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import types
import functools
def copy_func(f):
"""Based on http://stackoverflow.com/a/6528148/190597 (Glenn Maynard)."""
g = types.FunctionType(f.__code__, f.__globals__, name=f.__name__,
argdefs=f.__defaults__,
closure=f.__closure__)
g = functools.up... | d661876d8568c5f33ae07682c874edd8d71dd7c9 | 3,641,673 |
from typing import List
def augment(img_list: list, hflip: bool = True, rot: bool = True) -> List[np.ndarray]:
"""
Augments the image inorder to add robustness to the model
@param img_list: The List of images
@param hflip: If True, add horizontal flip
@param rot: If True, add 90 degrees rotation
... | 3d953ba2c9ce869ec612644d9a5370690c930e22 | 3,641,674 |
def _neurovault_collections(parts, query):
"""Mocks the Neurovault API behind the `/api/collections/` path.
parts: the parts of the URL path after "collections"
ie [], ["<somecollectionid>"], or ["<somecollectionid>", "images"]
query: the parsed query string, e.g. {"offset": "15", "limit": "5"}
... | 5ee1e6b9b59fb12e76c38c20cde65c18c3fd201a | 3,641,675 |
def display_states():
""" Display the states"""
storage_states = storage.all(State)
return render_template('7-states_list.html', states=storage_states) | b9dc5c739546fee0abce077df1bba38587062f1a | 3,641,676 |
def recompress_folder(folders, path, extension):
"""Recompress folder"""
dest = runez.SYS_INFO.platform_id.composed_basename("cpython", path.name, extension=extension)
dest = folders.dist / dest
runez.compress(path, dest, logger=print)
return dest | 5cadc1a0b32509630cd3fa5af9fd758899e4bf94 | 3,641,677 |
import pathlib
def guessMimetype(filename):
"""Return the mime-type for `filename`."""
path = pathlib.Path(filename) if not isinstance(filename, pathlib.Path) else filename
with path.open("rb") as signature:
# Since filetype only reads 262 of file many mp3s starting with null bytes will not find... | 84f6b2f80b341f330e3f6b9e65b4863d055f8796 | 3,641,678 |
def filter_ptr_checks(props):
"""This function will filter out extra pointer checks.
Our support to primitives and overflow pointer checks is unstable and
can result in lots of spurious failures. By default, we filter them out.
"""
def not_extra_check(prop):
return extract_property_... | e5964637c3f1a27521f5305673c9e5af3189e15d | 3,641,680 |
import time
def makeKeylistObj(keylist_fname, includePrivate=False):
"""Return a new unsigned keylist object for the keys described in
'mirror_fname'.
"""
keys = []
def Key(obj): keys.append(obj)
preload = {'Key': Key}
r = readConfigFile(keylist_fname, (), (), preload)
klist = []
... | 13e79fbb9ac8ad207cc2533532c6be6bb0372beb | 3,641,681 |
def getwpinfo(id,wps):
"""Help function to create description of WP inputs."""
try:
wpmin = max([w for w in wps if 'loose' in w.lower()],key=lambda x: len(x)) # get loose WP with most 'V's
wpmax = max([w for w in wps if 'tight' in w.lower()],key=lambda x: len(x)) # get tight WP with most 'V's
info = f"... | 0dcf6c205a1988227e23a77e169a9114f1fdf2cc | 3,641,682 |
def build_word_dg(target_word, model, depth, model_vocab=None, boost_counter=None, topn=5):
""" Accept a target_word and builds a directed graph based on
the results returned by model.similar_by_word. Weights are initialized
to 1. Starts from the target_word and gets similarity results for it's children
... | ffd32cef2b44fd9e9cd554cd618091dfe8e5377f | 3,641,683 |
def sample_normal_gamma(mu, lmbd, alpha, beta):
""" https://en.wikipedia.org/wiki/Normal-gamma_distribution
"""
tau = np.random.gamma(alpha, beta)
mu = np.random.normal(mu, 1.0 / np.sqrt(lmbd * tau))
return mu, tau | 0f11ce95cfb772aeb023b61300bdb03d827cab37 | 3,641,685 |
def _dice(terms):
"""
Returns the elements of iterable *terms* in tuples of every possible length
and range, without changing the order. This is useful when parsing a list of
undelimited terms, which may span multiple tokens. For example:
>>> _dice(["a", "b", "c"])
[('a', 'b', 'c'), ('a', 'b'),... | bb8f567d82405864c0bf81b2ee9f3cb89b875d11 | 3,641,687 |
from datetime import datetime
def parse_date(val, format):
"""
Attempts to parse the given string date according to the
provided format, raising InvalidDateError in case of problems.
