content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from typing import Any
def try_to_cuda(t: Any) -> Any:
"""
Try to move the input variable `t` to a cuda device.
Args:
t: Input.
Returns:
t_cuda: `t` moved to a cuda device, if supported.
"""
try:
t = t.cuda()
except AttributeError:
pass
return t | 9b6643f169c1eb8fc65de8b1bff55668f8cba950 | 58,700 |
def filter_status_sensitive(production_id):
"""
敏感状态
:param production_id:
:return:
"""
if not production_id:
return False
condition = {
'production_id': production_id,
'status_delete': STATUS_DEL_NO
}
production_sensitive_info = get_production_sensitive_row(*... | 358bda8e224d86380a318d86cf3d1b89b65135b3 | 58,701 |
def diff6circlek(delta, gamma, energy_kev=None, wavelength=1.0, lab=None):
"""
Calcualte incident and final wavevectors in diffractometer axis using detector angles
:param delta: float angle in degrees in vertical direction (about diff-z)
:param gamma: float angle in degrees in horizontal direction (abo... | ef6d6efd7ec6892b0ead82acf66bb833144b5752 | 58,702 |
def fixtableforhtml(tablecolumn):
"""
fix the formatting to make the decimals into percents and
add comma seps to long numbers
"""
new_table = []
for x in tablecolumn:
if float(x) < 1:
x = str(round(float(x) * 100, 2))+"%"
else:
x = int(float(x))
... | f57f2ef4145a7389e6160316750e64d0903ddc02 | 58,703 |
def refine_baseline(baseline, heights, detection_maps, downsample, crop_engine, detection_threshold=0.3):
"""
Refines the input baseline using fitting 2nd order polynom to the baseline detection map.
:param baseline: numpy array of input baseline coords
:param heights: list of input line heights [ascend... | f36e5edc52fd10b69b259528421d4904acbc365e | 58,704 |
def provides(iface):
"""
Matches an object that provides the given interface.
"""
return Provides(iface) | a142ab3aa391fc84c56a91b3c41e3e22c119ce62 | 58,705 |
def getGasDensity(grid=None, ppar=None):
"""Calculates the gas density distribution in a protoplanetary disk.
Parameters
----------
grid : radmc3dGrid
An instance of the radmc3dGrid class containing the spatial and frequency/wavelength grid
ppar : dictionary
A diction... | 113b4a18f0a420ccea8fdaf9674521465af5132a | 58,706 |
def extract_finding(doc, audit):
"""
Given a header, examine the relevant context and see if we have
a finding on our hands that corresponds to the given audit.
"""
headers = sentences(doc, "HEADER")
if not headers:
return None
# we know this page has a header. attempt to extract the... | 657b8f9f1fcbec4646e53540c1865acad2b1f151 | 58,707 |
from scipy.optimize import brentq
def s_of_rew(rew,A_w,G0,Rg,ah):
"""
Inverse function of rew_of_s. Uses brentq for root finding.
Parameters
----------
rew : float
rest equivalent width of absorption
A_w : float
Defined in eq. 6, Tinker & Chen 2008, ApJ
G0 : float
N... | f9cfe1daa8ff64385b9007981f7c07732df5e70e | 58,708 |
def get_instance_characteristics(instance):
"""
Returns a tuple of the node & edge model classes and the instance_type
for the provided instance
"""
try:
# Assume a queryset of nodes was provided
_NodeModel = instance._meta.model
_EdgeModel = instance._meta.model._meta.get_fi... | e0df14a4c68a595493a697ac3807281e54184cf3 | 58,709 |
import argparse
def _get_deploy(args: argparse.Namespace, validator: PrivateKey) -> Deploy:
"""Returns delegation deploy to be dispatched to a node.
"""
# Set standard deploy parameters.
deploy_params = pycspr.factory.create_deploy_parameters(
account=validator,
chain_name=args.chain_... | ac24f5cff3167f11ac40560ad5f2ae44c15263ce | 58,710 |
def zebra_puzzle():
"""Return a tuple (WATER, ZEBRA) indicating their house numbers."""
houses = first, _, middle, _, _ = [1, 2, 3, 4, 5]#Replace string with number in a list
print houses
orderings = list(itertools.permutations(houses)) #make a list of unordered houses
#print list(orderings)
ret... | 017e64d91f8cd1a6b0ece56dd1b15c9d020e1b9a | 58,711 |
def open_CTmax_data():
"""Return an xarray.Dataset with CTmax data from OBIS.
TODO: improve provenance!
