sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
e1b8e53a876933b84e6863e9f287bc57180961114ca9db8d2eb456ce1dc30024 | Python | 4,602 | 135 | import mne
from scipy.signal import detrend
import sys, os
from tqdm import tqdm
from glob import glob
import numpy as np
import itertools
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import re
from sklearn.metrics import accuracy_score, balanced_accuracy_score
from sklearn.model_selection... |
2236303689bf094f5ae577290651fb8b3f7af2b331c5ab68ef110bb8cdcfaecd | Python | 4,603 | 118 | import os
import matplotlib.pyplot as plt
import matplotlib.patches as mplpatches
import numpy as np
import pysam
from bisect import bisect_left
from tqdm import tqdm
from scipy import stats
def getReadQual(bam):
readToQual = {}
samfile = pysam.AlignmentFile(bam, "rb")
for s in samfile:
if s.is_map... |
107204c1298c94819c6613d706b51fbb42f4744a71525108c03300f4df8bdb8c | Python | 4,604 | 134 | import glob
import os
import json
import argparse
import pandas as pd
def get_parser():
parser = argparse.ArgumentParser(description='Check if AcquisitionDuration, RepetitionTime, VolumeTiming, '
'SliceTiming are available in the JSON metadata for *_T2star.json ')
... |
4e14622103ab02d7b5894c9bd47cbd5bafaca8c3613a61d9ef2ba20f572cace0 | Python | 4,606 | 136 | """Progress reporting channel for pipeline steps.
Modelled on :mod:`logging`: deep pipeline code emits progress by calling the module-level
functions here, with no reporter threaded through its signature, and the top level decides
where those emissions go. Emitting when nothing is bound is a no-op, so the workers can ... |
0d2b6f197dead74933fa35016417cae3add862ae0fa9f92afa0104eee81ea327 | Python | 4,607 | 72 | import os
import numpy as np
import matplotlib.pyplot as plt
import hickle as hkl
from grid_cell.ploter import error_bar_plot
from grid_cell.toy_locf import LOCFExperiment, run_experiments
from global_setting import *
n_boot = 5
# base_params = {'n_neuron': 5, 'n_data': 5000, 'std_frac': 0.2, 'dl': 0.1, 'box_size': [0... |
3861ac0e63fa84b1b4cb95101904f208a2242f7ab51687012eb7da120fa800ef | Python | 4,608 | 105 | # Module for neural network models
# This module defines the neural network architectures used for facial emotion recognition,
# including a recurrent neural network with an attention mechanism.
import torch
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
from torch import nn
class Attention... |
0611fa49cbdd40b53396efe2148903b94851d241accf924a13390fabad82abd5 | Python | 4,609 | 148 | """Tests for Presets accessor class.
Tests the Presets(MutableMapping[str, Preset]) accessor by mocking
APIManager to verify mapping interface and convenience methods.
"""
import json
import tempfile
from pathlib import Path
from unittest.mock import MagicMock
import pytest
from zndraw.accessors import Presets
from... |
a83e2e02b63dc6e969ce629207968a7fb7344ae390b2c299b439c1a26007bd97 | Python | 4,611 | 130 | import random
import torch
from pathlib import Path
from torch.utils import data as data
from basicsr.data.transforms import augment, paired_random_crop
from basicsr.utils import FileClient, get_root_logger, imfrombytes, img2tensor
class Vimeo90KDataset(data.Dataset):
"""Vimeo90K dataset for training.
The k... |
33cd4aa57bc9b293ad18f629fa70c5fdf9cc4c8f303943a683280d12da48321f | Python | 4,613 | 172 | import itertools
import logging
import math
from contextlib import contextmanager
from typing import Callable, Optional, TypedDict, Union
import torch
import torch.nn as nn
class _Stats(TypedDict):
variance_in: float
variance_out: float
n_samples: int
IndexFn = Callable[[], None]
def _check_consisten... |
04411168ce59fd7b876adb36429115869084ffd6dc6758d01fc09f51fcc7d85e | Python | 4,615 | 132 | from medperf.exceptions import CleanExit, InvalidArgumentError
import pytest
from unittest.mock import ANY
from medperf.tests.mocks.execution import TestExecution
from medperf.tests.mocks.dataset import TestDataset
from medperf.tests.mocks.benchmark import TestBenchmark
from medperf.commands.dataset.associate import A... |
ddd37f597cb42923a49c23aeae11cec680ec8f1b1359af1aeae1d68bd8aa27dd | Python | 4,616 | 132 | '''
Date: 2022-11-21 15:53:39
LastEditors: yuhhong
LastEditTime: 2022-11-22 23:35:52
'''
import os
import argparse
import pprint
import pandas as pd
from rdkit import Chem
# suppress rdkit warning
from rdkit import RDLogger
RDLogger.DisableLog('rdApp.*')
from utils import ATOM_LIST, convert2cls
'''
preprocess:
1.... |
1f6ea3d68fe865ae01cfb5d05b608cb5e2080222d7f07f7bce794eddc0bc19e2 | Python | 4,619 | 141 | _base_ = [
'../_base_/datasets/ade20k.py', '../_base_/default_runtime.py',
'../_base_/schedules/schedule_160k.py'
