content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def get_model_names(model='all'):
"""
Returns all available model names as a list of strings.
Parameters
----------
models: str
OPTIONAL. Default value is 'all' in which case all keys in default_models are returned.
If 'mixed' is passed, only the MixedFluid model names are return... | 9ebf63306e298877c64fc80ce82e54381e005764 | 59,600 |
from operator import add
from typing import Concatenate
def compile_bigrus_attention(shape, n_hidden_layers, hidden_units_size, dropout_rate, word_dropout_rate, lr, mode):
"""
Compiles a BiGRU based on the given parameters
:param mode: Depending on your choice : ['Single Task', 'Multi Task-1', 'Multi Task... | e3e8b1ca514e1dbb6c93e5f933aa19d8c9f48953 | 59,601 |
def get_dom_attr_value(dom, tag_name, attr_name):
"""
Return value of a tag's attribute from dom (XML file).
Arguments:
tag_name -- name of dom tag in which the attribute is found.
attr_name -- name of dom attribute for which the value should be returned.
"""
tag=dom.getElementsByTag... | 26f31fd7db526bb5503b7ce156b19a99705041d1 | 59,602 |
def render_xml(request, template, context=None, **kwargs):
"""Safely renders xml, stripping out nasty control characters."""
if context is None:
context = {}
rendered = render_xml_to_string(request, template, context)
if 'content_type' not in kwargs:
kwargs['content_type'] = 'text/xml'
... | 5212ce2a41bb5a968d85f1e70d4b200866d46897 | 59,603 |
from pathlib import Path
def read_camera_intrinsics(settings_path: Path) -> CameraIntrinsics:
"""
Read the camera intrinsics from file
:param settings_path: The path to the camera settings file, output by the NDDS exporter
:return:
"""
camera_settings = read_json(settings_path)
return Came... | 3a4745818c71357e6fe2d1f207f40a2ad42b0321 | 59,604 |
def share_server_get(context, id, session=None):
"""Get share server DB record by ID."""
return IMPL.share_server_get(context, id, session=session) | e7ba5854d72687c1c791bc2ddcd1edd1ca8086a4 | 59,605 |
def get_profile_for_plotting(equilibrium_list):
"""
List of symmetric equilibrium
:param equilibrium_list:
:return: Representative profile.
"""
selected_profile = None
sample_team = 0
strategy_of_interest = simmodel.SIMPLE_INFLATE_STRATEGY
for profile in equilibrium_list:
... | f07547821c5e92e7596d5474da6b736b29b3c306 | 59,606 |
def _hermite_moment_nonlinear(u,mu,sigma,mu3,mu4,fisher=True):
"""
Hermite moment models for nonlinear responses
"""
if fisher:
mu4 = mu4 + 3
if mu4 > 3 :
h3 = mu3/6
h4 = (mu4-3)/24
c4 = (np.sqrt(1+36*h4)-1)/18
c3 = h3/(1+6*c4)
k = 1/(np.sqrt(1+2*c3... | c93b116c23066a21f68ac47ac051410540259dd4 | 59,607 |
def fmeasure(confusion_matrix):
"""Compute the f-measure of the linkage.
The f-measure is calculated as:
2 * (precision * recall) / (precision + recall).
Parameter Description:
confusion_matrix : The matrix with TP, FP, FN, TN values.
The method returns a float value.
"""
... | c148f52952d5d5a71c6880dc5777e83eaac1f5f8 | 59,608 |
def probability_of_category_A(stimulus_i, category_a_exemplars, category_b_exemplars, w, c, r, alpha, b):
"""
Function that calculates the probability of stimulus_i belonging to category A. Note that this assumes there are
only two categories in total, which is typical of categorization experiments (equatio... | 33eb4c7b105f310e43d2b55ae0221e01e56b9390 | 59,609 |
def role_list(auth=None, **kwargs):
"""
List roles
CLI Example:
.. code-block:: bash
salt '*' keystoneng.role_list
salt '*' keystoneng.role_list domain_id=b62e76fbeeff4e8fb77073f591cf211e
"""
cloud = get_operator_cloud(auth)
kwargs = _clean_kwargs(**kwargs)
return clou... | 90bfa586af63155eb298138eb9007df38aaefd77 | 59,610 |
def Inv_UpSample(name, x, scale=False, reverse=False):
"""
Upsample the given inputs by factor 2x2, but will decrease the channel num by factor of 4, such that
the overall number of units remains unchanged
:param name: name scope
:param x: given inputs, [NHWC]
:param scale: if true, scale the sp... | 472267e1be3c596f5c4dffb49b3ed66f21f19ad5 | 59,611 |
def collide(Aleft, Aright, Bleft, Bright):
"""
optimised for speed.
