content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def jaccard_similarity_coefficient(A, B, no_positives=1.0):
"""Returns the jaccard index/similarity coefficient between A and B.
This should work for arrays of any dimensions.
J = len(intersection(A,B)) / len(union(A,B))
To extend to probabilistic input, to compute the intersection, use ... | fe408565827f61323513d7d3b562bd79a23e47ec | 13,700 |
def get_argument_from_call(call_node: astroid.Call,
position: int = None,
keyword: str = None) -> astroid.Name:
"""Returns the specified argument from a function call.
:param astroid.Call call_node: Node representing a function call to check.
:param int... | e4b7e054c4728f5b74bcbbe1678816a910f64bda | 13,701 |
def snake_string(ls):
"""
Question 7.11: Write a string sinusoidally
"""
result = []
strlen = len(ls)
for idx in xrange(1, strlen, 4):
result.append(ls[idx])
for idx in xrange(0, strlen, 2):
result.append(ls[idx])
for idx in xrange(3, strlen, 4):
result.append(l... | 391f7cef4289c5746f77598501aeaa7ae93d31bc | 13,702 |
def _prepare_memoization_key(args, kwargs):
"""
Make a tuple of arguments which can be used as a key
for a memoized function's lookup_table. If some object can't be hashed
then used its __repr__ instead.
"""
key_list = []
for arg in args:
try:
hash(arg)
key_li... | c83e08c42886ba0e7f6e4defe5bc8f53f5682657 | 13,703 |
def kl_divergence_with_logits(p_logits = None,
q_logits = None,
temperature = 1.):
"""Compute the KL between two categorical distributions from their logits.
Args:
p_logits: [..., dim] array with logits for the first distribution.
q_logits: [..., ... | 1950dea9e5c6d040ce464e0861b09469742810c4 | 13,704 |
from typing import Any
from datetime import datetime
def convert_bosch_datetime(dt: Any = None) -> datetime:
"""Create a datetime object from the string (or give back the datetime object) from Bosch. Checks if a valid number of milliseconds is sent."""
if dt:
if isinstance(dt, str):
if dt.... | 845e9de019b700b2ab37ebb4a1b577d0bd068638 | 13,705 |
def day_log_add_id(day_log):
"""
その日のログにID(day_id)を割り振る
:param day_log:
:return:
"""
for v in range(len(day_log)):
day_log[v]['day_id'] = v + 1
return day_log | c4608b07e86c074a11cf78d171490ec152092eeb | 13,706 |
def cisco_ios_l3_acl_parsed():
"""Cisco IOS L3 Interface with ip address, acl, description and vlan."""
vlan = Vlan(id="300", encapsulation="dot1Q")
ipv4 = IPv4(address="10.3.3.13", mask="255.255.255.128")
acl_in = ACL(name="Common_Client_IN", direction="in")
acl_out = ACL(name="TEST_ACL_03", direct... | 25c7ad34695499bb6426ff71a9893c233b54a925 | 13,707 |
def brillance(p, g, m = 255):
"""
p < 0 : diminution de la brillance
p > 0 : augmentation de la brillance
"""
if (p + g < m + 1) and (p + g > 0):
return int(p + g)
elif p + g <= 0:
return 0
else:
return m | b40169e487521c146c4c0777517492205951cf16 | 13,708 |
def fetch_fact():
"""Parse the command parameters, validate them, and respond.
Note: This URL must support HTTPS and serve a valid SSL certificate.
"""
# Parse the parameters you need
token = request.form.get('token', None) # TODO: validate the token
command = request.form.get('command', None)
... | 8e5175b19d2548428e852dd9f476333dbe40481d | 13,709 |
def payback(request):
"""
微信支付回调函数
:param request:
:return:
"""
return HttpResponse('payback') | e178abe0effe6359a664dca434e181390c1a56c1 | 13,710 |
from datetime import datetime
def get_index_shares(name, end_date=None):
"""获取某一交易日的指数成分股列表
symbols = get_index_shares("上证50", "2019-01-01 09:30:00")
"""
if not end_date:
end_date = datetime.now().strftime(date_fmt)
else:
end_date = pd.to_datetime(end_date).strftime(date_fmt)
... | 7a9e2890d0508b00d15da4688980736776199cfa | 13,711 |
def erfcx(x):
"""Elementwise scaled complementary error function.
.. note::
Forward computation in CPU cannot be done if
`SciPy <https://www.scipy.org/>`_ is not available.
Args:
x (:class:`~chainer.Variable` or :ref:`ndarray`): Input variable.
