sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
07b3052f31f7f808efe34ce4c3eb8dd2be03161b2b619840162e004f3a9eef34 | Python | 8,335 | 215 | '''
Module focused on the implementation of Higher Order SVD
(HOSVD) technique.
'''
import torch
import numpy as np
class HOSVD():
def __init__(self, mode_number_list):
"""
Class that handles Higher Order SVD.
Use the tensor of interest shape as parameter, if all the hosvd modes
ar... |
70e145301060954f149de832cb6922868833ed375f9cd55e62991a481e798d1e | Python | 8,335 | 211 | # Copyright (c) 2021 PaddlePaddle Authors. 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
#
# Un... |
826a4d48aef8130ae8f3742dd0e892fe0e7bb59f70a07f46ada155a442148291 | Python | 8,337 | 211 | import glob
import platform
import nibabel
import os
import numpy as np
import torch
from monai.transforms import Compose, Spacingd, ToTensord, LoadImaged, AddChanneld, ThresholdIntensityd, LoadImage, ScaleIntensityRanged, NormalizeIntensityd
from monai.data import NiftiSaver
from segment_to_segmentbox import generate_... |
f95fdbfe3c26ca8341c19ee7a87190208e330c153ddbd4a36a7ce63c29bad0c8 | Python | 8,341 | 207 | import os
import tempfile
from types import SimpleNamespace
import numpy as np
import torch
from ase.build import molecule
from ase.calculators.singlepoint import SinglePointCalculator
from mace.data.lmdb_dataset import LMDBDataset
from mace.data.utils import KeySpecification, update_keyspec_from_kwargs
from mace.too... |
e862e8e24cc273d371d9ebc16905ec4600649187ed058f8a4ef9411bb85f860d | Python | 8,348 | 186 | import h5py
import sys
import numpy as np
"""
sl files use an lz4 compression filter for which a plugin needs to be installed
Mac:
sudo port install hdf5-lz4-plugin
Ubuntu: (http://gisaxs.com/index.php/HDF5)
sudo add-apt-repository ppa:eugenwintersberger/pni
sudo apt-get update
sudo apt-get install hdf5-plugin-lz4
... |
fa22bfffb8c68dbf6557ceec7f7cc87941bbc20a14eb3224319d4759478d7b5b | Python | 8,357 | 207 | """
Code adapted from https://github.com/ozan-oktay/Attention-Gated-Networks to facilitate LRP,
original code was released under the MIT License copied below:
MIT License
Copyright (c) 2018 Ozan Oktay
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documen... |
2ae827c526ac111828548f6b835503f9e5dc84b248f0244ad2a616bd40d017a2 | Python | 8,383 | 266 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jun 22 21:36:36 2020
@ Modified by Hoseok Choi
"""
"""
Created on Sun Aug 16 21:40:26 2020
@author: Soonhyun Yook
"""
import inspect, os, sys
import numpy as np
from keras.models import Sequential
import tensorflow
from keras.layers import TimeDist... |
4687e628391c2677d8e5f1ff6e557df5130a03c4bb26fe961498ba474da8f61d | Python | 8,384 | 210 | from chromadb.api.types import Embeddings, Documents, EmbeddingFunction, Space
from typing import List, Dict, Any, Optional
import os
import numpy as np
from chromadb.utils.embedding_functions.schemas import validate_config_schema
import warnings
class OpenAIEmbeddingFunction(EmbeddingFunction[Documents]):
def __... |
8a8de51761a43f2178f8d770e30bb57e470b6cf93175e8bf095077a7e497570d | Python | 8,390 | 211 | from __future__ import annotations
import argparse
from pathlib import Path
from typing import Any, Iterable, Sequence
import attrs
import more_itertools as itx
from snakebids import bidsapp
from snakebids.bidsapp.args import ArgumentGroups
from snakebids.exceptions import ConfigError
from snakebids.plugins.base imp... |
37904f68c1ed5575ff6ef8a3a524ec1c1be035c70c2ee4222389cda8b16fbc0a | Python | 8,391 | 243 | from collections.abc import Iterable, Sequence
from itertools import pairwise
import numpy as np
from qtpy.QtCore import QPointF, QRect, QRectF, Qt
from qtpy.QtGui import QColor, QColorConstants, QImage, QPainter
from idtrackerai import Blob
from idtrackerai.GUI_tools import CanvasPainter
def find_selected_blob(
... |
3ce03389d50bc419cc934b13086927fe5297a6b0d14e3fc68768f6175e616926 | Python | 8,393 | 210 | import os
import json
import random
from scipy.io import loadmat
from online import *
allowed_extensions = ['.mat']
def get_system(config):
if config.input_space and not config.online:
return System(config=config, input_space=config.input_space), 'offline'
elif config.input_space and config.online:
... |
6f350a48bfb95ee020fe7495c41210927fa311b567b25b863eaca91068d3821e | Python | 8,399 | 265 |
import numpy as np
from functools import partial
from sleepy.processing.signal import Signal
from sleepy.gui.tagging.model.event import EventTypeNotSupported, PointEvent, IntervalEvent
from sleepy.test.debug import tracing
class Engine:
def run(algorithm, filter, dataset, settings = None):
"""E... |
7441ed6814a0f13b54573fbc2b5080fcec56f25a0a758fe2b88802e74a1bdab4 | Python | 8,403 | 271 | """Test for ExternalProcess component with empty metadata bug"""
import pytest
import json
import tempfile
import os
import sys
import numpy as np
import numpy.testing as npt
from reinvent_plugins.components.comp_external_process import ExternalProcess, Parameters
def create_test_script(script_content: str) -> str:... |
11b4728d8b03e13dab072b0786dada38fb9d08c6e1ccf2045f3907b7491fca04 | Python | 8,409 | 227 |
import torch
import torch.nn as nn
from collections import OrderedDict
from hyper_dti.settings import constants
from hyper_dti.models.noise import EncoderHead
from hyper_dti.models.context import ContextModule
from hyper_dti.models.mlp import Classifier
from hyper_dti.models.utils.initialization import get_initialize... |
c9e5e04d08cc4e56013bcec421b1f2d5369121f16d52753e35224737391c7ff8 | Python | 8,423 | 188 | import re
from typing import Optional, Sequence
import config
import numpy as np
import pytorch_lightning as pl
import torch
from torch import nn, optim
from learning.loss import ComposedLoss, DeepLoss, SoftDiceLoss
def dice_torch(true: torch.Tensor, pred: torch.Tensor):
intersection = torch.logical_and(true, p... |
3ae0b07e75ad71255d0f7026e1cf8a209f7ba46808c040825975c502a67d1963 | Python | 8,424 | 249 | """
Created on Wed Jun 16 13:47:51 2021
@author: Mathieu Scheltienne
"""
import cv2
from ._visual import _Visual
from ... import logger
class Cross(_Visual):
"""
Class to display a cross, e.g. a fixation cross.