"""
# quickest rejections first;
if Aright < Bleft:
return(False)
if Aleft > Bright:
return(False)
if Aleft == Bleft: return(1) # I have to cheat here otherwise it returns 0 which will evaluate as False;
... | d66afddce5f7a464446d598d948cc74c0d97a70a | 59,612 |
def wendlingModel_2(y, P, h = 1./512, u = np.zeros(1), couplIntra = 0, couplInter = 0 ):
""" Modified Wendling's neural mass model ODEs
y: last state
P: model parameters
h: step (1/Fs)
u: stimulation input - 2 elements u[0] voltage deflection to all cells. u[1] sums the stimulus to the model input ... | 79c409da2692f21c3ccb0e081d25926d0de30b7b | 59,613 |
def construct_graphql_query(dict_object, queryDict=None, key="query"):
"""
{"name": "wallet",
"key": "username",
"fields": ["owner", "upcoming_earnings",
{'name': "transactions",
'key': None,
"fields": ["display", "type"] }]}
:returns
query{
wallet(username:""){
... | 27af54cc6f10e57cc9e6d98dc0816f51d82dd103 | 59,614 |
import shutil
def delete_directory(path):
"""
Deletes a ticket attachments directory from disk
"""
path = '{}/{}'.format(settings.MEDIA_ROOT, path)
try:
shutil.rmtree(path)
return path
except:
return False | 42b06b7eb563cfea86409afd85df2964c69dad15 | 59,615 |
def sort_SMILES_list_by_MW(SMILES_list):
"""
sort smiles by molecular weight
"""
if len(SMILES_list) == 0:
return [-1]
mw_list = [calc_MW_from_SMILES_list(i) for i in SMILES_list]
dataset = (list(zip(mw_list, SMILES_list)))
dataset.sort(key=lambda x: x[0])
mw_list, SMILES_list =... | bc21a370c767b849978882882bdd0641b0f702e2 | 59,616 |
from typing import Tuple
def fetch_dbt_data(dbt: DbtCloud) -> Tuple[dict, dict]:
"""call dbt api for all latest runs and jobs
Args:
dbt (DbtCloud): dbt cloud api instance
Returns:
Tuple[dict, dict]: dict of both runs and jobs
"""
all_runs = get_all_runs(dbt)
all_jobs = get_al... | a832fdcc7083e106da6f92dbabb71906cb64968d | 59,617 |
from typing import List
import ray
import random
def run_wrk_on_all_nodes(trial_length: str,
num_connections: int,
http_host: str,
http_port: str,
all_endpoints: List[str] = None):
"""
Use ray task to run one w... | 48c95de8ec87d789b984925a81914db28167fe98 | 59,618 |
def plaintext():
"""Test 6: Plaintext"""
return b"Hello, World!", {"Content-Type": "text/plain"} | 8005ee608a45956d5aa9fc4edf34c9ee3c8605d6 | 59,619 |
def get_simbad_names(name, verbose=False):
"""
Get list of alternate names from Simbad
Parameters
----------
name : str
Name to resolve
verbose : bool
Verbosity flag
Returns
-------
List of names
"""
t = Simbad.query_objectids(name)
if t is not None and... | 6d0518f75d21891792b9820f9654e73261d3b384 | 59,620 |
def logout_view(request):
"""Logging off the user
:param request: Django's HTTP Request object
:return: Redirect to homepage
"""
logout(request)
return redirect("homepage") | ad11a78c918f89b199f62f371fa40be2b5c9d153 | 59,621 |
import os
def save_path(filename):
"""Save path of last opened file"""
if len(filename) > 1:
fp = open(config_path + '\\path.txt', 'w')
path, fname = os.path.split(filename)
fp.write(path)
fp.close()
else:
path = '.'
return path | 7a4bd7c7608fe8cd7b30cdfd207f61d033a9204b | 59,622 |
import re
def generate_stencil(pcb_footprints, config):
# type: (list, Config) -> dict
"""
Generate BOM from pcb layout.
