content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import json
def load_config(config_file):
"""
加载配置文件
:param config_file:
:return:
"""
with open(config_file, encoding='UTF-8') as f:
return json.load(f) | 85bab8a60e3abb8af56b0ae7483f2afe992d84b4 | 26,334 |
def decode(var, encoding):
"""
If not already unicode, decode it.
"""
if PY2:
if isinstance(var, unicode):
ret = var
elif isinstance(var, str):
if encoding:
ret = var.decode(encoding)
else:
ret = unicode(var)
els... | da59232e9e7715c5c1e87fde99f19997c8e1e890 | 26,335 |
def vehicle_emoji(veh):
"""Maps a vehicle type id to an emoji
:param veh: vehicle type id
:return: vehicle type emoji
"""
if veh == 2:
return u"\U0001F68B"
elif veh == 6:
return u"\U0001f687"
elif veh == 7:
return u"\U000026F4"
elif veh == 12:
return u"\U0... | 8068ce68e0cdf7f220c37247ba2d03c6505a00fe | 26,337 |
import functools
def np_function(func=None, output_dtypes=None):
"""Decorator that allow a numpy function to be used in Eager and Graph modes.
Similar to `tf.py_func` and `tf.py_function` but it doesn't require defining
the inputs or the dtypes of the outputs a priori.
In Eager mode it would convert the tf.... | 5ed18b1575ec88fe96c27e7de38b00c5a734ee91 | 26,338 |
from typing import List
from typing import Dict
def constituency_parse(doc: List[str]) -> List[Dict]:
"""
parameter: List[str] for each doc
return: List[Dict] for each doc
"""
predictor = get_con_predictor()
results = []
for sent in doc:
result = predictor.predict(sentence=sent)
... | 30dd8eca61412083f1f11db6dc8aeb27bc171de9 | 26,339 |
def extract_results(filename):
""" Extract intensity data from a FLIMfit results file.
Converts any fraction data (e.g. beta, gamma) to contributions
Required arguments:
filename - the name of the file to load
"""
file = h5py.File(filename,'r')
results = file['results']
keys = sorted_nicely(... | c4a9f4f66a53050ea55cb1bd266edfa285000717 | 26,341 |
async def bundle_status(args: Namespace) -> ExitCode:
"""Query the status of a Bundle in the LTA DB."""
response = await args.di["lta_rc"].request("GET", f"/Bundles/{args.uuid}")
if args.json:
print_dict_as_pretty_json(response)
else:
# display information about the core fields
p... | 2efb12b4bba3d9e920c199ad1e7262a24220d603 | 26,342 |
def determine_step_size(mode, i, threshold=20):
"""
A helper function that determines the next action to take based on the designated mode.
Parameters
----------
mode (int)
Determines which option to choose.
i (int)
the current step number.
threshold (float)
The ... | 9b59ebe5eeac13f06662e715328d2d9a3ea0e9a2 | 26,343 |
def scroll_down(driver):
"""
This function will simulate the scroll down of the webpage
:param driver: webdriver
:type driver: webdriver
:return: webdriver
"""
# Selenium supports execute JavaScript commands in current window / frame
# get scroll height
last_height = driver.execut... | 7d68201f3a49950e509a7e389394915475ed8c94 | 26,344 |
from datetime import datetime
def processing():
"""Renders the khan projects page."""
return render_template('stem/tech/processing/gettingStarted.html', title="Processing - Getting Started", year=datetime.now().year) | 53f6c69692591601dcb41c7efccad60bbfaf4cf7 | 26,345 |
def conv_unit(input_tensor, nb_filters, mp=False, dropout=0.1):
"""
one conv-relu-bn unit
"""
x = ZeroPadding2D()(input_tensor)
x = Conv2D(nb_filters, (3, 3))(x)
x = relu()(x)
x = BatchNormalization(axis=3, momentum=0.66)(x)
if mp:
x = MaxPooling2D(pool_size=(3, 3), strides=(2, ... | 7c24dae045c38c073431e4fab20687439601b141 | 26,346 |
import torch
def combine_vectors(x, y):
"""
Function for combining two vectors with shapes (n_samples, ?) and (n_samples, ?).
Parameters:
x: (n_samples, ?) the first vector.
In this assignment, this will be the noise vector of shape (n_samples, z_dim),
but you shouldn't need to know ... | 700ea418c6244dc745bf6add89ad786c4444d2fe | 26,347 |
def expandMacros(context, template, outputFile, outputEncoding="utf-8"):
"""
This function can be used to expand a template which contains METAL
macros, while leaving in place all the TAL and METAL commands.
