content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def showCatalog():
"""This showCatalog handler will diplay the home page for both a user not
logged in and one for a logged in user.
"""
categories = session.query(Category).order_by(asc(Category.name))
# Limit the query to a maximum of 10 and order by the most recent
# items added, which is id... | e2a50c7478536fe573b6f7860e0976de3a832692 | 3,633,331 |
def is_fill_compute_seq(seq):
"""Test whether *seq* can be converted to a FillComputeSeq.
True only if it is a FillCompute element
or contains at least one such,
and it is not a Source sequence.
"""
if is_source(seq):
return False
is_fcseq = False
try:
is_fcseq = any(map... | f6cca52b2ed7065ae950eca48071120c83a735bc | 3,633,332 |
def upload_model(uploadfile, name=None): # noqa: E501
"""upload_model
# noqa: E501
:param uploadfile: The model YAML file to upload. Can be a GZip-compressed TAR file (.tgz, .tar.gz) or a YAML file (.yaml, .yml). Maximum size is 32MB.
:type uploadfile: werkzeug.datastructures.FileStorage
:param ... | 95a759bc6d5cc806a8a8df1945816275784ab132 | 3,633,333 |
from mpl_toolkits.mplot3d import Axes3D
import mcubes
def visual_callback_3d(fig=None, plot_each=1):
"""
Returns a callback than can be passed as the argument `iter_callback`
of `morphological_geodesic_active_contour` and
`morphological_chan_vese` for visualizing the evolution
of the levelsets. On... | 1f69691a983f9afabbe53e761e95138a1aa64e40 | 3,633,334 |
def _erfint(x):
"""
Integral of the error function.
Parameters
----------
x : float or array
Argument.
Returns
-------
float or array
Integral of the error function.
"""
return x * erf(x) - 1.0/np.sqrt(np.pi) * (1.0-np.exp(-x**2)) | e397f62fb35caf5d71eaebd3eb9dc8ce0ba5c9d5 | 3,633,335 |
from typing import Optional
from typing import Union
def zeros(shape: Optional[Union[int, tuple, list]] = None) -> 'ArrayInterval':
"""
Instantiate an `ArrayInterval` filled with zeros.
Note: The difference from numpy is that the argument shape is optional.
When shape is None, some operations a... | 2d6348e327798b3019c6fd2d42827c64660cad02 | 3,633,337 |
def anova_total_mean_square(Ns, means, sigmas):
"""
This function performs an average over multiple sets of observations, each with its own standard deviation.
For example: 5 simulations compute RMSDs+-Sigma of the same protein. What is the aggregate?
See: http://www.burtonsys.com/climate/composite_stan... | b3cc0aa7fd66521f6692bd10c66b1e7b00e59566 | 3,633,338 |
def compute_lsb(n_bits, fsr_min, fsr_max, half_bit=None):
"""
Computes the least significant bit (LSB) magnitude in the stage MDAC and
sub-ADC to achieve a desired full scale range (FSR). The input FSR and
output FSR are assumed to be the same so only one value is returned.
:param n_bits: Number of... | 03520c71de04e654841c47c40a109431d315163d | 3,633,339 |
def proximity_matrix(rf, X, normalize=True):
"""
Calculate proximity matrix
:param rf:
:param X:
:param normalize:
:return:
"""
leaves = rf.apply(X)
n_trees = leaves.shape[1]
prox_mat = np.zeros((leaves.shape[0], leaves.shape[0]))
for i in range(n_trees):
a = leaves... | 781c08f242e52afa7430761124a344456c0efec1 | 3,633,340 |
def upload_to_s3_v2(local_path: str, bucket_name: str, object_name: str):
"""
path_output: local dir file path
bucket_name: name of s3 bucket
key_path: key path + file name = object name
"""
s3 = boto3.client("s3")
response = s3.upload_file(local_path, bucket_name, object_name)
return re... | 844b1c07daeb44f49e1071516da0802d843d4790 | 3,633,341 |
def marks(category, mark=None, category_marks=None, public=False):
"""Assign marks to a test or suite of tests, grouped by a category."""
def decorator(test_item):
if mark is None and category_marks is None:
raise ValueError("One of mark or category_marks must be defined")
test_item... | 2d47a8df4f610dbc081dd57fce169e2f89b88ca4 | 3,633,342 |
import secrets
def get_random_ua():
"""return a random user-agent string from file"""
# stop condition, file does not exists, not readable...
# + file operation
with open('headers.txt') as hbuffer:
all = hbuffer.readlines()
return secrets.choice(all).strip() | 0d6a924c07bbad2398966bed590bf3307f5c475d | 3,633,343 |
def is_nondecreasing(arr):
""" Returns true if the sequence is non-decreasing. """
return all([x <= y for x, y in zip(arr, arr[1:])]) | 593ac54669ef217e258380bf41ce067935ee53f0 | 3,633,344 |
def underscore_to_camelcase(value):
"""
Converts underscore notation (something_named_this) to camelcase notation (somethingNamedThis)
>>> underscore_to_camelcase('country_code')
'countryCode'
>>> underscore_to_camelcase('country')
'country'
>>> underscore_to_camelcase('price_GBP')
'pri... | 94bb5c007d3b50112c62ca9b3e97c5bf4f155fff | 3,633,345 |
def findCenter(S):
"""Find the approximate center atom of a structure.
