content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def fft_fftn(*args, **kwargs):
"""Call the core fft library function fftn.
If the anfft library is used, enable 'measure' optimization.
"""
if using_fft_library == "anfft":
return fft.fftn(*args, measure=True, **kwargs)
else:
return fft.fftn(*args, **kwargs) | 804bd06b668edb98e646885561df833a4eedcdfa | 42,595 |
import psutil
def total() -> int:
"""
The total amount of space provided by the storage.
:return: The amount of storage space in Bytes.
"""
storage = psutil.disk_usage('/')
return storage.total | 26435b41c0fa894db2bb24c6a04b1e39ae35b386 | 42,597 |
import functools
import time
def timing(unit="millisecond", message="{func.__name__}() {time:.3f} {unit}"):
"""Measures the execution time of the function.
The value that can be used for specified the ``unit`` parameter are:
======== ================= ==================
Short Long ... | 73a7b2db1ebf01ee16a811f67ca6c10ca55b379d | 42,599 |
import copy
import six
def cloud_init_interface(name, vm_=None, **kwargs):
"""
Interface between salt.cloud.lxc driver and lxc.init
``vm_`` is a mapping of vm opts in the salt.cloud format
as documented for the lxc driver.
This can be used either:
- from the salt cloud driver
- because y... | d6ff5cae7655e6a30e1d6f1a95af948ab78aeebb | 42,601 |
def fdc_flux_and_wind(timestamp, sonicU, sonicV, sonicW, sonicT, heading,
rateX, rateY, rateZ, accX, accY, accZ, lat):
"""
Description:
Calculates the 3 L2 flux data products and the 3 L1 wind direction data products
from the FDCHP instrument. It is anticipated that wrappe... | 404034af0f70f7e9aeb49a3b7b00a6267bc3c546 | 42,602 |
def to_class_name(value):
"""Convert the current view's object to a usable class name.
Useful for outputting a css-class for targetting specific styles or
javascript functionality on a per-view basis, for example:
<div class="siteContainer {% if request.path == '/' %}home{% else %}{{ object|to_class_n... | 384f566d3808c19d7ba1357b7cddc69a92ca0b5a | 42,603 |
def _create_fold(X, ids):
"""Create folds from the data received.
Returns
-------
Data fold.
"""
if isinstance(X, list):
return [x[ids] for x in X]
elif isinstance(X, dict):
return {k: v[ids] for k, v in X.items()}
else:
return X[ids] | 8c1308913f470632657b909114806875a30fa17f | 42,605 |
def kill_background_grayscale(image, bg):
"""Make the background 0
Args:
image (3-D array): Numpy array (H, W, C)
bg (tuple): RGB code of background (R, G, B)
Returns:
image (2-D array): Binarized image of shape (H, W)
The background is 0 and everything else is 1
"""
... | 11314c91224b545365302d48bf124c40da1fd7fb | 42,606 |
def smooth(x: np.ndarray, window_len: int = None, window: str = "flat") -> np.ndarray:
"""Smooths the data using a window with requested size.
Code from https://scipy-cookbook.readthedocs.io/items/SignalSmooth.html
This method is based on the convolution of a scaled window with the signal.
The signal i... | a7be7852401828ada3012cdc2a1fb897e7c0a353 | 42,607 |
def average_inter_cluster_distance(data, cluster_labels, centroids):
"""
Computes the average inter-cluster distance i.e the average distance between all clusters.
We have assumed the distance between two clusters is the distance between the centroids of
said clusters
Args:
data (ndarray):... | 01a2348650dc656d1b293d9138a8450955e6a2d0 | 42,608 |
def is_model(val):
"""Returns true if the value represents a valid model.
This is a custom validator that Connexion uses to verify the model field
in request bodies.
Keyword arguments:
val -- the model value
"""
if val is None:
return True
model = Model()
allowed_models = ... | 96d8482b32b42cf510fe3dd0b49559885428bcbb | 42,611 |
def eval_one_epoch(sess, coord, model, cv_num_batch, epoch):
""" Cross validate the model on given data. """
d_counter = 0
g_counter = 0
cv_g_adv_loss = 0.0
cv_g_mse_loss = 0.0
cv_g_l2_loss = 0.0
cv_g_loss = 0.0
cv_d_rl_loss = 0.0
cv_d_fk_loss = 0.0
cv_d_loss = 0.0
# We run D... | 02d58f04c514dfd20a7be139a9daa0352c540945 | 42,612 |
def calculateCurvature(yRange, fit_cr):
"""
Returns the curvature of the polynomial `fit` on the y range `yRange`.
