content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import os
def gas_3parallel(method="nikuradse"):
"""
:param method: Which results should be loaded: nikuradse or prandtl-colebrook
:type method: str, default "nikuradse"
:return: net - STANET network converted to a pandapipes network
:rtype: pandapipesNet
:Example:
>>> pandapipes.net... | b06b11bc346e430252901fe8fec19402e1e6aff9 | 3,630,700 |
def get_coordinates(df, year: str):
"""
Add column to the given DataFrame which contains coordinates of
all films filmed at given year.
"""
df = df[df["Year"] == year]
coordinates = []
geolocator = Nominatim(user_agent="main.py")
for i in range(120):
df_location = df.iloc[i, 2]
... | ed08cddf7c8a0333dc6cfca4e4c70703bff029f0 | 3,630,701 |
from pathlib import Path
import json
def get_partyname_wordlist(
json_path: Path,
filter_full_name: t.List = [],
name_keys: t.List = ["full_name", "label", "short_name", "other_names"],
lowercase: bool = False,
add_spaces: bool = False,
):
"""Create a set of all possible and abreviatoions of p... | ed10da9f689af8f56cc2fc4eeb899764a5512646 | 3,630,702 |
def ceil_even(x):
"""
Return the smallest even integer not less than x. x can be integer or float.
"""
return round_even(x+1) | 098f1fb847aa36f288f6b43030627ab5570117a6 | 3,630,703 |
def dict_to_PI(d, classes):
"""
Convert a dictionary to a PresentationInfo,
using a pre-fetched dictionary of CssClass objects
"""
if d['prestype'] == 'command':
return PresentationInfo(prestype=d['prestype'], name=d['name'])
else:
c = classes.get(d['name'])
if c is None:... | 620b0d21bc199046bf5dc05be0cba7269f340bbb | 3,630,704 |
import typing
def no_batch_embed(sentence: str) -> typing.List[float]:
"""Returns a list with the numbers of the vector into which the
model embedded the string."""
return model.encode(sentence).tolist() | 1351c4e3fc69ea261a149f864545c2c9275e78a5 | 3,630,705 |
def make_video(video_images_files, name, fps=30):
"""Given list of image files, create video"""
# create video
print('\nCreating video...')
clip = ImageSequenceClip(video_images_files, fps)
# write video
clip.write_videofile(name)
return clip | 54037289258c5bfd5f682d6f75a442158949b228 | 3,630,706 |
def find_internal_gaps(seq):
"""
Accepts a string and returns the positions of all of the gaps in the sequence which are flanked by nt bases
:param seq: str
:return: list of [start,end] of all of the internal gaps
"""
gaps = find_gaps(seq)
seq_len = len(seq) -1
internal_gaps = []
iu... | a890eba3dff6c8be186c6be1a2477daf658a65e6 | 3,630,707 |
def test_loop(model, ins, batch_size=None, verbose=0, steps=None):
"""Abstract method to loop over some data in batches.
Arguments:
model: Model instance that is being evaluated in Eager mode.
ins: list of tensors to be fed to `f`.
batch_size: integer batch size or `None`.
verbose: verbosit... | 9bed19f31eabdad791091bd68196e90d422a65e1 | 3,630,708 |
def find_bands(bands, target_avg, target_range, min_shows):
"""
Searches dictionary of bands with band name as keys and
competition scores as values for bands that are within the
range of the target average and have performed the minimum
number of shows. Returns a list of bands that meet the search
... | 1b2b93f0a1d4236ad62102205606eff8afb3802a | 3,630,709 |
def get_named_targets():
""" Return a list of named target date ranges """
return ["std_train", "std_val", "std_test", "std_ens", "std_all", \
"std_future", "std_contest_fri", "std_contest", "std_contest_daily", "std_contest_eval", \
"std_contest_eval_daily", "std_paper", "std_paper_daily"] | 23a15efff1facc5028e980d659ca6d2f61cdddf0 | 3,630,710 |
import scipy
def create_edge_linestrings(G_, remove_redundant=True, verbose=False):
"""
Ensure all edges have the 'geometry' tag, use shapely linestrings.
Notes
-----
If identical edges exist, remove extras.
