sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
0a83a080d8336f4794f7171ba140d0f047892889cd3ea48f93a11b58b2987ffc | Python | 3,029 | 89 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 agr... |
2b73bcdf8b0bffc3578469b90c218e703580228f4f9ae909a29fbb808ba07b82 | Python | 3,029 | 89 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""Folding the case embedding of a fitting into its first layer.
The case embedding is the same block of input columns for every atom, so the
fold moves its product with the first-layer weight into the bias. The folded
fitting carries no case embedding and gives the outputs... |
548a4c070fe41b1c6dfe2ee6251599fd36d70931b288e30f0b369664dc22624a | Python | 3,030 | 107 | # Copyright 2026 DeepMind Technologies Limited
#
# 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 agr... |
a55a7cb72f2d9ee7d43635dbf0d1a753e418b13fe4d01485ba569bd2a2f8fe55 | Python | 3,030 | 78 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 agr... |
332a75c01cfad7a48186da768f2f5d8e17dbd8769d9c5e8870d2325c30a95238 | Python | 3,031 | 110 | # Copyright 2026 DeepMind Technologies Limited
#
# 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 agr... |
fbf9a56d804e3bb39d03994a38e67557e447dc25f28b74822c7553bde702ba8a | Python | 3,033 | 78 | from __future__ import division
import mkl
mkl.set_num_threads(1)
import sys
import numpy as np
from SPHARM.lib import spharm
import SPHARM.lib.parallel as prl
from SPHARM.lib import plotting as plt
import SPHARM.lib.segmentation as sgm
import SPHARM.lib.vrml_parse as vr
#################################
args = sy... |
07d64982daa86bd13570b41f14c853c7aa1c7ef720b58497e1ae170d6c24999a | Python | 3,036 | 80 | # Copyright 2019 DeepMind Technologies Ltd. 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 appl... |
70fa68ed4bf022e329d2d079d1cc49eb036f67b5b537a958d1c5104ed29b9455 | Python | 3,036 | 90 | #-------------------------------------------------------------------------------
# elftools: dwarf/abbrevtable.py
#
# DWARF abbreviation table
#
# Eli Bendersky (eliben@gmail.com)
# This code is in the public domain
#-------------------------------------------------------------------------------
from __future__ import ... |
55b1c6617d371a21af53c0f8a8ad175962796a70548713931588cbe7ab6fa559 | Python | 3,037 | 76 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 agr... |
b229dfea2b27ff7fe1e2676ac4821626da41807ec2187f95b8047962c9008bfe | Python | 3,037 | 54 | # aggregating the main steps of ontology-based and weakly supervised rare disease identification from clincal notes
# ruuning step1 requires SemEHR-processed output
from subprocess import Popen, STDOUT
import argparse
import time
start_time = time.time()
parser = argparse.ArgumentParser(description="an implement... |
754ebac2f4f1cea518fb852ab2f1213ef719cf0cfef004e7ddfd0c6faf646db8 | Python | 3,038 | 90 | """Global Alignment Kernel from tslearn."""
__author__ = ["fkiraly"]
from sktime.dists_kernels.base import BasePairwiseTransformerPanel
from sktime.dists_kernels.base.adapters import _TslearnPwTrafoAdapter
class GAKernel(_TslearnPwTrafoAdapter, BasePairwiseTransformerPanel):
r"""Global Alignment Kernel, from ts... |
2d77e4914c87f0726eb1e68d5aab189f043a376290bb87fce164b4397f5918f8 | Python | 3,041 | 87 | import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
def model_predict(model, X, label):
'''Predict class for data'''
y = model.predict(X)
# Get resutls back to categories
y = label[y]
# ypA_rfrg results back to a data frame/series
y = pd.Series(y)
# Recover original ... |
5fa4db61287d68ba6d2588c5c387f3dda036aab269f45e36404d77d34d65e48a | Python | 3,041 | 71 | from torch import nn
import torch
from vp_suite.base import VPModelBlock
class ConvLSTM(VPModelBlock):
r"""
This class implements a convolutional LSTM, as introduced in Shi et al. (https://arxiv.org/abs/1506.04214) and
implemented in https://github.com/Hzzone/Precipitation-Nowcasting. This is the 'origin... |
4a17cc2f52957f1bfa5228cbc38cc801ae900efa31c95452a25c779c5963a9dd | Python | 3,043 | 79 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 agr... |
874fdb56e533dd4a6b40f44f9b5912b89cd1991e1ca9f7c59645c99e6ee36192 | Python | 3,045 | 101 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
from onnx.helper import make_tensor
class LabelEncoder(Base):
@staticmeth... |
f3cd6a77c6683ffaf62b5b8ab86eea9b70f8d4d3aa0992e8b0813ae75e18db14 | Python | 3,045 | 77 | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import matplotlib as mpl
