sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
414129ac4fef31a5af73476dec5532e8dc2214e6f373016988e2774ab3c015eb | Python | 1,178 | 43 | #!/usr/bin/python3
def vcf_to_plink2(vcf):
sys.stdout = sys.__stdout__
cmd = ['plink2',
'--vcf', vcf,
'--make-pgen',
"--out", args.out,
'--vcf-half-call', 'm',
'--exclude-if-info', 'MAF < ' + args.maf,
'--extract-if-info', 'R2 >= ' + a... |
c07e5c38c2990612e80ce1bff563b8c9208f894f3d281d60085ff5a6483ce460 | Python | 1,178 | 51 | from enum import Enum, auto
class QmTarget(Enum):
'''Enum class for the different QM attributes to be used.'''
# POLARISABILITY
POLARISABILITY = auto()
NORMALISED_POLARISABILITY = auto()
# dispersion energy
SVP_DISPERSION_ENERGY = auto()
TZVP_DISPERSION_ENERGY = auto()
# electronic... |
cead8e18e8a05b548f6a76d45381f8adc07d85cbc4a10654842f891bb4e19f48 | Python | 1,178 | 38 | import os
import pandas as pd
import numpy as np
import unittest
import sys
sys.path.append(os.path.dirname(os.path.realpath(__file__)) + "/../../src")
from hornet.uml import energy_filter
class TestEnergyFilter(unittest.TestCase):
def setUp(self):
# Create a sample DataFrame for testing
self.df =... |
45e01339d754cacfb56a41bca9acc636c23ea9b44133f1e1ec91f0f558a00614 | Python | 1,179 | 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,... |
4d0361c9ea6a7d31ca4e5775dcd6f0a78673fd96907d874533440d82cf60aee3 | Python | 1,179 | 37 | import os
from torchdrug import data, utils
from torchdrug.core import Registry as R
@R.register("datasets.SIDER")
@utils.copy_args(data.MoleculeDataset.load_csv, ignore=("smiles_field", "target_fields"))
class SIDER(data.MoleculeDataset):
"""
Marketed drugs and adverse drug reactions (ADR) dataset, grouped ... |
d7c4656a32722f2f47ff44a8d63e35f431495417bb74528a2e03a5f88c94c7f2 | Python | 1,179 | 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,... |
39bf534cffb560c8116caaab8c4919bfcb52a368a76c4a561876b2a34272b80d | Python | 1,180 | 26 | """Packages containing all the possible attributes to recordings, such as
- channels (module "chan") with class:
- Chan
- anatomical info (module "anat") with class:
- Surf
- annotations and sleep scores (module "annotations") with class:
- Annotations
Possibly include forward and i... |
3d600373074a971cf3afe2f3619077c0bf7b07cf6de7c09a45d8cfa06b79f7a8 | Python | 1,180 | 38 | #!/bin/env python3
'''
YAML file containing info about the particles to draw them
'''
import pdlfeynman as fy
import yaml
all_particles = fy.particle.PARTICLES
all_reactions = fy.reaction.REACTIONS
splitting_reactions = [r for r in all_reactions if len(r.reactants) == 1 and 1 < len(r.products)]
base = {
fy.partic... |
4d0698128921c5f3eec5a66a2f0bfdcab6b68adff9118236934e44b85827afbf | Python | 1,180 | 31 | from math import floor
from PIL import ImageDraw
import random
from typing import Optional
class Shape:
"""Base class for shapes"""
def __init__(self, x: int, y: int, width: int, height: int):
self.x = x
self.y = y
self.width = width
self.height = height
def draw(self, draw... |
4d5ccd36a9134675c3bfb7b80994a0a8f330bba7fe229fcbf7446218d618d633 | Python | 1,180 | 35 | import numpy as np
from cirrocumulus.data_processing import handle_selection_ids
def test_dimension_filter(dataset_api, input_dataset, test_data):
process_results = handle_selection_ids(
dataset_api=dataset_api,
dataset=input_dataset,
data_filter={
"filters": [{"field": "louva... |
7bf917f0630427072267474772c6784bbb59fff044a40e56da328f4317fd1f98 | Python | 1,180 | 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
... |
b700985df746e58829f0c66e8902c11cf47ae85f4929480ddee24908ca9f578c | Python | 1,180 | 43 | #!/usr/bin/env python3
# A script that plots Chi-1 vs CHi2 scatterplot
from sys import argv, stderr
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as mcl
COLUMN_CHI1 = 4
COLUMN_CHI2 = 5
chi1 = []
chi2 = []
for line in open(argv[1]) :
tokens = line.strip().split()
if len(tokens) > CO... |
bfe41c5648da597e727f4c5aba9f7f2b249a9d596677a2e1bb31211a99938935 | Python | 1,180 | 44 | """distutils.command.install_headers
Implements the Distutils 'install_headers' command, to install C/C++ header
files to the Python include directory."""
from ..core import Command
# XXX force is never used
class install_headers(Command):
description = "install C/C++ header files"
user_options = [
... |
74c840ce0aee634c0a095967fa7172c22590370d47e6ef3cbd2f136ded8e045c | Python | 1,181 | 43 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Copyright (C) 2012 Computational Neuroscience Group, NMBU.
