content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import numpy
def normal_function( sigma, width ):
"""
Defaulf fitting function, it returns values from a normal distribution
"""
log2 = log(2)
sigma2 = float(sigma)**2
lo, hi = width, width+1
def normal_func(value, index):
return value * exp( -index*index/sigma2 * log2 ) ... | 797b4eb00db5a0d4675b547664982f537da9e6ab | 23,100 |
def style_get_url(layer, style_name, internal=True):
"""Get QGIS Server style as xml.
:param layer: Layer to inspect
:type layer: Layer
:param style_name: Style name as given by QGIS Server
:type style_name: str
:param internal: Flag to switch between public url and internal url.
Publ... | bdc67d562c8e2020374094ce3fb15cd525f4dd37 | 23,101 |
def remove_duplicates(l):
"""
Remove any duplicates from the original list.
Return a list without duplicates.
"""
new_l = l[:]
tmp_l = new_l[:]
for e in l:
tmp_l.remove(e)
if e in tmp_l:
new_l.remove(e)
return new_l | 81132e3b23592589c19ddb11f661e80be6984782 | 23,102 |
import functools
def in_boudoir(callback):
"""Décorateur : commande utilisable dans un boudoir uniquement.
Lors d'une invocation de la commande décorée hors d'un boudoir
(enregistré dans :class:`.bdd.Boudoir`), affiche un message d'erreur.
Ce décorateur n'est utilisable que sur une commande définie ... | ed086805f2d865331f559406218f9a9ecd4a7194 | 23,103 |
import argparse
import time
def parse_input():
""" Sets up the required input arguments and parses them """
parser = argparse.ArgumentParser()
parser.add_argument('log_file', help='CSV file of log data')
parser.add_argument('-e, --n_epochs', dest='n_epochs',
help='number of tr... | d87a59d31c2face243614ab64b5b08833f0537dd | 23,104 |
def xyz_to_pix(position, bounds, pixel_size):
"""Convert from 3D position to pixel location on heightmap."""
u = int(np.round((position[1] - bounds[1, 0]) / pixel_size))
v = int(np.round((position[0] - bounds[0, 0]) / pixel_size))
return (u, v) | d38b45d573a689f72fda4a7ed477be831bea26a8 | 23,105 |
import random
def get_random_lb():
""" Selects a random location from the load balancers file.
Returns:
A string specifying a load balancer IP.
"""
with open(LOAD_BALANCERS_FILE) as lb_file:
return random.choice([':'.join([line.strip(), str(PROXY_PORT)])
for line in lb_file]... | 2f8620a213bfc87dd3eae662ace409a31597931b | 23,106 |
def enlarge(n):
"""
Multiplies a number by 100
Param: n (numeric) the number to enlarge
Return the enlarged number(numeric)
"""
return n * 100 | 6685af169c8e321ceabc0086d1835d459a627a59 | 23,107 |
import re
def ResolveWikiLinks(html):
"""Given an html file, convert [[WikiLinks]] into links to the personal wiki:
<a href="https://z3.ca/WikiLinks">WikiLinks</a>"""
wikilink = re.compile(r'\[\[(?:[^|\]]*\|)?([^\]]+)\]\]')
def linkify(match):
wiki_root = 'https://z3.ca'
wiki_name = match.group(1).rep... | bef3e309aa2489e720a1742e327e9dd4edf6d720 | 23,108 |
def handle_new_favorite(query_dict):
"""Does not handle multi-part data properly.
Also, posts don't quite exist as they should."""
for required in POST_REQUIRED_PARAMS:
if required not in query_dict:
return False
# not yet safe to use.
post_id = str(string_from_interwe... | 7caed7d280870cb7a67b1bfd53200ec3486a4f41 | 23,109 |
def steam_ratings(html_text):
"""Tries to get both 'all' and 'recent' ratings."""
return {
"overall": steam_all_app_rating(html_text),
"recent": steam_recent_app_rating(html_text),
} | 71cb3e85e9a1f01e5d4b080372b24c2f848bf7cf | 23,110 |
def separation_cos_angle(lon0, lat0, lon1, lat1):
"""Evaluate the cosine of the angular separation between two
direction vectors."""
return (np.sin(lat1) * np.sin(lat0) + np.cos(lat1) * np.cos(lat0) *
np.cos(lon1 - lon0)) | a7e1a7ecdfd0ab7f1dc58b99190cc9eeab7fcf20 | 23,111 |
import sys
def getArg(flag):
"""
Devolve o argumento de uma dada flag
"""
try:
a = sys.argv[sys.argv.index(flag) + 1]
except:
return ""
else:
return a | 7400d0f449334350910bc5926b5fbf5333d3ea10 | 23,112 |
def get_band_params(meta, fmt='presto'):
"""
Returns (fmin, fmax, nchans) given a metadata dictionary loaded from
a specific file format.
