content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def find_rising_edge(x, y, *, threshold=None, interp=False):
"""Find the first `x` where `y` exceeds `threshold` (along the last axis).
`x` and `y` must have the same shape.
If `threshold` is None, it will be inferred as half the rise from min(y) to max(y).
If `interp` is True, linearly interpolate b... | 69c8601987cac8e44dc89d52499d907f58dc225c | 36,800 |
def normalize_os_name(os_name):
"""
:API: public
"""
if os_name not in OS_ALIASES:
for proper_name, aliases in OS_ALIASES.items():
if os_name in aliases:
return proper_name
logger.warning('Unknown operating system name: {bad}, known names are: {known}'
.format(bad=os_nam... | ca7e921580ae72d77d4d16158f45edefac2cd8b6 | 36,801 |
def make_prediction(*, path_to_images) -> float:
"""Make a prediction using the saved model pipeline."""
# Load data
# create a dataframe with columns = ['image', 'target']
# column "image" contains path to image
# columns target can contain all zeros, it doesn't matter
dataframe = path_to_ima... | 80d30707ecbacdae50c0f986bb3c66a504cc3740 | 36,802 |
def vmanage_login(host: str, username: str, password: str):
"""
"""
return Authentication(
host=host,
user=username,
password=password
).login() | f127072880035b30e652d87f4af1b8bcd5110ffd | 36,803 |
def load_image():
"""Load image from file, then scale and rotate.
Returns CV2 object."""
if display_histogram == 1:
image = cv2.imread(filename, cv2.IMREAD_GRAYSCALE)
else:
image = cv2.imread(filename, cv2.IMREAD_COLOR)
image_resized = cv2.resize(image, None, fx=scale, fy=scale,... | edaea5b59d6e87c8315bbc556d460b7cbefa2737 | 36,804 |
def handle_odd_pad_bwd(dx, odd_padding):
"""
handle odd padding mode backward
Args:
dx, the backward tensor
odd_padding, the odd_padding
Returns:
tensor, the output
"""
# (axis, left padding if True else right padding)
flags = [(2, True), (2, False), (3, True), (3, F... | fbf75299db943be3930db77abd21b0dd59c263bf | 36,805 |
import logging
def gwas_snp_to_precluster(gwas_snp, populations):
"""
Extract neighbourhood of GWAS snp
Args:
* [ GWAS_SNP ]
* [ string ] (populations)
Returntype: GWAS_Cluster
"""
mapped_ld_snps = postgap.LD.calculate_window(gwas_snp.snp)
logging.info("Found ... | aaa3ac23e0797cfda134f7a105c0e0c33ff8c7a6 | 36,806 |
import argparse
def parse_args():
"""Parse command-line arguments."""
def _bool(val):
return bool(strtobool(val))
parser = argparse.ArgumentParser(description='Deploy MargiPose jobs to Kubernetes',
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
p... | 4097bf81811dd2696d0d86b1050b608cb851109f | 36,807 |
def block_shuffle(indices, block_size, one_based=ONE_BASED):
# TODO(allie): Handle zero-indexing here too (currently assuming first frame index = 1)
"""
Shuffles indices according to 'blocks' of size block_size. All 'blocks' start with index 1.
inputs:
indices (array-like, shape (N,)): integers... | f7d6d590d92d1147c7255aebb86ab13b270e591c | 36,808 |
def cleanup_ud(ds):
"""More cleaning and calculation of derived variables."""
# remove spikes in temperature
for v in ["t1", "t2"]:
ds[v] = despike(ds[v], ds.attrs["spike_thresh_t"])
# despike T, C
ibefore = 1
iafter = 1
for v in ["c1", "c2", "t1", "t2"]:
ds[v].data = helpe... | ff97f13667f07fd79aa3400ffea65d4b958d3163 | 36,809 |
import collections
def ParseIoStatsLine(line):
"""Parses a line of io stats into a IoStats named tuple."""
# Field definitions: http://www.kernel.org/doc/Documentation/iostats.txt
IoStats = collections.namedtuple('IoStats',
['device',
'num_r... | 2764dc96f0720359f906f1b27763738331f63e19 | 36,810 |
from sqlalchemy import create_engine
from sqlalchemy.pool import NullPool
def sql_readaspd(db_dets, query):
"""
Pull a SQL query output and read it into a Pandas DataFrame
Parameters
----------
db_dets: str
URL of a postgreSQL database that will be connected to.
