content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import math
def sin(c):
"""
sin(a+x)= sin(a) cos(x) + cos(a) sin(x)
"""
if not isinstance(c,pol): return math.sin(c)
a0,p=c.separate();
lst=[math.sin(a0),math.cos(a0)]
for n in range(2,c.order+1):
lst.append( -lst[-2]/n/(n-1))
return phorner(lst,p) | a6ec312df4362c130343133dae9a09b377f56cf5 | 10,700 |
def _calc_metadata() -> str:
"""
Build metadata MAY be denoted by appending a plus sign
and a series of dot separated identifiers
immediately following the patch or pre-release version.
Identifiers MUST comprise only ASCII alphanumerics and hyphen [0-9A-Za-z-].
"""
if not is_appveyor:
... | ccbd4912622808b5845d8e30546d6eb27e299342 | 10,701 |
import functools
def authorization_required(func):
"""Returns 401 response if user is not logged-in when requesting URL with user ndb.Key in it
or Returns 403 response if logged-in user's ndb.Key is different from ndb.Key given in requested URL.
"""
@functools.wraps(func)
def decorated_function(*p... | 12c0d645b0b26bf419e413866afaf1b4e7a19869 | 10,702 |
import torch
def pad_col(input, val=0, where='end'):
"""Addes a column of `val` at the start of end of `input`."""
if len(input.shape) != 2:
raise ValueError(f"Only works for `phi` tensor that is 2-D.")
pad = torch.zeros_like(input[:, :1])
if val != 0:
pad = pad + val
if where == '... | 77caa028bb76da922ba12492f077811d2344c2a9 | 10,703 |
from typing import List
import itertools
def seats_found_ignoring_floor(data: List[List[str]], row: int, col: int) -> int:
"""
Search each cardinal direction util we hit a wall or a seat.
If a seat is hit, determine if it's occupied.
"""
total_seats_occupied = 0
cardinal_direction_operations ... | e5442d757df6304da42f817c975969723ad0abca | 10,704 |
def product_design_space() -> ProductDesignSpace:
"""Build a ProductDesignSpace for testing."""
alpha = RealDescriptor('alpha', lower_bound=0, upper_bound=100, units="")
beta = RealDescriptor('beta', lower_bound=0, upper_bound=100, units="")
gamma = CategoricalDescriptor('gamma', categories=['a', 'b', '... | 93468cc7aaeb6a6bf7453d2f3e974bc28dece31f | 10,705 |
def compute_percents_of_labels(label):
"""
Compute the ratio/percentage size of the labels in an labeled image
:param label: the labeled 2D image
:type label: numpy.ndarray
:return: An array of relative size of the labels in the image. Indices of the sizes in the array \
is corresponding to the... | 6dfe34b7da38fa17a5aa4e42acc5c812dd126f77 | 10,706 |
def removepara(H,M,Hmin = '1/2',Hmax = 'max',output=-1,kwlc={}):
""" Retrieve lineal contribution to cycle and remove it from cycle.
**H** y **M** corresponds to entire cycle (two branches). I.e. **H**
starts and ends at the same value (or an aproximate value).
El ciclo M vs H se separa ... | 1d70c60f60b3ab7b976a0ec12a3541e5a7e53426 | 10,707 |
def flush():
"""
Remove all mine contents of minion.
:rtype: bool
:return: True on success
CLI Example:
.. code-block:: bash
salt '*' mine.flush
"""
if __opts__["file_client"] == "local":
return __salt__["data.update"]("mine_cache", {})
load = {
"cmd": "_m... | fe7d120362393fcb4380473cdaf76e153646644a | 10,708 |
def polygon_to_shapely_polygon_wkt_compat(polygon):
"""
Convert a Polygon to its Shapely Polygon representation but with WKT
compatible coordinates.
"""
shapely_points = []
for location in polygon.locations():
shapely_points.append(location_to_shapely_point_wkt_compat(location))
ret... | 54c889d2071cc8408c2bb4b739a30c3458c80f4c | 10,709 |
import six
def ccd_process(ccd, oscan=None, trim=None, error=False, masterbias=None,
bad_pixel_mask=None, gain=None, rdnoise=None,
oscan_median=True, oscan_model=None):
"""Perform basic processing on ccd data.
The following steps can be included:
* overscan corr... | 610a53693ff84ba2e1a68662dd0a19e55228c129 | 10,710 |
def get_role_keyids(rolename):
"""
<Purpose>
Return a list of the keyids associated with 'rolename'.
Keyids are used as identifiers for keys (e.g., rsa key).
A list of keyids are associated with each rolename.
