sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
fa72cb194c60492b1770d83f52a2402d5053014aa7055408feab533bb741919a | Python | 1,942 | 54 | import sys
import numpy as np
sys.path.append(' /home/kusch/Documents/project/co_simulation/TVB-NEST-proof/lib/soft/lib/python3.8/site-packages/')
from neurolib.models.aln import ALNModel
from neurolib.utils.loadData import Dataset
import matplotlib.pyplot as plt
print("start "); sys.stdout.flush()
path_mpi_input = ... |
29fd6df3f1e229625c8a8ddaf4fab30f88ba6555f9a031b62d7d2affcba88cab | Python | 1,945 | 41 | import json
import pickle
import argparse
import torch
from torch.utils.data import DataLoader
from dig.ggraph3D.dataset import QM93DGEN, collate_fn
from dig.ggraph3D.method import G_SphereNet
from dig.ggraph3D.evaluation import RandGenEvaluator
parser = argparse.ArgumentParser()
parser.add_argument('--model_path', t... |
0ed9c308096c1c0e02dd10bfc1aaa57052991bee61fa0f3496f7a1f760a269d4 | Python | 1,946 | 59 | """
Divide the signal in each channel by their max/mean/median value.
"""
import numpy as np
import argparse
from pathlib import Path
import neo
import quantities as pq
import os
import sys
from utils.io_utils import write_neo, load_neo
CLI = argparse.ArgumentParser()
CLI.add_argument("--data", nargs='?', type=Path, ... |
7125a986656680d1c4a8b84866cf03e279ffa769257615ce1faa96cbba8a8a95 | Python | 1,947 | 48 | from unittest import TestCase
import torch
import torch.nn as nn
from smithers.ml.models.rednet import RedNet
from smithers.ml.models.fnn import FNN
if torch.cuda.is_available():
device = torch.device('cuda')
else:
device = torch.device('cpu')
class Testrednet(TestCase):
def test_constructor_0(self):
... |
b5b234532a997d42a7d7d9b7a9c31f90f713e9e7e6a74cd1eabe7478e92843c9 | Python | 1,947 | 53 | import argparse
import numpy as np
import pandas as pd
import warnings
from scipy.stats import ttest_1samp
# Create an argument parser
parser = argparse.ArgumentParser(description='Load data, make predictions, and save results.')
parser.add_argument('file_name', type=str, help='Path to the data file')
parser.add_argum... |
3c97346c7024532440d5c6a357f4207a5d1945905b4f5be4ba90dbf7fb846dc3 | Python | 1,948 | 61 | import os
strA = "h"
strB = "rs"
# Process input lines and categorize them into output files based on conditions
def process_file(input_file, output_prefix):
with open(input_file, 'r') as infile:
for line in infile:
parts = line.strip().split('\t')
if len(parts) >= 4:
... |
e36ec51fa99e8de21011fa3aa9a7166e616d761b8ac5bdb8e979b72a0e7354c1 | Python | 1,948 | 48 | from typing import List
import pandas as pd
from reinvent.chemistry.library_design.reaction_definitions.leaving_groups_dto import (
LeavingGroupsDTO,
)
class StandardDefinitions:
def __init__(self, definitions_path: str):
# TODO: implement in config default path for reaction definitions
self... |
9cd9a8ffc8893d4abcb364be38a9346c433f99f7c19cfb616dae731e5969a233 | Python | 1,950 | 73 | import seaborn as sns
import matplotlib.pyplot as plt
from scipy.cluster.hierarchy import leaves_list
import numpy as np
from scipy.stats import pearsonr
def plot_hline_dend(position, text, c="gray", s=":", w=2):
plt.axhline(y=position, color=c, ls=s, lw=w)
plt.annotate(
text,
(0, position),
... |
9df8447710025e94fee35670610f8930849748671243956f243aac8ba991f00e | Python | 1,951 | 65 | """Visualization for Geometric Statistics."""
import logging
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D # NOQA
import geomstats.backend as gs
from geomstats.geometry.special_euclidean import SpecialEuclidean
SE2_GROUP = SpecialEuclidean(n=2, point_type="matrix")
SE2_VECT = SpecialEucli... |
74b4fa9ccdd1896247adad7b92b94eab730a0326a61d40ae1272b36b380e2960 | Python | 1,952 | 59 | """
Divide the signal in each channel by their max/mean/median value.
"""
import numpy as np
import argparse
import neo
import quantities as pq
import os
import sys
from utils.io_utils import write_neo, load_neo
CLI = argparse.ArgumentParser()
CLI.add_argument("--data", nargs='?', type=str, required=True,
... |
aee01b7b4802e96abc9913f87e1c895dbe87fd012359c0780b8a50bf6cc9867e | Python | 1,952 | 47 | import unittest
from rdkit.Chem.rdmolfiles import MolToSmiles
from reinvent.chemistry import conversions
from reinvent.chemistry.library_design import bond_maker, attachment_points
from reinvent.chemistry.library_design.fragment_reactions import FragmentReactions
from tests.chemistry.fixtures.test_data import (
M... |
5ffa0c3f2c75896aae2f347a9b6918fe986e241b4dceaa625be3df599d3a7a4c | Python | 1,954 | 58 | r"""Compute a geodesic in BHV space between two fully resolved trees with 5 leaves.
