sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
11b62bfde999b15b045499081e60f839d1fb186418feb9c51e815402ed4e6763 | Python | 8,337 | 187 | """
converts electrode (or for that matter, any point) coordinates in MRI space
to coordinates in freesurfer mesh space.
Requires subject ID to find coords data (in electrodenames_coordinates_native_and_T1.csv) and
the two matrices Norig and Torig which can be obtained using mri_info
Run:
python voxcoords_to_fs.p... |
5efd985be5f65a7e8c797c1cab72190434b9a81c50718e25ce8741f5eb275b54 | Python | 8,337 | 226 | import os
import shutil
import tempfile
import argparse
import datetime
import json
import time
import numpy as np
import matplotlib.pyplot as plt
import torch
import torch.nn.functional as F
from monai import transforms
from monai.apps import DecathlonDataset
from monai.config import print_config
from monai.data impo... |
7b5c5bc04d300408d5add06f55e85a33a517a27773be5973621e656eb27d9047 | Python | 8,337 | 270 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
'''Define ParameterSpace for benchmarking of scaling with different MPI pools
'''
import os
import numpy as np
import operator
import pickle
import hashlib
import parameters as ps
def sort_deep_dict(d):
'''
sort arbitrarily deep dictionaries into tuples
Argum... |
f0778e3b962e988c436e42e762bf3e69d17d7f0139558ab334de293e4b9efccb | Python | 8,337 | 227 | # 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... |
933e6b26729937bea96c5dc50284196b68f0a425fc2a4d2f72d5a6273b67a28d | Python | 8,339 | 231 | import os
import tempfile
# Importing bpy prepends the user's Blender extension wheels (e.g.
# ~/.config/blender/*/extensions/.local/site-packages) to sys.path, shadowing
# this environment's packages with whatever the enabled extensions ship -
# including possibly incomplete copies while an extension is being rebuilt... |
137a7f63e2df4ca23a9cd2b75414af7599782d63e0e30ac600e50b6c00606fb4 | Python | 8,340 | 198 | import torch
import torch.nn as nn
from torch.nn.functional import softmax
from pywebio.platform.tornado import start_server
from pywebio import STATIC_PATH
from pywebio.input import file_upload
from tornado.ioloop import IOLoop
from pywebio.input import *
from pywebio.output import *
from ipywidgets import Bu... |
c1944522a88151d2c773455a125cf9fec86499970381510076186ce83b4b8c55 | Python | 8,340 | 198 | '''
Description:
Compare model predictions of six scRNA-seq datasets.
Author:
Jiaqi Zhang <jiaqi_zhang2@brown.edu>
'''
import copy
import os
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import scanpy
from plotting.__init__ import *
from plotting.PlottingUtils import computeVisEmbeddin... |
fdca89b121fadda4b56e06ec631f43487edcaa8382e5d688209ba1d4aa1c431c | Python | 8,346 | 247 | import torch
import torch.nn as nn
import torch.optim as optim
from torch.optim.lr_scheduler import ReduceLROnPlateau
class TrivialEncoder(nn.Module):
def __init__(self, input_size, hidden_sizes, output_size):
super(TrivialEncoder, self).__init__()
# place holder layer does nothing
self.l... |
d9443bc082a6099a82340c761a35fa2a0bbcdd3350af5b50fe5554e9d70cace6 | Python | 8,349 | 213 | # MEGIT file IO functions
import os
import base64
import copy
import csv
import json
import h5py as h5
import zlib
import hashlib
import numpy as np
import cv2 as cv
import warnings
"""Function list:
# Video IO functions
img2vid(img_list, vid_name, fps=30, vid_path=None): Create a lossless AVI v... |
0f7d49b0082274b3104c814c287188aa2f79e4cc6c8b0cbeb4ee602b58aa3090 | Python | 8,350 | 201 | """
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 deeplabcut
import os,sys,pydoc
media... |
504d8e1e77632a1b27161edb9674ebf41489fe77173f959d03b37667a9ff4645 | Python | 8,350 | 184 | """Region list/tree mixin for the CCF boundary editor.
Carries the flat region-list and hierarchical region-tree widgets: building
their rows from the current slice + atlas hierarchy (``_refresh_region_list``,
``_refresh_region_tree``), the tree's click/context-menu handlers, and the
flat-list click handler that ... |
341f42350aa70fd703fb63cb40e187409c0b4049e53781443c649667e7007ed4 | Python | 8,351 | 163 | from pddlstream.algorithms.downward import fd_from_fact, substitute_derived, is_applicable, apply_action, \
fd_from_evaluation, task_from_domain_problem, get_problem, get_action_instances
from pddlstream.algorithms.reorder import separate_plan, get_stream_stats, dynamic_programming
from pddlstream.algorithms.schedu... |
8f3ba23ee740fa50535a5a498d0c58b69914cc7b4a30ba078586237e7f0d756e | Python | 8,351 | 190 | """
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 os
from pathlib import Path
import cv2
from dee... |
6c6537b2115b549e2fa2bc28f0105158d6e90462dd2568296ae8b3cc34324da4 | Python | 8,352 | 229 | """
Implementation of multi-variate EMD according to:
N Rehman and DP Mandic "Multivariate empirical mode decomposition"
Proc. R. Soc. A (2010) 466, 1291-1302 doi:10.1098/rspa.2009.0502
"""
from __future__ import division, print_function
import copy
import numpy as np
from scipy.interpolate import splre... |
47711f5012fb0ffe4e5a571b256452a648bd60e506c9c0b90070afbf560f0415 | Python | 8,353 | 199 | import numpy as np
import torch
from torch import nn
from torch.nn import functional as F
from torch.autograd import Variable
from inv_vae.models.graph_conv import GraphConv
class VAE(nn.Module):
'''
graph auto-encoders.
