sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
9cbdb5d8050dc3406ed1a8def77f4cc127186c4f13f6a484c951e3cf3d81cfe5 | Python | 13,353 | 349 | from collections import defaultdict
from functools import lru_cache
from flask import url_for
from codex.configuration import MIN_SYN_THRESHOLD
from codex.data.brain_regions import neuropil_hemisphere, NEUROPIL_DESCRIPTIONS
from codex.data.neurotransmitters import lookup_nt_type_name, NEURO_TRANSMITTER_NAMES
from cod... |
bb3675b567e72978309036501bb554f02d53f3e45074cfd44ee7590cbf80c043 | Python | 13,355 | 422 | import smbus2 as smbus
import time
import numpy as np
import multiprocessing as mp
import threading
from PIL import Image, ImageDraw, ImageFont
import adafruit_ssd1306
import busio
class I2c:
def __init__(self, is_values):
self.is_values = is_values
self.i2c = smbus.SMBus(1)
self.co2_addr = 0x29... |
8d4cc02fd64a10e500d7ae3b83354c85a70972e14ed7d433c678ab303e228dd8 | Python | 13,360 | 367 | import warnings
from rdkit import Chem
from rdkit.Chem import AllChem
from torchdrug.core import Registry as R
# orderd by perodic table
atom_vocab = ["H", "B", "C", "N", "O", "F", "Mg", "Si", "P", "S", "Cl", "Cu", "Zn", "Se", "Br", "Sn", "I"]
atom_vocab = {a: i for i, a in enumerate(atom_vocab)}
degree_vocab = ran... |
5362da213a9f79c7121dd105671b73ca048f0fe4bb2b7a365eefab3dd6515bda | Python | 13,363 | 406 | # -*- coding: utf-8 -*-
import itertools
from functools import reduce
from typing import Iterable
import torch
from supar.structs.fn import sampled_logsumexp, sparsemax
from supar.utils.common import MIN
class Semiring(object):
r"""
Base semiring class :cite:`goodman-1999-semiring`.
A semiring is defin... |
5f4fb5d9e66536c214a3e6dfb2fac4b5ed99905c292ed1de48c7f6504067d1f8 | Python | 13,377 | 382 | import os
import sys
import json
import h5py
import copy
import collections
import numpy as np
import pandas as pd
import scipy.stats
import textwrap
import util_figures
def get_color_and_label_from_model_tag(model_tag):
"""
"""
if "human" in model_tag.lower():
color = "k"
label = "Human ... |
61bb811efeac65adf318d65c8b0fb0e201ff891289edee85f3ce828d8a6521aa | Python | 13,380 | 299 | """
Copright © 2023 Howard Hughes Medical Institute, Authored by Carsen Stringer and Marius Pachitariu.
"""
import os
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import zscore
from sklearn.decomposition import PCA
import cv2
from fig_utils import *
def fig6(root, alldat, save_figure=True):
... |
6106159c0ccd25ee4d06069e8858147699a5408214f96f56f23f8f5a18600c0f | Python | 13,381 | 359 | from monai.transforms import Transform, Compose, LoadImage, EnsureChannelFirst
import torch
import skimage
import torch
import SimpleITK as sitk
import numpy as np
from PIL import Image
from io import BytesIO
import matplotlib.pyplot as plt
import SimpleITK as sitk
from matplotlib.colors import ListedColormap
import ba... |
d4f7d3d88416214ea77bbfc94331b5a66756ae37b4f9379ba90d94ab04c56890 | Python | 13,381 | 409 | # 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... |
c6eace110a6551aeab0ca63e872997a9f956f83250840adcbec9e4e07988f27f | Python | 13,385 | 263 | import dsmil as mil
import torch
import torch.nn as nn
from torch.utils.data import DataLoader
import torchvision.models as models
import torchvision.transforms.functional as VF
from torchvision import transforms
import sys, argparse, os, glob, copy
import pandas as pd
import numpy as np
from PIL import Image
from co... |
d60065af786407385adc263e09b47495afea3e2aa312a8b5b5aa5c983e8d7ec6 | Python | 13,385 | 263 | import dsmil as mil
import torch
import torch.nn as nn
from torch.utils.data import DataLoader
import torchvision.models as models
import torchvision.transforms.functional as VF
from torchvision import transforms
import sys, argparse, os, glob, copy
import pandas as pd
import numpy as np
from PIL import Image
from co... |
a7eddcf37139f838e5905df91b43bdfa48d0469a1e8cffb6ff3d21c59f9ea25e | Python | 13,387 | 432 | # common.py
from .core import *
from .helpers import DelimitedList, any_open_tag, any_close_tag
from datetime import datetime
# some other useful expressions - using lower-case class name since we are really using this as a namespace
class pyparsing_common:
"""Here are some common low-level expressions that may b... |
3f065d16bd6b5a3188fd63fc32ed28fefe081b010b3488b7e48dc93c67a4d8a8 | Python | 13,389 | 332 | """
Set of tests for adaptive exponential integrate-and-fire mean-field model.
