mod_id, mod_list):
"""
Returns the mod for given mod or None if it isn't found.
Parameters
----------
mod_id : str
The mod identifier to look for
mod_list : list[DatRecord]
List of mods to search in (or dat file)
Returns
-------
DatRecord or Non... | 1fac309e4dfadea6da34946eb695f77cbbd61f92 | 31,361 |
def resize(image):
"""
Resize the image to the input shape used by the network model
"""
return cv2.resize(image, (IMAGE_WIDTH, IMAGE_HEIGHT), cv2.INTER_AREA) | 315b43be9fc33740466fb6671119fbc97a2c853a | 31,362 |
def exp_f(name):
""""Similar to E but trains to full 3001 epochs"""
print("e82 but with seq length 2000 and 5 appliances and learning rate 0.01 and train and validation on all 5 houses")
source = RealApplianceSource(
filename='/data/dk3810/ukdale.h5',
appliances=[
['fridge freeze... | fceb234feb9848e6a2618e4f5433345265d1b839 | 31,363 |
def indices_2_one_hot(indices, n):
"""
Converts a list of indices into one hot codification
:param indices: list of indices
:param n: integer. Size of the vocabulary
:return: numpy array with shape (len(indices), n)
"""
one_hot = np.zeros((len(indices), n), dtype=np.int8)
for i in range... | c74864bf23cbd56dbc9de12f250570b9df9cdf8c | 31,364 |
from typing import Set
def extract_tables(query: str) -> Set[Table]:
"""
Helper function to extract tables referenced in a query.
"""
return ParsedQuery(query).tables | cb48448b09f9aac90a85ca2bd7011f32fcbe6e6f | 31,365 |
def master_operation(matrix):
"""
Split the initial matrix into tasks and distribute them among slave operations
"""
workers = MPI.COMM_WORLD.Get_size()
accumulator = []
task_queue = []
if not matrix[0][0]:
task_queue.append([(0, 0)])
while True:
sent_workers = []
... | c936abd299cd0181138f4f4c87a5cf306be06c7a | 31,366 |
def _weight_mean_color(graph, src, dst, n):
"""Callback to handle merging nodes by recomputing mean color.
The method expects that the mean color of `dst` is already computed.
Parameters
----------
graph : RAG
The graph under consideration.
src, dst : int
The vertices in `graph... | 13fe474363578f704dfe8e16be725628a6e3ca5f | 31,367 |
def predict(model, pTestSet, pModelParams, pNoConvertBack):
"""
Function to predict test set
Attributes:
model -- model to use
testSet -- testSet to be predicted
conversion -- conversion function used when training the model
"""
#copy the test set, before invalidated rows and... | 4d6aa09bc1223732d73ea7f37aed2ccc28e879b3 | 31,368 |
def poisson_log_likelihood(x, log_rate):
"""Compute the log likelihood under Poisson distribution.
log poisson(k, r) = log(r^k * e^(-r) / k!)
= k log(r) - r - log k!
log poisson(k, r=exp(l)) = k * l - exp(l) - lgamma(k + 1)
Args:
x: binned spike count data.
log_rate: The (log... | dc797090efceb4266a90e89125fb5a9acc5b2da7 | 31,369 |
import math
def distance(point1, point2):
""" Return the distance between two points."""
dx = point1[0] - point2[0]
dy = point1[1] - point2[1]
return math.sqrt(dx * dx + dy * dy) | 7605d98e33989de91c49a5acf702609272cf5a68 | 31,370 |
import math
def order_of_magnitude(value):
"""
Returns the order of magnitude of the most significant digit of the
specified number. A value of zero signifies the ones digit, as would be
the case in [Number]*10^[Order].
