sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
15ba439cd728f6490d8972161722e9605634a3ab745ceac1b5c05c1432b1012a | Python | 4,705 | 102 | from PymoNNto.Exploration.Network_UI.TabBase import *
class hist_tab(TabBase):
def __init__(self, weight_attr='W', title='Weight Dist.', timesteps=1000, mask_param='Input_Mask', mask_color_add=(-100, -100, -100)):#mask_param=None #
super().__init__(title)
self.weight_attr = weight_attr
sel... |
4514cabf32ec253b0b469bb58c8f732ee94c44c60aea71c041d59e0fad181557 | Python | 4,705 | 143 | """Tests for core ABF, TIFF, and sweep-access file-loader behavior."""
from pathlib import Path
import numpy as np
import sanpy
from sanpy.fileloaders.fileLoader_abf import fileLoader_abf
from sanpy.fileloaders.fileLoader_base import fileLoader_base
# from sanpy.fileloaders.fileLoader_tif import fileLoader_tif
def... |
4c8524e92c2e78acf2119a8bfcd9cfff2be90234f6ee5020637b66661f2e12ae | Python | 4,706 | 135 | import logging
from contextlib import suppress
import cv2
import numpy as np
from idtrackerai import (
Blob,
IdtrackeraiError,
ListOfBlobs,
ListOfFragments,
ListOfGlobalFragments,
Session,
)
from idtrackerai.utils import track
def fragmentation_API(
session: Session, list_of_blobs: ListO... |
dd1130ed814e590310af69e5a28ee62f8daf3a4908e4aaa2576611e2382b10c9 | Python | 4,712 | 165 | import pytest
import geomstats.backend as gs
import geomstats.datasets.utils as data_utils
from geomstats._mesh import Surface
from geomstats.test.data import TestData
from geomstats.vectorization import repeat_point
from .manifold import ManifoldTestData
from .riemannian_metric import RiemannianMetricTestData
clas... |
a8ff314ae8db05dab1dc9446356339cb8b16a51aef98d07b8eac0a158d315a50 | Python | 4,713 | 114 |
from sparse_ct.tool import plot_grid
from sparse_ct.data import image_to_sparse_sinogram, ellipses_to_sparse_sinogram
from sparse_ct.reconstructor_2d import (
IRadonReconstructor,
SartReconstructor,
SartTVReconstructor,
Sar... |
e01c833923275f233b37be44e0969e1e1621118554726e427234111b57ef9e52 | Python | 4,714 | 190 | ## IMPORT BASIC LIBS FOR SCRIPT
import scipy as sc
from scipy import io
from scipy import linalg
import bstates as bs
import pickle
import numpy as np
import feather
import h5py
import pandas as pd
from sklearn.decomposition import PCA
import os
from sys import argv
## TREATING ARGV VARS
nPats = int(argv[1]) # NUMBE... |
d6a04bd7c6989230019b17ecf029ab1b77075857101abedb070f4fcb4dc00878 | Python | 4,716 | 126 | # 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.
from argparse import Namespace
import logging
from typing import Union, Tuple, Optional
import torch
import torch.nn as nn
import torch.nn.fu... |
04910495e45ea3c1d11c0d9184c626514d5d9c251050a4524733dac6b5607cc2 | Python | 4,717 | 117 |
import numpy as np
import os
from os import path
from glob import glob
import sys
import h5py
from tensorflow.python.ops.gen_batch_ops import batch
sys.path.append('MEISTER')
from utils import *
from processing import *
from signal_model import *
from train import *
import subspaceMSI as subspace
fro... |
78937e850e6a0c264968e3a21755c266f7e4b9956231aaf4f4a9677b8b5fce77 | Python | 4,719 | 148 | """A simple script to convert reinvent3 models to reinvent4 models
This script will update the paths to the model classes and add meta information
to the model file. Run this after having created the symlinks with the script
in support.
"""
import os
from dataclasses import dataclass
from typing import Tuple
import ... |
53b84c5c692fc0ae0d9060d7b25aee5db6b2702bfbc83d7ee944c717aa224707 | Python | 4,720 | 125 | # 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... |
554634cda856f33f1a16e61a411b4cd49a1d4e67d34b9af048690a9a8cd29408 | Python | 4,725 | 133 | # -*- coding: utf-8 -*-
pepbdb_inputdir = '/home/ec2-user/SageMaker/efs/data/CAMP/paper/' #tar -xvzf'd version of pepbdb-20200318
querys=[]
import csv
import os
def check_abnormal_aa(peptide_seq):
len_seq = len(peptide_seq)
cnt = 0
standard_aa = ['G','A','P','V','L','I','M','F','Y','W','S','T','C'... |
4d593111352d2b1c5c174e5e654226bf2145dff56388f47847319fe4abaf47e3 | Python | 4,726 | 156 | import pytest
import torch
from e3nn import o3
from nequip.data import AtomicDataDict, register_fields, deregister_fields
from nequip.nn import GraphModuleMixin
from nequip.utils.test import (
assert_AtomicData_equivariant,
assert_permutation_equivariant,
)
class BadModule(GraphModuleMixin, torch.nn.Module... |
69f26154f15181904b08271b589f655d139416f22a1dfcc73a484afcf9c21238 | Python | 4,727 | 134 | from PymoNNto.Exploration.Evolution.common_UI import *
from PymoNNto.Exploration.Evolution.PlotQTObjects import *
class Overview_UI(UI_Base):
def update_order(self):
for i in range(self.listwidget.count()):
item = self.listwidget.item(i)
#print(i, item.text())
smg=self.... |
f06113fc1a1d9805ca680227452f0e3efdbf1c923733f8ceeba2777fc5e2726f | Python | 4,728 | 149 | import ase.io
import numpy as np
import pytest
import torch
from mace.calculators import MACECalculator
from tests.helpers import CUET_AVAILABLE, base_mace_params, run_mace_train # noqa: F401 # pylint: disable=unused-import
