content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def show_topics(A, vocabulary, topn=5):
"""
find the top N words for each of the latent dimensions (=rows) in a
"""
topic_words = ([[vocabulary[i] for i in np.argsort(t)[:-topn-1:-1]]
for t in A])
return [', '.join(t) for t in topic_words] | 886e4afcfa3594f352474ca54ce79d430f09e508 | 3,615,300 |
def parse(
handle,
sequences=None,
query_file=None,
query_ids=None,
max_evalue=0.01,
min_identity=30,
min_coverage=50,
):
"""Parse Tabular results from remote BLAST search performed via API.
Since the API provides no option for returning query coverage, which is a metric we
want... | 55ade045fa1f2828059036e55a474f80f129fd37 | 3,615,301 |
def read_graph(in_graph, in_graph_is_binary=True):
"""Reads input graph file as GraphDef.
:param in_graph: input graph file.
:param in_graph_is_binary: whether input graph is binary, default True.
:return: input graphDef.
"""
assert gfile.Exists(in_graph), 'Input graph pb file %s does not exist... | ba235b503737f35284f85234ca82297775317e4f | 3,615,302 |
import skimage # Defer slow imports
import skimage.transform # Defer slow imports
import scipy
def _find_anomalies(cy_ims, iqr_bounds):
"""
Given a cy stack of images for a field, find the anomalies.
Arguments:
cy_ims: array (n_cycles, height, width)
iqr_bounds: The inter-quartile-range... | 4f38605fe8b80f8c37c4c0b80c9956aeb6908aed | 3,615,303 |
from typing import Mapping
from typing import Any
import uuid
from datetime import datetime
def new_contract_from_user(data: Mapping[str, Any]) -> "SmartContractModel":
"""
Used in creating new contracts
Input: SmartContract::L1::Create DTO
Returns: SmartContractModel object
"""
if data.get("v... | e87485b7ebccaf4d6b4b2f4e869a674a047e2673 | 3,615,304 |
def mes_com_acentos(mes_a_mudar):
"""Retorna Mês com Maiúsculas e Acentos."""
meses_a_exibir = {
'janeiro': 'Janeiro',
'fevereiro': 'Fevereiro',
'marco': 'Março',
'abril': 'Abril',
'maio': 'Maio',
'junho': 'Junho',
'julho': 'Julho',
'agosto': 'Agos... | 8361d7e747d524242eeb572b839305d58021b35d | 3,615,305 |
def _load_glove(path):
"""
Loads GloVe pre-trained embedding model via gensim
"""
tmp_file = get_tmpfile('temp_glove_w2v_format.txt')
glove2word2vec(path, tmp_file)
return gensim.models.KeyedVectors.load_word2vec_format(tmp_file) | d3eb03153b65739dc5d991c4ca9984207dd81d6e | 3,615,306 |
import logging
def change_settings(settings: SettingsModel) -> bool:
"""
Change downloader settings by re-initializing the downloader.
### Arguments
- settings: The settings to change.
### Returns
- returns True if the settings were changed.
"""
settings_dict = settings.dict()
... | 9f7d03933a6b86affabe881859ebbde099fb447f | 3,615,307 |
def flip_chars(items):
"""Flip all chars in an input str of items."""
return ''.join([flip_char(x) for x in items]) | f2e53101b66d625a8bb327699aa7216e48987bdd | 3,615,308 |
def run_prog(code):
"""Meh
"""
mem = {}
mask = None
for line in code:
op, args = parse_line(line)
if op == "MASK":
mask = args
elif op == "MEMSET":
for addr in apply_mask(mask, args["addr"]):
mem[addr] = args["value"]
return sum(m... | 04d83fa510a0344bbaf354ef05792a62545ce39a | 3,615,309 |
def get_best_k(use_saved_k, labvitals_time_series_list_val, labels_val, k_list):
"""gets the best_k either from the database or from finding it
with the help of the method find_best_k
Args:
use_saved_k (Bool): should the value be taken from the databse?
labvitals_time_series_list_val (Li... | 88e13b52b34ac0c3ec22f786399bdc21fcad0392 | 3,615,310 |
def interp_operator_2d( dims_in, dims_out,
pack_index_in=None,
pack_index_out=None ):
"""Make one interpolation operator to work on a "flattened"
2D array
Do this by tiling and repeat the separate interpolation operators
Parameters
----------
di... | d316b47558643e03d436c6831253b8f205ab662f | 3,615,311 |
def x2p(X = Math.array([]), tol = 1e-5, perplexity = 30.0):
"""Performs a binary search to get P-values in such a way that each conditional Gaussian has the same perplexity."""