Parameters
----------
length : int
The number of pixels used to draw the len... |
36069c87d91162d5f41c18cdcfc6ac82c91d9f0271c125fb54b0c4293800558f | Python | 8,427 | 204 | # -*- coding: utf-8 -*-
#
#
# PyRates software framework for flexible implementation of neural
# network model_templates and simulations. See also:
# https://github.com/pyrates-neuroscience/PyRates
#
# Copyright (C) 2017-2018 the original authors (Richard Gast and
# Daniel Rose), the Max-Planck-Institute for Human Cogn... |
5a6f80b0bc18abfad481677ed8a51d0666c781cb518968662e382d194599f4d6 | Python | 8,430 | 177 | # Copyright (c) 2021 PaddlePaddle Authors. 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 appli... |
d0d1c368aa50deef47c8bf46e799b51ba6cda82a4d9ca55157f939ca32333645 | Python | 8,439 | 244 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# OS stuff
import os
import sys
import warnings
from pathlib import Path
# Computational stuff
import numpy as np
import matplotlib as mplb
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec, GridSpecFromSubplotSpec
from matplotlib import font_manag... |
0bd315f5987526ff5dc99e7d53ccff20d3ef6229b1fcd935a0f932dd8ff18ef2 | Python | 8,441 | 250 | # copyright (c) 2021 PaddlePaddle Authors. All Rights Reserve.
#
# 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 applica... |
caba36cc6aa39fdbcbef8a3da00165ce35a83d456a6de0bddfb690cab371ca23 | Python | 8,450 | 168 | import itertools
from typing import List, Tuple, Dict
import warnings
from deeperwin.configuration import set_with_flattened_key, Configuration
import copy
from deeperwin.run_tools.dispatch import dispatch_job, build_experiment_name, setup_experiment_dir, dump_config_dict, idx_to_job_name
from deeperwin.run_tools.geome... |
0127f78919b9d91115f5e7c7d7392ccaab8903550422752ae3a7ba6158c82f53 | Python | 8,451 | 263 | from tqdm.auto import tqdm, trange
import numpy as np
import torch
from sample_for_integral import project2simplex
from util import NesterovGD
@torch.no_grad()
def estimate_weight_wonbr(
Y, M, X, sigma_yx, prior_x_mode, prior_x, context, n_epochs=10000, tol=1e-5, update_alg='gd', verbose=True):
"""
min 1/2σ^2 |... |
3e6b09e687fbba4e19fc8d9a348227689d92ae8de8e5346182dbaae9d2cf990b | Python | 8,451 | 247 | # Copyright 2020-2025 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
from openfl.experimental.workflow.interface import FLSpec
from openfl.experimental.workflow.placement import aggregator, collaborator
from tests.end_to_end.utils.exceptions import ReferenceFlowException
import io
import math
import logging
... |
f7d4f656f49b63464b3d2e461e01a028bffe878ed7fdccbf0ec906603a2e6a5f | Python | 8,452 | 275 | import json
import copy
from math import floor, ceil
import numpy as np
from corgie.helpers import crop
def get_bcube_from_coords(start_coord, end_coord, coord_mip, cant_be_empty=True):
xs, ys, zs = [int(i) for i in start_coord.split(",")]
xe, ye, ze = [int(i) for i in end_coord.split(",")]
bcube = Bound... |
47c8799bbfaa6d2e601266df424448969270e1cc31c33422fd8222bdd86781e5 | Python | 8,453 | 257 | from abc import ABC, abstractmethod
from typing import Tuple, Dict, Any
import gym
import numpy as np
import torch
from ..datasets.preprocess import subsample, gray_scale, binary_image, crop
from ..encoding import Encoder, NullEncoder
class Environment(ABC):
# language=rst
"""
Abstract environment class... |
d62a2c75dcf10c4cea49d2b4dc46010db8404e328050713f96f1f92dcbecd786 | Python | 8,453 | 262 | import logging
from typing import Dict, List, Optional
import torch
from prettytable import PrettyTable
from mace.tools import evaluate
def custom_key(key):
"""
Helper function to sort the keys of the data loader dictionary
to ensure that the training set, and validation set
are evaluated first
... |
a7468d7f8836eac8df5a35617bc468d7c9d07e51a27f7a0b72b7a289859667b7 | Python | 8,456 | 261 | """constants.py: Module that stores several useful constants for the project."""