]
norm_cfg = dict(type='SyncBN', requires_grad=True)
crop_size = (512, 512)
data_preprocessor = dict(
type='SegDataPreProcessor',
size=crop_size,
mean=[123.675, 116.28, 103.53],
std=... |
800720ea448ea6b110f8f18a3e5ec181c76ad2424327500f67e323366abf244d | Python | 4,620 | 126 | import json
from tqdm import tqdm
import os
from sklearn.utils import shuffle
import re
import argparse
def cut_sent(para):
para = re.sub('([。，,！？\?])([^”’])', r"\1\n\2", para) # 单字符断句符
para = re.sub('(\.{6})([^”’])', r"\1\n\2", para) # 英文省略号
para = re.sub('(\…{2})([^”’])', r"\1\n\2", para) # 中文省略号
... |
e8b49498e2d615ac5c8b44290abdfe6e00c5dad92072b84d9cd8a9c30b42d2db | Python | 4,624 | 126 | import importlib
import numpy as np
import random
import torch
import torch.utils.data
from functools import partial
from os import path as osp
from basicsr.data.prefetch_dataloader import PrefetchDataLoader
from basicsr.utils import get_root_logger, scandir
from basicsr.utils.dist_util import get_dist_info
__all__ =... |
0fdf24db2a3bea224bd52f763052f6bb8d69f8f1299fbfe9ea3a8d1c9c6ed2f7 | Python | 4,628 | 90 | from PyQt5 import QtWidgets, QtCore, QtGui
class DeleteMultipleDialog(QtWidgets.QDialog):
def __init__(self, parent, data_manager):
QtWidgets.QDialog.__init__(self, parent, flags = QtCore.Qt.WindowTitleHint | QtCore.Qt.WindowCloseButtonHint)
self.data_manager = data_manager
se... |
2956d225effee72990548d04ca5440b9501920d412bfb11446ba7351c177c33f | Python | 4,631 | 88 | import argparse
import torch
import scanpy as sc
from vgae import agent
import joblib
def str2bool(v):
if isinstance(v, bool):
return v
if v.lower() in ('yes', 'true', 't', 'y', '1'):
return True
elif v.lower() in ('no', 'false', 'f', 'n', '0'):
return False
... |
f9783f51b964a92d23688363ef0f5f527e5dcd7017b39bccd852f06b1fc9d8af | Python | 4,631 | 159 | """
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 io
import logging
import os
import random
import numpy as np
import pytest
import requests
import torch
from ase.io import read
from... |
03230d0ce679a45ba3205df42a59e16688323ecc278168ef6f4c3da02fcf5c08 | Python | 4,634 | 133 | # 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.
import sys
import json
import parser
from pathlib import Path
import numpy as np
import util
def select_examples_TQA(data... |
83dc2c05c884b41d4650804c64ec82e429f94bc14f7c49fd9df5916850e1f4f5 | Python | 4,640 | 153 | import logging
from abc import ABC, abstractmethod
from typing import Optional, Union
from .files import InputFiles
from .utils import Progress
from .modifiers import (
SingleEndModifier,
PairedEndModifier,
PairedEndModifierWrapper,
ModificationInfo,
)
from .steps import SingleEndStep
logger = logging... |
0d3846a79dbcb57bd5ca7e2a9456f548d9812124703dca3917777ce861b7b7a3 | Python | 4,641 | 129 | #!/usr/bin/env python3
"""
The purpose of this script is to convert redcap data (ethnicity, gender, race)
into a table for Inclusion Enrollment Report
Parameters
------------
csv_fname: str
the REDcap downloaded file, which contains ethnicity, gender, race information
Return
------------
df_tally: pand... |
2984f14b72764fd7a7040b2affe8cf2c7374467ef7b1e5deb55cae3bca29a89d | Python | 4,642 | 161 | #!/usr/bin/env python
# coding=utf-8
# Copyright 2023 Statistics and Machine Learning Research Group at HKUST. All rights reserved.
"""A simple shell chatbot implemented with lmflow APIs.
"""
import logging
import json
import os
import sys
sys.path.remove(os.path.abspath(os.path.dirname(sys.argv[0])))
import warnings
... |
2efffadaf0e8c84291afc7ff9cce7c0b99826e86ee60ea2b1fa92d63415ab648 | Python | 4,642 | 113 | import numpy as np
import matplotlib.pyplot as plt
import os
from sklearn.decomposition import PCA
from sklearn.model_selection import train_test_split
from grid_cell.sphere_manifold import Circle_Manifold, get_circle_mesh, plot_cov_ellipse
from grid_cell.gpr_covnet import GPR_CovNet
from grid_cell.manifold_fitter impo... |
154666117a0d881bea8a6ad6824e1d43c9bb7ef042f7a48355e67921260fc649 | Python | 4,643 | 91 | """Pipeline tests for the GARD_label concord, run against a real built concord.
Skipped by default unless pytest is run with --pipeline. Run with:
uv run pytest tests/pipeline/test_gard_label.py --pipeline --no-cov -v
GARD_label is the only concord in this pipeline derived from labels rather than an asserted map... |
2b060d09c875a4154f367a891d664a718032cec4a80e25f9f580111825ea1ca1 | Python | 4,643 | 151 | """Long-signal speedup benchmark: Python vs Rust multitaper.
Runs `multitaper_spectrogram` on increasingly long signals at Fs=200 Hz and
reports median wall-clock time over 3 trials (one warm-up run is discarded)
for both the pure-Python and Rust backends.
