sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
a63650f47e92d1db4de01071111a44ec0e7c17d003b5fe60dde5904e65e3cde9 | Python | 744 | 22 | import argparse
import numpy as np
import mne
def get_edf_annotations(edf_file, outfile):
# Load edf file
raw = mne.io.read_raw_edf(edf_file, preload=False)
# read annotations
anno = raw.annotations.description
print(anno)
print(type(anno))
np.save(outfile, anno)
if __name__ == "__main__... |
a32e4926584b6b1eb3062638dd76c247b976e4eb15be6640a0e14337afc5169d | Python | 745 | 31 | from . import annotations, base, selections
from .annotations import (
MoleculeAnnotation,
MoleculeAnnotationManager,
MoleculeInfo,
)
from .base import Molecule
from .calculations import CalculationManager
from .dssp import DSSPCalculation
from .hbonds import HBondCalculation
from .imd import StreamingTraje... |
c09d62e850ae01df0daab7a89d6a0bc7666127e9ce5de08c9257a0f71fbc7011 | Python | 745 | 22 | import os
import sys
read_dir_path = sys.argv[1]
output_dir_path = sys.argv[2]
model_name = sys.argv[3]
dir_list = os.listdir(read_dir_path)
batch=0
modeltype = ''
if model_name == "TINYX011":
batch=128
modeltype = 'tinynoskipx011'
model_path = '../../bonito/models/' + model_name + '/'
for dir in dir_lis... |
3680a78c9e03144678e44a3ed817572ec5890b01a46a2b75b69ff5ee96a5795c | Python | 746 | 26 | # copied from setuptools.logging, omitting monkeypatching
from __future__ import annotations
import logging
import sys
def _not_warning(record):
return record.levelno < logging.WARNING
def configure():
"""
Configure logging to emit warning and above to stderr
and everything else to stdout. This beh... |
72b1d9baeefc0c9d6d49caaad3bdc80fa3731cb17ed1c7432ac14d7782d6461e | Python | 746 | 24 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... |
a64ad456ec79301874322db2fa13111084f71669c62b04ffd89f41ba91fae322 | Python | 746 | 38 | # external
import pytest
# project
import textdistance
ALG = textdistance.Matrix
# https://en.wikipedia.org/wiki/Needleman%E2%80%93Wunsch_algorithm
NW_MATRIX = {
('A', 'A'): 10,
('G', 'G'): 7,
('C', 'C'): 9,
('T', 'T'): 8,
('A', 'G'): -1,
('A', 'C'): -3,
('A', 'T'): -4,
('G', 'C'): -5... |
1eb0cddaa4d113aefc222ff02f51553de58f474dfc935b28825d26893fd36d95 | Python | 747 | 33 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
import common_setup
REVS = ["issue558-base", "issue558-v1"]
LIMITS = {"search_time": 300}
SUITE = suites.suite_satisficing_with_ipc11()
CONFIGS = {
"lazy_wa3_ff": [
"--heuristic", "h=ff()",
"--search", "lazy_wastar(h,w=3... |
cb2c4c298f9011c4325635f9d16217a4b981363d602d9cebc7ae0a26ef211be0 | Python | 747 | 26 | from constants import *
from src.models.rey_regressor import reyregressor
from src.models.rey_regressor_v2 import reyregressor_v2
from src.models.rey_classifier import rey_classifier_3, rey_classifier_4
from src.models.rey_multilabel_classifier import rey_multiclassifier
def get_classifier(arch, num_classes: int = 2)... |
e2a240742fd7bdac664d07edb03b09d9a3e65150a39e152e957bf13efd932d79 | Python | 747 | 34 | from __future__ import print_function
import os
import sys
import argparse
name = 'gui'
help = 'opens the topaz GUI in a web browser'
def add_arguments(parser=None):
if parser is None:
parser = argparse.ArgumentParser('Opens the topaz GUI in a web browser.')
return parser
def main(args):
# ope... |
f0b71c3f890624015ee5971b5fe8c7602783d13b7948c6865ef7f3302f87e0a8 | Python | 747 | 26 | import os, sys
from distutils.sysconfig import get_python_inc
from setuptools import setup, Extension, find_packages
def getInclude():
dirName = get_python_inc()
return [dirName, os.path.dirname(dirName)]
def setup_package():
__version__ = '0.1'
url = 'https://github.com/donglaiw/ExM-Toolbox'
set... |
11d6f4c6e41dd19860f5e1681accfb87d6684ed432d98b886d978b1cfc9e5d18 | Python | 748 | 25 | # -*- coding: utf-8 -*-
from .chain import LinearChainCRF, SemiMarkovCRF
from .dist import StructuredDistribution
from .tree import (BiLexicalizedConstituencyCRF, ConstituencyCRF,
Dependency2oCRF, DependencyCRF, MatrixTree)
from .vi import (ConstituencyLBP, ConstituencyMFVI, DependencyLBP,
... |
42b1c3774e8fb5252a51f7669ebd3b0fb6b7e8b0d26709783a1409c8cedfb4b2 | Python | 748 | 31 | # set QT_API environment variable
import os
import sys
import argparse
os.environ["QT_API"] = "pyqt5"
import qtpy
# qt libraries
from qtpy.QtCore import *
from qtpy.QtWidgets import *
from qtpy.QtGui import *
# app specific libraries
import control.gui as gui
#import control.gui_2cameras_async as gui
#import control... |
84948cc41f191ed2645e49303e00020bfde408cd7d925930e51a43a6cc9ea614 | Python | 748 | 27 | import sys
import pytest
argv = sys.argv
argv = argv[argv.index("--") + 1 :]
# run this script like this:
# /Applications/Blender.app/Contents/MacOS/Blender -b -P tests/run.py -- . -v
# /Applications/Blender.app/Contents/MacOS/Blender -b -P tests/run.py -- . -k test_color_lookup_supplied
def main():
# bpy.ops.... |
ceecc17dc083d93d4be6613171027063b50827a312c3335b0f5a8d64f9d3274c | Python | 748 | 26 | from autograd import make_vjp
from autograd.builtins import tuple
from autograd.extend import defvjp, primitive, vspace
@primitive
def fixed_point(f, a, x0, distance, tol):
_f = f(a)
x, x_prev = _f(x0), x0
while distance(x, x_prev) > tol:
x, x_prev = _f(x), x
return x
def fixed_point_vjp(ans... |
f2fe5b794da1d5cd78e5948947b1ebbc9eb098072c82d56947db4036b6d3d5d1 | Python | 748 | 35 | # .. an example to test decorator with precision keyword argument ..