mpl.rcParams['pdf.fonttype'] = 42
mpl.rcParams['ps.fonttype'] = 42
mpl.rcParams['font.family'] = 'Arial'
# settings
cellclass_ordered_v2 = ["Cycling Dorsal NEC", "Cycling Ventral NEC", "Cycling NE... |
7a5081c5fba01bfb85c2770aae8d2f02a04f248de46a0f10013090528bc4dcc2 | Python | 3,046 | 97 | from __future__ import annotations
from pathlib import Path
import numpy as np
import pytest
from jetnet.datasets import QuarkGluon
from pytest import approx
# TODO: use checksum for downloaded files
test_file_list_withbc = [
"QG_jets_withbc_0.npz",
"QG_jets_withbc_1.npz",
]
test_file_list_withoutbc = [
... |
bd3f59fa6c14bce250e42f9028e02f09e4fb74afa8fed765bc8336e45a1f61d4 | Python | 3,046 | 82 | import json
import logging
import os
import urllib
from pathlib import Path
import numpy as np
import torch.utils.data.dataloader
from torch.utils.data import Dataset
from tqdm import tqdm
from flair.data import Corpus, DataPair, FlairDataset, Image, Sentence
from flair.file_utils import cached_path
log = logging.ge... |
734bd3b01af3aae588c9c6b398d6e3cd73f0b5a40d2299c00f9efba426a7280f | Python | 3,047 | 72 | # Copyright 2019 DeepMind Technologies Ltd. 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 appl... |
07def4f0a796ea9b81f3be26be67d8141c9f98156d486a2dba4e04d8c130fbf5 | Python | 3,049 | 98 | # coding=utf-8
# Copyright (C) 2021. Huawei Technologies Co., Ltd. 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
#
# ... |
735d9d450175d74a7363804a8393ea2f1a677915c5542bb9e1a537866cfd1301 | Python | 3,049 | 85 | import os
import dotenv as de
import numpy as np
import pandas as pd
from atom3d.datasets import LMDBDataset
from atom3d.util.voxelize import dotdict, get_center, gen_rot_matrix, get_grid
from torch.utils.data import DataLoader
de.load_dotenv(de.find_dotenv(usecwd=True))
class CNN3D_TransformSMP(object):
def ... |
6c6e1806cc2d8f675e8507add01af53e2bc2be79c4e115b78aef0ac29d5464c3 | Python | 3,056 | 92 | #!/usr/bin/env python
from __future__ import print_function
import sys,os
import argparse
import logging
desc = 'Summarize PAF file generated by minimap2'
epi = """DESCRIPTION:
Summarize PAF file (see https://github.com/lh3/miniasm/blob/master/PAF.md)
to get information such as:
* chimeric contig (Supplementary align... |
ac74b99e3ade43a952b22dc1a519e396fcf82dd00fd72a4af8aa7c8fbae34b69 | Python | 3,058 | 90 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 agr... |
ae33b9c2e1388b80d5f59b851953c14176d4315c2dfd33192e9641bb29cc152f | Python | 3,058 | 69 | import numpy as np
def attribution_correction(attr_score):
return attr_score - np.mean(attr_score, axis=2, keepdims=True)
def cosine_similarity(x1, x2):
scalar_product = np.average(np.sum(np.sum(np.multiply(x1, x2), axis=2), axis=1)/(np.sqrt(np.sum(np.sum(np.multiply(x1,x1), axis=2), axis=1)) * np.sqrt(np.... |
09731dada56411269726ec26c801f027107d47cc0ef63dc1517b79d53b944583 | Python | 3,059 | 106 | """
Tutorial demonstrating a network with electrical synapses, both bidirectional and rectified.
"""
from sns_toolbox.connections import ElectricalSynapse, NonSpikingTransmissionSynapse
from sns_toolbox.neurons import NonSpikingNeuron
from sns_toolbox.networks import Network
from sns_toolbox.renderer import render
im... |
ad70b553197bae27ce3e6855f3af8fe7829b7dc5e609211979cf44593adf388f | Python | 3,060 | 93 | # Copyright 2019 DeepMind Technologies Ltd. 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 appl... |
d4b5580d7e01be0786bb1a38c24658ccee61956f5e08c5df90d3779981bcbf92 | Python | 3,060 | 78 | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
import torch.nn.functional as F
from mmcls.utils import get_root_logger
from ..builder import HEADS
from .vision_transformer_head import VisionTransformerClsHead
@HEADS.register_module()
class DeiTClsHead(VisionTransformerClsHead):
def __init... |
4d1561156f04f13e91dc68eea5fa33ff4c22e9980036767dbe3401fd86addfce | Python | 3,061 | 104 | # Mocapy: A parallelized Dynamic Bayesian Network toolkit
#
# Copyright (C) 2004 Thomas Hamelryck
#
# This library 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... |
7431f9441aeefe0c37272bd5c107e32aae3bafa7f7e9e9b31fb95e2992273771 | Python | 3,063 | 86 | # Copyright 2023 DeepMind Technologies Limited
#
# 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 agr... |
ddc3b9c33d8e31b2c02329b2c6654b9ad9bd93cc44884e5a3a9e3ab2bfec4d02 | Python | 3,064 | 115 | """
Django settings for web project.
