sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
7d758b1a6fd9a00126ed9698548cc3f420457c44017a7bfc40ad782055137092 | Python | 6,839 | 201 | # Copyright 2024 DeepMind Technologies Limited
#
# 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 applicable law or agr... |
89c99e0928bd831cf97913b67cd59ff44ff6e15389f6ba81f562538b8b46e668 | Python | 6,840 | 181 | import logging
import os
import subprocess
import time
import click
import dotenv as de
import pandas as pd
import parallel as par
de.load_dotenv(de.find_dotenv(usecwd=True))
def __subprocess_run(cmd):
try:
logging.debug(cmd)
subprocess.check_output(
cmd,
universal_newlin... |
3f378ec4f7890f798fc109424ab9c40fb00a7fb05e48e56b80a8b3f2b67312e0 | Python | 6,841 | 166 | """
This scripts generates figure 5a : Cumulative histogram of visual left/right selectivity
Internal notes:
from the notebook : naive-vs-proficient-mice-passive-prop-sig-neurons
"""
import pandas as pd
import pickle as pkl
import numpy as np
import os
import glob
import matplotlib.pyplot as plt
import matplotlib as m... |
05f3116cc9c1a28618a27bbda1b524275d30cb6efc71f3c9e9a42f2e6c4082e6 | Python | 6,843 | 169 | import torch
from onmt.translate.decode_strategy import DecodeStrategy
def sample_with_temperature(logits, sampling_temp, keep_topk):
"""Select next tokens randomly from the top k possible next tokens.
Samples from a categorical distribution over the ``keep_topk`` words using
the category probabilities ... |
4ca7eb24326823cab8720cd37faaabf9a8a59b0c3c835e5a3e1f5867f3c7e7e4 | Python | 6,844 | 218 | #!/usr/bin/python
"""
Run all gbc IV's as a batch
"""
import matplotlib
matplotlib.use("Qt5Agg")
from matplotlib import rc
rc("text", usetex=True)
matplotlib.rcParams["pdf.fonttype"] = 42
matplotlib.rcParams["ps.fonttype"] = 42
import sys
from pathlib import Path
from collections import OrderedDict
import datetime
... |
d9197a9b5d4df532ac8d7f2b8e5288cd77a43abb2f15e096974a8f2b2f471e87 | Python | 6,845 | 212 |
import numpy as np
import pandas as pd
from matplotlib.colors import to_rgba, to_rgba_array
import pytest
from numpy.testing import assert_array_equal
from seaborn._core.plot import Plot
from seaborn._marks.bar import Bar, Bars
class TestBar:
def plot_bars(self, variables, mark_kws, layer_kws):
p = P... |
08b0ff4627d9302d8cc68fa54caf43101c4792e2f967ba82c0750e604ea4bb4b | Python | 6,847 | 171 | import re
import shutil # for removing and creating folders
from pathlib import Path
# import genomic_benchmarks.utils.datasets as datasets
import pandas as pd
from genomic_benchmarks.utils.datasets import (
_check_dataset_existence,
_download_url,
_fastagz2dict,
_get_dataset_name,
_get_reference_... |
8a73c53b80c8ed88149bdd53b054de17e7a7f0acb5f9fc1ba5b43d5f4c81563f | Python | 6,847 | 176 | """ Translation main class """
from __future__ import unicode_literals, print_function
import torch
from onmt.inputters.text_dataset import TextMultiField
from onmt.utils.alignment import build_align_pharaoh
class TranslationBuilder(object):
"""
Build a word-based translation from the batch output
of tra... |
5c7428c0eac1e958e46598d07b455cdddeca1141460d45ee99c787254786e1fe | Python | 6,849 | 208 | #!/usr/bin/env python
"""Train models."""
import os
import signal
import torch
import onmt.opts as opts
import onmt.utils.distributed
from onmt.utils.misc import set_random_seed
from onmt.utils.logging import init_logger, logger
from onmt.train_single import main as single_main
from onmt.utils.parse import ArgumentPa... |
8b9e3014487c6a3860b7d8b5b5e659b8d0a6c291744287dc929ef7e91fabdbf0 | Python | 6,849 | 202 | # Copyright (c) OpenMMLab. All rights reserved.