The center of the structure is the atom closest to (0.5, 0.5, 0.5)
Returns the index of the atom.
"""
best = -1
bestd = len(S)
center = [0.5, 0.5, 0.5] # the cannonical center
for i in range(len(S)):
d = S.... | 634945a5560b3791f3835f3da090decd1b06b933 | 3,633,346 |
def add_noise(rots, level):
"""adds random noise to a rotation matrix."""
noised_rots = [[np.random.uniform(-level,level,4)]*23]*rots.shape[0]
noised_rots = Quaternions(np.array(noised_rots))
return rots+noised_rots | 8886f11b90a2d0098b4776100ee9834d433012fb | 3,633,347 |
def content_tree_update(request):
"""Returns all content of a given contenttree."""
assert request.contenttree.patched, "contenttree should be patched here..."
# SANITIZE JSON DATA
jsoncontent = request.json_body['content']
data = remove_unvalidated_fields(jsoncontent, peerreview_update_schema)
... | dcfc1932aa9fec431e138f205a143b792b6130f7 | 3,633,348 |
def compute_overlap_region(db_ref, db_new):
"""
Computes the overlapping/shared region between two images.
Outputs:
- Corner coordinates of the overlapping region in the SRS
- Corresponding pixel indexes in both input images
"""
cornerCoord_ref = gdal.Info(db_ref, format='json')['co... | 664f1825c75c0b33d0b0c5ba4686d132790ad363 | 3,633,349 |
from typing import List
import math
def _calculate_team_size_score(
projects: List[dict], assignments: List[AssignmentTuple], project: dict, student: dict
) -> int:
"""Calculates the weighted score based on how far away from the average team size this project would
be after assigning the student
A... | 47fcb0ea3feb637b558e6df10abd0aa993dbf965 | 3,633,350 |
import string
def encode(data):
""" Encodes a string to the 'cstring' encoding supported by the replay DTD.
Args:
data: string value to be encoded
Returns:
String containing the encoded value
Raises:
None
"""
chars = string.letters + string.digits + " ?!:."
retur... | 9fc3482c53eed42678aa3c7cbbf915c85b28cc68 | 3,633,351 |
import types
from typing import Dict
from typing import Any
from typing import List
def gen_frame_symbol(
data: types.PulseInstruction, formatter: Dict[str, Any], device: device_info.DrawerBackendInfo
) -> List[drawings.TextData]:
"""Generate a frame change symbol with instruction meta data from provided fram... | 8b38222cd294f42eb58dfcc36b10361ce7869a81 | 3,633,352 |
def leanlauncher_download_version(version=LATEST_VERSION, path=DEFAULT_INSTALL_PATH):
"""
Installs the specified version of Minecraft to the specified path
Parameters:
version (str): the version of Minecraft to be installed, by default the latest
path (str): the path to install Minecraft to, by default ~... | 35193ec3ca5d1ad1b23b84d35fec002997bb948e | 3,633,353 |
def Weierstrass_Enneper(f, g, z, imag_unit=1j):
"""
Compute the Weierstrass Enneper parametrization for given 'Weierstrass data'.
:param sympy expression f: h'/g, with h the height function
:param sympy expression g: Gauss map.
:param sympy variable z: Complex variable.
:param imag_unit: Represe... | a47648e52600fd5fff37fb0ee7477b67c587ad0b | 3,633,354 |
def human_size(size_bytes):
"""
format a size in bytes into a 'human' file size, e.g. B, KB, MB, GB, TB, PB
Note that bytes will be reported in whole numbers but KB and above will have
greater precision. e.g. 43 B, 443 KB, 4.3 MB, 4.43 GB, etc
"""
suffixes_table = [('B', 0), ('KB', 1), ('MB', ... | d3489ee85c419711d82e35003426ef2915143c17 | 3,633,356 |
def html_color_to_rgba(html_colour, alpha):
"""
:param html_colour: Colour string like FF0088
:param alpha: Alpha value (opacity)
:return: RGBA semitransparent version of colour for use in css
"""
html_colour = html_colour.upper()
if html_colour[0] == '#':
html_colour = html_colour[1... | 4f28938aa89d62198cc3052a480e0e0744560a79 | 3,633,357 |
from typing import OrderedDict
def _assign_category_colors(uses, cmap, use_colors=None, assigned_colors=None):
"""Set a dictionary of nice colors for the use blocks.