Returns:
~chainer.Variable... | 60f1655a6e390ca935f80d33e0d9156879b56c41 | 13,712 |
def fetch_data_async(blob, start_index, end_index, rpc=None):
"""Asynchronously fetches data for a blob.
Fetches a fragment of a blob up to `MAX_BLOB_FETCH_SIZE` in length. Attempting
to fetch a fragment that extends beyond the boundaries of the blob will return
the amount of data from `start_index` until the ... | 518f1ef45c19b8a7be55940d9abdeaf0fe014835 | 13,713 |
def get_legal_moves(color, size, board):
"""
Get Legal Moves
"""
legal_moves = {}
for y in range(size):
for x in range(size):
reversibles = get_reversibles(color, size, board, x, y)
if reversibles:
legal_moves[(x, y)] = reversibles
return legal_... | eaab0b7fededbe660b02974f675877b97e3327f4 | 13,714 |
def edition(self, key, value):
"""Translates edition indicator field."""
sub_a = clean_val("a", value, str)
if sub_a:
return sub_a.replace("ed.", "")
raise IgnoreKey("edition") | 715724dffb4ef6d72c173afbf8186acfdf9f20e3 | 13,715 |
from typing import Dict
from typing import Set
import itertools
def get_site_data(hostname: str) -> SiteData:
"""Get metadata about a site from the API"""
url = f"https://{hostname}/w/api.php"
data = dict(
action="query",
meta="siteinfo",
siprop="|".join(
[
... | 83ca853c6fb2ebadf6473b8f5da0008b145717b0 | 13,716 |
def clear_monitor(nodenet_uid, monitor_uid):
"""Leaves the monitor intact, but deletes the current list of stored values."""
micropsi_core.runtime.get_nodenet(nodenet_uid).get_monitor(monitor_uid).clear()
return True | ad39c344f41fcf307f85d09add71eeeac66b30c1 | 13,717 |
def loadGrammarFrom(filename, data=None):
"""Return the text of a grammar file loaded from the disk"""
with open(filename, 'r') as f:
text = f.read()
lookup = mako.lookup.TemplateLookup(directories=[relativePath('grammars')])
template = mako.template.Template(text, lookup=lookup)
#
base_... | 0a0bbd0f2af5db4c673d7dbd31259a3977adb9cf | 13,718 |
def create_generator_selfatt(generator_inputs, generator_outputs_channels, flag_I=True):
"""
Add Conditional Self-Attention Modual to the U-Net Generator.
By default, 256x256 => 256x256
Args:
generator_inputs: a tensor of input images, [b, h, w, n], with each pixel value [-1, 1].
generator_... | bfcc81955c7849e84053c45ea7a593570059bf28 | 13,719 |
def by_tag(articles_by_tag, tag):
""" Filter a list of (tag, articles) to list of articles by tag"""
for a in articles_by_tag:
if a[0].slug == tag:
return a[1] | 642472a89cb624ed02a6e8ec488b72856ac231a9 | 13,720 |
def experiment(dataset='SUPPORT', quantiles=(0.25, 0.5, 0.75), prot_att='race',
groups=('black', 'white'), model='dcm', adj='KM',
cv_folds=5, seed=100, hyperparams=None, plot=True, store=False):
"""Top level interface to train and evaluate proposed survival models.
This is the top le... | 79ec44d4d62a42dea4f7e612cd4291ce8fbc5585 | 13,721 |
def ldns_str2rdf_type(*args):
"""LDNS buffer."""
return _ldns.ldns_str2rdf_type(*args) | d121f8534c64b7597d775e5443b706c962ec738a | 13,722 |
import hashlib
import _crypt
def scramble(password, message):
"""scramble message with password"""
scramble_length = 20
sha_new = partial(hashlib.new, 'sha1')
if not password:
return b''
stage1 = sha_new(password).digest()
stage2 = sha_new(stage1).digest()
buf = sha_new()
buf.... | 9ad006a5626d7b4ca3f8220dc4cbdd719a3cbac8 | 13,723 |
def dp_port_id(switch: str, port: str) -> str:
"""
Return a unique id of a DP switch port based on switch name and port name
:param switch:
:param port:
:return:
"""
return 'port+' + switch + ':' + port | 479891e41b51114744dcbb2b177180c19cd1bfd5 | 13,724 |
import requests
def request_item(zip_code, only_return_po_boxes=False, spatial_reference='4326'):
"""
Request data for a single ZIP code, either routes or PO boxes.
Note that the spatial reference '4326' returns latitudes and longitudes of results.
