content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def fetch_BLESS():
"""
Fetch Baroni and Marco categorization dataset
Parameters
-------
Returns
-------
data : sklearn.datasets.base.Bunch
dictionary-like object. Keys of interest:
'X': words
'y': cluster assignment
References
----------
Baroni et al. "... | eec5be91c7ae5821264e229f22bf5eebccd7e2a8 | 81,456 |
def convolve(X, kernel, mode='same'):
"""
Parameters
----------
X : (データ数, 高さ, 幅, チャンネル)の4次元配列からなる入力データ
Returns
-------
col : 2次元配列
"""
if X.ndim == 3:
H, W, C = X.shape
pad, stride = 1, 1
filter_h, filter_w = 3, 3
kernel = kernel.reshape([3, 3])
... | 1aa1858a651b8113c5d08d035772540bd63e7b00 | 81,457 |
def sign(x):
"""
Sign function
"""
return 1 if x >= 0 else -1 | 20d85cf36d183c96e75fa3b795bf7f05f558e3b8 | 81,458 |
def is_selection_within_a_line(view):
"""Returns true if the selection is within single line, but not zero-width."""
selection = view.sel()
if len(selection) == 0:
# Null selection
return False
# selection_coverage will be the region that covers all selections.
selection_coverage = s... | 441a964140db24040a3180975f9f7fd29a2299c2 | 81,459 |
def savings_flexible_product_position(self, asset: str, **kwargs):
"""Get Flexible Product Position (USER_DATA)
GET /sapi/v1/lending/daily/token/position
https://binance-docs.github.io/apidocs/spot/en/#get-flexible-product-position-user_data
Args:
asset (str)
Keyword Args:
recvWin... | a47d0032e6da7853960ed4cfa807c5793926e9c5 | 81,460 |
def redirecttargetsupported(ui, target):
"""Determine whether a redirect target entry is supported.
``target`` should come from the capabilities data structure emitted by
the server.
"""
if target.get(b'protocol') not in SUPPORTED_REDIRECT_PROTOCOLS:
ui.note(
_(b'(remote redirec... | f3ff6c2ff5e1ae373914de9927315b9f96ec6b56 | 81,461 |
def reg_update_strlist(*args):
"""
reg_update_strlist(subkey, add, maxrecs, rem=None, ignorecase=False)
Update list of strings associated with given key.
@param subkey: key name (C++: const char *)
@param add: string to be added to list, can be NULL (C++: const char
*)
@param maxrecs: lim... | c8d8944315ab0cf43461cefdc1330c223d0dc7be | 81,462 |
def sorted_pearson_corr(data: pd.DataFrame) -> pd.DataFrame:
"""Calculate correlations between columns and sort them by absolute value.
Calculate Pearson correlations between all pairs of distinct columns and
sort them in descending order by their absolute value.
Columns named 'time' or being constant ... | 1d27070cea55a2d2d9ab1224e32cc5fe8af978bb | 81,463 |
def get_publisher():
"""get_publisher"""
log.info("initializing publisher")
pub = None
auth_url = ""
if FORWARD_ENDPOINT_TYPE == "redis":
auth_url = FORWARD_BROKER_URL
else:
auth_url = FORWARD_BROKER_URL
pub = Publisher(name="{}_{}".format(SOURCE, "-redis"),
... | 82b65605b4e2830ce81c72a09efa0d0bc23397a9 | 81,465 |
def mesh_box():
"""Box triangle mesh."""
points = np.array([[0., 0., 0.], [10., 0., 0.], [0., 20., 0.],
[10., 20., 0.], [0., 0., 30.], [10., 0., 30.],
[0., 20., 30.], [10., 20., 30.]])
cells = np.array([[0, 4, 6], [0, 6, 2], [5, 1, 3], [5, 3, 7], [0, 1, 5],
... | 61f8c25abb75013edecafb87f376552e1a36b349 | 81,466 |
def create_train_test_data(datasize, host, port, imbalance_multiplier, test_size):
"""
Args:
datasize: number of positively identified items to generate
host: the host for the dataset (accidents)
port: the port for the host
imbalance_multiplier: Multiplier of the non-accident siz... | 1ccd112f9f8f02ea84c122d9522d2e5aa4d419c8 | 81,467 |
import concurrent
def blocking(params=None):
"""
Mark function for thread execution
"""
def wrapper(handler):
logger.info(f"Wrap block {handler.__name__}")
async def caller(*args, **kwargs):
wrapped = partial(handler, *args, **kwargs)
logger.info('Executing tas... | 55edc16f7cd47954932a9d198addfdee6e4756d3 | 81,468 |
def _check_est(est):
"""Check if a given estimator is valid"""
# Check estimator exist and return the correct function
estimators = {
'cov': np.cov,
'scm': _scm,
'lwf': _lwf,
'oas': _oas,
'mcd': _mcd,
'sch': _sch,
'corr': np.corrcoef
}
if cal... | cc6f9a28808822d75164d21ca1b93d9f3b84733d | 81,469 |
def NumProperties():
"""(read-only) Number of Properties this Circuit Element."""
