content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def migrate_data(conn: redis.StrictRedis, data: dict) -> list:
"""
Uploads the given data to the given redis database connection
"""
pipe = conn.pipeline()
for key, value in data.items():
command_and_formatter = TYPE_TO_PUT_COMMAND[value["type"]]
command = command_and_formatter[0]
... | 7e54d3bd0c5e302d3e2f173a53bf6cd6a9a6f6fb | 3,637,381 |
def dummy_location(db, create_location):
"""Give you a dummy default location."""
loc = create_location(u'Test')
db.session.flush()
return loc | ec6ffa3b42e07c88b8224ee2aaaf000853a4169f | 3,637,382 |
from pathlib import Path
def get_resources_path() -> Path:
""" Convenience method to return the `resources` directory in this project """
return alpyne._ROOT_PATH.joinpath("resources") | 35b90856e00fbee8aeb373350cef77596a5f2a71 | 3,637,383 |
import math
def sk_rot_mx(rot_vec):
"""
use Rodrigues' rotation formula to transform the rotation vector into rotation matrix
:param rot_vec:
:return:
"""
theta = np.linalg.norm(rot_vec)
vector = np.array(rot_vec) * math.sin(theta / 2.0) / theta
a = math.cos(theta / 2.0)
b = -vecto... | 9ba2abfd877d87423db02b224fed30ec59dc90f7 | 3,637,386 |
def split_line(line, points, tolerance=1e-9):
"""Split line at point or multipoint, within some tolerance
"""
to_split = snap_line(line, points, tolerance)
return list(split(to_split, points)) | 46a4ae55ff655c864154d37108689d81ad77daf1 | 3,637,387 |
import copy
def cross_validation(docs, values, k):
"""
docs: Dict with text lists separate by value
values: Target values texts
k: Steps of cross validation
"""
group_size = {}
confusion_matrix = []
m = {'true':{}, 'false':{}}
for value in values:
group_size[v... | 625a45edf45dc88db6e8c3b5342604891f899ebc | 3,637,389 |
def quote_plus(url, safe='/', encoding=None, errors=None):
"""Wrapper for urllib.parse.quote_plus"""
return uquote_plus(url, safe=safe, encoding=encoding, errors=errors) | 159a5e1e25bf35ee08b14f6dca871a4d0bb7f411 | 3,637,390 |
def averageSeriesWithWildcards(requestContext, seriesList, *position): #XXX
"""
Call averageSeries after inserting wildcards at the given position(s).
Example:
.. code-block:: none
&target=averageSeriesWithWildcards(host.cpu-[0-7].cpu-{user,system}.value, 1)
This would be the equivalent of
``target=... | 479be75db3498a1882c8a27d1a13de85102c52a6 | 3,637,391 |
def errore_ddp_digitale(V):
"""
Calcola l'errore della misura di ddp del multimetro digitale
supponendo che si sia scelta la scala corretta.
La ddp deve essere data in Volt
"""
V=absolute(V)
if V<0.2: return sqrt(V**2*25e-6+1e-8)
if V<2: return sqrt(V**2*25e-6+1e-6)
if V<20: retur... | d6504dfce600f5d9af2af33115c2e07b8033cf03 | 3,637,392 |
def extractLine(shape, z = 0):
"""
Extracts a line from a shape line.
"""
x = shape.exteriorpoints()[0][0] - shape.exteriorpoints()[1][0]
y = shape.exteriorpoints()[0][1] - shape.exteriorpoints()[1][1]
return (x, y, z) | c61021b1e3dc6372d9d7554a7033bbd3ab128343 | 3,637,395 |
import logging
def get_fragility_model_04(fmodel, fname):
"""
:param fmodel:
a fragilityModel node
:param fname:
path of the fragility file
:returns:
an :class:`openquake.risklib.scientific.FragilityModel` instance
"""
logging.warn('Please upgrade %s to NRML 0.5', fname... | 62633b156f18c6e722321cf937ea06741aa7a65f | 3,637,396 |
def substring_in_list(substr_to_find, list_to_search):
"""
Returns a boolean value to indicate whether or not a given substring
is located within the strings of a list.