"""
if fmt == 'presto':
fbot = meta['fbot']
nchans = meta['nchan']
ftop = fbot + nchans * meta['cbw']
fmin = min(fbot, ftop)
... | 61e9b0781559de431e5189b89f69a0763b039d8f | 23,113 |
import functools
def logging(f):
"""Decorate a function to log its calls."""
@functools.wraps(f)
def decorated(*args, **kwargs):
sargs = map(str, args)
skwargs = (f'{key}={value}' for key, value in kwargs.items())
print(f'{f.__name__}({", ".join([*sargs, *skwargs])})...')
... | 25822434fe331c59ce64b6f9cd5ec89b70b2542a | 23,114 |
def yandex_mean_encoder(columns=None, n_jobs=1, alpha=100, true_label=None):
"""
Smoothed mean-encoding with custom smoothing strength (alpha)
http://learningsys.org/nips17/assets/papers/paper_11.pdf
"""
buider = partial(
build_yandex_mean_encoder,
alpha=alpha,
)
return Tar... | b38ac44cb2ff12c33f415d716cc4e13006eabf0b | 23,115 |
from typing import Optional
import math
from typing import Counter
def cure_sample_part(
X: np.ndarray,
k: int,
c: int = 3,
alpha: float = 0.3,
u_min: Optional[int] = None,
f: float = 0.3,
d: float = 0.02,
p: Optional[int] = None,
q: Optional[int] = None,
n_rep_finalclust: Opti... | b85d2f23bd1b64a0f17abc5178cfc25e442419b5 | 23,116 |
def get_serializer(request):
"""Returns the serializer for the given API request."""
format = request.args.get('format')
if format is not None:
rv = _serializer_map.get(format)
if rv is None:
raise BadRequest(_(u'Unknown format "%s"') % escape(format))
return rv
# we... | 90c11efea0a8636ef3b6b4ca87f4d377d3e0be52 | 23,117 |
from typing import Optional
import pickle
def deserialize_result(r: bytes, *, deserializer: Optional[Deserializer] = None) -> JobResult:
"""Given bytes, deserializes them into a JobResult object.
:param r: bytes to deserialize.
:param deserializer: Optional serializer to use for deserialization. If not ... | 049a453a7277f30a38019ca59bedbc458fbaf84c | 23,118 |
def form_symb_dCdU():
"""Form a symbolic version of dCdU"""
dCdU = form_nd_array("dCdU",[3,3,8*12])
for I in range(3):
for J in range(3):
for K in range(3,8*12):
dCdU[I,J,K] = 0
return dCdU | ec802da453dd7c522bf5725fd70fd16a2406c12e | 23,119 |
import torch
def predict(X, y, clf, onehot_encoder, params):
"""
Runs a forward pass for a SINGLE sample and returns the output prediction.
Arguments:
X (list[int]) : a list of integers with each integer an input class of step
y (list[int]) : a list of integers with each integer an output ... | 8e0aa3c687a3ad24e02f730a5dca31f4fd36c6ad | 23,120 |
def parse_modules_and_elabs(raw_netlist, net_manager):
"""
Parses a raw netlist into its IvlModule and IvlElab objects.
Returns a tuple: (modules, elabs)
modules is a list of IvlModule objects.
elabs is a list of IvlElab objects.
"""
sections = parse_netlist_to_sections(raw_netlist)
mod... | 029d5a86de450eb6c104cc2582e21fe854c557e7 | 23,121 |
def scrub_dt_dn(dt, dn):
"""Returns in lowercase and code friendly names of doctype and name for certain types"""
ndt, ndn = dt, dn
if dt in lower_case_files_for:
ndt, ndn = scrub(dt), scrub(dn)
return ndt, ndn | 853959c073f45be0ffc97dfd8733d2b10a837a32 | 23,122 |
def by_uri(uri):
"""A LicenseSelector-less means of picking a License from a URI."""
if _BY_URI_CACHE.has_key(uri):
return _BY_URI_CACHE[uri]
for key, selector in cc.license.selectors.SELECTORS.items():
if selector.has_license(uri):
license = selector.by_uri(uri)
_B... | 1dc3dfe4070857984768e1af6462927fd08daf77 | 23,123 |
def read_S(nameIMGxml):
"""
This function extract the images's center from the xml file.
Parameters
----------
nameIMGxml : str
the name of the file generated by MM3D.