Usage:
python test_rust_speedup.py
Prints a compact mark... |
6ae3210a625f9d5d8ef10429e522932affe6a8ef0eb1e21a3d1e30c1d7b1276e | Python | 4,650 | 132 | import argparse
import pathlib
import ase
import ase.io as aio
import numpy as np
import torch
from mace.calculators import mace_off
from rdkit import Chem
from simgen.calculators import MaceSimilarityCalculator
from torch_scatter import scatter_logsumexp
def rdkit_mol_2_ase(mol):
if mol is None:
return ... |
057eeb63fae654d726507b649f2e3e62f9b589ecae3f7b1be34ef4006edbc0b1 | Python | 4,651 | 148 | #!/usr/bin/env python
"""
MeteWIBELE: finalize prioritization module
Copyright (c) 2019 Harvard School of Public Health
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, inclu... |
ae2205ac5d2d820acee98910ebad4c989881bafa2b2aaea39779fbe9c871f392 | Python | 4,651 | 108 | from __future__ import annotations
from typing import Optional
from heudiconv.utils import SeqInfo
def create_key(
template: Optional[str],
outtype: tuple[str, ...] = ("nii.gz", "dicom"),
annotation_classes: None = None,
) -> tuple[str, tuple[str, ...], None]:
if template is None or not template:
... |
6782c7d36f1e7510fdd787a19f481bdb46b5b1f6d7305f8f38d9fb6879a32820 | Python | 4,653 | 142 | # Copyright (c) 2021, EleutherAI
#
# 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 writi... |
ae365ef1597b14c7d94d3622a09893e7cd333b26094349b34d1d3c9336503fa9 | Python | 4,659 | 144 | """
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 argparse
from pathlib import Path
class Flags:
def __init__(self) -> None:
self.parser = argparse.ArgumentParser(
... |
8d8c800744bbb1fa12d4440d83bea0d30b7e105618bbb4dd49f0df175e8391f0 | Python | 4,660 | 138 | from typing import Union
import numpy as np
from abc import ABC, abstractmethod
NEURAL_METADATA_REGISTRY = {}
def register_metadata(name: str):
"""
Decorator to register a neural dataset class.
Args:
name (str): name of the dataset to be used.
Returns:
function: returns the... |
e7171b5119634d4683749dae68a0b64fc58fa7d930ef471f5cd9982a47834f07 | Python | 4,660 | 98 | # sys.path.append("/home/plent/Documenten/Gitlab/NeuralODEs/jax_neural_odes")
from jaxkineticmodel.load_sbml.sbml_load_utils import separate_params
from jaxkineticmodel.load_sbml.sbml_load_utils import construct_param_point_dictionary, separate_params_jac
import numpy as np
import jax.numpy as jnp
import jax
class J... |
bb89d7321622452fa51119b1795ebb58fc0ae7aab489bc321352db8505862a1f | Python | 4,661 | 129 | import requests
import os
from .ProvenanceObject import ProvenanceObject
from .dependency import Dependency
from .task_status import TaskStatus
from .dataset import DataSet
from .performance import Performance
from datetime import datetime
dfa_url = os.environ.get('DFA_URL',"http://localhost:22000/")
class Task(Pro... |
2428608314fce5d46bca8bd6e54383ff901a3900274da1f1755fb37e48768bfd | Python | 4,667 | 133 | import os
from kgx.graph.nx_graph import NxGraph
from kgx.sink import SqlSink
from kgx.transformer import Transformer
from tests import TARGET_DIR
from kgx.utils.kgx_utils import create_connection, drop_existing_tables
NAMED_THING = "biolink:NamedThing"
SUBCLASS_OF = "biolink:sub_class_of"
def test_write_sqlite():
... |
09ee4a0c6106ceb3c0a5ee7787467c8ad857cebd6ebae24e6856ce3b13241671 | Python | 4,668 | 154 | # #############################
#
# Copyright (C) 2018
# Jennifer Dreiling (dreiling@gfz-potsdam.de)
#
#
# #############################
import numpy as np
from BayHunter import rfmini
class RFminiModRF(object):
"""Forward modeling of receiver functions based on SeisPy (Joachim Saul).
"""
def __init__(... |
91a8da730f67702b004c51f39b301758aaa7ccfca4abc49c08aaf153aa9a26ee | Python | 4,670 | 154 | """CircleCurve geometry for ZnDraw."""
import math
import typing as t
import numpy as np
from pydantic import Field, field_validator
from .base import BaseGeometry, InteractionSettings, Vec3
class CircleCurve(BaseGeometry):
"""A circular/elliptical curve for camera orbit paths.