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 you... |
ca077cba418d05624fd2e2a1daaa51172fcd5078e8e83ecbc1a1397c3942adf3 | Python | 1,181 | 31 | import pathlib
from pandas._typing import FilePath
from ord.data.data_llm import DEFAULT_PROMPT_TEMPLATE, ReactionData, LlmData
from ord.utils import json_dump, json_load
def make_cre_dataset_singular(cre_singular_json: FilePath):
data = json_load(cre_singular_json)
records = []
meta_record = dict(test_... |
2309a26f25bd0529ff47c6c721eb66326dfba170ca08c056377e8d7266244a9a | Python | 1,182 | 41 | import numpy as np
from .utils import AtomsDataset, register_dataset
from typing import List, Optional
from ase import Atoms
@register_dataset("rmd17")
class RevisedMD17(AtomsDataset):
def __init__(
self,
datapath: str,
indices: Optional[List[int]] = None,
cutoff: float = 4.0,
... |
0e24fa3d5ed51401c40f91fe7c0757ad481d462afe31dbb1063c1e33440692e6 | Python | 1,184 | 41 | # -*- coding: utf-8 -*-
from glob import glob
from tempfile import TemporaryDirectory
import os
import pytest
from dcm2bids.dcm2niix_gen import Dcm2niixGen
from dcm2bids.utils.utils import DEFAULT
TEST_DATA_DIR = os.path.join(os.path.dirname(__file__), "data")
@pytest.mark.skip(reason="Too long for now")
def test... |
ed5a5e74fe29bc5dab5ffd7401b274692af7bd0065cb4f7abc8c1207e79902af | Python | 1,184 | 29 | """
toposampling - Topology-assisted sampling and analysis of activity data
Copyright (C) 2020 Blue Brain Project / EPFL & University of Aberdeen
This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as
published by the Free Software Foundation... |
28c5b8459981fa689f6a9545c6b602f65c763bec1ff5b54d655c15217d86144f | Python | 1,185 | 39 | #!/usr/bin/env python
import os
import pandas as pd
from nilearn import masking as nmask
from bids.layout import BIDSLayout
### create mask across subjects
# project location
proj_path = '/project/3011157.03/Simon/proj_2022_CABB_movie/MRI'
# location of movie data
fmriprep_path = os.path.join(proj_path, 'BIDS_movi... |
4a0efd9b3726925136f92ba298de2d3664c98d5597777f47c34385b6438a358c | Python | 1,185 | 37 | import cocotb
from cocotb.clock import Clock
from cocotb.triggers import RisingEdge, Timer
from elasticai.creator.testing.cocotb_prepare import read_testdata
@cocotb.test()
async def precomputed_test(dut):
data = read_testdata(dut._name)
clock_period_ns = 10
dut.enable.value = 1 # Has no impact
dut.... |
4e30bbb6b6ec7952e358990850af1d2ca1355c38da017b0eea22d111844495f1 | Python | 1,185 | 23 | # AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/06_constants.ipynb.
# %% auto 0
__all__ = ['ROOT_DIR', 'DATA_DIR', 'NTBK_DIR', 'IMGS_DIR', 'RES_DIR', 'WORM_FILE', 'EB_BODIES_FILE', 'EB_BODIES_PSEUDO_4',
'EB_BODIES_PSEUDO_6', 'EB_BODIES_PSEUDO_25', 'EB_BODIES_PSEUDO_82', 'DYNGEN_INFO_FILE', 'DYNGEN_EXPR_F... |
c11fd89285c984824341b0050d27ac33039aa484d6a18d1357d23c2fadf720e0 | Python | 1,185 | 42 | import torch
import torch.nn as nn
class FreqEncoder(nn.Module):
def __init__(self, input_dim, max_freq_log2, N_freqs,
log_sampling=True, include_input=True,
periodic_fns=(torch.sin, torch.cos)):
super().__init__()
self.input_dim = input_dim
self.incl... |
de1b9f44fbabaf7cc5f6f33f1e4d7f84186a8e460fc5079fed74af2be6dbd751 | Python | 1,185 | 41 | from pylearn2.utils import serial
import sys
_, model_path = sys.argv
model = serial.load(model_path)
space = model.generator.get_output_space()
from pylearn2.config import yaml_parse
from pylearn2.gui.patch_viewer import PatchViewer
import numpy as np
dataset = yaml_parse.load(model.dataset_yaml_src)
grid_shape = No... |
f22219be1c2cf2077ae2244cb54a888af4cbb8e8ed8550036c9f9dde722eed44 | Python | 1,187 | 34 | #!/usr/bin/env python
from setuptools import find_packages, setup
import NDATools
with open("README.md", "r") as fh:
long_description = fh.read()
setup(
name='nda_tools',
description="NIMH Data Archive Python Client",
install_requires=['boto3>=1.36.18', 'tqdm', 'requests', 'packaging', 'pyyaml', 'ke... |
2b553d3a4ecae2b34915056247f090ff8e7bb9d5d6a56bedb13485fc19deee7f | Python | 1,189 | 47 | ##