import random
import warnings
import numpy as np
import torch
import torch.distributed as dist
from mmcv.parallel import MMDataParallel, MMDistributedDataParallel
from mmcv.runner import (DistSamplerSeedHook, build_optimizer, build_runner,
get_di... |
a8642c917bb9249707dea8a4cacbf14013dfaeafb0efe462bf0bf4f1af3ba97f | Python | 6,850 | 188 | from ray.rllib.env.multi_agent_env import MultiAgentEnv
from ray.tune.registry import register_env
import random
from gym.spaces import Discrete, Box, Dict
import copy
import numpy as np
from open_spiel.python.rl_environment import TimeStep, Environment
from mprl.rl.envs.opnspl.valid_actions_mask_env import ValidAction... |
0ede6fe4676e9c223c009c132ef0f17543fd8265c3f53ef0b75a5f563785aa56 | Python | 6,853 | 195 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from collections import namedtuple
import numpy as np
import logging
from ray.rllib.utils.annotations import override
from ray.rllib.policy.policy import Policy
from ray.rllib.models.catalog import ModelCatalo... |
dffa2fe7e376a01ceba184a9a550d52d3ac84616a7c7a5763abb0e46c457cec2 | Python | 6,855 | 169 | # -*-coding:utf-8-*-
import torch
import torch.nn as nn
import torch.nn.init as init
import torch.nn.functional as F
from torch.autograd import Variable
import math
import sys
import numpy as np
import os
def conv3x3(in_planes, out_planes, stride=1):
return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=... |
c7d2fc5e493a6b9a2ae3f58cf416528afbc03185e8f50b614aeab559dee72880 | Python | 6,856 | 207 | """
This scripts generates figure 3c : Example Choice neuron
"""
import pandas as pd
import pickle as pkl
import numpy as np
import os
import glob
import matplotlib.pyplot as plt
import matplotlib as mpl
from tqdm import tqdm
# Plotting
import sciplotlib.polish as splpolish
import sciplotlib.style as splstyle
imp... |
d479f3604c0373f128be3030dba9ee76aa3b205604805a33a2db7b0bbdbdae24 | Python | 6,857 | 206 | """
This scripts generates figure 3b : Example Visual R-L neuron
"""
import pandas as pd
import pickle as pkl
import numpy as np
import os
import glob
import matplotlib.pyplot as plt
import matplotlib as mpl
from tqdm import tqdm
# Plotting
import sciplotlib.polish as splpolish
import sciplotlib.style as splstyle
... |
276b4ab9b47f3369fd104423e4033b796b45388f167dc0349d412f3a34242e93 | Python | 6,858 | 202 | import torch
import torch.nn as nn
from torch import Tensor
from torch.nn.parameter import Parameter
from spikingjelly.clock_driven import neuron, layer
from .blocks import SeparableSEWResBlock
###############
### SCALING ###
###############
class MultiplyBy(nn.Module):
def __init__(self, scale_value: float... |
ad4affa5a0549239fba763eabaa2b12b231f6337114534062aa2df08b6b3afe9 | Python | 6,858 | 216 | """
Test synaptic connections between two different cell types.
usage: test_synapses.py [-h] [-t {simple,multisite}] [-c]
{sgc,tstellate,dstellate,tuberculoventral}
{bushy,tstellate,dstellate,octopus,tuberculoventral,pyramidal}
Compute AN only PSTH in postsynaptic cell... |
2c95206b17d532a2b1aedc2fd0c1cc8c50cf487f40ce7c8ba13bd4eec22dcac8 | Python | 6,861 | 213 | import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_array_equal, assert_array_almost_equal
from seaborn._core.groupby import GroupBy
from seaborn._stats.density import KDE, _no_scipy
from seaborn._compat import groupby_apply_include_groups
class TestKDE:
@pytest.fixture
de... |
b757f6d4bd4aebb8b8f1ce5c2509d8b8d251d9e976b7e9f6ced91e75590a6316 | Python | 6,861 | 207 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""Build and export compressed pt_expt inference models."""
import logging
from typing import (
TYPE_CHECKING,
)
from deepmd.pt_expt.utils.serialization import (
deserialize_to_file,
serialize_from_file,
)
if TYPE_CHECKING:
from deepmd.pt_expt.model.model ... |
65c136b49b271a2e0961809d0ad926fe55a1a32aa4fd06fad79353bc1bc77be9 | Python | 6,862 | 207 | """
This scripts generates figure 3c : Example Auditory R-L neuron
"""
import pandas as pd
import pickle as pkl
import numpy as np
import os
import glob
import matplotlib.pyplot as plt
import matplotlib as mpl
from tqdm import tqdm
# Plotting
import sciplotlib.polish as splpolish
import sciplotlib.style as splstyle... |
48f5db1609c84354a7f1a9b935f2ec8a8bc618c4fc075c9f2159dc3cb6ecbd54 | Python | 6,865 | 164 | # coding: utf-8
from itertools import chain, starmap
from collections import Counter
import torch
from torchtext.data import Dataset as TorchtextDataset
from torchtext.data import Example
from torchtext.vocab import Vocab
def _join_dicts(*args):
"""
Args:
dictionaries with disjoint keys.
Return... |
490255da405f80cbb57365f6bcda73bf644fc8dcc61a5985800a122a6b2c2c25 | Python | 6,865 | 167 | from __future__ import division
import os
import pandas as pd
import numpy as np
from helper_lib import filelib
from SPHARM.classes.surface import Surface
from SPHARM.classes.moving_surface import MovingSurface
from SPHARM.lib import transformation as tr
def compute_spharm(**kwargs):
"""
Compute spherical ha... |
e456d8c3daaeeb77428065bfb8d34135805868c5fa7529d7839cd050464659e9 | Python | 6,865 | 120 | """
Convert to h5 utility.
