content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import types
def get_task_name(task):
"""Gets a tasks *string* name, whether it is a task object/function."""
task_name = ""
if isinstance(task, (types.MethodType, types.FunctionType)):
# If its a function look for the attributes that should have been
# set using the task() decorator provi... | 181682d930cf358f2532406f1558b007aa09a41f | 16,037 |
def EventAddPublication(builder, publication):
"""This method is deprecated. Please switch to AddPublication."""
return AddPublication(builder, publication) | 39cf5facf251370fd86a004477f848dafd41976c | 16,038 |
def convModel(input1_shape, layers):
"""" convolutional model defined by layers. ith entry
defines ith layer. If entry is a (x,y) it defines a conv layer
with x kernels and y filters. If entry is x it defines a pool layer
with size x"""
model = Sequential()
for (i, layer) in enumerate(layers):
... | d1a49a42ab0fc4eecd40783345f09121a773ae02 | 16,039 |
def cached_open_doc(db, doc_id, cache_expire=COUCH_CACHE_TIMEOUT, **params):
"""
Main wrapping function to open up a doc. Replace db.open_doc(doc_id)
"""
try:
cached_doc = _get_cached_doc_only(doc_id)
except ConnectionInterrupted:
cached_doc = INTERRUPTED
if cached_doc in (None, ... | 82118a5c9c43aaf339e7ca3ab8af9680fbd362d1 | 16,040 |
import torch
def dense2bpseq(sequence: torch.Tensor, label: torch.Tensor) -> str:
"""converts sequence and label tensors to `.bpseq`-style string"""
seq_lab = dense2seqlab(sequence, label)
return seqlab2bpseq | ec0a5d681fef518068042aa2830ee4d2ef3231c8 | 16,042 |
from datetime import datetime
def _base_app(config):
"""
init a barebone flask app.
if it is needed to create multiple flask apps,
use this function to create a base app which can be further modified later
"""
app = Flask(__name__)
app.config.from_object(config)
config.init_app(app)
... | f5f40ed9ea740c5b9bc9ebb8490136179d06f777 | 16,043 |
def applyC(input_map,nbar,MAS_mat,pk_map,Y_lms,k_grids,r_grids,v_cell,shot_fac,include_pix=True):
"""Apply the fiducial covariance to a pixel map x, i.e. C[x] = S[x]+N[x].
We decompose P(k;x) = \sum_l P_l(k) L_l(k.x) where x is the position of the second galaxy and use spherical harmonic decompositions.
P_... | 91346d935217f540a91947b0a00e91e0125794ef | 16,044 |
def invert_injective_mapping(dictionary):
"""
Inverts a dictionary with a one-to-one mapping from key to value, into a
new dictionary with a one-to-one mapping from value to key.
"""
inverted_dict = {}
for key, value in iteritems(dictionary):
assert value not in inverted_dict, "Mapping i... | c8cba85f542c5129892eeba4168edf6d9715b54e | 16,045 |
def biosql_dbseqrecord_to_seqrecord(dbseqrecord_, off=False):
"""Converts a DBSeqRecord object into a SeqRecord object.
Motivation of this function was two-fold: first, it makes type testing simpler; and second, DBSeqRecord does
not have a functional implementation of the translate method.
:param DBSeq... | 9129c5efd9025a04f0693fd2d35f420b28c2ea91 | 16,046 |
import re
def parse_rpsbproc(handle):
"""Parse a results file generated by rpsblast->rpsbproc.
This function takes a handle corresponding to a rpsbproc output file.
local.rpsbproc returns a subprocess.CompletedProcess object, which contains the
results as byte string in it's stdout attribute.
"""... | 64be049b5cb96a3e59f421327d1715cee84e2300 | 16,048 |
from typing import get_type_hints
def _invalidate(obj, depth=0):
"""
Recursively validate type anotated classes.
"""
annotations = get_type_hints(type(obj))
for k, v in annotations.items():
item = getattr(obj, k)
res = not_type_check(item, v)
if res:
return f"{... | a1881d45414a4a034456e0078553e4aa7bf6471a | 16,049 |
def convtranspose2d_output_shape(h_w, kernel_size=1, stride=1, pad=0, dilation=1, out_pad=0):
"""Calculates the output height and width of a feature map for a ConvTranspose2D operation."""
h_w, kernel_size, stride, pad, dilation, out_pad = num2tuple(h_w), num2tuple(kernel_size), num2tuple(stride), num2tuple(pad... | e1ded212929e7e24b138335ae3d9006b1dcfb759 | 16,051 |
def set_multizone_read_mode(session, read_mode, return_type=None, **kwargs):
"""
Modifies where data is read from in multizone environments.
