sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
b23f3630cb8274941bf1a623a12acbaae8146b6bb8a527062217a5e186506825 | Python | 7,513 | 204 | import math
from typing import Callable, Iterable, List, Optional, Tuple
import torch
from torch import Tensor
from torch.optim import Optimizer
class AdEMAMix(Optimizer):
r"""Adapted from https://github.com/frgfm/Holocron/blob/main/holocron/optim/ademamix.py
Implements the AdEMAMix optimizer from `"The... |
21e2258a21d4f87a031028b856f6e237d6a2a09666ba9ec942aa73e277ee570e | Python | 7,526 | 155 | import torch
from .base_model import BaseModel
from . import networks
class Pix2PixModel(BaseModel):
""" This class implements the pix2pix model, for learning a mapping from input images to output images given paired data.
The model training requires '--dataset_mode aligned or np_array_aligned' dataset.
... |
931628b7765f3f8576a51f6aeaefb58fe6dae81e9681895966aa1ce555aed8c4 | Python | 7,527 | 254 | #!usr/bin/env python
# -*- coding: utf-8 -*-
import argparse
import ast
import os
from typing import Optional
import click
from deprecated import deprecated
from GANDLF.cli import (
deploy_targets,
mlcube_types,
run_deployment,
recover_config,
copyrightMessage,
)
from GANDLF.entrypoints import app... |
e7546e8183645e43abc435131687aa111862f7e0bd3aa7972b6b44f1282a79af | Python | 7,530 | 197 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# 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 applicable l... |
6b6b5ed33d2defacbfacdd051569a4f1e16965847eb74af5a21025f66c790488 | Python | 7,531 | 236 | """
DisplayDensityPlot
==================
**DisplayDensityPlot** plots measurements as a two-dimensional density
plot.
A density plot displays the relationship between two measurements (that
is, features) but instead of showing each data point as a dot, as in a
scatter plot, the data points are binned into an equally... |
eae957094bedec5a082e2daadd05f321649a8dc3229314b646a0e510d594eb5e | Python | 7,537 | 211 | from glob import glob
import sys
import random as rd
import numpy as np
import scipy.io as scio
from joblib import Parallel, delayed
import multiprocessing as mp
import time as tme
##############################################################################
# FILES ... |
7bab9e0d90d4f9971262526d53f39db6c40ba9be3119204f91f1bbf5c8b2fef1 | Python | 7,539 | 184 | import collections
import numpy
import imageio.v3
from ..constants.image import MD_SIZE_S, MD_SIZE_C, MD_SIZE_Z, MD_SIZE_T, MD_SIZE_Y, MD_SIZE_X
from ..preferences import config_read_typed
from ..reader import Reader
SUPPORTED_EXTENSIONS = {'.png', '.bmp', '.jpeg', '.jpg', '.gif'}
# bioformats returns 2 for these, i... |
753954255bcd50fd3aa602194af39719241680858f8fb48385a8500cf440e295 | Python | 7,544 | 139 | from collections import namedtuple
# a label and all meta information
Label = namedtuple('Label', [
'name', # The identifier of this label, e.g. 'car', 'person', ... .
# We use them to uniquely name a class
'id', # An integer ID that is associated with this label.
# The IDs are used to represent th... |
7b47e4f82d6af847a7127b3b9faa6a9d9d23e002e0ff806424793b1aa9321a7c | Python | 7,545 | 216 | # -*- coding: utf-8 -*-
"""
Data transformations
====================
The statistics of intermittent precipitation rates are particularly non-Gaussian
and display an asymmetric distribution bounded at zero.
Such properties restrict the usage of well-established statistical methods that
assume symmetric or Gaus... |
7c7b83d011e17af77fa4683bd6138bb76d8203b92ce647ded703108b028a9ee3 | Python | 7,546 | 212 | from abc import ABC, abstractmethod
from functools import partial
import numpy as np
import bayesflow as bf
from scipy.stats import beta
from likelihoods import sample_static_diffusion_process, sample_random_walk_diffusion_process
from priors import sample_scale, sample_ddm_params, sample_random_walk
class DiffusionM... |
145767129f2c17f8b5e8a9ca1638b6a3efc5acce1c3e622709b32b80766c0d8a | Python | 7,554 | 197 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# 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 applicable l... |
df3acd9ef32e37d6e364b9021d125640ed18566c53715d49ab092e2a2a7a8472 | Python | 7,554 | 197 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# 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 applicable l... |
797b32b4a26538d489b5d76fe6e518c5895b9d0e88684f712cf69efe3c5873d1 | Python | 7,556 | 197 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# 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 applicable l... |
e52ac9f3994223a5f4a11c2b40de146d1f4c68fbc5f2fbd6870330f3ca445d85 | Python | 7,565 | 221 | """
pysteps.blending.clim
=====================
Module with methods to read, write and compute past and climatological NWP model
skill scores. The module stores the average daily skill score for the past t days
and updates it every day. The resulting average climatological skill score is
the skill the NWP model skill ... |
f0bd42e59bb46df9d577fc64cf65faf2fe81e0402a9d2b4264ed7292903dc829 | Python | 7,574 | 199 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# 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 applicable l... |
84fed0b84602da8c85edb258d0f0fd00565963110799d9cf77a5dad563a0ae20 | Python | 7,578 | 208 | import os.path as osp