In [BHV01], Figure 18, there are depicted the trees T and T', as well as the respective
splits named e1, e2, f1, f1 at the axes. Furthermore, the geodesic between T and T' is
depicted, and in this example, this scenario is reconstructe... |
84a33c5c5b78cf68491ef54a97a493d6f073b49d0d32b969f2d130c366c8e1fa | Python | 1,954 | 63 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
9074d2da98973d066f9a10dced7062a281560300b448dab67eee7f50b900d09c | Python | 1,955 | 67 | """
Does the Python binding give what the MATLAB toolbox gives?
It must, and not approximately: both call the very same C. This is not a
reimplementation of TFCE in Python, it is the same max-tree with a different
caller, so anything other than bit-identical output means a binding bug -- a
transposed volume, a face li... |
e44265e99261fbf74d8a62575066e82e98e63b1461a62b2a5ab29fd9ebf69f74 | Python | 1,955 | 53 | """
Check whether the input data representation adheres to the stage's requirements.
Additionally prints a short summary of the data attributes.
"""
import numpy as np
import argparse
from pathlib import Path
from utils.io_utils import load_neo
from utils.neo_utils import analogsignal_to_imagesequence, imagesequence_... |
6f2892b86d10bac21f0ab666a4c0cdb753a948e3a4ae011d25cbf19a91778a41 | Python | 1,960 | 59 | import argparse
from torch.optim import Adam
from . import register_optimizer
from .base_optim import BaseOptim
@register_optimizer("adam")
class AdamOptimizer(BaseOptim, Adam):
"""
`Adam <https://arxiv.org/abs/1412.6980>`_ optimizer
"""
def __init__(self, opts, model_params) -> None:
BaseOp... |
c25f9b75429fc84fe50964a923b525d891111cdf0e3f619431c973136490dba3 | Python | 1,960 | 62 | # Copyright (c) 2021 PaddlePaddle 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 appli... |
efc2493fb8039fa5d40db6463735c0861500305181251abf7fadf578d1faf0a9 | Python | 1,961 | 45 | import shutil
from dig.sslgraph.evaluation import GraphUnsupervised
from dig.sslgraph.utils import Encoder
from dig.sslgraph.dataset import get_dataset
from dig.sslgraph.method import GraphCL, InfoGraph, MVGRL
def test_GraphUnsupervised():
root = './dataset'
dataset = get_dataset('MUTAG', task='unsup... |
a85ab02a16aa90159bc07278622dab2024466165181820dcd24caacc2e2e2a98 | Python | 1,962 | 69 | import unittest
from deeprank_gnn.NeuralNet import NeuralNet
from deeprank_gnn.ginet import GINet
import torch
import os
CWD = os.path.dirname(os.path.realpath(__file__))
def _model_base_test(database, model, task='reg', target='test_target', plot=False):
device_name = 'cuda:0' if torch.cuda.is_available() else... |
d1de99fcb4f940f1dcd5f0c8c4d069f99c4d37a1f5cdcd819d31587c51cd1c3b | Python | 1,962 | 48 | # Copyright (C) 2020-2025 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""You may copy this file as the starting point of your own model."""
import argparse
import os
import numpy as np
from tqdm import tqdm
def create_data(collaborators, dst, total_dataset_size_per_col):
num_samples = 1
input_sha... |
f288e0f3e2491ceca856e86dda4e32796e7b8923cf9f23fbbfc8914753368c6c | Python | 1,962 | 55 | import pytest
import geomstats.backend as gs
from geomstats.test.vectorization import generate_vectorization_data
from geomstats.test_cases.geometry.base import VectorSpaceOpenSetTestCase
from geomstats.test_cases.geometry.riemannian_metric import RiemannianMetricTestCase
class PoincareBallTestCase(VectorSpaceOpenSe... |
2ad95182903ea0130e2aa7ecd92efa95aad2b52fd13b2ff49ca14cb5b3d3ec63 | Python | 1,965 | 65 | import sys
import os
import mdtraj as md
from mdtraj import Trajectory
from mdtraj.formats import DTRTrajectoryFile
from mdtraj.utils import in_units_of
sys.path.insert(1, "/project/dinner/scguo/ci-vsd/python")
from util import zero_h_occupancy
TOPFILE = "/project/dinner/scguo/ci-vsd/unbiased/000/civsd.prmtop"
def ... |
ef17f858db139b796aff538c560ec625036a4d6e32cb4e0da9f62678fac6afe7 | Python | 1,965 | 62 | import os
import shutil
import pytest
import unittest
import torch
from reinvent.runmodes.create_model.create_mol2mol import create_model
@pytest.mark.integration
@pytest.mark.usefixtures("json_config")
class TestCreateModel(unittest.TestCase):
def setUp(self):
self.workdir = self.json_config["MAIN_TEST... |
0cb2e724183842878808db2b997b4a1057940e78f6c43822bad810c234265e3d | Python | 1,968 | 62 |
class Graph():
def __init__(self, V):
self.V = V
self.graph = [[0 for column in range(V)] \
for row in range(V)]
################################################
# This function returns true if graph G[V][V]
# is Bipartite, else false
d... |
90a38efd0856ecf71ba16ee5ccbf574c2ef747ee8bf86ee7af3e6e38f5eba97f | Python | 1,969 | 52 | # Copyright (c) 2020 PaddlePaddle 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 appli... |
a5c47334c6975d5ddfb2f785ea6a67bf4eebda73887af88556b017e3b8f0f5e3 | Python | 1,970 | 65 | import geomstats.backend as gs
from geomstats.test.data import TestData
from .base import VectorSpaceOpenSetTestData
from .riemannian_metric import RiemannianMetricTestData
class PoincareBallTestData(VectorSpaceOpenSetTestData):
xfails = ("projection_belongs",)