Usually, it is "Orientation-Im[n°i].JPG.xml"
Returns
-------
numpy.ndarray: the center of the IMG ... | f4054827c8ecfa6d81ac752e8ac46e4cccbc5245 | 23,124 |
def AddBatchJob(client):
"""Add a new BatchJob to upload operations to.
Args:
client: an instantiated AdWordsClient used to retrieve the BatchJob.
Returns:
The new BatchJob created by the request.
"""
# Initialize appropriate service.
batch_job_service = client.GetService('BatchJobService', versio... | 6c48997e4739f05fe6df826654a45b6f7deafc1b | 23,125 |
def bellmanFord(obj,source):
"""Determination of minimum distance between vertices using Bellman Ford Algorithm."""
validatePositiveWeight(obj)
n = CountVertices(obj)
minDist = dict()
for vertex in obj.vertexList:
if vertex == source:
minDist[vertex] = 0
else:
... | 83cdbab547741a070ef694b4cea8f16355eb4af5 | 23,126 |
from typing import Callable
import inspect
import click
def auto_default_option(*param_decls, **attrs) -> Callable[[_C], _C]:
"""
Attaches an option to the command, with a default value determined from the decorated function's signature.
All positional arguments are passed as parameter declarations to :class:`cli... | e1813faf2c0d936333edf4d2a1b111dec6c7a376 | 23,127 |
import os
def get_filename_from_url(url):
"""
Convert URL to filename.
Example:
URL `http://www.example.com/foo.pdf` will be converted to `foo.pdf`.
:type url: unicode
:rtype: unicode
"""
name, extension = os.path.splitext(os.path.basename(urlsplit(url).path))
fin = "{filen... | b53ff1d2a8878f3d477e1579a16f9de29af4e6b3 | 23,128 |
def zCurve(seq):
"""Return 3-dimensional Z curve corresponding to sequence.
zcurve[n] = zcurve[n-1] + zShift[n]
"""
zcurve = np.zeros((len(seq), 3), dtype=int)
zcurve[0] = zShift(seq, 0)
for pos in range(1, len(seq)):
zcurve[pos] = np.add(zcurve[pos - 1], zShift(seq, pos))
return zc... | 4118274fc3bee084777847553dcfa9c4dc92c6c9 | 23,129 |
def getgeo():
""" Grabbing and returning the zones """
data = request.args.get('zone_name', None)
print data
#Check if data is null - get all zones
out = []
if data:
rec = mongo.db.zones.find({'zone_name':data})
else:
rec = mongo.db.zones.find()
for r in rec:
r.p... | 822e8e995ae47d887340a2750eeda5646dfa9d5b | 23,130 |
def photo_upload(request):
"""AJAX POST for uploading a photo for any given application."""
response = None
if request.is_ajax() and request.method == 'POST':
form = PhotoForm(
data=request.POST, files=request.FILES, use_required_attribute=False,
)
if form.is_valid():
... | e760570d07f43800c05f4d1d8b36b9cb84804003 | 23,131 |
def table_str(bq_target):
# type: (BigqueryTarget) -> str
"""Given a BigqueryTarget returns a string table reference."""
t = bq_target.table
return "%s.%s.%s" % (t.project_id, t.dataset_id, t.table_id) | 95053c839d2bc1e4d628261d669a73a6b9dcb309 | 23,132 |
def any_to_any_translate_back(content, from_='zh-CN', to_='en'):
"""
中英，英中回译
:param content:str, 4891个字， 用户输入
:param from_: str, original language
:param to_: str, target language
:return: str, result of translate
"""
translate_content = any_to_any_translate(content, from_=from_, to... | def5100d73712fd1f244913aca725328cbe02b4d | 23,133 |
def to_short_site_cname(user, site):
"""
订阅源显示名称，最多 10 个汉字，支持用户自定义名称
"""
if isinstance(site, dict):
site_id = site['id']
site_cname = site['cname']
else:
site_id = site.id
site_cname = site.cname
if user:
cname = get_user_site_cname(user.oauth_id, site_id... | 70b4874af06e4185a72a45ff82838b2d00cdcec6 | 23,134 |
def load_roed_data(full_output=False):
""" Load master table with all labels """
mtab = load_master_table()
df1 = table.Table.read("roed14_stars.fits").to_pandas()
def renamer(x):
""" match master table Star with Name """
x = x.strip()
if x.startswith("BD") or x.startswith("CD"):... | 8698b478abb9a3e617ce9a23feb89fecf220e341 | 23,135 |
import math
def calculate_distance(p1, p2):
"""
Calculate distance between two points
param p1: tuple (x,y) point1
param p2: tuple (x,y) point2
return: distance between two points
"""
x1, y1 = p1
x2, y2 = p2
d = math.sqrt(pow(x2 - x1, 2) + pow(y2 - y1, 2))
return d | 756b609a91e17299eb879e27e83cd663800e46dd | 23,136 |
def statistics(request, network):
""" some nice statistics for the whole pool """
# some basic statistics
days = 1
current_height, all_blocks, pool_blocks, pool_blocks_percent, bbp_mined = get_basic_statistics(network, days)
miners_count = get_miner_count(network, days)
graph_days = 7
t... | d44033323bfe041ee53109a9274ff2fd9c9d9df3 | 23,137 |
from textwrap import dedent
def package_load_instructions(inst_distributions):
"""Load instructions, displayed in the package notes"""
per_package_inst = ''
for dist in inst_distributions:
if dist.type == 'zip':
per_package_inst += dedent(
"""
# Loadi... | 321a7486f27a3cb327ae7556e317bc53c24726ac | 23,138 |
def specialize_transform(graph, args):
"""Specialize on provided non-None args.
