content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import math
def floatToJson(x):
"""Custom rule for converting non-finite numbers to JSON as quoted strings: ``"inf"``, ``"-inf"``, and ``"nan"``. This avoids Python's bad habit of putting literal ``Infinity``, ``-Infinity``, and ``NaN`` in the JSON (without quotes)."""
if x in ("nan", "inf", "-inf"):
... | 938700c100d9176f6d950aee9ddf8f90109bedcc | 8,387 |
import math
def systematic_uncertainties():
"""tabulates sources of uncertainty and sums them in quadrature"""
result_m = [
0.066, # [0.07-0.12] 0.066 ± 0.019
0.019, # [0.12-0.20] 0.019 ± 0.009
0.002, # [0.20-0.30] 0.002 ± 0.009
-0.006, # [0.30-0.4... | 71941441b09a593ebc2a3e396d2b86684bc75cfe | 8,390 |
def extract_metamap(json_, key):
"""
Task function to parse and extract concepts from json_ style dic, using
the MetaMap binary.
Input:
- json_ : dic,
json-style dictionary generated from the Parse object related
to the specific type of input
- key : str,
string d... | 543b1470f36ee85dde2c2447ecc204544ef8fd52 | 8,391 |
def get_testinfo_by_reference(ref_name, ref_type):
""" get test content by reference name
@params:
ref_name: reference name, e.g. api_v1_Account_Login_POST($UserName, $Password)
ref_type: "api" or "suite"
"""
function_meta = parse_function(ref_name)
func_name = function_meta["func_na... | 967b32149ae094d2ef86cc88b2131047b98b1f09 | 8,392 |
import logging
def game_info(uuid: str) -> dict:
"""
return info about game by uuid
:param uuid:
:return: message
"""
logging.info(uuid)
logging.info(games.keys())
if UUID(uuid) in games.keys():
select_game: Game = games.get(UUID(uuid))
return {
"uuid": uuid... | 15faaab2f256830a0f2537ada4c742f703a74783 | 8,393 |
def miller_rabin(n, a):
"""
Miller-Rabin Primality Test
Returns true if n is a (probable) prime
Returns false if n is a composite number
"""
s = 0
d = n - 1
while d % 2 == 0:
s = s + 1
d = d >> 1
x = square_and_multiply(a, d, n)
if x != 1 and x + 1 != n:
f... | 2de6b54c05d4052e5d2c8fd915a0a2814a7da28f | 8,394 |
def luhn_sum_v1(num):
"""
First version of luhn_sum; uses a list which it modifies in-place.
"""
nums = [int(i) for i in reversed(str(num))]
for i in xrange(1, len(nums), 2):
nums[i] *= 2
return sum(sum(divmod(i, 10)) for i in nums) | c2ff96069710a2321d9871608d0d9bbaddc18d30 | 8,395 |
def get_rate_discounted_rate(item_code, customer, company, so_number = None):
""" This function is use to get discounted rate and rate """
item_group = frappe.get_value("Item", item_code, 'item_group')
# parent_item_group = frappe.get_value("Item Group", item_group, 'parent_item_group')
count = frappe.db.sql(f"""
... | 8560bf5846a0500941840d59fb79cd721196a7ca | 8,396 |
def sum_obs_np(A):
"""summation over axis 0 (obs) equivalent to np.sum(A, 0)"""
return np.einsum("ij -> j", A) if A.ndim > 1 else np.sum(A) | c14abc00b2ea6fa64c32fe7ac10f0007cb4705e8 | 8,398 |
def _macos_command_line_infoplist_impl(ctx):
"""Implementation of the internal `macos_command_line_infoplist` rule.
This rule is an internal implementation detail of
`macos_command_line_application` and should not be used directly by clients.
It merges Info.plists as would occur for a bundle but then p... | d70a47def85cff62fc21e907a9f0a246a9b1c192 | 8,399 |
def get_custom_data_format(*args):
"""
get_custom_data_format(dfid) -> data_format_t
Get definition of a registered custom data format.