----
inputs:
----
outputs:
'''
def __init__(s... |
5ec7c68c82a7fe3870df30c56c8ddb7370cdadc357a49512bdd964ee93d65b70 | Python | 8,353 | 195 | from __future__ import annotations
from shutil import which
import pytest
DFTBPLUS_EXISTS = bool(which("dftb+"))
pytestmark = pytest.mark.skipif(not DFTBPLUS_EXISTS, reason="Needs DFTB+")
import os
from logging import INFO, getLogger
import numpy as np
from ase.build import bulk, molecule
from quacc import JobFai... |
d47ccb3d5155bec715502fd92bfd344ebbe935c880a3c4e38b409adeac62eb9c | Python | 8,353 | 207 | # Step 1 of 4: Create k-dimensional bins of neurons, using k selection paramaters and a kd-tree
# Number of bins is dependent on configuration file, which specifies bin size
# Number of bins is 2^n for the smallest integer n such that 31346/2^n <= (bin size)
##
## Load packages
##
print('Loading packages', flush=Tr... |
737313e47f1fe014e730cdb938972dbf830dcd32bebe49c4ece5ada7e6726162 | Python | 8,355 | 216 | import copy
import shutil
import time
import numpy as np
import os
import torch
import torch.backends.cudnn as cudnn
from torch import optim
from torch.utils.tensorboard import SummaryWriter
from src.training.train_utils import AverageMeter, accuracy
from src.utils import timestamp_human
class ClassificationTrainer... |
56c51153b2b9c792e8c1cd0115b644b61223792e9dc9d247e174d98bc88f9b3f | Python | 8,357 | 175 | 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
import pandas as pd
import numpy as np
from PIL import Image
from collecti... |
c5008290eb42c90502e90c5da56dc245ed2f79fdb52148dce86c5b8ec978a754 | Python | 8,357 | 129 | """Paired fixed-context measurements, controls, and cross-prompt persistence."""
from __future__ import annotations
import hashlib
import json
import logging
import os
import time
from pathlib import Path
import numpy as np
import torch
from .connectome import load_graph, sha256
from .environment import inspect_environ... |
0c8ae7f38c7c1964c024d47ef27ef314fb0adbad62b5c7d3716131341536e477 | Python | 8,359 | 177 | """Maintainer-fitted midsagittal planes, committed to the repository.
No fit ever runs on a user's machine. The maintainer fits each atlas once,
inspects the result, and commits the parameters to ``planes.json`` beside this
module; users get them with the repository. ``scripts/fit_hemisphere_planes.py``
is what d... |
54d8a69c74af7bc0ffb52f958707d70854f7e5768547fbe7d1a575f838227c63 | Python | 8,360 | 166 | import numpy as np
from sklearn.metrics import precision_score, recall_score, f1_score
from matplotlib import pyplot as plt
import tqdm
import os
from sklearn.metrics import confusion_matrix
def contingency_analysis(gt, pred, num_clusters, num_classes, unknown_value = 0):
# gt: 1-dim array of integers, ground tr... |
64adb32341f50696768459105d09d8696ff92a895a9149460b60ba0898fa0d18 | Python | 8,362 | 193 | from __future__ import print_function
import time
from itertools import product, islice
from random import choice
from dimensions.common import BOWLS, CUPS
from learn_tools.active_gp import STRADDLE_ACTIVE_GP, VAR_ACTIVE_GP, BATCH_MAXVAR_GP, BATCH_STRADDLE_GP
from learn_tools.active_rf import BATCH_STRADDLE_RF, BATCH... |
dc59a64ee390acbb48a43f7d096d086a080bc89d343ccd9e82d8a1e60edc5dff | Python | 8,365 | 281 | #
# 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,... |
1618a28fbee1ec200bc120341f97adfbe729fadfa35fe0c51efaea401fdc63e9 | Python | 8,367 | 208 | from typing import Callable, Sequence, Dict, Union
import numpy as np
from ..base_transform import EEGTransform
class Concatenate(EEGTransform):
r'''
Merge the calculation results of multiple transforms, which are used when feature fusion is required.
.. code-block:: python
transform = Concate... |
8d1cad8cd82ca38ee6457b3a42c8b277a518e791ac142a1964ec2153f4b7c70c | Python | 8,368 | 190 | import os
import numpy as np
from pandas import read_csv, DataFrame
from pyrelimri.icc import sumsq_icc
def triang_to_fullmat(corr_1darray, size: int):
"""
Convert a 1D array representing the lower triangular part of a correlation matrix (including diagonal)
into a full NxN correlation matrix.
