content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import json
def get_tiff_param(tiff_file):
"""Obtain relevant parameters of TiffFile object"""
xy_dim, description = lookup_page(tiff_file.pages[0])
shape = tiff_file.asarray().shape
if tiff_file.is_fluoview:
return get_fluoview_param(description, xy_dim, shape)
elif tiff_file.is_imagej... | d161f142780e86e19cb2a8e7e9440c4768509119 | 3,630,900 |
def get_number_of_classes(model_config):
"""Returns the number of classes for a detection model.
Args:
model_config: A model_pb2.DetectionModel.
Returns:
Number of classes.
Raises:
ValueError: If the model type is not recognized.
"""
meta_architecture = model_config.WhichOneof("model")
meta... | d87605b6025e1bc78c7436affe740f7591a99f68 | 3,630,901 |
from typing import Optional
def to_xy0(
xyz: npt.ArrayLike, radius: Optional[float] = 1.0, stacked: Optional[bool] = True
) -> np.ndarray:
"""
Convert geocentric xyz coordinates to longitude (φ) and latitude (λ)
xy0 (i.e., φλ0) coordinates.
Parameters
----------
xyz : ArrayLike
A ... | 9f3e94def7f7fa5d34a791fcd054068874f5621b | 3,630,902 |
def getDataset(filepath = ""):
"""
Reads a comma separated variables (csv) file and creates a dataset.
A dataset has the following components: Variables, Data, Types, Groups, Sorts
To call each componenet of a dataset, do the following.
Say you have a dataset named: somedata
somedata['VARIABLES'... | cb3ae7b9b392a702729078df009452cff0a965b6 | 3,630,903 |
def draw_matches(img0, img1, kpts0, kpts1, match_idx,
downscale_ratio=1, color=(0, 255, 0), radius=4, thickness=2):
"""
Args:
img: color image.
kpts: Nx2 numpy array.
match_idx: Mx2 numpy array indicating the matching index.
Returns:
display: image with drawn... | 17b118bf175bef066292b370a7f0571425900fc3 | 3,630,904 |
def shorten_build_target(build_target: str) -> str:
"""Returns a shortened version of the build target."""
if build_target == '//chrome/android:chrome_java':
return 'chrome_java'
return build_target.replace('//chrome/browser/', '//c/b/') | 03af53f1fcacae9a4e0309053075806d65275ce9 | 3,630,905 |
from datetime import datetime
import copy
def store_initial_role_data(dynamo_table, arn, create_date, role_id, role_name, account_number, current_policy, tags):
"""
Store the initial version of a role in Dynamo
Args:
role (Role)
current_policy (dict)
Returns:
None
"""
... | 2c6a54a3b6fc414e638e3ba2870201c73b37a2b1 | 3,630,906 |
def apply_shift(x, shift, out):
"""
Translates elements of `x` along axis=0 by `shift`, using linear
interpolation for non-integer shifts.
Parameters
----------
x : ndarray
Array with ndim >= 1, holding data.
shift : float
Shift magnitude.
out : ndarray
Array wit... | 86e58c536cbc2fb43bb049aab6d0d4d733308bbd | 3,630,907 |
import platform
def get_socket(dname, protocol, host, dno):
"""socket = get_socket(dname, protocol, host, dno)
Connect to the display specified by DNAME, PROTOCOL, HOST and DNO, which
are the corresponding values from a previous call to get_display().
Return SOCKET, a new socket object connected to ... | d2703d7747ffac8d142f170dd153169f111f8b5d | 3,630,908 |
def azureblobstorage_folder_list(node_addon, **kwargs):
""" Returns all the subsequent folders under the folder id passed.
"""
return node_addon.get_folders() | d6934946a428e592ab2644ffbfb0a28ebb2ad9c8 | 3,630,909 |
def summary_statistics(is_significant, time_interp, n_records_at_t, n_window):
"""Compute summary statistics."""
# Initialize
significant_number = np.zeros(len(time_interp))
significant_relative = np.zeros(len(time_interp))
max_records_around_t = np.zeros(len(time_interp))
for j in xrange(len(... | e970e78a1dfe96220f8ff49a85deccc5dc00f673 | 3,630,910 |
from typing import Tuple
import random
def draw_two(max_n: int) -> Tuple[int, int]:
"""Draw two different ints given max (mod max)."""
