content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def mahalanobis(data, produce=None):
"""
Calculate mahalanobis distance on a matrix of column vectors.
Assumes that rows are observations and columns are features.
Parameters
----------
data : numpy array or pandas dataframe
The data to calculate distances on (columns are variables... | b6dff6cfe12b4c44b6a97a6bd1f51a2250b7b63f | 3,647,000 |
def text(el):
"""
Helper to get the text content of a BeautifulSoup item
"""
return el.get_text().strip() | 7b34c77c79677a73cc66532fe6305635b1bdac43 | 3,647,001 |
def collect_DAC_pow(dig, IF_freq):
"""TODO: Desciption what I, the function, do"""
return external_ATS9870_CS_VNA.collect_amp(dig, IF_freq) | 42f649520b950357419c6c26d3d5426849855929 | 3,647,002 |
def get_sha512_manifest(zfile):
"""
Get MANIFEST.MF from a bar file.
:param zfile: Open (!!!) ZipFile instance.
:type zfile: zipfile.ZipFile
"""
names = zfile.namelist()
manifest = None
for name in names:
if name.endswith("MANIFEST.MF"):
manifest = name
b... | 7ef150bb3e89f8723649ee983085a413ec8a31df | 3,647,003 |
def plot_heatmap(filename, xdata, ydata, binx, biny, title = None, xlabel = None, ylabel = None, dpi = 150, figsize = (10,10), tfont = 17, lfont = 14):
"""
Present variables as a 2D heatmap
to correlate magnitude and direction.
"""
def get_bin_id(mybins, vv):
for ibin in range(len(mybins)-1)... | 3397bf2fc02932056411ef8addde264fa50b9ea5 | 3,647,004 |
def cmake_var_string(cmake_vars):
"""Converts a dictionary to an input suitable for expand_cmake_vars.
Ideally we would jist stringify in the expand_cmake_vars() rule, but select()
interacts badly with genrules.
TODO(phawkins): replace the genrule() with native rule and delete this rule.
Args:
cmake_va... | 3f0fb115c54f6ee1e0e923b67412e36ca56b2ea7 | 3,647,005 |
def scattering_transform1d(n_classes, sequence_length):
""" Scattering transform
"""
log_eps = 1e-6
x_in = layers.Input(shape=(sequence_length))
x = Scattering1D(8, 12)(x_in)
x = layers.Lambda(lambda x: x[..., 1:, :])(x)
x = layers.Lambda(lambda x: tf.math.log(tf.abs(x) + log_eps))(x)
x = layers.GlobalAveragePo... | 53547918c5a0efa5c0e3766c770903b146eff19e | 3,647,006 |
import zlib
def addFileContent(session, filepath, source_file_name, content_hash,
encoding):
"""
Add the necessary file contents. If the file is already stored in the
database then its ID returns. If content_hash in None then this function
calculates the content hash. Or if is avail... | fdd77f23151ed9627c5d9bbfb157839810c9655a | 3,647,007 |
def model_fn_builder(num_labels, learning_rate, num_train_steps,
num_warmup_steps):
"""Returns `model_fn` closure for TPUEstimator."""
def model_fn(features, labels, mode, params): # pylint: disable=unused-argument
"""The `model_fn` for TPUEstimator."""
input_ids = featur... | 570f5297fbcc57eaae1d08e9ee816207db707ffd | 3,647,008 |
def to_numeric_df(kdf):
"""
Takes a dataframe and turns it into a dataframe containing a single numerical
vector of doubles. This dataframe has a single field called '_1'.
TODO: index is not preserved currently
:param df:
:return: a pair of dataframe, list of strings (the name of the columns
... | 5eba4585ca55360bfff959b4f46580cc747e3f93 | 3,647,009 |
def FancyAnalyzer(expression=r"\s+", stoplist=STOP_WORDS, minsize=2,
maxsize=None, gaps=True, splitwords=True, splitnums=True,
mergewords=False, mergenums=False):
"""Composes a RegexTokenizer with an IntraWordFilter, LowercaseFilter, and
StopFilter.
>>> ana = FancyAn... | 50fddbbdc22770b3a9b732bb328bf48c0407aafe | 3,647,010 |
def find_res_shift(x_min, x_max, y_min, y_max, z_min, z_max, target_id, my_sites, res_two_three_dict, my_mols, color_list, button_list):
"""Function to find the relavant residue shifts"""
print "FINDING MAX SHIFTS"
max_shift = []
# Get the delta value
delta = 5.0
# Filter residues to the ones wi... | d46a146071f5cd48ab1382d03ac4678cc2c301fd | 3,647,011 |
def lookup(*getters):
"""Find data by provided parameters and group by type respectively"""
getters = list(reversed(getters))
def wrap(struct):
while getters:
_type, getter = getters.pop()
if _type == G_TYPE_KEY:
struct = getter(struct)
contin... | 937a44e8366016cb136f0b40a91448b97c52357d | 3,647,012 |
def compute_one(t, lhs, rhs, **kwargs):
""" Join two pandas data frames on arbitrary columns
The approach taken here could probably be improved.
