sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
2a81b7617afa6a49995990662bfcbfcc4d4e7d7dd12a8771242d4d82f1aeb415 | Python | 3,971 | 122 | import torch
from .manifold import Manifold
from diff_frech_mean.frechetmean.utils import EPS, cosh, sinh, tanh, arcosh, arsinh, artanh, sinhdiv, divsinh
class Poincare(Manifold):
def __init__(self, K=-1.0, edge_eps=1e-3):
# print(K,'K')
# print(self)
# print(Manifold)
# sadsd
... |
a0cb4bf5f8f500e4cb22bd1bf3e57361eb4bf76e2a8d6d58e0139e2a42d9b646 | Python | 3,971 | 131 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
'''
Fig4c
usage:
python Fig4c_soma_viz.py --p /Users/jiangshengdian/Desktop/Daily/PhD_project/Platform/fullmorpho/py/soma_marker_in_vtk/soma_0_vs_1.marker
'''
import pandas as pd
import numpy as np
import os
import math
import argparse
import vtk
import vtkmodules.vtkInte... |
ec68c8971217e12b64cf9f8d0d912cbded162e6396b9b42648ab026d1b5f72cb | Python | 3,971 | 123 | """Linear model fitting utilities.
Port of fitLinearPRModel.m and PhotoreceptorModelLinWrapper.m
"""
from dataclasses import dataclass, field
import numpy as np
from scipy.optimize import minimize
from scipy.signal import lfilter
from scipy.signal.windows import gaussian
from .biophys_model import BiophysModel
from... |
5da3cc04ab9d4225a0105220f78100c1f18a9e9f94e589270caa7fbcc23d47f8 | Python | 3,972 | 104 | # -*- coding: utf-8 -*-
"""Basic functions for dataset loaders"""
def sparse_batch(batch_size, drop_remainder=False, num_parallel_calls=8,
atomic_props=['f_data', 'q_data', 'f_weights', 'oxidation']):
"""This returns a dataset operation that transforms single samples
into sparse batched sampl... |
b25985361bf1921209de02fdd393cca95b8614ae538a8976f431256a4c636961 | Python | 3,972 | 142 | # 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... |
44a33ad3d48bdd96b9de13cda9b2138992faae60f9ac5d10e7ae04c03a780048 | Python | 3,973 | 132 | import random
from pathlib import Path
import cocotb
import pytest
from cocotb.clock import Clock
from cocotb.triggers import RisingEdge
import elasticai.creator_plugins.bram as dut
from elasticai.creator.arithmetic import int_arithmetic
from elasticai.creator.testing import CocotbTestFixture, eai_testbench
from elas... |
a4e2484f642db6956a912fa0ef2c02f99ecb439e0e07e93c0735f88bdef3f215 | Python | 3,973 | 117 | """
Optuna example that demonstrates a pruner for Keras.
In this example, we optimize the validation accuracy of hand-written digit recognition using
Keras and MNIST, where the architecture of the neural network and the learning rate of optimizer
is optimized. Throughout the training of neural networks, a pruner obser... |
048ba1bce6ed719691bccdce4cd16e661c17ef6fa4a105519987393d4fcdf344 | Python | 3,974 | 160 | """ Misc. utility methods
"""
import argparse
import hashlib
import inspect
import os
import numpy as np
import bifrost
SYNTHMORPH_SHAPE = (160, 160, 192)
def update_image_array(image, updated):
"""Update ANTs.Image image array but preserve metadata
Args:
image - ants.ANTsImage
updated: array... |
28570e345711c4287b66916b9d0f03eeb8991e9bc94ce343f11dd0a9c98a896f | Python | 3,974 | 114 | import numpy as np
from .pr2_utils import DRAKE_PR2_URDF, set_group_conf, REST_LEFT_ARM, rightarm_from_leftarm
from .utils import HideOutput, load_model, base_values_from_pose, has_joint, set_joint_position, \
joint_from_name, get_box_geometry, create_shape, Pose, Point, STATIC_MASS, NULL_ID, CLIENT, set_pose, \
... |
2d8f3259478b4503e8e9005e9042adbd7ba84dece0f91e0260120c177f868547 | Python | 3,974 | 107 | # 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... |
46142c37987b9d47494645c62a8047c29c2df37cd7e661a76626665db87d3380 | Python | 3,974 | 118 | #
# 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,... |
88fddf3c78678953c91caece53f095edabfe47ff18b217ec9a31a245b2830931 | Python | 3,976 | 142 | """Radiation pattern of a dipole in vacuum using Brillouin-zone integration."""