"""
url = BASE_URL.format(
zip_code=str(... | 956a2a86f0960a888046bfd5a8e3c2d7c56bc9dc | 13,725 |
def smoothen_histogram(hist: np.array) -> np.array:
""" Smoothens a histogram with an average filter.
The filter as defined as multiple convolutions
with a three-tap box filter [1, 1, 1] / 3.
See AOS section 4.1.B.
Args:
hist: A histogram containing gradient orientation counts.
... | bdcc5de3df5aa2aad33653cce237f7f07d825b9d | 13,726 |
from typing import Tuple
def end_point(min_radius: float, max_radius: float) -> Tuple[int, int]:
"""
Generate a random goal that is reachable by the robot arm
"""
# Ensure theta is not 0
theta = (np.random.random() + np.finfo(float).eps) * 2 * np.pi
# Ensure point is reachable
r = np.rando... | 8d6a79195108e8354fad986f93da5f089b6df0d7 | 13,727 |
def expand_tile(value, size):
"""Add a new axis of given size."""
value = tf.convert_to_tensor(value=value, name='value')
ndims = value.shape.ndims
return tf.tile(tf.expand_dims(value, axis=0), [size] + [1]*ndims) | 50adf652fff47418d1f8f1250a2a6d01f712da76 | 13,728 |
from typing import Mapping
from typing import Any
def parse_header(
info: Mapping[str, Any],
field_meta_data: Mapping[str, FieldMetaData],
component_meta_data: Mapping[str, ComponentMetaData]
) -> Mapping[str, MessageMemberMetaData]:
"""Parse the header.
Args:
info (Mapping[st... | a8043c62070c540712074c60e01e3c9c3ebfe99b | 13,729 |
def amina_choo(update, context): #3.2.1
"""Show new choice of buttons"""
query = update.callback_query
bot = context.bot
keyboard = [
[InlineKeyboardButton("Yes", callback_data='0'),
InlineKeyboardButton("No", callback_data='00')],
[InlineKeyboardButton("Back",callback_data='3.... | b43d2e6d63e111b9a2f70fd71e5da765ef923746 | 13,730 |
def lighten(data, amt=0.10, is255=False):
"""Lighten a vector of colors by fraction `amt` of remaining possible intensity.
New colors are calculated as::
>>> new_colors = data + amt*(1.0 - data)
>>> new_colors[:, -1] = 1 # keep all alpha at 1.0
Parameters
----------
data : matplot... | 195faa21ba30989f900b9b7f2b655a97074d8833 | 13,731 |
def _determine_function_name_type(node):
"""Determine the name type whose regex the a function's name should match.
:param node: A function node.
:returns: One of ('function', 'method', 'attr')
"""
if not node.is_method():
return 'function'
if node.decorators:
decorators = node.... | d80cfd4aabdd79023d636c7425b04e747420ad36 | 13,732 |
from typing import Optional
import platform
import os
import json
def find_egl_engine_windows(association: str) -> Optional[UnrealEngine]:
"""Find Epic Games Launcher engine distribution from EngineAssociation string."""
if platform.system() != "Windows":
return None
if os.path.isfile(DAT_FILE):
... | c01ac3e18de3c851120847989ae5937cb7e81288 | 13,733 |
from typing import Tuple
import datasets
from typing import List
from typing import Dict
from re import T
def create_dataset(
template_path:
str = 'com_github_corypaik_coda/projects/coda/data/coda/templates.yaml',
objects_path:
str = 'com_github_corypaik_coda/projects/coda/data/coda/objects.jsonl',
... | 915bb616e165b55234f140f2ea1577644876ddb7 | 13,734 |
def escape_blog_content(data):
"""Экранирует описание блога."""
if not isinstance(data, binary):
raise ValueError('data should be bytes')
f1 = 0
f2 = 0
# Ищем начало блока
div_begin = b'<div class="blog-description">'
f1 = data.find(b'<div class="blog-content text">')
if f1 >= 0... | 285825b253de8ef9b67d7d3f1bdaa7a28f2e918c | 13,735 |
import csv
def read_csv(file_path, delimiter=",", encoding="utf-8"):
"""
Reads a CSV file
Parameters
----------
file_path : str
delimiter : str
encoding : str
Returns
-------
collection
"""
with open(file_path, encoding=encoding) as file:
data_in = list(csv.... | a4f1da219b0e5d752ff606614e93abbfc3d30597 | 13,736 |
from typing import Tuple
from pathlib import Path
def get_cmd_items(pair: Tuple[str, Path]):
"""Return a list of Albert items - one per example."""
