sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
f4d394bb0df8c8ac23115c1c1f7e99577422c65c92484113681cbbc1e76b5f37 | Python | 2,141 | 82 | # -*- coding: utf-8 -*-
# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
"""
Base module variables
"""
from ._version import get_versions
__version__ = get_versions()["version"]
del get_versions
__author__ = "tedana developers"
__copyright__ = "Copyrig... |
2ba937745a31bd81f7d35ce305d979364e5b469c720859237d79989c6b6cde42 | Python | 2,142 | 79 | import random
from torchvision.transforms import functional as F
class Compose(object):
def __init__(self, transforms):
self.transforms = transforms
def __call__(self, image):
for t in self.transforms:
image = t(image)
return image
def __repr__(self):
format_st... |
930f4043f5022bbc56b6a0c817415f327d208107ed0d42e209d6160f5f2e2772 | Python | 2,142 | 80 | """Core recipes for Psi4."""
from __future__ import annotations
from importlib.util import find_spec
from typing import TYPE_CHECKING
from monty.dev import requires
from quacc import job
from quacc.recipes.psi4._base import run_and_summarize
has_psi4 = bool(find_spec("psi4"))
if TYPE_CHECKING:
from typing imp... |
a68dbdfc5d4cb7ca99a6c1635fb115c004f4c9d0bf35b5626bd8158bb47fc170 | Python | 2,142 | 59 | # Copyright 2017 Elisey Zanko
#
# 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, sof... |
c0679c66d0a9a85a349c0b4e7b31da8c2e84a145be79f55acc3941c8744d4543 | Python | 2,142 | 70 | import os
import toml
import logging
import jobflow as jf
from ase.io import read
from quacc import get_settings
from quacc.recipes.newtonnet.ts import ts_job, irc_job, neb_job
# Load configuration from TOML file
config = toml.load('inputs_using_newtonnet.toml')
# Constants from TOML file
REACTANT_XYZ_FILE = config['... |
cce7c65c22d39fe291126ce597981af7fde899ac91791a855a437e8ee2f31416 | Python | 2,142 | 72 | import torch
import pandas as pd
class SubsetDataset(torch.utils.data.Dataset):
def __init__(self, X:pd.DataFrame, y:pd.DataFrame):
super().__init__()
self.X= X
self.y= y
def __len__(self):
return len(self.X)
def __getitem__(self, index):
return self.X[index], se... |
ce9e605584c15c14eb360bf77ba5d5c63ac80bb12e7a64cb4e48bfb2096433ee | Python | 2,142 | 73 | # %%
import os
os.environ['CUDA_VISIBLE_DEVICES'] = "0"
import numpy as np
import torch
import torch.nn as nn
from torch_geometric.data import DataLoader
import argparse
from scipy.stats import spearmanr
from metrics import get_cindex
from dataset import *
from model import MGraphDTA
from utils import *
def val(model... |
d0061dfd2d8ee66d8aed752780b516250c638d669392fe2cad22b33adbfeccb2 | Python | 2,142 | 76 | """Processes ECoG and LFP data to generate Granger causality values."""
import os
import sys
from pathlib import Path
cd_path = Path(__file__).absolute().parent.parent
sys.path.append(os.path.join(cd_path, "coherence"))
from coh_connectivity_processing import granger_processing
from coh_handle_files import load_file... |
3ee7f3cd2ad5334fd4b9aa3dfb70305ac3197199a79513e2d0865c50fa80baba | Python | 2,143 | 72 | """This module contains functions to evaluate the training results."""
import numpy as np
import pandas as pd
from sklearn.metrics import accuracy_score
from sklearn.tree import DecisionTreeClassifier
def _proc_data(df, continuous_cols, label_name=None):
"""Transform dataframe into matrix of features and its lab... |
b0a20cb2a75df54ea98086e7b555f8956f1e28370401d2bbaa4eecb798d088f2 | Python | 2,143 | 61 | import os
import unittest
import tempfile
from torcheeg.io import MetaInfoIO
class TestMetaInfoIO(unittest.TestCase):
def setUp(self):
self._directory = tempfile.TemporaryDirectory()
self.addCleanup(self._directory.cleanup)
self._io_path = self._directory.name
def test_init(self):
... |
b338d05b30b0613c0b741a21ec3c3ffb8af9c9f90896a45616b8e377769dcdf8 | Python | 2,143 | 62 | import warnings
from elasticai.creator.ir2vhdl import Node as VhdlNode
from .clocked_combinatorial import ClockedInstance
from .node_factory import (
InstanceFactoryForCombinatorial,
)
@InstanceFactoryForCombinatorial.register()
def sliding_window(node):
return SlidingWindowNode(node)
def _check_input_out... |
b4c3c60cf1ef1a704df5e1be958d65fe8ea7759b73e467ec71059c3491413dea | Python | 2,143 | 71 | import os
import toml
import logging
import jobflow as jf
from ase.io import read
from quacc import get_settings
from quacc.recipes.newtonnet.ts import ts_job, irc_job, geodesic_job
# Load configuration from TOML file
config = toml.load('inputs_using_newtonnet.toml')
# Constants from TOML file
REACTANT_XYZ_FILE = co... |
c2ff9e514d42ed2bef39d0962ad4f085b1ee279dd58cbc7a9d63caf339d57277 | Python | 2,143 | 65 | import os
import numpy as np
import pandas as pd
from click.testing import CliRunner
from scbs.cli import cli
from scbs.diff import parse_cell_groups
def test_parse_cell_groups():
group_df, groups = parse_cell_groups(
"tests/data/tiny_diff/cell_groups.csv", "tests/data/tiny_diff/"
)
assert len(g... |
d77b562c1cb742117c6e087b5d00dbe7ece258b350d4795031ca60ace6aa62a4 | Python | 2,143 | 91 | # Node-group asset "LCh to Color" (GeometryNodeTree), dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# _build_group() is the source of truth: the docstring, __init__ and accessors are regenerated from it on the next dump.
