content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def download_from_url_if_not_in_cache(cloud_path: str, cache_dir: str = None):
"""
:param cloud_path: e.g., https://public-aristo-processes.s3-us-west-2.amazonaws.com/wiqa-model.tar.gz
:param to_dir: will be regarded as a cache.
:return: the path of file to which the file is downloaded.
"""
retu... | f0549e14b4219303ce48f992d684330338958370 | 3,648,800 |
from mne.viz.backends.renderer import _get_renderer
from mne_connectivity.base import BaseConnectivity
def plot_sensors_connectivity(info, con, picks=None,
cbar_label='Connectivity'):
"""Visualize the sensor connectivity in 3D.
Parameters
----------
info : dict | None
... | 3d236d8e8802f65c6388eeeafa327a252f9a75be | 3,648,801 |
import re
import json
def str_to_list_1(string):
"""
Parameters
----------
string : str
The str of first line in each sample of sample.txt
Returns
---------
final_list: lst
"""
final_list = []
li = re.findall(r'\[... | 92b4b11a339d2101a0af5408caee58cc9b9668a1 | 3,648,802 |
import torch
def batched_nms(boxes, scores, idxs, iou_threshold):
"""
Same as torchvision.ops.boxes.batched_nms, but safer.
"""
assert boxes.shape[-1] == 4
# TODO may need better strategy.
# Investigate after having a fully-cuda NMS op.
if len(boxes) < 40000:
return box_ops.batched... | 2800d7e488fd018350c98c846138675b2ef79090 | 3,648,803 |
def one_mini_batch(data, batch_indices):
"""
产生每一次的小的batch
:param data:
:param batch_indices:
:return:
"""
batch_data = {
"raw_data": [data[i] for i in batch_indices],
"word_id_list": [],
"label_vector": []
}
for data in batch_data["raw_data"]:
batch_d... | 2bbbd62a00422431bb3322ebfce26d7fe95edc09 | 3,648,804 |
def reset_password(reset_key):
"""Checks the reset key. If successful, displays the password reset prompt."""
username = auth_utils.check_reset_key(reset_key)
if username is None:
flask.flash(
'Invalid request. If your link has expired, then you will need to generate a new one. '
... | 4f8e30a1669837c31b3dc2f77df441c50c6439dd | 3,648,805 |
import scipy
def williams_diff_test(corr_func: SummaryCorrFunc,
X: np.ndarray,
Y: np.ndarray,
Z: np.ndarray,
two_tailed: bool) -> float:
"""
Calculates the p-value for the difference in correlations using Williams' Tes... | afda90296b544233ba34f3abdd87d72b360de832 | 3,648,806 |
from typing import Tuple
from typing import List
import sqlite3
def load_students(max_meeting_seconds: int) -> Tuple[List[str], int]:
"""Loads student names and wait times from the database."""
try:
with sqlite3.connect("students.db") as conn:
cursor = conn.cursor()
try:
... | b5b2a003216507df413cba7bea1171cd4667ee1f | 3,648,807 |
def coords(gd0, c, pad=True):
"""Return coordinates along one of the three axes.
Useful for plotting::
import matplotlib.pyplot as plt
plt.plot(gd.coords(0), data[:, 0, 0])
plt.show()
"""
L = np.linalg.norm(gd0.cell_cv[c])
N = gd0.N_c[c]
h = L / N
p = gd0.pbc_c[c] or... | 42541198f7a57fe6346b49eeaa4961336bd47c3a | 3,648,808 |
def get_associated_genes(variants_list: list) -> pd.DataFrame:
"""
Get variant gene information from BioMart.
More information on BioMart here: https://www.ensembl.org/info/data/biomart/index.html
:param variants_list: the list with variant ids.
:return: dataframe with variant and gene information
... | e267afb387496a99701872db94b46543e8c7406a | 3,648,809 |
def crc16(data) :
"""Compute CRC16 for bytes/bytearray/memoryview data"""
crc = _CRC16_START
for b in data :
crc = ((crc << 8) & 0xFFFF) ^ _CRC16_TABLE[(crc >> 8) ^ b]
return crc | ac7dc27ebc47d1bc444050b9adba81d0ac26167a | 3,648,810 |
def sigma(j: int, N: int = 1) -> np.ndarray:
"""
"""
s = [s0, s1, s2, s3]
dims = [4] * N
idx = np.unravel_index(j, dims)
return tensor(s[x] for x in idx) | c312222f5a037723f9b7920a971d93e36e3b3e4b | 3,648,811 |
def backcasting(
predictor,
window,
curves,
distance="RMS",
columns=("cases", "deaths"),
min_series=14,
step=1,
):
"""
Perform a backcasting performance analysis of the given model. For the sake
of this method, the model is just a function that receives an epidemic curve
data... | 0e0eafc06ab6ab4578be1b299fc70ae88796a72d | 3,648,812 |
from typing import Dict
from typing import Callable
from typing import List
def find_keys(d: Dict[K, V], predicate: Callable[[V], bool]) -> List[K]:
"""Find keys where values match predicate."""
return [k for k, v in d.items() if predicate(v)] | 68febd42bcd65ff52a786e4941dd5abf7d6a36ee | 3,648,813 |
def get_maya_property_name(prop, ignore_channel=False):
"""
Given a property, return a reasonable Maya name to use for it.