"""
import unittest
import numba
import numpy as np
import pytest
import xarray as xr
from jitcdde import jitcdde_input
from neurolib.models.aln import ALNModel
from neurolib.models.multimodel.builder.aln import (
ALN_EXC_DEFAULT_PARAM... |
780db2b660bae86d7e8907d3eb91c18f76921d3913abbe07b24344e93a0d061d | Python | 13,398 | 322 | from torch.utils.data import Dataset, DataLoader
import torchvision.transforms as transforms
import random
import numpy as np
from PIL import Image
import torch
import os
from autoaugment import CIFAR10Policy, ImageNetPolicy
transform_weak_c1m_c10_compose = transforms.Compose(
[
transforms.Resize(320),
... |
8a21d1a5a92e1785a4562f122d7ae34598b82ce23e34b1997059f9aad162b9ca | Python | 13,401 | 338 | import os
import glob
import numpy as np
import torch
import torch.nn as nn
from torch.utils.data import Dataset
from torchvision import transforms
from scipy.io import loadmat
from cfg import parser
from core.model import YOWO
from core.utils import *
from core.eval_results import *
####### Load configuration arg... |
4d44dbad397732ffe4081a254be6ac6a3a48fc315b26ae84a9bc713c7606d945 | Python | 13,406 | 346 | import torch
from torch import nn
from torch_cluster import knn_graph, radius_graph
from torchdrug import core, data
from torchdrug.layers import functional
from torchdrug.core import Registry as R
@R.register("layers.geometry.BondEdge")
class BondEdge(nn.Module, core.Configurable):
"""
Construct all bond ed... |
86b09999329ce2276c26519799a6069f65f7405b747b80e03247be719b7bc484 | Python | 13,408 | 364 | # -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.experiment import ARGPARSER
from lab.steps import Step
from downward.experiments import DownwardExperiment, _get_rev_nick
from downward.checkouts imp... |
7b1665c288b571a7604fefd6b70eafc4e78a1223185e295b42257123047f0d7c | Python | 13,409 | 383 | import numpy as np
from bonito.nn import Permute, layers
import torch
from torch.nn.functional import log_softmax, ctc_loss
from torch.nn import Module, ModuleList, Sequential, Conv1d, BatchNorm1d, Dropout
from fast_ctc_decode import beam_search, viterbi_search
class ModelTinyNoSkipX1(Module):
"""
Model templ... |
48b546304467c5496694eb6c78049bfad6feee813fd5434bc2e9ea2b5192a690 | Python | 13,413 | 340 | #
# 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,... |
834cb46a2e45d466f1ed9178f03a84f426e5694da54264e4400b43a8e66b90bb | Python | 13,413 | 342 | """
rCCA
====
This script shows how to use reconvolution canonical correlation analysis (rCCA, see [1]_ and [2]_) from PyntBCI for
decoding c-VEP trials. The rCCA method uses a template matching classifier where templates are estimated using
reconvolution and spatial and temporal filters using canonical correlation ana... |
10a2f5426cc2750b036042853988854d93dbadaf129c419c43e6b8928907462d | Python | 13,416 | 410 | # pylint: disable=no-member, too-many-locals, too-many-arguments, too-many-instance-attributes, invalid-name, attribute-defined-outside-init, no-name-in-module
"""Training scripts"""
from importlib import import_module
import gc
import os
import time
import warnings
from pprint import pprint
import math
import torch
f... |
2a407c4f374a0cdf129e2ba9d25a87bb887a9d46b80cccf4e057d125f21023b4 | Python | 13,422 | 444 | __author__ = "Ryan Galloway <ryan@rsgalloway.com>"
__version__ = "0.1.1"
# ---------------------------------------------------------------------------------------------
# SUMMARY
# ---------------------------------------------------------------------------------------------
"""The QRangeSlider class implements a hori... |
6e82552cc4fe81714f6f8122b3c699474b4d32f44fbb5e337d8a6e46a9967f68 | Python | 13,424 | 470 | """Utilities for handling SMILES strings and RDKit mols and conformers.
Author: Seth Axen
E-mail: seth.axen@gmail.com
"""
import os
import re
import copy
import logging
from collections import namedtuple
import rdkit
import rdkit.Chem
import rdkit.Chem.PropertyMol
from rdkit.Chem.PropertyMol import PropertyMol
from p... |
b0f7f03ff1857d088a8eab135b7b17ff2bd4d9d3aab3933c76a0eb1da38edf84 | Python | 13,425 | 91 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.reports import Attribute, geometric_mean
from common_setup import IssueConfig, IssueExperiment, DEFAULT_OPTIMAL_SUITE, is_test_run
BENCHMARKS_DIR=os.path.expanduser('~/repos/downward/benc... |
c8b4c2093630d641e69266936216a411887513513894d3b629f30fe62a2498a9 | Python | 13,425 | 91 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.reports import Attribute, geometric_mean
from common_setup import IssueConfig, IssueExperiment, DEFAULT_OPTIMAL_SUITE, is_test_run
BENCHMARKS_DIR=os.path.expanduser('~/repos/downward/benc... |
9b3130f803bf2afc182d9162a39d0ef9ebf310bbbb27ba9418875a24650cddfa | Python | 13,426 | 281 | # Step 3 of 4: Create .sbatch and .json files for running TriDy