return lib.CktElement_Get_NumProperties() | f8260794b6a0bceec630429aa54c78ccfd67d02d | 81,471 |
def unflatten_dataframe(
data: np.ndarray,
columns=None,
index=None,
num_rows=None,
num_cols=None,
index_name=None,
columns_name=None,
) -> pd.DataFrame:
"""
Reverse a flatten_dataframe operation to reconstruct the original unflattened dataframe
Args:
data (np.ndarray): ... | dfa6f07ce2e15504b23882f44078ce6ee4082174 | 81,472 |
def subscribe_to_basket_action(newsletter):
"""Subscribe to Basket action."""
def subscribe_to_basket(modeladmin, request, queryset):
"""Subscribe to Basket or update details of already subscribed."""
ts = [(mozillians.users.tasks.update_basket_task
.subtask(args=[userprofile.id,... | dabad4ae6068e27c9ab5ed0d2f2b7a2e79d7ec4f | 81,473 |
def dict_hangman(num_of_tries):
"""
The function return the "photo" of the hangman.
:param num_of_tries: the user's number of guessing
:type num_of_tries: int
:return: the photo of the hangman
:rtype: string
"""
HANGMAN_PHOTHOS = {
'1': """ x-------x""",
'2':
"""
x-------x
|
|
|
|
|""",
'3': """
... | 3864d3072fa0fe9fea6c7e02733e466669335c80 | 81,474 |
import scipy
def tocoo(X):
"""
Convert an array to a sparse COO array.
If the input is already an `sparse.COO` object, this returns the object directly; otherwise it is converted.
"""
if isinstance(X, sp.COO):
return X
elif isinstance(X, sp.DOK):
return sp.COO(X)
elif scip... | 4c3b0eb42ee094b3304bae4c0a33684b767ddcf2 | 81,476 |
from typing import OrderedDict
from typing import Dict
import torch
def get_sample_scheme(n_agents, obs_spaces, act_spaces):
""" get sample batch and buffer specifications
specify how to encode experience in SampleBatch/EpisodeBatch
use hierarchical keys: obs/agent_idx/obs_sub_fields
"""
... | 008ef294fdae1e3426dd027402e49f914fd6a755 | 81,477 |
def read_words(path):
"""
From a TIMIT file, reads the word info
Parameters
----------
path : str
path to file
Returns
-------
list of dicts
each dict has spelling, begin, end
"""
output = []
sr = 16000
prev = None
with open(path, 'r') as fi... | e3ad680e179ff07615d88503c614ee1a706d3bf5 | 81,478 |
def build_void(lines, start, end):
"""
Builds a void from the given parameters.
Parameters
----------
lines : `list` of `str`
The lines of the section.
start : `int`
The starting index of the void.
end : `int`
The void's last line's index +1.
Returns
-------... | 25cad6592033f34a67a65be9d1c1b1c507d33ddd | 81,480 |
from typing import Optional
async def list_cameras(options: Optional[str] = ""):
"""
Returns the list of cameras managed by the processor.