:param pcb_footprints: list of footprints on the pcb
:param config: Config object
:param extra_data: Extra fields data
:return: dict of BOM tables (qty, value, footprint... | 493386d3a4bcb8b4184bd027d9e43da01b4954e3 | 59,623 |
def inspect_calibration_surface(df, param_zf, microns_per_pixel):
"""
To run:
dict_fit_plane, fig_xy, fig_xyz, fig_plane = correct.inspect_calibration_surface(df, param_zf, microns_per_pixel)
:param df:
:param param_zf:
:param microns_per_pixel:
:return:
"""
if 'x' not in df.column... | 90aec909eb00aa06d879e34fbf72bb2e19c38fa8 | 59,624 |
import subprocess
import warnings
def execute(*args, **kwargs):
"""Run an executable, but suppress its output."""
try:
return subprocess.run(*args, check=True, stdout=subprocess.DEVNULL, **kwargs)
except FileNotFoundError:
warnings.warn(
"{} not in path, skipping".format(args[0... | 76db362ff75b597a8be3d512c890583502d17f0f | 59,625 |
def check_inside_points(points, cur_boxes):
"""
points: [num, n]
cur_boxes: [m 7]
return: [num, m]
"""
# first cast points to second format
points = points.copy()
cur_boxes = cur_boxes.copy()
points_xyz = points[:, :3]
points_xyz = points_xyz[:, [0, 2, 1]]
cur_boxes = cur_bo... | d458c067bbf87e8b5f2a53e7284f548db093ee60 | 59,626 |
def data_route():
"""`/data/` endpoint handler"""
filename = get_filename(request)
path = request.args.get("path")
selection = request.args.get("selection")
format_arg = request.args.get("format")
flatten = parse_bool_arg(request.args.get("flatten"), fallback=False)
with h5py.File(filename,... | 8f9304d0efc045660dead59ef983e2b2ab6ca801 | 59,627 |
def drop_voxels_with_mean_negative_amplitudes(df):
"""drop all voxels that have an average negative amplitude (across stimuli)
"""
groupby_col = ['voxel']
if 'indicator' in df.columns:
groupby_col += ['indicator']
try:
# in this case, we have the full dataframe (with each bootstrap
... | 2799c866b411ff0e63cdcc4b28adf3bde9595f4e | 59,628 |
def categorical_focal_ignoring_last_label(alpha=0.25,gamma=2):
"""
Focal loss implementation
Variables:
weights: numpy array of shape (C,) where C is the number of classes
Usage:
weights = np.array([0.5,2,10]) # Class one at 0.5, class 2 twice the normal weights, class 3 10x.
... | bf93ffb8dbadee85756c8e9204e809917b409f94 | 59,629 |
def split_peaks(prot_arr, pr, skp=0):
"""
split peaks in n samples giving skp fractions of window
returns
'right_bases': array([32]), 'left_bases': array([7])
"""
peaks = list(st.peak_picking(prot_arr))
left_bases = peaks[1]["left_bases"]
right_bases = peaks[1]["right_bases"]
fr_peak... | 47dc06e53d46e146e42116274473f46e0c2f0dac | 59,630 |
from typing import List
def download_media(
client: pyrogram.client.client.Client,
chat_id: str,
last_read_message_id: int,
media_types: List[str],
) -> int:
"""Download media from Telegram.
Parameters
----------
client: pyrogram.client.client.Client
Client to interact with Te... | 1171043981ac8fb4e25dfbaa5c74c1f72d728d1f | 59,631 |
import re
def follow_directions(starting_point, starting_orientation, *directions):
"""Given a starting point, starting orientation
and a list of directions of the form DN, where D
is R (right) or L (left) and N is an integer,
return the ending point and orientation."""
point = starting_point
... | 5d276bd25a317e1051c56596df7e165a6dc39593 | 59,632 |
from . import routes
def create_app():
"""
create and return the flask application
"""
app = Flask(__name__)
# pylint: disable=import-outside-toplevel
app.register_blueprint(routes.bp)
return app | d751ba54c1ad4f60abb0a452aad7e428ac2a7bb6 | 59,633 |
from .pb import test_pb2
from .pb import test_pb2_grpc
import random
import string
def test_mock_stream_stream_call(import_path):
"""Test Bidirectional Streaming gRpc Call"""
class TestServicer(test_pb2_grpc.GRPCTestServicer):
_server_id = random.randint(2, 2 ** 10)
def BidirectionalStreami... | ab10c22a2b186a9defd551550933ef17923640d0 | 59,634 |
def flip_y(prob=0.8):
"""
Construct a transformation randomly containing X/Y flips (or not).
Args
flip_x_chance: The chance that the result will contain a flip along the X axis.
flip_y_chance: The chance that the result will contain a flip along the Y axis.
Returns
a homogeneous... | 381ed2efde5e7e8e6d44adeea3a2006daa539222 | 59,635 |
def column_stats(collection, column, stats_type):
"""Aggregates over a given property of the objects in a collection, calculating the sum, min, max, mean,
sample standard deviation, sample variance, total standard deviation and total variance of the selected property.