@param dfid: data format id (C++: int)
@return: data format definition or NULL
"""
return _ida_bytes.get_custom_data_format(*args) | 8b8751f94a409dc656efbe8131de66a0916be9ea | 8,400 |
def memory(info, func, expr):
"""
checks if the function has been called with the same argument previously and
if so, returns the same results instead of running the function again
args:
-
"""
rows=None
if info:
if func in info.evaluated:
if expr in info.evaluated[func]:
rows = info... | 693ad671b21efbc872508b7a5a4c4aa31852d10a | 8,401 |
def friend_invitation_by_email_verify_for_api( # friendInvitationByEmailVerify
voter_device_id, invitation_secret_key, web_app_root_url=''):
"""
:param voter_device_id:
:param invitation_secret_key:
:param web_app_root_url:
:return:
"""
status = ""
success = False
# If a v... | 5765f5e06a40de81b36a2dc594f6f67ec236ddcb | 8,402 |
import torch
def _load_image(fnames, dim=None, device=None, label=False):
"""Load a N-D image from disk"""
dat, affine = _map_image(fnames, dim)
if label:
dtype = dat.dtype
if isinstance(dtype, (list, tuple)):
dtype = dtype[0]
dtype = dtypes.as_torch(dtype, upcast=True)... | 8f5dae0666d0173e57a8f0005a4f6d491d2bd58f | 8,404 |
from typing import Tuple
import ctypes
def dtpool(name: str) -> Tuple[int, str, bool]:
"""
Return the data about a kernel pool variable.
https://naif.jpl.nasa.gov/pub/naif/toolkit_docs/C/cspice/dtpool_c.html
:param name: Name of the variable whose value is to be returned.
:return:
Nu... | 96584733f7f2ad93ed50e0e48ccd1040eb08dd17 | 8,406 |
def add_similar_tracks(position_or_range = ":", howmany=5, relative_positions=True):
"""
Adds Up to the value of howmany tracks similar to
each track on the current playlist.
parameters:
===========
# position_or_range: The position of the track to add similar tr... | 778eadc4d00de1aa2f293d963cdd643499f234dd | 8,407 |
def get_hot_article_tags():
"""
获取文章的所有标签
:return: 返回所有文章的标签
"""
return Tag.objects.filter(is_hot=True) | d4158308ef3ea3cbce646548dc47def9e35fcef7 | 8,408 |
from unittest.mock import patch
def patch_user_interface_null() -> MockedUserInterfaceNull:
"""Patch player interface with no players."""
return patch("steam.api.interface", return_value=MockedUserInterfaceNull()) | 8491d7beef4dfbf949cfb5a27106a948e30487c2 | 8,409 |
import signal
import numpy
def first_localmax_index(data):
"""Return index of first local maxima.
If there is no local maxima (e.g. if all the values are zero),
it will simply return zero.
"""
localmax_indexes = signal.argrelextrema(data, numpy.greater, mode='wrap')
if localmax_indexes[0]... | 7cd7baa8d564dd2175e6fd8877a733fca41e63ef | 8,411 |
def _rds_clone_ ( dataset , name = '' ) :
"""Clone dataset
>>> dataset = ...
>>> cloned = datatset.clone ( 'new_name')
"""
name = name if name else dsID ()
return ROOT.RooDataSet ( dataset , name ) | f3e3156987eafb99f05fb99a2d8371c65959faf9 | 8,412 |
def abbink_onset_detector(signal=None, rest=None, sampling_rate=1000.,
size=None, alarm_size=None, threshold=None,
transition_threshold=None):
"""Determine onsets of EMG pulses.
Follows the approach by Abbink et al.. [Abb98]_.
Parameters
----------
... | 0ae968c46ff4e5dd5496f09b637a1d5c039ab9fa | 8,414 |
def _process_image(filename, coder):
"""Process a single image file.
Args:
filename: string, path to an image file e.g., '/path/to/example.JPG'.
coder: instance of ImageCoder to provide TensorFlow image coding utils.
Returns:
image_buffer: string, JPEG encoding of RGB image.
height: integer,... | 6d978af3360692159300b4450cdd851aae842098 | 8,416 |
def float_feature(value):
"""Wrapper for inserting float features into Example proto.
"""
if not isinstance(value,list):
value = [value]
return tf.train.Feature(float_list=tf.train.FloatList(value=value)) | 9333af60465a251883b3efe70de26ce9ce483657 | 8,419 |
def my_charts(request):
"""
define personal graphics page behavior
"""
data = [0, 0, 0, 0]
if request.method == 'POST':
month = request.POST.get('month')
if month is not None:
current_user_id = request.user.id_user
if month == 'all':
all_class... | adc11d0748246c753581675eee19b2780b16b832 | 8,420 |
def matrix2yzy_extrinsic(rotation_matrices: np.ndarray) -> np.ndarray:
"""
Ry(k3) @ Rz(k2) @ Ry(k1) = [[c1c2c3-s1s3, -s2c3, s1c2c3+c1c3],
[c1s2, c2, s1s2],
[-c1c2s3, s2s3, -s1c2s3+c1c3]]
"""
rotation_matrices = rotation_matrices.reshape((-1... | 8a37e65751a26d3fd5c360ce9068626bfee5c594 | 8,421 |
def smallest_subarray_with_given_sum(arr, s):
"""Find the length of the smallest subarray whose sum is >= s.