# \file multiply.py
# \brief Script multiply images with each other.
#
# \author Michael Ebner (michael.ebner.14@ucl.ac.uk)
# \date October 2017
#
import os
import SimpleITK as sitk
import pysitk.python_helper as ph
import niftymic.base.data_writer as dw
from niftymic.utilities.input_arparser impor... |
7859cac0bcacba25cb6d0dfc42490982612f30b889f6ef8d6348e034b64cacda | Python | 1,189 | 35 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
88363d1203ae2741899d089ad98e5659eaa784805086b4bd2a57e8f46465ae8f | Python | 1,189 | 41 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from setuptools import setup
with open("esm/version.py") as infile:
exec(infile.read())
with open("README.md") as f:
readme = f.rea... |
47307a175ad1a6e6c371767fb4cec01c8d065699d422d4f4e61803e81026a0c0 | Python | 1,190 | 26 | #
# 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,... |
fe7dab1cecc8604053dc140001c1f8c7afb16b25ac4b2d97bdb4f5db424bd192 | Python | 1,190 | 43 | #!/usr/bin/env python
# Copyright (c) 2020 Intel Corporation
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
"""
This module provides an example controller for actors, that use an external
software for longitudinal and lateral control command calc... |
6482d5f3e3d852fa5917da95763782126daf05e27f74d68496418cb8b37ef63d | Python | 1,191 | 23 | from .dictionary import PerfectHash, Dictionary
from .graph import Graph, PackedGraph, cat
from .molecule import Molecule, PackedMolecule
from .protein import Protein, PackedProtein
from .dataset import MoleculeDataset, ReactionDataset, ProteinDataset, \
ProteinPairDataset, ProteinLigandDataset, \
NodeClassific... |
bcda89e8ebb92b85bcda179510b466c6bd8a50b041c9c2718728b1782efaf45d | Python | 1,191 | 46 | import json
import os
from abc import ABC, abstractmethod
import pandas as pd
from cirrocumulus.api import get_file_path
class AbstractDataset(ABC):
def __init__(self):
super().__init__()
@abstractmethod
def read_dataset(self, filesystem, path, keys, dataset):
pass
@abstractmethod
... |
31b5e0c1ae425a256a03428c8eed5ad325b4e17f5183628f9e996d1cb4216cd9 | Python | 1,192 | 42 | from typing import Any, Dict
import torch
import torch.nn.functional as F
from torch import nn, Generator
from ..prixfixe import FinalLayersBlock
class BHIFinalLayersBlock(FinalLayersBlock):
def __init__(
self,
in_channels: int = 320,
seqsize: int = 110,
hidden_dim: int = 64,
... |
3acc49abc062126bdff79795dc1daac81e58eec3a34fde4c2322c8b17fce4d88 | Python | 1,192 | 44 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from downward import suites
from common_setup import IssueConfig, IssueExperiment
REVS = ["issue551-base", "issue551-v1"]
BENCHMARKS = os.path.expanduser('~/downward-benchmarks')
SUITE = suites.suite_satisficing()
CONFIGS = [
IssueConfig("lama-first", [],... |
493fa67642d7f4a34ad37dbbb86725f0f60075f4bfa032240ec9bb1aaa6c21d0 | Python | 1,192 | 35 | import os
class Settings:
def __new__(cls):
cls.DEFAULT_OUTPUT_DIR_NAME = 'output'
cls.PROCESSING_DIR_NAME ='img_process'
if not hasattr(cls, 'instance'):
cls.instance = super(Settings, cls).__new__(cls)
return cls.instance
def output_suffix(self):
return f'LM{self.large_median}_SM{sel... |
850b1a57efdf0a70f26f73e935ab4a0fe0db2bb6f1a154ddcfea86aed5c9f639 | Python | 1,192 | 41 | ################################################################################