i = random.randint(0, max_n)
j = (i + random.randint(1, max_n - 1)) % max_n
return i, j | 9ebb09158c296998c39a2c4e8fc7a18456428fc6 | 3,630,911 |
def compareFloats(a, b, rtol=1.0e-5, atol=opscore.RO.SysConst.FAccuracy):
"""Compares values a and b
Returns 0 if the values are approximately equals, i.e.:
- |a - b| < atol + (rtol * |a + b|)
Else 1 if a > b, -1 if a < b
Inputs:
- a, b: scalars to be compared (int or float)
- atol: absolut... | 6ff9e55040bfbefea11ef6f10cdc88b5e2fa7a77 | 3,630,912 |
def net_import_share_constraint_rule(backend_model, constraint_group, carrier, what):
"""
Enforces demand shares of net imports from transmission technologies for groups of locations,
on average over the entire model period. Transmission within the group are ignored. The share
is relative to ``demand`` ... | 30add5ca89d2b995742e52eec759ca9504029e57 | 3,630,913 |
def loss_gaussian(X):
"""
encode X by CNML
"""
Xmat = np.matrix(X)
n, m = Xmat.shape
if n == 1:
Xmat = Xmat.T
n, m = Xmat.shape
else:
pass
if n <= 0:
return np.nan
Xc = Xmat - np.mean(Xmat, 0)
S = np.dot(Xc.T, Xc / n)
detS = sl.det(S)
l... | b9e7db0b25f8b9b6104d653561b3e13a154a742b | 3,630,914 |
def integrand(x, n):
"""
Bessel function of first kind and order n.
"""
return jn(n, x) | 6b5dce69f94285518cc6e23b4ae23f22e0e981fc | 3,630,915 |
def get_forms_tuple(*args):
"""
Converts a string of grammemes to a tuple of two sets:
- set of tags for declension
- set of tags for refining the word form
"""
forms = list()
specs = list()
for arg in args:
for key in force_str(arg).split(','):
if key in INFL... | 9f8264b29e0828ffa01af6da1704d7f9c889e167 | 3,630,916 |
def truncate(inputs, channels, data_format):
"""Slice the inputs to channels if necessary."""
if data_format == 'channels_last':
input_channels = inputs.get_shape()[3].value
else:
assert data_format == 'channels_first'
input_channels = inputs.get_shape()[1].value
if input_channe... | 965574da9af5e85c80ce66ed13b36d13b5cffbef | 3,630,917 |
def do_rating_by_user(parser, token):
"""
Returns a User's Rating of a Snippet, if any.
Example::
{% get_rating_by_user user.id object.id as rating %}
"""
bits = token.contents.split()
if len(bits) != 5:
raise template.TemplateSyntaxError("'%s' tag takes exactly four ar... | 761e3414bc3c292e315c25d79e1c7417e6f894c7 | 3,630,918 |
import os
def get_read_counts_total_table(path, pool):
"""
This table is used for "Fraction of Total Reads that Align to the Human Genome" plot
"""
full_path = os.path.join(path, AGBM_READ_COUNTS_FILENAME)
read_counts_total = pd.read_csv(full_path, sep='\t')
col_idx = ~read_counts_total.colum... | dae44903051eabbce1118363fc51c8566861484b | 3,630,919 |
def get_label_funcs_threshold(bin_count=10, lower=1e-9, upper=1e-3, bin_func=bin_func_sum):
"""
:param bin_count: Number of different thresholds to encode the goes flux into.
:param lower: Lower limit for valid goes flux values.
:param upper: Upper limit for valid goes flux values.
:param bin_func: ... | 561dbc5b468b2b657908403ef39e630fe66649d9 | 3,630,920 |
def modify_layer(layer, name, norm = None, dropout = None):
"""Add BatchNorm and/or Dropout on top of `layer`"""
if dropout is not None:
name = "%s-dropout" % (name)
layer = Dropout(dropout, name = name)(layer)
if norm is not None:
name = "%s-%snorm" % (name, norm)
layer =... | 169905b19fe29d1beee2b4a3b5a5e97cb9ca9e93 | 3,630,921 |
def create_access(terms_to_check, new_term):
"""
Breaks a new_term up into separate constituent parts so that they can be
compared in a check_access test.
Returns a list of terms that should be inserted.
"""
protos = new_term.match.get('protocol', ['any'])
sources = new_term.m... | 61a3a6b786f61b56698e360a6b6acaf393d0fa15 | 3,630,922 |
def versionPropertiesDictionary(sql_row_list):
"""
versionPropertiesDictionary(sql_row_list)
transforms a row gotten via SQL request (list), to a dictionary
"""
properties_dictionary = \
{
"id": sql_row_list[0],
"model_id": sql_row_list[1],
"version": sql_row_list[2]... | ab8cdd166bf8a187945c44fd416c3a4cf4634d02 | 3,630,923 |
def register():
"""
Register a new user
"""
logger.debug('register()')
return render_template('register.html', user=None) | 9306168e54b6b2bdff532792d1ffa493608cc5b8 | 3,630,924 |
import logging
def verify_received_aes_key(key: dict, rsa_public_key) -> bool:
"""
Verifies the AES key received as a dict and passed here is valid.