:type session: zadarapy.session.Session
:param session: A valid zadarapy.session.Session object. Required.
:type read_mode: str
:param read_mode: For mu... | 0831bfd722514cab792eef38838e357209a0971f | 16,052 |
import re
def get_name_convert_func():
"""
Get the function to convert Caffe2 layer names to PyTorch layer names.
Returns:
(func): function to convert parameter name from Caffe2 format to PyTorch
format.
"""
pairs = [
# ------------------------------------------------------... | 4e3cbe0885a0d23d5af151bc0cea7127156aa9c9 | 16,053 |
def generate_dict_entry(key, wordlist):
"""Generate one entry of the python dictionary"""
entry = " '{}': {},\n".format(key, wordlist)
return entry | 57ab3c063df0bde1261602f0c6279c70900a7a88 | 16,054 |
def record_to_dict(record):
"""
Transform string into bovespa.Record
:param record: (string) position string from bovespa.
:return: parsed Record
"""
try:
record = bovespa.Record(record)
except:
return None
return {
'date': record.date, 'year': record.date.year,
... | 3065d233a0186a72330165c9b082c819369ef449 | 16,055 |
def sample_product(user, **params):
"""Create and return a custom product"""
defaults = {
'name': 'Ron Cacique',
'description': 'El ron cacique es...',
'price': 20,
'weight': '0.70',
'units': 'l',
'featured': True,
}
defaults.update(params)
return Pro... | 310b2ee775e5497597dd68cf6737623e40b78932 | 16,056 |
def _find_op_path_(block, outputs, inputs, no_grad_set):
"""
no_grad_set will also be changed
"""
input_names = set([inp.name for inp in inputs])
output_names = set([out.name for out in outputs])
relevant_op_flags = [True] * len(block.ops)
# All the inputs of the block are used if inputs i... | 05d1b18f883906cc41fa84f6f27f061b30ced4b8 | 16,057 |
def clean_gltf_materials(gltf):
"""
未使用のglTFマテリアルを削除する
:param gltf: glTFオブジェクト
:return: 新しいマテリアルリスト
"""
return filter(lambda m: m['name'] in used_material_names(gltf), gltf['materials']) | 7e429dceb84d48298897589172f976ea907ddcab | 16,058 |
def create_root(request):
"""
Returns a new traversal tree root.
"""
r = Root()
r.add('api', api.create_root(request))
r.add('a', Annotations(request))
r.add('t', TagStreamFactory())
r.add('u', UserStreamFactory())
return r | ebc64f7f49bf6b3405b9971aa0b30e72b3d13c5f | 16,059 |
def sort_basis_functions(basis_functions):
"""Sorts a set of basis functions by their distance to the
function with the smallest two-norm.
Args:
basis_functions: The set of basis functions to sort.
Expected shape is (-1, basis_function_length).
Returns:
sorted_basis: The so... | 18b11f80c7d08eb6435d823e557ec9ea4e028b92 | 16,060 |
def info_materials_groups_get():
"""
info_materials_groups_get
Get **array** of information for all materials, or if an array of `type_ids` is included, information on only those materials.
:rtype: List[Group]
"""
session = info_map.Session()
mat = aliased(info_map.Material)
... | 49dcf0785be8d9a94b4bb730af6326d493e79000 | 16,062 |
def relu(x):
"""
Compute the relu of x
Arguments:
x -- A scalar or numpy array of any size.
Return:
s -- relu(x)
"""
s = np.maximum(0,x)
return s | 40b838889b62abca0a88788436b5d648261a3c67 | 16,064 |
def line(value):
"""
| Line which can be used to cross with functions like RSI or MACD.
| Name: line\_\ **value**\
:param value: Value of the line
:type value: float
"""
def return_function(data):
column_name = f'line_{value}'
if column_name not in data.columns:
... | 07b4f9671ae06cf63c02062a9da4eb2a0b1a265a | 16,066 |
import json
import requests
def goodsGetSku(spuId,regionId):
"""
:param spuId:
:param regionId:
:return:
"""
reqUrl = req_url('goods', "/goods/getGoodsList")
if reqUrl:
url = reqUrl
else:
return "服务host匹配失败"
headers = {
'Content-Type': 'application/json',
... | 23c3960384529c7a45e730a612cc7999fa316bd4 | 16,067 |
def get_scheduler(config, optimizer):
"""
:param config: 配置参数
:param optimizer: 优化器
:return: 学习率衰减策略
"""
# 加载学习率衰减策略
if config.scheduler_name == 'StepLR':
scheduler = optim.lr_scheduler.StepLR(optimizer, step_size=config.StepLR['decay_step'],
... | 1e4be51c74ed6c35bde3343547c4a7a88736179a | 16,069 |
def pipeline_dict() -> dict:
"""Pipeline config dict. You need to update the labels!"""