"""
result = [s for s in list_to_search if substr_to_find in s]
return len(result) > 0 | 77521a1c5d487fa110d5adecb884dd298d2515e5 | 3,637,397 |
def downsample_image(image: np.ndarray, scale: int) -> np.ndarray:
"""Downsamples the image by an integer factor to prevent artifacts."""
if scale == 1:
return image
height, width = image.shape[:2]
if height % scale > 0 or width % scale > 0:
raise ValueError(f'Image shape ({height},{width}) must be div... | 7d011bda8dc2fccc9782e621bb61d7ab68992640 | 3,637,398 |
def getQueryString( bindings, variableName ):
""" Columns a bunch of data about the bindings. Will return properly formatted strings for
updating, inserting, and querying the SQLite table specified in the bindings dictionary. Will also
return the table name and a string that lists the columns (properly formatted... | 9cc81601cde229cc5f5bf53ef73997efc515ed2b | 3,637,399 |
def multiplicities(pattern):
""" Return a dictionary keyed by the geodesics in the given pattern, with values equal to the number of times the geodesic occurs."""
g = geodesics(pattern)
ans = {}
x = 0
for i in g:
if i == x:
ans[i] += 1
else:
x = i
... | 24eee8bcb3ce39927d1f60e89216b583e9eb12db | 3,637,400 |
def show_menu():
""" Shows a menu """
print '================== ' + util.HEADER + 'WORKFLOW MENU' + util.ENDC + ' =================='
print '1) Development - Create a git branch off of staging'
print '2) Merge - Merge your development branch to staging (GitHub)'
print '3) Build - Builds project, and... | 27d9733342a4fbbf64bf6635a06329043c843c9d | 3,637,401 |
def imap4_utf7_decode(data):
"""Decode a folder name from IMAP modified UTF-7 encoding to unicode.
Input is bytes (Python 3) or str (Python 2); output is always
unicode. If non-bytes/str input is provided, the input is returned
unchanged.
"""
if not isinstance(data, bytes):
return byte... | 9d0acbc22ce3079cff7849f992e924d9610f1154 | 3,637,402 |
def get_characters(character_path, character_dim):
"""Reads list of characters .txt file and returns embedding matrix and mappings from characters to character ids.
Input:
character_path: path to characters.txt
character_dim: integer
Returns:
emb_matrix: Numpy array shape (len(characters... | 5f523aa15ea03f79cf2fa1a313e6196dbcb1f650 | 3,637,403 |
def french_to_english(french_text: str) -> str:
"""This function translates from french to english
Parameters
----------
french_text : str
french text to translate
Returns
-------
str
translated text
"""
language_translator = translator_instance()
response = lan... | 1c2b4d3526394e22251bf68b2d2f035db9b3e5f6 | 3,637,405 |
from pathlib import Path
from typing import Iterable
def prefit_histograms(
rex_dir: str | Path,
samples: Iterable[str],
region: str,
fit_name: str = "tW",
) -> dict[str, TH1]:
"""Retrieve sample prefit histograms for a region.
Parameters
----------
rex_dir : str or pathlib.Path
... | 372a9d223b58473e3a90633b88a8800f7eadeabb | 3,637,406 |
def ymstring2mjd( ymstr ):
"""
The `ymstring2mjd` function enables array input.
Documentation see the `_ymstring2mjd` function.
"""
ymstr = np.array(ymstr,ndmin=1)
ymstr_count = np.size(ymstr)
mjd = np.zeros(ymstr_count,dtype=np.float_)
for ix in range(ymstr_count):
try:
... | 6f20be92833729ac712fe1a89c545d01015d5af2 | 3,637,407 |
def average(l):
""" Computes average of 2-D list """
llen = len(l)
def divide(x):
return x / float(llen)
return list(map(divide, map(sum, zip(*l)))) | 67395ce4417022a673565a8227c684b7649a5e6a | 3,637,408 |
def slugify3(text, delim=u'-'):
"""Generates an ASCII-only slug."""
result = []
for word in _punct_re.split(text.lower()):
result.extend(unidecode(word).split())
return unicode(delim.join(result)) | dbabf44a4681d613d7f7a1a096a32c66640e5185 | 3,637,409 |
from datetime import datetime
def teacher_registeration(request):
"""
Info: Registeration for the teacher.
Request-Body: email_id -> str
password -> str
image -> file
name -> str
date_of_birth -> str
education_qualification ->... | 96152e3c628360d498d497c23c6cd4c6a39a743b | 3,637,410 |
def check_response(response):
""" Checks that a response is successful, raising the appropriate Exceptions otherwise. """
status_code = response.status_code
if 100 < status_code < 299:
return True
elif status_code == 401 or status_code == 403:
message = get_response_data(response)
... | 4afd0003619cc90759778f513e2a692a7b81309d | 3,637,411 |
from typing import Iterator
from typing import Tuple
def walk_storage_from_command(command: instances.FilesRelatedCommand,
filesystem: Filesystem
) -> Iterator[Tuple[str, str, str]]:
"""Typical iteration by command settings."""
return walk(command.st... | 675e476fb2dcd2253181b7b4eeedbf43b58db54f | 3,637,412 |
import logging
def parse_csv_data(csv_filename: FileIO) -> list[str]:
"""Returns contents of 'csv_filename' as list of strings by row"""
try:
return open(csv_filename).readlines()
except FileNotFoundError:
logging.warning("File with path '%s' not found", csv_filename)
return [] | daf826d97a983b8ab3b1ebeb1b063b890c256236 | 3,637,413 |
import math
def _interpolate_sym(y0, Tkk, f_Tkk, y_half, f_yj, hs, H, k, atol, rtol,
seq=(lambda t: 4*t-2)):
"""
Symmetric dense output formula; used for example with the midpoint method.