"""
return {
"cameras": get_cameras(options)
} | 85c57cc9bdb25abdb392ee29cda69ca06f5ad599 | 81,481 |
import json
def loadDataset():
"""
Loading and Spliting Dataset
"""
train, test, val = [], [], []
print("==> Loading Training Set")
with open("./data/Batch_1_train_filter.json") as json_file:
train = json.load(json_file)
#train = pd.DataFrame(train_file)
... | 1dd7602da719d2917202c312a3c0fef9fda36c64 | 81,482 |
def check_seq_len(tokens, mask):
""" Warn user and shorten sequence if the tokens are too long, otherwise return original
Args:
tokens (List[List[str]]): List of token sequences
mask (List[List[int]]): List of mask sequences
Returns:
tokens (List[List[str]]): List of token sequence... | a17125b6752d17be2a0f8079154d29d141a57b2a | 81,483 |
def efficientnet_b2(pretrained=False, **kwargs):
""" EfficientNet-B2 """
model = _gen_efficientnet(channel_multiplier=1.1, depth_multiplier=1.2, **kwargs)
if pretrained:
model.load_state_dict(load_state_dict_from_url(model_urls['efficientnet_b2']))
return model | 2eb2073a46cb591048c4724faafd8431585b4dbf | 81,484 |
def plot_ccfrv_servalrvc(data, shiftserval=True, title='', stats=['std', 'wstd'], **kwargs):
"""
stats : {'std', None}
Show std of the parameter
"""
# Plot style
if kwargs is None:
kwargs = dict()
kwargs['linestyle'] = kwargs.get('linestyle', 'None')
kwargs['marker'] = kwarg... | 000effbcc5311b44ed28ddaf4892403cd8468e70 | 81,485 |
import numpy as np
def random_complex_matrix(matrix_size):
"""
Generate a random, square, complex matrix of size `matrix_size`.
"""
return (np.random.rand(matrix_size, matrix_size)
+ 1j * np.random.rand(matrix_size, matrix_size)) | 4f8f486ebe53b87115631783696715dff6fae92d | 81,486 |
def service_operations_by_systemctl(dut, service, operation, skip_error_check=False):
"""
Author: Chaitanya Vella (chaitanya-vella.kumar@broadcom.com)
Function to do the service operations using systemctl
:param dut:
:param service:
:param operation:
:return:
"""
command = "systemctl... | e136a764024614843b43c01132e51263fcb611bd | 81,487 |
def split_warnings_errors(output: str):
"""
Function which splits the given string into warning messages and error using W or E in the beginning of string
For error messages that do not start with E , they will be returned as other.
The output of a certain pack can both include:
... | aaf0ea05f5d32247f210ae1696ea58824629d075 | 81,488 |
def get_hourly_data_dict(csv_path):
"""
Generate a Pandas DataFrame containing hourly count data.
Parameters
----------
csv_path: str
Location of CSV containing hourly count data from NeuroPace.
Returns
-------
df_hour: pandas.DataFrame
"""
df_hour = pd.rea... | 7b52c266807aed8d71b001d5117a35cff3a8b6b5 | 81,491 |
def bcut_from_rel(bvals, relbthresh=0.04):
"""
Given a sequence of b values and a relative b threshhold between
"undiffusion weighted" and "diffusion weighted", return the absolute b
corresponding to the threshhold.
"""
minb = np.min(bvals)
maxb = np.max(bvals)
return minb + relbthresh *... | 6b8a85c0772d436bf33150af5a2c5146d9fbc5e7 | 81,493 |
def reverse_complement(x):
"""Return reverse complement."""
a = str()
for i in x:
a = base_complement(i)+a
return a | 5b66194e690d765bd50928ddc20fd13ccce340d2 | 81,494 |
def random_color() -> str:
# type: () -> str
"""
Generates a random color in the form of string of RGB hex values.
For example; `#ffffff`, `#123456`, `#a42c30`, etc.
Returns:
A random color in the form of string of RGB hex values.
"""
r = hex(np.random.randint(0, 256))[2:]
g = hex(... | c55075c8fc28ee981a9af1f70d34413b0b970fff | 81,495 |
def createCalibrationArrays(board, combinedCorners):
"""
Creates arrays from the chessboard and detected corners for solving camera properties.
Args:
board: 2D Chessboard Coordinate Array
combinedCorners: Array of arrays of coordinates of detected chessboard corners
Returns:
im... | 65c4993ac8de41d7b5144bfe19651b4af4b16f9f | 81,497 |
def var_label(var, precision=3):
"""Return label of variable node."""
if var.name is not None:
return var.name
elif isinstance(var, gof.Constant):
h = np.asarray(var.data)
is_const = False
if h.ndim == 0:
is_const = True
h = np.array([h])
dstr ... | 1dd17043e7c931489347645e1cd994f3c8fe461c | 81,498 |
import numpy
def subtract_3_rasters(
raster_path_a, raster_path_b, raster_path_c, target_path):
"""Calculate target = a-b-c and ignore nodata."""
a_nodata = pygeoprocessing.get_raster_info(raster_path_a)['nodata'][0]
b_nodata = pygeoprocessing.get_raster_info(raster_path_b)['nodata'][0]
c_noda... | ec1e03181cff2e3c37595a7246374f204c3a73f1 | 81,499 |
from xmodule.modulestore.django import modulestore
def serialize_course(course_id):
"""
Serializes a course into py2neo Nodes and Relationships
Args:
course_id: CourseKey of the course we want to serialize
Returns:
nodes: a list of py2neo Node objects
relationships: a list of ... | e034d188de47d35c2b70e15d3d7a33eee346210b | 81,500 |
from typing import Type
import json
def json_load(cls: Type[C], fp) -> C:
"""Deserialize an instance of type 'cls' from JSON read from a read()-
supporting object.