pipeline_dictionary = {
"name": "german_business_names",
"features": {
"word": {"embedding_dim": 16, "lowercase_tokens": True},
"char": {
"embedding_dim": 16,
... | d9e15fb1a09678d65b30a49b7c7c811843420c57 | 16,070 |
def _is_hangul_syllable(i):
"""
Function for determining if a Unicode scalar value i is within the range of Hangul syllables.
:param i: Unicode scalar value to lookup
:return: Boolean: True if the lookup value is within the range of Hangul syllables, otherwise False.
"""
if i in range(0xAC00, 0... | 793519ec33a8920ea13328b0e5a4f814c859b0d3 | 16,071 |
def shape14_4(tik_instance, input_x, res, input_shape, shape_info):
"""input_shape == ((32, 16, 14, 14, 16), 'float16', (1, 1), (1, 1))"""
stride_w, stride_h, filter_w, filter_h, dilation_filter_w, dilation_filter_h = shape_info
pad = [0, 0, 0, 0]
l1_h = 14
l1_w = 14
c1_index = 0
jump_stride... | 5606e2e6445ea5415960e1784009bcc75de29669 | 16,072 |
from typing import Dict
from typing import Any
from typing import Optional
from typing import Iterator
from typing import Union
from typing import List
def read_json(
downloader: Download, datasetinfo: Dict, **kwargs: Any
) -> Optional[Iterator[Union[List, Dict]]]:
"""Read data from json source allowing for J... | 77183992d42d9c3860965222c3feda23aca588dc | 16,073 |
import json
def json_dumps_safer(obj, **kwargs):
"""Convert obj to json, with some extra encodable types."""
return json.dumps(obj, cls=WandBJSONEncoder, **kwargs) | 816e97051553f1adc4c39a7c5e4559fb3a354197 | 16,074 |
def load_data(filename: str):
"""
Load house prices dataset and preprocess data.
Parameters
----------
filename: str
Path to house prices dataset
Returns
-------
Design matrix and response vector (prices) - either as a single
DataFrame or a Tuple[DataFrame, Series]
"""
... | 74707af8839b37de80d682d715ed8000375cdd7c | 16,075 |
from uuid import uuid4
from redis import Redis
from qiita_core.configuration_manager import ConfigurationManager
from qiita_db.sql_connection import SQLConnectionHandler
from moi.job import submit_nouser
def test(runner):
"""Test the environment
* Verify redis connectivity indepedent of moi
* Verify data... | ea4f8f50e3d85c3df6f7c890b5b91140a63bac65 | 16,076 |
def validate_model(model):
"""
Validate a single data model parameter or a full data model block by
recursively calling the 'validate' method on each node working from
the leaf nodes up the tree.
:param model: part of data model to validate
:type model: :graphit:GraphAxis
:return: ov... | 009c629fe80af65f574c698567cb6b5213e9c888 | 16,078 |
def simple_get(url):
"""
Attempts to get the content at `url` by making an HTTP GET request.
If the content-type of response is some kind of HTML/XML, return the
text content, otherwise return None.
"""
filename = "{0}.html".format(url.split("/").pop().lower())
filepath = abspath(join(dirna... | 60b7714a439d949f42b1b8de6064c8ba087ccfdc | 16,079 |
def ensemble_tsfresh(forecast_in, forecast_out, season, perd):
"""
Create rolled time series for ts feature extraction
"""
def tsfresh_run(forecast, season, insample=True, forecast_out=None):
df_roll_prep = forecast.reset_index()
if insample:
df_roll_prep = df_roll_prep.drop... | 3bcef19cd495c043e51a591118c1ae8e043290b5 | 16,080 |
from affine import Affine
def transform_from_latlon(lat, lon):
"""
Tranform from latitude and longitude
NOTES:
- credit - Shoyer https://gist.github.com/shoyer/0eb96fa8ab683ef078eb
"""
lat = np.asarray(lat)
lon = np.asarray(lon)
trans = Affine.translation(lon[0], lat[0])
scale = A... | 1f6fccfddd23423c0a621efa74a62cdb61b53665 | 16,082 |
from typing import OrderedDict
def xml_to_json(xml_text: str) -> OrderedDict:
"""Converts xml text to json.
