content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import warnings
def derivest(fun, x, par = None, **kwargs):
"""
Estimate the derivative of a function of one variable.
Arguments:
fun : Callable object with signature fun(x, *args) -> float, with x the
(scalar) argument, and args an optional list of parameters.
... | 7a66b5499ccb5e72125a2b323929c2196d747c48 | 56,979 |
def norm(vec):
""" Calculate norm of a vector or list thereof
Args:
vec (Vector or List[Vector]): vector(s) to compute norm of
Returns:
Scalar or List[Scalar]: norms
"""
if len(vec.shape) == 1: # it's just a single column vector
return np.sqrt(vec.dot(vec))
else: # tr... | c225467905ccd30b826d8ef5e0112bb23f106ec9 | 56,980 |
import PIL
def get_image_size(img_filename,img_directory_path):
"""
Return the size of the specified image
img_filename : the name of the image file
img_directory_path : the path to the directory where the image is
Return : (width, height)
width : the width in pixel of the image
height : t... | b46934940f1c62f9110efa219e042a39026db76c | 56,981 |
import torch
def train_deep_encoder(torch_dataset, model, optimizer, criterion, lr, n_epochs,
batchsize, verbose=False):
"""Train label encoder for categorical features
Parameters
----------
torch_dataset : Torch_Dataset
Dataset to feed the NN containing categorical fea... | c89aa6be474233d7521361190f7fdfc0b1cc29a3 | 56,982 |
def convert(s):
"""
Convert a probability string to a float number.
:param s: probability string.
:return: a float probability.
"""
try:
return float(s)
except ValueError:
num, denom = s.split('/')
return float(num) / float(denom) | 84333f21edfdcb2f3c917f23c23b9d399c5f6e56 | 56,983 |
def tree_ones_like(tree: Pytree) -> Pytree:
"""
Return a new tree with the same structure as t, but with all values set to
1.
"""
return jax.tree_util.tree_map(lambda x: jnp.ones_like(x), tree) | 3fa06e05111741eda6a5af8f558e2e6dce29755e | 56,984 |
def writeOctetStream(oStr, minValue = 0):
"""
@summary: write string as octet stream with per header
@param oStr: octet stream to convert
@param minValue: min length value
@return: per header follow by tuple of UInt8
"""
length = len(oStr)
mlength = minValue
if length - minValue... | 0eeb4578f51b4488e762d3f49b1d5c5accdd5b4d | 56,985 |
from typing import Sequence
def _find_fuzzy_line(
py_line_no: int,
py_by_line_no: Sequence[str],
cheetah_by_line_no: Sequence[str],
prefer_first: bool,
) -> int:
"""Attempt to fuzzily find matching lines."""
stripped_line = _fuzz_py_line(py_by_line_no[py_line_no])
cheetah_l... | 07e088df7ca73d52d47d37ff0971c43c496bc68a | 56,986 |
def S_vib(r,r0,B0,M,grun,T):
"""Vibrational entropy."""
x = debye_temp(r,r0,B0,M,grun) / T
return 3*kb*(4.0/3*debye_func(x) - np.log(1-np.exp(-x))) | 4fbbde4a33219947d523e2ab3d190a441a77333d | 56,988 |
def countExtn(fimg, extname='SCI'):
"""
Return the number of 'extname' extensions, defaulting to counting the
number of SCI extensions.
"""
closefits = False
if isinstance(fimg, string_types):
fimg = fits.open(fimg)
closefits = True
n = 0
for e in fimg:
if 'extn... | 44051dcef1bef901d4905d7b4b805dc9140a32c0 | 56,989 |
def tensor(dimensions):
"""
Create a tensor
:param dimensions: The list of dimensions
:return: A tensor
"""
global csp
check_engine()
csp.variables.append(csp.int(size=None, deep=dimensions))
return csp.variables[-1] | e96338ed9df016bb425642f4fd05de4775aa2d92 | 56,990 |
import random
def makeData(test=False):
""" Make the data and return a dict that contains the data and goal."""
# open the files, I already made them smaller; they contain 3000 pics each
Ball = np.load("../data/sBasketball.npy")
LightBulb = np.load("../data/sLight_bulb.npy")
Sun = np.load("../dat... | 427fca4cb41b776f4281dadda2971930214a2864 | 56,991 |
from typing import Union
from pathlib import Path
import re
def model_from_checkpoint(
filename: Union[Path, str],
model_name=None,
backbone_name=None,
classes=None,
is_coco=False,
img_size=None,
map_location=None,
strict=False,
revise_keys=[
(r"^module\.", ""),
],
... | 4296da4efc9499a8d10d09a5c0a2329bbc8cb54d | 56,992 |
def get_problem(pid=None, name=None, tid=None, show_disabled=True):
"""
Gets a single problem.