If ignore_channel is True, return the property for the whole vector, eg. return
'.translate' instead of '.translateX'.
This doesn't create or query anything. It just generates... | 591a49f054db3936d5a345919a2c69491b6f345e | 3,648,814 |
from typing import Concatenate
def model_deepFlavourReference_test(Inputs,nclasses,dropoutRate=0.1,momentum=0.6):
"""
reference 1x1 convolutional model for 'deepFlavour'
with recurrent layers and batch normalisation
standard dropout rate it 0.1
should be trained for flavour prediction first. after... | f92f977a5570e647bf394d450bd5a5dea918aeba | 3,648,815 |
import pathlib
def load_spyrelet_class(spyrelet_name, cfg):
"""Load a spyrelet class from a file (whose location is defined in cfg)"""
# discover spyrelet file and class
spyrelet_path_str, _ = get_config_param(cfg, [CONFIG_SPYRELETS_KEY, spyrelet_name, CONFIG_SPYRELETS_FILE_KEY])
spyrelet_class_name, ... | 877c8a626e7abe3e41146475dc030966c0b9f41e | 3,648,816 |
def see_documentation():
"""
This function redirects to the api documentation
"""
return jsonify({
'@context': responses.CONTEXT,
'rdfs:comment': 'See http://www.conceptnet.io for more information about ConceptNet, and http://api.conceptnet.io/docs for the API documentation.'
}) | 46de921c855797b1b7d231a4cb88c57026ece947 | 3,648,817 |
import time
def fit_imputer(df, tolerance=0.2, verbose=2, max_iter=20, nearest_features=20, imputation_order='ascending',
initial_strategy='most_frequent'):
"""
A function to train an IterativeImputer using machine learning
Args:
df: dataset to impute
tolerance: Tolerance ... | 9ca798c61ee555ad7d58da16660aeb12518c9b7e | 3,648,818 |
from django.shortcuts import render
def jhtml_render(request, file_type=None,json_file_url=None, html_template=None, json_render_dict=None, json_render_func=None, file_path=None, url_name=None, app_name=None):
"""
:param request:
:param file_type: json/temp_json
:param json_file_url:
:param html_... | b5d61d69a2c27d883aad60953c7366c6724b905e | 3,648,819 |
import sys
import os
import tempfile
def intermediate_dir():
""" Location in temp dir for storing .cpp and .o files during
builds.
"""
python_name = "python%d%d_intermediate" % tuple(sys.version_info[:2])
path = os.path.join(tempfile.gettempdir(),"%s"%whoami(),python_name)
if not os.path.... | 123f18287ae54bf257cbb74e0fe2d4bfca1df564 | 3,648,820 |
from PIL import Image
import os
def image(cache_path, width, height):
""" Generate a custom-sized sample image """
# Create unique path
size = (width, height)
filename = "%sx%s.png" % (width, height)
path = os.path.join(cache_path, filename)
# Check if image has already been created
if no... | df58a08937b5740fb5e4bc433f99c8de9b779c73 | 3,648,821 |
def truncate(text, length=30, indicator='...', whole_word=False):
"""Truncate ``text`` with replacement characters.
``length``
The maximum length of ``text`` before replacement
``indicator``
If ``text`` exceeds the ``length``, this string will replace
the end of the string
``who... | 82bf86407f57fc8f3524120c27c9231ad39ec2b2 | 3,648,822 |
def prefix_sums(A):
"""
This function calculate of sums of eements in given slice (contiguous segments of array).
Its main idea uses prefix sums which
are defined as the consecutive totals of the first 0, 1, 2, . . . , n elements of an array.