query: str
... | 73d936aa8a9658a35efdb8e4ac451aca9c68abea | 36,811 |
def grid2spec(gfield):
"""Transform a field on physical grid to spectral space
Args:
gfield: numpy array with shape (time(optional), y, x, z(optional))
"""
if _is_single_layer(gfield):
y_loc = -2
else:
y_loc = -3
ny, nx = gfield.shape[y_loc], gfield.shape[y_loc+1]
... | 224d3e5e739b5b08dc380a161f9bba14e6915771 | 36,812 |
def parse_bits_transmission(
bits: list[str], pos: int = 0, indent: int = 0
) -> tuple[int, int]:
"""Parse a message accoring to the Buoyancy Interchange Transmission System (BITS)
Args:
bits (list[str]): message in binary representation
pos (int): current position in the bit stream
... | 30c05c10b3529b70db61dde81b11f44eeec43e4c | 36,813 |
def get_pixel_neighbors(height, width):
"""
Estimate the 4 neighbors of every pixel in an image
:param height: image height
:param width: image width
:return: pixel index - neighbor index lists
"""
pix_id = []
neighbor_id = []
for i in range(height):
for j in range(width):
... | 3e49081fdc59ff2b0df54b84e0cf8c5983ec7b2c | 36,814 |
def parse_copy_running_config_startup_config(raw_result):
"""
Parse the 'copy running-config startup-config' command raw output.
:param str raw_result: copy running-config startup-config
raw result string.
:rtype: dict
:return: The parsed result of the copy running-config startup-config:
... | 01bba91527d64e32dc4eabe08de791e45b1c2040 | 36,815 |
def make_bson(obj):
"""Given a Python (JSON compatible) dictionary, returns a BSON string.
(This hijacks the Python -> BSON conversion code from pymongo, which is needed for
converting queries. Perhaps this dependency can be removed in a later version.)
:param obj: object to be encoded as BS... | 1b8e862280b3287377fe1cc95d7e28f618fc90a9 | 36,816 |
from typing import Optional
from typing import Union
import json
def plot_hail_file_metadata(
t_path: str,
) -> Optional[Union[Grid, Tabs, bokeh.plotting.Figure]]:
"""
Takes path to hail Table or MatrixTable (gs://bucket/path/hail.mt), outputs Grid or Tabs, respectively.
Or if an unordered Table is pr... | e3158b525a9f632efa2c592ec4ae802c075bad52 | 36,817 |
import os
def load_values_from_environment(prefix="", overrides=None):
"""Reads values from the environment.
If ``prefix`` is a non-empty string, only environment variables with the
given prefix will be returned. The prefix, if given, will be stripped from
any returned keys.
If ``overrides`` is ... | 95e8b0714cb52faeb0e380222e6a539b33a8cdc7 | 36,818 |
def get_user_details(request):
"""
DataHub account registration form for social accounts.
Gives new users a chance to choose a DataHub username and set their email
address.
Called by the Python Social Auth pipeline's get_user_details step. For
more details, look for pipeline.py and the SOCIAL_... | 297fa9a15bd9671c827261157118f5fc6d722a96 | 36,819 |
import logging
import os
from datetime import datetime
import platform
import errno
def build_results_dir(params):
""" function to create the final result directory for a job/test.
Intent is to make backwards compatible with Gazebo.
"""
logger = logging.getLogger('pav.runjob.build_results_dir')
... | ec61c9dbb4e2f2183485cf4b5c353fa2b418c9e6 | 36,820 |
from typing import Optional
def _cqv(
data: NumArrayLike,
ndigits: Optional[int] = 4,
interpolation: Optional[str] = "linear",
multiplier: Optional[int] = 1,
) -> float:
"""Internal function to calculate cqv."""
# ------------------- convert data to pandas.core.series.Series ------------------... | 179b9060152851c9a898aa70ce4d8a68f13b11a2 | 36,821 |
def GetCulpritsForFailures(failures):
"""Gets culprits for the requested failures.
Args:
failures (list of AtomicFailures)
Returns:
(list of findit_result.Culprit)
"""
culprit_keys = set([
failure.culprit_commit_key
for failure in failures
if failure and failure.culprit_commit_key
... | 7fc5270c687a0056f6a61d5fea09efdc529ef2d5 | 36,822 |
from typing import Optional
from typing import Dict
def get_object_perms(obj: models.Model, user: Optional[User] = None) -> Dict:
"""Return permissions for given object in Resolwe specific format.
