sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
9dac64e498cd588cb56e257bda522676b866626cc661fb03d16e8ade8b483446 | Python | 7,166 | 221 | import ast
import yaml
import copy
import argparse
from argparse import ArgumentParser, RawDescriptionHelpFormatter
class ArgsParser(ArgumentParser):
def __init__(self):
super(ArgsParser, self).__init__(
formatter_class=RawDescriptionHelpFormatter)
self.add_argument(
"-o", ... |
5a47db2a454139d3a0155269cd18693adf6424c0feab104a668973012ef3b772 | Python | 7,167 | 227 | # -*- 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 C... |
4bd76f42b3d762abaf3b12eea329b3b01f3daac16612d2418bff804561cf6f7d | Python | 7,168 | 168 | import argparse
import numpy as np
import pandas as pd
import tensorflow as tf
import random as python_random
from keras.models import Sequential
from sklearn.model_selection import KFold
from keras.layers import Dense, Conv1D, MaxPooling1D, Flatten, Dropout
from sklearn.model_selection import train_test_split
from skl... |
6fdd4776cd20b9be21d86fc77c309d439f1699796fefc8aa46618aa32ea7107c | Python | 7,169 | 200 | import sys
import os
import numpy as np
import networkx as nx
import random
from rdkit import Chem
from rdkit.Chem import rdmolops
from rdkit.Chem import rdMolDescriptors
from rdkit import DataStructs
import torch
import torch.nn.functional as F
def mol_to_nx(mol):
G = nx.Graph()
for atom in mol.GetAtoms()... |
07639c72dfbea95da393fcd01554833d9590b4aceba37731f5a5eb97597359ae | Python | 7,172 | 186 | from brian2.units import *
from brian2 import seed
""" JSON PARAMETERS HERE (+DEFAULTS) """
# Simulation
duration = 1*second # simulation duration
debugging = False # run in debugging mode (numpy vs cython, no optimization, reporting)
# population sizes per area | [E, I]
N_EC = [] # def: [10e3, 1e3]
N_DG = [] # def: ... |
607dfc9008a967fc3bf7a97c5730c919b206c7fb653b896c776f64750f1a3f80 | Python | 7,172 | 170 | '''
Module focused on the implementation of Prediction Convolutional Layers
'''
import torch
import torch.nn as nn
class PredictionConvolutions(nn.Module):
'''
Convolutions to predict class scores and bounding boxes using lower and
higher-level feature maps.
The bounding boxes (locations) are predict... |
a78f710cd7067b59636a1c5b3990c93100c734c1bc211ce6e1126797a7408812 | Python | 7,179 | 186 | """`SparseUvuTensorProduct` must agree with the `e3nn.o3.TensorProduct` it replaces.
The class is a hand-written torch specialisation of the sparse `uvu` tensor
products PolarMACE uses, written so that it can also read and write
cuEquivariance's `ir_mul` layout. It builds its weights from a reference
`o3.TensorProduct... |
d7290aee77c06ee4727dc50c5709db8513fc211bbdc30575eb34cdf15e099b39 | Python | 7,181 | 204 | from chromadb.api.types import (
SparseEmbeddingFunction,
SparseVectors,
Documents,
)
from typing import Dict, Any, TypedDict, Optional
import numpy as np
from typing import cast, Literal
from chromadb.utils.embedding_functions.config_validation import (
validate_embedding_function_kwargs_are_safe,
)
fr... |
dc5927cb9ebca3349ef0cc248fb91a265ac0b7dc05371fcbfa986deca6b3bc2b | Python | 7,183 | 215 | import numpy as np
from pydfc import DFC
def test_create_dFC_state_based():
## STATE BASED ##
# create 5 FCSs with 3 regions representing 5 states
FCSs = np.array(
[
[[0.1, 0.2, 0.3], [0.4, 0.5, 0.6], [0.7, 0.8, 0.9]],
[[0.2, 0.3, 0.4], [-0.5, -0.6, -0.7], [0.8, 0.9, 0.1]]... |
be244407268c88238bc1c264af1a30c77ff8af7a12924fe5a4f934cfa0c03c72 | Python | 7,189 | 212 | import tensorflow as tf
# A Spatial Transformer specialized for affine transforms.
# https://github.com/kevinzakka/spatial-transformer-network
def spatial_transformer_network(input_fmap, theta, out_dims=None, **kwargs):
"""
Spatial Transformer Network layer implementation as described in [1].
