content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def _entity_namespace_key(entity, key):
"""Return an entry from an entity_namespace.
Raises :class:`_exc.InvalidRequestError` rather than attribute error
on not found.
"""
ns = entity.entity_namespace
try:
return getattr(ns, key)
except AttributeError as err:
util.raise_(... | ffd063523a8011a8ee2dd3700920a0523465d6cc | 3,654,508 |
def get_messages(mtype, read=False, uid=None):
""" Returns query for messages. If `read` is True it only queries for unread messages """
query = Message.select().where(Message.mtype << mtype)
query = query.where(Message.receivedby == current_user.uid if not uid else uid)
if read:
query = query.w... | 7959a0510d8f6794ff40d8467d09b0833279be10 | 3,654,509 |
import numpy
def coords_to_indices(coords, top, left, csx, csy, shape, preserve_out_of_bounds=False):
"""
Convert coordinates to array indices using the given specs.
Coordinates outside of the shape are not returned.
:param coords: Tuple of coordinates in the form ([x...], [y...])
:param top: T... | 89b99ffc159c56855792d0daeb8bdb5a5d04ad9f | 3,654,510 |
def sanitize_vcf_file(vcf_file, out_file, snp_log_file, sample_log_file, logging, min_count=1, max_missing=0.25,
max_alt_states=4, disruptive_threshold=1,window_size=30,max_snps=2):
"""
Filter a user provided vcf and write a filtered vcf file
Parameters
----------
vcf_file [str... | b5d96e9224b5eddad1dff8dcf2caf558522376bc | 3,654,511 |
from typing import Optional
from typing import Any
def geq(column: str, value: Optional[Any]) -> str:
"""
>>> geq("col", None)
'1'
>>> geq("col", 1)
'col >= 1'
>>> geq("col", "1")
"col >= '1'"
"""
if not value:
return "1"
if isinstance(value, str):
return f"{col... | 9216b8e2480232840ad37d8fe0e5c0f07b88873f | 3,654,512 |
from keras.layers import Conv2D, Dense
from palmnet.layers import Conv2DCustom
from palmnet.layers.sparse_facto_sparse_tensor_deprecated import SparseFactorisationDense
def count_model_param_and_flops(model, dct_layer_sparse_facto_op=None):
"""
Return the number of params and the number of flops of 2DConvolut... | 142b04ad327f662d315d7c92322df8aef2ae9871 | 3,654,513 |
def longest_match(list1, list2):
"""
Find the length of the longest substring match between list1 and list2.
>>> longest_match([], [])
0
>>> longest_match('test', 'test')
4
>>> longest_match('test', 'toast')
2
>>> longest_match('supercalifragilisticexpialidocious', 'mystical califor... | 4a84dacbb0d59fc7f9c4b59e87e55c72416b8c80 | 3,654,514 |
def deserialize_config(data, **kwargs):
"""Create instance of a JobConfiguration from a dict.
Parameters
----------
data : dict
Dictionary loaded from a serialized config file.
Returns
-------
JobConfiguration
"""
registry = Registry()
config_module = data["configurati... | eff887d4e676935742b8169c62a9a581b5f239ce | 3,654,515 |
import numpy
def pmat06(date1, date2):
"""
Wrapper for ERFA function ``eraPmat06``.
Parameters
----------
date1 : double array
date2 : double array
Returns
-------
rbp : double array
Notes
-----
The ERFA documentation is below.
- - - - - - - - - -
e r a P m... | 69b38637701d804ca83733d7f55fca1fd57a5b72 | 3,654,516 |
def _splitData(data):
"""Takes either a cursor or result set and returns result set and list of columns."""
if hasattr(data, 'fetchall'):
rows = data.fetchall()
cols = data.columns()
elif isinstance(data, list):
rows = data
if hasattr(rows[0], '_fields'):
cols = r... | 9953be08f29fb457782e5401c3dfded8f780924b | 3,654,517 |
import multiprocessing
def get_cpu_count():
"""
Try and estimate the number of CPU on the host. First using multiprocessing
native function, other using content of /proc/cpuinfo. If none of those
methods did work, 4 is returned.
"""
try:
cpucount = multiprocessing.cpu_count()
excep... | db58112537c4a111ec1ef24eeab70227678d6d1e | 3,654,518 |
def get_relation_data(collection, relation_paths):
"""Prepare relations for usage inside extend_relations."""
out = []
for path in relation_paths:
promote = path.get("promote", False)
numpy_path = []
for step in path["steps"]:
if isinstance(step, str):
ste... | 8b4cd9145995aee5e3c9b880073dfd10320b24e5 | 3,654,519 |
def generate_paddle_quads():
"""
This function builds a matrix of paddles, each row in the matrix
represents the paddle skin (four colors) and each column represents
the size.
