sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
8a706e7643676eb8755c8befe648c3e079254c109b894693d75e8ce4fde31ad4 | Python | 5,541 | 148 | # b0_correction.py
import numpy as np
import matplotlib.pyplot as plt
import SimpleITK as sitk
import scipy.ndimage
def formula(value):
"""Converts the raw B0 map values into millimeter shifts."""
G_read_percentFLASH = 5.563298 / 100
PVM_GradCal = 42797.5
new_value = value / (G_read_percentFLASH * PVM... |
f75cfc5c85f435d9962634de676caec9d917c37c76305fec604e4dac3c0eb43a | Python | 5,544 | 132 | import torch
import torch.nn as nn
import copy
from .so3 import SO3_Embedding
from .radial_function import RadialFunction
class EdgeDegreeEmbedding(torch.nn.Module):
"""
Args:
sphere_channels (int): Number of spherical channels
lmax_list (list:int): List of ... |
6f71177f54a85ea7093a7791ebe80d4aa424b6a502e439982954a4be11389392 | Python | 5,545 | 182 | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmengine.optim import OptimWrapper
from mmengine.structures import PixelData
from torch import nn
from torch.optim import SGD
from mmseg.models import SegDataPreProcessor
from mmseg.models.decode_heads.cascade_decode_head import BaseCascadeDecodeHead
fr... |
29c93fd853659aa98ccd226c8e1566ba1fdb2c5d21196df2ebd2e4a79123ab14 | Python | 5,546 | 157 | import shutil
import numpy as np
from guppy.extractors import (
CsvRecordingExtractor,
DoricRecordingExtractor,
NpmRecordingExtractor,
NwbRecordingExtractor,
TdtRecordingExtractor,
)
from guppy.orchestration.read_raw_data import _build_event_to_extractor
from guppy_test_data import STUBBED_TESTING... |
5b1fe670fc3f3bc6157361ba680cf022a957c4b5843336063517d265289dbbef | Python | 5,549 | 153 | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmengine import Config
from mmengine.structures import PixelData
from mmseg.models.decode_heads import Mask2FormerHead
from mmseg.structures import SegDataSample
from mmseg.utils import SampleList
from .utils import to_cuda
def test_mask2former_head()... |
e51d28710cd74cf8de38751add747d5b1ce393096c40b4b01c1d1c89c1bd9415 | Python | 5,551 | 153 | #!/usr/bin/env python
import logging
import os
import os.path as op
import re
import subprocess
import time
import json
from collections import deque, OrderedDict
from datetime import date
import inotify.adapters
from inotify.constants import IN_MODIFY, IN_CREATE, IN_ISDIR
from py.path import local as localpath
from t... |
5f4914cdfdbff5311d178f55138341834a3d8b6f4e50dea66d4030de17269201 | Python | 5,552 | 165 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Apr 6 10:38:45 2023
@author: george
"""
#%matplotlib qt
from matplotlib import pyplot as plt
import numpy as np
import skimage.io as skio
from skimage.filters import threshold_otsu
from skimage.morphology import closing, square, remove_small_objects,... |
db08216ed2328211a306d8516b27972b107a8262bc94a0e53a493200d4b187a5 | Python | 5,552 | 197 | """Expsyn synapse parameter fitting"""
# pylint: disable=R0914
import os
import argparse
import bluepyopt as bpopt
import bluepyopt.ephys as ephys
def create_model(sim, do_replace_axon, return_locations=False):
"""Create model and optionally return locations dict"""
if sim not in ['nrn', 'arb']:
r... |
cfa9da6d17ee0e0441c6b2728f35ca9cb6452bf7250e48865756555610462749 | Python | 5,556 | 145 | import numpy as np
import pandas as pd
import panel as pn
import pytest
from guppy.analysis.io_utils import write_hdf5
from guppy.analysis.standard_io import write_binned_metrics_to_hdf5
from guppy.frontend.binned_metrics_view import (
BinnedMetricsView,
binned_metrics_sites,
build_binned_metrics_view,
)
... |
c178288e5253a1c405ef34859de3cb89b837e8c16cf8d8fc6dca5697810715bc | Python | 5,557 | 133 | # coding=utf-8
# Copyright 2021 The IDEA 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 a... |
fd068aad013e931bc82f9e40c0fac20f17880c70715e5d4e9cee690534ced302 | Python | 5,557 | 202 | """Chat REST API endpoints for room messages."""
from datetime import UTC, datetime
from typing import Annotated
from fastapi import APIRouter, Query, status
from sqlalchemy import func
from sqlmodel import col, select
from zndraw.broadcast import broadcast_to_room
from zndraw.dependencies import (
AccessEditDep... |
f58e4aa0b1882b2486d27af12b1427dc1400c2e4c3b794cd4266ff05abb455ad | Python | 5,558 | 175 | import math
from typing import Optional
import torch
import torch.utils.data
from torch.utils.data import DataLoader
import pytorch_lightning as pl
from datasets.utils.pad_tensors import PadTensors
from datasets.utils.transforms import (
Flatten,
)
import tonic
from tonic.transforms import ToFrame
import hydra
im... |
9d3784168c51ecb7149395fa7fd8c17c577ab9e1ba7a4caf3d1af969dc4026c4 | Python | 5,559 | 159 | #!/usr/bin/env python3
#
# Copyright 2015, Daehwan Kim <infphilo@gmail.com>
#
# This file is part of HISAT 2.
#
# HISAT 2 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 of the License, or
# ... |
af3558a4ff8e7f0a10dc6b3934364c0c4a7dca5dd90c7e411b03251ce0dd0483 | Python | 5,559 | 137 | import tensorflow as tf
import gpflow
from gpflow.kernels import MultioutputKernel, Combination, Kernel
from gpflow import covariances
from gpflow.config import default_float, default_jitter
from gpflow.base import TensorLike
from gpflow.inducing_variables import (
SharedIndependentInducingVariables,
)
from gpflow.... |
2af41c8e3021e5e60feb5259c69e36f22619e963f32c34e56ebf1d62e7ea3040 | Python | 5,563 | 159 | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule
from mmseg.registry import MODELS
from ..utils import resize
from .decode_head import BaseDecodeHead
class ACM(nn.Module):
"""Adaptive Context Module used in APCNet.