"""
Test profiling using command line ``profile`` function (either
``TimeStamper`` or ``LineProfiler``) with precision specified as command
line parameter.
The precision argument specified in the decorator, therefore, is not used.
"""
import time
@p... |
189d7cd04c99aa2b47ed701ec31c6ff1ebac7aaf760cdf7530b875284486c3d1 | Python | 749 | 21 | from __future__ import annotations
from logging import INFO, WARNING, getLogger
def test_emmet_task_doc_log_filter(caplog):
logger = getLogger("emmet.core.tasks")
with caplog.at_level(INFO, logger="emmet.core.tasks"):
logger.info("Getting task doc in: /path/to/calculation")
logger.info("Anot... |
63efb0844ccc4007b9f6bf797c326fee644aa7784a092ebc5f4bff2814832439 | Python | 749 | 31 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
import configs
import common_setup
REVS = ["issue436-base", "issue436-v2"]
LIMITS = {"search_time": 1800}
SUITE = suites.suite_satisficing_with_ipc11()
default_configs_satisficing = configs.default_configs_satisficing(extended=True)
CONFIGS... |
db8365258e588c2bb93c6fcea3ffac08ba5e71e86c534915aa4f7767e82e0f78 | Python | 749 | 22 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
''' Script to submit to cluster supplemental ROI analyses '''
import os
from warnings import filterwarnings
from stormdb.cluster import ClusterBatch
from stormdb.access import Query
project = 'MINDLAB2020_MEG-AuditoryPatternRecognition'
os.environ['MINDLABPROJ']=project
o... |
2367c4cdba17ddce7682f1d02787bcff05d9e6b26e4d93a62ec55c0b180f8a6f | Python | 750 | 30 | from collections.abc import Callable
from typing import Protocol
from .convolution import DummyLowerable
class Translator(Protocol):
def register(self, name: str) -> Callable: ...
class LoweringPassPluginSymbol:
def __init__(self, fn: Callable[[DummyLowerable], str]):
self._fn = fn
def load_lo... |
724883282ebc8294adf92da19ac5c3c57cccffa1b57ba7f4df22b4b4c51e1acc | Python | 750 | 27 | # -*- coding: utf-8 -*-
from .affine import Biaffine, Triaffine
from .dropout import IndependentDropout, SharedDropout, TokenDropout
from .gnn import GraphConvolutionalNetwork
from .lstm import CharLSTM, VariationalLSTM
from .mlp import MLP
from .pretrained import ELMoEmbedding, TransformerEmbedding
from .transformer ... |
79f2f73bf1fc4330abdc5557ad4d0658df9bade6425236abbada5b85a1699ff5 | Python | 750 | 34 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import downward.suites
import common_setup
import configs
CONFIGS = configs.default_configs_satisficing(ipc=False, extended=False)
# The following lines remove some configs that we don't currently
# support.
DISABLED = [
]
for key, value in list(CONFIGS.items()):
... |
c3d86785515f9b9c49210d2282993aeea5a22a7f3339d0f2c72df0eb77d8f0a7 | Python | 750 | 38 | # Copyright (c) OpenMMLab. All rights reserved.
from mmcv.cnn import MODELS as MMCV_MODELS
from mmcv.cnn.bricks.registry import ATTENTION as MMCV_ATTENTION
from mmcv.utils import Registry
MODELS = Registry('models', parent=MMCV_MODELS)
BACKBONES = MODELS
NECKS = MODELS
HEADS = MODELS
LOSSES = MODELS
CLASSIFIERS = MOD... |
8477d4b8377157aaccb2699c6b5be1b1d6c861878301d6b941c0a64ac5ee4368 | Python | 751 | 26 | from .model_zoo import TimmRegressor
def build_model(config):
model_type = config.MODEL.TYPE
# accelerate layernorm
if config.FUSED_LAYERNORM:
try:
import apex as amp
layernorm = amp.normalization.FusedLayerNorm
except:
layernorm = None
prin... |
0dd9030c9b366c1162e5c1861f40e59969b9b2a79066b9c371b050d651337174 | Python | 752 | 25 | from __future__ import print_function, division
from topaz.utils.picks import scale_coordinates
name = 'scale_coordinates'
help = 'scale particle coordinates for resized images'
def add_arguments(parser):
parser.add_argument('file')
parser.add_argument('-s', '--scale', default=0.25, type=float, help='scaling... |
8676fc2f3c16be2a892a752234a245abb6849b17025384dc851b9abd7af7d111 | Python | 753 | 29 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import downward.suites
import common_setup
import configs
CONFIGS = {}
INCLUDE = ("lazy", "lama")
EXCLUDE = ("lazy_greedy_add", "lazy_greedy_cea", "lazy_greedy_cg")
for key, value in configs.default_configs_satisficing(ipc=False, extended=True).items():
if any(x in ... |
c322126730d4ec0760c3571940eb221c29104b8ebba2a87ea0dd5f948bdb789d | Python | 753 | 23 | ############
# https://github.com/lessw2020/mish/blob/master/mish.py
# This code was taken from the repo above and was not created by me (Fabian)! Full credit goes to the original authors
############
import torch
import torch.nn as nn
import torch.nn.functional as F
# Mish - "Mish: A Self Regularized No... |
b854107b118b48c5c364e54b0d581a7c0dbeb63c29d06f16a685574e770e2730 | Python | 754 | 29 | import pandas as pd
from subprocess import Popen, PIPE, DEVNULL, STDOUT
DEBUG = 1
def execute_command(cmd):
"""Wrapper for executing CLI commands.
