content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import os
def get_dftd3_energy(ipt):
""" Grimme's D3 correction to energy """
fxyz, func, iabc = ipt
sabc = ' -abc' if iabc else ''
cmd = "dftd3 %s -func %s -bj%s | grep Edisp | awk '{print $NF}'"%(fxyz,func,sabc)
#print(cmd) #; sys.exit(2)
e = eval(os.popen(cmd).read().strip())
return e | 9c0098fd619e202b867b956b56227124d10cae8a | 28,000 |
import itertools
def get_state_vect_cols(prefix=''):
"""Get the column names of the state vector components with the
provided `prefix`.
:param prefix: The prefix that is used in front of the state vector
components in the column names, examples are `physics_pred` and
`physics_err` or none... | d61c5ebd2aad8c679dda50fa1e310ebf11480e01 | 28,001 |
import types
def set_df_index(typingctx, df_t, index_t=None):
"""used in very limited cases like distributed to_csv() to create a new
dataframe with index
"""
# TODO: make inplace when dfs are full objects
def codegen(context, builder, signature, args):
in_df_arg = args[0]
index =... | 7bdbdee58bc2a8a71583d43d637a6fa9ab7e8224 | 28,002 |
import six
import shlex
def parse_options(options=None, api=False):
"""
Parse given option string
:param options:
:type options:
:param api
:type api: boolean
:return:
:rtype:
"""
if isinstance(options, six.string_types):
args = shlex.split(options)
options = v... | f8a2b3671dab3ffc5f23bd937181324bc1c0d9c7 | 28,003 |
import random
from datetime import datetime
def data_for_column(column: dict, kwargs: dict, size: int) -> list:
"""Generates data for schema column
:param dict column: Column definition
:param dict kwargs: Faker keyword arguments
:param int size: Number of rows
:return: List of random data for a ... | d2ba76d48d80cc256f1959d8fa617b81301119d0 | 28,004 |
def peak_bin(peaks, i):
"""Return the (bin) index of the ith largest peak. Peaks is a list of tuples (i, x[i])
of peak indices i and values x[i], sorted in decreasing order by peak value."""
if len(peaks) > i:
return peaks[i][0]
else:
return np.nan | fc667fe04c856e3090ded9ca8eb0a45d51cda74a | 28,005 |
def fetch_all(path, params=None, client=default_client):
"""
Args:
path (str): The path for which we want to retrieve all entries.
Returns:
list: All entries stored in database for a given model. You can add a
filter to the model name like this: "tasks?project_id=project-id"
"""... | d663414388b9b6e105fab42d8e4d9cde558322cf | 28,006 |
from datetime import datetime
import calendar
def plotter(fdict):
""" Go """
pgconn = get_dbconn('coop')
cursor = pgconn.cursor(cursor_factory=psycopg2.extras.DictCursor)
ctx = get_autoplot_context(fdict, get_description())
station = ctx['station']
table = "alldata_%s" % (station[:2],)
nt... | 4b11cee286494963afb43cfc5b6ab7e56c281476 | 28,007 |
def link_library_dynamic(hs, dep_info, object_files, my_pkg_id):
"""Link a dynamic library for the package using given object files.
Returns:
File: Produced dynamic library.
"""
dynamic_library = hs.actions.declare_file(
"lib{0}-ghc{1}.{2}".format(
pkg_id.library_name(hs, my_pkg_id),
hs.too... | 5171d75c71b52e2487ff1d349add86c042a84062 | 28,008 |
def save_mvgcca_latents_space(X, W, model, path, prefix, epochs):
"""Saves the list containing the common latent space Z and all the views latent space Z_m.
- X : [np.array(n x d1),...,np.array(n x dM)] multivews features ; n number of instances; dm dimension of views m ; M number of views
... | dc0fbb15dd73e44bf1b1b2c74b173cfb6b8cf1d8 | 28,009 |
def TDC_sampling(in_channels, mode='downsampling'):
"""
wrapper_function: -> TIC_sampling
[B, in_channels, T, F] => [B, in_channels, T, F//2 or F*2]
in_channels: number of input channels
"""
return TIC_sampling(in_channels, mode) | 8458e9fe9bfd6bc92af2940b4c3ea5d2f09eb40a | 28,010 |
def bmxbm(s, t, batch_first=True):
"""
Batched matrix and batched matrix multiplication.