from typing import TYPE_CHECKING
... |
db162f050d31e4768f6c481b02a695352ef0214029cee07fcc30aa1dcbde0c91 | Python | 2,143 | 55 | from dataset import TCGA_Project_Dataset, TCGA_Program_Dataset, METABRIC_Dataset
from utils.logger import setup_logging
from pathlib import Path
from utils import set_random_seed
SEED = 1126
set_random_seed(SEED)
if __name__ == '__main__':
setup_logging(Path('./Logs/Tests/'))
project_id = 'TCGA-PRAD'
dow... |
fe2f7a386333d9fce8e1722940eaa313b82f61e3e5a1fb8c4795aefd9bb2943a | Python | 2,143 | 26 | """posthoc_rival_disagreements_2026-09-30.py (descriptive, post hoc). The rival counts 1,208 neurons with a literature
GABA/glutamate identity that are excitatory in Shiu et al.'s file and 1,399 literature-cholinergic neurons that are
inhibitory. How many of them are the default (no transmitter call -> the file's rule)... |
0ef3355a81d9b5ec0a9b000bf9181d6df7627ae5c091c31e00700a6f26b00a11 | Python | 2,144 | 89 | # Node-group asset "Force Gravity" (GeometryNodeTree), dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# _build_group() is the source of truth: the docstring, __init__ and accessors are regenerated from it on the next dump.
from typing import TYPE_CHECKING... |
f55966e7c555e643ed7deb5c8488f963ea0077e1103cb12c59ab80f60db03d13 | Python | 2,144 | 58 | # 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... |
8605dfb54f9e6aee0c5b11d22eab933337a962ae413c2db3842921377825072f | Python | 2,145 | 69 | """HTTP cache implementation.
"""
import os
from contextlib import contextmanager
from typing import Generator, Optional
from pip._vendor.cachecontrol.cache import BaseCache
from pip._vendor.cachecontrol.caches import FileCache
from pip._vendor.requests.models import Response
from pip._internal.utils.filesystem impo... |
bec88125662d5eca028456d03f5e6afcba23ea90cf284337e8bac1421e984778 | Python | 2,145 | 70 | import numpy as np
import scipy.stats as stats
def multregr(_X, _y, a = 0.05, opts = None):
# function [hatb, bci, haty, hatM, covM, hats2, t, rsq, F, pF, r] = multregr(X, y, a);
#
# Performs multivariate regression of input data X for output vector y, assuming a linear
# relationship y = Xb, giving confidence... |
ef85dbef8276993bc4c4099dac081ae11b8784c6ecd338b66030b74d3376eb4f | Python | 2,145 | 69 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
A very generic case where the same morphology on different file formats
is loaded in LFPy using a generic template specification, defined by
file LFPyCellTemplate.hoc
Execution:
python example_LFPyCellTemplate.py
Copyright (C) 2017 Computational Neuroscience Grou... |
eff8bc57107fce573f22fb9c6193d934dbb329042e3276433d57cbd30c9f2f56 | Python | 2,145 | 64 | import torch
from torch import nn
from torch.nn import functional as F
from torchdrug import layers
class ConditionalFlow(nn.Module):
"""
Conditional flow transformation from `Masked Autoregressive Flow for Density Estimation`_.
.. _Masked Autoregressive Flow for Density Estimation:
https://arxi... |
a1e996407757f4120273001acea0f7830b4e07629b650f5e0ceb3fd19cb65997 | Python | 2,146 | 59 | import numpy as np
import pytest
from scipy import sparse
from pertpy.tools.core import _is_raw_counts
@pytest.mark.parametrize(
"data,expected",
[
# Dense arrays - positive cases
(np.array([[1, 2, 3], [4, 0, 5]]), True), # integers with zeros
(np.array([[0, 0], [0, 0]]), True), # a... |
62c6f1309e1593f5a8245e1f8647a5c02c130ff84ee768209ea1c70274bdd1c5 | Python | 2,147 | 83 | # Syncopy benchmark suite.
# See "Writing benchmarks" in the asv docs for more information.
import syncopy as spy
from syncopy.synthdata.analog import white_noise
class SelectionSuite:
"""
Benchmark selections on AnalogData objects.