# Initialize some variables
print("Computing pairwise distances...")
(n, d) = X.shape;
sum_X = Math.sum(Math.square(X), 1);
D = Math.add... | 7e85e26a7dfd446abfe1546860c7676b4d44287d | 3,615,312 |
import base64
def b64encode(value):
"""
Encode a value in base64
"""
return base64.b64encode(value) | 988abf5a9d2c0c1f38f16fbf8f80fd43aa115223 | 3,615,313 |
import os
import pkgutil
import importlib
def load_module_attrs(pkg_path, func, recursive=False):
"""Get attributes from modules, use ``func`` to filter attributes,
``func`` must return a list.
"""
attrs = list()
root_pkg = os.path.basename(ROOT_DIR)
pkg_name = root_pkg + pkg_path.split(root_p... | 386a62ae75dbb9f769c734fff980131983410b48 | 3,615,314 |
import os
def get_audio_embedding_model_path(input_repr, content_type):
"""
Returns the local path to the model weights file for the model
with the given characteristics
Parameters
----------
input_repr : "linear", "mel128", or "mel256"
Spectrogram representation used for model.
c... | 8a3d0a5d09896467b672e8dde47b1a6a500cdce8 | 3,615,315 |
import os
import sys
import subprocess
def get_git_sha1():
"""Try to get the git SHA1 with git rev-parse."""
git_dir = os.path.join(os.path.dirname(sys.argv[0]), '..', '.git')
try:
git_sha1 = subprocess.check_output([
'git',
'--git-dir=' + git_dir,
'rev-parse',
... | 38e1bb662229939f5f1aeec396e4c9d11c93bb73 | 3,615,316 |
def update(profile_id):
"""
Update A Profile
---
/api/profiles/edit/{profile_id}:
put:
summary: Update A Profile.
security:
- APIKeyHeader: []
tags:
- Profile
parameters:
- in: path
name: profile_id
required: true
schema:
... | 1314df4f9b452423e995e35513d607fd13043160 | 3,615,317 |
def kornia_list(magn: int = 4):
"""
Returns standard list of kornia transforms, each with magnitude `magn`.
Args:
magn (int): Magnitude of each transform in the returned list.
"""
transform_list = [
# spatial
K.RandomHorizontalFlip(p=1),
K.RandomRotation(degrees=90.0... | fd6fa7a1214484bc0f7c1f6511fe4b525f7d15c5 | 3,615,318 |
def phrase_replacement(structured_phrases, short_phrases):
"""replaces phrases in structred_phrases with phrases from short_phrases if the short phrase is contained in the longer phrase"""
short_set = set(short_phrases)
return [_rewrite_doc(doc, short_set) for doc in structured_phrases] | 6971ab9044ee43da9172dcf15845a8e52890bd64 | 3,615,319 |
from copy import copy
def struct(typename, field_names, verbose=False):
"""Returns a new class with named fields.
>>> Point = struct('Point', 'x y')
>>> Point.__doc__ # docstring for the new class
'Point(x, y)'
>>> p = Point(11, y=22) # instantiate with positional ar... | 74dcfd6e0a0c83a6679691e49f09a528eb8e6a4a | 3,615,320 |
def zip_tasks_verbose_output(table, stdstreams):
"""Zip a list of strings (table) with a list of lists (stdstreams)
:param table: a formatted list of tasks
:param stdstreams: for each task, a list of lines from stdout/stderr tail
"""
if len(table) != len(stdstreams):
raise ValueError('Can on... | 33d74cd274ec39330cbc127a3088a430b80d234a | 3,615,321 |
def stable_softmax(x, axis=2):
""" Numerically stable softmax:
softmax(x) = e^x /(sum(e^x))
= e^x / (e^max(x) * sum(e^x/e^max(x)))
Args:
x: An N-dimensional array of floats
axis: The axis for normalizing over.