The curve lies in the XY pl... |
9a56c52418979aee43851237eef3005d766ba6cdb7c4a3a4997a2864c7c56d3d | Python | 4,670 | 128 | import copy
from typing import cast
from cwl_utils.types import CWLObjectType
from ruamel.yaml.comments import CommentedMap
from schema_salad.exceptions import ValidationException
from schema_salad.sourceline import indent
from .context import LoadingContext, RuntimeContext
from .errors import WorkflowException
from ... |
8d08486a5894a8e34dae033333b4632151ce0116049f2dbf54ca634031d55736 | Python | 4,672 | 117 | import os
import gensim
from Utils.dataloader_RSNA_BONE import *
from Utils.models import *
from Utils.TrainModelRSNA import *
from Utils.config import *
from multiprocessing import Process
# OPTIONAL: Load the "autoreload" extension so that code can change
#%load_ext autoreload
# OPTIONAL: always reload modules so t... |
6c550fe86931db80a4817e0c7e0f61b3572fd638147b8547072d41f6188f2f93 | Python | 4,673 | 190 | import argparse
import dataclasses
import glob
import json
import os
import re
from typing import List
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
fig_width = 2.5
fig_height = 2.1
plt.rcParams.update({"font.size": 6})
colors = [
"#1f77b4", # muted blue
"#d62728", # brick red
... |
781ac3bd67238fbde89103b9f94a6a9e83bd01c4283af3acf210c202dba577d7 | Python | 4,673 | 179 | """Recording classes"""
"""
Copyright (c) 2016-2020, 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 published
by the Fre... |
b25f33097bad303ea98e9bce4809dfe079d754890ad2e58df71d0e4221f352e4 | Python | 4,673 | 156 | import os
from sys import stderr
from kgx.utils.kgx_utils import get_toolkit
from kgx.validator import Validator
from kgx.graph.nx_graph import NxGraph
from kgx.transformer import Transformer
from tests import RESOURCE_DIR
from bmt import Toolkit
toolkit = Toolkit()
def test_validator_bad():
"""
A fake test ... |
e10976ddf12394e8586d1aaa95f40f43e8588ff238189bfa15240c30c2132dea | Python | 4,673 | 123 | """Regression: a failing taskiq dispatch must release the inflight lock."""
from __future__ import annotations
import asyncio
import contextlib
import uuid
async def _seed_internal_provider(async_session_factory):
"""Create an @internal provider in the DB and return its full_name."""
from zndraw_auth import... |
f04a25b92f799e9faf6a2bbe57fb80d6f8b05f4c5c07634007af157d0eb0f34a | Python | 4,674 | 133 | # -*- coding: utf-8 -*-
import django.core.validators
from django.db import migrations, models
import django.db.models.deletion
forward = """
CREATE OR REPLACE FUNCTION refresh_skeleton_summary_table() RETURNS void
LANGUAGE plpgsql AS
$$
BEGIN
-- Remove all entries
TRUNCATE catmaid_ske... |
c7d2129d9aa1cda9d72c86690ec16c58c9040462d3dbf16c9a468a9541a91d76 | Python | 4,676 | 133 | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmseg.models.backbones import TIMMBackbone
from .utils import check_norm_state
def test_timm_backbone():
with pytest.raises(TypeError):
# pretrained must be a string path
model = TIMMBackbone()
model.init_weig... |
d2fd95c35b2a941a35a577ebd6bf9033a0036831af065c1fd8ac45f5a77151e3 | Python | 4,680 | 106 | """
Copyright (c) 2022 EPFL-BBP, All rights reserved.
THIS SOFTWARE IS PROVIDED BY THE BLUE BRAIN PROJECT ``AS IS''
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE BLUE BRAIN PROJE... |
bd48a9f00165a84d500737d2b427b6f710135e0605b8be149132e8ad66236418 | Python | 4,681 | 185 | import torch
from torch import nn, einsum
from torch.nn import Module, ModuleList
import torch.nn.functional as F
from einops import rearrange, repeat
class GEGLU(Module):
def forward(self, x):
return x * F.gelu(x)
def FeedForward(dim, mult = 4, dropout = 0.):
return nn.Sequential(
... |
f1682030e7875b536638f9a3e0d3946ae6adda6f11e97eb5ac403cb2ba022b7f | Python | 4,681 | 136 | """IBEA selector"""
"""
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 published
by the Free So... |
020e25df1931c4b9e88ab278801aa4bf8d8c4a95acda60fd69024efdf518405f | Python | 4,683 | 123 | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import os.path as osp
import mmengine
import numpy as np
import torch
def vit_jax_to_torch(jax_weights, num_layer=12):
torch_weights = dict()
# patch embedding
conv_filters = jax_weights['embedding/kernel']
conv_filters = conv_filters.p... |
18e8b8afbaf399ef0ff483eef193edecce4388a2642a6246c5492a506bda2be1 | Python | 4,684 | 140 | '''
Date: 2022-11-23 11:29:36
LastEditors: yuhhong
LastEditTime: 2022-12-12 12:57:28
'''
import os
import argparse
import numpy as np
from tqdm import tqdm
import yaml
import pandas as pd
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
from torch.utils.data import DataLoa... |
928649e0d65e607954e2856e34a1390e1c2ac3e147ba353e0edd669bd87b622e | Python | 4,692 | 138 | # -*- coding: utf-8 -*-
"""
Created on Tue Sep 24 18:54:47 2024
@author: AC
"""
import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, c... |
16050fe591aaa4b1c7990d3db9a707118640901448ebe9f3ce66cf78fd1089ed | Python | 4,695 | 114 | import logging
from dataclasses import dataclass
import torch
from mace.data import AtomicData
from simgen.manifolds import PriorManifold
from simgen.utils import get_system_torch_device_str
# if get_system_torch_device_str() == "mps":
# torch.set_default_dtype(torch.float32)
# else:
# torch.set_default_dtyp... |
5373590c93ff3b39cc99ca63f4719afad90336869288ff470313002d5e83082f | Python | 4,695 | 103 | # pytest unit tests for isct_antsRegistration
import os
import numpy as np
import nibabel as nib
from spinalcordtoolbox.utils.sys import run_proc, printv
from spinalcordtoolbox.utils.fs import tmp_create, rmtree
from spinalcordtoolbox.scripts import sct_dice_coefficient
def test_ants_registration():
"""
T... |
ee40ec0a72833ba8ed1fa511c0ca30ef4a11eb97590af0f96e630491875cd2ab | Python | 4,698 | 128 | import shutil
from pathlib import Path
import pandas as pd
import pytest
from guppy.testing.api import (
group_analysis,
label_groups,
locate_run_folder,
step1,
step2,
step3,
step4,
)
from guppy_test_data import STUBBED_TESTING_DATA
@pytest.mark.filterwarnings("ignore::UserWarning")
def ... |
4241bb24d10e73b88b49ec57b9655561bb441e296caa2c167fad905ff4d9f94b | Python | 4,702 | 123 | """
Command-line entry point for GuPPy (Guided Photometry Analysis in Python).