Parameters that are specialized on are removed.
"""
mng = graph.manager
graph = transformable_clone(graph, relation=f'sp')
mng.add_graph(graph)
for p, arg in zip(graph.parameters, args):
if arg is not No... | 44b892312ff677bdc5bee84bf5df1e1dc4bd5ba5 | 23,139 |
from functools import reduce
import operator
import itertools
def Multiplication(k):
"""
Generate a function that performs a polynomial multiplication and return coefficients up to degree k
"""
assert isinstance(k, int) and k > 0
def isum(factors):
init = next(factors)
return redu... | 23a663231e44b09cd446e9ba1d269e7b123efc1d | 23,140 |
def safe_divide(a, b):
"""
Avoid divide by zero
http://stackoverflow.com/questions/26248654/numpy-return-0-with-divide-by-zero
"""
with np.errstate(divide='ignore', invalid='ignore'):
c = np.true_divide(a, b)
c[c == np.inf] = 0
c = np.nan_to_num(c)
return c | 104970a64f5d77f674a46f9da08b039345fa546a | 23,141 |
def plot_lc(data=None, model=None, bands=None, zp=25., zpsys='ab', pulls=True,
xfigsize=None, yfigsize=None, figtext=None, model_label=None,
errors=None, ncol=2, figtextsize=1., show_model_params=True,
tighten_ylim=False, fname=None, **kwargs):
"""Plot light curve data or model l... | b700a03ce9e16cdbcc32d22ac4a9124e70feba70 | 23,142 |
def read_image(filepath, gray=False):
"""
read image
:param filepath:
:param gray:
:return:
"""
if gray:
return cv2.cvtColor(cv2.imread(filepath), cv2.COLOR_BGR2GRAY)
else:
return cv2.cvtColor(cv2.imread(filepath), cv2.COLOR_BGR2RGB) | d5743c8ad517f5c274e3ac64d6082ea36539cfe3 | 23,143 |
from ...hubble.helper import parse_hub_uri
def mixin_hub_pull_parser(parser):
"""Add the arguments for hub pull to the parser
:param parser: the parser configure
"""
def hub_uri(uri: str) -> str:
parse_hub_uri(uri)
return uri
parser.add_argument(
'uri',
type=hub_... | 9f62462baecc744ab7b7e3e78b5446a3d5347569 | 23,144 |
from typing import Tuple
from typing import List
import yaml
from typing import Dict
def load_config() -> Tuple[List, List]:
"""Get configuration from config file.
Returns repo_paths and bare_repo_dicts.
"""
if config_file.exists():
with open(config_file, "r") as ymlfile:
config =... | e9f483c6cc3ff1335a5d9866cc577e72a9a8084f | 23,145 |
def deindented_source(src):
"""De-indent source if all lines indented.
This is necessary before parsing with ast.parse to avoid "unexpected
indent" syntax errors if the function is not module-scope in its
original implementation (e.g., staticmethods encapsulated in classes).
Parameters
-------... | 227d5e8e35b251f02ce5e9237f8120d2dd9c7e4b | 23,146 |
def home():
"""Render the home page."""