To join on two columns we force each column to be the index of the
dataframe, perform the join, and then reset the index back to the left
side's original... | c050fdeae2e354be3748984a32ad96b81593355b | 3,647,013 |
def simulate(mat, det, e0=20.0, dose=defaultDose, withPoisson=True, nTraj=defaultNumTraj, sf=defaultCharFluor, bf=defaultBremFluor, xtraParams=defaultXtraParams):
"""simulate(mat,det,[e0=20.0],[withPoisson=True],[nTraj=defaultNumTraj],[dose=defaultDose],[sf=defaultCharFluor],[bf=defaultBremFluor],[xtraParams=defaul... | 5ffdf63038fa2ba4305001f1b1ec5da0c13ebf3d | 3,647,014 |
def link_match_family(link, family_name):
"""Checks whether the a link can be used in a given family.
When this function is used with built-in family names, it tests whether the link name can be
used with the given built-in family. If the family name is not known, we return True because
the user is wor... | 7d95556b5ff6537bc994d7b017263ced13d4efc0 | 3,647,015 |
import tqdm
def auc(test_set, user_factors, subreddit_factors, subreddits, users):
"""
Returns the auc score on a test data set
"""
num_users = len(test_set)
total = 0
# treat the signal as 1 as per the implicit bpr paper
for subreddit, user, signal in tqdm.tqdm_notebook(test_set... | 93179ede0fb84e7f491f147d1a356036d2908a2f | 3,647,016 |
def convert_AST_to_expr(ast):
"""Creates expression from the AST."""
converter = ASTToInstrBlockConverter()
instrs = converter.my_visit(ast)
return instrs[0] | b4dca77c48cd0001a2f55c71a077a6b195a181ce | 3,647,017 |
import time
def add_data_from_api(service, repo, variable_type, keys):
"""Retrieves Github API data. Utilizes the function from github_api/github.py to do so.
This function adds the retrieved variables directly to the data dictionary.
Args:
service (Service): Service object with API connection an... | 32361d85fb92efd03b79f74f8db2e02a8fcd9866 | 3,647,018 |
def part1(data):
"""
>>> part1(read_input())
0
"""
return data | 1482c41b112a3e74775e71c4aabbd588de2b6553 | 3,647,019 |
import torch
def get_rectanguloid_mask(y, fat=1):
"""Get a rectanguloid mask of the data"""
M = y.nonzero().max(0)[0].tolist()
m = y.nonzero().min(0)[0].tolist()
M = [min(M[i] + fat, y.shape[i] - 1) for i in range(3)]
m = [max(v - fat, 0) for v in m]
mask = torch.zeros_like(y)
mask[m[0] : ... | 0ff3ab25f2ab109eb533c7e4fafd724718dbb986 | 3,647,020 |
import re
def colorize_output(output):
"""Add HTML colors to the output."""
# Task status
color_output = re.sub(r'(ok: [-\w\d\[\]]+)',
r'<font color="green">\g<1></font>',
output)
color_output = re.sub(r'(changed: [-\w\d\[\]]+)',
r'<font... | 80759da16262d850b45278faede4b60b7aa4a7c6 | 3,647,021 |
import argparse
def parse_args():
"""Parse command-line arguments"""
parser = argparse.ArgumentParser(
description='Stop a subjective evaluation without ' +
'destroying resources')
parser.add_argument('--aws_api_key', help='The public API key for AWS')
parser.add_argument(
... | 661a9bdec94b88c06f6d4080ef20cc31f81901ff | 3,647,022 |
def parse_user_date(usr_date: str) -> date:
"""
Parses a user's date input, prompts the user to input useful date data if user's date was
invalid
Args:
usr_date : str, user input of date info. Should be in <yyyy/mm/dd> format
Returns:
valid datetime.date() object
"""
expected_len = len("yyyy/mm/dd")
if usr... | 10becdce6ef4fdc5606ce110b09e102c186dfc04 | 3,647,023 |
def up_sampling_block(x, n_filter, kernel_size, name,
activation='relu', up_size=(2, 2)):
"""Xception block
x => sepconv block -> sepconv block -> sepconv block-> add(Act(x)) =>
"""
x = layers.UpSampling2D(size=up_size, name=name+'up')(x)
if activation:
x = layers.Activ... | 001fdb6475da138bedfdb891af6e657e5ce6160c | 3,647,024 |
def connected_components(graph):
"""
Connected components.