Args:
collection (FeatureColl... | c4792043d44b0f6d23c843d0df6dde9603c1d426 | 59,636 |
import os
import json
def read_data(directory):
"""
Read the data and associated files from the
data directory and return it in the form of arrays
args:
directory: The data directory specified by FLAGS.data_dir
"""
if not os.path.exists(FLAGS.logs_dir+FLAGS.config_id+'/'):
... | 3228b47d8214dad4f78c21961cccc18250c81f0c | 59,637 |
def EGCD(a, b):
"""
Extended Euclidean algorithm
computes common divisor of integers a and b.
a * x + b * y = gcd(a, b)
returns gcd, x, y or gcd, y, x.
Sorry, I can't remember
"""
if a == 0:
return (b, 0, 1)
else:
b_div_a, b_mod_a = divmod(b, a)
... | 81a9365bfe2b82f0856489710afb7186d1fcf803 | 59,638 |
def _get_module(module: Module, name: str) -> Module:
"""Recursively get a sub-module from a module.
Args:
module: A `torch.nn.Module`.
name: The name of the submodule to return, in the form of a period-delinated
string: `sub_module.subsub_module.[...].leaf_module`.
Returns:
... | 913f9920c9079aa2d746d8e61469611181664f9f | 59,639 |
from typing import List
import os
def get_topologies(scenario: str) -> List[str]:
"""Get topology list of specified built-in scenario name.
Args:
scenario(str): Built-in scenario name.
Return:
List[str]: List of topology name.
"""
scenario_topology_root = f'{scenarios_root_folder... | dc697ce159c9db4a15355bcfd7957730bb2a9b0f | 59,640 |
import html
def description_card():
"""
:return: A Div containing dashboard title & descriptions for tab 1.
"""
return html.Div(
id="description-card",
children = [
html.H3("Welcome to CZviz"),
dcc.Markdown('''This app allows you to explore the full dataset and ... | 5a2a2d0c042fa408c10bc0e0f86f0ec63a06828e | 59,641 |
import csv
def np_float_array_from_file(data_file, delimiter=" ", header=False, gather_hist=False):
"""
Adds to the basic np.loadtxt by performing data checks.
@param data_file: file expected to have space-separated values, with the same number of entries per row
@param delimiter: default is a space-s... | 0a48de03974f425677425d61e89433011387b5c0 | 59,642 |
def _evaluate(p_eval_step,
params, eval_batch):
"""Computes evaluation metrics.
Args:
p_eval_step: Parallelized evaluation step computation.
params: Model state.
eval_batch: Batch of evaluation examples.
Returns:
Raw model predictions and metrics.
"""
n_devices_per_host = jax.l... | 11d17ec8bedcd3cbfacf7e6cc12fef5a4f95221c | 59,643 |
def _assemble_frequencies(animal_obj, start_time, end_time):
""" Converts the coordinates of the animal trajectory into frequency data over the grid.
Gathers the frequency data for approximating the heatmap representing the amount of
time an animal spent in each location over a specified time interval.
... | 1e4fe463e49bafb91f7e95088c12c3580313d66d | 59,644 |
import argparse
def parse_command_line(argv):
"""
Parse command line arguments. See the -h option.
Args:
argv (str): Command line arguments, including caller filename.
Returns:
dict: Dictionary of command line arguments and their parsed values.
"""
parser = argparse.Argument... | a05422b71605356e22be53c4b0fc2fcafcc9ec85 | 59,645 |
def compute_ood_logsums(
choosers,
logsum_settings,
nest_spec, logsum_spec,
od_skims,
locals_dict,
chunk_size,
trace_label):
"""
Compute one (of two) out-of-direction logsums for destination alternatives
Will either be trip_origin -> alt_dest or alt_d... | 7d8edd8ee79ac2e06ddbaf9f09ea801e3f61eed8 | 59,646 |
def view_profile(request, username=None):
""" Display profile info, such as snippets, tags, and followed users """
#Set current user and check if it's my profile
if username is None or username == request.user.username:
user = request.user
my_profile = True
else:
user = get_obje... | ec2e4b296dc01bf46e59983af84d658b6e058536 | 59,647 |
def filter_attr(the_dict, attr_names):
"""
Only return the item that in the attr_names list
:param the_dict:
:param attr_names: comma separated names
:return: dict
"""
if isinstance(the_dict, dict):
attrs = attr_names.split(',')
return dict((k, v) for k, v in the_dict.items... | 1ca5ad38af808c6a533c3abb22ce7cc26d5f82f2 | 59,648 |
def _GetFlagMetavar(flag, metavar=None, name=None, markdown=False):
"""Returns a usage-separator + metavar for flag."""