"""
matdata = sio.loadmat(
'data/MI-traits-data/obis_Tmax.mat', struct_as_record=False, squeeze_me=True
)
data = matdata['obis']
return xr.Dataset(
dict(
lat=x... | 36f7e3fad89be3bbcb7c68b4598afc6292722bb5 | 58,712 |
import os
def _count_frames_in(input_directory = '.'):
"""Calculates the number of frames in the input directory.
The function calculates the number of frames in the input directory. The
frames should be named frame_xxxx.png, where xxxx is the number of the frame.
The numbers should start from 1 and should b... | af4ef559a3e866f82fb31778920f94013ea38929 | 58,713 |
def main( argv ):
""" Script execution entry point """
# initialize and start the user interface
#ui = timecalc()
#ui.mainloop()
if len( argv ) > 1:
if len( argv ) == 5:
arg = ' '.join( argv[ 1 : ] )
else:
arg = argv[ 1 ]
num = number( arg )
... | 119d5247f1f57b7fcb7a793665c36442066d23e6 | 58,714 |
from bs4 import BeautifulSoup
from pathlib import Path
def clean_html(html: str) -> str:
"""Removes script tags and their contents"""
soup = BeautifulSoup(html, "html.parser")
for script in soup(FORBIDDEN_TAGS):
script.decompose()
for img in soup.find_all("img"):
img.name = "span"
... | b21db67976ee6b4c35701a0c26408920fff497d7 | 58,715 |
import os
def run_vcfeval_roc_plot(job, context, roc_table_ids, names=[], kind=None, number=0, title=None,
show_scores=False, line_width=2, ps_plot=False):
"""
Draw some rocs from the vcfeval output. Return (snps_id, nonsnps_id,
weighted_id)
kind specifies the subtype of ... | d8cd5098bdf7894bd32b3be34775c3a388fc3340 | 58,716 |
import time
def internalKey(key = None):
"""Internal Key
Generates or validates an internal key so services can communicate with
each other
Arguments:
key (str): Passed to validate a key
Returns:
bool
"""
# Pull in salt
global __msSalt
# Generate a timestamp
iTime = int(time())
# If no key was pa... | 3f9d0a92710417701f56c22b58e90fe9b517cc56 | 58,717 |
def squint2(t, r, orbit, attitude, side, sin_az=0.0, h=0.0):
"""Find squint angle given imaging time and range to target.
"""
p, v = orbit.interpolate(t)
R = attitude.rotmat(t)
axis = R[:,0]
angle = np.arcsin(sin_az)
dem = ie.pyDEMInterpolator(height=h)
xyz = rdr2geo_cone(axis=axis, angl... | 62033e43c5e76e9a46d682cbca9d5efe5333f671 | 58,718 |
import re
def update_issue_status(condition_str):
"""Replace issue URL with 'True' or 'False' based on its active state.
If there is an issue URL is found, this function will try to query state of the issue and replace the URL
in the condition string with 'True' or 'False' based on its active state.
... | 9aa4e2cd0b91e42c1ce2031eeba5fb8f33dbc67e | 58,719 |
def generate_action_dict():
""" Generate a list of all possible uci moves and their action number lookup
Return:
actions: lookup dictionary for converting uci into actions(number)
inverse_actions: lookup dictionary for converting actions to uni
"""
# normal uci moves
standard_uci = []
... | 267d80bcf64d76e7742b48de2d6c49507c6710bd | 58,720 |
import time
def check_update(from_currency, to_currency):
""" check if last update is over 30 mins ago. if so return True to update, else False """
if from_currency not in ccache: # if currency never get converted before
ccache[from_currency] = {}
if ccache[from_currency].get(to_currency) is None:
ccache[from_... | be6561d9a94595499196b15b9a2eb1461bef18c5 | 58,721 |
import math
def facto(mult):
""" Product of factorials of multiplicities in the multiset """
if not is_natural_multiset(mult):
raise Exception("Coefficient only works for natural multisets")
result = 1
for a in mult.sp.iter_all():
result *= math.factorial(mult(*a))
return result | 2ac95f97f65fd4c73da6ccfb53dd4055fea6b728 | 58,722 |
def export(cfg, args):
"""
Modifies program config variables.