Keep this module cheap to import. The pipeline steps run their multiprocessing pools under
the "spawn" start method, and a spawned worker is a fresh interpreter that must materialize
``__main__`` before it can unpickle its task. Here ``__ma... |
7919ca40f9e617d3ebf56d19171721442d81a998ad9097e9aafedf3582cc290f | Python | 4,702 | 130 | """
Function to compare two mRS probability distributions and find the
difference in utility across the full distributions.
e.g. when both probability distributions have mRS=0, the difference
in utility is 0. When one has mRS=0 and the other mRS=1, the difference
is 0.97 - 0.88 = 0.09.
"""
import numpy as np
def f... |
8a1ab1ce2557774e4939d9b3bc0d28c0485199ce3f712bfc2d8f2bd1c864115b | Python | 4,710 | 105 | from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
forward = """
CREATE TABLE data_source (
id int GENERATED BY DEFAULT AS IDENTITY PRIMARY KEY,
user_id int REFERENCES auth_user(id) NOT NULL,
project_id in... |
1dab4b4077f74ffecb3e57eaf22f0d3a4da9252edce1ee733d5aa18b99c7c799 | Python | 4,711 | 139 | """
GBMPurity.py
This script performs inference using the GBMPurity model on given input data.
The input data path is specified via command line arguments.
"""
import argparse
import torch
import pandas as pd
import numpy as np
from typing import Tuple, List, Optional
import sys
sys.path.insert(1, './src/modelling')
... |
4aec46dc3db16b890606e7f0d9f03555369354f964d5a70be6cb1623df637ebc | Python | 4,714 | 173 | import numpy as np
from myphdlib.general.toolkit import psth2
from sklearn.decomposition import PCA
from sklearn.preprocessing import MinMaxScaler, StandardScaler
from sklearn.impute import SimpleImputer
from sklearn.cluster import AgglomerativeClustering
from sklearn.metrics import silhouette_samples, silhouette_score... |
b358aa761c16870df9aa80247eff29fd11ed81a8afdb5cc4ba6621d19bd125a0 | Python | 4,715 | 122 | import pandas as pd
import numpy as np
from scipy.integrate import solve_ivp
def calc_bold_signal(neurons, results_coherent, results_incoherent, results_nonadap, T, dts,
dts_bold = 100, t0 = 0, t0adap = 6000):
"""
Calculates the blood-oxygen-level-dependent (BOLD) signal generated by the simulated
neuronal activ... |
d9ae7c69a47dfbecbf9a86632032a45f66e63e0c447ef77625fc1383cf21773e | Python | 4,715 | 131 | """
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 os
import numpy as np
import pytest
from ase.io import read
from ase.neighborlist import NeighborList, NewPrimitiveNeighborList
from... |
a39a5e6d34b64a1a3710029d01e127cc59609d32d4b5a319ed01792ed257dc24 | Python | 4,719 | 152 | """
trainGBMPurity.py
This script trains GBMPurity using single-cell RNA-sequencing data from GBMap resource (Ruiz-Moreno et al., 2022).
It includes data preprocessing, model definition, and training with early stopping.
Author:
Morgan Thomas <scmpht@leeds.ac.uk>
Date: 2024-07-08
"""
import anndata as ad
im... |
5072af77f87b2a9ce270f337c09f1ca280e0945c835e04ddac4ad180cb24dd68 | Python | 4,722 | 170 | # SPDX-License-Identifier: Apache-2.0
# coding: utf-8
# YuanYang
import math
import cv2
import numpy as np
def nms(boxes, overlap_threshold, mode='Union'):
"""
non max suppression
Parameters:
----------
box: numpy array n x 5
input bbox array
overlap_threshold: float ... |
63aeeef1e3f1586a55a208e2cf7a0a38bd527d7439dd033dc8355dbd4401fbdd | Python | 4,727 | 98 | """Pipeline tests for the NCBIGene data handler.
