sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
9eaf45f0c5ab67f8d698ee6655b5754fc6a0d0bc0ba2619c5146805cab6cb54a | Python | 1,139 | 35 | import glob
import json
from google.protobuf.json_format import ParseDict, ParseError
from json_repair import repair_json
from ord_schema.message_helpers import find_submessages
from ord_schema.proto.reaction_pb2 import Reaction, Compound, ProductCompound
from ord.utils import json_load, json_dump
data = []
reaction... |
edad4c938c99583e88fd9cb46faf1841a8007349c671fe773bbeaea3ebcd71b5 | Python | 1,139 | 50 | import argparse
from meep.materials import Al
import meep as mp
def main(args):
resolution = 40
cell_size = mp.Vector3(z=10)
boundary_layers = [
mp.PML(1, direction=mp.Z) if args.pml else mp.Absorber(1, direction=mp.Z)
]
sources = [
mp.Source(
src=mp.GaussianSource... |
a746dc6aad7bedce73e05cb381ad565b086aa2081a9c9a4fc9151f3398617153 | Python | 1,140 | 41 | import bpy
import numpy as np
class AnnotationInterface:
"""
Base class for Annotation Interface
AnnotationManager creates a dynamic AnnotationInterface for every instance
of an annotation. All the annotation specific inputs and the common
annotation params are exposed though this interface for t... |
deeee4b71d8354770f48d38b903b75536c214fe83202688f9d36e23d330a9baa | Python | 1,140 | 24 | #
# MIT License
#
# Copyright (c) 2022 GT4SD team
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge,... |
43399ad0394663705398be6f74efbefb2da7a7ffdb1699737dbee78a1c8af318 | Python | 1,141 | 47 | import click
import h5py
import numpy as np
import os
##########
# inputs #
##########
@click.command()
@click.option('--scores',
'score_files',
required=True,
multiple=True,
type=click.Path(exists=True, readable=True),
help='h5 ISM score file')
@cl... |
0df9bf97db9efb3da20fdd6d9f8d5c391c08e21b6ad9d3782200194c135c5c22 | Python | 1,142 | 35 | from analyse import *
import os
import subprocess
from jinja2 import Template
import time
proteins = initProteins()
proteins.to_pickle('proteins.pkl')
submission = Template("""#!/bin/bash
#SBATCH --job-name={{name}}
#SBATCH --nodes=1
#SBATCH -t 10:00:00
#SBATCH --mem=30GB
#SBATCH -o {{name}}/cmap_{{replica}}_out
#SBA... |
d40d66fa7693adf7be9ca0d634c2ab1c405370d1f37e4fe710b70227ecd95eb3 | Python | 1,142 | 46 | import meep as mp
def main():
c = mp.Cylinder(radius=3, material=mp.Medium(index=3.5))
e = mp.Ellipsoid(size=mp.Vector3(1, 2, mp.inf))
src_cmpt = mp.Hz
sources = mp.Source(
src=mp.GaussianSource(1, fwidth=0.1), component=src_cmpt, center=mp.Vector3()
)
if src_cmpt == mp.Ez:
... |
382bc687b18a8a582a9d6585b601bd336d46a67785ba6ce50968ce1e5195a590 | Python | 1,143 | 54 | # -*- coding: utf-8 -*-
import json
from pathlib import Path
from collections import OrderedDict
def load_json(filename):
""" Load a JSON file
Args:
filename (str): Path of a JSON file
Return:
Dictionary of the JSON file
"""
with open(filename, "r") as f:
data = json.loa... |
e47b5e8e69babaa75aa21b781d1c940c317bb17ba6d71bfc34ec0fcfcf4b15bd | Python | 1,143 | 68 | from __future__ import annotations
from typing import TYPE_CHECKING
import numpy as np
if TYPE_CHECKING:
from numpy.typing import NDArray
def add(a: float, b: float) -> float:
"""
A function that adds two numbers.
Parameters
----------
a
First number to add.
b
Second nu... |
dc53382cfa371eb9a8bdb068d42978a6d38b35130a8ca7421cd171b0565d8c82 | Python | 1,144 | 35 | import os
import torch
class Logger(object):
"""
Save checkpoints to file.
"""
def __init__(self, cfg, args, slam
):
self.verbose = slam.verbose
self.ckptsdir = slam.ckptsdir
self.shared_c = slam.shared_c
self.gt_c2w_list = slam.gt_c2w_list
s... |
1fd2faeda8d873539700209ec1596f14c79ec55409e8e12dec97d700a7b09bfc | Python | 1,145 | 38 | from typing import Dict, Union
import numpy as np
from ..base_transform import EEGTransform
class Flatten(EEGTransform):
r'''
Flatten the input EEG representation.