@param str val (e.g. 2014-08-12)
@param str format (e.g. %Y-%m-%d)
@return datetime.date
"""
try:
... | 4686bf46d12310ee7ac4aa1986df55b598909a06 | 3,641,688 |
def get_capture_dimensions(capture):
"""Get the dimensions of a capture"""
width = int(capture.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(capture.get(cv2.CAP_PROP_FRAME_HEIGHT))
return width, height | 9a13253c1ca5c44b7a1ef4440989b1af9abcb776 | 3,641,689 |
def ad_modify_user_pwd_by_mail(user_mail_addr, old_password, new_password):
"""
通过mail修改某个用户的密码
:param user_mail_addr:
:return:
"""
conn = __ad_connect()
user_dn = ad_get_user_dn_by_mail(user_mail_addr)
result = conn.extend.microsoft.modify_password(user="%s" % user_dn, new_password="%s"... | 7cc5c654517ad3f175e06500310f0bbfec516ad1 | 3,641,692 |
def markup_record(record_text, record_nr, modifiers, targets, output_dict):
""" Takes current Patient record, applies context algorithm,
and appends result to output_dict
"""
# Is used to collect multiple sentence markups. So records can be complete
context = pyConText.ConTextDocument()
# Split... | 2eee4560a411bcd7ef364b6ed9b37cc2870cd3b5 | 3,641,693 |
import inspect
def get_file_name(file_name):
"""
Returns a Testsuite name
"""
testsuite_stack = next(iter(list(filter(lambda x: file_name in x.filename.lower(), inspect.stack()))), None)
if testsuite_stack:
if '/' in testsuite_stack.filename:
split_character = '/'
els... | 97172600d785339501f5e58e8aca6581a0a690e0 | 3,641,694 |
import torch
def track_edge_matrix_by_spt(batch_track_bbox, batch_track_frames, history_window_size=50):
"""
:param batch_track_bbox: B, M, T, 4 (x, y, w, h)
:return:
"""
B, M, T, _ = batch_track_bbox.size()
batch_track_xy = batch_track_bbox[:, :, :, :2]
batch_track_wh = batch_track_bbox[:... | 5303f401d925c26a1c18546ba371a2119a41ec3d | 3,641,695 |
def _file(space, fname, flags=0, w_ctx=None):
""" file - Reads entire file into an array
'FILE_USE_INCLUDE_PATH': 1,
'FILE_IGNORE_NEW_LINES': 2,
'FILE_SKIP_EMPTY_LINES': 4,
'FILE_NO_DEFAULT_CONTEXT': 16,
"""
if not is_in_basedir(space, 'file', fname):
space.ec.warn("... | d8a04244c90f3f730c297a8dbaa1372acd61993b | 3,641,696 |
def prepare_features(tx_nan, degree, mean_nan=None, mean=None, std=None):
"""Clean and prepare for learning. Mean imputing, missing value indicator, standardize."""
# Get column means, if necessary
if mean_nan is None: mean_nan = np.nanmean(tx_nan,axis=0)
# Replace NaNs
tx_val = np.where(np.isnan(... | 2f9fd73cd04b40a85556573a62a083a0ffaa725c | 3,641,697 |
def _write_matt2(model, name, mids, nmaterials, op2, op2_ascii, endian):
"""writes the MATT2"""
#Record - MATT2(803,8,102)
#Word Name Type Description
#1 MID I Material identification number
#2 TID(15) I TABLEMi entry identification numbers
#17 UNDEF None
key = (803, 8, 102)
nfields = 17... | 607b94a6c1e3daf4b482acbb1df1ce967f1bce3b | 3,641,698 |
def all_subclasses(cls):
"""Returns all known (imported) subclasses of a class."""
return cls.__subclasses__() + [g for s in cls.__subclasses__()
for g in all_subclasses(s)] | 8b9a2ecd654b997b5001820d6b85e442af9cee3b | 3,641,699 |
def _find_popular_codon(aa):
"""
This function returns popular codon from a 4+ fold degenerative codon.
:param aa: dictionary containing amino acid information.
:return:
"""
codons = [c[:2] for c in aa["codons"]]
counts = []
for i in range(len(codons)):
pc = codons[i]
cou... | a555a9d42ea4dfa0260d9d4d2040de3c6fca69a0 | 3,641,700 |
import pathlib
def initialize_cluster_details(scale_version, cluster_name, username,
password, scale_profile_path,
scale_replica_config):
""" Initialize cluster details.
:args: scale_version (string), cluster_name (string),
username (str... | 5508733e0bfbd20fb76ecaaf0df7f41675b0c5c8 | 3,641,701 |
def load(data_home=None):
"""Load RWC-Genre dataset
Args:
data_home (str): Local path where the dataset is stored.
