sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
8767e97666dcd0e4161422e72bd2d5b21fc3a912c897070a17a3afd871c8f874 | Python | 2,912 | 86 | """
@file: input_representation.py
Created on 20.06.18
@project: jc39qevo-deep-learning-project
@author: queensgambit
Input representation for the Crazyhouse board state which is passed to the neural network
"""
import DeepCrazyhouse.src.domain.variants.input_representation as variants
from DeepCrazyhouse.src.domain.... |
e22dfd5d9df3a99296813ec64659e81162c897fff5988a12ac958bb6adeb2006 | Python | 2,912 | 65 | # 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.
"""Plot the shape modes of a given PCA shape model.
This tool gener... |
883a993ffcf381f6abdbc0338ef7f1d85932f9b7f8446e1c396dfcbff39cc294 | Python | 2,913 | 90 | import unittest
import os
import shutil
import numpy as np
from ddt import ddt
from SPHARM.classes.spectrum import Spectrum
from SPHARM.classes.time_spectrum import TimeSpectrum
@ddt
class TestTimeSpectrumClass(unittest.TestCase):
def test_add_spectrum_and_plotting(self):
tsp = TimeSpectrum()
... |
a5c609757633c8b42479e38ade849bfb325116c864856b7f7e16c035f4bd0f95 | Python | 2,914 | 99 | from netplotbrain import plot as npbplot
import pytest
import pandas as pd
import matplotlib.pyplot as plt
# Example node and edges dataframes included with package
nodes = pd.read_csv('./examples/example_nodes.tsv', sep='\t', index_col=0)
edges = pd.read_csv('./examples/example_edges.tsv', sep='\t', index_col=0)
# S... |
c069c1f0191d05c57087636525ddf7582c8f3e367d85d692f16a9ee91c164f49 | Python | 2,914 | 82 | import scanpy as sc
from anndata import AnnData
import numpy as np
import pytest
from scipy.sparse import csr_matrix
from palantir.utils import run_local_variability
# Mock data for dense matrix
def mock_anndata_dense(n_cells, n_genes, layer_keys, obsp_keys):
rng = np.random.default_rng()
ad = AnnData(rng.ra... |
70d79fde77e718408deaad587f0c2eafbc2bd31ed053bf7545d7c3935c2fb53e | Python | 2,915 | 72 | import torch.nn as nn
import torch
import torch.nn.functional as F
from torch.distributions import Bernoulli
from torch.autograd import Variable
from scipy.special import gamma
import numpy as np
import math
import pdb
from .ResNetFeat import create_feature_extractor
class FeatureNet(nn.Module):
def __init__(sel... |
c0c6b710405152289cf92772a5dc115514c15ee4b65c0b1249ff78db00b093fa | Python | 2,915 | 94 | import pytest
import torch
from torch.nn.modules import GroupNorm
from torch.nn.modules.batchnorm import _BatchNorm
from mmcls.models.utils import SELayer
def is_norm(modules):
"""Check if is one of the norms."""
if isinstance(modules, (GroupNorm, _BatchNorm)):
return True
return False
def test... |
ed2e73c413978cdb6bfb9ffd16f6822266e6ec94361f75c452eb26e571847d50 | Python | 2,915 | 60 | import scanpy as sc
import numpy as np
import pandas as pd
import sys
def format_DEGs(adata):
keys = ["names","scores","logfoldchanges","pvals","pvals_adj","pts"]
for i,key in enumerate(keys):
a = pd.DataFrame(adata.uns["rank_genes_groups"][key]) # transfer to data frame
b = pd.DataFrame(a.v... |
d5209f3a4f90c4764af81025316d36e547332de4d1b4b654443f62735613849c | Python | 2,917 | 99 | # 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... |
2f57b97dfeeb28a4ed3dce347b7caa9fb4d194c6051f879879dcfe503e110827 | Python | 2,920 | 85 | import scanpy as sc
import numpy as np
import pytest
from scipy.sparse import csr_matrix
from palantir.utils import run_local_variability
# Mock data for dense matrix
def mock_anndata_dense(n_cells, n_genes, layer_keys, obsp_keys):
rng = np.random.default_rng()
ad = sc.AnnData(rng.random((n_cells, n_genes)))... |
b451e48ac7e2e9e20ae3ca16699939a26231c2180dbe70cc88a8af05366b94d4 | Python | 2,920 | 87 | import numpy as np
import pyqtgraph as pg
class ColorBar(pg.GraphicsObject):
def __init__(self, cmap, width, height, ticks=None, tick_labels=None, label=None):
pg.GraphicsObject.__init__(self)
# handle args
label = label or ''
w, h = width, height
stops, colors = cmap.get... |
0ca2c3e5d4add31d1b4b15e11e4a80d1c7c245dd75d2ac6055377d1bd4ef1c07 | Python | 2,921 | 81 | from pathlib import PosixPath
from typing import Optional
import ants
import numpy as np
from ants.core import ANTsImage
from rich import print
def get_coords(x: np.ndarray,
margin: list = [8, 8, 8],
offset: list = [0, 0, 0]) -> list:
"""Get coordinates of a given ROI, and apply a m... |
a90d66609178c2ef58085e46dee973b1bd48976ac2038de213ac4659806e52c4 | Python | 2,921 | 80 | #Copyright (C) 2021. Huawei Technologies Co., Ltd. All rights reserved.