Time: O(n)
Space: O(1)
>>> smallest_subarray_with_given_sum([2, 1, 5, 2, 3, 2], 7)
2
>>> smallest_subarray_with_given_sum([2, 1, 5, 2, 8], 7)
1
>>> smallest_subarray_with_giv... | 4a1d63619fc200c32ffae80dc7d404f486efcdd1 | 8,422 |
from typing import OrderedDict
def create_lit_model(
model: str,
input_types: "OrderedDict[str, lit_types.LitType]", # noqa: F821
output_types: "OrderedDict[str, lit_types.LitType]", # noqa: F821
attribution_method: str = "sampled_shapley",
) -> lit_model.Model:
"""Creates a LIT Model object.
... | 355eaebe6e59733d1831f993d56462ee36e4ff9a | 8,423 |
from typing import List
from typing import Dict
from typing import OrderedDict
def show_lightning_round_zero_correct(database_connection: mysql.connector.connect
) -> List[Dict]:
"""Return list of shows in which a panelist answers zero Lightning
Fill-in-the-Blank round que... | 5c218639fd2321239d9f791221f2ad30f17ead02 | 8,424 |
import requests
def get_webpage(page_url):
"""Get the OOTS index webpage and return the content."""
result = requests.get(page_url)
if result.status_code == 200:
return result.text
else:
_logger.error(
colored(
"Unable to read the OOTS data,please check your... | e9b88f69b9dca0d5cf525a26e7e43fd118698225 | 8,425 |
def generate_config(context):
""" Entry point for the deployment resources. """
properties = context.properties
name = properties.get('name', context.env['name'])
bastion_props = {
'zone': properties['zone'],
'network': properties['network'],
'machineType': properties['machineT... | f22dbb3cb3500766badb6c28eb3de35b6ba5ba3c | 8,426 |
import inspect
def dump_args(func):
"""Decorator to print function call details - parameters names and effective values.
"""
def wrapper(*args, **kwargs):
func_args = inspect.signature(func).bind(*args, **kwargs).arguments
func_args_str = ', '.join('{} = {!r}'.format(*item) for item in fu... | 673158019aa3a8343718b9648b61ef4a3699f050 | 8,427 |
from typing import Tuple
def bigaussian(
n_particles: int,
mean: Tuple[float, float, float, float, float],
geometric_emittance_h: float,
geometric_emittance_v: float,
sigma_p: float,
) -> np.array:
"""Generate a bigaussian distributed distribution.
Args:
n_particles: Number of par... | a8c7b9cf7500fde899cdcc163a31450b59d0d7d0 | 8,428 |
def horizontal_tile(silhouette, reps = 2):
"""Places two silhouettes side-by-side with an empty line in the middle."""
silhouette = np.append(silhouette,np.zeros((silhouette.shape[0],1)),axis=1)
return np.tile(silhouette,(1,reps))[:,:] | ddccc0ff9cb7f1fba56dfc52de723f5253729952 | 8,429 |
def grads_norm(parameters):
"""get grad norms of the parameters, useful for model inspection"""
t = [p.grad for p in parameters if p.grad is not None]
return many_l2_norm(*t) | 9904f5313f63387ba0c4f139029759118f2ecae8 | 8,430 |
def django_admin_add_object(request, context):
"""show add object"""
if request and request.user.is_staff and (context.get('object', None) or context.get('model', None)):
object_class = context.get('model', None)
if not object_class:
object_class = context['object'].__class__
... | 909c79cc75913afff341eed84286edd79352fc0c | 8,431 |
def get_config():
"""Returns an instance of the configured config class.
:return: Project's defined Adyen configuration.