"""
if args[1] == 'color':
color_triple = export_color(args)
cfg['color'] = color_triple
changed = tuple(color_triple)
elif args[1] == 'time':
time_period = export_time(args)
cfg['time'] = time_pe... | d8f9b8f4a5ca22ad6f1ffa10807e73b5078ea65c | 58,723 |
def build_sampler(tokenizer, device=None):
"""Build the appropriate sampler according to the configs."""
if FLAGS.model_type == 'text':
model_fn = lambda prompts: text_model_fn(tokenizer.vocab_size)( # pylint: disable=g-long-lambda
prompts, is_training=False, cache_steps=FLAGS.sample_memory_size)
s... | 03bb0162ee076516cf35be96182e925e3606e688 | 58,724 |
import fnmatch
import os
def find_data_files(package_dir, patterns, excludes=()):
"""Recursively finds files whose names match the given shell patterns."""
paths = set()
def is_excluded(s):
for exclude in excludes:
if fnmatch.fnmatch(s, exclude):
return True
return False
for directory,... | 4889ba4dea6b70f0935afd8efdbeaf5179d4a742 | 58,725 |
from typing import Sequence
from typing import Iterator
def apply(masks: Sequence[int], value: int) -> Iterator[int]:
"""Apply each bit mask to the given value using bitwise AND.
Args:
masks: Bit masks to apply.
value: Value to mask.
Returns:
Iterator with each mask independentl... | 6eafc88977eea0d50173a4c37c12b43f5c80a870 | 58,726 |
from scipy.optimize import fmin_cobyla
def _fit_dipoles(fun, min_dist_to_inner_skull, data, times, guess_rrs,
guess_data, fwd_data, whitener, ori, n_jobs, rank):
"""Fit a single dipole to the given whitened, projected data."""
parallel, p_fun, _ = parallel_func(fun, n_jobs)
# parallel ove... | 251a9f38ca7f8545ca2da5e2b9f70da479a23a58 | 58,727 |
import matplotlib.pyplot as plt
import array
def launch(x1: 'array', x2: 'array', percent: float = 20., isplot: bool = False):
"""
Outilers identifier for 2D data.
x1 -- array of the first variable.
x2 -- array of the second variable.
percent -- maximum percent of data to be filtered (default 20%)... | 128f66012e7ab93cd96b2d7b2a9eddb019bfe8de | 58,728 |
import threading
def thread_get_album(update: Update, context: CallbackContext) -> int:
"""Creates a thread to get the album"""
language = context.user_data["bot_lang"]
text = context.bot_data["texts"][language]["get_album"]
chat_id = update.effective_user.id
update.callback_query.answer()
_,... | 0ced06d7175717697c4aebddfceb2b8d946f72c2 | 58,729 |
import random
def _compute_loss_and_metrics(
params, batch, rng,
model, is_experts_model,
auxiliary_loss_factor,
router_z_loss_factor):
"""Computes cross-entropy loss and metrics for classification tasks.
Args:
params: Model state (parameters).
batch: Current batch of examples.
rng: R... | 553356a3c51d66809a6352947410ffb036465aa8 | 58,730 |
def filter_df_for_pred_a(df, list_freq_outliers):
"""
Exclude frequency outliers according to list and drop all hex bin / time window combinations with 0 RTA's
"""
df_pred_a = df.loc[~df["h3_zone_6"].isin(list_freq_outliers)]
df_pred_a = df_pred_a.reset_index()
df_pred_a = df_pred_a.drop(["uid",... | 1115c845593ec2aabf55f6c5d52f4ef8b23fc121 | 58,731 |
def create_modules(module_defs):
"""
Constructs module list of layer blocks from module configuration in module_defs
"""
hyperparams = module_defs.pop(0)
output_filters = [int(hyperparams['channels'])]
module_list = nn.ModuleList()
for i, module_def in enumerate(module_defs):
modules... | 5ecebd8260f6926ed63396b19adc099129d2946c | 58,732 |
def jinja_plugin_factory(options):
"""
Basic implementation of the `GeneralTemplateInterface`.
Supports ``loader_func`` and ``getmtime_func``, as well as
string and file loading but ignores ``mode`` since it's a
text based template engine.
All options passed to this function are forwarded to t... | 16d353ccfcbad598a92cb17767e6eca0075e5e98 | 58,733 |
import glob
def build_context(**kwargs: dict):
"""
Build Context takes an arbitrary dictionary and merges with a dictionary
which reflects configuration read from a json file.
"""
def read_config(config_file):
# read the job configuration
try:
file_location = glob.glob... | b3b9f6bd975a163602ad73c1b7ffa1488ab00f89 | 58,734 |
def import_string(module: str):
"""
Import the given module path.
"""
try:
_module, func = module.strip(' ').rsplit('.', 1)
except ValueError:
raise ImportError('It looks like module {} is not a valid module'.format(module))
mod = import_module(_module)
try:
... | 331fbff3851315a5ff892e7c493e726eab2ec3f9 | 58,735 |
import cdms2, cdutil, numpy
def join_scalar_data(*args ):
""" This function joins the results of several reduced variables into a
single derived variable. It is used to produce a line plot of months
versus zonal mean.
