sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
e284a6a273401c36bc231978f07eac6093ae19283089f28ac421ca84a25ee7b1 | Python | 3,090 | 116 | import tensorflow as tf
import os
import nibabel as nib
import numpy as np
import random
import re
from skimage.transform import resize
from pathlib import Path
from const import *
def int64_feature(value):
return tf.train.Feature(int64_list=tf.train.Int64List(value=[value]))
def int64_list_feature(value):
... |
f8fcb134952d26c94dfcb6042a9857b9e81010c0b4bc6a2756b4ba3277a610a5 | Python | 3,092 | 58 | ###############################################################################
# This script execute an automated search of all possible combinations of two #
# sets of terms. The search is done in scopus. The script retrieves all scopus#
# results and store them in json files. The search can be updated by changing #
... |
fde19bab4102159fe3c782377afc59a8615aa10bbd520a0b4b8c77d1194d8496 | Python | 3,094 | 101 | """
Tests that work on both the Python and C engines but do not have a
specific classification into the other test modules.
"""
from io import StringIO
import pytest
import pandas as pd
import pandas._testing as tm
@pytest.mark.parametrize(
"data,thousands,decimal",
[
(
"""A|B|C
1|2,334... |
170c73a4cbed88e2161b63cd9e40b29d4c04c2dc9134772f2f240c7e0eef7cb6 | Python | 3,095 | 105 | """
Implementation of DataFrame.filter and Series.filter with a boolean mask.
"""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
Any,
Literal,
)
import numpy as np
from pandas._libs import lib
from pandas.core.dtypes.common import is_bool_dtype
from pandas.core.dtypes.generic im... |
d20e9ded96cdcb3d84172c18ef7099b8dcc4bb0ef15a28cff688398845382cf4 | Python | 3,095 | 106 | """
paq2py
Read PAQ file (from PackIO) into python
Lloyd Russell 2015
"""
import numpy as np
def paq_read(file_path=None, plot=False):
"""
Read PAQ file (from PackIO) into python
Lloyd Russell 2015
Parameters
==========
file_path : str, optional
full path to file to read in. if none i... |
398980b5b97a91812ef3d9c8a27cec7c43cfa84c08562767bb10d182e97d2f9a | Python | 3,096 | 90 | # coding: utf-8
"""Implementation of the 'qc' command.
"""
import logging
from atropos.commands.base import (
BaseCommandRunner, Pipeline, SingleEndPipelineMixin, PairedEndPipelineMixin)
from atropos.commands.stats import (
SingleEndReadStatistics, PairedEndReadStatistics)
from atropos.util import run_interrupt... |
8b66574e2df69953e1ec9ed9f7d71472c861e0901c98cd3557cea519d9cbf8f0 | Python | 3,096 | 52 | #! /usr/bin/env python
import argparse
import os
import pandas as pd
parser = argparse.ArgumentParser(description='Output a BED file of the final ORF ratings generated by rate_regression_output.py')
parser.add_argument('--inbed', default='transcripts.bed', help='Transcriptome BED-file (Default: transcripts.bed)')
par... |
117e329e74ce45f3b2fc5add011a7e8b087f123f63d985225901039fa2e88abd | Python | 3,097 | 79 | # Copyright 2025 Xanadu Quantum Technologies Inc.
# 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 agre... |
4be5aa7d60d5a13c5f30d1adb29028f96458370a953f2c92e8dbacd4d84c3c44 | Python | 3,097 | 96 | import pytest
from pandas.errors import Pandas4Warning
import pandas as pd
import pandas._testing as tm
@pytest.mark.parametrize(
"meth, kwargs",
[
("truncate", {}),
("tz_convert", {"tz": "UTC"}),
("tz_localize", {"tz": "UTC"}),
("infer_objects", {}),
("astype", {"dty... |
01d6496880dc14f0b5722e00a97d942dc9e828376a855a1a0e46819114c5108e | Python | 3,098 | 100 | import numpy as np
import pytest
from pandas._libs.parsers import (
_maybe_upcast,
na_values,
)
import pandas as pd
import pandas._testing as tm
from pandas.core.arrays import (
ArrowStringArray,
BooleanArray,
FloatingArray,
IntegerArray,
)
def test_maybe_upcast(any_real_numpy_dtype):
# ... |
19fd5d1d8570ecda263ced4e7cd0a5361b16053f87cb89b10d5863d728d13ad2 | Python | 3,098 | 53 | import torch
from torchvision import datasets, transforms
import argparse
def setup_cifar10(n_train=40000, n_val=10000, n_test=10000, batch_size=32, data_dir='data'):
transform = transforms.Compose(
[transforms.ToTensor(),
transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))])
train_datase... |
a1c6b0dbff955a5bfbc8b9f327ea2e5ca260efa487fa75ade67514a69cb4abdb | Python | 3,098 | 91 | from datetime import date
import numpy as np
import pytest
from pandas.errors import Pandas4Warning
import pandas as pd
import pandas._testing as tm
class TestAstype:
def test_astype(self):
ci = pd.CategoricalIndex(list("aabbca"), categories=list("cab"), ordered=False)
result = ci.astype(objec... |
5dc48d1871b1fdf5c2a846f7333d432a0b62b176478d89d07da818d60a94e551 | Python | 3,099 | 89 | # Copyright 2018-2021 Xanadu Quantum Technologies Inc.