Signing a metadata file, such as 'root.json' (Root role),
involves signing or verifyin... | 4888a09740560d760bfffe9eecd50bfa67ff0613 | 10,711 |
def _DX(X):
"""Computes the X finite derivarite along y and x.
Arguments
---------
X: (m, n, l) numpy array
The data to derivate.
Returns
-------
tuple
Tuple of length 2 (Dy(X), Dx(X)).
Note
----
DX[0] which is derivate along y has shape (m-1, n, l).
DX[1] ... | 4aff05c2c25089c9f93b762a18dad42b0142db09 | 10,712 |
def load_spectra_from_dataframe(df):
"""
:param df:pandas dataframe
:return:
"""
total_flux = df.total_flux.values[0]
spectrum_file = df.spectrum_filename.values[0]
pink_stride = df.spectrum_stride.values[0]
spec = load_spectra_file(spectrum_file, total_flux=total_flux,
... | 31d1cbbee8d999dac5ee0d7f8d4c71f7f58afc3b | 10,713 |
def included_element(include_predicates, exclude_predicates, element):
"""Return whether an index element should be included."""
return (not any(evaluate_predicate(element, ep)
for ep in exclude_predicates) and
(include_predicates == [] or
any(evaluate_predicate(elem... | 00e0d66db26e8bca7e3cb8505596247065422cb6 | 10,714 |
def _insertstatushints(x):
"""Insert hint nodes where status should be calculated (first path)
This works in bottom-up way, summing up status names and inserting hint
nodes at 'and' and 'or' as needed. Thus redundant hint nodes may be left.
Returns (status-names, new-tree) at the given subtree, where ... | 956fe03a7f5747f93034501e63cc31ff2956c2d6 | 10,715 |
def make_sine(freq: float, duration: float, sr=SAMPLE_RATE):
"""Return sine wave based on freq in Hz and duration in seconds"""
N = int(duration * sr) # Number of samples
return np.sin(np.pi*2.*freq*np.arange(N)/sr) | 622b03395da5d9f8a22ac0ac30282e23d6596055 | 10,716 |
def _widget_abbrev(o):
"""Make widgets from abbreviations: single values, lists or tuples."""
float_or_int = (float, int)
if isinstance(o, (list, tuple)):
if o and all(isinstance(x, string_types) for x in o):
return DropdownWidget(values=[unicode_type(k) for k in o])
elif _matche... | f5a57f2d74811ff21ea56631fd9fb22fea4ae91f | 10,717 |
def get_conditions():
"""
List of conditions
"""
return [
'blinded',
'charmed',
'deafened',
'fatigued',
'frightened',
'grappled',
'incapacitated',
'invisible',
'paralyzed',
'petrified',
'poisoned',
'prone',
... | 816ccb50581cafa20bdefed2a075a3370704cef4 | 10,718 |
def negative_predictive_value(y_true: np.array, y_score: np.array) -> float:
"""
Calculate the negative predictive value (duplicted in :func:`precision_score`).
Args:
y_true (array-like): An N x 1 array of ground truth values.
y_score (array-like): An N x 1 array of predicted values.
R... | 28f1d4fce76b6201c6dbeb99ad19337ca84b74c5 | 10,719 |
def flat_list(*alist):
"""
Flat a tuple, list, single value or list of list to flat list
e.g.
>>> flat_list(1,2,3)
[1, 2, 3]
>>> flat_list(1)
[1]
>>> flat_list([1,2,3])
[1, 2, 3]
>>> flat_list([None])
[]
"""
a = []
for x in alist:
if x is None:
... | 5a68495e507e9a08a9f6520b83a912cf579c6688 | 10,720 |
from typing import List
def do_regression(X_cols: List[str], y_col: str, df: pd.DataFrame, solver='liblinear', penalty='l1',
C=0.2) -> LogisticRegression:
"""
Performs regression.
:param X_cols: Independent variables.
:param y_col: Dependent variable.
:param df: Data frame.
... | 8a65d49e64e96b3fc5271545afe1761382ec1396 | 10,721 |
def gaussian_smooth(var, sigma):
"""Apply a filter, along the time dimension.
Applies a gaussian filter to the data along the time dimension. if the
time dimension is missing, raises an exception. The DataArray that is
returned is shortened along the time dimension by sigma, half of sigma on
... | 809ec7b135ab7d915dd62ad10baea71bfd146e34 | 10,722 |
import logging
def make_ood_dataset(ood_dataset_cls: _BaseDatasetClass) -> _BaseDatasetClass:
"""Generate a BaseDataset with in/out distribution labels."""
class _OodBaseDataset(ood_dataset_cls):
"""Combine two datasets to form one with in/out of distribution labels."""
def __init__(
self,
... | c1c26206e352932d3a5397f047365c8c5c8b7fa7 | 10,723 |
def _title_case(value):
"""
Return the title of the string but the
first letter is affected.