"""
def setup(self):
self.adata = white_noise(nSamples=25000... |
a9b3a85d10ddc54e70545359b9ceeafba9de092156edc1a9b581c540c8a5e5f9 | Python | 2,147 | 81 | """VHDL implementation of HDL abstractions."""
from elasticai.creator.hdl_ir import Node
from elasticai.creator.ir2vhdl import (
EntityTemplateDirector,
Instance,
LogicSignal,
LogicVectorSignal,
NullDefinedLogicSignal,
Signal,
)
from .protocols import HDLInstance, HDLTemplateDirector, Template... |
d8e316b629c7cc73f8d99d5bcc5cb77dd4940903f895a93776f87f5b977d5660 | Python | 2,147 | 76 | import pytest
import torch
import elasticai.creator.nn.fixed_point as nn_creator
from elasticai.creator.arithmetic import FxpArithmetic, FxpParams
from elasticai.creator.nn import Sequential
from elasticai.creator.nn.fixed_point.math_operations import (
MathOperations,
)
from tests.integration_tests.nn.fixed_point... |
dcf81709b8103fc0774efb50c696d24dafc00984554a093c5cb51d8b56efa210 | Python | 2,147 | 78 | # 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... |
e2f287acbb6be4c744eddc9b588e1fe86e572549781600ad3d8486ab9217bf90 | Python | 2,148 | 48 | # coding: utf-8
from .config import cfg
import torch
from itertools import product as product
from math import ceil
class PriorBox(object):
def __init__(self, image_size=None):
super(PriorBox, self).__init__()
# self.aspect_ratios = cfg['aspect_ratios']
self.min_sizes = cfg['min_sizes']
... |
09629e0a2632653f7e67ad272dee6c608a027474e63b0b87baf0efc0f6661de5 | Python | 2,149 | 49 | import pandas as pd
import numpy as np
import os
import pysam
# Step2: Get hg38 Reference and Altered SNC fa files of DA-cCREs
fa = pysam.FastaFile("../hg38.fa")
SNCs_df = pd.read_csv('../SNCs_hg38_995-matched.txt', sep='\t')
SNCs_df['Ref'] = SNCs_df['Ref'].map(str.upper)
SNCs_df['Anc'] = SNCs_df['Anc'].map(str.uppe... |
0c8a75f7781b79269ca2bb571e08b2ff7fc596e88d669bbc9cfc7b538e698f53 | Python | 2,149 | 58 | """Bookmark add / remove / activate slots for the viewer.
Small cohesive cluster - pulled into a mixin so viewer.py doesn't
have to carry it. Consumer class must provide ``self._bookmarks``
(a ``set[int]``), ``self._bookmark_list`` (a QListWidget),
``self._slice_slider`` (QSlider), ``self.annotation``,
``self.cu... |
f52cc445015059f152f077cfb8fe90e4b48a248ec40514bcba8eb6c4becbe337 | Python | 2,149 | 56 | """Adapter for lifelines survival predictions."""
from __future__ import annotations
from abc import ABC
import pandas as pd
from SurvivalEVAL.evaluations.custom_types import NumericArrayLike
from .pycox_evaluator import PycoxEvaluator
class LifelinesEvaluator(PycoxEvaluator, ABC):
def __init__(
self... |
a237f5ad3dec3755ab0d8acb57107dc764203e9f22bfa8e43e5feeec2ec73bd4 | Python | 2,151 | 76 | ##
# \file write_random_motion_transforms.py
# \brief Create and write random motion transforms
#
# \author Michael Ebner (michael.ebner.14@ucl.ac.uk)
# \date November 2017
#
import numpy as np
from niftymic.utilities.input_arparser import InputArgparser
import niftymic.validation.motion_simulator as m... |
a4d8b153abdfefe6c3e3ebe30890ad52f47d35197f1e7e347cb76464e1fae0f1 | Python | 2,151 | 54 | # read in the data
import numpy as np
import torch
def ReconstructFrame(data, mask, shape, fill_value = np.nan ):
temp_data = np.empty((*shape,data.shape[-1]))
temp_data[:] = fill_value
temp_data[mask] = data
return temp_data
def pass_through_model_batch(coords, latents, model, x_normalizer, y_normal... |
b1fdef7389c40d21906211c2f6f48e6a0a9a1a657863d60983a62bda31315473 | Python | 2,151 | 53 | from unittest import TestCase
from pyseg.vtk_ext import vtkFilterRedundacyAlgorithm
from pyseg.globals import *
import vtk
__author__ = 'martinez'
class TestVtkFilterRedundacyAlgorithm(TestCase):
def test_Execute(self):
reader = vtk.vtkXMLPolyDataReader()
# reader.SetFileName('../data/anchors.v... |
d27c771023e7425793889abe3438e12523d93947dd54322a4d2e0e81a70ff8e2 | Python | 2,151 | 64 | # 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... |
0961185467f45ff98287029f60e58b0e934381ee7950f4ccdbc3d41d8fd0a609 | Python | 2,152 | 71 | import inspect
import types
import typing
from typing import TYPE_CHECKING
import bpy
from PIL import Image
if TYPE_CHECKING:
from ..entities.molecule import MoleculeAnnotationManager
from ..session import MNSession
def get_all_class_annotations(cls) -> dict:
"""Get all the annotations from the class inc... |
975f0ed97a553ff12dcd7ed8c4481836eb77f2f88e81b3cff366644b0d99a276 | Python | 2,152 | 83 | import os
import pandas as pd
from calvados.cfg import Config, Job, Components
import subprocess
import numpy as np
from argparse import ArgumentParser
parser = ArgumentParser()
parser.add_argument('--name',nargs='?',required=True,type=str)
parser.add_argument('--pH',nargs='?',required=True,type=float)
args = parser.p... |
c5e303fcb0a7b2328006b76bf1a8c011e3de53ef5942e102ed1db5e6c92d20ff | Python | 2,153 | 78 | import pytest
import torch
import elasticai.creator.nn.fixed_point as nn_creator
from elasticai.creator.arithmetic import FxpArithmetic, FxpParams
from elasticai.creator.nn import Sequential
from elasticai.creator.nn.fixed_point.math_operations import (
MathOperations,
)
from tests.integration_tests.nn.fixed_point... |
08602aedf5c35b5e5ece816bac13d051cd1eb359456da3f9e4f3c209558c3d2b | Python | 2,154 | 60 | import pandas as pd
import torch
import torch.nn as nn
import argparse
# Parse command-line arguments with default values
parser = argparse.ArgumentParser(description='Run MLP model on input data.')