... |
9e1209df040d3218098c6d3c73abb04b957c27c9689cffea75b3a5b0b7a29292 | Python | 5,572 | 199 | import torch
from torch import nn
from einops import rearrange, repeat
from einops.layers.torch import Rearrange
# helpers
def pair(t):
return t if isinstance(t, tuple) else (t, t)
# classes
class PreNorm(nn.Module):
def __init__(self, dim, fn):
super().__init__()
self.norm = nn.LayerNor... |
acf166a4066784f873c27e916692260e1e76064592ae98b948591ba50e05d54b | Python | 5,574 | 127 | # gff3 to fasta
from parse_gene_anno import parse_gff_tree
import subprocess
CP = {"A": "T", "T": "A", "C": "G", "G": "C",
"N": "N", "a": "t", "t": "a", "c": "g", "g": "c"}
def r_c(seq):
new_seq = []
for c in seq[::-1]:
new_seq.append(CP[c])
return "".join(new_seq)
def get_fa(fn):
ch ... |
24d52dd9eaf260c01ef7b618a24485266aa152cdceccf6dde1115bfafc34ffc4 | Python | 5,577 | 160 | from utils.QuickNII_functions import read_QUINT_JSON, find_plane_equation
from utils.generate_target_slice import generate_target_slice
import numpy as np
import cv2
import matplotlib.pyplot as plt
import nrrd
import sympy as sp
from sympy import symbols, solve
def generate_rectangular_image(img, pts):
# De... |
0d3de85b3c0796a1fda665b4dd3070ed8b6d68a2dd1faf19e522d542fabeae9a | Python | 5,580 | 130 | import logging
import src.datahandlers.mesh as mesh
import src.datahandlers.umls as umls
from src.babel_utils import glom, read_identifier_file, write_compendium
from src.categories import ORGANISM_TAXON
from src.metadata.provenance import write_concord_metadata
from src.prefixes import MESH, NCBITAXON, UMLS
from src.... |
1be8605933f6018ee00fa337a4e74399155c37ec18ef776f7957b44b362583d8 | Python | 5,583 | 182 | import os
import ot
import torch
import random
import numpy as np
import scanpy as sc
import scipy.sparse as sp
from torch.backends import cudnn
# from scipy.sparse import issparse
from scipy.sparse.csc import csc_matrix
from scipy.sparse.csr import csr_matrix
from sklearn.neighbors import NearestNeighbors
def filter_... |
40e0a02d3dc57b99cce46089eee6725691cb363cf0b62ceef68179ead5fcde14 | Python | 5,586 | 149 | """Unit tests for the shared clique-building helper.
``src.model.cliques.glom_from_files`` is the skeleton that each compendium's
``compute_cliques_for_impact_report`` (and, ideally, its ``build_compendia``) routes
through. The anatomy CLI test exercises it end-to-end; these tests cover the generic
hooks directly: the... |
dca1542d92466107073da15803ae6ac15f64af67f4f357257e719d286f563ee0 | Python | 5,587 | 175 | # !git clone https://github.com/uber-research/TuRBO/
# Commented out IPython magic to ensure Python compatibility.
# %cd TuRBO
# !pip install .
import numpy as np
import pandas as pd
from tqdm import tqdm
import time
from collections import namedtuple
from abc import ABC, abstractmethod
from collections import default... |
151c0584af9b95d21a92f397e63fbb3b0657d41a840c50dd5295c91a8aa1fe89 | Python | 5,591 | 128 | import numpy as np
import tensorflow as tf
import time
import datetime
import os
import sys
import h5py
from pathlib import Path
import evidential_deep_learning as edl
from .util import normalize, gallery
class Deterministic:
def __init__(self, model, opts, dataset="", learning_rate=1e-3, tag=""):
self.lo... |
ab355070f74696b97474036c7428ab9b307e6d2b2a855f1560b542201cfaab79 | Python | 5,592 | 153 | import numpy as np
import pandas as pd
import pytest
import xgboost as xgb
from xgboost import testing as tm
from xgboost.testing.data import run_base_margin_info
try:
import modin.pandas as md
except ImportError:
pass
pytestmark = pytest.mark.skipif(**tm.no_modin())
class TestModin:
@pytest.mark.xfai... |
88f535e9e8642048ec48ef238351fcaebe73ca6197a356587cb74a1ad08a6835 | Python | 5,593 | 156 | # Copyright DST Group. Licensed under the MIT license.