Args:
A: an array represents number of mushroom... | d61e49eb4a973f7718ccef864d8e09adf0e09ce2 | 3,648,823 |
from run4it.api.scripts import script_import_polar_exercices as script_func
def polar_import():
"""Import data from Polar and save as workouts"""
return script_func('polar_import') | 6a7075184e5c44a3092670fffc94360ef9a363c4 | 3,648,824 |
def dijkstra(G, Gextra, source, target_set, required_datarate, max_path_latency):
"""
:returns a successful path from source to a target from target_set with lowest path length
"""
q = DynamicPriorityQueue()
q.put((source, 0.0), priority=0.0)
marked = set()
parents = {source: None}
while not q.empty():
path_l... | 6a8ff88b7a56308e099d3f9e50c8645c3281a68e | 3,648,825 |
def build_single_class_dataset(name, class_ind=0, **dataset_params):
"""
wrapper for the base skeletor dataset loader `build_dataset`
this will take in the same arguments, but the loader will only iterate
over examples of the given class
I'm just going to overwrite standard cifar loading data for n... | c8d05ecc1292562e846bc62724a224c20746037a | 3,648,826 |
def gamma_trace(t):
"""
trace of a single line of gamma matrices
Examples
========
>>> from sympy.physics.hep.gamma_matrices import GammaMatrix as G, \
gamma_trace, LorentzIndex
>>> from sympy.tensor.tensor import tensor_indices, tensorhead
>>> p, q = tensorhead('p, q', [LorentzInd... | 8eb5bf4ba1f1d0e170a88a7b798b65273db8c1fd | 3,648,827 |
import copy
def preprocess(comment):
"""Pre-Process the comment"""
copy_comment = copy.deepcopy(comment)
# Replacing link
final_comment = replace_link(copy_comment)
nftokens = get_nf_tokens(comment)
return final_comment, nftokens | f7286d5ca3e668b70385cd72485bb81eb8f9eec1 | 3,648,828 |
def voc_label_indices(colormap, colormap2label):
"""Map a RGB color to a label."""
colormap = colormap.astype('int32')
idx = ((colormap[:, :, 0] * 256 + colormap[:, :, 1]) * 256
+ colormap[:, :, 2])
return colormap2label[idx] | 481eccab328da13c4a49b2cf69d8e0e1cf1e48ab | 3,648,829 |
def make_noisy_linear(w=1, std=1):
"""Factory for linear function <w,x> perturbed by gaussian noise N(0,std^2)"""
@Oracle
def noisy_linear(x):
return np.dot(x, w) + np.random.normal(scale=std)
return noisy_linear | 80ec4a37dbbe6dc837707fa9a6e93e27d8dea9b9 | 3,648,830 |
def distance(turtle, x, y=None):
"""Return the distance from the turtle to (x,y) in turtle step units.
Arguments:
turtle -- the turtle
x -- a number or a pair/vector of numbers or a turtle instance
y -- a number None None
call: distan... | f09b320c2b07374bebd2fd8c16084e7bf676523d | 3,648,831 |
import copy
def asy_ts(gp, anc_data):
""" Returns a recommendation via TS in the asyuential setting. """
anc_data = copy(anc_data)
# Always use a random optimiser with a vectorised sampler for TS.
if anc_data.acq_opt_method != 'rand':
anc_data.acq_opt_method = 'rand'
anc_data.max_evals = 4 * anc_data.... | 1514263314cd92b053bfcd655872a03785b47af0 | 3,648,832 |
import re
def checkParams(opts):
"""
检查模块名是否符合命名规则
检查目录是否存在
"""
res = {}
for opt, arg in opts:
if opt in ('--name'):
if re.match('^[a-zA-Z_][a-zA-Z0-9_]*$', arg):
res['name'] = arg
else:
return res
elif opt in ('--dir'):
... | 5b8306a1c9805786e4a98509dcea3af59ffd04d1 | 3,648,833 |
def nms(bboxes, iou_threshold, sigma=0.3, method='nms'):
"""
Note: soft-nms, https://arxiv.org/pdf/1704.04503.pdf
https://github.com/bharatsingh430/soft-nms
"""
best_bboxes = []
while len(bboxes) > 0:
max_ind = np.argmax(bboxes[:, 4])
best_bbox = bboxes[max_ind]
be... | 10f3f65bd00599aa77f2d832754febfeeed7ca55 | 3,648,834 |
def smart_cast(value):
"""Intelligently cast the given value to a Python data type.
:param value: The value to be cast.