# Dataset name
MASS_SS_NAME = "mass_ss"
MASS_KC_NAME = "mass_kc"
INTA_SS_NAME = "inta_ss"
MODA_SS_NAME = "moda_ss"
CAP_SS_NAME = "cap_ss"
PINK_NAME = "pink_nn"
NSRR_SS_NAME = "nsrr_ss"
# Database split
TRAIN_SUBSET = "train"
VAL_SUBSET =... |
dd7b4759c68e699eaa5eef19b07283485355affc2c4177408182acf225acf111 | Python | 8,457 | 214 | import os
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from tqdm import tqdm
# load
PATH_OUT = 'Results/inferring_dtis/'
if not os.path.exists(PATH_OUT):
os.makedirs(PATH_OUT)
print(f"Folder '{PATH_OUT}' created successfully.")
datasets = ['DrugBank', 'BIOSNAP', 'Binding... |
0efa80e724c38c905da52075eaa127beec79aaf9a1c387ea6b69bd45cf441ab8 | Python | 8,461 | 276 | """Scoring component for generic Maize workflows
Calls Maize workflows in a serialized format, utilizing the`ReinventEntry`
and `ReinventExit` nodes to provide a consistent JSON interface.
Example use:
.. code-block:: toml
[stage.scoring.component.Maize]
params.executable = "/home/me/miniforge3/envs/maize-dev/b... |
44d643bd18b9fc5833b941e74d9729b86e4d8effe3acd9f16166c6e230d0bfa3 | Python | 8,465 | 245 | # -*- coding: utf-8 -*-
#
# Configuration file for the Sphinx documentation builder.
#
# This file does only contain a selection of the most common options. For a
# full list see the documentation:
# http://www.sphinx-doc.org/en/master/config
# -- Path setup ------------------------------------------------------------... |
d76a2ea9cac6009a3046304e3c60034a45a90c740a62fe01a10ee729f5ff3ef6 | Python | 8,470 | 287 | # -*- coding: utf-8 -*-
"""
Created on Thu Apr 22 14:30:31 2021
@author: nicol
"""
import os, glob, tqdm
from skimage.io import imread, imsave
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib import rc
import matplotlib as mpl
import scipy.ndimage as ndi
fro... |
084afec9ff3d33f0a82e0a9698d3ed30ead259cf649ced6acf227cd12443e8e4 | Python | 8,486 | 227 | # Copyright 2020-2025 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""AggregatorGRPCServer module."""
import logging
from concurrent.futures import ThreadPoolExecutor
from multiprocessing import cpu_count
from random import random
from time import sleep
from grpc import StatusCode, server, ssl_server_cre... |
bbf3d3d15bbbed99ab954c9e7e5ea6a694c4141774c5d5c73e9222821b382748 | Python | 8,487 | 262 | # Copyright 2020-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""SKCPipeline module."""
import copy as co
import gzip as gz
import numpy as np
from sklearn import cluster
from openfl.pipelines.pipeline import TransformationPipeline, Transformer
class SparsityTransformer(Transformer):
"""A tra... |
c6ec1a4300251469c011958f23d605559eca5246870e132f54c651728b5f60e5 | Python | 8,487 | 257 | # WiltingPriesemann toolbox for MR estimation
# Authors: Jens Wilting & Viola Priesemann
# Max-Planck-Institute for Dynamics and Self-Organization
# Am Fassberg 17
# D-37077 Goettingen
# Germany
#
# Minimal toolbox for MR estimation according to
# Wilting & Priesemann, 2018
import numpy as np
import scipy.stats
import... |
999655f674991dcd7cdfdd7e70d94719670e782d31420c763c2b8fa9171d74ef | Python | 8,489 | 255 | import lungmask
from lungmask import mask
from monai import transforms
from monai.transforms.intensity.array import ThresholdIntensity
from monai.transforms.spatial.array import Resize, Spacing
from monai.transforms.utility.dictionary import ToTensord
import torch
import numpy as np
from monai.transforms import (Compos... |
9c55f645429529ab48006169e2e9b162bf3384aff3abae9ca0a9f419b5d4272c | Python | 8,494 | 257 | from typing import Any, Dict, List
import pytest
from chromadb.api.collection_configuration import (
load_collection_configuration_from_json,
load_create_collection_configuration_from_json,
load_update_collection_configuration_from_json,
)
from chromadb.api.types import (
Documents,
Embeddings,
... |
078855b6bff20669ea03905a39a79a63e543eb22a79d3531eb311c21df59f075 | Python | 8,501 | 195 | """
# Fingerprinting - CAMCAN Cohort
## HCTSA Similarity variance
Script - hctsa similarity
Author: Frédéric St-Onge
Date created: 2021-12-08
Date modified:
Version: 1.0
--------
Purpose:
--------
This script is made to compute temporal similarity like in the paper by Golia et al. (2020; eLife). In this paper,... |
7ecfa7b28d0631922976bac8c376825004ba5b6cf334055276f3f1677ed9bebf | Python | 8,501 | 238 | """Inspect one remote DANDI NWB asset through PyNWB and LINDI."""