Sample command to create new dataset
- python3 utils/convert_h5.py -dd /home/masterthesis/shayan/nas_drive/Data_Neuro/OASISchallenge/FS -ld /home/masterthesis/shayan/nas_drive/Data_Neuro/OASISchallenge -trv datasets/train_volumes.txt -tev datasets/test_volumes.txt -id MALC -rc Neo -o COR -df ... |
4f015cc66d429dcc8044d484136909a830f0cdcff15017e14ce0f4bf32652d25 | Python | 6,871 | 198 | """BOSS classifier, from pyts."""
# copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
__all__ = ["BOSSVSClassifierPyts"]
from sktime.base.adapters._pyts import _PytsAdapter
from sktime.classification.base import BaseClassifier
class BOSSVSClassifierPyts(_PytsAdapter, BaseClassifier):
"""Bag... |
fb78552ed28e2ecbf758a93b9cdbfea6d407f4bb721ebb73a036a0374b98e722 | Python | 6,873 | 168 | import argparse
import os, sys, pickle
from datetime import datetime
from math import inf, log, log2, exp, ceil
import torch
from torch.utils.data import DataLoader
import torch.optim as optim
import torch.optim.lr_scheduler as sched
from cormorant.engine.args import setup_shared_args, BoolArg, Range
import logging
... |
654aeb7bb05f37b560f4537bf88209599132b4bcb18ce67f70a32d0d45bd9efe | Python | 6,877 | 212 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Creates Figure 3 from Wang et al. (2023) Temporal stability of intracranial EEG
abnormality maps for localizing epileptogenic tissue.
Calculates time-varying D_RS from abnormalities before plotting.
Gabrielle M. Schroeder
CNNP Lab, Newcastle University
May 2023
"""
... |
585ff47f16543ad7438b3eac6827290561f3dec45a8081efbaeeedfd6c7734fe | Python | 6,885 | 252 | """This module implements spectral weighting filters for the sound pressure level (SPL)
in air according to [IEC-61672]_. Spectral weighting is part of aucoustic measurements.
It is used by sound level meters for example. The weighting functions are derived
from different equal loudness contours of human hearing. The w... |
8aad30fc8068930b792966bc82a59b1a68e5e2f28d7b15e2bc3f526c7856a0a1 | Python | 6,887 | 206 | """Forecasting Datasets."""
__author__ = ["jgyasu"]
__all__ = ["ForecastingData"]
import warnings
from inspect import signature
import pandas as pd
from sktime.datasets import load_forecastingdata
from sktime.datasets.base._base import InvalidSetError
from sktime.datasets.forecasting._base import BaseForecastingDat... |
ccf0be6f0318edf7c0149ca6435374dc78d0e088b4eb89dfc7e7e43882a7680e | Python | 6,891 | 226 | #!/usr/bin/env python
import click
from click_option_group import optgroup
import json
import numpy as np
import os
import pandas as pd
from sklearn.metrics import average_precision_score, roc_auc_score
import sys
sys.path.insert(0, os.path.join(os.path.abspath(os.path.dirname(sys.argv[0])),
... |
f00abafd9a837f5b841cd958958dfb925d53348de63ebd657e6473eb170d693a | Python | 6,894 | 186 | #!/usr/bin/env python3
# Copyright (C) 2019 Christoph Gorgulla
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# This file is part of VirtualFlow.
#
# VirtualFlow is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the ... |
c13c1f84466033dc053416c444f9ff009d23c970ce7beb2ccc3de214850669c2 | Python | 6,897 | 233 | from __future__ import division
import os
import numpy as np
import pandas as pd
from skimage import io
import warnings
from multiprocessing import Process
import time
import sys
def _print_progress(procdone, totproc, start):
donepercent = procdone*100/totproc
elapse = time.time() - start
tottime = totp... |
c8d97d1188810e4057afae08ef4a03ab2ff137633e906b91dd04422760ab9672 | Python | 6,898 | 142 | import pickle
import numpy as np
def get_data(config):
print('Reading data')
if config.transfer_learning:
dir_path = f'../DeepCRISTL2/data/{config.pre_train_data}/' # TODO - use tl data
conf = False
else:
dir_path = f'../DeepCRISTL2/data/pre_train/{config.pre_train_data}/'
... |
53d70f692d22e31787abaa4442753b717a1707bbaf093e823f778cdb8e497816 | Python | 6,906 | 194 | # -*- coding: utf-8 -*-
from functools import partial
import six
import torch
from torchtext.data import Field, RawField
from onmt.inputters.datareader_base import DataReaderBase
class TextDataReader(DataReaderBase):
def read(self, sequences, side, _dir=None):
"""Read text data from disk.