"""
return ((1 + (2*fit_cr[0]*yRange*ym_per_pix + fit_cr[1])**2)**1.5) / np.absolute(2*fit_cr[0]) | 6f949d46604287e0555f297ee4b777b0f132f594 | 42,614 |
def globals_videos_filter(find):
"""
SECTION : channel, videos, comment
DESCRIPTION : Find substrings from the channel title to narrow down the search results.
USAGE : Extraction of the comments takes less number of videos after the tile search.
"""
# ====================== Setup ===============... | 1dd65be99dc570bcf2b1be2b6c9f74e877b889f3 | 42,615 |
def Msg(schema, msg):
"""Report a user-friendly message if a schema fails to validate.
>>> validate = Schema(
... Msg(['one', 'two', int],
... 'should be one of "one", "two" or an integer'))
>>> validate(['three'])
Traceback (most recent call last):
...
InvalidList: should be on... | 16d1382ef0fe9d8c8476b8773d98405e89e75f85 | 42,616 |
def leaf_hyponyms(synset):
"""
Get the set of leaf nodes from the tree of hyponyms under the synset
"""
hyponyms = []
_recurse_leaf_hyponyms(synset, hyponyms)
return set(hyponyms) | fef038beadca56b8c1ff9af2313b669aff667276 | 42,617 |
def rand_sol(A, b):
"""Generate a random solution to the equation Ax=b."""
assert np.linalg.matrix_rank(A) <= len(b)
A_plus = np.linalg.pinv(A)
x = A_plus @ b
return x + (np.eye(x.shape[0]) - A_plus @ A) @ np.random.normal(size=x.shape) | df5256180f50bebe6fb9836247694e2a63c3d0b6 | 42,619 |
def get_fig_axes_lpr(dims=(8, 6), facecolor='#ffffff', gridcolor='#e0e0e0'):
"""
Get a matplotlib figure object, with lpr-themed face and gridcolors.
This theme is white background, gray gridlines, and .5 alpha.
"""
fig, ax = get_fig_axes(dims, facecolor, gridcolor)
fig.patch.set_alpha(0.5)
... | f6f096f24c54f4f522c84fbc9df910d9d5a7dd6d | 42,620 |
import functools
def read_dataset(cfg, file_pattern, training=False):
"""Reads a dataset, and handles repetition and shuffling.
Args:
file_read_func: Function to use in tf.contrib.data.parallel_interleave, to
read every individual file into a tf.data.Dataset.
file_pattern: A file patte... | 6db095958ac9d809fce32ca9a0c725e6169bcc2d | 42,621 |
def _add_option_if_supported(repository_ctx, cc, option):
"""Checks that `option` is supported by the C compiler. Doesn't %-escape the option."""
result = repository_ctx.execute([
cc,
option,
"-o",
"/dev/null",
"-c",
str(repository_ctx.path("tools/cpp/empty.cc"))
])
return [o... | 458c750790e1518b362d76299c5b1c23cde0fc17 | 42,622 |
from typing import Optional
from typing import Sequence
from typing import Mapping
def get_volume(filters: Optional[Sequence[pulumi.InputType['GetVolumeFilterArgs']]] = None,
most_recent: Optional[bool] = None,
tags: Optional[Mapping[str, str]] = None,
opts: Optional[pulum... | b70f9331ffea137144c57d6076c40bf26b7d11d4 | 42,623 |
import requests
async def getWikiSummary(message, title):
"""
Display the wikipedia article summary of the article with the given title
Parameters:
message - discord.client.message object being responded to
title - string of the wikipedia article title
"""
try:
query = (
... | a0443a1f7954b02c80ba9cc1de0de931cbc07af8 | 42,624 |
def tilted_L1_prox_1d(x, step, quantile=0.5):
"""
prox(x) = argmin_z rho_quantile(z) + (0.5 / step) * ||x - z||_2^2
See Lemma 1 of ADMM for High-Dimensional Sparse Penalized
Quantile Regression
"""
if step < np.finfo(float).eps:
return 0
t_a = quantile * step # tau / alpha
if x >... | 68597383b68c5cc8cf44aabe23fd6815d54bd2ec | 42,625 |
import pickle
import json
def set_task_params(data, workspace):
"""根据request设置task的参数。只有在task是TaskStatus.XINIT状态时才有效
Args:
data为dict,key包括
'tid'任务id, 'train'训练参数. 训练
参数和数据增强参数以pickle的形式保存在任务目录下的params.pkl文件
中。
"""
tid = data['tid']
train = data['train']
assert ... | 01b1ca6aaf981fb8835d0c45ad48d0602dda4185 | 42,627 |
import opcode
def extractPkScriptAddrs(version, pkScript, netParams):
"""
extractPkScriptAddrs returns the type of script, addresses and required
signatures associated with the passed PkScript. Note that it only works for
'standard' transaction script types. Any data such as public keys which are
... | db417d2dc486835b9510c106be2396de6d561665 | 42,628 |
from app import app
import re
def process_dollar(api_dict):
"""
输入：{'value': 'xfjc@zb', 'lx': "xfxs_cfxfbz", "name": "$index", "index": "xfjc"}
输出：{'value': 'xfjc@zb', 'lx': "xfxs_cfxfbz", "name": "xfjc", "index": "xfjc"}
"""
# 处理 $引用
# order = -$index name=$timetype name=$qh
# tra... | 54d28069fa87ce1a59e6b7ebf39fc47e2f93dd0c | 42,629 |
def dict_map(**fs):
"""Map especific elements in a dict.