pytestmark = [pytest.mark.network]
device = "cuda" if torch.cuda.is_available() else "cpu"
... |
bf14626576acc773aa32cfda0bc493bf2492cfce37eb8b62399cd425e21581fa | Python | 4,729 | 136 | import pytest
import unittest
import torch
import torch.utils.data as tud
from reinvent.models.transformer.core.dataset.paired_dataset import PairedDataset
from reinvent.models.transformer.core.vocabulary import SMILESTokenizer
from reinvent.runmodes.utils.helpers import set_torch_device
from tests.test_data import E... |
f92c6fdd3ee089a5283ac2b78fefaa405b3d82671764a4826668235fa6b5adb3 | Python | 4,735 | 148 | import pickle
import numpy as np
import torch
import pandas as pd
from sklearn import model_selection
from torch.utils.data import Dataset
from torch.utils.data.sampler import Sampler
try: # Handling API difference between pytorch 1.1 and 1.2
from torch.utils.data.dataloader import default_collate
except ImportEr... |
fa712cb066c6bd59a4999b32cfc43469b7065e124a70246604a065a1b8f77d3a | Python | 4,737 | 185 | import click
import procspec
import torchfields
from corgie import scheduling, argparsers, helpers
from corgie.log import logger as corgie_logger
from corgie.layers import get_layer_types, DEFAULT_LAYER_TYPE, str_to_layer_type
from corgie.boundingcube import get_bcube_from_coords
from corgie.argparsers import (
L... |
812c3d9589d3717aa656941e1eee4705e2e86b3c8bc2206dd9fe328d8298da80 | Python | 4,742 | 89 | """Author independence has strict boundaries and cannot use missing metadata."""
import polars as pl
from vdjdb.curate.authors import author_pairs, parse_authors
def fixture() -> pl.DataFrame:
rows = []
for ref, names in [("1", ["a", "b", "senior"]), ("2", ["a", "d", "other"]),
("3", [... |
7276b241dc2739126ed1ffa6b2a31ebf75b821b76ebf85dd4cacdbcb9b6fc291 | Python | 4,744 | 123 | # Copyright 2025 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import importlib
import logging
from flwr.proto import grpcadapter_pb2
from google.protobuf.message import DecodeError
from openfl.protocols import aggregator_pb2
logger = logging.getLogger(__name__)
def flower_to_openfl_message(flower_messa... |
a7161b8c6058db8a2d58807ee6b8d34eef47a3cb843ac874842bf2107bfeb4fe | Python | 4,747 | 121 | # This file is a part of the `nequip` package. Please see LICENSE and README at the root for information on using it.
"""
Utilities for `nequip-package`, mainly to handle externing and mocking modules.
"""
from nequip.__init__ import _DISCOVERED_NEQUIP_EXTENSION
from typing import Callable, Dict, Final, List, Set, It... |
0c18928569af4f336649a40d0e9659e24eb0ae2c8881cc426457a0fdd3a52460 | Python | 4,748 | 135 | # ==============================================================================
# Copyright 2025 Technical University of Denmark
# Author: Nikolas Borrel-Jensen
#
# All Rights Reserved.
#
# Licensed under the MIT License.
#
# 3D: used for converting the full dome to quarter dome for domain decomposition
# ============... |
b1669eb754a1a9b75a1380bdc7aaeeb24f71a63faded255e7c39113a939caf2b | Python | 4,748 | 130 | # 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 math
from fairseq import metrics, utils
from fairseq.criterions import register_criterion
from .label_smoothed_cross_entropy import (... |
6338e94921265d9fa4227b9c0ee1e238b4312d029619414f6206c7ea5a384fd2 | Python | 4,756 | 163 | """
"""
import os, sys
import logging
import argparse
import glob
from typing import *
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
def timestep_from_fname(fname: str) -> int:
"""
Get the timestep from the given filename
>>> timestep_from_fname("generated_0_timestep_0.cs... |
d07cfc1f68a71cf075ad5d2eaa54fc400e349f439600ac39740e2b9877883700 | Python | 4,757 | 125 | from chromadb.api.types import EmbeddingFunction, Space, Embeddings, Documents
from typing import List, Dict, Any
import numpy as np
from chromadb.utils.embedding_functions.config_validation import (
validate_embedding_function_kwargs_are_safe,
)
from chromadb.utils.embedding_functions.schemas import validate_confi... |
d981517dbee8c807377de5204c2f35d319519c7e6df75fad58f93a2bb82d10b5 | Python | 4,757 | 123 | from collections.abc import Iterable
from qtpy.QtCore import Qt, Signal # type: ignore[reportPrivateImportUsage]
from qtpy.QtWidgets import (
QHBoxLayout,
QRadioButton,
QScrollArea,
QSpinBox,
QVBoxLayout,
QWidget,
)
from idtrackerai import Blob, Fragment
class MarkMetadata(QScrollArea):
... |
2eda0ba0b0b6558a69973f7a695f7cbbaa9dcd2eea6fa864914058ec55303367 | Python | 4,763 | 101 | # Module for calculating aSNR (arbitrary signal to noise ratio) of a fluorescence trace when the step boundaries are known
# Copyright (C) 2023: Max F. K. Wills & Ian C. Eperon
# FluoroTensor: identification and tracking of colocalised molecules and their stoichiometries in multi-colour single molecule imaging via de... |
2695e65e7eea344242dd54e659ba7b943c895413fb22aa82e4b23bda74400c16 | Python | 4,765 | 118 | # This file is a part of the `nequip` package. Please see LICENSE and README at the root for information on using it.