# Copyright (c) 2021-2024, Lawrence Livermore National Security, LLC.
# Produced at the Lawrence Livermore National Laboratory.
# Written by D. Jones <djones@llnl.gov> and UCSD collaborators in listed in CONTRIB.md
#
# All rights reserved.... |
cbd0671d280dd2cb702f4f68ea10be6a78a9844b23f2f0b353aed54cfe881ead | Python | 1,192 | 30 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
37482c0e1df6ff5e353871dca507eaf65e9814ca4a7fe52400cebf3a5d1dacfb | Python | 1,193 | 37 | # Material "Transparent", 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 Tr... |
e46a18539f3a4abc5444cbc39ff8c13092278adbe2260e0ee7e88e53ee88d166 | Python | 1,193 | 39 | """Utilities for defining models
"""
import operator
from typing import Any, Callable, Type
class KeyBasedCompareMixin:
"""Provides comparison capabilities that is based on a key"""
__slots__ = ["_compare_key", "_defining_class"]
def __init__(self, key: Any, defining_class: Type["KeyBasedCompareMixin"]... |
1719297dc26f34cc61fd270a866355fc833309cc1f63f0e2543c8962c20eb2b2 | Python | 1,194 | 13 | """posthoc_real_pn_dep_levels_2026-09-29.py (POST HOC, descriptive): why does depression lower the fit to the real PNs?
Mean PN response in driven and undriven glomerulus-odour pairs, model with/without depression vs real (Seki)."""
import sys; sys.path.insert(0, 'D:/eucys/03-CODE')
import numpy as np, SIGN_FROM_FUNCTI... |
9050363d392959c884cb880ec62af41eeaab90a6f42bf704bd835e5c3f98cb4f | Python | 1,194 | 39 | from setuptools import setup, find_packages
setup(
name='CryoVesNet',
version='0.5.0',
url='https://github.com/Zuber-group/CryoVesNet',
packages=find_packages(),
license='MIT', # Please confirm or change the license as appropriate
author='Amin Khosrozadeh, Guillaume Witz, Benoît Zuber',
au... |
bb883354bc5fdedabbb2ce7ed2c4f180cdd0185dba5f2d19cb52ebbcfc791223 | Python | 1,194 | 35 | import os
from regtools.registration.core.stage_dirs import STAGE1_DIRNAME, STAGE1_DIRNAME_LEGACY, resolve_stage1_dir
def test_prefers_new_name(tmp_path):
new = tmp_path / STAGE1_DIRNAME
new.mkdir()
assert resolve_stage1_dir(str(tmp_path)) == str(new)
def test_falls_back_to_legacy(tmp_path):
... |
ce3375b89b1d3949a80e69bb261c446ad38cff273c75010c7f3bc8091c1928d4 | Python | 1,194 | 39 | from __future__ import print_function
from __future__ import division
import numpy as np
import logging
def upsample_filt(alg='nn', dtype=None):
if alg == 'nn':
x = np.array([[0., 0., 0., 0.],
[0., 1., 1., 0.],
[0., 1., 1., 0.],
[0., 0., 0.... |
d881a05ee13b87fcfe809dc32c7208d8b9a239d3ce48d3f791345f2943ef34e5 | Python | 1,194 | 48 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
"""
Before you can run the experiment you need to create duplicates of the
two tasks we want to test:
cd ../benchmarks/tidybot-opt11-strips
for i in {00..49}; do cp p14.pddl p14-$i.pddl; done
cd ../parking-opt11-strips
for i in {00..49}; do cp pfile04-015.pddl pfile04-01... |
f5d8cf9dcfca401819054f5f2b2f49c0f4cab102942882ba970f3a34995ad56c | Python | 1,194 | 26 | #
# 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,... |
075e301ce50d2c7d0af51525625ad6af7e8fc1d1c90fcbd860c2d96007b025d0 | Python | 1,195 | 45 | import numpy as np
from numba import jit
@jit(fastmath=True, nogil=True, nopython=True)
def exponential(x, slope: float = 1, offset: float = 0):
return np.exp(slope * x) + offset
@jit(fastmath=True, nogil=True, nopython=True)
def linear(x, slope: float = 1, bias: float = 0):
return slope * x + bias
@jit(f... |
53868df1e691d0433b652949c05944834ed1349cb04d010035c7b01e90c08fda | Python | 1,195 | 43 | ######################################################################
#
# energy.py: calculate the energy of a molecule
#
######################################################################
from __future__ import print_function
from openbabel import openbabel
import sys
# Make sure we have a filename
try:
filen... |
6d3b7986e56c6be8548384a83d285eac0403d9d78f9ec37b6e612633ae22a61b | Python | 1,195 | 29 | from .colors import Color
from .shapes import Shape
from .textures import Texture
from typing import Optional
class Stimulus:
"""Combination of a shape and a color or texture.
Used to generate the actual stimulus picture."""
def __init__(self, shape: Shape, pattern: Color | Texture,
background_... |
b3380b74723c5ee20f80827bf990cb39b1e92ae97f4a3d7471cf3a2c53b6631c | Python | 1,195 | 22 | from setuptools import setup
setup(
name='nails',
version='1.0.0',
packages=['helper', 'helper.base', 'helper.utils', 'helper.losses', 'helper.metrics', 'helper.datasets',
'helper.decoders', 'helper.decoders.fpn', 'helper.decoders.pan', 'helper.decoders.unet',
'helper.decoders.m... |
c44f89fb9749bc4383af68f16dcfcd3c95b1b2baaf7b17928b9c7fc4d4fe2f23 | Python | 1,195 | 34 | """Signal-to-noise ratio (SNR) calculation."""
import numpy as np
def signal_to_noise_ratio(signal: np.ndarray, dwell_time: float, window_width: float | int = 3000) -> float:
"""Calculate the signal to noise ratio in dB.