with open(pair[-1], "r") as f:
lines = [li.strip() for li in f.readlines()]
items = []
for i, li in enumerate(lines):
if not li.startswi... | 92d34ce5af3a3dbe162adf0766382120d0458c46 | 13,737 |
import importlib
def import_activity_class(activity_name, reload=True):
"""
Given an activity subclass name as activity_name,
attempt to lazy load the class when needed
"""
try:
module_name = "activity." + activity_name
importlib.import_module(module_name)
return True
e... | b4cea3fad1f08a5758972847d3e03a41f89f223c | 13,738 |
def rgb2hsv(rgb):
"""
Reverse to :any:`hsv2rgb`
"""
eps = 1e-6
rgb = np.asarray(rgb).astype(float)
maxc = rgb.max(axis=-1)
minc = rgb.min(axis=-1)
v = maxc
s = (maxc - minc) / (maxc + eps)
s[maxc <= eps] = 0.0
rc = (maxc - rgb[:, :, 0]) / (maxc - minc + eps)
gc = (maxc - ... | febb268b1b691897c28447ff00a29785742dfc0c | 13,739 |
def fig_colorbar(fig, collections, *args, **kwargs):
"""Add colorbar to the right on a figure."""
fig.subplots_adjust(right=0.8)
cax = fig.add_axes([0.85, 0.15, 0.05, 0.7])
cbar = fig.colorbar(collections, cax, *args, **kwargs)
plt.pause(0.1)
return cbar | a3156d24e28407938661c003d30b80a4d57638e6 | 13,740 |
def _merge_css_item(item):
"""Transform argument into a single list of string values."""
# Recurse lists and tuples to combine into single list
if isinstance(item, (list, tuple)):
return _merge_css_list(*item)
# Cast to string, be sure to cast falsy values to ''
item = "{}".format(item) if i... | c6f0c8769761640d5b0d98168cee1308f3209072 | 13,741 |
def extract_arguments(start, string):
""" Return the list of arguments in the upcoming function parameter closure.
Example:
string (input): '(blocks, threads, 0, THCState_getCurrentStream(state))'
arguments (output):
'[{'start': 1, 'end': 7},
{'start': 8, 'end': 16},
... | 8e6e3fecc0643aa3f55108916a7c6892a96f13aa | 13,742 |
def augment_img(img):
"""Data augmentation with flipping and rotation"""
# TODO: Rewrite with torchvision transform
flip_idx = np.random.choice([0, 1, 2])
if flip_idx != 0:
img = np.flip(img, axis=flip_idx)
rot_idx = int(np.random.choice([0, 1, 2, 3]))
img = np.rot90(img, k=rot_idx, axes... | 4f124954b1dba8e27360a1c4664f0de46fd1a4d0 | 13,743 |
def iter_archive(path, method):
"""Iterate over an archive.
Args:
path: `str`, archive path
method: `tfds.download.ExtractMethod`, extraction method
Returns:
An iterator of `(path_in_archive, f_obj)`
"""
return _EXTRACT_METHODS[method](path) | dda105efc20583f54aed26a55112cfc56380ad68 | 13,744 |
def unfoldPath(cwd, path):
"""
Unfold path applying os.path.expandvars and os.path.expanduser.
Join 'path' with 'cwd' in the beginning If 'path' is not absolute path.
Returns normalized absolute path.
"""
if not path:
return path
path = _expandvars(path)
path = _expanduser(path... | ae11a69e6b2a3b0be4b3f266960d6004e99bd261 | 13,745 |
import os
import sys
import yaml
def readConfig(config):
"""
This function reads configuration file and combine it with parameters from
console input to generate the configuration list.
Args:
* config: configuration file to be readed
Options:
* keyfile (-k): str, path to a file c... | 27d494c5e76f13def4785997565893caeddc59b2 | 13,746 |
import sys
def main(argv):
"""Decide whether the needed jobs got satisfactory results."""
inputs = parse_inputs(
raw_allowed_failures=argv[1],
raw_allowed_skips=argv[2],
raw_jobs=argv[3],
)
jobs = inputs['jobs'] or {}
jobs_allowed_to_fail = set(inputs['allowed_failures'] ... | 4abc60eb17bc6ddb1e51611cecda7c1d2ecde686 | 13,747 |
def get_predictions(logits):
"""
Convert logits into softmax predictions
"""
probs = F.softmax(logits, dim=1)
confidence, pred = probs.max(dim=1, keepdim=True)
return confidence, pred, probs | c83a47140534e27bb14991d4c8b2192a2a02cd46 | 13,748 |
def lookup_capacity(lookup_table, environment, cell_type, frequency, bandwidth,
generation, site_density):
"""
Use lookup table to find capacity by clutter environment geotype,
frequency, bandwidth, technology generation and site density.