If `None`, looks for the data in the default directory, `~/mir_datasets`
Returns:
(dict): {`track_id`: track data}
"""
if data_home is None:
data_... | 61d09f64ec7f36bc1dac6bfc6bea8e47fe82248b | 3,641,702 |
import copy
def collate_spectra_by_source(source_list, tolerance, unit=u.arcsec):
"""Given a list of spec1d files from PypeIt, group the spectra within the
files by their source object. The grouping is done by comparing the
position of each spectra (using either pixel or RA/DEC) using a given tolerance.
... | a82b470685ee53f3fe2de5e41a3f212e32a4d606 | 3,641,703 |
def tolist(obj):
"""
Convert given `obj` to list.
If `obj` is not a list, return `[obj]`, else return `obj` itself.
"""
if not isinstance(obj, list):
return [obj]
return obj | f511f4ebb86977b2db8646e692abc9840c2ae2d1 | 3,641,704 |
def bip44_tree(config: dict, cls=hierarchy.Node) -> hierarchy.Node:
"""
Return the root node of a BIP44-compatible partially ordered hierarchy.
https://github.com/bitcoin/bips/blob/master/bip-0044.mediawiki
The `config` parameter is a dictionary of the following form:
- the keys of the dictionary a... | bd88895932b66963aa7f63f30ad49ac009ea41f1 | 3,641,705 |
def delete_useless_vrrp_subnets(client, to_delete, project_id):
"""
:param 'Client' client
:param dict((prefix_length, type, master_region, slave_region),
(state:quantity)) to_delete
:rtype: list
"""
result = []
vrrp_subnets = client.vrrp.list(project_id=project_id)
for k... | b16019b026c32d310f9f938a7ca1fada31d02d84 | 3,641,706 |
import torch
import warnings
def barycenter_wbc(P, K, logweights, Kb=None, c=None, debiased=False,
maxiter=1000, tol=1e-4):
"""Compute the Wasserstein divergence barycenter between histograms.
"""
n_hists, width, _ = P.shape
if Kb is None:
b = torch.ones_like(P)[None, :]
... | 453c40ed988d4fe86dc202f816c5eb3bb6cbd452 | 3,641,707 |
def logistic_predict(weights, data):
"""
Compute the probabilities predicted by the logistic classifier.
Note: N is the number of examples and
M is the number of features per example.
Inputs:
weights: (M+1) x 1 vector of weights, where the last element
corresp... | 52c2ff3ed4b854de645b2252b4949b4a7a68bda1 | 3,641,709 |
def score_matrix(motifs, k):
"""returns matrix score formed from motifs"""
nucleotides = {'A': [0]*k, 'T': [0]*k, 'C': [0]*k, 'G': [0]*k}
for motif in motifs:
for index, nucleotide in enumerate(motif):
nucleotides[nucleotide][index] = nucleotides[nucleotide][index] + 1
i = 0
matr... | ce9f7b770ce75d4e872da7b3c9b4fa3fbcd1e900 | 3,641,710 |
def log_loss(y_true, dist_pred, sample=True, return_std=False):
""" Log loss
Parameters
----------
y_true: np.array
The true labels
dist_pred: ProbabilisticEstimator.Distribution
The predicted distribution
sample: boolean, default=True
If true, loss will be averaged acro... | 0f3d19111593441011cfb1e532be50a19d423390 | 3,641,711 |
import scipy
def matrix_pencil_method_old(data, p, noise_level=None, verbose=1, **kwargs):
""" Older impleentation of the matrix pencil method with pencil p on given data to
extract energy levels.
Parameters
----------
data -- lists of Obs, where the nth entry is considered to be the correlat... | 4bcb435b3b16b153d0d1f1689f542df1fdc74ca8 | 3,641,712 |
def ext_sum(text, ratio=0.8):
"""
Generate extractive summary using BERT model
INPUT:
text - str. Input text
ratio - float. Enter a ratio between 0.1 - 1.0 [default = 0.8]
(ratio = summary length / original text length)
OUTPUT:
summary - str. Generated summary
"""
bert_... | 99285d08425340f70984ce0645efdbaaa3e9072a | 3,641,713 |
def khinalug_input_normal(field, text):
"""
Prepare a string from one of the query fields for subsequent
processing: replace common shortcuts with valid Khinalug characters.
"""
if field not in ('wf', 'lex', 'lex2', 'trans_ru', 'trans_ru2'):
return text
text = text.replace('c1_', 'č̄')
... | b9b9413ae461b6a03aa8c0db4396658dbe242c91 | 3,641,714 |
from typing import List
from typing import Dict
from typing import Any
def _shift_all_classes(classes_list: List[ndarray], params_dict: Dict[str, Any]):
"""Shift the locale of all classes.