# /// script
# requires-python = ">=3.13,<3.14"
# dependencies = [
# "dandi>=0.81,<0.82",
# "lindi==0.4.6",
# "platformdirs>=4.3,<5",
# "pynwb>=4.2,<5",
# ]
# ///
from __future__ import annotations
import argparse
import time
from coll... |
09f05bc1187af8915125490deb650be6061fa1019801a1eea94c696d5130cc70 | Python | 8,506 | 166 | # %%
import os
import numpy as np
import time
import h5py
import sys
from scipy import sparse
from scipy.io import savemat, loadmat
import multiprocessing as mp
sys.path.insert(1, '../..') # the path containing "suns" folder
os.environ['KERAS_BACKEND'] = 'tensorflow'
# os.environ['CUDA_VISIBLE_DEVICES'] = '0' # Set w... |
d62b753bd1986edf6bf9ca760ddf56ac6387ebbc4be3ad33832464d872c9eb14 | Python | 8,508 | 252 | import pytest
from nequip.utils.unittests.model_tests_ase_integration import ASEIntegrationMixin
from nequip.utils.unittests.model_tests_train_time_compile import TrainTimeCompileMixin
from nequip.utils.unittests.model_tests_lammps import LAMMPSMLIAPIntegrationMixin
from nequip.utils.unittests.model_tests_torchsim impo... |
0f2f32e8d20d7f540661bec977bdfb090f42be6d656800f67b496d20b941f1a9 | Python | 8,513 | 190 | import math
import json
from openpyxl.worksheet.table import Table, TableStyleInfo
from openpyxl.styles import Alignment
from nilearn import plotting,image,surface,datasets
from utilityFunctions_yz import *
import collections
bn_atlas_file = 'PROJECT_DIR/scripts/features/bnatlas_tree.json'
parent_substitutions={
... |
1188834ce19d7bfa1486cadc63bac3c9a921be71b6d93def279241f618bcd057 | Python | 8,514 | 256 | """Scalar product of a Riemannian metric.
Define the product of a Riemannian metric with a scalar number.
Public Methods:
register_scaled_method(func_name, scaling_type)
Public classes
ScalarProductMetric
Lead author: John Harvey.
"""
from functools import wraps
import geomstats.backend as gs
import geoms... |
4c43793f4be48f4bfabb6f26502e52eb3ce3b0c1ab7d0d9a23034f14ebeed4cb | Python | 8,516 | 246 | """Sample SMILES from a model
LibInvent, LinkInvent and Mol2Mol need input SMILES while Reinvent does not.
The output is a list of SMILES including the fragments where applicable and
the negative log likelihood if requested.
"""
__all__ = ["run_sampling"]
import logging
from torch.utils.tensorboard import SummaryWri... |
ad0703fb7b900891d095da64c4ff049ae18fad80041f8b6400f3f50ce219babe | Python | 8,523 | 259 | import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from neuron import h, gui
from scipy import stats as st
h.load_file("nrngui.hoc")
h.load_file("import3d.hoc")
h.load_file("models/biophys_HL23MN1.hoc")
h.load_file("models/biophys_HL23PN1.hoc")
h.load_file("models/biophys_HL23BN1.hoc")
h.load_file("... |
4ced1d0a06ee48b29e0a5b5fe057320eaa962809078ae0076636bbeecf978c36 | Python | 8,526 | 197 | # Copyright (c) 2021 PaddlePaddle Authors. 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 appli... |
4a2ad9a2376440a784e26ba16004e3db42c3ef420c8c01047c404743555bf88d | Python | 8,529 | 184 | import torch
from torch import Tensor
from torch_geometric.utils.loop import add_remaining_self_loops
from dig.version import debug
from ..models.utils import subgraph
from .utils import symmetric_edge_mask_indirect_graph
from torch.nn.functional import cross_entropy
from .base_explainer import ExplainerBase
fr... |
7a2626d7da71ae5c98c133e23dbcb73da3ed9408eb279e945aa6eeeb9fe9e08e | Python | 8,542 | 260 | # -*- coding: utf-8 -*-
import os
import argparse
import logging
import torch
from torch.nn import CrossEntropyLoss, KLDivLoss, NLLLoss, SmoothL1Loss, BCELoss, BCEWithLogitsLoss
import torch
from torch import nn
import torch.optim as optim
from torch.optim.lr_scheduler import ReduceLROnPlateau
import torch.utils.da... |
9a98698d2af8863a64eb52ff892f02e94797f3f0e6377c7b18326ebcc986e342 | Python | 8,542 | 229 | import multiprocessing
from concurrent.futures import Future, ThreadPoolExecutor, wait
import random
import threading
from typing import Any, Dict, List, Optional, Set, Tuple, cast
import numpy as np
from chromadb.api import ClientAPI
import chromadb.test.property.invariants as invariants
from chromadb.api.segment imp... |
ab1969a148fbb13c015b689f94bbed6a9072e151f2e068c36474612d767cf6fc | Python | 8,543 | 227 | """Plugin for editing experimental metadata and sweep conditions."""
from __future__ import annotations
from functools import partial
from typing import Any
from PyQt5 import QtCore, QtGui, QtWidgets
import sanpy
from sanpy.interface.plugins import sanpyPlugin
class SetMetaData(sanpyPlugin):
"""Edit experimen... |
40c45513625a90d4a39077099ee657d362c9f85fa2d49ed4a63edf7732721d7c | Python | 8,549 | 193 | """
Estimate the logarithmic multi-unit activity (MUA) by averaging the power
in a given frequency range.