# Directories for stroing the results will be created.
# A file containing all the command to be executed is also created, named runfiles.sh. This can be executed with "bash runfiles.sh"
# Temporary pipeline.py and toolbox.py files are created as well, to... |
e4657ea3354df152b995d80711ebdd2791f04dfa9464c13cc5a09d7172bfee75 | Python | 13,428 | 397 | import bpy
import MDAnalysis as mda
import pytest
import molecularnodes as mn
from molecularnodes.session import MNSession
from .constants import data_dir
def test_session_present():
assert isinstance(mn.session.get_session(), mn.session.MNSession)
def test_persistent_handlers_added():
load_handlers = [hand... |
fb39c4e1a170a87ac4e2f9007e13b5d4135b5c8cb89e44359e841dcdbf45abcb | Python | 13,429 | 360 | import os
import shutil
import tempfile
from pathlib import Path
from typing import TYPE_CHECKING, Literal
import bpy
from ..utils import suppress_stdout
if TYPE_CHECKING:
from .base import Canvas
# formats an animation can be assembled into; matching is case-insensitive
_ANIMATION_FORMATS = Literal["MP4", "GIF",... |
0f699fee846441738b823e2c26535444390c0b85b09fbab1c45c831dd99d6585 | Python | 13,432 | 369 | """Ordered collections of schema entries representing a single section of the HED vocabulary."""
from hed.schema.hed_schema_constants import HedKey, HedKeyOld, HedSectionKey
from hed.schema.hed_schema_entry import HedSchemaEntry, HedTagEntry, UnitClassEntry, UnitEntry
entries_by_section = {
HedSectionKey.Properti... |
c55610589a4b00d39d49ed9d4787171ba3acdc015c1681f64eca25fdca7dd846 | Python | 13,432 | 409 | ################################################################################
# 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.... |
d9971355a5f064fa9e32541cd09b2c2840b80bfabc1dba42a8bfd0f01cf70251 | Python | 13,434 | 390 | import tracemalloc
import numpy as np
import pandas as pd
import pytest
from lifelines import WeibullAFTFitter
from SurvivalEVAL import SurvivalEvaluator
from SurvivalEVAL.evaluations.prediction_error import (
brier_multiple_points,
brier_multiple_points_ic,
brier_score_ic,
)
from SurvivalEVAL.evaluations... |
0a8886690d96e84b5080babe6d0642a6c067609fe395e145b253bf3ccfc00375 | Python | 13,437 | 345 | """
Iterative burst detection on single-channel time-frequency or lagged
coherence matrices algorithm.
Authors: James Bonaiuto <james.bonaiuto@isc.cnrs.fr>
Maciej Szul <maciej.szul@isc.cnrs.fr>
Adaptation: Sotirios Papadopoulos <sotirios.papadopoulos@univ-lyon1.fr>
"""
import numpy as np
from mne.filter imp... |
204b1ad97ef7e6e4b7d9e99f626f454524a20c920f4227c128fe0e86284ceb2e | Python | 13,437 | 406 | # 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... |
b92523913e6ff8b8d64c53a89c8fee403d4bbbcdec406013887c7aff99053ebb | Python | 13,437 | 397 | # 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... |
27301a7c63dcddb4aec80d5df8c9495a264c1c0e3bef2208910f95f885e700f5 | Python | 13,438 | 346 | import math, torch
from torch.nn.parameter import Parameter
import torch.nn.functional as F
from torch.nn.modules.module import Module
import torch.nn as nn
class general_GCN_layer(Module):
def __init__(self):
super(general_GCN_layer, self).__init__()
@staticmethod
def multiplication(A, B):
... |
d9203501517e38b7d1249e43dcb06dadb7c8d72a7eb76e8f89f3f60aba2ae267 | Python | 13,438 | 340 | import getpass
import time, os, sys
from collections import Counter
from copy import deepcopy
from enum import Enum
import numpy as np
from wsilearn.utils.cool_utils import print_mp, print_mp_err
from wsilearn.dataconf import DataConf
from wsilearn.dl.np_transforms import NumpyToTensor
from wsilearn.utils.df_utils imp... |
5f890e0516170e2f473084b75fb326c7d4e739044a9c678a03a1a4b2fd817132 | Python | 13,441 | 248 | import os
import pysam
from tqdm import tqdm
import pandas as pd
import numpy as np
#%%# Summary site level data
def geo_mean_overflow(iterable,epsilon = 1e-6):
if len(iterable) == 0:
return 0
return np.exp(np.log(iterable+1e-6).mean())
def read_sites(sites_f):
putative_site_df = pd.read_excel(site... |
a0c86ab37ee61a716c9918a6a2f7beffd6729e97501dfe589949951c1cc32143 | Python | 13,445 | 375 | """
Geometry module that contains geometric functions
"""
# Copyright (C) 2021 Blue Brain Project, EPFL
#
# 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
# ... |
3515f17072577727047c02123e12df8b62213338dedb9bb59578a88e78d7a445 | Python | 13,448 | 288 | #
# 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,... |
80165c4443521761b74311bf21a6ef4b5cce6dbd3e137106981dfb181bc484ba | Python | 13,457 | 398 | import os
from abc import ABC, abstractmethod