Args:
cmd (str): Command to execute.
"""
if (DEBUG):
print(cmd)
process = Popen(cmd, shell=True, stdout=PIPE)
else:
pro... |
3b155b1ce4aadee4e6d646ca96b5c54707d60c3bf463f17cad2553c2b2060a80 | Python | 755 | 31 | from numpy.testing import assert_array_almost_equal
from pytest import raises
from wonambi import Dataset
from .paths import ktlx_file
def test_xltek_data():
d = Dataset(ktlx_file)
data = d.read_data(begsam=1000, endsam=1001, chan=('FZ', ))
assert_array_almost_equal(data.data[0][0, 0], -90.119315)
def... |
5e5c4a94e4e6220b584f5848b4f4a09cfa72aec11c450bd682f2584ce3ac9190 | Python | 755 | 27 | import trimesh
from trimesh.exchange import ply
from trimesh.smoothing import filter_laplacian
class CreateTriMesh:
def __init__(self, reduction, smoothing):
self.reduction = reduction
self.smoothing = smoothing
def __call__(self, vertx, faces, normals):
mesh = trimesh.Trimesh(vertice... |
cfc563f12afa524967116dfe7ca8d04179fd26284152bde2c6fa42eb20aa4c39 | Python | 755 | 28 | import os
import sys
from contextlib import contextmanager
from typing import Iterator
@contextmanager
def suppress_output() -> Iterator[None]:
out_fd = sys.stdout.fileno()
err_fd = sys.stderr.fileno()
out_dup_fd = os.dup(out_fd)
err_dup_fd = os.dup(err_fd)
try:
with (
open(os... |
a22f5b4c1cce19ab91089e24a8fc617e82526b7cf811fd288a021ee007886545 | Python | 756 | 33 | from ..neuralnodes import params
import dataclasses
@dataclasses.dataclass
class Params(params.Params):
filter_inh_dur: float = 8.0
filter_inh_gain: float = 1.0
filter_delay: float = 7.0
filter_exc_dur: float = 4.0
filter_exc_gain: float = 0.1
taum: float=1
tref: float=.001
taua: flo... |
b5b2daa6c08ebe30d4e442f463857d06d4f0606c0311c48cb96de9b49ee4c55b | Python | 756 | 30 | # built-in
from math import isclose
# external
import pytest
# project
import textdistance
ALG = textdistance.JaroWinkler
@pytest.mark.parametrize('left, right, expected', [
('elephant', 'hippo', 0.44166666666666665),
('fly', 'ant', 0.0),
('frog', 'fog', 0.925),
('MARTHA', 'MARHTA', 0.961111111111... |
d7ad80015dd7bc0cafe1b486d8b73b92a2e338c78667ec7c15345a8699fb839e | Python | 756 | 26 | import cv2
import numpy as np
np.random.seed(0)
class GaussianBlur(object):
# Implements Gaussian blur as described in the SimCLR paper
def __init__(self, kernel_size, min=0.1, max=2.0):
self.min = min
self.max = max
# kernel size is set to be 10% of the image height/width
sel... |
226af26d295edbe25eb71585066c60e34767882fa8df66a0448d7442fb5ff9f5 | Python | 757 | 29 | import numpy as np
from .basic_euclidean import eucl_dist
def discret_frechet(t0, t1):
"""
Usage
-----
Compute the discret frechet distance between trajectories P and Q
Parameters
----------
param t0 : px2 numpy_array, Trajectory t0
param t1 : qx2 numpy_array, Trajectory t1
Retur... |
8f211e5a92df15e4d23bdf6c81bc6892842d995e1bfec96cd7a2aa9e1ecfac1b | Python | 757 | 29 | import yaml
import os
from pathlib import Path
GLOBAL_PARAMS_PATH = Path("global_params.yaml")
def load_params(name:str) -> dict:
with open(name, "r") as f:
params = yaml.safe_load(f)
return params
def load_experiment_params(name:str, project_name:str) -> dict:
params_path = Path(os.getcwd()) / ... |
d302f3bf372c672c533e1a5ee3026b038089352acc8709dea24860533e28e62c | Python | 757 | 23 | import torch
from .defaults import get_default_config
def update_config(config):
if config.dataset.name in ['CIFAR10', 'CIFAR100']:
dataset_dir = f'~/.torch/datasets/{config.dataset.name}'
config.dataset.dataset_dir = dataset_dir
config.dataset.image_size = 32
config.dataset.n_cha... |
eb5cadb25a029a70dba00a83c26b1d7e800838e8a94868c4acd4d11c76682e09 | Python | 758 | 18 | # class from: https://github.com/tanjimin/C.Origami/blob/main/src/corigami/data/data_feature.py
# made for comparison with the c.origami to compare with HiC data
import numpy as np
import cooler
class HiCDataset():
def __init__(self, hic_file_name, res):
self.hic_dataset = cooler.Cooler(f"{hic_file_name}:... |
baad8cc3482b2fd2ba7fcbb880b86103794aaa665e8d80cedb5684515f298e5a | Python | 759 | 31 | from __future__ import annotations
import pytest
def mock_execute(self, *args, **kwargs):
pass
@pytest.fixture(autouse=True)
def patch_execute(monkeypatch):
from ase.calculators.onetep import OnetepTemplate
monkeypatch.setattr(OnetepTemplate, "execute", mock_execute)
def mock_read_results(self, dire... |
e5a43894e83c8e396e396527411faa111fc7f5292f90708a09dab2d6c1c7116d | Python | 759 | 28 | from median.buffer import Buffer
from median.filter_median import FilterMedian
fm7 = FilterMedian(L=7, dtype=int, initB=[5, 7, 8, 8, 9, 10, 11])
def update_desc(buffer: Buffer, value: float | int):
print(f"Insert: {value:>3}")
print(f"Before: | {' | '.join([f'{i:>2}' for i in buffer.getBuffer()])} |")
bu... |
4fc0ce129f0efd7ffb84207d6991996f5dd85a39c330a1d46f4537300e25a910 | Python | 760 | 28 | """Small Qt helpers shared by the viewer module and its mixins.