# 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... |
cebc145e51a623de5de72d2309198ea8e9efff9c6f3f09c9490fb8aa8cd72d66 | Python | 3,099 | 113 | # -*- coding: utf-8 -*-
"""
Created on Mon Nov 9 17:31:36 2020
Port of MATLAB function sequenceness_crosscorr.m
@author: Simon Kern
"""
import numpy as np
from numba import njit
def _corrcoef(*args, **kwargs):
try: # try jax implementation, magnitudes faster
import jax
jax.config.update("jax_... |
91dc06d9c131ec83ab91be1584c1cfc60863bee57568359cdffca0aa4ef13223 | Python | 3,100 | 114 | import numpy as np
def cartesian_to_spherical(r: np.ndarray) -> np.ndarray:
"""
Convert Cartesian coordinates to spherical coorindates.
Parameters
----------
r : numpy.ndarray
Array of Cartesian coordinates x, y, z.
Returns
-------
np.ndarray
Array of spherical coordin... |
005c8087d1a905c5312bce19c16b2fe31f523991e8be838f7a8edffebdf0abe1 | Python | 3,102 | 101 | #MIT License
#
#Copyright (c) 2019 Iñigo Prada Luengo
#
#Permission is hereby granted, free of charge, to any person obtaining a copy
#of this software and associated documentation files (the "Software"), to deal
#in the Software without restriction, including without limitation the rights
#to use, copy, modify, merge,... |
536c6ac8d609372aeb05637b201d0f0bb16869710e1adc0ad59b6e0b41a0565b | Python | 3,102 | 90 | __all__ = ["PeptideMS2Predictor"]
import itertools
import os
from logging import Logger
from typing import Any, Iterable, List, Mapping, Optional, Union
import pandas as pd
import torch
from ....speclib.pep.spec import PeptideMS2Spectrum
from ....util.progress import ProgressFactoryProto
from ...common.prediction im... |
5579f73f495ad9a58eb94e092915f56531a810cde7390e3e59c08bb5c8585550 | Python | 3,102 | 128 | # %%
from pathlib import Path
import pandas as pd
from julearn.model_selection import RepeatedContinuousStratifiedKFold
from julearn.pipeline import PipelineCreator
from julearn.utils import configure_logging
from sklearn.gaussian_process.kernels import RBF
# Needs to install skrvm
# pip install https://github.com/Ja... |
9c6f1c48813a5bdc8b9cb8fe862e2bd18de09b78db38cac0b01a51f064a3467f | Python | 3,103 | 96 | import numpy as np
import pandas as pd
import pandas._testing as tm
class TestValueCounts:
# GH#7735
def test_value_counts_unique_datetimeindex(self, tz_naive_fixture):
tz = tz_naive_fixture
orig = pd.date_range("2011-01-01 09:00", freq="h", periods=10, tz=tz)
self._check_value_count... |
374be61817b6728a79e662e0c13b2cfd5cc81a40d8256ab3da0cc6cdd52634e6 | Python | 3,105 | 70 | """Inati method for coil sensitivity map calculation."""
import torch
from einops import einsum
from mrpro.data.SpatialDimension import SpatialDimension
from mrpro.utils.sliding_window import sliding_window
def inati(
coil_img: torch.Tensor,
smoothing_width: SpatialDimension[int] | int,
) -> torch.Tensor:
... |
82a9223f79e80bb6128b237f21a0cdd2ce1fdf8a23c2cbd963434a97e6f7bffc | Python | 3,105 | 80 | import tensorflow as tf
def network1(config, n_celltypes, n_features, training=False):
"""
Creates network from config file (config), number of celltypes (n_celltypes)
"""
model = tf.keras.Sequential()
for l in range(config["n_hidden_layers"]):
# model.add(tf.keras.layers.Dense(config["hid... |
b3fd00a5958a4160ebed7088dddeed7c54313ce5c931ba2ff17d5df56f2fa55f | Python | 3,105 | 75 | import pathlib
import importlib.resources
import numpy as np
from PyQt6 import QtCore, QtWidgets
class KeyValueTableWidget(QtWidgets.QTableWidget):
def __init__(self, *args, **kwargs):
"""A table widgets with two columns for key-value visualization"""
super(KeyValueTableWidget, self).__init__(*ar... |
d853f53e91287cb3c0d54ea3d96c8720ff4671070c282083bc4a2ae894fe153e | Python | 3,106 | 115 | import numpy as np
class NeuroScanMessage():
def __init__(self) -> None:
# 初始化，定义各种请求类型
self.initial()
def initial(self):
# infoType
self.InfoType = dict(
InfoType_Version = 1,
InfoType_BasicInfo = 2,
InfoType_ChannelInfo = 4... |
a004918405fdd200f4aba0cde05486a9dbe7ef88d178190aabd8e53bdb04584d | Python | 3,116 | 65 | from botocore.client import Config
import ibm_boto3
import os
import sys
from pathlib import Path
# from shutil import copyfile
# from tqdm import tqdm
# import tensorflow as tf
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__fi... |
37207a9a3f582759e92f1c5a5b02aec7367a557d09756e99059b1848aae623e9 | Python | 3,118 | 96 | """Radial phase encoding (RPE) trajectory class with sunflower pattern."""
import numpy as np
import torch
from mrpro.data.KTrajectory import KTrajectory
from mrpro.data.traj_calculators.KTrajectoryCalculator import KTrajectoryCalculator
from mrpro.utils.reshape import unsqueeze_tensors_left
GOLDEN_RATIO = 0.5 * (5*... |
bc970637174ab25f62688be16201c4ff11b469301733daffb24d55e99b4bb5c2 | Python | 3,119 | 78 | """Regression tests for the 2.0 release-blocker batch (silent-wrong-behavior
class): seed 0, legacy seq_len, SAC multi_gpu guard, adaptive-LR resume."""