"""
paddle_base_width = 32
paddle_height = 16
x = 0
y = paddle_height * 4
spritesheet = []
for _ ... | e82259d5e203257574c5ae91ad4a5c3a625e5b5a | 3,654,520 |
def cut(img):
"""
Applies central horizontal threshold in Fourier spectrum
"""
# Apply fourier transform and shift
img_fft = fftn(img)
img_fft_shift = fftshift(img_fft)
# Print spectrum before
plt.imshow(np.abs(img_fft_shift), cmap='gray', norm=LogNorm(vmin=5))
plt.show()
# Fi... | 74ce6db709aaa91fec2321dc6cc70fc6d5a8c552 | 3,654,521 |
def csrmm2(m, n, k, descrA, csrValA, csrRowPtrA, csrColIndA, B, handle=None,
C=None, nnz=None, transA=CUSPARSE_OPERATION_NON_TRANSPOSE,
transB=CUSPARSE_OPERATION_NON_TRANSPOSE, alpha=1.0, beta=0.0,
ldb=None, ldc=None, check_inputs=True):
""" multiply two sparse matrices: C = transA... | fffbecab90dfb831a4429aed759c0218b065aa4d | 3,654,522 |
def is_translated(path):
""" Checks if all files in the translation has at least one translation.
Arguments:
path (str): path to po-file
Returns: True if all files in translation has at least one translation,
otherwise False.
"""
po = polib.pofile(path)
files = []
for ... | eeacbbc8ff068684e56d79e1aaa65d564b2e33ec | 3,654,523 |
def pylm_component(name):
"""Decorator for registering a class to lightmetrica"""
def pylm_component_(object):
# Get base class
base = object.__bases__[0]
base.reg(object, name)
return object
return pylm_component_ | 531c7e3f224b824b438011d4be348a76154b3444 | 3,654,524 |
import torch
def dice_score(input_mask, target_mask, eps=1e-5):
"""
input mask: (B * K, HW) #probabilities [0, 1]
target_mask: (B * K, HW) #binary
"""
dims = tuple(range(1, input_mask.ndimension()))
intersections = torch.sum(input_mask * target_mask, dims) #(B, N)
cardinalities = torch.su... | 8fbe4b7aaec4a45d7dec4705e4c3feb348250b64 | 3,654,525 |
def append_write(filename="", text=""):
"""
appends a string at the end of a text file (UTF8)
and returns the number of characters added
"""
with open(filename, "a", encoding="utf-8") as f:
f.write(text)
return len(text) | 6767f61b6624b82d732e7277507d03c3f4daf04a | 3,654,526 |
import torch
def psnr(img1, img2):
"""
compute PSNR between two images
"""
MSE = torch.mean((img1-img2)**2)
return 10*torch.log10(1**2/MSE) | f216733631d224aa27f5c5a395c143c3768f8f28 | 3,654,527 |
def is_scalar(dims):
"""
Returns True if a dims specification is effectively
a scalar (has dimension 1).
"""
return np.prod(flatten(dims)) == 1 | d2f2f1a1f2dd66ec01d9e653315d37b4ee4990e1 | 3,654,528 |
def applyMinv(obj, inputs, shape_cache):
"""Simple wrapper around a component's applyMinv where we can reshape the
arrays for each input and expand any needed array elements into full arrays.
"""
inputkeys = sorted(inputs.keys())
for key in inputkeys:
pre_process_dicts(obj, key, inputs, sha... | 9fd805408bea659f26eec93b430e450ea9228145 | 3,654,529 |
import json
import requests
import time
def get_county_data():
"""Get the raw data from coronavirus-tracker-api.herokuapp.com."""
url = ('https://coronavirus-tracker-api.herokuapp.com/v2/locations?source=csbs')
raw_data = None
while raw_data is None:
try:
raw_data = json.loads(requests.request('GET'... | 33404a65e6242b7416304f7194dc2a5c7f073d5d | 3,654,531 |
def r2lm(measured_y, estimated_y):
"""
r^2 based on the latest measured y-values (r2lm)
Calculate r^2 based on the latest measured y-values. Measured_y and estimated_y must be vectors.