class PoincareBallMetricTestData(RiemannianMetric... |
020ef05ad759eeb47fbcf123c05c8a660a7d892733d3347652472782e688f9c6 | Python | 1,973 | 70 | # Copyright (c) 2020 PaddlePaddle 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
#
# Unle... |
ff1a39569757dce07f060b3a114605578ef39fe30b98b29650808d45b730c6f3 | Python | 1,974 | 64 | import socket
import torch
import torch.distributed as dist
from utils import logger
def is_master(opts) -> bool:
node_rank = getattr(opts, "ddp.rank", 0)
return node_rank == 0
def dist_barrier():
dist.barrier()
def is_start_rank_node(opts) -> bool:
node_rank = getattr(opts, "ddp.rank", 0)
def... |
966d1f001e9a42dc7268473f298b5431c984b3df92e54b778eeb0c3a3857ff9f | Python | 1,975 | 57 |
import torch
def tv_2d_l2(img):
assert len(img.shape) == 2
numel = img.shape[0] * img.shape[1]
x_variance = torch.sum(torch.pow(img[:, :-1] - img[:, 1:], 2))
y_variance = torch.sum(torch.pow(img[:-1, :] - img[1:, :], 2))
return (x_variance + y_variance) / (numel)
def tvd_2d_l2(img, direction='x... |
d9cea65741b2657b2fd7ff71bec44b0842daa01d11e4dd103feb3310ffce31de | Python | 1,975 | 59 | import argparse
from torch.optim import AdamW
from . import register_optimizer
from .base_optim import BaseOptim
@register_optimizer("adamw")
class AdamWOptimizer(BaseOptim, AdamW):
"""
`AdamW <https://arxiv.org/abs/1711.05101>`_ optimizer
"""
def __init__(self, opts, model_params) -> None:
... |
605bd486a538cb1cdf5f1f654a1a06d40e7ae8ff88d1c0931e346b27660cbb91 | Python | 1,976 | 57 | from ._tp_scatter_base import TensorProductScatter
class OpenEquivarianceTensorProductScatter(TensorProductScatter):
_nequip_custom_ops_libs = ("openequivariance",)
def __init__(
self,
feature_irreps_in,
irreps_edge_attr,
irreps_mid,
instructions,
use_opaque: b... |
fceb1f9aeaafd77a5a07128f3d2081016cc00256cd006a1cff31aaaef2611652 | Python | 1,976 | 58 | from corgie.stack import Stack
from corgie.log import logger as corgie_logger
from corgie.argparsers import create_layer_from_dict, create_layer_from_spec
import json
def spec_to_stack(spec, prefix, layers):
"""Create Stack by filtering a dict of layers
Args:
spec (dict): job_specs including src_img, ... |
acd438f113b860a35399940a7d5e5de2bc299b6e0de814daf85b8a295736c29e | Python | 1,977 | 75 | from __future__ import annotations
import logging
import os
from pathlib import Path
from typing import Union
logger = logging.getLogger(__name__)
_cache_root: Path = Path(".cache")
def set_cache_root(root: Union[str, Path], create=False):
global _cache_root
_cache_root = Path(root)
if create and not ... |
887c7e8e9199381e9f19c8dec452ed49f895b454fb22501e08c6e3e62b476be0 | Python | 1,978 | 68 | """
Functions for building dendrogram trees and manage their levels
"""
import numpy as np
from scipy.cluster.hierarchy import linkage, fcluster
import warnings
def tree_modules(W, num_clust):
Z = linkage(W, "weighted", "correlation")
T = fcluster(Z, num_clust, criterion="maxclust")
return T
def level_... |
8b39c4a0dbb10fc73d005c885ce5c63887c2eb7fad3524c2847cb3c41ee2ff1b | Python | 1,978 | 65 | #!/usr/bin/env python3
"""
Stream a recorded fif file on LSL network.
Command-line arguments:
#1: Stream name
#2: Raw FIF file to stream
#3: Chunk size
#4: Trigger file
If no argument is supplied, prompts for the server name and for the path to
the '-raw.fif' file to play.
Example:
python nd_strea... |
ed29265e27a85280b80406ea31b26e6580d5f68fbb4bfb90110df766674335c1 | Python | 1,980 | 68 | import os
import neo
import matplotlib.pyplot as plt
import warnings
from snakemake.logging import logger
from pathlib import Path
def load_neo(filename, object='block', lazy=False, *args, **kwargs):
try:
filename = Path(filename)
if filename.suffix == '.nix':
kwargs.update(mode='ro')
... |
2fc8dda3301544b20c1f948e51eefd0a5c4a76f29acfa99bd46f3180afd44311 | Python | 1,981 | 68 | import os
import neo
import matplotlib.pyplot as plt
import warnings
from snakemake.logging import logger
from pathlib import Path
def load_neo(filename, object='block', lazy=False, *args, **kwargs):
try:
filename = Path(filename)
if filename.suffix == '.nix':
kwargs.update(mode='ro')
... |
23287f54b269fa46e19a1f772b0282d15355f500f4ca75d269f4e9b8fe23363a | Python | 1,982 | 67 | """
See:
"""
from typing import Union
from pprint import pprint
import pyabf
path = 'data/20191009_0005.abf'
path = '/Users/cudmore/data/theanne-griffith/07.20.21/2021_07_20_0013.abf'
abf = pyabf.ABF(path)
class epochTable():
def __init__(self, abf : pyabf.ABF):
self._epochList = []
print('sweepX pnts:', len... |
92a893b7323a086e267258f5355d422f1405c699709a59163a87e19d7f7ac72c | Python | 1,984 | 80 | import os
import glob
import random
import fnmatch
import re
import sys
class_id = {"nofight": 0, "fight": 1}
def get_list(path, key_func=lambda x: x[-11:], rgb_prefix='img_', level=1):
if level == 1:
frame_folders = glob.glob(os.path.join(path, '*'))
elif level == 2:
frame_folders = glob.glo... |
00a0774f9da34042a19cf7f8395a22796a201f421f747e8b9747072820d86794 | Python | 1,991 | 86 | """
Pytest configuration and fixtures for stats module tests.