Downloads the full gene_info.gz (>1 GB compressed) and runs
pull_ncbigene_labels_synonyms_and_taxa over every row, so these tests are marked both
`pipeline` and `slow` and are skipped by default. Run with:
uv run pytest tests/pipeline/test_ncbigene.py --pipeline --... |
5412597d5dce4eeb12799778fc44de5a0860e06b9c5a937417383cf101605381 | Python | 4,730 | 121 | """
Main.py
- main entry point to start DL experiments
"""
import os.path
import yaml
import logging
import argparse
import wandb
from datetime import datetime
import sys
sys.path.insert(0, '../iml-dl')
from dl_utils.config_utils import *
import warnings
class Main(object):
def __init__(self, config_file):
... |
4e62fd16f55e46dbe13acbd242fc17019528b7c4451d3a82f9aaf9ff54fafd2e | Python | 4,735 | 105 | # import cProfile, pstats
# pr = cProfile.Profile()
# pr.enable()
# test the performance of methods depending on the number of datapoints
import numpy as np
import matplotlib.pyplot as plt
import hickle as hkl
import os
from grid_cell.sphere_manifold import Circle_Manifold, get_circle_mesh
from grid_cell.ori_tuning_ma... |
5260c5a5aeb79bcd025283ca445c209498f1e24df9c95325097e4ad01bcbce7b | Python | 4,740 | 160 | import contextlib
import os
import sys
import h5py
import numpy as np
import pytraj as pt
import nearl.features
import nearl.featurizer
import nearl.io
from nearl.io import Trajectory
class MisatoTraj(Trajectory):
def __init__(self, pdbcode, misatodir, **kwarg):
# Locate the topology and trajectory file... |
d35c197f197c99a9f213ba3a577e9ddc9b0a93e0feab420044b19dc0ceb44cd2 | Python | 4,744 | 127 | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.metrics import silhouette_score
from sklearn.cluster import AgglomerativeClustering
def fit_and_predict(X, n_clusters):
model = AgglomerativeClustering(n_clusters=n_clusters, linkage='ward')
labels = model.fit_predi... |
2684dd9e6fbee099cd95bab83ff09d8ba87fbb1bd35ffbf6c4fdd7a844b24220 | Python | 4,745 | 127 | """Tonic / basal fluorescence analysis.
Pharmacological experiments care about slow shifts in the overall fluorescence
level after a drug injection rather than event-triggered transients. This module
averages the already-preprocessed z-score and dF/F traces over user-defined
absolute-time epoch windows, producing one ... |
93ab80ca84f4e8e927eed98e9c11a0cca338a00c1ad210eb4c9c1c2eea4269b7 | Python | 4,749 | 106 | """Live streaming contract tests for DandiNwbRecordingExtractor.
These tests hit the real DANDI Archive and are intended for **local use only**.
They are deselected in CI (see ``.github/workflows/run-tests.yml``) because
streaming from DANDI is subject to network flakiness and upstream availability.
Run locally with:... |
54940d7f1e26adf75bfe3289995bc3f386e74dcc0ddce0dc522cc484da193b5f | Python | 4,754 | 106 | # 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... |
60a06b3bed5d35728ec2780d1c8befb024df0a19699a1c2c31bf30d93a1f9cf0 | Python | 4,754 | 142 | import numpy as np
import math
def calculate_XYZ_pad_old(alignment, bounds):
"""
alignment is a quicknii alignment
bounds is the shape of the volume minus 1
"""
Ox, Oy, Oz, Ux, Uy, Uz, Vx, Vy, Vz = alignment
#bounds = np.array(volume.shape) - 1
X_size = np.sqrt(np.sum(np.square((Ux, Uy, Uz... |
98b411285581e9dab702e637591a1cb46e1c9f34f754a6da733cbdc800ab0690 | Python | 4,754 | 144 | """Existence-hiding invariants for the namespaced POST /v1/rooms."""
from __future__ import annotations
from typing import TYPE_CHECKING
from uuid import uuid4
import pytest
if TYPE_CHECKING:
from httpx import AsyncClient
async def _register_and_login(
client: AsyncClient,
email: str,
password: st... |
c808be4ca7b86a22334ce03e4d2ba71c9ef954f5dca58565e8672d095168ace0 | Python | 4,754 | 113 | import numpy as np
def check_shapes_same(output, target):
if output.shape != target.shape:
raise ValueError('Shapes of output {} and target {} do not match.'.format(output.shape, target.shape))
def check_classes_enumerated_along_correct_axis(array, axis, num_classes):
if array.shape[axis] != num_clas... |
344c26439376cb25e4ba58ac7a03796e614a37ed4f28647878733209119968a5 | Python | 4,755 | 136 | """Taskiq-side executor for @internal providers.
Resolves the filesystem handler from configured settings, invokes
``Provider.read(handler)``, and POSTs the result to the server via
the same ``/v1/joblib/providers/{id}/results`` endpoint that remote
providers use.