The ... |
be36360668804642709ccfcc77d975590f3098203b767fc26c6b4baffe75e382 | Python | 7,190 | 204 | # Author: Youzhi Luo (yzluo@tamu.edu)
# Updated by: Anmol Anand (aanand@tamu.edu)
import random
import torch
import torch.nn.functional as F
from torch.utils.data import Dataset
from torch_geometric.utils import degree
class DegreeTrans(object):
r"""
This class is used to add vertex degree based node feature... |
b73054003562c0894198a99ba8d837b991f2d0ee960c4bded73e74d33a327d3c | Python | 7,199 | 256 | # -*- coding: utf-8 -*-
import os
import argparse
import logging
import matplotlib
matplotlib.use("Agg")
bounds = dict()
bounds[0] = (1., 150.) # theta
bounds[1] = (0.01, 0.35) # theta_rho
bounds[2] = (0.1, 200.) # nu_ab
bounds[3] = (0.001, 1.0) # nu_ba
bounds[4] = (0.01, None) # migTime
bounds[5] = (0.01, 1.0) # mig... |
ed5bec7fb90f2c88a459c12c5154b4a433d713e4f80958042f30d17c09511a7a | Python | 7,199 | 213 | import math
import geomstats.backend as gs
from geomstats.test.data import TestData
from .base import LevelSetTestData, VectorSpaceOpenSetTestData
from .diffeo import DiffeoComparisonTestData
from .invariant_metric import InvariantMetricMatrixTestData
from .lie_group import MatrixLieGroupTestData
from .pullback_metri... |
ecfd945122f47b6397123028023c084a9ec6342ec3b2529c99a6178d950cad92 | Python | 7,200 | 211 | ###########################################################################################
# Tools for torch
# Authors: Ilyes Batatia, Gregor Simm
# This program is distributed under the MIT License (see MIT.md)
###########################################################################################
import functoo... |
7ffde08de31bef0b7e6598429b9eb967390f39d93a4aef8b7a84aedc29bd0a68 | Python | 7,203 | 254 | import copy
import numpy as np
import pandas as pd
from pysurvival.utils._functions import _logrankScores
# %matplotlib inline for Jupyter notebooks
def as_bytes(string_array, python_version=3):
""" Transforming an array of string into an array of bytes in Python 3
"""
if python_version >= 3:
r... |
c65472c7a61e2d7eb24e9066ffd9babb86503926e8200468757cfbc18d16a603 | Python | 7,207 | 218 | """Shared helpers for the MACE test suite.
Consolidates the fixtures/utilities that used to be copy-pasted across test
files:
* ``run_mace_train`` — run ``mace/cli/run_train.py`` (or another CLI script)
in a subprocess with the repo prepended to ``PYTHONPATH``, replicating the
historical pattern used throughout t... |
3ef4b5cada9fe57f702216bf8785fdececbb9cbd6fc615c6f164cd697d1e8650 | Python | 7,208 | 185 | import torch
from torch import Tensor
from torch_geometric.nn import MessagePassing
from torch_geometric.nn import global_add_pool, global_mean_pool, global_max_pool, GlobalAttention, Set2Set, GENConv, DeepGCNLayer
import torch.nn.functional as F
from torch.nn import ReLU
from torch_geometric.nn.conv.gcn_conv import gc... |
c87e680fdd901a61cfdca78d52fc34cf3f35d38e1613b3693bf85d324311c74e | Python | 7,208 | 212 | # 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
#
# Unless required by appli... |
8a659f0eae247e5af0cc544360a37db8fab921134dc262382f62309cb77c328b | Python | 7,211 | 206 | import logging
import torch
from typing import Optional, Tuple, Callable, Union
import numpy as np
from dynaphos.utils import (Map, cartesian_to_complex, polar_to_complex,
complex_to_polar)
def get_visual_field_coordinates_from_cortex(
params: dict, coordinates_cortex: Optional[M... |
6b9b092e10026f9a8495fd65958be5c66f231c74f4088313d696e80d24d8d07b | Python | 7,213 | 198 | import argparse
import os
import torchvision.transforms as transforms
from torchvision.utils import save_image
from torch.utils.data import DataLoader
import torch
from models import *
from datasets import *
import numpy as np
import nibabel as nib
import torch.autograd as autograd
parser = argparse.Argume... |
c3cdbca12f1fc13481f69358e5f065edcaa18738439cf30cad1e4b45c6fa65c9 | Python | 7,215 | 228 | import click
from cloudfiles import CloudFiles
from cloudvolume import PrecomputedSkeleton, Skeleton
import numpy as np
import os
import pickle
from corgie import scheduling, argparsers, stack
from corgie.log import logger as corgie_logger
from corgie.boundingcube import get_bcube_from_vertices
from corgie.argparsers ... |
859169aeb95c7919ae8137f4fe34fba047ebf311d6240b13418ab1ed4bc62e52 | Python | 7,216 | 183 | from __future__ import annotations
import logging
import os.path
from result_caching import store_dict
import pandas as pd
from tqdm import tqdm
from brainio_base.assemblies import NeuroidAssembly
from model_tools.activations.core import flatten
from model_tools.utils import fullname
from custom_model_tools.hooks impor... |
8b9653f5f1f2c735c0fc82bcb25b02248910aeec4973f679d2ba92aeedf45c5e | Python | 7,218 | 189 |
import numpy as np
import sys
import pickle
import math
amino_acid_set = { "A": 1, "C": 2, "E": 3, "D": 4, "G": 5, "F": 6, "I": 7, "H": 8, "K": 9, "M": 10, "L": 11,
"N": 12, "Q": 13, "P": 14, "S": 15, "R": 16, "T": 17, "W": 18, "V": 19, "Y": 20, "X": 21 }
amino_acid_num = 21
ss_set = {"C": 1, "H": ... |
f87807c8b67f2335a3bd079c305cd7b46bcfacd6b15cc3abba9d32e31b353f31 | Python | 7,218 | 245 | #!/usr/bin/python
from smfishHmrf.HMRFInstance import HMRFInstance
from smfishHmrf.DatasetMatrix import DatasetMatrix, DatasetMatrixSingleField, DatasetMatrixMultiField
from smfishHmrf.spatial import rank_transform_matrix, calc_silhouette_per_gene
import sys
import os
import math
import subprocess
import numpy as np
im... |
7ea19aea18df4103b4e52009d07ff4792716a06f7686a880eee548a25946e14b | Python | 7,229 | 213 | # Copyright (C) 2020-2023 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import sys
from openfl.experimental.workflow.interface import FLSpec, Aggregator, Collaborator
from openfl.experimental.workflow.runtime import LocalRuntime
from openfl.experimental.workflow.placement import aggregator, collaborator
cl... |
41577261bd4c53595e96f1d856a0e90ce5c2c21f767cf89cceaaf04651c35505 | Python | 7,230 | 195 | # Copyright (C) 2020-2021 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""You may copy this file as the starting point of your own model."""