:param value:
:return:
"""
x = abs(float(value))
offset = 0 ... | 53a4b1be76199864fee69d4333049fb1f2371e46 | 31,372 |
def compute_discounted_R(R, discount_rate=1):
"""Returns discounted rewards
Args:
R (1-D array): a list of `reward` at each time step
discount_rate (float): Will discount the future value by this rate
Returns:
discounted_r (1-D array): same shape as input `R`
but the valu... | 50a18277e749faa73c725217824091a71d00f991 | 31,373 |
def setup_dom_for_char(character, create_dompc=True, create_assets=True,
region=None, srank=None, family=None, liege_domain=None,
create_domain=True, create_liege=True, create_vassals=True,
num_vassals=2):
"""
Creates both a PlayerOrNpc instan... | 3c806c560e0691440bc7d7399467eecb563745f0 | 31,374 |
def cumulative_sum(t):
"""
Return a new list where the ith element is the sum of all elements up to that
position in the list. Ex: [1, 2, 3] returns [1, 3, 6]
"""
res = [t[0]]
for i in range(1, len(t)):
res.append(res[-1] + t[i])
return res | 14b2ef722f72e239d05737a7bb7b3a6b3e15305f | 31,375 |
from typing import Tuple
def update_documents_in_collection(resource) -> Tuple[Response, int]:
"""Endpoint for updating multiple documents."""
try:
collection_name = services.check_resource_name(resource)
request_args = request.args.copy()
filters = ["_projection", "_sort", "_limit",... | 743b7bf3c3d2be765da181b5fbceef3309f91b48 | 31,377 |
def generate_prior_data(Pi, a_prior, b_prior):
"""Return column data sources needed to generate prior distribution."""
# Prior probability distribution
n = 1000
x = np.linspace(0, 1, n)
dist = beta(a_prior, b_prior)
p = dist.pdf(x)
# Arrays for the area under the curve patch
xs = np.hs... | 1bce66203f0b3ad6ab74fb346a81ec15ff2b7d63 | 31,378 |
def InteractionFingerprintAtomic(ligand, protein, strict=True):
"""Interaction fingerprint accomplished by converting the molecular
interaction of ligand-protein into bit array according to
the residue of choice and the interaction. For every residue
(One row = one residue) there are eight bits which re... | ecdfc34e5c6cb5c5ca3fcf008629b1d3face158c | 31,379 |
from typing import Union
def add_subject_conditions(
data: pd.DataFrame, condition_list: Union[SubjectConditionDict, SubjectConditionDataFrame]
) -> pd.DataFrame:
"""Add subject conditions to dataframe.
This function expects a dataframe with data from multiple subjects and information on which subject
... | 7475af9b13685604678b4d566e9b2daa4f6f82ef | 31,380 |
def chinese_remainder(n1: int, r1: int, n2: int, r2: int) -> int:
"""
>>> chinese_remainder(5,1,7,3)
31
penjelasan : 31 adalah nomor yang paling kecil
ketika dibagi dengan 5 kita dapat hasil bagi 1
ketika dibagi dengan 7 kita dapat hasil bagi 3
"""
(x, y) = extended_euclid(n1, n2)
m... | e98882790c9c4bdd1e23f1d9b49d7a30ddaf7e81 | 31,381 |
from typing import Iterable
def query_factorize_industry_df(factorize_arr, market=None):
"""
使用match_industries_factorize可以查询到行业所对应的factorize序列，
使用factorize序列即组成需要查询的行业组合，返回行业组合pd.DataFrame对象
eg: 从美股所有行业中找到中国企业的行业
input：ABuIndustries.match_industries_factorize('中国', market=EMarketTargetType.E_... | 7060336e59b54d87f061a6163367b22c056edb6a | 31,383 |
import yaml
def rbac_assign_roles(email, roles, tenant=None):
"""assign a list of roles to email"""
tstr = " -tenant=%s " % (tenant) if tenant else ""
roles = ",".join(roles)
rc = run_command("%s user-role -op assign -user-email %s -roles %s %s" % (
g_araalictl_path, email, roles,... | 27bc4835052fd3e6c5e2660ab47c12b49ff426ef | 31,384 |
def haversine_np(lon1, lat1, lon2, lat2):
"""
Calculate the great circle distance between two points
on the earth (specified in decimal degrees)
Reference:
https://stackoverflow.com/a/29546836/7657658
https://gist.github.com/mazzma12/6dbcc71ab3b579c08d66a968ff509901
"""
lon1, la... | ace51c2e9e93a42270f669d4b8d48ce87ff660d6 | 31,385 |
import re
def extract_current_step(current_status_string):
""" Attempts to extract the current step numeric identifier from the given status string. Returns the step
number or None if none.