import argparse
from enum import Enum
from typing import Tuple
import math
import matplotlib.pyplot as plt
import meep as mp
import numpy as np
RESOLUTION_UM = 50
WAVELENGTH_UM = 1.0
NUM_POLAR = 30
NUM_AZIMUTH = 50
FIELD_DECAY_THRESHOLD... |
2cf5394014ced5b7dae517c6c605c229d87986d8b475ee8e103a6d401332a164 | Python | 3,977 | 106 | import torch
import time
import h5py
from collections import OrderedDict
from network import ddnn_run
import net_parameters, net_setup
from network import config_params
from torchvision import transforms
from utils.loaders import save_object
import matplotlib.pyplot as plt
from utils.complex_utils import comp... |
d3af39185e84eab7e3498d9021c184e26b15d3f08006d4b7703db608df5b89ec | Python | 3,977 | 113 | #
# Copyright (C) from 2009 to Present EPAM Systems.
#
# This file is part of Indigo toolkit.
#
# 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
#
... |
3837937246e3a2d4067c4bf7098e835c759ce066aa1f8c37920f8c9c1433d0bd | Python | 3,978 | 127 | # Node-group asset "Find Bonds" (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
fr... |
1561c2dbec2faf4646d90daa4990beb57c124f83cc4c3f46db3ee7c100862bdf | Python | 3,979 | 99 | # QM40data_search.py
# Created by Ayesh Madushanka
# Created on: June 4, 2024
import os
import pandas as pd
from rdkit import Chem
# help function generation
def help_func():
print("Welcome to the QM40 dataset data seraching modular!!!!")
print("QM40 dataset includes a main dataset which has 163K molecules... |
7bbdc3ba47535b1fadf83cb6b48fcbf51aaf71a2780a6f5cd0f7cd6eaf735c92 | Python | 3,979 | 107 | # Node-group asset "Boolean Last" (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
... |
4117e20929fd7e38047603981cab7c834f2ea17eadd15b09bdd326eef92cac6c | Python | 3,980 | 132 | # %% Package Imports
import sys, os
sys.path.append(os.path.abspath(".."))
sys.path.append(os.path.abspath("."))
import torch
import torch.nn as nn
import torch.optim as optim
import prosper_nn.models.hcnn
from prosper_nn.utils import sensitivity_analysis
from prosper_nn.utils import visualize_forecasts
import prosp... |
790a0406d678c8d86f7e2119f2d6bae505f0fd588518dd0cedda6b3b1c9e74b1 | Python | 3,980 | 130 | from collections.abc import Callable, Iterable
from dataclasses import dataclass
from types import FunctionType
from typing import Any, Protocol, override
import pytest
import elasticai.creator.function_dispatch as FD
import elasticai.creator.plugin as pl
from elasticai.creator.plugin import PluginLoaderBase
@datac... |
eb5972efac06375bf861353bb38f8c01a0f7206dfaff9e4e85c52aad41fffdf4 | Python | 3,980 | 96 | #!/usr/bin/env python
# Purpose: Create a .csv file of Nx17 dice coefficients to assess similarity between MSHBM parcs
# Input: ind_parcellation output from Kong2019 pipeline
# Output: 1 Nx17 .csv file with dice coefficients
#
# Note: Users may need to run 'which python' and paste the correct path following the shebang... |
2dee67cccf80f57b491388af6701b24388057d5e0ecc552db7fa61d5dc3f2a3e | Python | 3,981 | 131 | """
Script for computing the RDF of a Graph
Input: - A pickle file with GraphMCF
- RDF parameters
Output: - New properties to are added to the Graph
- Fgiures with the RDF
"""
__author__ = 'Antonio Martinez-Sanchez'
# ################ Package import
import gc
import os
import... |
41819941e192f379d399b5f9eb4d0daa90073a520009cf992007709e290df502 | Python | 3,981 | 138 | import pytest
import tensorflow as tf
import numpy as np
import numpy.testing as npt
import random
from pinn.networks.pinet2 import DotLayer, ScaleLayer, PIXLayer
from utils import rotate
class TestPiNet2:
@pytest.mark.forked
def test_pixlayer_rank2(self):
n_atoms = 10
n_dims = 3
n_c... |
4308986a3c0a1d0610a0d7c77127405d4d4026e6923a8b45e58a987b48a7794b | Python | 3,981 | 128 | # Node-group asset "Transparent Outline Internal" (ShaderNodeTree), 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 ... |
fa7b370ed9050a62cb9fdea99d80b21ad11e5ad50d21ec9240c6ff77619808a3 | Python | 3,982 | 122 | """
Benchmarks for loading structures and evaluating the node groups that style them.
Run locally with `uv run pytest benchmarks --codspeed`, which reports wall-clock times.
In CI they run under CodSpeed's CPU simulation, which tracks results over time and
reports changes on pull requests.