import sys, os
# sys.path.insert(0, '..')
import time
import numpy as np
import matplotlib.pyplot as plt
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch_geometric.datasets import MNISTSuperpixels
import torch_geometric.transforms as T
from torch_geometric.data impor... |
faf376f5a1c7729faeff80eb92943d7f5a312cf16b6adc3efc999d262ae077da | Python | 7,583 | 203 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Nov 8 18:12:28 2018
@author: Nikolai M Chapochnikov
the point of this file is just to read the connectivity data and to export
it into formats that are readable. So basically i would do it just once
and then i would only use the exported datasets, whi... |
75a1c4e7c86ad00a9a4c5a3a2f43072d03552159643dc36e345f5c29c9c7317c | Python | 7,584 | 167 | # -*- coding: utf-8 -*-
import torch.multiprocessing
torch.multiprocessing.set_sharing_strategy('file_system') # https://github.com/facebookresearch/maskrcnn-benchmark/issues/103
import numpy as np
import torch
import random
from torch.utils.data import DataLoader
from src.utils.db5_data import Unbound_Bound_Data
fr... |
4fd65e86c537e63e91149412dc5fac11f6d22bd0351c739c279fc0f16593f54f | Python | 7,589 | 198 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# 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 applicable l... |
54984820b2f2ed33888c19185142649448e6bd0c8ecfbb0744bb143d4f89b513 | Python | 7,591 | 190 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Oct 5 15:58:38 2021
@author: filtsem
This script caluclates the explain variance of phoneme features by subtstracting the acoustic+freq model from the full model for both low and high entropy word models.
Then plot the language vs word entropy graphs... |
36121f9c855d06da92e8fd6cc0b711b20d1b5848dfab0985d67246db69480e09 | Python | 7,593 | 243 | '''
JHK
Python script for computing PDF ratio
*PDF ratio = [PDF of total period] / [PDFs of each decade]
'''
from netCDF4 import Dataset
import numpy as np
import os, pathlib
#==========================================================
# Set main directory
#==========================================================
h... |
53830f66a2fbc74b5f3811c89e6f17cdef8173d193c1fddad5bb9986864c04ca | Python | 7,595 | 161 | """
File name: evaluate_feature_importance.py
Author: Esra Zihni
Date created: 10.08.2018
This is the main script to evaluate the importance of predictors. It reads the
implementation and path options from the config.yml script. It loads the training and
test sets, loads the specified trained model(s) and calculates... |
57db756b85cb1460319c3a9790a38a614682117aa6fe042e642876a9ac13935d | Python | 7,598 | 241 | # -*- coding: utf-8 -*-
"""
pysteps.utils.reprojection
==========================
Reprojection tools to reproject grids and adjust the grid cell size of an
input field to a destination field.
.. autosummary::
:toctree: ../generated/
reproject_grids
"""
from pysteps.exceptions import MissingOptionalDependenc... |
e5b85816cc861fd7b42d3da50245ec7a582b36dcecc00a4ddde751a4e2df7d97 | Python | 7,598 | 198 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# 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 applicable l... |
9c896e614d8cf5a699be9b05917479751edf18d16d5e24e151c0e1776ffe355e | Python | 7,599 | 245 | # -*- coding: utf-8 -*-
import os
import numpy as np
import pytest
import pysteps
from pysteps.timeseries import autoregression, correlation
pytest.importorskip("pyproj")
def test_estimate_ar_params_ols():
R = _create_data_univariate()
for p in range(1, 4):
phi = autoregression.estimate_ar_params... |
602b5842254c7f810e165499e9a050302b78b9cb177603141687dc64c83a6c22 | Python | 7,602 | 208 | import os.path as osp
import sys, os
# sys.path.insert(0, '..')
import time
import numpy as np
import matplotlib.pyplot as plt
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch_geometric.datasets import MNISTSuperpixels
import torch_geometric.transforms as T
from torch_geometric.data impor... |
8d69ef008643dc831be6045bd6ba9fa38dd628fa36ce124132d8af08190f5094 | Python | 7,604 | 100 | import numpy as np
from pydantic import validate_call, Field, ConfigDict
from typing import Annotated, Optional, Tuple, Union
from cellprofiler_library.types import ObjectSegmentation, Image2DGrayscale, ParentsOf
from cellprofiler_library.measurements.measurement_model import LibraryMeasurements
from cellprofiler_libra... |
4185110713d0048cfded77bf0463cc76bd44837fc4c347c4db14a06fce16a856 | Python | 7,605 | 242 | import numpy as np
import pdb2sql
class SASA(object):
def __init__(self, pdbfile):
"""Simple class that computes Surface Accessible Solvent Area.