:rtype: :class:`AbstractAdyenConfig`
By default, this function will return an instance of
:class:`adyen.settings_config.FromSettingsConfig`. If
:data:`ADYEN_CONFIG_CLASS` is... | 16a26bd31752211d2aa7a22858f0317ba90b5bad | 8,432 |
import math
def aperiodic(amp, samples):
"""an aperiodic oscillating signal
Parameters
----------
amp : float
values range over +-amp
samples : int
number of samples to generate
Returns
-------
ndarray
"""
periods = np.abs(sine(samples, samples, 1)) + samples... | 42428a16fbfee7cf2a9d8b566fc122e9c56b7e6a | 8,433 |
import base64
def removeHs(ctab):
"""
Removes any hydrogens from the graph of a molecule. CTAB is urlsafe_base64 encoded string containing single molfile or
concatenation of multiple molfiles.
cURL examples:
curl -X GET ${BEAKER_ROOT_URL}removeHs/$(cat removeHs.mol | base64 -w 0 | tr "+/" "-_")
curl -X G... | f3064e2ce3a1db1bb260da49da2df3fb1eaf1310 | 8,434 |
def judge_key(key: str, up: any):
"""判断key是否存在"""
if dict == type(up):
if key in up:
return True
else:
for dict_key, dict_value in up.items():
if dict == type(dict_value) or list == type(dict_value):
result = judge_key(key, dict_value)
... | ee0086259343df30cfc7b72951a165b557a843f9 | 8,435 |
def apply_changes(patch_obj_dic, file_dic):
"""
If all checks are passed, write the changes to the patch file. Note that the original file is overwritten
:return:
"""
success = False
error_title = None
error_msg = None
# Checks that mutually exclusive options have not been set together. ... | ad52721ab338b0124869c32c2e08f202deeb981f | 8,436 |
def construct_1D_scan_fast(gate, swing, n_pt, t_step, biasT_corr, pulse_lib, digitizer, channels,
dig_samplerate, dig_vmax=2.0, iq_mode=None, acquisition_delay_ns=None,
enabled_markers=[], channel_map=None, pulse_gates={}, line_margin=0):
"""
1D fast scan pa... | cbbffe77187cfd923b1e9b5982fb1e2b6319a854 | 8,437 |
def assemble_f_local(ck, f_func, p1, p2, p3):
"""
Assemble the local contribution to the f_load_lv for the element
Parameters
----------
ck : np.array
basis function coef. matrix.
f_func : function
load function.
p1 : np.array
first vertex of the triangle element.
... | 9912026fbde63b0cf6780a8b3fc8131dbc99c809 | 8,438 |
def take_turn(num_rolls, opponent_score, dice=six_sided):
"""Simulate a turn rolling NUM_ROLLS dice, which may be 0 (Free Bacon).
Return the points scored for the turn by the current player. Also
implements the Hogtimus Prime rule.
num_rolls: The number of dice rolls that will be made.
oppone... | f072341dde309a7b612da896d2db348c92a7f0c4 | 8,439 |
def __sort_vertices(points):
"""Return vertices that are sorted by average center of all points."""
points = list(set(points))
if len(points) < 3:
return None
start_point = __find_average_center(points)
start_vector = Vector3D.by_points(start_point, points[0])
return sorted(points, key=lambda point:
... | b89374b1b8e06c3bcc87b074239c1cc13ecd7de4 | 8,440 |
from typing import List
from typing import Tuple
def create_feature(
tokens: List[str],
label_ids: List[int],
words_map: List[Tuple[int, int, bool]],
max_seq_length: int,
tokenizer: PreTrainedTokenizer,
cls_token_at_end=False,
cls_token="[CLS]",
cls_tok... | 7dccdf98a07ec254abc14c15bba4c5ea307e8f2b | 8,441 |
from scipy.stats import norm, uniform
def calculate_log_likelihood_and_derivative_at_parameter_point_with_mRNA(protein_at_observations,model_parameters,mean_protein,measurement_variance,mRNA_parameters):
"""
Calculates the log of the likelihood, and the derivative of the negative log likelihood wrt each param... | 9d187b23c5a56e15c2bd900242823e5780991f7c | 8,444 |
def SEORedirectMiddleware(get_response):
"""
Intercepts 404 errors and checks the database for any defined
redirecs that match the current request path.
"""
def middleware(request):
response = get_response(request)
if response.status_code != 404:
return response
... | 750e8f3603114c8a6474f2fdfde76cefea1eacf7 | 8,445 |
def b2s(src):
"""
Convert from bytes to string
:param src: bytes
:return: string
"""
return src.decode(encoding=UTF_ENCODING) | 3a71fe7684ce57833db6861a250b0ba1d5fbfd47 | 8,446 |
def get_finetune_lfo_type(header: bytes) -> AutomationLfoType:
"""Return finetune LFO type."""
assert isinstance(value := _unpack(header, "FINETUNE_LFO_TYPE"), int), type(value)
return AutomationLfoType(value) | 2dcaf71353d0641dd1f0cac1bf83ecc720cd666b | 8,447 |
def locate(client: Client, structure: Structure) -> str:
"""Locates the respective structure."""
return client.run('locate', structure) | 93e2d83c6be7cc5d4a628233ccdadda2f9a914a5 | 8,448 |
def teraflops_for_accelerator(accel):
"""
Stores the number of TFLOPs available to a few accelerators, including driver handicaps.