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
import tqdm
from openfl.federated import PyTorchTask... |
238fd7c6fdd6ae6c86ddcb97113330ab4467ca93f7fad514a982c819f89747cd | Python | 7,233 | 281 | """Logging and monitoring support
Setup for Python and RDKit logging. Setup for remote monito
"""
from __future__ import annotations
__all__ = [
"CsvFormatter",
"VERBOSE",
"setup_logger",
"enable_rdkit_log",
"setup_responder",
"setup_reporter",
"get_reporter",
]
import json
import os
im... |
baae0f50e90b2124be0c23caf74b63db224010ff1f665a010b5e62421558eb2e | Python | 7,236 | 214 | from __future__ import annotations
import time
from pathlib import Path
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import gridspec
from pdfrw import PdfDict, PdfReader
from pdfrw.buildxobj import pagexobj
from pdfrw.toreportlab import makerl
from reportlab.lib.pagesizes impor... |
49f30acd26bc1610f5256eff5b42417107dd54c9fa286424a5a5f2a74c0af239 | Python | 7,244 | 195 | from tensorflow import keras
import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, Flatten, Input, BatchNormalization,ReLU
#from tensorflow.keras.layers import Conv1D, Reshape, MaxPooling1D,Conv1DTranspose, UpSampling1D
from tensorflow.keras.cal... |
63e48227c53141fc4431990538c1b3e729e2fe744a530df8829f1829fe0acd06 | Python | 7,246 | 196 | from lungmask import mask
import lungmask
import SimpleITK as sitk
import numpy as np
import nibabel
import platform
import glob
import torch
import skimage
from tqdm import tqdm
from monai.transforms import Compose, LoadImaged, ToTensord, Spacingd, DivisiblePadd, SpatialCropd, ToNumpyd, AddChanneld, SqueezeDimd, Resiz... |
fa5b7a0cba34938c5046b16acce11cad6e5b417c68e99610d87f55b2e11e66ff | Python | 7,246 | 112 | #!/usr/bin/env python3
# PYTHON_ARGCOMPLETE_OK
import argparse
import sys
def main(args=None):
args = _parse_input_args(args)
if args.command == "setup":
from deeperwin.run_tools.setup_calculations import setup_calculations
setup_calculations(args)
if args.command == "restart":
from... |
b87f1642a6bf3f803f40dd6d87e969c5cc78de75627188ed0b2914f16300c205 | Python | 7,251 | 179 | """Load canonical CSV-like ``.sanpy`` recordings."""
import re
from typing import Optional
import numpy as np
import pandas as pd
from sanpy.fileloaders.epochTable import epochTable
from sanpy.fileloaders.fileLoader_base import fileLoader_base, recordingModes
from sanpy.sanpyLogger import get_logger
logger = get_lo... |
d72c985fc239ec9e076c0d22530962f745cd62cdb76642b42b8e2a52c83c81bb | Python | 7,251 | 163 |
import os
import sys
import json
import math
import pickle
import numpy as np
import pandas as pd
from hyper_dti.settings import constants
objectives = {
'RandomForest': {
'BCE': 'gini',
'MSE': 'squared_error',
'MAE': 'absolute_error',
},
'XGBoost': {
'BCE': 'binary:logist... |
b88a3eed9e16c207da74ca5c52c2a68467fbb522ee3349c41dab8e2b812bab1d | Python | 7,258 | 173 | """The VDJdb confidence score.
`score/confidence.py` was 39 % covered while deciding the number every consumer filters on. These
pin the two behaviours the released scores depend on - the `n/m` frequency parse where `n` is a
cell count, and the maximum over the sample signature - plus each branch of the two sub-scores... |
24ce2a4eb453d30b783c924273a28d74dfbb013fb50d3c3fd746a85092da0c2c | Python | 7,270 | 211 | # -*- coding: utf-8 -*-
"""
Created on Fri Jul 23 11:25:14 2021
@author: nicol
"""
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Dec 12 15:25:17 2018
@author: ngritti
"""
import time, os, glob
from tqdm import tqdm
import numpy as np
from skimage.io import imread
import seaborn ... |
e9e8fbae840498993d9ead29ca6f753e017cdae735091ff1fddf2fe02fc9f516 | Python | 7,272 | 303 | """Execution backends.
Lead authors: Johan Mathe and Niklas Koep.
"""
import importlib
import logging
import os
import sys
import types
import geomstats._backend._common as common
def get_backend_name():
return os.environ.get("GEOMSTATS_BACKEND", "numpy")
BACKEND_NAME = get_backend_name()
BACKEND_ATTRIBUTE... |
f672689b0e408aa68b7999b095f082cc1a2c72181175df895d28ccd5ac827647 | Python | 7,272 | 185 | """
Tests for one-sample permutation tests.
Tests both basic functionality and statistical correctness.