"""
return value[0].upper() + value[1:] | 037bce973580f69d87c2e3b4e016b626a2b76abb | 10,724 |
import requests
def zoom_api_call(user, verb, url, *args, **kwargs):
"""
Perform an API call to Zoom with various checks.
If the call returns a token expired event,
refresh the token and try the call one more time.
"""
if not settings.SOCIAL_AUTH_ZOOM_OAUTH2_KEY:
raise DRFValidationEr... | 5c359a4a7acd69a942aedcb78fc156b8218ab239 | 10,725 |
import os
def copy_javascript(name):
"""Return the contents of javascript resource file."""
# TODO use importlib_resources to access javascript file content
folder = os.path.join(os.path.dirname(os.path.realpath(__file__)), "js")
with open(os.path.join(folder, name + ".js")) as fobj:
content =... | 927a9a87c3590f76b00f3a1085de4c6e103eeeff | 10,726 |
def addHtmlImgTagExtension(notionPyRendererCls):
"""A decorator that add the image tag extension to the argument list. The
decorator pattern allows us to chain multiple extensions. For example, we
can create a renderer with extension A, B, C by writing:
addAExtension(addBExtension(addCExtension(noti... | 914d2395cdf9c5f52f94eef80e3f7469a70eb0ae | 10,727 |
def mechaber(mechaber_name):
"""Route function for visualizing and exploring Mechabrim."""
mechaber = Mechaber.query.filter_by(mechaber_name=mechaber_name).first_or_404()
# page = request.args.get("page", 1, type=int)
# mekorot = sefer.mekorot.order_by(Makor.ref).paginate(
# page, current_app.co... | 56e1b0130ec3f14c389c8d1e4e31fe500cd3a5d3 | 10,728 |
def get_symmetry_projectors(character_table, conjugacy_classes, print_results=False):
"""
:param character_table: each row gives the characters of a different irreducible rep. Each column
corresponds to a different conjugacy classes
:param conjugacy_classes: List of lists of conjugacy class elements
... | 8780ef1a9ebb3f6e6960d04d07677e323e7565b9 | 10,729 |
from typing import List
def is_permutation_matrix(matrix: List[List[bool]]) -> bool:
"""Returns whether the given boolean matrix is a permutation matrix."""
return (all(sum(v) == 1 for v in matrix) and
sum(any(v) for v in matrix) == len(matrix)) | b53d6f4ba6e8e1ba445783350de831b614aa187e | 10,730 |
import torch
def DPT_Hybrid(pretrained=True, **kwargs):
""" # This docstring shows up in hub.help()
MiDaS DPT-Hybrid model for monocular depth estimation
pretrained (bool): load pretrained weights into model
"""
model = DPTDepthModel(
path=None,
backbone="vitb_rn50_384",
n... | 0a5cb661e9e0f08daae73b8c49ba8324e0cfb3e9 | 10,731 |
def show_counts(input_dict):
"""Format dictionary count information into a string
Args:
input_dict (dictionary): input keys and their counts
Return:
string: formatted output string
"""
out_s = ''
in_dict_sorted = {k: v for k, v in sorted(input_dict.items(), key=lambda item... | 078d1f7599b22741f474c0e6d1b02f44edfc1f9b | 10,732 |
def encipher_railfence(message,rails):
"""
Performs Railfence Encryption on plaintext and returns ciphertext
Examples
========
>>> from sympy.crypto.crypto import encipher_railfence
>>> message = "hello world"
>>> encipher_railfence(message,3)
'horel ollwd'
Parameters
========... | b1a56cdb255065b18caa4ba6da1fa11759f87152 | 10,733 |
import inspect
def format_signature(name: str, signature: inspect.Signature) -> str:
"""Formats a function signature as if it were source code.
Does not yet handle / and * markers.
"""
params = ', '.join(
format_parameter(arg) for arg in signature.parameters.values())
if signature.return_... | a14fde11850d420d15d2f9d7f3ac4cbe9aee03cc | 10,734 |
def extract_ratios_from_ddf(ddf):
"""The same as the df version, but works with
dask dataframes instead."""
