content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def coords_to_id(traversed):
"""calculate the id in level-order from the coordinates
Args:
input: traversed tree as list of dict
Returns:
traversed tree (dict) with id as key
"""
traversed_id = {}
#print('coords to id, traversed ', traversed)
for node in traversed:
... | 91f993f9693e01983de1f7fa124dcb5cb39a92f9 | 25,600 |
def dataframe_to_ipy_image(df, f=None, **kwargs):
"""Create IPython Image from PIL Image.
Args:
df - dataframe to render
f - operation to perform on PIL Image (e.g. f=lambda img: img.rotate(-90, expand=True))
kwargs - arguments to IPython.display.Image, such as width and height for html display
... | 44348ac041067620bfa37cdedb22f3544e6bc940 | 25,601 |
import os
import yaml
def get_yaml_file_info(file_name):
"""Loads a yaml file into a dictionary
Args:
file_name (str): The file to load
Returns:
Raises:
ProgramError
"""
if not os.path.isfile(file_name):
print("Cannot find file %s" % file_name)
raise ProgramE... | 516c1484515d26d97dca44d2e2d04eb6fb852026 | 25,602 |
def read_dmarkov(columns, rows, D, symbolization_type, division_order, suffix=["normal", "gaussian002"]):
"""
Reads the result files for the D-Markov algorithm. The function requires a configuration for the parameters of
the D-Markov. The suffix parameter indicates if the non-modified files should be loaded... | c9fec2d46cbc8c3f4bcf7fc112779432dd6e9155 | 25,603 |
import torch
def compute_output_shape(observation_space, layers):
"""Compute the size of the output after passing an observation from
`observation_space` through the given `layers`."""
# [None] adds a batch dimension to the random observation
torch_obs = torch.tensor(observation_space.sample()[None])
... | 865b9b90f39f5726feb16da70afc515071991fd7 | 25,604 |
def tenure_type():
""" RESTful CRUD controller """
return s3_rest_controller(#rheader = s3db.stdm_rheader,
) | bfee3c2be579e1db6e8799b4a9d3156130b802a9 | 25,605 |
def _format_port(port):
"""
compute the right port type str
Arguments
-------
port: input/output port object
Returns
-------
list
a list of ports with name and type
"""
all_ports = []
for key in port:
one_port = {}
one_port['name'] = key
port... | 2fa65686b6b764afc97a200a02baec65645c9879 | 25,606 |
import os
def getTileName(minfo,ti,xIndex,yIndex,level = -1):
"""
creates the tile file name
"""
global LastRowIndx
max = ti.countTilesX
if (ti.countTilesY > max):
max=ti.countTilesY
countDigits= len(str(max))
parts=os.path.splitext(os.path.basename(minfo.filename))
if par... | e48dea5c57e018c1ab99a865a5ceacf6dbd91e29 | 25,607 |
import io
def proc_cgroups(proc='self'):
"""Read a process' cgroups
:returns:
``dict`` - Dictionary of all the process' subsystem and cgroups.
"""
assert isinstance(proc, int) or '/' not in proc
cgroups = {}
with io.open(_PROC_CGROUP.format(proc), 'r') as f:
for cgroup_line i... | 95cb24cbbb4167dd2fa26ce36d78e5f532f10c1a | 25,608 |
import csv
def load_csv_data(
data_file_name,
*,
data_module=DATA_MODULE,
descr_file_name=None,
descr_module=DESCR_MODULE,
):
"""Loads `data_file_name` from `data_module with `importlib.resources`.
Parameters
----------
data_file_name : str
Name of csv file to be loaded fr... | 3629dded45954c25e538c53b5c7bc5d0dfec0a39 | 25,609 |
def ptFromSudakov(sudakovValue):
"""Returns the pt value that solves the relation
Sudakov = sudakovValue (for 0 < sudakovValue < 1)
"""
norm = (2*CA/pi)
# r = Sudakov = exp(-alphas * norm * L^2)
# --> log(r) = -alphas * norm * L^2
# --> L^2 = log(r)/(-alphas*norm)
L2 = log(sudakovVal... | 8ba504749f13ed1046799b5456d1f6f3c74bfc1e | 25,610 |
def _set_lod_2(gml_bldg, length, width, height, bldg_center):
"""Adds a LOD 2 representation of the building based on building length,
width and height
alternative way to handle building position
Parameters
----------
gml_bldg : bldg.Building() object
A building object, where bldg is ... | 309f66319c5cce07adbcb456548b3c29f707d96c | 25,611 |
def load_data(filename: str):
"""
Load Agoda booking cancellation dataset
Parameters
----------
filename: str
Path to house prices dataset
Returns
-------
Design matrix and response vector in either of the following formats:
1) Single dataframe with last column representing ... | 808b0e1344352a6645ef090019ac5015172e096c | 25,612 |
def send_mail(subject, message, from_email, recipient_list, html_message='',
scheduled_time=None, headers=None, priority=PRIORITY.medium):
"""
Add a new message to the mail queue. This is a replacement for Django's
``send_mail`` core email method.