This supports classes that use PEP-526 type annotations, and is meant to
work especially well with classes that use [`@dataclass`], such ... | bd1c13eb624b092283c8d6186351eecf9ed3d2c4 | 81,501 |
def get_sensors_model_detail(sim, sensor_names: list) -> (np.array, np.array, np.array):
"""
Get the sensor ID, sensor ADR and sensor DIM of a list of sensor names as string
Args:
sim (MjSim): mujoco py simulation
sensor_names (list): list with sensor names as strings, e.g. ['force_sensor',... | 8b15d43e66016d2c6d393b7495a696ceb4c3765e | 81,502 |
def pdf_with_params(rt, params):
"""Helper function that calls full_pdf and gets the parameters
from the dict params.
"""
v = params['v']
V = params['sv']
z = params['z']
Z = params['sz']
t = params['t']
T = params['st']
a = params['a']
return hddm.wfpt.full_pdf(rt, v=v, V=V... | 7b30efd46496616dba7700b55da82b1a022e7bc3 | 81,503 |
def neighbors_graph(ingraph, source, beamwidth=4, maxnodes=10,
max_iter=100, tol=1e-4):
""" Neighbors of source node in ingraph """
assert ingraph.is_directed(), "not implemented for undirected graphs"
centrality = nx.eigenvector_centrality_numpy(ingraph,
... | 424359092b13ae00e50d8c6768c14987f2065e89 | 81,504 |
def find_time_travelers(data_dir):
"""
Some edges cite forwards in time...
"""
case_metadata = pd.read_csv(data_dir + 'raw/case_metadata_master_r.csv',
index_col='id')
edgelist = pd.read_csv(data_dir + 'raw/edgelist_master_r.csv')
# some edges travel forwards in... | d870c09c749ca1e57e771855bceb66581249ac50 | 81,505 |
import numpy
def log_fbank(signal,samplerate=16000,win_length=0.025,win_step=0.01,filters_num=26,NFFT=512,low_freq=0,high_freq=None,pre_emphasis_coeff=0.97):
"""Calculate log of features.
"""
feat,energy=fbank(signal,samplerate,win_length,win_step,filters_num,NFFT,low_freq,high_freq,pre_emphasis_coeff)
... | d7f246e1efd83f26018dd3dbe5b72f17e215d032 | 81,506 |
from datetime import datetime
def readall_msgs(boxid):
""" Mark all messages in a box as read """
now = datetime.datetime.utcnow()
q = Message.update(read=now).where(Message.read.is_null()).where(Message.receivedby == current_user.uid)
q.where(Message.mtype == boxid).execute()
socketio.emit('notif... | 5fdc854b128e5163bc7ba82f33c7c6fce328a217 | 81,507 |
def negotiation_failed(err=None):
"""
Construct a template for SSH connection
"""
tpl = { 'ssh-event': 'negotiation-failed' }
if err is not None:
tpl['error'] = err
return tpl | 9f0b608ee0e062ce932ea0f2a22aab7cdc7156f8 | 81,509 |
import numpy as np
from scipy.stats import rankdata
def MI_basic(x, y, h_method = 'sturge', ranking = True):
"""This function calculates the mutual information between the time series x(t) and its delayed version x(t+tau)
using equi-spaced partitions. The size of the partition is based on the desired bin siz... | 44a160071b2c905ddb92215eb92044b1f63b0db7 | 81,510 |
def csv_add_gmt8(file_src,col_name,file_dest):
"""
add GMT8 time to CSV by re-format one column
"""
df = pd.read_csv(file_src)
df[col_name + "GMT8"] = df[col_name].apply(date_to_gmt8)
df_save=df.drop(['Unnamed: 0'], axis=1)
df_save.to_csv(file_dest)
return df_save | 13abf6f305e85fa68c4fafbb585995f4ef216b99 | 81,511 |
async def list_by_server(hub, ctx, server_name, resource_group, **kwargs):
"""
.. versionadded:: 2.0.0
Gets a list of virtual network rules in a server.
:param server_name: The name of the server.
:param resource_group: The name of the resource group. The name is case insensitive.