Function returns permissions for given object ``obj`` in following
format::
{
"type": "gr... | 3aca9eacb250086dc449fad41d570f958ad71655 | 36,823 |
def fixed_from_old_hindu_lunar(l_date):
"""Return fixed date corresponding to Old Hindu lunar date l_date."""
year = old_hindu_lunar_year(l_date)
month = old_hindu_lunar_month(l_date)
leap = old_hindu_lunar_leap(l_date)
day = old_hindu_lunar_day(l_date)
mina = ((12 * year) - 1) * ARYA_SOLAR... | b9dc05384d1e92ba55bec1b6b4e373122bf76fcc | 36,824 |
def get_zrand_mask(zrand, percentile=95):
"""
Calculates stable regions of `zrand` based on `percentile`
Parameters
----------
zrand : (C, K, M) array_like
Local similarity of clustering solutions in SNF parameter space
percentile : [0, 100] float, optional
Percentile of `zrand`... | 6e41367c27d4159497d57089c1feee01b45b20ca | 36,825 |
def remove_small_areas(img, min_area):
"""
Segmenta uma imagem em várias regiões com propriedades em comum e gera
uma imagem resultado, deixando de fora todas as regiões que possuam
areas menores do que o limiar passado. Esse processo é realizado para
remover áreas pequenas (no geral... | 4cc7d7120e35317e6b077c4500c1eb3580887b6d | 36,826 |
def show_pages(parser, token):
"""
Show page links.
Usage::
{% show_pages %}
It is only a shortcut for::
{% get_pages %}
{{ pages }}
You can set *ENDLESS_PAGINATION_PAGE_LIST_CALLABLE* in your settings.py
as a callable used to customize the pages that are displayed.
... | b412602108544c4560b757807317f043c36619e7 | 36,827 |
from image import is_b64
import logging
def check_file(file, direction):
""" Validate a user input
This function ensures that the user enters a valid file list
where the list contains a non-empty filename, b64 image, and a valid
processing steps array.
Args:
direction (str): either "uplo... | a22ded240f771a98efc0d613b851dcc84bd95c03 | 36,828 |
from typing import Counter
def check_valid_solution(solution, graph):
"""Check that the solution is valid: every path is visited exactly once."""
expected = Counter(
i for (i, _) in graph.iter_starts_with_index()
if i < graph.get_disjoint(i)
)
actual = Counter(
min(i, graph.get... | ec22134973153605b3a9b7a2ac7f180ffe55f97e | 36,829 |
import copy
def filter_props(props):
"""Filter props from the Component arguments to exclude:
- Those without a "type" or a "flowType" field
- Those with arg.type.name in {'func', 'symbol', 'instanceOf'}
Parameters
----------
props: dict
Dictionary with {propName: propMetadata}... | df2dad9d174702e40d2410fba2cc2b21b05ddfd3 | 36,830 |
import numpy
def sqr_ts(timeseries, nodata=-9999):
"""sqr - Interquaritle range (IQR)
It computes the interquaritle range of the time series.
:param timeseries: Your time series.
:type timeseries: numpy.ndarray
:param nodata: nodata of the time series. Default is -9999.
:type nodata: int
... | 21e98734dfa95036cc6194ac253c1cb2eb275d25 | 36,831 |
import argparse
def parse_args(cloud_args=None):
"""parameters"""
parser = argparse.ArgumentParser('mindspore classification training')
parser.add_argument('--platform', type=str, default='Ascend', choices=('Ascend', 'GPU'), help='run platform')
# dataset related
parser.add_argument('--data_dir',... | 02336100602fb4dd21d6e33760d5fca2afe699e5 | 36,832 |
from typing import Union
from typing import Collection
def to_shape(data: Union[Collection, Tensor], add_batch=False, exact_shape=True) -> Union[Collection, Tensor]:
"""Compute the shape of tensors within a collection of `data`recursively.
This method can be used with Numpy data:
```python
data = {"x... | 00693cd854252805dcbef7ee9ba85c804a896166 | 36,833 |
def Color(colorname):
"""pygame.color.Color(colorname) -> RGBA
Get RGB values from common color names
The color name can be the name of a common english color,
or a "web" style color in the form of 0xFF00FF. The english
color names are defined by the standard 'rgb' colors for X11.
... | ef553c482014d9e2275d5ae64016cbb27e34272b | 36,834 |
from typing import List
from typing import Union
def _create_output(sdfg: SDFG,
inputs: List[UfuncInput],
outputs: List[UfuncOutput],
output_shape: Shape,
output_dtype: Union[dtypes.typeclass,
List[dtype... | 1435886ecf87896e2d82d9a1425c24034d769b25 | 36,835 |
import multiprocessing
def from_image_files(
images_dir: str,
extensions: str | tuple[str, ...] = '.jpg',
selection: set[str] = set(),
) -> Statistics:
"""From a directory path with images, will generate the stats of all
images. The statistics generated are: mean, std, max, and min.