Args:
xml_text (str): xml text to be parsed
Returns:
OrderedDict: an ordered dict representing the xml text as json
"""
return xmltodict.parse(xml_text) | 243156c6f0b3b0f0bf92d8eeaa3ecf52f5846fc8 | 16,083 |
import requests
def getWeather(city, apikey):
"""
天気を取得する
リクエストにAPIKeyと都市をパラメーターに入れる
https://openweathermap.org/forecast5
"""
payload = {
'APIKEY': APIKEY,
'q': CITY
}
r = requests.get(
APIBASE,
params=payload
)
return r | 41a61d1bd9d1bd5d835963c305d0692babd6b64a | 16,085 |
def func1(xc):
"""Function which sets the data value"""
s = .1
res = np.exp(-xc**2/(2*s**2))
return res | 75ab06abf5b348746e322cf41660cfb908d69b62 | 16,086 |
def GetEnabledDiskTemplates(*args):
"""Wrapper for L{_QaConfig.GetEnabledDiskTemplates}.
"""
return GetConfig().GetEnabledDiskTemplates(*args) | c07707de13be5c055386659be620831b2f057d64 | 16,087 |
def is_pull_request_merged(pull_request):
"""Takes a github3.pulls.ShortPullRequest object"""
return pull_request.merged_at is not None | 0fecf82b96f7a46cfb4e9895897bd4998d6f225b | 16,088 |
def arraytoptseries(arr, crs={'epsg': '4326'}):
"""Convert an array of shape (2, ...) or (3, ...) to a
geopandas GeoSeries containing shapely Point objects.
"""
if arr.shape[0] == 2:
result = geopandas.GeoSeries([Point(x[0], x[1])
for x in arr.reshape(2, -1).T... | b193f9bcb4144b81becca1acaa8285f8cafaaff2 | 16,089 |
async def get_kml_network_link():
""" Return KML network link file """
logger.info('/c-haines/network-link')
headers = {"Content-Type": kml_media_type,
"Content-Disposition": "inline;filename=c-haines-network-link.kml"}
return Response(headers=headers, media_type=kml_media_type, content=... | 699ac59529ce085264a79dfdd048c96b3771e0a8 | 16,090 |
def splitToPyNodeList(res):
# type: (str) -> List[pymel.core.general.PyNode]
"""
converts a whitespace-separated string of names to a list of PyNode objects
Parameters
----------
res : str
Returns
-------
List[pymel.core.general.PyNode]
"""
return toPyNodeList(res.split()) | 44e8780833ed2a5d7418c972afb9e184ca82670b | 16,091 |
def get_jira_issue(commit_message):
"""retrieve the jira issue referenced in the commit message
>>> get_jira_issue(b"BAH-123: ")
{b'BAH-123'}
>>> messages = (
... b"this is jira issue named plainly BAH-123",
... b"BAH-123 plainly at the beginning",
... b"in parens (BAH-123)",
... b"(BAH... | b0bf47319c492ec297dd9898645a10ce8a53b43f | 16,092 |
def get_mean_std(dataloader):
"""Compute mean and std on the fly.
Args:
dataloader (Dataloader): Dataloader class from torch.utils.data.
Returns:
ndarray: ndarray of mean and std.
"""
cnt = 0
mean = 0
std = 0
for l in dataloader: # Now in (batch,... | d943ae5244743749fa6a2186aacfbf0ea160d17b | 16,094 |
import random
import math
def create_random_camera(bbox, frac_space_x, frac_space_y, frac_space_z):
""" Creates a new camera, sets a random position for it, for a scene inside the bbox.
Given the same random_seed the pose of the camera is deterministic.
Input:
bbox - same rep as output from get_scene... | 8cfa86127d569493a2456e13ae5924da886640a9 | 16,096 |
def temp2():
""" This is weird, but correct """
if True:
return (1, 2)
else:
if True:
return (2, 3)
return (4, 5) | c63f5566a6e52a3b5d175640fce830b7aad33ebe | 16,097 |
from typing import Tuple
def compute_blade_representation(bitmap: int, firstIdx: int) -> Tuple[int, ...]:
"""
Takes a bitmap representation and converts it to the tuple
blade representation
"""
bmp = bitmap
blade = []
n = firstIdx
while bmp > 0:
if bmp & 1:
blade.ap... | 3bf6672280629dee8361ee3c0dbf5920afa4edda | 16,098 |
import time
def get_ntp_time(ntp_server_url):
"""
通过ntp server获取网络时间
:param ntp_server_url: 传入的服务器的地址
:return: time.strftime()格式化后的时间和日期
"""
ntp_client = ntplib.NTPClient()
ntp_stats = ntp_client.request(ntp_server_url)
fmt_time = time.strftime('%X', time.localtime(ntp_stats.tx_time))... | 17881970361994e329e1154478c8abb8171461f9 | 16,100 |
def read_data(path, names, verbose=False):
"""
Read time-series from MATLAB .mat file.