.. code-block:: python
from torcheeg import transforms
t = transforms.Flatten()
t(eeg=np.random.randn(62,... |
25bf9247a5b6643494028c6426e5e9bf4fabc779cd831476731ae5a63f795047 | Python | 1,145 | 34 | """
collect all notebooks in examples, and check that they run without error
"""
from __future__ import annotations
from pathlib import Path
import nbformat
import pytest
from nbclient.exceptions import CellExecutionError
from nbconvert.preprocessors import ExecutePreprocessor
this_file_loc = Path(__file__).parent
... |
7c3c36e0a4f3ca4ede735f22ddc46c22aea0eb732cd78326e0c2030406057264 | Python | 1,145 | 32 | from PyQt5 import QtGui, QtWidgets
class ColorbarSlice(QtWidgets.QWidget):
def __init__(self):
super(ColorbarSlice, self).__init__()
self.initUI()
def initUI(self):
self.pen = QtGui.QPen(QtGui.QColor(
200, 200,
200)) # Set the initial pen (which dra... |
6c61a6e9a611b84e120637e3c8bb4b7e7f2c92619be5cbe3e0d300a1ab53b02b | Python | 1,147 | 60 | #!/bin/env python3
'''
Test constructor for filament
'''
import numpy as np
import ithildin as ith
# empty filament, faces optional
print(1)
try:
f = ith.Filament()
print(f)
print(f.faces)
except Exception as e:
print(e.__class__.__name__, e)
# this one should be illegal
print(2)
try:
f = ith.Fila... |
79697b06340f5100ac87523f07387b809057779b9a4c811fe53b51094d4868a4 | Python | 1,147 | 33 | '''
Provides default parameters used to instantiate the network.
'''
params = {
# Simulation time (in ms).
't_sim': 1000.0,
# Resolution of the simulation (in ms).
'sim_resolution': 0.1,
# Masterseed for NEST and NumPy.
'master_seed': 55,
# Recording interval of the membrane potential (in ... |
7a64062eb8ada39e664a72eb0af7e7b9121393dc23a1f86f22a3ee2c077dde50 | Python | 1,147 | 29 | """
DeepLabCut2.0 Toolbox (deeplabcut.org)
copyright A. & M. Mathis Labs
https://github.com/AlexEMG/DeepLabCut
Please see AUTHORS for contributors.
https://github.com/AlexEMG/DeepLabCut/blob/master/AUTHORS
Licensed under GNU Lesser General Public License v3.0
"""
from deeplabcut.pose_estimation_tensorflow.dataset imp... |
ef9e9ee9876d1d3e78f81913889116999c6e9d777a9cfbb128c3a6b36bf2ef31 | Python | 1,147 | 39 | """Prepare ADE20K dataset"""
import click
import zipfile
from pathlib import Path
from segm.utils.download import download
def download_ade(path, overwrite=False):
_AUG_DOWNLOAD_URLS = [
(
"http://data.csail.mit.edu/places/ADEchallenge/ADEChallengeData2016.zip",
"219e1696abb36c8ba... |
45ee735196049299056ecad9e62660ade6cc79e01120570a47aecf523fb287ef | Python | 1,148 | 34 | """
Optuna example that optimizes simple quadratic functions.
In this example, we optimize two objective values.
Unlike single-objective optimization, an optimization gives a trade-off between two objectives.
As a result, we get the best trade-offs between two objectives, a.k.a Pareto solutions.
"""
import optuna
... |
befc66f04ccb4b8ecd766b2f616bd1ecf5267a9b2a7f5df1f44b313caa0a02fc | Python | 1,148 | 24 | #
# MIT License
#
# Copyright (c) 2022 GT4SD team
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge,... |
de00e58ab56830f161ffcc4562e0a3028a098e8f42b322b07cbb5bd2dc5ea3af | Python | 1,148 | 28 | from elasticai.creator.file_generation.savable import Path, Savable
from elasticai.creator.file_generation.template import InProjectTemplate
class MacDesign(Savable):
def __init__(self, name: str, vector_width: int, fxp_params):
self._name = name
self._vector_width = vector_width
self._fxp... |
edf0daccddf2d29b6f032dc82eddc07b946f3eab23c7aa916036bd8610432d69 | Python | 1,148 | 32 | method_label_map = {
"gnn_imp": "PEPerMINT",
"isvd": "ISVD",
"iterative": "MICE",
"knn": "KNN",
"missforest": "RF",
"minprob": "MinProb",
"mindet": "MinDet",
"bpca": "BPCA",
"bpca_t": "BPCA Transpose",
"dae": "DAE",
"vae": "VAE",
"mean": "Average",
"median": "Median",... |
035f861ef04f9a13c4ddc3b11f19cef702477a08be86cf2c3d6fe09ea6e074bf | Python | 1,149 | 42 | # Librairies
import os
import sys
code_path = os.path.split(os.path.split(os.getcwd())[0])[0]
sys.path.append(code_path)
from scipy.sparse import load_npz
import networkx as nx
import argparse
from setting import *
# Arguments
argParser = argparse.ArgumentParser()
argParser.add_argument("-n", "--name", type=str, help... |
7b411b366cbeea9ec84779de409ab3cb375c5de4b0f50d4862e3a402877467ec | Python | 1,149 | 38 | import torch
from prosper_nn.models.hcnn import HCNN
import prosper_nn.utils.generate_time_series_data as gtsd
import prosper_nn.utils.create_input_ecnn_hcnn as ci
# Define network and data parameters
past_horizon = 10
forecast_horizon = 5
n_features_Y = 2
n_data = 20
n_state_neurons = 3
batchsize = 5
# Initialise H... |
c12a625f848d593fd5190f8d6799de6489ca0ff67df3794783876d9f56e0d8df | Python | 1,149 | 33 | # Configuration file for the Sphinx documentation builder.