Parame... |
7998c32804465e770c8578af33af3e19e8c047a22f628b7d000c085e14663c09 | Python | 8,369 | 247 | """
Tensorflow Hub Object Detection.
| Copyright 2017-2022, Voxel51, Inc.
| `voxel51.com <https://voxel51.com/>`_
|
"""
import csv
from pathlib import Path
from PIL import Image
import tensorflow as tf
import tensorflow_hub as hub
class TensorFlowHubDetector:
"""Object Detector wrapper class that simplifies use... |
81071dd9b26b52cd5c245fe3258c2128532197925ab536a9bb9a4708edd7a915 | Python | 8,369 | 243 | import os
from sklearn.metrics import roc_auc_score
from tqdm import tqdm
from torch.utils.data import DataLoader
from torchvision import datasets, transforms
import torch
import torch.nn as nn
import pandas as pd
import os
import time
import random
import torch.nn.functional as F
import numpy as np
from mpl_toolkits.m... |
0eb0b581e1cc51ef4fa6afa8c61949ac1fea46d45daff36af7ff710360274434 | Python | 8,370 | 174 | # ------------------------------------------------------------------------
#
# 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... |
ac79f01289a3b0b824b1ff9c508521018299f041c2c06a2c2ace0058450cf7f5 | Python | 8,372 | 199 | """"""
"""
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 softw... |
d596b75e2b695b0c855116b81f43d26dac91bfed6bfc75f643b84c673e3a8aa1 | Python | 8,372 | 128 | """SFF_GENERAL.py 2026-09-29. Pre-registration: 04-NOTES/PREREG-2026-09-29-SFF-GENERAL.md
Can the LN signs be read back from a PN recording in general? Four hidden truths (the laboratory prior + 3 random), one
search (ESCALATE: single-type sweeps, pair moves among the 20 largest types when stuck), started from the cl... |
39faa954c7baab727732098ec137bdbe591be66e63d5efe63bf557d5ad1339b1 | Python | 8,373 | 227 | #!/usr/bin/env python
"""Utility classes to parse SAMPL submissions."""
# =============================================================================
# GLOBAL IMPORTS
# =============================================================================
import os
import io
import glob
import numpy as np
import pandas a... |
17a1196ad464fe7124212c10e1442ebbbec28230434c2afda5b5d88f65f497b8 | Python | 8,376 | 136 | #!/usr/bin/env python
from __future__ import division, print_function
import argparse
import sys
import numpy as np
import topaz.denoise as dn
from topaz.cuda import set_device
from topaz.denoise import Denoise, denoise_stack, denoise_stream
from topaz.denoising.datasets import (make_hdf5_datasets,
... |
5df8384660bdf60f2067c5b15ac7a7676805c4248005f22d3f3d71edb99978a1 | Python | 8,377 | 240 | #
# 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,... |
5093df8bb1603ee143d02285dc9d601de315b57dc00da71f4ef8465499af2ec1 | Python | 8,378 | 135 | # 20230503
import os
import datetime
import argparse
import random
import numpy as np
import torch
import logging
import logging.config
class OptInit():
def __init__(self):
# dataset
parser = argparse.ArgumentParser(description='PyTorch implementation of EV-GCN')
# dataset
... |
9f7bea80ef568745f5cccc8dcfbe568574e313c0f5f51e58a19ce641512e4581 | Python | 8,379 | 231 | """
(*)~---------------------------------------------------------------------------
Pupil - eye tracking platform
Copyright (C) 2012-2020 Pupil Labs
Distributed under the terms of the GNU
Lesser General Public License (LGPL v3.0).
See COPYING and COPYING.LESSER for license details.
------------------------------------... |
4e41beea3327548e1d78283919f82cb9b658fcc9abccf53360e74d0dd51e3501 | Python | 8,382 | 202 | """
DenseNet121
Difference from densenet in torchvision for higher resolution:
1. Modify the stride of first convolution layer (7x7 with stride 2) into 1
2. Remove the first max-pooling layer
"""
import re
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.model_zoo as model_zoo
fr... |
794fecd91d87a98f61d9baddc2725d6535ccb15479917d6bdc2dcdd104b5fbed | Python | 8,382 | 175 | import logging
import math
import pathlib
import traceback
from typing import List
import botocore
from boto3.s3.transfer import TransferConfig
from tqdm import tqdm
from NDATools import exit_error
from NDATools.Utils import get_s3_client_with_config, deconstruct_s3_url, get_directory_input
from NDATools.upload.batch... |
04bc885c8ac159c28f12966f3b73fee2246e1ea24cea95109d09d7ba3b90563a | Python | 8,384 | 231 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from figure_10 import fig_exc_inh_contrib
from plot_methods import plotPowers, plot_population, plot_signal_sum_colorplot, plot_signal_sum
from cellsim16popsParams_modified_spontan import multicompartment_params
import analysis_params
import plotting_helpers as phlp
import ... |
d208c96cade36a9c8a8d60244967b4cae963e1c338abdcfb03d89253ce7cc1de | Python | 8,384 | 233 | import shutil, os
import subprocess
from pathlib import Path
from tqdm import tqdm
from wsilearn.utils.cool_utils import *
from wsilearn.utils.path_utils import PathUtils
def subprocess_cmd(command, verbose=False):
process = subprocess.Popen(command,stdout=subprocess.PIPE, shell=True)
print('runnning cmd %s... |
1ecdd6ea0a22e58013d78edff7634aacc1026af7fb07ff4dcd2025108855256b | Python | 8,387 | 146 | """Identical external injection with and without the external neural cue (real model).