@attention: Indentification of connected components is meaningful only for non-directed graphs.
@type graph: graph
@param graph: Graph.
@rtype: dictionary
@return: Pairing that associates each node to its connected component.
... | 80c5bfc679c1dc274db6a3bf8f8becfa1fc99d4f | 3,647,025 |
import typing
def format_keyvals(
entries: typing.Iterable[typing.Tuple[str, typing.Union[None, str, urwid.Widget]]],
key_format: str = "key",
value_format: str = "text",
indent: int = 0
) -> typing.List[urwid.Columns]:
"""
Format a list of (key, value) tuples.
Args:
... | eb1769a3d7b47b6b4f24f02dcffd3639592c8dc6 | 3,647,026 |
def get_item_workdays(scorecard):
""" Gets the number of days in this period"""
supplier = frappe.get_doc('Supplier', scorecard.supplier)
total_item_days = frappe.db.sql("""
SELECT
SUM(DATEDIFF( %(end_date)s, po_item.schedule_date) * (po_item.qty))
FROM
`tabPurchase Order Item` po_item,
`tabPurchas... | cec620114ae784e5c272d41b6e1028175b466691 | 3,647,027 |
def load_data(ticker='SNAP', barSizeSetting='3 mins', what='TRADES'):
"""
loads historical tick data
"""
if what == 'TRADES':
folder = '/home/nate/Dropbox/data/ib_full_adj/data/'
elif what == 'ADJUSTED_LAST':
folder = '/home/nate/Dropbox/data/ib_split_adj_only/data/'
bss = barSi... | 8ad01227131322f7780e75e1e72f89b1da3fef0b | 3,647,028 |
def time_human(x):
""" Gets time as human readable """
# Round time
x = round(x, 2)
for number, unit in [(60, "s"), (60, "min"), (24, "h"), (365, "days")]:
if abs(x) < number:
return f"{x:.2f} {unit}"
x /= number
return f"{x:.2f} years" | 3f7f51ac7454e429fc30da64eed075aaf1f10b5b | 3,647,029 |
from typing import Dict
def transaction_json_to_binary_codec_form(
dictionary: Dict[str, XRPL_VALUE_TYPE]
) -> Dict[str, XRPL_VALUE_TYPE]:
"""
Returns a new dictionary in which the keys have been formatted as CamelCase and
standardized to be serialized by the binary codec.
Args:
dictionar... | 94516b8418fc25d1966d6f5c969f9b4e411100ab | 3,647,030 |
def conv3x3(in_planes, out_planes, stride=1, groups=1):
"""3x3 convolution with padding"""
return nn.Conv1d(in_planes, out_planes, kernel_size=7, stride=stride,
padding=3, bias=False, groups=groups) | 90fa7549a2ba8722edab3712bac4d3af7fb5f2f2 | 3,647,031 |
def limit_sub_bbox(bbox, sub_bbox):
"""
>>> limit_sub_bbox((0, 1, 10, 11), (-1, -1, 9, 8))
(0, 1, 9, 8)
>>> limit_sub_bbox((0, 0, 10, 10), (5, 2, 18, 18))
(5, 2, 10, 10)
"""
minx = max(bbox[0], sub_bbox[0])
miny = max(bbox[1], sub_bbox[1])
maxx = min(bbox[2], sub_bbox[2])
maxy = ... | fa5b7763b30442fba137814ac7b0336528c4540b | 3,647,032 |
def _load_taxa_incorp_list(inFile, config):
"""Loading list of taxa that incorporate isotope.
Parameters
----------
inFile : str
File name of taxon list
config : config object
Returns
-------
{library:[taxon1, ...]}
"""
taxa = {}
with open(inFile, 'rb') as inFH:
... | d614f2be0c5ad4fa61d1d70915428324d7af97b4 | 3,647,033 |
def get_subsections(config: Config) -> t.List[t.Tuple[str, t.Dict]]:
"""Collect parameter subsections from main configuration.
If the `parameters` section contains subsections (e.g. '[parameters.1]',
'[parameters.2]'), collect the subsection key-value pairs. Otherwise,
return an empty dictionary (i.e. ... | 0cb022fb6ae192736186a519c6ffbcf9bcfdf541 | 3,647,034 |
def calc_psi(B, rev=False):
"""Calc Flux function (only valid in 2d)
Parameters:
B (VectorField): magnetic field, should only have two
spatial dimensions so we can infer the symmetry dimension
rev (bool): since this integration doesn't like going
through undefined region... | 80beea86346fadd7e96b82c1da6eba56bde597fd | 3,647,035 |
def infer_printed_type(t):
"""Infer the types that should be printed.