Generated by 'django-admin startproject' using Django 4.1.5.
For more information on this file, see
https://docs.djangoproject.com/en/4.1/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/4.1/ref/settings/
"""
from pathlib imp... |
6b96aadcf77821753b987dd0a2912808b1a11167dc2defd30a101936afc85b19 | Python | 3,065 | 87 | # Copyright 2023 DeepMind Technologies Limited
#
# 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 agr... |
471fa887978b2d52b820b3383c095413dd40707393b423a9ebdf2afcc0c23807 | Python | 3,067 | 88 | # Copyright 2023 DeepMind Technologies Limited
#
# 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 agr... |
749ea1d9183f22d377c6941db739620e97d12ca44ac475bb8a591845aa111461 | Python | 3,067 | 112 | # Copyright 2019-2020 The ASReview 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 appl... |
638ee5959b562d12c7ec7742fb38e0c36d079b8efdd0c3c1301cd8979a68d2ac | Python | 3,069 | 84 | from typing import Callable, Iterable, List, Tuple
import numpy as np
from sklearn.metrics import accuracy_score, f1_score
from torch_geometric.data import HeteroData
f_score = lambda x, y: f1_score(x, y, zero_division=1)
EPS_ZERO = 1e-8
def color_agreement(color_true: List[int], color_pred: List[float], metric_f:... |
9c609f5073fe9057429a7787343d8a4e0943b436fd00a32e983c0d132a658ad7 | Python | 3,071 | 94 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 agr... |
a51439cc612651fb4fd54e2718e17436fb6f573c4e112f6bb1770082e8090a0f | Python | 3,071 | 107 | #!/usr/bin/env python
import click
from functools import partial
from multiprocessing import Pool
import numpy as np
import os
import pandas as pd
from sklearn.preprocessing import quantile_transform
import subprocess as sp
from tqdm import tqdm
bar_format = "{percentage:3.0f}%|{bar:20}{r_bar}"
# Globals
scripts_dir ... |
c90d9d723dbd3a8213351c54e4cbe6a1060e012f53f4f3b0e4b3d8c0c24cf761 | Python | 3,071 | 127 | import itertools
import numpy as np
def ell(i, x):
r = np.linspace(0, 1, 4)
ind = list(set(range(4)) - set([i]))
num = (x - r[ind[0]]) * (x - r[ind[1]]) * (x - r[ind[2]])
den = (r[i] - r[ind[0]]) * (r[i] - r[ind[1]]) * (r[i] - r[ind[2]])
return num / den
def psi(i, x):
ind = [0, 1, 2, 3]
... |
530bc5b2f8ac90a8212d2e73bbf79d9e5bc7d0b22912e2d0b279425513954676 | Python | 3,073 | 92 | #!/usr/bin/env python3
"""
Generate a script to move files and update import iris.
"""
import os
from IPython import embed
#source locations TODO we should support arbitrary bases here and enforce subfolder namespace purity
GIT_BASE = '~/git/NIF-Ontology/'
GIT_FOLDER = os.path.expanduser(GIT_BASE + '.git/')
with... |
b1bc5707d0b61170041ca70fc25121d95a6dcc873594a89f7d3aff3f1a51fd46 | Python | 3,073 | 77 | # Copyright 2019 DeepMind Technologies Ltd. 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 appl... |
f96a424b74bedd77372fb7e28b28dfc3b38df04f8c652bec71e817703248a1d9 | Python | 3,075 | 95 | from matplotlib import pyplot as plt
import numpy as np
def plot_overlay(t, lfp, mantle, savename=None):
fig, ax = plt.subplots(figsize=(6,4))
ax.plot(t, lfp, color="blue")
ax.set_xlabel("sec")
ax.set_ylabel("V")
ax2 = ax.twinx()
ax2.plot(t, mantle, color="orange")
ax2.set_ylabel("a.u.")