from typing import List, Tuple
import numpy as np
import pandas as pd
from tqdm import tqdm
from pathlib import Path
import functools
from wsilearn.utils.cool_utils import timer, showims, multiproc_pool2, showim
from wsilearn.utils.df_utils import print_df
from wsilearn.u... |
ea4755d2cc94d8b3da295243458f66df5881ea961646699fcde5bb754d6b24ce | Python | 13,459 | 294 | # 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... |
0e2c677397767c400c0ff9f592b943da94e3c5638de25e5acbc49aeba2cc3da5 | Python | 13,467 | 434 | #!/usr/bin/env python
# coding: utf-8
# ## Analysis of feature selection results; single-cancer holdouts
#
# For our "cross-cancer" feature selection method, we expect it to provide a performance improvement (or at least to be more resistant to drops in performance) "across" cancer types; or in other words, when a si... |
99a86e504dd483c88536ecd489899dbc0fea66e43cd29e2b237bfd750d9e76f5 | Python | 13,467 | 395 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from plot_methods import plot_signal_sum_colorplot, plot_signal_sum, plot_signal_power_colorplot, calc_signal_power
from cellsim16popsParams_default import multicompartment_params
import analysis_params
import plotting_helpers as phlp
import hybridLFPy.helpers as hlp
from h... |
f082e4378be043704a4e711dd9352f5004f224c629775f9d71da34dfb62351c8 | Python | 13,470 | 363 | # 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... |
19aba78bf151de249e7035b20e5bd92196cedfb6cd50fab2d0669ca8d6e14597 | Python | 13,471 | 379 | #!/usr/bin/env python
#================================================================
# Copyright (C) 2023 Yufeng Liu (Braintell, Southeast University). All rights reserved.
#
# Filename : multi-levels_analyzer.py
# Author : Yufeng Liu
# Date : 2023-02-07
# Description :
#
#=========... |
f95061e113612729be1aefa0bf6d5eebbd358d828dfb70d8347ce677ccef4610 | Python | 13,474 | 374 | """Utility functions for TorchSim recipes."""
from __future__ import annotations
from copy import deepcopy
from importlib.util import find_spec
from typing import TYPE_CHECKING, Any, Literal, TypedDict, cast
from monty.dev import requires
from quacc.schemas.torchsim import PROPERTY_FN_REGISTRY, TSModelType
has_tor... |
fee68b82f3c493d58cfd7281fc240596e20b09077f46f36b28021c9457384a0d | Python | 13,474 | 380 | # utils.py
# Created by Ayesh Madushanka
# Created on: May 16, 2024
import numpy as np
import pandas as pd
import os
import sys
import subprocess
import shutil
from rdkit.Chem import AllChem
from rdkit import Chem
# save dataframes as csvs
def save_df(datafrm: str, new_name: str):
datafrm.to_csv(new_name, inde... |
e9dc7abc8c9ff2cafc644f02b5265e88e2e8adf74ee701fc146c704360c95f95 | Python | 13,476 | 94 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.reports import Attribute, geometric_mean
from common_setup import IssueConfig, IssueExperiment, DEFAULT_OPTIMAL_SUITE, is_test_run
BENCHMAR... |
a2978c1536f9326ff378b24c54b28d2a00a626cace832b404eac9a9868aa6191 | Python | 13,487 | 352 | """
Script for doing Univariate statistical spatial analysis for a 3D distributed point pattern
Input: - XML file with a particle list
- Parameters for setting the statistical analysis
- Tomogram mask (optional)
Output: - Graphs with the results of the statistical analysis
"""
... |
7899dc834a7cdf39b51533ef33d6ae353ea86af22f5da89b9911437f5aa6c246 | Python | 13,488 | 331 | # testing.py
from contextlib import contextmanager
import typing
from .core import (
ParserElement,
ParseException,
Keyword,
__diag__,
__compat__,
)
class pyparsing_test:
"""
namespace class for classes useful in writing unit tests
"""
class reset_pyparsing_context:
"""
... |
9cd8b2f1a3ee3a720aadbed6d9b2e7610898d3f4ba587eabe9fd3668fba29daf | Python | 13,494 | 191 | # ------------------------------------------------------------------------
#
# 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
#
# Unle... |
dc2b3f2984d2aab00c4a80b6cde056c8e9fdf3c3fc081823d77d7ee0466b50df | Python | 13,498 | 336 | # 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... |
e7b2c78cef1c8e037a855d2e0e215f9779ccba0a07080eded65ccc9ab4705c4d | Python | 13,505 | 385 | from functools import partial
import torch
import torch.nn as nn
from timm.models.efficientnet import EfficientNet
from timm.models.efficientnet import decode_arch_def, round_channels, default_cfgs
from timm.models.layers.activations import Swish
#from timm.models.layers import convert_splitbn_model, convert_sync_bat... |
51c5d9dea9ffe0e8fbd2ce8a3aeb3e601c6def48661fe5189f637a5db94a4464 | Python | 13,508 | 357 | #!/bin/env python3
"""
Points, Lines, etc.