The method follows some of the approaches presented in:
Solvent accessible surface area approximations for rapid and
accurate protein... |
d76e6ca57d4fca81c148e30c007e9981d21cfeb17b84f6a020ac265363f36af4 | Python | 7,611 | 209 | from turtle import pos
import matplotlib.pyplot as plt
import tensorflow as tf
import tensorflow_probability as tfp
from tensorflow_probability.python.distributions import kullback_leibler
from sklearn.preprocessing import MinMaxScaler
import matplotlib.pyplot as plt
from scipy import interpolate
import os
import Metri... |
7268133e8819b66f08e267e13c2a0bce6d4e83a7b920b8571811137dbbb31361 | Python | 7,613 | 188 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Oct 5 15:58:38 2021
@author: filtsem
This script caluclates the explain variance of acoustic features by subtstracting the phoneme features+freq model from the full model for both low and high entropy word models.
Then plot the language vs word entro... |
c8274ca09d84233eaa9912e3fdcafa7fdb708add66eec8712cb4f33aec8ecbb6 | Python | 7,614 | 201 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# 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 applicable l... |
1b2b50a1bf053cea703cecb16a60fef07621fbb30dd82180f5e411ddc1d9f1d9 | Python | 7,618 | 247 | # -*- coding: utf-8 -*-
"""
Implementation of UNet with Inception Convolutions - UInc
"""
import torch.nn.functional as F
import torch
from GANDLF.models.seg_modules.ResNetModule import ResNetModule
from GANDLF.models.seg_modules.InceptionModule import InceptionModule
from GANDLF.models.seg_modules.IncDownsamplingModu... |
cf102ad65b3fd7e3d7edd9436db08ec7cbfbc1ebf75e67885ddc823cbc8e1694 | Python | 7,618 | 174 | import argparse
import json
import os
import numpy as np
from sklearn.manifold import MDS
from utils import get_dataset, timer
def get_mds(dissimilarity_matrix, is_euclidean=None, random_state=6):
embedding = MDS(n_components=2, dissimilarity="precomputed",
random_state=random_state)
retur... |
6b09c41ef68a0ee40cf51e73f6c4b64dfbe77c26e32b467e8c0c9c0f8b404c71 | Python | 7,625 | 239 | import itertools
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
from sklearn.metrics import accuracy_score, f1_score, roc_auc_score, matthews_corrcoef
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from DCiPatho_config import... |
b09c15992ea042c412f17c28bb5145660d20483c10750c6edc8ac04bb00887d1 | Python | 7,626 | 185 | """ Bottleneck Self Attention (Bottleneck Transformers)
Paper: `Bottleneck Transformers for Visual Recognition` - https://arxiv.org/abs/2101.11605
@misc{2101.11605,
Author = {Aravind Srinivas and Tsung-Yi Lin and Niki Parmar and Jonathon Shlens and Pieter Abbeel and Ashish Vaswani},
Title = {Bottleneck Transformers f... |
1940b0d7d2e985c8839c4984f42623f56cc92fd8e730595024bd8e6a23af1594 | Python | 7,637 | 199 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# 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 applicable l... |
37c31bf7ddcfc710f424bf1e0bf0d8a82a163e84a4a1b776f030041799484734 | Python | 7,650 | 196 | import logging
from pdb2sql import pdb2sql
import re
import os
from typing import List
import h5py
from scipy.spatial import distance_matrix
import numpy
import torch
import torch.cuda
from torch_scatter import scatter_sum
from deeprank.config import logger
from deeprank.models.pair import Pair
from deeprank.operate.... |
26d211e37c0992912e6b6a2031accb0e1cc3d783972413a890583b0339b73cba | Python | 7,654 | 191 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# 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 applicable l... |
d5d87dba0d91a91909dde95c84e1d00194b494721ad683db5daea2e5951baf67 | Python | 7,667 | 180 | import tensorflow as tf
import bayesflow as bf
import bayesloop as bl
import numpy as np
import sympy
import os
from custom_network import OneDimensionalAmortizer
from configuration import default_settings
class NeuralCoalMiningExperiment:
"""Wrapper for estimating the dynamic model of coal mining disasters usin... |
94152e7339bc59d4734a0a7b0673f0bf0cd468ffe762bb466b52041a11966cd5 | Python | 7,675 | 203 | import argparse
import os
from pathlib import Path
import warnings
import numpy as np
import random
import pandas as pd
import pytorch_lightning as pl
import torch
import yaml
from torch.utils.data import DataLoader
from classifier import ClassifierLightning
from data import MILDataset, get_multi_cohort_df
from optio... |
6a1c273078adefc0691b16bc562a15b8928777791109567bf33a7c9ae0f49cc2 | Python | 7,679 | 214 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any... |
e447ef40b28e62991bd6e0c28ffa8b5d83f744c47a4fb75731ddf55ea7371cae | Python | 7,679 | 242 | from datetime import timedelta
import os
import numpy as np
import pytest
from pysteps import io, motion, nowcasts, verification
from pysteps.nowcasts.linda import forecast
from pysteps.tests.helpers import get_precipitation_fields
linda_arg_names = (
"timesteps",
"add_perturbations",
"kernel_type",
"... |
f5b2b32f793f6974cb7bd1a3a7404a740787d29a20e3c8fd80c09c6f6ecfa3c0 | Python | 7,696 | 192 | """
Training runfile
Date: September 2018
Author: Ignacio Heredia
Email: iheredia@ifca.unican.es
Github: ignacioheredia
Description:
This file contains the commands for training a convolutional net for image classification.