Arguments
---------
G_ : networkx graph
Input networkx graph, with e... | 478459007538c8d250b1d6f518300d9476866df4 | 3,630,711 |
def get_licenses(service_instance, license_manager=None):
"""
Returns the licenses on a specific instance.
service_instance
The Service Instance Object from which to obrain the licenses.
license_manager
The License Manager object of the service instance. If not provided it
will... | f0c4f7fdc2418f09e7c7e319b8ec670f98db9ca3 | 3,630,712 |
def is_installed(request, project_id=None):
"""Check whether the extension {{ cookiecutter.project_name }} is installed."""
return JsonResponse({'is_installed': True, 'msg': '{{ cookiecutter.project_name }} is installed'}) | ab25af53719e832d5f97b1f8757d630f6d4fec40 | 3,630,713 |
import os
def predict(model, data, out_fname = None):
"""
Description:
-----------
This function is used to predict the EV values for a given dataframe
Parameters:
-----------
model: The model to be finetuned (tf.keras.models.Model)
data: The dataframe to be predicted (pandas.DataFra... | 5207523a3247f8bfbc816cf53e122c3924266846 | 3,630,714 |
def line_order(line):
"""Recursive search for the line's hydrological level.
Parameters
----------
line: a Centerline instance
Returns
-------
The line's order
"""
if len(line.inflows) == 0:
return 0
else:
levels = [line_order(s) for s in line.inflows]
... | d2342477abc9d53fbbe02c5c426b518ee59ca732 | 3,630,715 |
def get_data_colums(epoch):
"""Return the data columns of a given epoch
:param epoch: given epoch in a numpy array, already readed from .csv
"""
ID = epoch[:,0];
RA = epoch[:,1];
RA_err = epoch[:,2];
Dec = epoch[:,3];
Dec_err = epoch[:,4];
Flux = epoch[:,5];
Flux_err = epoch[:,... | ba497f0aacf8356b80c8c433af05716b90519665 | 3,630,716 |
def reset_columns_DataFrame(df, new_columns=None):
"""
Rename *all* columns in a dataframe (and return a copy).
Possible new_columns values:
- None: df.columns = list(df.columns)
- List: df.columns = new_columns
- callable: df.columns = [new_columns(x) for x in df.columns]
- str && df.shap... | 7251ec76dcf828ad1ebc4bf96dfc19a2059f37f5 | 3,630,717 |
def bin_position(max_val):
"""returns position features using some symbols. Concatenate them at the end of
sentences to represent sentence lengths in terms of one of the three buckets.
"""
symbol_map = {0: " `", 1: " _", 2: " @"}
if max_val <= 3:
return [symbol_map[i] for i in range(max_val)... | 2c6caf100c07d56211ba8f8bfcef103dd623c6f5 | 3,630,718 |
def norm(g,scale=True):
"""normalises a network on the last axis, scale decides if there is a learnable multiplicative factor"""
g.X=BatchNormalization(axis=-1,scale=scale)(g.X)
return g | ef9a26e93b870a3d2cfd85aed3cf24d8129b464a | 3,630,719 |
def makeEvent(rawEvent, time = 0):
"""Create a midi event from a raw event received from the sequencer.
"""
eventData = rawEvent.data
if rawEvent.type == SSE.NOTEON:
result = NoteOn(time, eventData.note.channel, eventData.note.note,
eventData.note.velocity
... | 5b7a24dfecfb5f0e1531e799dd0e77d9bb548360 | 3,630,720 |
def rule2(n):
"""2sqrt"""
k = map(lambda x:x*2,rule1(n))
return k | 7ea1b5e06be20ab4832e68536e210d8baf036925 | 3,630,721 |
def charge_sublayers(ich):
""" Parse the InChI string for the formula sublayer.
:param ich: InChI string
:type ich: str
:rtype: dict[str: str]
"""
return automol.convert.inchi.charge_sublayers(ich) | 6532fc0ab5bd5b8a1e97ec5297a8394f67a6066d | 3,630,722 |
import os
def f_split_path(fpath, normpath=True):
"""
Splits path into a list of its component folders
Args:
normpath: call os.path.normpath to remove redundant '/' and
up-level references like ".."
"""
if normpath:
fpath = os.path.normpath(fpath)
allparts = []
... | 0a0fafe2263cb77727609053866f7c1b95fa12d0 | 3,630,723 |
import os
def get_path(*args):
""" utility method"""
return os.path.join(THIS_DIR, 'primitives_data', *args) | 5d274e81a3b6bd621ff54ce841f26a978406928d | 3,630,724 |
import requests
def mixcloud_profile():
""" Display the authorized user's profile """
# Note: We would normally do this but Mixcloud requires specific parameters
#client_id = current_app.config['CONFIG']['accounts']['mixcloud']['client_id']
#mixcloud_session = OAuth2Session(client_id, token=session['... | 18f0f29b31e0becb04fd2a6bb59763298f246668 | 3,630,725 |
def search_metas(metas, criteria, keywords):
""" Note: storage may contain message from others """
msgs = []
for meta in metas:
if not satisfy_criteria(criteria, meta):
continue
if keywords == None or len(keywords) == 0:
msgs.append(meta)
continue
... | 6bdf1593b2591ab0bc1a028ae854e19858614cda | 3,630,726 |
import logging
def count_large_cargos(b):
"""Gather number of large cargos in each planet."""