:param dict key: An AES key, as a dictionary.
:param rsa_public_key: The RSA public key of the author.
:return bool: True if the information is a va... | 53d0578d8761a06be260b7a63dff97e123a4e010 | 3,630,925 |
def remove_indices(dist_array, indices):
"""
Remove given indices from dist_array
:param dist_array: a flattened version of the dist_matrix in the format of entries (node0/ window0, node1/ window1, distance),
usually sorted
:param indices: indices which should be removed
:return:
""... | 3b61645655a19c18889f7a02b8bfda0368091873 | 3,630,926 |
def bow_net(data, dict_dim, emb_dim=128, hid_dim=128, hid_dim2=96, class_dim=2):
"""
Bow net
"""
# embedding layer
emb = fluid.layers.embedding(
input=data,
size=[dict_dim, emb_dim],
param_attr=fluid.ParamAttr(name="@HUB_senta_bow@embedding_0.w_0"))
# bow layer
bow =... | 94c7f0483c98644d943815ba92e00cbee0196e50 | 3,630,927 |
def close_story(request):
"""
Tags: logs+stories
---
Closes an open story.
---
story_id:
in: path
type: string
required: true
"""
auth_context = auth_context_from_request(request)
# Only available to Owners for now.
if not auth_context.is_owner():
raise... | 4b28978c99c26f76bbe04d62a55ca22ba9d40676 | 3,630,928 |
def convert_dates_to_ISO(date: str, date_2: str):
"""Assumes both dates are current system year. If the latter one occurs chronologically
before the former (i.e given "december 4 2021" and "january 4 2021", january comes first in the year.
This means that the second date is likely the next year, so we'll assume tha... | 7fd68c06ad5abff67e5bd69c1a23530f985857e0 | 3,630,929 |
def findliteralblocks(blocks):
"""Finds literal blocks and adds a 'type' field to the blocks.
Literal blocks are given the type 'literal', all other blocks are
given type the 'paragraph'.
"""
i = 0
while i < len(blocks):
# Searching for a block that looks like this:
#
# ... | 43b2472784744e5d1c17b5b4e306b23c953223fa | 3,630,930 |
import argparse
def get_parser():
""" Return parser """
parser = argparse.ArgumentParser(description='BioWardrobe Migration', add_help=True)
parser.add_argument("-c", "--config", help="Path to the BioWardrobe config file", default="/etc/wardrobe/wardrobe")
logging_level = parser.add_mutually_exclusive... | 6f72a0ea5891acaf895b0c190b6f1774e1290731 | 3,630,931 |
import requests
def urlcheck():
"""takes all devurls and checks their header return"""
urlstatus = []
for elem in get_bundle_dev_url():
appads = "https://" + elem[1] + "/app-ads.txt"
try:
x = requests.head(appads, timeout=3.5, allow_redirects=True)
except requests.excep... | b4f8aa5cdd8cc4aab9b2a4ddf204ab3dd43f0792 | 3,630,932 |
def get_vpc_dhcp_options(dhcp_options_id=None,filters=None,tags=None,opts=None):
"""
Retrieve information about an EC2 DHCP Options configuration.
## Example Usage
### Lookup by DHCP Options ID
```python
import pulumi
import pulumi_aws as aws
example = aws.ec2.get_vpc_dhcp_options(dhc... | 05d73c3d230c3e815e47aa8c6134c89efb814439 | 3,630,933 |
import os
def moduleName(file):
"""Extract a module name from the python source file name, with appended ':'."""
return os.path.splitext(os.path.split(file)[1])[0] + ":" | 4f5035e80ddd3df7a8a93585bebf25e2e3300b49 | 3,630,934 |
def ms2str(v):
"""
Convert a time in milliseconds to a time string.
Arguments:
v: a time in milliseconds.
Returns:
A string in the format HH:MM:SS,mmm.
"""
v, ms = divmod(v, 1000)
v, s = divmod(v, 60)
h, m = divmod(v, 60)
return f"{h:02d}:{m:02d}:{s:02d},{ms:03d}" | 5d50aa072584e5ad17d8bd3d08b0b0813aced819 | 3,630,935 |
import operator
def regroup(X, N):
"""
Regroup the rows and columns in X.
Rows/Columns that are N apart in X are adjacent in Y.