Options allow specifing pre-defined elements for some categories."""
use_colors = OrderedDict() if use_colors is None else use_colors
a... | 085d0ca707990c84cd51464ee8f65f90500b7060 | 3,633,358 |
def GetClientContext(client_id, token):
"""Get context for the given client id.
Get platform, os release, and arch contexts for the client.
Args:
client_id: The client_id of the host to use.
token: Token to use for access.
Returns:
array of client_context strings
"""
client_context = []
clie... | 3ecddfeb58e99d06951aab4fe359bc1291b43a2a | 3,633,359 |
import math
def calculate_slope_intercept(line):
"""
Calculating slope nd intercept for a line
"""
for x1, y1, x2, y2 in line:
if x2-x1 == 0:
return math.inf, 0
slope = (y2-y1)/(x2-x1)
intercept = y1 - slope * x1
return slope, intercept | e21ff81a36cef7a995a98f7adf0302e8397a8139 | 3,633,360 |
def get_welcome_response():
""" If we wanted to initialize the session to have some attributes we could
add those here
"""
session_attributes = {}
card_title = "Welcome"
speech_output = "I'm the Magic Conch Shell. Ask me a question"
# If the user either does not reply to the welcome messag... | 8a900efd3ef7129c1a9ff408e49591945dad83a1 | 3,633,361 |
from typing import Optional
def rmcgs(A: np.ndarray, m: Optional[int] = None, r: Optional[int] = None) -> np.ndarray:
"""
Compute the product: B <- G * S * A where G has size m * r and elements from the standard
normal distribution, rescaled by 1/sqrt(m), and S is a CountSketch of size r * n. The matrix
... | 25325d1b2c75a07468fdce63fb5481da99c93105 | 3,633,362 |
def start_multi_svf():
"""
This is function for satrt multi SVF GUI
:return: result, details
"""
app.logger.info("Try to start multi SVF GUI for test")
cli_rest_port_list = []
svf_num = int(request.form.get("svf_num"))
try:
cli_rest_port_list = StartMultiSvf(svf_num=svf_num, log... | 1dd3585e5fcfa96d225645d382ee5ab064bc4073 | 3,633,363 |
import glob
def get_files_by_pattern(root, pattern='a/b/*.ext', strip_root=False):
"""Optionally to only return matched sub paths."""
# Get the abspath of each directory images.
ret = glob.glob(osp.join(root, pattern))
# exclude the root str, so the ret is spec['patterns']. such as ['images/train/*.jp... | 905e4c4d08d228074a8036cdf5511f9eb7330f8c | 3,633,364 |
import torch
def gumbel_softmax(logits, temperature=1, hard=False):
"""
ST-gumple-softmax
input: [*, n_class]
return: flatten --> [*, n_class] an one-hot vector
"""
y = gumbel_softmax_sample(logits, temperature)
if not hard:
return y
shape = y.size()
_, ind = y.max(dim=-1... | 4ce2b64115c4a4ce87677aa99e0422c00524c5d3 | 3,633,365 |
def _load_augmentation_aug_all():
""" Load image augmentation model """
def sometimes(aug):
return iaa.Sometimes(0.5, aug)
return iaa.Sequential(
[
# apply the following augmenters to most images
iaa.Fliplr(0.5), # horizontally flip 50% of all images
ia... | e39a08f0166d8a6a379427a895b196891bf70fe1 | 3,633,366 |
import logging
import traceback
def zk_get_mq_servers(zookeeper_servers, logger = logging.getLogger(__name__)):
"""
Get list of mq servers from zookeeper
:param zookeeper_servers: list of zookeeper servers
:param logger: logger to use
:return: list of mq servers or None
"""
mq_servers = No... | 2201ac305ea1b44fe8baa0582bfc84bf39472dbe | 3,633,367 |
from datetime import datetime
def _make_todays_date() -> str:
""" build today's date as a standard format """
return datetime.now().strftime("%a %d-%b") | fdb9bc420689081586ac19fe91a17ea871576d59 | 3,633,369 |
import re
def add_review_suggestion_flags(df,
text_col,
result_col='result_binary'):
"""
attempt to add on some logical "manual review suggested" flags onto cases to reduce false positive/negative classifications. currently
flags cases w... | e2083d65f54b82dd9eba19b6b2d32806e2cd086d | 3,633,370 |
def create3DMatrix(data, trialTable, events, trialList, trialDur, fs, normalize, baselineDur=0.1):
"""
"""
trials = trialTable.copy()
trials = trials[trials['trialNum'].isin(trialList)]
totalTrialNum = np.max(trials['trialNum'])
m = trials.shape[0]
print m, totalTrialNum
electrodeNumber... | 1627f506a03bb7f07c30c6c70581ac40bd64d7fc | 3,633,371 |
def followed_list(username):
"""关注列表
"""
current_user = models.get_current_user()
user = models.get_user(username=username)
page = request.args.get('page', 1, type=int)
followed_list = user.followed.paginate(page, error_out=False)
user_list = [i.followed for i in followed_list.items]
ret... | 5634ce5e7fc6b344f7ad2b3461e9f294cee225d3 | 3,633,372 |
def add_edge_degree(graph, k=3):
"""
Add k edges to defend based on top edge degree centrality entries :cite:`tong2012gelling`.