"""
# Older format: `Step 12 :`
# Newer format: `Step 4/13 :`
step_increment = re.search(r"Step ([0-9]+)... | 8bbee5b13140394e3e04021eccd43d2b4c3b4c14 | 31,387 |
import warnings
def unique1d(ar1, return_index=False, return_inverse=False):
"""
Find the unique elements of an array.
Parameters
----------
ar1 : array_like
This array will be flattened if it is not already 1-D.
return_index : bool, optional
If True, also return the indices a... | 8ac57d97079d60215dc96fd33d1f176129445662 | 31,388 |
def login_required(func):
"""
Decorator check required login and active user
:param func:
:return:
"""
@wraps(func)
def decorated_view(*args, **kwargs):
if current_app.login_manager._login_disabled:
return func(*args, **kwargs)
elif not current_user.is... | 894d162a8fd50c0e4fba810c0f575865994ba00e | 31,389 |
def prepare_statement(template, values):
"""Correctly escape things and keep as unicode.
pyscopg2 has a default encoding of `latin-1`: https://github.com/psycopg/psycopg2/issues/331"""
new_values = []
for value in values:
adapted = adapt(value)
adapted.encoding = 'utf-8'
new_val... | 68af78444da86cdf73f74f84f5c7f0743b591e5c | 31,390 |
def addgroup(request):
"""Add group form."""
return render(
request,
'addgroup.htm',
context={},
) | dce8da2641b35bbdb1062463e9bc954b70c9d1d2 | 31,391 |
def cached_function_method_signature(ctx: MethodSigContext) -> CallableType:
"""Fixes the `_CachedFunction.__call__` signature to be correct.
It already has *almost* the correct signature, except:
1. the `self` argument needs to be marked as "bound";
2. any `cache_context` argument should be r... | 7b1b9893afe4f1e723eed7894b0adf9221c24d1d | 31,392 |
def load_valid_data_full():
"""
load validation data from disk
"""
hdf5_file_valid = h5py.File(HDF5_PATH_VALID, "r")
data_num_valid = hdf5_file_valid["valid_img"].shape[0]
images_valid = np.array(hdf5_file_valid["valid_img"][:]) # your test set features
labels_valid = np.array(hdf5_file_val... | bc586424e6fc2669107c7548220461a089bbad16 | 31,393 |
import json
def import_slab_structures(filename):
"""Read 2D water structures from file and return a dictionary of it.
Parameters
----------
filename : str
Filename of the file containing the bulk structures
Returns
-------
filedict : dict
Dictionary of the structures
... | d6ca4d5c7b5c264d55cd26f638dfb4ec34bce259 | 31,394 |
import re
def handle_email(text):
"""Summary
Args:
text (TYPE): Description
Returns:
TYPE: Description
"""
return re.sub(r'(\w+@\w+)', Replacement.EMAIL.value, text) | c96e3f5791394d5200c309e5ea1a285aae85a3df | 31,395 |
def LowerCustomDatatypes():
"""Lower custom datatypes.
See tvm::datatypes::Registry for more information on adding custom datatypes.
Returns
-------
fpass : tvm.ir.transform.Pass
The result pass
"""
return _ffi_api.LowerCustomDatatypes() | cb55a578a3daabf6e95a64bc95ba75643d2f14bd | 31,396 |
import typing
def apply_if_or_value(
maybe_value: typing.Optional[typing.Any],
operation: typing.Callable[[typing.Any], typing.Any],
fallback_value: typing.Any,
) -> typing.Any:
"""Attempt to apply operation to maybe_value, returning fallback_value if
maybe_value is None.