"""
if batch_first:
equation = "aij,ajk->aik"
else:
equation = "ija,jka->ika"
return tf.einsum(equation, s, t) | 6ac60eb1ffeed2caad312fd4691d689e705986c0 | 28,011 |
import re
def get_all_semantic_case_ids():
"""Get iterator over test sorted IDs of all cases in the SBML semantic
suite"""
pattern = re.compile(r'\d{5}')
return sorted(str(x.name) for x in SBML_SEMANTIC_CASES_DIR.iterdir()
if pattern.match(x.name)) | d4a5cba008010f02398bb61c32f06450610de350 | 28,012 |
def generate_points(n=500, min_=0, max_=1):
"""
Generate a list of n points.
Parameters
----------
n : int
min_ : float
max_ : float
Returns
-------
list
List of length n with tuples (x, y) where x is in [min_, max_] and
y is either 0 or 1.
"""
assert ma... | fe2dbe0ed281716a465804d67014badab96fb414 | 28,013 |
def gce(nvf):
"""
Write the necessary code for launch the VNF using GCE
:param nvf:
:return: vagrantfile code
"""
element = Template(u'''\
config.vm.box = "{{image}}"
config.vm.provider :google do |google, override|
google.google_project_id = {{google_project_id}}
google.google_client_email = {... | 588c2472b2a957a1eda64bef526b6410103b72b2 | 28,014 |
import os
def save_pretrained_models(
model: nn.Module,
config: DictConfig,
path: str,
) -> DictConfig:
"""
Save the pretrained models and configs to local to make future loading not dependent on Internet access.
By loading local checkpoints, Huggingface doesn't need to download pr... | f33fb55d8a152581c906470156a0dc8c87dadef4 | 28,015 |
from datetime import datetime
def get_ethpm_birth_block(
w3: Web3, from_block: int, to_block: int, target_timestamp: int
) -> int:
"""
Returns the closest block found before the target_timestamp
"""
version_release_date = datetime.fromtimestamp(target_timestamp)
while from_block < to_block:
... | c2448152cea2a3c9a9dd227a5126e2dd0767b773 | 28,016 |
def Line(p0, p1=None, c="r", alpha=1, lw=1, dotted=False, res=None):
"""
Build the line segment between points `p0` and `p1`.
If `p0` is a list of points returns the line connecting them.
A 2D set of coords can also be passed as p0=[x..], p1=[y..].
:param c: color name, number, or list of [R,G,B] c... | 1a56c260ad0d3478b51db03fa267898c637bf819 | 28,017 |
def date_dd(dataset, source):
"""Display 3 blocks: 1. image of the patent, 2. choice block, 3. text block for date. 2 is
artifical and should be ignored"""
def get_stream():
# Load the directory of images and add options to each task
stream = Images(source)
for eg in stream:
... | fae232b97ab4d758aceea806ebc95816db3cb044 | 28,018 |
def sort(array=[12,4,5,6,7,3,1,15]):
"""Sort the array by using quicksort."""
less = []
equal = []
greater = []
if len(array) > 1:
pivot = array[0]
for x in array:
if x < pivot:
less.append(x)
elif x == pivot:
equal.append(x)
... | bc31df069f8e985d620032b9053bd8f13880780f | 28,019 |
def _derive_country_JP(place):
"""Derive Japanese place names."""
derived = []
if _JP_FU_SUFFIX.search(place.asciiname):
bare = _JP_FU_SUFFIX.sub("", place.asciiname)
derived += [bare, bare + " prefecture", bare + " pref"]
elif _JP_KEN_SUFFIX.search(place.asciiname):
bare = _JP_K... | aea2aec9611457e63de335c3fe333be74c0efa6f | 28,020 |
from typing import Optional
async def remove_completed_game(player_id: str, game_id: str) -> Optional[dict]:
"""
Updates the player's current games by removing a game from it.
:param player_id: the object id of the player
:param game_id: the object id of the game
:return: an awaitable resolving ... | 2e5f4ec3af053d1f1685e6a576d8027db585bc87 | 28,021 |
def triangulate_dlt(Ps, ys):
"""Triangulate 3D position between two 2D correspondances using the direct
linear transformation (DLT) method.
If any 2D correspondance is missing (i.e. NaN), returns triangulated
position as NaN value as well.
TODO: Normalize input data (see HZ, p104. "4.4 Transformat... | 0e291bdcd3b95eb6dd29f3f5a305d0fe88c07072 | 28,022 |
def is_multioutput(y):
"""Whether the target y is multi-output (or multi-index)"""
return hasattr(y, "shape") and y.ndim == 2 and y.shape[1] > 1 | bcdaa46c304fec50c173dffca5f1f1d5d8871a58 | 28,023 |
def read_all(db: Session):
""" Get all dimensions.
:param db:
:return: List[QuestionModel]
"""
question = db.query(QuestionModel).all()
return question | a854c4667dc30918cd1e9ec767d65fa8ad1fb5ca | 28,024 |
def get_all_tenants(context):
"""Returns a list of all tenants stored in repository.