def find_planets():
return sln.finds(sln.find(b, By.ID, 'planetList'),
By.CLASS_NAME, 'planetlink')
num_planets = len(find_planets())
logging.info('Found {} planets'.format(num_planets))
... | 31b462da2a54be6979b6b7861709caa27af5e37b | 3,630,727 |
def get_project(service, project_id):
"""Build service object and return the result of calling the API 'get' function for the projects resource."""
operation = service.projects().get(projectId=project_id).execute()
return operation | 9c512fbf2476039524e67178ada36fd15ebe8cee | 3,630,728 |
def parse(src: str):
"""
Compila string de entrada e retorna a S-expression equivalente.
"""
return parser.parse(src) | 4ffcc39b63839c5668b3ea435064249f60dbf222 | 3,630,729 |
import ast
from typing import Tuple
from typing import List
from typing import Set
def get_parser_init_and_actions(source: ast.Module) -> \
Tuple[List[ast.AST], str, Set[str]]:
"""
Function used to extract necessary imports, parser and argument creation
function calls
Parameters
--------... | 0a8920d69f51a7a379ee8415efcd277d3adcdc48 | 3,630,730 |
from pathlib import Path
from typing import Dict
def write_json_to_file(filepath: Path, jsonstr: Dict[str, str], indent: int = 4, eof_line=True):
"""Dosyaya JSON yazar.
Dosya bulunamazsa ekrana raporlar hata fırlatmaz
Arguments:
filepath {Path} -- Okunacak dosyanın yolu
jsonstr {Dict[str,... | 59fdf74661350811c0fcd685d5949c37376e53d7 | 3,630,731 |
import os
def get_version():
""" str: The package version. """
global_vars = {}
# Compile and execute the individual file to prevent
# the package from being automatically loaded.
source = read(os.path.join("test_python_package", "__version__.py"))
code = compile(source, "version.py", "exec"... | 2f2769927e050dab348ff421aa541066184f322d | 3,630,732 |
def aTimesFiltered(data, filterFunction, microBin=False):
"""
Filter a list of arrivalTimes
===========================================================================
Input Meaning
---------------------------------------------------------------------------
data Object with ... | b71a08c8431fc2c7cb8bca6c075d798ebea48db4 | 3,630,733 |
import select
def get_publication_group(project, group_id):
"""
Get all data for a single publication group
"""
connection = db_engine.connect()
groups = get_table("publication_group")
statement = select([groups]).where(groups.c.id == int_or_none(group_id))
rows = connection.execute(statem... | f17c54800d8f4e84e7433a23a7d222e4d3d67bbf | 3,630,734 |
import traceback
import six
def format_traceback(exc_info, encoding='utf-8'):
"""
Returns the exception's traceback in a nice format.
"""
ec, ev, tb = exc_info
# Skip test runner traceback levels
while tb and _is_relevant_tb_level(tb):
tb = tb.tb_next
# Our exception object may h... | c962b11bf629908b7575e6cf25ffebeb2b5956ec | 3,630,735 |
import os
def creatadata(datadir=None,exprmatrix=None,expermatrix_filename="matrix.mtx",is_mtx=True,cell_info=None,cell_info_filename="barcodes.tsv",gene_info=None,gene_info_filename="genes.tsv",project_name=None):
"""
Construct a anndata object
Construct a anndata from data in memory or files on dis... | b0b64920032836fe0c79de1827afa166c4a5d59c | 3,630,736 |
def test_declarative_region_modifier_zoom_in():
"""Test that '+' suffix on area string properly decreases extent of map."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.field = 'Temperature'
contour.level = 700 *... | 6d68ec6a15cc451226379f65cef69820f2169de7 | 3,630,737 |
def get_report(path):
"""
Downloads the MVP report.
:param path:
:return:
"""
return flask.send_from_directory(Parameters.TMP_DIR, path) | f6f9cc18c901b3ac89769f7bfb758ff538699269 | 3,630,738 |
def qbinomial(n, k, q = 2):
"""
Calculate q-binomial coefficient
"""
c = 1
for j in range(k):
c *= q**n - q**j
for j in range(k):
c //= q**k - q**j
return c | 43c167aa506bd9ee6b87163d10da5b02e297e067 | 3,630,739 |
def _igraph_from_nxgraph(graph):
"""
Helper function that converts a networkx graph object into an igraph graph object.