#This program is free software;
#you can redistribute it and/or modify
#it under the terms of the MIT License.
#This program is distributed in the hope that it will be useful,
#but WITHOUT ANY WARRANTY; without even the implied warranty of
#MERCHA... |
fd27161ce2efbe4141466861ee17170f07ed4634091a6c229278b73b6d398a3a | Python | 2,921 | 102 | # 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... |
1756ec1e081c274da1c64dd33645136c38c8a10c387ba817f99dd8dc4825a9d8 | Python | 2,926 | 91 | # 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... |
d4df01b59229ac366c2c9acac0822f6665cdcd71a475d42497edac4e175b5bcc | Python | 2,928 | 74 | import unittest
import numpy as np
from q2_matchmaker._stan import _case_control_sim, _case_control_full
from q2_matchmaker._stan import _case_control_data, _case_control_single
from skbio.stats.composition import alr_inv, clr
# class TestCaseControl(unittest.TestCase):
#
# def setUp(self):
# np.random.se... |
1a2a086b847c340fca2e941d3119f346238eb0045f97ec463606c96088d89bfe | Python | 2,931 | 89 |
"""
Base default handler to load torchscript or eager mode [state_dict] models
Also, provides handle method per torch serve custom model specification
"""
import abc
import logging
import os
import json
import torch
logger = logging.getLogger(__name__)
class BaseHandler(abc.ABC):
def __init__(self):
s... |
54450fb5ff00fdd03012a6447e495ca3186193ff850d7df74c7a34b8558ca065 | Python | 2,931 | 97 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import ml_dtypes
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
class Celu(Base):
@staticmethod
def export() -> Non... |
6e571fbe2d0d01bddf8b29e7555c24b237a9e18b3b846a47293bbf5b8a973de6 | Python | 2,931 | 97 | """
Params.py
A classs to create parameter structures
First version: Paul Manis on 2014-01-31.
Distributed under MIT/X11 license. See license.txt for more infofmation.
This code is deprecated for future use - use the built-in Python
@dataclass instead.
It is included here because past simulations may have had Params... |
8863e41273a8597ba8fdacc1cf05f16d1b161ec1b85b6f02236d23a83dd61989 | Python | 2,931 | 64 | """
Explore the range of pre-built functional subnetworks
William Nourse
December 3rd 2021
"""
from sns_toolbox.networks import Network #, AdditionNetwork (This would import the code that we remake here
from sns_toolbox.neurons import NonSpikingNeuron
from sns_toolbox.connections import NonSpikingTransmissionSynapse
f... |
e50168977a8b7febefc8bb832c9a892d1a61fc00f42d5eb192f0ddc7fff428a5 | Python | 2,932 | 95 | # Copyright 2019-2021 The AmpliGraph Authors. All Rights Reserved.
#
# This file is Licensed under the Apache License, Version 2.0.
# A copy of the Licence is available in LICENCE, or at:
#
# http://www.apache.org/licenses/LICENSE-2.0
#
###############################################################################... |
046b64e14bff8c2b5afe4fb7cbf3eb71c267df91f9a66d5a33eae4f5c2c1e8c6 | Python | 2,935 | 62 | # 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... |
48e21546241b1d0d954eaac8804e80c796beb15f8864392843aaea6d39509565 | Python | 2,935 | 74 | # Copyright 2019-2026 The AmpliGraph Authors. All Rights Reserved.