"""
import pytest
import numpy as np
from nltools.algorithms import one_sample_permutation_test
from nltools.algorithms.inference.one_sample import _one_sample_statistics
class TestOneSamplePermutation:
"""T... |
74c331a16d1e690142ace2a2ed0f21b8f55fe68de9f59e356c75d7929d937186 | Python | 7,275 | 183 | # This file is a part of the `nequip` package. Please see LICENSE and README at the root for information on using it.
import torch
import lightning
from lightning.pytorch.callbacks import Callback
from nequip.train import NequIPLightningModule
class TrainingStatsMonitor(Callback):
"""Monitor and log detailed trai... |
d0ebe2861f039ea61d0f2e19496121605ceefa0f477cfc0b641e604bd2a14fb9 | Python | 7,278 | 153 | from pathlib import Path
import os
import pandas as pd
import torch
import copy
from utils import save_projection_axes
from data_classes import VOPADataset
import numpy as np
def parse_args():
import argparse
parser = argparse.ArgumentParser(
description='...'
)
parser.add_argument(
'... |
a4da0fc9ff9832f67fb9f60c9a766612a807659300fb8cd6ded28d4b974b5866 | Python | 7,281 | 187 | import os.path as osp
import json
from numpy import random
from rdkit import Chem
from rdkit.Chem.Scaffolds import MurckoScaffold
from sklearn.utils import shuffle
from tqdm import tqdm
def main():
split_ratio = [0.6, 0.2, 0.2]
split_root = '/mnt/dive/shared/kaleb/Datasets/PubChemQC/utils/splits'
print... |
1426ccf2fe746757ad3a7a344a47f827786dbe3e377d10e6edb69f025c7ed62e | Python | 7,283 | 260 | #!/usr/bin/env python
import sys
from psychopy import prefs
prefs.general['audioLib'] = ['pygame']
from psychopy import visual, gui, event, logging
from psychopy import sound, core
import time as ptime
import serial
import os
from os.path import join as pjoin, exists as pexists
import json
import csv
import datetime
im... |
09ba73805e0ca0255dffda75a8915e90298595241981605e22fd1942db2104e8 | Python | 7,287 | 230 | """Sore a list of SMILES
Passes a list of SMILES to a scoring function of choice.
"""
from __future__ import annotations
__all__ = ["run_scoring"]
import os
import re
from collections import Counter
import logging
from typing import List, Tuple, Callable
import numpy as np
from reinvent.scoring.scorer import Score... |
541369b4a50fa171c224a24e890927164a996378f6c50895e153cbc634856aa7 | Python | 7,287 | 247 | import numpy as np
import pandas as pd
import imageio as io
from tqdm import tqdm
import pathlib
import numpy as np
from skimage.draw import disk
from PyQt5.QtCore import QObject, pyqtSignal
def line_w_sphere(s, p0, p1, r0, r1, color=1, spacing=[1, 1, 1]):
"""Draw a line with width in 3D space
Ar... |
a8ae774ac8f6b5da44bca364e17e4ee443a843ebfb088fbb4109f90eb3cebe4e | Python | 7,291 | 331 | import numpy as np
import seaborn as sns
import torch
import torch.nn as nn
import utils as u
import analysis_utils as au
import fit_data as fd
class Perception(nn.Module):
def __init__(
self,
w_L=0.0, w_N=0.0, hidden_size=2, is_fc=False,
):
super().__init__()
self.is_fc = ... |
43639fb4666d8cf52ba0ed6602beb4e58a1abdfe0f91cd01c1e1af7b96963c09 | Python | 7,294 | 172 | #perform LRP thourgh AG-Sononet
import torch
import torch.nn as nn
import ISNetLayers as LRP
import ISNetFunctions as f
import globals
class LRPFinalLayers(nn.Module):
def __init__(self,model,e):
#perform LRP through last layers of AG-sononet
#model: dictionary with all layers and fdw indexes (net.... |
ba089377686fdcf693c251303dba0b7e98b539935b99110bd56b7d797002d3aa | Python | 7,297 | 238 | # /// script
# requires-python = ">=3.11"
# dependencies = [
# "marimo",
# "nltools>=0.6.0",
# ]
# ///
# Univariate regression — marimo notebook. Source of truth for the docs page; rendered to the docs page by scripts/marimo_to_zensical.py.
import marimo
__generated_with = "0.24.0"
app = marimo.App(width="med... |
46c131a4c2fd47b6d2206dd067b44798729fa6317f9ec829497140e897360f5b | Python | 7,300 | 118 | """
This is the configuration file for fine-tuning.
We implemented two pretrain tasks: mask prediction and mask contrastive learning.
--- Mask prediction is just the same pretrain task used in original BERT paper, predicting the ids of masked tokens
--- Mask contrastive learning is our propsed pretraini... |
c61a20959fe7f5ce5b786a4910d210aab778fd27b57e3e758b163a24c5e4eb6b | Python | 7,300 | 169 | r"""Subspace reconstruction of the low-res MSI transients from the predefined
high resolution basis. Basis transients need to be computed from the given high
resolution experimental transients.
"""
import os
import argparse
import logging
import pickle
from tqdm import tqdm
import subspaceMSI as subspace
... |
685e33ff1bf144633ec487225bf9fcda935770fed0fd2da4350449a09dadd1eb | Python | 7,301 | 118 | """
This is the configuration file for fine-tuning.
We implemented two pretrain tasks: mask prediction and mask contrastive learning.