"""
nodes = graph.nodes(data=True)
new_igraph = igraph.Graph()
for node in nodes:
new_igraph.add_vertex(name=str(node[0]), species=node[1]["specie"], coords=node[1]["co... | 04525dbdda343fdc1b572639eea0f4e5933ffb39 | 3,630,740 |
def _tiramisu_parameters(preset_model='tiramisu-67'):
"""Returns Tiramisu parameters based on the chosen model."""
if preset_model == 'tiramisu-56':
parameters = {
'filters_first_conv': 48,
'pool': 5,
'growth_rate': 12,
'layers_per_block': 4
}
... | 74e2dadf2a6af864b3f9dfec6241bf71833676f8 | 3,630,741 |
import time
import requests
import json
def send_msg(request):
"""
发送消息
:param request:
:return:
"""
to_user = request.GET.get('toUser')
msg = request.GET.get('msg')
url = 'https://wx.qq.com/cgi-bin/mmwebwx-bin/webwxsendmsg?lang=zh_CN&pass_ticket=%s' %(TICKET_DICT['pass_ticket'],)
... | a028f37567e6fca6dc5e4b7c9e1ce826a184a5e1 | 3,630,742 |
import os
import stat
def get_type(path, follow=True, name_pri=100):
"""Returns type of file indicated by path.
path :
pathname to check (need not exist)
follow :
when reading file, follow symbolic links
name_pri :
Priority to do name matches. 100=override magic
This t... | 45a20cc179d569f5c993e9b90de393f210ab524d | 3,630,743 |
import os
def ELA(impath, Quality=90, Multiplier=15, Flatten=True):
"""
Main driver for ELA algorithm.
Args:
impath: Path to image to be transformed.
Quality (optional, default=90): the quality in which to recompress the image. (0-100 integer).
Multiplier (optional, default=15): v... | dced44b4db1ef25bd914b2609a0e7eb9dd07d8b9 | 3,630,744 |
import yaml
def create_deployment_for_compin(compin: ManagedCompin, assessment: bool = False) -> str:
"""
Creates a Kubernetes deployment YAML descriptor for a provided compin. The compin's deployment template is enhanced
in the following ways:
(1) A node selector is added in order to ensure that... | 90bb543a0c384b188f8284f4688a98d7e443d0c2 | 3,630,745 |
import requests
def titles_request() -> 'Response':
"""Request titles.
https://wiki.anidb.net/w/API#Anime_Titles
"""
return requests.get(_TITLES) | 41aebc83511d440a91e5be0c866702260536dccc | 3,630,746 |
def get_jds(text):
"""Given a text (string), returns a list of the Journal Descriptors contained"""
scores = jdi.GetJdiScoresByTextMesh(text, InputFilterOption(LegalWordsOption.DEFAULT_JDI))
output_filter_option = OutputFilterOption()
output_filter_option.SetOutputNum(3)
result = OutputFilter.Proc... | 9b508adfce00ba49a6b3fd303c98cb0056d62863 | 3,630,747 |
from pathlib import Path
import subprocess
def rpsbproc(results):
"""Convert raw rpsblast results into CD-Search results using rpsbproc.
Note that since rpsbproc is reliant upon data files that generally are installed in
the same directory as the executable (and synthaser makes no provisions for them
... | d3fbc8bc6456ed340db58f3809552c13e03a2c1b | 3,630,748 |
def replacespecial(string, char_replacement=replacements):
"""Return unicode string with special characters replaced"""
return "".join(c if c not in char_replacement else char_replacement[c] for c in string) | 67d3e397ab35392a242cab48e1ad628b19d1a488 | 3,630,749 |
def parse_orcid_response(response):
"""
This safely digs into the ORCID user summary response and returns consistent dict
representation independent of the user's visibility settings.
"""
return {
"orcid": get_nested_key(response, "orcid-identifier", "path"),
"email": get_nested_key... | 5fdbc6307b7146c0454e824d18269314e7d89569 | 3,630,750 |
def discrete_metropolis_hastings(P, n_samples = 10000, n_iterations = 10000, stepsize = None):
"""
Perform a random walk in the discrete distribution P (array)
"""
#ensure normality
n = np.sum(P)
Px = interp1d(np.linspace(0,1,len(P)), P/n)
x = np.random.uniform(0,1,n_samples)
... | 3167ac2e03763693ea70bec7fee9071074331515 | 3,630,751 |
def vat(x, logits, model, v, eps, xi=1e-6):
"""
Generate an adeversarial perturbation.