Importing from a tiny module avoids a circular import: mixins can't
import from viewer.py (they're imported BY viewer.py), but both
need the ``_block_signals`` context manager.
"""
from __future__ import annotations
def _block_signals(widget)... |
9c0fdb19668370bdbb9c814689897e066ea525cefaad26c793468eb5b04ed8d9 | Python | 760 | 23 | from __future__ import annotations
from pathlib import Path
import pytest
from ase.io import read
from numpy.testing import assert_equal
from quacc.atoms.deformation import make_deformations_from_bulk
FILE_DIR = Path(__file__).parent
def test_make_deformations_from_bulk():
atoms = read(FILE_DIR / "ZnTe.cif.gz... |
12b0cc5360d03995972e35de1d534b9fe9421bc6d6d1f8b3bf29ee968a782718 | Python | 761 | 22 | import argparse
import json
import torch
from MolNexTR import molnextr
import warnings
warnings.filterwarnings('ignore')
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--model_path', type=str, default=None, required=True)
parser.add_argument('--image_path', type=str, ... |
1a743b7304c197663a1f2ca078534b0bbe9c1169e41d271d9ba74286355c3971 | Python | 761 | 20 | from collections import defaultdict
from unittest import TestCase
from codex.data.catalog import _CODEX_DATA_SCHEMA
class CatalogTest(TestCase):
def test_column_intersections(self):
col_counts = defaultdict(int)
for cols in _CODEX_DATA_SCHEMA.values():
for c in cols:
co... |
68504c99b9aa63000e917f6cd57c9a8c690013bd618cd0819b0eb65f63411585 | Python | 761 | 25 | try:
import binutil # required to import from dreamcoder modules
except ModuleNotFoundError:
import bin.binutil # alt import if called as module
from dreamcoder.domains.text.main import main, LearnedFeatureExtractor, text_options
from dreamcoder.dreamcoder import commandlineArguments
from dreamcoder.utilitie... |
7776da30d5dad14fa1b28ad8744a0a7ea5bd6bd83397b577b251af71fc63b4d9 | Python | 761 | 23 | from .classifier_ops import *
from config import classifier_list
def get_classifier(args):
bias_flag = args.classifier_bias
num_features = args.num_features
num_classes = args.num_classes
if not args.classifier in classifier_list:
raise NotImplementedError("Unsupported Classifier: {}"... |
e154daf8dcca4759e059775e72e442561bd8af11314b90299a0914e8f0c2418a | Python | 761 | 22 | # Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
import glob, os
import pandas as pd
from DiscRisk_constants import dir_NHANES_dataset
dirs_collections = glob.glob(dir_NHANES_dataset + r'/*Data')
for dir_collection in dirs_collections:
if not os.p... |
4a5f670de4e5ca24ebcac84086272ab43da8eaa8625b97c4ed25ccdd115c1f23 | Python | 762 | 28 | """
This script flattens NeSys .xyz files containing in-brain coordinates.
"""
import os
def flatten_xyz(fname):
result = ["RGB 0 0 0\n"]
with open(fname,"r") as xyz:
for line in xyz:
if not (line.startswith("SCALE") or line.startswith("#") or line.startswith("RGB") or line.s... |
ae2ed92c0fb9e9eae83c32df8d28d524c9e8f00691d7d6e9a9e9c27482db429f | Python | 762 | 31 | # set QT_API environment variable
import os
import sys
import argparse
os.environ["QT_API"] = "pyqt5"
import qtpy
# qt libraries
from qtpy.QtCore import *
from qtpy.QtWidgets import *
from qtpy.QtGui import *
# app specific libraries
import control.gui_2cameras_sync as gui
#import control.gui_2cameras_async as gui
#... |
cfd27eeda9a2acafc9a9a4b72296addff99bb35edfc445d027439b13f74d745b | Python | 762 | 25 | #! /usr/bin/env python
from lab.parser import Parser
parser = Parser()
LEGACY_TO_NEW_EXIT_CODES = {
'critical-error': 'search-critical-error',
'input-error': 'search-input-error',
'unsupported-feature-requested': 'search-unsupported',
'unsolvable': 'search-unsolvable',
'incomplete-search-found-no... |
7060d0853f94c7db8ff016e85b8240e5fcb94da4af4f31b2f02c754aeaf364b8 | Python | 763 | 25 | """
Modified by Mayank Kabra
Adapted from DeepLabCut2.0 Toolbox (deeplabcut.org)
Copyright A. & M. Mathis Labs
https://github.com/AlexEMG/DeepLabCut
Please see AUTHORS for contributors.