from ._base_datamodule import NequIPDataModule
from nequip.utils import download_url, extract_zip
from nequip.utils.logger import RankedLogger
import os
from typing import Union, Sequence, Optional, Li... |
3724d487761294deed807e156f7ab799c578c99d137f0dd4cfeb8aab0ce2029a | Python | 4,768 | 111 | from dig.threedgraph.dataset import MD17
import shutil
def test_MD17():
root = './dataset'
dataset = MD17(root=root, name='aspirin')
assert len(dataset) == 211762
assert dataset.__repr__() == 'MD17(211762)'
assert len(dataset[0]) == 4
assert dataset[0].z.size() == (21,)
assert dataset[0].p... |
f446f7f7ca8b3d4c53e2a35a111b66abc42c68aff188d9a3a1798f32cc18955b | Python | 4,769 | 122 | # Based on the code from: https://github.com/klicperajo/dimenet,
# https://github.com/rusty1s/pytorch_geometric/blob/master/torch_geometric/nn/models/dimenet.py
import torch
from torch_scatter import scatter
from torch_sparse import SparseTensor
from math import sqrt, pi as PI
from torch_geometric.nn import knn... |
bc5410872c5787fff4f07a2027ad0c76a0a84dab9d2dfcce87055f7c302731c7 | Python | 4,771 | 110 | # 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... |
ab1ac0a0e588fded0ac30d37ce5e671129f27731b16495a07a844911223478c7 | Python | 4,772 | 138 | # 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... |
d18e0d80238db540738dfb13491d55f3646b2cf88bfea40d08a9ed86352020d8 | Python | 4,772 | 157 | from copy import deepcopy
import torch
from odl.contrib.torch import OperatorModule
from odl.tomo import fbp_op
from odl.operator.operator import OperatorRightScalarMult
from dival.reconstructors.standard_learned_reconstructor import (
StandardLearnedReconstructor)
from dival.reconstructors.networks.iterative imp... |
2defb2130aedb08c5f57e011a5c935b7ce174b4e5f862c690eea3d0892ff4e62 | Python | 4,775 | 158 | import random
import pytest
import geomstats.backend as gs
from geomstats.geometry.special_euclidean import (
SpecialEuclidean,
SpecialEuclideanMatricesLieAlgebra,
_SpecialEuclideanMatrices,
)
from geomstats.test.parametrizers import DataBasedParametrizer
from geomstats.test_cases.geometry.base import Lev... |
4a3cfc81c5f3b30cb3a70a201676560d70e4e9015a56a22ef5b0ed7bb7991cd8 | Python | 4,779 | 113 | """Split data in sets and normalize (per recording)."""
import glob
import json
import os
import pickle
import numpy as np
if __name__ == "__main__":
# Arguments for splitting and normalizing
speech_features = ['envelope', 'mel']
splits = [80, 10, 10]
split_names = ['train', 'val', 'test']
over... |
c73f7ba9d8aa366db115065459e655fb1a5aef6930adad83c68ab7c8a8aa94c1 | Python | 4,779 | 146 | import numpy as np
import scipy.signal
from PyQt5 import QtCore, QtGui, QtWidgets
import matplotlib.pyplot as plt
from sanpy.sanpyLogger import get_logger
logger = get_logger(__name__)
import sanpy
from sanpy.bAnalysisResults import analysisResultDict, get_plot_result_definitions
from sanpy.interface.plugins impor... |
44be6b0a0524b72e2fd845c4c98cf7dd17011f437dadb99ce6a7128967d30f09 | Python | 4,780 | 124 | import pytest
import geomstats.backend as gs
from geomstats.geometry.grassmannian import Grassmannian
from geomstats.test.test_case import TestCase
from geomstats.test.vectorization import generate_vectorization_data
from geomstats.test_cases.geometry.base import LevelSetTestCase
from geomstats.test_cases.geometry.rie... |
b572fb8ce763242c45b6b96f3447f8b4ab4e740ab89bbd2ec9164fe7ca7c0a02 | Python | 4,781 | 137 | # -*- coding: utf-8 -*-
"""
Created on Wed Mar 1 11:42:35 2023
@author: nicol
"""
# -*- coding: utf-8 -*-
"""
Created on Wed Feb 22 11:53:34 2023
@author: gritti
"""
import os, glob, tqdm
from skimage.io import imread
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import rc
import pandas as pd
... |
25a033ac709872b411ebb4514ec81dde7f9f972d817673c6e3d3613592549bfa | Python | 4,782 | 148 | import os
from glob import glob
import logging
import argparse
import subprocess
from pathlib import Path
import tempfile
from typing import *
from tqdm.auto import tqdm
PROTEINMPNN_SCRIPT = os.path.expanduser("~/software/ProteinMPNN/protein_mpnn_run.py")
assert os.path.isfile(PROTEINMPNN_SCRIPT), f"Expected {PROTEIN... |
67e15b73e42d6be6974736eab378afad51d0d01d84144018c0498ee175ce549a | Python | 4,782 | 166 |
import sys
import numpy as np
import psi4
# read in args
# structure file
xyzfile = sys.argv[1]
# orbital basis
basisname = sys.argv[2]
# auxiliary basis
auxbasis = sys.argv[3]
# level of theory
theory = sys.argv[4]
xyzprefix = xyzfile.split('.')[0]
psi4.set_memory('128 GB')
psi4.set_num_threads(16)
psi4.core.set... |
32871ce96332edbc26702b4d9760e9d18343ad379694c8dce66e8016e53bc327 | Python | 4,784 | 136 | """
Time-frequency analysis using Morlet wavelets or multitapers
TFR computed on each raw file, from the beginning until the end.