Returns:
output: softmax(x) along the specifi... | 144e65a287591901316b29932ddbb1b989a1c199 | 3,615,322 |
from typing import Union
def is_chinese(x: Union[int, str]) -> bool:
"""Recognizes whether the server/uid is chinese
:param x: A server or a genshin uid
"""
return str(x).startswith(("cn", "1", "2", "5")) | e63d7e98a3dcdaeb9f9853715dcd8f466d9a293b | 3,615,323 |
def add_edit_button(user_id):
"""Determines if home page requires an edit button
Args:
user_id:
user_id being used to request home page
Returns:
list
list of dictionaries containing buttons
"""
button_list = [
{
"textButton": {
"text": "START ... | 0bcc8a9e81af2b809ef6e2cbab0bba9c7d188258 | 3,615,324 |
def not_found(error):
""" error handler """
return make_response(jsonify({'error': 'Not found'}), 404) | b09e9c47df42a40c3c241d5b6631726b7bebb580 | 3,615,325 |
import resource
def port(port_data):
"""Represents a view for a port object"""
keys = ('id', 'network_id', 'mac_address', 'fixed_ips',
'device_id', 'admin_state_up', 'tenant_id', 'status')
return resource(port_data, keys) | fc4d987aa75c7548f8f9a2edfb00e5ccbf3849ad | 3,615,326 |
from matplotlib._pylab_helpers import Gcf
def connection_info():
"""
Return a string showing the figure and connection status for
the backend. This is intended as a diagnostic tool, and not for general
use.
"""
result = []
for manager in Gcf.get_all_fig_managers():
fig = manager.c... | e2b0fa877a02b19a2306269b1d8fac0901f7a0c4 | 3,615,327 |
def get_bridge(ip):
"""The name to be used for the bridge interface connecting the VMs and the host."""
return "spirebr%s" % ip.packed.hex().upper() | 898347580052cce492bb12d60668fc7661a7f811 | 3,615,328 |
def test1():
"""test case 1
Returns:
matrix: np.array
vector b: np.array
vector c: np.array
vector j: np.array
"""
A = np.array([
[-2, -1, -4, 1, 0],
[-2, -2, -2, 0, 1]
])
b = np.array([-1, -1.5])
c = np.array([-4, -3, -7, 0, 0])
J = np.ar... | ca1836d985fef266aeb67d7b74ddfbfa2f20f053 | 3,615,329 |
import os
def read_text_file(file_path):
"""
Read text file utility
Read the text file from the given path
if file is not present, exit
params: file_path - string
returns: file_data - list
"""
logger.debug("<<<< 'Current Executing Function' >>>>")
if os.path.exists(file_pat... | 4f5afc570b969bd3f0e7f0382c015298fb677244 | 3,615,330 |
import pickle
def try_deserialize_handler(serialized_handler):
"""Reverse function of try_serialize_handler.
Args:
serialized_handler: serialized handler str or None.
Returns:
handler instance or None.
"""
if serialized_handler:
return pickle.loads(serialized_handler) | bc91e26c65add4e74affd148b8ed550fe923c925 | 3,615,331 |
from typing import Optional
async def load_from_server(
component_builder: Optional[ComponentBuilder] = None,
project: Optional[Text] = None,
project_dir: Optional[Text] = None,
remote_storage: Optional[Text] = None,
model_server: Optional[EndpointConfig] = None,
wait_time_between_pulls: Optio... | 94e2e8a477af31761756c1ed1d887c75b0177a9a | 3,615,332 |
def unravel_index(ind, tensor_shape):
"""no official tensorflow implementation for this yet;
this is based on one proposed in https://github.com/tensorflow/tensorflow/issues/2075
"""
ind = tf.expand_dims(tf.cast(ind, tf.int64), 0)
tensor_shape = tf.expand_dims(tf.cast(tensor_shape, tf.int64), 1)
... | 64070c8a832843884436bbc1107ea5be946dd7be | 3,615,333 |
def write_tfrecord_from_tensorrec_dataset(tfrecord_path, dataset):
"""
Writes the contents of a TensorRec Dataset to a TFRecord file.
:param tfrecord_path: str
:param dataset: tf.data.Dataset
:return: str
The tfrecord path
"""
session = get_session()
iterator = create_tensorrec_itera... | 6108e384cdb1ecefa3b87ee1d11f78c3dbc56b26 | 3,615,334 |
def _convert_universal_format(format):
"""Converts Universal Date Time Format to Python strftime format string"""
i = 0
token_string = format
python_format = format
token_map = sorted(_DATETIME_FORMAT_MAP, key=lambda t: t[0], reverse=True)
calculated_tokens = {}
for f in token_map:
i... | d9b747c044e37317352ab402da080845ef39b2df | 3,615,335 |
from typing import Tuple
def get_loader(dataset: str, batch_size: int) -> Tuple:
"""
:param dataset: The name of the dataset we want to use. Either JSB_Chorales, MuseData, Nottingham, or Piano_midi.
:param batch_size: how many sequences to train on at once.
:return: DataLoaders for training, testing, ... | bc900e42f7d1523dbc1a629d27f4668caa6e0a10 | 3,615,336 |
def hardwareVersionToString (hwversion):
"""
Converts a raw integer value into a human readable string a.b.c.d.