Additional notes:
* On the training routine: Preliminary tests show that using a custom lr mu... |
c4095d456d41804bb994a625be41614b48ec1676f468728e219f4d83aa41a528 | Python | 7,702 | 205 | from asteroid_filterbanks import make_enc_dec
from ..masknn.attention import SepFormer, SepFormer2
from asteroid.models.base_models import BaseEncoderMaskerDecoder
class SepFormerTasNet(BaseEncoderMaskerDecoder):
"""SepFormer separation model, as described in [1].
Args:
n_src (int): Number of masks t... |
ad1cb188c0cc7c9e097b51d176ee424259730b55bf86b7470f562e39b72433be | Python | 7,705 | 181 | import pandas as pd
import torch
import torch.utils.data as Data
from sklearn.model_selection import KFold
from torch.utils.data import DataLoader
from DCiPatho_config import Config
from DCiPatho_network import DCiPatho
from DCiPatho_trainer import Trainer
from Utils.tool import roc, acc, F1, mcc, data_reprocess_from_... |
1ca77af001f9735271cae16f4ce49b22fa215b198849c6b1758f7018f0a701fc | Python | 7,719 | 224 | from sklearn.ensemble import RandomForestRegressor
from sklearn.datasets import make_regression
import argparse
from rdkit.Chem import AllChem
import pandas as pd
from rdkit import Chem
from rdkit import DataStructs
import numpy as np
import matplotlib.pyplot as plt
import math
import random
import os
from ... |
e5644190e2e42c35d2e2377e3aa7ade751f13b54fbf104661513517642162f64 | Python | 7,721 | 211 | #
# nate berry
# 2023-04-01
#
# ---------------------------------------------------------
# NOTES:
# - produce vizualizaitons for sample entropy
#
# ---------------------------------------------------------
# ---------------------------------------------------------
import numpy as np
import pandas as pd
import m... |
0573b4eebaf867c72b6a8b2e92c163936d261de6af116e93437cbad90086966a | Python | 7,723 | 210 | import csv
import numpy as np
# R_kCal = 1.986e-3 # kCal/(K*mol)
R_kCal = 1.987191683e-3 # kCal/(mol*K)
R = 8.31e-3 # kJ/(K*mol)
F = 96.48 # kC/mol
J_per_cal = 4.184
default_T = 298.15 # K
default_I = 0.25 # mM
default_pH = 7.0
default_c0 = 1 # M
default_pMg = 10
default_nMg = 0 # added AJG
default_RT = R * def... |
8e25d0553f775edbf3ba8c56c23550999f6d452ce5d5f1dff3a1c6d13c28ff26 | Python | 7,737 | 238 |
from scipy.ndimage.filters import gaussian_filter1d
from sklearn.utils import resample
### PATH VARIABLES ##############################
cache_directory = '/mnt/nvme0/ecephys_cache_dir_2'
code_directory = '/home/joshs/GitHub/neuropixels_platform_paper'
###################################################
df = pd.... |
5e429237a383265eb7740cc0c054a4dc1d074e64c8bf4bd6cc6b2b3a08b621a1 | Python | 7,739 | 171 | import cv2
import numpy as np
import skimage
import tqdm.auto as tqdm
from .utils import enforce_4D
def _get_occlusions(image, num_patches=25, percent_overlap=0.5, background_value=0, **kwargs):
image = enforce_4D(image)
if percent_overlap >= 1 or percent_overlap <= 0:
raise ValueError("Overlap must ... |
051e4e0be9cd706458131ce23be64097737b65df5e76b18fd42566d93acb934a | Python | 7,740 | 180 | # -*- coding: utf-8 -*-
"""
@author: bartulem
Concatenate NPX recordings (ap|lf) into one .bin file.
This script should be run if multiple sessions need to be merged (before running Kilosort2).
The primary reason for merging is the desire to keep the same cell IDs across the recorded
sessions. It should be said tha... |
c9ec6d9a2fee912e33ae83369733f1484b6545c113374f3f77838901b70924f2 | Python | 7,741 | 210 | import torch.nn as nn
import torch.nn.functional as F
import math
from torch.nn import init
def conv3x3(in_planes, out_planes, stride=1):
return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride, padding=1, bias=False)
class PreActBlock(nn.Module):
'''Pre-activation version of the BasicBlock.'''... |
bc652adb543f506a42dfa56e9183cc399c0d15a9f530b1c357468e43bd052c4e | Python | 7,743 | 186 | # This file is part of pyunicorn.