The algorithm is as follows:
1. Replace all constant types with None.
2. Apply type-inference on the resulting type.
3. For the first internal type variable that appears, find a constant
whose type contains that variab... | 1ad880fc92db2e64ba6ea81f7481efa99b0bd044 | 3,647,036 |
def bias_variable(shape):
"""
返回指定形状的偏置量
:param shape:
:return:
"""
b = tf.Variable(tf.constant(0.0, shape=shape))
return b | ff2bb945414508d1dfc1db0b028cf1feeebeb6d8 | 3,647,037 |
def drag_eqn(times,g,r):
"""define scenario and integrate"""
param = np.array([ g, r])
hinit = np.array([0.0,0.0]) # initial values (position and velocity, respectively)
h = odeint(deriv, hinit, times, args = (param,))
return h[:,0], h[:,1] | d79150dd894244c11fa882d62da2f33b1173c144 | 3,647,038 |
def virtual_potential_temperature_monc(theta, thref, q_v, q_cl):
"""
Virtual potential temperature.
Derived variable name: th_v_monc
Approximate form as in MONC
Parameters
----------
theta : numpy array or xarray DataArray
Potential Temperature. (K)
thref : numpy array or xarr... | d4c3da0a5f4f2826edce53f610f8ba384845ebb2 | 3,647,039 |
def promote_user(username):
"""Give admin privileges from a normal user."""
user = annotator.credentials.find_one({'username': username})
if user:
if user['admin']:
flash("User {0} is already an administrator".format(username), 'warning')
else:
annotator.credentials.u... | 6a938c341f152991741d35dfd1c693743c07f805 | 3,647,040 |
def slide_number_from_xml_file(filename):
"""
Integer slide number from filename
Assumes /path/to/Slidefile/somekindofSlide36.something
"""
return int(filename[filename.rfind("Slide") + 5:filename.rfind(".")]) | dcfbc322b30a39041ab15b8496f097a5a5329865 | 3,647,041 |
import io
def massivescan(websites):
"""scan multiple websites / urls"""
# scan each website one by one
vulnerables = []
for website in websites:
io.stdout("scanning {}".format(website))
if scanner.scan(website):
io.stdout("SQL injection vulnerability found")
v... | b2be56bf07d00c8839813d66acd337c75b9823ef | 3,647,042 |
import re
def is_strong_pass(password):
"""
Verify the strength of 'password'
Returns a dict indicating the wrong criteria
A password is considered strong if:
8 characters length or more
1 digit or more
1 symbol or more
1 uppercase letter or more
1 lowercase let... | bfd1832951ba3059d8c542fa0b9d708a2416a4d4 | 3,647,043 |
def plot_config(config, settings=None):
"""
plot_config: obj -> obj
---------------------------------------------------------------
Sets the defaults for a custom experiment plot configuration object
from configobj.
The defaults are only set if the setting does not exist (t... | 3b17e97c68bcec31856cb0dc4d7f3db4280a748f | 3,647,044 |
import os
def load_spectrogram(spectrogram_path):
"""Load a cante100 dataset spectrogram file.
Args:
spectrogram_path (str): path to audio file
Returns:
np.array: spectrogram
"""
if not os.path.exists(spectrogram_path):
raise IOError("spectrogram_path {} does not exist".... | 34c0db598558886ee48518a464dc90242b82d2f8 | 3,647,045 |
def evaluate_fN(model, NHI):
""" Evaluate an f(N,X) model at a set of NHI values
Parameters
----------
NHI : array
log NHI values
Returns
-------
log_fN : array
f(NHI,X) values
"""
# Evaluate without z dependence
log_fNX = model.__call__(NHI)
return log_fNX | e952a29fdf5864b26dc534140b2ccfb0b59fe24b | 3,647,046 |
def generate_volume_data(img_data):
"""
Generate volume data from img_data.
:param img_data: A NIfTI.get_data object, img_data[:][x][y][z] is the tensor matrix information of voxel (x,y,z)img_data:
:return: vtkImageData object which stores volume render object.
"""
dims = [148, 190, 160] # siz... | b726d1484944a3f827cae836ca30cf8c7e81d493 | 3,647,047 |
def pipe(bill_texts_df):
"""
soup = bs(text, 'html.parser')
raw_text = extractRawText(soup)
clean_text = cleanRawText(raw_text)
metadata = extract_metadata(soup)
"""
bill_texts_df['soup'] = \
bill_texts_df['html'].apply(lambda x: bs(x, 'html.parser'))
bill_texts_df[... | 73a8a850fa15f8ad33f9f823f9b2b4d6f808826b | 3,647,048 |
def _as_static(data, fs):
"""Get data into the Pyglet audio format."""
fs = int(fs)
if data.ndim not in (1, 2):
raise ValueError('Data must have one or two dimensions')
n_ch = data.shape[0] if data.ndim == 2 else 1
audio_format = AudioFormat(channels=n_ch, sample_size=16,
... | b76d4c49107f8b9679e975bd2ce114314289d181 | 3,647,049 |
def preprocess_data(cubes, time_slice: dict = None):
"""Regrid the data to the first cube and optional time-slicing."""