Args:
accel (str): A string descriptor of which accelerator to use. Must be either "3090" or "V100".
Returns:
accel_flops (int): an integer of how many TFL... | a491beb06baf73325e2e7b5f0876e98ea312e2aa | 8,449 |
def reduced_supercell_vectors(ab, n):
"""
Returns all possible reduced in-plane lattice vectors and
transition matrices for the given starting unit cell lattice
vectors(ab) and the supercell size n
Args:
ab: a, b lattice vectors
n: (int) supercell size
"""
uv_list = []
... | fba60388b42beb170bfba96a9aeeccc4e1d74dbf | 8,450 |
import json
def jsonify(*args, **kwargs):
"""Creates a `Response` with the JSON representation of
the given arguments with an`application/json` mimetype. The
arguments to this function are the same as to the `dict`
constructor.
Example usage:
from cocopot import jsonify
@app.rout... | 04fe7d2808081f9a9f9b7eb610e168c8329298cb | 8,451 |
def logged_in_profile(client):
"""Add a Profile and logged-in User"""
user = UserFactory.create(username="george")
client.force_login(user)
return user.profile | b4ed5872cf8da789f3e6ab001b8afc556c0faa50 | 8,452 |
def get_storage_backend():
"""
Return the singleton instance of the storage backend in use.
"""
global _STORAGE_BACKEND
if _STORAGE_BACKEND is None:
module, klass = ClassLoader.split(str(config.STORAGE_BACKEND_CLASS))
cl = ClassLoader(module, klass, config.STORAGE_BACKEND_ARGS)
... | d23315854bf736637f483f1d802b868d4c45ff8a | 8,453 |
def _pr_compile(regex, cleanup=None):
"""Prepare a 2-tuple of compiled regex and callable."""
return (_re_compile(regex), cleanup) | 832e794bef679272231e336aa2128cf1457abb8d | 8,454 |
def config():
"""
Configuration via config.json (introduced in Anki 2.1)
"""
try:
getConfig = mw.addonManager.getConfig
except AttributeError:
return LEGACY_CONFIG
return getConfig(__name__) | cc099497d55ccef8195b47dd4d080695e9af370c | 8,455 |
def ping(request):
"""
This view returns a dummy json. It is meant to be used to check whether
the server is alive or not
"""
return Json(None) | 54f8d05454913b4119f1580f5d8a19a878e76c13 | 8,456 |
import numpy as np
import copy
def copy_ffn(model):
"""Copy feed forward network model.
Args:
model: A previously created ffn model
Returns:
A copy of the model
"""
#init model as list holding data for each layer start with input layer
newmodel = []
newmodel.append({
... | 5bde1163d5d53a75839b15aaa38a28ecc54b195c | 8,457 |
def is_big(label: str) -> bool:
"""Returns whether or not a cave is large based on its label"""
return label.isupper() | 7abdb0c5687e7870c96b767dc498e1f3c4ed21fe | 8,459 |
def fast_mult_polynoms(a, b):
"""Fast multiply of two polynoms in GF(2^8) using the log table
NB. This is NOT constant-time and leaks secret values in timing differences.
DO NOT USE THIS CODE TO IMPLEMENT SECURE APPLICATIONS
"""
if a == 0 or b == 0:
return 0
return POWER_X1_TABLE[(LOG_... | 3d670b2380963c50f74eb2f671ccdf7378ce58aa | 8,460 |
def get_page_for_group(user_groups, slug):
"""
Returns a page associated with user_groups given a slug.
"""
try:
page = get_pages_for_group(user_groups).get( slug = slug)
except Page.DoesNotExist:
page = None
return page | 6ea742688f07ca2ee0dd1ee4665598e074759229 | 8,461 |
def read_gps(gps_path):
"""Read GPS feed in CSV.
Expects GPS structured as:
vehicle_id: str
Internal system identification of the vehicle.
Should be unique per vehicle, and is used for tracking the
vehicle as it proceeds through the system.
route_id: str
... | 2ec09b69646b31e38b07e25bf2ffa0f0c002f52b | 8,462 |
def _ureduce(a, func, **kwargs):
"""
Internal Function.
Call `func` with `a` as first argument swapping the axes to use extended
axis on functions that don't support it natively.
Returns result and a.shape with axis dims set to 1.