# Copyright (C) 2008--2026 Jonathan F. Donges and pyunicorn authors
# URL: <https://www.pik-potsdam.de/members/donges/software-2/software>
# License: BSD (3-clause)
#
# Please acknowledge and cite the use of this software and its authors
# when results are used in publications or publi... |
d378b28a1b3a1fcca7cd3cc3a1cb99cbd23657a76659460291fedf97fbddd7df | Python | 7,744 | 229 | import re
from copy import deepcopy
import nibabel as nib
import numpy as np
from traitlets import Instance, Unicode, Dict
from traitlets.config import Config
from mrHARDI.base.application import (mrHARDIBaseApplication,
required_file,
... |
24a4ce1c02db76abeda01b06563b2fee4aaf204d0f98b88479b50b3065602c9b | Python | 7,756 | 213 | import os
from glob import glob
import argparse
from itertools import product
from datetime import datetime
import numpy as np
import SimpleITK as sitk
from helpers import *
from dbx import *
import wetransfer
from sklearn.model_selection import KFold
from tensorflow.keras.utils import get_custom_obj... |
bbe80c9381a83565fc7ef87d6e082543d0e3272ed96eb834278e0dcf1679a6c1 | Python | 7,764 | 259 | __all__ = ['imread', 'imsave']
import numpy as np
from PIL import Image
from ...util import img_as_ubyte, img_as_uint
def imread(fname, dtype=None, img_num=None, **kwargs):
"""Load an image from file.
Parameters
----------
fname : str or file
File name or file-like-object.
dtype : numpy ... |
5771c4e5433b11e9fdc66f108821488dcff225bee2659ab679385068aef6b909 | Python | 7,775 | 187 | import numpy as np
import pytest
import cellprofiler_core.utilities.grid
import cellprofiler_core.image
import cellprofiler_core.measurement
import cellprofiler.modules.definegrid
import cellprofiler_core.object
import cellprofiler_core.pipeline
import cellprofiler_core.workspace
GRID_NAME = "grid"
INPUT_IMAGE_NAME ... |
a0b9c42e81a0fcd3603abb04ce53ee2e8137772a6845d9ed4bccce722929d763 | Python | 7,777 | 180 | import numpy
import scipy.ndimage
from typing import Annotated, Optional
from pydantic import Field, validate_call, ConfigDict
from cellprofiler_library.types import ObjectSegmentation, ObjectSegmentationIJV
from cellprofiler_library.functions.segmentation import center_of_labels_mass, relate_children
from cellprofile... |
3dab1b26773bf29df00ea2d51e33afc0b3decd4aab9ba5616e95af514264803c | Python | 7,779 | 200 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any... |
5df4a827cedd77a2bb1f658fe17eac4c49a6923721bfeacda7426dcbe5eb2ae0 | Python | 7,780 | 234 | # Neural Oblivious Decision Ensembles
# Author: Sergey Popov, Julian Qian
# https://github.com/Qwicen/node
# For license information, see https://github.com/Qwicen/node/blob/master/LICENSE.md
"""Dense ODST Block"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Function
fr... |
4dbce8944ee606014ed4faada2648fbf0019d4877753c173634ee1cf5e1912ec | Python | 7,784 | 217 | from __future__ import absolute_import
from __future__ import division
import numpy as np
import scipy.sparse
import scipy.ndimage
from .cpmorphology import minimum_enclosing_circle, fixup_scipy_ndimage_result
from .cpmorphology import fill_labeled_holes, draw_line
from centriole._np_compat import np_cumproduct
def ... |
e6083f70fd6fa5df12460cd034d9550bc8ee2a785706c54318de30606b67772b | Python | 7,786 | 203 | """Tests for the check that rejects redundant alignments.
When bowtie2 looks for more than one alignment per read (-k, -a), it
rejects a new alignment that shares a dynamic-programming cell with one it
has already found for the read: the same read position aligned to the same
reference position on the same strand. The... |
6222ca4f9a072f33e9b057546e0a26b0cc791f593d9e6d0a7af6b44ff15e34bd | Python | 7,787 | 209 | """ PyTorch MARS Optimizer
Code simplified from https://github.com/AGI-Arena/MARS
Paper: MARS: Unleashing the Power of Variance Reduction for Training Large Models - https://arxiv.org/abs/2411.10438
@article{yuan2024mars,
title={MARS: Unleashing the Power of Variance Reduction for Training Large Models},
author=... |
0d96e1d0b822505b3ffb1a11382b8a8c2e75cc837e68462d3e0f3c456f100abd | Python | 7,789 | 176 | import argparse
import json
import os
import numpy as np
from sklearn.manifold import MDS
from utils import get_dataset, timer
def get_mds(dissimilarity_matrix, is_euclidean=None, random_state=6):
embedding = MDS(n_components=2, dissimilarity="precomputed",
random_state=random_state)
retur... |
476d0ebd1025cedf6e0bbab1cfce526589d6875c99423805c8498b3925fc5101 | Python | 7,793 | 192 | import numpy as np
from scipy import ndimage
from .dataset import Datasets, Dataset
# CONSTANT WHERE TO FIND THE DATA
from config import VESSEL_DIR
import SimpleITK as sitk
import os
import matplotlib.pyplot as plt
from matplotlib.pyplot import Normalize
# import pyqtgraph as pg
import pandas as pd
from .download impo... |
2308ae1090c9266ad64bc947c3cd6aca32ca42f038956230061e7cf1227a85e6 | Python | 7,794 | 180 | import inspect
import re
from typing import Optional, Tuple, List
import torch
def _torch_version() -> Tuple[int, int]:
major, minor = re.match(r'(\d+)\.(\d+)', torch.__version__).groups()
return int(major), int(minor)
def onnx_forward(onnx_file, example_input):
import onnxruntime
sess_options = o... |
c636d325ae535d8d5aab5d24d1459d776e0da93745da60052e31ac3eed652872 | Python | 7,802 | 240 | # -- coding: utf-8 --
"""
pysteps.visualization.motionfields
==================================
Functions to plot motion fields.