Args:
pid: The problem id
name: The name of the problem
show_disabled: Boolean indicating whether or not to show disabled problems. Defaults to True
Returns:
The problem dictio... | 5e781b867bd4ebc26d451e522262a954dd2ea27c | 56,993 |
def mock_boto_client_upload_success(*args, **kwargs):
"""
Mock boto client, so uploading always returns success
"""
return MagicMock() | 3fec23fa670a9066ae9fc881d0cf1d874f9cf480 | 56,994 |
def git_log_file(file_name):
"""要求文件路径是相对于git仓库更目录到文件完整路径"""
cmd = "git log -1 %s |grep Date" % file_name
return cmd | e7d0481d4ee7e1a68492df07ed9c35e95a87ab5c | 56,995 |
import json
def sfjson_loads(s):
"""Exception safe json.loads()"""
try:
return rlk_jsonloads(s)
except json.decoder.JSONDecodeError:
return {} | cbc7bc01d895cc0cce46b9c8d865eeee31442e3d | 56,996 |
import math
def calc_tols(polys_truth, tick_dist=5, max_d=250, rel_tol=0.25):
""" Calculate tolerance values for every GT baseline according to https://arxiv.org/pdf/1705.03311.pdf.
:param polys_truth: groundtruth baseline polygons (normalized)
:param tick_dist: desired distance of points of the baseline... | c26cecf5a8bdd2fbca85aa1d3bc6fce4593869e2 | 56,997 |
def to_terminal(group: list, outcomes: list) -> float:
"""
Create a terminal node value
:param group: group of samples with target as last element
:return: most representative class value for group
"""
outcomes = [row[-1] for row in group]
return [max(set(outcomes), key=outcomes.count), outc... | 886c397aaef82d1e38c371436c69b4152f6ce760 | 56,998 |
def _log_multivariate_normal_density_spherical(X, means, covars):
"""Compute Gaussian log-density at X for a spherical model."""
cv = covars.copy()
if covars.ndim == 1:
cv = cv[:, np.newaxis]
if cv.shape[1] == 1:
cv = np.tile(cv, (1, X.shape[-1]))
return _log_multivariate_normal_dens... | f74f18c76103bed534c1d98c4931dab9a2f12a72 | 56,999 |
from typing import Union
from pathlib import Path
from typing import Any
def load_from_cache(filepath: Union[Path, str]) -> Any:
"""Load a Python object pickled in a file located at `filepath`.
This function will raise a `FileNotFoundError` if the cache file doesn't
exist. It is the responsibility of the... | 79155d66afb6915bc8bbe4aeae0529615bb961e7 | 57,001 |
from typing import Coroutine
def _coro_get_awaitable_iter(o):
"""Interal helper function to get an awaitable iterator.
Corresponding impl.:
https://github.com/python/cpython/blob/3.5/Objects/genobject.c#L783-L823
"""
if isinstance(o, (Coroutine, CoroWrapper)) or gen_is_iterable_coroutine(o):
... | d47e3d1df45beb6ea2622ee90bdcbcebdc17e48b | 57,002 |
def kronecker_prod(x, y):
"""Returns the tensor / Kronecker product of 2 complex matrices, x and y.
:param x: A complex matrix.
:type x: torch.Tensor
:param y: A complex matrix.
:type y: torch.Tensor
:raises ValueError: If x and y do not have 3 dimensions or their first
... | 1b968d0eb9132419a476b0631f8be7184999b2d7 | 57,003 |
def _instance_data(data):
"""Returns input data with correct shape.
For any one-element array, i.e. array of shape (1, ) or (1, 1)
returns the single object inside it as a built-in type.
Parameters
----------
data : array_like or scalar or NotImplemented
Data to be converted. Could be... | 2bad0dae958f69a2221e4f11b7a0a3c1f4abb114 | 57,004 |
def get_koji_build_info_url_from_flask(id_: int = None,) -> str:
"""
provide absolute URL to p-s koji build logs view meant to set in a commit status
"""
with application.app_context():
return url_for(
"builds.koji_build_info",
id_=id_,
_external=True, # _ext... | 578e07300a47d73984a6cbce95b45b2ba26bf0b6 | 57,005 |
def remove_well_known_protos(filenames):
"""Remove "well-known" protos for objc.