Parameter... | bc2e07891646c7bf5e49c22f7022a2f44df215e5 | 36,836 |
def _memoized_fibonacci_aux(n: int, memo: dict) -> int:
"""Auxiliary function of memoized_fibonacci."""
if n == 0 or n == 1:
return n
if n not in memo:
memo[n] = _memoized_fibonacci_aux(n - 1, memo) + \
_memoized_fibonacci_aux(n - 2, memo)
return memo[n] | 9a6d8646139d6ae9f6f63d2e990545fd088407eb | 36,837 |
import logging
def make_app(table_size, update_size, update_rate):
"""Create a Tornado application for the webserver."""
MANAGER.host_table("table", TABLE)
MANAGER.host_view("view", VIEW)
if table_size is not None and TABLE.size() < table_size:
current_size = TABLE.size()
while curre... | f4670831d6a8dfc8afa232b6198988a2babad2e3 | 36,838 |
import nibabel as nib
def get_scan_info(in_file):
""" Get useful scan-parameters.
Function to extract some useful scan-parameters.
Parameters
----------
in_file : str
Path to (functional!) nifti-image
Returns
-------
TR : float
Time-to-repetition of file
"""
... | dde7b2bfcbeee7bccddef8678f717b2f40b5c4df | 36,839 |
def merge_sort(array_of_numbers):
"""
This should split the array into single numbers and then recombine
the list into a single sorted list in a recursive way.
:param array_of_numbers:
:return:
"""
length = len(array_of_numbers)
split = int(length/2)
if length <= 1:
return ... | 4fb90843689bb213b5dfa0460e99126c9aa16778 | 36,840 |
import socket
def select_random_ports(n):
"""Selects and return n random ports that are available."""
ports = []
for i in xrange(n):
sock = socket.socket()
sock.bind(('', 0))
while sock.getsockname()[1] in _random_ports:
sock.close()
sock = socket.socket()
... | 93145b58e6ecce60da9ae96527ca8e61c794f7ed | 36,841 |
import argparse
import ast
def parse_args():
"""init."""
# yapf: disable
parser = argparse.ArgumentParser()
model_g = ArgumentGroup(parser, "model", "model configuration and paths.")
model_g.add_arg("bert_config_path", str, "data/cased_L-24_H-1024_A-16/bert_config.json",
"Path... | c25345de4e8a2a4f11243ecc76eb2900dfb3436e | 36,842 |
def choose_targets(label_dic_set, m, label_dic, source_label):
"""
This differs from random.sample which can return repeated
elements if seq holds repeated elements.
"""
#global count1
#global count2
targets = set()
if len(label_dic_set[source_label]) > m:
#print(1)
whil... | e350ab8c504d59f3a1db8a9977924c4ad3ba96af | 36,843 |
def sinkhorn(C, log_w_p, log_w_q, key, alpha=0.01):
"""Uses sinkhorn iterations to solve an optimal transport problem.
Computes the optimal cost and transport plan for moving mass from an
atomic measure p to another atomic measure q.
Args:
C: The cost matrix, C_ij contains the cost of moving mass from the... | f1796ce1c2fe347cf24e81bf121a0ad4d9e6193d | 36,844 |
def string_count_words(string: str) -> dict:
"""Count occurrences of individual words in a given string
This function counts occurrences of each separate words. It returns
a dictionary, in wich keys correspond to words and values
to the number of occurrences.
Args:
string (str): String for the countin... | cd51101a33fb4fd4c8488718549362fa25ebb360 | 36,845 |
import torch
def compute_class_freqs(labels):
"""
https://www.kaggle.com/eugennekhai/chest-x-ray-pytorch-lightning-densnet121
Compute positive and negative frequences for each class.
Args:
labels (np.array): matrix of labels, size (num_examples, num_classes)
Returns:
positive_freq... | 94915525c138038c20093e3f5c6499383e293369 | 36,846 |
def cayley_menger_analysis(vertices, d = 2):
"""
Determines volume and circumradius for a tetrahedron given the vertices
https://westy31.home.xs4all.nl/Circumsphere/ncircumsphere.htm#Coxeter
"""
if d == 3:
cm_matrix = np.array([[0, 1, 1, 1, 1], [1, 0, distance.sqeuclidean(vertices[0], vertic... | 794d387adf8bafdba0e4b81aa9635069335da62a | 36,847 |
from pathlib import Path
import os
def module_dir_path(request):
"""Assure a directory exists in this module.