Runs the same sampled stream three times with one scheduled injection: cue off, cue on the
16 DA-annotated neurons, and cue on a size-matched random control group. Before the injection
the three runs are identical by construction (s... |
0bd7c353a71ad9d27ae7a8d52b5c42480a968d2a0f956404afb381dcdcb5ea2f | Python | 8,389 | 219 | deprecated_params = dict(Lambda='lambda_')
def update_param(name, param):
if name == 'lambda':
param['ptype'] = 'numeric, [numeric]'
param['dtype'] = 'Union[float, List[float]]'
return param
return None # param untouched
def class_extensions():
def rule_importance(self):
... |
1387638ad2845575a8fcd598301da40f9ec9c6c8c57760f09e4134bfc9df1281 | Python | 8,389 | 254 | from __future__ import annotations
import gzip
import logging
import os
import shutil
from pathlib import Path
from shutil import copytree
import pytest
from ase.build import bulk
from ase.io import read
from cclib.io import ccread
from maggma.stores import MemoryStore
from monty.json import MontyDecoder, jsanitize
... |
861f3ed43832f879cc0ef82b0f3fc8d7d892f50a8cdb4b50eebf4f3877e917fe | Python | 8,392 | 200 | """
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
Added with:
Pretraining boosts out-of-domain robustness fo... |
304b2ebc786f3e9b896fc11b2ca00c1b300832ff71318595709b077099cf9822 | Python | 8,395 | 230 | # A module to perform GUI-tasks outside a GUI
import numpy as np
from pyclamp.dsp.dtypes import *
from pyclamp.dsp.fpfunc import *
def rescale(x, xlo, xhi, Xlo = 0., Xhi = 1.):
dx = xhi - xlo
if dx == 0.: return x
return Xlo + (Xhi - Xlo) * (x - xlo) / dx
class xygui:
X = None
Y = None
x = None
y = Non... |
db0c5dccdc8ef1d3ef235297e911de900be1bb69da5a88bd34ee05ed01449d9e | Python | 8,395 | 271 | from dreamcoder.domains.arc.arcInput import num_to_id, load_task
from dreamcoder.domains.arc.arcPrimitives import Grid, Input
from dreamcoder.domains.arc.arcPrimitives import primitive_dict as p
from dreamcoder.domains.arc.main import ArcNet
from dreamcoder.task import Task
import numpy as np
import random
import torch... |
87ffe1599cfeab145ccbd6c224fb6677318118be234bda13292c2a5a031fdf96 | Python | 8,397 | 262 | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from einops import rearrange
import os
from timm.models.layers import trunc_normal_
import numpy as np
from segm.model.vit import PatchEmbedding
from segm.model.blocks import Block, FeedForward, CABlock
from segm.model.utils import init_wei... |
32477b2382004f6eb5869fd76941bc5fbe01c2f5578f4c866249987f42a389d5 | Python | 8,398 | 304 | #!/usr/bin/env python3
from argparse import ArgumentParser
from os import environ
from pathlib import Path
from shutil import copyfile, rmtree
from ssl import create_default_context, CERT_NONE
from subprocess import run
from sys import exit
from urllib.request import urlopen
from zipfile import BadZipFile, ZipFile
p... |
4f61d0751e9eddc6387fe090c8868325e1611f4021a69c8a86fa8162322a6d24 | Python | 8,398 | 249 | from __future__ import annotations
import glob
import logging
import os
from pathlib import Path
from shutil import rmtree
import numpy as np
import pytest
from ase.build import bulk, molecule
from ase.calculators.emt import EMT
from ase.calculators.lj import LennardJones
from ase.io import read
from ase.optimize imp... |
69276e4d38d7963b34395b5d39eab68b18ac2bfbee6b655bd15826e600fc4e79 | Python | 8,398 | 231 | # 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... |
e87b4e0e45b1fd11e116401aa4a88bd3bc3ea4fd6c6e0a9c7b64f175bb6969f5 | Python | 8,398 | 230 | import numpy as np
from jitcdde import input as system_input
from symengine import exp
from ....utils.stimulus import OrnsteinUhlenbeckProcess
from ..builder.base.constants import EXC, INH
from ..builder.base.network import Network, SingleCouplingExcitatoryInhibitoryNode
from ..builder.base.neural_mass import NeuralMa... |
efbb51bed5e7a943d6a7cb0300334d7df60bc01bddefbc83bfe7bc87f58deaf1 | Python | 8,399 | 194 | def class_extensions():
@property
def baseline_hazard_frame(self):
if (self._model_json is not None
and self._model_json.get("output", {}).get("baseline_hazard", {}).get("name") is not None):
baseline_hazard_name = self._model_json["output"]["baseline_hazard"]["name"]
... |
43f1c5519b96fa2b5f7189a4f63904a1fadcaffcc2a7315a16d1c615f3d2991a | Python | 8,402 | 275 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# pymrmr documentation build configuration file, created by
# sphinx-quickstart on Tue Jul 9 22:26:36 2013.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# auto... |
9d8e3e7f7e6f896d66e1ffe8a320524a8f5f77597e45a7a8e01f98dbec921482 | Python | 8,408 | 228 |
import os
import os.path as osp
import numpy as np
import torch
import pandas as pd
from torch_geometric.data import InMemoryDataset
from torch_geometric import data as DATA
from rdkit import Chem
from rdkit.Chem import MolFromSmiles
import networkx as nx
from rdkit import Chem
from rdkit.Chem import ChemicalFeatures
... |
a73a0904cc8b5a1d601074a1d84d42127f38e77fefa0f1ff76e52f50f48a4ca4 | Python | 8,408 | 160 | # Copyright (C) 2019 by Computational Science Lab, UPF <http://www.compscience.org/>