... |
fb608cecf8d8e9d848cb633840a2ddb3f26e3d7abd42e186fda1c20552eeb270 | Python | 3,078 | 90 | # coding=utf-8
# Copyright (C) 2021. Huawei Technologies Co., Ltd. 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
#
# ... |
232d147652b6069a01c1dddd50755ed4e96e2d57c3b284a70e54c78a6e888d3e | Python | 3,079 | 132 | import sys
import _pickle as pickle
import numpy
print('\n$1 NETWORK_PATH (col1: gene; col2: gene)\n$2 EXP_POOL_PATH (col 1: gene; other col: exp value)\n$3 OUT_DATA_PATH\n')
NETWORK_PATH=sys.argv[1]
EXP_POOL_PATH=sys.argv[2]
OUT_DATA_PATH=sys.argv[3]
SPLIT=':'
class Person_PCC_Data:
def __init__(self, EXP, POOL... |
6f20554139c722f3a5fffde57ad97c377275b3c56b05d6a42e1ec6b98d39cf2c | Python | 3,079 | 100 | from __future__ import print_function
"""
Utility class for spawning and controlling CLI processes.
See: http://stackoverflow.com/questions/375427/non-blocking-read-on-a-subprocess-pipe-in-python
"""
import sys, time
from subprocess import PIPE, Popen
from threading import Thread
try:
from Queue import Queue, Em... |
2a513bdb0454121fd6e506cf35b9ea5f8836284c7c458671c17f52657f7df9cf | Python | 3,080 | 97 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
from typing import Any
import numpy as np
class SVMAttributes:
def __init__(self):
self._names = []
def add(self, name: str, value: Any) -> None:
if isinstance(value, list) an... |
42d7c9deb2cfa747d0c802da676fe383631ae817cce4a8faf6707352c47292ae | Python | 3,080 | 91 | from __future__ import print_function
import numpy as np
from .augment import Augment, Blend
from .perturb import Grayscale
from .section import Section, PartialSection, MixedSection
__all__ = ['Grayscale2D', 'Grayscale3D', 'GrayscaleMixed',
'PartialGrayscale2D', 'MixedGrayscale2D']
class Grayscale3D(Au... |
6724d53656c0ef94d1d3ca775b1b3c638d9340f87c7c5e94120ae30567ceb0f7 | Python | 3,080 | 55 | import argparse
import sys
import JH_error_list
def net_param_setting(net_type, dataset):
# =====================================================================================================================#
# ==================================== Hyper Parameter of Network ==================================... |
bcd25a7ccc37db979c48ef54c602a55c9a496ddb488d01cbcea7bff90a434b54 | Python | 3,080 | 89 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 agr... |
a19df9a252c4430109c11b9de24232686bc5745656069462c14caa73b4693ca1 | Python | 3,082 | 85 | """Build a tiny Hugging Face snapshot of the Tabby backbone.
The release ships no checkpoints, and ``*.safetensors`` is git-ignored, so the
checkpoint-loading tests generate their own sample snapshot instead of reading
one from the repository. The layout produced here is the one the loaders
accept in production -- a ... |
b4a615c944158e70740667084349d201da80a7085f31197f5605ea9c4b1f0419 | Python | 3,082 | 99 | # -*- coding: utf-8 -*-
"""
Created on Thu December 10 11:41:02 2022
@author: Pawan Panwar, Quanpeng Yang, Ashlie Martini
PyL3dMD: Python LAMMPS 3D Molecular Dynamics/Descriptors
Copyright (C) 2022 Pawan Panwar, Quanpeng Yang, Ashlie Martini
This file is part of PyL3dMD.
PyL3dMD is free software: you ... |
f85dba90e5f4a95dd3132b1bca29255bae3aba752f86714bcb846de2e9269999 | Python | 3,082 | 87 | # coding=utf-8
# Copyright (C) 2021. Huawei Technologies Co., Ltd. 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
#
# ... |
c128886236314e90d0215ae7c634d8b46524ce8f2f24409e58ebabd78ed48147 | Python | 3,083 | 89 |
#=======================================================================================================================
# Copyright (C) 2021 Matvey Safroshkin, Grigory Arutyunov, Patrick Mueller
# Computer Vision Studio
# Friedrich Miescher Laboratory of the Max Planck Society
# Systems Biology of Development, Univer... |
93d9500d090d472a4e6d163275721431d80e6c42b3abc35ded8dafe345446932 | Python | 3,084 | 102 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 agr... |
98fb46970724c1e68d816eafd9601d70c9ec7143d7d36f7c0a61d333a630f1ec | Python | 3,084 | 76 | import pytest
import numpy as np
import pandas as pd
import scanpy as sc
from anndata import AnnData
from pandas.testing import assert_frame_equal
from palantir.utils import determine_multiscale_space
def test_determine_multiscale_space_with_dict(mock_dm_res):
"""Test determine_multiscale_space with dictionary i... |
75927cc892a1a604f698d991769e064d98165395ad6535d7e325e17f5387ccb8 | Python | 3,085 | 96 | """decoder.py"""
"""
Author: Yimin Yang
Last revision date: Jan 18, 2022
Function: Decoder of AA_TransUNet
"""
import torch
import torch.nn as nn
class SingleConv(nn.Module):
"""
Double convolution block that keeps that spatial sizes the same
"""
def __init__(self, in_ch, out_ch, norm_layer=None):
... |
78b391b92fad559d24538ce28fa4afd5cb86d9e6979ee42534f268ad08be9929 | Python | 3,085 | 64 | import numpy as np
import os
import torch
from tqdm import tqdm
from atom3d.util.transforms import prot_graph_transform, mol_graph_transform, PairedGraphTransform
from atom3d.datasets import LMDBDataset
from torch_geometric.data import Data, Batch, DataLoader
import atom3d.util.graph as gr
class GNNTransformLEP(o... |
1c0c146abd9412eb3c394098987690dee0575c8d969a6e1c13e18b59d100d4a2 | Python | 3,086 | 86 | import face_recognition