:param graph: an undirected NetworkX graph
:param k: number of edges to add
:return: a list of edges to add
"""
info = defaultdict(list)
info['added'] = get_c... | eded75ffc4eabe155124fe95023694df367f3d01 | 3,633,373 |
def number_of_fishers():
""" Prompt the user for the number of fishermen entering the draw."""
try:
number = int(input("How many fishermen will enter the competition: "))
return number
except ValueError:
print("Please enter an integer for the number of competing fishermen") | bd3ff25865d67851c8a1742a8cfa808a317716f0 | 3,633,374 |
def plot_histogram(df, x, bins, xlabel=None, ylabel=None, title=None, figsize=(8, 5)):
"""
"""
fig = plt.figure(figsize=figsize)
ax = fig.gca()
ax.hist(df[x], bins=bins, color='#8d1a93')
ax.set_xlabel(xlabel, fontsize=16)
ax.set_ylabel(ylabel, fontsize=16)
ax.set_title(title, fontsize ... | 42801361386edea3065974bdca2a589be0b964ef | 3,633,375 |
def pygmo_gaco(
criterion,
x,
lower_bounds,
upper_bounds,
*,
population_size=None,
batch_evaluator=None,
n_cores=1,
seed=None,
discard_start_params=False,
#
stopping_max_iterations=STOPPING_MAX_ITERATIONS_GENETIC,
kernel_size=63,
speed_parameter_q=1.0,
oracle=... | f8cf4e423b928393e4c028412da4f302376fb248 | 3,633,376 |
def get_project_by_id(project_id: str) -> Project:
"""
Get a project by its project_id, with project model and project data joined.
:param project_id: project id of the project
:return: Project with the project id
"""
query = (
Project.select(Project, ProjectModel, ProjectData)
... | 2a8986c8e2541f43d30bee2cb1bcac14df68b716 | 3,633,377 |
def hist_similarity(image_1, image_2):
"""color hist based image similarity
@param image_1: np.array(the first input image)
@param image_2: np.array(the second input image)
@return similarity: float(range from [0,1], the bigger the more similar)
"""
if image_1.ndim == 2 and image_2.ndim == ... | 76358cff7b3a33f44fecefd289805a1fea88e1c4 | 3,633,378 |
def slotter_obj():
""" Return basic slotter object """
return Slotter() | f4b8805c8ca26bfc22da79b49a9c287c35428f86 | 3,633,379 |
def gaussian(wavelength, w, sigma, amp=1., norm=True):
"""
Computes a gaussian for a given central wavelength, sigma and amp
.. math::
G = \\frac{A}{\sigma \sqrt{2 \pi}} \exp{\left( \\frac{ (w - w_0)^2 }{2 \sigma^2 } \\right) }
Args:
wavelength (np.ndarray): wavelength array to cal... | 7e757691fbe27641a4cfd983678dd0ccd2cbdfbd | 3,633,381 |
def summarize_samples(samples, run_parallel):
"""Back compatibility for existing pipelines. Should be replaced with summary when ready.
"""
return samples | 20c742e751f9ea1f783572f031fe144baf73293e | 3,633,382 |
def get_keywords(string):
"""Get keywords for a given string.
Args:
string (str): A string to get keywords for.
Returns:
(list): A list of keywords.
"""
keywords = string.lower().split(' ')
keywords = [x.strip() for x in keywords if x]
keywords = list(set(keywords))
retur... | 8d4e0781701dc3574583baf417c573967638e86f | 3,633,383 |
def calc_mass_loading_factor(OIII_results, OIII_error, hbeta_results, hbeta_error, hbeta_no_outflow_results, hbeta_no_outflow_error, statistical_results, z, header):
"""
Calculates the mass loading factor
eta = M_out/SFR
Using the calc_sfr.calc_sfr_koffee and the calc_mass_outflow_rate functions
... | 6504b328e749e98eb4b3612533701e562973d882 | 3,633,384 |
def truecircle(radius, rho):
"""Create a "true" circular mask with anti-aliasing.