The directory name is given by the environment variable
combining the module name and "_DIR". For example,
module test_foo.py will use the environment variable
named TEST_FOO_DIR. Return... | f1debd9ee663c1be2165e229e76aa360e9dd03dc | 36,848 |
async def async_setup_entry(hass, entry):
"""Set up a bridge for a config entry."""
await async_setup_bridge(hass, entry.data['host'],
username=entry.data['username'])
return True | de649b60ec38c85807860c9e64c46c6f9019d25f | 36,849 |
import os
def find_test_pack_root():
"""Walks upward from the current directory until it finds a directory
containing .stbt.conf
"""
root = os.getcwd()
# This gets the toplevel in a cross-platform manner "/" on UNIX and
# (typically) "c:\" on Windows:
toplevel = os.path.abspath(os.sep)
... | 456e46db25b888395e4f2e4b9b5146594d9a9a97 | 36,850 |
def make_non_parallel_copy(model):
"""Make a non-data-parallel copy of the provided model.
torch.nn.DataParallel instances are removed.
"""
def replace_data_parallel(container):
for name, module in container.named_children():
if isinstance(module, nn.DataParallel):
... | 2a82494a6b6ef3ac8ca08bd210d3ae2c95a9b9e4 | 36,851 |
from re import T
from typing import Callable
def from_dependent_matroid(matroid: tuple[set[T], list[set[T]]]) -> Callable[[set[T]], int]:
"""Construct a nulity function from a matroid defined by dependent sets.
Args:
matroid (tuple[set[T], list[set[T]]]): A matroid defined by dependent sets.
Ret... | b449d8d260fe4ec3dd684266c8f990cdc9872309 | 36,852 |
def convolve(image, psf, return_Fourier=False):
""" Convolves given image by psf.
Args:
image: a JAX array of size [nx, ny], either in real or Fourier space.
psf: a JAX array, must have same shape as image.
return_Fourier: whether to return the real or Fourier image.
Returns:
The resampled kimage... | 02010e1f0a39a412ac11ff62c5990218334a93ec | 36,853 |
def read_csv(file: PATH_TYPE) -> pd.DataFrame:
"""A wrapper for ``pd.read_csv`` which tries to handle errors gracefully.
Args:
file: The CSV file to read.
Returns:
A ``DataFrame`` containing the contents of the file.
"""
try:
return pd.read_csv(file, encoding="utf-8")
e... | 0cb4a2840d0f1718759356705149aa0025db6baa | 36,854 |
def tfm_shear(x_angle=0.0, y_angle=0.0, shape=(0, 0)):
"""
Generate a shear transformation matrix.
:param x_angle: The angle to shear the image in horizontal direction
:param y_angle: The angle to shear the image in vertical direction
:param shape: The shape of the image to be transformed
:retu... | 28614a617791142a9955495827a76f957b08ff46 | 36,855 |
import subprocess
import tempfile
import os
import pathlib
def run_pytype(code: str, check: bool) -> subprocess.CompletedProcess: # pylint: disable=g-doc-args
"""Runs pytype on the specified code.
Raises:
subprocess.CalledProcessError if check=True and pytype return is non-zero
Returns:
A subprocess.... | 70a9ffe16ae2d205f58046ffbb4fcaba74bfaf26 | 36,856 |
def _load(handler_obj):
"""
Load an :class:`.IHandler` handler object. The
handler_obj.load_type() defines whether
:func:`._load_module_function` or :func:`._load_module_class` is
to be used.
"""
if handler_obj.load_type() == "function":
return _load_module_function(handler_obj)
... | 57b207125c7be45b979f0c9a84722382b8078782 | 36,857 |
def comp_ac_fft_middlepad(data):
"""Compute auto-correlations from binned data (without normalization).
Uses FFT after zero-padding the time-series in the middle.
Parameters
-----------
data : nd array
time-series from binned data (numTrials * numBin).
Returns
-------
a... | 6bef88dd15e24e9d74654b8c407888066dd7efe5 | 36,858 |
import os
import json
def get_sagemaker_resource_config():
"""
Returns JSON for config if training job is running on SageMaker else None
"""
cluster_config = None
sm_config_path = '/opt/ml/input/config/resourceconfig.json'
if os.path.exists(sm_config_path):
with open(sm_config_path) as... | 5faf1d0ca27c0fe0fe6bbdfdbf731c68cede7e06 | 36,859 |
def get_mod_for_key(keycode):
"""
Finds the modifier that is mapped to the given keycode.
This may be useful when analyzing key press events.
:type keycode: int
:return: A modifier identifier.