"""
if (environment, cell_type, frequency, bandwidth, ge... | c98b25611cf72cc202fea060063f3020732a5282 | 13,749 |
def contig_slow(fn, num):
"""brute force, quadratic"""
data = parse(fn)
for i in range(len(data)-2):
for j in range(i + 2, len(data)-1):
s = sum(data[i:j])
if s == num:
return min(data[i:j]) + max(data[i:j]) | 69c086c605afc17a63def6e3958e340ddb7a32c3 | 13,750 |
def create_consts(*args) -> superclasses.PyteAugmentedArgList:
"""
Creates a new list of names.
:param args: The args to use.
"""
return _create_validated(*args, name="consts") | b10ab2d0e30e5cfb54c284d4557a98c0b3eb69c6 | 13,751 |
def opts2constr_feat_gen(opts):
"""Creates ConstFeatPlanes functor by calling its constructor with
parameters from opts.
Args:
opts (obj): Namespace object returned by parser with settings.
Returns:
const_feat_planes (obj): Instantiated ConstFeatPlanes functor.
"""
return Cons... | 5f664aae10f0584aca14ff58d2a984c29fd0dc2d | 13,752 |
def inhibit_activations(activations, times, window_length):
"""
Remove any activations within a specified time window following a previous activation.
TODO - this is extremely slow for non-sparse activations
Parameters
----------
activations : ndarray
Provided activations
times : nda... | 5665ae196430d993d40f5f4941cecde0d79d7a80 | 13,753 |
def cmd_convert_items_to_cheetah_list(list):
"""
Cheetah templates can't iterate over a list of classes, so
converts all data into a Cheetah-friendly list of tuples
(NAME, DESCRIPTION, ENUM, HAS_BIT_OFFSET, BIT_OFFSET, BITS, TYPE, MIN, MAX, DEFAULT)
"""
temp = []
for i in list:
... | ff6933dce38d6ddcd74df72ce321d8f16dfd5074 | 13,754 |
def pose223(pose:gtsam.Pose2) -> gtsam.Pose3:
"""convert a gtsam.Pose2 to a gtsam.Pose3
Args:
pose (gtsam.Pose2): the input 2D pose
Returns:
gtsam.Pose3: the 3D pose with zeros for the unkown values
"""
return gtsam.Pose3(
gtsam.Rot3.Yaw(pose.theta()), gtsam.Point3(pose.x(... | 0a6d738d9cbe035be55a884a1523c985d547f25f | 13,755 |
import random
def pivot_calibration_with_ransac(tracking_matrices,
number_iterations,
error_threshold,
concensus_threshold,
early_exit=False
):
... | 0ce7c7bd8afbc88093793601da2b0333b40766cb | 13,756 |
def find_companies_name_dict():
"""
Finds companies names and addresses
:return: a dict with resource name eg.area of companies and url of available data
"""
base = "https://data.gov.ro/api/3/action/"
query = "Date-de-identificare-platitori"
address = url_build.build_url_package_query(base,... | 74526747f45a4c5491e4778759baca53a638c97f | 13,757 |
import typing
def error_to_response(request: web.Request,
error: typing.Union[Error, ErrorList]):
"""
Convert an :class:`Error` or :class:`ErrorList` to JSON API response.
:arg ~aiohttp.web.Request request:
The web request instance.
:arg typing.Union[Error, ErrorList] er... | 792c3fccd8d7fee708d850169fd943010e92ab05 | 13,758 |
def read(handle):
"""read(handle)"""
record = Record()
__read_version(record, handle)
__read_database_and_motifs(record, handle)
__read_section_i(record, handle)
__read_section_ii(record, handle)
__read_section_iii(record, handle)
return record | 90921ec1779c313505a838863509838bd858d0b7 | 13,759 |
import json
def validate_telegam():
"""Validate telegram token and chat ID
"""
configs = InitialConfig()
confs = ["chat_id", "bot_token"]
conf_dict = {}
if request.method == "GET":
for conf in confs:
conf_dict[conf] = getattr(configs, conf)
conf_json = json.dump... | f597d75672639dc2a39eb100f7221c508f62cf06 | 13,760 |
def hour(e):
"""
:rtype: Column
"""
return col(Hour(ensure_column(e))) | 492d9e21f2f7c3fd6107dd4000c8273efaa0357c | 13,761 |
def infer_gaussian(data):
"""
Return (amplitude, x_0, y_0, width), where width - rough estimate of
gaussian width
"""
amplitude = data.max()
x_0, y_0 = np.unravel_index(np.argmax(data), np.shape(data))
row = data[x_0, :]
column = data[:, y_0]
x_0 = float(x_0)
y_0 = float(y_0)
... | 784e88e5cd58def8467cbe0a851b37cc1fefe9dd | 13,762 |
import math
def extract_freq(bins=5, **kwargs):
"""
Extract frequency bin features.