:param context: context of the transaction
"""
return context.session.query(db_models.AristaProvisionedProjects) | 62d8fed653f5b8e380caa47f5f408ecab860a58b | 28,025 |
import os
def load_sample_nni(series='short'):
"""Returns a short-term (5min) or long-term (60min) series of sample NNI found in the pyhrv/files/ directory.
Docs:
Parameters
----------
series : string, optional
If 'long', returns a 60min NNI series, if 'short', returns a 5min NNI series
Returns
-------
... | d3ffd2208321f432312f87922deb4aac22c87ce5 | 28,026 |
def total_sub_pixels_2d_from(mask_2d: np.ndarray, sub_size: int) -> int:
"""
Returns the total number of sub-pixels in unmasked pixels in a mask.
Parameters
----------
mask_2d : np.ndarray
A 2D array of bools, where `False` values are unmasked and included when counting sub pixels.
sub_... | 98461ffe073172db596570630ccfbd27384c7e3a | 28,027 |
import logging
import sys
def connectOutputLogger(file=None, logger_name='output'):
"""
Function that connects the output logger.
This is always enabled and hardwired to
generate logging.INFO level messages only.
@params file : Output file to store these messages into.
@default None : If file... | ce3b0f2a9910afd1ea364177f746353559f63bd2 | 28,028 |
from simtk import unit as simtk_unit
import torch
def formaldehyde_conformer(formaldehyde) -> torch.Tensor:
"""Returns a conformer [A] of formaldehyde with an ordering which matches the
``formaldehyde`` fixture."""
formaldehyde.generate_conformers(n_conformers=1)
conformer = formaldehyde.conformers[... | f5a9a19f6dd8e26a121e496161fa6da7b8f63047 | 28,029 |
import warnings
def reduce_function(op_func, input_tensor, axis=None, keepdims=None,
name=None, reduction_indices=None):
"""
Handler function for Tensorflow depreciation of keep_dims for tf 1.8
and above, but tf 1.4 requires keep_dims
:param op_func: expects the function to handle ... | f6433479bcb01a8fc5dfc2c08dd70bf2fe500e94 | 28,030 |
from typing import Mapping
def filter_dict(function_or_value, dict_to_filter):
"""
Filter by value
>>> filter_dict(123, {'a': 123, 'b': 1234})
{'b': 1234}
Filter by value not applicable
>>> filter_dict(123, {'a': 1234, 'b': 5123})
{'a': 1234, 'b': 5123}
Embedded filter by val... | 6403f716c21a1cfef046174899183858837bb92e | 28,031 |
import click
from typing import OrderedDict
import json
import sys
def _buy(config, client, machine_auth, resource, info_only=False, payment_method='offchain', header=(),
method='GET', output_file=None, data=None, data_file=None, maxprice=10000):
"""Purchase a 402-enabled resource via CLI.
This func... | 52a139a4c0ac7cff9fb788b646d2e2744f3506dd | 28,032 |
def resnet50(pretrained=False, **kwargs):
"""Constructs a ResNet-50 model.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet
"""
model = ResNet(Bottleneck, [3, 4, 6, 3], **kwargs)
return model | ba0f11d8645f3dcc5ccc48ec718de0c6ff624930 | 28,033 |
import torch
import math
def irfft(x, res):
"""
:param x: tensor of shape [..., m]
:return: tensor of shape [..., alpha]
"""
assert res % 2 == 1
*size, sm = x.shape
x = x.reshape(-1, sm)
x = torch.cat([
x.new_zeros(x.shape[0], (res - sm) // 2),
x,
x.new_zeros(x.... | 8f383523bc0c4ed6895d8aad0aca2758401d2fe5 | 28,034 |
import torch
def calc_ranks(idx, label, pred_score):
"""Calculating triples score ranks.
Args:
idx ([type]): The id of the entity to be predicted.
label ([type]): The id of existing triples, to calc filtered results.