import inspect
from pprint import pprint
from CybORG.Agents.SimpleAgents.BaseAgent import BaseAgent
from CybORG.Shared.Enums import TernaryEnum
from ipaddress import IPv4Network
SUCCESS_TO_TEXT = {
TernaryEnum.FALSE.value: 'The action failed!',
TernaryEnu... |
9c920f39f856589e37401ad497eeb92d1eefec3de36e3223baa2f5e9e0559f23 | Python | 5,593 | 196 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Utility functions for downloading datasets from OSF
"""
import os
import re
from collections import defaultdict
from pkg_resources import resource_filename
import json
MATCH = re.compile(
r'space-(\S+)_(?:den|res)-(\d+[k|m]{1,2})_'
)
def _groupby_match(fnames):
... |
00b4d33f810d6d76e0772b479d44031d34dae4c96f36b9b2a503f98084ba2a1d | Python | 5,596 | 132 | #!/usr/bin/env python
## ----------------------------------------
## scikit-ribo
## ----------------------------------------
## a module for preprocessing gtf/bed files
## ----------------------------------------
## author: Han Fang
## contact: hanfang.cshl@gmail.com
## website: hanfang.github.io
## date: 10/28/2016
#... |
60da5b01dab2facbc8b24d1e9fd7c0bef3af10b4721096f4974a0d1cb635512f | Python | 5,596 | 182 | import ast
import json
import logging
from typing import List
import numpy as np
import torch
from ase import Atoms
from e3nn import o3
from mace import modules
from mace.data import AtomicData
from mace.data.utils import (
config_from_atoms_list,
random_train_valid_split,
)
from mace.tools import AtomicNumber... |
9a768643c60c5692b5a41686ffdf5ace2189093d0c286b1191392410feb6397f | Python | 5,597 | 86 | import argparse
from fengshen.pipelines.tcbert import TCBertPipelines
from pytorch_lightning import seed_everything
def main():
seed_everything(123)
total_parser = argparse.ArgumentParser("Topic Classification")
total_parser = TCBertPipelines.piplines_args(total_parser)
args = total_parser.parse_args()... |
102e4bed4aadf2d4e90058e4e728be3999c8cb43ea876df958e1c0b6c2ab6c5d | Python | 5,606 | 147 | import numpy as np
import torch.nn.functional as F
from scipy.interpolate import interp1d
from scipy.signal import medfilt
from scipy.ndimage import maximum_filter1d, gaussian_filter1d
def cone_postprocessing(cone_pred, w, maximum_filter_size):
cone_prob = F.softmax(cone_pred, dim=0).detach().cpu().numpy()
co... |
e59f05ed4ced3eabd67c8cf51ac64d824871e58b9683c454611486bdbaeb4d12 | Python | 5,607 | 146 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
# pyre-strict
# pyre-ignore-all-errors[2,3]
import sys
import time
from typing import Any, Callable, Dict, List
import numpy as np
def timeit(
num_iters: int = -1, warmup_iters: int = 0
) -> Callable[[Callable[[], Any]], Callable[[], Dict[s... |
0d0ea09b20e1b957e67d146d894cb9aa7aae59b85608d2101955c44514b54f35 | Python | 5,610 | 161 | """
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 torch.optim as optim
from torch.nn.parallel.distributed import DistributedDataParallel
from ocpmodels.common import d... |
806ae31b75cc9e4e0d75e77d63fa71438fb2c73d21dca0e920cb352d3151bc8a | Python | 5,611 | 140 | from natsort import natsorted
import numpy as np
from pathlib import Path
import os
from os.path import join
from nnunet_mednext.dataset_conversion.utils import generate_dataset_json
import SimpleITK as sitk
import gc
import multiprocessing as mp
from functools import partial
def preprocess_dataset(ribfra... |
849614b00cf175d9862605570ef46787011453638dc6c6ac49a47a801ebc727b | Python | 5,612 | 168 | from rest_framework import status
from medperf.tests import MedPerfTest
from parameterized import parameterized, parameterized_class
class CertificateTest(MedPerfTest):
def generic_setup(self):
# setup users
cert_owner = "cert_owner"
ca_owner = "ca_owner"
key_owner = "key_owner"
... |
a2a95e41bf84dcdcc9b5126afb4c25e7fefe273a66b94e66a32ee1a029899790 | Python | 5,614 | 153 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import numpy as np
import pandas as pd
import deeplift
from deeplift.layers import NonlinearMxtsMode
from deeplift.conversion import kerasapi_conversion as kc
import utils
# =============================================================================
# set variables... |
f4d82b6d50bacefa7671192f6d849560edb356588769565c2df15b7f1460cd92 | Python | 5,620 | 166 | import numpy as np
def mvmd(signal, num_modes, alpha, init=0, sampling_rate=1, tolerance=1e-3, tau=1e-2, verbose=False):
"""
Multivariate Variational Mode Decomposition (MVMD)
The function MVMD applies the "Multivariate Variational Mode Decomposition (MVMD)" algorithm to multivariate or multichannel data ... |
883dec16aefb8c832bd836674216c407320fb1aa7e6ebb81aedce345df31e2e4 | Python | 5,626 | 137 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# 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://w... |
7029f84c04216f1b8a78012d4489bcc6081c654f923c53ea501f1a08b4f910dd | Python | 5,630 | 134 | # coding=utf-8
# Copyright 2022 IDEA-CCNL The HuggingFace Inc. team. 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
#
... |