The result is the grand average of TFRs over all epochs.
Kyuhwa Lee, 2018
"""
import sys
import mne
import scipy
import numpy as np
from pathlib import Path
import mne.time_frequency
imp... |
1d14219cba5de8767029b2f10e1d4f016df0b5b68bb7beb724494f6c3b808ca1 | Python | 4,786 | 122 | import numpy as np
import pytest
from openfl.databases.persistent_db import PersistentTensorDB
from openfl.utilities.types import TensorKey
#############################################
# Pytest Fixtures #
#############################################
@pytest.fixture
def persistent_db():
... |
a9a9734fe8d40e7ac46ae131b15950031db5b563f3d5061db53496ff51ed8641 | Python | 4,787 | 138 | from chromadb.utils.embedding_functions.schemas import validate_config_schema
from chromadb.api.types import Embeddings, Documents, EmbeddingFunction
from typing import Dict, Any, cast
import json
import numpy as np
class AmazonBedrockEmbeddingFunction(EmbeddingFunction[Documents]):
"""
This class is used to ... |
e19a9786e619d500d00a5e0f8f49debea7c685c0d9b77a1c9c00a6799f21466a | Python | 4,787 | 183 |
import numpy as np
from skimage.data import shepp_logan_phantom
from skimage.transform import radon, iradon, iradon_sart, resize
from skimage.color import gray2rgb
from skimage import io
from scipy.io import loadmat
import sys
def db2ratio(db):
"""
For power:
db=10*log(ratio)
ratio=10**(db/10)
""... |
3a2338325688386ac12820cfc1178a12750b037eda0e0769f42690544dd56715 | Python | 4,793 | 118 | from typing import List, Dict
import numpy as np
from reinvent.chemistry.library_design import FragmentReactions
from reinvent.chemistry.library_design.reaction_definitions.standard_definitions import (
StandardDefinitions,
)
from reinvent.chemistry.library_design.reaction_filters.reaction_filter_configruation imp... |
6a3458be39ff1cead5a4f804fc060bd4499f9c337c4dd31fb8308d76e0e49b14 | Python | 4,793 | 141 | """Define immutable application state for the DANDI NiceGUI demonstration."""
from __future__ import annotations
from dataclasses import dataclass
from typing import Protocol
from dandi_dataset import (
DandiAssetSummary,
DandiDataset,
DandiDatasetMetadata,
DandiSweepPlotData,
)
@dataclass(frozen=T... |
33c1a4b5db2ea073a34596abf91c19eebc0c077ca03db17acecdd2bb0fe68c05 | Python | 4,794 | 165 |
import warnings
import numpy as np
from sklearn.metrics import matthews_corrcoef
def mcc_score(y_true, y_prob, threshold: float):
"""
Matthews Correlation Coefficient can be computed in three different ways,
1. for training computed on threshold 0.5
2. for validation computed for 0.5 but also include... |
e8a3411d1b752d72f08dcd865000479e7f7614225233b9d5529c28ca29664c42 | Python | 4,794 | 99 | """
Computation of local energies and forces.
"""
import jax
import numpy as np
from jax import numpy as jnp
from deeperwin.configuration import ForceEvaluationConfig
from deeperwin.utils.utils import get_el_ion_distance_matrix, get_full_distance_matrix
import functools
def get_el_el_potential_energy(r_el):
n_el =... |
7ec7fcf33c46f9e6ffcc9c9ca02ba6b0d502b278d3ea3822e063d6c437974e3b | Python | 4,797 | 137 | """
File containing a regular Multi-Layer Perceptron (MLP) implemented in haiku.
"""
from typing import Iterable, Optional, Callable, Literal
import jax
import jax.numpy as jnp
import numpy as np
import haiku as hk
from jax import numpy as jnp
from kfac_jax import register_scale_and_shift
from deeperwin.configuratio... |
e7ce2601592227d8aeffbcba15ecc79b8c12bbe412d368ca152f7faf8a4e54a4 | Python | 4,799 | 149 |
import torch
from torch import nn, Tensor
from typing import Optional, Tuple
from ..layers import (
get_normalization_layer,
ConvLayer,
Dropout,
LinearSelfAttention,
)
from ..modules import BaseModule
from ..misc.profiler import module_profile
class LocationPreservingVit(BaseModule):
"""
Th... |
c4dc5e45078920a7e1bef637b3ac4468ca6990ac70d005a854d131a15cb8bd24 | Python | 4,801 | 156 | from pathlib import Path
from typing import Union, Optional
import openpyxl
from openpyxl.styles import Font
import sys
import argparse
ID_SPACE = (15000, 16000)
FREE_IDS = list(range(ID_SPACE[0] + 1, ID_SPACE[1]))
PREFIX = 'BCIO'
ID_WIDTH = 6
def register_id(id: Union[str, int]) -> Optional[int]:
if isinstanc... |
31de3a9636c36775749cc1da41055e06426f542bf016d58fd9802c410bef0a8e | Python | 4,802 | 139 | import time
import logging
import pickle
from pathlib import Path
from typing import Any, Dict, Tuple
import numpy as np
import pandas as pd
import jax
from jax.random import split
import optax
import plasticity.synapse as synapse
import plasticity.data_loader as data_loader
import plasticity.losses as losses
import ... |
952e01a92f8fd930faf80c043aef75c4d672c6322ccf418a0bf6e43540afa44a | Python | 4,806 | 125 | """Tests for two-sample permutation tests."""
import pytest
import numpy as np
from nltools.algorithms import two_sample_permutation_test
class TestTwoSamplePermutation:
"""Test two-sample permutation tests."""