parser.add_argument('--input_file_path', type=str, default='./validation/intact_positive_PPI_2024-07-11-08-09.GNN_input.... |
66371b57fedb6fb84ea7832de629c96d48c10dd90d947522223cb29811dd5d28 | Python | 2,154 | 55 | # EyeNED OCT-ONH segmentation and feature extraction
# Copyright (C) 2024 Erasmus MC
# 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, either version 3 of the License, or
# (at your optio... |
505f7625d9de3c692301f4601e86c2232a0f05f5f0fa453803097285127e5486 | Python | 2,155 | 59 | import numpy as np
import scipy.sparse as sp
import torch
import torch.utils.data as data_utils
import networkx as nx
import random
class EdgeSampler(data_utils.Dataset):
'''
The framework code for class EdgeSampler is borrowed from https://github.com/shchur/overlapping-community-detection/blob/master/nocd/sa... |
f6c17b181870034ccbd6be798abd90f29695b110b8603051a156a6b2228483ce | Python | 2,155 | 72 | # Special token ID for End-of-Sequence
EOS_TOKEN_ID = 0
# Offset is the index at which ordinary vocabulary tokens start
VOCAB_OFFSET = 1
class Tokenizer(object):
"""Docstring for Vocab."""
def __init__(self, config):
"""Mapping from symbols to numbers
:vocab: dict-like from str to int
... |
ff7954a7569a4a3c5602cc05370ba1ba9098531e19c6c1085f8b39c83ba5afb4 | Python | 2,155 | 82 | """Constructor for spin-echo spectrum sequence."""
from math import pi
import pypulseq as pp
from console.utilities.sequences.system_settings import system as default_system
def constructor(
rf_duration: float = 200e-6,
dead_time: float = 0.,
num_samples: int = 256,
acq_bandwidth: float | int = 20e3... |
423e413e760cdfcd2a50060b17024b6258041d43f568cf614533d0ee972461dc | Python | 2,156 | 69 | # 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... |
b6373ccee6f70f75042afa935497aa255b61cbed6dbfe8a9ee3e5dd7e0ef3ff2 | Python | 2,156 | 60 | from typing import Any
from torch import Tensor
from torch.nn import Conv1d as TorchConv1d
from torch.nn import Module
from torch.nn.utils import parametrize as P
class Conv1d(TorchConv1d):
"""A 1d convolution.
The weights and bias are fake quantized during initialization.
Make sure that math_ops is a mo... |
2003fd49b3b86e4ad3926e69ee9c48513f751016f070612916dd6a598ea1d746 | Python | 2,157 | 61 | from typing import Any
from torch import Tensor
from torch.nn import Conv2d as TorchConv2d
from torch.nn import Module
from torch.nn.utils import parametrize as P
class Conv2d(TorchConv2d):
"""A 2d convolution.
The weights and bias are fake quantized during initialization.