# we basicaly abuse map_partition's ability to expand indexes for lack of a working
# groupby(level) in dask
return ddf.map_partitions(extract_ratios_from_df, meta={'path': str, 'ratio': str, ... | fcb816677d3d0816b2327d458a3fdd1b820bac9e | 10,735 |
def check_if_prime(number):
"""checks if number is prime
Args:
number (int):
Raises:
TypeError: if number of type float
Returns:
[bool]: if number prime returns ,True else returns False
"""
if type(number) == float:
raise TypeError("TypeError: entered float ty... | 0a15a4f133b12898b32b1f52a317939cf5e30d34 | 10,736 |
import inspect
def get_signatures() -> {}:
"""
Helper method used to identify the valid arguments that can be passed
to any of the pandas IO functions used by the program
:return: Returns a dictionary containing the available arguments for each pandas IO method
"""
# Creates an empty dictionar... | 243b798e1c4c57a89749fff1d33be660ab4e973b | 10,737 |
import os
import json
def _load_flags():
"""Load flag definitions.
It will first attempt to load the file at TINYFLAGS environment variable.
If that does not exist, it will then load the default flags file bundled
with this library.
:returns list: Flag definitions to use.
"""
path = os.g... | ebf3e78296c2fd8e4590f87f87bd27b9252539f8 | 10,738 |
from typing import Optional
from typing import Union
import os
def _get_indentation_option(explicit: Optional[Union[str, int]] = None) -> Optional[str]:
"""Get the value for the ``indentation`` option.
Args:
explicit (Optional[Union[str, int]]): the value explicitly specified by user,
:da... | ea1cfff674d620d879efec5490bbb13563e47bf4 | 10,739 |
from typing import List
def batch_answer_same_context(questions: List[str], context: str) -> List[str]:
"""Answers the questions with the given context.
:param questions: The questions to answer.
:type questions: List[str]
:param context: The context to answer the questions with.
:type context: s... | b58df72f1252427ea3e58e2f8379b8e77ea55273 | 10,740 |
import torch
def complex_multiplication(x: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
"""
Multiplies two complex-valued tensors. Assumes the tensor has a named dimension "complex".
Parameters
----------
x : torch.Tensor
Input data
y : torch.Tensor
Input data
Returns
... | ed427e8f79c5bcf782da4e1c21b02528a2ccb96d | 10,741 |
import typing
def dynamic_embedding_lookup(keys: tf.Tensor,
config: de_config_pb2.DynamicEmbeddingConfig,
var_name: typing.Text,
service_address: typing.Text = "",
skip_gradient_update: bool = False,
... | c1d69548e60ff00e55ab04fe83607cae31b6558c | 10,742 |
def register_unary_op(registered_name, operation):
"""Creates a `Transform` that wraps a unary tensorflow operation.
If `registered_name` is specified, the `Transform` is registered as a member
function of `Series`.
Args:
registered_name: the name of the member function of `Series` corresponding
to ... | c0fb56a8e93936a4c45e199e28889ccef67d19de | 10,743 |
def add_climatology(data, clim):
"""Add 12-month climatology to a data array with more times.
Suppose you have anomalies data and you want to add back its
climatology to it. In this sense, this function does the opposite
of `get_anomalies`. Though in this case there is no way to obtain
the climatol... | 28845fc1455bc317d158b503ed07a7d0c1af5655 | 10,744 |
from typing import List
def already_exists(statement: str, lines: List[str]) -> bool:
"""
Check if statement is in lines
"""
return any(statement in line.strip() for line in lines) | 194d8c6c48609f5a2accacdb2ed0857815d48d1d | 10,745 |
import random
def uniform(lower_list, upper_list, dimensions):
"""Fill array """
if hasattr(lower_list, '__iter__'):
return [random.uniform(lower, upper)
for lower, upper in zip(lower_list, upper_list)]
else:
return [random.uniform(lower_list, upper_list)
fo... | 59bcb124f0d71fd6e5890cd1d6c200319ab5910e | 10,746 |
import torch
def prepare_data(files, voxel_size, device='cuda'):
"""
Loads the data and prepares the input for the pairwise registration demo.
Args:
files (list): paths to the point cloud files
"""
feats = []
xyz = []
coords = []
n_pts = []
for pc_file in files:
... | 1c11444d4f6ca66396651bb49b8c655bedf6b8fa | 10,747 |
def reshape(box, new_size):
"""
box: (N, 4) in y1x1y2x2 format
new_size: (N, 2) stack of (h, w)
"""
box[:, :2] = new_size * box[:, :2]
box[:, 2:] = new_size * box[:, 2:]
return box | 56fbeac7c785bd81c7964d7585686e11864ff034 | 10,748 |
import json
def sort_actions(request):
"""Sorts actions after drag 'n drop.