#
# For the full list of built-in configuration values, see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Project information -----------------------------------------------------
# https://www.sphinx-doc.org/en/master... |
2806683ee2ee05ccd491f4e95f902b0c15c57884c375f26549f1fc9295e37f13 | Python | 1,150 | 41 | extensions = dict(
skip_default_set_params_for=['training_frame', 'ignored_columns', 'response_column',
'max_confusion_matrix_size', 'distribution', 'offset_column'],
set_required_params="""
parms$training_frame <- training_frame
args <- .verify_dataxy(training_frame, x, y)
par... |
6690a5f5959b916139f55413db358e49d463965fa9f7196ece65c0e4322cbea6 | Python | 1,150 | 39 | from . import loadDefaultParams as dp
from . import timeIntegration as ti
from ..model import Model
class HopfModel(Model):
"""
Stuart-Landau model with Hopf bifurcation.
"""
name = "hopf"
description = "Stuart-Landau model with Hopf bifurcation"
init_vars = ["xs_init", "ys_init", "x_ou", "y... |
83947e3d71ac2c87bd9b62ea2ecc7bc947ac732e675b5eb63fc1d1c03e43af6f | Python | 1,150 | 42 | import timm
import torch.nn as nn
class TimmUniversalEncoder(nn.Module):
def __init__(self, name, pretrained=True, in_channels=3, depth=5, output_stride=32):
super().__init__()
kwargs = dict(
in_chans=in_channels,
features_only=True,
output_stride=output_stride,... |
269053f69cdb46d6c43d9257f44b76f4c271cac54ac14adb4766bcc2584ca69b | Python | 1,151 | 40 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
import suites
configs = [
IssueConfig(
"cegar-landmarks-10k",
["--search", "astar(cegar(subtasks=[landmarks()],max_states=10000))"]),
Issu... |
3d475c82fe7697d87ead9fc8d9ecd7beee105e245068825bf460a73e044f26b9 | Python | 1,151 | 27 | import torch
import torch.nn as nn
import math
class pdfam_gau_module(torch.nn.Module):
def __init__(self, channels=None):
super(pdfam_gau_module, self).__init__()
self.learn_eps = nn.Parameter(torch.zeros([1, channels, 1, 1]))
self.learn_coef = nn.Parameter(torch.ones([1, channels,... |
6a2a0d8516e32e66d65927af43cdf3b3781cbd4fef1d933878761c8528293a76 | Python | 1,151 | 40 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
import suites
configs = [
IssueConfig(
"cegar-landmarks-10k",
["--search", "astar(cegar(subtasks=[landmarks()],max_states=10000))"]),
Issu... |
8d56eef385841b9a42f4595b30144fabe470183f1d41f9465b0870d7e7035940 | Python | 1,152 | 50 | import argparse
from pathlib import Path
def add_run_cru_arguments(parser: argparse.ArgumentParser) -> None:
parser.add_argument(
"--mesh-file",
type=Path,
default=Path.cwd() / "cru_mesh" / "cru_mesh.h5"
)
parser.add_argument(
"-o",
"--outdir",
type=Path,
... |
c104b27100846c9e8492fdcd22e6cf7d0c22803d4428b852b15ccb7f1f761bdf | Python | 1,152 | 38 | from cloudvolume import CloudVolume
from cloudvolume.lib import Vec, Bbox
import numpy as np
from copy import deepcopy
padding = Vec(128, 128, 0)
start = Vec(0, 0, 0) - padding
stop = Vec(2048, 2048, 100) + padding
bbox = Bbox(start, stop)
offset = Vec(20002, 12009, 65)
dirs = {#'img': 'image',
'mit_new': 'mit_new... |
b653eb2e7b242511dc6ab4cdef9c0ad270b565824a5c48cd330a44f563f1c083 | Python | 1,153 | 40 | """
Created on 25/05/2020
:author: Chinchien Lin
:summary: Visualise an image
"""
import sys
import matplotlib.pyplot as plt
from src.commands.abstract_preprocessing_command import AbstractPreprocessingCommand
from src.utils.frequency_downsampling import FrequencyDownsampling
from src.io.interpreters i... |
c07ceb81f75950c44f051d647b5960e6686a46c0526e311838cb2e157407f636 | Python | 1,153 | 36 | """The purpose of this module is implement PEP 621 validations that are
difficult to express as a JSON Schema (or that are not supported by the current
JSON Schema library).
"""
from typing import Mapping, TypeVar
from .error_reporting import ValidationError
T = TypeVar("T", bound=Mapping)
class RedefiningStaticFi... |
164bb03b6b12bdb2babf753139ec1ec3a43b16b7941daf7aea2ee45852a3acb7 | Python | 1,154 | 34 | import sys, os
from pandas.io.parsers import read_csv
import numpy as np
import pandas as pd
try:
gtffile = sys.argv[1]
outputfile = sys.argv[2]
except:
sys.exit("Please, give: (1) gtf file; (2) exons")
#### Convert gtf file in an easy to handle data frame ####
df = read_csv(gtffile, comment='#', header=N... |
662a02e596431137c972edfa590f524f3592be562aa08304aacecba8df91e896 | Python | 1,154 | 22 | import torch.nn as nn
from .modules import Activation
class SegmentationHead(nn.Sequential):
def __init__(self, in_channels, out_channels, kernel_size=3, activation=None, upsampling=1):
conv2d = nn.Conv2d(in_channels, out_channels, kernel_size=kernel_size, padding=kernel_size // 2)
upsampling = nn... |
400c8ef317d742025035c23746043f0bcb186eaf5bd060b3faf1456dc0a340f0 | Python | 1,155 | 25 | #
# MIT License
#
# Copyright (c) 2022 GT4SD team
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge,... |
77294088ba0cf215c7a83b4d96120f51d5c02b8e0597fcfe22f803c615a39316 | Python | 1,155 | 24 | #
# MIT License
#
# Copyright (c) 2022 GT4SD team
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge,... |
96c8f720c535082923b038d8a5845fea518d906cdeb9a22563b5d709f06caf04 | Python | 1,156 | 35 | import argparse
import json
import os
import pandas as pd
from src.analyze.performance_measures import PerformanceMeasures
parser = argparse.ArgumentParser()
parser.add_argument('-r', '--results-dir', type=str, default=None)
args = parser.parse_args()
def main(results_dir):
try:
with open(os.path.join(r... |
32bdab82a5874b8c5620a75b7ea6f8cd2f946ae2cea0154318ae757642cc66f3 | Python | 1,157 | 32 | """Testing CLI command convert."""