"""
import itertools
from p... |
602699148bcf6fb641f589c601844307bc318a3a81bef29ff0b5a7745d32527a | Python | 3,983 | 61 |
import argparse
import sys
import subprocess
import os
from nilearn import image as img
import pandas as pd
import glob
# Main function
if __name__ == '__main__':
usage = """post_fmriprep.py <path_to_BOLD.nii.gz> <path_to_confound.tsv> <list_of_confounds_to_regress>
e.g. post_fmriprep.py /m/nbe/scratch/braindata/e... |
7c4040c2cd49c5716d4b6c81a7fdb237ada5cdfe4e802104c4be3a865d9ff84f | Python | 3,983 | 153 |
"""
Original Author: Samuel Blau
Modifier: Anup Kumar
Module for adding calculations to a FireWorks LaunchPad.
Includes functions to add transition state and IRC (Intrinsic Reaction Coordinate)
calculations to a LaunchPad for QChem using the FireWorks workflow management tool.
"""
import toml
import glob
import jo... |
537c3df896f6b9d32e314ec8f82440000b45b4bae9f5aded310463a90c141f87 | Python | 3,985 | 139 | # 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... |
d9fae072171ef861391a1f528c4255f8c4dca71cb71bdf84b3c9a97baea71edb | Python | 3,986 | 121 | import sys
import textwrap
from optparse import Values
from typing import List
from pip._internal.cli.base_command import Command
from pip._internal.cli.status_codes import SUCCESS
from pip._internal.utils.misc import get_prog
BASE_COMPLETION = """
# pip {shell} completion start{script}# pip {shell} completion end
""... |
0941688e2769e364f00b00782ad09b6fae8e65609d26b460cf33f2563cd82c15 | Python | 3,988 | 80 |
### algorithm predicted v. homology inferred - to get protein IDs and orthogroup IDs and compare them
#orthology based organelle protein families and species trees retrived from 10.1371/journal.pbio.3002608
import pandas as pd
###COMPARE TARGETP with OGs and PLOT at the same time- comparision takes time, so ... |
6e78e97ffc917186b507b4876bf0ece6135eafbaec152f28644e0bd751ea72bf | Python | 3,988 | 127 | # 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... |
9af07442888e825d3a48bd0870d686178b8b246d8d1a3f112a3bf26df694977d | Python | 3,988 | 128 | #
# 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,... |
a7a630c48b48ce2e6fe2093593131027c149a1ca7cfb1c082c6fb236192b2a55 | Python | 3,988 | 116 | """
oxasl.gui.dist_corr_tab.py
Copyright (c) 2008 University of Nottingham
"""
import wx
from oxasl.gui.widgets import TabPage
class AslDistCorr(TabPage):
"""
Tab page containing options for distortion correction
"""
FIELDMAP = 0
CALIB_IMAGE = 1
def __init__(self, parent, idx, n):
T... |
ca52b9390c81969ac98f907881b793f8bdbcc2d6d9dcac78b0ac26946fcf28f9 | Python | 3,988 | 116 | # 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... |
ec997fbc6eb1935ab63992da9d1465d10bf19eb16068aa84632e95883f5970b8 | Python | 3,988 | 121 | # Node-group asset "Break Bonds" (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
f... |
024fd2332212ea399faf5ba1565fe8f2f01ea3baf5865dfbca1610cbcf7be11f | Python | 3,989 | 150 | import numpy as np
import random
import pickle
import warnings
warnings.filterwarnings('ignore')
import numpy as np
from torch.utils.data import Dataset
class S2R_Dataset_train(Dataset):
def __init__(self, mode, args):
super().__init__()
self.args = args
self.mode = mode
self.... |
e24fda2f3c9cacb683b2b659a4a9f85fdbbef037366a877b59ed231432cd5943 | Python | 3,989 | 108 | """Physical-unit measurements and summary rollups for cellpose detections.
Pure functions — no cellpose, no Qt. The only I/O is reading a TIFF's
resolution tags. Unit-testable without a GPU or the cellpose model.
"""
from __future__ import annotations
import pandas as pd
__all__ = ["resolve_pixel_size_u... |
1163efd9a2a18c1231a8068a1f3c4e58039e7978cd6dd426c779efde540a406d | Python | 3,991 | 101 | # 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... |
336733e5874dfb5ccf84611f02d5ba7dda939d9acd87fb08faf97cb710482087 | Python | 3,992 | 119 | """GUI wiring for the "Affine method" dropdown -> --affine_method.
Two layers, mirroring test_reg_effort_cli_args.py (pure) and
test_parameters_tab_ants_overrides.py (Qt introspection + live widget).