Almost a convenience... | fe67fbc1b71ed22fa3da516df82a72cb64e30f33 | 31,397 |
import torch
def make_pyg_dataset_from_dataframe(
df: pd.DataFrame, list_n: list, list_e: list, paired=False, mode: str = "all"
) -> list:
"""Take a Dataframe, a list of strings of node features, a list of strings of edge features
and return a List of PyG Data objects.
Parameters
----------
d... | 267787c7b527a92421fa7e83ca75bf2a8083ec2a | 31,398 |
def ucfirst(string: str):
"""Return the string with the first character in upper case."""
return _change_first_case(string, upper=True) | 4f52744dc62f4db7437451de3120691bbb184298 | 31,399 |
def gumbel_softmax(log_pi, tau=0.1, axis=1):
"""Gumbel-Softmax sampling function.
This function draws samples :math:`y_i` from Gumbel-Softmax distribution,
.. math::
y_i = {\\exp((g_i + \\log\\pi_i)/\\tau)
\\over \\sum_{j}\\exp((g_j + \\log\\pi_j)/\\tau)},
where :math:`\\tau` is a tem... | 91751a5bd8069c71de5dbe9f2cbbc7757daff140 | 31,400 |
def has_active_lease(storage_server, storage_index, now):
"""
:param allmydata.storage.server.StorageServer storage_server: A storage
server to use to look up lease information.
:param bytes storage_index: A storage index to use to look up lease
information.
:param float now: The curre... | 544b17489bc766a15bf2eca5cddab55c1bf473dd | 31,401 |
def MXfunc(A, At, d1, p1):
"""
Compute P^{-1}X (PCG)
y = P^{-1}*x
"""
def matvec(x):
return p1 * x
N = p1.shape[0]
return LinearOperator((N, N), matvec=matvec) | c2c1d6361756779f9318a9356251c8ba1a610057 | 31,403 |
from ._filter import filter_
from typing import Callable
def filter(predicate: Predicate[_T]) -> Callable[[Observable[_T]], Observable[_T]]:
"""Filters the elements of an observable sequence based on a
predicate.
.. marble::
:alt: filter
----1---2---3---4---|
[ filter(i: i>2) ... | b56f4ed6e770d9b623362cca92a791d7f1ef5fa7 | 31,404 |
def scb_to_unit(scb):
"""Convert codes used by Statistics Sweden to units used by the NAD GIS files."""
scbform = 'SE/' + '{:0<9}'.format(scb)
if scbform in g_units.index:
return g_units.loc[scbform, 'G_unit']
else:
return 0 | 1c878492bb0bb4e8c7b7874097c86fa8bbc93329 | 31,405 |
def img_to_square(im_pic):
""" 把图片处理成正方形
:param im_pic:
:return:
"""
w, h = im_pic.size
if w >= h:
w_start = (w - h) * 0.618
box = (w_start, 0, w_start + h, h)
region = im_pic.crop(box)
else:
h_start = (h - w) * 0.618
box = (0, h_start, w, h_start + w)... | ae672ea715cb982272eddaff0417d4f64926894c | 31,407 |
from typing import List
def load_sentence(
filename: str,
with_symbol: bool=True
) -> List[str]:
"""コーパスをロードする。"""
if with_symbol:
tokens = [
list(sent.split()) + [config.END_SYMBOL]
for sent in (_.strip() for _ in open(filename))
]
else:
tokens = [
... | 3f494b740a4ed157f163329de8cc0568e5541cdc | 31,408 |
def to_str(bytes_or_str):
"""
The first function takes a bytes or str instance and always returns
a str.
"""
if isinstance(bytes_or_str, bytes):
value = bytes_or_str.decode('utf-8')
else:
value = bytes_or_str
return value | 4a73559039501764a00e697c092d20426949058d | 31,409 |
def configure_ampliseq(request):
"""View for ampliseq.com importing stuff"""
ctx = get_ctx_ampliseq(request)
return render_to_response(
"rundb/configure/ampliseq.html", ctx, context_instance=RequestContext(request)
) | 90cdd14de158efc79b5cad11feaa115878469866 | 31,410 |
import struct
def _copy(s):
"""Creates a new set from another set.