--- Mask prediction is just the same pretrain task used in original BERT paper, predicting the ids of masked tokens
--- Mask contrastive learning is our propsed pretraini... |
12884ca27e8636b3188dc556096f700d4cad4eebc62febfda2a31b6e800eff3c | Python | 7,307 | 220 | """Classical Reinvent de novo model
See:
https://doi.org/10.1186/s13321-017-0235-x (original publication)
https://doi.org/10.1021/acs.jcim.0c00915 (REINVENT 2.0)
"""
from __future__ import annotations
from typing import Tuple, TypeVar, Iterator, TYPE_CHECKING
import torch
import torch.nn as tnn
from reinvent.models... |
909f740c59f16ca08e1bcdb08614c8ad5bac7f37c1e799299f30175a15afb6c4 | Python | 7,313 | 183 | import numpy as np
from odl.tomo import fbp_op
from dival.datasets import Dataset, CachedDataset, generate_cache_files
def generate_fbp_cache_files(dataset, ray_trafo, cache_files, size=None,
filter_type='Hann', frequency_scaling=1.0):
"""
Generate cache files for a CT dataset, w... |
5f751d12ab40572b7c88c3d7f8937bb8ad0206a8caa4b11b65ceb0c9075eceb0 | Python | 7,314 | 221 | import math
import pytest
import geomstats.backend as gs
from geomstats.test.random import get_random_times
from geomstats.test.vectorization import generate_vectorization_data
from geomstats.vectorization import get_batch_shape
class ProjectionTestCaseMixins:
def test_projection(self, point, expected, atol):
... |
fc2e6600eb63b29400587eff29f37b56d4106ecea13f1b4b01d07f96796cec43 | Python | 7,316 | 200 | import argparse
import os
import numpy as np
import torch
import pytorch_lightning as pl
from pytorch_lightning.callbacks import ModelCheckpoint, EarlyStopping
from pytorch_lightning.loggers import WandbLogger
from torch_geometric.loader import DataLoader as GeometricDataLoader
from pathlib import Path
# Imports from ... |
d389038d1c54511469bd822bf8c44c6581c0065f55bb372bea984c097eb15a6e | Python | 7,317 | 112 | #*----------------------------------------------------------------------------*
#* Copyright (C) 2024 ETH Zurich, Switzerland *
#* SPDX-License-Identifier: Apache-2.0 *
#* *
... |
774195645341016c8217b3a73cbd5e2c7d977eba39e28da2f6edcab6eef1d82b | Python | 7,322 | 196 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Dec 12 15:25:17 2018
@author: ngritti
"""
# from csbdeep.models import CARE
# from deeprest.rawDataClass import rawData
# from deeprest.modelClass import modelRest
# from deeprest.timeLapseClass import sampleTimeLapse
import time, os, glob
from tqdm imp... |
6540b0335fee06a1ae2ac447646abcd3b358ffc80a7a43eec2354955831e86ad | Python | 7,323 | 220 | """model.py
Functions for Model.ipynb
"""
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
import matplotlib.gridspec as gridspec
import pandas as pd
import functions as fc
import plotting_help as ph
dpi = 300
axis_lw = 0.4
axis_ticklen = 2.5
font = {'family': 'arial',
'weight':... |
e4e9a3321d706922fb4db19d9b0f37aafa71250a07266fb5c0d2797439ad8124 | Python | 7,324 | 384 | """Numpy based computation backend."""
import numpy as _np
from numpy import (
abs,
all,
allclose,
amax,
amin,
angle,
any,
arange,
arccos,
arccosh,
arcsin,
arctan2,
arctanh,
argmax,
argmin,
asarray,
broadcast_arrays,
broadcast_to,
ceil,
cl... |
252a493c25a326d57b93cacfd71564b3e90c0218934ad02b6505b7704e3ee9bb | Python | 7,326 | 166 | import jax
import jax.numpy as jnp
import jax.scipy.sparse.linalg
from typing import Any, Callable, Optional, Tuple, Union
from deeperwin.configuration import SRCGOptimizerConfig
from deeperwin.optimization.opt_utils import build_optax_optimizer, build_lr_schedule
from deeperwin.utils.utils import pmap, pmean, tree_dot... |
72e7e1deedc2ba5cc9cc4952838c9ecdced3e369f81a4b52cd5babf29ae7b114 | Python | 7,326 | 190 | import os
import sys
import cv2
import numpy
import argparse
import tifffile
from tqdm import tqdm
from skimage import filters
from skimage import feature
from scipy import ndimage as ndi
from scipy.ndimage.interpolation import geometric_transform
class DriftEstimatorOFFarneback(object):
FARNEBACK_PARAMETER = {"... |
a4c549cfc8d425644e052e83fb33a4a24eea1e607421dea12889f25994b42fe0 | Python | 7,328 | 248 | from dataclasses import astuple, dataclass
import numpy as np
import torch
from copy import deepcopy
class Binarizer:
def __init__(self, binarization):
self.bin = binarization
def __call__(self, tens):
if self.bin is None:
return tens
elif self.bin[0] == "neq":
... |
c2623f9dcf9df96a2d37ce7a7790c2aa3fc17a5fe4b8a49c80029b772f46fff5 | Python | 7,330 | 218 | # Authors: Mainak Jas <mainakjas@gmail.com>
import numpy as np
import pytest
from hnn_core import simulate_dipole
from hnn_core.optimization.optimize_evoked import (
_consolidate_chunks,
_split_by_evinput,
_generate_weights,
_get_drive_params,
optimize_evoked,
)
def test_consolidate_chunks():
... |
b85110e756a28a2f7e3e6cbb8bccbc37486fc85be0090b1b34538441f1b95b86 | Python | 7,331 | 198 | """Tests for nltools.algorithms.similarity — similarity and correlation metrics."""