"""
from __future__ import annotations
import asynci... |
eaa9ea57684f188fe3e33a81ec0610befb63bba45839f47fa864c4af21b1585c | Python | 4,755 | 134 | # -*- coding: utf-8 -*-
import django.core.validators
from django.db import migrations, models
import django.db.models.deletion
forward = """
CREATE OR REPLACE FUNCTION refresh_skeleton_summary_table() RETURNS void
LANGUAGE plpgsql AS
$$
BEGIN
-- Remove all entries
TRUNCATE catmaid_ske... |
54f4e4763f06f246e67cfd11cfc112a9ee82c297931315000023f7d1a163cbcc | Python | 4,758 | 183 | from pathlib import Path
import time
import pickle
import gzip
import torch
import torch.nn.functional as F
import contextlib
from functools import wraps, lru_cache
from filelock import FileLock
from equiformer_pytorch.version import __version__
from einops import rearrange
# helper functions
def exists(val):
... |
858b30d87634dc9ca6bb9334b9c4574f526d6bede4a81a0395b476b1a6308bc4 | Python | 4,760 | 130 | #!/usr/bin/env python3
"""
The purpose of this script is to convert redcap data (ethnicity, gender, race)
into a table for Inclusion Enrollment Report
Parameters
------------
csv_fname: str
the REDcap downloaded file, which contains ethnicity, gender, race information
Return
------------
df_tally: pand... |
5a2582abb7a6f3a48501ebdf4d3075b94bee45892494bbd4b34a0772288c03ce | Python | 4,766 | 147 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Apr 16 05:37:22 2020
@author: takeiyuuichi
"""
import mne
from mne.preprocessing import create_ecg_epochs
import os
from mne.io import Raw
import mne
import matplotlib.pyplot as plt
from mne.preprocessing import create_... |
f89f6d119d188326dc6bcb13034c22c43b0b2e45d42d49ea39b8f1da463c9a5d | Python | 4,766 | 129 | import keras
import numpy as np
import pytest
from dante.neural_surrogate import AckleySurrogateModel
from dante.obj_functions import Ackley, ObjectiveFunction
from dante.tree_exploration import OptTask, TreeExploration
from dante.utils import generate_initial_samples
@pytest.fixture
def ackley_function():
retur... |
2e87d983a33ddec4cb12b964b72c20306b868f60fd6367c0b04d5387e5e16f07 | Python | 4,772 | 150 | #!/usr/bin/env python
#
# Resample data using nibabel
#
# Copyright (c) 2014 Polytechnique Montreal <www.neuro.polymtl.ca>
# License: see the file LICENSE
# TODO: add possiblity to resample to destination image
import sys
from typing import Sequence
import textwrap
from spinalcordtoolbox.utils.sys import init_sct, s... |
f0caedb507b0025fd418fada49ed1dde4b7eb55e6fe1620eb0576afe1b9f6330 | Python | 4,772 | 168 | #!/usr/bin/python
# -*- coding: utf-8 -*-
# This script fetches treenodes from the database and renders them to
# stack-sized PNGs
from math import pi as M_PI # used by many snippets
import sys
import psycopg2
import os
import numpy as np
import yaml
import cairo
if not (cairo.HAS_IMAGE_SURFACE and cairo.HAS_PNG_FU... |
c319abb44ca8ece379000d69a025d2651cd22ce9845025b70c366727ea9bedf3 | Python | 4,774 | 132 | from django.db import migrations
forward = """
CREATE OR REPLACE VIEW catmaid_table_info
AS
SELECT pc.oid AS rel_oid, pc.relname AS rel_name,
pn.nspname AS rel_schema, c.column_name AS column_name,
c.ordinal_position AS pos
FROM information_schema.columns c, pg_class pc... |
70c123214842187d8c8b96f8f6215bbb237a89d9c146aead124c232eee95929b | Python | 4,776 | 140 | """IBEA selector"""
from __future__ import division
from past.builtins import xrange # pylint: disable=W0622
"""
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
... |
96efbc844bf1614482741191ba2009c4ed00daaffd13436c86402cbd32694ad1 | Python | 4,780 | 126 | import sys
import os
import argparse
import pathlib
from tqdm import tqdm
import json
import torch
import torch.nn as nn
# https://github.com/PyTorchLightning/pytorch-lightning/issues/11663
import sentencepiece; import pytorch_lightning as pl; import clip
from transfer_experiments.train import LinearClassifier
from ... |
9dd318443ca5660f81664c69f560d8ec0b86051c2903bb8c789c006df43c392b | Python | 4,780 | 130 | """Mock recording extractor for unit testing."""
from pathlib import Path
from typing import ClassVar
import numpy as np
from guppy.extractors.base_recording_extractor import BaseRecordingExtractor
from guppy.utils._hdf5_io import write_hdf5
_MOCK_EVENTS = ["mock_signal", "mock_control", "mock_ttl"]
_MOCK_SAMPLING_... |
f12faca6ef77a54956903fb8e4f6fb90e8ef81c901fe0f17568612ba6b8bd423 | Python | 4,784 | 116 | import torch
import pandas as pd
import numpy as np
import os
import argparse
from tqdm import tqdm
from params import datapath, num_workers
from data import read_config, get_datasets
# from main import setup_pretraining
import models
from training import Trainer
from proc_4_decodability import feature_decodability, f... |
5ec0894526016117edbad5315ebde5b38d2f7847ef9b2a50b7540795a2109983 | Python | 4,792 | 124 | import numpy as np
import pandas as pd
import random
import copy
from scipy import special
def simulate_4prl(parameters, num_trials, pval, minswitch, num_action, agent_id):
"""
#### Inputs ####
parameters : model parameter values (list)
num_trials : number of trials we want to simulate for an age... |
53f96311946a9411e0087c7a75b50667d45553f1d82e3a1e1f0a9ce7554e34f8 | Python | 4,794 | 187 | from medperf.exceptions import InvalidArgumentError
import pytest
from medperf.commands.benchmark.update_associations_poilcy import (
UpdateAssociationsPolicy,
)
@pytest.mark.parametrize("mode", ["", "allow", "false"])
def test_invalid_model_modes(mocker, mode):
# Arrange
obj = UpdateAssociationsPolicy(1... |
70aad2c4160fa5be8c4a734596b069cb40d2f078fbe53ebb382b702f59ca735b | Python | 4,795 | 116 | #!/usr/bin/env python2.7
import sys, os
import argparse
from multiprocessing import Lock, Value, Pool
from collections import Counter
import chisel
src = os.path.dirname(chisel.__file__)
from ..Utils import *
from chisel import Plotter
def parse_args():
description = "CHISEL command to generate a BED file for... |
1c0dee259792a8d688dab36950f7349aac576ff89e98cebe96eb1c8426fc1be8 | Python | 4,799 | 117 | # Copyright (c) 2021, EleutherAI