if metavar is None:
metavar = flag.metavar or flag.dest.upper()
separator = '=' if name and name.startswith('--') else ' '
if isinstance(flag.type, arg_parsers.ArgList):
metavar = flag... | e8fef13fa12ea47b41ec5328dba7efb56991e9e9 | 59,649 |
def getTempDirectory(rootDir=None):
"""
returns a temporary directory that must be manually deleted
"""
if rootDir is None:
return tempfile.mkdtemp()
else:
while True:
rootDir = os.path.join(rootDir, "tmp_" + getRandomAlphaNumericString())
if not os.path.exist... | d29ff7d01fd24e5281f33d9d94b5d413c52cf47b | 59,650 |
def test_single_for_builtin_function_numpy_sum():
"""
Feature: JIT Fallback
Description: Test fallback with control flow.
Expectation: No exception.
"""
@ms_function
def control_flow_for():
x = np.array([1, 3, 5, 7, 9])
y = np.array([0, 2, 4, 6, 8])
result = x
... | 5801d02abed47cd65d33e12056717eaabe90ab64 | 59,651 |
from typing import Optional
import re
def get_default_branch_from_remote(
remote: str,
) -> Optional[str]:
"""
Get default branch from remote.
:param remote: the remote name
:return: the default branch, or None if it failed
"""
# https://stackoverflow.com/questions/28666357/git-how-to-get... | c18e20cdd5d861dc324296761c71bb5d4416e471 | 59,652 |
import re
def oerp_get_ids_from_order(po_id, oerp):
"""
Fetches the product IDs of a purchase order
:param po_id: The openERP purchase order ID
:param oerp: the openERP lib instance
:return: an array containing the openERP product IDs of a purchase
"""
po_id = int(po_id.lower().replace("po... | 88b87ed35317818f7d3bc3d693cd025385734756 | 59,653 |
def form_update_node(user, handle_id, form, property_keys=None):
"""
Take a node, a form and the property keys that should be used to fill the
node if the property keys are omitted the form.base_fields will be used.
Returns True if all non-empty properties where added.
"""
meta_fields = ['relati... | 1f1d33cd18bc6f1f186114f038065fe0518a93ca | 59,654 |
import zlib
def decompress_zip(data, # type: bytes
shape, # type: Tuple[int, int]
depth, # type: int
version # type: int
): # type: (...) -> np.ndarray
"""
Decompress zip (zlib) encoded data.
{}
"""
data = zlib.... | 3cd7d24287a8c6991de4997d83108b16251c0491 | 59,655 |
def add_user_key(request, **kwargs):
"""
Create a new User API key.
Requires a name and a readonly boolean.
"""
user = request.user
name = request.POST.get("name")
readonly = convert_to_bool(request.POST.get("readonly"))
api_key, key = UserAPIKey.objects.create_key(
name=name,... | 500512fa5f336f5d6f0aae44312ab1621005bd57 | 59,656 |
def find_neighbors_for_1D(cog, target_res, max_codon_dist=3):
"""
Overloaded version of find neighbors 1D
that allows us to find the neighbors
of only the residues we want
Parameters:
-----------
cog : dictionary
dictionary of residue ids and their
centers of geomeetry
m... | 69cf517735ca18c2f442e457ad7d59f0a33db768 | 59,657 |
def batch_norm_relu(inputs, is_training):
"""Performs a batch normalization followed by a ReLU."""
_BATCH_NORM_DECAY = 0.997
_BATCH_NORM_EPSILON = 1e-5
axis = 1
# Workaround because there is currently no NCHW fused BN on CPU
if not tf.test.is_built_with_cuda():
inputs = tf.transpose(inpu... | aeca62585c5b53f50d82e087530228629252d1ef | 59,658 |
import os
import errno
def find_file_in_path(filename, search_path) :
"""General utility to search for a file name in a path
:param str filename: name of the file to locate, absolute path ignores search_path
:param list(str) search_path: list of directories where the files may be located
"""
# o... | 68d4cfc693357e9cdb8949dec66fcc121d4467ec | 59,659 |
def decode_soft_encoding_batch_rgb(x_batch, y_batch, q_ab, epsilon = 1e-8, T = 0.38, x_post_fn = None, version = 0, usegpu = False, **kwargs):
"""
q_ab = np.load(os.path.join(module_dir, "data", "pts_in_hull.npy").replace("\\", "/"))
x_batch: L channel (batchsize, height, width, 1), (height, width) --> gray... | 93a24748166047a3a9748715f46ed995975bd0a1 | 59,660 |
import torch
def word_to_one_hot(word, word2idx):
"""Return the one hot encoding of the word given to this function.