Examples:
```pycon
>>> dict_map(a=int, b=str)(dict(a='1', b=123, c=True))
{'a': 1, 'b': '123', 'c': True}
>>>
```
"""
def _change_dict(d):
d = d.copy()
for k, f in fs.items():
if k in d:
... | ac67bf69df2aa1aead3da7443a83a09974f8a545 | 42,630 |
def Create(database_ref):
"""Create a database session."""
client = apis.GetClientInstance('spanner', 'v1')
msgs = apis.GetMessagesModule('spanner', 'v1')
req = msgs.SpannerProjectsInstancesDatabasesSessionsCreateRequest(
database=database_ref.RelativeName())
return client.projects_instances_databases_s... | 9b132156d2fc5b3c7081806373f32092cd2b268c | 42,632 |
def q12_jac(qs, epsilon):
"""The Jacobian of the mapping from q1, q2 to costheta, phi
"""
s2 = sinh(epsilon*qs[1])
c2 = cosh(epsilon*qs[1])
sp = sinh(epsilon*(qs[0] + qs[1]))
sm = sinh(epsilon*(qs[0] - qs[1]))
cp = cosh(epsilon*(qs[0] + qs[1]))
cm = cosh(epsilon*(qs[0] - qs[1]))
cs... | 484226905c6da48b5ae6ba8fa185bfb8a11e0292 | 42,633 |
from typing import Any
def lambda_handler(event: dict, context: Any):
"""
:param event: S3 notification event
:param context: Lambda Context runtime methods and attributes
"""
input_prefix = 'raw/'
input_suffix = '.csv'
output_prefix = 'transformed/'
output_suffix = '.snappy.parquet'
... | bbf03e278a5c908d8d903db7a7d867d34c5d3b31 | 42,634 |
def normalize_name(name):
"""
Given a key name (e.g. "LEFT CONTROL"), clean up the string and convert to
the canonical representation (e.g. "left ctrl") if one is known.
"""
if not name or not isinstance(name, basestring):
raise ValueError('Can only normalize non-empty string names. Unexpect... | bfb07c13c1cbe9ec92c43cb87edb19aab7135fc9 | 42,635 |
from typing import Callable
from typing import Any
import asyncio
def bmasync(func: Callable[[Any], Any]) -> Callable[[Any], Any]:
"""async function decorator"""
_setup_loop()
@wraps(func)
def wrapper(*args, **kwargs) -> Any:
return asyncio.ensure_future(func(*args, **kwargs))
return wra... | 88782e0b71d5aa19b741973d03f0c959723deb95 | 42,637 |
def goto_y(new_y):
"""
Move tool to the new_y position at speed_mm_s at high speed. Update curpos.y with new position.
If a failure is detected, sleep so the operator can examine the situation.
Since the loss of expected responses to commands indicates that the program does not know
the exact po... | de28ca9d2b495f5a7915b76c291a060c91292884 | 42,638 |
import copy
def _nested_loop_join_outer(g_list, arg_str, bindings, operands):
"""
E.g Join two Predicates P1(x,y) and P2(x,z,y) with groundings
(x1,y1) : g11 (ground object) and (x1,z1,y1) : g12
(x2,y2) : g21 (ground object) and (x2,z2,y2) : g22
(x1,y3) : g31 (ground object) an... | b54f45cd1bbc1f92dd85d25e57400bafe7a92a29 | 42,639 |
def StrContains(input_string, substring):
"""
Return True if the substring is contained in the concrete value of the input_string
otherwise false.