"""
action_list = request.POST.get("objs", "").split('&')
if len(action_list) > 0:
pos = 10
for action_str in action_list:
action_id = action_str.split('=')[1]
action_obj = Action.object... | 80f2042858f7a0ecad3663ae4bf50ad73935be3b | 10,749 |
def fetch_file(parsed_url, config):
"""
Fetch a file from Github.
"""
if parsed_url.scheme != 'github':
raise ValueError(f'URL scheme must be "github" but is "{parsed_url.github}"')
ghcfg = config.get('github')
if not ghcfg:
raise BuildRunnerConfigurationError('Missing configur... | c688a68aeaa4efa0cda21f3b58a94075e4555004 | 10,750 |
import calendar
def number_of_days(year: int, month: int) -> int:
"""
Gets the number of days in a given year and month
:param year:
:type year:
:param month:
:type month:
:return:
:rtype:
"""
assert isinstance(year, int) and 0 <= year
assert isinstance(month, int) and 0 < ... | d585f037292eef36ecc753fbf702035577513a15 | 10,751 |
import six
import sys
def safe_decode(text, incoming=None, errors='strict'):
"""Decodes incoming str using `incoming` if they're not already unicode.
:param incoming: Text's current encoding
:param errors: Errors handling policy. See here for valid
values http://docs.python.org/2/library/codecs.h... | 8bd5a4ef516f925f7967ab50dffff0d7273f547c | 10,752 |
from functools import reduce
def medstddev(data, mask=None, medi=False, axis=0):
"""
This function computes the stddev of an n-dimensional ndarray with
respect to the median along a given axis.
Parameters:
-----------
data: ndarray
A n dimensional array frmo wich caculate the median s... | bbab9eede714d7c64344af271f8b6e817723d837 | 10,753 |
def load_npz(filename: FileLike) -> JaggedArray:
""" Load a jagged array in numpy's `npz` format from disk.
Args:
filename: The file to read.
See Also:
save_npz
"""
with np.load(filename) as f:
try:
data = f["data"]
shape = f["shape"]
re... | 640add32dab0b7bd12784a7a29331b59521a0f8a | 10,754 |
import re
def _egg_link_name(raw_name: str) -> str:
"""
Convert a Name metadata value to a .egg-link name, by applying
the same substitution as pkg_resources's safe_name function.
Note: we cannot use canonicalize_name because it has a different logic.
"""
return re.sub("[^A-Za-z0-9.]+", "-", r... | 923ff815b600b95ccb5750a8c1772ee9156e53b2 | 10,755 |
def my_view(request):
"""Displays info details from nabuco user"""
owner, c = User.objects.get_or_create(username='nabuco')
# Owner of the object has full permissions, otherwise check RBAC
if request.user != owner:
# Get roles
roles = get_user_roles(request.user, owner)
# Get ... | 55c3443f24d56b6ea22e02c9685d6057dfc79c7e | 10,756 |
def handler500(request):
"""
Custom 500 view
:param request:
:return:
"""
return server_error(request, template_name='base/500.html') | 91db9daeaac6f7f6b2207a3c8be7fa09f932b50f | 10,757 |
def get_badpixel_mask(shape, bins):
"""Get the mask of bad pixels and columns.
Args:
shape (tuple): Shape of image.
bins (tuple): CCD bins.
Returns:
:class:`numpy.ndarray`: 2D binary mask, where bad pixels are marked with
*True*, others *False*.
The bad pixels are foun... | 2e636aef86d2462815683a975ef99fbcdeeaee19 | 10,758 |
def model_fn(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... | d4883d451b749f06c718d37f1a49e4f4709d6695 | 10,759 |
import six
import yaml
def maybe_load_yaml(item):
"""Parses `item` only if it is a string. If `item` is a dictionary
it is returned as-is.
Args:
item:
Returns: A dictionary.
Raises:
ValueError: if unknown type of `item`.
"""
if isinstance(item, six.string_types):
... | 9288012f0368e2b087c9ef9cd9ffaca483b4f11b | 10,760 |
def histeq(im,nbr_bins=256):
"""histogram equalize an image"""
#get image histogram
im = np.abs(im)
imhist,bins = np.histogram(im.flatten(),nbr_bins,normed=True)
cdf = imhist.cumsum() #cumulative distribution function
cdf = 255 * cdf / cdf[-1] #normalize
#use linear interpolation of cdf to ... | bbb0e758e519a7cfcc866e3193cd1ff26bf5efbc | 10,761 |
def txgamma(v, t, gamma, H0):
"""
Takes in:
v = values at z=0;
t = list of redshifts to integrate over;
gamma = interaction term.