"""
subject = force_text(subject)
... | a97103e5e56463170122252073ebcc873306c708 | 25,613 |
def proxy_a_distance(source_X, target_X):
"""
Compute the Proxy-A-Distance of a source/target representation
"""
nb_source = np.shape(source_X)[0]
nb_target = np.shape(target_X)[0]
train_X = np.vstack((source_X, target_X))
train_Y = np.hstack((np.zeros(nb_source, dtype=int), np.ones(nb_targe... | fe0102cfd2a5a3cadb64a5ddfb7705e7b8440028 | 25,614 |
import json
def load_metadata(stock_model_name="BlackScholes", time_id=None):
"""
load the metadata of a dataset specified by its name and id
:return: dict (with hyperparams of the dataset)
"""
time_id = _get_time_id(stock_model_name=stock_model_name, time_id=time_id)
path = '{}{}-{}/'.format(... | 1171bf3a06327e907449872755315db8c34565c8 | 25,615 |
from typing import List
import torch
def evaluate(env: AlfEnvironment, algorithm: RLAlgorithm,
num_episodes: int) -> List[alf.metrics.StepMetric]:
"""Perform one round of evaluation.
Args:
env: the environment
algorithm: the training algorithm
num_episodes: number of epis... | 0218f1a38be8f897ac3b2a70036213877f5f7654 | 25,616 |
from pagure.hooks import BaseHook
def get_plugin_names(blacklist=None, without_backref=False):
"""Return the list of plugins names.
:arg blacklist: name or list of names to not return
:type blacklist: string or list of strings
:arg without_backref: whether or not to include hooks that
have ba... | 7f3b560334a5680fdcb4a47929613706bb699393 | 25,617 |
def is_autosync(*args):
"""
is_autosync(name, type) -> bool
is_autosync(name, tif) -> bool
Is the specified idb type automatically synchronized?
@param name (C++: const char *)
@param type (C++: const type_t *)
"""
return _ida_typeinf.is_autosync(*args) | 0f7eacc9931897f5fc0f076d0e07e0f1e1e01bce | 25,618 |
def scanboards(dirpath):
"""Scans the directory for board files and returns an array"""
print("Scanning for JSON board data files...", end = "")
files = [x for x in subfiles(dirpath) if x.endswith(".json") and not x.endswith("index.json")]
print("Found {} in \"{}\"".format(len(files), dir... | 9cfce78b06fef0b8f7ebaa3d1c5904dfd3e0ec56 | 25,619 |
def router_get_notification() -> dict:
"""Lista todas as configurações do BOT Telegram."""
logger.log('LOG ROTA', "Chamada rota /get_all.")
return {"configuracoes": TelegramNotifier.make_current_cfg_dict()} | 46faf67e02d537de49616085a1bcbb30f3087805 | 25,620 |
def script_filter_maximum_value(config):
""" The scripting version of `filter_maximum_value`. This
function applies the filter to the entire directory (or single
file). It also adds the tags to the header file of each fits file
indicating the number of pixels filtered for this filter.
Parame... | 8eccc2356c803d63c1ddfc7603e1dc784ccc49fe | 25,621 |
import time
def pretty_date(d):
""" returns a html formatted pretty date """
special_suffixs = {1 : "st", 2 : "nd" , 3 : "rd", 21 : "st", 22 : "nd", 23 : "rd", 31 : "st"}
suffix = "th"
if d.tm_mday in special_suffixs:
suffix = special_suffixs[d.tm_mday]
suffix = "<sup>" + suffix + "</sup>"
day = ti... | 7d6675f115021ddd46b2a614e831c9fae8faf7ad | 25,622 |
from datetime import datetime
import dateutil
def update(model, gcs_bucket, gcs_object):
"""Updates the given GCS object with new data from the given model.