CLI Exampl... | 53998fc4f1d48e159b90a575929d81da3263717c | 81,512 |
def test_conf(request):
"""Fixture function for command-line option."""
return request.config.getoption('test_conf') | 55eb956e75c3716a240987b69070be963d3bad21 | 81,513 |
def _get_type_and_value(entry):
"""Parse dmidecode entry and return key/value pair"""
r = {}
for l in entry.split('\n'):
s = l.split(':')
if len(s) != 2:
continue
r[s[0].strip()] = s[1].strip()
return r | e6dd2068f10085c2dac233f1f71512e5874c5adc | 81,514 |
def delete_personal_message(request, pk=None):
"""
Create a view that allows user to delete a personal message to him / her
"""
user = User.objects.get(email=request.user.email)
contactuserposts = ContactUser.objects.all()
contactuserpost = get_object_or_404(ContactUser, pk=pk)
if request.me... | 2fc933a189b244c6e25a33fb22dc2d0e9ee7fd63 | 81,515 |
import torch
def qeuler(q, order, epsilon=0):
"""
Convert quaternion(s) q to Euler angles.
Expects a tensor of shape (*, 4), where * denotes any number of dimensions.
Returns a tensor of shape (*, 3).
"""
assert q.shape[-1] == 4
original_shape = list(q.shape)
original_shape[-1] = 3
... | 1926af959690b397dcfe2b712e3ff04b19285eed | 81,516 |
def action_greedy(state, actions_ctrl, height, width):
"""
when training, enemy is greedy policy
"""
state_copy = state.copy()
board_width = state_copy['board_width']
board_height = state_copy['board_height']
beans_positions = state_copy[1]
snakes_positions = {key: state_copy[key] for ke... | 0e0de7abd7ea31f1d19fec68534b8999fde8843e | 81,517 |
def tanh(z):
""" An AlComplex compatible hyperbolic tangent function.
Parameters
----------
z : Python numeric type or AlComplex
Returns
-------
AlComplex
"""
return AlComplex.from_python_complex(cm.tanh(z.to_python_complex())) | 09e25f2fd4ecd4a9a7940b787624d1855d7165fc | 81,519 |
import numpy
import random
def randomPairs(n_records: int, sample_size: int) -> IndicesIterator:
"""
Return random combinations of indices for a square matrix of size n
records. For a discussion of how this works see
http://stackoverflow.com/a/14839010/98080
"""
n: int = n_records * (n_record... | 40d5ae4eb117944971b2d0efe4ccbf7603f04dae | 81,521 |
from google.cloud import kms
def create_key_version(project_id, location_id, key_ring_id, key_id):
"""
Creates a new version of the given key.
Args:
project_id (string): Google Cloud project ID (e.g. 'my-project').
location_id (string): Cloud KMS location (e.g. 'us-east1').
key_ri... | d70306e786dfffad5c9f6e8da288488f7166ff1a | 81,522 |
def parse_instance_envs(env_raws, instances):
"""
Replaces the values in the environment variables for values
that exist in this infrastructure
Supported:
- role.PUBLIC_IP -> adds the public ip
- role.PRIVATE_IP -> adds the first private ip retrieved by facts
- r... | b2677af3641e2e4a0cef1d15c977afc230e61cfc | 81,523 |
def GetAllData(fe_fd, csv_file, agg_num, hop):
"""
Input: Features folder(String), CSV file(String), agg_num(Integer), hop(Integer).
Output: Loaded features(Numpy Array) and labels(Numpy Array).
Loads all the features saved as pickle files.
"""
# read csv
with open( csv_file, 'rb') as f:
... | da3f8b29b7e1216b46b290baabda3cfd23caab17 | 81,524 |
def ready() -> bool:
"""Checks if the storage system is ready.
Returns
-------
bool
Whether or not the configured storage system is ready.
"""
return storage_ready() | a9c509d38f62727f2d43ffa71ad6f2dcb6ab5d40 | 81,525 |
import torch
from operator import xor
from operator import and_
from operator import not_
def sha256(message):
"""
h0 = expand_constant(num_to_32_bits(h0n))
h1 = expand_constant(num_to_32_bits(h1n))
h2 = expand_constant(num_to_32_bits(h2n))
h3 = expand_constant(num_to_32_bits(h3n))
h4 = expand... | 09615149938f2922d463606af94edbf01c0e1430 | 81,526 |
def check_if_two_hsps_overlap(hsp_obj1, hsp_obj2):
"""Takes two HSP objects and returns True if their ranges overlap, and
False if not.