:type value: str
"""
# Handle integers first because is_bool() may interpret 0s and 1s as booleans.
if is_integer(value, cast=True):
return int(value)
elif is_flo... | 73676278e8c8bf54536fd3c9982cad7f6064cb75 | 3,648,835 |
from rdkit.Chem import Draw
from rdkit.Chem import AllChem
from IPython.display import SVG, display
import io
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
def _draw_mol_with_property( mol, property, **kwargs ):
"""
http://rdkit.blogspot.com/2015/02/new-drawing-code.html
Parameters
... | 5f680f750b01d2f178df125dbaff6f737bbbcfc8 | 3,648,836 |
from typing import List
from typing import Dict
import math
def find_host_biz_relations(bk_host_ids: List[int]) -> Dict:
"""
查询主机所属拓扑关系
:param bk_host_ids: 主机ID列表 [1, 2, 3]
:return: 主机所属拓扑关系
[
{
"bk_biz_id": 3,
"bk_host_id": 3,
"bk_module_id": 59,
"b... | 9cd9891a97b5ad3db88a0e8a631775b1dc8c24c7 | 3,648,837 |
def atom_to_atom_line(atom):
"""Takes an atomium atom and turns it into a .cif ATOM record.
:param Atom atom: the atom to read.
:rtype: ``str``"""
name = get_atom_name(atom)
res_num, res_insert = split_residue_id(atom)
return "ATOM {} {} {} . {} {} . {} {} {} {} {} 1 {} {} {} {} {} {} 1".forma... | 30e9f9191947b23dffd9e3f6d63f697de325e5f0 | 3,648,838 |
from .....main import _get_bot
from typing import Union
from typing import Optional
async def edit_chat_invite_link(
token: str = TOKEN_VALIDATION,
chat_id: Union[int, str] = Query(..., description='Unique identifier for the target chat or username of the target channel (in the format @channelusername)'),
... | 7c83316e0e86eb223b40ed9bf69126d79a4651b4 | 3,648,839 |
def post_live_migrate_at_source(adapter, host_uuid, instance, vif):
"""Performs the post live migrate on the source host.
:param adapter: The pypowervm adapter.
:param host_uuid: The host UUID for the PowerVM API.
:param instance: The nova instance object.
:param vif: The virtual interface of the i... | 0a4165abe0373a96b2b222d4eaa9316649d607b2 | 3,648,840 |
import re
def conv2date(dtstr,tstart=None):
"""Convert epoch string or time interval to matplotlib date"""
#we possibly have a timeinterval as input so wrap in exception block
m=re.search("([\+\-])([0-9]+)([dm])",dtstr)
if m:
if m.group(3) == "m":
dt=30.5*float(m.group(2)) #s... | b848f45c04bf9ef77fa3af395afb992f6302fb4f | 3,648,841 |
def resnet18(pretrained=False, **kwargs):
"""Constructs a ResNet-18 model.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet
"""
model = ResNet(MaskedBasicblock, [2, 2, 2, 2], **kwargs)
if pretrained:
model.load_state_dict(model_zoo.load_url(model_urls['resnet... | 94e339a390723e7dbdec4d95b7f4bb3600faae1f | 3,648,842 |
def logioinfo(func):
"""
This function is to add IO information
"""
def write(exec_info):
"""
This function is to add bucket and object Io information
Parameters:
exec_info
Returns:
write
"""
log.info('in ... | ef8f1361e87cd246353debab11d7ad5c97f62058 | 3,648,843 |
import pytz
def weather(api_token, city, start, end):
"""
Returns an hourly report of cloud cover, wind and temperature data for the
given city. The report is always in full days. Timestamps are in UTC.
Start and end dates are interpreted as UTC.
"""
a = Astral()
city = a[city]
# hour... | 2d8457cc8388613825dad54686988194eed85b2b | 3,648,844 |
from skimage.transform import iradon
def skimage_radon_back_projector(sinogram, geometry, range, out=None):
"""Calculate forward projection using skimage.
Parameters
----------
sinogram : `DiscreteLpElement`
Sinogram (projections) to backproject.
geometry : `Geometry`
The projecti... | 8158569eca46907091bfbca6aba57cd2a6afa6bf | 3,648,845 |
def get_segment_hosts(master_port):
"""
"""
gparray = GpArray.initFromCatalog( dbconn.DbURL(port=master_port), utility=True )
segments = GpArray.getSegmentsByHostName( gparray.getDbList() )
return segments.keys() | 565921e4b7d46ec357666d50dee7dcdb7127759e | 3,648,846 |
from typing import List
from typing import Dict
from typing import Any
def get_saved_albums(sp: Spotify) -> List[Dict[str, Any]]:
"""Returns the list of albums saved in user library"""
albums = [] # type: List[Dict[str, Any]]
results = sp.current_user_saved_albums(limit=50)
albums.extend(results["ite... | 525074d9f957b71c0b355d3d343e088d29792363 | 3,648,847 |
def createMergerCatalog(hd_obj, obj_conditions, cosmo, time_since_merger=1):
"""
Function to create Major Merger (MM) catalog
@hd_obj :: header file for the object of interest
@obj_conditions :: prior conditions to define the object sample
@cosmo :: cosmology used in the notebook (Flat Lambda CDM)
... | ee0ac59fe1a8fa9a40a934caa32ff53cd171f3dc | 3,648,848 |
import subprocess
def get_test_subprocess(cmd=None, **kwds):
"""Return a subprocess.Popen object to use in tests.