Args:
classes_list: List of classes as numpy arrays.
params_dict: Dict including the shift values for al... | 2176e5f4da6aecc25386e978182887fb8568faaa | 3,641,715 |
def fully_connected_layer(tensor,
size=None,
weight_init=None,
bias_init=None,
name=None):
"""Fully connected layer.
Parameters
----------
tensor: tf.Tensor
Input tensor.
size: int
Number of output... | 605cc52e8c5262aead6cb758488940e7661286b1 | 3,641,716 |
from pathlib import Path
def fetch_osborne_magnetic(version):
"""
Magnetic airborne survey of the Osborne Mine and surroundings, Australia
This is a section of a survey acquired in 1990 by the Queensland
Government, Australia. The line data have approximately 80 m terrain
clearance and 200 m line... | 2a0575557a18ca4442f0cf21ee51ccd94d316ffa | 3,641,717 |
from sympy.core.symbol import Symbol
from sympy.printing.pycode import MpmathPrinter as Printer
from sympy.printing.pycode import SciPyPrinter as Printer
from sympy.printing.pycode import NumPyPrinter as Printer
from sympy.printing.lambdarepr import NumExprPrinter as Printer
from sympy.printing.tensorflow import Tensor... | cf7b65c503d1a7873f0ddacfb3f6aa841340ee0e | 3,641,718 |
def _matches(o, pattern):
"""Match a pattern of types in a sequence."""
if not len(o) == len(pattern):
return False
comps = zip(o,pattern)
return all(isinstance(obj,kind) for obj,kind in comps) | e494016affa28e9018f337cb7184e96858701208 | 3,641,719 |
import csv
from io import StringIO
def excl_import_route():
"""import exclustions from csv"""
form = ExclImportForm()
if form.validate_on_submit():
imported = []
try:
for row in csv.DictReader(StringIO(form.data.data), EXPORT_FIELDNAMES, quoting=csv.QUOTE_MINIMAL):
... | 780c5646b2a5771691c538cb71bfde390cd9b847 | 3,641,720 |
def receiver(signal, **kwargs):
"""
A decorator for connecting receivers to signals. Used by passing in the
signal and keyword arguments to connect::
@receiver(signal_object, sender=sender)
def signal_receiver(sender, **kwargs):
...
"""
def _decorator(func):
sig... | dbbde0855b2a657adaff9fa688aa158053e46579 | 3,641,721 |
from typing import final
def create_new_connected_component(dict_projections, dict_cc, dict_nodes_cc, g_list_, set_no_proj, initial_method,
params, i, file_tags=None):
"""
If needed, create new connect component and update wanted dicts.
:param dict_projections: Embedding... | 18b8c046e78f17b125bf85250953c9d7a656892a | 3,641,722 |
def laguerre(x, k, c):
"""Generalized Laguerre polynomials. See `help(_gmw.morsewave)`.
LAGUERRE is used in the computation of the generalized Morse
wavelets and uses the expression given by Olhede and Walden (2002),
"Generalized Morse Wavelets", Section III D.
"""
x = np.atleast_1d(np.asarray(... | 4eac2e1cbd9fd2097763b56129873aa6af4e8419 | 3,641,723 |
import math
def find_all_combinations(participants, team_sizes):
""" Finds all possible experience level combinations for specific team
sizes with duplicated experience levels (e.g. (1, 1, 2))
Returns a list of tuples representing all the possible combinations """
num_teams = len(team_sizes)
part... | d3f4de9911a1fc427fc2e01433634ccf815f9183 | 3,641,726 |
def normalized_copy(data):
"""
Normalize timeseries data, using the maximum across all regions and timesteps.
Parameters
----------
data : xarray Dataset
Dataset with all non-time dependent variables removed
Returns
-------
ds : xarray Dataset
Copy of `data`, with the a... | cfcb94458deb6caa1125cfcf2904652900babc87 | 3,641,728 |
def _get_exception(ex: Exception) -> Exception:
"""Get exception cause/context from chained exceptions
:param ex: chained exception
:return: cause of chained exception if any
"""
if ex.__cause__:
return ex.__cause__
elif ex.__context__:
return ex.__context__
else:
re... | 3f670dc237ebd865e31c7d0fd3719e2ea929de6d | 3,641,729 |
from typing import Any
from typing import Dict
def recursive_normalizer(value: Any, **kwargs: Dict[str, Any]) -> Any:
"""
Prepare a structure for hashing by lowercasing all values and round all floats
"""
digits = kwargs.get("digits", 10)
lowercase = kwargs.get("lowercase", True)
if isinstanc... | e274c3976405838054d7251fdca8520dc75c48fd | 3,641,730 |
from typing import Set
def rip_and_tear(context) -> Set:
"""Edge split geometry using specified angle or unique mesh settings.