Parameters:
X (np.ndarray): Image to be regrouped
N (list): Size of 1D DCT performed (could give int)
Returns:
Y (np.ndarray): Regoruped image
"""
#... | d4492e71a42a69d86d0e2a1c21bf05d13dfe13d7 | 3,630,936 |
def uint_to_two_compl(value: int, length: int) -> int:
"""Convert int to two complement integer with binary operations."""
if value >> (length - 1) & 1 == 0: # check sign bit
return value & (2 ** length - 1)
else:
return value | (~0 << length) | a0b7bd5192a3f12119ea7ec1a58ca785c37369bf | 3,630,937 |
def synthetic_pattern_program():
"""A program that tests pattern matching of `PrimOp` outputs.
Returns:
program: `instructions.Program`.
"""
block = instructions.Block(
[
instructions.prim_op(
[], ("one", ("five", "three")), lambda: (1, (2, 3))),
instructions.prim_op... | c3f55b75301604a394d9f0ec01d4198a27f90c8e | 3,630,938 |
def generator(z, out_channel_dim, is_train=True, alpha=0.2):
"""
Create the generator network
:param z: Input z
:param out_channel_dim: The number of channels in the output image
:param is_train: Boolean if generator is being used for training
:param alpha : leaky relu rate
:return: The tens... | 9bea06f8c78aadc2e9a4287ce44b12422cfead99 | 3,630,939 |
import re
def manual_filtration(word, neg_list):
"""作用在 word 上, 若该词为负例则返回 True, 否则返回 False"""
pattern_1 = r',|\.|:|;|"'
pattern_2 = r'行|示|为|较|见|天|音'
pattern_3 = r'切除|标本|摄取|存在|活检|穿刺|开口|引流|胸痛|患者|治疗|不适|受限|疼痛|基本|压缩'
pattern_4 = r'^[A-Za-z0-9_]+$'
remove_word_list = neg_list + ['病理', '癌', '炎', '占位'... | 6957c8a3b86073060ffeded9c5a7c7badf1005cc | 3,630,940 |
def two(f):
"""Church numeral 2: same as successor(successor(zero))"""
"*** YOUR CODE HERE ***"
return lambda x: f(f(x)) | 0ae1c89aca0a3fa85319882d49aea0cc05c12b7a | 3,630,941 |
import warnings
def _find_indexes(obj, var_name, min_limit, max_limit, use_dask):
"""
Function to find array indexes where failing limit tests
Parameters
----------
obj : Xarray.Dataset
Dataset containing data to use in test
var_name : str
Variable name to inspect
min_limi... | ad59ce154bf056d0ede5b98250fc95265ec83c89 | 3,630,942 |
def asinh_grad(orig, grad):
"""Returns [grad * 1/((1 + (x ^ 2)) ^ (1/2))]"""
x = orig.args[0]
ones = ones_like(x)
return [grad * ones / sqrt(ones + (x * x))] | 6cdcc4b0271aa8173059fe165fc77a556da79834 | 3,630,943 |
def inject_test_seed(seed, signature, user_data_dir):
"""Injects the given test seed.
Args:
seed (str): A variations seed.
signature (str): A seed signature.
user_data_dir (str): Path to the user data directory used to launch Chrome.
Returns:
bool: Whether the injection succeeded.
"""
seed_d... | 838c4f0a2bd969327f0733c270659243caa3a881 | 3,630,944 |
import math
def _scale_stage_depth(stack_args, repeats, depth_multiplier=1.0, depth_trunc='ceil'):
""" Per-stage depth scaling
Scales the block repeats in each stage. This depth scaling impl maintains
compatibility with the EfficientNet scaling method, while allowing sensible
scaling for other models ... | e1411f4c62bf5834a994d6c0313ea77e7368ee2c | 3,630,945 |
def tokenize(s):
"""
Ковертирует строку в питон список токенов
"""
return s.replace('(',' ( ').replace(')',' ) ').split() | 639baad1a6ec7640abe6752ad44e1f8585a9aafe | 3,630,946 |
def vote_entropy(votes, classes):
"""Calculates the vote entropy for measuring the level of disagreement in
QBC.
Parameters
----------
votes : array-like, shape (n_samples, n_estimators)
The class predicted by the estimators for each sample.
classes : array-like, shape (n_classes)
... | 2f8232d85fae5511555eba469d7b7c33b375a8e0 | 3,630,947 |
def printModelDict(localsDict):
"""Convert serverConfig model configuration to a dictionary. This writes
the dictionary as text. This does not create a usable modelDict, just one to
use to print out the dictionary as python code."""
modelDict={}
parmsDict={}
tcDict={}
dbs=DATABASES
scTe... | af8450e0d2807198de5f09d3245ff8100f9e8cdf | 3,630,948 |
import ctypes
def ira_equinox(jd_tdb, equinox, accuracy=0):
"""
To compute the intermediate right ascension of the equinox at
the input Julian date, using an analytical expression for the
accumulated precession in right ascension. For the true equinox,
the result is the equation of the origins.