On those platforms we get these for free as a part of the protobuf runtime.
We only need them for nanopb.
Args:
filenames: A list of filenames, each naming a .proto file.
Returns:
The filenames with members of google/p... | 9aa14b70e9251fe4d8ff42277be969d23f3ecdba | 57,006 |
def count_cigar_ops(cigar):
"""
For curious people: regexes are very slow for parsing CIGAR strings.
cigar: Unicode
"""
b = 0
num_m, num_i, num_d = 0, 0, 0
for i in range(len(cigar)):
if cigar[i] <= '9':
continue
# Check if there are no digits before the op char.... | 7efacce3a9b13249718ae140e79a5800b8682ff5 | 57,007 |
def get_dwtype_floor_area(dwtype_floorarea_by, dwtype_floorarea_ey, sim_param):
"""Calculates the floor area per dwelling type for every year
Parameters
----------
dwtype_distr_by : dict
Distribution of dwelling types base year
assump_dwtype_distr_ey : dict
Distribution of dwelling ... | 3b87386bbf5bf051aec5d43ebd47f3359885c8b4 | 57,008 |
def generate_field_shift(mask_image, vector_shift=(10, 10, 10), gaussian_smooth=5):
"""
Shifts (moves) a structure defined using a binary mask.
Args:
mask_image ([SimpleITK.Image]): The binary mask to shift.
vector_shift (tuple, optional): The displacement vector applied to the entire binar... | 1082bd23455d138ee69f3c2663d61cd346e1d917 | 57,009 |
def Credible_Set(position, pos_prob, threshold):
"""Function that finds the credible set according to a set threshold"""
total = sum(pos_prob)
bounds = threshold*total
#make into tuples
tuple_vec = []
for i in range(0, len(position)):
tup = (position[i], pos_prob[i])
tuple_vec.ap... | 01a587c0e7e6de995fd77c85f30011784018c383 | 57,010 |
def apply_size_filter(segmentation, input_, size_filter, exclude=None):
""" Apply size filter to segmentation.
Arguments:
segmentation [np.ndarray] - input segmentation.
input_ [np.ndarray] - input height map.
size_filter [int] - minimal segment size.
exclude [list] - list of se... | 8a5ee3f88c609cad09a5d179c24dfb0f77f7034e | 57,011 |
def load_Sentinel1(site, StartDate, EndDate):
"""
Function to retrieve and filter Sentinel-1 images
args:
aoi: region of interest
StartDate: Starting date to filter data
EndDate: End date to filter data
returns:
Image collection of Sentinel-1 images
"""
filtere... | 4887a2aabdfee9c689b774fef323a783ac50cd58 | 57,012 |
import logging
def recover_lost_connection(connection:obd.OBD, fast:bool, timeout:float)->obd.OBD:
"""
Recover lost connection and return a new working connection handle.
"""
logging.info("recovering lost connection")
connection.close()
sleep(CONNECTION_WAIT_DELAY)
connection = get_obd_con... | f68968193c80be49142e05de8aae02e3fc3e144e | 57,013 |
def get_ps_aux(connection_obj, search_string, device="dut"):
"""
API to get the ps aux output
Author: Chaitanya Vella (chaitanya-vella.kumar@broadcom.com)
:param conn_obj:
:param search_string:
:param device:
:return:
"""
command = "sudo ps aux"
if search_string:
command ... | d9f359f607a3b9f83fd8300874008ce35be2d750 | 57,014 |
def estimate_power(sim, test, auto=False):
"""Compute the mean of the estimated power of 5 replications over sample sizes."""
if test == "MaxMargin":
test = ["MaxMargin", "Dcorr"]
dim_range = find_dim_range(find_dim(sim))
est_power = np.array(
[
np.mean(
[
... | 67550a596285cff028712f9558ba8ec6e699a892 | 57,015 |
from pathlib import Path
import re
def listdir_with_only(path, names=None, ext=None):
"""Lists items in the directory conforming name regexes or extensions."""
dir_ = Path(path)
if not dir_.is_dir():
raise ValueError('path must be a directory.')
names = names if names else []
ext = ext if ... | 66aab005255f1a52c88577df02c53c2ab020469f | 57,016 |
def look_and_say(n):
"""Returns the nth term of the "look and say" sequence, which is defined as follows: beginning
with the term 1, each subsequent term visually describes the digits appearing in the previous term.