Make sure that math_ops is a mo... |
8e5b3f4759c631a3b56f0ae51d1bfb876174e0a4951c91217b9abfef02be2619 | Python | 2,157 | 34 | """posthoc_brian2_gap_2026-10-02.py (POST HOC, after R1 of PREREG-2026-10-02-KEYSTONE-ROBUST failed)
Why does one v2LN30 (root ...5919) break 29 of 48 channels in my spiking cut-out but only 1 of 8 in Shiu's Brian2 code on the
whole brain? Same 8 channels: (a) my simulator on the cut-out, 2 trials and 5 trials; (b) my ... |
ab939a397e833055f328f076b68b6c45d8734d58092d06c39f2ba0c89fde4612 | Python | 2,158 | 76 | import pytest
import torch
import elasticai.creator.nn.fixed_point as nn_creator
from elasticai.creator.arithmetic import FxpArithmetic, FxpParams
from elasticai.creator.nn import Sequential
from elasticai.creator.nn.fixed_point.math_operations import (
MathOperations,
)
from tests.integration_tests.nn.fixed_point... |
bfcfaa2c3a4b663ee70f937f2e7a19bb98e7074fde6322c7ebe83912b7fb70a3 | Python | 2,158 | 54 | from collections import defaultdict
def assign_names_from_annotations(neuron_data):
token_to_cell_counts = defaultdict(int)
cell_to_potential_names = defaultdict(list)
for rid, nd in neuron_data.items():
token_to_cell_counts[nd["group"]] += 1
cell_to_potential_names[rid].append(nd["group"... |
262514cad5e64481d9d5112364a3732fe86c33f5a464aa4f54ae1894669e5309 | Python | 2,159 | 36 | """
Created on Tue Jun 28 02:32:18 2022
@author: Haotian Teng
"""
import toml
import numpy as np
import seaborn as sns
from matplotlib import pyplot as plt
from xron.nrhmm.hmm_relabel import get_effective_kmers
chunk_control = np.load("/home/heavens/bridge_scratch/ime4_Yearst/IVT/control/rep1/kmers_xron_4000_noise/c... |
54487a0e1b525a75fab9427a27d6bfde0e2246a506521bc0ba1adc8342cb160d | Python | 2,159 | 51 | """Shared non-PIR test fixtures.
The orientation/permutation bugs this repo has hit (``_reorient_voxel_points``)
all stayed hidden because the default fixtures are PIR (the Allen CCF ships PIR,
which is the identity permutation). A test suite that only exercises the
symmetric default certifies exactly the configu... |
6bc6ea68181b033c56342feeb01514baa6fe31a94e2a0d5dcb76a83bae3fa900 | Python | 2,159 | 59 | #!/usr/bin/env python
"""The setup script."""
from setuptools import setup, find_packages
with open("README.rst") as readme_file:
readme = readme_file.read()
with open("HISTORY.rst") as history_file:
history = history_file.read()
requirements = []
test_requirements = []
setup(
author="Mitchell Robert... |
6df2f07b48d4348789c6c59552d4928cade5adacb1279dc9a9c1aaf725b11e02 | Python | 2,159 | 61 | # MIT License
# Copyright (c) 2023 Qiyun Wu
# 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... |
0934fb10034e7abde381af5ab22f5fa0172c5046106e3967d0d0bdd1f48c6d4d | Python | 2,160 | 76 | import pytest
import torch
import elasticai.creator.nn.fixed_point as nn_creator
from elasticai.creator.arithmetic import FxpArithmetic, FxpParams
from elasticai.creator.nn import Sequential
from elasticai.creator.nn.fixed_point.math_operations import (
MathOperations,
)
from tests.integration_tests.nn.fixed_point... |
bcaaf30611a863013263e18bd8a6e6aa0f141a7d27de8ed7d7d24a44e00b920e | Python | 2,161 | 58 | from itertools import combinations, product, permutations
from scipy.spatial.kdtree import KDTree
import numpy as np
from motion_planners.utils import INF, compute_path_cost, get_distance
def compute_median_distance(path1, path2):
differences = [get_distance(q1, q2) for q1, q2 in product(path1, path2)]
retur... |
348b9380fea5bb9282fc21e76dcc1a5071913bb2c7c82cd1bc7b6d4dc4e09315 | Python | 2,162 | 73 | """
Tests module distance
# Author: Vladan Lucic
# $Id$
"""
from __future__ import absolute_import
__version__ = "$Revision$"
from copy import copy, deepcopy
import unittest
import numpy
import numpy.testing as np_test
import scipy
#from pyto.segmentation.test import common
from pyto.segmentation.distance import... |
717efb8e7a2a83b8474ac1bc107e70d07d84942d1eab563450492b2d06e39da7 | Python | 2,162 | 64 | """Run mean-field theory
------------------------
This example script shows a mean-field theoretical analysis using for network
parameters using
NNMT - the Neuronal Network Meanfield Toolbox (https://github.com/INM-6/nnmt).
"""
import os
import numpy as np
from mesocircuit import mesocircuit_framework as mesoframe
im... |
254de89e75226333d5ad3164f572286b9a2e260f08402e9682172d0113840f30 | Python | 2,163 | 76 | import tensorflow as tf
import numpy as np
import pytest
from pinn.networks.pinet import PiNet
from pinn.networks.pinet2 import PiNet2
from utils import rotate
class TestEquivar:
def test_pinet(self, mocked_data):
pinet = PiNet(
atom_types=[0, 1],
)
for batch in mocked_data:
... |
3c47ef33f7e4bd3f8965a9e9651f1bce7307250288ca21c1d1aa74447129d94f | Python | 2,163 | 91 | # Node-group asset "OKLab to LCh" (GeometryNodeTree), dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# _build_group() is the source of truth: the docstring, __init__ and accessors are regenerated from it on the next dump.