"""
x = hsp_obj1.hit_range
y = hsp_obj2.hit_range
overlap = check_if_two_hsp_ranges_overlap([x, y])
return overlap | 9f031a0e889c03c7662006cbeba23c4f17ab5304 | 81,527 |
import torch
def make_identity(shape: torch.Size) -> torch.Tensor:
"""
:param shape: shape of the desired matrix
:return: matrix which is zeroes everywhere and ones on diagonal
"""
result = torch.zeros(shape)
for i in range(np.minimum(shape[0], shape[1])):
result[i, i] = 1.0
ret... | a7339c9d20152e4fdfddce209716caeaf7704247 | 81,529 |
from sklearn.metrics import mutual_info_score
def mi(x, y):
""" Mutual Information (MI) between two images. """
return mutual_info_score(x.ravel(), y.ravel()) | c31b45f60160d505f7a96d69a013c3fd0c5842f4 | 81,530 |
def _replace_strings(obj, old, new, inplace=False):
"""
Recursively replaces all strings in the given object.
This function is specifically meant to help with saving and loading
of config dictionaries and should not be considered a general tool.
"""
if not inplace:
obj = obj.copy()
... | 3f7661a53ab8cbb836eee68b1bb3d1df9e73c4a5 | 81,531 |
def symmetrize(input_df, source_col_name, dest_col_name, value_col_name=None,
multi=False, symmetrize=True):
"""
Take a dataframe of source destination pairs along with associated
values stored in a single GPU or distributed
create a COO set of source destination pairs along with values w... | b8082a6b5e43d2da36112f92ae85cc0dbc693942 | 81,532 |
def slavic_findpeaks(data, spacing=1, limit=None):
"""
Searches for peaks in data
History:
-nov 2015: Janko Slavic, update
-mar 2013: janko.slavic@fs.uni-lj.si
Finds peaks in `data` which are of `spacing` width and >=`limit`.
:param data: values
:param spacing: minimum spacin... | 8c3c9569bd69fa7fdbf1b6e125409e82d9fca510 | 81,533 |
def hello_world() -> str:
""" Say something! """
return "Hello World!" | 22deba02b863355d150653caf744a65950a2fec5 | 81,534 |
def test_control_flow_ref():
"""
Feature: Control flow graph sinking scenarios.
Description: If the return value of subgraph is Ref, should run graph mode with kernelbykernel.
Expectation: No exception.
"""
class IFFuncNet(nn.Cell):
def __init__(self):
super().__init__()
... | c9fac191db1276ce8d86816a2a56b24478403873 | 81,535 |
import math
def wshorten(text, width=80, placeholder='…', pos='right'):
"""Shorten the text to fit in the given width even if not all characters\
occupy only one column in a terminal.
:param str text: the text
:param int width: the width
:param str placeholder: the placeholder
:param str pos:... | 962777e1b2b2e3393b334d0a2a2ab18c48732ddc | 81,536 |
def authenticated_user_required(f):
"""
Декоратор проверки того, что к обращение к требуемому ресурсу системы
производится аутентифицированным пользователем
"""
def action(request, *args, **kwargs):
user = request.user
if not user or not user.is_authenticated():
if reque... | abf8a85fd94ae75b06b928e6b1707ccdd329a842 | 81,537 |
def get_data(count):
"""
Use this function to generate data, returns a touple containing
a list, a dictionary and a nested dictionary.
"""
l = []
d = {}
nd = {}
for i in range(count):
d[lipsum(1)] = lipsum(10)
l.append(lipsum(3))
nd[lipsum(1)] = {i: lipsum... | 26104b4416a3161d194515cb3977dff73e1265a6 | 81,538 |
def normalise(imgs):
"""
Normalises the two images by taking their channel means:
img = (img-mean)/255
Args:
imgs:
Returns:
"""
rgb_max = 255.0
rgb_mean = np.mean(imgs, axis=(0, 2, 3), keepdims=True)
imgs = (imgs - rgb_mean)
imgs /= rgb_max
return imgs | e5f5ce7b81537aedb1d16a29240cceddf65bcf86 | 81,539 |
def compute_accuracy(predictions, y):
"""Computes the accuracy of predictions against the gold labels, y."""
predictions, y = predictions.to('cpu'), y.to('cpu')
return np.mean(np.equal(predictions.numpy(), y.numpy())) | 270fd5bd97c18b73285701af1c4173ab29c1612a | 81,540 |
def range_geometric_row(number, d, r=1.1):
"""Returns a list of numbers with a certain relation to each other.