The first few terms are as follows:
1
11
21
1211
111221
Ex: the fo... | 5cb341d0bce8bc363b2b734e9da66a07b7da2434 | 57,017 |
def compound_alternative_forms(forms, sec_pos, forms_ind_or_con, forms_imp):
"""
compuond all alternative forms into a set
:return:
"""
if not forms:
if forms_imp:
forms = {sec_pos: forms_ind_or_con, 'imp': forms_imp}
else:
forms = {sec_pos: forms_ind_or_con}
... | 9b81aea6ef9edbe71560d2ca1d001a3971928c00 | 57,018 |
def hasher_unsigned(first_last_name: str, mask, init: int=HASH_INIT) -> int:
"""The hash function to hash the combined first + last name into a check value"""
h = init
for c in first_last_name:
h = (h * HASH_PRIME + ord(c)) & mask
return h | e0b4133762ad7fb41c3aac89bcfe3849ffcfb4f2 | 57,019 |
async def get_weakness_chart(type_name: str, generation: int = APP_DEFAULT_GEN):
"""This path returns the weaknesses of pokemon with type {type_name}."""
if not is_valid_type(type_name.capitalize(), generation=generation):
return {"error": "%s is not a valid type for generation %s" % (type_name, generat... | 2637488f22ca353427d5febbd60058041ef4132f | 57,020 |
def difficulty_rank(sentence: Text) -> int:
"""Calculates 'sentence' difficulty level. Returns Integer."""
chars = len(sentence)
words = len(word_tokenize(sentence))
return words + (chars//5) | 2b072b1518d850c2aa88198e20d331459753e278 | 57,021 |
def read_list(filename):
"""
Read a list from a JSON file.
:param filename: file name (string).
:return: list.
"""
_list = []
# open output file for reading
try:
with open(filename, 'r') as filehandle:
_list = load(filehandle)
except IOError as e:
logge... | f798234633e84a2082a0394e5480b2b355edc57c | 57,022 |
def _preprocess_hash(hash_str: str) -> SanitizedObservable:
"""Ensure Hash has minimum entropy (rather than a string of 'x')."""
str_entropy = entropy(hash_str)
if str_entropy < 3.0:
return SanitizedObservable(None, "String has too low an entropy to be a hash")
return SanitizedObservable(hash_st... | efe932c6df9b6e2ab566ba2029bf75bc7b6c6233 | 57,023 |
from typing import Union
def make_wordcloud(data: Union[dict, list, object, str, tuple],
opts: dict = None,
round: int = None
):
"""Make a word cloud.
Accepts data from a string, list of lists or tuples, a dict with
terms as keys and counts/frequenc... | 0a9b1b9dfe5311ae7a4edd0b909526cd0d4d9e13 | 57,025 |
def deleteDuplicates2(self, head: ListNode) -> ListNode:
"""
recursive
:param self:
:param head:
:return:
"""
if not head:
return head
if head.next and head.val == head.next.val:
while head.next and head.val == head.next.val:
head = head.next
return s... | 185c15ebe61dba769d8ef04aa1f5a28603b807d1 | 57,026 |
import random
def generate(length: int = 1) -> str:
"""Generates a random string of alphanumeric characters of the given length.
If no length is specified, a single character is returned.
On Python 3.5, this string is pseudo-randomly generated using
:py:mod:`random`. With 3.6 and later, the randomnes... | b04f0e448e4308601741121dd2892f990fe6ee64 | 57,027 |
def get_balance(user):
"""
Get UND Balance for a user
\b
:param user: The EOS user account name.
"""
cleos = get_cleos()
ret = cleos.run(['get', 'currency', 'balance', 'unif.token', user, 'UND'])
stripped = ret.stdout.strip()
if len(stripped) > 0:
my_balance = stripped
... | 8a2d2d863139ddbbe2ea61b8cc32a7f2ad282fa5 | 57,028 |
import requests
import json
def get_recommended_fees():
"""Retrieves current recommended fastest fees from bitcoinfees API in satoshis
"""
uri = 'https://bitcoinfees.earn.com/api/v1/fees/recommended'
response = requests.get(uri)
if response.status_code == 200:
fees = json.loads(response... | 1311f6de617caf1755c1588378d106b252f24c4e | 57,029 |
from typing import Tuple
import numpy
def clip_solution(
x: ndarray,
g: ndarray,
H: ndarray,
constraints: Tuple[ndarray, ndarray, ndarray, ndarray],
delta: float,
) -> Tuple[ndarray, bool, int]:
"""
x: S个N-dim的列向量
先 assert 它们都是单位向量
- 根据a = argmin f(a): a * gx + a^2 * 0.5xHx获得缩放尺度
... | 6444b5d7d913796b0c7a008a23a4e93210b2c6cd | 57,030 |
def property_node_uriref(property_name):
"""
Create a Survol property node.