Parameters
----------
path : str
Path (relative or absolute) to the time series file.
names : list
Names of the requested time series incl. the time array itself
verbose : bool, optional
... | 978870d4517b5e5ab66186747c326794d6d43814 | 16,101 |
async def search(q: str, person_type: str = 'student') -> list:
"""
Search by query.
:param q: `str` query to search for
:param person_type: 'student', 'lecturer', 'group', 'auditorium'
:return: list of results
"""
url = '/'.join((BASE_URL, SEARCH_INDPOINT))
params = {'term': q,
... | 83913866f45a44202ccddbc9352fef9799caf751 | 16,102 |
def format_data_hex(data):
"""Convert the bytes array to an hex representation."""
# Bytes are separated by spaces.
return ' '.join('%02X' % byte for byte in data) | 27239052d9ca0b12c19977e79d512e0cab04182e | 16,103 |
def disp(cog_x, cog_y, src_x, src_y):
"""
Compute the disp parameters
Parameters
----------
cog_x: `numpy.ndarray` or float
cog_y: `numpy.ndarray` or float
src_x: `numpy.ndarray` or float
src_y: `numpy.ndarray` or float
Returns
-------
(disp_dx, disp_dy, disp_norm, disp_ang... | e9d8166827e86a8e2180ba357a450aca817fdff4 | 16,106 |
def get_landmark_from_prob(prob, thres=0.5, mode="mean", binary_mask=False):
"""Compute landmark location from the model probablity maps
Inputs:
prob : [RO, E1], the model produced probablity map for a landmark
thres : if np.max(prob)<thres, determine there is no landmark detected
m... | fad614088e587e389f15b0700bf442a956d498b0 | 16,107 |
import socket
def request(
url,
timeout: float,
method="GET",
data=None,
response_encoding="utf-8",
headers=None,
):
"""
Helper function to perform HTTP requests
"""
req = Request(url, data=data, method=method, headers=headers or {})
try:
return urlopen(req, timeout... | 80f130101290442d538fa3f416f5650800547c6b | 16,108 |
from typing import Any
from typing import Optional
from typing import get_args
from typing import get_origin
def get_annotation_affiliation(annotation: Any, default: Any) -> Optional[Any]:
"""Helper for classifying affiliation of parameter
:param annotation: annotation record
:returns: classified value o... | db6efd7dfb0ed0272e7491547669de8f235b2b35 | 16,109 |
def sort_dict(original):
"""Recursively sorts dictionary keys and dictionary values in alphabetical order"""
if isinstance(original, dict):
res = (
dict()
) # Make a new "ordered" dictionary. No need for Collections in Python 3.7+
for k, v in sorted(original.items()):
... | 8c194af76160b0e4d3bad135720e051a4d4622b0 | 16,111 |
import requests
def playonyt(topic):
"""Will play video on following topic, takes about 10 to 15 seconds to load"""
url = 'https://www.youtube.com/results?q=' + topic
count = 0
cont = requests.get(url)
data = str(cont.content)
lst = data.split('"')
for i in lst:
count+=1
if... | 49f4285dc0e0086d30776fc0668bac0e4c19dbc5 | 16,112 |
def train_classifier(classifier, features, labels):
"""This function must concern itself with training the classifier
on the specified data."""
return classifier.fit(features, labels) | ef74548aeb6e245d8728caf3205163c249046aae | 16,113 |
def work_on_disk(dev, root_mb, swap_mb, image_path):
"""Creates partitions and write an image to the root partition."""
root_part = "%s-part1" % dev
swap_part = "%s-part2" % dev
if not is_block_device(dev):
LOG.warn(_("parent device '%s' not found"), dev)
return
make_partitions(dev,... | 195ded6deae958b7efa41bcfdda1d3d68cabb23d | 16,114 |
def get_annotation_names(viewer):
"""Detect the names of nodes and edges layers"""
layer_nodes_name = None
layer_edges_name = None
for layer in viewer.layers:
if isinstance(layer, napari.layers.points.points.Points):
layer_nodes_name = layer.name
elif isinstance(layer, napar... | 20e64a6719b945eceda341d5a42da178818cb1a1 | 16,115 |
def remap(kx,ky,lx,ly,qomt,datai):
"""
remap the k-space variable back to shearing
periodic frame to reflect the time dependent
Eulerian wave number
"""
ndim = datai.ndim
dim = np.array(datai.shape)# datai[nz,ny,nx]
sh_data = np.empty([dim[0],dim[1],dim[2]])
tp_data = np.empty([dim[0],dim[2]])
sh... | 6ea415df88c0db2ba26ef0fc8daa35b12a101ef8 | 16,116 |
def fips_disable():
"""
Disables FIPS on RH/CentOS system. Note that you must reboot the
system in order for FIPS to be disabled. This routine prepares
the system to disable FIPS.