import subprocess
import os
def test_unordered():
"""Tests for converting unordered SWC file."""
os.chdir(os.path.dirname(__file__) + '/data')
proc = subprocess.Popen(['swc', 'convert', 'fail_unordered.swc',
'-o', '/tmp/test_treem.swc'],
... |
9a44f074151ca6a1c6e902e1ca463d783ceacad3d81b8a2312789d1868c2e7c6 | Python | 1,157 | 54 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
from common_setup import IssueConfig, IssueExperiment
REVS = ["issue592-base", "issue592-v3"]
SUITE = suites.suite_optimal_strips()
CONFIGS = [
IssueConfig("lm_zg", [
"--landmarks",
"lm=lm_zg()",
"--heuristic",
... |
9f0aaf5876f98fd86d16965f643f6a1338227ca866dac6ddead78464bd3d1d0c | Python | 1,157 | 38 | from elasticai.creator.file_generation.on_disk_path import OnDiskPath
from elasticai.creator.nn.fixed_point import Linear
from elasticai.creator.nn.fixed_point.lstm.layer import (
FixedPointLSTMWithHardActivations,
LSTMNetwork,
)
from elasticai.creator.vhdl.system_integrations.firmware_env5 import FirmwareENv5
... |
e7774ae379c38d90983aeba2b7cf99bd671cf8abfd358e059c4eeec7f08f6f20 | Python | 1,158 | 37 | import os
from torchdrug import data, utils
from torchdrug.core import Registry as R
@R.register("datasets.ToxCast")
@utils.copy_args(data.MoleculeDataset.load_csv, ignore=("smiles_field", "target_fields"))
class ToxCast(data.MoleculeDataset):
"""
Toxicology data based on in vitro high-throughput screening.
... |
fbb8e891ad4191b03991716c0762477587ea5617ea3a59e80ea5a170d8a0aad4 | Python | 1,158 | 32 | """Testing CLI command convert."""
import subprocess
import os
def test_unordered():
"""Tests for converting unordered SWC file."""
os.chdir(os.path.dirname(__file__) + '/data')
proc = subprocess.Popen(['swc', 'convert', 'fail_unordered.swc',
'-o', '/tmp/test_treem.swc'],
... |
0538da8ceb1ea9e4d20c52ad048f21f310e70dd79fb32f62c0d734983386a53c | Python | 1,159 | 24 | #
# MIT License
#
# Copyright (c) 2022 GT4SD team
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge,... |
4ced56a5d46745128436460421ad7a3019255101005596aa087bfd00d8322db3 | Python | 1,159 | 41 | import neuralnodes.params
import dataclasses
@dataclasses.dataclass
class Params(neuralnodes.params.Params):
filter_inh_dur: float = 8.0
filter_inh_sigma: float = 2.0
filter_inh_gain: float = 1.0
filter_delay: float = 7.0
filter_exc_dur: float = 4.0
filter_exc_sigma: float = 0.5
filter_e... |
6bd9c44685be6a9f1965ce704ac95d28ed6851c7d7148e86f10509e3120753ae | Python | 1,159 | 24 | #
# MIT License
#
# Copyright (c) 2022 GT4SD team
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge,... |
cc921d6e323a4f910fbd6439be3b70d9e5c90670373ab2a856867ea558245fc0 | Python | 1,159 | 24 | #
# MIT License
#
# Copyright (c) 2023 GT4SD team
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge,... |
df9dc91342a01f5629e37366018052e80bc27e4b88c64817a73deb042012424e | Python | 1,159 | 31 | """Testing CLI command convert."""
import os
import subprocess
def test_unordered(tmp_path):
"""Tests for converting unordered SWC file."""
os.chdir(os.path.dirname(__file__) + '/data')
proc = subprocess.Popen(['swc', 'convert', 'fail_unordered.swc',
'-o', tmp_path / 'test_tr... |
150958c0d8e2b1da85e969938cb57d021d1bd7df4e744d0d6f14e463a3148784 | Python | 1,160 | 35 | # Material "Squishy", dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# The class is a recipe for the material's shader tree — build recreates the material and runs it into material.node_tree.
from bpy.types import ShaderNodeTree
from nodebpy import TreeBu... |
2cb7cf56138902ab8497a87923365c21e36b41b53b464aca77aa54f9b20e7a12 | Python | 1,160 | 40 | """
This script crops the atlases in the atlases folder, changes their datatype to
a minimum and compresses the files with a high enough compression level. This
all to reduce the disk size and control the load time (driven by the level of
compression).