"""
import numpy as np
from elephant.spectral import welch_psd
from elephant.signal_processing import butter
from scipy.stats import zscore
import quantities as pq
import matplotlib.pyplot as plt
import seaborn as... |
1976c091316b8e566c54f8e6ff884b6a2acb8cf43079484edd50a3b62b8091e1 | Python | 8,552 | 224 | import numpy as np
import matplotlib.pyplot as plt
import copy
from scipy.io import loadmat
from sklearn.decomposition import PCA
from matplotlib.gridspec import GridSpec
from matplotlib.collections import LineCollection
from matplotlib import colors as mcolors
import matplotlib.patheffects as pe
def preprocess(dat... |
292eefbb6380284704e3fd1211e5f39a65538af714d8cf73a6aec254ef2640ea | Python | 8,555 | 193 | """
Estimate the logarithmic multi-unit activity (MUA) by averaging the power
in a given frequency range.
"""
import numpy as np
from elephant.spectral import welch_psd
from elephant.signal_processing import butter
from scipy.stats import zscore
import quantities as pq
import matplotlib.pyplot as plt
import seaborn as... |
be4bb35b3b09ae05ce45f3040ecc08639a045644e1bf984319ee6d0c61f6987e | Python | 8,556 | 252 | import json
import logging
from pathlib import Path
from shutil import copyfile
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from torch.optim.lr_scheduler import MultiStepLR
from torch.optim.sgd import SGD
from idtrackerai import Session, conf
from idtrackerai.utils import load_id_images
fro... |
66ba1abdbbc86ffafc729cb91fe8b7fdd6607cef5af283c21dd5849ee9fd5b5a | Python | 8,557 | 184 | """What happened to the id you had.
An id that vanishes is the failure a consumer cannot diagnose: a reference that used to resolve
returns nothing, and nothing distinguishes a correction from a deletion. So every level keeps a
lifecycle row, and the row holds only what a build cannot recompute (``ROADMAP.md`` section... |
73e1f690029c701e8fbcf694865ddd0c837d7a87dea585a9f7ead0b9e697e10f | Python | 8,562 | 283 | # Copyright (c) 2021 PaddlePaddle Authors. 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
#
# Un... |
ef5d3fd44c70aa28284a08aeb92c1c8ae2d318aebdb78326b2e422f447abf343 | Python | 8,562 | 229 | import pickle
import numpy as np
from aux_fun import remove_SPH , construct_target_B, performance
from regularization import get_firing_power, alarm_generation, alarm_processing
from evaluation import alarm_evaluation, sensitivity, FPR_h, statistical_validation
from datetime import timedelta as dt
import time as ... |
b6e9ab01df6144c848c83d2b5eb6d89f9bb4bf564c9015d166e8b68bf6384e7c | Python | 8,567 | 166 | # %%
import os
import numpy as np
import time
import h5py
import sys
from scipy.io import savemat, loadmat
import multiprocessing as mp
sys.path.insert(1, '../..') # the path containing "suns" folder
os.environ['KERAS_BACKEND'] = 'tensorflow'
# os.environ['CUDA_VISIBLE_DEVICES'] = '0' # Set which GPU to use. '-1' use... |
33024fc9c0452a1a11d0d58386439136240983c40d38d1db152075943a0fa7f4 | Python | 8,568 | 168 | # %%
import os
import numpy as np
import time
import h5py
import sys
from scipy import sparse
from scipy.io import savemat, loadmat
import multiprocessing as mp
sys.path.insert(1, '../..') # the path containing "suns" folder
os.environ['KERAS_BACKEND'] = 'tensorflow'
# os.environ['CUDA_VISIBLE_DEVICES'] = '0' # Set w... |
2f08d6f1bfc31873a5842f826ca2771c46db592edb25e139445003d6b94c6cbb | Python | 8,569 | 476 | from reinvent.datapipeline.filters.regex import SMILES_TOKENS_REGEX
KNOWN = [
(
"Cc1cccc(C2Sc3ccccc3NC3=C2C(=O)c2ccccc23)c1F",
[
"C",
"c",
"1",
"c",
"c",
"c",
"c",
"(",
"C",
"2",
... |
f2359eaf632f94c8eca03bf58b38f4e5f1bdebb5cb3451a81efce60add15bb76 | Python | 8,569 | 249 | # Copyright (c) 2020 PaddlePaddle Authors. 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 appli... |
69937ae1a33aef9b71607e8c8512045fc3bc01cc3572fa8ae3572d89625a2e9d | Python | 8,570 | 232 | from chromadb.api.types import Embeddings, Documents, EmbeddingFunction, Space
from typing import List, Dict, Any, Union, Optional
import os
import numpy as np
from chromadb.utils.embedding_functions.schemas import validate_config_schema
from chromadb.utils.embedding_functions.utils import _get_shared_system_client, ge... |
e749772e086654575c3036d4c9f2099399164a99e326fda8a08b7447a8a5cb1b | Python | 8,574 | 233 | import numpy as np
import pandas as pd
import polars as pl
import pytest
from nltools.data.designmatrix import DesignMatrix
class TestDesignMatrixConstruction:
"""Test all supported ways to create a DesignMatrix."""