# Copying and distribution is allowed under AGPLv3 license
#
# This script generates 3D voxel-based molecular representations from ligand PDB files.
# It uses the RDKit library for chemical processing, MoleculeKit for voxel descriptor ... |
bf7c1ed5bca6b6abc4fa3ffbc824a76f86b4272df6b37cf548b67317dd4da636 | Python | 8,409 | 237 | """distutils.command.install_lib
Implements the Distutils 'install_lib' command
(install all Python modules)."""
import os
import importlib.util
import sys
from ..core import Command
from ..errors import DistutilsOptionError
# Extension for Python source files.
PYTHON_SOURCE_EXTENSION = ".py"
class install_lib(C... |
22b1ac24057be78f7d16abbee2b76ce815b0c9150b2b48466702b088465a6e78 | Python | 8,410 | 219 | # Import necessary libraries
import os
import torch
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import Button
from PIL import Image
import imageio # Import imageio for GIF creation
# Enable automatic casting for mixed precision training with CUDA
torch.autocast(device_type="cuda", dtype... |
a04d55061a61356f86f93eb44803c87fc030cf9ec18c3b71a5ce6524178090e9 | Python | 8,411 | 184 | import pandas as pd
import os
from tabulate import tabulate
import matplotlib.pyplot as plt
from src.analyze.utils import init_mpl
from src.utils import map_to_score_grid
from constants import DATA_DIR, SCORE_COLUMNS
from src.preprocessing2.process_ratings import merge_rating_files
COLORS = init_mpl()
RATINGS_COLUMN... |
6e08da535cb563cab3ee5a475a7f92d6cb27368afa2223a78b309ed340fd364a | Python | 8,412 | 292 | import numpy as np
import numba
from ...utils import model_utils as mu
def timeIntegration(params):
"""Sets up the parameters for time integration
:param params: Parameter dictionary of the model
:type params: dict
:return: Integrated activity variables of the model
:rtype: (numpy.ndarray,)
... |
3b511b20967136b3e10b2ef313e04df0aa6db5ce4d5ab9de31121de9ad8bf472 | Python | 8,413 | 155 | import numpy as np
import nibabel as nib
import h5py
import os
import pkg_resources
from .multregconn import *
from .corrcoefconn import *
from .pc_multregconn import *
from .. import tools
dilateMM = 10
partitiondir = pkg_resources.resource_filename('ActflowToolbox.dependencies', 'ColeAnticevicNetPartition/')
defaul... |
886c09719f81ac43e7a830d34a32bc22ff882da54fb2be315c9025c2231213be | Python | 8,414 | 253 | # 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... |
b82388935107b7ce9a1188517af81c118db98da41f6778dc2edf75c5085edbd0 | Python | 8,419 | 285 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Fit Tensor Factor Regression model
Training
Created on Thu Dec 13 2019
@author: jmagraner
"""
#%% SLURM custer scheduler specs
# As we are submitting a large number of jobs, add these lines before importing
# anything to enforce SLURM resource allocation, since set... |
75c3829c646fac8a02df5ec8be26c8ec9cfb907cf75a3e6e4aaf073f8552377b | Python | 8,421 | 283 | import operator
import os
import random
import sys
import dask.array as da
import dask.dataframe as dd
import joblib
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from dask.distributed import Client
from sklearn.ensemble import RandomForestClassifier
fro... |
f0ef2296f10a3e2b0cf2b2dbd900e27a37458cdf9130a559bd0bca054a1941aa | Python | 8,421 | 223 | """Interface class for acquisition parameters."""
import json
import logging
from collections.abc import Iterable
from dataclasses import asdict, dataclass, field
from pathlib import Path
from typing import Any, Optional
from console.interfaces.dimensions import Dimensions
from console.interfaces.enums import DDCMetho... |
fba52b083d3fe4445af1af31282434f0f1e87669a474dd7528a309e781120ce3 | Python | 8,421 | 231 | """Graph encoders."""