Args:
bins (int): The number of frequency bins (besides OOV)
Returns:
(function): A feature extraction function that returns the log of the \
count of query tokens within each frequency bi... | b07f2f1810a26c2d04366d5516aac0ca79b547bb | 13,763 |
import typing
def create_private_key_params(key_type: str) -> typing.Type[PrivateKeyParams]:
"""Returns the class corresponding to private key parameters objects of the
given key type name.
Args:
key_type
The name of the OpenSSH key type.
Returns:
The subclass of :any:`Pr... | 6702f93f8cd8dc3fd104db5d63efd7db4bbaa38e | 13,764 |
import json
import requests
def get_response(msg):
"""
访问图灵机器人openApi
:param msg 用户输入的文本消息
:return string or None
"""
apiurl = "http://openapi.tuling123.com/openapi/api/v2"
# 构造请求参数实体
params = {"reqType": 0,
"perception": {
"inputText": {
... | 9a542b56a3ed3db8b8a9306ea3d425054a4ca64b | 13,765 |
import torch
def lm_sample_with_constraints(lm_model,
max_decode_steps,
use_cuda,
device,
batch_size=1,
alpha_0=1,
alpha=1,
... | cbccd2c0a2b91fa3e5ff5efb8b394fe7418f5b8b | 13,766 |
import torch
import tqdm
def validate_official(args, data_loader, model, global_stats=None):
"""Run one full official validation. Uses exact spans and same
exact match/F1 score computation as in the SQuAD script.
Extra arguments:
offsets: The character start/end indices for the tokens in each cont... | 09385e491c25ac238aebabe7d887f73b4c0bd091 | 13,767 |
def tuple_list_to_lua(tuple_list):
"""Given a list of tuples, return a lua table of tables"""
def table(it):
return "{" + ",".join(map(str, it)) + "}"
return table(table(t) for t in tuple_list) | 71ec1a29f5e23b8bf82867617fe157fbba4a2332 | 13,768 |
def reset_user_messages(request: Request):
"""
For given user reset his notifications.
"""
profile: Profile = get_object_or_404(Profile, user=request.user)
profile.messages = 0
profile.save()
return Response(status=status.HTTP_200_OK) | 628347dea707b0bd2ecc63cc004a3f62cb85e967 | 13,769 |
import functools
def define_scope(function, scope=None, *args, **kwargs):
"""
A decorator for functions that define TensorFlow operations. The wrapped
function will only be executed once. Subsequent calls to it will directly
return the result so that operations are added to the graph only once.
Th... | 988f2f711dc227bfe8df5c7074d354c37d079fdb | 13,770 |
from typing import Union
from typing import List
from typing import Dict
import yaml
from typing import OrderedDict
def load_yaml(fname: str) -> Union[List, Dict]:
"""Load a YAML file."""
try:
with open(fname, encoding='utf-8') as conf_file:
# If configuration file is empty YAML returns No... | 5fd0b9d2dea7d07b7bb98f6a9ae3ce98be3962e0 | 13,771 |
def fancy_vector(v):
"""
Returns a given 3-vector or array in a cute way on the shell, if you
use 'print' on the return value.
"""
return "\n / %5.2F \\\n" % (v[0]) + \
" | %5.2F |\n" % (v[1]) + \
" \\ %5.2F /\n" % (v[2]) | 2340f22aa87da00abad30b9946c374f34b38496d | 13,772 |
def findpath_split(seq, ss1, ss2, md, th = 5, w = None):
""" Calculate findpath barriers for smaller components.