.. autosummary::
:toctree: ../generated/
motion_plot
quiver
streamplot
"""
from pysteps.visualization import utils
VALID_PLOT_TYPES = ("quiver", "streamplot", "stream")
... |
ed05384f8c0a6469f7fa9e36e4202969e7f8e29e3478e66c12c47cc8d3eda673 | Python | 7,803 | 199 | import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib import animation
from tqdm.notebook import tqdm
from scipy import stats
from sklearn.metrics import r2_score
def true_vs_estimated(ground_truths, post_means, post_sds, param_names, dpi=300,
figsize=(20, 4), s... |
c771c70e0767c1aa689af3a6f88e8dab3c6a6081bafb95f3c8538ae7f8eec0e7 | Python | 7,810 | 156 | import numpy
from numpy.typing import NDArray
from typing import List, Union, Optional, Annotated, Tuple
from cellprofiler_library.types import ImageGrayscale, ImageGrayscaleMask, ObjectLabel, ObjectSegmentation
from pydantic import validate_call, Field, ConfigDict, BaseModel
from cellprofiler_library.functions.measure... |
590006e5370b5adb48c68485a8bb5b3b8b4924494de7f7ec748b12f0a435242a | Python | 7,813 | 136 | """
ClinicalASL - Clinical Arterial Spin Labeling processing pipeline
ASL data preparation module.
Repository: https://github.com/JSIERO/ClinicalASL
Author: Jeroen Siero
Institution: UMCU (University Medical Center Utrecht), The Netherlands
Contact: j.c.w.siero@umcutrecht.nl
Description:
Functions for preparing... |
2729531b4ebe668ca037fd16d473002ac7975fd5fe42b257f6fe91fff51ab7c1 | Python | 7,829 | 236 | import os
import pickle
import h5py
import numpy as np
from deeprank.tools import sparse
class NormalizeData(object):
def __init__(self, fname, shape=None):
"""Compute the normalization factor for the features and targets of a
given HDF5 file.
The normalization of the features is done ... |
a7b5f033b12e22a60b240fa23f48ecd1ea0ebbda31c286152d783a5b36f5ca18 | Python | 7,832 | 239 | """Regression tests against the ptsa 3.0.6 baseline.
Each fixture in `tests/data/regression_fixtures/*.npz` was generated
by running a load-bearing PTSA operation (Morlet, Butterworth,
Resample, MonopolarToBipolar) against a deterministic seeded input
in the reference env. This module loads each fixture and asserts th... |
d502fed6d115ba6a2e846b9d8720b77e27ea442701d2368b2660e523068857e7 | Python | 7,851 | 182 | # -*- coding: utf-8 -*-
"""
Created on Sat Aug 7 18:23:18 2021
@author: Jing Li, Small steps make changes. dnt_seq@163.com
"""
from sklearn.manifold import TSNE
# from sklearn.datasets import load_iris
from sklearn.decomposition import PCA
import matplotlib.pyplot as plt
import seaborn as sns
import pand... |
a5e431e1a7ea574c732c5668e816b8b98edd896d3331b108c39e23fa15be4ab0 | Python | 7,854 | 204 | from hashlib import sha256
from tensorflow.keras import backend as K
import numpy as np
import tensorflow as tf
import settings
#
# LRP calculation
#
from tensorflow.keras import backend as K
import utils
def estimate_relevance(save_dir, network_params, name='intuitive', relevance_params={}):
print(n... |
9e6527d7331a24502e2075d3997da85ba380e478930e7ffc108d3b5f86aa7a64 | Python | 7,858 | 237 | # -*- coding: utf-8 -*-
"""
Created on Tue Aug 9 01:19:05 2022
@author: Manuel
"""
__author__ = "Manuel R. Popp"
#### parse arguments-----------------------------------------------------------
import argparse
import urllib.request # in case it isn't loaded properly by arcgis
def parseArguments():
parser = argpa... |
a2afd27b4dca93baf3473ac0f5f501bc798f6a205249bc3d5eb2cebd4e2cd814 | Python | 7,862 | 291 | import os
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
##############################################################################
# Constants
dataset = "hcp"
parcellation = "schaefer200x17"
idiff_path_combined_bins = os.path.join(
"..... |
4c3a14d66f0e33e21fcff8108d4dec4439d6cb4c0eded7edf42949e2ec2b50d9 | Python | 7,869 | 198 | import numpy as np
from utils import DepthNorm
from io import BytesIO
from PIL import Image
from zipfile import ZipFile
from tensorflow.keras.utils import Sequence
from augment import BasicPolicy