import copy
import numpy as np
import pytest
import torch
from rl_games.torch_runner import Runner
from tests.test_critical_fixes import (_load_params, CARTPOLE_YAM... |
78b1915926d9bd8a36fdf9ac2a8112b79e232c400e0f294fac38aa140decfa8a | Python | 3,120 | 111 | # py3
import sys
import os
import pysam
import pybedtools
from pybedtools import BedTool
#print len(sys.argv)
if len(sys.argv) != 5:
sys.exit('Usage: python sc_atac_readcounter.py [Input Bam file] [Input Index table (NA if no table)] [peak BED] [Output file]')
inputbam = sys.argv[1]
indextable = sys.argv[2]
type1bed... |
f3dac8b2b5fe70a70853084656aa3ecd24770cab76d65f3801f0ea2c2509e729 | Python | 3,120 | 132 | """
This script demonstrates
* the rationale of locally low rank regularization for DWIs.
Author: Zhengguo Tan <zhengguo.tan@gmail.com>
"""
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Circle, Rectangle
import sigpy as sp
from sigpy import linop, util
import h5py
import os
DIR... |
370007db7651e32e810ffe76ee4cd2b64952d581ffa0d829f92097903666cb1a | Python | 3,121 | 91 | """support pyarrow compatibility across versions"""
from __future__ import annotations
import sys
from typing import Any
from pandas.util.version import Version
PYARROW_MIN_VERSION = "16.0.0"
try:
import pyarrow as pa
_palv = Version(Version(pa.__version__).base_version)
pa_version_under17p0 = _palv < ... |
961409734f0d827cf4efcacf000120809d63e8e63d5c3372ffa45cf61fc3a42b | Python | 3,122 | 74 | from training import *
from training.label_processor import process_labels
from utilities.utilities import *
if __name__ == "__main__":
data_create = sys.argv[1]
add_suffix = sys.argv[2]
normal = sys.argv[3] == "True"
nb_examples = None
if len(sys.argv) > 4:
nb_examples = int(sys.argv[4])... |
d53903c593e780e3e1d9387bcd9bb262bed664d095e55b4bd2b9b7e9a55411b7 | Python | 3,122 | 90 | import json
import os
import struct
import sys
import traceback
import urllib.request
from dclab.external.packaging import parse as parse_version
from PyQt6 import QtCore
class UpdateWorker(QtCore.QObject):
finished = QtCore.pyqtSignal()
data_ready = QtCore.pyqtSignal(dict)
@QtCore.pyqtSlot(str, str)
... |
d5e9c3b45177794cc79e032fc0ddf285d55fca69228a3684e1bd45c03aa6ad06 | Python | 3,123 | 107 | import os
import random
import numpy as np
import pandas as pd
import tensorflow as tf
from sklearn.metrics import mean_squared_error as mse
def rmse_fn(x, y):
return mse(x, y, squared=False)
def pcor(x, y):
return np.corrcoef(x, y)[0][1]
def ccc_fn(y_true, y_pred):
cor = np.corrcoef(y_true, y_pred)[0... |
b118da0b8c0f65eb482ddc1577c8a48428dbf2734da21efbf4c821d610c8460b | Python | 3,124 | 43 | import numpy as np
np.random.seed(26)
import os, torch
basedir = os.path.abspath(os.path.dirname(__file__))
os.chdir(basedir)
file_path = os.path.abspath(os.path.join(basedir, 'literature_data'))
data_path = os.path.abspath(os.path.join(basedir, 'data'))
# 1. drug_disease
drug_disease_co = torch.Tensor(np.loadtxt(os... |
6c823ef9f7098830f805309b679324c0c5ff4de326be7320fa75b352e9575287 | Python | 3,125 | 98 | """
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
import logging
import os
from ocpmodels.common.registry import registry
from ocpmodels.trainers.forces_trainer import ForcesTrainer
class ... |
465688bbfcf2af433d875c42fb1113069120c258c669b026ae0762ef0feea8f0 | Python | 3,126 | 116 | """
Tests that work on both the Python and C engines but do not have a
specific classification into the other test modules.
"""
import csv
from io import StringIO
import pytest
import pandas as pd
import pandas._testing as tm
from pandas.io.parsers import TextParser
xfail_pyarrow = pytest.mark.usefixtures("pyarrow... |
8f402cfa54d2035a6654b433ab24cba481109dbd9a1a2893795581afe28826b4 | Python | 3,129 | 72 | """Tests the conjugate gradient operator."""
import torch
from mrpro.operators import ConjugateGradientOp, EinsumOp, LinearOperatorMatrix
from mrpro.utils import RandomGenerator
def random_linearop(size: tuple[int, int], rng: RandomGenerator):
"""Create a random LinearOperator."""