Uses last_modified to determine the date to get items from. Bases the
identity of entities in the GCS object on their 'id' field -- existing
ent... | 66bde1371383f16c9449a3aec29e894e6a473d44 | 25,623 |
import logging
def setup_logging(
logger: logging.Logger = logging.getLogger(__name__),
verbose: bool = False,
debug: bool = False,
) -> logging.Logger:
"""Configure logging."""
if debug:
logger.setLevel(logging.DEBUG)
elif verbose:
logger.setLevel(logging.INFO)
else:
... | 22024a54fdc6f7a1a542121f032baef33649fe02 | 25,624 |
import os
def train_protocol():
""" train the model with model.fit() """
model = create_cnn_model(tf_print=True)
model.compile(optimizer='adam', loss='mean_squared_error')
x_all, y_all = load_data_batch(num_images_total=30000)
model.fit(x=x_all, y=y_all, batch_size=128, epochs=50, verbose=1,
... | e9c999c8c5ac53b675a06da5898cccd33aac2bef | 25,625 |
def member_requests_list(context, data_dict):
""" Show request access check """
return _only_registered_user() | c3ffdf798aabc80b3bd91160e9a580ff38c9540d | 25,626 |
def get_conductivity(sw_tdep,mesh,rvec,ham_r,ndegen,avec,fill,temp_max,temp_min,tstep,sw_tau,idelta=1e-3,tau0=100):
"""
this function calculates conductivity at tau==1 from Boltzmann equation in metal
"""
def calc_Kn(eig,veloc,temp,mu,tau):
dfermi=0.25*(1.-np.tanh(0.5*(eig-mu)/temp)**2)/temp
... | 0304781bac6160b353a90e5bce061faa89075bc0 | 25,627 |
from typing import List
from typing import Union
import time
def time_match(
data: List,
times: Union[List[str], List[int], int, str],
conv_codes: List[str],
strptime_attr: str,
name: str,
) -> np.ndarray:
"""
Match times by applying conversion codes to filtering list.
Parameters
... | 0480f5ca3e29ebcc4f44bef5a81db8fb36f78616 | 25,628 |
def find_best_input_size(sizes=[40]):
""" Returns the average and variance of the models """
accuracies = []
accuracy = []
t = []
sigma = []
time = []
#sizes = np.arange(5, 80, 5)
for size in sizes:
#for size in [80]:
accuracy = []
N = 20
for j in range(N):
... | 3d22441d07b44779cde6c4347669a435568f0378 | 25,629 |
import torch
def eval_acc(trainer, dataset="val"):
"""
"""
trainer.model.eval()
with torch.no_grad():
shot_count = 0
total_count = 0
for inputs,targets in trainer.val_dataset():
inputs = nested_to_cuda(inputs, trainer.device)
targets = nested_to_cuda(tar... | 452861ccb5805778d5dd0bc83226b73539b8aebb | 25,630 |
import os
import sys
def which(program):
"""
Find a program in PATH and return path
From: http://stackoverflow.com/q/377017/
"""
def is_exe(fpath):
found = os.path.isfile(fpath) and os.access(fpath, os.X_OK)
if not found and sys.platform == 'win32':
fpath = fpath + ".ex... | b58fe57517bf66301ff1de0e8f345674a5796d9d | 25,631 |
def _floor(n, base=1):
"""Floor `n` to a multiple of `base`"""
return n // base * base | 49019e4aa925b4f77a7f13f9919d36948bd132cc | 25,632 |
import os
def record_pid(ptype: str, running: bool = True) -> int:
"""
记录程序运行的PID
"""
pid = os.getpid() if running else -1
if ptype == 'bpid':
i = dao.update_config([ConfigVO(const.Key.Run.BPID.value, pid)], True)
elif ptype == 'fpid':
i = dao.update_config([ConfigVO(const.Key.... | 0000a2688a58744f6fdbc8c531f298d8c2154645 | 25,633 |
def fixed_timezone(offset): # type: (int) -> _FixedTimezone
"""
Return a Timezone instance given its offset in seconds.
"""
if offset in _tz_cache:
return _tz_cache[offset]
tz = _FixedTimezone(offset)
_tz_cache[offset] = tz
return tz | 401303d1893bc2ab7bee19ba09161549a2cc7fb2 | 25,634 |
def getFactoriesInfo():
"""
Returns a dictionary with information on how to create an object Sensor from its factory
"""
return {'Stitcher':
{
'factory':'createStitcher'
}
} | 75806002b1ada6bd1a87c9bde6b2e47f587d988d | 25,635 |
from typing import Dict
from typing import List
from typing import Optional
def pending_observations_as_array(
pending_observations: Dict[str, List[ObservationFeatures]],
outcome_names: List[str],
param_names: List[str],
) -> Optional[List[np.ndarray]]:
"""Re-format pending observations.