Args:
x: tensor, batch of labeled input images of shape [batch, height, width, channels]
logits: tensor, holding model outputs of input
model: tf.keras model
v: ... | 6e8c50018e9b49e38d32c92acc3ae5fcce4654c0 | 3,630,752 |
def bond_yield(price, face_value, years_to_maturity, coupon=0):
"""
"""
return (face_value / price) ** (1 / years_to_maturity) - 1 | 4c4a90f0fb29564acdad05138ca17932da39eb61 | 3,630,753 |
import ctypes
def getTime(type_of_clock):
"""
Arg:
type_of_clock...int
case '1': CLOCK_REALTIME;
case '2': CLOCK_MONOTONIC;
case '3': CLOCK_MONOTONIC_COARSE;
case '4': CLOCK_MONOTONIC_RAW;
case '5': CLOCK_BOOTTIME;
default: CLOCK_REALTIME;
Return:
... | 7fee5476bf967ca5fa74abfa4722a8ad2570a975 | 3,630,754 |
def ar_gain(alpha):
"""
Calculate ratio between the standard deviation of the noise term in an AR(1) process and the resultant
standard deviation of the AR(1) process.
:param alpha: Parameter of AR(1)
:return: Ratio between std of noise term and std of AR(1)
"""
return np.sqrt((1 + alpha) / ... | 966b2ade2aa0a70d71df2c9ee1567271bb988f07 | 3,630,755 |
import csv
def fetch_data_2014():
"""For import data year 2014 from excel"""
static = open("airtraffict.csv", newline="")
data = csv.reader(static)
static = [run for run in data]
static_2014 = []
for run in static:
if run[3] == "2014":
static_2014.append(run)
return sta... | bd31335f2f4344330ca0c390d33891d2c8b7b843 | 3,630,756 |
from typing import Counter
def classifyChord(chordPosition):
"""
:param chordPosition:所有音符的位置，所有音符都是在不同弦上，并且各位置的距离是限制在人类手掌范围内的。
例如：([6, 5], [5, 7], [4, 7], [3, 5], [2, 5])，表示6弦5品，5弦7品，4弦7品，3弦5品，2弦5品
:return:和弦类型，是一个列表，用来表示所有非空弦音，从低品到高品对应的个数。
例如：输入([6, 5], [5, 7], [4, 7], [3, 5], [2, 5])，返回[[5,3],... | 1c9af3737f2e4ba2437a457e74f37fbbe1ff0406 | 3,630,757 |
def clean_columns(data):
"""
Removes : EventId, KaggleSet, KaggleWeight
Cast labels to float.
"""
data = data.drop(["DER_mass_MMC", "EventId", "KaggleSet", "KaggleWeight",], axis=1)
label_to_float(data) # Works inplace
return data | 073b41bfeaf9a3236698b04b74a621efffa135cf | 3,630,758 |
def update_active_boxes(cur_boxes, active_boxes=None):
"""
Args:
cur_boxes:
active_boxes:
Returns:
"""
if active_boxes is None:
active_boxes = cur_boxes
else:
active_boxes[0] = min(active_boxes[0], cur_boxes[0])
active_boxes[1] = min(active_boxes[1], cu... | dfa1c9b32b9af9c6c9a1fb321f907dad51f9cca0 | 3,630,759 |
def get_user_request():
"""Return the user's json."""
assert namespace_manager.get_namespace() == ''
person = get_person()
values = person.to_dict()
return flask.jsonify(objects=[values]) | be8d8a36ce096d6ac74cad3c62cdaaeb0ad2e326 | 3,630,760 |
def paginate_data(counted, limit, offset):
"""
Custom pagination function.
:param counted:
:param limit:
:param offset:
:return: {}
"""
total_pages = ceil(counted / int(limit))
current_page = find_page(total_pages, limit, offset)
if not current_page:
return None
bas... | b34f55efac09c277b0ffabffa5012b29087f8cde | 3,630,761 |
import torch
def ones(shape, dtype=None):
"""Wrapper of `torch.ones`.
Parameters
----------
shape : tuple of ints
Shape of output tensor.