CLI Example:
.. code-block:: bash
salt '*' ash.fips_disable
"""
installed_fips_pkgs = _get_install... | d31cc5ad6dd71ec0f3d238051a7b2a64b311c0fd | 16,117 |
from datetime import datetime
def buy_sell_fun_mp_org(datam, S1=1.0, S2=0.8):
"""
斜率指标交易策略标准分策略
"""
start_t = datetime.datetime.now()
print("begin-buy_sell_fun_mp:", start_t)
dataR = pd.DataFrame()
for code in datam.index.levels[1]:
# data = price.copy()
# price = datam.que... | 8d3b78b9d266c3c39b8491677caa0f4dfb9f839a | 16,119 |
import collections
import abc
def marshall_namedtuple(obj):
"""
This method takes any atomic value, list, dictionary or namedtuple,
and recursively it tries translating namedtuples into dictionaries
"""
recurse = lambda x: map(marshall_namedtuple, x)
obj_is = partial(isinstance, obj)
if ha... | 87d24fe1b273bfcf481679a96710be757baf08a5 | 16,120 |
import torch
def prep_image(img, inp_dim):
"""
Prepare image for inputting to the neural network.
Returns a Variable
"""
# print("prepping images")
img = cv2.resize(img, (inp_dim, inp_dim))
img = img[:,:,::-1].transpose((2,0,1)).copy()
img = torch.from_numpy(img).float().div(255... | 02ebc73a32a24d59c53da9bfb99485f3a4f6dee2 | 16,121 |
from typing import Dict
from typing import List
import math
def best_broaders(supers_for_all_entities: Dict,
per_candidate_links_and_supers: List[Dict],
num_best: int = 5,
super_counts_field: str = "broader_counts",
doprint=False,
... | 9aa9826c43e67a28eeca463b107296e093709246 | 16,122 |
def clump_list_sort(clump_list):
"""Returns a copy of clump_list, sorted by ascending minimum density. This
eliminates overlap when passing to
yt.visualization.plot_modification.ClumpContourCallback"""
minDensity = [c['Density'].min() for c in clump_list]
args = np.argsort(minDensity)
list... | 732e747e36c37f9d65ef44b6aa060d5c9d04e3d1 | 16,123 |
from typing import Dict
from typing import Any
from typing import Type
import types
from typing import Optional
def _prepare_artifact(
metadata_handler: metadata.Metadata,
uri: Text,
properties: Dict[Text, Any],
custom_properties: Dict[Text, Any],
reimport: bool, output_artifact_class: Type[types.... | d30dcd579c73c71173f10207ab80d05c761c7185 | 16,124 |
import re
def ParseCLILines(lines, skipStartLines=0, lastSkipLineRe=None, skipEndLines=0):
"""Delete first few and last few lines in an array"""
if skipStartLines > 0:
if lastSkipLineRe != None:
# sanity check. Make sure last line to skip matches the given regexp
if None == re.... | dc445765f42df25b8d046e3f2303d85109a3d419 | 16,125 |
def initialize_parameters(n_x, n_h, n_y):
"""
Argument:
n_x -- size of the input layer
n_h -- size of the hidden layer
n_y -- size of the output layer
Returns:
params -- python dictionary containing your parameters:
W1 -- weight matrix of shape (n_h, n_x)
... | 785985b79b9284ba8c6058c8e9c4018955407cf8 | 16,126 |
from datetime import datetime
def get_df_from_sampled_trips(step_trip_list, show_service_data=False, earliest_datetime=None):
"""Get dataframe from sampled trip list.
Parameters
----------
step_trip_list : list of lists
List of trip lists occuring in the same step.
show_service_data: bool... | 36bba80f0c46862df0390cf4e4279eeb33002e86 | 16,128 |
def compute_v_y(transporter, particles):
"""
Compute values of V y on grid specified in bunch configuration
:param transporter: transport function
:param particles: BunchConfiguration object, specification of grid
:return: matrix with columns: x, theta_x, y, theta_y, pt, V y
"""
return __com... | 4a17e0c0e4612534483187b6779bcf5c179c0fcc | 16,129 |
def run_fn(fn_args: TrainerFnArgs):
"""Train the model based on given args.