164352e5f1b09cc80419c05091225fb4290df3b1f8f9b6a5c901617d76f782a1 | Python | 5,631 | 209 | from brainsmash.config import parcel_labels_lr
from .utils import is_string_like
import tempfile
from os import path, system
import nibabel as nib
import pandas as pd
from pathlib import Path
import numpy as np
"""
Flexible data I/O - based on murraylab/brainsmash
"""
def dataio(x):
"""
Data I/O for core cla... |
09ce5815a2ba1944bf2a8be5c384b3b932635b364ecd5b0866f44d34821bd976 | Python | 5,637 | 138 | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List, Optional
from torch import Tensor, nn
from mmseg.registry import MODELS
from mmseg.utils import (ConfigType, OptConfigType, OptMultiConfig,
OptSampleList, SampleList, add_prefix)
from .encoder_decoder import EncoderDecod... |
c1423ac21e8b866ada54a87301d626979be2a230eab5d84e6b4213aa7a07cd0d | Python | 5,638 | 122 | import numpy as np
import matplotlib.pyplot as plt
from sklearn.linear_model import LogisticRegression
from grid_cell.manifold_fitter import label_mesh
from grid_cell.gkr import GKR_Fitter
import grid_cell.torus_geometry as tg
from scipy.stats import norm
from sklearn.decomposition import PCA
from grid_cell.ori_tuning_... |
5d4eb4bd34a19dd57dfff0df20e320eb434c27956efc1e89a7abc7c8b4218c31 | Python | 5,640 | 146 | import glob
import os
import sys
import numpy as np
import pickle
import tqdm
import warnings
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import util.config as config
from numpy.core.fromnumeric import argsort
import lib.heart_volume.heart_utils as hu
def count():
base_path = os.... |
922e8ad40f52243c2d0e3f0f318ef742a664ad336887138ef85b071b379e386a | Python | 5,641 | 171 | # -*- coding: utf-8 -*-
"""
Functions for step 1
Author: Tiziana Tocci
"""
import os
import pandas as pd
import numpy as np
def select_one_condition(df, cond_column, cond_to_select):
"""
Function to select part of dataframe based on a condition.
Parameters
----------
df : pandas... |
29c9f0078bd43a1dbc6bba27653bac1e035ec0bbb18c1ae06418e13e0ffb00ac | Python | 5,644 | 163 | """Functions to create neuroml morphology"""
"""
Copyright (c) 2016-2022, EPFL/Blue Brain Project
This file is part of BluePyOpt <https://github.com/BlueBrain/BluePyOpt>
This library is free software; you can redistribute it and/or modify it under
the terms of the GNU Lesser General Public License version 3.0 as pu... |
c051dd38ad12b890ca8b6d5e0b00e4f1d12c72fb28917b24081428af9710c4f7 | Python | 5,644 | 159 | """
Custom build backend for XGBoost Python package.
Builds source distribution and binary wheels, following PEP 517 / PEP 660.
Reuses components of Hatchling (https://github.com/pypa/hatch/tree/master/backend) for the sake
of brevity.
"""
import dataclasses
import logging
import os
import pathlib
import tempfile
from... |
83c444fa1980a022facf2ebd17abd4ba8ed2a21ab669832c701ef27ff00a9d0b | Python | 5,646 | 163 | # -*- coding: utf-8 -*-
from typing import List, Tuple, Union
from django import forms
from django.forms.widgets import Widget
import catmaid.fields
class Swatch(Widget):
"""A simple widget that shows a color field for the RGBAWidget."""
template_name = 'catmaid/widgets/swatch.html'
class LabeledMultiWid... |
4303bc9f87978d9b9cad4f6d0f3a60c7eb0ca344491986a98d3342e48b4e645b | Python | 5,647 | 198 | from luna.paths import LunaPaths
from luna import candidate_info, dataset
from luna.ct import Ct
from luna.prepcache import LunaPrepCacheApp
from torch.utils.data import DataLoader
from Utils.models import *
from Utils.TrainModelLUNA import *
from Utils.config import *
from tqdm import tqdm
import matplotlib.pyplot as ... |
b7d35c43b7da11077a4f129090d3f3f26fd62ebaf0a9eb9cfa045fcafe2157bc | Python | 5,648 | 148 | import numpy as np
import tensorflow as tf
import tensorflow.keras.backend as K
import itertools
def face_normals(vertices, faces):
edges1 = tf.gather(vertices, faces[:, 1]) - tf.gather(vertices, faces[:, 0])
edges2 = tf.gather(vertices, faces[:, 2]) - tf.gather(vertices, faces[:, 0])
return tf.linalg.l2_... |
a0a0e22fc3800b4a7b4fa0e2fc737c78223c97fee325a3064bdca72d0d957d95 | Python | 5,650 | 172 | import re
from pathlib import Path
import pytest
from .util import get_data, get_main_output, needs_docker
test_factors = [(""), ("--parallel"), ("--debug"), ("--parallel --debug")]
@needs_docker
@pytest.mark.parametrize("factor", test_factors)
def test_wf_without_container(tmp_path: Path, factor: str) -> None:
... |
e1f4a742ba7edb0562d1c73e4bb270e5451cdad537ac15bd02fc78e7a5f22ef0 | Python | 5,650 | 183 | import numpy as np
from transforms3d.affines import decompose, compose
from transforms3d.euler import mat2euler, euler2mat
from scipy.ndimage import rotate, shift
def transf_from_parameters(T, R):
"""
Use python module transforms3d to extract transformation matrix from
translation and rotation parameters.... |
73f7089ae5fdacdfcaaf3deca1ca6d9f84d89e7deb9cf97589622a9ef17ba42f | Python | 5,657 | 181 | # Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import math