"""
from glob import glob
import nibabel as nb
from nilearn.image... |
589b42db195051380213b7e5181c9267bed58c74699b643d45f5acd40087bb95 | Python | 1,160 | 30 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# ht... |
5eb8e28aeedd16c8d1aa47e9d2f1791143120c4813258d35ca4c00f78283e2b5 | Python | 1,161 | 44 | #!/bin/env python3
"""
Example script to calculate conduction velocity and action potential duration
"""
import ithildin as ith
import matplotlib.pyplot as plt
import numpy as np
# read simulation results
sd = ith.SimData.from_stem("results/phase_68")
apd, tarr, tdea = ith.pulse.duration(sd.vars["u"], t=sd.times, u_... |
88cbb4a8e9312e2e5a8fae0ff547fa56568758d38ba9f6ea534d480f840c1de2 | Python | 1,161 | 27 | print "----------------------------------------------------------------------------------------------------------------------------------------------------------"
print "TAURS-MH is dependent on Bismark, PICARD, python, bowtie, pysam,and samtools. Please make sure you have all of these on your system and provide path f... |
b24b3dc1d58c2f77a6695c94cffa14721d5fdd01a7d43aa1e5c285b9933f68b3 | Python | 1,161 | 29 | # Diana Giraldo
# Mayo, 2023
import numpy as np
import nibabel as nib
def get_slicingdims(lr_fpath, hr_fpath):
LR = nib.load(lr_fpath)
HR = nib.load(hr_fpath)
LR2HR_ornt = nib.orientations.ornt_transform(start_ornt = nib.orientations.io_orientation(LR.affine),
... |
b55c13eff83758dc10de48e4b0dc5d2973e7adc22d4d32c4027de3e0f29e8841 | Python | 1,161 | 24 | #
# MIT License
#
# Copyright (c) 2022 GT4SD team
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge,... |
46d308f1c8f918bee3b30896df1e69420dc64aa2004d386f75e4725c25aef8c1 | Python | 1,162 | 46 | import numpy as np
import matplotlib.pyplot as plt
from soundsig.plots import boxplot_with_colors
from soundsig.spikes import plot_raster
def test_plot_raster():
np.random.seed(123456789)
max_nspikes = 20
ngroups = 8
max_cells_per_group = 4
spike_trials = list()
groups = dict()
for k i... |
5e073b218d7d53fa4c1fbbfd50e9c2dd359340d2a08a0903a42009b6a0078770 | Python | 1,162 | 24 | #
# MIT License
#
# Copyright (c) 2022 GT4SD team
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge,... |
7540aaf1819c1fbe40e327d6e5dec12acd4020a626e22b6eb47ec805cee5b79d | Python | 1,162 | 36 | from gt4sd.frameworks.gflownet.arg_parser.parser import parse_arguments_from_config
from gt4sd.frameworks.gflownet.envs.graph_building_env import GraphBuildingEnv
from gt4sd.frameworks.gflownet.envs.mol_building_env import MolBuildingEnvContext
from gt4sd.frameworks.gflownet.tests.qm9 import QM9Dataset, QM9GapTask
from... |
d2711fe10ceb6f8e24d78b58a49034f6f93cdedac0195ac9b6761a3f6de21979 | Python | 1,162 | 37 | import os
from torchdrug import data, utils
from torchdrug.core import Registry as R
@R.register("datasets.ZINC250k")
@utils.copy_args(data.MoleculeDataset.load_csv, ignore=("smiles_field", "target_fields"))
class ZINC250k(data.MoleculeDataset):
"""
Subset of ZINC compound database for virtual screening.
... |
e52c9b5efb19902beb1805ac0c7b491be88989c0a8c3c6da2ffe56768f13ea04 | Python | 1,162 | 32 | import unittest
import os
import random
import shutil
from torcheeg.model_selection import train_test_split_per_subject_cross_trial
from torcheeg.datasets import DEAPDataset
class TestTrainTestSplitPerSubjectCrossTrial(unittest.TestCase):
def setUp(self):
shutil.rmtree('./tmp_out/')
os.mkdir('./t... |
65a592ca6e192aacc5838903ec62a6738c9dace80e1ace8bd85cdd86843aa8c0 | Python | 1,163 | 49 | import os
import torch
import pandas as pd
import matplotlib.pyplot as plt
from run import *
LR = 1e-4
input_size = 280
output_sizes = [2]
batch_size_label = 128
hidden_sizes = [2048, 2048]
Epoch = 7
l2_lambda = 0
K = 5
accs= []
accs_inclass=[]
Permute = 1
pred_all = []
for perm in range(Permute):
predict... |
56c0b4b799bee9fd1856bf7a3d592cf771b710317c312358e0aa5432f3da8430 | Python | 1,164 | 46 | from __future__ import annotations
from platformdirs import PlatformDirs, __version__
PROPS = (
"user_data_dir",
"user_config_dir",
"user_cache_dir",
"user_state_dir",
"user_log_dir",
"user_documents_dir",
"user_runtime_dir",
"site_data_dir",
"site_config_dir",
)
def main() -> No... |
8fd3fcfcb31fbe5eb59b7b69eee5714021a36598399c48dd0ebecf73afd2f195 | Python | 1,164 | 45 | import sys, os
from pandas.io.parsers import read_csv
import numpy as np
from collections import Counter
import pandas as pd
import pysam