"""
return rdflib.URIRef(LDT[property_name]) | 9994639f3883bfa8ccf97c15bfee6e2e7839f8d1 | 57,031 |
from typing import Tuple
from typing import Optional
from datetime import datetime
def try_to_format_date(might_be_date: str, date_format: str) -> Tuple[bool, Optional[date]]:
"""
return a datetime object is parsed
"""
try:
d = datetime.strptime(might_be_date, date_format)
return True, d
except ValueError:
... | 0bfa9be5d4b3a542f80682a53b9bd63d8efbeb51 | 57,032 |
def get_text_ls(filename):
"""Returns text of file as a list of strings"""
with open(filename, 'r') as f_in:
return f_in.readlines() | 5b788f38e683c82648224b7cc1b5875a0f602dce | 57,033 |
def rebuild_command(args):
"""Rebuilds a unicode command string prepared to be stored in a file
"""
return "%s\n" % (" ".join(args)).replace("\\", "\\\\") | 38643f1e2c7414683a4b2d89c517aa8c432bb9a3 | 57,034 |
import string
import secrets
def generate_secure_random_string(stringLength=10):
"""Generate a secure random string of letters, digits and special characters """
password_characters = string.ascii_letters + string.digits + string.punctuation
return ''.join(secrets.choice(password_characters) for i in rang... | 66a0d5863f1955b036e95479bbde40c6ee031437 | 57,035 |
def get_title(soup):
"""Given a soup, pick out a title"""
if soup.title:
return soup.title.string
if soup.h1:
return soup.h1.string
return '' | bcec80e0c6e5163ed90a4975b81a5c5a3d418132 | 57,036 |
def locate_peaks(data,sorted=False):
"""<numpy array> return all (index,value) pairs of the spectral peaks in the given data,
with the option of being sorted in descending order of data value"""
indices = filter(lambda j: data[j]>=max([data[j-1],data[j+1]]),range(1,len(data)-1))
result = zip(in... | 9f6e09e96d4490fc9e848e833f531883b844f41c | 57,037 |
def get_quality(all_qualities, pref=0, *args):
"""Gets the best, middle or lowest quality from
the Quality types given.
Args:
all_quality: iterable having all qualities
from best to lowest
*args: qualities to sort
pref: (0,1,2) int
... | 94d0aeb3d15f07e860d8779df0d181607ad2b38e | 57,038 |
def blur(rgb: np.ndarray, sigma: float) -> np.ndarray:
"""ぼかし。sigmaは0～1程度がよい？"""
rgb = cv2.GaussianBlur(rgb, (5, 5), sigma)
if rgb.ndim == 2:
rgb = np.expand_dims(rgb, axis=-1)
return rgb | a836903535a47e916590ba0685eb4158301ec962 | 57,039 |
import numpy
import pandas
def bin_library_quantification(quantification, quantification_name, bins=None):
"""Bin a library quantification file
default bins are [0.1, 1, 2, 5, 10, 50, 500, 5000, 1e9]
"""
if bins is None:
bins = DEFAULT_BINS
histogram = {}
for col in quantification:
... | 3f6923284a3e1ac771c82f35567536839548ddc2 | 57,040 |
def add_motif(genome, motif, index):
"""
Replace from the index to index+len(motif) in the genome
with the motif selected
"""
try:
# If this can be done is because index is an integer
index = index-len(motif)
return genome[:index]+motif+genome[index+len(motif):]
except:
... | b4fa3f957fc440a837a0f65fd431f1fc9119f077 | 57,041 |
from datetime import datetime
def get_yearly_mb_temp_prcp(gdir, time_range=None, year_range=None):
"""Read climate file and compute mass balance relevant climate parameters.
Those are the positive melting temperature at glacier terminus elevation
as energy input and the amount of solid precipitation onto ... | e4889eb7dcf629d700402135ce9c56bde60990c6 | 57,042 |
def get_nsx_resource_binding(client, name, id):
"""
:param client: nsx resource client
:param name: name of neutron object
:param id: id of neutron object
:return: return the nsx resource id
"""
nsx_name = utils.get_name_and_uuid(name, id)
nsx_resource = client.find_by_display_name(nsx_n... | 34d680fb2f54352ff10acdc9a04f833ab1ec09a9 | 57,043 |
def latest(name, minor_only=True, region=None, keyid=None, key=None, profile=None):
"""
Ensures the Elasticsearch domain specifies runs on the latest compatible
version of elasticsearch, upgrading it if it is not.