By default stdout and stderr are redirected to /dev/null and the
python interpreter is used as test process.
It also attemps to make sure the process is in a reasonably
initialized sta... | 85d62aeb20b56c604199fc3c2812cf366e7fa1ee | 3,648,849 |
from typing import Union
from typing import Dict
from typing import List
from typing import Any
import json
def make_response(code: int, body: Union[Dict, List]) -> Dict[str, Any]:
"""Build a response.
Args:
code: HTTP response code.
body: Python dictionary or list to jsonify.
Returns:
... | bae0a8720085bdf3734724b00df8d856e362602a | 3,648,850 |
def sql2dict(queryset):
"""Return a SQL alchemy style query result into a list of dicts.
Args:
queryset (object): The SQL alchemy result.
Returns:
result (list): The converted query set.
"""
if queryset is None:
return []
return [record.__dict__ for record in queryset] | c55fa18773142cca591aac8ed6bdc37657569961 | 3,648,851 |
from typing import OrderedDict
import itertools
def build_DNN(input_dim, hidden_dim, num_hidden, embedding_dim=1, vocab_size=20,output_dim=1 ,activation_func=nn.Sigmoid):
""" Function that automates the generation of a DNN by providing a template for
pytorch's nn.Sequential class
Parameters
--------... | 5b7476b20aacb0d6b0f78da6f97f9a1d3262d43c | 3,648,852 |
def float_to_bin(x, m_digits:int):
"""
Convert a number x in range [0,1] to a binary string truncated to length m_digits
arguments:
x: float
m_digits: integer
return:
x_bin: string
The decimal representation of digits AFTER '0.'
Ex:
Input 0.75... | f95e72d9449b66681575b230f6c858e8b3833cc2 | 3,648,853 |
from typing import Callable
from typing import List
def apply(func: Callable, args: List):
"""Call `func` expanding `args`.
Example:
>>> def add(a, b):
>>> return a + b
>>> apply(add, [1, 2])
3
"""
return func(*args) | f866087d07c7c036b405f8d97ba993f12c392d76 | 3,648,854 |
def random_energy_model_create(db: Session) -> EnergyModelCreate:
"""
Generate a random energy model create request.
"""
dataset = fixed_existing_dataset(db)
component_1 = fixed_existing_energy_source(db)
return EnergyModelCreate(name=f"EnergyModel-{dataset.id}-" + random_lower_string(),
... | db5ac3decf6094bef271005732fd9b78a3870be3 | 3,648,855 |
def _indices_3d(f, y, x, py, px, t, nt, interp=True):
"""Compute time and space indices of parametric line in ``f`` function
Parameters
----------
f : :obj:`func`
Function computing values of parametric line for stacking
y : :obj:`np.ndarray`
Slow spatial axis (must be symmetrical a... | 43a1f8761fb4e2ad32225ebf9e96f0aa2cdf0afd | 3,648,856 |
def indicators_listing(request,option=None):
"""
Generate Indicator Listing template.
:param request: Django request object (Required)
:type request: :class:`django.http.HttpRequest`
:param option: Whether or not we should generate a CSV (yes if option is "csv")
:type option: str
:returns: ... | 772ec90af7b104b4a9712742064d3aba758aab6f | 3,648,857 |
def parse_sensor(csv):
"""
Ideally, the output from the sensors would be standardized and a simple
list to dict conversion would be possible. However, there are differences
between the sensors that need to be accommodated.
"""
lst = csv.split(";")
sensor = lst[SENSOR_QUANTITY]
if sen... | 6673e12403090d130f0ac5590097794ae8f191aa | 3,648,858 |
from datetime import datetime
def samiljeol(year=None):
"""
:parm year: int
:return: Independence Movement Day of Korea
"""
year = year if year else _year
return datetime.date(int(year), 3, 1) | 6ae717e12aa3dc5bd1d273e240294d2bc6a294ff | 3,648,859 |
def get_entries(xml_file):
"""Get every entry from a given XML file: the words, their roots
and their definitions.