Args:
fn_args: Holds args used to train the model as name/value pairs.
"""
# get transform component output
tf_transform_output = tft.TFTransformOutput(fn_args.transform_output)
# read input data
train_dataset... | 15c8202ad6955052bbd1da2984aedb9887c390af | 16,131 |
def log_likelihood(X, Y, Z, data, boolean=True, **kwargs):
"""
Log likelihood ratio test for conditional independence. Also commonly known
as G-test, G-squared test or maximum likelihood statistical significance
test. Tests the null hypothesis that X is independent of Y given Zs.
Parameters
--... | 00493131d78506c5a6cbb9e04bda51b69f1a04ca | 16,132 |
def conjugada_matriz_vec(mat:list):
"""
Funcion que realiza la conjugada de una matriz o vector complejo.
:param mat: Lista que representa la matriz o vector complejo.
:return: lista que representa la matriz o vector resultante.
"""
fila = len(mat)
columnas = len(mat[0])
resul = []
f... | ad883dae9161f4e60f933caf93703544e16bfb4d | 16,133 |
def features2matrix(feature_list):
"""
Args:
feature_list (list of Feature):
Returns:
(np.ndarray, list of str): matrix and list of key of features
"""
matrix = np.array([feature.values for feature in feature_list], dtype=float)
key_lst = [feature.key for feature in feature_li... | f60cdb904489cca3ab926dbc8d396804367e4a7a | 16,134 |
import re
def is_heading(line):
"""Determine whether a given line is a section header
that describes subsequent lines of a report.
"""
has_cattle = re.search(r'steer?|hfrs?|calves|cows?|bulls?', line, re.IGNORECASE)
has_price = re.search(r'\$[0-9]+\.[0-9]{2}', line)
return bool(has_cattle) a... | ccbc80f7db61f7ba82aa88e54112d1995d457764 | 16,136 |
def get_channel_messages(channel_id):
""" Holt fuer einen bestimmten Kanal die Nachrichten aus der Datenbank"""
session = get_cassandra_session()
future = session.execute_async("SELECT * FROM messages WHERE channel_id=%s", (channel_id,))
try:
rows = future.result()
except Exception:
... | 7a3821dd8e93c4d49dfeecea200a881fdcb3f1a4 | 16,137 |
def train(traj,
pol, targ_pol, qf, targ_qf,
optim_pol, optim_qf,
epoch, batch_size, # optimization hypers
tau, gamma, # advantage estimation
sampling,
):
"""
Train function for deep deterministic policy gradient
Parameters
----------
tra... | 14c09f3ce1f30366be3b8d0e0b965bdc1c677834 | 16,138 |
def merge_dicts(dict1, dict2):
""" _merge_dicts
Merges two dictionaries into one.
INPUTS
@dict1 [dict]: First dictionary to merge.
@dict2 [dict]: Second dictionary to merge.
RETURNS
@merged [dict]: Merged dictionary
"""
merged = {**dict1, **dict2}
return merged | 67e96ba9c9831e6e2aa4bbd6cd8b8d1d5edb93c4 | 16,140 |
import pagure.api
import pagure.lib.query
def check_api_acls(acls, optional=False):
"""Checks if the user provided an API token with its request and if
this token allows the user to access the endpoint desired.
:arg acls: A list of access control
:arg optional: Only check the API token is valid. Skip... | 81d658036c5b31e3471e48ef44f4eb26e571c49a | 16,141 |
def china_province_head_fifteen():
"""
各省前15数据
:return:
"""
return db_request_service.get_china_province_head_fifteen(ChinaTotal, ChinaProvince) | 18dc3f22c05b3580bcd983361efc03bd3cdae43b | 16,143 |
def pipeline(x_train,
y_train,
x_test,
y_test,
param_dict=None,
problem='classification'):
"""Trains and evaluates a DNN classifier.