Args:... |
f8f200fcb8ab1e2df024200427a42ce2b185ef34168d697bf08ad5e8ae7ae23f | Python | 6,910 | 232 | #!/usr/bin/env python
import click
from click_option_group import optgroup
from functools import partial
import json
from multiprocessing import Pool
import numpy as np
import os
import pandas as pd
from pandas.errors import EmptyDataError
import sys
sys.path.insert(0, os.path.join(os.path.dirname(sys.argv[0]), os.par... |
829bbb164e77cdec37b4bd832661adbabbb4112ecc20e279c58d8607cae354b2 | Python | 6,912 | 187 | """evaluate_precipitation.py"""
"""
Author: Yimin Yang
Last revision date: Jan 18, 2022
Function: Run this to evaluate the trained model
Ref: https://github.com/HansBambel/SmaAt-UNet
"""
import torch
from torch import nn
import numpy as np
import os
import pickle
from tqdm import tqdm
from Models.AA_TransUNet import ... |
e5419b55daa991148790615ae2616e148e7d241588c73e6a0426bd128d341655 | Python | 6,914 | 214 | import os.path
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import networkx as nx
import pyvista
# from VesselGen.utils.graph_modelling import *
from collections import OrderedDict
from VesselGen.preprocessing.read_to_networkx import VtkNetwork
from matplotlib import rc... |
bf46ab931ed400ab562386749f9f8ed05007cd34ccb93ad940a3c2b465b8f211 | Python | 6,915 | 191 | from __future__ import annotations # for ArrayLike type in docs
from typing import Dict, Union, Tuple
from numpy.typing import ArrayLike
import numpy as np
# for calculating jet features quickly,
# TODO: replace with vector library when summing over axis feature is implemented
import awkward as ak
from coffea.nanoev... |
5014e0a96126d0495017348796a4b8297af961b4d22c7ee75972a3ca7e41d0f3 | Python | 6,917 | 174 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import json
import tensorflow.compat.v1 as tf
import internals.modeling as modeling
from tensorflow.python.framework.ops import disable_eager_execution
disable_eager_execution()
flags = tf.flags
... |
c32c1eaddf424e5efaca4d0e10a7717aca1788be9406efddc4946f58619ec2ff | Python | 6,917 | 244 | # Copyright 2026 DeepMind Technologies Limited
#
# 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 applicable law or agr... |
5421f4156343a3c6f8ac43b5e466a248ff94e820ab4710c9521a573be3166c45 | Python | 6,918 | 212 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 applicable law or agr... |
028a93e2b52a73bb9ebd71f7f6b21c8babb3ce11ba75d32ea93407fda9cac998 | Python | 6,919 | 178 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
'''
Unittests for starting a job
'''
import unittest
from openbabel import openbabel
from src import JobConfig
from src.gaapi import operator_types
from src.gaapi import generators
from src.gaapi import Individual
import main as main_program
import shutil
import os
fr... |
701dcbe9e46e2f75c62b9d185e41df4c496fec9e856467c3f4cac3d371fed906 | Python | 6,924 | 248 | """
Toolbox for simulating compositional data from ScRNA-seq
This toolbox provides data generation and modelling solutions for compositional data with different specifications.
This data might e.g. come from scRNA-seq experiments.
The covariates are represented by ``X``, the cell count matrix is denoted ``Y``.
To sta... |
5978f33c321008755e118f6897c2384d8152d28079217bed21bf54146e1ce1a9 | Python | 6,926 | 186 | import os
import os.path as osp
import shutil
import sys
import warnings
from setuptools import find_packages, setup
def readme():
with open('README.md', encoding='utf-8') as f:
content = f.read()
return content
def get_version():
version_file = 'mmcls/version.py'
with open(version_file, 'r'... |
ee834b9de8bcc4a0eb867f9588f1c5b96f54380fcdc5d30aee6ed460f30aabd7 | Python | 6,926 | 136 | import torch
import torch.nn as nn
from cormorant.models import CormorantAtomLevel, CormorantEdgeLevel
from cormorant.nn import MaskLevel, DotMatrix
from cormorant.nn import CatMixReps
from cormorant.cg_lib import CGProduct, CGModule
import logging
class ENN(CGModule):
"""Base equivariant neural network archit... |
4d14d886eed3ee13aa0ef861bf2792c9d2f250e0e5db0aaf0b24f3fb1f202d91 | Python | 6,929 | 199 | # Copyright 2026 DeepMind Technologies Limited
#
# 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 applicable law or agr... |
c4e0570ba1f9536d9f363bf22a181c850214248f4d248d94dec2557df5408d53 | Python | 6,929 | 209 | # Copyright 2026 DeepMind Technologies Limited
#
# 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 applicable law or agr... |
0bf85eece4559c6c08855bcc64a9c3ce31a57dba47e04ae1ac7559fbce23f3be | Python | 6,931 | 206 | # Copyright 2019-2020 The ASReview Authors. All Rights Reserved.