It calculates a polynomial to interpolate any value from t0 (time at y0) to
t0+H (time at Tkk... | a8ab6765a2eff3c3a847c79f3524059cca831796 | 3,637,415 |
def _gtin_fails_checksum(gtin: str) -> bool:
"""Determines if the provided gtin violates the check digit calculation.
Args:
gtin: a string representing the product's GTIN
Returns:
True if the gtin fails check digit validation, otherwise False.
"""
padded_gtin = gtin.zfill(14)
existing_check_digit ... | 04d3857fd66e592938fa352be7a59f1784e3e00f | 3,637,416 |
import operator
def mergeGuideInfo(seq, startDict, pamPat, otMatches, inputPos, effScores, sortBy=None):
"""
merges guide information from the sequence, the efficiency scores and the off-targets.
creates rows with too many fields. Probably needs refactoring.
for each pam in startDict, retrieve the g... | 39ea084851f6ba6c1726ed181ac4f3ab10b71472 | 3,637,417 |
def search_orf(seq:str, min_orf:int) -> list:
"""Search full orf over ceration length in 6 frames"""
scod = "M"
send = "*"
orf_regions = {}
# Load 6 reading frames
seq1 = seq
seq2 = seq1[1: ]
seq3 = seq1[2: ]
seq4 = rc_seq(seq1)
seq5 = seq4[1: ]
seq6 = seq4[2: ]
# Shrink ... | 8d4e4c5d18e12aec5511bc06e5f0f532aec6e532 | 3,637,418 |
import json
def getPath():
"""
Gets path of the from ./metadata.json/
"""
with open('metadata.json', 'r') as openfile:
global path
json_object = json.load(openfile)
pairs = json_object.items()
path = json_object["renamer"]["path"]
return path | 03047172e653b4b4aee7f096a67291ad460969c9 | 3,637,419 |
from typing import Optional
def read_ann_h5ad(file_path, spatial_key: Optional[str] = None):
"""
read the h5ad file in Anndata format, and generate the object of StereoExpData.
:param file_path: h5ad file path.
:param spatial_key: use .obsm[`'spatial_key'`] as position. If spatial data, must set.
... | fbe003cd011833b5dad215fd2ae7eea59a58aa8d | 3,637,420 |
def get_token(token_method, acc=None, vo=None, idt=None, pwd=None):
"""
Gets a token with the token_method provided.
:param token_method: the method to get the token
:param acc: Rucio account string
:param idt: Rucio identity string
:param pwd: Rucio password string (in case of userpass auth_typ... | b04a60546e1aefdc2b8a2d2b0b7019f61c11ecc3 | 3,637,421 |
def valid_float_0_to_1(val):
"""
:param val: Object to check, then throw an error if it is invalid
:return: val if it is a float between 0 and 1 (otherwise invalid)
"""
return validate(val, lambda x: 0 <= float(x) <= 1, float,
'Value must be a number between 0 and 1') | 81b92a1f8d3212905c2080d995da65d84916fae9 | 3,637,422 |
def get_usps_data():
"""
"""
trainset = dsets.USPS(root='./data',
train=True,
transform=transforms.ToTensor(),
download=True)
testset = dsets.USPS(root='./data',
... | 2bb47e25b6d15e4b8a2e597320d9adfee6ff3008 | 3,637,423 |
def logout():
"""
Logs out a user
Returns:
(str): A JWT access token
"""
res = {}
try:
response = jsonify({"msg": "logout successful"})
unset_jwt_cookies(response)
return make_response(response), 200
except Exception as e:
res["data"] = None
r... | 478da4504b2804990f7e2f2c8de7a5578e23b64e | 3,637,424 |
def bm_reduction(mat):
""" Performs the Bloch-Messiah decomposition of single mode thermal state.