@pytest.mark.parametrize(
"input_data,kwargs,expected_cols",
[
(n... |
47528c718b8f5d6d56b752ea1ee3f7048ba122b425f50c341e4c3ac6adcfbe2d | Python | 8,575 | 194 | """
Estimate the logarithmic multi-unit activity (MUA) by averaging the power
in a given frequency range.
"""
import numpy as np
from elephant.spectral import welch_psd
from elephant.signal_processing import butter
from scipy.stats import zscore
import quantities as pq
import matplotlib.pyplot as plt
import seaborn as... |
33ab9b731bfcfcabcbbd7a7cdc5096fd2bd9cb48acbdcfd8f9ff9b4106170fff | Python | 8,578 | 264 | # Copyright (C) 2020-2023 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
from openfl.experimental.workflow.interface.fl_spec import FLSpec
from openfl.experimental.workflow.interface.participants import Aggregator, Collaborator
from openfl.experimental.workflow.runtime import LocalRuntime
from openfl.experime... |
8ba6749ab026c1f3b2c1dc47939577b76f6373e8de0c5645e318f8af515c0803 | Python | 8,581 | 261 | from matplotlib.backends.backend_pdf import PdfPages
import matplotlib
import numpy as np
import renderapi
import argschema
from ..schemas import *
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from matplotlib.colors import Normalize
import mpl_scatter_density
def transform_pq(tspecs, matches):
p = []
... |
5f16e81983d496b673424c40781ebe604ea6e8ae07ede80560693d22153eaf8d | Python | 8,588 | 174 | from plotly import graph_objs as go
import numpy as np
import json
import pickle5 as pickle
import os
from scipy.io import savemat
#
bn_atlas_file = '/Users/zhangyuan/Desktop/Sherlock/projects/sryali/2019_DNN/scripts/features/bnatlas_tree.json'
with open(bn_atlas_file) as f:
bn_atlas=json.load(f)
def generate... |
c54998885b86875e7726d5ae6702f438c5284545d3607f3b0bbeb661ed6e0888 | Python | 8,604 | 219 | # -*- coding: utf-8 -*-
"""
Twig-profreafing analysis of presynaptic inputs
Clean code for publication
@author: Sebastian Molina-Obando
"""
#Importing packages
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import os
import numpy as np; np.random.seed(0)
... |
5c0e4397dd748519265a6dcea8557e7d5bb23f66940ae646287a531b7ea17ce2 | Python | 8,612 | 148 | """PubMed author lists as a reviewed input to offline provenance checks."""
from __future__ import annotations
import unicodedata
import urllib.parse
from pathlib import Path
from xml.etree import ElementTree
import polars as pl
AUTHOR_TABLE = Path("proofreading/pubmed_authors.tsv")
def author_key(name: str) -> st... |
9062d40d51739ec6d4d712502830c31be06c1c2af90296a6fb81a853a289e7e5 | Python | 8,612 | 231 | import math
import geomstats.backend as gs
from geomstats.test.data import TestData
from .complex_riemannian_metric import ComplexRiemannianMetricTestData
LN_3 = math.log(3.0)
EXP_4 = math.exp(4.0)
class Siegel2TestData(TestData):
def belongs_test_data(self):
data = [
dict(point=gs.array([[... |
83d009b8c0fcf8addb06d450eefbab683227d829769f75b2f1921174e004a6dc | Python | 8,619 | 264 | import os
import numpy as np
import pandas as pd
#import logging
import time
from itertools import product
import torch
import torch_geometric.transforms as T
from sklearn.metrics import roc_auc_score, average_precision_score
from gridsearch_GeNNius import GridSearchModel, EarlyStopper, shuffle_label_data
print('-')... |
de7d0a7836aeee7a2755a8b5df3c4ae66b30eefcd54dad782ce537bb77223cc6 | Python | 8,620 | 253 | # Copyright (C) 2020-2023 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import sys
import numpy as np
from openfl.experimental.workflow.interface import FLSpec, Aggregator, Collaborator
from openfl.experimental.workflow.runtime import LocalRuntime
from openfl.experimental.workflow.placement import aggregator... |
0cd168faed710b8f12c001b7a0b34658887775c7077728a247fe40652eae9877 | Python | 8,621 | 248 | # Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.abs
from pathlib import Path
from t... |
656ebcae87018b1d1ae7ba6a59e702c617782c9b5bfb5b9c8055492af42f9ada | Python | 8,621 | 245 | # Copyright (c) 2022 PaddlePaddle Authors. 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
#
# Un... |
18d746dd889541f8c461bce2625056c101c6938b890bf18ba1a1f5dc6838b6da | Python | 8,625 | 220 | import torch
from torch_geometric.nn import MessagePassing
from torch_geometric.nn import global_add_pool, GENConv, DeepGCNLayer
import torch.nn.functional as F
from torch.nn import ReLU
from torch_geometric.nn.conv.gcn_conv import gcn_norm
from ogb.graphproppred.mol_encoder import AtomEncoder, BondEncoder
def make_m... |
bf63adda95e5ab796707cb22bf3d35fb23bc18be7703663d4d937045dfb10b7d | Python | 8,631 | 194 | # TWO-NN: Intrinsic dimension estimator by a minimal neighborhood information.