#
# This file is Licensed under the Apache License, Version 2.0.
# A copy of the Licence is available in LICENCE, or at:
#
# http://www.apache.org/licenses/LICENSE-2.0
#
from ampligraph.datasets.data_indexer import DataIndexer
import numpy as np
imp... |
1125fd61046d71366f5630d24b7a9b41aeb6576cc31170dff285d71acd90c857 | Python | 2,936 | 68 | import matplotlib.pyplot as plt
import numpy as np
import pickle
data = pickle.load(open('dataBackendTimesNonspikingDense.p', 'rb'))
numNeurons = data['shape']
npRawTimes = data['numpy']
npAvgTimes = np.mean(npRawTimes,axis=1)*1000
npVar = np.std(npRawTimes,axis=1)*1000
torchCPURawTimes = data['torchCPU']
torchCPUAv... |
a322b8b7a253bec774182da00a60a24a3c339d5aba3d2b84dffe42511a4c8065 | Python | 2,939 | 84 |
"""
Test the embedded auditory nerve model with a set of tone pips.
(Zilany et al. 2014; requires MATLAB)
This demonstrates the lowest-level access to the auditory nerve model that is
available in the cnmodel API. For higher-level tools, see test_sound_stim.py
(which uses an_model.get_spiketrain) and test_sgc_input.p... |
c8228e70c837321e0401d2a3336936df5a14cafae8641505db85ac6a5531e69e | Python | 2,939 | 89 | # 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... |
7d8502b458ea2c00c2cb021e924f67e0f136bedf70b60d9456993f5df856efbc | Python | 2,940 | 85 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This prog... |
befacb2cedfb5487a86719dc5cfcb855b6f3dc59bdfa81d1c8b0d56d21e182d1 | Python | 2,942 | 75 | import numpy as np
from scipy.io import loadmat
from os.path import join as pjoin, isdir, realpath, dirname, basename
"""
Details on the origins of these parcellation could be found in
loadPrecomputedAtlasCorticalParcellation.m in src repo from Raamana's PhD.
The internal structure of those Matlab structs contains... |
4a928eb939a5923d4e582a41e38407b30540cbc1b7583cb9a9e975dd87d8ef0c | Python | 2,943 | 80 |
#=======================================================================================================================
# 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... |
2d18f05651ba3130fd5f9c68c612db552e0289214087cf8fbf2518c0216ac995 | Python | 2,944 | 63 | import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import anndata as ad
import scanpy as sc
from matplotlib.colors import ListedColormap
sns.set_context("poster")
sns.set_palette("colorblind")
sc.settings.figdir = "./figures/"
def main():
seed = 1029 # set randomness for dim. reduction and c... |
3a731dd7fb8f1e199e1ae166b2f337db58aa9143c86ed378c6c7b879fde242dc | Python | 2,945 | 86 | # 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... |
62dd610556a93fd49d54cbbddcdb9ade172ffe1f299a681e3fa988f5588801e4 | Python | 2,948 | 94 | import sys
from matplotlib import pyplot as plt
import seaborn as sns
sns.set_style("white")
import pandas as pd
colors = sns.color_palette("RdYlBu", 13)
colors = sns.cubehelix_palette(7, start=2, rot=0, dark=0.05, light=.95, reverse=False)
colors = sns.color_palette("Set1", 13)
df_exome = pd.read_csv(sys.argv[1],... |
c862425884d5a38e2773967e0e9bb482c5b0848c11580aa3228d944caf16e0e4 | Python | 2,948 | 85 | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from ..builder import HEADS
from .multi_label_head import MultiLabelClsHead
@HEADS.register_module()
class MultiLabelLinearClsHead(MultiLabelClsHead):
"""Linear classification head for multilabel task.
Args:
num_class... |
83a3f8f16f6dd14927dcb83f58e06bddd079d88decb9dc8808048873875efa6d | Python | 2,950 | 96 | # -*- coding: utf-8 -*-
#
# Copyright © 2023 Charles E. Vejnar
#
# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at https://www.mozilla.org/MPL/2.0/.
#
import logging
import os
import subprocess
fro... |
004f028f503819c5a5541c67d1013e6c407fee88ba3975a4c53060d756cd8324 | Python | 2,951 | 71 | from __future__ import division
import os
import sys
import pandas as pd
import numpy as np
from SPHARM.classes.surface import Surface
from SPHARM.classes.image_stack import ImageStack
from helper_lib import filelib
from mayavi import mlab
#################################
args = sys.argv[1:]
if len(args) > 0:
p... |
4b5a90b9fd853aadb970b0f61af55470481467fbd5c0aaac73a32b615d0664f8 | Python | 2,951 | 57 | """Shared fixed-mask proportion metrics, including honest constant-map handling."""