"""
#pdb.set_trace()
nargs = len(args)
M = []
for arg in args:
... | 20a69cd2559c146c31a72817c79db8d0510103fe | 58,736 |
def group(seq, groupSize, noneFill=True):
"""Groups a given sequence into sublists of length groupSize."""
ret = []
L = []
i = groupSize
for elt in seq:
if i > 0:
L.append(elt)
else:
ret.append(L)
i = groupSize
L = []
L.appe... | a7314803cb3b26c9bd69a2dbc2c0594181085c2c | 58,737 |
def client_response_factory():
"""Custom response factory for client."""
return ResponseFactory() | 99838198b2004d531c147141b62890ef8d29e0f3 | 58,738 |
import os
def get_module_data(filepath: str):
"""Create module data dictionary that `cppimport` uses"""
fullname = os.path.splitext(os.path.basename(filepath))[0]
return setup_module_data(fullname, filepath) | 9b7554f5a118aef5f2786951557373d08ddccb88 | 58,739 |
import torch
def membrane(field, voxel_size=1, bound='dct2', dim=None, weight=None):
"""Precision matrix for the Membrane energy
Note
----
.. This is exactly equivalent to SPM's membrane energy
Parameters
----------
field : (..., *spatial) tensor
voxel_size : float or sequence[float]... | 9ac91c6b79ce10977ba51c13fcc929aa352744e2 | 58,740 |
from sys import flags
def define_image(data_format=True):
"""Register image specific flags.
Args:
data_format: Create a flag to specify image axis convention.
Returns:
A list of flags for core.py to marks as key flags.
"""
key_flags = []
if data_format:
flags.DEFINE_enum(
name="dat... | eeb1d6dae6220ea28aa95e93164ad5e5d7d4405b | 58,741 |
def get_dataset(config, attack_ds_config, add_x_train=None, add_y_train=None):
"""
@param config:
@param attack_ds_config:
@param add_x_train: x_train samples to add to training set
@param add_y_train: y_train samples to add to training set
@return:
"""
dataset = config.dataset.dataset
... | 55b1561e513de6705dfdbb43fee2aa5eb592392a | 58,742 |
def attrdict_setup(attrdict=milc.attrdict.AttrDict):
"""Setup a simple AttrDict object for testing.
"""
simple_dict = attrdict()
simple_dict['a'] = True
simple_dict['b'] = False
return simple_dict | a66613df54baa1e04a435184e488dbf1b7b46123 | 58,743 |
from typing import List
from typing import Any
def find_duplicates(list_: List[Any]) -> List[Any]:
"""
Find the elements duplicated in a list.
"""
dbg.dassert_isinstance(list_, list)
# Count the occurrences of each element of the seq.
set_l = set(list_)
v_to_num = [(v, list_.count(v)) for ... | 5f97f384395b530527df801239340cac7fde740d | 58,744 |
def create_response_payload_with_status(command_request, method_name, create_user_response=None):
"""
Helper method to create the payload for responding to a command request.
This method is used for all method responses unless the user provides another
method to construct responses to specific command r... | fab9c14046bbbad71f78c2671abf6786bb0a42c8 | 58,745 |
def splitdrive(p):
"""Split a pathname into drive and path. On Posix, drive is always
empty."""
return p[:0], p | 14524196f9f2018fed85081f1825592d244ac50f | 58,746 |
def conv3x3(in_planes, out_planes, stride=1):
"""3x3 convolution with padding"""
return PartialConv2d(in_planes, out_planes, kernel_size=3, stride=stride,
padding=1, bias=False) | 917ded11178349308c46a3ee1187dcb6624c409d | 58,747 |
def namespace_embedded(db_ns: str) -> bool:
"""Return true if this namespace requires IDs to have namespace embedded.
This function first maps the given namespace to an identifiers.org
namespace and then checks the registry to see if namespaces need
to be embedded in IDs. If yes, it returns True. If no... | 283e4436df750d6846fd549fb2aa227e3ae72c90 | 58,748 |
def NoisyNode(num_centroids=2, **kwargs):
"""
Returns a function that takes a graph and adds noise to the
node features except for the centroids.