dtype : data-type, optional
Data type of output tensor, by default None
"""
return torch.ones(shape, dtype=dtype) | a234936baa16c8efdc63e903d8455895ab7f2f0c | 3,630,762 |
def parse_catalog(catalog):
"""parses an atom feed thinking that it is OPDS compliant"""
author = None
title = None
links = []
entries = []
updated = None
for child in catalog:
if child.tag == LINK_ELEM:
links.append(parse_link(child))
elif child.tag == ENTRY_EL... | 1a6b0b6d8b94f916f37f976cfa6feb7e4c7d6178 | 3,630,763 |
def get_queue(shares):
"""Transform category sizes to block queue optimally
catsizes = [cs1, cs2, cs3, cs4] - blocks numbers of each color category
"""
# Defining catsizes matching the MSE-limit
# amount = 1 # starting amount
# lim = 0.03 # MSE-limit
# while True:
# error = 0
... | acb8bd7372a2338b36c77c03776af45fc2727d89 | 3,630,764 |
def view_post(request, slug):
"""View post view"""
post = get_object_or_404(Post, slug=slug)
if not post.published:
raise Http404
ret_dict = {
'post': post,
}
ret_dict = __append_common_vars(request, ret_dict)
return render(request, 'blog/view_post.html', ret_dict) | 5d777e6664555172a159b11ee3e6796a2767401a | 3,630,765 |
def relhum(temperature, mixing_ratio, pressure):
"""This function calculates the relative humidity given temperature, mixing
ratio, and pressure.
"Improved Magnus' Form Approx. of Saturation Vapor pressure"
Oleg A. Alduchov and Robert E. Eskridge
http://www.osti.gov/scitech/servlets/purl/548871/
... | 3db1b72a96ac76fce041b8c5462d77ab5f0db9bb | 3,630,766 |
def submit(year, day, part, session=None, input_file=None):
"""
Puzzle decorator used to submit a solution to advent_of_code server and provide
result. If input_file is not present then it tries to download file and cache it
for submiting solution else it require to be provided with input_file path whic... | f90b52eaa5e1ee78f257f33fd8454380e57dd71e | 3,630,767 |
def mse(y, y_pred):
"""
Computes mean squared error.
Parameters
----------
y: np.ndarray (1d array)
Target variable of regression problems.
Number of elements is the number of data samples.
y_pred: np.ndarray (1d array)
Predicted values for the given target va... | 87c13131be28f92d3b9d75192d2e0e0d651979cc | 3,630,768 |
from django.db import transaction
from django.db import transaction
def update_items(item_seq, batch_len=500, dry_run=True, start_batch=0, end_batch=None, ignore_errors=False, verbosity=1):
"""Given a sequence (queryset, generator, tuple, list) of dicts run the _update method on them and do bulk_update"""
st... | c734f097db2ef8d5ff620cfd6386d53db4ed4543 | 3,630,769 |
def hue_weight(image, neighbor_filter, sigma_I = 0.05):
"""
Calculate likelihood of pixels in image by their metric in hue.
Args:
image: tensor [B, H, W, C]
neighbor_filter: is tensor list: [rows, cols, vals].
where rows, and cols are pixel in image,
... | 976a93ee7a5a83280485e1cd693b2cf10e67421a | 3,630,770 |
def build_blueprint_with_loan_actions(app):
"""."""
blueprint = Blueprint(
'invenio_circulation',
__name__,
url_prefix='',
)
create_error_handlers(blueprint)
endpoints = app.config.get('CIRCULATION_REST_ENDPOINTS', [])
pid_type = 'loan_pid'
options = endpoints.get(pi... | 0081a7795bbcab334c6a56991ebd3727e3799d5b | 3,630,771 |
def featurize_and_to_numpy(featurizer, X_train, y_train, X_test, y_test):
"""
Featurize the given datasets, and convert to numpy arrays.
"""
featurizer.fit(X_train)
X_train_feats = featurizer.transform(X_train)
X_test_feats = featurizer.transform(X_test)
X_train_np = X_train_feats.astype(np... | 71e325e79770e4d049760e7701b98e8628b1c91f | 3,630,772 |
def noise_per_box_v2_(boxes, valid_mask, loc_noises, rot_noises,
global_rot_noises):
"""add noise for each box and check collision to make sure noisy bboxes do not collide with other boxes
loc_noises and rot_noises are some noisy candidates, first successful noisy bbox candidate is cho... | 68e75778dd6da7b1cbe4d1dfbf83b60034d43f61 | 3,630,773 |
def calculate_cornea_center_wcs(u1_wcs, u2_wcs, o_wcs, l1_wcs, l2_wcs, R, initial_solution):
"""
Estimates cornea center using equation 3.11:
min ||c1(kq1) - c2(kq2)||
The cornea center should have the same coordinates, however, in the presents of the noise it is not always the case.
Thus, the task... | 67f153fbe39baf3b435f7fe11b2b2da611f08aab | 3,630,774 |
def luminosity(S_obs, z, D_L=0, alpha=0):
"""Get radio luminosity with error. Default is LDR2. See
https://www.fxsolver.com/browse/formulas/Radio+luminosity.