import numpy as np
from scipy import sparse
from scipy.spatial import cKDTree
from .coverage_retrain import evaluate_sparse
from .metrics import _safe_spearman
def moran(values, neighbors):
values = np.asarray(values, dtype=np.flo... |
deb787b85538905331da625c5f6c49d7cdf76be04241237955db19cfe8bd1f4d | Python | 2,951 | 74 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""Backend-neutral training cursor and selection-RNG checkpoint contract."""
import unittest
from deepmd.dpmodel.train.data_progress import (
collect_training_data_progress,
preserve_training_data_progress,
restore_training_data_progress,
)
from deepmd.utils im... |
6eae9bad131cb17df0bf7dc6fa86134e56a634f6d60e4e209b734fa7b0c90f5e | Python | 2,954 | 96 | # 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... |
dc712500d4a3057c28cc258d6558c228a07de2b17eefcf96a3a439a6522e3bff | Python | 2,966 | 85 | # -*- 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 ... |
45ef3d954490bef3c6adbc13c485abda62475942c7d756445aa1553b60bcf9ca | Python | 2,967 | 85 | # 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... |
da6a65527eb40568cd0c4db6d4e0d12b54baac635a9c30dd3ddf18226e23107b | Python | 2,967 | 107 | import numpy as np
from ANNarchy import *
# import matplotlib.pyplot as plt
import time
import pickle
# Personal stuff to send an email once data collection is finished
import sys
sys.path.extend(['/home/will'])
from email_utils import send_email
"""
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
e42fb3344ef188462345b9683da03faaa5892d7786fec704d4f516d359b5d89e | Python | 2,967 | 116 | import sys, os
import numpy as np
import json
def main(*args):
source_file = args[0]
target_folder = args[1]
if len(args) > 2:
print("Too many args")
print(
"USAGE: python3 mot_to_absolute path_to_source_file path_to_target_dir --include_confidence"
)
sys.exit(0... |
814b417246044ff521357dfceb16a0e949f9ca514cf62480f5a9ed1d14b62484 | Python | 2,968 | 93 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
from onnx.reference.op_run import OpRun
def softmaxcrossentropy(
x, target, weight=None, reduction="mean", ignore_index=None, get_log_prob=None
):
input_shape = x.shape
... |
9e600e89beeab8ce1fdb0027bda42f1a922c5ebc4fca33295fa97c5afecabe85 | Python | 2,969 | 125 | CONTRACTION_MAP = {
"ain't": "is not",
"aren't": "are not",
"can't": "cannot",
"can't've": "cannot have",
"'cause": "because",
"could've": "could have",
"couldn't": "could not",
"couldn't've": "could not have",
"didn't": "did not",
"doesn't": "does not",
"don't": "do not",
"hadn't": "had not",
"hadn't've": "had not hav... |
0145aa0e678714b5240cd018c84a8f006c2a6a3e74741c6663d539668a6e7595 | Python | 2,970 | 82 | #! /usr/bin/env python
#
# Copyright (C) 2012-2018 Michael Waskom
DESCRIPTION = "seaborn: statistical data visualization"
LONG_DESCRIPTION = """\
Seaborn is a library for making statistical graphics in Python. It is built on top of `matplotlib <https://matplotlib.org/>`_ and closely integrated with `pandas <https://pa... |
29f7c131ba5a08df6cdbb80cd4336e8f6563d9e0baca57010dfe59d1c152e536 | Python | 2,970 | 88 | """
estimate_weights.py
Provides crude weight estimation for cue configurations from Shaverdian
et al. (2022). We assume cue inputs can be described by vectors
pointing towards the true position of the cue. This script then attempts
to find a combination of magnitudes in order to minimise the difference
between the su... |
f279eace5e5bc22b662f78ae6f798805c570591a06515b04b20400af3ea58ce5 | Python | 2,970 | 87 | # Copyright 2019-2021 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... |
a7ceece5d71f6a3a1bdaea2cedb25886fd5fcce4eb2397d29c110773e12608ae | Python | 2,971 | 111 | # -*- coding: utf-8 -*-
"""
sync.py
@author: derricw
Provides some classes useful for synchronization and data alignment.