Args:
word (str): The word for which one hot representation is required.
word2idx (Dict): The dictionary mapping from word to indices.
Returns:
x (torch.Tensor): The on... | 6628f25695cacb202dd51be070ff03f9a594654d | 59,661 |
def dcopy(x):
"""
Returns a deep copy of an array.
Parameters
----------
x: array-like
The array to create a deep copy of.
Returns
-------
array-like:
The deep copy of the input.
"""
backend = getBackend(x)
if backend == 'numpy':
return x.copy()
... | 4a7cc6da52c6c3f7fc106c38524adfe3735a5806 | 59,662 |
def dhcp_offer_packet(eth_dst='00:01:02:03:04:05',
eth_src='06:07:08:09:10:11',
ip_src='0.0.0.0',
ip_dst='255.255.255.255',
ip_len=308,
ip_tos=16,
ip_ecn=None,
ip_dscp=None,
ip_ttl=128,
... | a763f6b2303624912d8fe0d91928a310be1f2b74 | 59,663 |
def save_video_categories(regionCode: str):
"""儲存該國籍的主題內容
Args:
regionCode (str): 國籍簡碼
Returns:
[bool]: 成功或報錯
"""
category = videos.get_video_category(regionCode=regionCode)
if not isinstance(category, dict):
return False
for i in category['items']:
schemas ... | 2ed1d9806727ee79a3560a7d03cc8ec0782836c1 | 59,664 |
from pathlib import Path
from typing import Type
def parse_text_level(file_path: Path) -> LevelElements:
"""Parses a level layout file into `LevelElements`.
Takes a file path to the level layout and converts the ASCII characters into
a grid of level elements (Python objects).
Args:
file_path... | c3122292474520d89426c59de9969072c824f767 | 59,665 |
from typing import Container
async def get_subscriber_subscriptions_handler(
request: web.Request, *,
subscription_service: SubscriptionService = Provide[
Container.subscription_service
],
) -> web.Response: # noqa
"""Handle subscriber subscriptions getting requests."""
ne... | 302f3e5c2f1eb397bd0305251f5b6b1bd425f140 | 59,666 |
def primary_trefoil_y(rho, phi):
"""Zernike primary trefoil Y."""
return rho**3 * e.cos(3 * phi) | f9a73da106bd4979996b609981f28a481f0b84c4 | 59,667 |
def top_5_categorical_accuracy(y, y_pred):
"""
Return the top 5 categorical accuracy of the predictions
"""
return top_n_categorical_accuracy(y, y_pred, 5) | 28b53e83e94489e903936740f815560c17e68c98 | 59,668 |
def get_to_do_filename():
"""
Asks users to enter a filename od an existing To Do file.
The user should be repeatedly prompted for a filename until a existing one is entered.
Use os.path.isfile(to_do_list_file) to check if to_do_list_file exists
:return: the existing To Do filename
"""
#... | 1aa4022315736435cfc518a1b8e15c9acb160712 | 59,669 |
async def update_item(key, value):
"""Update an existing key."""
# Query db.
result = await collection.update_one({"_id": key}, {"$set": {"value": value}})
if result.matched_count:
return result.raw_result
else:
raise HTTPException(status_code=404, detail="Item not found.") | 235e981cba897cbebc00d90b012e295e7bcbc426 | 59,670 |
import base64
def deserialize(employee_str) -> Employee:
"""
Given an base64 encoded string parse and convert to Employee object
:param employee_str: base64 encoded string
:return: Employee Object
"""
decoded = base64.b64decode(employee_str)
employee_obj = Employee()
employee_obj.Parse... | 1e516fbc5da575afe5ad9fe867f449ec3574a0fb | 59,671 |
def rev_comp(seq: str) -> str:
"""
Generates the reverse complement of a sequence.
"""
comp = {
"A": "T",
"C": "G",
"G": "C",
"T": "A",
"B": "N",
"N": "N",
"R": "N",
"M": "N",
"Y": "N",
"S": "N",
"W": "N",
"K... | cb6b95d2d3f15910ff3ad793d99bb56de898026e | 59,672 |
def strip_variables(raw_df, targ_hd):
"""
Some of the ncdf files do not have a <complete> collection of variables
(e.g. Rnet, Qg), such that the matrices are different shapes. In order
to be able to concatenate all fluxnet datasets together, this function
strips out the uncommon variables.
"""
... | b732faf83d5946807c6e74b13297e52ced18ff1d | 59,673 |
def check_unique(ser : pd.Series) -> any:
"""Check uniquness. If duplicated, raise Error.