from typing import TYPE_CHECKING
... |
9558752b2fc33a186ac769a93be17d1d65984932b8a90107706313cb4b995029 | Python | 2,163 | 71 | # 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... |
4114d86d447014284f5694c76cfebdb72882dc2163ddc76bb39aed11c6d2d7df | Python | 2,164 | 71 | import sys, math,copy
from pybioshell.core.data.io import find_pdb
from pybioshell.core.data.basic import Vec3Cubic
from pybioshell.std import vector_core_data_basic_Vec3Cubic
if len(sys.argv) < 3 :
print("""
Reads PDB file with wrapped coordinates (from simulation with periodic boundary conditions), unwraps th... |
477819ab5ee4d195e159982d6d0d0df2820152a6fa63f15b551199e82ddd86b6 | Python | 2,164 | 63 | from elasticai.creator.file_generation.savable import Path
from elasticai.creator.file_generation.template import (
InProjectTemplate,
module_to_package,
)
from elasticai.creator.vhdl.auto_wire_protocols.port_definitions import create_port
from elasticai.creator.vhdl.design.design import Design
from elasticai.c... |
ad1c86cae379cd3117ac5c04dfb50c2ddd15804858f407428967f965d419763e | Python | 2,164 | 74 | """VICReg loss module.
Copyright (c) 2024 University of Michigan. All rights reserved.
Licensed under the MIT License. See LICENSE for license information.
"""
import torch
from torch import nn
import torch.nn.functional as F
def off_diagonal(x):
n, m = x.shape
assert n == m
return x.flatten()[:-1].view... |
8fd9976dd3b5f802b858ff2a18ca506efd38918ca5cb712fbfecf02ecc836e69 | Python | 2,165 | 73 | # 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... |
c452b03e5f93eb543a9c60249e068d2f483e881975b5a70763bd57f1528693dd | Python | 2,165 | 86 | import os
import sys
import ast
import tempfile
from contextlib import contextmanager
from rdkit import RDLogger
def input_choice(prompt, choice=("y", "n")):
"""
Print a prompt on the command line and wait for a choice.
Parameters:
prompt (str): prompt string
choice (tuple of str, opti... |
1c2b0592c66924b7933f734493f9e0ac079755146d4ebb7287d78e001a113f80 | Python | 2,166 | 99 | import re
from ._functools import method_cache
# from jaraco.text 3.5
class FoldedCase(str):
"""
A case insensitive string class; behaves just like str
except compares equal when the only variation is case.
>>> s = FoldedCase('hello world')
>>> s == 'Hello World'
True
>>> 'Hello World'... |
72bd912e4cdfcb57456d64396fe5d7a05fdf0b46c911bf9996dae4d77572621b | Python | 2,166 | 68 | import matplotlib
matplotlib.use("Agg")
import torch
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
import yaml, io
with open("./config/simul_study_config.yaml", 'r') as stream:
config= yaml.safe_load(stream)
config["default_path"]= str(config["default_path"])
config["split"]= float(c... |
e109dcab5688dd7b985ab63699004c3d8d9909806c96e1197ad0583e38284f3a | Python | 2,168 | 46 | 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.model import standardize
class TestStandardize(unittest.TestCase):
def setUp(self):
self.df = pd.DataFrame({
'etot': [1, 2, 3]... |
2ed7df7a62ce162e654c29f71b06411e7398155e581cd0fa68b9de658820f318 | Python | 2,170 | 75 | """
Script for loading Google's Open Images dataset into FiftyOne and saving as a
persistent Dataset.
| Copyright 2017-2022, Voxel51, Inc.
| `voxel51.com <https://voxel51.com/>`_
|
"""
import argparse
from pathlib import Path
import sys
sys.path.append(str(Path(__file__).resolve().parent.parent))
from error_analysis... |
f607fb1febdfd221fe447162c8a5d3f3f95a7283ddf2f2ae9035b13c6adc1577 | Python | 2,170 | 74 | import pytest
import requests
from pertpy.data import _dataloader
@pytest.fixture(autouse=True)
def _no_sleep(monkeypatch):
"""Keep retries instant so the tests never actually wait."""
monkeypatch.setattr(_dataloader.time, "sleep", lambda _seconds: None)
def test_download_retries_on_transient_error_then_su... |
da6ed9443d748ed42eb6205842db2b9e1320cdeb15f81b0073ec3133649783d9 | Python | 2,171 | 70 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment, RelativeScatterPlotReport
DIR = os.path.dirname... |
079fb1466fe136952e047df86ea591d7afa68536dd4b02a68239ea1ccd5a7c41 | Python | 2,172 | 102 | from __future__ import annotations
from quacc import flow, job, subflow
def test_decorators(tmp_path, monkeypatch):
monkeypatch.chdir(tmp_path)
@job
def add(a, b):
return a + b
@job
def mult(a, b):
return a * b
@job
def make_more(val):
return [val] * 3
@sub... |
6639b62068aa99d260dbeed192823e869934e503533eba2d606ab2b8acd7820d | Python | 2,172 | 60 | #
# 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,... |
778c9ef99c754672ff05ca857bc4635ded946cfd0f480e8590dd0c15530847f8 | Python | 2,172 | 61 | import sys
import os
import re
def CenterPrint(tmp_filenm,tmp_rep):
os.chdir('distances')
fly_list = []
for file_nm in os.listdir('.'):
if file_nm.startswith('fly-'):
fly_list.append(file_nm)
fly_list = sorted(fly_list)
f_out_nm = '_'.join([tmp_filenm,str(tmp_rep),'centroid.txt'... |
f4deb42739085b257ba577e54528366c10e9cedafa910a02663678d5b1015b8d | Python | 2,173 | 68 | """
Optuna example that demonstrates a pruner.