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import manifolds
from layers.att_layers import GraphAttentionLayer
import layers.hyp_layers as hyp_layers
from layers.layers import GraphConvolution, Linear, get_dim_act
import utils.math_utils as pmath
from N... |
14b5bb397de438cd6581de4412927e3accca03dcfc10b5bc2f20c89fef3883d7 | Python | 8,423 | 203 | """
DenseNet121
Difference from densenet in torchvision for higher resolution:
1. Modify the stride of first convolution layer (7x7 with stride 2) into 1
2. Remove the first max-pooling layer
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.model_zoo as model_zoo
from collect... |
12adc7d580df052ee6e19fd2448ca4ff5e9914c74690333c5f883890b0bce7ef | Python | 8,425 | 203 | ''' Script to plot statistical analyses of source localized decoding patterns '''
import mne
#%gui qt
#import matplotlib
#%matplotlib qt
from nilearn import datasets
from nilearn import surface
from nilearn import plotting
from nilearn.plotting import plot_stat_map
from nilearn.image import index_img
fsaverage = dat... |
6a3ced387fbd23b280ff8c2a0d8ca0b476bac54055660169999f0513be071c72 | Python | 8,425 | 329 | import io
import posixpath
import zipfile
import itertools
import contextlib
import sys
import pathlib
if sys.version_info < (3, 7):
from collections import OrderedDict
else:
OrderedDict = dict
__all__ = ['Path']
def _parents(path):
"""
Given a path with elements separated by
posixpath.sep, gen... |
91e2fad4e01ad8af10832878193fc018f763b22c07d8a622d694b69483897c9d | Python | 8,426 | 216 | import argparse
import random
import sys
import numpy as np
import os
import pandas as pd
from tabulate import tabulate
from tqdm import tqdm
import torch
from constants import BIN_LOCATIONS1, BIN_LOCATIONS2
from old_code.dataloaders import get_regression_dataloader_eval
from src.training.train_utils import count_par... |
bbcdd535bdb82fde02380643daf45a9eebab60c018b778ac6b45c795d42e36af | Python | 8,426 | 237 | #!/usr/bin/env python3
"""Convert ring-fragments.txt and rigid-fragments.txt into compact C headers.
Reads:
data/ring-fragments.txt -- SMARTS pattern + xyz lines per fragment
data/rigid-fragments.txt -- SMILES + (atomic_num, xyz) lines per fragment
Writes:
data/ringfragments.h
data/rigidfragments.h
Each h... |
612a5f2e1536a3310dbab79712a509098ccc97dc9968ab6a5fdb113a34d2be54 | Python | 8,428 | 269 | import os
import multiprocessing
from collections import defaultdict
import torch
from torch import distributed as dist
cpu_group = None
gpu_group = None
def get_rank():
"""
Get the rank of this process in distributed processes.
Return 0 for single process case.
"""
if dist.is_initialized():
... |
a0c730820d4f575494ac87aad1205c9c7e7f866ecb08bf1eb89bb71109f4fc78 | Python | 8,429 | 200 | """Preparing the LEMON EEG data
[STEP 1] Preprocessing sensor space data
NOTE: This script was adapted from Quinn2022_GLMSpectrum `lemon_preproc.yml`.
"""
# Install dependencies
import os
import glob
import mne
import logging
import numpy as np
from scipy import io
from pathlib import Path
from osl import preprocessi... |
eaab247b91f2023cc35954ac8dd9c130f6271fb1d76b0ff2cb34c23736412c27 | Python | 8,429 | 248 | """ Estimation module: This module contains functions to estimate the model """
import numpy as np
from itertools import compress
import random
from scipy.optimize import minimize
from TaskAgent.EnAgent import Agent
from TaskAgent.en_task_agent_int import task_agent_int
import matplotlib.pyplot as plt
from TaskAgent.E... |
43cd63917e7f887097a4254968175dc853f63b65ccf6f97a3077b8ea6127aa4c | Python | 8,431 | 285 | from __future__ import annotations
from pathlib import Path
import pytest
from ase.atoms import Atoms
from quacc.calculators.espresso.espresso import Espresso, EspressoTemplate
from quacc.calculators.espresso.utils import grid_copy_files, prepare_copy_files
def test_grid_copy_files_non_gamma():
directory = Pat... |
363bc4df8aff615692cd452683aa20a686ffc638c22c2943ad21ce3a730dcee1 | Python | 8,432 | 236 | # 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... |
6e0778ce1d284dbe5f794e994b1fcaadbb61deb040576ed42df65020966c8c90 | Python | 8,440 | 223 | ###############################################################################
#
#
#
###############################################################################
import numpy as np
import os, csv
import matplotlib.pyplot as plt
from numba import types
from numba.typed import Dict
from scipy.signal import find_peaks... |
b4902b340b149e6f92071fca80f1556347a8ed5826a6b347fd7972fb1e0a9e9d | Python | 8,441 | 244 | # Node-group asset "Starfile Instances" (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_CHE... |
79e59d5a6c59bb32927808758ea0ff40ae22334a5008eb98ec9a25636dce4955 | Python | 8,444 | 195 | #! /usr/bin/env python
from __future__ import print_function
import itertools
import normalize
import pddl
import timers
REDUCE_CONDITIONS = True # caelan: speeds up instantiation
class PrologProgram:
def __init__(self):
self.facts = []
self.rules = []
self.objects = set()
def p... |
4d505dcfdf568a725248327ababfd8d433d7ae1ed626f372edd37ae62fea64ad | Python | 8,445 | 188 | import torch
import torch.nn.functional as F
from utils import setup_logger, load_dataset, feature_generator, adj_polynomials, l2_reg_loss, cluster_infer, cluster_number, \
to_sparse_tensor
from sampler import get_edge_sampler
from model import PolyGCN
from loss import BerPossionLoss
import stopping
from optimizer ... |
7a70434cd24a2e35401612c9776e9fad795c321aaeff97e2321961e6c420ed4b | Python | 8,447 | 165 | """
Tests for the login flows (bot password, clientlogin, OAuth) against the
simulated MediaWiki API. Both the happy paths and the failure paths are
covered, without any real credentials or network access.