return EinsumOp(rng.complex... |
914c6fb78fa5d5aa9d9dcfdceb03c220cfa95c928d3f0e64d1f7fdc3377efc6b | Python | 3,129 | 86 | from datetime import (
datetime,
timedelta,
)
import pytest
from pandas._libs.tslibs.timezones import dateutil_gettz as gettz
import pandas.util._test_decorators as td
import pandas as pd
import pandas._testing as tm
class TestTimestampToPyDatetime:
def test_to_pydatetime_fold(self):
# GH#45087... |
75f804c87065b7d3964b9c09a791e8b57610036f9657b6b5f641c852c795ac18 | Python | 3,131 | 52 | from botocore.client import Config
import ibm_boto3
# import types
import os
import sys
import pdb
import pandas as pd
import numpy as np
import pickle
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from ... |
fbcd3bef950d0d7bc6aa65f96b03b76b3e67e9378d68fee20b810b8f87beca18 | Python | 3,131 | 95 | import sys
sys.path.append('.')
from CommonSystem.Config import Config
from EventController import EventController
from tqdm import tqdm
from psychopy import event, visual, core
import os
import time
config = Config()
config.addSTI = 'StimulationSystem/pics'
config.addTG = 'StimulationSystem/target/green_... |
f50196dc63c6c78cd6cd37e1d84adaef1a30090ec910ffa8b08d99eb9aa7348c | Python | 3,132 | 94 | import operator
import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
class TestMatMul:
def test_matmul(self):
# matmul test is for GH#10259
a = pd.DataFrame(
np.random.default_rng(2).standard_normal((3, 4)),
index=["a", "b", "c"],
... |
85d746a3f5192c4e5dd0c12b2aee2c59e815ff9a93025aa0a8a4402933b787bf | Python | 3,133 | 100 | from tests import TestCaseNeSVoR
from nesvor.svr.registration import VolumeToVolumeRegistration
from nesvor.image import Volume
from nesvor.transform import RigidTransform
from tests.phantom3d import phantom3d
from nesvor.utils import ncc_loss
import torch
class TestVVR(TestCaseNeSVoR):
@staticmethod
def get_... |
890b2d1d010b45c3043a21e0ed2bf646a397ebc37101cfe07dcab4df79784d55 | Python | 3,133 | 91 | import os
import numpy as np
np.seterr(all="raise")
from deepglyco.speclib.common.combine import NonRedundantSpectraConsensus
from deepglyco.speclib.gpep.filter import GlycoPeptideSpectrumFilter
from deepglyco.speclib.gpep.hdf import GlycoPeptideSpectralLibraryHdf
from deepglyco.speclib.gpep.inmemory import GlycoPe... |
0d88d89a1571303626a7147d6409b6bc6ff42404834c76bae11bdbc3de2c3cd7 | Python | 3,139 | 89 | """Module for build dynamic fields."""
from collections import Counter, defaultdict
import torch
from onmt.utils.logging import logger
from onmt.utils.misc import check_path
from onmt.inputters.inputter import get_fields, _load_vocab, \
_build_fields_vocab
def _get_dynamic_fields(opts):
# NOTE: not support tg... |
277b2f4fb0768cfb058ce63e96e069a25af1604a0786a0195fa902de47af671f | Python | 3,139 | 99 | # Copyright 2020 Google LLC
#
# 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 agreed to in writing, ... |
b3ffbbfdb10ddcea93c2f41e592579e8b344b5b4449fbed04932f7ec6598e96f | Python | 3,139 | 88 | __all__ = ["GlycoPeptideBranchMS2TreeLSTM"]
import dgl
import torch
from torch import nn
from dgl.ops import copy_u_sum # type: ignore
from ..ms2.model import GPeptideMS2Output, GlycanMS2FragmentNN, GlycanMS2Output, GlycoPeptideMS2RatioOutput
from ....util.collections.dict import chain_item_typed
from ..common.data i... |
39116bed2c264eb55772d448ac3f7cf6b17e339718ec72dade9cd3845f43f5b3 | Python | 3,140 | 89 | __all__ = ["GlycoPeptideRTPredictor"]
import os
from logging import Logger
from typing import Any, List, Mapping, Optional, Union
import numpy as np
import pandas as pd
import torch
from ....util.progress import ProgressFactoryProto
from ...common.prediction import PredictorBase
from ..common.data import GlycoPeptid... |
f7756230f8747e69bbfbe3d71d6ceef59fbfa5a276a60e318320295a8a80fb31 | Python | 3,140 | 112 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
@pytest.fixture
def m():
return 5
@pytest.fixture
def n():
return 100
@pytest.fixture
def cols():
return ["jim", "joe", "jolie", "joline", "jolia"]
@pytest.fixture
def vals(n):
vals = [
np.random.default_r... |
686ff009d0498e9109b1d62fea3c735f89d04e6683d80a04553e9705a626dc93 | Python | 3,141 | 126 | """Path-related utilities for PCNtoolkit."""
import os
def get_default_home_dir() -> str:
"""Get the default home directory for PCNtoolkit.
Returns
-------
str
The default home directory path
"""
if home_dir := os.environ.get("PCN_HOME_DIR"):
return home_dir
# Try user's... |
66104638bd9b8964d7d450fc71594f8eaf1a2f89a17a938edfbd69e37e6981ce | Python | 3,143 | 93 | '''
Utils for use in seaborn_plot.py. These are mostly taken from ss_helpers.py,
but used separately to avoid the necessity of activating conda.