Fixtures defined here are automatically available to all test files
in this directory and subdirectories.
"""
import pytest
import numpy as np
import polars as pl
@pytest.fixture
def random_state():
"""Provide a fixed random state for reproducibility... |
9c1ea06b728efcef09a73067d3b5509eb782ba1d6e45f72d80169d1f55cee1ab | Python | 1,991 | 75 | # -*- coding: utf-8 -*-
import os
import argparse
import logging
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
# use this format to tell the parsers
# where to insert certain parts of the script
# ${imports}
def parse_args():
# Argument Parser
parser = argparse.ArgumentParser()
#... |
a35358ad0fbecc3d95fb5d00831d2c4e06e32c0f0f68bea75db46ad1d1b37e1c | Python | 1,992 | 49 | # Copyright 2020-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""Median module."""
import numpy as np
from openfl.interface.aggregation_functions.core import AggregationFunction
class Median(AggregationFunction):
"""Median aggregation."""
def call(self, local_tensors, *_) -> np.ndarray:
... |
6c779ba3fb7780385b4863c697b68d6621ed48d29dec45abb1a0c27272bde5b4 | Python | 1,993 | 67 | # ==============================================================================
# Copyright 2023 Technical University of Denmark
# Author: Nikolas Borrel-Jensen
#
# All Rights Reserved.
#
# Licensed under the MIT License.
# ==============================================================================
from typing impo... |
7b3284dd16035801e07214ad2b7cb5930258c9b2cb2a9af218ed085a14835186 | Python | 1,995 | 63 | import random
from torch_geometric.data import Batch
class RandomView():
r"""Generate views by random transformation (augmentation) on given batched graphs,
where each graph in the batch is treated independently. Class objects callable via
method :meth:`views_fn`.
Args:
candidates (list... |
f9db0bf14d246d9a34aa6782d1382bf7f98c3f2f5128a20f63f872b2e65df93b | Python | 1,997 | 61 | import torch
from torch import sigmoid
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
class bce_loss(nn.Module):
def __init__(self, weights=None, use_gpu=False):
super(bce_loss, self).__init__()
self.weights = weights
self.use_gpu = use_gpu
def forward(self, ... |
99c4511aa3e5730ce3671af63f5919046e44ec5926798bc0c402a07cca694060 | Python | 1,998 | 53 | from setuptools import setup, find_packages
PYRATES_TEAM = "Richard Gast, Daniel Rose"
INSTALL_REQUIREMENTS = ['numpy',
'networkx',
'pandas',
'ruamel.yaml',
'sympy',
'scipy'
... |
a8c88eebd4040162e2ec4139ece270ba9dd92cb2a358f48339d1dacdcb3bdc98 | Python | 1,998 | 53 | import jax
from jax import numpy as jnp
import haiku as hk
from typing import Dict, Optional
from deeperwin.configuration import Configuration
from deeperwin.loggers import LoggerCollection
from deeperwin.utils.utils import getCodeVersion
from deeperwin.checkpoints import delete_obsolete_checkpoints
def initialize_t... |
b30c2cea8a9d9012dbdd660dd47c6599b8a5cb20dd21a56197d5a08d3ac27e01 | Python | 1,998 | 78 | import random
import pytest
from geomstats.geometry.lower_triangular_matrices import (
LowerTriangularMatrices,
StrictlyLowerTriangularMatrices,
)
from geomstats.test.parametrizers import DataBasedParametrizer
from geomstats.test_cases.geometry.base import (
LevelSetTestCase,
MatrixVectorSpaceTestCase... |
275535983c5cde4b8be042acf9cffa7f1cf6828181fe5a4fe0f88de28a7869d7 | Python | 2,000 | 55 | from nequip.data import AtomicDataDict
from nequip.nn import (
GraphModel,
SequentialGraphNetwork,
AtomwiseLinear,
AtomwiseReduce,
)
from nequip.nn.compile import CompileGraphModel
from nequip.nn.embedding import NodeTypeEmbed
from nequip.utils import dtype_from_name, torch_default_dtype
def test_grap... |
40b6cb7ef50c067b9a5e5fa0969e4d1a01ba581c63ce8c721f8bce1fb9db885c | Python | 2,000 | 76 | """Compute scores with Qptuna models"""
from __future__ import annotations
__all__ = ["Qptuna"]
import pickle
from typing import List
import logging
import json
import numpy as np
from pydantic.dataclasses import dataclass
from .component_results import ComponentResults
from .add_tag import add_tag
from ..normalize... |
0ee1d04bad4a2398a4486f5b7a036962e6c162b1f361b5fb7d19965691a9e72a | Python | 2,002 | 58 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
415f07e14e002205579b467bc17ce9335b4814c81382b4049d703f1271631c0e | Python | 2,002 | 65 | import os
import shutil
import pytest
import unittest
import torch
from reinvent.runmodes.create_model.create_reinvent import create_model
@pytest.mark.integration
@pytest.mark.usefixtures("json_config")
class TestCreateModel(unittest.TestCase):
def setUp(self):
self.workdir = self.json_config["MAIN_TES... |
7481a625a97b74681022597deabec3c73beaa318f2792638720d9b27c9382178 | Python | 2,006 | 49 | from concurrent.futures import ThreadPoolExecutor
from chromadb.config import DEFAULT_TENANT
from chromadb.test.conftest import ClientFactories
def test_multiple_clients_concurrently(client_factories: ClientFactories) -> None:
"""Tests running multiple clients, each against their own database, concurrently."""