:param input_string: the string we want to check
:param substring: the string we want to check if it's contained inside the input_string
:return: Tr... | b04c22d567be6d1fce664f99719169b4585d75ea | 42,640 |
def rescale_frontoparallel(p_fp,box_fp,p_im):
"""
The fronto-parallel image region is rescaled to bring it in
the same approx. size as the target region size.
p_fp : nx2 coordinates of countour points in the fronto-parallel plane
box : 4x2 coordinates of bounding box of p_fp
... | 6a3f817146ad22c67e99b558c24358cc39f40c62 | 42,641 |
from typing import Iterable
def get_closest(iterable: Iterable, target):
"""Return the item in iterable that is closest to the target"""
if not iterable or target is None:
return None
return min(iterable, key=lambda item: abs(item - target)) | 9548954317e90574d7a6d232bc166bde2eea7863 | 42,642 |
def has_tf_tensor(input):
"""Check if a variable is a `tf.tensor` or nested list of `tf.tensor`s."""
return has_tensor(input, 'tf') | 171622c11ec9dd79176a8abd544cbf2dd0a309a4 | 42,643 |
from datetime import datetime
def datetime_from_isformat(date_string):
"""Construct a datetime from the output of datetime.isoformat()."""
if not isinstance(date_string, str):
raise TypeError('fromisoformat: argument must be str')
# Split this at the separator
dstr = date_string[0:10]
tst... | 46df2bbba6160f6931ed9d3fe122178be1498da0 | 42,644 |
def merge_two_reconstructions(r1, r2, config, threshold=1):
"""Merge two reconstructions with common tracks."""
t1, t2 = r1.points, r2.points
common_tracks = list(set(t1) & set(t2))
if len(common_tracks) > 6:
# Estimate similarity transform
p1 = np.array([t1[t].coordinates for t in com... | 2982da052533bb7bb822c0d313c952f6a21c340a | 42,645 |
def _reorder_for_extension_array_stack(arr, n_rows: int, n_columns: int):
"""
Re-orders the values when stacking multiple extension-arrays.
The indirect stacking method used for EAs requires a followup
take to get the order correct.
Parameters
----------
arr : ExtensionArray
n_rows, n_... | 7e7521137d62ed4d98f11aead367c0e00c8aad65 | 42,646 |
import scipy
def RemoveBackground(_tod, rms,x,y, sampleRate=50, cutoff=1.):
"""
Takes the TOD and set of indices describing the location of the source.
Fits polynomials beneath the source and then applies a low-pass filter to the full
data. It returns this low pass filtered data
"""
time = np.... | 796cf3361753823d4ae456d05c78af24cf6d4017 | 42,647 |
import collections
def utils_vlan_ports_list(duthosts, rand_one_dut_hostname, rand_selected_dut, tbinfo, ports_list):
"""
Get configured VLAN ports
"""
duthost = duthosts[rand_one_dut_hostname]
cfg_facts = duthost.config_facts(host=duthost.hostname, source="persistent")['ansible_facts']
mg_fac... | e9d0c5aa6fbfbfe9fe5ecce4e389c6f286ee875b | 42,648 |
def GetExtraVars():
"""Returns the captured variables by the function."""
g = tf.get_default_graph()
if isinstance(g, func_graph.FuncGraph):
return g.variable_captures
return function.get_extra_vars() | f460ef66895d07b28f18001d5602cd20c1e581f6 | 42,649 |
def get_log():
"""Get the filtered setAttr commands from the logs.
:return: List of all setAttr commands.
"""
with open(FILE_NAME, "r") as f:
attr_log = [line for line in f.read().splitlines()
if line.startswith("setAttr") and not "|" in line]
return attr_log | c0f55748dc6153b8beb7b6a9cd1cb19742354ab6 | 42,650 |
from typing import Callable
def on_epoch_complete(func: Callable) -> FunctionCallback:
"""Decorator for creating a callback from a function. The function will be
executed when the ``Events.EPOCH_COMPLETE`` is triggered. The function
should take :class:`argus.engine.State` as the first argument.
"""
... | 35603f263f65b99d05dfd54dcae06b208523922c | 42,651 |
def normalise(matrix):
"""Normalises the agents' cumulative utilities.
Parameters
----------
matrix : list of list of int
The cumulative utilities obtained by the agents throughout.
Returns
-------
list of list of int
The normalised cumulative utilities (i.e., utility share... | 594a46c9f1f741509ac56439779597545e63f25d | 42,652 |
def rgb_to_irg(rgb):
""" converts rgb to (mean of channels, red chromaticity, green chromaticity) """
irg = np.zeros_like(rgb)
s = np.sum(rgb, axis=-1) + 1e-6
irg[..., 2] = s / 3.0
irg[..., 0] = rgb[..., 0] / s
irg[..., 1] = rgb[..., 1] / s
return irg | 09a2e76c85c1f08d4db4332bdc32db7d94270710 | 42,653 |
def basic_nmt_bilstm_luong_att():
"""Hparams for LSTM with luong attention."""