import cv2
# This is a demo of running face recognition on a video file and saving the results to a new video file.
#
# PLEASE NOTE: This example requires OpenCV (the `cv2` library) to be installed only to read from your webcam.
# OpenCV is *not* required to use the face_recognition library. It... |
b65f1ed01deb85ac82e6cf0f5aa7c0030e827e199b597354f27a043a2c38c6e5 | Python | 3,086 | 94 | # Copyright 2019 DeepMind Technologies Ltd. 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 appl... |
cc7e924359b8a0ce6176be1a5d1e56ae24f7385937191164a61010bd46337a0d | Python | 3,091 | 71 | # Copyright 2007 Zachary Pincus
# This file is part of CellTool.
#
# CellTool is free software; you can redistribute it and/or modify
# it under the terms of version 2 of the GNU General Public License as
# published by the Free Software Foundation.
def procustes_alignment(points, reference, weights = None, allow_ref... |
e507035001deb9abcc5177ea40b88580e4b9eb78723685fac503427bdfa25389 | Python | 3,091 | 104 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
class ReduceLogSum(Base):
@staticmethod
def export_nokeepdims() -> N... |
cb88e3c17bed312368baeb188bf6a955a38dc2771d600741db507629537c82c2 | Python | 3,092 | 109 | """
test_simple_synapses
Test synapses between cell types.
Usage:
python test_synapses.py <pre_celltype> <post_celltype>
Supported cell types: sgc, bushy, tstellate, dstellate, tuberculoventral, pyramidal
"""
import sys
import argparse
import pyqtgraph as pg
from cnmodel.protocols.simple_synapse_test import ... |
89184311720ae4c5c0995b598834dace802607061a28af3f5efbf8ae1ca96c34 | Python | 3,093 | 95 | """ Used as a master args reader for scripts that read, add, and update Interlex data through its API
Usage: api_wrapper.py [-h | --help]
api_wrapper.py [-v | --version]
api_wrapper.py <argument> [-f=<path>] [-o=<path>] [-p | -b]
Arugments:
addTerms Add terms|cdes|annotatio... |
383fd9f816fb575d8b18e229cea4f3fcee2ac3417d486a15d40a46ff69a56743 | Python | 3,095 | 102 | from __future__ import annotations
from io import BytesIO
from typing import TYPE_CHECKING
from optuna._experimental import experimental_class
from optuna._imports import try_import
from optuna.artifacts.exceptions import ArtifactNotFound
if TYPE_CHECKING:
from typing import BinaryIO
with try_import() as _impo... |
d41dbe7ae3a54b45ea20ebeec7205052048ef66d4a45b8bf5f9101c717ebeec9 | Python | 3,096 | 83 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 agr... |
5123dde171fafc9ea19e1caeadc961978a251749f967f474dc4508a2e4aeb9d5 | Python | 3,097 | 83 | import numpy as np
ORIENTATION = {
'coronal': "COR",
'axial': "AXI",
'sagital': "SAG"
}
def rotate_orientation(volume_data, volume_label, orientation=ORIENTATION['coronal']):
if orientation == ORIENTATION['coronal']:
return volume_data.transpose((2, 0, 1)), volume_label.transpose((2, 0, 1))
... |
fad36998b6207d27e56cb1ae03bee1155e54f4194fc1036757d1a6384d242858 | Python | 3,098 | 74 | # Copyright 2019 The TensorFlow 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 applica... |
f2aa83601aee1017c17ad71387a8bf65f4a03053590b8185a7d44390b50f8b3f | Python | 3,101 | 83 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 agr... |
bf734c3eca8153b19bd5ff5197678e4a7584895594367c8bade63afa4a1890e9 | Python | 3,102 | 95 | """Critical-difference diagram evaluator for benchmark results."""