"""
l = ser.unique()
if len(l) != 1:
raise Exception("Duplication found", l)
return(l[0]) | 7f5c5bef6447812f02cb0dd4c7ed6f44b37c12a6 | 59,674 |
import getpass
def mm_connect():
"""
Connects to a FTP-Server using the Info given in the param file
USRN and PSWD can be None to interactively get the Info.
THIS IS NOT SECURE and should be replaced with SFTP in the next Versions
"""
""" monkeypatch https://stackoverflow.com/questions/440577... | 13b03ba5ad4ad1a0e9681604ac9202bd4b6096ff | 59,675 |
import ctypes
def platformDisplay(device):
"""Get platform display from device specifier
device -- EGLDeviceEXT, gbm card* path, or gbm card* ordinal (index)
returns display, created_device (or None if passed in)
raises RuntimeError if we can't create the display
"""
created_device = dis... | 2f7e807d6ef844d76c2d10fbbccb21d54007b5b6 | 59,676 |
def _parse_dsn(dsn_text,defaults):
"""
Convert a DSN MIME part to a dictionnary keyed by DSN fields
"""
res = []
for sub in dsn_text.split("\n"):
if ':' in sub:
res.append(map(str.strip, sub.split(':', 1)))
res = dict(res)
for d in defaults.keys():
if not d in re... | 6637acda9c66085fce9af8eca63cbe7ad8e1a989 | 59,677 |
def find_nuc_indel(gapped_seq, indel_seq):
"""
This function finds the entire indel missing in from a gapped sequence
compared to the indel_seqeunce. It is assumes that the sequences start
with the first position of the gap.
"""
ref_indel = indel_seq[0]
for j in range(1,len(gapped_seq)):
... | d1f258229300f965d9e6d0a8fba0a7cb6a071131 | 59,678 |
def expected_dice_game ():
"""Function that generates expected accumulative of dice roles in accordance to probability theory."""
def evaluateSides (list):
"""Function that generates a list of numbers that occur on each side of a normal dice"""
# initiate loop mechani... | 2c224b4d4f7ee96a643eb65f605094c1f07663c1 | 59,679 |
def data_scientists_who_like(target_interest):
"""Find the ids of all users who like the target interest."""
return [user_id
for user_id, user_interest in interests
if user_interest == target_interest] | 89a2473037d1ef30830b5383d4c39b52953e70ae | 59,680 |
from io import StringIO
import traceback
def serialize_known_exception(e):
"""
Serialize a cloudify exception into a dict
:param e: A cloudify exception
:return: A JSON serializable payload dict
"""
tb = StringIO.StringIO()
traceback.print_exc(file=tb)
trace_out = tb.getvalue()
# ... | e0c24480373d4d4d2be99f8cd4b2b8193a1f5120 | 59,681 |
def users():
""" Convert PostHistory.xml to pandas dataframe """
parsed_xml = et.parse("../../data/raw/Users.xml")
dfcols = ['Id','AccountId','CreationDate', 'Reputation','Views','UpVotes','DownVotes','LastAccessDate']
df_xml = pd.DataFrame(columns=dfcols)
i=0
for node in parsed_xml.getroot():
... | edd3e2831e9fe2286fa74fd448f10fc0c059a901 | 59,682 |
import os
def get_sample_writer(name, base=".."):
"""Returns a tensorboard summary writer
"""
return SummaryWriter(log_dir=os.path.join(base, SUMMARY_WRITER_DIR_NAME, name)) | 19edabf3d40ed61fa66edd656e85400bfa8145bd | 59,683 |
def echo_an(ma, ga, Lpk, dist, t_age, gamma, tpk, tt, deltaE_over_E=ct._deltaE_over_E_):
"""
Analytic formula for the echo spectral irradiance [Jy], with transition time as input, and assuming constant DM density. NOTE: the frequency dependence prefactor, usually (nu/nu_pivot)^-alpha, is factorized out.
Pa... | fa17ef6b9d3a51b4e5a9fbf896acd29d4a76df98 | 59,684 |
def log_out(request):
"""Log out page. Roure for 'logout'."""
logout(request)
messages.info(request, "Logged out")
return redirect("login") | 990c42a9b5de6a8c720f4d58d7c62ebc22a66af4 | 59,685 |
def _match_identifier_re():
"""
匹配BundleId
"""
return r'^Identifier:\s*([a-zA-Z0-9_\-\.]+)\s*$' | cbca0e2924e77c43211bdadba4d434c178eb8e18 | 59,686 |
from typing import Any
from typing import Tuple
from typing import Iterator
def create_generators(
df: pd.DataFrame, train: pd.DataFrame, val: pd.DataFrame, test: pd.DataFrame, plot_augmentations: Any
) -> Tuple[Iterator, Iterator, Iterator]:
"""Accepts four Pandas DataFrames: all your data, the training, val... | ae4619ebf9efad29dcadca56e342824320f31713 | 59,687 |
def get_stats_for_unweighted_hpo_aggregate_metric(
hpo_object, metric, date, hpo_name,
tables_and_classes_counted, statistics_to_average):
"""
Function is used once an HPO is found and warrants its own
AggregateMetricForHPO because it has a unique set of date
and metric parameters.