import numpy as np
import pytest
from nltools.algorithms.similarity import (
fisher_r_to_z,
fisher_z_to_r,
compute_similarity,
_compute_multivariate_similarity,
transform_pairwise,
)
class TestFisherTransform:
... |
07be7027fd6015741b72df1095dd1958d1b55a20c3c9890e61d2ae0defea5062 | Python | 7,335 | 245 | """Generate schema-backed tables while MkDocs renders the Methods page."""
from __future__ import annotations
from datetime import date
from enum import Enum
import math
from types import UnionType
from typing import TYPE_CHECKING, Any, Mapping, Sequence, get_args, get_origin
if TYPE_CHECKING:
from mkdocs.config... |
c991b2b473aaf5b4801d4543f817368b48e265188e5f7494a48034b5dcf18840 | Python | 7,352 | 197 | # Copyright (c) 2021 Big Data and Multi-modal Computing Group, CRIPAC
# 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, c... |
b125224e1f5a4950d53d6f582707a1633962e46cf597d5ad5a2af53a4040d630 | Python | 7,353 | 214 | import os
import numpy as np
import logging
import argparse
import time
import torch
import torch_geometric.transforms as T
from sklearn.metrics import roc_auc_score, average_precision_score
from GeNNius import Model, EarlyStopper, shuffle_label_data
from utils import plot_auc
#####################################... |
c940b51cc77484ea0197021656fb60ec9061e510f092aba8f29b0cce2b396d85 | Python | 7,353 | 184 | from PymoNNto.Exploration.Network_UI.TabBase import *
class stdp_buffer_tab(TabBase):
def __init__(self, title='STDP'):
super().__init__(title)
def add_recorder_variables(self, neuron_group, Network_UI):
return
def initialize(self, Network_UI):
self.stdp_tab = Network_UI.Next_Tab... |
ac277f00fd158f85894eb19ca1bb92c3ab0e958bbd838761bd1eac99cc3dd363 | Python | 7,367 | 196 | """Unit tests for visualization."""
import matplotlib
import matplotlib.pyplot as plt
import geomstats.backend as gs
import geomstats.visualization as visualization
from geomstats.geometry.hyperbolic import Hyperbolic
from geomstats.geometry.hypersphere import Hypersphere
from geomstats.geometry.matrices import Matri... |
0c5b2587cdb0f33677ab900b89ed7b180959aa8d6b6a92750b88804eac673f4e | Python | 7,370 | 199 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Dec 28 16:37:02 2022
@author: shah
"""
import tensorflow as tf
from Models import UNetfairSIM, ModelFineTunning
from DataGeneratorPreprocessing import CustomDataGenerator
from Utils import compileDNN, safelyCreateNewDir
import os, datetime,argparse, js... |
677956d4f10aac5c067577f2dd15fa95bdad2078a8752e6d956eb5928ee0bbad | Python | 7,371 | 167 | from unittest import TestCase
import types
import torch
import torch.nn as nn
import numpy as np
from torch.utils.data import TensorDataset, DataLoader
from smithers.ml.utils_rednet import get_seq_model, PossibleCutIdx, spatial_gradients, projection, forward_dataset
if torch.cuda.is_available():
device = torch.dev... |
cd0ef346f94dc7950bfebcaa86d5dad66d78f08da9cc7c15af803e5affd7168c | Python | 7,374 | 262 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import math
from functools import partial
__all__ = [
'ResNet', 'resnet10', 'resnet18', 'resnet34', 'resnet50', 'resnet101',
'resnet152', 'resnet200'
]
def conv3x3x3(in_planes, out_planes, stride=1):
# ... |
255d2a7ccfc8461b685ffbdd64c7b2cf8f1ca6671b9152a6abd2f9bdf1f4bfd2 | Python | 7,383 | 200 | # 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
#
# Unless required by appli... |
9663497948c4db45027fd1e0433ca762ba142bca66c422e495c944c8a045efe0 | Python | 7,383 | 178 | """
Analysis of Delayed Differential Equations
==========================================
In this tutorial, you will learn how to implement and solve delayed differential equation (DDE) systems via PyRates.
DDEs take the general form
.. math::
\\dot{\\mathbf{y}} = \\mathbf{f}(\\mathbf{y}, t, \\mathbf{y_{\tau}})
... |
30cfa3d9da5be545a92657e02240a1eac6a711b026b3c38f449b62b44701cc67 | Python | 7,385 | 230 | import experiment as exp
from canvas import Canvas
import random
import asyncio
class RandomShapes(Canvas):
def __init__(self, canvas_id, n_nodes, logger, shape="Circle"):
super().__init__(canvas_id, on_connect=self.on_connect, on_disconnect=self.on_disconnect, logger=logger)
# self.interval = int... |
144dfaf66a7fbd2ac1b5414bb050cbdd5e87f0ebcd0407866b55a987a3d4c87e | Python | 7,394 | 179 | """Unit tests for the pure helpers in ``nltools.data.braindata.viewer``.