Doing this makes editing a template which uses METAL macros easier,
becau... | 04aad464f975c5ee216e17f93167be51eea8f6e6 | 26,348 |
def graph_papers(path="papers.csv"):
"""
Spit out the connections between people by papers
"""
data = defaultdict(dict)
jkey = u'Paper'
for gkey, group in groupby(read_csv(path, key=jkey), itemgetter(jkey)):
for pair in combinations(group, 2):
for idx,row in enumerate(pair... | 43cae08f303707b75da2b225112fa0bc448306d9 | 26,349 |
def tariterator1(fileobj, check_sorted=False, keys=base_plus_ext, decode=True):
"""Alternative (new) implementation of tariterator."""
content = tardata(fileobj)
samples = group_by_keys(keys=keys)(content)
decoded = decoder(decode=decode)(samples)
return decoded | 8ea80d266dfe9c63336664aaf0fcac520e620382 | 26,350 |
def juego_nuevo():
"""Pide al jugador la cantidad de filas/columnas, cantidad de palabras y las palabras."""
show_title("Crear sopa de NxN letras")
nxn = pedir_entero("Ingrese un numero entero de la cantidad de\nfilas y columnas que desea (Entre 10 y 20):\n",10,20)
n_palabras = pedir_entero("I... | ec42615c3934fd98ca5975f99d215f597f353842 | 26,351 |
def mk_sd_graph(pvalmat, thresh=0.05):
"""
Make a graph with edges as signifcant differences between treatments.
"""
digraph = DiGraph()
for idx in range(len(pvalmat)):
digraph.add_node(idx)
for idx_a, idx_b, b_bigger, p_val in iter_all_pairs_cmp(pvalmat):
if p_val > thresh:
... | f219d964ec90d58162db5e72d272ec8138f8991e | 26,352 |
def body2hor(body_coords, theta, phi, psi):
"""Transforms the vector coordinates in body frame of reference to local
horizon frame of reference.
Parameters
----------
body_coords : array_like
3 dimensional vector with (x,y,z) coordinates in body axes.
theta : float
Pitch (or ele... | 2e0e8f6bf3432a944a350fb7df5bdfa067074448 | 26,353 |
def negloglikelihoodZTNB(args, x):
"""Negative log likelihood for zero truncated negative binomial."""
a, m = args
denom = 1 - NegBinom(a, m).pmf(0)
return len(x) * np.log(denom) + negloglikelihoodNB(args, x) | 8458cbc02a00fd2bc37d661a7e34a61afccb6124 | 26,354 |
def combine(m1, m2):
"""
Returns transform that combines two other transforms.
"""
return np.dot(m1, m2) | 083de20237f484806c356c0b29c42ff28aa801f6 | 26,355 |
import torch
def _acg_bound(nsim, k1, k2, lam, mtop = 1000):
# John T Kent, Asaad M Ganeiber, and Kanti V Mardia.
# A new unified approach forthe simulation of a wide class of directional distributions.
# Journal of Computational andGraphical Statistics, 27(2):291–301, 2018.
"""
... | 45d96fee1b61d5c020e355df76d77c78483a3a0b | 26,356 |
def melspecgrams_to_specgrams(logmelmag2 = None, mel_p = None, mel_downscale=1):
"""Converts melspecgrams to specgrams.
Args:
melspecgrams: Tensor of log magnitudes and instantaneous frequencies,
shape [freq, time], mel scaling of frequencies.
Returns:
specgrams: Tensor of log magnitudes... | 34090358eff2bf803af9b56c210d5e093b1f2900 | 26,358 |
from scipy.stats.mstats import gmean
import numpy as np
def ligandScore(ligand, genes):
"""calculate ligand score for given ligand and gene set"""
if ligand.ligand_type == "peptide" and isinstance(ligand.preprogene, str):
# check if multiple genes needs to be accounted for
if isinstance(eval... | 68141e9a837619b087cf132c6ba593ba5b1ef43d | 26,359 |
def eval(x):
"""Evaluates the value of a variable.
# Arguments
x: A variable.
# Returns
A Numpy array.