__all__ = ["CriticalDifferenceDiagram"]
from skbase.utils.dependencies import _check_soft_dependencies
from sktime.benchmarking.analysis._base import BaseBenchmarkAnalyzer
class CriticalDifferenceDiagram(BaseBenchmarkAnalyzer):
"""Critical-diff... |
6a3e932a75c7268f672731079083d0e91337ab74c1eda13616829aa22fe002c3 | Python | 3,103 | 105 | import pytest
import importlib
import atom3d.util.formats as fo
# -- Reading PDB-like formats --
numres = {'103l':290,'117e':1029,'11as':740,'2olx':4}
def test_read_any_pdb():
for c in numres.keys():
bp = fo.read_any('tests/test_data/pdb/'+c+'.pdb')
nr = len([r for r in bp.get_residues()])
... |
10d5a416caa51521aad5f8170852487cad8498bc0a881f1061e54778089428ff | Python | 3,104 | 102 | import sys
import numpy as np
Pposition={}
Lposition={}
ResinameP={}
ResinameL={}
Atomline=[]
residuePair=[]
if len(sys.argv) <1 :
print("python python2_L.py xxx")
filebase=sys.argv[1]
print(filebase)
for line in open(filebase+'_w.pdb'):
tem_B=' '
if len(line)>16:
tem_B=line[16]... |
91ccfd48bd34bcb04fad7c3cd56ede8ad3a49d6c09274b8dc43930bdda416022 | Python | 3,104 | 102 | import sys
import numpy as np
Pposition={}
Lposition={}
ResinameP={}
ResinameL={}
Atomline=[]
residuePair=[]
if len(sys.argv) <1 :
print("python python2_L.py xxx")
filebase=sys.argv[1]
print(filebase)
for line in open(filebase+'_w.pdb'):
tem_B=' '
if len(line)>16:
tem_B=line[16]... |
d504b25dbe990f87793dbd0ce1598a7e1788d242774e85608f20c9011055a5e9 | Python | 3,104 | 88 | """Independent t-test evaluator for benchmark results."""
__all__ = ["TwoSampleTTest"]
import itertools
import numpy as np
import pandas as pd
from sktime.benchmarking.analysis._base import BaseBenchmarkAnalyzer
class TwoSampleTTest(BaseBenchmarkAnalyzer):
"""Independent two-sample t-test on each ordered pair... |
dbed157b735a699a32b4379a99324b2dbae01284faa7e1f4d90105bb09d33115 | Python | 3,109 | 92 | import html
from typing import Union
from flair.data import Sentence
TAGGED_ENTITY = """
<mark class="entity" style="background: {color}; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 3; border-radius: 0.35em; box-decoration-break: clone; -webkit-box-decoration-break: clone">
{entity}
<span style="fon... |
e4c9ff9c5a6e5ff0e665d615bbaba6e68ff6cd7d6feb216fb0abb4b4d0c05458 | Python | 3,112 | 85 | from flair.data import Dictionary, Sentence
from flair.embeddings import WordEmbeddings
from flair.models import TokenClassifier, SequenceTagger
from flair.tokenization import SpaceTokenizer, StaccatoTokenizer
def test_prediction_changes_tokenization():
# simple dummy model
dictionary = Dictionary()
dict... |
46e693c27c2557c4764e8ae999c35a871da8d1353855322d896a57b0cd214485 | Python | 3,113 | 67 | import numpy as np
import ast
import scipy
import matplotlib.pyplot as plt
import cv2
from keras.applications.resnet50 import ResNet50, preprocess_input
from keras.preprocessing import image
from keras.models import Model
import sys
def pretrained_path_to_tensor(img_path):
# loads RGB image as PIL.I... |
1be1b552673b743157c63c56e3aae4b34217567c207ff0c6018bd2aab0ac05a3 | Python | 3,116 | 81 | import logging
from pathlib import Path
from transformer_smaller_training_vocab import reduce_train_vocab
from flair.embeddings import Embeddings, StackedEmbeddings, TransformerEmbeddings
from flair.models import FewshotClassifier
from flair.nn import Model
from flair.nn.model import ReduceTransformerVocabMixin
from ... |
80ac39947a67bf630f122c9ba23207822a500dc0f287b23790a6c2ab220e897a | Python | 3,116 | 60 | import re
import unittest
from pathlib import Path
import pytest
from pyontutils.utils import get_working_dir
from nifstd_tools.docs import FixLinks
working_dir = get_working_dir(__file__)
if working_dir is None:
name = 'pyontutils'
else:
name = working_dir.name
base = ('/' + name + '/nifstd/test' + '/')
gitb... |
1eacc485afeb6291208fa9ef0f2f648144034c2f204cae130d4142640a1f7126 | Python | 3,117 | 103 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
# Ported from skchange (BSD-3-Clause), original authors: johannvk
"""L1 (absolute difference) cost function."""