https://github.com/AlexEMG/DeepLabCut/blob/master/AUTHORS
Licensed under GNU Lesser General Public License v3.0
Adapted from DeeperC... |
7ebb6bbfea810d4eec865e8151a7152593957ddbca0d6809b42f23ff1c5e23f0 | Python | 763 | 31 | # set QT_API environment variable
import os
import sys
import argparse
os.environ["QT_API"] = "pyqt5"
import qtpy
# qt libraries
from qtpy.QtCore import *
from qtpy.QtWidgets import *
from qtpy.QtGui import *
# app specific libraries
import control.gui_toupcam_IMX571 as gui
#import control.gui_2cameras_async as gui
... |
02856f6aa338d001c9dd207cbaf0ade2996e13e26978ea00fb794a326b84cf93 | Python | 764 | 30 | import pytest
import pertpy as pt
@pytest.fixture
def test_data(rng):
X = rng.normal(size=(100, 10))
Y = rng.normal(size=(100, 10))
C = rng.normal(size=(100, 10))
return X, Y, C
def test_compare_class(test_data):
X, Y, C = test_data
pt_comparison = pt.tl.PerturbationComparison()
result ... |
215bd94549926135c811d8a863967be343a84df5b982783d173ef3d2b4c9146b | Python | 764 | 16 | """Atlas-specific utilities (Allen CCF, Waxholm).
This package owns code that's specific to the brain atlas data formats
the registration pipeline depends on. Separated from regtools.utils to
make the dependency direction explicit: atlas-specific tools live here,
generic utilities stay in regtools.utils.
Submo... |
fc0e820564acaac950e0092376a0b86df84c476da1984b2bbe901539aaeb4979 | Python | 764 | 24 | import warnings
import functools
__all__ = ["deprecated"]
def deprecated(func):
"""This is a decorator which can be used to mark functions
as deprecated. It will result in a warning being emitted
when the function is used."""
@functools.wraps(func)
def new_func(*args, **kwargs):
warnings... |
343f38460358e26dd07e35394bec3b13ec72bb36edc3b4978dbfdaac29208ae7 | Python | 765 | 30 | import torch
from prosper_nn.models.feedforward.feedforward import FFNN
# Set model and data parameter
input_dim = 10
hidden_dim = 15
output_dim = 1
n_batches = 100
batchsize = 5
# Initialise Deep Feedforward Neural Network
feedforward = FFNN(input_dim=input_dim,
hidden_dim=hidden_dim,
... |
5069914af1da1214167a6cd75248cf0f17d87aac4ed879a2931d9e67cc3ed5cc | Python | 767 | 22 | import numpy as np
seven_circle = np.array([[0,0,1,1,1,0,0],
[0,1,1,1,1,1,0],
[1,1,1,1,1,1,1],
[1,1,1,1,1,1,1],
[1,1,1,1,1,1,1],
[0,1,1,1,1,1,0],
[0,0,1,1,1,0,0]])
five... |
50a6477573123d0fd7ead0c5405fc5387c34bfbea0b43f6f8747332528505ad5 | Python | 767 | 21 | from ETL.Transform.tf_SLICER_BIDS import sclicer_bids_integration
# Main program
if __name__ == "__main__":
"""
Main workflow to convert NIFTI files to BIDS format
1. Read the export_info.json file to get the subject information
2. Create the BIDS root and derivatives dir and Patients dir (if not exis... |
8eea3a9a6438b6fae6f262bffa4b8251e821a790218c03ee25b3af1c67a0471b | Python | 767 | 34 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
import common_setup
REVS = ["issue558-base", "issue558-v1"]
LIMITS = {"search_time": 300}
SUITE = suites.suite_satisficing_with_ipc11()
CONFIGS = {
"lazy_wa3_ff": [
"--heuristic",
"h=ff()",
"--search",
"l... |
dfb6cf249c00dbbf5f7e62051a2ad6ab43bb92d68eabdf888636e375fe39942a | Python | 767 | 26 | from pathlib import Path
# Paths
HOME_DIR = Path.home()
PARSING_MODEL_DIR = HOME_DIR / ".local/share/bllipparser/GENIA+PubMed"
# Observation constants
CARDIOMEGALY = "Cardiomegaly"
ENLARGED_CARDIOMEDIASTINUM = "Enlarged Cardiomediastinum"
SUPPORT_DEVICES = "Support Devices"
NO_FINDING = "No Finding"
OBSERVATION = "ob... |
319755fe7ffff98ffa8448ba17f0e56b648484b06baababae622cb78cc683996 | Python | 768 | 26 | import math, random
def selectPopSize(meanFoldChange, maxFoldChange):
foldChange = 1+randBoundedExp(meanFoldChange-1, maxFoldChange-1)
if random.random() <= 0.5:
return foldChange
else:
return 1/foldChange
def selectGridOfTimesLogScale(gridSize, maxTime):
gridTimes = []
interval = ... |
71be753258bb92f771ad57e36ebbe40efd9690fe347881d49830795aaceb2020 | Python | 768 | 36 | # I/O utilities sub-package
# TIFF reading, NIfTI creation, and unified data loading
from .tiff_io import (
read_tif_section,
read_tif_wrapper,
get_stacked_data,
read_multipage_tif,
read_tif_page,
is_multipage_tif,
get_tif_page_count,
load_tiff_volume,
check_section_shap... |
83519a598a3974b32fd927c499bb4a25309cbe0c6e90cf973ff2cd963dc0a3eb | Python | 768 | 27 |
try:
import binutil # required to import from dreamcoder modules
except ModuleNotFoundError:
import bin.binutil # alt import if called as module
from dreamcoder.domains.logo.main import main, list_options, LogoFeatureCNN
from dreamcoder.dreamcoder import commandlineArguments