Note that this operation is blocking until the upgrade is complete.
:param str name:... | 5e7ac23220d92cf8c638bdd4ff89cca014059fec | 57,045 |
def annotate(query_text: str):
"""
annotate plain text with links to wikipedia pages
"""
plain_text = unquote(query_text)
response = model.annotate(plain_text)
return {
"request": query_text,
"response": response
} | f1862d697267075edff64dcea5cf196cc187a8c5 | 57,046 |
def collect_mysqldump_options(config, mysqldump, client):
"""Do intelligent collection of mysqldump options from the config
and add any additional options for further validation"""
options = []
if config['flush-logs']:
options.append('--flush-logs')
if config['flush-privileges']:
if ... | c1e1b45bf62b6b7c5c8701bb78cc198cde4c2a16 | 57,047 |
from .model import Model
from .detail.model_implementation import (
force_offset_model,
offset_model_jac,
offset_model_derivative,
offset_equation,
offset_equation_tex,
)
def force_offset(name):
"""Offset on the the model output.
Parameters
----------
name ... | 127aa452877e12d95850d98bbcc8416c15e2df10 | 57,048 |
def parse_user_agents(text):
"""."""
user_agents = ioc_grammars.user_agent.searchString(text)
return _listify(user_agents) | dede1b1b5ce99e663efc891466683e7ac13af9eb | 57,051 |
def featurizeDoc(doc):
"""
get key : value of metadata
"""
doc_features = []
for key in doc:
doc_features.append("{0}: {1}".format(key, doc[key]))
return doc_features | 7204fe1ded828112e69c120c944a5a16cc00f628 | 57,052 |
def get_lsr_pwaves(p_idx, lsr, post_stim=0.1, sr=1000., lat_th=0):
"""
Get indices of laser-triggered P-waves, spontaneous P-waves, successful
laser pulses, and failed laser pulses
@Params
p_idx - indices of P-waves
lsr - laser stimulation vector
post_stim - P-waves within $post_stim s of la... | 5e27bc106d649d4924e9ff5e2a6894ebb995f39d | 57,053 |
def get_flux(shot, time, phis=[222.5*deg2rad], labels=['TS']):
"""
"""
flux_grids = {}
flux = {}
for label,phi in zip(labels,phis):
flux_grids[label] = get_flux_grid(shot, time, phi=phi)
# Build the interpolation functions
for label in labels:
sample_coords = list(zi... | ef2d2d78f76ae3c0a61336b3b3ab038eb0fa204d | 57,054 |
def log_sum_exp(Z):
""" Compute log(\sum_i exp(Z_i)) for some array Z."""
return np.max(Z) + np.log(np.sum(np.exp(Z - np.max(Z)))) | 808329e0cfe14e124433cb0ad48eb4e4f78ebe14 | 57,055 |
def f(f_prob):
"""Deterministic forecast matching observation o."""
return f_prob.isel(member=0, drop=True) | 4163e9a40916bd6c1dbf00e6ed635cf2b78bcfc7 | 57,056 |
def setup(the_model, rolling_length, rolling_radius, vertical_load,
cycles=[1], speed=1.0, slip=0.0, rail_ext=0.0, num_cycles=1,
initial_depression=0.1, inbetween_step_time=1.e-6, inbetween_max_incr=100,
max_incr=1000, min_incr=100):
"""Setup the loading for the rollover simulation
... | b76efc23a43986fed7032ede6c707227d6de267c | 57,057 |
def wait_for_handshake(sim, ifname, basename="s_axi_control_", dataname="DATA"):
"""Wait for handshake (READY and VALID high at the same time) on given
interface on PyVerilator sim object.
Arguments:
- sim : PyVerilator sim object
- ifname : name for decoupled interface to wait for handshake on
... | 41f35cf15751fab44bca275cc2381e83e8908cd1 | 57,058 |
def mysin(x):
"""
My sine. Note that this is only accurate for small x.
"""
return x | 9589b1a3106b13ff230e614dcfc1477b422c9879 | 57,060 |
import logging
def get_module_logger(module_name, level=None):
"""
Get a logger for a specific module.
:param module_name: str
Logic module name.
:param level: int
:param sh_level: int
Stream handler log level.
:param log_format: str
:return: Logger
Logger object.