def extract_zip(input_zip):
input_zip=ZipFile(input_zip)
return {name: input_zip.read(name) for name in input_zip.n... |
4509a0532e2f65763302fb13bcb27492dba778ecbc45540d7fcab886e91ad6d2 | Python | 7,870 | 212 | import tensorflow as tf
import tensorflow_addons as tfa
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import cm
from matplotlib.colors import ListedColormap , Normalize
from mpl_toolkits.axes_grid1 import make_axes_locatable
from scipy import interpolate
from matplotlib.collections import LineColle... |
d9183f9d943519f96f003be5ada7421008f3797330be1f9f980e133ed00e3c30 | Python | 7,872 | 162 | """ HardCoRe-NAS
Papers:
* `HardCoRe-NAS: Hard Constrained diffeRentiable Neural Architecture Search` - https://arxiv.org/abs/2102.11646
"""
from functools import partial
import torch.nn as nn
from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
from ._builder import build_model_with_cfg
from ._builder ... |
1a931f2a85185822cae74dbb0c6c0cafc38c780c3af2940f852a775b515dd0ab | Python | 7,874 | 182 | # -*- coding: utf-8 -*-
"""
Created on Sat Aug 7 18:23:18 2021
@author: Jing Li, Small steps make changes. dnt_seq@163.com
"""
from sklearn.manifold import TSNE
# from sklearn.datasets import load_iris
from sklearn.decomposition import PCA
import matplotlib.pyplot as plt
import seaborn as sns
import pand... |
6433e68c1d45d1b6d9fb4e3c4d41f052ce6b4baab2abf3f0f129e26f5e53da14 | Python | 7,874 | 222 | #!/usr/bin/env python3
# Copyright 2021 Alexander Meulemans, Matilde Tristany, Maria Cervera
#
# 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
... |
822f28f262a1a221935a5d8234b3a150e58f5dddcd25e75b0edd1d846afa26df | Python | 7,884 | 174 | from . BedGraphTrack import BedGraphTrack
from . GenomeTrack import GenomeTrack
import numpy as np
from matplotlib import cm
DEFAULT_BEDGRAPHMATRIX_COLORMAP = 'viridis'
DEFAULT_BEDGRAPHMATRIX_INDIVIDUAL = 'grey'
DEFAULT_BEDGRAPHMATRIX_SUMMARY = '#1f77b4' # mpl.rcParams["axes.prop_cycle"].by_key()["color"][0]
class ... |
2c85ed4d509324dc2f654861b5ff1fc8a6125e2a6486a26e325a60244f47f498 | Python | 7,901 | 198 | from __future__ import print_function
import svgwrite
import sys
import os
import logging
logger = logging.getLogger('root')
logger.propagate = False
boxWidth = 10
box_size = 15
v_spacing = 3
colors = {'G': '#F5F500', 'A': '#FF5454', 'T': '#00D118', 'C': '#26A8FF', 'N': '#B3B3B3', 'R': '#B3B3B3', '-': '... |
0e891dce4fb51e7e3f8082500b9be3e93b2f0618fa7433b2c8d7143806f49590 | Python | 7,905 | 234 | '''
Skivi is written/maintained/developed by:
S. Chris Colbert - sccolbert@gmail.com
Skivi is free software and is part of the scikit-image project.
Skivi is governed by the licenses of the scikit-image project.
Please report any bugs to the author.
The skivi module is not meant to be used directly.
Use skimage.i... |
31522ab1d27d60b6fcb36aa13f15f97d598b92fe5c32fa3657e77bf74c83a5cb | Python | 7,905 | 199 | """Adopt a published registry snapshot in all four clients."""
from __future__ import annotations
import argparse
import gzip
import hashlib
import io
import json
import re
import sys
import urllib.request
from pathlib import Path
from typing import cast
from jsonschema import Draft202012Validator, ValidationError
... |
a3be0047cc745ab6bd61f4d765fbcfd94031fc4f30af25414435c7e96933347f | Python | 7,907 | 202 | """
Base Class for all WGANs
Create other WGANs by inherite from the upper WGAN Class and overwrite __init__ and plot_results
"""
import torch
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import copy
from torch.utils.data import DataLoader
import torch.optim as optim
import seaborn as sns
impo... |
5984d57c088d55bc303adc1e7c6e03bdffb8432f0aa25def257a15597460b0b2 | Python | 7,921 | 196 | """
Readers are modular classes designed to read in image data. Like modules, readers can also be added as plugins
using this template class. Place readers into the plugins directory to load them on startup.
A typical reader plugin will add support for a specific file format or protocol.