These cover palette generation, display-window and threshold-slider maths, and
background resolution, using synthetic arrays and affines — no network, no
browser, no widget construction. The LUT, colormap and slice-type helpers are
pinned through... |
45102d7976106c616dc12c8df9bbc9d2cb008b467b979829074458e0eb1cd4d8 | Python | 7,400 | 233 | # /// script
# requires-python = ">=3.11"
# dependencies = [
# "marimo",
# "nltools>=0.6.0",
# ]
# ///
# Inter-Subject Correlation — marimo notebook. Source of truth for the docs page; rendered to the docs page by scripts/marimo_to_zensical.py.
import marimo
__generated_with = "0.23.9"
app = marimo.App(width="... |
acc5aeb8d2f507524638b4343ca1b51e180a726dd073243e7b2c1483dc9837ec | Python | 7,403 | 218 | import os
import xml.etree.ElementTree as ET
import numpy as np
import pyedflib
from sleeprnn.data import utils
# This path is expected to be the parent path of the paths listed in NSRR_DATA_PATHS
NSRR_PATH = os.path.abspath("/home/ntapia/Projects/Sleep_Databases/NSRR_Databases")
NSRR_DATA_PATHS = {
"shhs1": {
... |
c7f088158c93b3daaf296f687cecf6e04d6015bcf6c2cd1263347f0e9349966e | Python | 7,406 | 209 | from chromadb.api.types import (
SparseEmbeddingFunction,
SparseVectors,
Documents,
)
from typing import Dict, Any, TypedDict, Optional
from typing import cast, Literal
from chromadb.utils.embedding_functions.config_validation import (
validate_embedding_function_kwargs_are_safe,
)
from chromadb.utils.e... |
0c2805f977629e8bcc926a86d56e2953c2f10ef300bbc308b51864362933bf57 | Python | 7,409 | 248 | """The vector space of Hermitian matrices.
Lead author: Yann Cabanes.
"""
import logging
import geomstats.backend as gs
from geomstats import algebra_utils as utils
from geomstats.geometry.base import ComplexMatrixVectorSpace
from geomstats.geometry.complex_matrices import ComplexMatrices, ComplexMatricesMetric
from... |
7f832e72c60979515fd23f7fdb07425e7b6ee638870f1a0a5b3e05864dfc7f48 | Python | 7,409 | 224 | # Copyright 2020-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""Experimental Collaborator module."""
import time
from logging import getLogger
from typing import Any, Callable, Dict, Tuple
import dill
class Collaborator:
r"""The Collaborator object class.
Args:
collaborator_name ... |
9dc305e3ba35c1bc46bfaee9631df7458ddcd1f62e3d82aab48808a9d07e03eb | Python | 7,411 | 216 | """
Created on Mon October 23 11:05:36 2023
Description: Visualization functions for
Paper url: https://www.biorxiv.org/content/10.1101/2023.09.11.557230v2
@author: Ekaterina Kuzmina, ekaterina.kuzmina@skoltech.ru
@author: Dmitrii Kriukov, dmitrii.kriukov@skoltech.ru
"""
import numpy as np
import matplotlib.pyplot a... |
a7c68714b4422cb05643668fa1f5ad2b035c2a394f3f25a51e7ccb31411e0372 | Python | 7,411 | 222 | __all__ = ["MmpPairGenerator"]
from argparse import Namespace, RawDescriptionHelpFormatter, ArgumentParser
from time import time
import logging
import tempfile
from mmpdblib.do_fragment import fragment_command
from mmpdblib.do_index import index_command
import numpy as np
import os
import pandas as pd
from .pair_gene... |
363b78c872993b13b05e97af38bdca7dd6715911b83e3675aa012149069d4573 | Python | 7,413 | 193 | from typing import ClassVar, Dict, Optional
import logging
import threading
import uuid
from chromadb.api import ServerAPI
from chromadb.api.base_http_client import BaseHTTPClient
from chromadb.config import Settings, System
from chromadb.telemetry.product import ProductTelemetryClient
from chromadb.telemetry.product.e... |
17b0b25fd880b6237eb157bf165177b58a4ee8c43c64be532052e4c197f6a95c | Python | 7,421 | 199 | # -*- coding: utf-8 -*-
"""
Created on Thu Apr 22 14:27:39 2021
@author: nicol
"""
import os, glob, tqdm
from skimage.io import imread, imsave
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import rc
import matplotlib as mpl
from skimage.metrics import normalized_root_mse as nrmse
im... |
780f75c8ab025882f67625bce671e385bc2b94eb772524613fc321138f37e8b3 | Python | 7,427 | 176 | # based on https://github.com/lopeneljxi/keras-unet-collection
from __future__ import absolute_import
import tensorflow as tf
from tensorflow.keras.layers import Input
from tensorflow.keras.models import Model
from .backbone_zoo import backbone_zoo, bach_norm_checker
from .layer_utils import *
def UNET... |
3bf787ec1e528607ec83867b6f960ef13686724b10145601499c96ea4f21666a | Python | 7,432 | 164 | # 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... |
52cf155913268c8fe758f100f3631a57f466228d1c7fa8c1d051f536127932d5 | Python | 7,432 | 171 | import argparse
import numpy as np
import pandas as pd
import tensorflow as tf
import random as python_random
from keras.models import Sequential
from sklearn.model_selection import KFold
from keras.layers import Dense, Conv1D, MaxPooling1D, Flatten, Dropout
from sklearn.model_selection import train_test_split
from skl... |
76dcd624c1843e195a50fbeb6cacecacf11d6a017fbdf76dd05b3f31ecec3c65 | Python | 7,432 | 245 | """Reward strategies for Reinforcement Learning"""
from __future__ import annotations
__all__ = [
"RLReward",
"dap_strategy",
"mascof_strategy",
"mauli_strategy",
"sdap_strategy",
"dap_reinforce_strategy",