... | 2b451f6fc15b9f96e343d5577626a62fd57662b7 | 59,688 |
def part2(commands):
"""
down X increases your aim by X units.
up X decreases your aim by X units.
forward X does two things:
It increases your horizontal position by X units.
It increases your depth by your aim multiplied by X.
Calculate the horizontal position and depth you would ... | 68664bc4fc708f67d4cbce121f16f273aeeffd86 | 59,689 |
def cantor_pairing(a, b):
"""Create an unique number from two natural numbers
For more information about the Cantor pairing function, have a look at:
https://en.wikipedia.org/wiki/Pairing_function
This create an unique number from two natural numbers according to
.. math::
\pi (a,b):={\frac{... | d8849a7c7a8497393e77f2b93e3555a09f704bf3 | 59,690 |
import functools
def class_from_constructor(cls, func, **kwargs):
"""Creates a new class by extending the given one and using func as a
constructor of the new class.
Keyword arguments are passed to a metaclass."""
# For unknown reasons __doc__ attribute of type objects is
# read-only, and update... | 3159ff9387f2b5f7dc32ef8dc969a2266b46dd14 | 59,691 |
import os
def file_writer_method (method):
"""Decorator for simplifying writing of files.
Enables the given method to handle both filenames and file objects.
The given method must take a file object as its second argument
(the first argument being 'self', of course). This decorator will
take a ... | 947706cc61ab0386529cf6d2f39592dbec34119f | 59,692 |
def codeblock(text):
"""
Returns text in a Markdown-style code block
:param text: Str
:return: Str
"""
return "```\n" + text + "\n```" | fb8fd7314273b47ace577a72c705742d6646aa0d | 59,693 |
def get_Rx(theta):
"""Define matrix for rotation (roll) about x axis."""
Rx = matrix([[1, 0, 0],
[0, cos(theta), -sin(theta)],
[0, sin(theta), cos(theta)]])
return Rx | 3ce94a9e7472deaaaccd44ead970fa14c31e1f26 | 59,694 |
def max(x: Tensor, axis: int = None) -> Tensor:
"""Returns the maximum value of the input tensor."""
output = Tensor(np.max(x.data, axis=axis), requires_grad=x.requires_grad)
def backward_fn():
if x.requires_grad:
local_gradient = output.grad.data * (x.data == output.data)
... | 14e91fbc5bf8bb539fcc28c6b5ae0760da9cf395 | 59,695 |
from authlib.integrations.requests_client import OAuth2Session
def set_oauth_cb(config):
"""Implement client support for KIP-768 OpenID Connect.
Apache Kafka 3.1.0 supports authentication using OpenID Client Credentials.
Native support for Python is coming in the next release of librdkafka
(version 1... | b4ee2f6574e81fcf19f662697580531655407594 | 59,696 |
def calculate_frechet_distance(mu1, sigma1, mu2, sigma2, eps=1e-6):
"""Numpy implementation of the Frechet Distance.
The Frechet distance between two multivariate Gaussians X_1 ~ N(mu_1, C_1)
and X_2 ~ N(mu_2, C_2) is
d^2 = ||mu_1 - mu_2||^2 + Tr(C_1 + C_2 - 2*sqrt(C_1*C_2)).
Stable version ... | 6ca6e8be17607427c02fa3bc82667a730a7db1fc | 59,697 |
def findDeviceID():
""" This method finds all devices available to play on a spotify account and returns the device to be used for playback. It always returns the ID of the Amazon Echo unless it is unavailable.
Returns:
deviceID(String): Returns the id of the Amazon Echo if it is available or the next... | 1bf9b8e510e697e0ae19f4834c1536d02a40960a | 59,698 |
def init_patched_conic(x,
rf = 1837400.0,
r0 = 6371000.0 + 185000.0,
phi0 = 0.0,
D = 384402000.0,
V = 2.649e-6 * 384402000.0):
"""Generic objective function. x is [lam1, v0]."""
lam1 ... | f1c6ab98114155f44ccc86effd7503cfebffb8fa | 59,699 |
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