#
# Author: Maria d'Errico <mariaderr@gmail.com>
#
# Licence: BSD 3 clause
from __future__ import annotations
import warnings
import numpy as np
import heapq
from sklearn.base import BaseEstimator
from sklearn.utils.validation import check_... |
0e97d4ef3983d091ec2012a54dd6de9f4e215ac30d1302f6f2af8574089cce41 | Python | 8,637 | 167 | # %%
import os
import numpy as np
import time
import h5py
import sys
from scipy import sparse
from scipy.io import savemat, loadmat
import multiprocessing as mp
sys.path.insert(1, '../..') # the path containing "suns" folder
os.environ['KERAS_BACKEND'] = 'tensorflow'
# os.environ['CUDA_VISIBLE_DEVICES'] = '0' # Set w... |
914a5e72c20d5d83bc7fcf9e4f51cea9169785d4b7d2682dd2d7df3f32b7aa42 | Python | 8,642 | 238 | # Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this sof... |
4b1e953fb234366037dc6971434614e2ec82148128b4c6a8fb10638814019a2b | Python | 8,647 | 287 | import os
import click
from corgie import scheduling
from corgie import helpers, stack
from corgie.log import logger as corgie_logger
from corgie.boundingcube import get_bcube_from_coords
from corgie.cli.compute_stats import ComputeStatsJob
from corgie.argparsers import (
LAYER_HELP_STR,
corgie_optgroup,
c... |
1921f74b601d24d4bf00955e9d847650f035e81531d4a372e935fc287e5ede1a | Python | 8,648 | 270 | import flammkuchen as fl
import numpy as np
from joblib import Parallel, delayed
from split_dataset import EmptySplitDataset, Blocks
from fimpy.alignment.volume import (
find_shifts_sobel,
shift_stack,
sobel_stack,
)
from skimage.registration import phase_cross_correlation
from fimpy.alignment.plane import... |
8a43c377ea2cf17045719d1c07812f57b73610bc58226193f87378a78a4f37ad | Python | 8,650 | 229 | import numpy as np
from sleeprnn.common import constants
from sleeprnn.detection import metrics
from sleeprnn.detection.feeder_dataset import FeederDataset
from sleeprnn.helpers import misc
def performance_vs_iou_with_seeds(
dataset,
predictions_dict,
optimal_thr_list,
iou_curve_axis,
iou_hist_bi... |
4eecbae38ab5e86c3d5dcc2e7364e2a3b772fb34232a8095c8113b02f47dbb13 | Python | 8,655 | 234 | """Similarity metrics and correlation."""
import itertools
import numpy as np
from scipy.spatial.distance import cdist
from scipy.stats import rankdata
from .regression import regress
def fisher_r_to_z(r):
"""Convert correlation coefficients to Fisher z values.
Args:
r (float | np.ndarray): Correl... |
a4387a9079f974f60ecd8df98a6eac32aec6ea01ba72f48c3039eacc2997701d | Python | 8,658 | 234 | """Module to report usage analytics and check for updates."""
import json
import logging
import os
import sys
from contextlib import suppress
from datetime import datetime
from enum import Enum
from functools import lru_cache
from importlib import metadata
from pathlib import Path
from platform import platform, python... |
2b1efe97cf022e82cd43ccd00c2347560cf23c65f86988627edee3d800cdb6bf | Python | 8,664 | 238 | #!/usr/bin/env python3
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
import method.io as io
import method.nn as nn
import numpy as np
import argparse
import kerastuner as kt
from tensorflow.keras.callbacks import EarlyStopping
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import S... |
9e88c42bab9ba8eb1954eed4a724e3410da09dde560d4ae8f2267c03b7b8b8a2 | Python | 8,664 | 219 | """Review artwork from existing TCREmp memberships and inferred junction boundaries.
Run `python images/render_splash.py` with rsvg-convert installed.
Reads the committed display selection; no scientific analysis is run.
"""
import csv
import html
import math
import subprocess
from pathlib import Path
OUT = Path(__fi... |
119dac9968d1237f31d56c8a3a9896fd07e0e76896e8b238ce41808a9e450306 | Python | 8,665 | 197 | import torch
from torch.utils.data import DataLoader,TensorDataset
from modelClasses import *
from utilityFunctions import *
from sklearn.metrics import confusion_matrix, classification_report, precision_recall_fscore_support
os.environ['CUDA_LAUNCH_BLOCKING'] = '1'
models_sessions_list = ['LR_S1', 'LR_S2', 'RL_S1', ... |
1ca0ef499eae2d313206d80557c55efb37840d0d592f87668718c5b155079f24 | Python | 8,665 | 256 | import os
from typing import cast, ClassVar
from chromadb.telemetry.product import ProductTelemetryEvent
class ClientStartEvent(ProductTelemetryEvent):
def __init__(self) -> None:
super().__init__()
# Lazy import to avoid circular imports
from chromadb import is_in_colab
self.in_c... |
9bab59ae235d5cdda5cb8563392cb1a0509d4ad1fa4d8961e37e4b9a4e920693 | Python | 8,673 | 161 | # Copyright 2020 Forschungszentrum Jülich GmbH and Aix-Marseille Université
# "Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements; and to You under the Apache License, Version 2.0. "
from mpi4py import MPI
import numpy as np
from nest_elephant_tvb.transformation.communic... |
7036d6e68e9402fd478e968753e9e83bbe2eb92de089377df4fe31f0c09bd536 | Python | 8,675 | 271 | """Useful helper functions of all kinds"""
import json
import os
import errno
import pickle
import warnings
import numpy as np
import matplotlib.transforms as transforms
from tompy import CustomPDF
from matplotlib.patches import Ellipse
def pickle_read(path):
with open(path, "rb") as file:
out = pickle... |
a94306be0a2ce2e48403c92fdbedae2d110ba29bf5a843b88de48bee70b96141 | Python | 8,677 | 217 | # Copyright (c) 2023 PaddlePaddle Authors. 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 ap... |
ee24cbd820ba06c58cfb6e71ab26706371d14f7ca62d1b87e168f8217647a404 | Python | 8,679 | 197 | """The matplotlib panels: the computation they draw, and the null trap that broke it once.