#
# 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 appl... |
2c6525b8599ec1d727ca39ef87dcda35f5fbcfc9547c6777c92e7c2089b4bcc7 | Python | 6,935 | 212 | # Copyright 2019 DeepMind Technologies Ltd. All rights reserved.
#
# 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 appl... |
559a01ccd710c29424084b39d55eed38814bd28bfee379dceb69ed37720f3c5e | Python | 6,935 | 199 | # Copyright 2019 DeepMind Technologies Ltd. All rights reserved.
#
# 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 appl... |
abb2b1edce5676dadd77ab48d1e3cb4652da66461a87fc63efccf5cddcf9b4f2 | Python | 6,937 | 198 | from __future__ import annotations
import functools
import textwrap
from typing import Any
from typing import TYPE_CHECKING
from typing import TypeVar
import warnings
from packaging import version
from optuna._experimental import _get_docstring_indent
from optuna._experimental import _validate_version
if TYPE_CHEC... |
a52bfef5dba8395b963793f3bb59e88869c78aa6a3c91e3215378469944f2dc8 | Python | 6,939 | 169 | """Benchmarking for classification estimators."""
__author__ = ["jgyasu"]
__all__ = ["ClassificationBenchmark"]
from collections.abc import Callable
from typing import Any
from sktime.benchmarking._benchmarking_dataclasses import (
FoldResults,
TaskObject,
)
from sktime.benchmarking.benchmarks import (
B... |
236eb6656c82f055edf11d27d0d4e0eb06a9e4f16b110d42c4f4961756535df2 | Python | 6,942 | 83 | """
Data structures for model_run
XM13 with cooperative nacn channels
XM13A: reduce channel density to match input resistance with more complex
cells from SBEM data (original densities were based on soma-alone assumption)
"""
ChannelData = u"""
This table describes the REFERENCE ion channel densities (and voltag... |
07854246013a32990bc9be2ffd9a0c2e7e53f5a3e80fc4f9a81191b4aee80e92 | Python | 6,943 | 189 | # Copyright (C) 2022-2025 Shijiazhuang Xianyu Digital Biotechnology Co., Ltd
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 of the License, or
# (at your option) any la... |
8159315d82aae07b4028bf5701281d9c8795cd263f512c99525d708b7793e63f | Python | 6,947 | 266 | # -*- coding: utf-8 -*-
"""
Created on Tue Oct 25 20:39:04 2016
@author: daniel
"""
#from math import sqrt
results_directory = './results'
#-----------------------------------------------------------#
# 1. General recording and simulation parameters #
#------------------------------------------------------... |
d0cd97a131c6a45f3d2ff3781868355dc00fd0328521d6cf2b537757a5be1414 | Python | 6,947 | 170 | import numpy as np
import torch
from transformers import BertTokenizer, BertModel, logging
from Bio import SeqIO
import time
import pandas as pd
import tqdm
import scipy
import pickle
def embed_proteins(species_dict,
model_path="Rostlab/prot_bert",
max_length=2500, # truncate se... |
2f6088979efe3be9324a1bc4df880da9fbcd5674e66fa2a0a77da939bebbcbd8 | Python | 6,948 | 179 | __author__ = ["chrisholder", "TonyBagnall"]
from typing import Any
import numpy as np
from sktime.dists_kernels._numba_distances.base import (
DistanceAlignmentPathCallable,
DistanceCallable,
NumbaDistance,
)
class _ErpDistance(NumbaDistance):
"""Edit distance with real penalty (erp) between two ti... |
dd0a81db9086e22a8f352f48b8750b4684a2a46ad486abdddc3f47d769493cf7 | Python | 6,952 | 165 | import argparse
import shutil
import glob
import os
from multiprocessing import Pool
class DrugScreenSorterTool:
"""
A class to sort images into the right directory structure
for using EmbryoNet in the analysis of images taken in
different wells of multiter plates.
The prerequisites for this scri... |
845151cd5a55c11f48f3a63817cb4c4763c1123af9bde52ee0306618546fff13 | Python | 6,957 | 167 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 applicable law or agr... |
b26e13b5f0b9d64257a19f264b41cf09fd9c6e88b6af1bb141b35bbbed56fe97 | Python | 6,957 | 191 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Mar 7 2023
@author: swcanner
Current settings for B Factor visualization:
`BFactor = 0.0` : Nonbinder
`BFactor = 40.0` : CAPSIF:G Predicted Binder
`BFactor = 59.9` : CAPSIF:V Predicted Binder
`BFactor = 99.9` : CAPSIF:V and CAPSIF:G Predicted Bin... |
91d599861f071c20ae89e4370e8ba0f18df79864f2edf3ec24ecf1deb40834a9 | Python | 6,963 | 203 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 applicable law or agr... |
02a44d8467502d6244a5200a37cd41ad0da4d3d9834c014e0e7ed7c17cd113e2 | Python | 6,964 | 185 | # coding=utf-8
# Copyright (C) 2021. Huawei Technologies Co., Ltd. All rights reserved.
#
# 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
#
# ... |
dd48a250ba1a11733bd9508c5b5db826e6eee8ebfe0152e3c16a3f6787046cce | Python | 6,965 | 173 | # Copyright 2019 DeepMind Technologies Ltd. All rights reserved.