Returns a function f = [dt/dz, d(a)/dz,
d(e'_m)/dz, d(e'_de)/dz,
d(... | a1506ea0b54f468fd63cd2a8bd96e8a9c46a92f3 | 10,762 |
def text_pb(tag, data, description=None):
"""Create a text tf.Summary protobuf.
Arguments:
tag: String tag for the summary.
data: A Python bytestring (of type bytes), a Unicode string, or a numpy data
array of those types.
description: Optional long-form description for this summary, ... | 43d652ebb9ab1d52c0514407a3c47d56816cbb65 | 10,763 |
def sanitize_input(args: dict) -> dict:
"""
Gets a dictionary for url params and makes sure it doesn't contain any illegal keywords.
:param args:
:return:
"""
if "mode" in args:
del args["mode"] # the mode should always be detailed
trans = str.maketrans(ILLEGAL_CHARS, ' ' * len(ILL... | 063d314cb3800d24606b56480ce63b7dda3e8e51 | 10,764 |
def sum_to(containers, goal, values_in_goal=0):
"""
Find all sets of containers which sum to goal, store the number of
containers used to reach the goal in the sizes variable.
"""
if len(containers) == 0:
return 0
first = containers[0]
remain = containers[1:]
if first > goal:
... | db5297929332a05606dec033318ca0d7c9661b1d | 10,765 |
def rt2add_enc_v1(rt, grid):
"""
:param rt: n, k, 2 | log[d, tau] for each ped (n,) to each vic (k,)
modifies rt during clipping to grid
:param grid: (lx, ly, dx, dy, nx, ny)
lx, ly | lower bounds for x and y coordinates of the n*k (2,) in rt
dx, dy | step sizes of the regular grid
... | 3af0b8e15fdcc4d9bbeb604faffbd45cf013e86b | 10,766 |
import heapq
def draw_with_replacement(heap):
"""Return ticket drawn with replacement from given heap of tickets.
Args:
heap (list): an array of Tickets, arranged into a heap using heapq.
Such a heap is also known as a 'priority queue'.
Returns:
the Ticket with the least tick... | 06eb982ecf32090da51f02356a6996429773e233 | 10,767 |
import requests
import platform
def is_docker_reachable(docker_client):
"""
Checks if Docker daemon is running.
:param docker_client : docker.from_env() - docker client object
:returns True, if Docker is available, False otherwise.
"""
errors = (
docker.errors.APIError,
reques... | 9bea3a564d9357c5a700c9abbfaa36564f4b9adf | 10,768 |
def get_string(entry):
"""
This function ...
:param entry:
:return:
"""
value = entry.split(" / ")[0].rstrip()
return value | 38a1dc41fd06b49aa8724cc783466b485c9017fb | 10,769 |
from typing import Any
import string
import os
import yaml
def read_yaml_env(fname: str) -> Any:
"""Parse YAML file with environment variable substitution.
Parameters
----------
fname : str
yaml file name.
Returns
-------
table : Any
the object returned by YAML.
"""
... | 5c3b929bb4b76d2c041b2db92649a62a5d91e61a | 10,770 |
import collections
def get_top_words(words):
"""
Получить список наиболее часто встречающихся слов, с указанием частоты
:param words: список слов для анализа
:return: [(слово1, количество повторений слова1), ..]
"""
return collections.Counter(words).most_common() | 632317f57e734a93b6f3f20dfef001028b40c6b3 | 10,771 |
def get_slope(x, y, L):
"""
Funcao que retorna o slope da serie temporal dos dados
"""
try:
x=np.array(x).reshape(-1, 1)
y=np.array(y).reshape(-1, 1)
lr=LinearRegression()
lr.fit (x[:L],y[:L])
return lr.coef_[0][0]
except:
return 0 | 23f3419049ee1372d5963823e2f52b895bc766e8 | 10,772 |
from typing import Dict
from typing import Any
def _minimize_price(price: Dict[str, Any]) -> Price:
"""
Return only the keys and values of a price the end user would be interested in.
"""
keys = ['id', 'recurring', 'type', 'currency', 'unit_amount', 'unit_amount_decimal', 'nickname',
'prod... | 7414e0f3e5ae11f55b5781a679e593294122aed2 | 10,773 |
def project(signals, q_matrix):
"""
Project the given signals on the given space.
Parameters
----------
signals : array_like
Matrix with the signals in its rows
q_matrix : array_like
Matrix with an orthonormal basis of the space in its rows
Returns
-------
proj_sig... | 0d6aa780d0d424260df5f8391821c806e12c81e5 | 10,774 |
def all_movies():
"""
Returns all movie in the database for Movies
service
"""
movies = ut.get_movies()
if len(movies) == 0:
abort(404)
return make_response(jsonify({"movies":movies}),200) | d8b2e3a66adf52830d7027953c22071449d2b29a | 10,775 |
def format_map(mapping, st):
"""
Format string st with given map.