The function divides one number into a list of d numbers [n0, n1, ...], such
that their sum is number and the relation between the numbers is defined
with n1 = n0 / r, n2 = n1 / r, n3 = n2 / r... | 92e7f9f1b85011323cf5e90002d8f9151ae17e0e | 81,541 |
def get_decks(df):
"""Search for the information of all decks inside a dataframe, given the feature 'Cabin'
Parameters
----------
df : panda dataframe
Returns
-------
Original dataframe with a new feature called 'Deck'
"""
df['Deck'] = df['Cabin'].apply(get_deck)
# Mod... | be613c8a6301ce1c81bcaa2147416c01161e1f8d | 81,542 |
def delete(center, keys):
""" Delete keys from all workers """
return IOLoop().run_sync(lambda: _delete(center, keys)) | 51cc3625ea2a0a91cc9fda72cf21e70f66021e59 | 81,543 |
import hashlib
def getIdHash(id):
""" Return md5 prefix based on id value"""
m = hashlib.new('md5')
m.update(id.encode('utf8'))
hexdigest = m.hexdigest()
return hexdigest[:5] | a9e8d67fae494cd2eaac41b6258be69ed10b667a | 81,544 |
def compute_mean_std(arrays, axis=0, keepdims=False, dtype=np.float64, ddof=1):
"""
Computes the total mean and standard deviation of a set of arrays across
a given axis or set of axes, using Welford's algorithm.
"""
kwargs = dict(axis=axis, keepdims=True, dtype=dtype)
n = m = s = 0
for data... | 55c55c44bfe5c4d3a7c2be1d06b15d32e23f5713 | 81,545 |
def page_index():
"""the default homepage for Dalton"""
return render_template('/dalton/index.html', page='') | 121319a74d59e98dbcbdab75e035bdcabde1c608 | 81,546 |
import requests
def load_url(url, nlp):
"""
Process url to get content for analysis. [WIP feature (see readme)]
"""
try:
url_request = requests.get(
url,
headers={"User-agent": f"Espial/v0.1"},
)
except Exception:
return False
html_doc = Document... | 3a621535c58a06f560b4de16f51a58448dfcce9d | 81,547 |
from datetime import datetime
def filter_on_times(df, start_time, end_time, reverse=False):
"""
Filter df keeping rows with index times in [start_time, end_times].
- reverse: reverse the filtering
"""
dbg.dassert_type_is(df, pd.DataFrame)
dbg.dassert_type_is(start_time, datetime.time)
dbg... | e72f5b10b772c4c562a8f69822a38b08be28bb46 | 81,548 |
def _SubTestsDictEntry(sub_test_paths, has_rows, deprecated):
"""Recursively gets an entry in a sub-tests dict."""
entry = {
'has_rows': has_rows,
'sub_tests': _SubTestsDict(sub_test_paths, deprecated)
}
if deprecated:
entry['deprecated'] = True
return entry | 825f37da4ae4a57c485b49b7aa9a3ee15bbaa2b9 | 81,549 |
def reverse_and_collapse(in_str: str) -> str:
"""
Solution: Iterate backwards and copy chars to a new string if they don't equal the last char of that new string.
Time: O(n) -> Iterate every char
Space: O(n) -> Construct another string with max size = length of input string
"""
if not in_str:
raise ValueError... | 4d8c9224420a3bbe73ef6347cccaae0e20441943 | 81,550 |
import time
def _get_selenium_webelements(parent, kwargs, min_elements, wait):
"""Get all Selenium elements matching the kwargs.
Parameters
----------
parent : browser or element
The browser or element.
kwargs : dict
Keyword arguments.
min_elements : int, optional
The ... | 0a16c6a040d4dbabeabb2cf8c24a8141c2754931 | 81,551 |
def exists(_env):
"""Always activate this tool."""
return True | 62ba86e515af9da467e7e3425e692c589b8c7fd8 | 81,552 |
def video_call_setup_teardown(log,
ad_caller,
ad_callee,
ad_hangup=None,
video_state=VT_STATE_BIDIRECTIONAL,
verify_caller_func=None,
verify... | f245350e60326bb7b52c921d164a68da5e97c91e | 81,553 |
def AADT_splits(df_spl):
"""Calculates AADT per vehicle type.
Args: df_spl, a pandas dataframe.
Returns: df_spl, a pandas dataframe containing new columns:
dir_aadt: directional aadt
aadt_auto: auto aadt
pct_auto, pct_bus, pct_truck : percentage mode splits of auto and bus.