form = SearchForm()
search_results = None
if form.validate_on_submit():
search_term = form.username.data
cur = conn.cursor()
cur.execute(f"SELECT * FROM student WHERE name = '{search_term}';")
search_results = cur.fetchall()
... | d578e4ba95af57828dfa6f483ad9aa0aeac8ea92 | 23,147 |
def capacity():
"""
Returns the raw capacity of the filesystem
Returns:
filesystem capacity (int)
"""
return hdfs.capacity() | c9e220b19a1a1a200d2393bb98116be1767370b9 | 23,148 |
async def deploy(current_user: User = Depends(auth.get_current_user)):
""" This function is used to deploy the model of the currently trained chatbot """
response = mongo_processor.deploy_model(bot=current_user.get_bot(), user=current_user.get_user())
return {"message": response} | cb7d53f605616e8a979dd144b786313c99f7a244 | 23,149 |
def find_rocks(img,rgb_thresh=(100, 100, 60)):
""" Find rock in given image frame"""
color_select = np.zeros_like(img[:,:,0])
# Require that each pixel be above all three threshold values in RGB
# above_thresh will now contain a boolean array with "True"
# where threshold was met
above_thresh = ... | f0bffadfdf826f1f649029f3aaf224d07681589e | 23,150 |
from pathlib import Path
def maybe_start_with_home_prefix(p: Path) -> Path:
"""
If the input path starts with the home directory path string, then return
a path that starts with the home directory and points to the same location.
Otherwise, return the path unchanged.
"""
try:
return Pa... | 6ee4e49e8dfb9bc68a1c10f5ea792715fb5d5336 | 23,151 |
def parse_nrc_lexicon():
"""Extract National Resource Council Canada emotion lexicon from http://saifmohammad.com/WebPages/lexicons.html
Returns:
{str: [str]} A defaultdict of emotion to list of associated words
"""
emotion2words = defaultdict(list)
with open(NRC_LEXICON) as lexicon_file:
... | 869988934a7ab6a1b0b601f96472ff85a2686975 | 23,152 |
def rouge_2_fscore(predictions, labels, **unused_kwargs):
"""ROUGE-2 F1 score computation between labels and predictions.
This is an approximate ROUGE scoring method since we do not glue word pieces
or decode the ids and tokenize the output.
Args:
predictions: tensor, model predictions
labels: tensor,... | 1c0ab9b514c36cf9947b31624e8a2cf308cdfe6b | 23,153 |
from datetime import datetime
def clear_log():
"""clear log file"""
if MODE == "debug":
log_line = f"start {str(datetime.today())} \n\n"
with open("temp/log.txt", "w", encoding="latin-1") as myfile:
myfile.write(log_line)
return () | 9a12f62b2de98ab8ef176ca23b7dbb49ca1486ea | 23,154 |
def enhancedFeatureExtractorDigit(datum):
"""
Your feature extraction playground.
You should return a util.Counter() of features
for this datum (datum is of type samples.Datum).
## DESCRIBE YOUR ENHANCED FEATURES HERE...
##
"""
features = basicFeatureExtractorDigit(datum)
"*** YOUR CODE HERE ***"... | 564e324cd12b2cb98bd65cb053b5acea2f4d5831 | 23,155 |
import sys
def query_yes_no(question, default="yes"):
"""Ask a yes/no question via raw_input() and return their answer.
"question" is a string that is presented to the user.
"default" is the presumed answer if the user just hits <Enter>.
It must be "yes" (the default), "no" or None (meaning
... | fae49b63a25c11be8183cff47b36a8dd5b7f2615 | 23,156 |
def tested_function(x):
"""
Testovana funkce
Da se sem napsat vselijaka cunarna
"""
freq = 1
damp_fac = 0.1
val = np.sin(freq * x)
damp = np.exp(-1 * damp_fac * abs(x))
return val * damp | 95808b55ace5b0536104f02de874344aa02d7033 | 23,157 |
def parse_line(line):
"""
Parses a (non-comment) line of a GFF3 file. The attribute field is parsed into a dict.
:param line: line to parse as string
:return: dict with for each column (key) the corresponding value
"""
parts = line.strip().split('\t')
output = {}
if len(parts) != len(... | 0ea071c5a4165fd2bbbe77798bec09b033250c72 | 23,158 |
import requests
from datetime import datetime
def get_time_string(place: str = "Europe/Moscow"):
"""
Get time data from worldtimeapi.org and return simple string
Parameters
----------
place : str
Location, i.e. 'Europe/Moscow'.
Returns
-------
string
Time in format '%... | f15ef5a843317c55d3c60bf2ee8c029258e1cd78 | 23,159 |
from typing import Type
from typing import Dict
from typing import Callable
def new_worker_qthread(
Worker: Type[WorkerProtocol],
*args,
_start_thread: bool = False,
_connect: Dict[str, Callable] = None,
**kwargs,
):
"""This is a convenience function to start a worker in a Qthread.