"""
return st.format_map(mapping) | 462e0a744177d125db50739eac1f2e7a62128010 | 10,776 |
def communities_greedy_modularity(G,f):
"""
Adds a column to the dataframe f with the community of each node.
The communitys are detected using greedy modularity.
G: a networkx graph.
f: a pandas dataframe.
It works with networkx vesion: '2.4rc1.dev_20190610203526'
"""
if not(set(f.name... | cfca6ef66730f3a6ef467f1c51c66c5d46296351 | 10,777 |
import json
def load_loglin_stats(infile_path):
"""read in data in json format"""
# convert all 'stats' to pandas data frames
with open(infile_path) as infile:
data = json.load(infile)
new_data = {}
for position_set in data:
try:
new_key = eval(position_set)
ex... | c307ff2cf4e07bbb7843971cceaf74744422276c | 10,778 |
def _simple_logistic_regression(x,y,beta_start=None,verbose=False,
CONV_THRESH=1.e-3,MAXIT=500):
"""
Faster than logistic_regression when there is only one predictor.
"""
if len(x) != len(y):
raise ValueError, "x and y should be the same length!"
if beta_start is ... | c37190b167e634df31127f79163aaeb56bac217e | 10,779 |
def preemphasis(signal,coeff=0.95):
"""perform preemphasis on the input signal.
:param signal: The signal to filter.
:param coeff: The preemphasis coefficient. 0 is no filter, default is 0.95.
:returns: the filtered signal.
"""
return np.append(signal[0],signal[1:]-coeff*signal[:-1]) | c5173708e7b349decd34ac886493103eaadb023d | 10,780 |
from sacremoses import MosesTokenizer
from sacremoses import MosesPunctNormalizer
def build_moses_tokenizer(tokenizer: MosesTokenizerSpans,
normalizer: MosesPunctNormalizer = None) -> Callable[[str], List[Token]]:
"""
Wrap Spacy model to build a tokenizer for the Sentence class.
... | 0dee31ab9030e387dd6907efad60c188eb0241b2 | 10,781 |
from typing import Callable
from typing import Hashable
from typing import Union
def horizontal_block_reduce(
obj: T_DataArray_or_Dataset,
coarsening_factor: int,
reduction_function: Callable,
x_dim: Hashable = "xaxis_1",
y_dim: Hashable = "yaxis_1",
coord_func: Union[str, CoordFunc] = coarsen... | 07fc497ae8c5cd90699bc73bfbeab705c13ed0c6 | 10,782 |
def statements_api(context, request):
"""List all the statements for a period."""
dbsession = request.dbsession
owner = request.owner
owner_id = owner.id
period = context.period
inc_case = case([(AccountEntry.delta > 0, AccountEntry.delta)], else_=None)
dec_case = case([(AccountEntry.delta ... | 87a1ec3e5fc5730eda30367a5f9f34aef6cf7339 | 10,783 |
def fp(x):
"""Function used in **v(a, b, th, nu, dimh, k)** for **analytic_solution_slope()**
:param x: real number
:type x: list
:return: fp value
:rtype: list
"""
rx = np.sqrt(x * 2 / np.pi)
s_fresnel, c_fresnel = sp.fresnel(rx)
return - 2 * 1j * np.sqrt(x) * np.exp(-1j * x) * np.s... | 202000557fb239e589ffd4d7b9709b60678ab784 | 10,784 |
def get_truck_locations(given_address):
"""
Get the location of the food trucks in Boston TODAY within 1 mile
of a given_address
:param given_address: a pair of coordinates
:return: a list of features with unique food truck locations
"""
formatted_address = '{x_coordinate}, {y_coordinate}'.... | f1d5e290c5c46e1587a2f98c2e82edee3890fc05 | 10,785 |
import inspect
import warnings
def _getRelevantKwds(method, kwds):
"""return kwd args for the given method, and remove them from the given kwds"""
argspec = inspect.getargspec(method)
d = dict()
for a in kwds:
if a not in argspec.args:
warnings.warn("Unrecognized kwd: {!r}".format(... | bca410b99e750f233a5e4476413e6bacfa52dcb9 | 10,786 |
import requests
def find_overview_details(park_code):
""" Find overview details from park code """
global API_KEY
fields = "&fields=images,entranceFees,entrancePasses,operatingHours,exceptions"
url = "https://developer.nps.gov/api/v1/parks?parkCode=" + park_code + "&api_key=" + API_KEY + fields
... | 95cf281828154c45eae1e239f33d2de8bcf9e7fa | 10,787 |
import torch
def embed_nomenclature(
D,
embedding_dimension,
loss="rank",
n_steps=1000,
lr=10,
momentum=0.9,
weight_decay=1e-4,