Args:
s: A set, as returned by `sets.make()`.
Returns:
A new set containing the same elements as `s`.
"""
return struct(_values = dict(s._values)) | b505af5037d0aa889aa8ed707eaf69d572e54f84 | 31,411 |
import random
def particle_movement_x(time):
"""
Generates a random movement in the X label
Parameter:
time (int): Time step
Return:
x (int): X position
"""
x = 0
directions = [1, -1]
for i in range(time):
x = x + random.choice(directions)
return x | 0dff68080dbfd56997cffb1e469390a1964a326f | 31,412 |
def find_match_characters(string, pattern):
"""Find match match pattern string.
Args:
params: string
pattern
Returns:
Raises:
"""
matched = []
last_index = 0
if not string or not pattern:
return matched
if string[0] != pattern[0]:
return matc... | 6d3bc3844c20584038e41c22eeead7325031b647 | 31,413 |
from typing import Union
def columnwise_normalize(X: np.ndarray) -> Union[None, np.ndarray]:
"""normalize per column"""
if X is None:
return None
return (X - np.mean(X, 0)) / np.std(X, 0) | 24b5995a5b36738e1c9eecf427fdb4ed83d43145 | 31,415 |
def line_intersect(a1, da, b1, db):
"""
compute intersection of infinetly long lines
"""
dba = np.array(a1) - np.array(b1)
da_perpendicular = perp(da)
num = np.dot(da_perpendicular, dba)
denom = np.dot(da_perpendicular, db)
dist_b = (num / denom)
return dist_b*db + b1 | 5be8211d3f31d7984820349dfbbb1e05592287a4 | 31,417 |
def sequence_(t : r(e(a))) -> e(Unit):
"""
sequence_ :: (Foldable r, Monad e) => r (e a) -> e ()
Evaluate each monadic action in the structure from left to right, and
ignore the results. For a version that doesn't ignore the results see
sequence.
As of base 4.8.0.0, sequence_ is just sequenceA... | 85c36cc767f60eaccd8d91cdc4d14ca2370069f7 | 31,418 |
import re
def param_validated(param, val):
"""Return True if matches validation pattern, False otherwise"""
if param in validation_dict:
pattern = validation_dict[param]
if re.match(rf'{pattern}', val) is None:
log.error("Validation failed for param='%s', "
"v... | 4359b20437e8cfd21b82b5952cc1c9026e6dca13 | 31,419 |
def remove_keys_from_array(array, keys):
"""
This function...
:param array:
:param keys:
:return:
"""
for key in keys:
array.remove(key)
return array | 3143b8e42eb1e1b2f5818a254bcec3631c30f5ea | 31,420 |
def create_tree_data(codepage, options, target_node, pos):
"""Create structure needed for Dijit Tree widget """
tree_nodes = []
for opt in options:
code = opt['code']
cp = codepage + code
add_tree_node(tree_nodes, cp, code+"-"+opt['label'], cp)
tree_data = {
... | fededfc4bc3e39860221783459d324a15f16d081 | 31,421 |
def detect_octavia():
"""
Determine whether the underlying OpenStack is using Octavia or not.
Returns True if Octavia is found in the region, and False otherwise.
"""
try:
creds = _load_creds()
region = creds['region']
for catalog in _openstack('catalog', 'list'):
... | 265e01730cfc2b7e1870c0364ddb4cd5d7c4b336 | 31,422 |
def add_cache_control_header(response):
"""Disable caching for non-static endpoints
"""
if "Cache-Control" not in response.headers:
response.headers["Cache-Control"] = "no-cache, no-store, must-revalidate"
return response | 06f3f4a7259076be535b4ea0ca719a13e9e665a0 | 31,423 |
from typing import List
def clean_new_import_aliases(
import_aliases: List[ImportAlias],
) -> List[ImportAlias]:
"""Clean up a list of import aliases."""