... |
cace11f6d74497d1521ac4e290bee8aa928db82afc107ee56fcad481d010600a | Python | 2,006 | 65 | import argparse
from pathlib import Path
import os
def _arg_parser() -> argparse.ArgumentParser:
parser = argparse.ArgumentParser(
description='this is Single Sensillum Sort v.XX authors: Georg Raiser, XX',
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
argument_default=argparse.SU... |
cb83a9616b45e8a720e24eb31b03a820721e8e2ae40cda5f220f4df452c6facc | Python | 2,006 | 73 | import random
import pytest
from geomstats.geometry.poincare_half_space import (
PoincareHalfSpace,
PoincareHalfSpaceMetric,
)
from geomstats.test.parametrizers import DataBasedParametrizer
from geomstats.test_cases.geometry.poincare_half_space import PoincareHalfSpaceTestCase
from geomstats.test_cases.geomet... |
e4586a871b92b79aafd4dffbef028f75ae18503464bcf7c4c176496ee4782df0 | Python | 2,007 | 64 | """Strict conversion of SanPy values to portable JSON values."""
from __future__ import annotations
import enum
import json
import math
from dataclasses import asdict, is_dataclass
from datetime import date, datetime
from pathlib import Path
from typing import Any
import numpy as np
import pandas as pd
def json_va... |
7a384d1423a6258d7eb0bf9618d78175acc58ec480e8d8d40e12f7f938c50ce7 | Python | 2,008 | 56 | """Paths, resolved once from the repo root.
Every legacy script in ``py_src/`` hard-codes ``../chunks`` and must be run from inside ``py_src/``.
Nothing here uses a relative path; the root is found by walking up for a marker file, so the CLI
works from any working directory.
"""
from __future__ import annotations
fro... |
5271c6667350aa38c26be90c1c079af2e4d6b8edec0a7878c1cac1eb2568d079 | Python | 2,009 | 44 | # Check Pytorch installation
import torch, torchvision
from torch import nn
print(torch.__version__, torch.cuda.is_available())
import cv2
import matplotlib.pyplot as plt
import mmcv
import numpy as np
import pandas as pd
import nibabel as nib
import imageio
import os
from monai import metrics
from monai.utils.enums i... |
bde819ce22b236a3b88c51a247cb500137a60a9ff7af9b72de8799b7f8f69b16 | Python | 2,009 | 61 | # ==============================================================================
# Copyright 2023 Technical University of Denmark
# Author: Nikolas Borrel-Jensen
#
# All Rights Reserved.
#
# Licensed under the MIT License.
# ==============================================================================
import io
import... |
03167b19d602f60d3964b9b32ca4f0d39d7f11bbc443c17d08862938d7180db2 | Python | 2,010 | 74 | import threading
from types import TracebackType
from typing import Optional, Type
class ReadWriteLock:
"""A lock object that allows many simultaneous "read locks", but
only one "write lock." """
def __init__(self) -> None:
self._read_ready = threading.Condition(threading.RLock())
self._r... |
93d38e3ecde5cf5ce3f136060a5ecee0f9a5e90afd20780827c3a081eeb23be1 | Python | 2,010 | 65 | """Write the two row-oriented resources in requested representations."""
from __future__ import annotations
from pathlib import Path
from typing import Any
import pandas as pd
from .json_codec import canonical_json
def prepare_table(table: pd.DataFrame) -> pd.DataFrame:
"""Copy a table and encode structured o... |
e12821aece2ab028a247faad980a17a655035153c56305183e90b75d16cbd452 | Python | 2,013 | 41 | import numpy as np
import torch
from torch.utils.data import DataLoader
import argparse
import sys
import os
from evaluate import Tester
from data import *
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--testfile', type=str, help='path to the test file for pretrain')
p... |
1f073c6861621db964113210a55c2c1ccfcb2c191c69a4b8c1a3701fa7ecb27a | Python | 2,014 | 74 | from brian2.units import *
from brian2 import defaultclock
""" Fixed parameters required by the equations """
tau_Cl = 100.*ms # removal rate of chloride ions in excitatory cells; healthy 0.1s | epilepsy 0.5s or 1.0s, page 88, Aussel
Ek = -100.*mV # resting potential of potassium chann... |
5c91168f83ae895107969d3e4f4ecffb7dddc5cf01f70653a65c09bf1a64843f | Python | 2,014 | 42 | import json
import argparse
from rdkit import RDLogger
from torch_geometric.loader import DenseDataLoader
from dig.ggraph.method import GraphDF
from dig.ggraph.evaluation import ConstPropOptEvaluator
from dig.ggraph.dataset import ZINC800
RDLogger.DisableLog('rdApp.*')
parser = argparse.ArgumentParser()
parser.add_ar... |
e55f8561ded08285e1b9772397be93ffd6b307f4c1755b051376599a8225f861 | Python | 2,014 | 71 | from geomstats.test.data import TestData
class DiffeoTestData(TestData):
def diffeomorphism_vec_test_data(self):
return self.generate_vec_data()
def diffeomorphism_belongs_test_data(self):
return self.generate_random_data()
def inverse_vec_test_data(self):
return self.generate_ve... |
7b97b520cc90a467b52e80486b5497a5bb311a6219d1e0e99451817869c62e5f | Python | 2,015 | 60 | """Plot a geodesic of SE(2).