Parameters
----------
samples : `int`, optional
number of samples in the square output array
radius : `float`, optional
radius of the shape in the square output array. radius=1 will fill the
rho :... | e721d99d99b89ca24637e20d9577b2725cc29525 | 3,633,386 |
def distancia(ponto1, ponto2):
"""
Calcula a distância entre dois pontos
"""
xdif = ponto2.getx() - ponto1.getx()
ydif = ponto2.gety() - ponto1.gety()
dif = (xdif**2 + ydif**2)**0.5
return dif | 36a980a1081133fb6496585c25cca5782ceef06d | 3,633,387 |
import time
def foo(x, sleep_time):
"""Dummy function for the tests"""
time.sleep(sleep_time)
return [{"type": "objective", "name": "objective", "value": x}] | 3d55a0b0776acec0badd10e38be724afc3015c2f | 3,633,388 |
def aug_ims(ims, fliplr=0, flipud=0, T=0):
"""Augment images with flips and transposition."""
ims_aug = np.array(ims, copy=True)
for i in range(len(ims_aug)):
if fliplr: # flip left right
ims_aug[i] = np.fliplr(ims_aug[i])
if flipud: # flip up down
ims_aug[i] = np.f... | 59f8c44f0efcb70c17f828351b0f59787c3dd677 | 3,633,389 |
def bt_search(btree, key):
"""基于二叉树查询操作"""
bt = btree
while bt is not None:
entry = bt.data
if key < entry.key:
bt = bt.left
elif key > entry.key:
bt = bt.right
else:
return entry.values
return None | 1b358087c10a4d0d6fe79b023340fafeafb81914 | 3,633,390 |
def make_reply(msgname, types, arguments, major):
"""Helper method for constructing a reply message from a list or tuple
Parameters
----------
msgname : str
Name of the reply message.
types : list of kattypes
The types of the reply message parameters (in order).
arguments : list... | 9c55089e1d6fe6b5a4345f444f2551a2c493f2e3 | 3,633,391 |
def empty_coord():
"""Return an empty coordinate tensor representing 1 residue-level pad character."""
coord_padding = np.zeros((NUM_COORDS_PER_RES, 3))
coord_padding[:] = GLOBAL_PAD_CHAR
return coord_padding | e4d8c4f24ebed354f5b083a4fc072e354c79a149 | 3,633,392 |
def grib_clone(msgid_src):
"""
@brief Create a copy of a message.
Create a copy of a given message (\em msgid_src) resulting in a new
message in memory (\em msgid_dest) identical to the original one.
\b Examples: \ref grib_clone.py "grib_clone.py"
@param msgid_src id of message to be cloned... | c01b3f626d11be8d218fdcd598e472c5fe748272 | 3,633,393 |
def layernorm(x, epsilon=1e-5, name='lnconv'):
"""Layer Normalization for conv. x must be [NCHW]"""
shape = x.get_shape().as_list()
with tf.variable_scope(name):
beta = tf.get_variable("beta", [1, shape[1], 1, 1], initializer=tf.constant_initializer(0.))
gamma = tf.get_variable("gamma", [1, ... | 9ae3bb3f6e0238de92f167bf45b05e3095541665 | 3,633,394 |
def create_graph_from_edges(edges):
"""
Create a graph from the `edges`
"""
G = nx.Graph()
for e in edges:
p1 = e[0]
p2 = e[1]
dist = LA.norm(np.array(p2) - np.array(p1))
G.add_edge(p1, p2, weight=dist)
return G | ac06c424fcfde720fbb4457c0baced0a0a41567d | 3,633,395 |
def far_field(frequency, radius, current, r, theta):
"""
Calculate the electric and magnetic far fields for a small circular loop.
:param r: The range to the field point (m).
:param theta: The angle to the field point (rad).
:param frequency: The operating frequency (Hz).
:param radius: The radi... | 29940432e3e4dbc427398a18e1d026d9e4c205c3 | 3,633,396 |
def rng_laplace(lambd=1, trunc=None):
"""
Generate random numbers from a Laplace distribution
Parameters
----------
lambd: float
The scale of the distribution
trunc: None, tuple
Specifies whether the distribution is truncated. If it's
not None then it must be a 2-tuple i... | d4ad9c23c5edef20babe59671e0464ef70ed74ae | 3,633,397 |
from typing import Sequence
from typing import Dict
from typing import List
def settings_to_connections(
settings: amicus.options.Configuration,
suffixes: Sequence[str]) -> Dict[str, List[str]]:
"""[summary]
Args:
settings (amicus.options.Configuration): [description]
suffixes (Sequen... | e2ec469014d5d26848d011feda717191ae8c452b | 3,633,398 |
def radec_from_pointing_object(pointing,
# default output in degrees
as_radians=False,
as_string=False):
"""Astropy object to ICRS format as strings"""
pnt_radec = pointing.transform_to(ICRS())
if as_string:
... | 8cdd5c6671ccfd12624df88dfdfce0f6e0f41856 | 3,633,399 |
def get_potentially_supported_ops():
"""Gets potentially supported ops.