Said decomposition writes a gaussian state as a a thermal squeezed-rotated-displaced state
The function returns the thermal population, rotation angle and squeezing parameters
"""
if mat.shape != (2, ... | 1e69f610e885140442cc81d62969e96c69b294b8 | 3,637,425 |
def pinlattice_2ring_full():
"""Full, non-test instance of PinLattice object for testing
Subchannel object"""
n_ring = 2
pitch = 1.0
d_pin = 0.5
return dassh.PinLattice(n_ring, pitch, d_pin) | 8b78274bf7ebe33808885fab24d73aaff6ed17b2 | 3,637,426 |
def dmenu_view_previous_entry(entry, folders):
"""View previous entry
Args: entry (Item)
Returns: entry (Item)
"""
if entry is not None:
text = view_entry(entry, folders)
type_text(text)
return entry | d39cbe86be00563bfd77c2d9254e51df726185db | 3,637,427 |
def unary_to_gast(node):
"""
Takes unary operation such as ! and converts it to generic AST.
javascript makes negative numbers unary expressions. This is our
current workaround.
"""
if node.operator == "-":
return {"type": "num", "value": node.argument.value * -1}
return {
"... | 5cf86896008e38510a8d6133e9f795c76b75a608 | 3,637,428 |
def _norm_intensity(spectrum_intensity: np.ndarray) -> np.ndarray:
"""
Normalize spectrum peak intensities.
Parameters
----------
spectrum_intensity : np.ndarray
The spectrum peak intensities to be normalized.
Returns
-------
np.ndarray
The normalized peak intensities.
... | daba7d3a33ea4baf630332e9528ede82dabe6691 | 3,637,429 |
def axes_to_list(axes_data: dict) -> list:
"""helper method to convert a dict of sensor axis graphs to a 2d array for graphing
"""
axes_tuples = axes_data.items()
axes_list = [axes[1].tolist() for axes in axes_tuples]
return axes_list | fb2e5ef1f2283e2f31e5c8828a3ec7ef94869c5c | 3,637,430 |
from typing import List
def list(
repo_info: str,
git_host: str = DEFAULT_GIT_HOST,
use_cache: bool = True,
commit: str = None,
protocol: str = DEFAULT_PROTOCOL,
) -> List[str]:
"""Lists all entrypoints available in repo hubconf.
:param repo_info:
a string with format ``"repo_owne... | 2b9a635a8ee97ecd46fa47b06b6d872b562d7ceb | 3,637,431 |
from typing import Callable
def repeatfunc(func: Callable, times: Int = None, *args):
"""Repeat calls to func with specified arguments.
Example: repeatfunc(random.random)
:param func: function to be called
:param times: amount of call times
"""
if times is None:
return starmap(func,... | cae37683fd45a66b0ebec6ee0ab5a07d0cb128d7 | 3,637,432 |
from typing import Iterable
import functools
import operator
def prod(values: Iterable[int]) -> int:
"""Compute the product of the integers."""
return functools.reduce(operator.mul, values) | 3f03200078daf1b0b27f777e7744144ab72ec7af | 3,637,433 |
def get_stars_dict(stars):
"""
Transform list of stars into dictionary where keys are their names
Parameters
----------
stars : list, iterable
Star objects
Return
------
dict
Stars dictionary
"""
x = {}
for st in stars:
try:
x[st.name] = ... | 6d627be48a96d8ba93bd13511a05c251f3a3f169 | 3,637,434 |
from typing import Tuple
def initialize_molecular_pos(
key: PRNGKey,
nchains: int,
ion_pos: Array,
ion_charges: Array,
nelec_total: int,
init_width: float = 1.0,
dtype=jnp.float32,
) -> Tuple[PRNGKey, Array]:
"""Initialize a set of plausible initial electron positions.
For each ch... | f9d787bcf24010a81789b3f6f2d65f7ea2582a95 | 3,637,435 |
def urlencode(query, *args, **kwargs):
"""Handle nested form-data queries and serialize them appropriately.
There are times when a website expects a nested form data query to be sent
but, the standard library's urlencode function does not appropriately
handle the nested structures. In that case, you ne... | e73d532d7d4bc6b2534ec2e9224e2ef91074b94e | 3,637,436 |
import scipy
def zca_whiten_np(images, epsilon=1e-6):
"""Whitening the images using numpy/scipy.