Also checks non-manifold geometry and hard edges.
Returns set of colors that are used to color meshes."""
processed = set()
angle_use_fixed = prefs.RenderFixedAngleUse
... | 6a67e9a90b4909c1aec8f7f784b2bc41750f5f79 | 3,641,731 |
def generate_primes(d):
"""Generate a set of all primes with d distinct digits."""
primes = set()
for i in range(10**(d-1)+1, 10**d, 2):
string = str(i)
unique_string = "".join(set(string))
if len(string) == len(unique_string): # Check that all digits are unique
if isprim... | 4edf615165144f2ab6e5d12533adc4357d904506 | 3,641,732 |
def poinv(A, UPLO='L', workers=1, **kwargs):
"""
Compute the (multiplicative) inverse of symmetric/hermitian positive
definite matrices, with broadcasting.
Given a square symmetic/hermitian positive-definite matrix `a`, return
the matrix `ainv` satisfying ``matrix_multiply(a, ainv) =
matrix_mul... | ccba9b0fc518e0482c6ac647d56abe0e86d3409c | 3,641,733 |
def gen_task3() -> np.ndarray:
"""Task 3: centre of cross or a plus sign."""
canv = blank_canvas()
r, c = np.random.randint(GRID-2, size=2, dtype=np.int8)
# Do we create a cross or a plus sign?
syms = rand_syms(5) # a 3x3 sign has 2 symbols, outer and centre
# syms = np.array([syms[0], syms[0], syms[1], sym... | aba9e78cf4d042cacd8787a90275947ba603b37c | 3,641,734 |
def init_susceptible_00():
"""
Real Name: b'init Susceptible 00'
Original Eqn: b'8e+06'
Units: b'person'
Limits: (None, None)
Type: constant
b''
"""
return 8e+06 | acc506bdea96b224f3627084bbee9e1a025bcff9 | 3,641,735 |
def spectrum_1D_scalar(data, dx, k_bin_num=100):
"""Calculates and returns the 2D spectrum for a 2D gaussian field of scalars, assuming isotropy of the turbulence
Example:
d=np.random.randn(101,101)
dx=1
k_bins_weighted,spect3D=spectrum_2D_scalar(d, dx, k_bin_num=100)
... | 88cdb3917d995fdf5d870ebfef3da90f8a4526fb | 3,641,736 |
from operator import and_
def get_previous_cat(last_index: int) -> models.Cat:
"""Get previous cat.
Args:
last_index (int): View index of last seen cat.
"""
cat = models.Cat.query.filter(and_(models.Cat.disabled == False, models.Cat.index < last_index)).order_by(
desc(models.Cat.index)... | bd4b6511ab7b2f004b8539e46109ce128d7af4dd | 3,641,737 |
def encode(file, res):
"""Encode an image. file is the path to the image, res is the resolution to use. Smaller res means smaller but lower quality output."""
out = buildHeader(res)
pixels = getPixels(file, res)
for i in range(0, len(pixels)):
px = encodePixel(pixels[i])
out += px
return out | 07f9622bc222f91cb614165e432b4584374030a3 | 3,641,738 |
def process_image(img):
"""Resize, reduce and expand image.
# Argument:
img: original image.
# Returns
image: ndarray(64, 64, 3), processed image.
"""
image = cv2.resize(img, (416, 416), interpolation=cv2.INTER_CUBIC)
image = np.array(image, dtype='float32')
image /= 255.
... | a139d0b82c82273de35d5e95b75cfd5f0e7635e3 | 3,641,739 |
def unnormalise_x_given_lims(x_in, lims):
"""
Scales the input x (assumed to be between [-1, 1] for each dim)
to the lims of the problem
"""
# assert len(x_in) == len(lims)
r = lims[:, 1] - lims[:, 0]
x_orig = r * (x_in + 1) / 2 + lims[:, 0]
return x_orig | 1d4cd35f45ab8594e297eb64e152a481c01905cd | 3,641,740 |
def scalar_projection(vector, onto):
"""
Compute the scalar projection of `vector` onto the vector `onto`.
`onto` need not be normalized.
"""
if vector.ndim == 1:
check(locals(), "vector", (3,))
check(locals(), "onto", (3,))
else:
k = check(locals(), "vector", (-1, 3))
... | d5b27d46e6d498b22adb1b081b9c7143c636307b | 3,641,741 |
def update_table(page_current, page_size, sort_by, filter, row_count_value):
"""
This is the collback function to update the datatable
with the required filtered, sorted, extended values
:param page_current: Current page number
:param page_size: Page size
:param sort_by: Column selected for sort... | e2669f3b98546731974e5706b8af9f6d82b47550 | 3,641,742 |
def load_mooring_csv(csvfilename):
"""Loads data contained in an ONC mooring csv file
:arg csvfilename: path to the csv file
:type csvfilename: string
:returns: data, lat, lon, depth - a pandas data frame object and the
latitude, longitude and depth of the morning
"""
data_line, lat, lon,... | a974e8607916e8fbc1b2beb7af8768d048aca8f0 | 3,641,744 |
def ez_execute(query, engine):
"""
Function takes a query string and an engine object
and returns a dataframe on the condition that the
sql query returned any rows.