:param int hwversion: raw value as received from the generator
:return str: a human readable string 'a.b.c.d'.
"""
if ((hwversion >> 30) & 1) != 0:
# new format 30-22 + 21-16
# mask here with 0xFF ... | 1f1fab23706e05fa593ef4cf56f3ec4e1a6f4c6f | 3,615,337 |
def pareto_mtl_search(ref_vecs,i,t_iter = 100, n_dim = 20, step_size = 1):
"""
Pareto MTL
"""
# randomly generate one solution
x = np.random.uniform(-0.5,0.5,n_dim)
# find the initial solution
for t in range(int(t_iter * 0.2)):
f, f_dx = concave_fun_eval(x)
weights... | 245a9358ea64db0c667025f18599a6f1fd996229 | 3,615,338 |
def get_region_stats_np(im: np.ndarray, region: Box) -> Stat:
"""Get array region stats using Numpy.
Parameters
----------
im : np.ndarray
Input image to analyze
region : Box
Coordinates for region
Returns
-------
Stat
Stat object containing various statistics o... | bc7fcad29c8638123d7b2d0bb7a0408e794d6dec | 3,615,339 |
def _create_pipeline(
pipeline_root: str,
csv_input_location: str,
taxi_module_file: tfx.dsl.experimental.RuntimeParameter,
push_destination: tfx.dsl.experimental.RuntimeParameter,
enable_cache: bool
):
"""Creates a simple Kubeflow-based Chicago Taxi TFX pipeline.
Args:
pipeline_root: The r... | c483ba700d2c4b0a2386cad997424ac4b10c6ee1 | 3,615,340 |
import numpy
def gz(tesseroid, lons, lats, radii, nodes, weights):
"""
Integrate gz using the Gauss-Legendre Quadrature
"""
order = len(nodes)
lonc, latc, rc, scale = _scale_nodes(tesseroid, nodes)
# Pre-compute sines, cossines and powers
sinlatc = numpy.sin(latc)
coslatc = numpy.cos(l... | 0e3878fa24fb00f810be03502f19c712b59044f9 | 3,615,341 |
def polynomial_coefficients_fast(r,s,alpha,beta,_=None):
""" Return the coefficients of the Farey polynomial of slope r/s.
The method used is the recursion algorithm.
Arguments:
r,s -- coprime integers representing the slope of the desired polynomial
alpha, beta -- parameters o... | 82ad772a4ae192b84b7cd2b2052315038d7dde9d | 3,615,342 |
def get_light_threshold(response):
"""Get light from response."""
light_threshold = response.get("highlight")
return light_threshold | 602d3b11fbabfa6c8b0d284a21b4b1ebb816d327 | 3,615,343 |
def variant_ids(
locus: hl.expr.LocusExpression, alleles: hl.expr.ArrayExpression, max_length: int = None
) -> hl.expr.ArrayExpression:
"""
Return a list of variant ids - one for each alt allele in the variant
"""
def compute_variant_id(alt):
return hl.rbind(
hl.min_rep(locus, [... | 0ecf119ddf9d4a97e99987afc69444a2179cc1dd | 3,615,344 |
def normalize_img_to_rgb(img_1_, img_h_, img_w_):
"""
Normalize the given image
"""
rgb_img_1 = cv2.imread(img_1_, 1)[:, :, ::-1]
rgb_img_1 = cv2.resize(rgb_img_1, (img_h_, img_w_))
rgb_img_1 = np.float32(rgb_img_1) / 255.
return rgb_img_1 | b3b385fd30e956f47b2648ed8dc71f5ecb552839 | 3,615,345 |
def getonts():
"""get the list of ont terms"""
return Ontterms.objects.all().filter(to_remove__isnull=True).order_by('title') | b69e6e59774d323113b2d21a3f75be5c8cedc347 | 3,615,346 |
def load_frame_building_sample_data():
"""
Sample data for the BuildingFrame object
"""
number_of_storeys = 6
interstorey_height = 3.4 # m
masses = 40.0e3 # kg
n_bays = 3
fb = models.FrameBuilding(number_of_storeys, n_bays)
fb.interstorey_heights = interstorey_height * np.ones(num... | 3d87d3e8a949fb1344ea13780cb529be427e1409 | 3,615,347 |
def analyze_group(group, verbosity, error_level):
"""analyze AD group object
group -- group object to be analyzed
verbosity - NAGIOS verbosity level - ignored
error_level - ignored
Returns the Nagios error code (always 0) and error message (group defn)
"""
return 0, '{name:%s, description:%... | 868746cedd1815df1b9188b02671c3d5431bf83b | 3,615,348 |
from typing import Sequence
import signal
def discount_rewards(x: Sequence, gamma: float) -> np.ndarray:
"""
Given vector x, computes a vector y such that
y[i] = x[i] + gamma * x[i+1] + gamma^2 x[i+2] + ...