Parameters
----------
signal
Centered spectrum of the acquired signal
... |
13728ed4b51578e27d2708c0c1217f20c4dda1a87c07d01a5a9c7c6ae9dddebb | Python | 1,196 | 36 | import os
from tqdm import tqdm
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import torch
import torch.nn as nn
from torchvision import datasets, transforms
from torch.utils.data import DataLoader, Dataset
class BaseDatasetShape(Dataset):
def __init__(self, data_root, num_data):
... |
bb65d24810bf31e0d9eb7f93b5e09bc02548b7f57e4a3d9997fcb132bdef2633 | Python | 1,196 | 35 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
1fc43345ed9135dcdebd7a2d1f60433f94672941b251ca90b6cb00ed2278b709 | Python | 1,197 | 35 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
52f9aa4c0c2aad1fd264a4eaf5ca98c4e343e79d0abb6e7ef36515d537ac5ef2 | Python | 1,198 | 36 | import unittest
import os
import random
import shutil
from torcheeg.model_selection import KFoldCrossSubject
from torcheeg.datasets import DEAPDataset
class TestKFoldCrossSubject(unittest.TestCase):
def setUp(self):
shutil.rmtree('./tmp_out/')
os.mkdir('./tmp_out/')
def test_k_fold(self):
... |
73dfc2c761505c76d68ce2ecac5909c35ef439539874bcfd0e3e322a8ca01146 | Python | 1,198 | 33 | from src.conv_onet import models
def get_model(cfg, nice=True):
"""
Return the network model.
Args:
cfg (dict): imported yaml config.
nice (bool, optional): whether or not use Neural Implicit Scalable Encoding. Defaults to False.
Returns:
decoder (nn.module): the network mod... |
a99351236d318e0387bdbc61eb0891467fda466a98c48f4fa95bd760cd5dedff | Python | 1,198 | 39 | import torch
from prosper_nn.models.dhcnn import DHCNN
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
deepness = 3
batchsize = 5
... |
d2d21a34042b7b76c75a9f88f2e81dd58b78897625a5852510594934571f9b7f | Python | 1,198 | 26 | #
# 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,... |
f94fdf46054940624ee2af4682adc2b574f25817bce19ce1ad431288b72ffa05 | Python | 1,198 | 55 | """
An undecorated example of a script that allocates memory in multiprocessing
workers to demonstrate the use of memory_profiler with multiple processes.
Run this script with mprof run -M multiprocessing_example.py
You can then visualize the usage with mprof plot.
"""
import time
import multiprocessing as mp
# Big ... |
10db09be8724994d8c425ca4f56d6a9ae24ba30f14ec05b2c263b884af77bb55 | Python | 1,199 | 44 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from downward import suites
from common_setup import IssueConfig, IssueExperiment
REVS = ["issue551-base", "issue551-v2"]
BENCHMARKS = os.path.expanduser('~/downward-benchmarks')
SUITE = suites.suite_satisficing_strips()
CONFIGS = [
IssueConfig("lama-firs... |
21b0a3a1e1e36b0f2bb9ff04c1b377ac8105ab855e29146fb89e930e6924e495 | Python | 1,199 | 44 | # pylint: disable=too-many-function-args, invalid-name
""" HCP ICA dataset with time-direction labels loading script"""
import numpy as np
import pandas as pd
from omegaconf import DictConfig
from src.settings import DATA_ROOT
def load_data(
cfg: DictConfig,
dataset_path: str = DATA_ROOT.joinpath("hcp_time/... |
398af327ea2b141404d9604ca4f893cfb5b303d708b4e88592d304101f1116b3 | Python | 1,199 | 29 | from .colors import Color
from .old_shapes import Shape
from .textures import Texture
from typing import Optional
class Stimulus:
"""Combination of a shape and a color or texture.
Used to generate the actual stimulus picture."""
def __init__(self, shape: Shape, pattern: Color | Texture,
backgro... |
40f9f219bb6fc2bb8b3aebb6dcbd72f212e84b55a0d1c30a0272e4ea195b8674 | Python | 1,199 | 35 | from typing import Any
import torch
class RoundToFloat(torch.autograd.Function):
@staticmethod
def forward(ctx: Any, *args: Any, **kwargs: Any) -> torch.Tensor:
if len(args) != 3:
raise TypeError(
"apply() takes exactly three arguments "
"(x: torch.Tensor, ... |
54dd4c4f23565c4d5b74809c0a3f3cc41e693b3fc2d11019e0b80ba4010ffe38 | Python | 1,199 | 39 | """GUI wiring for the DeepSlice auto-detect checkbox in the registration tab."""