Authors: Sara Mathieson, Rebecca Riley
'''
def parse_mini_lst(mini_lst):
return [float(x.replace("[",'').replace("]",'').replace(",",'')) for x in
mini_lst]
de... |
7d63ce0dd512e6f401af05456c44f8a1c755f2b87e32686f4875f398cecfa31f | Python | 3,146 | 88 | import argparse
import torch.cuda
from tqdm import tqdm
import numpy as np
import pandas as pd
from sequence_models.utils import parse_fasta
from sequence_models.pretrained import load_model_and_alphabet
parser = argparse.ArgumentParser()
parser.add_argument('model')
parser.add_argument('in_fpath')
parser.add_argume... |
ac544d75f61468cbed548a9e101dc7ea82345871266c199f67998d0acdb1f712 | Python | 3,147 | 137 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Mar 17 16:08:44 2020
@author: reisertm
"""
import sys
sys.path.append("/home/reisertm")
sys.path.append("/home/reisertm/nora/src/python")
import numpy as np
import tensorflow as tf
import math
from tensorflow.keras import Model
from tensorflow.keras ... |
558bef23104f3a0a67cea47fab78ac49fb3ee848aca3a8fde4818e21e7c6b7e2 | Python | 3,148 | 94 | ######################
### Import Library ###
######################
# My library
from molgraph.dataset import *
from molgraph.graphmodel import *
from molgraph.training import *
from molgraph.testing import *
from molgraph.visualize import *
from molgraph.experiment import *
# General library
import os
import argpars... |
78e0550c6ea388eafbd901e767079fe3df3d1558d3822fdbedfe4d1349586eaf | Python | 3,148 | 97 | __all__ = ["GlycoPeptideRTTrainer"]
import os
from logging import Logger
from typing import List, Mapping, Optional, Union
import torch
from ...util.weightloss import AutomaticWeightedLoss
from ....util.progress import ProgressFactoryProto
from ...common.training import TrainerBase
from ...pep.rt.loss import RTMAEL... |
2e2b50fddca541e61adcb9fcb52c90e7343aace1d3a4d09377c4105ef84d8946 | Python | 3,150 | 107 | #!/usr/bin/env python
'''
Testcases for the neural network training
'''
import windseer.utils as utils
import windseer
import os
import torch
import unittest
class TestDictutils(unittest.TestCase):
def test_dict_update(self):
dict_in = {
'a': 1,
'b': {
'changed':... |
738214069c2fde518164a43b11d621c730bfc133a0401ed04fdf10cdf7c1df8e | Python | 3,152 | 116 | from __future__ import annotations
import contextlib
import inspect
import os
import re
from typing import (
TYPE_CHECKING,
Any,
)
import warnings
if TYPE_CHECKING:
from collections.abc import Generator
from types import FrameType
@contextlib.contextmanager
def rewrite_exception(old_name: str, new_n... |
a4eeda637a00618b6a301c2a577dd8f21031c6f5d05932c17d8e7c64df52b405 | Python | 3,152 | 92 | ''' create_ppp_sync_submitter.py
Create a shell script to submit AWS S3 sync jobs to the cluster
for PPP imagery.
'''
import argparse
import re
import os
import colorlog
import inquirer
from aws_s3_lib import list_prefixes
# Configuration
MANIFOLDS = ['dev', 'prod', 'devpre', 'prodpre']
BASE = "/nrs/neuronbri... |
5ae0663b0cddaeb54e416766d513d533a58e54737cc92ce7f226756239102b3c | Python | 3,153 | 98 | from dataclasses import dataclass
import logging
import time
import numpy as np
import torch
from modules import (
dimensions,
model,
pretransformations,
posttransformations,
transformation_utils,
)
@dataclass
class EdsrDimensions(dimensions.Dimensions):
"""
Edsr dimen... |
5f0803998800a96be348d7658dac2cadb57cc20c15f98432b8c86af7aacc4f2c | Python | 3,153 | 87 | import numpy as np
import logging
from copy import deepcopy
# Class running stochastic gradient descent
# opt is an optimizable class that must provide the following functions:
# addProd(g0, step, g1): returns g0 + step * g1 for directions g0, g1
# getGradientSGD(coeff) returns coeff * gradient; the result can be ... |
b6a1c9558183d2b76de53aa2a232bdad8dd177186f087d0dcba8ae3e46204169 | Python | 3,157 | 92 | ''' create_ppp_sync_submitter.py
Create a shell script to submit AWS S3 sync jobs to the cluster
for PPP imagery.
'''
import argparse
import re
import os
import colorlog
import inquirer
import aws_s3_common.aws_s3_common as AW
# Configuration
MANIFOLDS = ['dev', 'prod', 'devpre', 'prodpre']
BASE = "/nrs/neuro... |
32c34c78586c3ffa7ef392c334a49a9248e194f27e61b87491cb0ddfaf2343a5 | Python | 3,160 | 94 | # Copyright 2018-2021 Xanadu Quantum Technologies Inc.
# 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... |
44c412338b7c0ccff2cebcc8e0e53f59cdbd32714218000a05e41eb1e9957887 | Python | 3,161 | 78 | ###############################################################
################################################################
import numpy as np
import matplotlib.pylab as plt
import matplotlib.gridspec as gridspec
import matplotlib
matplotlib.rcParams.update({'text.usetex': False, 'font.family': 'stixgeneral', 'mat... |
3a1b32bcdfeaa04e291aaa92741fa777dddc441f3c74b3cb68ead4472b0d7d04 | Python | 3,162 | 75 | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
import os
import cv2
from PIL import Image
class PAPQMNIST_SIL():
def __init__(self, list_IDs, labels, transform, path, batch_size, dim, n_channels,
n_classes, negative_class_name, positive_class_name, shuffle):... |
09879ab97fd4fbf64e96e05d008c7e3f2349b1503d5874c3dd416bdd1d343ac7 | Python | 3,163 | 94 | ######################
### Import Library ###
######################
# My library
from molgraph.dataset import *
from molgraph.simplemodel import *
from molgraph.training_simple import *
from molgraph.testing_simple import *
from molgraph.visualize import *
from molgraph.experiment import *
# General library
import os... |
51c795362545d95c2390c38c58054c5283364692b24b61b2ab22ef6a6c5d240a | Python | 3,165 | 71 | """
Methods to gather results from different subjects
"""
import os
from scanometrics.utils import logging
def quantifybrainstem(subjects_dir, subj_id, output_filename='brainstem_volume.txt'):
"""
Collects relevant brainstem information from morphometry output
:param subjects_dir: absolute or relative p... |
54725563de9c9dbd20a1017b1af102343f0bcd3afd24f1c44773c31f15dc371a | Python | 3,165 | 101 | # Copyright 2018-2023 Xanadu Quantum Technologies Inc.