### Initialize ###
try:
inputBamFile = sys.argv[1]
motifnum = int(sys.argv[2])
motifs = []
for i in range(motifnum):
motifs.append(sys.argv[3+i])
except:
... |
9be2785cefa0bc57ab958b05cf3497603bebc7cb4b6652454c2803c5cb67f228 | Python | 1,164 | 34 | from pip._vendor.packaging.utils import canonicalize_name
from pip._internal.distributions.base import AbstractDistribution
from pip._internal.index.package_finder import PackageFinder
from pip._internal.metadata import (
BaseDistribution,
FilesystemWheel,
get_wheel_distribution,
)
class WheelDistributio... |
a1ed6828bbac4770e5e3d015ae81e06eba8490ce65f2aff0fae967cf2b461a83 | Python | 1,165 | 42 | from __future__ import annotations
import pytest
prefect = pytest.importorskip("prefect")
from pathlib import Path
from quacc import flow, job
from quacc.utils.files import copy_decompress_files
def test_copy_files(tmp_path, monkeypatch):
monkeypatch.chdir(tmp_path)
@job
def create_file(name: str, co... |
bf97b56431bbc994c7de1ed38db4b96cce69f001b330f54ebbcb240ccbf887a9 | Python | 1,165 | 49 | from ._compat import Protocol
from typing import Any, Dict, Iterator, List, TypeVar, Union
_T = TypeVar("_T")
class PackageMetadata(Protocol):
def __len__(self) -> int:
... # pragma: no cover
def __contains__(self, item: str) -> bool:
... # pragma: no cover
def __getitem__(self, key:... |
1bf0aac67aab6e34958150459818127e48befab2a43e44901de8efd8a5a09a95 | Python | 1,166 | 37 | import unittest
from unittest.mock import patch
from IPython.core.interactiveshell import InteractiveShell
from memory_profiler import LineProfiler, MemitResult, load_ipython_extension
def sample_func(n):
arr = [1] * n
return len(arr)
class TestIPythonMagics(unittest.TestCase):
@classmethod
def set... |
82858b7ea528acd83a932398ff3676b740317fd905dfd5b897ed9883ee4ec5d6 | Python | 1,166 | 24 | #
# MIT License
#
# Copyright (c) 2022 GT4SD team
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge,... |
aa23167e7360cae970479dbbfaa13ce29f5b1d22a103b5d178a639b9ad5a47d9 | Python | 1,166 | 48 | # -*- coding: utf-8 -*-
#
# oxasl documentation build configuration file
#
# This file is execfile()d with the current directory set to its
# containing dir.
# -- General configuration ------------------------------------------------
import os
import sys
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirnam... |
3fcbbaedb39e3202a95eab2de603c39f6cf1559ada9263b8a2c43e3c9577cdfb | Python | 1,167 | 41 | import sys
from pybioshell.core.data.io import find_pdb
if len(sys.argv) < 2 :
print("""
Prints names of ligand molecules found in a given PDB file.
A ligand is defined as a residue located after TER field in a PDB chain
USAGE:
python3 list_pdb_ligands.py input.pdb
EXAMPLE:
python3 list_pdb_l... |
a1ee72e25ed1074f8bec45383e7f11136dffc2e7079bcf818454272f924dd3be | Python | 1,167 | 45 | #!/usr/bin/env python
from pathlib import Path
from setuptools import setup, find_packages
version = (
Path(__file__)
.parent.joinpath("src", "neuroquery_image_search", "data", "VERSION.txt")
.read_text()
.strip()
)
description = (
"Search the NeuroQuery dataset for studies with "
"activation... |
c3ad9bf772b36d9843ab1432100ad56a204675b900c9df6b33c6e7b27a03a7f3 | Python | 1,167 | 34 | # Written by Minh Nguyen and CBIG under MIT license:
# https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
import unittest
import torch
import cbig.Nguyen2020.rnn as rnn
class RnnCellTest(unittest.TestCase):
""" Unit tests for recurrent cells """
def setUp(self):
torch.manual_seed(0)
... |
f9959aead522a56f57baeb68a8fa2f0466c1c08363b7e68f500f35ac3595dd7e | Python | 1,167 | 33 | from torch import nn as nn
def conv_layer(in_channels, out_channels, kernel_size, norm_layer, padding):
return nn.Sequential(nn.Conv2d(in_channels, out_channels=out_channels, kernel_size=kernel_size, padding=padding),
norm_layer(out_channels),
nn.ReLU())
def con... |
e0a3bf31144469977e4a1172f0b9b176a7b459ebb3fe0eafd7a4e53da8feef7c | Python | 1,168 | 37 | '''
Created on 3 May 2018
@author: Miguel Molina Romero, Techical University of Munich
@contact: miguel.molina@tum.de
@license: LPGL
'''
import unittest
from dry.utils import generate_synthetic_data, DryException
class TestGenerateSyntheticData(unittest.TestCase):
def testEmptyBfile(self):
try:
... |
71faf6d04a97fcea5f379747cd2a9e458ca1049e6f0ef84114f702682b15eaae | Python | 1,169 | 28 | """Tests for the pipeline's h5ad write-back trigger helper + 3D forwarding."""