Parameters
----------
measured_y: numpy.array or pandas.DataFrame
estimated_y: numpy.array or pandas.Data... | f75c89ca3f99659a3e2e12555a3968745fad1007 | 3,654,532 |
def G_to_NX_sparse(X, Y):
"""convert sparse adj matrix to NetworkX Graph"""
Gs = []
N = len(Y)
for n in range(N):
x = X[n]
G = nx.DiGraph()
for i,j,w in x:
G.add_edge(i,j, weight=w)
Gs.append(G)
return Gs, Y | 8113ede05a0015119cceaa9c817b8bf3d46003c0 | 3,654,533 |
def pmf(k, n, a, b, loc=0):
"""JAX implementation of scipy.stats.betabinom.pmf."""
return lax.exp(logpmf(k, n, a, b, loc)) | efba7202231dde7d0dec1e56df7a52dccf7135a0 | 3,654,534 |
def discrete_bottleneck(x,
hidden_size,
z_size,
filter_size,
name,
mode=None,
startup_steps=50000,
bottleneck_kind='dvq',
num_bl... | ec1576b2b6a19a03995ec6dfb9a67592b925a28c | 3,654,535 |
def binarize_categorical(x, ids):
""" replace categorical feature with multiple binary ones """
x_ = np.zeros((x.shape[0], 1))
for idx in ids:
x_ = np.hstack((x_, binarize_categorical_feature(x[:, idx:idx+1])))
x = np.delete(x, ids, axis=1)
x = np.hstack((x, x_[:, 1:]))
return x | 625b551b437297c6a0c48f5ebfe2796c3be84c89 | 3,654,536 |
def import_json_dataset(fileset):
"""Returns a list of imported raw JSON data for every file in the fileset.
"""
d = []
for f in fileset:
d.append(import_json_data(f))
return d | 043720f9400cf2734598f6fe476077e004b8ef69 | 3,654,537 |
import math
def angle_difference(angle1, angle2):
"""
Calculates the difference between the given angles in clockwise direction as radians.
:param angle1: float
:param angle2: float
:return: float; between 0 and 2*Pi
"""
if (angle1 > 0 and angle2 >= 0) and angle1 > angle2:
return ... | 377d1915e58a96b7f1526dceb31febf45c90567b | 3,654,538 |
def merge_nd(nd_cdp, nd_lldp):
""" Merge CDP and LLDP data into one structure """
neis = dict()
nd = list()
for n in nd_lldp:
neis[(n['local_device_id'], n['remote_device_id'], n['local_int'], n['remote_int'])] = n
for n in nd_cdp:
# Always prefer CDP, but grab description from L... | 90d55ffdabb6c28198ee4c59bc36fdcb6fa54e62 | 3,654,539 |
def combine_divisions(division):
"""Return the new pattern after the rules have been applied to every division"""
size = int(sqrt(len(division)))
matrix = []
for r in xrange(size):
matrix.append([])
for c in xrange(r * size, (r + 1) * size):
matrix[len(matrix) - 1].append(di... | a112449421603a227e4ee470330aa1a1ece47762 | 3,654,540 |
import string
def modified_greedy(sentences,
tokenized,
model,
stopwords,
original_indices,
sent_representations,
objective_function,
min_sentence_length):
"""Implementation ... | b542c025fe870e1e7d41d33349de10a395a17eb3 | 3,654,542 |
def noiseless(rho, unitary):
"""Returns the noiseless predictions."""
rhotilde = unitary @ rho @ unitary.conj().T
elt = rhotilde[0, 0]
if elt >= 0.49999999:
return 0, elt
return 1, elt | bfa265046361b159e7d264aa8312b75cd7a0df3f | 3,654,543 |
def __get_service_info_from_thrift(root_path, idl_service, need_test_methods):
"""从指定IDL_Service和request_config配置表中，获取测试方法和Request的映射表"""
customized_request_config = yaml.load(
open(os.path.join(root_path, 'test_red', 'request_config.yaml')))
method_request = collections.OrderedDict()
idl_meth... | 0b736bb6b5411904bc28f887e6596c1242c324c9 | 3,654,544 |
def energy_calc(p, t):
"""
Calculates energy from power and time using the formula:
energy = power * time
Parameters
----------
p: Int or float
The power value of the equation.
t: Int or float
The time value of the equation (seconds).
Returns
-------
Int
... | 7df3180fdb56989e62a69305763455edbfa44ebc | 3,654,545 |
import logging
def api_images_list_json(version):
"""
Return Docker Image listing https://docs.docker.com/engine/api/v1.41/#tag/Image
:param version: Docker API version
:return: string of fake images associated with honeypot.
"""
logging.info("images-list - %s, %s, %s, %s, %s" % (
ver... | 083911840c02ddc79af5ed457c42a29a19f1c57f | 3,654,547 |
def _handle_eval_return(self, result, col, as_pyranges, subset):
"""Handle return from eval.
If col is set, add/update cols. If subset is True, use return series to subset PyRanges.
Otherwise return PyRanges or dict of data."""
if as_pyranges:
if not result:
return pr.PyRanges()
... | 84698bcb3b1f1e961ac7f3c4e347d65ce0790066 | 3,654,548 |
def compute_sigma0_sparse(V, dX, W_sensors, W_points, W_observations, column_dict):
"""
Computes the resulting standard deviation of the residuals for the current state of the bundle network.