... | 0fd2c8be1463da464700964c2d5ad895a40f4a9c | 57,061 |
from typing import Optional
def get_transit_gateway_multicast_group_source(group_ip_address: Optional[str] = None,
network_interface_id: Optional[str] = None,
transit_gateway_multicast_domain_id: Optional[str] = None,
... | a834db7d20610870ae7c64d0bae139ed262f9341 | 57,062 |
import glob
def getAllOfAFile(file_dir, ext):
"""
Returns a list of all the files the direcotry with the specified file extenstion
:param file_dir: Directory to search
:param ext: The file extension (IE: ".py")
"""
return glob.glob(file_dir+"/*"+ext) | 876a4f4b30653bd08454db9ee425d56fe408623d | 57,063 |
def support_jsonp(f):
"""Wraps JSONified output for JSONP"""
@wraps(f)
def decorated_function(*args, **kwargs):
print('s')
callback = request.args.get('callback', False)
if callback:
content = str(callback) + '(' + str(f().data) + ')'
return current_app.respon... | 0ccfed2ef7702a0d364376e84b1eb3bd1c917d68 | 57,064 |
def topk(x_in, weights, num_top_k, verbose=False):
"""
x_in: BNK4
weights: BNK
num_top_k: int
"""
# rate
num_kp = tf.shape(weights)[2]
# num_top_divider = config.num_top_divider
# num_top_k = tf.to_int32(num_kp / num_top_divider)
B = tf.shape(weights)[0]
num_pairs = tf.shape(... | d90bedffb6d5b406ff0406eb0d367dab1760858a | 57,065 |
def accumulate_strings(values, name="strings"):
"""Accumulates strings into a vector.
Args:
values: A 1-d string tensor that contains values to add to the accumulator.
Returns:
A tuple (value_tensor, update_op).
"""
tf.assert_type(values, tf.string)
strings = tf.Variable(
name=name,
in... | 2b59fe76c6c74d378db2ebe3521c72c3ab3cbc2a | 57,066 |
from typing import List
import tqdm
def sliding_convert_examples_to_features(
examples: List[InputExample],
label_list: List[str],
max_length: int,
tokenizer: PreTrainedTokenizer,
) -> List[InputFeatures]:
"""
Loads a data file into a list of `InputFeatures`
"""
label_map = {label: i ... | 50d2cf1f7aa94801aa91d3c39226a7b230bbdf7d | 57,068 |
def http_date(epoch_seconds=None):
"""
Format the time to match the RFC1123 date format as specified by HTTP
RFC7231 section 7.1.1.1.
`epoch_seconds` is a floating point number expressed in seconds since the
epoch, in UTC - such as that outputted by time.time(). If set to None, it
defaults to t... | 91f6fb9cd8ca69959669661d2a4ffe2c2d1fbfa2 | 57,069 |
def rms_error(observed_values, estimated_values):
"""Root-mean-squared Error function."""
N_values = np.prod(observed_values.shape)
sse = ss_error(observed_values, estimated_values)
rmse = sse_to_rmse(sse, N_values)
return rmse | 7899752378a38796fcc7974c3ff5728dd3a8744d | 57,070 |
def parse(data, raw=False, quiet=False):
"""
Main text parsing function
Parameters:
data: (string) text data to parse
raw: (boolean) unprocessed output if True
quiet: (boolean) suppress warning messages if True
Returns:
List of Dictionaries. Raw ... | cac4424857335484e9ef9258d6742e487d5d40d0 | 57,071 |
def convert_onnx_sub(operator, device=None, extra_config={}):
"""
Converter for `ai.onnx.Sub`.
Args:
operator: An operator wrapping a `ai.onnx.Sub` model
device: String defining the type of device the converted operator should be run on
extra_config: Extra configuration used to sele... | 4cfb98714ec23e1ea3e70be1bdede0fb805afd63 | 57,072 |
def infer_tree_dp(model: PairWiseFiniteModel,
subtree_mp=False) -> InferenceResult:
"""Inference using DP on tree.
Performs dynamic programming on tree.
Applicable only if the interaction graph is a tree or a forest. Otherwise
throws exception.