from typing import Tuple
import torch
import torch.nn as nn
import torch.nn.functional as F
from sam2.modeli... |
3df13f643ebf5dc6eeb0780881cfd2fffcb4b486917a7f655da2ed3f8278dcd6 | Python | 5,658 | 142 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# -----------------------------------
# @File : model.py
# @Time : 2024/03/13 17:59:40
# @Author: Zhang, Zehong
# @Email : zhang@fmp-berlin.de
# @Desc : None
# -----------------------------------
import torch
import torch.nn as nn
import math
import numpy as np
import ... |
134562bca0165bbf44749e6ee624ba30ade385ddf770d3bcd0b6af596f94268e | Python | 5,660 | 159 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import argparse
import os
import shutil
import itertools
from multiprocessing import Pool
import numpy as np
from dmriqcpy.analysis.stats import stats_mean_in_tissues
from dmriqcpy.io.report import Report
from dmriqcpy.io.utils import (add_online_arg, add_overwrite_arg... |
66f04d9cb1862aaedd7880b533500ccf5d2016ff67192ebafbd7b37ed4c3dc06 | Python | 5,663 | 171 | """Create tables for BluePyOpt paper"""
import json
def load_json(filename):
"""Load struct from json"""
return json.load(open(filename))
def create_feature_fields():
"""Create fields for param.json"""
features = json.load(open('features.json'))
fields_content = ''
print(features)
... |
905f307c4d4507859d613e103fcd10a2f8c62b931df8888a244a71a2dac1cb9b | Python | 5,663 | 194 | """Tests that run the program in a subprocess"""
import subprocess
import sys
import os
import pytest
from utils import datapath, assert_files_equal, cutpath
def test_run_cutadapt_process():
subprocess.check_call(["cutadapt", "--version"])
def test_run_as_module():
"""Check that "python3 -m cutadapt ..."... |
ade20f3cf355e4f3506cf67a9dc87bc902227f79d21d7cc641e0eab274c133f7 | Python | 5,667 | 158 | """Regression tests: local_token must not be used as client auth token.
When the CLI starts a local server, StateFileSource resolves the auth token
from state.json. Previously it returned the raw local_token (a random string)
which the server rejected as an invalid JWT (401 Unauthorized).
The fix stores a real admin ... |
d9d0facfe9a699a0f794b9561157f0a93333d33f85045a4a72bec32fd1f434a4 | Python | 5,672 | 158 | # -*- coding: utf-8 -*-
import datetime
import json
import tempfile
import os
import numpy as np
import pyn5
from pathlib import Path
from django.db import transaction
from django.test import TransactionTestCase, override_settings
from catmaid.models import WritableStack
from catmaid.control.stack import get_writabl... |
36c983f6c6efef851b38bb2e33f66da1387328c5d11427093aba88b428105ded | Python | 5,677 | 236 | #!/usr/bin/env python3
#
# Copyright 2018, Chanhee Park <parkchanhee@gmail.com> and Daehwan Kim <infphilo@gmail.com>
#
# This file is part of HISAT 2.
#
# HISAT 2 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 Foundatio... |
cdcdf1bf9b2f6b30e6bfc859ac85b9475ecf8ed30f7bb86f6c3101233ea3b37f | Python | 5,677 | 130 |
from CybORG.Shared.RewardCalculator import RewardCalculator
from CybORG.Simulator.State import State
from CybORG.Simulator.Actions.GreenActions import GreenAccessService, GreenLocalWork
from CybORG.Simulator.Actions.AbstractActions.Impact import Impact
from CybORG.Simulator.Actions.Action import InvalidAction
class B... |
0447fde40a844e2070537a98e2be633eaa5ccac8f6eb8c980533bda3aeff125f | Python | 5,679 | 147 | # _*_ encoding: utf-8 _*_
import copy
__author__ = 'wjk'
__date__ = '2020/6/30 11:00'
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class GPTDecoder(nn.Module):
r"""TransformerDecoder is a stack of N decoder layers
Args:
decoder_layer: an instance of the Transforme... |
f12d990b5f787856329b5686a67c622793b888f3ddd47e1ff379fbd576dfa2cb | Python | 5,679 | 160 | from rest_framework import status
from medperf.tests import MedPerfTest
from parameterized import parameterized, parameterized_class
class BenchmarkTest(MedPerfTest):
def generic_setup(self):
# setup users
bmk_owner = "bmk_owner"
prep_mlcube_owner = "prep_mlcube_owner"
ref_model_... |
201999a962eba27e0eeb948d78320ff20f2182b7fb14195712a454d27f353670 | Python | 5,684 | 206 | from kgx.graph.nx_graph import NxGraph
from kgx.graph_operations.graph_merge import (
merge_all_graphs,
merge_graphs,
merge_node,
merge_edge,
)
def get_graphs():
"""
Returns instances of defined graphs.
"""
g1 = NxGraph()
g1.name = "Graph 1"
g1.add_node("A", id="A", name="Node ... |
4a88370e6d1348714463eafcb5dfbd93f6a9145c354ec473b7f040558250bab6 | Python | 5,684 | 149 | # This file is part of h5py, a Python interface to the HDF5 library.
#
# http://www.h5py.org
#
# Copyright 2008-2013 Andrew Collette and contributors
#
# License: Standard 3-clause BSD; see "license.txt" for full license terms
# and contributor agreement.
"""
Testing native complex number datatypes.
"""
im... |
7c507670dc7208fff73e49d1152349c52ff0d66a358917a9e7dbfa36e0941ac9 | Python | 5,685 | 160 | # Copyright (c) OpenMMLab. All rights reserved.