In mos... | f607799bd7abf4b275d90bc4523dc9f0e8d2d200 | 23,160 |
import fnmatch
def contains(filename, value=None, fnvalue=None):
""" If a string is contained within a yaml (and is not a comment or key), return where we found it """
if filename in ALL_STRINGS:
for el in ALL_STRINGS[filename]:
if (value and value in el[0]) or (fnvalue and fnmatch.fnmatch... | 2c21aee4fe7121ad26e588b33dfa2f09f1d4066b | 23,161 |
def plot_with_overview(
ds,
tn,
forcing_vars=["dqdt_adv", "dtdt_adv"],
domain_var="q",
overview_window_width=4,
):
"""
Produce a forcing plot with timestep `tn` highlighted together with
overview plots of domain data variable `domain_var`. The width over the
overview plot is set with... | e02be6157853b5a0a409fe45a02f52d685913e22 | 23,162 |
def optimize(nn_last_layer, correct_label, learning_rate, num_classes):
"""
Build the TensorFLow loss and optimizer operations.
:param nn_last_layer: TF Tensor of the last layer in the neural network
:param correct_label: TF Placeholder for the correct label image
:param learning_rate: TF Placeholde... | b618626f7e458e1ef3ffda74af7532d93668a9cb | 23,163 |
def expanded_indexer(key, ndim):
"""Given a key for indexing an ndarray, return an equivalent key which is a
tuple with length equal to the number of dimensions.
The expansion is done by replacing all `Ellipsis` items with the right
number of full slices and then padding the key with full slices so tha... | a4fa3b1e4a106350348c128ef5ce8b86dac1f0c0 | 23,164 |
def downsample(
data, sampling_freq=None, target=None, target_type="samples", method="mean"
):
"""Downsample pandas to a new target frequency or number of samples
using averaging.
Args:
data: (pd.DataFrame, pd.Series) data to downsample
sampling_freq: (float) Sampling frequency of data... | 4dca048a77ac1f20d0ee1bac702c48e4311f8900 | 23,165 |
def available_commands(mod, ending="_command"):
"""Just returns the available commands, rather than the whole long list."""
commands = []
for key in mod.__dict__:
if key.endswith(ending):
commands.append(key.split(ending)[0])
return commands | 38a96ca9485e9814ba161550613d3d96db126693 | 23,166 |
def retrieve_browse(browse_location, config):
""" Retrieve browse image and get the local path to it.
If location is a URL perform download.
"""
# if file_name is a URL download browse first and store it locally
validate = URLValidator()
try:
validate(browse_location)
input_filen... | 6c5b5e916542db20584205588e5e2929df692b38 | 23,167 |
def add_suffix(input_dict, suffix):
"""Add suffix to dict keys."""
return dict((k + suffix, v) for k,v in input_dict.items()) | 7dbedd523d24bfdf194c999b8927a27b110aad3e | 23,168 |
from autots.tools.transform import GeneralTransformer
from autots.tools.transform import simple_context_slicer
from datetime import datetime
def ModelPrediction(
df_train,
forecast_length: int,
transformation_dict: dict,
model_str: str,
parameter_dict: dict,
frequency: str = 'infer',
predi... | afb3dccc20c2399a50c2564aeb0d1f214d80dd6a | 23,169 |
def make_year_key(year):
"""A key generator for sorting years."""
if year is None:
return (LATEST_YEAR, 12)
year = str(year)
if len(year) == 4:
return (int(year), 12)
if len(year) == 6:
return (int(year[:4]), int(year[4:]))
raise ValueError('invalid year %s' % year) | ced5617772af14a3e438cb268f58ceee3895083d | 23,170 |
def set_stereo_from_geometry(gra, geo, geo_idx_dct=None):
""" set graph stereo from a geometry
(coordinate distances need not match connectivity -- what matters is the
relative positions at stereo sites)
"""
gra = without_stereo_parities(gra)
last_gra = None
atm_keys = sorted(atom_keys(gra... | d26248883b90a561c8d70bb8a12be68affe40c2a | 23,171 |
def multiply_MPOs(op0, op1):
"""Multiply two MPOs (composition along physical dimension)."""
# number of lattice sites must agree
assert op0.nsites == op1.nsites
L = op0.nsites
# physical quantum numbers must agree
assert np.array_equal(op0.qd, op1.qd)
# initialize with dummy tensors and bo... | 62e9e250c46d281ccbb39c0ddf1082d45386a1d3 | 23,172 |
import json
from typing import OrderedDict
def build_list_of_dicts(val):
"""
Converts a value that can be presented as a list of dict.