__author__ = ["johannvk"]
import numpy as np
from sktime.detection._utils import check_mean
from sktime.detection.costs._base import ... |
b146c1bb6d417f42808901a56a8265665febf3b38af197fed18bb2ccd6ae1e32 | Python | 3,117 | 74 | """
Train models on synthetic data.
"""
import os
import numpy as np
from six.moves import cPickle
from tensorflow import keras
from gradient_correction import helper, model_zoo
#------------------------------------------------------------------------
num_trials = 50
model_names = ['cnn_deep', 'cnn_shallow']
activa... |
37a3e47ea8cf575acb4e81de3ffeef640814a50a9a6799473a7446d660a3b99c | Python | 3,118 | 109 | from __future__ import print_function
from collections import OrderedDict
import numpy as np
from . import utils
class Augment(object):
"""
Abstract interface.
"""
def __init__(self):
raise NotImplementedError
def prepare(self, spec, **kwargs):
return dict(spec)
def __call__... |
54b5613a24777c073e9b49fad950d70cbf3b484fda2779445a9264dfa1f9ad65 | Python | 3,118 | 85 | import torch
import logging
import models.modules.RCAN_arch as RCAN_arch
import models.modules.RNAN_arch as RNAN_arch
import models.modules.UAN_arch as UAN_arch
import models.modules.TTSR_arch as TTSR_arch
import models.modules.DEFIAN_arch as DEFIAN_arch
import models.modules.discriminator_vgg_arch as SRGAN_arch
import... |
04c281c3b4713c62d163fe142c3f8653f28a4d4235086df5ac5aeb69f3432a5a | Python | 3,119 | 94 | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmcls.models.backbones import RegNet
regnet_test_data = [
('regnetx_400mf',
dict(w0=24, wa=24.48, wm=2.54, group_w=16, depth=22,
bot_mul=1.0), [32, 64, 160, 384]),
('regnetx_800mf',
dict(w0=56, wa=35.73, wm=2.2... |
0ec0d31f61aea0e6102c43bf85a06ac4021f829a999910346fb692535c944f7e | Python | 3,123 | 90 | import numpy as np
from scipy.sparse import csr_matrix
# SAFE TEAM
#
#
# distributed under license: CC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.txt) #
#
def __padAndFilter(input_pairs, input_labels, max_num_vertices):
output_pairs = []
output_labels = []
output_len = []
... |
b7a2b7faceff21153d96c1c5663e048e1056e253339ce4bb72d68bdb9301c04a | Python | 3,125 | 64 | """Export run-level scores, seed summaries and every defined cluster point."""
import argparse
import json
from pathlib import Path
import numpy as np
import pandas as pd
def export_tables(root):
root = Path(root)
runs, points = [], []
for path in sorted(root.glob("*/*/*/result.json")):
record = ... |
3f071d359cd6a3d2deaffbe4c5b57327c8dfd56c476206117f689ddde4a3e047 | Python | 3,128 | 90 | # Copyright 2022 DeepMind Technologies Limited
#
# 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 agr... |
e7c871bc23c12eb34f9b349f3caa524d54ffdf02cc960847b9a28fa119fc41a4 | Python | 3,129 | 118 | """
A toy model of a soma plus a tapering dendrite, with synaptic inputs
scattered along the dendrite. This is to investigate how dendritic
electrotonus and tapering affect the shape of the EPSC at the soma
as recorded under voltage clamp
"""
import sys
import os
import numpy as np
import matplotlib.pyplot as mpl
impor... |
bc0b271963c3b4fb058461eae9c9110eb897ee2611a49f1b2e21c7d0af388f8d | Python | 3,132 | 114 | #!/usr/bin/env python
import os
import sys
import re
import subprocess
import numpy
import logging
BIN = os.path.join(os.path.dirname(__file__), "jpegdir", "jpeg")
if not os.path.exists(BIN):
print("jpeg is not built yet; use 'cd jpegdir; make' first")
sys.exit(0)
# sample output
#> GW:1979 GH:4349 R:0
#>>... |
c80649d43e2f3edcf3f455d8b5a7d529d422cbf366bf8efd548cbbe71fe7daa8 | Python | 3,132 | 88 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 agr... |
0c32038886b73062ecdc3a4a6927a908af0e6fafaf1f09aa43131c0a55624c95 | Python | 3,133 | 111 | #!/usr/bin/env python3
""" api access for google sheets (and friends)
Usage:
googapis auth (sheets|docs|drive)... [options] [--drive-scope=<SCOPE>...]