Args:
x_train: np.array or scipy.sparse.*matrix array of features of training data
y_train: np.array 1-D arra... | f01e20851c91dd9f6b3db889fdf713edc1eb37b9 | 16,145 |
def model_selection(modelname, num_out_classes,
dropout=None):
"""
:param modelname:
:return: model, image size, pretraining<yes/no>, input_list
"""
if modelname == 'xception':
return TransferModel(modelchoice='xception',
num_out_classes=num_o... | 67ba26ab4f7cbe8f4540eb10f2ef6e598b49ea2f | 16,146 |
def Packet_computeBinaryPacketLength(startOfPossibleBinaryPacket):
"""Packet_computeBinaryPacketLength(char const * startOfPossibleBinaryPacket) -> size_t"""
return _libvncxx.Packet_computeBinaryPacketLength(startOfPossibleBinaryPacket) | 58139b8d874d9292e63b6eb6afdbd9c5c2fa6f9d | 16,147 |
import itertools
def gen_positions(n, n_boulders):
"""Generates state codes for boulders. Includes empty rows
Parameters:
n: number of rows/columns
n_boulders: number of boulders per row
return value:
Possible boulder and alien states
"""
boulder_positions=[]; b_p=[]
a... | 0a20594f2e021bf8e190f6c7c726159fde0b8367 | 16,149 |
def analysis_linear_correlation(data1:np.array,
data2:np.array,
alpha:float = .05,
return_corr:bool = True,
verbose:bool = False)->bool:
"""
## Linear correlation analysis to test i... | 6eaf34a12281949236d28143399024ed30e834ad | 16,150 |
def sha256(buffer=None):
"""Secure Hash Algorithm 2 (SHA-2) with 256 bits hash value."""
return Hash("sha256", buffer) | 2e33c38c0f7b9dd019104a18e6842243773686ca | 16,151 |
import math
import torch
def nmc_eig(model, design, observation_labels, target_labels=None,
N=100, M=10, M_prime=None, independent_priors=False):
"""
Nested Monte Carlo estimate of the expected information
gain (EIG). The estimate is, when there are not any random effects,
.. math::
... | 8de69e87677a4a74fd04ce4cf302221121d00b2d | 16,152 |
import scipy
def _orient_eigs(eigvecs, phasing_track, corr_metric=None):
"""
Orient each eigenvector deterministically according to the orientation
that correlates better with the phasing track.
Parameters
----------
eigvecs : 2D array (n, k)
`k` eigenvectors (as columns).
phasing... | d6feebbd7b7748549ebc494bf8b00f0d9e313f7c | 16,153 |
def test_CreativeProject_auto_multivariate_functional(max_iter, max_response, error_lim, model_type):
"""
test that auto method works for a particular multivariate (bivariate) function
"""
# define data
covars = [(0.5, 0, 1), (0.5, 0, 1)] # covariates come as a list of tuples (one per covariate: (... | ee0cc1d34a1836c8ea9ec2b23de175f4b6d8ca75 | 16,154 |
def crossValidate(x, y, cv=5, K=None):
"""
:param y: N*L ranking vectors
:return:
"""
results = {"perf": []}
## cross validation ##
np.random.seed(1100)
kf = KFold(n_splits=cv, shuffle=True, random_state=0)
for train, test in kf.split(x):
x_train = x[train, :]
y_trai... | 820f5b53a38d2a64a3a1ee740d0fded020000bb7 | 16,155 |
def make_word_groups(vocab_words):
"""
:param vocab_words: list of vocabulary words with a prefix.
:return: str of prefix followed by vocabulary words with
prefix applied, separated by ' :: '.
This function takes a `vocab_words` list and returns a string
with the prefix and the words... | f940c602939ca3a9bab013f5847918f7ba4536ae | 16,156 |
def gpi_g10s40(rescale=False):
"""
Multiply by the 'rescale' factor to adjust hole sizes and centers in entrance pupil (PM)
(Magnify the physical mask coordinates up to the primary mirror size)
"""
demag = gpi_mag_asdesigned()
if rescale:
demag = demag/rescale # rescale 1.1 gives a bigge... | 4be151f7e99332be0f67d00619fe75def90c2b5d | 16,157 |
import inspect
def test_close_sections():
"""Parse sections without blank lines in between."""
def f(x, y, z):
"""
Parameters
----------
x :
X
y :
Y
z :
Z
Raises
------
Error2
error.
... | 793d92d989f3caa020c06ea798f7f34703abd747 | 16,158 |
def _int_converter(value):
"""Convert string value to int.
We do not use the int converter default exception since we want to make
sure the exact http response code.
Raises: exception_handler.BadRequest if value can not be parsed to int.
Examples:
/<request_path>?count=10 parsed to {'count':... | 6b5c99635211bf8ce2e3c2adc784f2a4e9ee355f | 16,160 |
from typing import List
def split_rule(rules, rule_name, symbols_to_extract: List[str], subrule_name: str):
"""
Let only options which are starting with symbols from symbols_to_extract.
Put the rest to a subrule.
"""
r = rule_by_name(rules, rule_name)
assert isinstance(r.body, Antlr4Selection... | aa4d2aac62c488e3cd8d002556edea3aaef7185b | 16,161 |
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