# This file is based on code by the authors denoted below and has been modified from its original version.
#
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in complian... |
17aabeb2c0063bcf1ef4a616e35ca23c29f707137f92244fd2f10d44f3eea14d | Python | 4,802 | 143 | import os
from importlib import import_module
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
class Loss(nn.modules.loss._Loss):
def __init__(self, args, ckp):
super(Loss, self)._... |
7eeff0a68d963b87c03c9c89fd4f67a22e663dbefd771cb9457a50c7b5d8e573 | Python | 4,803 | 136 | import torch
import torch.nn as nn
import torch.nn.functional as F
class SE_block(nn.Module):
def __init__(self, inchannels, reduction = 16 ):
super(SE_block,self).__init__()
self.GAP = nn.AdaptiveAvgPool3d((1,1,1))
self.FC1 = nn.Linear(inchannels,inchannels//reduction)
sel... |
aeb3b34d123fabf04781772589e45e416d0e9f5341f89f5161f6509f3676f938 | Python | 4,803 | 118 | # Copyright (c) OpenMMLab. All rights reserved.
"""MMSegmentation provides 21 registry nodes to support using modules across
projects. Each node is a child of the root registry in MMEngine.
More details can be found at
https://mmengine.readthedocs.io/en/latest/advanced_tutorials/registry.html.
"""
from mmengine.regis... |
2891ad04f75e77f6992f4f98291f6bd2dbc44dcdb703d3938aeb939d2c42a3a2 | Python | 4,804 | 185 | # Based on: https://github.com/HazyResearch/flash-attention/blob/4a6eaa9f27df6fff7ffb2c24e894938a687dd870/flash_attn/flash_attn_interface.py
import torch
import torch.nn as nn
import torch.nn.functional as F
import flash_attn_cuda
def _flash_attn_forward(
q,
k,
v,
out,
cu_seqlens_q,
cu_seqle... |
875c210d52b5f048adfcffcf977c7b366f0abbf13ef7d225cc63ce629ab83750 | Python | 4,807 | 129 | """Step-5 dashboard tab for whole-session time-binned metrics.
Reads the ``binned_metrics_<site>.h5`` tables Step 4 wrote and plots the selected
metric as bars under the trace it was reduced from. Sessions analysed without the
binned metrics parameter have no such tables, so the tab renders a short note
instead and ca... |
04d18ff2eac20c5c034b16c5d267f3f2ef005b488259b39b1f23d8e03120d863 | Python | 4,808 | 138 | import textwrap
import cv2
import numpy as np
from PyQt5.QtCore import QThread, pyqtSignal
from PyQt5.QtWidgets import QMessageBox
from numpy import ndarray
def turn_function_into_thread(inputfunction, emit_prog_signal=False, *arg, **kwargs):
class ThreadedFunction(QThread):
if emit_prog_signal:
... |
a12c048b0e909e4c42e704d6cdb1ed995c977c227b73dea29005aa78df920b08 | Python | 4,809 | 148 | ###########################################################################################
# Script for evaluating configurations contained in an xyz file with a trained model
# Authors: Ilyes Batatia, Gregor Simm
# This program is distributed under the MIT License (see MIT.md)
########################################... |
f5fdcc31bd5d78a100964988b48809ddae9e0a44cf17a894fd1238dbd15bff7c | Python | 4,810 | 148 | #!/usr/bin/env python
"""
MetaWIBELE: extract_cluster_CD-hit module
Extract the cluster information from CD-hit results
Copyright (c) 2019 Harvard School of Public Health
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"),... |
01355c974bcdd33eaf215474233374a2cd1b13023bed97d3cf8096258a68732e | Python | 4,811 | 93 | import pandas as pd
import numpy as np
import jsonlines
from unsloth import FastLanguageModel
import transformers
import argparse
def randomized_choice_options(num_choices):
choice_options = list(map(chr, range(65, 91)))
return np.random.choice(choice_options, num_choices, replace=False)
if __name__ == '__mai... |
3f17fa7eefdedc411f1bcf1f7a1c4bd7acf73b41476891acf9f19b07fe4d052d | Python | 4,811 | 128 | ##
## CPCantalapiedra 2019
import os
import sys
import time
from ..common import get_call_info
from ..emapperException import EmapperException
##
# Generator of hits from filename
def parse_seeds(filename):
for lineno, raw in enumerate(open(filename, 'r'), 1):
if raw.startswith('#') or not raw.strip():
... |
453298dab4d5b753031419b5039ebd9c52a2a38c39cd2b389cd6f98a6a5be798 | Python | 4,812 | 143 | import numpy as np
import pandas as pd
import os
import sys
from glob import glob
from tqdm import tqdm
import mne
import matplotlib.pyplot as plt
import seaborn as sns
import scipy.stats as stats
files = sorted(glob(f"/ptmp/kroma/m4d/models/leakage/eegnet/N170/*/eegnet_leakage.csv"))
df = pd.concat([pd.read_csv(f... |
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