"""
import inspect
import os
import sys
PROJECT_ROOT = os.path.abspath(os.path.join(os.path.dirname(__file_... |
bd54582b8c7f50537561de55c42be1b9793c4f9e775a285bda08cb211720fc0e | Python | 3,992 | 112 | import os
import glob
import numpy as np
import pandas as pd
from sklearn.utils import class_weight
from tensorflow.keras.utils import plot_model as tf_plot
from sklearn.model_selection import GroupShuffleSplit
def get_files(base_dir, resolution):
ext = ['jpg', 'jpeg']
ret_files = []
for f in glob.glob(f'... |
ed5b049af4a4d7e9b0149c7cf04c8b32659a3530c0e19ef91929ee930a66efe0 | Python | 3,992 | 94 | """Batch 2D reuses the single-run tab's advanced registration options through one
shared mapping (ParametersTab.registration_opts_dict), snapshotted into the batch
config so a saved batch is self-contained and can't drift from a single run.
row_to_opts + BatchConfig are pure (no Qt); the ParametersTab mapping is c... |
fcc8bc6c920a8c31235f43fc169983f0ad762a7ce76a1cb8ace2c4f2a0e89152 | Python | 3,992 | 170 | import pytest
from sleeplab_format.models import *
from sleeplab_format import writer
@pytest.fixture(scope='session')
def subject_ids():
return ['10001', '10002', '10003']
def subject_metadata(sid):
return {
'subject_id': sid,
'recording_start_ts': '2018-01-01T23:10:04',
'age': 24.... |
6d3cf5ae37d9bea016ccbb7b0890889f8b088984f4464c722074b54af209a248 | Python | 3,993 | 120 | # ----------------------------------------------------------------------
# Copyright (C) 2014-2015, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions apply:
#
# This program is free software: you can redistribute it and/... |
c7d229e2489c3e971e929fea50059144e12767487dac52f0bc08b9777dc45d3e | Python | 3,993 | 108 | """
t-SNE: Plots
We observe a tendency towards clearer shapes as the preplexity value increases.
The size, the distance and the shape of clusters may vary upon initialization,
perplexity values and does not always convey a meaning.
For further details, "How to Use t-SNE Effectively"
http://distill.pub/2016/misread-t... |
e3ecd9aed3c61e3a42e6739c23b21314d9890710733ccdbb3ee2db8e4d9f7db2 | Python | 3,993 | 106 | """Configure the logging of pyprep."""
# Authors: The PyPREP developers
# SPDX-License-Identifier: MIT
import logging
import sys
LOGGER_NAME = "pyprep"
DEFAULT_FORMAT = "%(asctime)s [%(levelname)s] %(name)s: %(message)s"
class _StreamHandler(logging.StreamHandler):
"""Marker subclass identifying the handler th... |
47c71d19ae2568f19361dcec4bd827f9ff5bc070e63ef491dd2ececff755fac5 | Python | 3,994 | 130 | import os
import toml
import glob
import shutil
import logging
from ase.io import read
from ase.atoms import Atoms
from quacc import get_settings
from quacc import strip_decorator
from typing import List, Dict, Any
from quacc.recipes.newtonnet.ts import ts_job, irc_job, neb_job
def neb_ts_hess_irc_newtonnet(
... |
f4e153e228b356e38b2ff51e2e4779778e03763f6e8d8e52f5ff15d7dfc0d88a | Python | 3,994 | 96 | """Evaluate the end-to-end pipeline on a split and print the paper's metrics.
python -m src.evaluate --data-dir data --split splits/split.json --subset test \
--seg-weights weights/mnuv3_seg_train_no_test_no.pth \
--cls-weights weights/classifier.pth --arch mnuv3
Reports accuracy, sensitivity, spe... |
ec5c676485320ddb77ab8f39aad89dce01cbc81c0b8f40e336f1a4559d85614d | Python | 3,995 | 94 | # 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... |
53f2871218e1c00ae165beb48a4abe2ed08408c62361662f4f546a2f43f9e4fa | Python | 3,996 | 107 | import os.path
import re
from collections import defaultdict
from ckg.graphdb_builder import mapping as mp, builder_utils
#########################
# Reactome database #
#########################
def parser(databases_directory, download=True):
config = builder_utils.get_config(config_name="reactomeConfig.yml",... |
7e5ee484da7e7886f7e048f0b854dee3ffa5eaa5caa4cfd4dd41e4ca165c3f62 | Python | 3,996 | 107 | # 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... |
b3bb6d384e1e6fbeb4e7752b7b4074ecfb9db273564f13a13a0eda6527b274a2 | Python | 3,996 | 146 | import os
import json
import csv
import numpy as np
from tqdm import tqdm
import argparse
import torch
from torch.utils.data import DataLoader, SequentialSampler
import transformers
from transformers import (
DNAKmerConfig,
DNASubConfig,
LongformerForSequenceClassification,
LongformerModel,
BertFo... |
657e12a5b001b832eb58a3598e04efc7e491b30c46faaf7d5f007ca1ea698fda | Python | 3,997 | 111 | import sys
import os
# Get the current script directory
current_script_directory = os.path.dirname(os.path.realpath(__file__))
# Get the root directory of your repository
root_directory = os.path.abspath(os.path.join(current_script_directory, os.pardir, os.pardir))
# Add the root directory to sys.path
sys.path.appen... |
0a4bd3d81fc327e7ab3844aeb97d6703c4a145be342a585669ffd43e977dccb9 | Python | 3,998 | 96 | import os
import numpy as np
from yacs.config import CfgNode
from .interpolate import getAllIdx
from skimage.transform import warp
from tiffile import imread, imwrite
from scipy.interpolate import RBFInterpolator
def rbf_interpolate(source: np.ndarray, target: np.ndarray, cspace: np.ndarray, indices: list, dim: int):
... |
ba7b049e8229d115888f8c404113e46b6eef74054b3178dd309897fd9448be28 | Python | 3,999 | 134 | """Plot community detection performance on empirical networks as box/strip plots."""