Args:
... | bc9bfff51b991b413b5861f55c8b0f55331ab763 | 25,636 |
import os
def sauv_record_jeu(pseudo, collec, numero, score):
"""
Sauvegarde le nouveau record dans le fichier de record.
:param pseudo: Pseudo du joueur ayant réalisé le nouveau record
:param collec: Collection du puzzle sur lequel il y a eu un nouveau record
:param numero: Numero du puzzle sur ... | 4b1e4176898eadc4fff965d0f9d4c2da37a7859a | 25,637 |
def inverted_conditional_planar(input_dim, context_dim, hidden_dims=None):
"""
A helper function to create a
:class:`~pyro.distributions.transforms.ConditionalPlanar` object that takes care
of constructing a dense network with the correct input/output dimensions.
:param input_dim: Dimension of inpu... | 8bf5ae5dd6d8743a3eb1506b26dec5cf51af2bde | 25,638 |
def create_category_index(categories):
"""Creates dictionary of COCO compatible categories keyed by category id.
Args:
categories: a list of dicts, each of which has the following keys:
'id': (required) an integer id uniquely identifying this category.
'name': (required) string representing category... | 226a39189d4203e2861bbba7334d5b8bbaa3b7df | 25,639 |
import torch
def n_step_returns(q_values, rewards, kls, discount=0.99):
"""
Calculates all n-step returns.
Args:
q_values (torch.Tensor): the Q-value estimates at each time step [time_steps+1, batch_size, 1]
rewards (torch.Tensor): the rewards at each time step [time_steps, batch_size, 1]... | 3bbd6026046328dc8ef63ab3e871f6c47636cb80 | 25,640 |
import os
def user(*args: str) -> str:
"""
Creates an absolute path from the specified relative components within the
user's Cauldron app data folder.
:param args:
Relative components of the path relative to the root package
:return:
The absolute path
"""
return clean(os.... | 6ab8750b5c29a1d23ed194adab569b4c7b7c87c3 | 25,641 |
import random
def random_split_exact(iterable, split_fractions=None):
"""Randomly splits items into multiple sample lists according to the given
split fractions.
The number of items in each sample list will be given exactly by the
specified fractions.
Args:
iterable: a finite iterable
... | 2b7ae86e55b9be225e94cfc983295beeb3ed08cf | 25,642 |
def calc_output_coords(source_dataset, config, model_profile):
"""Construct the coordinates for the dataset containing the extracted variable(s).
The returned coordinates container has the following mapping of attributes to
coordinate names:
* :kbd:`time`: :kbd:`time`
* :kbd:`depth`: :kbd:`depth`
... | 22759d734f5356bc0597db5528eac864df23d39c | 25,643 |
def computeMaskIntra(inputFilename, outputFilename, m=0.2, M=0.9, cc=1):
""" Depreciated, see compute_mask_intra.
"""
print "here we are"
return compute_mask_intra(inputFilename, outputFilename,
m=m, M=M, cc=cc) | 0eaf8b8845c12b1fc90cb032881dacf53a2c7d12 | 25,644 |
def read_space_delimited(filename, skiprows=None, class_labels=True):
"""Read an space-delimited file
skiprows: list of rows to skip when reading the file.
Note: we can't use automatic comment detection, as
`#` characters are also used as data labels.
class_labels: boolean
if true, the last ... | be25b4f6c3c775f12fdfef7f334b4886c85a514e | 25,645 |
def get_gas_price(endpoint=_default_endpoint, timeout=_default_timeout) -> int:
"""
Get network gas price
Parameters
----------
endpoint: :obj:`str`, optional
Endpoint to send request to
timeout: :obj:`int`, optional
Timeout in seconds
Returns
-------
int
Ne... | b7f18a5a5044d8aeee7a63b702b01944cbff597b | 25,646 |
def function_3():
"""This is a Function prototype in Python"""
print("Printing Docs String")
return 0 | 4268904e75772b9fef804931e3a3564fda333bc7 | 25,647 |
def client():
""" client fixture """
return testing.TestClient(app=service.microservice.start_service(), headers=CLIENT_HEADERS) | ea9997f9904057f0ffdc3175f081acb7e21e719d | 25,648 |
def get_character_bullet(index: int) -> str:
"""Takes an index and converts it to a string containing a-z, ie.
0 -> 'a'
1 -> 'b'
.
.
.