pred_score ([type]): The score of the triple predicted by the model.... | 1f3d56c9a93afdd314c9a244319ef78668426481 | 28,035 |
def GBT(trainingData, testData):
"""
Gradient Boosted Tree Regression Model
:param trainingData:
:param testData:
:return: Trained model, predictions
"""
gbt = GBTRegressor( maxIter=100, maxDepth=6, seed=42)
model = gbt.fit(trainingData)
predictions = model.transform(testData)
r... | 4e17c7188ccdd2676463a705a4e3ab4ccbc5adeb | 28,036 |
def fromcolumns(cols, header=None, missing=None):
"""View a sequence of columns as a table, e.g.::
>>> import petl as etl
>>> cols = [[0, 1, 2], ['a', 'b', 'c']]
>>> tbl = etl.fromcolumns(cols)
>>> tbl
+----+-----+
| f0 | f1 |
+====+=====+
| 0 | 'a'... | c033e0fbc11e18a73eb8216e4a3a2c79a0756bb8 | 28,037 |
import re
def function_sql(field, mysql_result_list):
"""
替换MySQL查询结果的方法
:param field: 第一个参数是yaml文件里面定义的字段
:param mysql_result_list: 第二个参数是MySQL查询结果列表
:return:
"""
if "{__SQL" in field:
mysql_index_list = re.findall("{__SQL(.+?)}", field)
# 获取索引列表
for i in mysql_in... | 769881ae5e3a7caa036c977785827e219e5ab92b | 28,038 |
import os
def get_data_path():
"""
Return the location of the settings file for the data readers.
"""
return os.path.dirname(__file__) | aaae8a5c9b5b18c8b2d9513cb4b7be6e466bb443 | 28,039 |
def enable_dropout(model, rate=None, custom_objects={}):
"""
Enables the droput layer - used for monte carlo droput based uncertainty computation
Note: the weights needs to be reloaded after calling this model
>>> model = enable_dropout(model)
>>> model.load_weights('path to model weight')
:par... | 2268c23bc5598fcf0befe76a15f0dbc444e28828 | 28,040 |
import ctypes
def get_max_torque_norm(p_state, idx_image=-1, idx_chain=-1):
"""Returns the current maximum norm of the torque acting on any spin."""
return float(_Get_MaxTorqueNorm(ctypes.c_void_p(p_state), ctypes.c_int(idx_image), ctypes.c_int(idx_chain))) | b6ae73ef269a192b5aafc96e939a0ab1f9a937be | 28,041 |
def filter_by_zscore(data, features, remove_z):
"""Remove rows with |z scores| > remove_z"""
return data[(np.abs(np.nan_to_num(zscore(data[features]), posinf=0.0, neginf=0.0)) < remove_z).all(axis=1)] | bbaad3ee7879d64dafb2e45062c6cbe97ff457bc | 28,042 |
def _GetProperty(obj, components):
"""Grabs a property from obj."""
if obj is None:
return None
elif not components:
return obj
elif (isinstance(components[0], _Key) and
isinstance(obj, dict)):
return _GetProperty(obj.get(components[0]), components[1:])
elif (isinstance(components[0], _... | d887613e06078fcde887d51c8f83cc9ddc8f16f8 | 28,043 |
def make_similarity_function(similarity=None, distance=None, radius=None):
"""
Function creating a similarity function returning True if the compared
items are similar from a variety of functions & parameters.
Basically, if a distance function is given, it will be inverted and if
a radius is given,... | b8eeeeb466f21f2b3605941253f56392c3e41e88 | 28,044 |
from typing import Optional
def prepare_error_message(message: str, error_context: Optional[str] = None) -> str:
"""
If `error_context` is not None prepend that to error message.
"""
if error_context is not None:
return error_context + ": " + message
else:
return message | ea95d40797fcc431412990706d5c098a07986156 | 28,045 |
def _options_from_args(args):
"""Returns a QRCodeOptions instance from the provided arguments.
"""
options = args.get('options')
if options:
if not isinstance(options, QRCodeOptions):
raise TypeError('The options argument must be of type QRCodeOptions.')
else:
# Convert t... | ff895e537a0d2c00f42e10f827b8176865902774 | 28,046 |
def calc_q_rq_H(region, R_type):
"""単位面積当たりの必要暖房能力
Args:
region(int): 省エネルギー地域区分
R_type(string): 暖冷房区画の種類
Returns:
float: 単位面積当たりの必要暖房能力
Raises:
ValueError: R_type が '主たる居室' または 'その他の居室' 以外の場合に発生する
"""
table_3 = get_table_3()
if R_type == '主たる居室':
return t... | 1b413f0d83d723e1ef01c558cbc54e8afddc65ac | 28,047 |
def tuple_compare_lt(left, right):
"""Compare two 'TupleOf' instances by comparing their individual elements."""
for i in range(min(len(left), len(right))):
if left[i] > right[i]:
return False
if left[i] < right[i]:
return True
return len(left) < len(right) | 8f93d0c1336fd63d7c7f04cf54680de25acfdafb | 28,048 |
def multilevel_roi_align(inputs, boxes, image_shape, crop_size: int = 7):
"""Perform a batch multilevel roi_align on the inputs
Arguments:
- *inputs*: A list of tensors of shape [batch_size, width, height, channel]
representing the pyramid.