import sys
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
import color_palette as cp
# --- I/O configuration ---
if "snakemake" in sys.modules:
result_file = snakemake.input["input_file"]
output_fi... |
5ba7b692b05fb0ec98a5c939a20b3bf3219f9510dc2286d371bc65d0935f55d4 | Python | 4,000 | 80 | import os
import sys
sys.path.append(os.path.dirname(os.path.dirname(__file__)))
import util
import time
import torch
import pprint
from torchdrug.utils import comm
from torchdrug import core, models, tasks, datasets, utils
from siamdiff import dataset, model, task, transform
# new added import for performing CG-scal... |
95caf484d2ce5097fdc0f4b3be1652eb0788a7bca01d0f19d3f998e3a062727b | Python | 4,002 | 113 | import tensorflow as tf
import keras
from keras import layers
from keras import ops
import keras_nlp
image_size = 2000 # We'll resize input images to this size
patch_size = 20 # Size of the patches to be extract from the input images 10, 20
num_patches = (image_size // patch_size)
projection_dim =128
num_heads = 12
... |
abc277660731522c3761f5d204d54b9fd77f42e82b4604648de667da6ed6077f | Python | 4,002 | 116 | # Node-group asset "Attribute Run" (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... |
d5d0cb4811b7813df4cb51f027846f96e0bb6093f681bc07c72a0095553a0b59 | Python | 4,003 | 124 | # Node-group asset "Outline" (CompositorNodeTree), 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
fro... |
0a74621b72d9325b9c714903bc94691a39e0f8d7ea152227eaabcf7887f7c446 | Python | 4,004 | 117 | #!/usr/bin/env python
#
# Copyright 2008, Google Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list... |
c14bac9573ce6a431f0b46bcf51a681949ce38d39e88ec3e44a1d364c7509771 | Python | 4,004 | 116 | #!/usr/bin/env python3
"""
Bonito training.
"""
import os
from argparse import ArgumentParser
from argparse import ArgumentDefaultsHelpFormatter
from pathlib import Path
from importlib import import_module
from bonito.data import load_numpy, load_script
from bonito.util import __models__, default_config, default_dat... |
efdf120ed4a20e4236d1ef60fbad7fc0fbff413f3cacb4ebce5557864bfa03ef | Python | 4,004 | 146 | # 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... |
239d41fbbfff46cce06dde5432cfa110d287153aa0ca0038cbd4a16bc2618eb1 | Python | 4,005 | 139 | """Configure Sphinx."""
# Authors: The PyPREP developers
# SPDX-License-Identifier: MIT
import sys
from datetime import datetime
from pathlib import Path
from intersphinx_registry import get_intersphinx_mapping
from sphinx.config import is_serializable
import pyprep
# If extensions (or modules to document with aut... |
2a1a38f17eb9c44d2c705ca521d7898ccd9b71bbd1befd21d1651b316ac90f70 | Python | 4,006 | 102 | ######################## BEGIN LICENSE BLOCK ########################
# The Original Code is mozilla.org 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 Reserved.
#
# Con... |
5efbf9fc4a1f22c7ff667d5605696a857b96846fa0349c117479e7b7f1a5d3c5 | Python | 4,006 | 110 | import matplotlib.pyplot as plt
from Functions.f_AnalysisStatistics import *
from Functions.f_AnalysisFunctions import *
from Functions.f_SignalProcFuncLibs import *
from Functions.f_AnalysisGraphs import *
import os
import pandas as pd
import scipy.io
import numpy as np
import scipy as sci
import matplotli... |
e096c6f7e8d596342ce467105694e2af457f46533455249e2f8ab2c9f2d657f8 | Python | 4,006 | 105 | """ Keeps track of the model configurations """
from sitetack.app.enums import PtmKind, OrganismKind, LabelKind
from sitetack.app.alphabet import Alphabet
from pathlib import Path
import importlib.util
import pandas
class Model:
""" Given a set of PTM, organism and label, this class represents a model """
d... |
6aa42e7cccd1c38e99a45973998698793dbe9f398a6fe86672b029a6927ceb69 | Python | 4,007 | 105 | ######################## BEGIN LICENSE BLOCK ########################