27 -> 'aa'
28 -> 'ab'
"""
result = chr(ord('a') + index % 26) # Should be 0-25
if index > 25:
current = index // 26
whi... | 357f68feb302f11a996b5446c642ad9ca1f0f8d3 | 25,649 |
import os
def get_masks_path(base_dir, trial, prune_iter):
"""Builds the mask save path"""
return os.path.join(
base_dir,
"trial_{:02d}".format(trial),
"prune_iter_{:02d}".format(prune_iter),
"masks",
) | 7da9d346aa42b5ea9d291b3422aa447cce02db53 | 25,650 |
def update_det_cov(
res: OptResult,
jacobian: JacobianValue):
"""Calculates the inv hessian of the deterministic variables
Note that this modifies res.
"""
covars = res.hess_inv
for v, grad in jacobian.items():
for det, jac in grad.items():
cov = propagate_uncert... | c505654be6f08dcf037337104b4077f6003db876 | 25,651 |
def simplex_init_modified(A, b, c):
"""
Attempt to find a basic feasible vector for the linear program
max: c*x
ST: Ax=b
x>=0,
where A is a (m,n) matrix.
Input Parameters:
A - (n,m) constraint matrix
b - (m,1) vector appearing in the constr... | fd415eedaec1138812fb054656c45450a53535b8 | 25,652 |
import os
def get_all_user_dir():
"""get the root user dir. This is the dir where all users are stored
Returns:
str: path
"""
return os.path.join(get_base_dir(), ALL_USER_DIR_NAME) | 225c30e1d956722c63facde6d876f757dc8c40d5 | 25,653 |
def LeakyRelu(
alpha: float,
do_stabilize: bool = False) -> InternalLayer:
"""Leaky ReLU nonlinearity, i.e. `alpha * min(x, 0) + max(x, 0)`.
Args:
alpha: slope for `x < 0`.
do_stabilize: set to `True` for very deep networks.
Returns:
`(init_fn, apply_fn, kernel_fn)`.
"""
return ABRelu(al... | 93a9f103c42979e5107291f818d387eb06feb41b | 25,654 |
def load_interp2d(xz_data_path: str, y: list):
"""
Setup 2D interpolation
Example:
x1, y1, z1, x2, y2, z2\n
1, 3, 5, 1, 4, 6\n
2, 3, 6, 2, 4, 7\n
3, 3 7, 3, 4, 8\n
xy_data_path will lead to a file such as:
1,5,6\n
2,6,7\n
3,7,8\n
y will be: [3, 4]
... | 0883c317c44a97a8e38c615285315adb22a091c5 | 25,655 |
def save_new_party(json_data):
"""saves a new party in the database
Args:
json_data (json) : party details
Returns:
json : api endpoint response
"""
# Deserialize the data input against the party schema
# check if input values throw validation errors
try:
data = p... | e6a11646c1aa13bfceabb1c143308fc985b3f59d | 25,656 |
import sys
def _system_path_separator():
"""
System dependent character for element separation in PATH variable
:rtype: str
"""
if sys.platform == 'win32':
return ';'
else:
return ':' | b89a77d5b444a1b806a75e9f024f2084e3cfc93f | 25,657 |
def cost_function(theta, X, y, lamda=0.01, regularized=False):
"""
Compute cost and gradient for logistic regression with and without regularization.
Computes the cost of using theta as the parameter for regularized logistic regression
and the gradient of the cost w.r.t. to the parameters.
using l... | e4002fc30455be730e6ba46db85588b113e24451 | 25,658 |
from pathlib import Path
import torch
def read_image_numpy(input_filename: Path) -> torch.Tensor:
"""
Read an Numpy file with Torch and return a torch.Tensor.
:param input_filename: Source image file path.
:return: torch.Tensor of shape (C, H, W).
"""
numpy_array = np.load(input_filename)
... | 987185e7b207ecae1abcf01fd5ea939ace0fb869 | 25,659 |
import argparse
def init_argparse():
"""Parses the required arguments file name and source database type and returns a parser object"""
parser = argparse.ArgumentParser(
usage="%(prog)s --filename 'test.dtsx' --source 'postgres'",
description="Creates a configuration file in the output directo... | 1c57c6712819d147ef7917d1100c20353339f7b4 | 25,660 |
def solution(n: int = 4000000) -> int:
"""Returns the sum of all fibonacci sequence even elements that are lower
or equals to n.