# 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... |
54960e17380bba959b8643133d278c95ea53a37cd38b4bc9a86f81ea060913cb | Python | 3,165 | 83 | #%%
# -*- coding: utf-8 -*-
import numpy as np
import sys,os
sys.path.append('./')
from utils.model import *
from utils.cal_param import *
from utils.move_detector import main
from utils.unet import *
from env_config import *
#=========================set values below==========================
# Load models
input_sh... |
509bf8b0772565313972eaeaf819dedaba20d52b781779cf3aaa056860a2ff17 | Python | 3,168 | 105 | import functools
import itertools
import logging
from multiprocessing import Pool, TimeoutError
import os
import signal
import sys
import time
from typing import Callable, List
import warnings
sys.path.append('/gscratch/stf/mpun/software/PyRosetta4.Release.python38.linux.release-299')
import h5py
import numpy as np
im... |
99f3a66fb8d9d81701a2fbc28c33e4e20041387cdb43cc72b8d8944de86c3291 | Python | 3,168 | 76 | import argparse, os, yaml
def strtobool(value):
# local replacement for distutils.util.strtobool (distutils was removed in Python 3.12)
value = str(value).strip().lower()
if value in ('y', 'yes', 't', 'true', 'on', '1'):
return 1
if value in ('n', 'no', 'f', 'false', 'off', '0'):
retur... |
6975e3d7cf95adb4b7f3ee02146789defa3d31a53987f97c824eb195693d1af0 | Python | 3,169 | 92 | from ecgdigitize import visualization
from typing import Optional, Union
from dataclasses import dataclass
from enum import Enum
import numpy as np
from ecgdigitize.image import ColorImage
from . import common
from .grid import detection as grid_detection
from .grid import extraction as grid_extraction
from .signal i... |
4727ce3569885a3e22330c4907292b77c4b078b3425fa19bdff7dae1bc13d921 | Python | 3,170 | 80 | import numpy as np, matplotlib.pyplot as plt, sys
import pumpprobe as pp
ds_list = "/projects/LEIFER/francesco/funatlas_list.txt"
funa = pp.Funatlas.from_datasets(
ds_list,
merge_bilateral=True,merge_dorsoventral=True,merge_AWC=True,
ds_exclude_tags="mut... |
1178b2dd9013771401e5a89e389eae00aa24ed7788bcfb081b3407590e14f021 | Python | 3,172 | 94 | __all__ = ["BatchProto", "MS2DataConverterProto", "MS2Dataset"]
import os
from logging import Logger
from typing import Any, Generic, List, Mapping, Optional, Protocol, TypeVar
import torch
from torch.utils.data import Dataset
from ...speclib.common.speclib import MS2SpectrumType, SpectralLibraryBase
from ...util.pr... |
000872265cd2ef3dea7a941e1bc09d865abe8a4e404eb369d38b7a3633b6d4f4 | Python | 3,176 | 71 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Jan 23 08:26:03 2022
@author: danielkerschensteiner
"""
import numpy as np
import pandas as pd
import tkinter as tk
import tkinter.filedialog
import glob
import os
def collect_columns(path_name, ind_col, target_col):
files = glob.glob(path_n... |
17534bdbad88bf95dd6d474869f6be0369ceb6665456dd42566044eb8c88549c | Python | 3,176 | 71 | """(Iterative) Walsh method for coil sensitivity map calculation."""
import torch
from mrpro.data.SpatialDimension import SpatialDimension
from mrpro.utils.filters import uniform_filter
def walsh(coil_images: torch.Tensor, smoothing_width: SpatialDimension[int] | int) -> torch.Tensor:
"""Calculate a coil sensit... |
b44bb0eb10c49af3c055a9ac532691917a318c0f339cb79c55481109e4340646 | Python | 3,176 | 110 | import pytest
import pandas as pd
import pandas._testing as tm
from pandas.core.reshape.merge import (
MergeError,
merge,
)
@pytest.mark.parametrize(
("input_col", "output_cols"), [("b", ["a", "b"]), ("a", ["a_x", "a_y"])]
)
def test_merge_cross(input_col, output_cols):
# GH#5401
left = pd.DataFr... |
bc17a5fbff57372e75f98b04ec9823eba12099af55f0e5463a83143f422f308b | Python | 3,176 | 96 | #