... | ce145a20c623e444623c6ae3f5d7d59910520a82 | 3,630,949 |
import os
def load_plugins(plugins_folder, verbose=True):
"""Import all plugins from target folder recursively."""
found_plugins = []
for pack in os.walk(plugins_folder):
for filename in pack[2]:
if "_" == filename[:1] or ".py" != filename[-3:]:
continue
... | f33cb1f4b817136ba9320ceda8174e74d9b4ffcd | 3,630,950 |
from typing import Sequence
from typing import Any
from typing import Callable
from typing import Dict
def _generate_steps(
episode: Sequence[Any],
step_fn: Callable[[Dict[str, Any]], Dict[str, Any]]) -> Dict[str, Any]:
"""Constructs a dictionary of steps for the given episode.
Args:
episode: Sequenc... | 4ddafb41501a1ab6b61b325ebb8db0c2bd40bf85 | 3,630,951 |
def format_results_data(results_data, compute_rank=True):
"""Formats results_data as sorted list of rows so it can be easily displayed as results_table
Appends user and ranks.
Side effect: This function modifies objects (i.e. individual results)
contained in results_data
"""
Result = namedtuple(... | 6fdceb3a07ebcc23b245e43a2eb3770f67073cd0 | 3,630,952 |
def encode_triangle(X, centroids):
"""
Perform triangle k-means encoding
"""
X3 = X.reshape(X.shape[0], 1, X.shape[1])
centroids3 = centroids.reshape(1, centroids.shape[0], centroids.shape[1])
z = np.sqrt(((X3 - centroids3) ** 2).sum(2))
means = z.mean(1).reshape(-1, 1)
return np.maximum... | 98f11930892b61d8a7ee653a4dab677a6d0543d1 | 3,630,953 |
def get_user_and_check_password(username, password):
"""
Called by account controller and/or AuthKit valid_password to return a user from local db
"""
try:
q = Session.query(User).select_from(join(User, UserLogin, User.login_details))
q = q.filter(User.id == make_username(usernam... | 3def5ad6bba4486d235d58b4f8f50cf3ac27b734 | 3,630,954 |
import hashlib
def get_db_for_id(id_value):
"""
Work out the database number containing a Review record with pk of
"id_value".
"""
# XXX: If we were interested in being able to add databases and do minimal
# data moving, it would be better to use a consistent hashing algorithm
# here (dist... | 7ece564172061e31c61168cba02b034ac2666533 | 3,630,955 |
def subclass(request):
"""Return a Object subclass"""
try:
params = request.param
except AttributeError:
params = {}
class TestObject(Object):
@property
def fields(self):
return params.get("fields", {})
TestObject.__name__ = params.get("name", "TestObjec... | 376578606f20ae8899dba01590675847a2c8e11f | 3,630,956 |
def is_index(file_name: str) -> bool:
"""Determines if a filename is a proper index name."""
return file_name == "index" | 7beb5779b61e25b4467eb7964478c78d44f28931 | 3,630,957 |
from typing import List
def _recv_n_get_rsp(event: "Event") -> List[str]:
"""Logging handler when an N-GET-RSP is received.
Parameters
----------
event : events.Event
The evt.EVT_DIMSE_RECV event that occurred.
"""
msg = event.message
cs = msg.command_set
dataset = "None"
... | 1ccc8951e212ecbacdd7a9e48986a646c15e9da2 | 3,630,958 |
def GenerateShardedFilenames(spec): # pylint:disable=invalid-name
"""Generate the list of filenames corresponding to the sharding path.
Args:
spec: Sharding specification.
Returns:
List of filenames.
Raises:
ShardError: If spec is not a valid sharded file specification.
"""
basename, num_sha... | 38fe085c7063c80d633221aab9c0159fc8bc68ac | 3,630,959 |
def _tseries_from_nifti_helper(coords, data, TR, filter, normalize, average):
"""
Helper function for the function time_series_from_nifti, which does the
core operations of pulling out data from a data array given coords and then
normalizing and averaging if needed
"""
if coords is not None:
... | 1e464b0f54536ab062ae32b49ed821f2d230f45f | 3,630,960 |
import hashlib
def hash_short(message, length=16):
""" Given Hash Function"""
return hashlib.sha1(message).hexdigest()[:length / 4] | bd071674ce5caf382dc73d27835f43409a6a49d2 | 3,630,961 |
def feincms_frontend_editing(cms_obj, request):
"""
{% feincms_frontend_editing feincms_page request %}
"""
if hasattr(request, 'session') and request.session.get('frontend_editing'):
context = template.RequestContext(request, {
"feincms_page": cms_obj,
'FEINCMS_ADMIN_ME... | 6e1e1e0ee771d4260ffd310f970bf53a045a48ba | 3,630,962 |
def _add_tensor_cores(tt_a, tt_b):
"""Internal function to be called from add for two TT-tensors.