- *boxes*: A tensor and shape [batch_size, num_b... | 3b150e6b6bcada3d3633f1edf61a99a566792849 | 28,049 |
def login():
"""Login user"""
# Instantiate login form
form = LoginForm()
username = form.username.data
if form.validate_on_submit():
# Query database for username and validate form submission
user = User.query.filter_by(username=username).first()
# if user exists
i... | fa1e1814d71bcbf04fda08b282f3f1a58965dcfb | 28,050 |
from datetime import datetime
import uuid
def serialize(obj):
"""JSON serializer for objects not serializable by default json code"""
if isinstance(obj, datetime.datetime):
serial = obj.isoformat(sep='T')
return serial
if isinstance(obj, uuid.UUID):
serial = str(obj)
retur... | c20abaac68e8f8c8314a6dbbaee128b54110705c | 28,051 |
def clean_names_AZ(col):
"""
Removes any non-alpha characters (excluding spaces) from a string.
Replaces these characters with an empty space. Trims outer whitespace.
Example
--------
>>> Input: "JOHN SMITH 2000"
>>> Output: "JOHN SMITH"
"""
return trim(regexp_replace(col, "[^A-Z ]+... | 4db710ec573087df59109046ea2a965c7545f1a2 | 28,052 |
def check_continent_node_membership(continents, continent_node_id):
"""The function checks that a node continent is bound
to the corresponding relation through 'label' membership.
"""
assert continent_node_id[0] == 'n', ("A node expected in "
"check_continent... | 7ef0895e26fdd495f54ac58ea35513178f00eb19 | 28,053 |
import string
def remove_punctuation(input_string):
"""
remove the punctuation of input
Parameters
----------
input_string : string
Returns
-------
output_string : string
string without punctuation
###from assignment encoder
"""
out_... | 2bbd1dc90d37c1ad16698092b6269c0fe601d902 | 28,054 |
from typing import Any
def field_value_between(value: Any = None, field: str = None,
lower: float = None, upper: float = None) -> bool:
"""
Validate value at the given field to be between the lower/upper boundaries.
"""
if not value:
return False
if not isinstance(... | 4ff2dfa814f0ddda7efca3ce19f137a0d86b9f40 | 28,055 |
import yaml
def j2_to_json(path_in, path_out, **kwargs):
"""Render a yaml.j2 chart to JSON.
Args:
path_in: the j2 template path
path_out: the JSON path to write to
kwargs: data to pass to the j2 template
Returns:
the file path and JSON string
"""
return pipe(
rend... | 2cd41eb29e293e44772855f7d66e7425eedaec8d | 28,056 |
def user_logged_out(connection,user):
"""
update login status to false when user has logged out
:param connection:
:param user:
:return:
"""
with connection:
return connection.execute(UPDATE_USER_LOGIN_STATUS_TO_FALSE,(user,)) | b355fa6e74180adb7504e60602cb164095e1898d | 28,057 |
def findGrayscaleTilesInImage(img):
""" Find chessboard and convert into input tiles for CNN """
if img is None:
return None, None
# Convert to grayscale numpy array
img_arr = np.asarray(img.convert("L"), dtype=np.float32)
# Use computer vision to find orthorectified chessboard corners in image
cor... | d3431c519f53c0a56b144dde8196d58000f2f788 | 28,058 |
def run(df, docs, columns):
"""
converts each column to type int
:param df:
:param columns:
:return:
"""
for doc in docs:
doc.start("t07 - Change type of {} to int".format(str(columns).replace("'", "")), df)
for column in columns:
df[column] = df[column].astype(int)
... | 5d360a764ad30a80c39d58f9aeb520d7c57f7903 | 28,059 |
import requests
def get_articles():
"""
Retreives the articles list (via an API request)
"""
endpoint = "%s%s" % (
settings.API_BASE_URL,
reverse("api:articles-list")
)
headers = DEFAULT_REQUESTS_HEADERS
r = requests.get(
endpoint,
headers=DEFAULT_REQUE... | fb2b59cc301890b8c6f4c6c115b6f08f4a4cbe72 | 28,060 |
import numpy
def fmin_ncg(f, x0, fprime, fhess_p=None, fhess=None, args=(), avextol=1e-5,
epsilon=_epsilon, maxiter=None, full_output=0, disp=1, retall=0,
callback=None, preconditioner = None):
"""
Unconstrained minimization of a function using the Newton-CG method.