# Examples
```python
>>> from keras import backend as K
>>> kvar = K.variable(np.array([[1, 2], [3, 4]]), dtype='float32')
>>> K.eval(kvar)
array(... | a9b5473cc71cd999d6e85fd760018d454c194c04 | 26,360 |
from typing import Optional
def triple_in_shape(expr: ShExJ.shapeExpr, label: ShExJ.tripleExprLabel, cntxt: Context) \
-> Optional[ShExJ.tripleExpr]:
""" Search for the label in a shape expression """
te = None
if isinstance(expr, (ShExJ.ShapeOr, ShExJ.ShapeAnd)):
for expr2 in expr.shapeEx... | a1e9ba9e7c282475c775c17f52b51a78c3dcfd71 | 26,361 |
def poly_learning_rate(base_lr, curr_iter, max_iter, power=0.9):
"""poly learning rate policy"""
lr = base_lr * (1 - float(curr_iter) / max_iter) ** power
return lr | fdb2b6ed3784deb3fbf55f6b23f6bd32dac6a988 | 26,362 |
def parent_path(xpath):
"""
Removes the last element in an xpath, effectively yielding the xpath to the parent element
:param xpath: An xpath with at least one '/'
"""
return xpath[:xpath.rfind('/')] | b435375b9d5e57c6668536ab819f40ae7e169b8e | 26,363 |
from datetime import datetime
def change_project_description(project_id):
"""For backwards compatibility: Change the description of a project."""
description = read_request()
assert isinstance(description, (str,))
orig = get_project(project_id)
orig.description = description
orig.lastUpdated =... | c6b59cfbbffb353943a0a7ba4160ffb0e2382a51 | 26,364 |
import unittest
def run_all(examples_main_path):
"""
Helper function to run all the test cases
:arg: examples_main_path: the path to main examples directory
"""
# test cases to run
test_cases = [TestExample1,
TestExample2,
TestExample3,
Tes... | 9a5176bff4e2c82561e3b0dbee467cd1dec0e63e | 26,365 |
def get_queue(queue):
"""
:param queue: Queue Name or Queue ID or Queue Redis Key or Queue Instance
:return: Queue instance
"""
if isinstance(queue, Queue):
return queue
if isinstance(queue, str):
if queue.startswith(Queue.redis_queue_namespace_prefix):
return Queue.... | 159860f2efa5c7a2643d4ed8b316e8abca85e67f | 26,366 |
def ptttl_to_samples(ptttl_data, amplitude=0.5, wavetype=SINE_WAVE):
"""
Convert a PTTTLData object to a list of audio samples.
:param PTTTLData ptttl_data: PTTTL/RTTTL source text
:param float amplitude: Output signal amplitude, between 0.0 and 1.0.
:param int wavetype: Waveform type for output si... | f4be93a315ff177cbdf69249f7efece55561b431 | 26,367 |
from typing import Union
from pathlib import Path
from typing import Tuple
import numpy
import pandas
def read_output_ascii(
path: Union[Path, str]
) -> Tuple[numpy.ndarray, numpy.ndarray, numpy.ndarray, numpy.ndarray]:
"""Read an output file (raw ASCII format)
Args:
path (str): path to the file
... | ef3008f6cf988f7bd42ccb75bfd6cfd1a58e28ae | 26,368 |
def AliasPrefix(funcname):
"""Return the prefix of the function the named function is an alias of."""
alias = __aliases[funcname][0]
return alias.prefix | 771c0f665ddad2427759a5592608e5467005c26d | 26,369 |
from typing import Optional
from typing import Tuple
from typing import Callable
def connect(
sender: QWidget,
signal: str,
receiver: QObject,
slot: str,
caller: Optional[FormDBWidget] = None,
) -> Optional[Tuple[pyqtSignal, Callable]]:
"""Connect signal to slot for QSA."""
# Parameters e... | 2ebeca355e721c5fad5ec6aac24a59587e4e86bd | 26,371 |
import torch
def get_detection_input(batch_size=1):
"""
Sample input for detection models, usable for tracing or testing
"""
return (
torch.rand(batch_size, 3, 224, 224),
torch.full((batch_size,), 0).long(),
torch.Tensor([1, 1, 200, 200]).repeat((batch_size, 1)),
... | 710a5ed2f89610555d347af568647a8768f1ddb4 | 26,372 |
def build_tables(ch_groups, buffer_size, init_obj=None):
""" build tables and associated I/O info for the channel groups.
Parameters
----------
ch_groups : dict
buffer_size : int
init_obj : object with initialize_lh5_table() function
Returns
-------
ch_to_tbls : dict or Table
... | 964bc6a817688eb8426976cec2b0053f43c6ed79 | 26,373 |
def segmentspan(revlog, revs):
"""Get the byte span of a segment of revisions
revs is a sorted array of revision numbers
>>> revlog = _testrevlog([
... 5, #0
... 10, #1
... 12, #2
... 12, #3 (empty)
... 17, #4
... ])
>>> segmentspan(revlog, [0, 1, 2, 3, 4])
17
>>... | 51624b3eac7bba128a2e702c3387bbaab4974143 | 26,374 |
def is_stateful(change, stateful_resources):
""" Boolean check if current change references a stateful resource """
return change['ResourceType'] in stateful_resources | 055465870f9118945a9e5f2ff39be08cdcf35d31 | 26,375 |
def get_session_from_webdriver(driver: WebDriver, registry: Registry) -> RedisSession:
"""Extract session cookie from a Selenium driver and fetch a matching pyramid_redis_sesssion data.