"""
... | d5a10dc8cf34093190ca0035b1cf9f256c841d1b | 81,554 |
def split_train_test(ds):
"""
Given the dataset, split in two datasets:
One is the Training set. Other is the Test set.
The proportion is 80% to 20% Respectively
Dataset -> Dataset, Dataset
"""
samples_train, samples_test, classes_train, classes_test = train_test_split(ds.data, ds.targ... | 62a6f68809383fa65f059fdb951de7f3cde4a46b | 81,555 |
import itertools
def _pairwise(iterable):
"""s -> (s0,s1), (s1,s2), (s2, s3), ..."""
a, b = itertools.tee(iterable)
next(b, None)
return zip(a, b) | 326b0cfe3374dcc5093dcb36d0f027921ac418c0 | 81,556 |
def normalize(s):
"""Removes all punctuation, whitespace, and accents. Converts to lowercase."""
return strip_accents(strip_non_alphanumerics(s)).lower() | 9b06e754aa4cf459eb35c75daee996d8664150ca | 81,557 |
from typing import List
def findalldevs() -> List[str]:
"""Return a list of capture devices."""
devs = ct.POINTER(_pcap.pcap_if_t)()
ebuf = ct.create_string_buffer(_pcap.PCAP_ERRBUF_SIZE)
status = _pcap.findalldevs(ct.byref(devs), ebuf)
if status:
raise OSError(ebuf.value.decode("utf-8", "... | 65ed4d1e2dff10d285ceda06453c1d59e1b248b2 | 81,559 |
def norm_layer_name(name):
"""Some heuristics to normalize a layer name from multiple sources.
For example, some depictions of VGG-16 use use upper case; others
use lower case. Some use hyphens; others use underscores. These
heuristics are by no means complete, but they increase the
likelihood that... | ec1d387010282178616c2e7a63b765ceea6078bc | 81,560 |
from typing import Tuple
def mask_2d_centres_from(
shape_native: Tuple[int, int],
pixel_scales: Tuple[float, float],
centre: (float, float),
) -> (float, float):
"""
Returns the (y,x) scaled central coordinates of a mask from its shape, pixel-scales and centre.
The coordinate system is define... | 4d06a452833370be99464ce55a4192484fce828c | 81,561 |
def union(mask_a, mask_b):
"""
This function ...
:param args:
:return:
"""
return mask_a + mask_b | f813cf9eeba22922b4146ac61bbe6a590d16d21f | 81,562 |
def get_compensation(host, token, compensation_pk, method=METHOD['https']):
"""
GET a serialized Compensation instance
compensation_pk (required)
Returns a dictionary with keys:
'status': The HTTP response code
'reason': The HTTP response reason
'data': Dictionary represe... | 0bcf2286670cdb29f929e3ba4acb24361b42d580 | 81,563 |
def square_dist(x, y, dim=1):
"""
"""
return (x-y).pow(2).sum(dim=dim) | f42f1964b7da0ef4cafe5e7db475bf8f429377bc | 81,564 |
import typing
import joblib
def _run_commands(commands, args):
"""コマンドの実行。"""
results: list[CommandResult] = []
# run formatters (serial)
for command in commands:
if CONFIG[command] and ALL_COMMANDS[command]["type"] == "formatter":
results.append(run_command(command, args))
#... | 4cf03b0d12ae9536151c45c10e27a1f02daeb37d | 81,566 |
def convert_list(element_list: list) -> list:
"""
Convert list of Python AST objects to cboost AST objects
"""
return [convert(e) for e in element_list] | c7c8571d053ed00f1044ba02c9cb59077a9e3ff7 | 81,568 |
import re
def doesExecutableWork(
exe_args: ExeArgs,
check_regex: RunRegex,
env_args: EnvArgs = EnvArgs(script="", args=None, do_source=False),
) -> str:
"""Checks if the given command line works.
Tries to run the command with the given arguments (see `runCommand`) and
parses the output of th... | fe8e97499228eab3692db3cfae977d1f426628c3 | 81,569 |
import fnmatch
def get_s3_data_paths(s3, bucket_name, root, file_types=["*.jsonl"]):
"""
Get all paths to particular file types in a S3 root location
s3: S3 boto3 resource
bucket_name: The S3 bucket name
root: The root folder to look for files in
file_types: List of file types to look for, or... | 3254565cafafaf8d11a35d8f3ffb44ba9f8c57b6 | 81,570 |
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