#
# 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 appl... |
8dc552fe94291ab0781393b52bdd5237b30c3e6c144969ae107eb980febb1d9c | Python | 6,967 | 211 | # Copyright 2026 DeepMind Technologies Limited
#
# 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 applicable law or agr... |
eb50fd57735cee142bbc2be433b29a7d2e7df7c55d067815434847238df2f3f1 | Python | 6,968 | 154 | import json
import math
import os
from pathlib import Path
import cv2
import numpy as np
import torch
from vp_suite.utils.utils import most
from vp_suite.base import VPDataset, VPData
from vp_suite.defaults import SETTINGS
class SynpickMovingDataset(VPDataset):
r"""
Dataset class for the Videos of the datas... |
08a5d239629f1897b35fdcaef552fc886567dc7da2f62349455dd504cf5f61b3 | Python | 6,972 | 210 | '''
Replacers are used to modify a population after crossover and mutation have occured
.. codeauthor:: Nicholas Browning
'''
from __future__ import print_function
from __future__ import absolute_import
from builtins import range
import numpy as np
from . import Individual
import pygmo as pg
from src import outproces... |
11cd95914fefa922afd6a6955c67a83d76e31e8e274d75df8569b26627846593 | Python | 6,973 | 175 | # Functions for sampling points from a 2D segmented image
import os
import warnings
from typing import List, Iterator, Tuple
import numpy as np
import numpy.typing as npt
from skimage import measure
import tifffile
from scipy.spatial.distance import pdist
import itertools as it
from pathos.pools import Proces... |
00c1c3c443836fc8ed639850676025318d3f9b79279b96b77256af09b756985b | Python | 6,974 | 197 | # Copyright 2022 DeepMind Technologies Limited
#
# 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 applicable law or agr... |
911756b3599b79f62012bdda726710d9aa844098e30cfb6a43a4d1fce7faae60 | Python | 6,977 | 220 | import os
import copy
import time
import math
import random
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.metrics import auc, precision_score, classification_report, plot_confusion_matrix, f1_score, confusion_matrix
from sklear... |
293b1d5dc9ffd4075afd66b59b736acffc78bc9329c4666bfcda88b3a68bafe7 | Python | 6,979 | 154 | import numpy as np
import torch
from torchvision.datasets import MNIST
from vp_suite.base import VPDataset, VPData
from vp_suite.defaults import SETTINGS
class MovingMNISTOnTheFly(VPDataset):
r"""
Dataset class for the dataset "Moving MNIST", as firstly encountered in
"Unsupervised Learning of Video Repr... |
38dc705c95358bef2f5060f9acd32d77a7c97aa53231d8cdbc8b21445c4ad2ff | Python | 6,981 | 178 | # BASILISK: A generative, probabilistic model of side chains in proteins
#
# Copyright (C) 2010 Tim Harder and Jes Frellsen
#
# BASILISK is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 ... |
c946a559c2c6664353a9b1a4626136746554acd7b6eaf11d585e709af7b1adff | Python | 6,982 | 224 | import numpy as np
import seaborn as sns
from matplotlib import patches
import matplotlib.pyplot as plt
from scipy.signal import gaussian
from scipy.spatial import distance
XY_CACHE = {}
STATIC_DIR = "_static"
plt.rcParams["savefig.dpi"] = 300
def poisson_disc_sample(array_radius, pad_radius, candidates=100, d=2, ... |
c4c514a1b0ff4f147199930bf4d4aa33feedde4f5a1474717301cdebfa05a597 | Python | 6,984 | 210 | import torch
import torch.nn as nn
from torchvision import datasets
from torchvision import transforms
import numpy as np
import torch.nn.functional as F
import torch.optim as optim
import sys
class ConvBlock(nn.Module):
def __init__(self, in_channels, out_channels, kernel_width, stride=1, pool_size=0):
... |
aa901eb858d5b5d5c55a7974630c7d249ce19c0115474d799ba78e8d44a51570 | Python | 6,986 | 181 | #!/usr/bin/env python
from __future__ import print_function
import sys,os
import re
import argparse
import logging
from collections import OrderedDict
# 3rd party
from intervaltree import Interval, IntervalTree
desc = 'Adding "contigs_report_contigs_filtered.mis_contigs.info" to feature table'
epi = """DESCRIPTION:
Ad... |
ef231ed335aea809c3e3045ead370144c6d546bdcb5c61759f7cbf0c1cbc1be9 | Python | 6,988 | 196 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 applicable law or agr... |
24275d5a941a3a8c8ee18f28075ef236ce9bbf6b53a001c1ee137a0ec6b54315 | Python | 6,989 | 261 | """
snapshot_comparison.py
This module performs learning rotations with different cue
conditions to determine effects on the R to E-PG mapping.