Arguments:
query {str} -- a Sql query string
engine {sqlalchemy.engine.base.Engine} -- a database engine object
... | c350d552f89dca550e766337fd7c071e138c43e6 | 3,641,745 |
def compute_lima_image(counts, background, kernel):
"""Compute Li & Ma significance and flux images for known background.
Parameters
----------
counts : `~gammapy.maps.WcsNDMap`
Counts image
background : `~gammapy.maps.WcsNDMap`
Background image
kernel : `astropy.convolution.Ker... | 8049f5a46ecf81459a64811aec917e72ec78a208 | 3,641,746 |
def get_list_from(matrix):
"""
Transforms capability matrix into list.
"""
only_valuable = []
counter = 1
for row_number in range(matrix.shape[0]):
only_valuable += matrix[row_number, counter::].tolist()
counter += 1
return only_valuable | bbfa52ff6a960d91d5aece948e9d416c3dcf0667 | 3,641,747 |
def g1_constraint(x, constants, variables):
""" Constraint that the initial value of tangent modulus > 0 at ep=0.
:param np.ndarray x: Parameters of updated Voce-Chaboche model.
:param dict constants: Defines the constants for the constraint.
:param dict variables: Defines constraint values that depend... | 51d55a03b608cef2c3b5d87fe5cb56bf73326ae3 | 3,641,749 |
import sqlite3
def disconnect(connection_handler):
""" Closes a current database connection
:param connection_handler: the Connection object
:return: 0 if success and -1 if an exception arises
"""
try:
if connection_handler is not None:
connection_handler.close()
... | aaba17e38ef48fe7e0be5ba825e114b6f5148433 | 3,641,750 |
def throw_out_nn_indices(ind, dist, Xind):
"""Throw out near neighbor indices that are used to embed the time series.
This is an attempt to get around the problem of autocorrelation.
Parameters
----------
ind : 2d array
Indices to be filtered.
dist : 2d array
Distances to be fi... | 638fb43ac484ffa0e15e3c19a5b643aae5a749d9 | 3,641,751 |
import math
def lead_angle(target_disp,target_speed,target_angle,bullet_speed):
"""
Given the displacement, speed and direction of a moving target, and the speed
of a projectile, returns the angle at which to fire in order to intercept the
target. If no such angle exists (for example if the projectile is slower t... | fb5dfddf8b36d4e49df2d740b18f9aa97381d08f | 3,641,752 |
import time
def acme_parser(characters):
"""Parse records from acme global
Args:
characters: characters to loop through the url
Returns:
2 item tuple containing all the meds as a list and a count of all meds
"""
link = (
'http://acmeglobal.com/acme/'
'wp-content/t... | 8e9fe3b020e05243075351d7eedbdba7a54d5d81 | 3,641,754 |
def standard_atari_env_spec(env):
"""Parameters of environment specification."""
standard_wrappers = [[tf_atari_wrappers.RewardClippingWrapper, {}],
[tf_atari_wrappers.StackWrapper, {"history": 4}]]
env_lambda = None
if isinstance(env, str):
env_lambda = lambda: gym.make(env)
if cal... | e9751e1b376cdee5ec0f9c27d8ab4bf2e303f35b | 3,641,756 |
def load_bikeshare(path='data', extract=True):
"""
Downloads the 'bikeshare' dataset, saving it to the output
path specified and returns the data.
"""
# name of the dataset
name = 'bikeshare'
data = _load_file_data(name, path, extract)
return data | 7cce01f22c37460800a44a85b18e6574d9d7f6fb | 3,641,757 |
def file2bytes(filename: str) -> bytes:
"""
Takes a filename and returns a byte string with the content of the file.