# Increase TEST_REVISION anytime you make changes to this function.
if time_slice:
cubes = [extract_time(cube, **time_slice) for cube in cubes]
first_cube = cubes[0]
# re... | 82e851bda39a4ab7716c7b9cd6038743961d9faf | 3,647,050 |
import base64
def password_to_str(password):
"""
加密
:param password:
:return:
"""
def add_to_16(password):
while len(password) % 16 != 0:
password += '\0'
return str.encode(password) # 返回bytes
key = 'saierwangluo' # 密钥
aes = AES.new(add_to_16(key), AES.M... | 60a6d361d6de3c41d2a27cd24312006920ad1013 | 3,647,051 |
from src.Emails.checker.mailru import checker
import re
import requests
def email_checker_mailru(request: Request, email: str):
"""
This API check email from mail.ru<br>
<pre>
:return: JSON<br>
</pre>
Example:<br>
<br>
<code>
https://server1.majhcc.xyz/api/email/checker/mailru?emai... | 2835439d3c7781efa0c244c881f42a404a8d3cad | 3,647,052 |
from typing import Callable
def guild_only() -> Callable:
"""A :func:`.check` that indicates this command must only be used in a
guild context only. Basically, no private messages are allowed when
using the command.
This check raises a special exception, :exc:`.NoPrivateMessage`
that is inherited... | 40307b2a8672180b2a3532380f11b2701bcf0dd8 | 3,647,053 |
from typing import Union
from typing import List
from typing import Callable
from typing import Any
from typing import Sequence
def make_lvis_metrics(
save_folder=None,
filename_prefix="model_output",
iou_types: Union[str, List[str]] = "bbox",
summarize_to_stdout: bool = True,
evaluator_factory: C... | cbb3df8d8e9daa7976a7be7d6c0588e943aecd5e | 3,647,054 |
def _calculate_cos_loop(graph, threebody_cutoff=4.0):
"""
Calculate the cosine theta of triplets using loops
Args:
graph: List
Returns: a list of cosine theta values
"""
pair_vector = get_pair_vector_from_graph(graph)
_, _, n_sites = tf.unique_with_counts(graph[Index.BOND_ATOM_INDICE... | 3a3283a67c743b2bb7f7a9627e6847dcfc286276 | 3,647,055 |
def load_plugin():
""" Returns plugin available in this module
"""
return HostTestPluginCopyMethod_Firefox() | 26df11d662b3d4f98a294df9c61841c1ab76e8fc | 3,647,056 |
import logging
def temp_url_page(rid):
"""
Temporary page where receipts are stored. The user, which visits it first, get the receipt.
:param rid: (str) receipt id (user is assigned to receipt with this id)
"""
if not user_handler.assign_rid_user(rid, flask.session['username']):
logging.w... | e5ebfe4602e427b4d96cdf1c0298057a5b472052 | 3,647,057 |
def extract_dependencies(content):
"""
Extract the dependencies from the CMake code.
The `find_package()` and `pkg_check_modules` calls must be on a single line
and the first argument must be a literal string for this function to be
able to extract the dependency name.
:param str content: The ... | d9f114695cb3622f4a8dbc23db3a97ed53b164ad | 3,647,058 |
def _block(x, out_channels, name, conv=conv2d, kernel=(3, 3), strides=(2, 2), dilations=(1, 1), update_collection=None,
act=tf.nn.leaky_relu, pooling='avg', padding='SAME', batch_norm=False):
"""Builds the residual blocks used in the discriminator in GAN.
Args:
x: The 4D input vector.
ou... | 21851730e1326b85023d88661da13020c37aa723 | 3,647,059 |
def createLaplaceGaussianKernel(sigma, size):
"""构建高斯拉普拉斯卷积核
Args:
sigma ([float]): 高斯函数的标准差
size ([tuple]): 高斯核的大小，奇数
Returns:
[ndarray]: 高斯拉普拉斯卷积核
"""
H, W = size
r, c = np.mgrid[0:H:1, 0:W:1]
r = r - (H - 1) / 2
c = c - (W - 1) / 2
sigma2 = pow(sigma, 2.... | aae788ba324a243691391a61b02e6a5f1b358c4e | 3,647,060 |
import os
def is_file_type(fpath, filename, ext_list):
"""Returns true if file is valid, not hidden, and has extension of given type"""
file_parts = filename.split('.')