"""
import pytest
from wikibaseintegrator import wbi_login
from wikibaseintegrator.wbi_helpers import edit_entity... |
19828f46fec2a63db5d9fa49bbe5f89eb045185a63bb2ba9faedf8ba5d570dfd | Python | 8,448 | 160 | import matplotlib.pyplot as plt
import matplotlib.ticker as plticker
import numpy as np
import os
import pandas as pd
import seaborn as sns
from typing import List, Tuple
from constants import *
from src.utils import assign_bin
from src.analyze.utils import init_mpl
colors = init_mpl(sns_style='ticks', colorpalette='... |
3102ee7013ebcf91bca4bf6b8360661c4afbf114fbb1bb359e56d50061572bce | Python | 8,449 | 210 | import filenames
import read_files
import numpy as np
ANOMALY_WINDOW_SIZE = 'NAB'
NORMALIZE_METRICS = True
ADJUST_ANOMALIES_POSEDGE = True
ROUND = 3
def calculate_anomaly_detection_metrics_main(dataset_filename: str, result_filename: str, detector: str,
data_dir: str = ... |
4022517ba17c086ca36fb853d64dc262cd254ae7320ebcf5fb9aae239592b634 | Python | 8,450 | 285 | from __future__ import annotations
import gzip
import os
import time
from logging import DEBUG, WARNING, getLogger
from pathlib import Path
import pytest
from quacc.utils.files import (
check_logfile,
copy_decompress_files,
find_recent_logfile,
load_yaml_calc,
make_unique_dir,
safe_decompress... |
fb4c253ebcf991348bedd4dc5cb135e4da6c34ac8e6c5cdec8c241cd75397842 | Python | 8,452 | 220 | from itertools import chain
from typing import List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
import torch.nn as nn
import torchmetrics
from torch.utils.data import DataLoader
from ..classifier import ClassifierTrainer, classification_metrics
class DualDataLoader:
def __init__(self, ... |
04e0f31047e1c333123175bd7b15f5c01a2eb388984cf6fd1357896a03ad995b | Python | 8,453 | 199 | import torch
import numpy as np
from model.HighResNet.model import HighResNet
from lib.utils import masked_MAE, masked_RMSE, masked_MAPE
import pytorch_lightning as pl
from model.RNN.model import Teacher
from model import const
class Supervisor(pl.LightningModule):
def __init__(self, adj_mx, scaler, hparams, dp... |
72e47f3626d507cd1f628d9bd7550bcc895c81b4172fc4ed7c50531e00a092d7 | Python | 8,456 | 232 | import torch
import torch.nn as nn
from transformers import BertPreTrainedModel, BertModel
class BertSiameseForSequenceClassification(BertPreTrainedModel):
def __init__(self, config):
super().__init__(config)
self.num_labels = config.num_labels
self.bert = BertModel(config)
self... |
ca230f1dad31c5f55c0fc3cf315cd3823355cb8be8fb08847f4cd07105af6888 | Python | 8,456 | 212 | import argparse
from datetime import datetime
from pathlib import Path
from warnings import filterwarnings
import lightning.pytorch as pl
import pandas as pd
import torch
import yaml
from lightning.pytorch.loggers import CSVLogger
from tqdm import tqdm
from dataset import TCGA_Program_Dataset
from datasets_manager imp... |
a122183a9e7a0a036c5341ccf3626bf288add9759df7ce2b1f8032f0c224b122 | Python | 8,458 | 217 | """Qualitative comparison of dynamic M/EEG resting-state networks
"""
# Set up dependencies
import os
import numpy as np
from sys import argv
from osl_dynamics import analysis
from osl_dynamics.inference import modes
from utils.data import load_data, save_data, load_order
from utils.visualize import DynamicVisualizer... |
6f67eaf659fcec252f3fd30c1b4977e3820d281363486a93ab6ed2a683c18338 | Python | 8,461 | 261 | """Module to detect arousals
"""
from logging import getLogger
from numpy import abs, argmin, asarray, hstack, mean, sum, vstack, where, zeros
from scipy.signal import spectrogram
try:
from PyQt5.QtCore import Qt
from PyQt5.QtWidgets import QProgressDialog
except ImportError:
pass
from .spindle import wi... |
90d20870e79591f82e69364002264ae7f96d3a3f37b24f2e4195458adccc20f6 | Python | 8,463 | 198 | """Multi-slice propagation mixin for the CCF boundary editor.