:rtype: xcb.xproto.ModMask
"""
return __keysmods.get(keycode, 0) | b65e81d2ace36547b799b680e7756f61fcc3118c | 36,860 |
from typing import List
from typing import Dict
from typing import Any
def remove_delay_fault(virtual_service_name: str,
routes: List[Dict[str, str]],
ns: str = "default",
version: str = "networking.istio.io/v1alpha3",
configu... | da0a10d6b2316cb1c2aa2fa777e87f3dc592cb8a | 36,861 |
def set_lm_labels(dataset, vocab, stm_lex, stm_win=3):
"""
set labels of bi-directional language modeling and sentiment-aware language modeling
:param dataset: dataset
:param vocab: vocabulary
:param stm_lex: sentiment lexicon
:param stm_win: window size (i.e., length) of sentiment context
:... | ec87003f9f427c5de5ea969f7040f7f10d49c3ea | 36,862 |
def pad_sequences(sequences, pad_func, maxlen = None):
"""
Similar to keras.preprocessing.sequence.pad_sequence but using Sample as higher level
abstraction.
pad_func is a pad class generator.
"""
ret = []
# Determine the maxlen
max_value = max(map(len, sequences))
if maxlen is None... | 5879ab8f8df7477b9d73c87b6c8065fcc43a66df | 36,863 |
def update(event, context):
"""
Runs on Stack Update
"""
physical_resource_id = event['PhysicalResourceId']
if event.get('ResourceType') == 'Custom::CWEventPermissions':
cwe = CWEventPermissions(event, logger)
logger.info("Updating CW Event Bus Policy - CR Router")
response =... | afca288f444ebd7acd2442d0178496b144528c8f | 36,864 |
def measure_arbitrary_sequence(qubits, sequence=None, sequence_function=None,
sequence_args=None, drive='timedomain', label=None,
detector_function=None, df_kwargs=None,
sweep_function=awg_swf.SegmentHardSweep,
... | b03a12875c070dbfb16e987307cf89444b57ea19 | 36,865 |
def LoadAnnotation(
seg_path,
prefix=None,
label_map=None,
reduce_zero_label=False,
imdecode_backend='pillow',
file_client: FileClient = FileClient(backend='disk'),
):
"""Load annotations for semantic segmentation.
**Args**:
- reduce_zero_label (bool): Wh... | 7dffe11c98a60ab10e7786cdb1be36e3b830b0d8 | 36,866 |
def random_translate(img, streering_angle, range_x, range_y):
"""
Randomly shift the image virtially and horizontally (translation).
"""
trans_x = range_x * (np.random.rand() - 0.5)
trans_y = range_y * (np.random.rand() - 0.5)
streering_angle += trans_x * 0.002
trans_m = np.float32([[1, 0, ... | 1ca533617da950657e4d8b1dbd6c681e381d2e1a | 36,867 |
def read_input_data(filename, arguments):
"""
Reads single input data
:param filename: relative path to file
:param arguments: image resize
:return: left image, right image
"""
cv_image = cv2.imread(filename)
if cv_image is None:
raise RuntimeError(f"Unable to open {filename}"... | 4857314f6b5ad682ef09a09aa5b567987d2d1aec | 36,868 |
import uuid
def get_uuid4():
""" make a random UUID
"""
s = uuid.uuid4()
return str(s) | 9643fb712c2181fbba4fabc36b61eecfa42a3dfd | 36,869 |
from typing import Union
def black76_vega(F: float,
K: Union[float, np.ndarray],
vol: Union[float, np.ndarray],
disc: float,
T: float) -> Union[float, np.ndarray]:
"""
Vega(s) for strike(s)
:param F: float, forward price
:param K: flo... | 61d10ce1adcdd8478ea789e1e7e2291d900fafba | 36,870 |
def replace_greek_uni(s):
"""Replace Greek spelled out letters with their unicode character."""
for greek_uni, greek_spelled_out in greek_alphabet.items():
s = s.replace(greek_spelled_out, greek_uni)
return s | 998d97421d3503de890cdccf60e32ae5e3ddba92 | 36,871 |
import torch
def load_GG2_images(images):
"""
Normalizes images and upscales them
"""
images = [fits.open(file, memmap=False)[0].data for file in images]
images = [torch.from_numpy(x.byteswap().newbyteorder()) for x in images]
#Normailze
normalize = [3.5239e+10, 1.5327e+09, 1.8903e+09, ... | eb50450c64748afcb043d7e0a779b5be03f9c4d4 | 36,872 |
def index():
"""Main page"""
return render_template('landing.html') | de60270e90eea3f42435a9c16ff0326545964b83 | 36,873 |
def has_computed_fields(context, obj):
"""
Return a boolean value indicating if an object's content type has associated computed fields.