Parameters
----------
a : array_like
Input tens... | 93be4e1a26dec25b74e6a9f330863ea7677cd614 | 8,463 |
def compute_autocorrelation_local(x, Fs, N, H, norm_sum=True):
"""Compute local autocorrelation [FMP, Section 6.2.3]
Notebook: C6/C6S2_TempogramAutocorrelation.ipynb
Args:
x: Input signal
Fs: Sampling rate
N: Window length
H: Hop size
norm_sum: Normalizes by the num... | 8e67de8279e0daae90ae3391064ea92b023dfafc | 8,464 |
def euclid_dist(vector_p1, vector_p2):
""" calculated the euclidean distance between 2 points """
distances = vector_p1 - vector_p2
return cp.hypot(distances[:, :, 0], distances[:, :, 1]) | 6f9d366cddb62f9ad1a8e26c9c2179fb73238a32 | 8,465 |
def _name_cleaner(agent_name):
"""Renames agent_name to prettier string for plots."""
rename_dict = {'correct_ts': 'Correct TS',
'kl_ucb': 'KL UCB',
'misspecified_ts': 'Misspecified TS',
'ucb1': 'UCB1',
'ucb-best': 'UCB-best',
'non... | e874745e804e07e385b377ec0ecd4247640ef6ce | 8,466 |
def add_training_args(parser):
"""Training arguments."""
group = parser.add_argument_group('train', 'training configurations')
group.add_argument('--experiment-name', type=str, default="gpt-345M",
help="The experiment name for summary and checkpoint")
group.add_argument('--batch... | 05c71d77320644fdaf00ef1638e76dbbce60ffb5 | 8,467 |
from typing import Optional
from typing import List
from typing import Dict
def _multi_class_confusion_matrix_plot(
thresholds: Optional[List[float]] = None,
num_thresholds: Optional[int] = None,
name: Text = MULTI_CLASS_CONFUSION_MATRIX_PLOT_NAME,
eval_config: Optional[config.EvalConfig] = None,
... | 9f670ad80ea10c05460815fd9af250d60b035d9e | 8,468 |
def innerL(i, os):
"""
Parameters
----------
i
os:OptStruct
Returns
-------
"""
ei = cal_ek(os, i)
if (os.labels[i] * ei < -os.tol and os.alphas[i] < os.C) or (
os.labels[i] * ei > os.tol and os.alphas[i] > 0
):
j, ej = select_j(i, os, ei)
alphaIol... | 1fc83191dbb16d863aef7c947408126d79c40099 | 8,469 |
import click
import logging
def create_client(ctx: click.Context, opts: ProxyContext) -> CumulocityClient:
"""Create Cumulocity client and prompt for missing credentials
if necessary.
Args:
ctx (click.Context): Click context
opts (ProxyContext): Proxy options
Returns:
Cumuloc... | cad28ef10409352fe25ae7310fbaae4a095b8a21 | 8,470 |
import struct
def get_float(data, index):
"""get a float value from data array"""
return struct.unpack('f', "".join(map(chr, data[4*index:(index+1)*4])))[0] | b78a5472bef42312bd765b6f9c58bfe9cddbf311 | 8,471 |
def gelu(tensor):
""" Gaussian Error Linear Unit - https://arxiv.org/abs/1606.08415 """
return 0.5 * tensor * (1 + tf.tanh(tf.sqrt(2 / np.pi) * (tensor + 0.044715 * tf.pow(tensor, 3)))) | acb5101815bb3cd0c30d602fefb0734707bf4acf | 8,472 |
def _uniqueElements(an_iterable):
"""
:param iterable an_iterable:
:param int idx:
:return list: has only one occurrence of each element
"""
used = []
unique = [x for x in an_iterable if x not in used and (used.append(x) or True)]
return unique | 8290d30e48c3ade4a547d7c3a8cf0c57b8d45b19 | 8,473 |
def guestbook_key(guestbook_name=None):
"""Constructs a Datastore key for a Guestbook entity with name."""
return ndb.Key('Guestbook', guestbook_name or 'default_guestbook') | fcff509ad5e48b58ffa823801af134c20e974b56 | 8,474 |
def _bias_scale(x, b, data_format):
"""The multiplication counter part of tf.nn.bias_add."""
if data_format == 'NHWC':
return x * b
elif data_format == 'NCHW':
return x * b
else:
raise ValueError('invalid data_format: %s' % data_format) | 19e5bb9419827f6e6976b1c5ed3cd40cdd676ad0 | 8,475 |
import re
def checkTableName(tables):
""" Check if table name has an underscore or not."""