-------------------
This submodule implements several classes to deal with points living in
N-dimensional space. Each point might have data attached to it. The main base
class is :py:class:`Points`. A :py:class:`Line` is just some
:py:class:`Points` which are ordered.
"""
fr... |
15f186f7e19a1078b2ba5846e99cc7b714a999c10e45f5008182c45d3441339e | Python | 13,511 | 449 | #! /usr/bin/python
# -*- coding: utf-8 -*-
"""
Experimental Database Management System.
Latest Version
"""
import inspect
import pickle
import time
import uuid
from datetime import datetime
import gridfs
from pymongo import MongoClient
def AutoFill(func):
def func_wrapper(self, *args, **kwargs):
d = in... |
e1ad92551e58e3079830e1fed80ee4eb2fa1031327e22f8035c90fcdac05eb3d | Python | 13,514 | 347 | import numpy as np
import pytorch_lightning as pl
import torch
import os
### from apex.optimizers import FusedAdam
from torch.optim import AdamW
from monai.inferers import sliding_window_inference
from monai.networks.nets import DynUNet
from monai.optimizers.lr_scheduler import WarmupCosineSchedule
from pytorch_lightn... |
992acc671482e46782fc4912b7feaebed028a5e0fa9ae2bba468a7817017609b | Python | 13,515 | 389 | # -*- coding: utf-8 -*-
#
# Test Peri-Stimulus Time Histogram
#
import matplotlib.pyplot as ppl
import numpy as np
import pytest
import dask.distributed as dd
# syncopy imports
import syncopy as spy
from syncopy.shared.errors import SPYValueError
from syncopy import synthdata as sd
from syncopy.statistics.spike_psth ... |
e1a5152fd6b2cd81dde4628186e900ccd0c9fb638492306c4e0ddcefa7aa7048 | Python | 13,516 | 232 | # coding=utf-8
# Copyright 2020 The Trax Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at... |
c6588fa77dc8ea524e9184d48f75912456e2e581291652e935db74243dc107bc | Python | 13,531 | 427 | #! /usr/bin/env python3
""" WARNING This script was changed on 26.04.2019
Now creates separate .rst file for every ap_ ex_ and ww_ example
Creates also bioshell-examples.rst file
Script creates these files in the right place in a documentation source
Must be run in doc_exammples/cc-examples/ and files goes to OUT_PA... |
37fce5ee727ac0bba8b72c532ee1e52182f09f8c1b8cfca8a86421efc09b0134 | Python | 13,533 | 327 | import scanpy as sc
import numpy as np
import dgl
import torch
from ..model.utils import add_degree
from sklearn.utils.extmath import randomized_svd
from scipy.sparse import csr_matrix, find
from sklearn.neighbors import KDTree
def preprocess(adata, common_genes=True,filter_min_counts=True, size_factors=True,... |
cbe311c170a1b8cf8e7d747b012313d5e22b2d7a7a2b89dac8ec0264ddef66b1 | Python | 13,540 | 301 | """
Binary risk-factor definitions per the 2024 Lancet Commission.
Loads merged_df_ES.csv, aggregates to one row per participant,
and creates 13 binary risk-factor columns.
Risk factors and their definitions
-----------------------------------
education_risk : Years of education <= 12
hearing_loss_risk ... |
09a41eda11dfe3f3ec0420f915b175a9cc5aab3b0b40cca551389ac4c19f3aa7 | Python | 13,541 | 315 | """Tests for regtools.ccf_boundary_editor.quantify."""
import numpy as np
import pytest
def _ml_on_x(width=10, offset=5.0):
"""A plane splitting the LAST axis at *offset*; higher index = right.
Deliberately not axis 0: a (Z, Y, X) volume's axis 0 is anterior-posterior,
and a test that split on... |
d32e8b8d00a8b023bbee445b3ab11518b352e77bfe8f32d71237921b64a5ac9d | Python | 13,541 | 438 | # 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... |
7a3dff14d4b97b89f930bf33c2558c5b7ffeb4d7ed73badfd5826c41323859dd | Python | 13,542 | 442 | """
==========================================================================
Fit single subject linear model to voltage evoked by stimulus presentation
==========================================================================
Mass-univariate analysis voltage data.