"""
tree = get_tree(xml_file)
# each <drv> is one entry
entries = []
for drv_node in tree.iter('drv'):
node_words = get_words_from_kap(drv_node.find('kap'))
ro... | f9647cf79be68afa03908433890e1abbff9284bf | 3,648,860 |
def comoving_radial_distance(cosmo, a, status):
"""comoving_radial_distance(cosmology cosmo, double a, int * status) -> double"""
return _ccllib.comoving_radial_distance(cosmo, a, status) | 72066b4b51a7728608d52c920bade33ecef0b920 | 3,648,861 |
import dateutil
def make_legacy_date(date_str):
"""
Converts a date from the UTC format (used in api v3) to the form in api v2.
:param date_str:
:return:
"""
date_obj = dateutil.parser.parse(date_str)
try:
return date_obj.strftime('%Y%m%d')
except:
return None | 5a2ed526c7bd0dae5a73a55c93d14ec158a0e6df | 3,648,862 |
import torch
def l2_mat(b1, b2):
"""b1 has size B x M x D, b2 has size b2 B x N x D, res has size P x M x N
Args:
b1:
b2:
Returns:
"""
b1_norm = b1.pow(2).sum(dim=-1, keepdim=True)
b2_norm = b2.pow(2).sum(dim=-1, keepdim=True)
res = torch.addmm(b2_norm.transpose(-2, -1),... | ad254c2c11dccab5dd97c7e72ef3b00c7b6143fb | 3,648,863 |
import fnmatch
import os
def find_files(base, pattern):
"""Return list of files matching pattern in base folder."""
return [n for n in fnmatch.filter(os.listdir(base), pattern) if os.path.isfile(os.path.join(base, n))] | e84dd19e6746d92de1852f162eaa997734ac245c | 3,648,864 |
def take_rich(frame, n, offset=0, columns=None):
"""
A take operation which also returns the schema, offset and count of the data.
Not part of the "public" API, but used by other operations like inspect
"""
if n is None:
data = frame.collect(columns)
else:
data = frame.take(n, of... | de3514d64a74addae76628c37f679693ba68550b | 3,648,865 |
def default_name(class_or_fn):
"""Default name for a class or function.
This is the naming function by default for registries expecting classes or
functions.
Args:
class_or_fn: class or function to be named.
Returns:
Default name for registration.
"""
return camelcase_to_s... | 1ed04a87916ae5d0fa9f1173d5fb9f97c26b32e9 | 3,648,866 |
import pathlib
import shutil
import random
import logging
def main(config_file: str, log_level: int) -> int:
"""Main function
Parameters
----------
TODO
"""
coloredlogs.install(
level=log_level * 10,
logger=LOG,
milliseconds=True,
)
# Parse config file
con... | 8d176c597f28588a54c2e24016be0e2caf048c0d | 3,648,867 |
def get_ip_result_by_input_method(
set_input_method,
module_input_method,
var_ip_selector,
username,
bk_biz_id,
bk_supplier_account,
filter_set,
filter_service_template,
produce_method,
var_module_name="",
):
"""
@summary 根据输入方式获取ip
@param var_module_name: 模块属性名
@... | aa12179a5706f213894962579e5d0be30209f14e | 3,648,868 |
from typing import cast
from typing import Sized
def function_size(container: Result) -> Result:
"""
The size() function applied to a Value. Delegate to Python's :py:func:`len`.
(string) -> int string length
(bytes) -> int bytes length
(list(A)) -> int list size
(map(A, B)) -> int map size
... | 33470b886ba2a632c98d2de8342e8a793a5b1ac4 | 3,648,869 |
def cluster_from_metis_config(config):
"""
Construct a Cluster from a metis-flavored object.
Args:
config (dict): Metis data.
Returns:
Cluster
"""
curie_settings = curie_server_state_pb2.CurieSettings()
cluster = curie_settings.Cluster()
cluster.cluster_name = config["cluster.name"]
log.info... | 3c5abca482d89e7142129b2fb76accb2fc5aa5f2 | 3,648,870 |
def _single_style_loss(a, g):
""" Calculate the style loss at a certain layer
Inputs:
a is the feature representation of the real image
g is the feature representation of the generated image
Output:
the style loss at a certain layer (which is E_l in the paper)
"""
N = a.shape... | f19d8fcfc467d4760a44d2cdb872791cc2ad2ffe | 3,648,871 |
def hyp_dist_o(x):
"""
Computes hyperbolic distance between x and the origin.
"""
x_norm = x.norm(dim=-1, p=2, keepdim=True)
return 2 * arctanh(x_norm) | 8864d8625798a8b41e2dd645cfe11e8d73d6d9d3 | 3,648,872 |
def check_image(url):
"""A little wrapper for the :func:`get_image_info` function.
If the image doesn't match the ``flaskbb_config`` settings it will
return a tuple with a the first value is the custom error message and
the second value ``False`` for not passing the check.