from dreamcoder.utilities import... |
b0c9a2ff4a1e99206d09f40aa1fe5a2a2efec93063873cc065a37eaa346cf9a8 | Python | 769 | 24 | import pytest
from pupil_recording_interface.decorators import device, stream, process
from pupil_recording_interface.device.video import VideoDeviceUVC
from pupil_recording_interface.stream import VideoStream
from pupil_recording_interface.process.display import VideoDisplay
class TestDecorators:
def test_devic... |
9ec09fd9778e9a4f27d9243e7fdbaf76bfcbe34d9a8799a25a437e8c5577f42a | Python | 770 | 36 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from downward import suites
import common_setup
DIR = os.path.dirname(os.path.abspath(__file__))
REPO = os.path.dirname(os.path.dirname(DIR))
REVS = ["issue414-base", "issue414"]
LIMITS = {"search_time": 1800}
SUITE = suites.suite_optimal_with_ipc11()
# T... |
f1359a9589f6fd0a96a1c9a0e138bd964ce26110539ccb9950b455c47e845540 | Python | 770 | 32 | import json
from typing import Any
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from pathlib import Path
from ..prixfixe.predictor import Predictor
from scipy import stats
import pandas as pd
class UnlockDNAPredictor(Predictor):
def __init__(self,
mode... |
e57070eede5ac23b853a955449dab6876d9a5eb14f62c449726bcbfe45bda7c3 | Python | 771 | 28 | from __future__ import print_function
import argparse
from topaz.utils.image import downsample_file
name = 'downsample'
help = 'downsample micrographs with truncated DFT'
def add_arguments(parser=None):
if parser is None:
parser = argparse.ArgumentParser()
parser.add_argument('file')
parser.add... |
63a85661972d70428de7bbdf9dcd3a26e1ad70423c5491f3301f600a44fd31cd | Python | 772 | 21 | """PeerJCode URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/4.1/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
C... |
93883bf2c4d2e1c9edec937568b14b316b6e01aed436d193b93d655ea906e2fe | Python | 772 | 27 | from setuptools import setup, find_packages
setup(
name="GZSper",
version="0.1.0",
packages=find_packages(),
install_requires=[
"scanpy",
"matplotlib",
"seaborn",
"pandas",
"numpy",
"scipy",
],
author="Benjamin-JHou",
author_email="zjy888zjy88... |
b426c9075951d6f7258e70414162f0f64b29316ad46a7a00d59bb4d0c5c666ec | Python | 772 | 35 | import os
import sys
sys.path.append(os.path.dirname(__file__))
from app.arrayexp import ArrayExp as Device
import numpy as np
class SDK():
def __init__(self, chip_num=1):
# self.ARRAYs = ARRAYs_4K(chip_num)
pass
def connect_device(self):
self.device = Device.ArrayExp()
... |
06f1e405bbcdbabfad36592452422477533f0f3f0e3fed7c1237bf9781e51ab7 | Python | 773 | 24 | import os.path
import subprocess
DIR = os.path.dirname(os.path.abspath(__file__))
TRANSLATE_DIR = os.path.dirname(DIR)
REPO = os.path.abspath(os.path.join(DIR, "..", "..", ".."))
BENCHMARKS = os.path.join(REPO, "misc", "tests", "benchmarks")
DOMAIN = os.path.join(BENCHMARKS, "gripper", "domain.pddl")
PROBLEM = os.path... |
3453bc3e6cd54118a2c98eeb5ed3913b5aaedf9a0e1b95f4c0db9d90bdaefb7c | Python | 773 | 32 | import os
from flask import current_app
from .envir import CIRRO_AUTH, CIRRO_DATABASE, CIRRO_MOUNT
def get_database():
return current_app.config[CIRRO_DATABASE]
def get_auth():
return current_app.config[CIRRO_AUTH]
remapped_urls = dict()
if os.environ.get(CIRRO_MOUNT) is not None:
tokens = os.enviro... |
d927c8866851c0d48873f21e6119e8d403202bb100970780e6e43990374e127a | Python | 773 | 41 | """Integration tests for dependencies.
Author: Seth Axen
E-mail: seth.axen@gmail.com
"""
class TestRequiredDependencies:
def test_rdkit(self):
import rdkit
def test_numpy(self):
import numpy
def test_scipy(self):
import scipy
def test_murmurhash(self):
import mmh3
... |
4478083f0b4e6e1e4a84cadddd8653925f336d51bee8e92697b61b157e04860d | Python | 774 | 27 | from contextlib import ExitStack, contextmanager
from typing import ContextManager, Generator, TypeVar
_T = TypeVar("_T", covariant=True)
class CommandContextMixIn:
def __init__(self) -> None:
super().__init__()
self._in_main_context = False
self._main_context = ExitStack()
@contextm... |
5f7f8a319db41e8dd5b6ac95697725a5e429173a24479344f2d6527ef295681f | Python | 774 | 33 | # SPDX-FileCopyrightText: 2015 Eric Larson
#
# SPDX-License-Identifier: Apache-2.0
from .adapter import CacheControlAdapter
from .cache import DictCache
def CacheControl(
sess,
cache=None,
cache_etags=True,
serializer=None,
heuristic=None,
controller_class=None,
adapter_class=None,
ca... |
9322e86a77217bc9b287b110a8013c6ba84ac99728547128dc4755453ee73d41 | Python | 774 | 30 | import torch
import numpy as np
import matplotlib
import seaborn as sns