Authors: José C. García Alanis <alanis.jcg@gmail.c... |
8314b819f6665b223c79b96012cfc0ba8909e5ca1144a856cbeb0f1ce8fb2a93 | Python | 13,545 | 390 | from . import get_submodules_from_kwargs
__all__ = ['load_model_weights']
def _find_weights(model_name, dataset, include_top):
w = list(filter(lambda x: x['model'] == model_name, WEIGHTS_COLLECTION))
w = list(filter(lambda x: x['dataset'] == dataset, w))
w = list(filter(lambda x: x['include_top'] == incl... |
3c877997cdeeb98e2123d1016a4f01d0e0a00d1b38d2c0e84bee0f83adb02f87 | Python | 13,552 | 610 | #!/usr/bin/env python
from __future__ import division, print_function
import math
from numpy import *
def i4_bit_hi1 ( n ):
#*****************************************************************************80
#
## I4_BIT_HI1 returns the position of the high 1 bit base 2 in an integer.
#
# Example:
#
# N Binary... |
161bc121d645c5143e753c246ffd2669d44a815042694310cfd239c6a8c4e624 | Python | 13,560 | 352 | """
Metadata about languages used by our model training code for our
SingleByteCharSetProbers. Could be used for other things in the future.
This code is based on the language metadata from the uchardet project.
"""
from string import ascii_letters
from typing import List, Optional
# TODO: Add Ukrainian (KOI8-U)
... |
187d1561cf7620655114741d1db7e16c2631531bf7918d5d4e9e040957696597 | Python | 13,565 | 345 | """
Prosper_nn provides implementations for specialized time series forecasting
neural networks and related utility functions.
Copyright (C) 2022 Nico Beck, Julia Schemm, Henning Frechen, Jacob Fidorra,
Denni Schmidt, Sai Kiran Srivatsav Gollapalli
This file is part of Propser_nn.
Propser_nn is free software: yo... |
e5d1a558d6ff756ae82ae567c251050047622c5371c55df5424af6adb50b161a | Python | 13,565 | 366 | ###########################################################################################
# #
# This sample shows how to evaluate object detections applying the following metrics: #
# * Precision x Recall curve ----> ... |
de61ee46f5dfb2afd0710cac0d015bf2a4ae76f4e2a25ef50ba21cdb0e7bb4a3 | Python | 13,566 | 196 | ######################## BEGIN LICENSE BLOCK ########################
# The Original Code is Mozilla Communicator client code.
#
# The Initial Developer of the Original Code is
# Netscape Communications Corporation.
# Portions created by the Initial Developer are Copyright (C) 1998
# the Initial Developer. All Rights R... |
b7cc9e5f579454691ebe7adaf69714f8c2efe45a4f945ad877196aac86dcacfb | Python | 13,567 | 394 | # 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... |
bbdbaa588b933f7bc05519fdb29fabef2fea790c55896665e1014ba40da1dcab | Python | 13,567 | 409 | """Utility functions for dealing with slabs."""
from __future__ import annotations
from copy import deepcopy
from logging import getLogger
from typing import TYPE_CHECKING, cast, overload
import numpy as np
from pymatgen.analysis.adsorption import AdsorbateSiteFinder
from pymatgen.core.structure import IStructure, S... |
603c05343789c6567e1a98d8ccb82adfb158284c950654dc13e3ee4abaffe75a | Python | 13,573 | 345 | # -*- coding: utf-8 -*-
#
# Load data from Syncopy containers
#
# Builtin/3rd party package imports
import os
import json
import h5py
import sys
import numpy as np
from glob import glob
# Local imports
from syncopy.shared.filetypes import FILE_EXT
from syncopy.shared.parsers import io_parser, data_parser, filename_pa... |
f8ed5f7baa1a4d9877436654337b59629bfb4e07e33494bcf0c6dcc88658b9d5 | Python | 13,573 | 438 | # 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... |
2cad597109860f070b35b21d30736018cbafbdfab9e5446b7da13f4c0984f35e | Python | 13,574 | 320 | #!/usr/bin/env python
#coding:utf-8
import numpy as np
import multiprocessing
import torch
import torch.nn as nn
import csv
import os
from transcal.utils import get_weight, ECELoss, VectorOrMatrixScaling, TempScaling, CPCS, TransCal, Oracle
import argparse
from datetime import datetime
import logging
import warnings
... |
fed24524c4d75108b6b59c1790972f3bd0eec2c7088dfd91c9ef2afa81275e9a | Python | 13,574 | 390 |
import numpy as np
from bonito.nn import Permute, layers
import torch
from torch.nn.functional import log_softmax, ctc_loss
from torch.nn import Module, ModuleList, Sequential, Conv1d, BatchNorm1d, Dropout
from fast_ctc_decode import beam_search, viterbi_search
class ModelTinyNoSkipX4(Module):
"""
Model temp... |
8111495363c30b306389218e7abc6215c79391e1de2a6218b8def724bc3c910e | Python | 13,581 | 343 | from __future__ import division
import logging