Parameters
----------
V : ndarray
An array of residuals of the difference between registered meas... | 05606efe21d61f67539eae627caea976a532f85f | 3,654,549 |
def fill(bitdef, value):
"""
Fill undefined bits with a value.
For example ``1..0100.1`` becomes ``111010011`` when filled with 1s.
Args:
bitdef (str): The bitdef to fill.
value (str): The value to fill with, "0" or "1".
Returns:
str: The filled bitdef.
"""
output ... | eef3ac59a2a7c4d1a25851a2ca14b3ffed6d1463 | 3,654,551 |
import requests
import json
def get_cman_info(state):
"""
Will take a list of congressmen and return the relevant attributes
:param congress_list: list of divs that contain congress data
:param state: state you are scraping
:return: list of relevant scraped attributes
"""
cman_attrs = []
... | afe180c4bbd930cfbfe42e28a769d07f2c4378cd | 3,654,552 |
def concatenate_data(data, field='normalized_data'):
"""
Concatenate trial data in a list of dictionaries
:param data: nested dict, contains all trial infos
:param field: str, dict key in info dict in general data structure
:return:
"""
time_series = np.concatenate([info[field] for info in d... | 7f3dfb7aed2ffedf2124a9f57df0abf8491d1af6 | 3,654,553 |
def _find_weight_ops(op, graph, weights):
""" Find the vars come from operators with weight.
"""
pre_ops = graph.pre_ops(op)
for pre_op in pre_ops:
### if depthwise conv is one of elementwise's input,
### add it into this same search space
if _is_depthwise(pre_op):
f... | 04e4a21079a3857815e39be3fe00e15aeac2f3b3 | 3,654,554 |
def get_GUI_presets_dict():
"""Return a dictionary of all of the available potential functions."""
preset_dict = {'cosine_potential': np.array([3.14, -6.28, 12.57, 0.01, 0,
0, 0, 0]).astype(str),
'two_gaussian_potential': np.array([2.67, -4, 4,... | 0034ecdbde2f27e1b8db25a82231fca9bc79485c | 3,654,555 |
def _escapeEnds(original):
"""Comment, function end.
Escape comment end, because non-greedy becomes greedy in context. Example:
blockCommentNonGreedy = '(\s*/\*[\s\S]+?\*/\s*){0,1}?'
"""
original = _escapeWildCard(original)
commentEscaped = original \
.replace(commentEndEscape, commentE... | 5a0df98f42d2df2b424cd6bfa7c533e0016557fe | 3,654,556 |
def handle_bad_request(error: BadRequest) -> Response:
"""Render the base 400 error page."""
rendered = render_template("base/400.html", error=error,
pagetitle="400 Bad Request")
response: Response = make_response(rendered)
response.status_code = status.BAD_REQUEST
ret... | 70c6c835ef31839ff7b637443c414abbb549bcb0 | 3,654,557 |
import torch
def top_k_top_p_filtering(
logits: torch.FloatTensor,
top_k: int = 0,
top_p: float = 1.0,
filter_value: float = -float("Inf"),
min_tokens_to_keep: int = 1,
) -> torch.FloatTensor:
"""
Filter a distribution of logits using top-k and/or nucleus (top-p) filtering
Args:
... | 0c2f8392dcc6ada2afb1dc33575465e194a52199 | 3,654,558 |
def parseFimo(fimoFile, strand):
""" parse the fimo.txt file
Args:
the fimo.txt file
strand = single or double
Returns:
fimoDict: a dict between motif ID and a list of sequences it occurs in
"""
#dict to store for each motif list of seqs that it occurs in
fimoDict = {}
#read the fimo.txt file
with open... | ea6e0765c474e367653571e9a88e6449fc947ff5 | 3,654,559 |
def pad_batch_dimension_for_multiple_chains(
observed_time_series, model, chain_batch_shape):
""""Expand the observed time series with extra batch dimension(s)."""
# Running with multiple chains introduces an extra batch dimension. In
# general we also need to pad the observed time series with a matching batc... | ec072f3fa5318ee3f4c82dcc0d3697a5160b257f | 3,654,560 |
from typing import Union
import re
def get_bytes(size: Union[str, int]) -> int:
"""Converts string representation of bytes to a number of bytes.
If an integer is passed, it is returned as is (no conversion).