"""
import argparse
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
from extended_ring_model import *
from dic... |
4d0cb5f1d6ce7c5b8e4bab2241ec25ccd951e1f4da7f9b001dc79f8f08561568 | Python | 6,991 | 221 | #!/usr/bin/env python3
from pathlib import Path
import rdflib
from pyontutils.utils import rowParse, relative_path
from pyontutils.namespaces import ilxtr
from neurondm.lang import *
from neurondm.phenotype_namespaces import BBP
class NeuronMarkram2015(NeuronEBM):
owlClass = ilxtr.NeuronMarkram2015
shortname... |
4c2b0a32bdcc2c4f1af51e16889985d8b9b6bacba860d61c70c843f9f05e2ab0 | Python | 7,004 | 229 | """
Implements bootstrap-based inference methods for model given in
Urban et al. (2023)
Implements methods for performing nonparametric bootstrap as well as
parametric likelihood-ratio bootstrap for various inferential objects
of interest.
"""
from multiprocessing import Pool
from functools import partial
import num... |
5fe6029eef5ed1a90bca2ebd4f7b8b36bcbc6e46bdb9a632a97410b301a463d4 | Python | 7,004 | 208 | # coding=utf-8
# Copyright (C) 2021. Huawei Technologies Co., Ltd. All rights reserved.
#
# 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
#
# ... |
c8ad7d02fe2813acf9b91792400fc75102b0f90846917efda4047e479c3654ad | Python | 7,007 | 215 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 applicable law or agr... |
19e547e13f95c5c4eaaf9289acdf8106ae75ffab09ff9f274bb2a71349db567e | Python | 7,010 | 223 | # Copyright 2019-2021 The ASReview Authors. All Rights Reserved.
#
# 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 appl... |
bedf2422369afb2798329aff3e880a63da0e104908087b623e3da34b18ee3674 | Python | 7,012 | 227 | from __future__ import print_function
from itertools import repeat
import collections
import math
import torch
import torch.nn as nn
from torch.nn import functional as F
__all__ = ['Model']
WIDTH = [16,32,64,128,256,512]
def _ntuple(n):
"""
Copied from the PyTorch source code (https://github.com/pytorch)... |
f7654d31bd01a418f95a72008cc09e74d25c654d7aef8490001ea636fc529cad | Python | 7,013 | 187 | import os
import sys
import matplotlib.pyplot as plt
import torch
from torch.utils import data
from flow_solver import *
from update_surface_shape import *
cwd = os.getcwd()
def build_dt(n,device):
re = torch.zeros([n,n],device=device)
re[0,:3] = torch.tensor([-1.5,2,-0.5],device=device)
lr... |
ee7aea48c70d0c0ca9aa731622d3163ac002dcfc9f28c5f6cf31bad3de1d4014 | Python | 7,014 | 155 | import os
import sys
import stat
from os.path import join as pjoin, exists as pexists, realpath
import numpy as np
import pickle
import networkx as nx
from neuropredict import run_workflow
from pyradigm import MLDataset
from graynet import parcellate
"""#---------------------------------#-----------------------------... |
44c090ca36b31a9f768ccb9834ea8d21987fed22b0d9a55facaa800c43ffe4b9 | Python | 7,015 | 178 | import logging
from pathlib import Path
from typing import Any, Optional, Union
import torch
import flair.embeddings
import flair.nn
from flair.data import Relation, Sentence
from flair.file_utils import cached_path
log = logging.getLogger("flair")
class RelationExtractor(flair.nn.DefaultClassifier[Sentence, Relat... |
4fe0143e231eb054fab8a21950df39f4ce3ea193651f29eb418022191ee0d993 | Python | 7,018 | 180 | # Copyright 2026 DeepMind Technologies Limited
#
# 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 applicable law or agr... |
fa8d533587008071ca689ff8986c7cdd34a938892f3d7f04016ae5ff20a19f07 | Python | 7,018 | 188 | #!/usr/bin/env python
'''
Example python script using anlffr functions, meant to be called from the
command line. This was originally created to analyze data from a Brainvision
EEG system that was already preprocessed in Matlab. There were three conditions
with two polarities each, stored in files of the form
'subjec... |
10c9b89c3f16f6ba63dd0d0362cd156a8aba0e7b8087ad41d0ff873cb266cb51 | Python | 7,020 | 233 | # coding=utf-8
# Copyright (C) 2021. Huawei Technologies Co., Ltd. All rights reserved.
#
# 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
#
# ... |
a04b715b4717c4ba961c75767e7af9113efe663556da84bc8eeb6b37dfd9692e | Python | 7,025 | 182 | # Copyright (C) 2022-2025 Shijiazhuang Xianyu Digital Biotechnology Co., Ltd
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 of the License, or
# (at your option) any la... |
2a30db78097ba59041ab15f3ec6b6294651ee738abd69a997e0e279abfc4683c | Python | 7,026 | 223 | """NIfTI header inspection utilities (``fslinfo`` / ``fslhd`` / ``fslval`` equivalents)."""