Returns:
list of str for op names.
"""
supported_ops = _get_potentially_supported_ops()
op_names = [s.op for s in supported_ops]
return op_names | 4fcbc8fd8e10f28d7c10e8b7a9b9d9475ef6b4b6 | 3,633,400 |
def hard_sigmoid_me(input_, inplace: bool = False):
"""jit-scripted hard_sigmoid_me function"""
return HardSigmoidJitAutoFn.apply(input_) | 83cb4ed8802b5e6a275167c3a44e51719efe6212 | 3,633,401 |
def demoji(tokens):
"""
This function describes each emoji with a text that can be later used for vectorization and ML predictions
:param tokens:
:return:
"""
emoji_description = []
for token in tokens:
detect = emoji.demojize(token)
emoji_description.append(detect)
retur... | ab0a200fca87b3b1dc22dfd6bbf374d35d7b8b50 | 3,633,402 |
from pathlib import Path
async def get_journal_entries_by_permalink_handler(
journal_permalink: str = Path(...),
entry_permalink: str = Path(...),
db_session: Session = Depends(db.yield_connection_from_env),
) -> RedirectResponse:
"""
Get specific journal entry by short link.
"""
try:
... | d6dcd12b7db6a57f518621212fda72c769e671aa | 3,633,403 |
def ignore_pre_big_bang(run):
"""
Remove metrics before timestamp 0.
"""
return [m for m in run if m[TS] >= 0]
#return [m for m in run if m[TS] >= 0 and m[TS] < MAX_TIME] | b5ff1cf5f3f67618c31da1defa5a397fbea8f9bb | 3,633,404 |
def signUp():
"""Sign up a new user.
:field phone [int]: user phone number
:field name [str]: user name
:field password [str]: user password (will be encrypted)
:returns [dict]: newly created user's info with auth token
"""
phone = handler.parse('phone', int)
name = handler.parse('name'... | 0ad7bb71135e86fe3f4d3873e510d4bb375c061c | 3,633,405 |
def next_player(player,list_player_names,player_index,open_card,given_card):
""" returns the next player
>>> list_player_names=['Mark','John','Harry','Henry']
>>> player_index=0
>>> player='Mark'
>>> next_player(player,list_player_names,player_index,('A', '♥', 11))
'John'
>>> player_index=3
... | 7c56bd1983b60ed2177914cc4203462c9b83f375 | 3,633,406 |
def loss_function(image, idx, c, omega):
"""
:param last_image: the previous generated frame
:param outputs: Generated image
:return: The sum of the style and content loss
"""
outputs = extractor(image)
style_outputs = outputs["style"]
content_outputs = outputs["content"]
style_loss... | 2c6dee61f1af7e48be34cbc47501062a0dc7fa03 | 3,633,407 |
def bra(seq, dim=2):
"""
Produces a multiparticle bra state for a list or string,
where each element stands for state of the respective particle.
Parameters
----------
seq : str / list of ints or characters
Each element defines state of the respective particle.
(e.g. [1,1,0,1] o... | 1199ac8336963a785e2d258416733612dc7a5558 | 3,633,408 |
def rmse_diff(model_data, subj_data):
"""this rmse only consider diff"""
R = np.array(model_data)
D = np.array(subj_data)
r_DIFF = np.round([np.mean(R[0:2])-np.mean(R[2:4]),
R[0]-R[1], R[2]-R[3]], 4)
d_DIFF = np.round([np.mean(D[0:2]) - np.mean(D[2:4]),
D[0] - D[1... | f9b06e74a95663ad3036b7c658bb55880eba1a03 | 3,633,410 |
def preparation_time_in_minutes(number_of_layers: int) -> int:
"""Calculate the preparation time per layer.
.:param number_of_layers: int number of layers.
.:return: int time in minutes derived from 'PREPARATION_TIME'.
Function that takes the actual number of layer of the lasagna and
return how muc... | 3377dbb30ef7f1ffdd41680b7f270baffb81a2ef | 3,633,411 |
def eliminate(board, i, j):
"""
Propagates the effects of fixing a cell to the affected neighbors
within the same square and vertical and horizontal lines
"""
value = board[i][j][0]
# Horizontal propagation
for k in range(n):
if j!=k and value in board[i][k]:
board[i][k].... | dd860418a1e57ed2484c20cf5765d926a653c9ab | 3,633,412 |
def prep_tweet_body(tweet_obj, args, processed_text):
""" Format the incoming tweet
Args:
tweet_obj (dict): Tweet to preprocess.
args (list): Various datafields to append to the object.