matplotlib.use('Agg')
import matplotlib.pyplot as plt
def confusion_matrix(output, target):
try:
from sklearn.metrics import confusion_matrix as cm
except ImportError:
raise RuntimeError("Confusion Matrix requires scikit-l... |
d60de55f3a0ce45d64831b60fbfb0b05c03386dc6061889bc825b03630163937 | Python | 774 | 30 | from setuptools import setup, find_packages
from hotpp import __version__
with open('README.md') as f:
long_description = f.read()
setup(
name="miaonet",
version=__version__,
author="Wang Junjie",
author_email="141120108@smail.nju.edu.cn",
url="https://git.nju.edu.cn/bigd4/tpn",
packages... |
063982c2ebff9909ddb0eb051e4ddf207f85c10bed1971e13443414026355f89 | Python | 776 | 18 | # -*- coding: utf-8 -*-
from .const import (AttachJuxtaposeConstituencyParser, CRFConstituencyParser,
TetraTaggingConstituencyParser, VIConstituencyParser)
from .dep import (BiaffineDependencyParser, CRF2oDependencyParser,
CRFDependencyParser, VIDependencyParser)
from .sdp import ... |
2343264f5cd36132c8a60c99bdb62bc83e135127923a309b86718485f736bd63 | Python | 776 | 27 | from .modeling_finetune import (
vit_base_patch16_224,
vit_giant_patch14_224,
vit_huge_patch16_224,
vit_large_patch16_224,
vit_small_patch16_224,
)
from .modeling_pretrain import (
pretrain_videomae_base_patch16_224,
pretrain_videomae_giant_patch14_224,
pretrain_videomae_huge_patch16_224... |
3b143c0f04dc9e975fc80c1355cab4521fe8dc3f700b29eb708f53c2876f8e54 | Python | 776 | 26 | # Testing the coherence
import numpy as np
import matplotlib.pyplot as plt
from soundsig.coherence import coherence_jn
from soundsig.signal import lowpass_filter
# Make two gaussian signals
sample_rate = 1000.0
tlen = 2.0 # 2 second signal
# Make space for both signals
s1 = np.random.normal(0, 1, int(tlen*sample_r... |
7366c5d023c06b00b2ceaf0078ad36dedc9469ddc1ffc368f98ad0ac4d1bd5f1 | Python | 776 | 28 | """ This simple demo will show you how to quickly get started with PySPI.
"""
import numpy as np
from pyspi.calculator import Calculator
import matplotlib.pyplot as plt
dataset = np.random.randn(
3, 1000
) # Generate multivariate data with 3 processes and 100 observations
calc = Calculator(
dataset=dataset, ... |
2ac0aab56745678fe5f9a11829616806dea23eefbdbd6b0b254b33c494bf2c95 | Python | 777 | 39 | from .blocks import \
UNetConvBlock, \
UNetAttentionBlock, \
UNetUpBlock
from .functions import \
_CONV_DICT, \
_CONV_TRANS_DICT, \
_AVG_POOL_DICT, \
_MAX_POOL_DICT, \
_NORM_DICT, \
_REFLECTION_PAD_DICT, \
_CENTER_CROP_DICT, \
_ACTIVATION_DICT, \
activation_from_str
fro... |
6f2abc75b9a11d5105dc446c6618bf4e2676b743540bebf4f70c1bdc0aeeaed1 | Python | 777 | 34 | # based on https://math.stackexchange.com/questions/1287634/implementing-ornstein-uhlenbeck-in-matlab
#
# Baseline implementation of standard OU process with constant mu and sigma.
import numpy as np
import pylab as pl
def gen_ou_process(th, mu, sig, t, N=1, x0=0):
# Allocate output vector, set initial condition
... |
e003d89c0d468671c6a6a25ee9b88b6acfa1f6f210bd9d36d4704961dd3cc88a | Python | 777 | 29 | # This file is for neuron's h setting
# set_h_before is used before network initialization
# set_h_after is used after network initialization
from neuron import h, load_mechanisms
def set_h_before(config):
cell_info = config["cell_info"]
cells_id_sim = cell_info["cells_id_sim"]
cells_name_dic = cell_inf... |
189e08f60c43dedefd8d3758509049ec5006dddabe289a6a9b691098bccea3bf | Python | 778 | 33 | from pytest import raises
from autograd.extend import defvjp
from autograd.test_util import check_grads
from autograd.tracer import primitive
def test_check_vjp_1st_order_fail():
@primitive
def foo(x):
return x * 2.0
defvjp(foo, lambda ans, x: lambda g: g * 2.001)
with raises(AssertionError... |
2cdc7bbea06775874753c62e26de7769bffcaf33064d756bbcc6fb099264c46d | Python | 778 | 32 | # SPDX-FileCopyrightText: 2015 Eric Larson
#
# SPDX-License-Identifier: Apache-2.0
try:
from urllib.parse import urljoin
except ImportError:
from urlparse import urljoin
try:
import cPickle as pickle
except ImportError:
import pickle
# Handle the case where the requests module has been patched to no... |
02258928d839ab7747ebcefadfc9d9b05c3cda50f7cb2f5bb5b938d3b338f877 | Python | 779 | 34 | from pupil_recording_interface.encoder import VideoEncoderFFMPEG
class TestVideoEncoderFFMPEG:
def test_get_ffmpeg_cmd(self):
""""""
cmd = VideoEncoderFFMPEG._get_ffmpeg_cmd(
"test.mp4", (1280, 720), 30.0, "libx264", "bgr24",
)
assert cmd == [
"ffmpeg",
... |
287e5db0575a7e0c256f28ec7979989ccacb4da9efa077a41b383c4f9548ad49 | Python | 779 | 25 | """Tests for optional file I/O in MLIP recipes."""