SE2 is equipped with the canonical Cartan-Shouten connection,
whose geodesics are the group geodesics, i.e. one parameter subgroups and the
left and right invariant canonical metric. In all cases the rotation part is
the same: it has constant angular velocity. The translation parts differe... |
2a814e3bd4a8d2b096ac32b2c9212dcfe439e38648e7dac49b37b2e2926ef6a0 | Python | 2,016 | 68 | import math
import geomstats.backend as gs
from geomstats.test.data import TestData
from .hermitian import HermitianMetricTestData
CDTYPE = gs.get_default_cdtype()
SQRT_2 = math.sqrt(2)
MAT9_33 = gs.array([[4, 0, 1j], [0, 3, 0], [-1j, 0, 4]], dtype=CDTYPE)
MAT10_33 = gs.array([[1, 1 + 1j, -3j], [1 - 1j, 0, 4], [3j... |
356a7ab4de8e7a93217121b445c02f43afff70e17788e7f7cce9e9429f23748a | Python | 2,018 | 51 | import torch
import torch.nn as nn
import torch.distributed as dist
from gather import GatherLayer
class NT_Xent(nn.Module):
def __init__(self, batch_size, temperature, world_size):
super(NT_Xent, self).__init__()
self.batch_size = batch_size
self.temperature = temperature
self.wor... |
717156af9d3ccd18d15001aaae498516f5412d0f91f6c94e225eec01db29e467 | Python | 2,019 | 54 | import glob
import argparse
from Bio.PDB import PDBParser
from Bio.PDB.Polypeptide import is_aa
import warnings
from Bio import BiopythonWarning
def three_to_one(code):
"""Convert three-letter amino acid code to one-letter code."""
aa_map = {
'ALA': 'A', 'ARG': 'R', 'ASN': 'N', 'ASP': 'D', 'CYS': 'C',
... |
877497cfe7bdb63f21dcf52f9556c90272f5f9483a698ffe48451d0ca5a9bacd | Python | 2,020 | 58 | """Tests for immutable application state used by the DANDI NiceGUI demo."""
from dataclasses import replace
import pytest
from gui.app_state import DandiAppState, DandiAppStateStore, OperationStatus
def test_store_publishes_complete_state_transitions() -> None:
"""Notify subscribers with the previous and repla... |
191a260fa3d97bcbd5c70b867f4b93d98dfc8bb5fcb3ae82f73caae0fdba23dc | Python | 2,021 | 67 | """
GPU_UTILS
====================
Nvidia-smi GPU memory parsing. Tested in nvidia-smi 370.23
The code is borrowed from Yaroslav Bulatov's post in Stack Overflow:
https://stackoverflow.com/questions/41634674/tensorflow-on-shared-gpus-how-to-automatically-select-the-one-that-is-unused/41638727#41638727
We thank Den... |
2d0614ffd8e3dde090562396c03e4d128487c821ee465ef792f3f35959843133 | Python | 2,021 | 60 | from unittest import TestCase
import torch
import torch.nn as nn
import numpy as np
from smithers.ml.layers.pcemodel import PCEModel
input_ = torch.rand(120, 50)
mean = torch.mean(input_, 0)
var = torch.var(input_, 0)
class TestPECModel(TestCase):
def test_constructor_pce_01(self):
pce = PCEModel(mean, va... |
e113071ee4ec41181f3ce49b1954697d6ab1a5521c322da36c46212aae8f29d4 | Python | 2,021 | 56 | # Copyright (c) 2022 PaddlePaddle 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 appli... |
129f7c9d2192e26136db5660c2c9ba044298c050aacef4a5b6d300dc37e956c1 | Python | 2,025 | 50 | # Copyright 2020-2025 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import pytest
import logging
from tests.end_to_end.utils import federation_helper as fed_helper
from tests.end_to_end.utils.tr_workspace import create_tr_workspace_gandlf
log = logging.getLogger(__name__)
def test_gandlf_segmentation(req... |
b2d6cfc8f8813efaa72d26ffd42a2cc42dcb28dabc44da52e2b74cffdd7c8b38 | Python | 2,025 | 66 | import logging
import chromadb.test.property.strategies as strategies
import hypothesis.strategies as st
from chromadb.api import ClientAPI
from chromadb.test.conftest import NOT_CLUSTER_ONLY, reset
from chromadb.test.property import invariants
from chromadb.test.utils.wait_for_version_increase import wait_for_version... |
9bee7e7d67d193f98c66ed46ff715bfab4f8d429589f96308a30dc0ddfb1d0cb | Python | 2,026 | 55 |
from skimage.color import gray2rgb
from sparse_ct.tool import plot_grid
from sparse_ct.data import image_to_sparse_sinogram
from sparse_ct.reconstructor_2d import (
IRadonReconstructor,
SartReconstructor,
SartTVReconstructor)
if __name__ == "_... |
9e3506b45bc14be070be6664ce76b07a9edfce2fab8cccdc6633dc43d256cdaf | Python | 2,026 | 61 | # -*- coding: utf-8 -*-
"""
Created on Tue Jun 29 14:21:17 2021
@author: Tom
"""