# invalid file
if not os.path.isfile(os.path.join(fpath, filename)):
return False
# hidden file
elif filename.startswith('.'):
... | 52213f023313e4edb5628fcebf47cb94bc2cfcbe | 3,647,061 |
def xp_rirgen2(room, source_loc, mic_loc, c=340, fs=16000, t60=0.5,
beta=None, nsamples=None, htw=None, hpfilt=True, method=1):
"""Generates room impulse responses corresponding to each source-microphone pair placed in a room.
Args:
room (numpy/cupy array) = room dimensions in meters, sha... | 2528cf725df14febb20c5634fbe9acbeadfd5a46 | 3,647,062 |
import warnings
def mean_bias_removal(hindcast, alignment, cross_validate=True, **metric_kwargs):
"""Calc and remove bias from py:class:`~climpred.classes.HindcastEnsemble`.
Args:
hindcast (HindcastEnsemble): hindcast.
alignment (str): which inits or verification times should be aligned?
... | 01155462155d9f718fa2a12053297903d47b6661 | 3,647,063 |
import requests
def request_sudoku_valid(sudoku: str) -> bool:
"""valid request"""
is_valid = False
provider_request = requests.get(f"{base_url}/valid/{sudoku}")
if provider_request.status_code == 200:
request_data = provider_request.json()
is_valid = request_data["result"]
# TODO:... | 274a6f3e617273d1a1d81777788865337d4d36ae | 3,647,064 |
def index():
"""
vista principal
"""
return "<i>API RestFull PARCES Version 0.1</i>" | 8b8b963f75395df665bcf0283528c9641b3ea20e | 3,647,065 |
def tag(dicts, key, value):
"""Adds the key value to each dict in the sequence"""
for d in dicts:
d[key] = value
return dicts | ffcfda13845fb8b522e50211184104a11da50398 | 3,647,066 |
def openpairshelf(filename, flag='c', protocol=None, writeback=False):
"""Returns a ProteinPairDB object, with similar functionality to shelve.open()"""
return ProteinPairDB(filename, flag, protocol, writeback) | 886a474aa67f729461995fe5427d5f68b9db9fe0 | 3,647,067 |
def createUser(emailid, password, contact_no, firstname, lastname, category, address, description, company_url, image_url, con=None, cur=None, db=None):
"""
Tries to create a new user with the given data.
Returns:
- dict: dict object containing all user data, if query was successfull
- Fals... | 05dc71db991e126d43fd9ddd044f1cf65f3e97c1 | 3,647,068 |
import pathlib
import subprocess
import json
import re
def sensor_pull_storage(appname, accesskey, timestring, *,data_folder = None, ttn_version=3):
"""
Pull data from TTN via the TTN storage API.
appname is the name of the TTN app
accesskey is the full accesskey from ttn. For TTN V3, this is is the
secret t... | 704a039d23443d4ec45968596ec948237e9a2c29 | 3,647,069 |
async def discordView(cls:"PhaazebotWeb", WebRequest:ExtendedRequest) -> Response:
"""
Default url: /discord/view/{guild_id:\d+}
"""
PhaazeDiscord:"PhaazebotDiscord" = cls.BASE.Discord
if not PhaazeDiscord:
return await cls.Tree.errors.notAllowed(cls, WebRequest, msg="Discord module is not active")
guild_id:st... | 76f222bdd5164c23c95803d47fc1af48d89192e2 | 3,647,070 |
def update_max_braking_decel(vehicle, mbd):
"""
Updates the max braking decel of the vehicle
:param vehicle: vehicle
:param mbd: new max braking decel
:type vehicle: VehicleProfile
:return: Updated vehicle
"""
return vehicle.update_max_braking_decel(mbd) | dea3bf14ca14363246539fd81cf853cd2c0ad980 | 3,647,071 |
from scipy.spatial.distance import pdist, squareform
def get_outlier_removal_mask(xcoords, ycoords, nth_neighbor=10, quantile=.9):
"""
Parameters
----------
xcoords :
ycoords :
nth_neighbor :
(Default value = 10)
quantile :
(Default value = .9)
Ret... | 8d01088401405613696ced2dbbd9c03940417f10 | 3,647,072 |
def _kp(a, b):
"""Special case Kronecker tensor product of a[i] and b[i] at each
time interval i for i = 0 .. N-1
It is specialized for the case where both a and b are shape N x m x 1
"""
if a.shape != b.shape or a.shape[-1] != 1:
raise(ValueError)
N = a.shape[0]
# take the outer pro... | b133557d88deac2d9357731d820de0522521d6f3 | 3,647,073 |
def strategy(history, alivePlayers, whoami, memory):
"""
history contains all previous rounds (key : id of player (shooter), value : id of player (target))
alivePlayers is a list of all player ids
whoami is your own id (to not kill yourself by mistake)
memory is None by default and t... | f211a0961269808d9a7b0a08758273d4a03b9136 | 3,647,074 |
def parse_fn(serialized_example: bytes) -> FeaturesType:
"""Parses and converts Tensors for this module's Features.