In this example, we optimize a classifier configuration using scikit-learn. Note that, to enable
the pruning feature, the following 2 methods are invoked after each step of the iterative training.
(1) :func:`optuna.trial.Trial.report`
(2) :func:`optuna.trial.Trial.should... |
59d55ea3070539b42de7e0c542b281408f93508c1d234d3a3b07085bce105cde | Python | 2,174 | 74 | # Import libraries
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
from torch.utils.data import Dataset, DataLoader
import torch.nn.functional as F
import matplotlib.pyplot as plt
import os
import pickle
import numpy as np
from sklearn import metrics
from sklearn.model_... |
928f1bfd17e1689e6cb23b034cbbf73555145d58da20f6a0c48399b6c1179727 | Python | 2,175 | 77 | #!/usr/bin/env python
from __future__ import print_function
import numpy as np
from pddlstream.algorithms.focused import solve_focused
from pddlstream.language.generator import from_fn, from_constant, from_test, universe_test, empty_test
from pddlstream.language.stream import StreamInfo
from pddlstream.utils import ... |
9377bfc56367e57eb093ab704ee7e8f8ddf954ad34b1001b3d34e6fa26a71b3f | Python | 2,175 | 58 | 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
... |
5cb572eb8703fa2b0e79919b09b56ff2adff808d3b5127db088e8d430483eef4 | Python | 2,176 | 61 | # 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... |
83d502f4f937be7c1ac09bcfc142883fcf5fd7423cdbb20de056e57baa85dac2 | Python | 2,176 | 64 | {
"connectome":{
"data_dir": "../../data",
"name": "MICrONS"
},
"save_path":"../../data",
"analyses":{
"simplex_counts":{
"save_suffix":"",
"kwargs":{"threads": 8},
"controls":{
"seeds":[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, ... |
0c4d17574e0125815ca982a572db75b1a5bcbf004a4af77f619de795e8f1c74d | Python | 2,177 | 70 | '''
Script that generates the ECFPs.
NOTE: It's very important that the ML table that you use lines up with the ECFPs.
So each line number in the ML table should correspond to the line number in the ECFPs .npy file.
This is incorporated in the ML-table generation script. Therefore, generate the ML-table after the EC... |
f16b532875d403fb81e641dfaa87ec2260741ff2f9a4db5f1597655b1720927d | Python | 2,177 | 78 | # 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... |
0b4eef3d39ced419a39393878fd1ad65ed2d9e132a0ffed25d10c5e09dd2cd0b | Python | 2,178 | 58 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from common_setup import IssueConfig, IssueExperiment, is_test_run
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue657-v1-base", "issue657-v1"]
CONFIGS = [
IssueConfig(h... |
b10c3411cd6ae96b748c4271eb79d5d13cdf14a702c2987e2f9a4e5fcdca1f14 | Python | 2,179 | 83 | ################################################################################
# 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.... |
b9bb3a6bbb318f72433512960b2094da3e6bd4207bae0c8e360673619aba0ffe | Python | 2,179 | 76 | # Copyright 2016 Julien Danjou
# Copyright 2016 Joshua Harlow
# Copyright 2013-2014 Ray Holder
#
# 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
#... |
fc86403dc5b95d5de73092db743cdbddc4b33a5d1e655d0f98329465954bbb6f | Python | 2,179 | 60 | import torch
import torch.nn as nn
class RevIN(nn.Module):
def __init__(self, num_features: int, eps=1e-5, affine=True, target_dim=None):
"""
:param num_features: the number of features or channels
:param eps: a value added for numerical stability
:param affine: if True, RevIN has ... |
9839db095fe72556b597ff87c4db8742249084be790d870fbee6c5169c2a69e8 | Python | 2,180 | 72 | from pathlib import Path
from random import randint
from typing import Any
import elasticai.creator.ir2verilog as ir
from elasticai.creator.file_generation import find_project_root as get_path_to_build
from elasticai.creator.ir import Registry, attribute
from elasticai.creator.ir2verilog import Ir2Verilog, factory
d... |
a19adc54e2f662b97784e00bdb7bceada40cda5bd874219718d0edd784c1c819 | Python | 2,180 | 68 | # -*- coding: utf-8 -*-
import tensorflow as tf
from .. import _logging as logging
from .core import *
__all__ = [
'PReluLayer',
]
class PReluLayer(Layer):
"""
The :class:`PReluLayer` class is Parametric Rectified Linear layer.