"""
with open(filename, 'rb') as f:
data = f.read()
return data | f917a265c17895c917c3c340041586bef0c34dac | 3,641,758 |
import json
def load_session() -> dict:
"""
Returns available session dict
"""
try:
return json.load(SESSION_PATH.open())
except FileNotFoundError:
return {} | 342c8e143c878cfc4821454cebfcc3ba47a2cd2a | 3,641,759 |
def _preprocess_zero_mean_unit_range(inputs, dtype=tf.float32):
"""Map image values from [0, 255] to [-1, 1]."""
preprocessed_inputs = (2.0 / 255.0) * tf.cast(inputs, tf.float32) - 1.0
return tf.cast(preprocessed_inputs, dtype=dtype) | 08238566a04ed35346b8f4ff0874fff7be48bded | 3,641,760 |
from typing import cast
def fill_like(input, value, shape=None, dtype=None, name=None):
"""Create a uniformly filled tensor / array."""
input = as_tensor(input)
dtype = dtype or input.dtype
if has_tensor([input, value, shape], 'tf'):
value = cast(value, dtype)
return tf.fill(value, inp... | 1879ac8669396dfe3fe351dae97a96cd8d6a8e5e | 3,641,761 |
from typing import Callable
import operator
def transform_item(key, f: Callable) -> Callable[[dict], dict]:
"""transform a value of `key` in a dict. i.e given a dict `d`, return a new dictionary `e` s.t e[key] = f(d[key]).
>>> my_dict = {"name": "Danny", "age": 20}
>>> transform_item("name", str.upper)(m... | a202fe59b29b0a1b432df759b4600388e2d9f72e | 3,641,762 |
def mock_dataset(mocker, mock_mart, mart_datasets_response):
"""Returns an example dataset, built using a cached response."""
mocker.patch.object(mock_mart, 'get', return_value=mart_datasets_response)
return mock_mart.datasets['mmusculus_gene_ensembl'] | bb9a8b828f0ac5bfa59b3faee0f9bcc22c7d954e | 3,641,763 |
import torch
def loss_function(recon_x, x, mu, logvar):
"""Loss function for varational autoencoder VAE"""
BCE = F.binary_cross_entropy(recon_x, x, size_average=False)
# 0.5 * sum(1 + log(sigma^2) - mu^2 - sigma^2)
KLD = -0.5 * torch.sum(1 + logvar - mu.pow(2) - logvar.exp())
return BCE + KLD | 38c0d6ab7a8388e007324bdcfb8611f0a3072c35 | 3,641,764 |
import scipy
def resize_img(img, size):
"""
Given a list of images in ndarray, resize them into target size.
Args:
img: Input image in ndarray
size: Target image size
Returns: Resized images in ndarray
"""
img = scipy.misc.imresize(img, (size, size))
if len(img.shape) ==... | 8a3ff8bfab0c864a6c0e4701be07b9296ad23f28 | 3,641,765 |
def cloudtopheight_IR(bt, cloudmask, latitude, month, method="modis"):
"""Cloud Top Height (CTH) from 11 micron channel.
Brightness temperatures (bt) are converted to CTHs using the IR window approach:
(bt_clear - bt_cloudy) / lapse_rate.
See also:
:func:`skimage.measure.block_reduce`
... | b68dfb37b27d3067c2956fc3653640393491e014 | 3,641,766 |
def info2lists(info, in_place=False):
"""
Return info with:
1) `packages` dict replaced by a 'packages' list with indexes removed
2) `releases` dict replaced by a 'releases' list with indexes removed
info2list(info2dicts(info)) == info
"""
if 'packages' not in info and 'releases' not in i... | 313fda757d386332e16a0a91bb4408fe3cb8c070 | 3,641,767 |
def calc_wave_number(g, h, omega, relax=0.5, eps=1e-15):
"""
Relaxed Picard iterations to find k when omega is known
"""
k0 = omega ** 2 / g
for _ in range(100):
k1 = omega ** 2 / g / tanh(k0 * h)
if abs(k1 - k0) < eps:
break
k0 = k1 * relax + k0 * (1 - relax)
... | 7173fc9f38547864943046fed1e74d9b5cc832b5 | 3,641,768 |
def emit_live_notification_for_model(obj, user, history, *, type:str="change", channel:str="events",
sessionid:str="not-existing"):
"""
Sends a model live notification to users.
"""
if obj._importing:
return None
content_type = get_typename_for_model_in... | 94e7e91ec73537aad71ab3839fbd203552d4fec2 | 3,641,769 |
def is_chitoi(tiles):
"""
Returns True if the hand satisfies chitoitsu.
"""
unique_tiles = set(tiles)
return (len(unique_tiles) == 7 and
all([tiles.count(tile) == 2 for tile in unique_tiles])) | c04149174bb779cd07616d4f419fc86531ab95dd | 3,641,770 |
import itertools
def get_hpo_ancestors(hpo_db, hpo_id):
"""
Get HPO terms higher up in the hierarchy.