0: subj_sent_check (bool): Check for subjectivity and sentiment.
1: subjectivity (num... | 9163d7bb10e3bb31849090d8ebfe4d00c19db2df | 3,633,413 |
import zlib
import time
import logging
def send_mfg_inspector_data(inspector_proto, credentials, destination_url,
payload_type):
"""Upload MfgEvent to steam_engine."""
envelope = guzzle_pb2.TestRunEnvelope()
envelope.payload = zlib.compress(inspector_proto.SerializeToString())
enve... | e809e49c2babe215c547960f60d6edca495601d4 | 3,633,414 |
def cache_lookup_only(key):
"""Turns a function into a fallback for a cache lookup.
Like the `cache` decorator, but never actually writes to the cache.
This is good for when a function already caches its return value
somewhere in its body, or for providing a default value for a value
that is suppos... | c142de5fb967860f8a5108d9b65cf21e32e9e674 | 3,633,415 |
def social_distancing_policy():
"""
Real Name: b'social distancing policy'
Original Eqn: b'1-PULSE(social distancing start, FINAL TIME-social distancing start+1)*social distancing effectiveness'
Units: b'dmnl'
Limits: (None, None)
Type: component
b''
"""
return 1 - functions.pulse(
... | 8cd71fb4cdfcffb11bb488beee6f33a5495e2eeb | 3,633,416 |
def mersenne_prime(n_max):
""" This is the description of the function 4 ~ Loves it + 3
Parameters
----------
n_max : int
for p up to n_max
Returns
-------
list
list of q
"""
primes = []
for a in range(0,n_max):
b = 2**a - 1
i... | 4aff17a7ed6c22b2817d0c37d1fb6b9dbaf243c2 | 3,633,417 |
def import_locus_intervals(path,
reference_genome='default',
skip_invalid_intervals=False,
contig_recoding=None,
**kwargs) -> Table:
"""Import a locus interval list as a :class:`.Table`.
Examples
---... | 3d27332ac4194f5f823bb234016d3941751e2072 | 3,633,418 |
def speech_tagging(test_data, model, tags):
"""
Inputs:
- test_data: (1*num_sentence) a list of sentences, each sentence is an object of line class
- model: an object of HMM class
Returns:
- tagging: (num_sentence*num_tagging) a 2D list of output tagging for each sentences on test_data
"""
tagging = []
######... | 8390fc6ff0b1008d50b248da0d348ac31b42626a | 3,633,419 |
def evaluate_if(hook_dict: dict, context: 'Context', append_hook_value: bool) -> bool:
"""Evaluate the when condition and return bool."""
if hook_dict.get('for', None) is not None and not append_hook_value:
# We qualify `if` conditions within for loop logic
return True
if hook_dict.get('if',... | b9d733568abf9d4bd7e7b7ed6e1ac43582728080 | 3,633,420 |
def find_vgg_layer(arch, target_layer_name):
"""Find vgg layer to calculate GradCAM and GradCAM++
Args:
arch: default torchvision densenet models
target_layer_name (str): the name of layer with its hierarchical information. please refer to usages below.
target_layer_name = 'features... | 97e578e061a592f5762313f4b7aecc42cda39cb7 | 3,633,421 |
def plain_bst():
"""Returns a plain binary search tree and a tuple of its nodes. The tree has the same structure as ref_bst."""
t = Tree.tree()
n1 = Tree.tree().treeNode(1)
n3 = Tree.tree().treeNode(3)
n4 = Tree.tree().treeNode(4)
n6 = Tree.tree().treeNode(6)
n7 = Tree.tree().treeNode(7)
... | 81667b4b122c88ec29146b5b739b44cbafda6c0f | 3,633,422 |
def test_confirm_name(monkeypatch, single_with_trials):
"""Test name must be confirmed for update"""
def incorrect_name(*args):
return "oops"
monkeypatch.setattr("builtins.input", incorrect_name)
execute("db set test_single_exp status=broken status=interrupted", assert_code=1)
def correc... | 9b9aee3fccda50d886d5c3362e5f3e19806a1929 | 3,633,423 |
import torch
def get_one_hot_reprs(batch_stds):
""" Get one-hot representation of batch ground-truth labels """
batch_size = batch_stds.size(0)
hist_size = batch_stds.size(1)
int_batch_stds = batch_stds.type(torch.cuda.LongTensor) if gpu else batch_stds.type(torch.LongTensor)
hot_batch_stds = tor... | 84dbf251039144b2bad5f461f40cec830d9331ca | 3,633,424 |
from typing import Tuple
def absolute_confusion_from_incidence(true_incidence, predicted_incidence) -> Tuple[float, float, float, float]:
"""Return the absolute number of true positives, true negatives, false positives and false negatives.