# Sort them
cleaned_import_aliases = sorted(import_aliases, key=lambda n: n.evaluated_name)
# Remove any trailing commas
last_name = cleaned... | 5f0b25798f353c999d325125e80c9ccb67b5afec | 31,424 |
def _format_td(timedelt):
"""Format a timedelta object as hh:mm:ss"""
if timedelt is None:
return ''
s = int(round(timedelt.total_seconds()))
hours = s // 3600
minutes = (s % 3600) // 60
seconds = (s % 60)
return '{:02d}:{:02d}:{:02d}'.format(hours, minutes, seconds) | 071f25c3c8cfc75cacf2fedc7002527897362654 | 31,425 |
def add_quad_reaction_node(graph, rxn):
"""
Adds a "Quad Reaction Node" (QRN) group of nodes to a graph, and connects
them to the correct compound nodes.
The QRN consists of two nodes constituting the intended forward direction
of the reaction and two nodes constituting the reverse direction. Each ... | 360e7c4e74ed58da9b85548c4d217e3d1f40150b | 31,426 |
def matrixFilter(np_image_2D, np_mask):
"""
Processing filtering with given matrix
Keyword argument:
np_image_2D -- two dimensional image(grayscale or single color channel)
np_mask -- mask matrix as numpy array
Return:
np_image_fil -- image as numpy 2D array, after specified filtering
... | 422de6c4c539ceb154827d511127f1b120519a2a | 31,428 |
def batch_split_axis(batch, n_split):
"""Reshapes batch to have first axes size equal n_split."""
x, y = batch
n = x.shape[0]
n_new = n / n_split
assert n_new == int(n_new), (
"First axis cannot be split: batch dimension was {} when "
"n_split was {}.".format(x.shape[0], n_split))
n_new = int(n_... | 0f413e40961b15b64bf118b2daa012e853dbc294 | 31,429 |
def right_align(value, length):
"""
:param value: string to right align
:param length: the number of characters to output (spaces added to left)
:return:
"""
if length <= 0:
return u""
value = text(value)
if len(value) < length:
return (" " * (length - len(value))) + va... | de8c42734b094514ebd45c2cb5517da806ec74b8 | 31,430 |
import yaml
from pathlib import Path
def test_disable_functions_as_notebooks(backup_spec_with_functions):
"""
Tests a typical workflow with a pieline where some tasks are functions
"""
with open('pipeline.yaml') as f:
spec = yaml.safe_load(f)
spec['meta']['jupyter_functions_as_notebooks']... | f5e5c8cc687a64d4c7593ef571e181d6cf4d27ce | 31,431 |
def generate_users_data(users):
"""
Generate users' rows (assuming the user's password is the defualt one)
:param users:
:return:
"""
headers = ['שם משתמש', 'סיסמה']
rows = [[user.username, DEFAULT_TEAM_USER_PASSWORD] for user in users]
rows.insert(0, headers)
return rows | c6d9ef03b3b28c31f59627be574c4d20328b5d82 | 31,433 |
def ListToMatrix(lv):
""" Convert a list of 3 or 4 ``c4d.Vector`` to ``c4d.Matrix``. """
if not isinstance(lv, list):
raise TypeError("E: expected list of vectors, got %r" % type(lv))
m = len(lv)
if not isinstance(lv[0], c4d.Vector):
raise TypeError("E: expected list elements of type c4... | b60e1f62d250ce1f7c8ef2772755c3a3ce878395 | 31,434 |
def loadEpithelium(name):
"""Returns an epithelium from a CSV file with the given name.
Precondition: name exists and it's in CSV format"""
assert type(name) == str, "name isn't a string"
recs = []
text = open(name)
i = 0
for line in text:
if i > 0:
recs.append(loadRecept... | 01e0c613faa71dbc77be650c3eba1f5006966f9e | 31,435 |
def focal_attention(query, context, use_sigmoid=False, scope=None):
"""Focal attention layer.