Does the actual assembling of the TT-cores to add two TT-tensors.
"""
ndims = tt_a.ndims()
dtype = tt_a.dtype
shape = shapes.lazy_raw_shape(tt_a)
a_ranks = shapes.lazy_tt_ranks(tt_a)
b_ranks = shapes.lazy_... | 07c1c79fff1547afe6c69fc82fe584f418432d8a | 3,630,963 |
from typing import OrderedDict
def create_mosaic_iterative(dataset_in, clean_mask=None, no_data=-9999, intermediate_product=None):
"""
Description:
Creates a most recent - oldest mosaic of the input dataset. If no clean mask is given,
the 'cf_mask' variable must be included in the input dataset, a... | 6ba190145b2b655decd7bdd770abd8a6390b09bc | 3,630,964 |
from typing import Sequence
from typing import cast
import collections
def dicom_file_loader(
accept_multiple_files: bool, stop_before_pixels: bool
) -> Sequence["pydicom.Dataset"]:
"""A Streamlit component that provides DICOM upload functionality.
Parameters
----------
accept_multiple_files : ``... | acaf9c54270a67f1893605a9a1d5b101dd02aba6 | 3,630,965 |
def get_substrings(source: str):
"""Get all substrings of a given string
Args:
string (str): the string to generate the substring from
Returns:
list: list of substrings
"""
# the number of substrings per length is the same as the length of the substring
# if the characters are... | 79f1db4184c51235a9d6beb8437f1647bc993958 | 3,630,966 |
import csv
def _write_output_csv(reader: csv.DictReader, writer: csv.DictWriter,
config: dict) -> list:
"""Reads each row of a CSV and creates statvars for counts of
Incidents, Offenses, Victims and Known Offenders with different bias
motivations.
Args:
reader: CSV dict ... | 057820c97100b626171250d4d97f90b07f0c48a7 | 3,630,967 |
def get_vehicle_lay_off_engine_acceleration(carla_vehicle):
"""
Calculate the acceleration a carla vehicle faces by the engine on lay off
This respects the following forces:
- engine brake force
:param carla_vehicle: the carla vehicle
:type carla_vehicle: carla.Vehicle
:return: acceleratio... | 84ca84d75866840e88cc6afdb615cbc0529ea311 | 3,630,968 |
from typing import Dict
from typing import Any
import sys
def create_data(name: str) -> Dict[str, Any]:
"""Arbitrary function that returns a dictionary.
This demonstration uses pydantic, but any dictionary can be tested!
"""
return User(id=sys.maxsize, name=name).dict() | 8d5e04da128e4ff55fcb3d2fc375f72ab876246b | 3,630,969 |
def _run_docker_shell_script(script_name, docker_dir, trailing_args=None,
env_variables=dict()):
"""
script_name (String) filename of a script in the nest/docker/ directory
docker_dir (String) directory of docker scripts in the nest repo. expected
to be /code_live/docker, but may be different is... | a68d85a6affd1905d312b91ccc85475c30809c22 | 3,630,970 |
def _create_functional_connect_edges_dynamic(n_node, is_edge_func):
"""Creates complete edges for a graph with `n_node`.
Args:
n_node: (integer scalar `Tensor`) The number of nodes.
is_edge_func: (bool) callable(sender, receiver) that returns tf.bool if connected. Must broadcast.
Returns:
A di... | 338b7a240f516703853af8f810f56e313fcb2b99 | 3,630,971 |
import os
def _BreakoutFilesByLinter(files):
"""Maps a linter method to the list of files to lint."""
map_to_return = {}
for f in files:
extension = os.path.splitext(f)[1]
if extension in PYTHON_EXTENSIONS:
pylint_list = map_to_return.setdefault(_PylintFiles, [])
pylint_list.append(f)
el... | 0f99bd166c9f1cfe73b10b745df3bca7ef4d3306 | 3,630,972 |
from operator import matmul
def simulateBERParallel(codes, channelfun, params, printValue=True):
"""
Simulates BER values at multiple SNRs, where the massively parallel algorithm is used. This implementation is especially designed for cupy.