In case top level item is not a list, it is wrapped with a list
Valid values examples:
- Valid dict: {"k": "v", "k2","v2"}
- List of dict: [{"k": "v"... | dfd92f619ff1ec3ca5cab737c74af45c86a263e0 | 23,173 |
def add_borders_to_DataArray_U_points(da_u, da_v):
"""
A routine that adds a column to the "right" of the 'u' point
DataArray da_u so that every tracer point in the tile
will have a 'u' point to the "west" and "east"
After appending the border the length of da_u in x
will be +1 (one new colu... | e9b3e057fb56a998821e84a96b77e00bac4e0923 | 23,174 |
def arg(prevs, newarg):
""" Joins arguments to list """
retval = prevs
if not isinstance(retval, list):
retval = [retval]
return retval + [newarg] | 8d591595add095542ad697b4bd54642a4a14a17c | 23,175 |
def quote_plus(s, safe='', encoding=None, errors=None):
"""Quote the query fragment of a URL; replacing ' ' with '+'"""
if ' ' in s:
s = quote(s, safe + ' ', encoding, errors)
return s.replace(' ', '+')
return quote(s, safe, encoding, errors) | e0a5ba9237550856b695e236e7a457c34f053ba0 | 23,176 |
def mod(x, y):
"""Implement `mod`."""
return x % y | f19c019ed3cf072b1b5d3ec851c14a824c14edb5 | 23,177 |
from typing import List
def _lower_batch_matmul(op: relay.Call, inputs: List[te.Tensor]) -> te.Tensor:
"""Lower a batch_matmul using cuBLAS."""
return cublas.batch_matmul(
inputs[0],
inputs[1],
transa=op.attrs["transpose_a"],
transb=op.attrs["transpose_b"],
dtype=op.che... | 2fa7be16c558e0edf9233d699139c004b44a93c2 | 23,178 |
from re import S
def cross_entropy_loss(inputs, labels, rescale_loss=1):
""" cross entropy loss with a mask """
criterion = mx.gluon.loss.SoftmaxCrossEntropyLoss(weight=rescale_loss)
loss = criterion(inputs, labels)
mask = S.var('mask')
loss = loss * S.reshape(mask, shape=(-1,))
return S.make_... | 7151ace5b1ac93439defe93a4d6e45002cbfb8a6 | 23,179 |
def as_wrapping_formatters(objs, fields, field_labels, formatters, no_wrap=None, no_wrap_fields=[]):
"""This function is the entry point for building the "best guess"
word wrapping formatters. A best guess formatter guesses what the best
columns widths should be for the table celldata. It does this ... | 1f60c9ebaebb919ab8d4478e029aed649931df8a | 23,180 |
import torch
def classification_metrics(n_classes: int = 2):
"""Function to set up the classification metrics"""
logger.info(f"Setting up metrics for: {n_classes}")
metrics_dict_train = torch.nn.ModuleDict(
{
"accuracy": Accuracy(),
"recall": Recall(),
"precisio... | b876c7ac3da006cf54bc04e91f13de5a35103dab | 23,181 |
def ping(device,
address,
ttl=None,
timeout=None,
tos=None,
dscp=None,
size=None,
count=None,
source=None,
rapid=False,
do_not_fragment=False,
validate=False,
vrf=None,
command=None,
output=None... | 1e13d1af7e9678bc8650bc3173858b148fbedc86 | 23,182 |
def find_host(connection, sd_name):
"""
Check if we can preform a transfer using the local host and return a host
instance. Return None if we cannot use this host.
Using the local host for an image transfer allows optimizing the connection
using unix socket. This speeds up the transfer significantl... | 462a380a4df1baac2fb45b071d266c3a6cf6b2d7 | 23,183 |
import numpy
import scipy
def _subSquare(vectors, var, full=False):
"""
given a series of vectors, this function calculates:
(variances,vectors)=numpy.linalg.eigh(vectors.H*vectors)
it's a seperate function because if there are less vectors
than dimensions the process can be accelerated, it j... | 8f588d3f64eaf892a1481983436c13d7c5010f12 | 23,184 |
def to_pickle(data):
"""
This prepares data on arbitrary form to be pickled. It handles any nested
structure and returns data on a form that is safe to pickle (including
having converted any database models to their internal representation).
We also convert any Saver*-type objects back to their norm... | e52dddec911b0ac548daed81452d041aee41f548 | 23,185 |
import requests
def spot_silver_benchmark_sge() -> pd.DataFrame:
"""
上海黄金交易所-数据资讯-上海银基准价-历史数据
https://www.sge.com.cn/sjzx/mrhq
:return: 历史数据
:rtype: pandas.DataFrame
"""
url = "https://www.sge.com.cn/graph/DayilyShsilverJzj"
payload = {}
r = requests.post(url, data=payload)
dat... | 8bfcc5d24116231835a41447fb284f346586628e | 23,186 |
def requires_all_permissions(permission, login_url=None, raise_exception=False):
"""
Decorator for views that defines what permissions are required, and also
adds the required permissions as a property to that view function.