"""Modified from https://github.com/JunMa11/SegWithDistMap/blob/
master/code/train_LA_HD.py (Apache-2.0 License)"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from scipy.ndimage import distance_transform_edt as distance
from torch import Tensor
fr... |
4efcf4110c12a6991f10b493e3dd78a05670975af5d5a9e9722b9d16321c5687 | Python | 5,688 | 164 | import os
from medperf.commands.association.utils import (
get_experiment_associations,
get_user_associations,
)
import yaml
from typing import List
import medperf.config as config
from medperf.entities.interface import Entity
from medperf.entities.schemas import TrainingExpSchema
from medperf.account_managemen... |
e5b1c1e7d2d5ebc90e1e712af2b1e58d7e7413777a9eb45d22da3c57528dfb31 | Python | 5,688 | 152 | try:
import cPickle as pickle
except:
import pickle
import gzip
import numpy
import os
import matplotlib
import matplotlib.pyplot as plt
from scipy import integrate
import pandas as pd
"""DATA IMPORT"""
base_dir1 = '/mnt/csoport31-2/Modellezo_csapat/CA1_pyramidal/Spine_project_validation_results58/Basic_set_n... |
bb705ed18dce9d1371a799d2474c977809b5bd5df75fcc1f1f92a78ef5824414 | Python | 5,689 | 159 | import torch
from egnn_pytorch import EGNN, EGNN_Sparse
from egnn_pytorch.utils import rot
torch.set_default_dtype(torch.float64)
def test_egnn_equivariance():
layer = EGNN(dim=512, edge_dim=4)
R = rot(*torch.rand(3))
T = torch.randn(1, 1, 3)
feats = torch.randn(1, 16, 512)
coors = torch.randn(... |
c764aeda6f42a80a670d73a1937ab1ea05b70b14c11f74538575a8ccaf2a35fa | Python | 5,690 | 139 | #!/usr/bin/env python
## ----------------------------------------
## scikit-ribo
## ----------------------------------------
## a module for visualization riboseq data
## ----------------------------------------
## author: Han Fang
## contact: hanfang.cshl@gmail.com
## website: hanfang.github.io
## date: 10/28/2016
##... |
d2a2af4795610f5e839327f054a7152a1328e0b691181705ac24c83971790b6e | Python | 5,690 | 167 | import nibabel
import os
import numpy as np
import dicom
import yaml
from scipy.ndimage import zoom
def prepare_tcia_images(input_path, output_path, cases, img_height, img_width):
for n, case in enumerate(cases):
print("\rprocessing tcia images:", n + 1, "/", len(cases), end="")
volumeID = "{:0>4... |
718e4dc06ec5c6d63a204a293c14367117d9d6f290e9704f6868a40e052c9fee | Python | 5,691 | 185 | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmseg.models.backbones.beit import BEiT
from .utils import check_norm_state
def test_beit_backbone():
with pytest.raises(TypeError):
# pretrained must be a string path
model = BEiT()
model.init_weights(pretrai... |
144033fe2b78576e8bee0886e2b1d1be6b22ff0d1de70b4e6c2cfae179612d68 | Python | 5,695 | 159 | #!/usr/bin/python
import logging
import os
import re
import sys
import polars as pl
from isorefiner.common import get_version, func_with_log, run_command, filter_bam
logger = logging.getLogger(__name__)
def main(args):
try:
# Set variables
raw_input_gtf = os.path.abspath(args.input_gtf)
... |
ca5736df0f5ac193ac5a9890d210c3859b5450901b819420175ecf06bba2c60b | Python | 5,696 | 118 | """Generate a mock NWB file for testing the NWB recording extractor with core pynwb 4.0 events.
IMPORTANT: This script must be run with pynwb>=4 and ndx-fiber-photometry==0.2.3 installed.
The events types (``EventsTable``, ``TimestampVectorData``) are part of the core NWB schema as of
NWB Schema 2.10.0 / pynwb 4.0, s... |
b9209e67a4f81a2919e7a9d287a998c562cd71944b74ccba807806fef2b63de6 | Python | 5,698 | 179 | from __future__ import print_function
import pytest
import numpy as np
from numpy.testing import assert_allclose
from keras.utils import test_utils
from keras import optimizers, Input
from keras.models import Sequential, Model, load_model
from keras.layers.core import Dense, Activation, Lambda
from keras.utils.np_util... |
a431d1e057de64d860ceed2fbf9e9aae7ff90dc93f6519844a10a8196036bab5 | Python | 5,699 | 140 | import numpy as np
import scipy.ndimage
from collections.abc import Iterable
from scipy.interpolate import interpn
from .transform import LinearTransform
class Slicing(tuple):
'''Slice tuple used for indexing subregions of a numpy array.'''