Args:
size (Union[str, int]): A string or integer representation of bytes to be converte... | 76cd67a0d581b79105a79bc84d66126d3201b07a | 3,654,561 |
def port_translation_func(req: AdvancedDataTypeRequest) -> AdvancedDataTypeResponse:
"""
Convert a passed in AdvancedDataTypeRequest to a AdvancedDataTypeResponse
"""
resp: AdvancedDataTypeResponse = {
"values": [],
"error_message": "",
"display_value": "",
"valid_filter_... | b8c41d8c3d3c2fa0a9e67b8ef9ff93422921e7e3 | 3,654,562 |
import random
def get_two_diff_order_index(start=0, stop=1, order=True, diff=True):
"""
Returns two integers from a range, they can be:
put in order (default) or unordered
always different(default) or can be repeated
start - integer (default = 0)
stop - integer (default= 1)
order -... | 7bd0e17efb969ea59e7a30d8fdaae55d901a718e | 3,654,564 |
import math
def GriewankRosenbrock(arr: np.ndarray, seed: int = 0) -> float:
"""Implementation for BBOB GriewankRosenbrock function."""
dim = len(arr)
r_x = np.matmul(_R(dim, seed, b"R"), arr)
# Slightly off BBOB documentation in order to center optima at origin.
# Should be: max(1.0, (dim**0.5) / 8.0) * r_... | 9a9ca4f043e60fb971c5212de33379c29aaade58 | 3,654,566 |
def listCurrentAuctionsByKeyword(username, keyword):
"""Listar os leilões que estão a decorrer"""
try:
valid = utils.validateTypes([keyword], [str])
if not valid:
return jsonify({'erro': 404})
auctions = db.listAuctions(keyword)
if auctions == "noResults":
... | c02c58a294b3d65821f36872dcf23e4f7abff49b | 3,654,567 |
from typing import Dict
def hash_dict(data: Dict) -> int:
"""
Hashes a Dictionary recursively.
List values are converted to Tuples.
WARNING: Hashing nested dictionaries is expensive.
"""
cleaned_dict: Dict = {}
def _clean_dict(data: Dict) -> Dict:
d: Dict = {}
for k, v in ... | 42b579151c90a42fadf2b53751978eec421ea03c | 3,654,569 |
def instrument_packages_ip_template(instrument, ip_version, template_name=None):
"""
Retrieves the specified instrument package template metadata
:param instrument: instrument used to make observation
:type instrument: str
:param ip_version: ip version description here
:type ip_version: float
... | 46d3cd57e05a64c03411c31d2b18ca47f670036d | 3,654,571 |
from typing import Literal
def add_feature_metadata(id, description, type):
"""Generate RDF metadata for a feature
:param id: if used to identify the feature
:param description: feature description
:param type: feature type
:return: rdflib graph after loading the feature
"""
g = Graph()
... | 0d4987807b3ed97baa50f8b14c588ef162b5c8ac | 3,654,572 |
import copy
def sink(input_flow_direction_raster):
"""
Creates a raster layer identifying all sinks or areas of internal drainage.
The value type for the Sink function output raster layer is floating point.
For more information, see
https://pro.arcgis.com/en/pro-app/help/data/imagery/sink-funct... | 6d1b22dacd48a0939b7822d62a4867b2b7574c42 | 3,654,573 |
def bad_multi_examples_per_input_estimator_out_of_range_input_refs(
export_path, eval_export_path):
"""Like the above (good) estimator, but the input_refs is out of range."""
estimator = tf.estimator.Estimator(model_fn=_model_fn)
estimator.train(input_fn=_train_input_fn, steps=1)
return util.export_model_a... | 539ec039451c53db72cb676881f48fbe45874dfa | 3,654,574 |
def vector_to_diagonal(v):
"""Converts a vector to a diagonal matrix with vector elements
as the diagonal elements of the matrix"""
diag_matrix = [[0 for i in range(len(v))] for j in range(len(v))]
for i in range(len(v)):
diag_matrix[i][i] = v[i]
return diag_matrix | 6cbaf54a083633a47af92acc7f69421ed68a1c0b | 3,654,575 |
from typing import Union
from pathlib import Path
from typing import List
def _get_filenames(path: Union[str, Path], media_type: MediaType) -> List[str]:
"""
Get filenames from a directory or a path to a file.
:param path: Path to the file or to the location that contains files.
:param media_type: Typ... | 953bcfce17c6db45772a8eac8890fa161c128322 | 3,654,576 |
from venusian import attach
def method(method_class):
"""Decorator to use to mark an API method.
When invoking L{Registry.scan} the classes marked with this decorator
will be added to the registry.
@param method_class: The L{Method} class to register.
"""
def callback(scanner, name, method_... | 4e40d265a4a5767686f0e37b4d1adf681ce36722 | 3,654,577 |
def generic_validator(check, error_message):
"""
Validator factory
>>> v = generic_validator(is_int, "invalid int")
>>> v(6)
6
>>> v("g")
Traceback (most recent call last):
...