Example::
def test_newsletter_referral(dbsession, web_server, browser, init):
'''Referral is tracker for... | 0faaa394c065344117cec67ec824ec5186252ee2 | 26,377 |
from typing import Tuple
def paper() -> Tuple[str]:
"""
Use my paper figure style.
Returns
-------
Tuple[str]
Colors in the color palette.
"""
sns.set_context("paper")
style = { "axes.spines.bottom": True,
"axes.spines.left": True,
"axes.spines.righ... | 6e53247c666db62be1d5bf5ad5d77288af277d2d | 26,379 |
import difflib
def _get_diff_text(old, new):
"""
Returns the diff of two text blobs.
"""
diff = difflib.unified_diff(old.splitlines(1), new.splitlines(1))
return "".join([x.replace("\r", "") for x in diff]) | bd8a3d49ccf7b6c18e6cd617e6ad2ad8324de1cc | 26,380 |
def GetStatus(operation):
"""Returns string status for given operation.
Args:
operation: A messages.Operation instance.
Returns:
The status of the operation in string form.
"""
if not operation.done:
return Status.PENDING.name
elif operation.error:
return Status.ERROR.name
else:
retu... | c9630528dd9b2e331a9d387cac0798bf07646603 | 26,382 |
def ft2m(ft):
"""
Converts feet to meters.
"""
if ft == None:
return None
return ft * 0.3048 | ca2b4649b136c9128b5b3ae57dd00c6cedd0f383 | 26,384 |
def show_colors(*, nhues=17, minsat=10, unknown='User', include=None, ignore=None):
"""
Generate tables of the registered color names. Adapted from
`this example <https://matplotlib.org/examples/color/named_colors.html>`__.
Parameters
----------
nhues : int, optional
The number of break... | 34b45185af96f3ce6111989f83d584006ebceb49 | 26,385 |
def get_all_lights(scene, include_light_filters=True):
"""Return a list of all lights in the scene, including
mesh lights
Args:
scene (byp.types.Scene) - scene file to look for lights
include_light_filters (bool) - whether or not light filters should be included in the list
Returns:
(list)... | 4570f36bdfbef287f38a250cddcdc7f8c8d8665d | 26,386 |
def get_df(path):
"""Load raw dataframe from JSON data."""
with open(path) as reader:
df = pd.DataFrame(load(reader))
df['rate'] = 1e3 / df['ms_per_record']
return df | 0e94506fcaa4bd64388eb2def4f9a66c19bd9b32 | 26,387 |
def _format_distribution_details(details, color=False):
"""Format distribution details for printing later."""
def _y_v(value):
"""Print value in distribution details."""
if color:
return colored.yellow(value)
else:
return value
# Maps keys in configuration to... | ccfa7d9b35b17ba9889f5012d1ae5aa1612d33b1 | 26,388 |
async def async_get_relation_id(application_name, remote_application_name,
model_name=None,
remote_interface_name=None):
"""
Get relation id of relation from model.
:param model_name: Name of model to operate on
:type model_name: str
:... | 2447c08c57d2ed4548db547fb4c347987f0ac88b | 26,389 |
from operator import or_
def get_timeseries_references(session_id, search_value, length, offset, column, order):
"""
Gets a filtered list of timeseries references.
This function will generate a filtered list of timeseries references belonging to a session
given a search value. The length, offset, and... | 67011d7d1956259c383cd2722ae4035c28e6a5f3 | 26,390 |
def mxprv_from_bip39_mnemonic(
mnemonic: Mnemonic, passphrase: str = "", network: str = "mainnet"
) -> bytes:
"""Return BIP32 root master extended private key from BIP39 mnemonic."""
seed = bip39.seed_from_mnemonic(mnemonic, passphrase)
version = NETWORKS[network].bip32_prv
return rootxprv_from_see... | ceb5f5e853f7964015a2a69ea2fdb26680acf2b3 | 26,392 |
def translate_text(
text: str, source_language: str, target_language: str
) -> str:
"""Translates text into the target language.
This method uses ISO 639-1 compliant language codes to specify languages.