import os
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple
import numpy as np
import nibabel as nib
from bcblib.imaging._types import NiftiLike
from bcblib.imaging.io import load_nifti
# --------... |
00f0eb1876a21d431f40b98c9b2074557a3622d5f9c2968d0d5a69de53feee60 | Python | 7,029 | 133 | import numpy as np
from numba import types, jit, prange
from stratego_env.game.stratego_procedural_impl import _get_state_from_player_perspective, _get_valid_moves_as_1d_mask, \
_get_partially_observable_observation, _get_fully_observable_observation, \
_get_action_1d_index_from_player_perspective, _get_next_s... |
b50d4e581154b07de55846b99082164cc12f2c212a8145caece3e0c3147a9742 | Python | 7,030 | 187 | # Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# 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 applica... |
dface173b235c521d60f2b2c44826fc9f993bdbad48c74fd4608e9fc25c9f967 | Python | 7,030 | 187 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 applicable law or agr... |
a3e691924f0bfd27038fb7aac36cad26c1e6244b9256d2599bd6783d403d21b2 | Python | 7,034 | 196 | # Copyright 2019 DeepMind Technologies Ltd. All rights reserved.
#
# 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 appl... |
c5f438c0a0e90ad6c12b0fcfed665a879e52d5556ecd6d262e8743f6c96dd444 | Python | 7,035 | 157 | """Compute cycle-by-cycle features."""
import warnings
import numpy as np
import pandas as pd
from bycycle.utils.checks import check_param_range
from bycycle.utils.dataframes import drop_samples_df
from bycycle.features.shape import compute_shape_features
from bycycle.features.burst import compute_burst_features
from... |
49c50ecf74c52ee2673c35dcbcc09f3463af6b04273908102da81017b5ed898e | Python | 7,036 | 192 | from __future__ import annotations
import pathlib
import pytest
import optuna
from optuna.artifacts import FileSystemArtifactStore
from optuna.artifacts import get_all_artifact_meta
from optuna.artifacts import upload_artifact
from optuna.artifacts._protocol import ArtifactStore
from optuna.testing.storages import S... |
b924f0dfbc9cbeeb7318bcde7e47c1f9bc2d620e9558726b7739dd27d59032c3 | Python | 7,037 | 202 | import numpy as np
import math
from numba import jit
import os
import hdf5plugin
os.environ["HDF5_PLUGIN_PATH"] = hdf5plugin.PLUGINS_PATH
import h5py
from typing import Dict, Tuple
# CODE BORROWED AND ADAPTED FROM THE DSEC GIT REPOSITORY
# (https://github.com/uzh-rpg/DSEC)
def rectify_events(x: np.ndarray, y: n... |
4ba4e9835a76826bb96f21d5aac5df92e8144ad2ddd45bbde04aac0f380453d1 | Python | 7,047 | 222 | # Copyright 2018-2025
# Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH
# 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/LICE... |
a4dcfb3def06d63e047ff92169a6ac841b5aedd33fbbcda132a83d68e00e9384 | Python | 7,052 | 151 | # SAFE TEAM
#
#
# distributed under license: CC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.txt) #
#
import argparse
import time
import sys, os
import logging
def getLogger(logfile):
logger = logging.getLogger(__name__)
hdlr = logging.FileHandler(logfile)
formatter = logging.... |
bd0cd18fc4ad76b8e84629d0eeec7a03a2039d6ec3e24804cf32dbf9047923d2 | Python | 7,054 | 189 | from matplotlib import colormaps
import matplotlib.cm as cm
import matplotlib.colors as pltcol
import numpy as np
import pandas as pd
def _colorarray_from_string(cmap, ncolors):
"""Get colormap array from string that loops through colors."""
if cmap in pltcol.ColorConverter.colors.keys():
colors = pl... |
4e83c697eea7d4954f54e7540a8bce0bd6528109f2b193b59817b7f1dd0b27d8 | Python | 7,055 | 185 | """
5. Running Bycycle on 3D Arrays
===============================
Compute bycycle features for 3D organizations of timeseries.
Bycycle supports computing the features of 3D signals using :class:`~.BycycleGroup`.
Signals may be organized in a different ways, including (n_participants, n_channels, n_timepoints)
or (n... |
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