import os
import pytest
from regtools.registration.pipeline import _h5ad_writeback_path
def test_writeback_path_only_for_h5ad():
assert _h5ad_writeback_path("/x/cells.h5ad", "/out/cells") == os.path.join("/out/cells", "cells_r... |
a0d1db6c3781ab79498f92e037b3aba48e35437ad6a01213f3359822eee4862d | Python | 1,169 | 24 | #
# MIT License
#
# Copyright (c) 2022 GT4SD team
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge,... |
aaab170ed8b03088d730488855268e8f01f96268ab09a2be748cdbebe5c9b0bd | Python | 1,169 | 36 | import codecs
import locale
import re
import sys
from typing import List, Tuple
BOMS: List[Tuple[bytes, str]] = [
(codecs.BOM_UTF8, "utf-8"),
(codecs.BOM_UTF16, "utf-16"),
(codecs.BOM_UTF16_BE, "utf-16-be"),
(codecs.BOM_UTF16_LE, "utf-16-le"),
(codecs.BOM_UTF32, "utf-32"),
(codecs.BOM_UTF32_BE,... |
25725acf0dfdde84d8bb14c6f2264d480ebd207de8b65c770d2b7f67452adde7 | Python | 1,170 | 32 | import math
import matplotlib.pyplot as plt
from scipy.stats import vonmises
input_data_file = "test_inputs/THR_chi1.dat" # The same input file as was used to run ap_fit_VonMises_mixture
n1, mu1, kappa1 = 16146, -1.02734, 99.996 # direct output from ap_fit_VonMises_mixture
n2, mu2, kappa2 = 2972, -3.01446, 17.8191
n3,... |
a760525689dce274c8814e375fa993d8827494f2519b3f3dc7ca1f3d985a9b87 | Python | 1,170 | 32 | import unittest
import os
import random
import shutil
from torcheeg.model_selection import train_test_split_per_subject_groupby_trial
from torcheeg.datasets import DEAPDataset
class TestTrainTestSplitPerSubjectGroupbyTrial(unittest.TestCase):
def setUp(self):
shutil.rmtree('./tmp_out/')
os.mkdir(... |
dc15b805b805324d982fbba52b3dd3a15f394def8e360b17ff0e4225786516d6 | Python | 1,170 | 24 | #
# MIT License
#
# Copyright (c) 2022 GT4SD team
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge,... |
76644d0928fdcf2d8c55fe825d3a02c50888cc574d68eb863ac0a0ad0fe747f3 | Python | 1,171 | 52 | # -*- coding: utf-8 -*-
"""
Created on Fri Mar 25 17:00:36 2022
@author: Shengze Cai
"""
import math
import numpy as np
import matplotlib.pyplot as plt
def LHSample(D, bounds, N):
# """
# :param D: Number of parameters
# :param bounds: [[min_1, max_1],[min_2, max_2],[min_3, max_3]](lis... |
bd06700cc025444b14127ab6bfb44ec1143829fbffe017a81fddd9495bed286d | Python | 1,171 | 37 | import os
from torchdrug import data, utils
from torchdrug.core import Registry as R
@R.register("datasets.Malaria")
@utils.copy_args(data.MoleculeDataset.load_csv, ignore=("smiles_field", "target_fields"))
class Malaria(data.MoleculeDataset):
"""
Half-maximal effective concentration (EC50) against a parasit... |
eeb03b370d13f5ca4109e0baeb1d328e66723e6e1aa5458324f6339d1bc976e1 | Python | 1,171 | 41 | from collections.abc import Iterator
from itertools import chain
from elasticai.creator.vhdl.design.signal import Signal
class Port:
def __init__(self, incoming: list[Signal], outgoing: list[Signal]):
self._incoming = set(incoming)
self._outgoing = set(outgoing)
@property
def incoming(se... |
101b83de7e729b0965b1a495802266ce974b8dc887d54344ba0356de66c7a012 | Python | 1,172 | 36 | # Material "Flat", dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# The class is a recipe for the material's shader tree — build recreates the material and runs it into material.node_tree.