To learn more about ISO 639-1, see:
https://www.w3schools.com/tags/ref_language_codes.as... | ed82dbb2fd89398340ed6ff39132f95758bfab97 | 26,394 |
def evt_cache_staged_t(ticket):
""" create event EvtCacheStaged from ticket ticket
"""
fc_keys = ['bfid' ]
ev = _get_proto(ticket, fc_keys = fc_keys)
ev['cache']['en'] = _set_cache_en(ticket)
return EvtCacheStaged(ev) | 86543ca98257cab28e4bfccef229c8d8e5b6893b | 26,395 |
from typing import Dict
def _get_setup_keywords(pkg_data: dict, keywords: dict) -> Dict:
"""Gather all setuptools.setup() keyword args."""
options_keywords = dict(
packages=list(pkg_data),
package_data={pkg: list(files)
for pkg, files in pkg_data.items()},
)
keyw... | 34f2d52c484fc4e49ccaca574639929756cfa4dc | 26,396 |
import six
def flatten(x):
"""flatten(sequence) -> list
Returns a single, flat list which contains all elements retrieved
from the sequence and all recursively contained sub-sequences
(iterables).
Examples:
>>> [1, 2, [3,4], (5,6)]
[1, 2, [3, 4], (5, 6)]
>>> flatten([[[1,2,3], (42,... | 041807c1622f644c062a5adb0404d14589cc543b | 26,397 |
from clawpack.visclaw import colormaps, geoplot
from numpy import linspace
from clawpack.visclaw.data import ClawPlotData
from clawpack.visclaw import gaugetools
import pylab
import pylab
from numpy import ma
from numpy import ma
import pylab
import pylab
from pylab import plot, xticks, floor, xlabel
def setplot(plot... | a777686f5b8fafe8c2a109e486242a16d25a463b | 26,398 |
from typing import Dict
import json
def load_spider_tables(filenames: str) -> Dict[str, Schema]:
"""Loads database schemas from the specified filenames."""
examples = {}
for filename in filenames.split(","):
with open(filename) as training_file:
examples.update(process_dbs(json.load(tr... | 1575d0afd4efbe5f53d12be1c7dd3537e54fc46c | 26,399 |
from typing import Dict
import array
def extract_float_arrays(blockids: str, data: bytes) -> Dict[str, array]:
"""Extracts float arrays from raw scope, background trace, and recorder
zoom binary data (block ids a, A, b, B, x, y, Y in the DLC pro 'Scope,
Lock, and Recorder Binary Data' format).
Args:
... | 8789f73d175b9d0f244b33b61d0fe1effa702ded | 26,400 |
def rotate_image(path):
"""Rotate the image from path and return wx.Image."""
img = Image.open(path)
try:
exif = img._getexif()
if exif[ORIENTATION_TAG] == 3:
img = img.rotate(180, expand=True)
elif exif[ORIENTATION_TAG] == 6:
img = img.rotate(270, expand=True... | b4f450a3f6cb01a4d9c8e6c384edeabd0366ac63 | 26,401 |
def predict():
"""Predict endpoint.
Chooses model for prediction and predcits
bitcoin price for the given time period.
@author: Andrii Koval, Yulia Khlyaka, Pavlo Mospan
"""
data = request.json
if data:
predict = bool(data["predict"])
if predict:
if predictor.p... | 90fbc72e3a57ad7dae3617bec20268c87a0c158a | 26,402 |
def splice_imgs(img_list, vis_path):
"""Splice pictures horizontally
"""
IMAGE_WIDTH, IMAGE_HEIGHT = img_list[0].size
padding_width = 20
img_num = len(img_list)
to_image = Image.new('RGB',
(img_num * IMAGE_WIDTH + (img_num - 1) * padding_width,
... | 97d4ab32f1a734fbd04e7c558062867c2e6bd3b4 | 26,403 |
def create_segmented_colormap(cmap, values, increment):
"""Create colormap with discretized colormap.
This was created mainly to plot a colorbar that has discretized values.
Args:
cmap: matplotlib colormap
values: A list of the quantities being plotted
increment: The increment used... | 9ab8a0a95896e1ae0f8777b705f920196afc6627 | 26,404 |
from io import StringIO
def division_series_logs():
"""
Pull Retrosheet Division Series Game Logs
"""
s = get_text_file(gamelog_url.format('DV'))
data = pd.read_csv(StringIO(s), header=None, sep=',', quotechar='"')
data.columns = gamelog_columns
return data | 414de8e0409bba9651bef81bbdc811e105d1d11f | 26,405 |
def release_date(json):
"""
Returns the date from the json content in argument
"""
return json['updated'] | 635efd7140860c8f0897e90433a539c8bd585945 | 26,406 |
def init_embedding_from_graph(
_raw_data, graph, n_components, random_state, metric, _metric_kwds, init="spectral"
):
"""Initialize embedding using graph. This is for direct embeddings.