hparams = base_nmt_bilstm(base_att(base_nmt()))
hparams.add_hparam("attention_gnmt", False)
hparams.add_hparam("attention_mechanism", "luong")
return hparams | 99c7e3fbd693043bffca3f6b577c15544d733511 | 42,654 |
def remove_projection_from_vector(v: Vector, w: Vector) -> Vector:
"""projects v onto w and subtracts the result from v"""
return subtract(v, project(v, w)) | 6bae31bb928bb6638334895a182ffab177921d31 | 42,655 |
def KK_RC77_fit(params, w, t_values):
"""
Kramers-Kronig Function: -RC-
Kristian B. Knudsen (kknu@berkeley.edu / kristianbknudsen@gmail.com)
"""
Rs = params["Rs"]
R1 = params["R1"]
R2 = params["R2"]
R3 = params["R3"]
R4 = params["R4"]
R5 = params["R5"]
R6 = params["R6"]
... | bf613e9cd228ceb42679a36e1225f72092dd898b | 42,656 |
import glob
def check_scope(
outdir: str,
logger: Logger = getLogger(__name__)
) -> int:
"""
Check if result is present in outdir.
Parameters
----------
outdir : str
The folder where results heve been written.
logger : Logger
The logger object.
Returns
-------... | 71462c2d2a892c36cc8cade32a94cceaac644665 | 42,657 |
def cvRetrieveFrame__Deprecated(*args):
"""cvRetrieveFrame__Deprecated(CvCapture capture, int streamIdx = 0)"""
return _highgui.cvRetrieveFrame__Deprecated(*args) | 58608bda7bf2cf8c75f5268586be20e3521a5a46 | 42,658 |
def main(global_config, **settings):
""" This function returns a Pyramid WSGI application.
"""
config = Configurator(settings=settings)
config.include('pyramid_chameleon')
config.add_static_view('static', 'static', cache_max_age=3600)
config.add_route('home', '/')
config.add_route('ups_view'... | e8380d1fb4df37ed26c9a24494571657a3cd3e10 | 42,659 |
def polynomial_graph_filter(coeff: np.array, laplacian: np.ndarray):
""" Return the laplacian polynomial with coefficients 'coeff'. """
power = np.eye(laplacian.shape[0])
filt = coeff[0] * power
for n, c in enumerate(coeff[1:]):
power = laplacian @ power
filt += c * power
return filt | b0276c1e392f258adc9479760a171e06378310aa | 42,660 |
def normalize(comic, face):
""" Normalize the images to [-1, 1]
"""
# YOUR CODE HERE
comic = (tf.cast(comic, tf.float32) /255.0 *2) -1
face = (tf.cast(face, tf.float32) /255.0 *2) -1
return comic, face | 6299e3640a623006d24720bbf371d7cdfd471df8 | 42,661 |
from typing import Tuple
from typing import Mapping
def label_array_3d() -> Tuple[np.ndarray, Mapping[Coordinates, ArrayLike[Number]]]:
"""Convenience method to return a 3D label array with corresponding physical coordinates."""
label_array = np.zeros((2, 5, 6), dtype=np.int32)
label_array[0, 0] = 1
l... | 052728d13210fe3b97717e5e38f42f1a3fd4ce78 | 42,665 |
def cmdline_from_pid(pid):
""" Fetch command line from a process id. """
try:
cmdline= open("/proc/%i/cmdline" %pid).readlines()[0]
return " ".join(cmdline.split("\x00")).rstrip()
except:
return "" | 61ca5cf3f109863e516a861f76dafd1d6e9dc749 | 42,666 |
def none_if_empty(tup):
"""Returns None if passed an empty tuple
This is helpful since a SimpleVar is actually an IndexedVar with
a single index of None rather than the more intuitive empty tuple.
"""
if tup is ():
return None
else:
return tup | 26ee7bb9720eaa532d901b9c1f6c4a0fb6f7a340 | 42,667 |
def print_melhor_time(funcao_atual_ou_futuro):
"""Função que imprirmi o melhor time.
Parameters
----------
funcao_atual_ou_futuro : list
Lista contendo um time de jogadores
Returns
-------
str
Texto organizando o time por posição
"""
gol, zag1, zag2, l... | 99c41728dea118cbcd8b6c61188f33f25a8663d1 | 42,668 |
def info_from_giphy(info, url):
"""Populate info object with info from *.giphy.com url."""