Examples:
googapis auth sheets
Options:
--store-file=<PATH>... write to a specific store file
-n --readonly set the readonly scope
-... |
203962cde75ffb75cb0b5d8094ef23b3b9c3200cc9489931347211fb38761ea2 | Python | 3,133 | 88 | # Copyright 2023 DeepMind Technologies Limited
#
# 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 agr... |
2a2dca93fbbefcd1f650918582ba55dbe56c6c9f0bd582aab224099ca5992c6d | Python | 3,140 | 90 | """
This scripts plots figure 6b from the paper.
This is the accumualtor model output for the trained mice.
Internal notes:
"""
import pandas as pd
import pickle as pkl
import numpy as np
import os
import glob
import matplotlib.pyplot as plt
import matplotlib as mpl
from tqdm import tqdm
# Plotting
import sciplotli... |
35f2a146bf147b483aced0007fd5bca2c3b307c69ba838d9be698150028d5498 | Python | 3,140 | 86 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
class DynamicQuantizeLinear(Base):
@staticmethod
def export() -> Non... |
9f6f289e643ac88ba5801a3ba998ae92b73cbcf492869b7d15c089246632e969 | Python | 3,140 | 68 | import os
import numpy as np
import nibabel as nib
from os.path import join as pjoin
from had_utils import save2cifti
from scipy.stats import pearsonr
from sklearn.preprocessing import StandardScaler
# define path
# make sure the dataset_path are modified based on your personal dataset downloading directory
dataset_pa... |
1e11a49336151481389d5d1eb20776a126e78f0b7ddbda77d8a6d89c6b52b559 | Python | 3,141 | 90 | # Copyright 2022 DeepMind Technologies Limited
#
# 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 agr... |
bf7c735db3bebe30df476869e6eefb915fdc6cc7b95e4f452f2f5297bf1c4738 | Python | 3,141 | 79 | import face_recognition
import cv2
import numpy as np
# This is a super simple (but slow) example of running face recognition on live video from your webcam.
# There's a second example that's a little more complicated but runs faster.
# PLEASE NOTE: This example requires OpenCV (the `cv2` library) to be installed onl... |
06454ad82cab7a3b8617610da6bcdcc30264c146809e5f4cd45264651cc7561d | Python | 3,142 | 116 | import resource
from time import sleep
from pyarrow import Table
from pyarrow import csv
import pyarrow as pa
from pyarrow.parquet import ParquetWriter
import pandas as pd
import sys
from datetime import timedelta
from timeit import time
import pathlib
file = sys.argv[1]
output_dir = sys.argv[2]
name_of_smiles_col... |
60e75a46bc3af962026a79a81a43f54f6fc4b1de34893ed3137a4918dd05ab04 | Python | 3,143 | 77 | # Copyright 2019 Google Inc. 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 applicable law or a... |
4e106ece432b5ef276a557632dd225bf08416b6a60b1934d38411a297c1e6829 | Python | 3,146 | 97 | # Copyright 2026 DeepMind Technologies Limited
#
# 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 agr... |
3d68a8b8099e56333e0e22f9a92828de03655b6dc000c254ba74cb763b8dc07b | Python | 3,147 | 90 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
# Ported from skchange (BSD-3-Clause), original authors: Tveten
"""Tests for the CircularBinarySegmentation detector."""
import numpy as np
import pandas as pd
import pytest
from sktime.detection._change_scores._from_cost import ChangeScore
from ... |
ba2afcf2ca26f6bf0b34fa4212ba58a9fc6a0bcc3e81f1d090e28b0e7a8e36d3 | Python | 3,147 | 91 | import numpy as np
import matplotlib.pyplot as plt
def count_accuracy(W_true, W_est, W_und=None):
"""
Compute FDR, TPR, and FPR for B, or optionally for CPDAG B + B_und.
Args:
W_true: ground truth graph
W_est: predicted graph
W_und: predicted undirected edges in CPDAG, asymmetric
... |
f9b5e113af0b79c18e61effac6ea3283891824b9fbc5c00ad33c0b4326b02d4c | Python | 3,148 | 131 | import _pickle as pickle
import sys
from scipy import stats
import numpy
import multiprocessing
print('''$1: Index Data\n$2: Output file''')
INDEX_DATA_FILE=sys.argv[1]
OUT_FILE=sys.argv[2]
SPLIT=':'
class Person_PCC_Data:
import numpy
def __init__(self, EXP, POOL_LENGTH, PCC_POOL,header):
self.EXP =... |
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