# File to test the hnn.py class.
#
# This file establishes the clebsch gordan coefficients, sets up an hnn with given parameters,
# loads holograms from .npy files, and then tests the network via a function call.
#
import os
import numpy as np
import tensorflow as tf
import protein_holography.network.hnn as hnn
i... |
659d04ae6879cc6144f406de5cb7f18220cac2f8f137ee5f8a8a0211fffd1588 | Python | 3,178 | 122 | import pandas as pd
import numpy as np
from scipy import stats, linalg
from statsmodels.stats import multitest
def calculate_median_absolute(x):
"""Calculate Absolute median value"""
return x.abs().median()
def significant_level(x, alpha=0.05, correction=None):
"""
Apply FDR correction to a pandas.... |
9eb9b88389352fa87632620b6e9972e542c635694cd52b58c972ee0a489c178d | Python | 3,178 | 89 | """
Base class to track job results
Authors:
Thomas A. Hopf
"""
from abc import ABC, abstractmethod
DEFAULT_RESULT_COLLECTION = "evcouplings_jobs"
DEFAULT_FILE_COLLECTION = "evcouplings_files"
class ResultTracker(ABC):
"""
Track job status and results in a database
"""
def __init__(self, connecti... |
6e75b2f0d4da61cd1d2ea47595098aa6dd6ed6ebf5c5807a1d0dc6432518bdcd | Python | 3,180 | 110 | import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import sys
import matplotlib.ticker as ticker
import matplotlib.transforms as transforms
from pathlib import Path
import math
from statistics import mean, stdev
from plotting_functions import *
#create figure and set font
fig, ax = plt.subplots()... |
de3ef6947e72062d70ce2a3a55937de850fdb460ff6162b0528e9396c63a6120 | Python | 3,180 | 98 | # Copyright 2018-2020 Xanadu Quantum Technologies Inc.
# 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... |
a967ebf112de9ad4d63d2a4cf530340ca4d3f8bb2ddfd95c606894cc7a3d2df2 | Python | 3,181 | 83 | from torchmetrics.functional import accuracy, precision, recall, auroc, f1, specificity
from torchmetrics import ConfusionMatrix
import torch
import pandas as pd
def calculate_metrics(pred_labels, target_labels, loss=torch.tensor([0])):
"""
This function should be replaceable with MetricCollection from torch ... |
6384cebbfb4a0a1723b2a733a1797c23b46c499ca70b5625205c2c480e12333c | Python | 3,182 | 80 | from StimulationProcess.BasicStimulationProcess import BasicStimulationProcess
from psychopy import core, visual, event
import time
class FinishProcess(BasicStimulationProcess):
def __init__(self) -> None:
super().__init__()
def change(self):
if self.controller.endBlock:
... |
43611d7d64ec97f7d771d31f494de53b17f1fb143bb607cc3b335247ac4e8afd | Python | 3,183 | 116 | """
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
import logging
from abc import ABC, abstractmethod
import torch
import wandb
from torch.utils.tensorboard import SummaryWriter
from ocpmodel... |
58a2e41769b71567f0b479d5e47332e6a42e3f3c7e3af1e21e480e8ca245ffc8 | Python | 3,184 | 81 | #!/usr/bin/env python
__author__="etseng@pacb.com"
import os, re, sys
from Bio import SeqIO
from csv import DictReader, DictWriter
from collections import Counter
FIELDNAMES = ['pbid', 'pbgene', 'length', 'refisoform', 'refgene', 'fl_count']
pbid_rex = re.compile('PB.(\d+).\d+')
def demux_for_subsamping(class_filena... |
f4f6c39a1cdb32452a4f4d47c42f50e2fd3ffd97732a396d7643984fcf741452 | Python | 3,186 | 65 | import os.path
import argparse
import logging
from base import loggingUtils
import base.surfaces as surfaces
from base.kernelFunctions import Kernel
from base import surfaceMatching
from base import secondOrderMatching as match
#import secondOrderMatching as match
def compute(tmpl, targetDir, outputDir, display=True, ... |
307fbb18e75093388ab588043212245ae9470f18854bcbe6370cf61b2b374bc4 | Python | 3,187 | 78 | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
import os
import cv2
from PIL import Image
class OC_SIL():
def __init__(self, list_IDs, labels, transform, path, batch_size, dim, n_channels,
n_classes, negative_class_name, positive_class_name, shuffle):
... |
6efa10ded111ca0add65a6829d39c7e81b5d20318d44c1abf86b073c95b86a29 | Python | 3,187 | 131 | """All acquisition enums."""
from enum import Enum, Flag, IntFlag, auto
class AcqFlags(Flag):
"""Acquisition flags.
NOTE: values in enum ISMRMRD_AcquisitionFlags start at 1 and not 0, but
1 << (val-1) is used in 'ismrmrd_is_flag_set' function to calc bitmask value [ISMb]_.
References
----------... |
80808661ef29fc05ce6e4fe4a13cf25ec9fe8c17d9c6fedf3e164c67d2cb7b7f | Python | 3,188 | 108 | import numpy as np
from scipy.signal import hilbert
from scipy.stats import zscore
import fbpca
from scipy.signal import medfilt2d
maskfile = "demodata/mask.npy"
ncomp = 20
def cpca(input_data, n_comps, n_iter=20, l = 10):
l += n_comps
n_samples = input_data.shape[0]
(U, s, Va) = fbpca.pca(input_data, k =... |
019c306bb90356ce4faf8856b378ca603e3a12f4c268d37120e6dcf19122178f | Python | 3,189 | 78 | #! /usr/bin/env python