import os
import sys
PROJECT_ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
if PROJECT_ROOT not in sys.path:
sys.path.insert(0, PROJECT_ROOT)
os.environ.setdefault("QT_QPA_PLATFORM", "offscreen")
imp... |
800287df8b487c03ee26905882c62bb02dd0ba8cd41374d95f20e613f76d5cd8 | Python | 1,199 | 44 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from downward import suites
from common_setup import IssueConfig, IssueExperiment
REVS = ["issue551-base", "issue551-v3"]
BENCHMARKS = os.path.expanduser('~/downward-benchmarks')
SUITE = suites.suite_satisficing_strips()
CONFIGS = [
IssueConfig("lama-firs... |
aa3695d3849ab9715bfaa5d479e35cb037baf3c17e014d998057883d3a999dc0 | Python | 1,199 | 27 | import tensorflow as tf
import numpy as np
# Elman dynamics
class RNN():
def __init__(self, input_size, hidden_size, add_noise=False):
xav_init = tf.contrib.layers.xavier_initializer
self.input_size = input_size
self.hidden_size = hidden_size
self.W = tf.get_varia... |
b63447d639b2bf97d1f0a4dd039b9bfec21bd5f393425ab6bb633bc46940e897 | Python | 1,199 | 22 | import argparse
from eval import main
parser = argparse.ArgumentParser(description='Evaluate few-shot prototypical networks')
default_model_path = 'results/best_model.pt'
parser.add_argument('--model.model_path', type=str, default=default_model_path, metavar='MODELPATH',
help="location of pretrai... |
03bf0bfab62a240062ab2ba17465283cb3753a405b0f266d002b9589fb8eed57 | Python | 1,200 | 27 | import argparse
import sys
from Bio import SeqIO
def do_count(passengers, alignments, countfile):
counts = initialize_counts(passengers)
for line in alignments:
tokens = line.rstrip().split('\t')
if tokens[2] != '*':
counts[tokens[2]] += 1
for key in counts.keys():
count... |
28a19afdee76fa18953307645b63a601824cbd110177dd5dd747073a7c8c4c5a | Python | 1,200 | 26 | #
# 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,... |
30bfd495365f9286a73f42b42b4f20a89107790eb7eaeecdc92abf74fb2b0227 | Python | 1,200 | 28 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
17fa0292c876fbc45ae53454a09513a74345f024444de1c364c19216159b4688 | Python | 1,201 | 52 | import sys
import traceback
import getopt
def main(parameters):
"""
The main function, which starts to software according to the given command line arguments.
:param parameters: the command line parameters:
* -h help
* -c command line
* -g graphic interface
"""
for o,a in parameters:
if o=="-h":
print("... |
1ecebb6e248615b58043ff201d366cc65c4ab073ef0f3890d55c397cb6b5f5de | Python | 1,201 | 31 |
from REACTRL.env_modules.net_framework import *
from REACTRL.env_modules.signal_conv import *
from REACTRL.img_modules.signal_data import train_loader, test_loader
from boss.bo.bo_main import BOMain
from boss.pp.pp_main import PPMain
from datetime import datetime
import pandas as pd
def func(X, model=None, method='ls... |
ef6e56ec8489ce849836d2e710fd45c197bf20c527d57aba34463015b5e0eb79 | Python | 1,201 | 57 | """
A simple log mechanism styled after PEP 282.
Retained for compatibility and should not be used.
"""
import logging
import warnings
from ._log import log as _global_log
DEBUG = logging.DEBUG
INFO = logging.INFO
WARN = logging.WARN
ERROR = logging.ERROR
FATAL = logging.FATAL
log = _global_log.log
debug = _globa... |
fc0d2e916eb04b90c5106cae5f6e523bab5de433f962d4714d188630cfcde38d | Python | 1,201 | 37 | import pandas as pd
import numpy as np
from rpy2 import robjects as ro
from rpy2.robjects import pandas2ri
from rpy2.robjects.packages import importr
from rpy2.robjects.vectors import StrVector, FloatVector
import rpy2.robjects.packages as rpacks
pandas2ri.activate()
R = ro.r
def call_Rpackage(call="function", design... |
feb769edd4eb1bf6fa9f3a16a48009aef0345d6502b958bf374400dec425a03f | Python | 1,201 | 40 | from pathlib import Path
import pytest
from scanpy import settings
from pertpy.metadata._metadata import MetaData
@pytest.fixture
def cachedir(tmp_path):
original = settings.cachedir
settings.cachedir = tmp_path
yield tmp_path
settings.cachedir = original
def test_download_metadata_skips_when_cach... |
1a8b6716a613b7d134249c197a780964e1a41d7ee077c218a366dbb665b8063f | Python | 1,202 | 35 | """Transform PyTorch models to IR.
The translation process is highly customizable.