log("--- Detected giphy")
url = url.replace("media.giphy.com", "i.giphy.com")
url = url.replace("media1.giphy.com", "i.giphy.com")
url = url.replace("media2.giphy.com", "i.giphy.com")
url = url.replace("gi... | dc3ce8ba6614b0a9d300fd779e1bffa24db21cce | 42,669 |
def gcf():
"""获取当前Axis"""
global g_figure
return g_figure | d77418bfb11b8327cbbf4715ebe778c7b0458649 | 42,670 |
def postrefine_frames(i_iter, frames, frame_files, iparams, pres_set, miller_array_ref, avg_mode):
"""postrefine given frames and previous postrefinement results"""
miller_array_ref = miller_array_ref.generate_bijvoet_mates()
txt_merge_postref = 'Post-refinement cycle '+str(i_iter+1)+' ('+avg_mode+')\n'
txt_mer... | bb64a6e26ad4188d69eee027e1e19188db95d759 | 42,671 |
def backend2(threescale, backend_usages):
"""
Second bound backend
Should deliver slight performance improvement
"""
return threescale.backends.read(backend_usages[1]["backend_id"]) | 4111d6f536aaea2e407e8ce00db27612561d4156 | 42,672 |
from typing import List
from typing import Optional
import numpy
def gen_cr_from_active_set(program: MPQP_Program, active_set: List[int], check_full_dim=True) -> Optional[
CriticalRegion]:
"""
Builds the critical region of the given mpqp from the active set.
:param program: the MQMP_Program to be sol... | 40c12cb236b077385001b32acea311fa38473e06 | 42,673 |
def get():
"""Get peaks dataset.
"""
# Get hosp. capacity data
data = capacidad_hospitalaria.get()
# Do not consider rows with UCI status.
data = data[~data['estatus_capacidad_uci'].isnull()]
# Find peaks and its statistics
peaks = []
for hospital, hospital_data in data.groupby('n... | f807aca8a380c441b9fcd4b35eef95c6410f5d1e | 42,674 |
import re
def extract_group_to_individual_class(df, parts_group, df_body_parts):
"""
Extract multiple keys from dataframe and combine them in a trackedgroup
Inputs:
_______
df : dataframe
parts_group : string
df_body_parts: list of strings
"""
parts_group_label = list(filter(lambda... | 89bfe6cd5ab664bff4c04fc1df208354775572ba | 42,675 |
import functools
def without_apply_rng(f: TransformedT) -> TransformedT:
"""Removes the rng argument from the apply function.
This is a convenience wrapper that makes the ``rng`` argument to
``f.apply`` default to ``None``. This is useful when ``f`` doesn't actually
use random numbers as part of its computat... | e7fbc7c483602a35eb92218ce81592d3e78ac14d | 42,676 |
def has_events(doc, include_negatives=False):
"""
Parameters
----------
doc: Document
include_negatives: Count document as having events when at least one trigger is not an abstain
Returns
-------
Whether the document contains any (positive) events
"""
if "events" in doc and doc... | f477acc68b7e4f539984c7b1fb227300a08d6e9e | 42,677 |
def update_named_ports(mig, named_ports):
"""
Set the named ports on a Managed Instance Group.
Sort the existing named ports and new. If different, update.
This also implicitly allows for the removal of named_por
:param mig: Managed Instance Group Object from libcloud.
:type mig: :class: `GC... | 3a2bd1f591e32629b6257454a491173fb96824e2 | 42,678 |
from typing import List
def get_allowable_kernels() -> List[str]:
"""Get all allowable kernel families.
:return:
"""
return list(KERNEL_DICT.keys()) | 4824c23003e34f56d78473e2065fb03f6907655d | 42,679 |
def lrCostFunction(theta, X, y, lambda_):
"""Compute cost and gradient for logistic regression with regularization
J = lrCostFunction(theta, X, y, lambda) computes the cost of using
theta as the parameter for regularized logistic regression and the
gradient of the cost w.r.t. to the parameters.
:pa... | 3a1dcc2f1c8a739ef1ee7363dc13080fadc4d538 | 42,680 |
def coe2rv(coe, mu):
""" Convert from Keplerian to Cartesian.
Ref:
Vallado 4th Ed. pg 118
Args:
coe (numpy.array): 6x1 array with Keplerian orbital elements
1: semimajor axis (LU)
2: eccentricity
3: inclination (radia... | 6b6ee90eee920c1db75ed6deaa904f37b5397420 | 42,681 |
import scipy
def adjacency(dist, idx):
"""Return the adjacency matrix of a kNN graph."""
M, k = dist.shape
assert M, k == idx.shape
assert dist.min() >= 0
# Weights.
sigma_list = []
for i in range(len(dist)):
pos = 0
while dist[i, pos + 1] != np.inf:
pos += 1
... | 424cfddb3ebc7e48c3ffb660c50ddca4f31e0782 | 42,684 |
import ipaddress
def discover_webmention_endpoint(target: str) -> WebmentionDiscoveryResponse:
"""
Return the webmention endpoint for the given target.
:param target: The target to discover the webmention endpoint for.
:type target: str
:return: The discovered webmention endpoint.
:rtype: str... | 1777dd340389d70b9b05846b98c3aa89a008ec80 | 42,685 |
def get_fts_endpoint(endpoint_str, key=None):
"""
Make a request to the FTS API for the given endpoint_str, and optionally takes a key for additional json filtering.