If the check is successful... | d0587dc987a079d49eb9a863d5203908acab41c4 | 3,648,873 |
def preprocess(dataset_file_path, len_bound, num_examples = None, reverse = False):
"""
It reads the required files, creates input output pairs.
"""
min_sentence_length = len_bound[0]
max_sentence_length = len_bound[1]
lines = open(str(dataset_file_path), encoding='utf-8', errors = 'ignore'... | 5849c1957ccab997bcf835bce2fec71b0a93cd6d | 3,648,874 |
def read_transcriptome(transcriptome):
"""
Parse transcriptome as a dictionary.
"""
result_dict = {}
for sequence in SeqIO.parse(transcriptome, 'fasta'):
result_dict[sequence.name] = sequence.seq
return result_dict | 008df223435de465cd6f36978305ca95bb15b270 | 3,648,875 |
from re import X
def magnus(w, n):
"""
The 'Magnus' map
"""
expr = w.subs(x,1+eps*X).subs(y,1+eps*Y) - 1
return limit(expr / eps**n, eps, 0) | 7faf1935b9348f41e6968b7da5fa59576ad874a5 | 3,648,876 |
import logging
def initCmdLineParser():
"""
Initiate the optparse object, add all the groups and general command line flags
and returns the optparse object
"""
# Init parser and all general flags
logging.debug("initiating command line option parser")
usage = "usage: %prog [options]"
p... | 0a311909888b441bf6dfc559df6f31ea5a5c9c5a | 3,648,877 |
def translate_node_coordinates(wn, offset_x, offset_y):
"""
Translate node coordinates
Parameters
-----------
wn: wntr WaterNetworkModel
A WaterNetworkModel object
offset_x: tuple
Translation in the x direction, in meters
offset_y: float
Translation in ... | da886a624b9038296d47ffe85a04e62f71f49def | 3,648,878 |
def get_demo_board():
"""Get a demo board"""
demo_board_id = 1
query = Board.query.filter(Board.id == demo_board_id)
query = query.options(joinedload(Board.tasks)).options(raiseload('*'))
board = query.one()
return BoardDetailsSchema().dump(board).data | 69b20a6c7446dc3813ec8d8c454a7a35443bf103 | 3,648,879 |
def cool_KI(n, T):
"""
Returns Koyama & Inutsuka (2002) cooling function
"""
return 2e-19*n*n*(np.exp(-1.184e5/(T + 1e3)) +
1.4e-9*T**0.5*np.exp(-92.0/T)) | 707b9e8d42e4d1b7db069c05b3b74e3f0b37f2e6 | 3,648,880 |
def main(args):
"""
main entry point for the manifest CLI
"""
if len(args) < 2:
return usage("Command expected")
command = args[1]
rest = args[2:]
if "create".startswith(command):
return cli_create(rest)
elif "query".startswith(command):
return cli_query(rest)
... | b89e68c6ef98722a55ff15e8473dec8c8437bf8d | 3,648,881 |
def compute_correlations(states):
"""compute_correlations.
Calculate the average correlation of spin 0 and every other spin.
Parameters
----------
states : list of states.
``len(states)`` must be >= 1!
Returns
-------
correlations : list of floats.
"""
return [
... | 471949aa63a3d65b262fb9dad1c77d160a3f5ac7 | 3,648,882 |
from typing import Sequence
from typing import Any
def parse_sample_str(elems: Sequence[Any]) -> AOList[str]:
""" Choose n floats from a distribution.
Examples:
>>> c = parse_sample_str([4, ["choose", ["one", "two"]]])
>>> c
Sample(4, ChooseS([StrConst('one'), StrConst('two')]))
"""
str... | 5996a3b0ed072d4a7a00d7e01cc74efdc65aa8ee | 3,648,883 |
def htlc(TMPL_RCV,
TMPL_OWN,
TMPL_FEE,
TMPL_HASHIMG,
TMPL_HASHFN,
TMPL_TIMEOUT):
"""This contract implements a "hash time lock".
The contract will approve transactions spending algos from itself under two circumstances:
- If an argument arg_0 is passed to the script ... | 9288458b228dabc1663901e03011feaa8ff9765c | 3,648,884 |
def parse(*args, is_flag=False, **kwargs):
"""alias of parser.parse"""
return _parser.parse(*args, is_flag=is_flag, **kwargs) | f40499277a12bd6e492e43fd7e4328124ac59814 | 3,648,885 |
def oauth_callback():
"""
return: str
"""
auth = tweepy.OAuthHandler(env.TWITTER_API_KEY, env.TWITTER_API_SECRET)
try:
auth.request_token = session['REQUEST_TOKEN']
verifier = request.args.get('oauth_verifier')
auth.get_access_token(verifier)
session['AUTH_TOKEN'],ses... | a15d7c88c97b23a3ce625e363882fff3197c55b5 | 3,648,886 |
from typing import Tuple
from typing import List
import random
def generate_random_instance(n_instants: int, cost_dim: int, items_per_instant: int = 1) -> \
Tuple[List[List[float]], List[List[List[float]]], float, float]:
"""Generates random values, costs and capacity for a Packing Problem instance.