Args:
seq: RNA sequence.
ss1: Structure 1.
ss2: Structure 2.
md: ViennaRNA model details.
th: Threshold of how many basepairs must change for an independent f... | 2d52102df31dd014ac60e28c7258bff833353b6a | 13,773 |
def get_root_relative_url(url_path):
"""Remove the root page slug from the URL path"""
return _clean_rel_url('/'.join(url_path.split('/')[2:])) | 7aca9c0ec8856615fe1777117f44a259d7b597c7 | 13,774 |
import os
import subprocess
def run_command(command, split=False, include_errors=False, cwd=None, shell=False, env=None):
"""Run command in subprocess and return exit code and output"""
sub_env = os.environ.copy()
if env is not None:
sub_env.update(env)
if include_errors:
error_pipe = ... | f3d4c0c1180a513872d6821a763495f1b97e85ee | 13,775 |
def exclusion_windows_matching(match_peaks):
"""
Discard the occurrences of matching and non-matchign ions when they are found in the window
(+-losses_window_removal) around M-xx or free bases ions
"""
output_dic = match_peaks
for key in match_peaks:
if match_peaks[key]:
fo... | 9c2b5bcdb283b197102d50fdd2aaa8eb49e2fc3b | 13,776 |
def any_of(elements):
"""
Check to see if the argument is contained in a list of possible elements.
:param elements: The elements to check the argument against in the predicate.
:return: A predicate to check if the argument is a constituent element.
"""
def predicate(argument):
return a... | adacf8fd632d25452d22dab0a8a439021083ec83 | 13,777 |
def find_year(films_lst: list, year: int):
""" Filter list of films by given year """
filtered_films_lst = [line for line in films_lst if line[1] == str(year)]
return filtered_films_lst | f4c11e09e76831afcf49154234dd57044536bce1 | 13,778 |
def func_BarPS(HA_Open, HA_Close, HA_PS_Lookback, PS_pct_level=[0.35, 0.5, 0.95, 0.97], combine=False):
"""
0. This function is for calculating price trend number of HA bar, by looking back HA_PS_Lookback HA bars,
according to the previous bars' distribution, find the range (i.e. -4,-3,-2,-1,0,1,2,3,4) o... | 8a57de8ee4e832afd6327afc808668d227bc2592 | 13,779 |
from typing import List
def filter_whitespace(stream: List[Part]) -> List[Part]:
"""Remove whitespace tokens"""
return flu(stream).filter(lambda x: x.token != Token.WHITESPACE).collect() | aa3b8d109b0d85db7c3aa286858426276afb80ba | 13,780 |
def merge_partial_dicts(interfaces_dict, partials_dict):
"""Merges partial interface into non-partial interface.
Args:
interfaces_dict: A dict of the non-partial interfaces.
partial_dict: A dict of partial interfaces.
Returns:
A merged dictionary of |interface_dict| with |partial_dict|.
... | 7efc47325e1af5c06b19c1bba02ec8b53d9473e0 | 13,781 |
def gen_code_def_part(metadata):
"""生成代码中定义类的部分。
"""
class_def_dict = validate(metadata)
class_def_list = list(class_def_dict.values())
code = templates.t_def_all_class.render(class_def_list=class_def_list)
return code | df01fb69984a0ba471a6e5ac24bbecb0a622dd1b | 13,782 |
def clang_plusplus_frontend(input_file, args):
"""Generate LLVM IR from C++ language source(s)."""
compile_command = default_clang_compile_command(args)
compile_command[0] = llvm_exact_bin('clang++')
return compile_to_bc(input_file, compile_command, args) | 1b2701f3e0fac240843b302dd2056bac857ecb74 | 13,783 |
from django.db.models import Model
def create_forward_many_to_many_manager(superclass, rel, reverse):
"""
Create a manager for the either side of a many-to-many relation.
This manager subclasses another manager, generally the default manager of
the related model, and adds behaviors specific to many-t... | c9c45ae0eca4a913affab0ed832a0568e46d9a4c | 13,784 |
def grp_render_dashboard_module(context, module, index=None, subindex=None):
"""
Template tag that renders a given dashboard module, it takes a
``DashboardModule`` instance as first parameter and an integer ``index`` as
second parameter, that is the index of the module in the dashboard.
"""
... | 515bf427c4c39dc28479f6fe7121dc1cb542745e | 13,785 |
def serialize_routing(value, explicit_type=None):
"""Custom logic to find matching serialize implementation and
returns it's unique registration string key
:param value: instance to serialize
:param explicit_type: explicit serialization type for value
:return: str key to find proper serialize im... | 792cb24fc68060fe7e24f064f411752c5d787c3d | 13,786 |
def get_projection_matricies(az, el, distance_ratio, roll = 0, focal_length=35, img_w=137, img_h=137):
"""
Calculate 4x3 3D to 2D projection matrix given viewpoint parameters.
Code from "https://github.com/Xharlie/DISN"
"""
F_MM = focal_length # Focal length
SENSOR_SIZE_MM = 32.