# The Original Code is mozilla.org 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 Reserved.
#
# Con... |
68446400d797d31dc67b7b1f0b81ac044d24f62486d22f92170443fb037f20e3 | Python | 4,008 | 94 | import json
import matplotlib.pyplot as plt
import numpy as np
import os
import pandas as pd
from src.analyze.utils import init_mpl
from src.analyze.performance_measures import PerformanceMeasures
from constants import N_ITEMS
_FIG_SIZE = (18, 6)
colors = init_mpl()
def make_plot(results_dir1, results_dir2=None, l... |
45031bec5763e678825a2b8a3b8ed891369e55aba8e8c41ae03ccb2b2500d00f | Python | 4,009 | 94 | import pandas as pd
import pickle
import numpy as np
import copy
import glob
import argparse
def used_classifier(CLF_HCSO,CLF_CHT,DF):
Index_RF = ['S_smooth_5 max','S_smooth_5 min','S_deriv_smooth_5 max','S_deriv_smooth_5 min','eig_smooth_5 max',
'eig_smooth_5 min','eig_deriv_smooth_5 max','eig_deriv_smooth_5 mi... |
84291562e3c1813b2a3c6d0bfe9b8ddc6b1bd49123ec120cb680101a9138fe69 | Python | 4,009 | 105 | #!/usr/bin/env python
import sys
import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from pathlib import Path
from PIL import Image
import shap
from tensorflow.keras import models, backend as K
from tensorflow.keras.preprocessing import image
import argparse
# Set log level for 'numba'
impo... |
a4efcb625dc4d208330d5f2ae8db68778170929cbd40b96c96013ab696cc78c5 | Python | 4,009 | 135 | from contextlib import ExitStack
from pathlib import Path
import cocotb as ctb
import pytest
from cocotb.clock import Clock
from cocotb.triggers import RisingEdge
from elasticai.creator.file_generation.resource_utils import get_file_from_package
from elasticai.creator.testing import eai_testbench
pytest_plugins = "e... |
f92cccddcbe69381cc182e6aee718974e104468b417e87f5514f0f164900249d | Python | 4,009 | 106 | #!/usr/bin/env python
"""Copyright (C) 2012 Computational Neuroscience Group, NMBU.
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later vers... |
77efb9d36829a040784b05acddffb802f8b049733cbf53a4a3debedffc287f51 | Python | 4,010 | 152 | # 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... |
95dd3d0e3f15b467a4de7e778a7b5e4a16ed2bf195c32ee2b798560611736fac | Python | 4,011 | 125 | # 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... |
14047334f0e273e81c1b9147d07bfc8b911944fc705125b4198fac872363a06a | Python | 4,015 | 122 | # Node-group asset "Separate Atoms" (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_CHECKIN... |
26ccb6fd1543302be99eed6326f008fb489d15d998bdae078235f905d6000938 | Python | 4,015 | 65 | ### Anikets bottom view dataset
# commands derived from cmd =['/groups/branson/home/kabram//bransonlab/apt_cache_2/aniket_bottom/combinedSideViewMA/20250808T015629_20250808T015637.json', '-name', '20250808T015629', '-train_name','gaussian_noise','-json_trn_file', '/groups/branson/home/kabram/bransonlab/apt_cache_2/ani... |
2ebbf2454922b26123bf29eeaa4d92a166768bb090e9513ed3b11ae32c99fe9f | Python | 4,015 | 109 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Copyright (C) 2020 Computational Neuroscience Group, NMBU.
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at yo... |
dcfbdc2df65a8518d0bad4810ea52c091bb9e3154fb2ba252b729798561c2917 | Python | 4,015 | 98 | """Routing tests for antsRegistration's affine_method split.
antsRegistration calls the two-stage split via the *module* attribute
(``two_stage.run_ants_intensity_split``), not a name imported into ants.py's
own namespace, so both tests monkeypatch ``two_stage.run_ants_intensity_split``
directly on the ``two_stag... |
dbe7ffee99cc27283576f1fa750f7b4dd33f9037ab583734273ab92450c940db | Python | 4,017 | 131 | # 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... |
8e133ce001672102e92bdf5300f6580ed5f25e1763a33ad9b880dfa1da714401 | Python | 4,019 | 120 | #
# 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,... |
9ca513afbf307ad05c5d0957db2f8d9c115a0efbeee98f96a4d8132b39d1af38 | Python | 4,019 | 124 | try:
from Tkinter import Tk, Canvas, Toplevel, LAST
except ModuleNotFoundError:
from tkinter import Tk, Canvas, Toplevel, LAST
import numpy as np
class PRMViewer(object):
def __init__(self, width=500, height=500, title='PRM', background='tan'):
tk = Tk()
tk.withdraw()
top = Toplev... |
ae36f48aaa3ffca3b13c315a65d442011cba084318f365b011ec4385fb36b819 | Python | 4,019 | 160 | # utils.py
import logging
import gzip
import bz2
import subprocess
from pathlib import Path
def open_by_suffix(file_name, mode='r'):
"""Opens file based on suffix."""