"""
content_type = ContentType.objects.get_for_model(obj)
return ComputedField.objects.filter(content_type=content_type).exists() | a820f164ba021a3b61fdb200c941cfbb1cb9aa42 | 36,874 |
from typing import Optional
from typing import List
from typing import Tuple
def _prepare_dataframes(
forecast_df: DataFrame,
truth_df: DataFrame,
percentiles: Optional[List[float]] = None,
experiment: Optional[str] = None,
) -> Tuple[DataFrame, DataFrame]:
"""Prepare dataframes for conversion to ... | 56b9c024e9b87f22be31d33ba0151545534e4901 | 36,875 |
def contour_and_point_distance(point):
"""
A reusable function that preloads a point and then
calculates the distance to a given contour.
:param point: an (x,y) tuple point
:return:
"""
return partial(geometry.distance_between_points, point) | da821b2c704e5aeb65719fce95a77e890c8e7f07 | 36,876 |
def replace_codepoints(text: str) -> str:
"""
Replaces Unicode codepoints in a string with the corresponding glyphs.
Multiple codepoints can be specified in the same string. Characters
which are not part of codepoint annotation are kept.
@param text: The text with codepoint annotations to be repla... | d55a608153e8873ef472403110d6534d919e6853 | 36,877 |
def grid2grid1D(f1, boxsize, ngridout, origin=0., originout=0., boxsizeout=None):
"""Remaps a dataset defined on 2D cartesian grid onto a new 2D cartesian grid.
Parameters
----------
f1 : array
The values of the 2D grid pixels.
boxsize : float
Box size.
ngridout : int
Gr... | 51ba20f50f689703043d1eb05761c1b6d07de95e | 36,878 |
def get_all_user_feedback(request):
"""
Returns a list of all the feedbacks for a given user
:param request:
:return: 200 successful
"""
feedbacks = Feedback.objects.filter(user=request.user).order_by('-created')
serializer = FeedbackSerializer(feedbacks, many=True)
return Response(seria... | 853dd1a29ade3b0874815be9074471aadda6c86f | 36,879 |
from re import T
def atom(env, args):
"""Atom has the value of 't' or 'f' according to
whether its argument is an atomic symbol. Thus:
(atom t) = t
(atom (quote (t f))) = f
"""
arg = args.car().eval(env)
if isinstance(arg, Symbol) or arg == F:
return T
return F | 671ff8c71ac17bfd443523205b95e4e9f5de8694 | 36,880 |
def ad_get_user_dn_by_mail(user_mail_addr):
"""
通过mail查询某个用户的完整DN
:param user_mail_addr:
:return: DN
"""
conn = __ad_connect()
conn.search(BASE_DN,
'(&(objectclass=person)(mail=' + user_mail_addr + '))', attributes=['distinguishedName'])
user_dn = conn.entries[0]['disting... | a826929a8f3106a823279462ec1f8a2b30693b00 | 36,881 |
from typing import Union
import io
from typing import IO
from typing import Any
import yaml
import sys
def safe_load_yaml_with_exceptions(yaml_file: Union[io.FileIO, IO[Any]]) -> Any:
"""Attempts to use ruamel.yaml.safe_load on the specified file. If successful, returns
the output. If not, formats a ruamel.ya... | a8449931fe521e3569fa3224963f7d71b4972c43 | 36,882 |
import collections
def get_interface_config_ipv6(ip_address, ip_subnet, ip_gateway):
"""
Return the interface configuration parameters for all IPv6 static
addressing.