def __new__(cls, start, stop):
if len(start) != len(stop):
... |
d7823d6fe120a267045c4a4746ac026cf53a07e6647fb8eb35e6d120410d4c6e | Python | 5,701 | 175 | import re
import traceback
from collections import defaultdict
import requests
from more_itertools import chunked
from src.prefixes import KEGGCOMPOUND
###
# KEGG
###
# KEGG has a set of compounds that have a 'sequence' tag
# according to https://www.genome.jp/kegg/compound/:
# Peptide entries in KEGG COMPOUND ... |
575e9fdae17815860588299edd6115f5820337cc84fe091bd43d03bf72069253 | Python | 5,707 | 123 | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
from typing import List
import mmengine.fileio as fileio
from mmseg.registry import DATASETS
from .basesegdataset import BaseSegDataset
@DATASETS.register_module()
class NYUDataset(BaseSegDataset):
"""NYU depth estimation dataset. The file st... |
c9befeda18ea5d20d1b1a5ca2a4ce572ddef0de318dd6897b0864c13f30da4fc | Python | 5,709 | 155 | # -*- coding: utf-8 -*-
import logging
from django.db import connection
from django.conf import settings
from django.contrib.auth import get_user_model
from django.contrib.auth.models import Group
from django.contrib.auth.decorators import user_passes_test
from django.http import HttpRequest, JsonResponse
from django.... |
132c3b19c4aa13f8d4cc0232b7773282ad2295296d547f83203dbc00040e14b4 | Python | 5,711 | 160 | # Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from logging import getLogger
import os
import sys
import torch
import socket
import signal
import subprocess
logger = g... |
e4b1c0e3258bc588b38723d7a5209f0a7df4da612ce3a54b2e951ee6ed8c2055 | Python | 5,714 | 137 | import jax.numpy as jnp
import jax.tree_util as tree
import numpy as np
from ase import Atoms
from typing import Any, Iterable, List, Mapping, Union
from jraph._src import graph as gn_graph
ArrayTree = Union[jnp.ndarray, Iterable['ArrayTree'], Mapping[Any, 'ArrayTree']]
# TODO: move this to mlff jraph_utils at som... |
33499da485055fa20b9f89fe73e73d18d3314ce2389110a1238e311318b456b6 | Python | 5,715 | 160 | """Base class for Lie groups."""
import numpy as np
from geomstats.invariant_metric import InvariantMetric
from geomstats.manifold import Manifold
import geomstats.vectorization as vectorization
class LieGroup(Manifold):
""" Base class for Lie groups."""
def __init__(self, dimension, identity):
sup... |
adba502385c7feaf45ad48f8332c0beb00b9a20f6c0006fa0a3b3e3f44dc93d3 | Python | 5,715 | 125 | import torch
from torchfunction.device import AutoDevice as device
BATCH_SIZE = 256
def get_cdm_input(bs=BATCH_SIZE, noise_inp=0.1):
input_tensor = torch.zeros(bs, 61, 4).to(device)
ctx = torch.randint(2, (bs, )).to(device)
cnd1 = torch.randint(6, (bs, )).to(device)
cnd2 = torch.randint(6, (bs, )).to(... |
b7a631a46a23b34139c0f5e20eae7152e88ffbed9536d6639ca0ded47408c227 | Python | 5,717 | 167 | import matplotlib.pyplot as plt
import matplotlib
import numpy
from importlib import reload
import sys
import os
import importlib
import types
# print(sys.modules.keys())
import multiprocessing
import multiprocessing.pool
original_packs = sys.modules.copy()
try:
import cPickle as pickle
except:
import pickle
im... |
fc18531b4e53e5ea80f8e7a8d406db542a02851a9a6ec390704dc5d4e7462057 | Python | 5,717 | 195 | """Unit tests for the AccessReadDep/AccessEditDep/AccessManageDep composites.
Uses the session fixture + direct calls to the async composites, bypassing
FastAPI's DI machinery (deferred to Tasks 10/11 integration tests).
"""
import pytest
from sqlmodel.ext.asyncio.session import AsyncSession
from zndraw.access impor... |
68d1d476570fd49ac096c0e9ebfb70863fbc4e26b69885ae50e512b0dde3b5f6 | Python | 5,720 | 199 | import binascii
import collections
import datetime
from typing import Optional
import pydicom
import SimpleITK as sitk
ImageMeta = collections.namedtuple(
'ImageMeta',
[
'path',
'series_uid',
'manufacturer',
'seq',
'series_desc',
'tr',
'te',
'fli... |
e9d7016635e0ad608705df7ae29d6c14eac4ae9e764a35aa4b604a1145cfa258 | Python | 5,720 | 123 | from typing import Union, Tuple, Optional
from torch_geometric.typing import (OptPairTensor, Adj, Size, NoneType,
OptTensor)
import torch
from torch import Tensor
import torch.nn.functional as F
from torch.nn import Parameter
import torch.nn as nn
from torch_sparse import SparseTens... |
3e0ea404373124753751fc09c074434ac114f29e78c532670686448f7d7c2ad7 | Python | 5,728 | 161 | """Tests of satisfying SoftwareRequirement via dependencies."""
import os
import tempfile
from getpass import getuser
from pathlib import Path
from shutil import which
from types import ModuleType
import pytest
from cwltool.context import LoadingContext
from cwltool.load_tool import load_tool
from cwltool.software_r... |
6be67c0d0decf23c6fbe4f9b5ba99f3300abcfde0e6926df8f287b332bd75a7c | Python | 5,728 | 178 | from pathlib import Path
import subprocess
import pandas as pd
from typing import Dict, Any
from ..logger import logger
from .workflow import SnakemakeWorkflow, WorkflowError
class NormalizationError(Exception):
pass
def validate_normalization_inputs(config: Dict[str, Any]) -> None:
"""
Validate inputs re... |
1f4b7decdab82187ece3a8c33512a98947c708c9fa4410d65118d576bc9b3afa | Python | 5,729 | 172 | # -*- coding: utf-8 -*-
"""
Created on Wed Jan 26 15:26:55 2022
@author: A0067501
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
class Interpolate(nn.Module):
"""
https://discuss.pytorch.org/t/using-nn-function-interpolate-inside-nn-sequential/23588
"""
de... |
e920425fe8ceab808baf22674b1de3a3137adac972313da383fdace1a8d5c6cb | Python | 5,734 | 171 | """
Tests for Transformer parallel mode (multiprocessing-based partitioned export).