Parameters
----------
init : str, optional
Type of initialization to use. Either random, or spectral, by ... | 22c2d939a47932b625491a1e685b055214753010 | 26,407 |
def basic_hash_table():
"""Not empty hash table."""
return HashTable(1) | b06e59c2a6767309e5394df6e51bdaf12c58d073 | 26,408 |
def scan_by_key(key, a, dim=0, op=BINARYOP.ADD, inclusive_scan=True):
"""
Generalized scan by key of an array.
Parameters
----------
key : af.Array
key array.
a : af.Array
Multi dimensional arrayfire array.
dim : optional: int. default: 0
Dimension along which th... | ea9556b3e2a87a08cca62d03da41edf5985d4156 | 26,409 |
def local_luminance_subtraction(image, filter_sigma, return_subtractor=False):
"""
Computes an estimate of the local luminance and removes this from an image
Parameters
----------
image : ndarray(float32 or uint8, size=(h, w, c))
An image of height h and width w, with c color channels
filter_sigma : ... | d9cc46a205f495c0107211d7222be27f40d6896b | 26,410 |
def createBank():
"""Create the bank.
Returns:
Bank: The bank.
"""
return Bank(
123456,
'My Piggy Bank',
'Tunja Downtown'
) | 676f0d6cf330e7832064393b543a5ffd1f1068d1 | 26,411 |
def str_to_bool(param):
"""
Convert string value to boolean
Attributes:
param -- inout query parameter
"""
if param.upper() == 'TRUE':
return True
elif param.upper() in ['FALSE', None]:
return False
else:
raise InputValidationError(
'Invalid query... | ef860e2b2e623d98576c04ef1e397604576d8d48 | 26,412 |
from typing import Optional
from typing import List
from typing import Dict
from datetime import datetime
def fetch_log_messages(attempt_id: Optional[int] = None,
task_id: Optional[int] = None,
min_severity: Optional[int] = None):
"""
Fetch log messages from the d... | 10e78d0ee14647cf7a390287208a28aa957551a4 | 26,415 |
def part_1_solution_2(lines):
"""Shorter, but not very readable.
A good example of "clever programming" that saves a few lines of code, while
making it unbearably ugly.
Counts the number of times a depth measurement increases."""
return len([i for i in range(1, len(lines)) if lines[i] > lines[i - 1]... | d393f0385a1afbea4c2f3b4d3f51d8e7d0ade204 | 26,417 |
def get_lifecycle_configuration(bucket_name):
"""
Get the lifecycle configuration of the specified bucket.
Usage is shown in usage_demo at the end of this module.
:param bucket_name: The name of the bucket to retrieve.
:return: The lifecycle rules of the specified bucket.
"""
s3 = get_s3()... | 380c884afddbf72db6474e60480bf75ebe67309e | 26,418 |
def compute_reward(ori, new, target_ids):
"""
Compute the reward for each target item
"""
reward = {}
PE_dict = {}
ori_RI, ori_ERI, ori_Revenue = ori
new_RI, new_ERI, new_Revenue = new
max_PE, min_PE, total_PE = 0, 0, 0
for item in target_ids:
PE = new_Revenue[item] - ori_Revenue[item]
# Eq. (3) in paper... | a64a1c47089924d373c7435c5018c63fd4edbe74 | 26,419 |
from typing import Any
import torch
import tqdm
def _compute_aspect_ratios_slow(dataset: Any, indices: Any = None) -> Any:
"""Compute the aspect ratios."""
print(
"Your dataset doesn't support the fast path for "
"computing the aspect ratios, so will iterate over "
"the full dataset an... | 8fd183a5c353503067666526bdf6722bb53a4317 | 26,420 |
import getopt
def parse_args(input_args):
"""
Parse the supplied command-line arguments and return the input file glob
and metric spec strings.
:param input_args: Command line arguments.
:return: A triplet, the first element of which is the input file glob,
the second element is the ... | a15327a3aa2aae86ef8ad14ebcae46b6f3593503 | 26,421 |
def _diffuse(field: jnp.ndarray, diffusion_coeff: float, delta_t: float) -> jnp.ndarray:
"""
Average each value in a vector field closer to its neighbors to simulate
diffusion and viscosity.