"""
parameters = collections.OrderedDict()
parameters['IPV6INIT'] = 'yes'
parameters['IPV6ADDR'] = netaddr.IPNetwork('%s/%u... | deb75b75e5e806965db30717dda902efa4d07263 | 36,883 |
def show_json(i):
"""
Input: {
}
Output: {
return - return code = 0, if successful
> 0, if error
(error) - error text if return > 0
}
"""
r=show(i)
if r['return']>0: return r
return... | 7b95ae3ab51a347d83a9038f8a1954d68290f6b7 | 36,884 |
from typing import List
from typing import Dict
import transformers
import torch
import tqdm
def tokenize_jiant_dataset(
tokenizer,
texts: List[str],
span1s: List[List[int]],
span2s: List[List[int]],
labels: List[str],
labels_to_ids: Dict[str, int],
max_seq_leng... | 824473158a9dbcba3889b5467c53cd0ec3553c5d | 36,885 |
from typing import Dict
def splitLR(geom: geo.base.BaseGeometry, splitter: String_or_Ring) -> SplitGeometry:
"""Split a geometry into a 'left' and 'right' side using the shapely API"""
left,right = [],[]
split_geom = ops.split(geom, splitter)
if len(split_geom)==1:
raise GeometryError("splitte... | 141c29677cf223dd5a2e2746685a7f850740bf5d | 36,886 |
def view():
"""Returns the ProteinViewer app view"""
viewer = ProteinViewer()
return viewer.view() | 9d3e890c9885a0796d8bba283e5fcc7529c3f26f | 36,887 |
def schaffer(X, Y):
"""constraints=100, minimum f(0,0)=0"""
numer = np.square(np.sin(X**2 - Y**2)) - 0.5
denom = np.square(1.0 + (0.001*(X**2 + Y**2)))
return 0.5 + (numer*(1.0/denom)) | dbdd3d35476013500762df9346b24e8a5b46eef8 | 36,888 |
from pathlib import Path
import os
import sys
import subprocess
def job_install(info):
"""install the package defined in info"""
sentinel_file = Path(
"/anysnake/bioconductor/%s/%s.sentinel" % (info["name"], info["name"])
)
def do():
R_cmd = ["/anysnake/R/bin/R", "--no-save"]
... | b8f725fbd058764f45fb862f473c74c7ec844f59 | 36,889 |
def get_producer(): # pragma: no cover
"""Create a Kafka producer."""
producer = Producer({"bootstrap.servers": Config.INSIGHTS_KAFKA_ADDRESS, "message.timeout.ms": 1000})
return producer | 6d357d2de307936cdaba38cd0e8ef805225f68ca | 36,890 |
def infer_capture_method(tx, rx):
"""
Infers the capture method from the indices of transmitters and receivers.
Returns: 'hmc', 'fmc', 'unsupported'
Parameters
----------
tx : list
One per timetrace
rx : list
One per timetrace
Returns
-------
capture_method : s... | d41f2cf3a6adf191ba092828d45eae265a8c5a81 | 36,891 |
import logging
def check_function(symbol, forward=None, backward=None, grad_input_vars=None,
shape=None, dtype=None, in_range=None, values=None,
exclude_targets=None, only_targets=None,
additional_params=None,
numerical_grads=None, numerical_... | a86ab09764e91c97d289e3726d2ca169b942faa1 | 36,892 |
def SieveFilter(*args, **kwargs):
"""
SieveFilter(Band srcBand, Band maskBand, Band dstBand, int threshold, int connectedness=4, char ** options=None,
GDALProgressFunc callback=0, void * callback_data=None) -> int
"""
return _gdal.SieveFilter(*args, **kwargs) | 2f36ad6f6a88e57aadea2fe38b8925d66603ce49 | 36,893 |
from sys import path
def rounded_corner_path(start_x, end_x, min_y, max_y):
"""creates a U shaped path between the start and end points."""
if start_x > end_x:
return rounded_corner_path(end_x, start_x, min_y, max_y).reversed()
radius = min(max_y - min_y, (end_x - start_x)/2)
paths = []
#f... | 119ed6d02496d5afd90079f5bded82e1a2f9042a | 36,894 |
def desc(col):
"""Sort by `col` descending."""
return Descending(col) | 0979d5628be8647ca8f1414f78150b42992542a2 | 36,895 |
def compare_names(tag, name, tagname=None):
"""Compare a tag against a filename and return if they're the same
Common substitutions will be tried.
Dates will only require the minimum provided data to match
"""
if tagname in DATE_TAGS:
return Date.parse(tag) == Date.parse(name) is not None
... | a61e1c98d0098ed71a31b2a48f046c934f15f284 | 36,896 |
import re
def clean_text(text: str, remove_punctuation=False) -> str:
"""Cleans the inputted text based on the rules given in the comments.
Code taken from: https://github.com/kk7nc/Text_Classification/
Args:
text (str): the text to be cleaned
remove_punctuation (bool): whether to remove ... | 0f666041724315696924808c335c0110b7ffc158 | 36,897 |
def doc(obj=None, itm=None, docs=None, prefix=None):
"""Python IVI documentation generator"""
st = ""
# add a dot to prefix when needed
if prefix is None or len(prefix) == 0:
prefix = ''
elif not prefix[-1] == '.':
prefix += '.'
# if something passed in docs, iterate ov... | aa5652169f5864fdcecc12a53b964c8e0488186b | 36,898 |
def buscaNumQueries():
"""
Pela leitura do arquivo de configuração config.ini, retorna o número de queries configuradas.
:return número de consultas cadastradas no arquivo de configuração
"""
# Cria um set com as queries registradas no arquivo de configuração
queries = set()
contador... | 0b2da81aa7eb8490e3556598982f601802bcf8d4 | 36,899 |
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