Parameters
... | bb2d4c3d1303adebe856f6c3ac13cd92beeee0ab | 28,061 |
def add_missing_flow_by_fields(flowby_partial_df, flowbyfields):
"""
Add in missing fields to have a complete and ordered
:param flowby_partial_df: Either flowbyactivity or flowbysector df
:param flowbyfields: Either flow_by_activity_fields, flow_by_sector_fields, or flow_by_sector_collapsed_fields
... | 49eb8810c7c2c4e852a40aa86e2d2d2a8506f253 | 28,062 |
from datetime import datetime
def calcular_diferencia_dias(fin_dia):
"""
Obtiene la diferencia de dias entre una fecha y hoy
"""
hoy = datetime.now()
end = datetime.strptime(str(fin_dia), '%Y-%m-%d')
return abs(end - hoy).days | 41b732f3bb09d2deca4be034273a5fed74971386 | 28,063 |
def matrix_base_mpl(matrix, positions, substitutions, conservation=None,
secondary_structure=None, wildtype_sequence=None,
min_value=None, max_value=None,
ax=None, colormap=plt.cm.RdBu_r,
colormap_conservation=plt.cm.Oranges, na_color="#bbb... | ef661fd556b3ba2e4c313e032e8ef3be532bb73d | 28,064 |
def gaussian_laplace(input, sigma, output=None, mode="reflect",
cval=0.0, **kwargs):
"""Multi-dimensional Laplace filter using Gaussian second derivatives.
Args:
input (cupy.ndarray): The input array.
sigma (scalar or sequence of scalar): Standard deviations for each axis
... | 6b5f184b658dd446a4f3ec7de0ee126f33663b0c | 28,065 |
def get_commits_after_forkpoint(main_dir, base_sha, head_sha, repo_name, log, secure_repo_name):
"""List commit hashes between base_sha and head_sha
:param main_dir: model directory
:param base_sha: base SHA i.e. point of the history when the branch started
diverging from the main branch.
:para... | 6b8f8609adb80903215fc11f08380db3f8deffcd | 28,066 |
def perimeter_mask(image, corner_fraction=0.035):
"""
Create boolean mask for image with a perimeter marked as True.
The perimeter is the same width as the corners created by corner_mask.
Args:
image : the image to work with
corner_fraction: determines the width of the perimeter
Re... | afc755dccfffa9ff68e060a6af3da0d38d323178 | 28,067 |
def vgg13_bn(**kwargs):
"""VGG 13-layer model (configuration "B") with batch normalization"""
model = VGG(make_layers(cfg['B'], batch_norm=True), **kwargs)
return model | 1fa3ffdbb301b55a48fc1912baab84006705e15f | 28,068 |
import regex
def convert_version_to_tuple(version: str) -> VersionTuple:
"""
Convert version info from string representation to tuple representation.
The tuple representation is convenient for direct comparison.
"""
m = regex.fullmatch(r"(?P<major>\d+)\.(?P<minor>\d+)", version)
if not m:
... | 6c197988ae2c98481f9b16f90f9ae3f7072ac7c8 | 28,069 |
from typing import Callable
def SU3GradientTF(
f: Callable[[Tensor], Tensor],
x: Tensor,
) -> tuple[Tensor, Tensor]:
"""Compute gradient using TensorFlow GradientTape.
y = f(x) must be a real scalar value.
Returns:
- (f(x), D), where D = T^a D^a = T^a ∂_a f(x)
NOTE: Use real v... | 93b029e0a2854e651d4c6ea5995f8d952f9a64e6 | 28,070 |
def create_app(config):
"""Flask application factory.
Returns:
Flask Application with BrazilDataCubeDB extension prepared.
"""
app = Flask(__name__)
BrazilDataCubeDB(app)
return app | d8ba6d7306508e4a55f9f3dbee5d17df16c56820 | 28,071 |
import string
def genpass_comprehension(length=8, chars=string.letters+string.digits):
"""Generate password using a list comprehension.
"""
# Can be rewritten as a list comprehension.
return ''.join([choice(chars) for i in range(length)]) | d77b89e2872eef92390d08f555adbb52f9da1c34 | 28,072 |
import functools
def typed(*types):
"""Type annotation.
The final type is the output type.
"""
if len(types) < 1:
raise SyntaxError('Too few arguments: typed{}'.format(types))
if len(types) > 3:
raise NotImplementedError('Too many arguments: typed{}'.format(types))
result_typ... | 90f100bebd5778d36eee1ad04b7c831b003ce604 | 28,073 |
from typing import Tuple
def insert_linebreaks(
input_fragments: StyleAndTextTuples,
max_line_width: int,
truncate_long_lines: bool = True) -> Tuple[StyleAndTextTuples, int]:
"""Add line breaks at max_line_width if truncate_long_lines is True.