Stolen from https://github.com/keras-team/keras-preprocessing/blob/master/keras_preprocessing/image/image_data_generator.py
A good answer on ZCA vs. PCA: https://stats.stackexchange.com/questions/117427/what... | 7937cfc928e5eb04166d789bbdb58f82bd4ecc35 | 3,637,437 |
def set_kernel(kernel, **kwargs):
"""kernelsを指定する
Parameters
----------
kernel : str or :obj:`gpytorch.kernels`
使用するカーネル関数を指定する
基本はstrで指定されることを想定しているものの、自作のカーネル関数を入力することも可能
**kwargs : dict
カーネル関数に渡す設定
Returns
-------
out : :obj:`gpytorch.kernels`
カーネル... | 6ac8e4655ea775233e4470200893039c53e2d3d6 | 3,637,438 |
def holding_period_return(multivariate_df: pd.DataFrame, lag: int, ending_lag: int = 0, skip_nan: bool = False):
"""
Calculate the rolling holding period return for each column
Holding period return for stock = Price(t - ending_lag) / Price(t - lag) - 1
:param multivariate_df: DataFrame
:param lag: ... | d0470a36704d11865323f1b07717f6d433ea59f5 | 3,637,439 |
def _unpack_var(var):
"""
Parses key : value pair from `var`
Parameters
----------
var : str
Entry from HEAD file
Returns
-------
name : str
Name of attribute
value : object
Value of attribute
Examples
--------
>>> var = "type = integer-attribut... | ea23bee3bdddda47c3ab608e41b086e5e8796bc8 | 3,637,440 |
import torch
def get_representation(keypoint_coordinates: torch.Tensor,
image: torch.Tensor,
feature_map: torch.Tensor) -> (torch.Tensor, torch.Tensor):
"""
:param keypoint_coordinates: Tensor of key-point coordinates in (N, 2/3)
:param image: Tensor of curre... | 0373f45121020b868dda2bd84dd650f2a398f635 | 3,637,442 |
async def async_setup(opp: OpenPeerPowerType, config: ConfigType):
"""Set up the System Health component."""
opp.components.websocket_api.async_register_command(handle_info)
return True | 993af39e4f1b59b535f800578df743d1dd27b925 | 3,637,443 |
import requests
def getSoup(url: str, ftrs: str = "html5lib") -> bsp:
"""
Function to extract soup from the url passed in, returns a bsp object.
"""
rspns = requests.get(url)
return bsp(rspns.content, ftrs) | ebd1d0914591b71b38e0977a4cdf86c964afb3c5 | 3,637,444 |
def _fit_HoRT(T_ref, HoRT_ref, a_low, a_high, T_mid):
"""Fit a[5] coefficient in a_low and a_high attributes given the
dimensionless enthalpy
Parameters
----------
T_ref : float
Reference temperature in K
HoRT_ref : float
Reference dimensionless enthalpy
... | a849ef860dd68f32fef012149eb1fc2a594b2691 | 3,637,445 |
import glob
def get_q_k_size(database,elph_save):
"""
Get number of k and q points in the (IBZ) grids
"""
# kpoints
db = Dataset(database+"/SAVE/ns.db1")
Nk = len(db.variables['K-POINTS'][:].T)
db.close()
# qpoints
Nq = len(glob('./elph_dir/s.dbph_0*'))
return Nq,Nk | 7ed941d40e90ba81e505e8f93e135b7cce256167 | 3,637,446 |
def false(feedback, msg, comment, alias_used="false"):
"""
Marks a post as a false positive
:param feedback:
:param msg:
:return: String
"""
post_data = get_report_data(msg)
if not post_data:
raise CmdException("That message is not a report.")
post_url, owner_url = post_data... | 6b894eaa3debbdb8029cd6cd9ab5074f63622b5f | 3,637,447 |
def so3_to_SO3_(so3mat):
"""
Convert so(3) to SO(3)
Parameters
----------
so3mat (tf.Tensor):
so(3)
N x 3 x 3
Returns
------
ret (tf.Tensor):
SO(3)
N x 3 x 3
"""
omgtheta = so3_to_vec(so3mat)
c_1 = near_zero(tf.norm(omgtheta,axis=1))
c_2 ... | 2c8b6e857acb9943e519b0604d9ef47ef80329ab | 3,637,448 |
from typing import Dict
def find_worst_offenders(
all_resource_type_stats: Dict[str, ResourceTypeStats],
version: str,
) -> Dict[str, ResourceTypeStats]:
"""
Finds the resource types with the worst polymorphing and nesting
"""
# find the resource type with the most number of shapes
most_po... | 73a4a8ce2b303f75be544753fde2f74fce8a39b1 | 3,637,449 |
def optimize(nn_last_layer, correct_label, learning_rate, num_classes):
"""
Build the TensorFLow loss and optimizer operations.
:param nn_last_layer: TF Tensor of the last layer in the neural network
:param correct_label: TF Placeholder for the correct label image
:param learning_rate: TF Placeholde... | 587ed3efcc1eb3e8c910a66590e8afd79f80627e | 3,637,450 |
async def all_pairs(factory, weth, dai, wbtc, paused_token):
"""all_pairs set up a very specific arbitrage opportunity.