Args:
query : [N, dim1]
context: [N, num_channel, T, dim2]
use_sigmoid: use sigmoid instead of softmax
scope: variable scope
Returns:
Tensor
"""
with tf.variable_scope(scope or "attention", reus... | 27f480b8911b3ff1a4367af6b7d5b9a549d24653 | 31,436 |
def format_float(x):
""" Pretty formatting for floats
"""
if pd.isnull(x):
return " ."
else:
return "{0:10.2f}".format(x) | 9f3cdc0ab41bc69807d178e1c4a56abec0ac6fab | 31,437 |
def random_points_and_attrs(count, srs_id):
"""
Generate Random Points and attrs (Use some UTM Zone)
"""
points = generate_utm_points(count, srs_id)
rows = []
for p in points:
rand_str = ''.join(choice(ascii_uppercase + digits) for _ in range(10))
rand_bool = bool(randint(0, 1))
... | 1dcdbb376f91d75c33baf40275a047393bf13fd5 | 31,438 |
from typing import Union
from typing import List
def trimap(adata, **kwargs) -> Union[Axes, List[Axes], None]:
"""\
Scatter plot in TriMap basis.
Parameters
----------
{adata_color_etc}
{edges_arrows}
{scatter_bulk}
{show_save_ax}
Returns
-------
If `show==False` a :class... | e3294c689e9081813c6e1defecdf20918dc02b8b | 31,439 |
import collections
def quantile(arg, quantile, interpolation='linear'):
"""
Return value at the given quantile, a la numpy.percentile.
Parameters
----------
quantile : float/int or array-like
0 <= quantile <= 1, the quantile(s) to compute
interpolation : {'linear', 'lower', 'higher', ... | 42e53b43d7ea580616d82fea4bdc08260de3b661 | 31,440 |
def random_new(algo=RNG_CMWC):
"""Return a new Random instance. Using ``algo``.
Args:
algo (int): The random number algorithm to use.
Returns:
Random: A new Random instance using the given algorithm.
"""
return tcod.random.Random(algo) | f6eef62d3eb483dbcb85d420262cf411d6934790 | 31,441 |
def get_kth_value(unsorted, k, axis=-1):
"""
Args:
unsorted: numpy.ndarray of any dimensionality.
k: int
Returns:
kth values along the designated axis.
"""
indices = np.argpartition(unsorted, k, axis=axis)[..., :k]
k_smallests = np.take_along_axis(unsorted, indices, axis=... | ab787a89c04d390424749916a6ec7958efcc931e | 31,442 |
def rdc_transformer(
local_data,
meta_types,
domains,
k=None,
s=1.0 / 6.0,
non_linearity=np.sin,
return_matrix=False,
ohe=True,
rand_gen=None,
):
# logger.info('rdc transformer', k, s, non_linearity)
"""
Given a data_slice,
return a transformation of the features data... | 420e0ca3dfedf23434cb1f2ee500a2d0f8969f52 | 31,443 |
async def get_layer_version(compatible_runtime=None,layer_name=None,version=None,opts=None):
"""
Provides information about a Lambda Layer Version.
"""
__args__ = dict()
__args__['compatibleRuntime'] = compatible_runtime
__args__['layerName'] = layer_name
__args__['version'] = version
_... | 57319a257b4e15e2d7ab2d14bfc43718967ea7e2 | 31,445 |
from typing import Optional
from typing import List
def get_header_names(header_annotation_names: Optional[List[str]],
doc: Optional[str] = None,
docs: Optional[List[str]] = None):
"""Get a list of header annotations and a dictionary for renamed annotations."""
# Get ... | e011af009e350e0ddbd5b18d19eb45816a7e8d6c | 31,446 |
def data_index(data, key):
"""Indexing data for key or a list of keys."""
def idx(data, i):
if isinstance(i, int):
return data[i]
assert isinstance(data, dict)
if i in data:
return data[i]
for k, v in data.items():
if str(k) == str(i):
... | f2b6d18bcd83eb0ffd9b355643e79b40459d8d6a | 31,447 |
def calculate_misfit(da):
""" For each force orientation, extracts minimum misfit
"""
misfit = da.min(dim=('origin_idx', 'F0'))
return misfit.assign_attrs({
'best_force': _min_force(da)
}) | 3dcba853b2e30d9fb5d3cbf96cfa6a00760335a6 | 31,448 |
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