from __future__ import annotations
from ase.build import bulk
from ase.calculators.emt import EMT
from quacc.recipes.mlip.core import relax_job
def test_relax_job_without_files(tmp_path, monkeypatch):
monkeypatch.chdir(tmp_path)
monkeypatch.setattr(
... |
5324934d4cf020c17c70d9f7f22fe410d2c0e69ae99ffc9c49684e146071873c | Python | 779 | 33 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import configs, suites
import common_setup
SEARCH_REVS = ["issue439-base", "issue439-v1"]
LIMITS = {"search_time": 300}
SUITE = suites.suite_satisficing_with_ipc11()
configs_satisficing_core = configs.configs_satisficing_core()
CONFIGS = {}
for name in [... |
574f1047e2031f33e5bcc8a13cbe3d147aaa66742c02de17a2be589ce0e2e631 | Python | 779 | 24 | import numpy as np
import pytest
import molecularnodes as mn
from .emdb_pooch import fetch_emdb_map
@pytest.fixture
def emdb_density_map(isolated_density_file):
# copy out of the pooch cache so the generated .vdb is written to a temp dir
return isolated_density_file(fetch_emdb_map("EMD-48397"))
@pytest.mark... |
2b3d249d761eea6fca8dec63906d7ec851f20d01b4b9c13cbf8008c9e03acb31 | Python | 780 | 32 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
import configs
import common_setup
REVS = ["issue436-base", "issue436-v1"]
LIMITS = {"search_time": 1800}
SUITE = suites.suite_optimal_with_ipc11()
configs_optimal_core = configs.configs_optimal_core()
CONFIGS = {}
for name in ['astar_merge... |
08180e08ab6cc9442f09dd339f1056077eb09d160e70252ecf96e4358636ad75 | Python | 781 | 30 | from datetime import datetime
from PyQt5.QtCore import QDateTime
from wonambi.widgets.modal_widgets import DateTimeDialog
from .paths import GUI_PATH
start_time = datetime(2018, 1, 1, 12, 0, 0)
duration = 120
def test_widget_labels(qtbot):
d = DateTimeDialog('lights out', start_time, duration)
qtbot.addWid... |
0bdb0861843757ed20020b8df1d07616146581b3ce72f7f351db0267e19a9107 | Python | 781 | 31 | import mne
import numpy as np
import torch
from omegaconf import OmegaConf
from utils import load_model, generate
def main(cfg):
# load diffusion model
model = load_model(
cfg=cfg.path.inference_config,
ckpt=cfg.path.model,
is_safetensor=True)
# load neuroral activity data
da... |
a7dc59241cba667c60e9b5ed55bf7e4ef45232c1446932e991aefa576c602b88 | Python | 781 | 30 | import torch
import torch.nn as nn
import torch.nn.functional as F
class simam_module(torch.nn.Module):
def __init__(self, channels=None, e_lambda=1e-4):
super(simam_module, self).__init__()
self.activaton = nn.Sigmoid()
self.e_lambda = e_lambda
def __repr__(self):
s = self.__... |
880777f1248d24a4335a3ad035b935824506a1159accfa145c6dee0b1f22b850 | Python | 782 | 29 | import re
class NameRegistry:
def __init__(self):
self._registry = {}
def _get_name_count(self, name):
return self._registry.get(name, 0)
def prepopulate(self, names):
for name in names:
match = re.match(r"(.+)_(\d+)$", name)
suffix = 0
if matc... |
ffd0d4a14cf598ac6abf7add05c510784970db0fdc2b1f312544a64e1b1db412 | Python | 782 | 45 | #!/usr/bin/env python
# coding: utf-8
# In[1]:
import numpy as np
import matplotlib.pyplot as plt
# In[45]:
IMAGE_SIZE = "232 x 300"
SAVE_DIR = "./ablation_study_{}".format(IMAGE_SIZE)
# In[43]:
results = [1.228, 1.1613, 1.259, 1.148]
labels = ['Vanilla', 'Only data aug', 'Only tta', 'Both tta + data aug'... |
48325c967ce990ea68c89999db700eec96507ddb1da5698e3b4c687f38bde584 | Python | 783 | 28 | from __future__ import annotations
# built-in
from itertools import permutations, product
from typing import Sequence
__all__ = ['words_combinations', 'find_ngrams']
def words_combinations(f, *texts) -> float:
m = float('Inf')
# split by words
texts = [t.split() for t in texts]
# permutations
t... |
5c3ea988a563a6100d9a38555a5ad56272f1552186ddc37e197e88306820bbba | Python | 783 | 30 | import uuid
from memory_profiler import profile
from queso.sensors.pennylane.sensor import brick_wall_probe
from queso.sensors.pennylane.sensor import Interaction, Measurement, Sensor
from queso.sensors.pennylane.sensor import Phase, U3
@profile
def test_calculate_state(method):
n_layers = 2
n = 10
prob... |
61372efa05d7d8662b06cfb34a8d2d05d1ea4a15d106d960fee0ea5b3531aca7 | Python | 783 | 28 | import numpy as np
class Rosenbrock_func:
def __init__(self, a=1, b=10):
self.a = a
self.b = b
self.name = 'rosenbrock'
self.formula = r'$\min\ f(x_1,x_2)={0}(x_1-1)^2+{1}(x_1^2-x_2)^2$'.format(self.a, self.b)
def function(self, x):
return self.a * (x[0] -... |
b7b6af9bbcc439d304d1a30c905a2f89367fa59179248d77d59ebe2f8b2f000b | Python | 783 | 29 | from __future__ import print_function,division
import sys
import os
import pandas as pd
import topaz.utils.star as star
from topaz.utils.conversions import star_to_coordinates
name = 'star_to_coordinates'
help = 'convert .star file coordinates to tab delimited coordinates table'
def add_arguments(parser):
pars... |
b64305a5e1a199fe793a29e08dc61023c76451b5834866a950e50ee584a4520f | Python | 784 | 25 | from typing import List, Optional
from cog import BaseRunner, File, Input, Path
class Runner(BaseRunner):
def run(
self,
text: str = Input(description="Required anchor field"),
# PEP 604 optional lists
opt_tags: list[str] | None = Input(
description="Optional list of s... |
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