Args:
codes (ndarray): an input codebook, which is gener... | 89df47bbe05b19f32276d608c260ae51ea9c7f28 | 3,630,973 |
from datetime import datetime
import json
def modify_app_description(s, base_url, app_id, description):
"""
Modifies the description of an app
"""
rjson = app_full(s, base_url, app_id)[1]
rjson["modifiedDate"] = str(
((datetime.today()) + timedelta(days=1)).isoformat() + "Z"
)
rjs... | e4f1529a31dd982b2ccf56d31542139f6cc564ef | 3,630,974 |
def search_tag(resource_info, tag_key):
"""Search tag in tag list by given tag key."""
return next(
(tag["Value"] for tag in resource_info.get("Tags", []) if tag["Key"] == tag_key),
None,
) | 5945631a3de7032c62c493369e82dd330ef2bc47 | 3,630,975 |
def compute_GARCH_price(theta,
num_periods,
init_price,
init_sigma,
risk_free_rate,
num_simulations=50000):
"""
Compute asset price at period t + s (s periods ahead) given estimated theta... | de6a6aca57bb6ea63cfa39221522798322bafdda | 3,630,976 |
def create_order_nb(size: float,
price: float,
size_type: int = SizeType.Amount,
direction: int = Direction.All,
fees: float = 0.,
fixed_fees: float = 0.,
slippage: float = 0.,
min... | 660940e9258f1b43352cf5e2b78e083b0c984bc7 | 3,630,977 |
def generate_noise_2d_fft_filter(F, randstate=None, seed=None, fft_method=None,
domain="spatial"):
"""Produces a field of correlated noise using global Fourier filtering.
Parameters
----------
F : dict
A filter object returned by
:py:func:`pysteps.noise... | 4c4dbe8b22cf73730bff84affa5ff592e0484a1c | 3,630,978 |
import os
def _get_image_files_and_labels(name, csv_path, image_dir):
"""Process input and get the image file paths, image ids and the labels.
Args:
name: 'train' or 'test'.
csv_path: path to the Google-landmark Dataset csv Data Sources files.
image_dir: directory that stores downloaded images.
Re... | fdde6e48c859579c41086e17c128e463145a430c | 3,630,979 |
def get_spending_features(txn, windows_size=[1, 7, 30]):
"""
This function computes:
- the cumulative number of transactions for a customer for 1, 7 and 30 days
- the cumulative average transaction amount for a customer for 1, 7 and 30 days
Args:
txn: grouped transactions of custome... | b648df3d1217074edec455a416e0eb698d8069ee | 3,630,980 |
def break_up(expr):
"""
breaks up an expression with nested parenthesis into sub expressions with
no parenthesis, with the innermost expressions first, that needs to be
calculated before doing the outer expression. also replaces the statement with
a single symbol in the larger expression
"""
p=0
new_ex... | 7f28290a3dadfec2bd42696bcf7be348288a7bca | 3,630,981 |
def fft_operation(file_path):
"""
FFT operation
:param file_path: Original wav file path
:return: freqs, 20 * log10(fft/max_fft), name
"""
wave_data, nchannels, sample_width, framerate, numframes = read_file(file_path)
abs_fft = np.abs(np.fft.fft(wave_data))
normalized_abs_fft = abs_fft... | 75c672298e3d8650e79ee56ce540006102a1b375 | 3,630,982 |
import six
def _expand_expected_codes(codes):
"""Expand the expected code string in set of codes.
200-204 -> 200, 201, 202, 204
200, 203 -> 200, 203
"""
retval = set()
for code in codes.replace(',', ' ').split(' '):
code = code.strip()
if not code:
continue
... | 52056db88bf14352d4cda2411f25855457defbd7 | 3,630,983 |
from typing import Optional
from pathlib import Path
import importlib
def predict(
seq: np.ndarray,
aa_cut: Optional[np.ndarray] = None,
percent_peptide: Optional[np.ndarray] = None,
model: Optional[GradientBoostingRegressor] = None,
model_file: Optional[Path] = None,
pam_audit: bool = True,
... | 50cb3adc03d017e7e94353dd9a9b15166e616d4a | 3,630,984 |
import collections
def _is_proper_sequence(seq):
"""Returns is seq is sequence and not string."""
return (isinstance(seq, collections.abc.Sequence) and
not isinstance(seq, str)) | d5f1f211330a9f4928b8cc8c7407adaf705fd4b2 | 3,630,985 |
def sigmoid(mat, target = None):
"""
Apply the logistic sigmoid to each element of the matrix mat.