This casts the audio_raw_pcm16 feature to float32 and scales it into the range
[-1.0, 1.0].
Args:
serialized_example: A serialized tf.train.ExampleProto with the features
dict keys dec... | 54e841987986027dc6d4d989fe6442ceecd022b8 | 3,647,075 |
import click
def cli(ctx: click.Context) -> int:
"""
Method used to declare root CLI command through decorators.
"""
return 0 | be5016c5c38f435b8a213a6ce39b5571aee809f1 | 3,647,076 |
def parse_clock(line):
"""Parse clock information"""
search = parse(REGEX_CLOCK, line)
if search:
return int(search.group('clock'))
else:
return None | a4464c979d31bab463f949bec83da99e72af6ca6 | 3,647,077 |
import requests
def block_latest(self, **kwargs):
"""
Return the latest block available to the backends, also known as the tip of the blockchain.
https://docs.blockfrost.io/#tag/Cardano-Blocks/paths/~1blocks~1latest/get
:param return_type: Optional. "object", "json" or "pandas". Default: "object".
... | a14fc3512138c1d15b32b09bd20ea03678964437 | 3,647,078 |
def get_courses():
"""
Route to display all courses
"""
params = format_dict(request.args)
if params:
try:
result = Course.query.filter_by(**params).order_by(Course.active.desc())
except InvalidRequestError:
return { 'message': 'One or more parameter(s) does ... | 6dcdcb5df4d0010661ffe92f55522638ae51a2b8 | 3,647,079 |
def zero_adam_param_states(state: flax.optim.OptimizerState, selector: str):
"""Applies a gradient for a set of parameters.
Args:
state: a named tuple containing the state of the optimizer
selector: a path string defining which parameters to freeze.
Returns:
A tuple containing the new pa... | 8a7cb65028866e4a7f3a03b589fa1bf5798a25e0 | 3,647,080 |
import scipy
def leftFitNormal(population):
"""
Obtain mode and standard deviation from the left side of a population.
>>> pop = np.random.normal(loc=-20, scale=3, size=15000)
>>> mode, sigma = leftFitNormal(pop)
>>> -22 < mode < -18
True
>>> round(sigma)
3
>>> pop[pop > ... | 28fbd93efa893dbb31e81d9875db97370f163716 | 3,647,081 |
from bs4 import BeautifulSoup
def get_stock_market_list(corp_cls: str, include_corp_name=True) -> dict:
""" 상장 회사 dictionary 반환
Parameters
----------
corp_cls: str
Y: stock market(코스피), K: kosdaq market(코스닥), N: konex Market(코넥스)
include_corp_name: bool, optional
if True, returnin... | c8e0242e1ddfcc4f32514f131f3a9797694202c1 | 3,647,082 |
def evaluate_template(template: dict) -> dict:
"""
This function resolves the template by parsing the T2WML expressions
and replacing them by the class trees of those expressions
:param template:
:return:
"""
response = dict()
for key, value in template.items():
if key == 'qualifier':
response[key] = []
... | 596516f9dfb81170212020cfb053339ddb49b716 | 3,647,083 |
def get_CommandeProduits(path, prefix='CP_',cleaned=False):
"""
Read CSV (CommandeProduits) into Dataframe. All relevant columns are kept and renamed with prefix.
Args:
path (str): file path to CommandeProduits.csv
prefix (str): All relevant columns are renamed with prefix
Returns:
... | 18c5c7e375abcc57c2cfcbc4f2c58ecec5aecf59 | 3,647,084 |
def hist_equal(image, hist):
"""
Equalize an image based on a histogram.
Parameters
----------
image : af.Array
- A 2 D arrayfire array representing an image, or
- A multi dimensional array representing batch of images.
hist : af.Array
- Containing the histogram o... | 70aeeb1822752c2f7fb5085d761bb9b309d29335 | 3,647,085 |
def get_close_icon(x1, y1, height, width):
"""percentage = 0.1
height = -1
while height < 15 and percentage < 1.0:
height = int((y2 - y1) * percentage)
percentage += 0.1
return (x2 - height), y1, x2, (y1 + height)"""
return x1, y1, x1 + 15, y1 + 15 | 78b65cdeeb4f6b3a526fd5dd41b34f35545f1e9d | 3,647,086 |
def train_model(network, data, labels, batch_size,
epochs, validation_data=None, verbose=True, shuffle=False):
"""
Train
"""
model = network.fit(
data,
labels,
batch_size=batch_size,
epochs=epochs,
validation_data=validation_data,
shuffle=s... | a2b093aef1b607cd34dd30e8c5f126e1efb3d409 | 3,647,087 |
def taoyuan_agrichannel_irrigation_transfer_loss_rate():
"""
Real Name: TaoYuan AgriChannel Irrigation Transfer Loss Rate
Original Eqn: 0
Units: m3/m3
Limits: (None, None)
Type: constant
Subs: None
This is "no loss rate" version.