@pytest.mark.parametrize("n_features", [10])
def test_basic_functionality(self, n_features):... |
1e546511f31b9f981f0004b44de9c7bae03a12ace0c33997405de23511b25973 | Python | 4,809 | 149 | # ------------------------------------------------------------------------------
# Copyright (c) Microsoft
# Licensed under the MIT License.
# Written by Bin Xiao (Bin.Xiao@microsoft.com)
# ------------------------------------------------------------------------------
from __future__ import absolute_import
from __futu... |
d86db8fdd6a63247c6333a60f41478d07ad32936f5f52d4c6070efd4460db737 | Python | 4,812 | 103 | # This file is a part of the `nequip` package. Please see LICENSE and README at the root for information on using it.
from ._ase_datamodule import ASEDataModule
from nequip.utils.file_utils import download_url, extract_tar
from nequip.utils.logger import RankedLogger
import os
from typing import Union, Sequence, List,... |
31a194569ebc9751d972f5a4b326fcf01db936d43edf0e95b64777cf3674d1c4 | Python | 4,813 | 139 | """Round-trip tests for DesignMatrix.write() and the file constructor.
Behavioral contract:
- Text formats are symmetric: whatever ``.write()`` produces for a given
extension, the constructor reads back. The separator follows the extension
(``.csv`` -> comma, everything else -> tab) on both sides.
- HDF5 is the me... |
1067808dcd5badc6b0c04e3b697b921b6dffc1fd885fceaf7f2bc73d0a7891b9 | Python | 4,815 | 150 | import gvp
from atom3d.datasets import LMDBDataset
import torch_geometric
from functools import partial
import gvp.atom3d
import torch.nn as nn
import tqdm, torch, time, os
import numpy as np
from atom3d.util import metrics
import sklearn.metrics as sk_metrics
from collections import defaultdict
import scipy.stats as s... |
3aca1680604b2dd1ecf8fa903b78636ad3e20139f31e837b845e70945188eaa0 | Python | 4,816 | 191 | import math
import numpy as np
from scipy import stats
import scipy.cluster.hierarchy as spc
import seaborn as sns
from matplotlib import pyplot as plt
from matplotlib.gridspec import GridSpec
from matplotlib.patches import Patch
def annotate_corr_grid(g, x, y, method="pearson"):
g.map_dataframe(annotate_corr, x=... |
c199be974755465176cbb90449f8e66ee2430fab87e2a2d0a5f447dbc9401256 | Python | 4,817 | 135 | # ------------------------------------------------------------------------------
# Copyright (c) Microsoft
# Licensed under the MIT License.
# Written by Bin Xiao (Bin.Xiao@microsoft.com)
# Modified by Ke Sun (sunk@mail.ustc.edu.cn)
# ------------------------------------------------------------------------------
from ... |
c002fdf909a0c38496120da587e39989d482e8954fc000c2621db76789cc903b | Python | 4,819 | 93 | """
Theta Neuron Mean-Field Model
=============================
Here, we will introduce the mean-field model of a network of all-to-all coupled theta neurons. The theta neuron model
is also known as the `Ermentrout-Kopell <http://www.scholarpedia.org/article/Ermentrout-Kopell_canonical_model>`_ model
and takes the for... |
4ce3fe03a27c48b1ef0c635bb061db4e3c7dd5da23e3a9b8c0d0b872e4b5ccf9 | Python | 4,820 | 156 | #Loads normalized and paganin filtered PSI micro CT data from a single hdf5 file and reconstructs it.
#Utilizes tomopy and astra toolbox to run a GPU-enabled FBP algorithm for quick recon times
import tomopy
import numpy as np
import h5py
import getopt, sys
#populate default variable values
sname = 'output.h5'
data_f... |
9639b856c128a1d9a0f91d910ab9a475bb5330ecd2fff07c659f0f9a63f06ea2 | Python | 4,822 | 156 | import pytest
import geomstats.backend as gs
from geomstats.exceptions import AutodiffNotImplementedError
from geomstats.test.test_case import TestCase
from geomstats.test.vectorization import generate_vectorization_data
class NumpyRaisesTestCase(TestCase):
def test_raises(self, autodiff_func):
with pyte... |
e5749c491447c47d82b06b4469b72ef494426ec5bf6881fd16f4af5b349ed52a | Python | 4,822 | 147 | """
Here we compare the calculation time for the simulation of a large network
(10^6 parameters) on SHIP, Brian2 and RockPool.