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from func_unsupervised_CC import fit
from IterativeMethod import iterativeCC
"""
Created on Mon Jun 24 16:04:07 2019
@author: Hannah Choi
"""
"""
This code finds intra- or inter-module h... |
b99d709c5fcf9e179311649e56ec98479c6b09b05efcae78c2646bc1dfb925c7 | Python | 13,582 | 386 | # -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.experiment import ARGPARSER
from lab.steps import Step
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.rep... |
d6c01ad7181492ee8efaef7863c65de10aa9965a13ab8dc46743a154e012457f | Python | 13,582 | 341 | #!/usr/bin/env python
# Copyright (c) 2018-2019 Intel Corporation
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
"""
This module contains a statistics manager for the CARLA AD leaderboard
"""
from __future__ import print_function
from dictor im... |
b988857e83c1a5af91a4e10dcf9682e85cfde38fc480d051aa617d13d23f4e74 | Python | 13,583 | 364 | # LIBRARIES
from argparse import ArgumentParser
from pytorch_lightning.metrics import Accuracy
import torch
import torch.nn
from torch.nn import functional as F
from torch import nn
import pytorch_lightning as pl
from torchmetrics import Accuracy
from vit_pytorch import ViT
from transformers import ViTConfig
import mat... |
500b333912cbc4749cb7f7ea7c316e35c050d560f34e99419d0941ed8a28b8df | Python | 13,585 | 433 | import pickle
import os
from typing import Union
import torch
import lmdb
class _EEGSignalIO:
@property
def write_pointer(self):
return len(self)
def keys(self):
raise NotImplementedError(
"Method keys is not implemented in class "
+ self.__class__.__name__
... |
e2cbd2f72673949ff24a3de3c51c554ed03718902841567f82aff63e852792dd | Python | 13,587 | 301 | """Export mixin for the CCF boundary editor.
Carries the editor's export actions - full-volume modified annotation +
quantification CSVs (``_on_export``), single-CCF-section export for the
section-browse mode (``_export_section_browse``), and the pipeline-format
per-region count CSVs (``_on_export_pipeline_counts... |
00b45be72c6e69b618754d341f9b0689b968ac6fe724c1cc5b2d91bb0bd85bfe | Python | 13,589 | 346 | """A Q-Chem calculator built on Pymatgen and Custodian functionality."""
from __future__ import annotations
from typing import TYPE_CHECKING
from ase.calculators.calculator import FileIOCalculator
from quacc.calculators.qchem.io import read_qchem, write_qchem
from quacc.calculators.qchem.params import cleanup_attrs... |
13fbf5f047bc95606809e8400de6a2893617e75c4fc0e910faca6b8ca90742e8 | Python | 13,589 | 341 | #!/usr/bin/env python
# Copyright (c) 2018-2019 Intel Corporation
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
"""
This module contains a statistics manager for the CARLA AD leaderboard
"""
from __future__ import print_function
from dictor im... |
a347a2e9b22fa72946cd8c5e00063932e1f5d768e5c735b37cc320ac99cba815 | Python | 13,595 | 325 | # -*- coding: utf-8 -*-
"""
Created on Tue Jun 23 2023
@author: Jonas A. Thiele
"""
### Visualizing differences between results from models trained with most relevant links vs. models trained with all links
### Determining overlap of most relevant links between states and intelligence components
import n... |
57e57b17add8fdd683a4913ee13695cd92e1ea497f5b4746412ebd2bdd991488 | Python | 13,596 | 376 | # 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... |
a03a1cc0f76e4bec2d2a483a7fd461f7ba864c5e08a63944b4bdbbb0ea91f12c | Python | 13,596 | 468 | import pandas as pd
import json
json_file= pd.read_json('cache/felipe/annotations.json')
im_dir = 'cache/felipe/Data'
ims = json_file.keys()
n_classes = 5
im = ims[0]
part_keys = None
def get_xy(ann):
return np.array([ann['cx'],ann['cy']])
all_lbls = []
for im in ims:
anns = json_file[im]
n_anns = len(a... |
2d9bfbdbcbaa85f59aaff0c41c16fba6757c0241cdfea4ea754286f84e8cc56c | Python | 13,600 | 341 |
# -*- coding: utf-8 -*-
"""
Created on Jun 4 2023
@author: Jonas A. Thiele
"""
### Apply models build in HCP sample to
### predict intelligence scores in the replication sample (PIOP1 and PIOP2 combined)
### for models that were trained with links (edges, connections) between specific nodes (from intellige... |
b058ec899669d4b2467796bfa8bed3daa750c6bad997e4386446ba7ae0d53ea6 | Python | 13,603 | 295 | from collections import Counter
from pddlstream.algorithms.common import evaluations_from_init, SOLUTIONS
from pddlstream.algorithms.constraints import add_plan_constraints
from pddlstream.algorithms.downward import parse_lisp, parse_goal, make_cost, set_cost_scale, \