:param model: Model for which to p... | e5cd16e5229846c2e038d47885fd5b6c477f20f6 | 57,073 |
from typing import Union
import platform
def get_platform_ca_certs() -> Union[bool, str]:
"""Get correct platform value for 'verify' parameter specifying CA certificates for TLS
@return: (bool or str) True for Windows, LINUX_CA_FILE for Linux"""
if platform.system() == 'Windows':
return True
... | 396edecf3e78c9e1171e4e08fc2cb1410e562f49 | 57,074 |
def set_weight_decay(model, weight_decay, skip_list={"decoder.attention.v", "rnn", "lstm", "gru", "embedding"}):
"""
Skip biases, BatchNorm parameters, rnns.
and attention projection layer v
"""
decay = []
no_decay = []
for name, param in model.named_parameters():
if not param.requir... | 7e2702d544497b03fffda4558f4aa5fcd2dd4f43 | 57,076 |
def extract_sample_info(sample_str):
"""Extract kit, sample, and technical replicate from sample_str.
Inputs -
sample_str - string from sample name
Returns -
tuple (kit, biological sample name, technical replicate)
"""
s = sample_str.replace('Ftube', '')
# The biological sample... | f67440528391e1c463bb940cad9e59e8e61aa4c3 | 57,077 |
def OffsetPosition(in_ra,in_dec,delta_ra,delta_dec):
"""
Offset a position given in decimal degrees.
Parameters
----------
in_ra: float
Initial RA (decimal degrees).
in_dec: float
Initial DEC (demical degrees).
delta_ra: float
Offset in RA (decimal degrees).
... | 7b027a2e0bf87dba9d1136e68af258b21223cedb | 57,078 |
def input_checks(catalogue, config, completeness):
""" Performs a basic set of input checks on the data
"""
if isinstance(completeness, np.ndarray):
# completeness table is a numpy array (i.e. [year, magnitude])
if np.shape(completeness)[1] != 2:
raise ValueError('Completeness T... | 4fb5e2a3241a2953ae2432add64dc69c1c2af4f6 | 57,079 |
def mad_outliers(x, cutoff=2, z_score_coeff=0.6745):
"""
Median Absolute Deviation outliers method.
It returns values as outliers if their residuals relative to the median exceeds 'n' times the ratio
to the MAD. The cutoff parameter represents this 'n' times quantity.
Main code: x_mad = np... | 0718a71d2fcde75356f016df4c56621534b379a7 | 57,080 |
def function_executor(type=None, mode=None, config=None, backend=None, storage=None,
runtime=None, runtime_memory=None, workers=None,
rabbitmq_monitor=None, remote_invoker=None, log_level=None):
"""
Generic function executor
"""
return FunctionExecutor(
... | 3b0fe732f0c87b13da44bae460d486608b685694 | 57,081 |
def create_mssql_adapter_with_integrated_security(
server: str,
db_name: str,
port: int = 1433,
encrypt: bool = False,
trust_certificate: bool = False,
) -> Adapter:
"""
Creates a SQL Alchemy database engine for Microsoft SQL Server, using
integrated security (aka SSPI, aka Windows domai... | 74f721a2a474dcbb92b742a5919b39a8473895f0 | 57,082 |
def datetime_isoformat(
tdt, format=DATE_EXT_COMPLETE + "T" + TIME_EXT_COMPLETE + TZ_EXT
):
"""
Format datetime strings.
This method is just a wrapper around isodate.isostrf.strftime and uses
Extended-Complete as default format.
"""
return strftime(tdt, format) | 269d675600a10ca75b754e2f4c9b92cf46f94ef5 | 57,083 |
def get_prime_factors(n):
"""
Find all prime factors in N and return them as a list.
"""
i = 2
factors = set()
while n > 1:
if n % i == 0:
factors.add(i)
n = n / i
else:
# only increment if we did not find a factor.
i = i + 1
i... | da6f13b1c910f4b90cf84bbb7cfe6ecc2b735863 | 57,084 |
import tqdm
from pathlib import Path
import concurrent
def download_list(uids, username, password, outdir, threads=1, show_progress=True):
"""Downloads a list of UIDS
Parameters
----------
uids:
A list of UIDs
username:
Username
password:
Password
outdir:
O... | 4a7b4f7724b41fb05580ebd2540c73b77b31d0ac | 57,085 |
def ping(): # pragma: no cover
"""
ignore connection validation with task server (celery)
"""
"""Simple task that just returns 'pong'."""
return "pong" | 9967a01f8c509e272e7215a843e513ce4dc9a2be | 57,086 |
def deep_index_items_by(items, key):
"""
Index a list of dicts by a given key.
Returns a dict of the arrays of items based on the value of `key` in each item.
"""
index = {}
for item in items or []:
try:
index_key = str((dpath.util.get(item, key) or "")).lower()
excep... | 1ce8788aab61401d3767c4d00e5cd1c477b1010f | 57,087 |
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