# noqa modified from https://stackoverflow.com/questions/18367511/how-do-i-automatically-handle-decompression-when-reading-a-file-in-python
... |
0231d9c2d8de88f4328952cbe8846cd0628f99d70f3046fbfd9bd4407b6a753f | Python | 4,021 | 123 | import math
import torch
def quaternion_to_matrix(quaternions):
"""
From https://pytorch3d.readthedocs.io/en/latest/_modules/pytorch3d/transforms/rotation_conversions.html
Convert rotations given as quaternions to rotation matrices.
Args:
quaternions: quaternions with real part first,
... |
342bd01fa9cbd2d32135698c7edf246e3e4f86c0c9cce9fcae79ba81aab272b3 | Python | 4,021 | 114 | import numpy as np
from elasticai.creator.file_generation.savable import Path
from elasticai.creator.file_generation.template import (
InProjectTemplate,
module_to_package,
)
from elasticai.creator.nn.integer.ram.design import Ram
from elasticai.creator.vhdl.auto_wire_protocols.port_definitions import create_p... |
57dd3b19bf1923ed164f3f5dcfe389917b15500ccc2bce791ada28c6c47ffdbd | Python | 4,021 | 92 | """
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 deeplabcut.utils import auxiliaryfuncti... |
8a9eee7a4b85cd40a4233b5ee3ff156d4a66c29cbd1b1dc775fee2a7f2460faf | Python | 4,021 | 151 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import colors
from PIL import Image
import os
### Animate Kuramoto model results###
def remove_img(fp_in):
"""
Remove all .png files inside the fp_in list
Use with caution.
Param... |
91033823f1235f348165d85c4814c5443e0babe8fb6798d91c9ac470add80d8c | Python | 4,021 | 106 | """Assign nodes to communities via Voronoi (nearest-centroid) clustering in embedding space."""
import sys
import numpy as np
import pandas as pd
from scipy import sparse
if "snakemake" in sys.modules:
emb_file = snakemake.input["emb_file"]
com_file = snakemake.input["com_file"]
output_file = snakemake.ou... |
dba83181984e378113434e56e5bb3a38ae9aaddb6f6703695c9327daf6f2eb0f | Python | 4,022 | 126 | from collections.abc import Callable
from itertools import chain
from typing import ParamSpec
import elasticai.creator.hdl_ir as ir
from elasticai.creator.hdl_ir import IrFactory, Node, Shape
from elasticai.creator.ir import Registry as _Registry
from .filter_params import FilterParameters
from .index_generators impo... |
2607466479f4a2141fafc80b54947459c010bfe832c7abb13a7c8b4c4a9242f7 | Python | 4,023 | 82 | import os
import sys
sys.path.append(os.path.dirname(os.path.dirname(__file__)))
import util
import time
import torch
import pprint
from torchdrug.utils import comm
from torchdrug import core, models, tasks, datasets, utils
from siamdiff import dataset, model, task, transform
# new added import for performing CG-sca... |
8845f9271b011c3a37a79bec08fc0585c1a1fd080382967c59360c1a4ed9447b | Python | 4,023 | 101 | # Dataset Size: 46469
# Unique Labels: 195
# Dataset Shape: (46469, 89, 89)
# Labels Shape: (46469,)
import gdown
import numpy as np
import os
np.random.seed(1234)
def get_raw_dataset():
url = 'https://drive.google.com/uc?id=1-IqQIFQ8X2wM0KU1qyIYZOvur8C_KdVh'
output = '../output/dataset.txt'
gdown.downl... |
ae881e7822a92cfdd46d089e310fab57539ccb354aef30fc07eea84686d169c2 | Python | 4,023 | 95 | #!/usr/bin/env python
# Copyright (c) 2018-2020 Intel Corporation
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
"""
This module provides additional atomic evaluation criteria required
to analyze if a scenario was completed successfully or failed... |
5780cfd4b3fd1375d729a99b05503f5cdccf869a1387268598dccaedbf92ecb2 | Python | 4,025 | 103 | """SupCon / SimCLR loss function
Adapted from HobbitLong/SupContrast.