ValidationError: [u'invalid int']
"""
# Validator closure
def inner_validator(value, *args, **... | 21134ecee1d8c23b10e94181c0c1aa602ce4b76e | 3,654,578 |
def get_molec_shape(mol, conf, confId, vdwScale=1.0,
boxMargin=2.0, spacing=0.2):
"""
Get the shape of a conformer of a molecule as a grid
representation.
"""
box = Chem.ComputeConfBox(conf)
sideLen = (box[1].x-box[0].x + 2*boxMargin,
box[1].y-box[0].y + 2*box... | 6a7b404224a116a52d70f7ab14d4301215c1700f | 3,654,579 |
import math
def autoencoder(dimensions=[784, 512, 256, 64]):
"""Build a deep denoising autoencoder w/ tied weights.
Parameters
----------
dimensions : list, optional
The number of neurons for each layer of the autoencoder.
Returns
-------
x : Tensor
Input placeholder to t... | d9cc8b6f2c8e7df0bc4fb580e1de20dc57f93c7a | 3,654,580 |
def _asymptotic_expansion_of_normalized_black_call(h, t):
"""
Asymptotic expansion of
b = Φ(h+t)·exp(x/2) - Φ(h-t)·exp(-x/2)
with
h = x/s and t = s/2
which makes
b = Φ(h+t)·exp(h·t) - Φ(h-t)·exp(-h·t)
exp(-(h²+t²)/2)
... | 9985b36e7f0dec1877d275a23ae747d9a57c1163 | 3,654,581 |
def date_read(date_string, *, convert_to_current_timezone: bool = False):
"""Read the given date (if possible)."""
return date_parse(date_string, convert_to_current_timezone=convert_to_current_timezone) | 96f21f7fcae995a9a17f6008c8e5a4161ed971f2 | 3,654,582 |
import urllib
def encode_name(name):
"""
Encode a unicode as utf-8 and then url encode that
string. Use for entity titles in URLs.
"""
return urllib.quote(name.encode('utf-8'), safe='') | 6e9d34516613ecdf0ce94fb9cfc594de7e76b72f | 3,654,583 |
def cmp_str(element1, element2):
"""
compare number in str format correctley
"""
try:
return cmp(int(element1), int(element2))
except ValueError:
return cmp(element1, element2) | 7c8df75bc1b1ad3997db4a4d6f1b58a37c4e1dd7 | 3,654,584 |
def post(text, appid=2, touser=None, toparty=None):
"""
party
"""
#print '=========',type(text)
if type(text) is unicode:
text = text.encode('utf8')
if not touser:
touser = []
if not toparty:
toparty = ['2']
url = 'https://qyapi.weixin.qq.com/cgi-bin/message/send?... | b2a92a274007b0502431a856457a244c12b925a9 | 3,654,587 |
import six
import codecs
def hex_encrypt(msg):
"""Hex encrypts a message.
:param bytes msg: string message to be encrypted.
:return: string for encrypted version of msg in hex.
:rtype: bytes
"""
if not cipher:
return msg
if not isinstance(msg, six.binary_type):
raise Value... | c2d913d181b8ceb33b3e7d99fc5f21b025da58ea | 3,654,588 |
import regex
async def filter_by_game_stats(opsdroid, string, room, action):
"""Match incoming messages against the current games stats."""
if room not in STAT_REGEXES.keys():
gamestats = await get_stat_names(opsdroid, room)
if not gamestats:
return []
STAT_REGEXES[room] = ... | 4971e5567c8a1b89aa47fdaab2e42e51620f475b | 3,654,590 |
def password_provider():
"""
Provides the full password check
"""
return [(n,) for n in range(5)] | afdb188844e4b0979528b290477130313679e4df | 3,654,591 |
def make_combiparameter(*args, **kwargs):
"""
Make a combined qcodes parameter.