Currently exercises the only supported combo: DuckDB source + N-Triples sink.
"""
import os
import tempfile
import pytest
try:
import duckdb
DUCKDB_AVAILABLE = True
except ImportError:
DUCKDB_AVAILABLE = False
from kgx.tr... |
6886cc5dcaa0524568583b95056b5cf3cf9f2fc3b5e17698a95790ff48d50cf2 | Python | 5,736 | 155 | import pandas as pd
import os
import numpy as np
import matplotlib.pyplot as plt
from CCF_translator.deformation.interpolation.NearestNDInterpolator import (
NearestNDInterpolator,
)
import nibabel as nib
def interpolate_volume(volume, mask):
# Get the shape of the volume
shape = volume.shape
# Create... |
ebb744fce802fe08b9da365d1d76495e8cd5a625d00e793e3b1aa28d94b182e3 | Python | 5,736 | 177 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
# pyre-strict
from typing import Optional
import torch
import torch.nn as nn
class SqueezeExcitation(nn.Module):
"""
Generic 2d/3d extension of Squeeze-and-Excitation (SE) block described in:
*Hu et al., Squeeze-and-Excitation ... |
2e21bde5c68ac74b73e3746c44deef51555d4ca8c9a1f9a480d3cf830b8cc253 | Python | 5,739 | 119 | """Read and write NWB files against the schema they were written with.
hdmf keeps one type map per process. Importing an NWB extension registers the installed version of
that extension there, and from then on a file whose cached namespace holds a *different* version is
built against the installed spec rather than its ... |
2454809b0215c6bbb6ea80a7c1a7cec96ba791a760d4659e9238ecfbc1eff39b | Python | 5,741 | 59 | ##
# CPCantalapiedra 2021
test_hmm = """
HMMER3/f [3.1b2 | February 2015]
NAME COG0012.faa.final_tree.fa
LENG 10
ALPH amino
RF no
MM no
CONS yes
CS no
MAP yes
DATE Fri Aug 3 19:28:36 2018
NSEQ 4522
EFFN 4.170202
CKSUM 2788465937
STATS LOCAL MSV -12.2126 0.69661
STATS LOCAL VITERBI -13.1336 0... |
45c8e75779d70fba1d9383e9b272869b3ec14c2ddb592ed3b6b1579e4c8c197c | Python | 5,741 | 177 | # --- Imports ---
import os
import torch
import umap
import numpy as np
import tqdm
import matplotlib.pyplot as plt
import Adversarial_Observation as AO
from Adversarial_Observation.Swarm import ParticleSwarm
# --- Global Config ---
optimize = 3 # Target class for the attack
# --- Main Function ---
def main():
... |
f39e79ec03b4621f05f97cf6267a4bfc70b766f857864b40116587c10befd228 | Python | 5,741 | 172 | # src/zndraw_joblib/models.py
from datetime import UTC, datetime, timedelta
from enum import StrEnum
from typing import Any, Optional
from uuid import UUID, uuid4
from sqlalchemy import (
Boolean,
DateTime,
ForeignKey,
Index,
String,
Text,
UniqueConstraint,
func,
)
from sqlalchemy.orm i... |
3880cc84f251cf171417a66d76070f51221dde370a4f6c2a1cd57c819b1847c7 | Python | 5,742 | 158 | # I tested with torch==2.4.0 (2.6.0 gives troubles, but we an deal with those if we want to go with that version)
# note there is a folder I am pulling from for imports aa couple of lines down, then also NNUnet V1 needs to be
# installed in the environment
import os
import subprocess
import shutil
import argparse
from... |
4ed92925a7aa21cb6dd168d208463105b6244f642d485efcb10b4cf9d0d6ec80 | Python | 5,743 | 180 | """Integration tests for /v1/groups endpoints."""
import pytest
from helpers import _register_and_login, auth_header, create_test_user_in_db
from httpx import AsyncClient
from sqlmodel.ext.asyncio.session import AsyncSession
@pytest.mark.asyncio
async def test_create_group_creator_is_admin(client: AsyncClient) -> No... |
286891577fcdb78f24541b0ad3b8066ac06bd61b739e041d3efe65ebc862e872 | Python | 5,747 | 144 | """Unit tests for resolving a session folder's acquisition format for NWB export.
NWB export reads a session's traces through one format's interfaces, so it has to collapse the set
of formats GuPPy detects in a folder into a single choice -- and refuse the folders where it cannot.
"""
import pytest
from guppy.utils.... |
0ee80a8f573866c59ab2f3c5008776bc72b24c117fc5fcb6ba7e837dc42db471 | Python | 5,748 | 158 | import SimpleITK as sitk
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
pd.options.mode.chained_assignment = None # default='warn'
import nibabel as nib
import os
from utils import get_mean_value, get_R_value, get_S_value, z_score_normalisation, optimale_scale_identification, hessian, get_Ht
f... |
ac83608ad3c21629ed4a5be0a9b31be4bd9341dcab247bdb422d5482999f1760 | Python | 5,748 | 115 | import numpy as np
import pandas as pd
import os
def load_target(gene: str, df_Sp: pd.DataFrame, df_Un: pd.DataFrame, n_replicates: int) -> tuple:
assert type(n_replicates) == int, "n_replicates must be an integer."
Sp_star = df_Sp.loc[gene].to_numpy(dtype=np.float64).reshape(n_replicates, -1).T
Un_star = ... |
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