Return the normalized json response as a pandas dataframe if successful, or None if not.
Example: endpoint_str = '/public/fts/flow?year=20... | b9ed08af1bd76d803dd606d116d701878c7ecfa6 | 42,687 |
def highest_paying_jobs(fse_client, plane_type, distance_limit=None, minimum_pay=0, top_n=5,
desired_trip_type=fse.TripTypes.TRIP_ONLY):
"""
For a type of aircraft find the top N which are rentable and have best $/NM jobs (accounting for capacity)
:param desired_trip_type: Set the t... | 533662fa9c968be69791b3edeee3d0f973a0379a | 42,689 |
def load_raf_db():
"""
load RAF-Db dataset
:param batch_size:
:return:
"""
print('loading RAF-Db dataset...')
train_dataset = RafFaceDataset(train=True, type='basic',
transform=transforms.Compose([
transforms.Resize(22... | f1a6f42d4383d1b9c9c7a2f466ba76bdbca2815f | 42,690 |
import decimal
def compute_tuple(lat, lon, resolution, slice):
"""Computes the tuple Geobox for a coordinate with a resolution and slice."""
decimal.getcontext().prec = resolution + 3
lat = decimal.Decimal(str(lat))
lon = decimal.Decimal(str(lon))
slice = decimal.Decimal(str(1.0 * slice * 10 ** -resolution)... | 95d10fd9fcc87f611234a335b32f689625969c79 | 42,691 |
def cast_as_int(input_val):
"""
Args:
input_val: A value of unknown type
Returns:
Int of the value, defaults to 0 if the value cannot be cast as an int.
Examples:
>>> cast_as_int('3')
3
>>> cast_as_int(3.55)
3
>>> cast_as_int('Three')
0
... | a7b6f3c03573c7db7d814f13e5493adaee3327e4 | 42,692 |
def get_encoder(layer, in_features, hidden_size, bidirectional=True):
"""Returns the requested layer."""
if layer == "lstm":
return LSTMEncoder(in_features, hidden_size,
bidirectional=bidirectional)
elif layer == "rcnn":
return RCNNEncoder(in_features, hidden_size,... | 106870327feae14e3c763ecdddfbe8dd2375666f | 42,693 |
from typing import Tuple
def sim_seird_decay(
s: float, e:float, i: float, r: float, d: float, beta: float, gamma: float, alpha: float, n_days: int,
decay1:float, decay2:float, decay3: float, decay4: float, end_delta: int, fatal: float
) -> Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]:
"""Sim... | 5175c7445ac3b95677b6283085f040df16470ec3 | 42,695 |
def toR3(Q):
"""
Transformation from Dual Quaternion to Euclidian Space Coordinates
Q: Symbolic Matrix (two - dimensional)
"""
z = np.array([[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, ... | e1a9b9baa888c656ffc1688d957133356005f9ef | 42,696 |
def discharge(da_x, da_y, feats, key='name', reverse=False):
"""
Wrapper function to compute discharge over line segments in a geopackage (opened with fiona)
:param da_x: DataArray - containing x-directional flow
:param da_y: DataArray - containing x-directional flow
:param feats: fiona features - ... | a7a3a61f51e2f1c0d4d8c336d8b9f9a8feee257a | 42,697 |
from orchestra import settings
def render_email_template(template, context):
"""
Renders an email template with this format:
{% if subject %}Subject{% endif %}
{% if message %}Email body{% endif %}
context must be a dict
"""
if not 'site' in context:
url = urlparse(setting... | 41ec8b4342494cf80e1a1629c140fe37bc31288c | 42,698 |
import re
def parse_BIO_tag(tag):
"""Parse given string as BIO tag.
The expected format is "[BIO]-TYPE", where TYPE is any non-empty
nonspace string, and the "-TYPE" part is optional.
Args:
tag (string): tag to parse.
Returns:
string pair: tag ("B", "I" or "O") and TYPE.