"""
### main features
rate = 100 # Hz
N = 500 # neurons per layer
nts = 1000 # number of time-steps
DT = 0.001 # time-step size
tau_beta = 0.01 # LIF neuron dynamics
tau_alpha = 0.0... |
444f3e741ffaa5100fed76970c73131f4b334c7dbc30e12d2b01ae5c9a91e8e1 | Python | 4,827 | 158 | """Create a Reinvent model from a list of SMILES strings"""
import sys
import tomllib
from dataclasses import asdict
import time
import datetime
import uuid
import pprint
import logging
try:
import torchinfo
except ImportError:
torchinfo = None
from reinvent import version
from reinvent.models import meta_da... |
71fd4302c7e051df5b8e18e17a88cb4837c271fddb5861635e3eec65e7f79fac | Python | 4,828 | 182 | """functions.py
Miscellaneous functions
"""
import numpy as np
from scipy import stats
from scipy.interpolate import interp1d
import pycircstat
import scipy as sc
# ------------------ Circular data operations ----------------------- #
def unwrap(signal, period=360):
unwrapped = np.unwrap(signal * 2 * np.pi /... |
954ccd0b77827ebbe42fb53f2dff2e839ea081542cbb66874da6450d19a4f9f0 | Python | 4,828 | 151 | """
For Fig 2B go to:
Z:\people\gritti\IRIR\supFig2_3
"""
import os
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import rc
import pandas as pd
plt.rcParams.update({'font.size': 15})
rc('font', size=8)
rc('font', family='Arial')
# plt.style.use('dark_background')
rc('pdf', fonttype=42)
if __n... |
54d17ba621dca20934b5d539b106e83d55d73097316bc88389240c4874a6f7ee | Python | 4,829 | 122 |
from pathlib import Path
import tarfile
import numpy as np
import matplotlib.pyplot as plt
# # Set matplotlib font rendering to use LaTex
# plt.rcParams.update({
# "text.usetex": True,
# "font.family": "serif",
# "font.serif": ["Computer Modern Roman"]
# })
if __name__ == "__main__":
stats_dir = Pat... |
c56cd02f8a609d284ff9ae65eb202326b4abefc936887cd98ca3c474905fa50d | Python | 4,829 | 153 | import numpy as np
import renderapi
from scipy.sparse import csr_matrix
from .utils import AlignerTransformException
__all__ = ['AlignerSimilarityModel']
class AlignerSimilarityModel(renderapi.transform.AffineModel):
"""
Object for implementing similarity transform.
"""
def __init__(self, transform... |
c030f23955382c1f6040d2ec2ddd330dcc40f8968d301ea7d2249a1f13039f5e | Python | 4,831 | 195 | """
GP METRICS
====================
This module allows the use of Gaussian Processes for property
prediction. It is basically a wrapper of GPmol within the
ChemORGAN architecture. It has been entirely programmed by
Carlos Outeiral.
The author whishes to thank Rodolfo Ferro for sharing his
library in the alpha phase.... |
9d435d7763dc2982ea5dce80ddeb8705557b80a7451d9af68ea54cac7ab0bcd5 | Python | 4,832 | 135 | # 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 contextlib
from typing import Optional
import torch
from fairseq.dataclass.configs import DistributedTrainingConfig
from fairseq.distr... |
380cc39f2f1da5f7798fa7fa6ddc6d609656d656f23d620d7acf3aacc93055be | Python | 4,833 | 138 | import torch
import torch.nn as nn
import torch.nn.functional as F
class DoubleConv(nn.Module):
"""(Convolution => [BN] => ReLU) * 2"""
def __init__(self, in_channels, out_channels, mid_channels=None):
super().__init__()
if not mid_channels:
mid_channels = out_channels
... |
4161a5b7a01ee76ef9657c526e3c5c727185bbdbd4e3feb6cc964a7b1f426758 | Python | 4,833 | 158 | """Write out a CSV summary"""
from __future__ import annotations
import logging
from typing import TYPE_CHECKING
import numpy as np
from reinvent.runmodes.samplers import PepinventSampler
if TYPE_CHECKING:
from reinvent.runmodes.RL.reports import RLReportData
csv_logger = logging.getLogger("csv")
logger = logg... |
edda5a63c9cd15463cc811b098b827b493590ad810036f8020de547233e646ac | Python | 4,835 | 105 | import sys
import os
import re
import numpy as np
import subprocess
import math
import scipy
import silhouetteRank.spatial_genes as spatial_genes
from shutil import copyfile
from operator import itemgetter
from scipy.spatial.distance import squareform, pdist
from scipy.stats import percentileofscore
from sklearn.metric... |
071babd29dd392391593836c97bfd5d069d8b51ae86d6f6558fd4cf3f29c75b4 | Python | 4,841 | 109 | import numpy as np
import argparse
import quantities as pq
import neo
from utils.parse import parse_string2dict, none_or_float, none_or_str
from utils.neo_utils import imagesequence_to_analogsignal, time_slice
from utils.neo_utils import analogsignal_to_imagesequence, flip_image, rotate_image
from utils.neo_utils impor... |
19bb94cfcbfbd7d7e05a52cb57f49dda547b7b0ba6833ccfdba2862fbcbf4fb6 | Python | 4,842 | 171 | """The MDM classifier on manifolds.
Lead authors: Daniel Brooks and Quentin Barthelemy.
"""
from scipy.special import softmax
from sklearn.base import BaseEstimator, ClassifierMixin
import geomstats.backend as gs
from geomstats.learning._template import TransformerMixin
from geomstats.learning.frechet_mean import Fr... |
f33255509d64b092635d03cebadaffb6940ecca2ad0e6c3e4bc467a03fa4f688 | Python | 4,842 | 131 |
import string
from pathlib import Path
import matplotlib.pyplot as plt
import numpy as np
import torch
from matplotlib import cm
import mlspm.preprocessing as pp
from mlspm.datasets import download_dataset
from mlspm.models import EDAFMNet
# # Set matplotlib font rendering to use LaTex
# plt.rcParams.update({
# ... |
1093b6cc0ff3e45690512f71b0fce12f9b2a0c877c4376bc2cb39bb20924271a | Python | 4,846 | 161 | import logging
from collections.abc import Callable, Iterable
from datetime import timedelta
from operator import length_hint
from pathlib import Path
from typing import IO, TypeVar
from rich.progress import (
BarColumn,
DownloadColumn,
FileSizeColumn,
Progress,
TaskProgressColumn,
TimeRemainin... |
71065cb4bad1f44d06fe4d82bdb7321af2dca8cb5e230d38a68ec0005d63b4c0 | Python | 4,854 | 127 | """The registry against a real VDJdb release zip.