"""
return 0 | 9fd8a84ae79cbeaf8c8259da815f9322f27b253f | 3,647,088 |
def lambda_handler(event, context):
"""
Find and replace following words and outputs the result.
Oracle -> Oracle©
Google -> Google©
Microsoft -> Microsoft©
Amazon -> Amazon©
Deloitte -> Deloitte©
Example input: “We really like the new security features of Google Cloud”.
Expected ... | 66dc2914dd04a2e265ed21542bd462b61344d040 | 3,647,089 |
def update_inv(X, X_inv, i, v):
"""Computes a rank 1 update of the the inverse of a symmetrical matrix.
Given a symmerical matrix X and its inverse X^{-1}, this function computes
the inverse of Y, which is a copy of X, with the i'th row&column replaced
by given vector v.
Parameters
----------
... | c811dbf699d8f93fa2fa5b3f68c5b23cf4131e9f | 3,647,090 |
import csv
def read_barcode_lineno_map(stream):
"""Build a map of barcodes to line number from a stream
This builds a one based dictionary of barcode to line numbers.
"""
barcodes = {}
reader = csv.reader(stream, delimiter="\t")
for i, line in enumerate(reader):
barcodes[line[0]] = i ... | 545a0d02dd76e774ba0de86431113ad9f36a098e | 3,647,091 |
def match_in_candidate_innings(entry, innings, summary_innings, entities):
"""
:param entry:
:param innings: innings to be searched in
:param summary_innings: innings mentioned in the summary segment
:param entities: total entities in the segment
:return:
"""
entities_in_summary_inning =... | 3551212f79c6ecb298ec6b55aa7b68213b950394 | 3,647,092 |
from typing import Optional
from typing import Union
from typing import Callable
from typing import Any
def checkpoint(
name: Optional[str] = None,
on_error: bool = True,
cond: Union[bool, Callable[..., bool]] = False,
) -> Callable[[Callable], Any]:
"""
Create a checkpointing decorator.
Args... | 39bab1a33523c34b04a2ed7f2efd6467de63b27b | 3,647,093 |
def return_int(bit_len, unsigned=False):
"""
This function return the decorator that change return value to valid value.
The target function of decorator should return only one value
e.g. func(*args, **kargs) -> value:
"""
if bit_len not in VALID_BIT_LENGTH_OF_INT:
err = "Value of bit_le... | 66121d389a389c6152fd4491ed8a698336e042a2 | 3,647,094 |
def get_integral_curve(f, init_xy, x_end, delta):
"""
solve ode 'dy/dx=f(x,y)' with Euler method
"""
(x, y) = init_xy
xs, ys = [x], [y]
for i in np.arange(init_xy[0], x_end, delta):
y += delta*f(x, y)
x += delta
xs.append(x)
ys.append(y)
return xs, ys | 0526643acd37b8d7c2646d3a21d54e9d9f16ef58 | 3,647,095 |
def compute_atime_posteriors(sg, proposals,
global_srate=1.0,
use_ar=False,
raw_data=False,
event_idx=None):
"""
compute the bayesian cross-correlation (logodds of signal under an AR noise model... | 1029f57fe500ef6f08eec56ab34539d3f9a80637 | 3,647,096 |
def search4vowels(pharse :str) -> set:
""""Return any vowels found in a supplied word."""
vowels = set('aeiou')
return vowels.intersection(set(pharse)) | 8a45c50828b6ba8d173572ac771eb8fe5ddc5a42 | 3,647,097 |
def rsort(s):
"""Sort sequence s in ascending order.
>>> rsort([])
[]
>>> rsort([1])
[1]
>>> rsort([1, 1, 1])
[1, 1, 1]
>>> rsort([1, 2, 3])
[1, 2, 3]
>>> rsort([3, 2, 1])
[1, 2, 3]
>>> rsort([1, 2, 1])
[1, 1, 2]
>>> rsort([1,2,3, 2, 1])
[1, 1, 2, 2, 3]
... | d9f67d713e55d50cd4468ad709f04c7bfea05c71 | 3,647,098 |
import os
def xdg_data_home():
"""Base directory where user specific data files should be stored."""
value = os.getenv('XDG_DATA_HOME') or '$HOME/.local/share/'
return os.path.expandvars(value) | db4212def5e4760bbe1da762a74cf09a9ee40d78 | 3,647,099 |
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