"""
... | 63b8eb2cb3ac183f668a0e9bf788fb7bd4e1ac88 | 42,700 |
from typing import Sequence
from typing import Mapping
from typing import Any
from datetime import datetime
def create_schema(
events: Sequence[Mapping[str, Any]],
links: Sequence[Mapping[str, str]],
tracking: Sequence[Mapping[str, Any]],
schema_id: str,
schema_name: str,
schema_dscpt: str,
) ... | fbd0712edc694b0b45f67c452dbd84cdacb7ed68 | 42,701 |
import math
def dadda_4to2_reduction(previous_bit_heap):
""" BitHeap Wallace reduction using 4:2 compressors """
next_bit_heap = BitHeap()
carry_bit_heap = BitHeap()
max_count = previous_bit_heap.max_count()
new_count = int(math.ceil(max_count / 2.0))
# each step reduce the height of the bit h... | 0256791f9be19af3c64eaa93036fb3cffbc5ac95 | 42,702 |
def modification_oeuvre(identifier):
"""
Route gérant la modification d'une oeuvre
:param id_publ: identifiant de l'oeuvre
:return : affichage du template modifier_oeuvre.html ou redirection
"""
# On renvoie sur la page html les éléments de l'objet oeuvre correspondant à l'identifiant de la route
if request.meth... | 68e808c41f12300b37fcd74746fd0dbfe88e9def | 42,703 |
def VisualizeAll3D(pts3D,ax,dataset_name, xlim, ylim, zlim):
"""
this function visualizes all 3D skeletons from one image
the form if pts3D is 4 by n numpy array, rows 0,1,2 are x,y,z, row3 is always 1
"""
bright_orange_cv2 = (255/255,79/255,0)
bright_blue_cv2 = (0, 229/255, 238/255)
... | 78eba088e513a3967dfe53a0ed02e3f218e9f640 | 42,704 |
def _contourf(darray,
x='lon',
y='lat',
transform=None,
# Facetgrids arguments
figsize=None,
size=None,
aspect=None,
ax=None,
row=None,
col=None,
col_wrap=None,
... | d6e1ed39851f00323fad0ea154cd29d62e7a4bad | 42,706 |
def chunk_textgrid_parser(textgrid_obj):
""" Parsses the Textgrid of One Chunk and Returns a List
Parameters
----------
textgrid_obj : praatio.Textgrid()
One Chunk's Textgrid Object imported using praatio
Returns
-------
textgrid_dict : dict
Dictionary of all of the Tiers f... | ab4d97da02ba0271e1549d4cb67a668e47008de6 | 42,708 |
def _set_values(loop_data):
"""Find rows corresponding to values in data
This is a private function, not meant for general use.
Input: dataframe
Output: dataframe
"""
# These are the indexes of all the data that are unassigned
value_indexes = loop_data.ix[(loop_data.loop==0)&... | 8b246756a12e48f39cd0d1c04c282cbc1a537e5b | 42,709 |
def abs(x):
"""Element-wise absolute value.
# Arguments
x: input tensor.
# Returns
A tensor.
"""
return KerasSymbol(mx.sym.abs(data=x.symbol)) | 9bc1f174aae297699f663aea4bb71a3954ec311f | 42,710 |
def build_module(
mod,
target,
params=None,
enable_acl=True,
tvm_ops=0,
acl_partitions=1,
disabled_ops=["concatenate"],
):
"""Build module with option to build for ACL."""
if isinstance(mod, tvm.relay.expr.Call):
mod = tvm.IRModule.from_expr(mod)
with tvm.transform.PassCo... | 82b6c732f59b759fea8f886f7f8b9399f0be7a27 | 42,711 |
def plus_frequente_occurence(vecteur, valeur_par_defaut=None):
"""Wrapper de la méthode first_valid_index d'un Pandas.Series.
Arguments d'entrée:
vecteur (pandas.Series)
valeur_par_defaut
Arguments de sortie:
(Python Object)
"""
return vecteur.value_counts(ascending=Fals... | e601ec1bf14a3668277767194615f98c28cae432 | 42,712 |
def _get_git_version():
"""Return version of git we use (might be bundled)"""
return __get_git_version(_git_runner) | 07d598f345cff674ad4a6d52f14ecbf46e0df0ed | 42,713 |
import rdflib as rl
from nidm.core import Constants
import json
def create_cde_graph(restrict_to=None):
"""Create an RDFLIB graph with the FSL CDEs
Any CDE that has a mapping will be mapped
"""
with open(cde_file, "r") as fp:
fsl_cde = json.load(fp)
fsl = Constants.FSL
nidm = Consta... | 00b8235cde1ab37f3c65586b1b4d3fb354e299ef | 42,714 |
def trajectory(ddir, file_prefix):
""" generate trajectory DataFile
"""
name = autofile.name.trajectory(file_prefix)
writer_ = autofile.write.trajectory
reader_ = _not_implemented
return factory.DataFile(ddir=ddir, name=name,
writer_=writer_, reader_=reader_) | f2a90ddcf96c040b0132b2f2b466089c443e36c4 | 42,715 |
import re
import base64
def _decode_base64(data, altchars=b'+/'):
"""Decode base64, padding being optional.
:param data: Base64 data as an ASCII byte string
:returns: The decoded byte string.
"""
data = re.sub(rb'[^a-zA-Z0-9%s]+' % altchars, b'', data) # normalize
missing_padding = len(data... | b5acd6beefd5183889391ee2e6c0b92352b77870 | 42,716 |
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