See THIRD_PARTY for third party license info.
https://github.com/HobbitLong/SupContrast/blob/master/losses.py
Author: Yonglong Tian (yonglong@mit.edu)
Date: May 07, 2020
"""
import torch
import torch.nn as nn
class SupConLoss(nn.Module):
"""... |
5581f743da288cbbcf829dda8aedc96a2cad7ce29dc4c78d524ff95b5bd14c16 | Python | 4,026 | 91 | # SPDX-FileCopyrightText: 2024 Blue Brain Project / EPFL
#
# SPDX-License-Identifier: AGPL-3.0-or-later
'''
Compute neighborhood complexity of (E-E) MICrONS connectome and controls
Note: This script generates some duplicated data. I have decided to keep it, because the files are small and potentially useful
in case ... |
a1ea45be3565b2e4e1773e598eaf207e57d65580a00fe8ece7ec206ffafc1e32 | Python | 4,026 | 112 | import optuna
import joblib
from datetime import datetime
import filenames
import anomaly_detection_metrics
import optimiser_config as oconf
import optimiser_func as ofunc
import main_config as conf
import printer
def objective_andeped(trial, algorithm, dataset, mode, test_id: str, omegas: list, modes_paths: list):... |
cefd296fb0775bb2b8fdaa3c6dd383a26630b26e7d0606f4aa44668c21bb59ec | Python | 4,027 | 90 | import json
import os
import subprocess
from dreamcoder.domains.arithmetic.arithmeticPrimitives import k1, k0, addition, subtraction, multiplication
from dreamcoder.frontier import Frontier, FrontierEntry
from dreamcoder.grammar import Grammar
from dreamcoder.program import Program
from dreamcoder.task import Task
fro... |
fedff5b3888a7c6ca5361a194d3a541aa6f41f67e0215ed0ca1a6f3b302fbba9 | Python | 4,027 | 112 | import numpy as np
from types import *
from pyclamp.dsp.channel import chWaev
from pyclamp.dsp.fpfunc import *
from pyclamp.dsp.wffunc import *
# An active channel modules
class feature(deltaxy): # step and ramp provider
def rety(self, _x = 0, _i = 0):
if isnum(_x): _x = [_x]
x = _x if type(_x) is np.ndarra... |
2f6284a652ba444c74ccd19e5ea30e1a1cb4c2dd98a9bea796c9b2ab8cdf9bec | Python | 4,030 | 89 | from pddlstream.algorithms.downward import apply_action, get_conjunctive_parts
from pddlstream.algorithms.instantiate_task import get_goal_instance
from pddlstream.utils import MockSet
from pddlstream.language.optimizer import UNSATISFIABLE
import pddl
import instantiate
def reinstantiate_action(state, instance, neg... |
6bc682a340a0718d1f3c61cf9d3dd710eeb7a764849d8273a32f18502c44fcaf | Python | 4,030 | 132 | """
Optuna example that optimizes multi-layer perceptrons using Tensorflow (Estimator API).
In this example, we optimize the validation accuracy of hand-written digit recognition using
Tensorflow and MNIST. We optimize the neural network architecture as well as the optimizer
configuration. As it is too time consuming ... |
76c3c56d269eb839fca63a095ae5c89a3d08033d2d433f6fe42b385693744d9e | Python | 4,030 | 78 | """
HEMIBRAIN_CONF_CONTROL.py - the control the conf test needs.
Tightening the conf cut removes T-bars. Removing T-bars lowers n and n_eff, which
RAISES the standard error and should make MORE neurons undetermined, not fewer.
So the observed fall (7.83% -> 6.18% of synapses at conf>=0.95) is a NET figure
fighting a... |
35e4373908d6422e1fb62bacab72fbd30e354d0ef3abd72849bc5afbaae96051 | Python | 4,031 | 98 | import torch
import torch.nn.functional as F
from typing import Dict, Callable
from .utils import expand_to
class Loss:
atom_prop = ["forces", "spin_torques"]
structure_prop = ["energy", "virial", "dipole", "polarizability"]
def __init__(self,
weight : Dict[str, float]={"energy": 1.0, ... |
89a135940029bbad280ebe9940aec1f28fe6def3a13af44a90fc5698177d5f8e | Python | 4,031 | 117 | # 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... |
96a049f47069afca7ea50c91dd7911a8f56120219a247d74c3859389943a7949 | Python | 4,031 | 100 | from lib2to3.pgen2.token import AWAIT
import os
import shutil
import numpy as np
path = "/home/zhaomengdi/Project/eworm/Celegans_as_deep_net_net/chemotaxis_net/components/param/cell/"
files= os.listdir(path)
s = []
params_AWCL = np.array([380, 2, 3e-05, -75, 1.6e-03,
0.0002, 0.0001, 0.001... |
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