Args:
*args : list of gates or parameters
(e.g. make_combiparameter("A1", "A3", station.gates.B1 ))
"""
station = qc.Station.default
parameters = []
for i in args:
if type(i) == str:
... | 6482187dc463c67e322a281181ba827eb39eb28d | 3,654,592 |
def get_delta_fmt(delta):
"""arbitrary colour formatting of rank delta
more red for bigger losses, more green for bigger gains
"""
col = (0, 0, 0, 255)
n = abs(delta)
s = delta
if delta < 0:
sat = min(n/200 + 0.2, 1)
r, g, b = hsv_to_rgb(0, sat, 1)
col = (r, g, b, 1)
... | a7860df4f19632c9623c39c38ac70a76f405ae56 | 3,654,593 |
def fit_pk_parms_1d(p0, x, f, pktype='pvoigt'):
"""
Performs least squares fit to find parameters for 1d analytic functions fit
to diffraction data
Required Arguments:
p0 -- (m) ndarray containing initial guesses for parameters
for the input peaktype
x -- (n) ndarray of coordinate... | 52dbff47fd8ad6f7727b0241bba48d2b10393a18 | 3,654,596 |
def tract_segmentation_single_example_lap (kdt_T_A, prototypes_T_A,sid, num_NN,T_A ):
""" step 1: tract segmentation from a single example using Jonker-Volgenant algorithm (LAPJV)
"""
E_t_filename= 'data/example/'+ str(sid) +'_'+str(tract_name)+'.trk'
print("Loa... | cc14e598f359fc9b92995bdc3a6a98192333b800 | 3,654,599 |
def url(method):
"""对于每一个URL的请求访问装饰器，在出错时返回对应的信息"""
@wraps(method)
def error_handler(*args, **kwargs):
try:
return success(method(*args, **kwargs))
except RequestError as r:
current_app.logger.exception(r)
# 返回对应异常类的字符串文档
return failed(reason... | cb2c36981372738b6b708d4e28566d4bb8ffcd90 | 3,654,600 |
def is_abbreviation(sentence):
"""
Evaluate a word to be an abbreviation if the immediate word before the
period contains a capital letter and not a single word sentence.
"""
sentence_split = sentence.split(" ")
if len(sentence_split) == 1:
return False
elif len(sentence_split[-1]) <... | a6f6ceae5b3b9adb7817a913e80a6af86b6d27d5 | 3,654,601 |
def compose_redis_key(vim_name, identifier, identifier_type="vdu"):
"""Compose the key for redis given vim name and vdu uuid
Args:
vim_name (str): The VIM name
identifier (str): The VDU or VNF uuid (NFVI based)
identifier_type (str): the identifier type. Default type is vdu. Also vnf is... | e9a03cf9ff704fea8b9cdf75c59695568e366649 | 3,654,602 |
def calGridID(locs, id, SPLIT = 0.0005):
"""
根据城市网格编号还原经纬度信息
:param locs:
:param id:
:param SPLIT=0.05:
"""
centerincrement = SPLIT/2.0
LNGNUM = int((locs['east'] - locs['west']) / SPLIT + 1)
latind = int(id / LNGNUM)
lngind = id - latind * LNGNUM
lat = (locs['south'] + latind * SPLIT)
lng = (locs['... | 8df119ff82bc1d3c14dbdfe358af6d956d6a52a2 | 3,654,603 |
def linear(x, *p):
"""[summary]
Arguments:
x {[type]} -- [description]
Returns:
[type] -- [description]
"""
return p[0] * x + p[1] | 07ef5fc7c5e78148528cccd09fe14c37cad22ead | 3,654,604 |
def convert_price_text(t):
"""
convert "$175/month' to 175
:param t:
:return: price, unit (i.e. 175, 'month')
"""
tok = t.split('$')[1]
if '/' in tok:
price, unit = tok.split('/')
else:
price = tok
unit = None
return float(price.strip().strip('$').replace(',... | b42d26dcd4eb1b2c2f8c5a63ddc9d48469e30a52 | 3,654,605 |
async def async_setup(hass, config):
"""Set up the WWLLN component."""
if DOMAIN not in config:
return True
conf = config[DOMAIN]
latitude = conf.get(CONF_LATITUDE, hass.config.latitude)
longitude = conf.get(CONF_LONGITUDE, hass.config.longitude)
identifier = '{0}, {1}'.format(latitud... | 3f0a4f5a017340780c8c1122425804e7862c3d0f | 3,654,606 |
from typing import Any
def __are_nearly_overlapped(
plane_predicted: NDArray[Any, np.int32],
plane_gt: NDArray[Any, np.int32],
required_overlap: np.float64,
) -> (bool, bool):
"""
Calculate if planes are overlapped enough (required_overlap %) to be used for PP-PR metric
:param required_overlap... | 7b686e7bb4b18e4e2e116cdfd14878acbcc4c92d | 3,654,607 |
def _get_prob_k_given_L(B, N=None):
"""
Helper function.