bad = set()
output = []
for i in tables:
if re.search('.*_.*', i):
bad.add(i)
if bad:
output.append("These tables have underscores in the name")
for i in bad:
... | 2847c20712e6ce92367772678d058a05b5d10dc3 | 8,476 |
def load_split_from_tfds_builder(builder,
batch_size,
split,
preprocess_example=None,
augment_train_example=None,
shuffle_buffer_size=None,
... | 63c73f65cedc1fff92ce9a02ea23822c8e411439 | 8,477 |
def analyze(tokens):
"""
表达式元素组合，形成操作树
"""
assert_non_empty(tokens)
# 数字或者操作符
token = analyze_token(tokens.pop(0))
# 如果是数字，直接放回就好了，继续求下一个，因为数字是自求解的，本身就是解
if type(token) in (int, float):
return token
# 如果是操作符，则需要组合为Exp表达式
if token in known_operators:
# 当前是操作符， 则需要检... | 369b0b3df423dd3a38e0756379442e428efb7ef3 | 8,479 |
from typing import Mapping
from typing import Any
def copy_dict(dic: Mapping[str, Any], depth: int = 1) -> Mapping[str, Any]:
"""Deep copy a dict
Args:
dic: The dict to be copied
depth: The depth to be deep copied
Returns:
The deep-copied dict
"""
if depth <= 1:
r... | a75f9ef7c8dc797ccdf47cdc3029c403b09e75cf | 8,480 |
def get_wrf_config(wrf_config, start_date=None, **kwargs):
"""
precedence = kwargs > wrf_config.json > constants
"""
if start_date is not None:
wrf_config['start_date'] = start_date
for key in kwargs:
wrf_config[key] = kwargs[key]
return wrf_config | c9e070b91ab93a7cb81a576aa799537361b7a26f | 8,481 |
from Bio import PDB
def pdb_to_structure(filename):
"""Import a structure object from a PDB file.
"""
try:
except ImportError:
print("I can't import Biopython which is needed to handle PDB files.")
raise
p = PDB.PDBParser()
structure = p.get_structure("S", filename)
for _ ... | 1b77b6bc5af75d03af847032827c07656addf4f3 | 8,482 |
def allocation_ncsist():
"""
Real Name: Allocation NCSIST
Original Eqn: IF THEN ELSE( ShiMen Reservoir Depth>=ShiMenReservoir Operation Rule Lower Limit , 6048, IF THEN ELSE( ShiMen Reservoir Depth >=ShiMenReservoir Operation Rule Lower Severe Limit, 6048*0.9 , 6048*0.8 ) )
Units: m3
Limits: (None, ... | f2b781869957d78dc59e6837a253bc0df29250bd | 8,483 |
def hamming(s1, s2):
"""Return the hamming distance between 2 DNA sequences"""
return sum(ch1 != ch2 for ch1, ch2 in zip(s1, s2)) + abs(len(s1) - len(s2)) | e3e1f3e9cc883f27d26f00c1b3c9495d29c1a139 | 8,484 |
import torch
def get_org_df(pr_label_f, metadata_df, seq_len):
"""
Returns the org_df given pr_label_f,metadata_df,
"""
org_r, org_c = torch.nonzero(pr_label_f, as_tuple=True)
org_df = cudf.DataFrame()
org_df["seq_row"] = cudf.Series(org_r)
org_df["org_seq_col"] = cudf.Series(org_c)
... | 543bfe8f95409eefeb792ee2f94d8518fa4a3fe3 | 8,486 |
from scipy.stats import norm
def binomial_proportion(nsel, ntot, coverage=0.68):
"""
Calculate a binomial proportion (e.g. efficiency of a selection) and its confidence interval.
Parameters
----------
nsel: array-like
Number of selected events.
ntot: array-like
Total number of eve... | 94b9d3cf766ca2f35f677a4421aabc1840097729 | 8,487 |
def nasnet_dual_path_scheme_ordinal(module,
x,
_):
"""
NASNet specific scheme of dual path response for an ordinal module with dual inputs/outputs in a DualPathSequential
module.