We want a opportunity that requires less then 2 WETH and provides significant profit as
to be able to separate profit from gas costs. If the numbers do not make sense it is because
th... | be03091afbcc95b6f4a46436881525f6cd4fdb63 | 3,637,451 |
def meeting_point(a, b, window=100, start=0):
"""
Determines the point where the moving average of a meets that of b
"""
cva = np.convolve(a, np.ones((window,))/window, mode='valid')
cvb = np.convolve(b, np.ones((window,))/window, mode='valid')
for x, (val_a, val_b) in enumerate(zip(cva, cvb))... | aa97ab0baed01f36e44dda4f21f6a1b2de3b86d9 | 3,637,452 |
from typing import Dict
from re import T
from typing import Optional
def fixed_dictionaries(
mapping: Dict[T, SearchStrategy[Ex]],
*,
optional: Optional[Dict[T, SearchStrategy[Ex]]] = None,
) -> SearchStrategy[Dict[T, Ex]]:
"""Generates a dictionary of the same type as mapping with a fixed set of
... | b37429efc30989eb180dc39849cfcc2d719af6b1 | 3,637,453 |
def estimate_R0(model, curves: pd.DataFrame, method="OLS", **kwargs) -> ValueStd:
"""
Estimate R0 from epidemic curves and model.
{args}
Returns:
A ValueStd with R0 and its associated standard deviation.
See Also:
naive_R0
OLS_R0
"""
return METHODS_R0[method](model... | 0b2443a2af250871afba542c77d73632dc005dc1 | 3,637,454 |
def get_bone_list(armature, layer_list):
"""Get Bone name List of selected layers"""
ret = []
for bone in armature.data.bones:
if is_valid_layer(bone.layers, layer_list):
ret.append(bone.name)
return ret | 1ed2c4030e962c0bc88119c5e5a18e7e12b49f04 | 3,637,455 |
def clean_packages_list(packages):
"""
Remove comments from the package list
"""
lines = []
for line in packages:
if not line.startswith("#"):
lines.append(line)
return lines | a6c942f9b90c8f6c610ba0b57728f3da48f35ded | 3,637,456 |
import random
def IndividualBuilder(size, possList, probList):
"""
Args:
size (int) - the list size to be created
PossArr - a list of the possible mutations
types (mutation, deletion,...)
ProbArr - a list of the probibilities of the possible
mutations occuring.
... | 055d582fffbc2e13a25a17012831c098fc89330d | 3,637,457 |
def getConfigId(dsn_string, test_data):
"""Returns the integer ID of the configuration name used in this run."""
# If we have not already done so, we query the local DB for the ID
# matching this sqlbench config name. If none is there, we insert
# a new record in the bench_config table and return the newly ge... | 2f0f4581f36e1e50bf5f006ea950b2611c194aeb | 3,637,458 |
def invert_contactmap(cmap):
"""Method to invert a contact map
:param :py:obj:`~conkit.core.ContactMap` cmap: the contact map of interest
:returns: and inverted_cmap: the contact map corresponding with the inverted sequence (1-res_seq) \
(:py:obj:`~conkit.core.ContactMap`)
"""
inverted_cmap = ... | 6b13bbe75b1184854a2686c12c6ae5f824383cdd | 3,637,460 |
def indexes_with_respect_to_y(Y):
"""
Checks Y and returns indexes with respect to the groups.
Parameters
----------
Y : numpy array like of one single output.
Corresponding to a categorical variable.
Returns
-------
List of indexes corresponding to each group.
"""
catego... | b0ad9062916c3c7d76acf7e699b6a7e7798ac054 | 3,637,461 |
def rrotate(x, disp):
"""Rotate x's bits to the right by disp."""
if disp == 0:
return x
elif disp < 0:
return lrotate(x, -disp)
disp &= 31
x = trim(x)
return trim((x >> disp) | (x << (32 - disp))) | 9ac6a4504de42a7f9f280ae169d523af6a228ce1 | 3,637,462 |
import logging
import copy
def search_for_start ( r, X, w0, applythreshold, hf0, pm=(.85,.93,1.,1.07,1.15), storeopt=False, modulation=False, doublemodulation=False):
"""Search for starting values
:Parameters:
*d*
data set
*w0*
coarse starting values
*pm*
... | d9a28ff06992624a3d60fcbe6e7f483281c7a12d | 3,637,465 |
def point_sample(input, points, align_corners=False, **kwargs):
"""
A wrapper around :func:`grid_sample` to support 3D point_coords tensors
Unlike :func:`torch.nn.functional.grid_sample` it assumes point_coords to
lie inside ``[0, 1] x [0, 1]`` square.