The by-year computation was verified against the R it replaces on the real corpus -- 408
(chain, metric, year) cells, zero differences. That check needs R and the full build, so it is not
in the suite. What is here is the proper... |
07224093aca3df244008c87b05c0f329070703c3d99b148c1dc82000103d1aae | Python | 8,689 | 180 | # Author: Youzhi Luo (yzluo@tamu.edu)
# Updated by: Anmol Anand (aanand@tamu.edu)
import os
import torch
import torch.nn.functional as F
import numpy as np
from torch_geometric.loader import DataLoader
from torch_geometric.datasets import TUDataset
from sklearn.model_selection import KFold, train_test_split
from dig.a... |
999c0a99f60191bfaa923db4c9664e80e352d8c87b5e1d4788a5d75a16d9efb3 | Python | 8,690 | 245 | from chromadb.api.types import Embeddings, Documents, EmbeddingFunction, Space
from typing import List, Dict, Any, Optional
import os
import numpy as np
from chromadb.utils.embedding_functions.schemas import validate_config_schema
import warnings
class HuggingFaceEmbeddingFunction(EmbeddingFunction[Documents]):
"... |
197845d4af79fdd3aac401efca88859c21a7aedcdabc448e916ac45a103bb380 | Python | 8,699 | 240 | import os
import unittest
import tempfile
import numpy as np
import torch
from transformers import BertConfig
from foldingdiff import modelling
ATOL, RTOL = 1e-6, 1e-3
class TestHuggingFaceBertModel(unittest.TestCase):
"""
Test the BERT model for diffusion built on HuggingFace library
"""
def setU... |
eae60ed5a3fb1bbc621304cf7615dc199222329efec5ad499eabf058dcf778b8 | Python | 8,705 | 228 | import matplotlib.pyplot as plt
import numpy as np
import csv
def load2(filename):
sim = []
col = []
num = []
mes = []
with open(filename, newline='') as csvfile:
reader = csv.reader(csvfile, delimiter=',')
for i, row in enumerate(reader):
if i>0:
sim.app... |
f1b503f2c6ca99ed5d5021058b110ab2d58fcfd662dff61a3347c835202cef85 | Python | 8,707 | 236 | # Copyright (c) 2023 PaddlePaddle Authors. 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 appli... |
b7bb7067598dc2024c56912c7da67586953cec528228173092d37dc5087205e2 | Python | 8,708 | 296 | """Initial value problem solvers implementation."""
from abc import ABC, abstractmethod
import scipy
import geomstats.backend as gs
import geomstats.integrator as gs_integrator
from geomstats.errors import check_parameter_accepted_values
from geomstats.numerics._common import result_to_backend_type
def _merge_scip... |
3041c51b1d6d14cfc69af89e941222dfea1fc515054a814fc363488965e4eae5 | Python | 8,710 | 321 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import bisect
import time
from collections import OrderedDict
from typing import Dict, Optional
try:
import torch
def type_as(a, b):... |
e21487c1cca26a5d9db6fca7c6488ff63061646b5185bb4c4590b46799dfc79c | Python | 8,712 | 280 | # Author: Guoqing Bao
# School of Computer Science, The University of Sydney
# Date: 2019-12-12
# GitHub Project Link: https://github.com/guoqingbao/Pathofusion
# Please cite our work if you found it is useful for your research or clinical practice
# %%
# from IPython import get_ipython
import os
# os.environ["CUDA_V... |
271e31703af6e34ce68b71ea44b86ad51ef0a095517b7da6c8853269495a499f | Python | 8,713 | 218 | #from __future__ import annotations
"""The Pepinvent enumeration module"""
__all__ = ["AAEnumerator"]
import csv
import itertools
import os
from typing import List, Tuple, Union, Dict
import logging
import pandas as pd
import torch
from rdkit import Chem
from reinvent.runmodes.enumeration.validation import AAEnumera... |
36efd80b5b3267958ab9f17114cbe8f1dcecc26d731403ad8d5f0533857dad0d | Python | 8,714 | 169 | # %%
import os
import numpy as np
import time
import h5py
import sys
from scipy import sparse
from scipy.io import savemat, loadmat
import multiprocessing as mp
sys.path.insert(1, '../..') # the path containing "suns" folder
os.environ['KERAS_BACKEND'] = 'tensorflow'
# os.environ['CUDA_VISIBLE_DEVICES'] = '0' # Set w... |
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