Carries the two cross-slice propagation commands: translation propagation
(``_on_propagate_active`` -> ``_propagate_to_slice``), which applies the active
component's net centroid shift to neighbouring slices with linear falloff and
same-hemisphere matc... |
e8cbae69357e9eb3bcacdd0e8e1fbe56337dd8f2ef9ff9fb7984f7d84df790ed | Python | 8,463 | 249 | from typing import Iterable, List, Tuple
import numpy as onp
import meep as mp
from . import ObjectiveQuantity
# Meep field components used to compute adjoint sensitivities
_ADJOINT_FIELD_COMPONENTS = [mp.Dx, mp.Dy, mp.Dz]
_ADJOINT_FIELD_COMPONENTS_CYL = [mp.Dr, mp.Dp, mp.Dz]
# The frequency axis in the array retu... |
454cb25f4f6d36fdb400a67992ed32a42ee59d833d724d1356ac1282919229cb | Python | 8,465 | 243 | import numpy as np
import torch
from torch import nn
def _crop_tensors_to_match(x1, x2, axis=-1):
dim_cropped = min(x1.shape[axis], x2.shape[axis])
x1_cropped = torch.index_select(
x1, dim=axis,
index=torch.arange(dim_cropped).to(device=x1.device)
)
x2_cropped = torch.index_select(
... |
ddf911a7c165b915a5a1381985fc132e4932382ef2e781b45e4743e5f03e7c03 | Python | 8,465 | 266 | #https://github.com/sanghvirajit/Medical-Image-Classification-using-CNN/blob/main/Medical_Image_Classification.ipynb
#Fixing issues faced during installation of libraries###
## cv2: https://stackoverflow.com/questions/63732353/error-could-not-build-wheels-for-opencv-python-which-use-pep-517-and-cannot-be
#pip3 inst... |
c1822bc73f029e55b68db8aa56dd79a85d02ae8309f226bafd0a4f2221b3ec09 | Python | 8,466 | 214 | import torch
from einops.layers.torch import Rearrange
from torch import nn
from torch.nn import functional as F
class CausalConv1d(nn.Conv1d):
def __init__(self,
in_channels,
out_channels,
kernel_size,
stride=1,
dilation=1,
... |
eed2c89c7d4a82d29d3472a1e15cb196efe0c620879e9328724ebe998326dfbd | Python | 8,467 | 194 | import numpy as np
from sklearn.utils.validation import (check_array, check_consistent_length)
def _ecdf(data):
"""
Estimates empirical cumulative distribution function of `data`
Taken directly from StackOverflow. See original answer at
https://stackoverflow.com/questions/33345780.
Parameters
-... |
be9a82a4ca00040efff2031bc0f28db102b55ddb7b40cc92e5c7ebf08e56644a | Python | 8,468 | 242 | """Convenience functions built on top of `make_vjp`."""
from collections import OrderedDict
try:
from inspect import getfullargspec as _getargspec # Python 3
except ImportError:
from inspect import getargspec as _getargspec # Python 2
import warnings
import autograd.numpy as np
from .builtins import tuple... |
3a9296a1e2976ec18bb5014a1f63c0567a5a7a9917e22046232bc713ec1a6141 | Python | 8,469 | 245 | #!/usr/bin/python3
# BUGF-Dream 2020 Traning Script by David Jones - (C) University College London 2022
import sys
import os
os.environ["XRT_TPU_CONFIG"] = "localservice;0;localhost:51011"
import time
import gc
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim... |
5ee8166a3664d765e07513befd268c2f41caf88ce853c993703d074b62c847af | Python | 8,469 | 156 |
# Collect predictions
from glob import glob
from pathlib import Path
import sys
import pandas as pd
import numpy as np
# sample used
#beh = 'crycog_ridgeCV'
beh = sys.argv[1]
n = sys.argv[2]
#opts = '_averaged-source_seitzman_nodes_average_runs_REST1_REST1_REST2_REST2-subs_651-params_FC_gm_FSL025_no_overlap_dt_flt01... |
779919cdcadcbeb225a8eb30c0ac1792fd3d328675e77b73085cf359b5c7fd12 | Python | 8,471 | 248 |
#Version 3
from fiji.plugin.trackmate import Model
from ij import WindowManager
from fiji.plugin.trackmate import Settings
from fiji.plugin.trackmate import TrackMate
from fiji.plugin.trackmate import SelectionModel
from fiji.plugin.trackmate import Logger
from fiji.plugin.trackmate.detection import DetectorKeys
from... |
e648f03f26b6bdccb7c59e35391d2d84f8711f130eb4198d77c5f385c6a3d1bb | Python | 8,472 | 222 | from typing import Optional, Dict, List, Type, Any
from .base import AtomicModule
from ..loss import Loss, MissingValueLoss, ForceScaledLoss, MACEHuberLoss
import pytorch_lightning as pl
import torch
import torch.nn.functional as F
import logging
log = logging.getLogger(__name__)
class LitAtomicModule(pl.LightningM... |
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