I... | 57ccf4cd5410d2358c434d94beb9bfbb0ca04820 | 3,648,887 |
def recommend_tags_questions(professional_id, threshold=0.01, top=5):
""" Recommends tags for an professional depending on answered questions.
:param professional_id: ID of the professional
:param threshold: Minimum percentage of questions with the tags.
:param top: Top N recommende... | 1b4bc6d37569d4794294028036e59437f66dc552 | 3,648,888 |
from .tools import make_simulationtable
from .model import reservoirs
def simulationtable(request):
"""
called when the simulation page starts to get used
"""
# convert to the right name syntax so you can get the COM ids from the database
selected_reservoir = request.body.decode("utf-8")
rese... | eaa60d02ee095d5efcc6a4f458bd4bb6745675d0 | 3,648,889 |
from datetime import datetime
def get_rate_limits(response):
"""Returns a list of rate limit information from a given response's headers."""
periods = response.headers['X-RateLimit-Period']
if not periods:
return []
rate_limits = []
periods = periods.split(',')
limits = response.head... | eed6504d712e91110763e28f400dab5faf9300a1 | 3,648,890 |
import numpy
def plot_breakdown_percents(runs, event_labels=[],
title=None, colors=None):
"""
Plots a bar chart with the percent of the total wall-time of all events for
multiple runs.
Parameters
----------
runs: Run object or list of Run objects
The list of ... | 788c0c466223a2e2aaa695c616fdfc649248b963 | 3,648,891 |
def gen3_file(mock_gen3_auth):
"""
Mock Gen3File with auth
"""
return Gen3File(endpoint=mock_gen3_auth.endpoint, auth_provider=mock_gen3_auth) | ee2af5d8b89c02e205101e0fe56dc58025d72e38 | 3,648,892 |
def rhs_of_rule(rule):
""" This function takes a grammatical rule, and returns its RHS """
return rule[0] | 004b99ac97c50f7b33cc798997463a28c3ae9a6f | 3,648,893 |
from typing import Union
from typing import Optional
from typing import Any
def flow_duration_curve(
x: Union[np.ndarray, pd.Series],
log: bool = True,
plot: bool = True,
non_exceeding:bool = True,
ax: Optional[Union[SubplotBase, Any]] = None,
**kwargs
) -> Uni... | 3bec0159553a814ac4c68b198a29bf3075f6d202 | 3,648,894 |
def get_fields(filters):
"""
Return sql fields ready to be used on query
"""
fields = (
("(SELECT p.posting_date FROM `tabPurchase Invoice` p Join `tabPurchase Invoice Item` i On p.name = i.parent WHERE i.item_code = `tabItem`.item_code And p.docstatus = 1 limit 1) as pinv_date"),
("CONCAT(`tabItem`._default_... | 592d7c051e3af4cb510e43caa774054976f68865 | 3,648,895 |
from typing import Counter
def count_POS_tag(df_pos):
"""Count how often each POS tag occurs
Args:
df_pos ([dataframe]): dataframe, where the entries are list of tuples (token, POS tag)
Returns:
df_pos_stats ([dataframe]): dataframe containing POS tag statistics
"""
# POS tag l... | a9ac14f34c020b78b02d6ae629cbddcdde39af8d | 3,648,896 |
import json
def catch_all(path):
"""
Gets dummy message.
"""
return json.dumps({
'message': 'no one was here',
'ms': get_epochtime_ms()
}) | b93190b546705c1115c1612e4bd79210ab0d8f85 | 3,648,897 |
import os
import zipfile
def make_archive_obj(filepath, fileobj=None, inmemory_processing=True, allow_unsafe_extraction=False):
"""This method allows for smart opening of an archive file. Currently this
method can handle tar and zip archives. For the tar files, if the python
library has issues, the file is attempt... | 7a5490b091ae0ca55c591fe16139d0df793a71e5 | 3,648,898 |
import typing
from typing import List
from functools import reduce
def dimensions_to_space_time_index(dims, t_idx = (), t_len = (), s_idx = (), s_len = (),
next_idx_valid = 0, invalid = False,
min_port_width = 0, max_port_width = 0, total_time = 0,... | bdb24e237ba99288be98112db0f09d6782193594 | 3,648,899 |
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