Returns input_fragments with each charact... | ec9faf8ff80e3500487634b759a136dc2deca684 | 28,074 |
def score_reactant_combination(candidate_combination, scoring_fcn):
""" Generates a score for a combination of reactant candidates according to the criteria. """
# Extract only the reactant candidate compound ID's.
reactant_ids = [combo[0] for combo in candidate_combination]
# Score the reactant candi... | 715a21bf24af0a60ba3ea421b7bf8dcebcca17fc | 28,075 |
import sys
def main(argv=None):
"""Provide the main entry point."""
help_builder.init("charmcraft", GENERAL_SUMMARY, COMMAND_GROUPS)
emit.init(EmitterMode.NORMAL, "charmcraft", f"Starting charmcraft version {__version__}")
if argv is None:
argv = sys.argv
extra_global_options = [
... | 6adf05b9883b698a69c3845df2f58f48953e98e8 | 28,076 |
import logging
import os
import json
def xmind_testsuite_to_json_file(xmind_file):
"""Convert XMind file to a testsuite json file"""
xmind_file = get_absolute_path(xmind_file)
logging.info('Start converting XMind file(%s) to testsuites json file...', xmind_file)
testsuites = get_xmind_testsuite_list(x... | d8c7c7aec99c76e7e2d1195dd4f557e68be3adfa | 28,077 |
def get_named_entities(df):
"""
Count the named entities that are neither A nor B.
Hopefully this correlates with class "Neither".
:param df: competition data with one extra field spacy_nlp_doc: precomputed nlp(text)
:return:
"""
named_df = pd.DataFrame(0, index=df.index, columns=["named_e... | 65469fe65c8808943343d952fd82ebe62bb9df97 | 28,078 |
def normalize(vectors):
"""
Normalize a set of vectors.
The length of the returned vectors will be unity.
Parameters
----------
vectors : np.ndarray
Set of vectors of any length, except zero.
"""
if len(vectors.shape) == 1:
return vectors / np.linalg.norm(vectors)
... | 839104d17a3ccbfd1191474bf95076445b4b0464 | 28,079 |
def get_all_requests(current_user):
"""Gets all requests"""
all_requests = []
for request in request_model.requests.values():
all_requests.append(request)
return jsonify(all_requests) | bcadfb936826b3a33f809cc95af1a991c5bf741e | 28,080 |
def RunManifestExe(target, source, env):
"""Calls RunManifest for updating an executable (resource_num=1)."""
return RunManifest(target, source, env, resource_num=1) | 629ffccb7b163514bd91c790894bdfec3683110e | 28,081 |
import torch
def dist_reduce_tensor(tensor, dst=0):
"""Reduce to specific rank"""
world_size = get_world_size()
if world_size < 2:
return tensor
with torch.no_grad():
dist.reduce(tensor, dst=dst)
if get_rank() == dst:
tensor.div_(world_size)
return tensor | d64d153145bffaf454dd3f46154db156b600bac3 | 28,082 |
def upload_blob(bucket_name, source_file_name, destination_blob_name):
"""Uploads a file to the bucket."""
storage_client = storage.Client()
bucket = storage_client.get_bucket(bucket_name)
blob = bucket.blob(destination_blob_name)
blob.upload_from_file(source_file_name)
print('File {} uploaded ... | b63d6bb0ede33d68d684b98968e3e94efbd0c5df | 28,083 |
def get_lines(matrix, loc):
"""Returns lines that pass though `loc`. Matrix can be indices.
Args:
matrix: a N by N matrix representing the board
loc: a tuple of loc coordinates
Returns:
Numerical values on the horizontal, vertical, and diagonal lines that
pass through loc.
... | 43909460e847d5dde88216cc37b902a56ba2d261 | 28,084 |
from bs4 import BeautifulSoup
from typing import Dict
def process_citations_in_paragraph(para_el: BeautifulSoup, sp: BeautifulSoup, bibs: Dict, bracket: bool) -> Dict:
"""
Process all citations in paragraph and generate a dict for surface forms
:param para_el:
:param sp:
:param bibs:
:param br... | 74418fafc2a2d828b702555b79b515d9b16d9f10 | 28,085 |
def duration(start_time, end_time=None):
"""Get a timedelta between end_time and start_time, where end_time defaults
to now().
WARNING: mixing tz-aware and naive datetimes in start_time and end_time
will cause an error.
"""
if not start_time:
return None
last_time = end_time if end_... | 89febebf342225525bf7543342b884f130e7b3f2 | 28,086 |
def get_commands(cfg, clargs, *, what, **kwargs):
"""
Delegates the creation of commands lists to appropriate functions based on `what` parameter.