PIXEL_ASPE... | a8ef5852510982851487e349336e41e61f7b582e | 13,787 |
def pix_to_coord(edges, pix, interp="lin"):
"""Convert pixel coordinates to grid coordinates using the chosen
interpolation scheme."""
scale = interpolation_scale(interp)
interp_fn = interp1d(
np.arange(len(edges), dtype=float), scale(edges), fill_value="extrapolate"
)
return scale.inv... | db9fcc47a273e9b39f6d5b6a39b59146866e5dd4 | 13,788 |
def create_action_urls(actions, model=None, **url_args):
"""
Creates a list of URLs for the given actions.
"""
urls = {}
if len(actions) > 0:
# Resolve the url_args values as attributes from the model
values = {}
for arg in url_args:
values[arg] = getattr(model, u... | f26477e0d046bfe6f73f25b2b086fad3b05a2646 | 13,789 |
def check_vfvx(x0, fx, fx_args, dfx, dfx_args=None, delta=1e-5):
"""
Check derivatives of a (vectorized) vector or scalar function of a vector
variable.
"""
if x0.ndim != 2:
raise ValueError('The variable must have two dimensions!')
if dfx_args is None:
dfx_args = fx_args
d... | a8cffcbf118394a1ea5d65835bade516035fe9fe | 13,790 |
def add_hovertool(p1, cr_traj, traj_src, sat_src, traj_df):
"""Adds a hovertool to the top panel of the data visualization tool plot."""
# Create the JS callback for vertical line on radar plots.
callback_htool = CustomJS(args={'traj_src':traj_src,'sat_src':sat_src}, code="""
const indices = cb_d... | f45245df7cd81ee8f0fc486d460be0c4338fd921 | 13,791 |
def backpage_url_to_sitekey(url):
"""http://longisland.backpage.com/FemaleEscorts/s-mny-oo-chics-but-oo-nn-lik-oo-me-19/40317377"""
(scheme, netloc, path, params, query, fragment) = urlparse(url)
sitekey = netloc.split('.')[0]
return sitekey | 6efa6d0bf73ab297144a7c6a35dbba920f77789e | 13,792 |
import torch
def batch_eye_like(X: torch.Tensor):
"""Return batch of identity matrices like given batch of matrices `X`."""
return torch.eye(*X.shape[1:], out=torch.empty_like(X))[None, :, :].repeat(X.size(0), 1, 1) | 266ee5639ce303b81e2cb82892e64f37a09695ff | 13,793 |
def cal_occurence(correspoding_text_number_list):
"""
calcualte each occurence of a number in a list
"""
di = dict()
for i in correspoding_text_number_list:
i = str(i)
s = di.get(i, 0)
if s == 0:
di[i] = 1
else:
di[i] = di[i] + 1
return di | aafabc6abdf4bf1df1b8d9e23a4af375df3ac75b | 13,794 |
def subtract(v: Vector, w: Vector) -> Vector:
"""simple vector subtraction"""
assert len(v) == len(w), 'Vectors need to have the same length'
return [vi - wi for vi, wi in zip(v, w)] | c6f8a9b19e07206a4d2637557c721bd97ad56363 | 13,795 |
from re import I
def f1():
"""
Filtering 1D.
"""
# Get center of the filter
c = int((size - 1) / 2)
# Pad the flatten (1D array) image with wrapping
If = np.pad(I.flatten(), (c), 'wrap')
# Initialize the resulting image
Ir = np.zeros(If.shape)
# Apply 1D convulation in the image
for x in range(c... | cc50f089148cdbaffbbdc7d6d734a066a6b08722 | 13,796 |
from typing import Optional
def _unify_data_and_user_kwargs(
data: 'LayerData',
kwargs: Optional[dict] = None,
layer_type: Optional[str] = None,
fallback_name: str = None,
) -> 'FullLayerData':
"""Merge data returned from plugins with options specified by user.
If ``data == (_data, _meta, _ty... | c0d472ef60bf69d67ef50d435715bfabe11c229e | 13,797 |
def get_sentence_embeddings(data):
"""
data -> list: list of text
"""
features = temb.batch_tokenize(data, tokenizer)
dataset = temb.prepare_dataset(features)
embeddings = temb.compute_embeddings(dataset, model)
return embeddings | cb1badd5cf9a244d7af8b40d219a467d0dff811e | 13,798 |
def sample_user(phone="+989123456789", full_name="testname"):
""" Create a sample user """
return get_user_model().objects.create_user(phone=phone,
full_name=full_name) | 418b12b4249c4beda4fed36664f2c9eb14f8adc4 | 13,799 |
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