from bpy.types import ShaderNodeTree
from nodebpy import TreeBuild... |
0a20aaf16a0b01d4dbb50f74f16da11c0dd4da9e9c6e7323786355cb39a35679 | Python | 1,173 | 31 | from setuptools import setup, find_packages
from os.path import join, dirname
requirementstxt = join(dirname(__file__), "requirements.txt")
requirements = [ line.strip() for line in open(requirementstxt, "r") if line.strip() ]
setup(
name="AutoOSS",
version="0.1.0",
author="Nian Wu",
author_... |
11a75646d1880bb8d552f4f47e094b848c282412a8487c201b75a40e19218404 | Python | 1,173 | 29 | import sys
import argparse
from .data import load_single
from .vis import draw_task, output_drawing
def taskprint():
if len(sys.argv) < 2:
print("Usage: arctask <task_id>")
return
task = load_single(sys.argv[1])
task.show()
def tasksave():
parser = argparse.ArgumentParser(description... |
294eed3961e4ec52952945b638d1b1d134fa81862088401bcad273d02b4a550d | Python | 1,173 | 49 | #!/usr/bin/env python
import syncopy as spy
import matplotlib.pyplot as plt
# Settings
plt.rcParams['pdf.fonttype'] = 42
saveFig = 1 # 0:not savefigs 1: save figs
# Load data
spikeData = spy.load('allen_spike.spy')
data_spk = spikeData.trials
samplerate = 1250
offset = -0.25 * samplerate # Offset in sa... |
c437104f25919ddb9fca9600e18cac0766fb457b3f45692a6c7edac69ae698db | Python | 1,173 | 37 | import os
from torchdrug import data, utils
from torchdrug.core import Registry as R
@R.register("datasets.FreeSolv")
@utils.copy_args(data.MoleculeDataset.load_csv, ignore=("smiles_field", "target_fields"))
class FreeSolv(data.MoleculeDataset):
"""
Experimental and calculated hydration free energy of small ... |
caf6b819fab21081802d301aaeb88ecf6aa426b9de402717edaa987e61db03e4 | Python | 1,173 | 32 | import os, re
from setuptools import setup, find_packages
with open('pinn/__init__.py') as f:
version = re.search("__version__ = '(.*)'", f.read()).group(1)
print(version)
def parse_reqs(filename):
with open(filename) as f:
return f.read().splitlines()
setup(name='pinn',
version=version,
... |
daee8483a6dbccb7661b3b8b5bfe4a78e9766b2e18aba6c7d25a8fde70d849ab | Python | 1,173 | 33 | import smart
def test_Compartment_initialization(compartment_kwargs_Cyto):
"""Test that we can initialize a Compartment"""
Cyto = smart.model_assembly.Compartment(**compartment_kwargs_Cyto)
assert Cyto.V is None
assert Cyto.cell_marker == compartment_kwargs_Cyto["cell_marker"]
assert Cyto.dimensi... |
bd4d6a79d5dcff3ac2201658173090dccf9480776ea603a271eecdc24fc83f88 | Python | 1,174 | 20 | import openai
import json
def get_completion(prompt):
inference = openai.Completion.create(
#model="curie:ft-llm-hackathon-synthesis-parsing-team-2023-03-29-22-57-05",
model="davinci:ft-llm-hackathon-synthesis-parsing-team-2023-03-30-00-54-58",
prompt=prompt,
max_tokens=1000,
stop=["###"])
... |
015dc0d96e18f2d1b6cbff3629d15b11e4261e991a8888777d0881d0dd97b64f | Python | 1,175 | 36 | # Material "Default", dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# The class is a recipe for the material's shader tree — build recreates the material and runs it into material.node_tree.
from bpy.types import ShaderNodeTree
from nodebpy import TreeBu... |
409bd2a63f7d251bc598ac1a63922925210f48333829a7b95a651d928e5610cb | Python | 1,175 | 37 | import torch.nn as nn
import torch.nn.functional as F
import torchvision.models as models
class ResNetSimCLR(nn.Module):
def __init__(self, base_model, out_dim):
super(ResNetSimCLR, self).__init__()
self.resnet_dict = {"resnet18": models.resnet18(pretrained=False, norm_layer=nn.InstanceNorm2d),
... |
d692fc936fd8312d89be9dbb4fc04279326cc045ed714e27114b069ba9967afe | Python | 1,175 | 22 | import matlab.engine
import numpy as np
import matplotlib.pyplot as plt
import pickle
targetPSTH = np.array([2, 4, 6, 4, 8, 3, 2, 4, 3, 5, 2, 3, 1, 5, 5, 2, 4, 4, 3, 5, 3, 2, 1, 1, 5, 4, 3, 4, 2, 3, 4, 5, 4, 5, 4, 5, 3, 5, 5, 6, 7, 4, 6, 1, 7, 10, 21, 18, 11, 11, 11, 10, 3, 5, 8, 11, 9, 8, 9, 11, 8, 12, 8, 3, 9, 5, ... |
276d664454cb7520c7f03827f4e33f8ad71a6c83185123cbed792ffd7a582f83 | Python | 1,176 | 39 | from importlib.metadata import version as _pypackage_version
from pathlib import Path
import tomlkit as toml
from tomlkit.toml_file import TOMLFile
class MetaFile:
version = "0.1"
def __init__(self, data):
self._data = data
@classmethod
def load(cls, file: Path) -> "MetaFile":
with ... |
27b8949d6186b0beeeb076394525233a10653385436eff1be7453b46035e70d1 | Python | 1,176 | 35 | import torch
from elasticai.creator.base_modules.math_operations_torch import TorchMathOperations
from tests.tensor_test_case import TensorTestCase
class TorchMathOperationsTest(TensorTestCase):
def setUp(self) -> None:
self.operations = TorchMathOperations()
def test_quantize(self) -> None:
... |
722228afe03b836ebd3228db05206b26c3cfdefd6f605d0fcf48571d6acda50d | Python | 1,176 | 33 | """Apply-transforms tab forwards the h5ad field mapping via --h5ad_map."""
import os
os.environ.setdefault("QT_QPA_PLATFORM", "offscreen")
import json
import pytest
pytest.importorskip("PySide6")
from regtools.registration.gui.apply_transforms_tab import ApplyTransformsTab
def test_h5ad_map_args_writ... |
24089944a96d00073503e5bf58a3c8ca766763078d645bad154afea9237c89e5 | Python | 1,178 | 24 | #
# MIT License
#
# Copyright (c) 2022 GT4SD team
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge,... |
397ec27ef7ebbc41efc2aa98a67d10185a800f1cb32a09a33e2b41f85fc3325b | Python | 1,178 | 49 | from elasticai.creator import ir
_ir_factory = ir.DefaultIrFactory()
def prepare_executor():
executor = ir.ExecutionOrderGraphReducer()
@executor.register()
def input(node: ir.Node, acc: str):
return f"{acc}input"
@executor.register()
def A(node: ir.Node, acc: str):
return f"{ac... |
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