"""
if D_L == 0:
D_L, _ = get_dl_and_kpc_per_asec(z=z)
return (S_obs * 4 * np.pi * (D_L ** 2)) / (1 + z) ** (1 + alpha) | 276c73e1575b67c918884bfc1f9a55feb3844a58 | 3,630,775 |
def add_categories_to(gifid, category_id):
"""
REST-like endpoint to add a category to a bookmarked gif
:returns: Customized output from GIPHY
:rtype: json
"""
user = (
models.database.session.query(models.users.User)
.filter(
models.users.User.token == flask.request... | 8444400fb198b1d2630b2097bc77e19a347e32ef | 3,630,776 |
import numpy
def vtk_image_to_array(vtk_image) :
""" Create an ``numpy.ndarray`` matching the contents and type of given image.
If the number of scalars components in the image is greater than 1, then
the ndarray will be 4D, otherwise it will be 3D.
"""
exporter = vtkImageExport()
... | e7640b69f7489d434da20a117ef46253198f7a7e | 3,630,777 |
def delete_network_acl(acl_id):
"""Delete a network ACL."""
client = get_client("ec2")
params = {}
params["NetworkAclId"] = acl_id
return client.delete_network_acl(**params) | 87fca1c7dcd258e5ffcce638d9d74a3a50fbd0e9 | 3,630,778 |
def catalog_sections(context, slug=None, level=3, **kwargs):
"""
Отображает иерерхический список категорий каталога.
Для каждой категории отображается количество содержащегося в ней товара.
Пример использования::
{% catalog_sections 'section_slug' 2 class='catalog-class' %}
:param context... | 2c75a83aebbb494549443d08c8d0c6b054a20804 | 3,630,779 |
def get_scrapable_links(
args, base_url, links_found, context, context_printed, rdf=False
):
"""Filters out anchor tags without href attribute, internal links and
mailto scheme links
Args:
base_url (string): URL on which the license page will be displayed
links_found (list): List of all... | ad078463ff146ea649250201f5cd625e277dc5d8 | 3,630,780 |
def AccuracyTestNMax():
"""[summary]
Test the accuracy using n-max random points
"""
plgs = getTestPolygons()
pnt = Point(0, 0)
# Calculate D using polygon partitioning method
print("---------D---------------")
for i in range(len(plgs)):
print(DistCalc.DistCalcPART(pnt, plgs[i]))... | 0f2fa1bf2990eafdf484123d4463056884a77cff | 3,630,781 |
import pandas
def read_source_MCI(csv_path: str | None = "volume_sum_icv_site.csv"):
"""
:param csv_path: str
:return: Train and test dataset of independent variables X and dependent variable y
"""
MRI_source_df = pandas.read_csv(csv_path)
X_df = MRI_source_df.iloc[:, 2:-2]
del X_df['age... | 3433f70d9da17a8eedfa9b3a7f047e4efb324dd0 | 3,630,782 |
import os
def get_exp_logger(sess, log_folder):
"""Gets a TensorBoard logger."""
with tf.name_scope('Summary'):
writer = tf.summary.FileWriter(os.path.join(log_folder), sess.graph)
class ExperimentLogger():
def log(self, niter, name, value):
summary = tf.Summary()
... | fe80f2db4f175e2ad4cc053fb5b29d0a54ea5772 | 3,630,783 |
import random
def rollDie():
"""returns a random int between 1 and 6"""
return random.choice([1, 2, 3, 4, 5, 6]) | 27a3d3586fe313d78a5aea6dab8d10c58e76df56 | 3,630,784 |
def calc_ari(A, B):
""" Adjusted Rand Index"""
A = {v: k for k, s in A.items() for v in s}
B = {v: k for k, s in B.items() for v in s}
df = pd.DataFrame({'A': A, 'B': B}).dropna()
A = df['A'].to_list()
B = df['B'].to_list()
return adjusted_rand_score(A, B) | 8904c6232e47428364f97c26d55492890dff6cc0 | 3,630,785 |
def encode_adj(adj, max_prev_node=10, is_full=False):
"""
:param adj: n*n, rows means time step, while columns are input dimension
:param max_degree: we want to keep row number, but truncate column numbers
:return:
"""
if is_full:
max_prev_node = adj.shape[0] - 1
# pick up lower tr... | 8c2f21705b3b1aeff64a1b02c0519e51bb101d65 | 3,630,786 |
def get_datasource_content_choices(model_name):
"""Get a list (suitable for use with forms.ChoiceField, etc.) of valid datasource content choices."""
return sorted(
[(entry.content_identifier, entry.name) for entry in registry["datasource_contents"].get(model_name, [])]
) | 3ce217f606e013e35189ffcdabff46c37060bf19 | 3,630,787 |
def setFDKToolsPath(toolName):
""" On Mac, add std FDK path to sys.environ PATH.