>>> solution(10)
10
>>> solution(15)
10
>>> solution(2)
2
>>> solution(1)
0
>>> solution(34)
44
"""
fib = [0, 1]
i = 0
while ... | b2c3983b9888ae8a10b4ceca2faf5d943b17fbe3 | 25,661 |
def triu(m: ndarray,
k: int = 0) -> ndarray:
"""
Upper triangle of an array.
"""
af_array = af.data.upper(m._af_array, is_unit_diag=False)
return ndarray(af_array) | 00b0b4a301b0b59214a53d8b741c7417bac95f3d | 25,662 |
def generate_annotation(overlay_path,img_dim,ext):
"""
Generate custom annotation for one image from its DDSM overlay.
Args:
----------
overlay_path: string
Overlay file path
img_dim: tuple
(img_height,img_width)
ext: string
Image ... | e9d334c834063ee27b5b9a9d597f084bc735f794 | 25,663 |
from datetime import datetime
def parse_episode_page(loc, contents):
"""Parse a page describing a single podcast episode.
@param loc: The URL of this page.
@type loc: basestring
@param contents: The raw HTML contents of the episode page from which
episode information should be parsed.
@ty... | 805e466c15741ee004059817efa70da66e470871 | 25,664 |
def _bitarray_to_message(barr):
"""Decodes a bitarray with length multiple of 5 to a byte message (removing the padded zeros if found)."""
padding_len = len(barr) % 8
if padding_len > 0:
return bitstring.Bits(bin=barr.bin[:-padding_len]).bytes
else:
return barr.bytes | 79e601bc30519e42c8dbf2369deea5b36a5851ff | 25,665 |
import os
import subprocess
import logging
def join(kmerfile, codonfile, minhashfile, dtemp):
"""Externally join with built-in GNU Coreutils in the order
label, kmers, codons ,minhash
Args:
kmerfile (str): Kmer csv file
codonfile (str): Codon csv file
minhashfile (str): Minhas... | d3a373573d87a0312ecb8291bb0c81479f6402b6 | 25,666 |
def align_address_to_page(address: int) -> int:
"""Align the address to a page."""
a = align_address(address) >> DEFAULT_PAGE_ALIGN_SHIFT
return a << DEFAULT_PAGE_ALIGN_SHIFT | 1211d3c1a3ae6b1bd183f3d1b1cfb1097fc7dc40 | 25,667 |
from typing import List
from sys import path
def virtual_entities(entity: AnyText, kind: int = Kind.HATCHES) -> EntityQuery:
"""Convert the text content of DXF entities TEXT and ATTRIB into virtual
SPLINE and 3D POLYLINE entities or approximated LWPOLYLINE entities
as outlines, or as HATCH entities as fil... | 9d02dab1d2ed975d206888f403358db9e56936b1 | 25,668 |
def getNamespace(modelName):
"""Get the name space from rig root
Args:
modelName (str): Rig top node name
Returns:
str: Namespace
"""
if not modelName:
return ""
if len(modelName.split(":")) >= 2:
nameSpace = ":".join(modelName.split(":")[:-1])
else:
... | abfb4c54f2dd1b54563f6c7c84e902ed4ee77b01 | 25,669 |
import re
def compile_rules(environment):
"""Compiles all the rules from the environment into a list of rules."""
e = re.escape
rules = [
(
len(environment.comment_start_string),
TOKEN_COMMENT_BEGIN,
e(environment.comment_start_string),
),
(
... | ca7971de422f66e9c9574c13306610e84a000271 | 25,670 |
import os
def get_output(db, output_id):
"""
:param db: a :class:`openquake.server.dbapi.Db` instance
:param output_id: ID of an Output object
:returns: (ds_key, calc_id, dirname)
"""
out = db('SELECT output.*, ds_calc_dir FROM output, job '
'WHERE oq_job_id=job.id AND output.id=?... | 8ad5cd6b5ca0808038ee29345b8d3e53e80fb9de | 25,671 |
def compute_window_based_feature(seq,
sample_freq,
func_handle,
window_length,
window_stride,
verbose=False,
**kwargs):
... | 4ab084d3459c617640e404b5232db4557b22c8b8 | 25,672 |
def read_cif(filename):
"""
read the cif, mainly for pyxtal cif output
Be cautious in using it to read other cif files
Args:
filename: path of the structure file
Return:
pyxtal structure
"""
species = []
coords = []
with open(filename, 'r') as f:
lines = f.... | d6d164a6425d088a17bb449b75e875047a5fbc29 | 25,673 |
import random
def custom_data_splits(src_sents, trg_sents, val_samples=3000, seed=SEED):
"""
splits data based on custom number of validation/test samples
:param src_sents: the source sentences
:param trg_sents: the target sentences
:param val_samples: number of validation/test samples
:param ... | 5a4754ce9fe400248a46f4868aeaa0b96ebd5760 | 25,674 |
def normalize(output):
"""将null或者empty转换为暂无输出"""
if not output:
return '暂无'
else:
return output | 18af58c74325522a64dcfd98a75f55e677c01ca3 | 25,675 |
def sgd(args):
""" Wrapper of torch.optim.SGD (PyTorch >= 1.0.0).