Marked ``release``: needs ``VDJDB_REFERENCE_ZIP`` and runs nightly, not per-PR. It is the check that
the positional contracts in ``vdjdb.schema`` describe the file consumers actually parse, rather than
what the source code says they should.
"""
from __future__ import a... |
f72cc3d316abc390f8e811b1100f2baf7a1404380fecefc97531c5be81c72e04 | Python | 4,854 | 146 | # 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... |
4062bbb16d91b78c499f6329b219cab99670ffbf5a7ab6c52695123dcb001dd7 | Python | 4,855 | 155 | """
NeuroLearn datasets
===================
functions to help download datasets
"""
## Notes:
# Need to figure out how to speed up loading and resampling of data
__all__ = [
"download_nifti",
"get_collection_image_metadata",
"download_collection",
"fetch_emotion_ratings",
"fetch_pain",
]
__autho... |
da41a6ecc7aaee2f844eec3128d80078c0c91341c721a86d6317dc0139eb9ddd | Python | 4,859 | 149 |
import json
from functools import partial
from PyQt5.QtCore import QSettings
from sleepy.gui.settings.view import SettingsView
from sleepy.gui.builder import Builder
from sleepy import SLEEPY_ROOT_DIR
from sleepy.gui.settings._view import VIEW
import pdb
class Settings:
def __init__(self, application... |
19f0a2027ff415af9f0366e49319c33ce74d0533f5305bfd29abaf039fdb2eca | Python | 4,860 | 147 | from __future__ import annotations
from enum import Enum
from pathlib import Path
from typing import Dict, Generic, Iterable, List, Mapping, Protocol, Sequence, overload
from typing_extensions import Self, TypeAlias, TypedDict, TypeVar
from snakebids.utils.containers import MultiSelectDict
_T_contra = TypeVar("_T_c... |
d49412d5783c46d6b63d504c33660d501d980ddb5e1029626a84de08613c1865 | Python | 4,860 | 147 | # Copyright (C) 2020-2023 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""Pipeline tests module."""
import numpy as np
import pytest
from openfl.pipelines.pipeline import Float32NumpyArrayToBytes
from openfl.pipelines.pipeline import TransformationPipeline
from openfl.pipelines.pipeline import Transformer
... |
8bb4e2fddd43967dc518035e60edfbd12ddfaa7f03b54690816147b989976b37 | Python | 4,863 | 144 | """MolScore adapter for REINVENT scoring
Wraps any scoring function exposed by MolScore for use as a REINVENT
scoring component. The user specifies the MolScore scoring function
class name and its keyword arguments via the REINVENT config.
"""
from __future__ import annotations
__all__ = ["MolScore"]
import loggin... |
a0e5e3d930e23b16eeb503e117520b39e08dbaa34651eeb08dc2bf3c8ba47e78 | Python | 4,863 | 138 | import collections
import numpy as np
class Normaliser:
def __init__(self,
sample_iterable,
normalisation_scope):
self._sample_iterable = sample_iterable
self._normalisation_scope = normalisation_scope
if self._normalisation_scope not in ["sample",
... |
2deff96fa79b954b74f3334ff41c46ffe2188cb0705ba661ff76c88ce5b61fd0 | Python | 4,864 | 111 | import warnings
warnings.filterwarnings("ignore")
# import pickle5 as pickle # this is for local run
import pickle # this is for sherlock run
import matplotlib as mpl
from utilityFunctions import *
high_res=True
parent_substitutions={
'Amyg, Amygdala': 'Middle Temporal Gyrus',
'CG, Cingulate Gyrus': 'Cingulat... |
c18b56b6bef488b9a8e1ecb0938dc66e74b2b994eb01f78ba4be6cd1f5e27206 | Python | 4,866 | 150 | """
Code to read in a json describing hyperparam sweep and create
scripts to execute each combination
"""
import os, sys
import logging
import argparse
import itertools
import json
from typing import *
logging.basicConfig(level=logging.INFO)
def params_to_cli_args(param_dict: Dict[str, Any]) -> str:
"""Format t... |
d84e2d0cd57d7c14a121951dbaa4119b7f4b2fac197a09f0c12d5dfd0bf5c804 | Python | 4,869 | 125 | import numpy as np
from odl import nonuniform_partition
from odl.tomo import Parallel2dGeometry, RayTransform
from dival.datasets.dataset import Dataset
def get_angle_subset_dataset(dataset, num_angles, **kwargs):
"""
Return a :class:`AngleSubsetDataset` with a reduced number of angles.
The angles in the... |
25f295e208fd2bc08e721ab215002ba8b6d9913283bda170a081a15e7e6458e1 | Python | 4,871 | 120 | """Which first interaction block a `--model MACE` run actually gets.
