content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def scale_intensity(data, out_min=0, out_max=255):
"""Scale intensity of data in a range defined by [out_min, out_max], based on the 2nd and 98th percentiles."""
p2, p98 = np.percentile(data, (2, 98))
return rescale_intensity(data, in_range=(p2, p98), out_range=(out_min, out_max)) | 57df2200fbefa4ab6f1c91f46063b1b1f147301e | 23,078 |
def raises_regex_op(exc_cls, regex, *args):
"""
self.assertRaisesRegex(
ValueError, "invalid literal for.*XYZ'$", int, "XYZ"
)
asserts.assert_fails(lambda: int("XYZ"),
".*?ValueError.*izznvalid literal for.*XYZ'$")
"""
# print(args)
# assert... | 9b0e6aa0692d2285467578083f76c888de9874c1 | 23,079 |
def getParInfo(sourceOp, pattern='*', names=None,
includeCustom=True, includeNonCustom=True):
"""
Returns parInfo dict for sourceOp. Filtered in the following order:
pattern is a pattern match string
names can be a list of names to include, default None includes all
includeCustom to include custom parame... | 01eafb065ef98e1fd4676898aeb8d0c5a7a74b9d | 23,080 |
def generate_crontab(config):
"""Generate a crontab entry for running backup job"""
command = config.cron_command.strip()
schedule = config.cron_schedule
if schedule:
schedule = schedule.strip()
schedule = strip_quotes(schedule)
if not validate_schedule(schedule):
sc... | d958c47e0673d19dbd8d8eb2493995cdc2ada7ff | 23,081 |
import attr
def to_dict(observation: Observation):
"""Convert an Observation object back to dict format"""
return _unprefix_attrs(attr.asdict(observation)) | 4ffd5ad24fee6bd983d7cb85ac7d1b9eeb56e751 | 23,085 |
def _consolidate_extrapolated(candidates):
"""Get the best possible derivative estimate, given an error estimate.
Going through ``candidates`` select the best derivative estimate element-wise using
the estimated candidates, where best is defined as minimizing the error estimate
from the Richardson extr... | 2641a56d852ed9e4065c7dfad4b1fd51ef581b91 | 23,086 |
import torch
def build_wideresnet_hub(
num_class: int,
name='wide_resnet50_2',
pretrained=True):
"""[summary]
Normalized
mean = [0.485, 0.456, 0.406]
std = [0.229, 0.224, 0.225]
Args:
name (str, optional): [description]. Defaults to 'wide_resnet50_2'.
pretr... | 39f977a9ab368bd9fa15fb36c600c350afca7f53 | 23,088 |
def get_phoenix_model_wavelengths(cache=True):
"""
Return the wavelength grid that the PHOENIX models were computed on,
transformed into wavelength units in air (not vacuum).
"""
wavelength_url = ('ftp://phoenix.astro.physik.uni-goettingen.de/v2.0/'
'HiResFITS/WAVE_PHOENIX-ACES... | ff5632086ffb3aa3eb6655c3ba18e182f0724bc4 | 23,089 |
def accuracy_boundingbox(data, annotation, method, instance): ## NOT IMPLEMENTED
"""
Calculate how far off each bounding box was
Parameters
----------
data: color_image, depth_image
annotation: pascal voc annotation
method: function(instance, *data)
instance: instance of object
... | 78fa63d5e2cbdad843feaddd277b98886789a517 | 23,091 |
import logging
def test_kbd_gpios():
"""Test keyboard row & column GPIOs.
Note, test only necessary on 50pin -> 50pin flex
These must be tested differently than average GPIOs as the servo side logic,
a 4to1 mux, is responsible for shorting colX to rowY where X == 1|2 and Y
= 1|2|3. To test the ... | 237f26a5da5711c480ef9dadbaa46170ca97c884 | 23,093 |
def fields_for_model(model):
"""
This function returns the fields for a schema that matches the provided
nautilus model.
Args:
model (nautilus.model.BaseModel): The model to base the field list on
Returns:
(dict<field_name: str, graphqlType>): A mapping of f... | 9eb6f1a51513ff6b42ab720a1196cea1402cac23 | 23,094 |
def _landstat(landscape, updated_model, in_coords):
"""
Compute the statistic for transforming coordinates onto an existing
"landscape" of "mountains" representing source positions. Since the
landscape is an array and therefore pixellated, the precision is limited.
Parameters
----------
lan... | 0205654ef8580a0d6731155d7d0c2b2c1a360e9c | 23,095 |
def presence(label):
"""Higher-order function to test presence of a given label
"""
return lambda x, y: 1.0 * ((label in x) == (label in y)) | 49c7e0b4b7af69c808917af7ab4d6b56a7a4ef89 | 23,096 |
def make_formula(formula_str, row, col, first_data_row=None):
# noinspection SpellCheckingInspection
"""
A cell will be written as a formula if the HTML tag has the attribute "data-excel" set.
Note that this function is called when the spreadsheet is being created. The cell it applies to knows ... | d9a41a2906151a050afa78e099278b7d5462faa9 | 23,098 |
def select(population, to_retain):
"""Go through all of the warroirs and check which ones are best fit to breed and move on."""
#This starts off by sorting the population then gets all of the population dived by 2 using floor divison I think
#that just makes sure it doesn't output as a pesky decimal. Then i... | 4dc1251f09e6bd976d170017bbd328563e9ef786 | 23,099 |
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 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 |
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 |
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 |
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 |
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 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 |
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 |
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 |
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 |
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 |
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