(`Torch2Ir`)[elasticai.creator.torch2ir.Torch2Ir] is responsible
for the translation process and will call *module handlers* to
extract attributes from modules. These attributes are then
attached to the corresponding nodes in the IR.
E... |
4ebb715694a22de0fb7ecf97f30781c2ad932b46524790b7f7fa108706d27afd | Python | 1,202 | 26 | import torch
import torch.nn as nn
from collections import OrderedDict
def load_video_pretrained_weights(model, video_resnet18_pretrain_path):
state_dict = torch.load(video_resnet18_pretrain_path)['state_dict']
new_state_dict = OrderedDict()
for k, v in state_dict.items():
name = k[7:] # remove 'mo... |
63a8b6235e1db9b594f0073affa9f21d5e683b4fdcc9843982b084a9f241f76d | Python | 1,202 | 48 | import unittest
class TestImports(unittest.TestCase):
@classmethod
def setUpClass(cls):
from neurolib.models.fhn import FHNModel
fhn = FHNModel()
fhn.run()
cls.model = fhn
from neurolib.utils.parameterSpace import ParameterSpace
pars = ParameterSpace({"x": [1... |
77c68eeaa24bc3701575a170b6fbf3c983f83d04cb9cfe7feb6eb536518f278e | Python | 1,202 | 32 | import torch.nn as nn
class Conv2_5d(nn.Conv3d):
"""
Decorater class for Conv2_5d, in which kernel size is (1, K, K) or (K, 1, K) or (K, K, 1).
Args:
unsqueeze_axis: optional, the default axis is -3, resulting in a kernel size of (1, K, K)
Other arguments are the same as torch.nn.Conv3d
... |
869ae6b4a85bc8af676d63ec72dd3eb8903e038495c27b3502e46c685dbcab17 | Python | 1,202 | 26 | #
# 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,... |
db132bbae0a5811a4e4d916fa79a030107d02fa259057083d3dddab5f5838520 | Python | 1,202 | 26 | #
# 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,... |
7f97e4f643486887332b633a48342c180497d76582a52f7018a92aed55385940 | Python | 1,203 | 42 | import importlib
import torch.nn as nn
# from .pdfam import *
# from .lap_experiments import *
def find_module_using_name(module_name):
if module_name == "none":
return None
module_base_path = "models.modules.attentions"
module_filename = module_name + "_module"
if 'pdfam' in module_name:
... |
9acc93f8a129d7871be9c158cc46d68dad8781317236a97156967f7065b7a2e6 | Python | 1,203 | 53 | from __future__ import annotations
import csv
from pathlib import Path
from typing import Iterable, Any
def save_configuration_csv(
output_dir: str | Path,
rows: Iterable[dict[str, Any]],
) -> Path:
"""
Save the effective configuration used in the analysis to:
<output_dir>/Technical_Record/c... |
cc517069fe8391649d051b3987716aadcf9e1716c9542ba25ccdf5ca2152f464 | Python | 1,203 | 34 | import os
import sys
import logging
import functools
from termcolor import colored
@functools.lru_cache()
def create_logger(output_dir, dist_rank=0, name=''):
# create logger
logger = logging.getLogger(name)
logger.setLevel(logging.DEBUG)
logger.propagate = False
# create formatter
fmt = '[%(... |
0870e680fdf176ee39b800328ceddfa920d86bf1ff7b839b9344ea792274868a | Python | 1,204 | 29 | from elasticai.creator.base_modules.tanh import Tanh as TanhBase
from .precomputed_module import PrecomputedModule
class Tanh(PrecomputedModule):
def __init__(
self,
total_bits: int,
frac_bits: int,
num_steps: int,
sampling_intervall: tuple[float, float] = (-float("inf"), ... |
2e3e57986af56c70026f76da27f875a3699092f3ee7e0e721e6bd552e842b185 | Python | 1,204 | 24 | # 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... |
3dae2205e814d7b991110cf12ad2a848d0a9e60dda27d4174007b643e4034315 | Python | 1,204 | 38 | from typing import (Any, Iterable, Literal, Optional, Protocol, Union,
runtime_checkable)
import numpy as np
from numpy.typing import NDArray
__all__ = ['Recording', 'RealArray']
RealArray = Union[NDArray[np.integer], NDArray[np.floating]]
@runtime_checkable
class Recording(Protocol):
"""I... |
58d4e65f063df8baef4a0293b288a0b6cd81c5771b0b421bc2cea924a2f00567 | Python | 1,204 | 36 | import xlrd # version 1.2.0
import numpy as np
def read_excel(filename, sheetname):
wb = xlrd.open_workbook(filename=filename)
sheet = wb.sheet_by_name(sheetname)
nrow = sheet.nrows
ncol = sheet.ncols
return sheet, nrow, ncol
def read_excel_array(filename, sheetname):
con_sht, nrow, ncol = read_excel(filena... |
886e522e7e5e1bea60a07d1032ddc3b1c2f526fc233a051a575fb608e17c25dd | Python | 1,204 | 37 | import bpy
from bpy.types import Collection