Implements stochastic gradient descent (optionally with momentum).
"""
args.lr = 0.01 if args.lr == -1 else args.lr
args.weight_decay = 0 if args.weight_decay == -1 else args.weight_decay
args.momentum = 0 if args.momentum == -1 ... | 17a852165766bcf02f92bac4c847684f2dcfb133 | 25,676 |
def normal_conjugates_known_scale_posterior(prior, scale, s, n):
"""Posterior Normal distribution with conjugate prior on the mean.
This model assumes that `n` observations (with sum `s`) come from a
Normal with unknown mean `loc` (described by the Normal `prior`)
and known variance `scale**2`. The "known scal... | 0bc94999ee10ce63ba0156510a9807523de6c085 | 25,677 |
def make_matrix(num_rows, num_cols, entry_fn):
"""retorna a matriz num_rows X num_cols
cuja entrada (i,j)th é entry_fn(i, j)"""
return [[entry_fn(i, j) # dado i, cria uma lista
for j in range(num_cols)] # [entry_fn(i, 0), ... ]
for i in range(num_rows)] | f706773245730eab3ce6cf41b0f6e81fbe3d52ab | 25,678 |
def add_relationtoforeignsign(request):
"""Add a new relationtoforeignsign instance"""
if request.method == "POST":
form = RelationToForeignSignForm(request.POST)
if form.is_valid():
sourceid = form.cleaned_data['sourceid']
loan = form.cleaned_data['loan']
... | 44e6a80ed4596b9dae48ce8f4ed37927feb1ec71 | 25,679 |
def check_url(url):
"""
Check if a URL exists without downloading the whole file.
We only check the URL header.
"""
good_codes = [httplib.OK, httplib.FOUND, httplib.MOVED_PERMANENTLY]
return get_server_status_code(url) in good_codes | f6dede6aaf41f404c182052cd4dc5708b9a0b879 | 25,680 |
def table(df, sortable=False, last_row_is_footer=False, col_format=None):
""" generate an HTML table from a pandas data frame
Args:
df (df): pandas DataFrame
col_format (dict): format the column name (key)
using the format string (value)
Return... | 05c7250673160f74fab6ca9ad46b02c7e948c9c8 | 25,681 |
from datetime import datetime
def ap_time_filter(value):
"""
Converts a datetime or string in hh:mm format into AP style.
"""
if isinstance(value, basestring):
value = datetime.strptime(value, '%I:%M')
value_tz = _set_timezone(value)
value_year = value_tz.replace(year=2016)
return ... | 0539cd58bfa4b7ee647ac88a58bcac93108d4819 | 25,682 |
def make_signal(time, amplitude=1, phase=0, period=1):
"""
Make an arbitrary sinusoidal signal with given amplitude, phase and period over a specific time interval.
Parameters
----------
time : np.ndarray
Time series in number of days.
amplitude : float, optional
A specific ampl... | 9f940922ae2a4bf1e3ff7d1c13351f4d07c40ca8 | 25,683 |
def train_data(X, y):
"""
:param X: numpy array for date(0-5), school_id
:param y: output for the data provided
:return: return the learned linear regression model
"""
regression = linear_model.LinearRegression()
regression.fit(X, y)
return regression | abaa0ba6f02ed111b6ec9b0945e9e26c643836be | 25,684 |
import re
def clean_text(s, stemmer, lemmatiser):
"""
Takes a string as input and cleans it by removing non-ascii characters,
lowercasing it, removing stopwords and lemmatising/stemming it
- Input:
* s (string)
* stemmer (object that stems a string)
* lemmatiser (object that le... | 0bcb14378c6b72e24526c7eff9f1daf2b6871152 | 25,685 |
def make_rst_sample_table(data):
"""Format sample table"""
if data is None:
return ""
else:
tab_tt = tt.Texttable()
tab_tt.set_precision(2)
tab_tt.add_rows(data)
return tab_tt.draw() | 160b28355f1bea80878417f2a92e5dc31dde66cd | 25,686 |
def is_thunk(space, w_obj):
"""Check if an object is a thunk that has not been computed yet."""
while 1:
w_alias = w_obj.w_thunkalias
if w_alias is None:
return space.w_False
if w_alias is w_NOT_COMPUTED_THUNK:
return space.w_True
w_obj = w_alias | 1918a7d79d02a2a20e6f7ead8b7a2dc6cfe05a85 | 25,687 |
def plot_roc_curve(
fpr,
tpr,
roc_auc=None,
ax=None,
figsize=None,
style="seaborn-ticks",
**kwargs,
):
"""Plots a receiver operating characteristic (ROC) curve.