Args:
input (Tensor): Feature map, sha... | 31e5d19c1eff260d337b4eee65b4eed08a1e070b | 3,637,466 |
from typing import Any
import time
def login_render(auth_url: str) -> Any:
"""Return login page.
Arguments:
auth_url {str} -- Link to last.fm authorization page.
"""
return render_template("login.html", auth_url=auth_url, timestamp=time()) | a1569ac51d6ce38feba6d263e03404a4af9ee566 | 3,637,468 |
def get_genres_from_games(games, their_games):
"""
From the games we will get the same genres
"""
genres = set()
for d in games:
n = d['id']
if n in their_games:
genres.add(d['Genre'])
return genres | 27bbf3c5ba40c6443e12b4119943c40879ceb622 | 3,637,471 |
def webfinger(request):
"""
A thin wrapper around Bridgy Fed's implementation of WebFinger.
In most cases, this view simply redirects to the same endpoint at Bridgy.
However, Bridgy does not support the ``mailto:`` and ``xmpp:`` resource
schemes - quite reasonably, since there's no possible way to ... | 86b9f28cc49fd3a253ad916a426385394ae8fed3 | 3,637,472 |
def inflection_points(points, rise_axis, run_axis):
"""
Find the list of vertices that preceed inflection points in a curve. The
curve is differentiated with respect to the coordinate system defined by
`rise_axis` and `run_axis`.
Interestingly, `lambda x: 2*x + 1` should have no inflection points, ... | c0044d0a46bc286c0b827fd557bdba74a07812a0 | 3,637,475 |
def compile(raw_model):
"""Compile a raw model.
Parameters
----------
raw_model : list of dict
A raw GPTC model.
Returns
-------
dict
A compiled GPTC model.
"""
categories = {}
for portion in raw_model:
text = gptc.tokenizer.tokenize(portion['text'])
... | 87607fdccac51acf367f0d7722b20ee8795f866b | 3,637,476 |
def get_elements_html_by_attribute(*args, **kwargs):
"""Return the html of the tag with the specified attribute in the passed HTML document"""
return [whole for _, whole in get_elements_text_and_html_by_attribute(*args, **kwargs)] | 726a3a6b8753fd6513f4860393076c9e3298a390 | 3,637,477 |
def patched_requests_mocker(requests_mock):
"""
This function mocks various PANOS API responses so we can accurately test the instance
"""
base_url = "{}:{}/api/".format(integration_params['server'], integration_params['port'])
# Version information
mock_version_xml = """
<response status = ... | 828425e11e38468ab2aacef397b6375c0ec65d6a | 3,637,478 |
def validate(model, model_name: str, dataloader_valid, class_weights, epoch: int,
validations_dir: str, save_oof=True):
"""
Validate model at the epoch end
Input:
model: current model
dataloader_valid: dataloader for the validation fold
device: CUDA or CPU
... | d9e1b172b9c28f30b80e43969cb39b4b1054a4b6 | 3,637,479 |
def shared_empty(dim=2, dtype=None):
"""
Shortcut to create an empty Theano shared variable with
the specified number of dimensions.
"""
if dtype is None:
dtype = theano.config.floatX
shp = tuple([1] * dim)
return theano.shared(np.zeros(shp, dtype=dtype)) | d199a069b4a47eeb97f2a87b6c35ed797764eb9f | 3,637,480 |
def add_kwds(dictionary, key, value):
"""
A simple helper function to initialize our dictionary if it is None and then add in a single keyword if
the value is not None.
It doesn't add any keywords at all if passed value==None.
Parameters
----------
dictionary: dict (or None)
A dictio... | 96aa104f86e521e419d51096b6c1f86e4b506c57 | 3,637,481 |
def _get_cindex(circ, name, index):
"""
Find the classical bit index.
Args:
circ: The Qiskit QuantumCircuit in question
name: The name of the classical register
index: The qubit's relative index inside the register
Returns:
The classical bit's absolute index if all regi... | 340105a2ddfe5fb2527171a7592390c9dd2937e5 | 3,637,483 |
def get_bin(pdf: str) -> str:
"""
Get the bins of the pdf, e.g. './00/02/Br_J_Cancer_1977_Jan_35(1)_78-86.tar.gz'
returns '00/02'.