`configure_model` keeps an allowlist of three blocks for the first layer, and
rewrites anything else to `RealAgnosticInteractionBlock` without saying so
(mace/tools/model_script_utils.py:282-289). So `--interaction_first` can name a
registered, valid... |
7d265c0deac0c82fcb5a73f50951d2c28aa088939dbc93199beaffb723b0e244 | Python | 4,872 | 150 | #!/usr/bin/env python3
"""
Used for EMA tracking a given pytorch module. The user is responsible for calling step()
and setting the appropriate decay
"""
import copy
from dataclasses import dataclass, field
import logging
import torch
from fairseq.dataclass import FairseqDataclass
@dataclass
class EMAModuleConfig... |
edc9c280ab2f0abce71ac811533c03c61fef7ee5815680f70e8c128ec0805358 | Python | 4,872 | 131 | # MODIFIED VERSION ONLY READING FILES
# working here (11Aprl)
import os
import numpy as np
import pandas as pd
import torch
import matplotlib.pyplot as plt
from sklearn.manifold import TSNE
from tqdm import tqdm
import json
import torch
from torch_geometric.data import HeteroData
import torch_geometric.transforms as... |
f9f8b70f58cfd22675248e1bdde14563e80e2b8b41ddc0b17615fd4fe45721a5 | Python | 4,874 | 141 | """The LinkInvent sampling module"""
__all__ = ["LinkinventSampler", "LinkinventTransformerSampler"]
from typing import List
import logging
import torch.utils.data as tud
from rdkit import Chem
from .sampler import Sampler, validate_smiles
from . import params
from reinvent.models.linkinvent.dataset.dataset import D... |
07f7325563e5684b7999332cd00fb85abfe734ccfcfe120805cd638eda893c06 | Python | 4,875 | 177 | import pytest
import numpy as np
from reinvent.scoring.transforms import DoubleSigmoid
from reinvent.scoring.transforms import ReverseSigmoid
from reinvent.scoring.transforms import Sigmoid
from reinvent.scoring.transforms import LeftStep
from reinvent.scoring.transforms import RightStep
from reinvent.scoring.transfo... |
a25acb7055e39f7de3e6c06720c421a93da70c9e367dd4be46c85e5f4a5de861 | Python | 4,875 | 126 | """
Run Time Optimization
=====================
In this tutorial, we will go through some of the options you have to improve the run-time of vector-field evaluations
based on the equation files generated by PyRates.
As an example, we will use a model of :math:`N = 100` interconnected leaky integrator units, the evolut... |
957fbdfb6a49668e3d40e6423fa632951276ece875084f878a26aba904af1401 | Python | 4,879 | 159 | """Pytorch based linear algebra backend."""
import numpy as _np
import scipy as _scipy
import torch as _torch
from torch.linalg import (
cholesky,
det,
eig,
eigh,
eigvalsh,
inv,
matrix_power,
qr,
solve,
)
from torch.linalg import matrix_exp as expm
from ..numpy import atol
from ..n... |
7d387b913d3b45aa264ccbbe0fb4520f2e4db320f995f3eb58044ef8e392bbac | Python | 4,882 | 120 | # call sampler
# call scoring
# TODO: what is missing? Amino acid correct chemistry check (from pepinvent fragments), log out amino acid names, correct input, run mode exposure
from __future__ import annotations
import csv
import logging
import os
from reinvent.models.model_factory import sample_batch
__all__ = ["r... |
ba8317c47da54dd0542f1476155faebd1612e2e1dcb8f5846520751796e668ee | Python | 4,882 | 191 | from __future__ import absolute_import
from scipy import stats
from scipy.stats import rv_continuous
import numpy as np
import sys
from .decorators import swap2zeroaxis
from .descriptive import resultant_vector_length
@swap2zeroaxis(['alpha'], [0])
def kappa(alpha, w=None, axis=None):
"""
Computes an approxi... |
6b7f1078071507da2ecdd348b335d4024257cb80811157a48a4cb5ec60daac1b | Python | 4,884 | 142 | from chromadb.api.types import EmbeddingFunction, Space, Embeddings, Documents
from chromadb.utils.embedding_functions.schemas import validate_config_schema
from typing import List, Dict, Any, Optional
import os
import numpy as np
import warnings
class VoyageAIEmbeddingFunction(EmbeddingFunction[Documents]):
"""
... |
3438fbd83750d00062c6361fffb4fd8253bea122274048155d699d9067f0565b | Python | 4,885 | 168 | """
Communicate with TimescaleDB databases.
Author: Tal Eisenberg, 2021
This module requires the psycopg2 library. psycopg2 is an optional dependency, and only
necessary when database communication is required.
The module tries to make a default connection to a localhost
"""
import multiprocessing as mp
try:
im... |
b55359caead77f461ca47c2f622bd5e4ec129270e3cc106c61e0010c4edc90df | Python | 4,885 | 127 | """Tests for nltools.algorithms.signal — temporal signal processing."""
import numpy as np
import polars as pl
import pytest
from nltools.algorithms.signal import downsample, upsample, calc_bpm, make_cosine_basis
class TestDownsample:
"""Test downsampling algorithm."""
def test_downsample_mean(self):
... |
db953e7015231535ce14c2294aa66771dc0f15d8deeec83b77aba6de502cbe86 | Python | 4,888 | 149 | import sys
import multiprocessing as mp
from PyQt5.QtGui import QTextCursor
from PyQt5.QtCore import QObject, pyqtSignal, pyqtSlot, QThread
from PyQt5.QtWidgets import QDialog, QVBoxLayout, QTextEdit
from neurodecode.logger import add_logger_handler
from neurodecode.utils.lsl import list_lsl_streams
#################... |
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