"""
return signal.lfilter([1], [1, -gamma], x[::-1], axis=0)[::-1] | 7b5f3cf4f40f5b1dc127aa6c850456dbd7bccaa1 | 3,615,349 |
def type_for_objcclass(objcclass):
"""Look up the :class:`ObjCInstance` subclass used to represent instances of the given Objective-C class in Python.
If the exact Objective-C class is not registered, each superclass is also checked,
defaulting to :class:`ObjCInstance` if none of the classes in the supercl... | 9dff18d82efdb780749dc57c0a6e0e0d587977c4 | 3,615,350 |
def command(name=None, descr=None, long_descr=None, examples=None, free_form=False, kind='command'):
"""Define a model command.
:param name: An optional name of the command. Defaults to the name of the function.
:param descr: A short description of the command
:param long_descr: A long de... | 9df0a43cbcefa3ba722f5fb7faa4a11e574eb39b | 3,615,351 |
def bilinearUpsample2Don3D(input_tensor):
""" Using tf.image.resize for bilinear interpolation """
""" ATTENTION: bilinear seems only works on 2D image """
##### NOTE: this bilinaer upsampling works on axies [1,2] in [0,1,2,3,4] #####
input_shape = input_tensor.shape
switch_axes = [0,3,1,2,4]
re... | f9df49c2cbfc0d19896aa7bb1edff1c8ff067bbc | 3,615,352 |
def fromhaeberlen(diso, delta, eta):
"""
Converts from the haeberlen convention to the PAS CSA tensor.
Parameters
----------
diso : float
diso == 1/3(d11 + d22 + d33)
delta : flaot
dzz - diso
eta : float
(dyy - dxx)/delta (0 <= eta <= 1)
Returns
----------
... | 9d01a784384ca7f0aaebbb59eebc5cab68ffe994 | 3,615,353 |
def gst00b(uta, utb):
""" Greenwich apparent sidereal time, consistent with IAU 2000 resolutions,
using truncated nutation model IAU 2000B.
:param uta, utb: UT1 as a two-part Julian date.
:type uta, utb: float
:returns: Greenwich apparent sidereal time in radians (float).
.. seealso:: |MANUAL... | 532b5967dd64e416ab16a0777cb26a9406788e2d | 3,615,354 |
import re
def search_bad_symbols_and_username(username):
"""Поиск зарезервированных слов и запрещенных символов"""
search_bad_symbols_result = 'No'
bad_username = ['root', 'admin', 'moderator', 'support', 'supports', 'helpdesk']
bad_symbols = ['&', ' ', '=', '+', '<', '>', ',', '.', '\"', '\'', '?', ... | 79beccff28ce3c319698e47e05353e1c8354522c | 3,615,355 |
def synthesize_edge_selector(sel_data,):
"""
Synthesizes an edge selector string based on what edges were selected.
"""
selector_str = '.edges("{filter}{axis}")' # {index}")'
axis_index = -1
axis_str = ""
filter_str = ""
index_str = ""
axis_str = None
axis_filter = None
# ... | a3ac7f30a77d6ec3747bdde30c11eb77ac1ba6ec | 3,615,356 |
import fnmatch
def FilterMatchesTest(filter_string, test_string):
"""Does something close enough to base/strings/pattern.h's MatchPattern() for
our purposes here."""
return fnmatch.fnmatch(test_string, filter_string) | 9f4cca026e60fe1b3fb0c2858477090fdf03c44e | 3,615,357 |
def make_path(components):
"""Build a path from a list of components."""
return '/{}'.format(
'/'.join([quote(str(c), '') for c in components if c])) | fc7cbf848e3c3ad8fd2a30ee1c01992c77d3be35 | 3,615,358 |
def price_task(request):
""" Lista de nomes, datas e VALORES das tarefas"""
context = {}
cliente = request.user
try:
cliente = Cliente.objects.get(usuario=cliente)
# filter mostra como está a saida em __str__
# do models da classe
# cronograma = Cronograma.objects.filter(... | 3c2021770ff6a7396880321a69470398e580fcb4 | 3,615,359 |
def quotation_detail(request, quotation_id):
""" View to show all record detail for a particular quotation """
try:
quotation = get_object_or_404(Quotation, pk=quotation_id)
except Exception as e:
messages.error(request, f'ERROR: {e}')
return redirect(reverse('quotations'))
co... | 2fe9bf09a6a21d7e6e80c7dcd57fa5f1d163561d | 3,615,360 |
def li(content, value: str="", accesskey:str ="", class_: str ="", contenteditable: str ="",
data_key: str="", data_value: str="", dir_: str="", draggable: str="",
hidden: str="", id_: str="", lang: str="", spellcheck: str="",
style: str="", tabindex: str="", title: st... | 732af5f05c942d1f60d3a575b64922140c2748bf | 3,615,361 |
from typing import List
from typing import Dict
def get_relations() -> List[Dict[str, str]]:
"""
Get the relations used for annotation for this app.