ignore_index=None,
):
"""
Embed a finite metric into a target embedding space
Args:
D (tensor): 2D-cost matrix of the finite metric
... | 1e9ca98dec0c3e42af0af483b6e9ef9efa11b225 | 10,788 |
def raw_env():
"""
To support the AEC API, the raw_env() function just uses the from_parallel
function to convert from a ParallelEnv to an AEC env
"""
env = parallel_env()
env = parallel_to_aec(env)
return env | dcb491c2beb50f73ba0fdab96bcd069916ce9b6d | 10,789 |
def cmd_line(preprocessor: Preprocessor, args: str) -> str:
"""the line command - prints the current line number"""
if args.strip() != "":
preprocessor.send_warning("extra-arguments", "the line command takes no arguments")
context = preprocessor.context.top
pos = context.true_position(preprocessor.current_positio... | 061bcf2ced6c22c77d81bb30ec00a5c1964c3624 | 10,790 |
import tempfile
import zipfile
import click
import os
def install_from_zip(pkgpath, install_path, register_func, delete_after_install=False):
"""Install plugin from zipfile."""
logger.debug("%s is a file, attempting to load zip", pkgpath)
pkgtempdir = tempfile.mkdtemp(prefix="honeycomb_")
try:
... | 16c430ed97e1e3ee29589bec42a103f7374bf60b | 10,791 |
from xml.dom import expatbuilder
from xml.dom import pulldom
def parse(file, parser=None, bufsize=None):
"""Parse a file into a DOM by filename or file object."""
if parser is None and not bufsize:
return expatbuilder.parse(file)
else:
return _do_pulldom_parse(pulldom.parse, (file,),
... | 0d4bc592143ecb7c093eceaf4f5fe0d18869ea9c | 10,792 |
import hashlib
def create_hash256(max_length=None):
"""
Generate a hash that can be used as an application secret
Warning: this is not sufficiently secure for tasks like encription
Currently, this is just meant to create sufficiently random tokens
"""
hash_object = hashlib.sha256(force_bytes(g... | 4856be59c475bcfc07137b62511de4d5c7531eb3 | 10,793 |
from io import StringIO
def assert_content_in_file(file_name, expected_content):
"""
Fabric assertion: Check if some text is in the specified file (result of installing a test product)
Provision dir: PROVISION_ROOT_PATH
:param file_name: File name
:param expected_content: String to be found in fil... | eba68222d39c55902da1c4c4ae7055b7edc170e0 | 10,794 |
import requests
import re
import os
def generate_substrate_fasta(df):
""" gemerates fasta sequence files containing sequences of
all proteins that contain phosphosites that do not have kinase
annotations in PSP or Networkin. The outputs of the function
will be used as input to run Networkin locally an... | 7e1350444fba35331977976c19607bb34915e2f0 | 10,795 |
import math
import numpy
def _calculate_hwp_storage_fut(
hwp_shapes, base_dataset_uri, c_hwp_uri, bio_hwp_uri, vol_hwp_uri,
yr_cur, yr_fut, process_pool=None):
"""Calculates carbon storage, hwp biomassPerPixel and volumePerPixel due to
harvested wood products in parcels on current landscape.
... | 71b597c62014c120a3deb99ceea14d84612e3b19 | 10,796 |
from datetime import datetime
def test_function(client: MsGraphClient, args):
"""
Performs basic GET request to check if the API is reachable and authentication is successful.
Returns ok if successful.
"""
response = client.ms_client.http_request(
method='GET', url_suffix='securit... | 24a66cca04c9493f7c0bbe13b54e8793188e0924 | 10,797 |
import os
def load(path='db'):
"""Recursivly load a db directory"""
if not os.path.isabs(path):
path = os.path.abspath(path)
env["datastore"].update({
"type": "yamldir",
"path": path,
})
return loaddir(path) | a51ece0de411618de0bef955adb596f8ea80efe5 | 10,798 |
def wcxf2arrays_symmetrized(d):
"""Convert a dictionary with a Wilson coefficient
name followed by underscore and numeric indices as keys and numbers as
values to a dictionary with Wilson coefficient names as keys and
numbers or numpy arrays as values.
In contrast to `wcxf2arrays`, here the numpy ... | 6cca03761b9799a3af7b933877ff70d6d68f7644 | 10,799 |
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