Parameters
----------
field
The vector field to diffuse. *Shape: [y, x, any].*
diffusion_coe... | e05763df93164bd7b4baa778720dbecc32fea228 | 26,422 |
def dAdzmm_ron_s0(u0, M, n2, lamda, tsh, dt, hf, w_tiled):
"""
calculates the nonlinear operator for a given field u0
use: dA = dAdzmm(u0)
"""
print(u0.real.flags)
print(u0.imag.flags)
M3 = uabs(np.ascontiguousarray(u0.real), np.ascontiguousarray(u0.imag))
temp = fftshift(ifft(f... | 57c958bca07b77eaa406cb6b95bf5719af34075b | 26,423 |
def create_support_bag_of_embeddings_reader(reference_data, **options):
"""
A reader that creates sequence representations of the input reading instance, and then
models each question and candidate as the sum of the embeddings of their tokens.
:param reference_data: the reference training set that deter... | 0b09423e9d62d1e5c7c99bd1ebede22ca490797a | 26,424 |
def get_hosts_cpu_frequency(ceilo, hosts):
"""Get cpu frequency for each host in hosts.
:param ceilo: A Ceilometer client.
:type ceilo: *
:param hosts: A set of hosts
:type hosts: list(str)
:return: A dictionary of (host, cpu_frequency)
:rtype: dict(str: *)
"""
hosts_cpu_total ... | aa6049b9d011d187e1a246a413835aafdbb5c6dc | 26,425 |
def _cloture(exc):
"""
Return a function which will accept any arguments
but raise the exception when called.
Parameters
------------
exc : Exception
Will be raised later
Returns
-------------
failed : function
When called will raise `exc`
"""
# scoping will sav... | b2e22f5b4bd267d1945b7f759f5ddfb1ee8c44e5 | 26,426 |
from typing import Dict
import json
def _with_environment_variables(cmd: str, environment_variables: Dict[str, object]):
"""Prepend environment variables to a shell command.
Args:
cmd (str): The base command.
environment_variables (Dict[str, object]): The set of environment
variab... | ae27d9e7a62f49e836f1c1b116205f318d9d0dd3 | 26,427 |
def update_spam_assets(db: 'DBHandler') -> int:
"""
Update the list of ignored assets using query_token_spam_list and avoiding
the addition of duplicates. It returns the amount of assets that were added
to the ignore list
"""
spam_tokens = query_token_spam_list(db)
# order maters here. Make ... | 4e7f4e5ae8a6b92ebd5a60a34d9330330690b663 | 26,428 |
import png
def png_info(path):
"""Returns a dict with info about the png"""
r = png.Reader(filename=path)
x, y, frames, info = r.read()
return info | 97b9df7dd7800f350695e8d678d25154c7a4b2b8 | 26,430 |
def _(data: ndarray, outliers: ndarray, show_report: bool = True) -> ndarray:
"""Process ndarrays"""
if type(data) != type(outliers):
raise TypeError("`data` and `outliers` must be same type")
# convert to DataFrame or Series
data = DataFrame(data).squeeze()
outliers = DataFrame(outliers).sq... | 1c478af8a6fffcf6240b2547782ee3fc256fdd0c | 26,431 |
import six
def bool_from_string(subject, strict=False, default=False):
"""
将字符串转换为bool值
:param subject: 待转换对象
:type subject: str
:param strict: 是否只转换指定列表中的值
:type strict: bool
:param default: 转换失败时的默认返回值
:type default: bool
:returns: 转换结果
:rtype: bool
"""
TRUE_STRINGS ... | 3c6efa416471da391e60b82aec3753d823ee2878 | 26,432 |
def prot_to_vector(seq: str) -> np.ndarray:
"""Concatenate the amino acid features for each position of the sequence.
Args:
seq: A string representing an amino acid sequence.
Returns:
A numpy array of features, shape (len(seq), features)"""
# convert to uppercase
seq = seq.upper()
... | ac5293ee67698243e4910c87944133f9697d8646 | 26,433 |
def set_partition(num, par):
"""
A function returns question for partitions of a generated set.
:param num: number of questions.
:param par: type of items in the set based on documentation.
:return: questions in JSON format.
"""
output = question_list_maker(num, par, 'set-par... | 71540d753020e5333558098b7edf96c4318fb316 | 26,435 |
def meanS_heteroscedastic_metric(nout):
"""This function computes the mean log of the variance (log S) for the heteroscedastic model. The mean log is computed over the standard deviation prediction and the mean prediction is not taken into account.