"""
return configuration.relations | 4f55f1ad9545305ccb20e329b2ad573d8f97aeea | 3,615,362 |
import sysconfig
def sem():
"""Create and return SEM (base class) instance with default config."""
return SEM(config, sysconfig) | 55fa3c510189e301d4603f00aba32ec32b4d9f57 | 3,615,363 |
from typing import Dict
def sort_by_color(e: Dict) -> float:
"""Sorting function, using a globally-declared color variable."""
return e[color] | 9748e621798ff8cd9a41a57b657bac78b3105536 | 3,615,364 |
def get_texts_from_url_and_selector(url: str, selector: str) -> t.List[str]:
"""Get the texts of the elements found at the url and selector"""
elements = get_elements_from_url_and_selector(url=url, selector=selector)
texts = [element.text for element in elements]
return texts | 898b6d461db94b143edfb4a73e0747635033ab76 | 3,615,365 |
def concrete_post(update, state, expr = None):
""" Apply an update concretely (compute concrete post). ".
"""
# TODO: axioms could change as scope changes
axioms = state.domain.background_theory(state.in_scope)
# print "concrete post: axioms = {}".format(axioms)
cons = compose_state_action(s... | e5f6856671e8dc8b1810895dfef50be3af141358 | 3,615,366 |
import random
def flat_monte_carlo(func, z_min, z_max, epsilon):
"""
Operate Monte Carlo integration on specified function. Random numbers are generated with a flat distribution function.
----------
Input:
func: the function of integrand
z_min: lower limit of the integration
z_... | 9f4fdb0a3f75ee9e0af2b6d3d0e6f439720d1fe9 | 3,615,367 |
def hbp_fn():
"""Create a 2d convolution layer with HBP functionality."""
set_seeds(0)
return HBPConv2d(
in_channels,
out_channels,
kernel_size,
stride=stride,
padding=padding,
dilation=dilation,
bias=bias,
) | ccfae6f3b41a508cbe9e8124587b65f90356603e | 3,615,368 |
from typing import List
import ctypes
def GetMonitorsRect() -> List[Rect]:
"""Return monitors rect"""
SM_CMONITORS = 80
monitorsCount = ctypes.windll.user32.GetSystemMetrics(SM_CMONITORS)
arrayType = ctypes.c_int * (monitorsCount * 4)
values = arrayType()
monitorsCount = _DllClient.instance().... | 5780f1af36c323fb9447619e30eb068870fa994d | 3,615,369 |
def _get_model_maker(complete_conf, cache=True):
"""Locate and instantiate class of data-scientist-provided ModelMaker
(which the data scientist inherited from ModelMakerInterface).
For this to work, your model module (.py file) needs to be in python's
sys.path (usually the case).
Also set the confi... | 5e33d9faf6260fcf16ae720bf66efc967a1ad693 | 3,615,370 |
import code
def main(_):
"""Run an interactive console."""
code.interact()
return 0 | e85a21c0197a599378c3f25022ec99cb557d6017 | 3,615,371 |
import mkl
import numpy
import scipy
def fit_r_mdv_scipy(configure, experiments, numbers, vectors, matrixinv, func, flux, method = "SLSQP"):
"""Low level function for model fitting using scipy.optimize.minimize
Args:
configures (dict): "model.configures" including various configulatoins of the model... | 5e4ffe4ec7fff423409ad019333585b0c3c04712 | 3,615,372 |
import heapq
def heapmerge(*inputs):
"""Like heapq.merge(), merges multiple sorted inputs (any iterables) into a single sorted output, but provides more convenient API:
each input is a pair of (iterable, label) and each yielded result is a pair of (item, label of the input) - so that it's known what input a g... | 580ec9f2f0793f8907390f5c7f8eebf4ac539b59 | 3,615,373 |
def histograma(img):
"""Calcula y representa el histograma de una imagen RGB.
Args:
img (Numpy array 3d): Un imagen RGB
Returns:
List: Devuelve una lista con el array del histograma de cada canal RGB.