"""
from psychopy import visual
from camstim.experiment import EObject
class SyncPulse(EObject):
"""
Digital IO pulse that can occur at various times in the experiment.
args
---... |
fb7df4188b8c5c39226a1fb73f955ffdbb9b3f8e4744b560413cbc0e21975555 | Python | 2,971 | 69 | import logging
import gc
# PyTorch modules
import torch
from torch.utils.data import DataLoader
# Cormorant modules and functions
from cormorant.engine import Engine
from cormorant.engine import init_logger, init_cuda
from cormorant.engine import init_optimizer, init_scheduler
from cormorant.models.autotest import corm... |
22ed8ebe7751785127c010235409a13fac7ce295c7f92914fba81c3c38d0d45a | Python | 2,973 | 91 | import psutil
from pyontutils.utils import makeSimpleLogger
log = makeSimpleLogger('nifstd-tools')
logd = log.getChild('data')
def memoryCheck(vms_max_kb):
""" Lookup vms_max using getCurrentVMSKb """
safety_factor = 1.2
vms_max = vms_max_kb
vms_gigs = vms_max / 1024 ** 2
buffer = safety_factor *... |
9a96965f4b017cf2a1a95f06abee9ad4ec85d241573dfecec2c62456941e8bea | Python | 2,973 | 93 | from __future__ import print_function
import numpy as np
from .augment import Augment
from .warping import warping
from .geometry.box import Box
class Warp(Augment):
"""Warping by combining 5 types of linear transformations:
1. Continuous rotation
2. Shear
3. Twist
4. Scale
... |
69b470a610489baeaba78242f9cd88500b0758d58f0f2b89fd62b5b317af2ce7 | Python | 2,974 | 112 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import ml_dtypes
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
class ReverseSequence(Base):
@staticmethod
def expo... |
cec633cebed47ddaefc13b9e23eba88ab624c1bb4b88fce2dd727754db15b0c4 | Python | 2,974 | 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... |
c27d95f06f11cd484e77c69f6498549b6d0d25c7445295e6b6ea17a8401fb329 | Python | 2,975 | 89 | # 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... |
19f08a908bcc3c4c80927ebba5c3d954fa56fffb1b4e340e87dea0d8d6bbf0de | Python | 2,976 | 70 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Created on Sun Mar 6 13:50:08 2016
@author: tpisano
"""
import os, sys, shutil
from xvfbwrapper import Xvfb; vdisplay = Xvfb(); vdisplay.start()
from tools.imageprocessing import preprocessing
from tools.registration.register import elastix_wrapper
from tools.utils.d... |
dee1a2e0f5f9016a77baf8e39d5a2669a8a5a77624b2fb8d030ea386e2cc7288 | Python | 2,976 | 100 | # 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... |
60051adfd31d9a4ccb8d11687e6e8b1f43aa18640c7d2c9ae227976701d48b6c | Python | 2,977 | 139 | import json
config = {}
config['Source'] = {}
config['Algorithm'] = {}
config['ResultRepresenter'] = []
config['classes'] = []
config['classes'].append(
{
"id":0,
"name":"BMP",
"color": [255,0,0],
})
config['classes'].append(
{
"id":1,
"name":"NODAL",
"color": [0,0,255],
})
config['classes'].... |
216c32dba32207e3106a3db7c1309f63a775411487c850b63b06131f5eecc147 | Python | 2,978 | 94 | """
Parse a hoc file generated by swc_to_hoc (in the neurovis package), producing
the reverse map from hoc sections back to the swc elements. This will be done
with a "hocx" file, which has the extended information about which swc segment
is associated with each hoc pt3dadd call.
The result is a text file that looks... |
923d79700115632d4a159a62dc77299a36fc87eb42fd15d847965073f8ea92e1 | Python | 2,978 | 79 | # 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... |
f9c376a9af7416f58326dd7924e3147bf435a3586c511bc3a16322dee2672276 | Python | 2,979 | 96 | # 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 MaxUnpool(Base):
@staticmethod
def export_1d() -> None:
... |
a932a9e8b6512cbcb47026cdf0c6599582c9d0468064f5535e4c9d1d341255de | Python | 2,980 | 96 | # 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... |
16cf098969137d8ce35894d8532e2cc7b5b7ef5689f57e3db49520d5f42f9c81 | Python | 2,983 | 93 | """data definitions that are widely used
"""
from typing import List, Union
# all the best "grade A" cells
gradeACells = [2, 5, 6, 9, 10, 11, 13, 17, 18, 30]
MixedMode = [9, 11, 17, 18] # according to Figure 2, supplemental figure 2
Coincidence = [2, 5, 6, 10, 13, 30] # according to figure 2, supplemental figure 3
... |
e40f236eff987af434e3991fe8aa095919956cb9ef015a412f276154eda4f423 | Python | 2,984 | 79 | """
Reused utilties that depend on packages outside the python standard library.