Parameters
----------
true_incidence: numpy.ndarray
t... | d235363a249523347087940d803e7dfbfc01a6de | 3,633,426 |
def test_every_iteration_model_updater_with_cost():
"""
Tests that the model updater can use a different attribute from loop_state as the training targets
"""
class MockModel(IModel):
def optimize(self):
pass
def set_data(self, X: np.ndarray, Y: np.ndarray):
sel... | 5775c0f2141f75cad46b143310f1fed64b508f37 | 3,633,427 |
def correlating_weight2_data(shots_discr, idx_qubit_ro, correlations, num_segments):
"""
"""
correlations_idx = [
[idx_qubit_ro.index(c[0]), idx_qubit_ro.index(c[1])] for c in correlations]
correl_discr = np.zeros((shots_discr.shape[0], len(correlations_idx)))
correl_avg = np.zeros((num_seg... | 4afb8c95f081e70fe50ed2b209e8e930ea0c4825 | 3,633,428 |
def create_test_network_6():
"""Aligned network with dropout for test.
The graph is similar to create_test_network_1(), except that the right branch
has dropout normalization.
Returns:
g: Tensorflow graph object (Graph proto).
"""
g = tf.Graph()
with g.as_default():
# An input test ima... | 820bea3f33b0f56d1d6148ee55764eb504bb977a | 3,633,429 |
import time
def timedcall(fn, *args):
"""
Run a function and measure execution time.
Arguments:
fn : function to be executed
args : arguments to function fn
Return:
dt : execution time
result : result of function
Usage example:
You want to time the function call "C = foo(A... | 60779c4f4b63796995d722133c304edf519ecd8f | 3,633,430 |
from pybind11_tests import ord_char, ord_char16, ord_char32, ord_wchar, wchar_size
def test_single_char_arguments():
"""Tests failures for passing invalid inputs to char-accepting functions"""
def toobig_message(r):
return "Character code point not in range({0:#x})".format(r)
toolong_message = "E... | dce3ef537fcc312d92b9f5ff5eb2ac00ff731a5e | 3,633,431 |
def tokuda_gap(i):
"""Returns the i^th Tokuda gap for Shellsort (starting with i=0).
The first 20 terms of the sequence are:
[1, 4, 9, 20, 46, 103, 233, 525, 1182, 2660, 5985, 13467, 30301, 68178, 153401, 345152, 776591, 1747331, 3931496, 8845866, ...]
h_i = ceil( (9*(9/4)**i-4)/5 ) for i>=0.
If ... | 710633e924cb6e31a866683b91da6489c781ba4a | 3,633,432 |
def trimf(x, p):
"""
Triangular membership function generator.
Parameters
----------
x : any sequence
Independent variable.
p: list of 4 values
lower than p[0] and higher than p[3] it returns 0
between p[1] and p[2] it returns 1
Returns
-------
y : 1d array
... | 7df01e466e55186c4d9e74466440077a0824eb47 | 3,633,434 |
def band_atom_orbitals_spin_polarized(
folder,
atom_orbital_dict,
output='band_atom_orbitals_sp.png',
display_order=None,
scale_factor=5,
color_list=None,
legend=True,
linewidth=0.75,
band_color='black',
unprojected_band_color='gray',
unprojected_linewidth=0.6,
fontsize=1... | 8ed107df12d8ef037116f0e87e8a62b6794ecbbb | 3,633,435 |
from typing import List
def _interpolate(mesh_1: Mesh, mesh_2: Mesh, steps: int = 1) -> List[Mesh]:
"""Interpolate two alike meshes.
This is suitable to fill the blank frames of an animated object
This function makes the assumption that same indices will be forming
the same triangle.
This functi... | 7209e00ac3cfc7996ec7e8cd1b0184b6ada40dea | 3,633,436 |
def dataset_service():
""" :rtype: dart.service.dataset.DatasetService """
return current_app.dart_context.get(DatasetService) | f2c8a3dfc39454449554930d2939cc45ed06f109 | 3,633,437 |
def calculate_concordance(aei_pvalues, eqtl_pvalues, threshold=0.05):
""" Returns
"""
eqtl_pvalues_i = np.nanargmin(eqtl_pvalues)
print(eqtl_pvalues_i)
print(aei_pvalues.iloc[eqtl_pvalues_i])
if aei_pvalues.iloc[eqtl_pvalues_i] <= threshold:
return(True)
else:
return(False) | f0371c81096ad9f1598c1291d853d717002e09e0 | 3,633,438 |
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