"""
if N is None:
N = int(B[0, 1])
return B / N | be1d0848b148b3413aaee2c5549bd6063e1f2d33 | 3,654,608 |
def base64_encode(s):
"""unicode-safe base64
base64 API only talks bytes
"""
if not isinstance(s, bytes):
s = s.encode('ascii', 'replace')
encoded = encodebytes(s)
return encoded.decode('ascii') | 6ef0722014aa56e22de102aa0ce8286416640f86 | 3,654,609 |
def _unpack_tableswitch(bc, offset):
"""
function for unpacking the tableswitch op arguments
"""
jump = (offset % 4)
if jump:
offset += (4 - jump)
(default, low, high), offset = _unpack(_struct_iii, bc, offset)
joffs = list()
for _index in xrange((high - low) + 1):
j, ... | af08ab85def5bf132227f20da8cb6032e2a9dff1 | 3,654,610 |
def force_orders(self, **kwargs):
"""User's Force Orders (USER_DATA)
GET /fapi/v1/forceOrders
https://binance-docs.github.io/apidocs/futures/en/#user-39-s-force-orders-user_data
Keyword Args:
symbol (str, optional)
autoCloseType (str, optional): "LIQUIDATION" for liquidation orders, ... | 6e848820e17e54df0f275ec4087d9c609d4e08fa | 3,654,611 |
def prosp_power_analysis_norm(d, sigma, pow_lev, alpha, direction):
"""
This function conducts pre-testing power analysis and
calculates the minimally required sample size for a normal sample.
@param d: difference between the mean differences under H1 and H0
@param sigma: standard deviation
@pa... | 319daf6434b774dcf3bf3f6f936a566e1640c175 | 3,654,612 |
def decision_tree_construction(examples, target_attribute, attributes, depth):
"""
:param examples: The data we will use to train the tree(x)
:param target_attribute: The label we want to classify(y)
:param attributes: The number(index) of the labels/attributes of the data-set
:return: The tree cor... | c9529deb71d3c0a89bbae053aae07e587d277255 | 3,654,613 |
import numpy
def mass_centered(geo):
""" mass-centered geometry
"""
geo = translate(geo, numpy.negative(center_of_mass(geo)))
return geo | 1081141d77383f857f986031fa03510fd2608741 | 3,654,614 |
def binaryMatrix(l, value=PAD_token):
"""
:param l:
:param value:
:return: seq: [3,4,5,0,0]
m: [[1],[1],[1],[0],[0]]
"""
m = []
for i, seq in enumerate(l):
m.append([])
for token in seq:
if token == PAD_token:
m[i].append(0)
... | 3c123b1ce8531bcde7c6673f8ca8a91f1300f0bb | 3,654,615 |
def load_map(mappath):
""" Attempt to load map with known loaders
"""
data = None
shirtloader = lambda path: fio.load_map(path)[0][0:3]
maploaders = [load_pfire_map, shirtloader]
for loader in maploaders:
try:
data = loader(mappath)
except (ValueError, OSError):
... | 2ab5c46e0b1ec0ed2e613b42c0553a1d6bcede36 | 3,654,616 |
def ifttt_account_options_topup_source():
""" Option values for topup source account selection"""
return ifttt_account_options(False, "Internal") | 83a0082ccc829c06c12fca2bb588db31468f51ef | 3,654,617 |
from bs4 import BeautifulSoup
def strip_classes(soup:BeautifulSoup, *args:str):
"""
Strip class from given tags in a BeautifulSoup object.
Args:
soup (BeautifulSoup): soup to clean
args ([str]): A list of tags to be unclassed
Returns:
soup (BeautifulSoup)
Modules:
... | c2195cd0eaf2cb3f741247b75411d252c7a85e8c | 3,654,618 |
import trace
def take_measurement(n_grid: np.int, n_rays: np.int, r_theta: np.float64) -> (
np.ndarray, np.ndarray, np.ndarray, np.ndarray):
"""
Take a measurement with the tomograph from direction r_theta.
Arguments:
n_grid: number of cells of grid in each direction
n_rays: number of parallel r... | f0ffac9da088402cff126bab9ee880ff33c460f1 | 3,654,619 |
def chrom_karyo_sort(chroms):
"""
:param chroms:
:return:
"""
ordered = []
unordered = []
for cname, size in chroms:
try:
ord = int(cname.lower().strip('chr'))
ordered.append((cname, size, ord * 10))
except ValueError:
ord = check_special_c... | 4531be10ad0c51e0257089aabda778357b2d7950 | 3,654,620 |
from typing import List
def calibrate_stereo(observations_left: List, observations_right: List, detector: FiducialCalibrationDetector,
num_radial: int = 4, tangential: bool = False, zero_skew: bool = True) -> (StereoParameters, List):
"""
Calibrates a stereo camera using a Brown camera mo... | bf9ee5b369f8614728db0023674c85a958a2559f | 3,654,621 |
from typing import Type
def register_producer_class(cls: Type[C]) -> Type[C]:
"""Registers the producer class and returns it unmodified."""
if not cls.TYPES:
raise ProducerInterfaceError(
f"Invalid producer. When defining producer, make sure to specify at least 1 type in the TYPES class va... | 7155ddb85077e2774fcc20c2d80345bd52ee86b1 | 3,654,622 |
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