"""
def inner(data):
graph, labels = data
features = graph[0][:, num_centroids:]
features += np.random.randn(*features.shape) * ... | 44a9bad800a19ddd5abc83876f0925a974fc1cfd | 58,749 |
def train_model_multi_output_w_tmt(x, y, param_grid=None, n_jobs=-1, cv=5):
"""Trains and does gridsearch on a keras nnet. Response can be multi output
Args:
x (np array): explanatory variables
y (np array): response variables. could be more than 1
n_jobs (int): number of cores to run on... | 4d12c393ce032c7dccb5a61b9acc06ccf180d66b | 58,750 |
import torch
def to_numpy(t: torch.Tensor):
"""Convert model output from Torch Tensor to numpy array."""
assert t.ndim == 4
# Inverse normalize [-1, 1] -> [0, 1], rescale [0, 1] -> [0, 255]
out = (torch.clamp(t * 0.5 + 0.5, 0, 1) * 255) \
.permute(0, 2, 3, 1) \
.detach() \
.c... | bbf142eb7c696aa11e2c1d476cc3a7b11eeae600 | 58,751 |
import operator
def decimate(x, q, n=None, ftype='iir', axis=-1, zero_phase=True):
"""
Downsample the signal after applying an anti-aliasing filter.
By default, an order 8 Chebyshev type I filter is used. A 30 point FIR
filter with Hamming window is used if `ftype` is 'fir'.
Parameters
-----... | e2b8258153284d943981975acc642e39cbaf9382 | 58,752 |
import hashlib
def get_interface_name(name, prefix='', max_len=constants.DEVICE_NAME_MAX_LEN):
"""Construct an interface name based on the prefix and name.
The interface name can not exceed the maximum length passed in. Longer
names are hashed to help ensure uniqueness.
"""
requested_name = prefi... | 0309fe509496393ac64d1dc61373d0a8e3c0a64e | 58,753 |
def differentiable_cumsum_capper(x, threshold, width):
"""Starts out 1 and decays to 0 so that (result * x).cumsum() <= threshold."""
cumsum = x.cumsum()
capped_cumsum = threshold - width * nn.softplus((threshold - cumsum) / width)
capped_x = jnp.concatenate([x[:1], jnp.diff(capped_cumsum)])
# The "double whe... | 166983a1ad7aab3b5070535f66cf28fdb82661f6 | 58,754 |
def angle_energy(angle_numbers, uint_crd_f, scalar_f, atom_a, atom_b, atom_c, angle_k, angle_theta0):
"""
Calculate the energy caused by 3-atoms angle term. Assume the number of angles is M and the
number of atoms is N.
.. math::
dr_{ab} = (x_b-x_a, y_b-y_a, z_b-z_a)
.. math::
dr_{c... | 1b34ae109dfe90c4c33a63298344d5806c896d1b | 58,755 |
def sub_mask_1d_indexes_for_mask_1d_index_via_mask_2d(mask_2d, sub_size):
""""For pixels on a 2D array of shape (rows, colums), compute a 1D array which, for every unmasked pixel on \
this 2D array, maps the 1D sub-pixel indexes to their 1D pixel indexes.
For example, for a sub-grid size of 2, the followin... | 4fedf5876127da4ed3b92422ce4da422e7d391a7 | 58,756 |
def plot_mc_value(observation_space: gym.spaces.Box, feature_map: FeatureMap, weights: np.ndarray, fig=None):
"""
Plot MountainCar value function
"""
xs = np.linspace(observation_space.low[0], observation_space.high[0])
ys = np.linspace(observation_space.low[1], observation_space.high[1])
gridx,... | c0481b606d9a84325bc9fece8c4b61fad02e8637 | 58,757 |
import math
def currin_exp_function(X):
"""
Compute the CurrinExp function.
The value is computed as defined in https://www.sfu.ca/~ssurjano/curretal88exp.html
:param X: dictionary containing the input points.
:return: the value of the CurrinExp function.
"""
x1 = X['x1']
x2 = X['x2']
... | 8cbcd384bcc49511a93e517c0b22c9c8d2837826 | 58,758 |
import gettext
def change_email_address():
"""Request a change of the current user's email address."""
current_user = g.user
form = ChangeEmailAddressForm(request.form)
if not form.validate():
return change_email_address_form(form)
new_email_address = form.new_email_address.data.strip()
... | abf3944e25880d543f0adca884d91ecd3917126d | 58,759 |
def run_single_with_display(wf, display):
"""Adds a display to the single runner. Everything still runs in a single
thread. Every time a job is pulled by the worker, a message goes to the
display routine; when the job is finished the result is sent to the display
routine."""
S = Scheduler(error_hand... | ca22f5c7fde36ceb7cd5c69a020a77ca4a47766b | 58,760 |
def solution(n):
"""Returns the largest palindrome made from the product of two 3-digit
numbers which is less than n.
>>> solution(20000)
19591
>>> solution(30000)
29992
>>> solution(40000)
39893
"""
# fetchs the next number
for number in range(n - 1, 10000, -1):
# ... | baccd41bdab7eed9dd7069caecc650834846e0d4 | 58,761 |
import math
def pressure_to_altitude(pres):
"""Convert a pressure (Pascals) to altitude (meters)"""
for i in range(len(_heights)-1,0,-1):
P0 = _basepress[i]
T0 = _basetemps[i]
if pres < P0:
if _isotherm[i]:
dh = _R * T0 / _g * math.log(P0 / pres)
... | fa46e0b438c4cf56355ecaa17f838a152f6680e5 | 58,762 |
def read(filename):
"""
Read a nmrglue table file.