"""
parts = pdf.split('/')
return parts[-3] + '/' + parts[-2] + '/' | a1e25162b8a353f508667ccb4fc750e51fcf611d | 3,637,484 |
def burkert_density(r, r_s, rho_o):
"""
Burkert dark matter density profile
"""
x = r / r_s
density = rho_o / ( (x) * (1.0 + x)**2)
return density.to('g/cm**3') | 8293a62b6c52c65e7c5fe7c676fd3807f301e40b | 3,637,486 |
def send_file(path):
"""
Route for file downloads
"""
# If the document path has a tilde, expand it
path_prefix = expanduser(DOCUMENT_DIRECTORY_PATH)
return send_from_directory(path_prefix, path) | 9c11acd930c7bc3851421e70b4822ac8efbc7c05 | 3,637,487 |
def locations__single(request, location_id: int):
"""
Renders the locations page, when a single location has been selected.
"""
context = {'geolocation': request.session.get('geolocation'),
'location_error': request.session.get('location_error')}
try:
location_id = validat... | 0b7ab51fe021a677ca87aecde1a9981095ef56ff | 3,637,488 |
def page_not_found(e):
"""
Application wide 404 error handler
"""
return render_template('404.html',
base_template=appbuilder.base_template,
appbuilder=appbuilder), 404 | a1c146b4d782a35d45ec0f351d12e09cdff9be1a | 3,637,489 |
def licols(A, tol=1e-10):
"""
Extracts a linearly independent set of columns from a given matrix A.
Solution found at https://nl.mathworks.com/matlabcentral/answers/108835-how-to-get-only-linearly-independent-rows-in-a-matrix-or-to-remove-linear-dependency-b-w-rows-in-a-m
:param A: matrix
:param to... | 96c15e65c7e12dc86342642c2b6cc1e147430cb4 | 3,637,490 |
def area_description(area,theory_expt):
""" Generate plain-language name of research area from database codes.
"""
area_name_by_area = {
"As" : "Astrophysics",
"BP" : "Biophysics",
"CM" : "Condensed matter",
"HE" : "High energy",
"NS" : "Network science",
... | d7743c2d80d9a74dd6a24f735b7c0a389eb36468 | 3,637,492 |
def parse_username_password_hostname(remote_url):
"""
Parse a command line string and return username, password, remote hostname and remote path.
:param remote_url: A command line string.
:return: A tuple, containing username, password, remote hostname and remote path.
"""
assert remote_url
... | 50410ad87865559af84b83ab6bdfae19e536791d | 3,637,493 |
def _random_inverse_gaussian_no_gradient(shape, loc, concentration, seed):
"""Sample from Inverse Gaussian distribution."""
# See https://en.wikipedia.org/wiki/Inverse_Gaussian_distribution or
# https://www.jstor.org/stable/2683801
dtype = dtype_util.common_dtype([loc, concentration], tf.float32)
concentratio... | 6ce80d87c4350e7816fcd50956639906bdf7244e | 3,637,494 |
from pathlib import Path
def resolve(path):
"""
fully resolve a path:
resolve env vars ($HOME etc.) -> expand user (~) -> make absolute
Returns:
pathlib.Path: resolved absolute path
"""
return Path(expandvars(str(path))).expanduser().resolve() | cc75751421206450f551617d558ec000d54ba54f | 3,637,496 |
def sas_2J1x_x(x):
"""return 2*J1(x)/x"""
if np.isscalar(x):
retvalue = 2*sas_J1(x)/x if x != 0 else 1.
else:
with np.errstate(all='ignore'):
retvalue = 2*sas_J1(x)/x
retvalue[x == 0] = 1.
return retvalue | 286dfb2c4df4120ff232e347f2381023a0bdaf40 | 3,637,497 |
def get_cross_matrix(vec: ndarray) -> ndarray:
"""Get the matrix equivalent of cross product. S() in (10.68)
cross_product_matrix(vec1)@vec2 == np.cross(vec1, vec2)
Hint: see (10.5)
Args:
vec (ndarray[3]): vector
Returns:
S (ndarray[3,3]): cross product matrix equivalent
"""
... | 2e95611fbe2bbd5ae6a94e490345e0d19c3a5e61 | 3,637,498 |
from typing import Tuple
from typing import Set
def apply_proteomics_elastic_relaxation(
original_model: Model,
objective_rule: Objective_rule = Objective_rule.MIN_ELASTIC_SUM_OBJECTIVE,
) -> Tuple[Model, Set]:
"""Relax the problem by relaxing the protein concentration constraints.
The relaxed proble... | d2dd9fa8f179535cf1a8e4dcb9abb8fbf1ce5633 | 3,637,499 |
import ast
def skip_node(node):
"""Whether to skip a step in the traceback based on ast node type."""
return isinstance(node, (ast.If, ast.While, ast.For)) | 2406d02190a4dccb3d1f5d743a742f82c97f6541 | 3,637,500 |
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