On all, check if tool is available.
"""
toolPath = 0
if sys.platform == "darwin":
paths = os.environ["PATH"]
if "FDK/Tools/osx" not in paths:
home = os.environ["HOME"]
fdkPath = ":%s/bin/FDK/Tools/osx" % (home)
os.environ... | 229f79954f5488f7bae067a5ad39a83d5b2fe527 | 3,630,788 |
import os
import builtins
def datasplit(datastream,split_param=None,split_value=0.2):
"""
Very flexible function for splitting the dataset into train-test or train-test-validation dataset. If datastream
contains field `filename` - all splitting is performed based on the filename (directories are ommited t... | 3554f795728edd7d4cc6b2595771811fc20897d7 | 3,630,789 |
def upd_p_fdtd_srl_2D_slope(p, p1, p2, fsrc, fsrc2, Nb, c, rho, Ts, dx, Cn,
A, B, C, x_in_idx, y_in_idx, x_edges_idx,
y_edges_idx, x_corners_idx,
y_corners_idx, slope_start):
"""
This FDTD update is designed for case 5: slope.
... | bb536af34d655b741ee84c0649adfb2dd76eed4e | 3,630,790 |
from datetime import datetime
import calendar
def PlistValueToPlainValue(plist):
"""Takes the plist contents generated by binplist and returns a plain dict.
binplist uses rich types to express some of the plist types. We need to
convert them to types that RDFValueArray will be able to transport.
Args:
p... | 4e78b5c85dce44846d27e7ca8b3ea2bceeeba5eb | 3,630,791 |
def columns_not_to_edit():
"""
Defines column names that shouldn't be edited.
"""
## Occasionally unchanging things like NIGHT or TILEID have been missing in the headers, so we won't restrict
## that even though it typically shouldn't be edited if the data is there
return ['EXPID', 'CAMWORD', 'O... | 430430c121d784727808b8e7c98d96bd846dc65f | 3,630,792 |
def cat_dog(s):
"""Solution of problem at http://codingbat.com/prob/p164876
>>> cat_dog('catdog')
True
>>> cat_dog('catcat')
False
>>> cat_dog('1cat1cadodog')
True
"""
last_3_chars = deque(maxlen=3)
cat = deque('cat')
dog = deque('dog')
count = 0
for c in s:
... | dacc2b2e7fc6e19980afff0c010a9d64bf45e163 | 3,630,793 |
def CanCreateGroup(perms):
"""Return True if the given user may create a user group.
Args:
perms: Permissionset for the current user.
Returns:
True if the user should be allowed to create a group.
"""
# "ANYONE" means anyone who has the needed perm.
if (settings.group_creation_restriction ==
... | b4149315cef8086042b30be4334a426cf15927d6 | 3,630,794 |
def quad_corner_diff(hull_poly, bquad_poly, region_size=0.9):
"""
Returns the difference between areas in the corners of a rounded
corner and the aproximating sharp corner quadrilateral.
region_size (param) determines the region around the corner where
the comparison is done.
"""
bquad_corne... | 1190b4ff43632c072c220b5bdfae29c239e8662f | 3,630,795 |
def _context_deleteserver(ip, port, server_name, config=None, disabled=None):
"""Delete a server context.
"""
if config is None or ('_isdirty' in config and config['_isdirty']):
config = loadconfig(APACHECONF, True)
scontext = _context_getserver(ip, port, server_name, config=config, disabled=dis... | cf41b61c4d8296373a4f4df4f1764485ec221466 | 3,630,796 |
def CreateStyleFromConfig(style_config):
"""Create a style dict from the given config.
Arguments:
style_config: either a style name or a file name. The file is expected to
contain settings. It can have a special BASED_ON_STYLE setting naming the
style which it derives from. If no such setting is fo... | 42c36df604b26cdad9f8b0571863bfbfd92c9df9 | 3,630,797 |
def build_weighted_matrix(corpus, tokenizing_func=basic_tokenizer,
mincount=300, vocab_size=None, window_size=10,
weighting_function=lambda x: 1 / (x + 1)):
"""Builds a count matrix based on a co-occurrence window of
`window_size` elements before and `window_size` elements after the
focal wo... | d21b220c7697fb59ed2a4590bd54d9bbb0331758 | 3,630,798 |
def checksum_data_16bit(data):
"""Calculate 16 bit checksum (really just summing up shorts) over a chunk."""
return reduce(lambda r, x: (r + x) & 0xFFFF, map(lambda (x, y): (ord(y) << 8) | ord(x), zip(*[iter(data)] * 2)), 0) | 4d453e5a02eb3359e5aa30442230604f45d6d27b | 3,630,799 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.