"""
import hashlib
from urllib.parse import quote as url_quote
import rdflib
rdflib.plugin.register('librdfxml', rdflib.parser.Parser,
'pyontutils.librdf', 'libRdfxmlParser')
rdflib.plugin.register('libttl', rd... |
10e297a18092fe7294c577cb249715dcba55aa43bb7be2671acde3fd312a24e9 | Python | 2,985 | 101 | """
"""
import logging
import numpy as np
import pandas as pd
import os
def logcpm(counts):
"""
Args:
- gene-cell matrix (pandas DataFrame)
"""
cov = counts.sum(axis=0)
logcpm = np.log10(counts.divide(cov, axis=1)*1000000 + 1)
return logcpm
def logtpm(counts, gene_lengths):
"""
... |
cb07e4378609e484ae922b7c1b55c7df476ce539bf028aa9ec77ad38b5b50063 | Python | 2,985 | 97 | # SPDX-License-Identifier: LGPL-3.0-or-later
from typing import (
Any,
)
import torch
from deepmd.dpmodel.atomic_model import (
DPUniMolAtomicModel,
)
from deepmd.dpmodel.model.dp_model import (
DPModelCommon,
)
from deepmd.dpmodel.output_def import (
OutputVariableDef,
)
from .make_model import (
... |
b1c5aa3a451e20236f99cf2cebb683ac5caa50a290d8d0864d5d1546ac172587 | Python | 2,988 | 107 | import numpy as np
from ANNarchy import *
# import matplotlib.pyplot as plt
import time
import pickle
# Personal stuff to send an email once data collection is finished
import sys
sys.path.extend(['/home/will'])
from email_utils import send_email
"""
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
695adaef83f45cfc7be5df471a2b30ff487ebdd1017ba966dd3a52ffd027febe | Python | 2,989 | 74 | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmcv.runner import BaseModule
from .make_divisible import make_divisible
class SELayer(BaseModule):
"""Squeeze-and-Excitation Module.
Args:
channels (int): The input (and output) ch... |
3aef2d765d3af73811dac89624d324aa42659c9cbac03adfc9fcf2b1e2fe206d | Python | 2,990 | 102 | # 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... |
d3fbdd6f9b0f44dc2a30db39fcd0467cf48c85ded4f4810ea149242da8200334 | Python | 2,990 | 71 | 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... |
ef634a1c60b466796e2a3718b0135ef032873a2865ac40364f20a5cd9ae6b595 | Python | 2,991 | 105 | import json
from sqlalchemy import create_engine, inspect, Table, Column
import pandas as pd
from ilxutils.args_reader import read_args
from ilxutils.scicrunch_client import scicrunch
import sys
import time
from ilxutils.interlex_sql import interlex_sql
import re
from collections import defaultdict
import requests as r... |
da71e08a94e6aeadb861452bcf7d530a71cf9744cef4e19494e07d8cb5c8433e | Python | 2,993 | 90 | #!/usr/bin/env python
from __future__ import print_function
import sys,os
import argparse
import logging
import tempfile
import subprocess
import time
desc = 'Removing javareconf from conda activation'
epi = """DESCRIPTION:
The script will search within the conda env directory for
the file: activate-r-base.sh
It wil... |
e7d7f29cf89e2be248d3a7cee66ac3e83587919e49107003182f5ae95925f08e | Python | 2,993 | 75 | from flair.data import Sentence
def test_sentence_context():
# make a sentence and some right context
sentence = Sentence("George Washington ging nach Washington.")
sentence._next_sentence = Sentence("Das ist eine schöne Stadt.")