"""
h=hpo_db.hpo.find_one({'id':hpo_id})
#print(hpo_id,h)
if 'replaced_by' in h:
# not primary id, replace with primary id and try again
h = hpo_db.hpo.find_one({'id':h['replac... | 2ef2c968bc3001b97529ccd269884cefad7a899f | 3,641,771 |
def mcBufAir(params: dict, states: dict) -> float:
"""
Growth respiration
Parameters
----------
params : dict
Parameters saved as model constants
states : dict
State variables of the model
Returns
-------
float
Growth respiration of the plant [mg m-2 s-1]
... | d31f201384fdab6c03856def1eed7d96fe28482a | 3,641,772 |
def space_boundaries_re(regex):
"""Wrap regex with space or end of string."""
return rf"(?:^|\s)({regex})(?:\s|$)" | 68861da6218165318b6a446c173b4906a93ef850 | 3,641,774 |
import requests
import json
import dateutil
def get_jobs():
"""
this function will query USAJOBS api and return all open FEC jobs.
if api call failed, a status error message will be displayed in the
jobs.html session in the career page.
it also query code list to update hirepath info. a hard-coded... | 46c69348b3f964fc1c4f35391aa5c7a8d049b47e | 3,641,775 |
def artanh(x) -> ProcessBuilder:
"""
Inverse hyperbolic tangent
:param x: A number.
:return: The computed angle in radians.
"""
return _process('artanh', x=x) | d93ec8e7059df02ebf7a60506d2e9896bc146b32 | 3,641,776 |
from thunder.readers import normalize_scheme, get_parallel_reader
import array
def fromtext(path, ext='txt', dtype='float64', skip=0, shape=None, index=None, labels=None, npartitions=None, engine=None, credentials=None):
"""
Loads series data from text files.
Assumes data are formatted as rows, where eac... | 9ab049954b23888c2d2a17786edde57dd90507c0 | 3,641,777 |
def flop_gemm(n, k):
"""# of + and * for matmat of nxn matrix with nxk matrix, with accumulation
into the output."""
return 2*n**2*k | b217b725e2ac27a47bc717789458fd20b4aa56c1 | 3,641,778 |
def index() -> str:
"""Rest endpoint to test whether the server is correctly working
Returns:
str: The default message string
"""
return 'DeChainy server greets you :D' | ce0caeb9994924f8d6ea10462db2be48bbc126d0 | 3,641,779 |
from typing import AnyStr
from typing import List
import json
def load_json_samples(path: AnyStr) -> List[str]:
"""
Loads samples from a json file
:param path: Path to the target file
:return: List of samples
"""
with open(path, "r", encoding="utf-8") as file:
samples = json.load(file... | b735e7265a31f6bc6d19381bfe9d0cbe26dcf170 | 3,641,781 |
import struct
import lzma
def decompress_lzma(data: bytes) -> bytes:
"""decompresses lzma-compressed data
:param data: compressed data
:type data: bytes
:raises _lzma.LZMAError: Compressed data ended before the end-of-stream marker was reached
:return: uncompressed data
:rtype: bytes
"""
... | 247c3d59d45f3f140d4f2c36a7500ff8a51e45b0 | 3,641,783 |
def validate(request):
"""
Validate actor name exists in database before searching.
If more than one name fits the criteria, selects the first one
and returns the id.
Won't render.
"""
search_for = request.GET.get('search-for', default='')
start_from = request.GET.get('start-from', def... | 39b9183cd570cce0ddfd81febde0ec125f11c578 | 3,641,784 |
def merge(left, right, on=None, left_on=None, right_on=None):
"""Merge two DataFrames using explicit-comms.
This is an explicit-comms version of Dask's Dataframe.merge() that
only supports "inner" joins.
Requires an activate client.
Notice
------
As a side effect, this operation concatena... | 847070e27007c049d0c58059ec9f7c66681f21bc | 3,641,785 |
def estimate_fs(t):
"""Estimates data sampling rate"""
sampling_rates = [
2000,
1250,
1000,
600,
500,
300,
250,
240,
200,
120,
75,
60,
50,
30,
25,
]
fs_est = np.median(1 / np.diff(t))... | 82dbd115e3c7b656302d10339cdfe77b60ab0620 | 3,641,786 |
def get_case_number(caselist):
"""Get line number from file caselist."""
num = 0
with open(caselist, 'r') as casefile:
for line in casefile:
if line.strip().startswith('#') is False:
num = num + 1
return num | b1366d8e4a0e2c08da5265502d2dd2d72bf95c19 | 3,641,787 |
from typing import Any
def build_param_float_request(*, scenario: str, value: float, **kwargs: Any) -> HttpRequest:
"""Send a post request with header values "scenario": "positive", "value": 0.07 or "scenario":
"negative", "value": -3.0.
See https://aka.ms/azsdk/python/protocol/quickstart for how to inco... | 3e310a92ebe5760a00abc82c5c6465e160a5881d | 3,641,788 |
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