fd_from_fact, get_conjunctive_parts, get_disju... |
9697bc1441ac1b48e8be3ba85c0d29fd73a09c878f68bd7420a8ede0e2c67fe9 | Python | 13,605 | 324 | from random import shuffle, choice
import os
import logging
import tensorflow as tf
import sys
from PIL import Image
logger = logging.getLogger(__name__)
global tf_image, tf_label, status
import random
import numpy as np
#from skimage.color import rgb2lab,rgb2hed
class Preprocess:
def __init__(self, directory_path... |
c2a4145a3ec1c6fb9c8d4b342aa5b96ee3cf80bbd63590ceebd7b3c09191b1e6 | Python | 13,606 | 275 | # Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... |
b30109bd6b2d219352d6b1dcf21ca8361c2037617741d4b103d9ab6e5b504703 | Python | 13,608 | 401 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import sys
sys.path.append(os.path.abspath('../'))
try:
import analysis.synchronization as synchronization
import analysis.connectivityMatrices as connectivityMatrices
except ModuleNotFoundError:
import KuramotoNetworksPackage.analysis.synchronization... |
23d9f38fb994d188febd3085b8edf944de3f742749ab2208ff4f48b26e2810bc | Python | 13,613 | 309 | import random
import numpy as np
from torch.utils.data import Dataset
import sys
import pandas as pd
from tqdm import tqdm
from sklearn.preprocessing import LabelEncoder
from collections import OrderedDict
import os
import math
import torch
import torch.optim as optim
import torch.optim.lr_scheduler a... |
0e83ce574b6f5337eeb0a88613e4ec8636092c603597333b734cc63da1c948c2 | Python | 13,617 | 285 | """
Bitwise decoding
================
This script shows how to use CCA and LDA on epochs within a trial, using PyntBCI, for decoding c-VEP trials. Epochs are
defined as the windows of data within a trial, synchronized to the onset of individual flashes. For each of these epochs
the classifier determines whether a flash... |
607d258240c648c5e481426d1beaeb244f2f7b7cf4cf24838a1a7f88b4a45d18 | Python | 13,618 | 339 | import os
import sys
import pdb
import glob
import json
import time
import resource
import numpy as np
import pandas as pd
import tensorflow as tf
import util_tfrecords
class CallbackPrinting(tf.keras.callbacks.Callback):
def __init__(self, display_step=1, epochs=None, **kwargs):
super(CallbackPrinting, ... |
fee526141ab895fb7bc69703d7a85e90398306cd9ce03edae5869ac28c3e87c5 | Python | 13,619 | 316 | """
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
"""
import wx
import os,sys,pydoc,platform
import webbrow... |
6d5b413567156c07a3baeff51640f35c53b60ba1de24a5af77c9f9e528cc466a | Python | 13,620 | 320 | """The registration tab drives the drawn midline end to end.
The panel can capture two clicks and the geometry can promote them; this is the
piece that arms the mode, derives the frame, and persists the result so the RUN
can read it back.
The frame derivation is the part that must not be guessed. ``ml_axis`` co... |
c2bee946e93b28adb24ef8486641db30852c8cbe898d6ad6a9937769a207cd5d | Python | 13,628 | 343 | from __future__ import print_function, division
import numpy as np
import scipy
import time
import os
import datetime
from learn_tools import helper
from operator import itemgetter
from learn_tools.learner import FAILURE, THRESHOLD, SUCCESS, score_accuracy
#from pybullet_tools.utils import interval_generator
from pd... |
c1718e4296fa3fa7175d5e7b335c2d8d9c0f8e661238829c35cc52ac214c6984 | Python | 13,632 | 380 | """Checker that validates event-level HED annotation quality for BIDS datasets."""
from hed.errors import ErrorContext, ErrorHandler, sort_issues
from hed.errors.error_types import TagQualityErrors
from hed.tools import EventManager, HedTagManager
class EventChecker:
"""Validates that HED-annotated events meet q... |
d1ff2c9334bc884a17bc5b62c4258837b9f033ede37aa71d8603f900a228ee5b | Python | 13,635 | 330 | import time
from dataclasses import fields
from pathlib import Path
from typing import Optional, Tuple
import numpy as np
from . import corrpts, utils, optimization, pointcloud
class SimpleICP:
"""Class for setting up and run simpleICP."""
def __init__(self) -> None:
"""Constructor method."""
... |
d3191d17fba18a86a7d102dbe67d0a5ebee311284a1ffb1804df176b625bca31 | Python | 13,637 | 300 | #%%
import numpy as np
import pandas as pd
import math
from pathlib import Path
ROOT_DIR = Path('/media/WDBlue/mcintosh/projects/Cam-CAN/PLS_wrapper_SC/results/')
RESULTS_NAME = 'SC_age_CattellTotal_1000_its_594_subs_0_to_150_age_range'
ATLAS = '220'
ROOT_DIR.joinpath(ROOT_DIR,RESULTS_NAME,'figure_files/').mkdir(pare... |
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