"mascof_reinforce_strategy",
"mauli_reinforce_strategy",
]
import logging
from ... |
b66c2396fcf9ba40bb67f6cfd1537a7a15ec858f18ec544387e9bec486f4a85b | Python | 7,433 | 202 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
@Author: An Tao
@Contact: ta19@mails.tsinghua.edu.cn
@File: dataset.py
@Time: 2020/1/2 10:26 AM
"""
import os
import torch
import json
import h5py
from glob import glob
import numpy as np
import torch.utils.data as data
shapenetpart_cat2id = {'airplane': 0, 'bag': 1,... |
106cf7e67078e6a938fdf8dd7f9098c2cded8486ac33df26c7f33042c067c3c7 | Python | 7,434 | 202 | # ruff: noqa: PLR2004
from __future__ import annotations
from math import inf
import pyparsing as pp
from hypothesis import assume, given
from hypothesis import strategies as st
import snakebids.tests.strategies as sb_st
from snakebids.core.datasets import BidsComponent, BidsDataset
from snakebids.io.printing import... |
291fdb23fa9b378e939b36f8c1ff2ee87811c093a8ed1f3c86e8baba8570398e | Python | 7,435 | 221 | from configuration import *
from spikeinterface.sortingcomponents.benchmark.benchmark_motion_interpolation import BenchmarkMotionInterpolationMearec
from spikeinterface.sortingcomponents.benchmark.benchmark_motion_interpolation import plot_distances_to_static
from spikeinterface.qualitymetrics import compute_quality_... |
7cf1f52f430f60c267717c2d21105b18b1ee83cd2a5de542c8671183a9567919 | Python | 7,445 | 263 | import click
from corgie import scheduling, helpers, stack
from corgie.log import logger as corgie_logger
from corgie.layers import get_layer_types, DEFAULT_LAYER_TYPE, str_to_layer_type
from corgie.boundingcube import get_bcube_from_coords
from corgie.argparsers import (
LAYER_HELP_STR,
create_layer_from_spe... |
80651f4ec1fb5137d9f32365df6632046195975f22484f2a9b5c3dfc15d4acb9 | Python | 7,446 | 197 | # 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
#
# Unless required by appli... |
a8d8699c6d857c502d99390d435f1865d51970403f6f5e34c6f830eda51b2eb8 | Python | 7,446 | 167 | import h5py
import sys
import numpy as np
from pyimzml.ImzMLWriter import ImzMLWriter
def imzml(input_filename, output_filename,smoothMethod="nosmooth",centroid=False):
import h5py
import numpy as np
### Open files
h5 = h5py.File(input_filename, 'r') # Readonly, file must exist
### get root group... |
30aa222e3c64bbc5a7ec2088ed36507603a12f7e9b64d0ba875e93f06c855365 | Python | 7,458 | 181 | """
Calculate the wave directions by either interpolating trigger times and
locations or by averaging the corresponding optical flow values.
"""
import neo
import numpy as np
import quantities as pq
import matplotlib.pyplot as plt
from matplotlib import patches
import os
import warnings
import argparse
import scipy
i... |
9e24c1885d3ae68be723323edd84824a2ffdefb566676a2529673b025cd508d6 | Python | 7,462 | 219 | import pytest
import renderapi
from test_data import (render_params,
montage_raw_tilespecs_json,
montage_parameters)
from bigfeta import bigfeta
from bigfeta import jsongz
import json
from marshmallow.exceptions import ValidationError
import copy
import os
import numpy as n... |
d6f96102d2371c6062fbc2ae222321877375f8bc73a2ffac934d0580953cb42a | Python | 7,466 | 182 | """
Calculate the wave directions by either interpolating trigger times and
locations or by averaging the corresponding optical flow values.
"""
import neo
import numpy as np
import quantities as pq
import matplotlib.pyplot as plt
from matplotlib import patches
import os
import warnings
import argparse
from pathlib im... |
027c02c7ad5aeb7750df88d637b09f56c26eb8fa49b87669937c7d70b55673fb | Python | 7,467 | 177 | import os
import warnings
import csv
import argparse
import numpy as np
import matplotlib.pyplot as plt
from scipy import signal as sig
import scipy.spatial.distance as dst
import parameters
from optlib import cost_func
# Main code
if __name__ == "__main__":
""" Exhibition of the functions to be used """
# ... |
e003a40c45df8ce36724f05843b8f3ce2882a813b3496f8006a3de8ddb07ecaf | Python | 7,470 | 252 | import argparse
import json
import os
import traceback
import numpy as np
from joblib import Parallel, delayed
from pydfc.ml_utils import extract_task_features, task_presence_classification
os.environ["MKL_NUM_THREADS"] = "1"
os.environ["NUMEXPR_NUM_THREADS"] = "1"
os.environ["OMP_NUM_THREADS"] = "1"
##############... |
8c4a2aa64672998716dc2510f4fe4b8518672837bd5dee03c6dd76b1da6687c8 | Python | 7,473 | 181 | """
Calculate the wave directions by either interpolating trigger times and
locations or by averaging the corresponding optical flow values.
"""
import neo
import numpy as np
import quantities as pq
import matplotlib.pyplot as plt
from matplotlib import patches
import os
import warnings
import argparse
import scipy
i... |
28d0581dbbbe1168624ab9bc9f4857dfe6ed1e865057fe17a4488b85d37cdb4a | Python | 7,474 | 140 | from collections import defaultdict
from utils_ds import *
LIGAND_TEST_GROUPS = [
["AmPhos", "CataCXium A", "Xantphos"],
["P(Ph)3", "P(Cy)3", "P(o-Tol)3"],
["P(tBu)3", "dtbpf", "dppf"],
["None", "SPhos", "XPhos"],
]
def ligand_splits(df):
"""Return training-first splits after normalizing spreads... |
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