Cada canal contendra un array de dos dimensiones, la primera contendra
la... | 782f69002220ad744efab496f7d71e0bff811957 | 3,615,374 |
from datetime import datetime
def get_all_data(start=datetime.date(1970, 1, 1), end=datetime.date(2099, 12, 31)) -> pd.DataFrame:
"""得到一段日期内的全部信息"""
return _calendar.get_all_data(str(start), str(end)) | 714bb182bbc4dbe3dc2a07378f7ce0c140d03a6b | 3,615,375 |
def tb_extent(table, db='main'):
"""Get the extent of the table"""
data = []
try:
conn = psycopg2.connect(conn_str(db))
cur = conn.cursor()
sql = f"""
SELECT ST_AsText(ST_SetSRID(ST_Extent(st_transform(wkb_geometry, 4326)),
4326)) As bextent
FROM {table};"... | c096fb8924379494e6c6a1475fdac47207f61eb0 | 3,615,376 |
from typing import Iterable
def _avro_pfb_schema(azul_avro_schema: Iterable[JSON]) -> JSON:
"""
The boilerplate Avro schema that comprises a PFB's schema is returned in
this JSON literal below. This schema was copied from
https://github.com/uc-cdis/pypfb/blob/1497bf50e5c85201f6bad9ca69616138b17b8c77/s... | 3019f3ae3005f625953eb8cdf0e9539d58ab5dd0 | 3,615,377 |
def _extend_job_info(connection, info):
"""Extends job info with connection/API related data."""
info['path'] = '/jobs/%s/%s' % (connection.id, info['uid'])
info['agent'] = {
'platform': connection.handshake_data[pagent.identity.KEY_PLATFORM],
'properties': connection.handshake_data[pagent.i... | 6865f76e5c0ea23e7c6910ca723c7d5c08f391bd | 3,615,378 |
def get_timeseries_data_as_df(quantum:object, entity:object, attribute:str=None):
"""
:param quantum: An instance of quantumleap where the timeseries data should be obtained from
:param entity: The entity of which the data should be obtained
:param attribute: The attribute of which the data should be ... | 505e2f2ea58c0e3681dd4eed3ed0437f81c9b5f3 | 3,615,379 |
async def login_for_access_token(
form_data: OAuth2PasswordRequestForm = Depends(),
db: AsyncSession = Depends(get_db_session),
):
"""Generate and return a token"""
user = await crud.backend_user.authenticate(db=db, user_name=form_data.username, password=form_data.password)
# check if OK
if us... | 636db7af85f0fb2e951bc6dfb1c3fb53b0213a89 | 3,615,380 |
from datetime import datetime
import pytz
def utc_float_to_pretty(utc_float=None, fmt=None, timezone=None):
"""Return the formatted version of utc_float
- fmt: a strftime format
- timezone: a timezone
If no utc_float is provided, a utc_float for "right now" will be used. If no
fmt is provided an... | a419d41818e2fbd5682f0dfc8b453f85da2b85a4 | 3,615,381 |
def find_teacher(req: str):
"""
Find teacher
:param req: Request
:return: Search result as string
"""
if len(req) < 3:
return r_teacher_find_symbols
req_f = f"%{req.lower()}%"
res = cur.execute("SELECT * FROM teachers WHERE teacherClassSearchable LIKE ? LIMIT 5", (req_f,)).fetch... | 0158f1cccf816d03b6cc4bc107096384ccbf38a7 | 3,615,382 |
def pause_synchronization():
"""
Pauses synchronization of files from Artella server
"""
client = get_artella_client()
return client.pause_downloads() | 9eff1128e4e80809ca0a96b86f64835489519cff | 3,615,383 |
def shortest_common_super_sequence(a, b):
"""
get the shortest common string for a and b
This cannot solve complex case like the one in the test case, when same
char repeats before the next common substring letter.
"""
def separate_by_char(letter, seq):
idx_seq = seq.find(letter)
... | 3a989f342269b1319c4fc3af48f894ef1bcb53fb | 3,615,384 |
def contains_carriage_return(text):
"""Check if carriage return is present."""
return "↵" in clean_string(text) | 13f470e652a231b43cfd890e5a9f444f466b3215 | 3,615,385 |
from datetime import datetime
def timestamp_to_datetime(
timestamp: float,
tzinfo: timezone = timezone.utc,
) -> datetime:
"""
Convert a given UNIX timestamp to a Python datetime object.