from databpy.collection import create_collection
def mn() -> Collection:
"Return the 'MolecularNodes' collection, creating it first if required"
return create_collection("Molecular Nodes")
def data() -> Collection:
"Return the MolecularNodes/data collection an... |
e38de355749d165314bde99c94f3cee7d71d627ccb5b17932063f9d5e0ac70c4 | Python | 1,204 | 48 | # Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under th... |
f1deada161c5dbd1f7f70b93f7b95a8b4265719a1b9ed71595ef1f5d823d36c8 | Python | 1,204 | 29 | from elasticai.creator.base_modules.silu import SiLU as SiLUBase
from .precomputed_module import PrecomputedModule
class SiLU(PrecomputedModule):
def __init__(
self,
total_bits: int,
frac_bits: int,
num_steps: int,
sampling_intervall: tuple[float, float] = (-float("inf"), ... |
f6793412af87bc643b6f9b6912dfa528b6273d7b57d3d8da80e3e71bb803db9c | Python | 1,204 | 34 | # SPDX-FileCopyrightText: 2024 Blue Brain Project / EPFL
#
# SPDX-License-Identifier: AGPL-3.0-or-later
# Function for comparing per-cell reliabilities using ROC analysis
# Basic functions
def renormalize_samples(sampleA,sampleB):
"Renormalize the two samples together to lie between 0 and 1"
t_min=np.amin([... |
5b86570dbac2d5db646ae0963861641611817d171441aaf5a1e77aef2dc064cd | Python | 1,205 | 24 | # 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... |
740891679e95971f20f064e5a355e88f39ac93ec840367cc24e175eb1da566fa | Python | 1,205 | 45 | from __future__ import absolute_import, division, print_function, unicode_literals
import argparse
import logging
import os
import sys
import tensorflow as tf
import matplotlib.pylab as plt
from tensorflow.keras import layers
from tensorflow.keras import models
import numpy as np
import PIL.Image as Image
import glob
... |
2c18034822b2c104413719944a823ac31e70e5c83d4f98ce443f5623f198317b | Python | 1,206 | 35 | import os
import tempfile
import warnings
from replicate.client import Client
from cog import ExperimentalFeatureWarning, Input, Path, Secret
warnings.filterwarnings("ignore", category=ExperimentalFeatureWarning)
def run(
image: Path = Input(description="Input image to test"),
replicate_api_token: Secret =... |
3111f79f76c394c89d8037f4a4c4356ab8cf2823f77929ec57972e00d5e974c4 | Python | 1,206 | 31 | # 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... |
454490c008bfa4dbf3fe29931e59bdb1f3330124061c965a27886f1895ae2bf1 | Python | 1,207 | 28 | """
Main run function for getting (and saving) connectivity matrix
last modified: András Ecker 09.2022
"""
import logging
from conntility.connectivity import ConnectivityMatrix
from assemblyfire.config import Config
from assemblyfire.utils import get_bluepy_circuit_from_root_path
L = logging.getLogger("assemblyfire"... |
5fe53c4c8bec8fb86d7046a2c281eed6fdbe150c1c88d57c0fde085a9011c582 | Python | 1,207 | 39 | import torch
from prosper_nn.models.crcnn import CRCNN
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
n_branches = 3
batchsize = ... |
684c28a9bdebaca6cba34a1cf044b7bbd097a209ccd0f98c5f62e88891c96992 | Python | 1,207 | 38 | import os
from torchdrug import data, utils
from torchdrug.core import Registry as R
@R.register("datasets.ClinTox")
@utils.copy_args(data.MoleculeDataset.load_csv, ignore=("smiles_field", "target_fields"))
class ClinTox(data.MoleculeDataset):
"""
Qualitative data of drugs approved by the FDA and those that ... |
b37cf37dd2b9c1d827d6252507df4e202ddba2dfbf47891f59b4f87b5038bf1a | Python | 1,207 | 45 | import jax.numpy as jnp
import jax.scipy as jsc
from jax import jit
from . import utils
@jit
def ln(input, filter):
try:
outputLinear = utils.conv(input, filter)
except:
outputLinear = input
return outputLinear[:input.shape[0], :]
@jit
def ln1d(input, filter):
try:
outputLinea... |
25cfda5113dc130ba174eb5ee6983294a7cd00a88315431c325f21981203747e | Python | 1,208 | 35 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
3794612ba4982f53f7a57e89d5eff168b79e5781703336fc7954545ca3a56f17 | Python | 1,208 | 53 | from pathlib import Path
from typing import TypedDict, Union
class Params(TypedDict):
chunk_size: int
rescale: bool
rescale_value: float
lowpass: bool
common_reference: str
spike_duration: float
amp_avg_duration: float
threshold: float
min_avg_amp: float
AHP_thr: float
neig... |
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