import sys
from tensorflow import keras as k
# Dependency - change to corret path before use!
randaugment_path = r'../../pathology-he-auto-augment/he-randaugment'
sys.path.append(randaugment_path)
# image variables
IM_FORMAT = 'jp... |
313058728732a4d3edd68b1993d0ff3686f934f07c9ec2316099572f4c5efe3e | Python | 2,028 | 58 | # Copyright 2020-2025 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import pytest
import logging
from tests.end_to_end.utils.tr_common_fixtures import (
fx_federation_tr,
fx_federation_tr_dws,
)
from tests.end_to_end.utils import federation_helper as fed_helper
from tests.end_to_end.utils.exceptions... |
518887d979653500c4b3dd5ec402bcfb4740704ed59da13650b90e012540b59b | Python | 2,028 | 65 | """Placeholders with error messages.
NumPy backend does not offer automatic differentiation.
The following functions return error messages.
"""
from geomstats.exceptions import AutodiffNotImplementedError
_USE_OTHER_BACKEND_MSG = (
"Automatic differentiation is not supported with numpy backend. "
"Use autogr... |
b5415d8d96bfa5a8d6ee25ca450dc1ffccf53ee8cc15865f88ec54b119549b08 | Python | 2,028 | 60 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
master_doc = 'index'
# -- Path setup ---------------------------------------------------... |
2b3ccfc4f34a71b30b61604565839d677875db384750d9e464ad89e2259be8bc | Python | 2,030 | 76 |
import torch
from torchvision import transforms
def get_training_augmentation():
train_transform = [
albu.HorizontalFlip(p=0.5),
albu.ShiftScaleRotate(scale_limit=0.5, rotate_limit=0, shift_limit=0.1, p=1, border_mode=0),
albu.PadIfNeeded(min_height=320, min_width=320, always_apply=True... |
79e1e09b3be927c125f7a0dc305c6e3f81b16d376a7d6d09967d96e4f52342d3 | Python | 2,031 | 69 | import os
import sys
def renumber_res(pdb_input, output_dir, start_res=1):
##get all chainIDs from the pdb file
chainIDs = []
with open(pdb_input, 'r') as f:
for line in f:
if line.startswith('ATOM'):
chainID = line[21]
if chainID not in chainIDs:
... |
fd3b3f6c01a3accb866495c29145dbbdd2aa33c4708165a2e14407d538452d26 | Python | 2,031 | 52 | from dcmrtstruct2nii import dcmrtstruct2nii, list_rt_structs
from glob import glob
import os
import platform
directory_split = "\\" if platform.system() == "Windows" else "/"
def format_scan(dicom_path, rstruct_path, savepath):
dcmrtstruct2nii(rstruct_path, dicom_path, savepath, mask_foreground_value=1, structure... |
135fd2fbe3be1aebf97968ab34ca653ed7447ed117fea5cbdc1671f752eab4e5 | Python | 2,032 | 46 | import json
import argparse
from rdkit import RDLogger
from torch_geometric.loader import DenseDataLoader
from dig.ggraph.dataset import QM9, ZINC250k, MOSES
from dig.ggraph.method import GraphAF
from dig.ggraph.evaluation import RandGenEvaluator
RDLogger.DisableLog('rdApp.*')
parser = argparse.ArgumentParser()
pars... |
d87791226c1f1ff1261036b03c17d2a7c24b3b7d7e29c13aaeb3e39e50620e72 | Python | 2,032 | 53 | """Tests for cross-cutting helpers in ``nltools.utils``."""
import warnings
import numpy as np
from nltools.utils import DesignMatrixWarning, _find_stack_level
class TestAttemptToImport:
"""``_attempt_to_import`` returns the module or ``None`` — no side-registry."""
def test_returns_module_on_success(self... |
9cbbd4d6d7053470fec92aae72d313e01321a6928963c271b4e129b73dee4b12 | Python | 2,033 | 65 | """Plot a geodesic in H2.
Plot a geodesic on the hyperbolic space H2.
With Poincare Disk visualization.
"""
import matplotlib.pyplot as plt
import geomstats.backend as gs
import geomstats.visualization as visualization
from geomstats.geometry.hyperboloid import Hyperboloid
def plot_geodesic_between_two_points(
... |
08e7303a2e2246360f8902978d9e7393de68742dc51ab19669ba3a7d8885728f | Python | 2,034 | 68 | import torch.nn as nn
from torch.utils.checkpoint import checkpoint as torch_checkpoint
class Bottleneck(nn.Module):
expansion = 4
def __init__(
self,
in_planes,
planes,
stride=1,
groups=1,
activation_class=nn.ReLU,
conv_class=nn.Conv3d,
affine=... |
ed6b5c77e1dce6daaeee9fcaa620c4907abea58fefbdaee1de27612689fcd858 | Python | 2,034 | 48 | import numpy as np
from bone_segmentation.DataStructures import ImageToPatientTransformation
from bone_segmentation.Viewer import ImageViewer
import config
from data.dataset import BratsTest
dataset_prefix = 'test'
dataset = BratsTest(None, None, None)
experiment_name = 'UNet-20220221-Brats184-256-geoaug-imaug-valid-... |
7f1a339ce62ddfbe97f232d5474b715a29fc6821afb62a86b94f52008960ae22 | Python | 2,035 | 65 | """
Visualize the wave detection by means of clustering the detected trigger
in (time,x,y) space.