Args:
timestamp: A UNIX timestamp (as a float).
tzinfo: A timezone object. Usually, everything... | 041b43383d68565086eb817379ba341dd2ce6883 | 3,615,386 |
import os
import statistics
def read_list_from_file(
files_list_path: str = FILES_LIST_PATH,
files_list_filename: str = FILES_LIST_FILENAME,
) -> list:
""" Import list from file """
if os.path.exists(f"{files_list_path}/{files_list_filename}"):
try:
with open(f"{files_list_path}/{... | 02e6b26f88a06f9ddbd8c93fe3b93d89fd175061 | 3,615,387 |
def handle_get(key):
"""Return a tuple containing True if the key exists and the message
to send back to the client."""
try:
return_value = DATABASE_DICT[key]
operation_status = True
except KeyError:
operation_status = False
return_value = None
return (operation_statu... | 8da98332545f97996294fdaea05684da6dfbe4f0 | 3,615,388 |
def preprocess_document(text):
"""Wrapper of the above."""
return create_tokens(lowercase_text(text)) | bae1e0d5789caaac3a9254037aa604f43b49dee3 | 3,615,389 |
def analizar_propuesta(propuesta, codigo):
"""Determina aciertos y coincidencias"""
aciertos = 0
coincidencias = 0
for i in range(DIGITOS):
if propuesta[i] == codigo[i]:
aciertos += 1
elif propuesta[i] in codigo:
coincidencias += 1
return aciertos,coincidencias | dd86380a1afb044ff922f8de64c4892976f17c6c | 3,615,390 |
def conditions_gen(conditions, safe=True):
""" Generate comma separated conditions.
Args:
conditions: An iterator that yields ConditionClause tuples.
Returns:
The string of the query.
"""
conditions_str = ''
connector = None
for index, condition in e... | 6a00557004ce4a3080df3d6d477df2014c681c7b | 3,615,391 |
def as_type(val, types):
"""Try converting `val`to each of `types` in turn, returning the first one that succeeds."""
errs = []
for type in make_seq(types):
try:
return type(val)
except Exception as e:
errs.append(e)
pass
raise TypeError('Could not con... | da30769367f6f295fde983ad637610ace14f2b6a | 3,615,392 |
import json
def cjson_parser(cjsonfile, trajfile=None):
"""Parse CJSON files
Parameters
----------
cjsonfile : str
Path to the CJSON file.
trajfile : str, optional
Name of trajectory file to be saved, by default None.
Returns
-------
atoms
A list of Atoms obje... | caf4b21b8a887408dc59c80672d39f5787a04bfa | 3,615,393 |
import ast
def get_version_from_module(content: str) -> str:
"""Get the __version__ value from a module."""
# adapted from setuptools/config.py
try:
module = ast.parse(content)
except SyntaxError as exc:
raise IOError(f'Unable to parse module: {exc}')
try:
return next(
... | bce0932d487bb778fd9dba5cbd0ae15c5f888fa6 | 3,615,394 |
def tableHeaders():
"""
tableHeaders table model headers
Returns:
list: header definitions
"""
data = [
[
"jobID",
{
"Type": "int",
"CastFunction": int,
"Label": " " + _(Text.txt0131) + " ",
"A... | 2b10d139efc5d3965cf8a636b9ad80c7cfbecaf3 | 3,615,395 |
import unicodedata
import re
def slugify(value, allow_unicode=False):
"""
Convert to ASCII if 'allow_unicode' is False. Convert spaces to hyphens.
Remove characters that aren't alphanumerics, underscores, or hyphens.
Convert to lowercase. Also strip leading and trailing whitespace.
From Django 2.... | c36a9c383f537ace0d7113994d36eae79f631073 | 3,615,396 |
import yaml
def cfg_to_algorithm(config_file):
""" Return instance of classification algorithm helper from config file
Args:
config_file (str): location of configuration file for algorithm
Returns:
tuple: scikit-learn estimator (object) and configuration file (dict)
Raises:
... | f8dde9cbb47e59e994e5ae688b7f432b89c46d3b | 3,615,397 |
import os
def _parse_instance_info(node):
"""Gets the instance specific Node deployment info.
This method validates whether the 'instance_info' property of the
supplied node contains the required or optional information properly
for this driver to deploy images to the node.
:param node: a target... | 58e97b86c2fd3b6fa4b97bb0a94b5c36fa95c8f4 | 3,615,398 |
def get_pdf_form():
"""
1. Call the envelope get method
"""
# import pdb; pdb.set_trace()
args = {
"account_id": session["ds_account_id"],
"document_id": 1,
"envelope_id": session["envelope_id"],
"envelope_documents": session["envelope_documents"],
"base_path"... | ddbcaff85e4424a8c7509c47a69f25428f942c94 | 3,615,399 |
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