assert sentence.right_context(1) == [sentence._next_sentence[0]]
as... |
3e4caf313274a3b75fd4159f81d0818a22f855439c16585c06f80f333e672bde | Python | 2,994 | 101 | # -*- encoding: utf-8 -*-
from neuron import h
import pyqtgraph as pg
import cnmodel.util as util
from .protocol import Protocol
from .. import cells
class SimpleSynapseTest(Protocol):
def reset(self):
super(SimpleSynapseTest, self).reset()
def run(self, pre_sec, post_sec, temp=34.0, dt=0.025,
... |
522d498c8102bfe5d8410a2a5385c3523939964db1277527d0ab4067321f54aa | Python | 2,995 | 101 | # 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... |
47d1fa0c7defcda74163eb117334aae5724848ee55f2db4dcdb7573315d480bf | Python | 2,996 | 109 | #!/usr/bin/env python
from Bio import SeqIO
from Bio.Seq import Seq
from Bio.SeqRecord import SeqRecord
import click
import importlib
import math
import random
import sys
lib = importlib.import_module("match-seqs-by-gc")
CONTEXT_SETTINGS = {
"help_option_names": ["-h", "--help"],
}
@click.command(no_args_is_hel... |
6bac0ca17e7185468a824646b2a658d21124264beb203b192e1a40abcb679c9d | Python | 2,996 | 86 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import Sequential, Linear, ReLU
from torch_geometric.nn import GINConv, global_add_pool
from torch_geometric.nn import global_mean_pool as gap, global_max_pool as gmp
# GINConv model
class GINConvNet(torch.nn.Module):
def __init__(sel... |
ff3c3d17b8b7806816438e5bba251d2eecf53bb706eaafe3d3c47aee9db51dc5 | Python | 2,998 | 102 | # 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... |
7ce13c5751f324e590e1fc7bc9bd71ec78fe7ed771fba46e394e2b72d72ef88e | Python | 3,001 | 108 | #!/usr/bin/env python3
from neurondm.sheets import Sheet
from neurondm import OntId, OntTerm, Config, NeuronEBM, Neuron
from pyontutils.utils import byCol, relative_path
from pyontutils.namespaces import ilxtr
from pyontutils.closed_namespaces import rdfs
class APIN(Sheet):
name = 'apinatomy-to-npo'
sheet_na... |
19d5f7240f8c0338c4af5a7a9b35a33d98c8f5afbe7a2f926a906206ba3a3a19 | Python | 3,002 | 69 | import logging
import gc
# PyTorch modules
import torch
from torch.utils.data import DataLoader
# Cormorant modules and functions
from cormorant.engine import Engine
from cormorant.engine import init_logger, init_cuda
from cormorant.engine import init_optimizer, init_scheduler
from cormorant.models.autotest import corm... |
d244dc4b7d72a23e4d9eff6656eb801d863bfdc702085eb8b667ce5c9b8edbb6 | Python | 3,003 | 84 | # 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... |
9d9bc1e500a88da1d2c17764df3380a2dfefe0d07deba9e5a6d69b12f0194ced | Python | 3,004 | 89 | """Dummy distances/kernels."""
__author__ = ["fkiraly"]
import numpy as np
from sktime.dists_kernels.base import BasePairwiseTransformerPanel
SUPPORTED_MTYPES = ["df-list", "nested_univ", "numpy3D"]
class ConstantPwTrafoPanel(BasePairwiseTransformerPanel):
"""Pairwise panel transformer that always returns a c... |
e1bd050fa23bd855b54b29e60caa4b04856fcf682ee284e9135551297e711e84 | Python | 3,006 | 111 | from numpy import random, array, zeros, empty
import os
from sklearn.model_selection import KFold
from sklearn.linear_model import LogisticRegression
from sklearn.svm import SVC
from xgboost import XGBClassifier
import joblib
def readTest(filename):
data = open(filename, "r")
lines = data.readlines()
data_feature... |
1af74e15342bd17e9787df53daa5ffe110769ede901ed5982e8b7deefb33dc3e | Python | 3,007 | 108 | from __future__ import annotations
import pandas as pd
from .STDataset import STDataset
def low_variance_filter(dataset: STDataset, var: float = 0) -> STDataset:
"""
Filter genes with low variance. This may also filter genes with 0 expressions.
Parameters
==========
dataset : STDataset
... |
9849b56cd1858d4777c39ad35f051507e8b7c1d34e4cde6e6b3125162ac33ead | Python | 3,007 | 101 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
# Ported from skchange (BSD-3-Clause), original authors: Tveten
"""Change score adapter that wraps any cost into a change score."""
__author__ = ["Tveten"]
from sktime.detection._utils import check_interval_scorer
from sktime.detection.base._bas... |
deadeeeaec92d550238b2d6d8424f37ad719c432bc056548d0f9c0090dc631fb | Python | 3,008 | 92 | # 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... |
47eba5ad18f4e9eac72e7065ba8a8cdd5f157bfe489fbeafa4f386dedc7377ab | Python | 3,009 | 97 | # -*- coding:utf-8 -*-
import os
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
from keras.preprocessing import text, sequence
from keras.models import Model
from keras.layers import Input, Embedding
from keras.layers.core import Dropout
from keras.layers.convolutional import Conv1D, AveragePooling1D
from keras.layers impo... |
795eec78bd6dd13001861270e37d7fac8bfec37428ef3e4c74ec112006188943 | Python | 3,009 | 99 | import pandas as pd
import os
BASE_PATH = 'data/main_dataframes/'
CORRECTION_FOLDER = 'data/main_dataframes/CrisprOR fixes/'
# EXPERIMENTS_TO_FIX = ['doench2016_hg19'
# 'hart2016-Rpe1Avg',
# 'hart2016-Hct1162lib1Avg',
# 'hart2016-HelaLib2Avg',
# ... |
bc602e69798c30cf50f4718fdb2ad48b15fa5a1d47ea7079b0a199c6936ac060 | Python | 3,015 | 91 | import numpy as np
import pandas as pd
from typing import Iterable, Union
from lee_et_al_2023.src import base
def load_gnn_rf_predictions(mol_codes):
"""Load GNN and RF ratings for a set of RedJade codes.