N.b. readers should not assum... |
05b790e88ebda902d1e92008b8570cbda34d2224f06bffe4f14568536d85b2b6 | Python | 7,939 | 157 | import numpy
from numpy.typing import NDArray
from typing import Optional, Tuple, Annotated, Union, List
from pydantic import Field, validate_call, ConfigDict, BaseModel
from cellprofiler_library.types import ObjectSegmentation, ObjectLabelMask
from cellprofiler_library.measurements.measurement_model import LibraryMea... |
e16a496143e0edc8bbfb7aabebdbf61dd2024d17ac3c476695bd870701326629 | Python | 7,943 | 248 | import numpy
import scipy.ndimage
from cellprofiler_core.constants.measurement import FF_CHILDREN_COUNT, FF_PARENT
from cellprofiler_core.module.image_segmentation import ObjectProcessing
from cellprofiler_core.object import Objects
from cellprofiler_core.setting.choice import Choice
from cellprofiler_core.setting.subs... |
c5d6cb6bbbaf263888fa93e1c28e2f3d2387c69600316085a9c5939437ea7859 | Python | 7,948 | 154 | from pathlib import Path
import os
os.environ['MNE_USE_NUMBA'] = 'false'
VERBOSE = True
dataset_dir = Path(r"../../data/tuh_eeg_abnormal")
output_dir = Path(r"output")
try:
os.mkdir(output_dir)
except:
pass
meta_dataframe_path = output_dir / "df_meta.pkl"
ica_meta_dataframe_path ... |
7ebd3ed1376c448622b04cc372c648c63fa139af27ae16de70726aeea4035d43 | Python | 7,951 | 218 | import copy
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
def Molformer(data, vocab, dist_bar, depth=2, embed_dim=32, ffn_dim=128, head=4, dropout=0.1,
aggregate=True, knn=0):
c = copy.deepcopy
attn = MultiScaleMultiHeadedAttention(head, embed_dim, dist_bar, knn... |
85ff1a104b23c17abda014d05093443002769add5b2e88dcff200ec2d049bb7a | Python | 7,953 | 222 | # -*- coding: utf-8 -*-
"""
Created on Mon Apr 11 11:16:14 2022
@author: Katharina Waury (k.waury@vu.nl)
"""
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import pickle
import os
import seaborn as sns
from Bio.SeqUtils.ProtParam import ProteinAnalysis
from imblearn.under_sampling import Rando... |
1a7820d0f901b8bd0e597eb289136d7978486b6cc1bd566c8a6ca2cc7e622805 | Python | 7,958 | 194 | import TCDF
import argparse
import torch
import torch.optim as optim
from model import ADDSTCN
import pandas as pd
import numpy as np
import networkx as nx
import pylab
import copy
import matplotlib.pyplot as plt
import os
import sys
# os.chdir(os.path.dirname(sys.argv[0])) #uncomment this line to run in... |
ac20cd3817fbd8615950f08e68510f4d04e203264e2c322eeb073a5e7aea3525 | Python | 7,977 | 261 | import pickle
import numpy as np
import ray
import torch
import yaml
from yaml.loader import SafeLoader
import pdb
import os
import matplotlib
import matplotlib.pyplot as plt
from tqdm import tqdm
from scipy.stats import gaussian_kde
matplotlib.rcParams.update({'font.size': 16})
torch.set_default_dtype(torch.float32... |
bf8afa7ef6cf40937d73fd1d49815770c6f0386762b6c3a5e68773a4d0888f14 | Python | 7,979 | 256 | # -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import os
df = pd.read_csv(os.path.join(os.getcwd(), 'data', 'unit_table.csv'), low_memory=False)
area_list = [['VISp', 'VISl', 'VISrl', 'VISam', 'VISpm', 'VIS', 'VISal','VISmma','VISmmp','VISli'],
['LGd','LD... |
e0d96dd62d2866240e166998dc4200fefffd6a7cfdd54d9f0767500f76851f56 | Python | 7,979 | 243 | """
Top-level trial data pre-processing
Authored by Eric Easthope
"""
import os
import warnings
import numpy as np
from pathlib import Path
from pynwb import NWBHDF5IO
from utils import overlap
# Filter warnings
warnings.filterwarnings("ignore")
DATA = "data"
DERIVED = "derived"
subjects = ["EC2", "EC9", "GP31", "... |
1f09acb260ac3bff64618845b2e031f06bc74b29c3576e37eb3118dbb7562b78 | Python | 7,986 | 182 | import torch
from torch import nn
import torch.utils.data as Data
import torch.nn.functional as F
from torch.autograd import Variable
import numpy as np
import copy
import math
import collections
torch.manual_seed(1)
np.random.seed(1)
class LayerNorm(nn.Module):
def __init__(self, hidden_size, variance_epsilon=1e... |
ad73246567299251b43eb1b5f8f3bb73a73fefb7086549dd38cb20d97e45d567 | Python | 7,994 | 244 | # -*- coding: utf-8 -*-
#
# DEEP-OC-image-classification documentation build configuration file, created by
# sphinx-quickstart.
#
# This file is execfile()d with the current directory set to its containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All config... |
1c33832033077ad3ff4ed420df3acaa4694495828115a63fcfe573018a4397e5 | Python | 7,995 | 224 | import wx
from cellprofiler_core.preferences import get_background_color
from cellprofiler_core.setting import BinaryMatrix
from ._module_view import ModuleView
from ..utilities.module_view import edit_control_name
class BinaryMatrixController:
"""A controller for the BinaryMatrix setting
"""
def __init... |
9c236b64efe920a7f0ef4e51b8b689f67efcddccabd67a025dbc8bfacde9ef21 | Python | 7,996 | 208 | """
@author: Johanna Rahm
Research group Heilemann
Institute for Physical and Theoretical Chemistry, Goethe University Frankfurt a.M.
Handle widgets of ImageSumming Jupyter Notebook.
"""
import tkinter as tk
import os
from tkinter.filedialog import askopenfilename
from ipywidgets import widgets
from IPython.display ... |
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