Parameters:
----------
module : nn.Module
... | aef487a25bc3349f14a112826ee4f8e8912dd324 | 8,488 |
import json
import traceback
def ifttt_budget_options():
""" Option values for the budget field """
if "IFTTT-Service-Key" not in request.headers or \
request.headers["IFTTT-Service-Key"] != get_ifttt_key():
return json.dumps({"errors": [{"message": "Invalid key"}]}), 401
try:
... | c987ca533fc0568e759e4e6c6affbdb7efeb4781 | 8,489 |
import sqlite3
def get_exp_date_stats(db_file_name, Table):
"""Caculate exp date stats of collection"""
conn = sqlite3.connect(db_file_name)
c = conn.cursor()
c.execute('''SELECT exp, count(exp) FROM {} GROUP BY exp'''.format(Table))
exp_dict = {}
results = c.fetchall()
for result in res... | 7641d6309939359c1d790b66a1310b5b78be99a4 | 8,490 |
import random
def create_default_identifier(node_address, token_address, target):
"""
The default message identifier value is the first 8 bytes of the sha3 of:
- Our Address
- Our target address
- The token address
- A random 8 byte number for uniqueness
"""
hash_ = sha... | ae63898d0130eda2cbc1a6e3861b288e9b1a4d10 | 8,491 |
def print_scientific_16(value: float) -> str:
"""
Prints a value in 16-character scientific notation.
This is a sub-method and shouldnt typically be called
.. seealso:: print_float_16 for a better method
"""
if value == 0.0:
return '%16s' % '0.'
python_value = '%16.14e' % value # ... | 18072bfb5cc51e83f1c26086558abc4019e4737e | 8,493 |
def _interpolate_target(bin_edges, y_vals, idx, target):
"""Helper to identify when a function y that has been discretized hits value target.
idx is the first index where y is greater than the target
"""
if idx == 0:
y_1 = 0.
else:
y_1 = y_vals[idx - 1]
y_2 = y_vals[idx]
edg... | 7a84bc846c8446aa7449732fdb60171d6f144863 | 8,494 |
def azimuth_range_to_lat_lon(azimuths, ranges, center_lon, center_lat, geod=None):
"""Convert azimuth and range locations in a polar coordinate system to lat/lon coordinates.
Pole refers to the origin of the coordinate system.
Parameters
----------
azimuths : array_like
array of azimuths d... | a68e9e6731393f454d5725267b5a7c56e2afaedd | 8,495 |
def count_path_recursive(m, n):
"""Count number of paths with the recursive method."""
def traverse(m, n, location=[1, 1]):
# return 0 if past edge
if location[0] > m or location[1] > n:
return 0
# return 1 if at end position
if location == [m, n]:
return ... | ad31718d179bf46966117ecfa414807e6d356634 | 8,496 |
def markdown(caller):
"""Renders the argument to markdown. Useful in `{% filter markdown() %} `
blocks
Args:
caller (str): Markdown source
Returns:
str: rendered HTML
"""
return render_markdown(caller) | fd3fcea8ae9cbac660c1f8971e89baa1c61467ac | 8,497 |
from typing import Dict
from typing import Any
def color_menu(colno: int, colname: str, entry: Dict[str, Any]) -> int:
# pylint: disable=unused-argument
"""color the menu"""
if entry.get("__shadowed") is True:
return 8
if entry.get("__deprecated") is True:
return 9
return 2 | 090dc76475fbe7507c9687127306c34b0652e16a | 8,499 |
def likelihood(sent, ai, domain, temperature):
"""Computes likelihood of a given sentence according the giving model."""
enc = ai._encode(sent, ai.model.word_dict)
score, _, _= ai.model.score_sent(enc, ai.lang_h, ai.ctx_h, temperature)
return score | 8332dfc8c2dba18a117768043dff67e632cc22ff | 8,500 |
def simulator(
theta,
model="angle",
n_samples=1000,
delta_t=0.001, # n_trials
max_t=20,
no_noise=False,
bin_dim=None,
bin_pointwise=False,
):
"""Basic data simulator for the models included in HDDM.
:Arguments:
theta : list or numpy.array or panda.DataFrame
... | 370e45499f85bd406a2f80230389dd6aa9866cf0 | 8,501 |
from pytato.utils import with_indices_for_broadcasted_shape
from typing import Union
def logical_not(x: ArrayOrScalar) -> Union[Array, bool]:
"""
Returns the element-wise logical NOT of *x*.
"""
if isinstance(x, SCALAR_CLASSES):
# https://github.com/python/mypy/issues/3186
return np.lo... | 922f7a0688590fad9492b7e654f97b2f34717ca8 | 8,502 |
def _build_xyz_pow(name, pref, l, m, n, shift=2):
"""
Builds an individual row contraction line.
name = pref * xc_pow[n] yc_pow[m] * zc_pow[n]
"""
l = l - shift
m = m - shift
n = n - shift
if (pref <= 0) or (l < 0) or (n < 0) or (m < 0):
return None
mul = " "
if pref =... | 0dbae02252b27845e795a586e2e28b58c948fa1d | 8,503 |
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