Args:
mol_codes: Molecules for which to retrieve predictions
"""
files = {
... |
b2ad221c95aece15aa4ce7a8a0c64e71452899f064c22aa9be0dab9cf9b5b54a | Python | 3,016 | 94 | # 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... |
5518887e3860550316bc7b81d7b04807197e6adc04642f24a9e74f5c2ffa5c3f | Python | 3,017 | 96 | #!/usr/bin/env python
import sys
import os
import math
import re
from os.path import isfile, join, isdir
from kn_common import pipetools,pipedef
from kn_pipeline_class import CPipeError,CPipeStep
class CPipeNNCell(CPipeStep):
def progress_update(self,txt):
if re.match(r'#PROGRESS#\d*#', txt):
progress=in... |
e5e5540e3231468d6d4688de8a2633680d84cdd8fa4dcf65f68b1764f61c2e3a | Python | 3,018 | 101 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
from onnx.reference.op_run import OpRun
def _batchnorm_test_mode(
x: np.ndarray,
s: np.ndarray,
bias: np.ndarray,
mean: np.ndarray,
var: np.ndarray,
epsilon:... |
4406829953a656d9b286c587d4ec51d07d467bfc3f9117f90d3e48452a2d7e2f | Python | 3,019 | 84 | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
from typing import List
import numpy as np
from mmcls.core import average_performance, mAP
from .base_dataset import BaseDataset
class MultiLabelDataset(BaseDataset):
"""Multi-label Dataset."""
def get_cat_ids(self, idx: int) -> List[int]:
... |
6c94ce2444e71cf989048133b4cbbb67cfb02074b0651410e92c09dba21ddc56 | Python | 3,019 | 68 | import logging
# PyTorch modules
import torch
from torch.utils.data import DataLoader
# Cormorant modules and functions
from cormorant.engine import Engine
from cormorant.engine import init_logger, init_cuda
from cormorant.engine import init_optimizer, init_scheduler
from cormorant.models.autotest import cormorant_test... |
24e139540e36945adbbdf99e68872a411d02e49a1a59ae2293299323470e0a18 | Python | 3,021 | 102 | # 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... |
cb8de14e0c4a57145f2104786cb76d8628efc4d2dc95d186ea194b07b938fb47 | Python | 3,022 | 86 | # 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... |
ac1792fbfab7571d3463b45688a7899f3b180b00557f7b0d3feef4683ff7be18 | Python | 3,023 | 88 | # 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... |
da59a027efe125debafc1b8b598de08f98e0f6274850be8c8d0ea29d34fbe995 | Python | 3,023 | 88 | # coding = utf-8
"""Sparsemax activation function.
Pytorch implementation of Sparsemax function from:
-- "From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classification"
-- André F. T. Martins, Ramón Fernandez Astudillo (http://arxiv.org/abs/1602.02068)
"""
import torch
import torch.nn as nn
... |
804d8985e4ff8c0f4737c64427cee2365dff74d90a39e92bda7bb42fbc73dfb2 | Python | 3,024 | 83 | # 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... |
c00487b26240e888e3bee94b7e1540d1cb2875f1bde93c9c4b9c4a2fb2f9021c | Python | 3,024 | 83 | """Conversion utilities for mtypes."""
__author__ = ["fkiraly"]
def _concat(fun1, fun2):
"""Concatenation of two converter functions, using the same store.
Parameters
----------
fun1, fun2 : functions in converter signature, see datatypes._convert
Returns
-------
function in converter s... |
315d3e313a1c4875bd54494502c69f298985ba82e9895f9457afaf17578dd5e9 | Python | 3,027 | 85 | import io
import torch
from PIL import Image
from torchvision import transforms
from torch.autograd import Variable
from .vision_handler import VisionHandler
class ObjectDetector(VisionHandler):
"""
ObjectDetector handler class. This handler takes an image
and returns list of detected classes and bounding... |
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