"""
if not target:
target = mat
err_code = _cudamat.apply_sigmoid(mat.p_mat, target.p_mat)
if err_code:
raise generate_exception(err_code)
return target | ba02fe038ce1d491b40b605baf43e4bf8afda057 | 3,630,986 |
def mutation_modify_controlaction(controlaction_id: str, actionstatus: ActionStatusType, error: str = None):
"""Returns a mutation for modifying the status and errors of the ControlAction
Arguments:
controlaction_id: The unique identifier of the ControlAction.
actionstatus: the status to update ... | f7ef2c0174fe8c31505d2397df38602c9cee46ac | 3,630,987 |
def get_colours(time, flux, data, nuv=[nuvwave, nuvtrans], u=[uwave, utrans], r=[rwave, rtrans], filter_pairs=None):
"""" Calculates the colours of a given sfh fluxes across time given the BC03 models from the magnitudes of the SED.
:time:
Array of times at which the colours should be calcu... | d03c33822918c50d30db06284fbe56571886228c | 3,630,988 |
def loginpage():
"""A route to login the user."""
year = date.today().year
return render_template("website/login.html",
base=get_base_data(year),
route=Routes,
year=year,
github_enabled=is_github_supp... | 282630fb7c4585cf0321c3fa3fc3ce55bfc33c8e | 3,630,989 |
from hypothesis.internal.conjecture.shrinker import dfa_replacement, sort_key
import math
def learn_a_new_dfa(runner, u, v, predicate):
"""Given two buffers ``u`` and ``v```, learn a DFA that will
allow the shrinker to normalise them better. ``u`` and ``v``
should not currently shrink to the same test cas... | ff0ba6d5831099d8d5f392b3cd7dec59ac3a3663 | 3,630,990 |
def generate_corrected_profiles (corr_factor, fwd_border_dicts, fwd_profile, plasmid_length, scale):
""" Correct the edges of the transcription profiles
"""
# New profile to hold the normalised data
Normalized_fwd_profile = np.ones(plasmid_length)*scale
# Cycle through each transcript (no idea why this is a dict)
... | d7fbd70e7651b7467d7cc6e754bb4baad1e8d2ca | 3,630,991 |
import json
import sys
import traceback
def base_handler(event: Event, loader_cls: type) -> Response:
"""Handler which is called when accessing the endpoint."""
response: Response = {"statusCode": 200, "body": json.dumps("")}
db_helper = DatabaseHelper()
try:
point = (
Point(event[... | b1336c6ae71724284d5221cce3858e31070b68d1 | 3,630,992 |
import os
def publish_image_dir():
"""
checks if publishing of images configured
and if so it returns the directory to publish
to (full path) or None
"""
root_dir = publish_root_dir()
if root_dir != None:
rel_dir = get_value_with_default(['publish', 'package_dir'], 'images')
... | 19ac151adb31488b300e08db34fea617d0e9b2ff | 3,630,993 |
def transforToManagerProxyObject(manager, data):
"""将不转换dict中的key
只支持基础数据，dict，list和tuple
tuple将会转换成list
result = data
"""
if isinstance(data, dict):
result = manager.dict()
for key in data:
result[key] = transforToManagerProxyObject(manager, data[key])
elif isinstance(data, list) or isinstance(data, tupl... | d9b0c17b1e1eb50a9bede908130d8444422b8fd4 | 3,630,994 |
import json
import time
def get_new_account_id(event):
"""Return account id for new account events."""
create_account_status_id = (
event["detail"]
.get("responseElements", {})
.get("createAccountStatus", {})["id"] # fmt: no
)
LOG.info("createAccountStatus = %s", create_accoun... | e782e930d09b2f02b10547e5a39e14bba852d896 | 3,630,995 |
from tvrenamer.common import tools
def list_opts():
"""Returns a list of oslo_config options available in the library.
The returned list includes all oslo_config options which may be registered
at runtime by the library.
Each element of the list is a tuple. The first element is the name of the
gr... | a650cf9fb8d3bfd0ee60e6301463ff62d3842f8f | 3,630,996 |
from datetime import datetime
def tokenize_for_t5_advice_training(encoder, subreddit=None, date=None, title=None,
selftext=None, body=None):
"""
Tokenizes the post title / post selftext / comment body.
If it's too long we'll cut some paragraphs at random from the selfte... | 5716eb12d2f1c7773fcb49abfe7c203375ef9c65 | 3,630,997 |
def hvdisp_plot_records_2d(records,
to_pe,
config,
t_reference,
time_stream=None,
tools=(x_zoom_wheel(), 'xpan'),
default_tools=('save', 'pan', 'box_zoom', 's... | 0fa08d4f71ef08c35a2121e4716bce213e39d9d8 | 3,630,998 |
import re
def join_url(url, *paths):
"""
:param url: api url
:param paths: endpoint
:return: full url
"""
for path in paths:
url = re.sub(r"/?$", re.sub(r"^/?", "/", path), url)
return url | 32e085acc64590901afcf3d4ded47f8be7d40119 | 3,630,999 |
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