"""
import numpy as np
import quantities as pq
import argparse
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
import seaborn as sns
import random
import warnings
from utils.io_utils import lo... |
4b5f4d637e6739bfc9433a2bd440ef4f15dd5cec9b95f6a5646c8c1e61a9786a | Python | 2,036 | 47 | # flake8: noqa
# pylint: skip-file
pybids_inputs = {
"bold": {
"filters": {"suffix": "bold", "extension": ".nii.gz", "datatype": "func"},
"wildcards": ["subject", "session", "acquisition", "task", "run"],
}
}
parse_args = {
"bids_dir": {
"help": "The directory with the input datase... |
c68d5ce0509752122108f9fa8a273aa8b79492dd3363eef3960c443fe303df2c | Python | 2,036 | 64 | from __future__ import annotations
from typing import Any
import pytest
from hypothesis import given
from hypothesis import strategies as st
from pytest_mock import MockerFixture
from snakebids.plugins.version import Version
from snakebids.tests.helpers import allow_function_scoped
@given(version=st.text())
def te... |
59ad84b0c6b3409c9ed9f08c5714db643554611ee6aaf530318194d1b7c2f550 | Python | 2,038 | 63 | from . import register_scheduler
from .base_scheduler import BaseLRScheduler
import argparse
import math
@register_scheduler("fixed")
class FixedLRScheduler(BaseLRScheduler):
"""
Fixed learning rate scheduler with optional linear warm-up strategy
"""
def __init__(self, opts, **kwargs) -> None:
... |
7a7f2650f9c3d010f60cc8c7c32f79b6ca26141dbeb52d80e0747d88f5d6a183 | Python | 2,039 | 60 | import numpy as np
import pandas as pd
from nltools.cross_validation import KFoldStratified
def check_valid_split(train, test, n_samples=None):
# Use python sets to get more informative assertion failure messages
train, test = set(train), set(test)
# Train and test split should not overlap
assert tra... |
06b834c5b51d07afda72ce02407c0a10e9e769c09c9d76fd7b60f6591c6dec9c | Python | 2,040 | 59 | import operator as op
import re
from typing import List, Tuple
from hypothesis import given
from hypothesis import strategies as st
from snakebids.utils.utils import matches_any
@given(st.text(), st.lists(st.text()))
def test_matches_any_with_eq_operator(item: str, match_list: List[str]):
if item not in match_l... |
f807fd72d77be9122a2e2d5cd9a579346c1519d6629da391a71b2b635f7d3775 | Python | 2,042 | 84 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
1e8bcfae4da843170da2e10740e14d484ac94417214186d6fbb5798b70be9784 | Python | 2,043 | 77 | #!/usr/bin/env python
import os
directory = "."
# All files in directory
allFiles = os.listdir(directory)
# Only the files we care about
files = []
for i in allFiles:
if i.startswith("snpCounts") and "human" in i:
files.append(i)
print(files)
snp_dict = {}
counter = 1
total = str(len(files))
for i in ... |
95d0d8a6c5ba13496d7ef95b2c53f6cbd19cc2927aaa6c4b3d1ecf222ce45f03 | Python | 2,044 | 64 | import os
from pathlib import Path
import shutil
import numpy as np
from torch import nn, optim
import torch
def test_xyz_read_write():
from mlspm.utils import read_xyzs, write_to_xyz
xyz_path = "./test.xyx"
# fmt: off
xyz = np.array([
[ 0.0, 0.1, 0.2, 0.3, 1], # (x, y, z, charge, eleme... |
c73d59052c61c40555083639070d3a2a01d776bf794706248c457e76f3c1bef8 | Python | 2,044 | 75 | # -*- coding: utf-8 -*-
from __future__ import print_function, division
from builtins import input
"""
Decoder speed test.
Results on i7-8700K machine:
1000 Hz, 6 channels, 500-sample window:
sklearn 0.17.1(pip) = 32.7 Hz, 0.19.1(conda) = 28.8 Hz
with intel-mkl library:
sklearn 0.17(pip) = 25.0 Hz, 0.19.1(conda)... |
95ccc7cee41bbfd63dccb31c418d2e6b1e2033403f4d3ced5899bda6cb4a6ace | Python | 2,045 | 52 | from torch import nn
class MLPHeader(nn.Module):
def __init__(self, input_dim, hidden_dim, output_dim):
super().__init__()
self.network = nn.Sequential(
nn.Linear(input_dim, hidden_dim),
nn.ReLU(),
nn.Linear(hidden_dim, output_dim)
)
def forward(self... |
3d6ed999cfdd32c67ae3418b0520e651aab7e4854da8f79f6830158f5c50dbab | Python | 2,046 | 73 | from PymoNNto import *
class LIF_main(Behavior):
def initialize(self, n):
self.set_parameters_as_variables(n)
n.v = n.vector('uniform')*n.v_rest
n.fired = n.vector() > 0
n.dt = 0.1
def iteration(self, n):
n.v += ((n.v_rest-n.v)+n.I)*n.dt
n.fired = n.v > n.v_th... |
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