Parameters
----------
layer : :class:`Layer`
Previous ... |
c0e9e3c5b5c3939981aad2dfcac50da0cdbeac0c64499bcf778615214f7dadd9 | Python | 2,180 | 47 | import os
import pandas as pd
def main():
results_dir = '/home/grads/tasnina/Projects/BIONIC-evals/bioniceval/results/'
pombe_coann_file = results_dir + 'icon_pombe_hyperparam_coannotation.tsv'
pombe_func_file = results_dir + 'icon_pombe_hyperparam_function_prediction.tsv'
pombe_module_file = re... |
cf1956c54a7391d648d0a7c78cd8746a9dc35e5dfc52eb9fdd52f0362b71d5b8 | Python | 2,180 | 42 | # script to replace values of the @chrs, @StartSites, @StopSites perl variables with suzukii contig information
import os
import re
env_vars = ['Altitude', \
'Annual_mean_wind_speed', \
'Annual_Precipitation', 'Precipitation_Seasonality', \
'Mean_Diurnal_Range', 'Mean_Temperature_of_Coldest_Quarter', 'Mea... |
a174b0b3dca4db56a482b896a68a3b72d5ee9db71991719b7b150ad5378deaac | Python | 2,181 | 59 | #!/usr/bin/env/python
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
class EarlyStoppingCriterion(object):
"""
Arguments:
patience (int): The maximum numb... |
03fd7e83d3037b7440000101924fa0b8804ae242851970dfc25345898f2f3c35 | Python | 2,182 | 71 | import pytest
from pupil_recording_interface.base import BaseConfigurable
from pupil_recording_interface.device.video import BaseVideoDevice
@pytest.fixture()
def configurable():
class Configurable(BaseConfigurable):
_config_attrs = {"configurable_type": "test"}
_ignore_args = ("arg3",)
... |
92e6c49575f76ffc9c7675ccae921a75599dfe2b4d8a7adc3aa21b3b9686cd05 | Python | 2,182 | 97 | # morphoglia/io/image.py
from __future__ import annotations
from pathlib import Path
from functools import lru_cache
from typing import Iterable
import cv2
from ..core.models import ImageRecord, DatasetIndex
from ..metadata.nomenclature import NomenclatureExtractor
class ImageIndexer:
"""
Discovers image file... |
ac6f16f3b87b8b7aef87ad9b608d68110d06563838d544a8c78da620a3c14c80 | Python | 2,182 | 61 | import os
import torch
def update_params(params, epoch, freeze_epoch):
"""
update parameters based on epoch
freeze_epoch (>=1): until which we only learn autoencoder, after which we reset alpha to the one specifed in param files
"""
loss_params = params["loss_param"]
# pretrain_ratio = 0.0
... |
9074df49ddc78a73318e4df1bc83f267ad750286bf142cd3fd68c47497aa7ab4 | Python | 2,183 | 83 | #!/usr/bin/env python
# coding: utf-8
import pandas as pd
import math
import numpy as np
from scipy import stats
from skimage import data
from skimage.transform import resize
import argparse
import sys
# parser = argparse.ArgumentParser(description= 'Preprocess .vcf files')
# parser.add_argument('number', type=int,... |
00a05b102462befad4391235f95681832b621d6bcbf803db2931ada60049e98a | Python | 2,184 | 69 | #!/usr/bin/env python
# Copyright (c) 2020 Computer Vision Center (CVC) at the Universitat Autonoma de
# Barcelona (UAB).
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
"""
This metric calculates the distance between the ego vehicle and
another a... |
2bb3285bc1d0a7da75fadd9c0961fb97357151ec88607e7906a66a9d5ebda434 | Python | 2,184 | 70 | # 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... |
4e364fb2177e5f05919abbbfd9b2403323d88fcbd15a50eeca0b50cbcf9d44b4 | Python | 2,184 | 76 | import argparse
import numpy as np
import torch
import trimesh
from tqdm import tqdm
def load_poses(path):
poses = []
with open(path, "r") as f:
lines = f.readlines()
for line in lines:
c2w = np.array(list(map(float, line.split()))).reshape(4, 4)
c2w[:3, 1] *= -1
c2w[:3, 2... |
3cfc498d62bbf2ec58e9b127a422bf971e288f7a3bc8360627c12c538d0a3009 | Python | 2,185 | 79 | # Node-group asset "Residue Name" (GeometryNodeTree), dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# _build_group() is the source of truth: the docstring, __init__ and accessors are regenerated from it on the next dump.
from typing import TYPE_CHECKING
... |
5deb542c426a89c00838ec282ba8c12a910738eba59aea2c06ba8f90e659a5bb | Python | 2,185 | 48 | # -*- coding: utf-8 -*-
import numpy as np
from scipy import interp
from matplotlib import pyplot as plt
from sklearn.metrics import auc
TARGET = ("CVD", "HF", "AFib", "CAD", "MI", "Stroke", "DENOVO")
ITERATION = tuple(range(100))
FEATURE = ("ALL", "LAB", "ECHO")
RESULT = np.load("result.npy")
AUROC = RE... |
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