Parameters
----------
filename : str
Filename of nmrglue table file to read.
Returns
-------
comments : list
List of comments (strings terminated with newline)
rec : recarray
Records array with named fields.... | f4d9b0dc040a3d38337783281c38cd471a7b4be7 | 58,763 |
import requests
import json
def get_decomposition(profile_counts, signatures='COSMIC30'):
"""
Decomposition of mutational profiles into a combination of signatures.
It is highly recommended to use profile_counts instead of profile in order to use Maximum Likelihood method
*signatures* should be one of... | be4f5a7777443c44004ae349c5fc437ffd56ed0b | 58,764 |
from django.utils import timezone
from sentry.app import tsdb
from sentry.models import Organization
import click
from typing import OrderedDict
import six
def organizations(metrics, since, until):
"""
Fetch metrics for organizations.
"""
stdout = click.get_text_stream("stdout")
stderr = click.ge... | 5d7659d124e12470515c4421a67c410f2c97849b | 58,765 |
import dbm
from datetime import datetime
import json
def export(start_date: str = Form(...), end_date: str = Form(...),
db: Session = Depends(dbm.get_db), user: UserModel = Depends(auth.get_user)):
"""Export pomodoros"""
start_date = datetime.strptime(start_date, "%Y-%m-%d")
end_date = datetim... | 3e05075c68f8103db759270e1ca610606eea4427 | 58,766 |
def get_bin_counts(array_in: NpArray,
num_bins_per_dim: int) -> NpArray:
"""Divide two dimensional input space into a grid and count points in each.
Point on the upper edge, which does happen in the data, go into the lower bin.
The occurrence of these points is an artefact of the rescaling don... | 3879310d554a61fc8d9e4c675d8e62a6be82d758 | 58,767 |
def parse_comments_from_back(line):
"""
Scan for tokens back to front in line.
Any token that does not start with a valid dice spec or a literal is a comment.
Return separately the line substring without comments and the comments.
Returns:
(line, comment):
line: Remainder of the... | 75f9acc697e18fdb0beb9decb1b383a43d1e5264 | 58,768 |
import numpy
import math
def f_internal(x, h, core_data):
"""
Creates an O(1) dummy function with unit bounds.
So, (I hope) the gradient and stencil are reasonably scaled.
I encode scale and noise awareness in this function, too. If your
function is not noise aware, I pass a zero noise back to imfil_core... | 0384bc7f4c7af5cd42738f467ddff45cbf2618f0 | 58,769 |
def radius_of_curvature(line, method="osculating"):
""" Compute curvature radius of LineString
:param line:
:param method: method for computing radius of curvature {'circumscribe', 'osculating'}
:return:
"""
def norm(xx, yy):
return np.sqrt(xx ** 2 + yy ** 2)
def tangent_vector(xi,... | 6d378bfb366d8f3592ef3f85174239f10a980086 | 58,770 |
def create():
"""Create a new post.
For a post to be created, details are submitted in the form. These details
are then inserted into the posts table in the database.
Returns:
Success JSON response if the operation succeeded.
Else a failed JSON response is returned with the correct err... | da3a657375796dc9f031ed355d0620ef0e55fd2a | 58,771 |
def decode(ids, encoder):
"""
Decode a list of IDs.
"""
ids = list(ids)
if text_encoder.EOS_ID in ids:
ids = ids[:ids.index(text_encoder.EOS_ID)]
return encoder.decode(ids) | 200d113e7ce9ab387b83cd926b8a0d7a4762fff6 | 58,772 |
import io
def _load_image_obj(fileobj):
"""
Turn a byte file object into an image
"""
return Image.open(io.BytesIO(fileobj)).convert("RGB") | 8ac45f3c8dee39d1f6d4181ca78bcabc26de5c28 | 58,773 |
def submit_edit():
""" handle file edit form """
# ... including student work pages.
# invoked from handle_post()
# the form text data is in the form dict key, i.e. request.form['edit_text']
# print_debug(' submit_edit: request.form : {}'.format(request.form.items()))
#
# request.form will l... | 6f88b891436f387c4425be2fba5e22abae908008 | 58,774 |
def vround(v):
"""Convert a numpy 1d array to a tuple for hashing.