Parameters
----------
cfg: dict
Configuration dictionary.
clargs: Namespace
Command line arguments.
cmds: iter(tuple(str))
what: str... | 360410064a24d547729722c4f5843d78af9444c8 | 28,087 |
def heappush(heap, item):
"""
>>> heappush([4, 4, 8, 9, 4, 12, 9, 11, 13], 7)
[4, 4, 8, 9, 4, 12, 9, 11, 13, 7]
>>> heappush([4, 4, 8, 9, 4, 12, 9, 11, 13, 7], 10)
[4, 4, 8, 9, 4, 12, 9, 11, 13, 7, 10]
>>> heappush([4, 4, 8, 9, 4, 12, 9, 11, 13, 7, 10], 5)
[4, 4, 5, 9, 4, 8, 9, 11, 13, 7, ... | 99e6814828e42da8a14f4d0873e62af920a800b8 | 28,088 |
def dx(scalar_field):
"""
Computes first derivative of a 1D scalar field
:param scalar_field:
:return:
"""
first_derivative = np.zeros((scalar_field.size - 1))
for i_scalar in range(scalar_field.size - 1):
i_next_scalar = i_scalar + 1
first_derivative[i_scalar] = scalar_fiel... | b0af862210a2a395dcdfdab2e921f2c305a536d2 | 28,089 |
import argparse
def makeParser():
"""
Make a command-line argument parser.
@return: An C{argparse.ArgumentParser} instance.
"""
parser = argparse.ArgumentParser(
description=('Print a JSON object containing reference to read '
'distances extracted from a SAM file.'))
... | d1dd832d1533eb5a506eca19a35499362b03feb7 | 28,090 |
def get_genetic_profiles(study_id, profile_filter=None):
"""Return all the genetic profiles (data sets) for a given study.
Genetic profiles are different types of data for a given study. For
instance the study 'cellline_ccle_broad' has profiles such as
'cellline_ccle_broad_mutations' for mutations, 'ce... | b409a1511112cafab0330a23684b3e255fa0a60c | 28,091 |
import string
def cipher(sentence, n_rotate):
"""
Cipher string with Caesar algorithm ( Anything else than letters stays the same. )
:param sentence: String containing sentence/sentences/word/words.
:param n_rotate: number to translate letters
:return: string with ciphered words
"""
upper ... | e0606949f254971431faf7899bd254f4792176d4 | 28,092 |
from typing import Union
from typing import List
def _assert_in_fc(
r: RestClient, uuids: Union[str, List[str]], all_keys: bool = False
) -> StrDict:
"""Also return data."""
if isinstance(uuids, str):
uuids = [uuids]
if all_keys:
data = r.request_seq('GET', '/api/files', {'all-keys': ... | 908f12309a93abc472e05598abbb0e5ee29cc798 | 28,093 |
def power_law(uref, h, href, shear):
"""
Extrapolate wind speed (or other) according to power law.
NOTE: see https://en.wikipedia.org/wiki/Wind_profile_power_law
:param uref: wind speed at reference height (same units as extrapolated wind speed, u)
:param h: height of extrapolated wind speed (same ... | cb5d002dfeed022af694060bfe9e516191835742 | 28,094 |
import os
def get_defaults():
"""
Returns default frequencies to project intensities onto as well as default
paths for locations of the pure and mixture spectroscopic data.
Returns
-------
frequency_range: numpy.ndarray
Frequencies over which to project the intensities.
p... | a38f8a1aa9f74cf5736c87e1ad6a6fbd556aa472 | 28,095 |
def binary_weight_convolution(inp, outmaps, kernel,
pad=None, stride=None, dilation=None, group=1,
w_init=None, wb_init=None, b_init=None,
base_axis=1, fix_parameters=False, rng=None,
with_bias=True):... | 3cae56fee85ba0c7679e9de7fd2743c9ce252d1a | 28,096 |
def dataset2Xy(dataset):
"""Convert a dataset (pd.DataFrame) to X, y and output_dim
where X is the features, y is the labels (one-hot vectors),
and output_dim is the number of labels overall.
Args:
dataset: A pandas dataframe that is composed of features
columns and th... | ef07873db639a7a9c34b149959acd419d4a0b9d3 | 28,097 |
from typing import Callable
import sys
def sysexit(func: Callable) -> Callable:
""" use the function return value as the system exit code """
@wraps(func)
def wrapper(*args, **kwargs):
sys.exit(func(*args, **kwargs))
return wrapper | 826b9b265a3df5d79cc1fa61cdccefbd5eca87fa | 28,098 |
def pairwise_list(a_list):
"""
list转换为成对list
"s -> (s0,s1), (s1,s2), (s2, s3), ..."
:param a_list: list
:return: 成对list
"""
if len(a_list) % 2 != 0:
raise Exception("pairwise_list error!")
r_list = []
for i in range(0, len(a_list) - 1, 2):
r_list.append([a_list[i], a... | 5142fb2e00c931ab57fc9028eb9b6df5a98c0342 | 28,099 |
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