Parameters
----------
nout : int
Number of out... | 75bc5ddb482cc0e99bb4f5f9b0d557321b57cf06 | 26,436 |
def ec2_connect(module):
""" Return an ec2 connection"""
region, ec2_url, boto_params = get_aws_connection_info(module)
# If we have a region specified, connect to its endpoint.
if region:
try:
ec2 = connect_to_aws(boto.ec2, region, **boto_params)
except (boto.exception.No... | d94b5a1359a31657aa2dffd1f0c11d9cd06493dd | 26,437 |
import glob
def read_lris(raw_file, det=None, TRIM=False):
"""
Read a raw LRIS data frame (one or more detectors)
Packed in a multi-extension HDU
Based on readmhdufits.pro
Parameters
----------
raw_file : str
Filename
det : int, optional
Detector number; Default = both
... | 98351f63a78a37ac8cbb3282e71903ee6dd6bbb1 | 26,438 |
def mu(n: int) -> int:
"""Return the value of the Moebius function on n.
Examples:
>>> mu(3*5*2)
-1
>>> mu(3*5*2*17)
1
>>> mu(3*3*5*2)
0
>>> mu(1)
1
>>> mu(5)
-1
>>> mu(2**10-1)
-1
"""
if n == 1:
re... | b8347480041de2dc9dfc469096293e3815eebbcd | 26,439 |
def find_last(arr, val, mask=None, compare="eq"):
"""
Returns the index of the last occurrence of *val* in *arr*.
Or the last occurrence of *arr* *compare* *val*, if *compare* is not eq
Otherwise, returns -1.
Parameters
----------
arr : device array
val : scalar
mask : mask of the a... | 376a21174bc26ca332768aadf96b84b06e7f55f5 | 26,440 |
def find_orphans(input_fits, header_ihdus_keys):
"""Return a dictionary with keys=(ihdu, key) and values='label' for missing cards in 'header_ihdus_keys'
Parameters:
-----------
input_fits: astropy.io.fits.HDUList instance
FITS file where to find orphan header cards
header_ihdus_keys: l... | bcc98722ba43450ff68367f776a84c0e193447d9 | 26,441 |
def Rotation_multiplyByBodyXYZ_NInv_P(cosxy, sinxy, qdot):
"""
Rotation_multiplyByBodyXYZ_NInv_P(Vec2 cosxy, Vec2 sinxy, Vec3 qdot) -> Vec3
Parameters
----------
cosxy: SimTK::Vec2 const &
sinxy: SimTK::Vec2 const &
qdot: SimTK::Vec3 const &
"""
return _simbody.Rotation_multiplyByB... | 93303a83224b29d9dddf09a64f36d7004ae2ace0 | 26,443 |
def sqrt(x: float):
"""
Take the square root of a positive number
Arguments:
x (int):
Returns:
(float): √x
Raises:
(ValueError): If the number is negative
"""
if x < 0:
raise ValueError('Cannot square-root a negative number with this '
... | ab43573010044ffa3861f6a13a58135be52c02b4 | 26,444 |
def get_tree_type(tree):
"""Return the (sub)tree type: 'root', 'nucleus', 'satellite', 'text' or 'leaf'
Parameters
----------
tree : nltk.tree.ParentedTree
a tree representing a rhetorical structure (or a part of it)
"""
if is_leaf_node(tree):
return SubtreeType.leaf
tree_t... | 15d292ab1f756594add92a6999c7874f6d7fc45b | 26,445 |
def intersection(ls1, ls2):
"""
This function returns the intersection of two lists without
repetition. This function uses built in Python function set()
to get rid of repeated values so inputs must be cast to list
first.
Parameters:
-----------
ls1 : Python list
The first list. Cannot be array.
ls2 : Pyt... | fb3bda67d8040da5f4f570e8ff10a8503e153f36 | 26,446 |
def params_count(model):
"""
Computes the number of parameters.
Args:
model (model): model to count the number of parameters.
"""
return np.sum([p.numel() for p in model.parameters()]).item() | 12bb8463f6eb722a5cb7e7adfdf869764be67944 | 26,448 |
from pathlib import Path
import platform
import shutil
def open_cmd_in_path(file_path: Path) -> int:
""" Open a terminal in the selected folder. """
if platform.system() == "Linux":
return execute_cmd(["x-terminal-emulator", "-e", "cd", f"{str(file_path)}", "bash"], True)
elif platform.system() ==... | 899424cd8ab2d76a5ca47d7219a7057d29bb5abe | 26,449 |
def get_f(user_id, ftype):
"""Get one's follower/following
:param str user_id: target's user id
:param str ftype: follower or following
:return: a mapping from follower/following id to screen name
:rtype: Dict
"""
p = dict(user_id=user_id, count=200, stringify_ids=True,
include... | 31371d823509c8051660ca0869556253af6b99cc | 26,450 |
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