"""
return tuple(np.round(v, 8)) | c196a465d07793fb0b68a9055741a8d40655b404 | 58,775 |
import sys
from pathlib import Path
def validate_payload(file_path: str) -> str:
"""Return the raw payload.
This allows us to read from a file or the stdin stream.
"""
if file_path.startswith(r'\@'):
# escape @ with \ to let the cli know that the payload starts with @
return file_path... | 35c9a978cb7f6713de9b2b0ea59a928104f1a099 | 58,776 |
def LSTM_triggerNG(tx, num_channels, num_outputs, kernel_init='normal', bias_init='zeros') -> Model:
"""Modified from Andrew Ng's Deeplearning.ai Sequence Modeling course on Coursera.
Originally used for trigger word detection.
Notes:
- Switched GRU cells to LSTM cells
- BiDirectional???
... | 877a6fce737f278bb95e6a4109c40ed5cf564d6b | 58,777 |
import random
def load_data(ticker, n_steps=60, scale=True, split=True, balance=False, shuffle=True,
lookup_step=1, test_size=0.15, price_column='Price', feature_columns=['Price'],
target_column="future", buy_sell=False):
"""Loads data from yahoo finance, if the ticker is a pd Data... | 566692d3f493f58981e9b7fdd04b887a8aa257fe | 58,778 |
import numpy as np
def BestDividing(dataSet, bestFeat):
"""
选出连续性特征最优划分点+返回其信息熵
Parameters
----------
dataSet:数据集
bestFeat：对哪个连续特征进行判断
Returns：最优划分点+其信息熵
-------
"""
bestEntropy = 1000.0 # 初始设一个不可能的超大熵
bestValue = 0.0
features = np.sort(dataSet[bestFeat].values)
... | 075834bfa205153411b49c3d431402bb93a316d6 | 58,779 |
import functools
def freezeargs(func):
"""
Transform all mutable objects into immutables using freeze
For the sake of lru_cache
"""
@functools.wraps(func)
def wrapped(*args, **kwargs):
args = tuple(freeze(arg) for arg in args)
kwargs = {k: freeze(v) for k, v in kwargs.items()}... | fe7760698e816b4f7c3599581a8d3d5b60dcb904 | 58,780 |
def classify_name(name):
"""Classify filename `name` as "crds", "oldcdbs", or "newcdbs".
>>> classify_name("jwst_miri_dark_0057.fits")
'crds'
>>> classify_name("s7g1700gl_dead.fits")
'oldcdbs'
>>> classify_name("07g1700gl_dead.fits")
'newcdbs'
>>> classify_name("bbbbbb.fits")
Tra... | 2599e44cabc2fdac8d09ec820acfc101a1129b1e | 58,781 |
import asyncio
def cli(ffmpeg, source, format_img, output, extra):
"""FFMPEG capture frame as image."""
async def capture_image():
stream = ImageFrame(ffmpeg_bin=ffmpeg)
return await stream.get_image(
input_source=source, output_format=format_img, extra_cmd=extra
)
im... | 3b6125ff5d23dd90c83c2a4011e4e71975575cc7 | 58,782 |
def template_modify(id, attrs):
"""
Modifies a template, configuring it with the given attributes.
Parameter *tech*:
The parameter *tech* must be a string identifying one of the supported
template techs.
Parameter *name*:
The parameter *name* must be a string giving a name for the template.
Parameter *... | f40a811e1bf756561895e097a2c83ed3392e69ea | 58,783 |
def parse_args(args):
"""
Parse command line argument and return parsed Namespace object.
Args:
args (list): List of arguments.
Returns:
argparse.Namespace: Parsed arguments Namespace object.
"""
parser = ArgumentParser()
group = parser.add_mutually_exclusive_group(required... | 6d00210c961898bb9f268353be4ce417551cdc01 | 58,784 |
import copy
from functools import reduce
def combine(beds, beds_sorted=False, postmerge=True):
"""
Combine a list of bed files or BedTool objects into a single BedTool object.
Parameters
----------
beds : list
List of paths to bed files or BedTool objects.
beds_sorted : boolean
... | 08e6d3dc61547bf3a6563e24aafb52c28dbc91f1 | 58,785 |
def get_lldp_neighbors(device):
"""Get current LLDP neighbor information.
Return a two-level dictionary with the LLDP neighbor information..
The first-level key is the local port (aka interface) name.