Args:
fpr: an array of false postive rates
tpr: an array of true postive rates
roc_auc (None): the... | d4d6f9d33857598a16b04097de035a5a7a3f354b | 25,688 |
def my_place_or_yours(our_address: Address, partner_address: Address) -> Address:
"""Convention to compare two addresses. Compares lexicographical
order and returns the preceding address """
if our_address == partner_address:
raise ValueError("Addresses to compare must differ")
sorted_addresses... | 991b2d44042520eea28817f33cbb9421d7b99a78 | 25,689 |
def get_dataset_json(met, version):
"""Generated HySDS dataset JSON from met JSON."""
return {
"version": version,
"label": met['data_product_name'],
"starttime": met['sensingStart'],
} | d84f3652866c83e8c1618a9f87bc3bf6b5c6a0cf | 25,690 |
def hlmoft_SEOB_dict(P,Lmax=2):
"""
Generate the TD h_lm -2-spin-weighted spherical harmonic modes of a GW
with parameters P. Returns a dictionary of modes.
Just for SEOBNRv2 SEOBNRv1, and EOBNRv2. Uses aligned-spin trick to get (2,2) and (2,-2) modes.
A hack.
Works for any aligned-spin time-do... | b963958e3defbed0e61cb0691fcef329ceadf313 | 25,691 |
def encode(value):
"""
pyg_mongo.encoder is similar to pyg_base.encoder with the only exception being that bson.objectid.ObjectId used by mongodb to generate the document _id, are not encoded
Parameters
----------
value : value/document to be encoded
Returns
-------
encoded value/docum... | fa7dec607dca66736e3b9203bf97289a0ffdd733 | 25,692 |
def locate_line_segments(isolated_edges):
"""
Extracts line segments from observed lane edges using Hough Line Transformations
:param isolated_edges: Lane edges returned from isolated_lane_edges()
:return: Line segments extracted by HoughLinesP()
"""
rho = 1
theta = np.pi / 180
threshold... | 3b26da0535b327dfac4b268552209c75481bb4d2 | 25,693 |
def proj(A, B):
"""Returns the projection of A onto the hyper-plane defined by B"""
return A - (A * B).sum() * B / (B ** 2).sum() | 982cdfb1564166dce14432bf24404f066e2acee3 | 25,694 |
def v6_multimax(iterable):
"""Return a list of all maximum values.
Bonus 2: Make the function works with lazy iterables.
Our current solutions fail this requirement because they loop through
our iterable twice and generators can only be looped over one time only.
We could keep track of the maximu... | 5539adb0dcb6c9db4f8f2f68487fc13c6aa8d067 | 25,695 |
import traceback
def format_traceback_string(exception):
"""Format exception traceback as a single string.
Args:
exception: Exception object.
Returns:
Full exception traceback as a string.
"""
return '\n'.join(
traceback.TracebackException.from_exception(exception).format... | debdf53966b26b6562671bf48d283a3bf10d85d5 | 25,696 |
def get_stored_file(file_id):
"""Get the "stored file" or the summary about the file."""
return JsonResponse(StoredFile.objects(id=ObjectId(file_id)).first()) | 860f6f5dd24e5ebaf59fff1f4c82f4b5c7ce6da5 | 25,697 |
def _compute_array_job_index():
# type () -> int
"""
Computes the absolute index of the current array job. This is determined by summing the compute-environment-specific
environment variable and the offset (if one's set). The offset will be set and used when the user request that the
job runs in a n... | 5c9b451af75f894ad49dc8aa95b7c1a80e6e9c96 | 25,698 |
def make_transpose(transpose_name, input_name, input_type, perm):
"""Makes a transpose node.
Args:
transpose_name: name of the transpose op.
input_name: name of the op to be the tranpose op's input.
input_type: type of the input node.
perm: permutation array, e.g. [0, 2, 3, 1] for NCHW ... | 21e05caed8a439f748f3fa939b5bff9864c2525d | 25,699 |
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