##############################################################################
## DendroPy Phylogenetic Computing Library.
##
## Copyright 2010-2015 Jeet Sukumaran and Mark T. Holder.
## All rights reserved.
##
## See "LICENSE.rst" for terms and conditions of usage.
##
## If you use this wo... |
e41143d1eab97da8a99a47820b0e0849f1150c31d5971b9d954f5b1f67666422 | Python | 3,189 | 86 | import os
import json
import csv
import pandas as pd
import numpy as np
import random
from .readPDB import getDataset, fastaname
def save_dataset_to_csv(csv_path, data, models_per_pair=5, use_ranking=False, data_dir=''):
contents = []
for index, row in data.iterrows():
label = 1 if row['type'] == 'p... |
b0607cadea732bbf396b1bac54ad4052c237b899e8510cbe6cc25c020a592c04 | Python | 3,190 | 74 | ## deprecated 12.02.2021 rieke / arco
# import pandas as pd
# import dask
# import dask.dataframe as dd
# # from compatibility import multiprocessing_scheduler
# def burst_detection_helper(proximal_voltage_series, st, burst_cutoff):
# sim_trial_index = proximal_voltage_series.name
# spike_times = st.loc[s... |
b0ca76e11f7a71a81a9fffbe09973f621ed72d03e10c195c3e028198bd5bbd7f | Python | 3,191 | 100 |
import re, sys, os
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..', 'resource-gcg', 'scripts'))
from tree import Tree
def A(q):
return q.split('/')[0]
def W(q):
return q.split('/')[1]
def depth(S):
return ( -1 if '-/-'==S[0] else
0 if '-/-'==S[1] else
1 if '... |
2c3c25e2275634e561bac5a85e09c090d1f7db12cabb923ce9c55d9842b64c8f | Python | 3,192 | 86 | import numpy as np
def initialize_population(population_size, dimension):
return np.random.rand(population_size, dimension)
def calculate_fitness(positions):
return np.sum(positions, axis=1)
def update_producers(positions, fitness_values, iteration, max_iterations, alert_value, safe_threshold):
... |
9e62aa54c3b880a95e492924bafd4130795c599de528fd657832460a925c5ce5 | Python | 3,194 | 74 | import itertools
import numpy as np
from elephant.spike_train_dissimilarity import van_rossum_distance, victor_purpura_distance
from elephant.spike_train_synchrony import spike_contrast
from neo.core import SpikeTrain
class Measure:
def __init__(self, firings, metric='rsync'):
'''
Function for calc... |
97d2693e530326a32ed4570fb027ff4e0baf5d15c7f0f75ecfcd1728a1699c60 | Python | 3,195 | 94 | from Analyze_Retinotopy import PrfMapping
from Analyze_PRF import AnalyzePrf
from Analyze_EccSF import AnalyzeEccSf
from Analyze_RadialBias import RbRatioAnalyses
if __name__ == '__main__':
# Create an instance of PrfMapping class
prf = PrfMapping(fov=20)
# Obtain model response profiles for sp... |
20b86b789aad9aab3b77c3feebccc91d065ca703110d919f7c87db21e328bf95 | Python | 3,197 | 82 | import torch
import torch.nn as nn
import torch.nn.functional as F
class SSIM(nn.Module):
"""Layer to compute the SSIM loss between a pair of images
"""
def __init__(self):
super(SSIM, self).__init__()
self.mu_x_pool = nn.AvgPool2d(3, 1)
self.mu_y_pool = nn.AvgPool2d(3, 1)
... |
978cf821b0abeda63bc52bb8dc5743657787f136aeaf3234445e8c338236e635 | Python | 3,197 | 79 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jul 29 17:48:31 2022
@author: mpeshwa
"""
#Importing required libraries
from Bio import SeqIO
from tqdm import tqdm
import random
from itertools import chain
import math
import pandas as pd
import numpy as np
import sys
import argparse
import random
d... |
0e549bc1ca411bc96670c6272e5e6c33e2687cf1aab1ae6200a396c1cd445a95 | Python | 3,198 | 97 | import os
import pickle
import shutil
import hashlib
import base64
import json
import numpy as np
import pandas as pd
from .log import auto_log
from .configs import CACHE_DIR
class CacheLoadError(Exception):
pass
class RobustJSONEncoder(json.JSONEncoder):
def default(self, obj):
if isinstance(obj,... |
68791807dfc2147cb10094612fe928264b41a777c940b822e89a291743d11b1b | Python | 3,199 | 87 | """Class for Zero Pad Operator."""
from collections.abc import Sequence
import torch
from mrpro.operators.LinearOperator import LinearOperator
from mrpro.utils.pad_or_crop import pad_or_crop
class ZeroPadOp(LinearOperator):
"""Zero Pad operator class."""
def __init__(self, dim: Sequence[int], original_sha... |
1d370b8e83d8650c9e5680bb5935e967b0ffab6a2187c5241f62e80a8a0f310a | Python | 3,200 | 80 | from rl_games.common.ivecenv import IVecEnv
# wrap your vector env so it resets for you under the hood
from gymnasium import spaces
def remove_batch_dim(space: spaces.Space) -> spaces.Space:
"""Recursively remove the first (batch) dimension from a Gym space."""
if isinstance(space, spaces.Box):
# ass... |
81a30491f96289a6318992fb45a48e22a3d73428e9580e4f95c9fd60d67b7f14 | Python | 3,200 | 103 | """
.. _decoding_md:
====================================================
Decoding Multidimensional Gradient
====================================================
Gradec provides .
"""
# Download HCP S1200 principal gradient
from gradec.fetcher import _fetch_gradients
gradients = _fetch_gradients(cortical=True)
#... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.