The second-level keys are 'system' for the remote system name
and 'port' for the remote port ID. O... | 7719e3de069bf39533ee0c9fadbc2f94be69bb61 | 58,786 |
import logging
def extract_email_confirmation_link(payload: str) -> str:
"""Find email confirmation link inside the plain text email payload."""
start = payload.find("https")
next_word = payload.find(" ", start)
if next_word != -1:
activation_link = payload[start:next_word]
else:
n... | 7b7367a63ee00cc78994d210bf7fadea2c6505b8 | 58,787 |
def WLS_fit(x_data=None, y_data=None, errors=None, weight_data=None,
xaxis_name=None, yaxis_name=None, f_name=None, data_lines=None,
data_name=None, quiet=True):
"""
Takes a filename string or x and y data as input. We are fitting the
equation A_ij*x_j=b_i of the form b=C+Dx.... | 672f552a2e6ff5e941418b98f0d837b48b97d5fb | 58,788 |
from django.conf import settings
def get_default_cachefile_backend():
"""
Get the default file backend.
"""
return get_singleton(settings.IMAGEKIT_DEFAULT_CACHEFILE_BACKEND,
'file backend') | 2a4d8bd03057a303c26b525ef087587b99a96baf | 58,789 |
def _make_ipy(nets):
"""Given a list of 2-tuples of (address, netmask), returns a list of
IP address objects"""
return [IP(addr) for addr, mask in nets] | 42e92d0b3bde9a0a4d46dcdf9ab093290b17c9b1 | 58,790 |
def Uleb128Encode(value: int) -> bytes:
"""Encodes the argument int to ULEB128 format.
Argument:
value: Unsigned integer.
Returns:
The values encoded as ULEB128 bytes.
"""
if value < 0:
raise ValueError(f'Cannot uleb128 encode negative value ({value}).')
uleb128_bytes = []
done = False
wh... | 68e3d4fb12ce82d9fcb44b634bc8570eddde9078 | 58,791 |
def ex2d_subbundle(image, imageivar, patches, spots, corners, pixpad_frac, regularize, model, psferr):
"""Extract an entire subbundle of patches. The patches' output shape (nspec, nwave) must be aligned.
Args:
image: full image (not trimmed to a particular xy range)
imageivar: image inverse var... | 9930d383aa3eefb01cdaafb0fda9c1ff2e277e7c | 58,792 |
def batch_norm(x, name, _ops, is_train=True):
"""Batch normalization."""
with tf.variable_scope(name):
params_shape = [x.get_shape()[-1]]
beta = tf.get_variable('beta', params_shape, tf.float32,
initializer=tf.constant_initializer(0.0, tf.float32))
gamma =... | dbbd42dd6e290a9c2a970e39e03397946016105e | 58,793 |
import itertools
def unique_slug(model, slug, instance=None, reserved_slugs=[]):
"""
Return unique slug for passed django model class.
:param model: Django model class
:param slug: String. Slug for make unique
:param instance: Django model instance
:return: String
"""
orig, apdx = spli... | 7db45470673316ab01552a936ce8b07cb9d27346 | 58,794 |
def apply_transform(x,
transform_matrix,
channel_axis=0,
fill_mode='nearest',
cval=0.):
"""Apply the image transformation specified by a matrix.
# Arguments
x: 2D numpy array, single image.
transform_matrix: Numpy arra... | 209f614dd2ad751a3b9e5b67024398ce62871385 | 58,795 |
def process_results(results, l1_idxes, l2_idxes):
"""Expands the None elements in l2 and substitutes the real l1 indexes"""
return set(process_result(result, l1_idxes, l2_idxes) for result in results) - set() | 4c01b7f161dd866d4acf74c2fd3f953963bbc758 | 58,796 |
def _graph_minus(graph, nodeset):
"""
"""
newgraph = nx.DiGraph()
for (n1, n2) in graph.edges():
if n1 not in nodeset and n2 not in nodeset:
newgraph.add_edge(n1, n2)
for n in graph.nodes():
if n not in nodeset:
newgraph.add_node(n)
return newgraph | 30e994eb143855afcd5be9d4c0052fd60a9d4a21 | 58,797 |
import os
def get_startup_path():
"""Takes no arguments
Gives a list of full startup paths on a computer
eg:
[
"C:\\Users\\ABC\\AppData\\Roaming\\Microsoft\\Windows\\Start Menu\\Programs\\Startup\\",
"C:\\Users\\John PC\\AppData\\Roaming\\Microsoft\\Windows\\Start Menu\\Programs\\Startup\\",
"C:\\Users\\Monica... | 1bc38ac5f714178f1090d7b1b4adb8bdcc9d3404 | 58,798 |
def create_worker(*, db_session: Session = Depends(get_db), worker_in: WorkerCreate):
"""
Create a new worker contact.
"""
worker = get_by_code(db_session=db_session, code=worker_in.code)
if worker:
raise HTTPException(status_code=400, detail="The worker with this code already exists.")
... | e3f680b81e2b5180929250fd6820fc78b5978b38 | 58,799 |
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