The permissions added to the view function can then be used by the sidebar
... | e2368c7f32185ebe1ee7cec50625a72b0fe9ec03 | 23,187 |
def hasTable(cur, table):
"""checks to make sure this sql database has a specific table"""
cur.execute("SELECT name FROM sqlite_master WHERE type='table' AND name='table_name'")
rows = cur.fetchall()
if table in rows:
return True
else:
return False | dfdb3db0901832330083da8b645ae90e28cfb26d | 23,188 |
def _check_wkt_load(x):
"""Check if an object is a loaded polygon or not. If not, load it."""
if isinstance(x, str):
try:
x = loads(x)
except WKTReadingError:
warn('{} is not a WKT-formatted string.'.format(x))
return x | 457a02cffa7f56e05ad7ca3a8df83f5f719346b7 | 23,189 |
def _yielddefer(function, *args, **kwargs):
"""
Called if a function decorated with :func:`yieldefer` is invoked.
"""
try:
retval = function(*args, **kwargs)
except:
return defer.fail()
if isinstance(retval, defer.Deferred):
return retval
if not (hasattr(ret... | b226984e1b4845783dc47f187d24482e040cc6c0 | 23,190 |
import scipy
import warnings
def dimension_parameters(time_series, nr_steps=100, literature_value=None,
plot=False, r_minmin=None, r_maxmax=None,
shortness_weight=0.5, literature_weight=1.):
""" Estimates parameters r_min and r_max for calculation of correlation
... | abec1b064b42083b9e60bb2cb4827d7fe8f7b2e9 | 23,191 |
import logging
import os
import subprocess
def GetAllCmdOutput(args, cwd=None, quiet=False):
"""Open a subprocess to execute a program and returns its output.
Args:
args: A string or a sequence of program arguments. The program to execute is
the string or the first item in the args sequence.
cwd: I... | 97d38ab449d7c9237370ba0cc531a2b2790e36c8 | 23,192 |
def seir_model_with_soc_dist(init_vals, params, t):
"""
SEIR infection model with social distancing.
rho = social distancing factor.
"""
S_0, E_0, I_0, R_0 = init_vals
S, E, I, R = [S_0], [E_0], [I_0], [R_0]
alpha, beta, gamma, rho = params
dt = t[1] - t[0]
for _ in t[1:]:
... | dae5ace760055f5bbb78f079b660e8d55587b2fe | 23,193 |
import torch
def greeq(data, transmit=None, receive=None, opt=None, **kwopt):
"""Fit a non-linear relaxometry model to multi-echo Gradient-Echo data.
Parameters
----------
data : sequence[GradientEchoMulti]
Observed GRE data.
transmit : sequence[PrecomputedFieldMap], optional
Map(... | 4190b82de68f6362bf6cec48e4e88419bab7b0da | 23,194 |
import sympy
import warnings
def _add_aliases_to_namespace(namespace, *exprs):
"""
Given a sequence of sympy expressions,
find all aliases in each expression and add them to the namespace.
"""
for expr in exprs:
if hasattr(expr, 'alias') and isinstance(expr, sympy.FunctionClass):
... | e90e311aacd9c9c41363badc690ad25c18501251 | 23,195 |
def rotICA(V, kmax=6, learnrate=.0001, iterations=10000):
""" ICA rotation (using basicICA) with default parameters and normalization of
outputs.
:Example:
>>> Vica, W = rotICA(V, kmax=6, learnrate=.0001, iterations=10000)
"""
V1 = V[:, :kmax].T
[W, changes_s] = basicICA(V1, learnrate, i... | 2db4bb0d5c5c5f70c9f7cf5a20b27fd2b146e26f | 23,196 |
import socket
def getipbyhost(hostname):
""" return the IP address for a hostname
"""
return socket.gethostbyname(hostname) | 9556f537e16fd710a566a96a51d4262335967893 | 23,197 |
def reduce_mem_usage(df) -> pd.DataFrame:
"""DataFrameのメモリ使用量を節約するための関数.
Arguments:
df {DataFrame} -- 対象のDataFrame
Returns:
[DataFrame] -- メモリ節約後のDataFrame
"""
numerics = [
'int8', 'int16', 'int32', 'int64', 'float16', 'float32', 'float64'
]
start_mem = df.memory_u... | b317c85aee9f51d221b3895bcc9ac1a6bc3535f6 | 23,198 |
import typing
def findparam(
parameters: _TYPE_FINDITER_PARAMETERS,
selector: _TYPE_FINDITER_SELECTOR
) -> typing.Iterator[_T_PARAM]:
"""
Return an iterator yielding those parameters (of type
:class:`inspect.Parameter` or :class:`~forge.FParameter`) that are
mached by the selector.... | 61da9c7e453d04bf2db9c5f923e815e250da4b53 | 23,199 |
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