sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
4fc21cddd7db225bb0c5cbfa18c6ddc75204b067a1fb24c741c0d4373fd3f303 | Python | 7,998 | 225 | # 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... |
8ea9121519539732b16e6b44a323b54238a7741cebb516791417ff78ed227e7e | Python | 7,998 | 179 | """CLI interface for imctools library"""
import argparse
from imctools.converters import (
export_acquisition_csv,
mcdfolder_to_imcfolder,
omefile_2_analysisfolder,
omefile_to_histocatfolder,
omefile_to_tifffolder,
omefolder_to_histocatfolder,
v1_to_v2,
)
from imctools.converters.exportacq... |
09d77d55be7d5f4f7382755e6f4ac948fb9bc07a87986fda0372ecc1e0da9df6 | Python | 8,004 | 196 | import torch
import numpy as np
from importlib import import_module
from .default import NormalNN
from .regularization import SI, L2, EWC, MAS
from clb_dataloaders.wrapper import Storage
class Naive_Rehearsal(NormalNN):
def __init__(self, agent_config):
super(Naive_Rehearsal, self).__init__(agent_config)... |
b3e443d57c808ce95da5eeb53efe23e08e2ba96cae299708c05f0b4351cc646a | Python | 8,006 | 170 | 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', '-': '#FFFFFF'}
d... |
f53005e7cc8c6f1cdcc5dbd2ac03c23d68386e553a9a2afdc73d4b456a7be1cc | Python | 8,016 | 250 | import pickle
import numpy as np
import deeprank.learn.modelGenerator
import torch.optim as optim
from deeprank.learn import NetworkGenerator, NeuralNet, DataSet
class saved_model(object):
def __init__(
self,
conv_layers_params=None,
fc_layers_params=None,
reward=... |
b79a52b23e8d6accab10fe4d810d26dfef79f4122b5f30526405182748a4c18f | Python | 8,017 | 212 | import math
import logging
import typing
import numpy as np
class RveInfo:
"""
This class stores all the constant values which are needed for the current RVE-Generation.
If one of theses Parameters is needed in any of the following classes/modules/functions for generating the RVE
it can be called by i... |
781606805fed38bb39b98f7f6f8cff642eaed970de583df67c21c4dcbf173f9d | Python | 8,018 | 207 | import numpy as np
from numba import njit
from configuration import default_lower_bounds, default_upper_bounds
@njit
def _sample_diffusion_trial(v, a, tau, beta=0.5, dt=0.001, s=1.0, max_iter=1e5):
"""Generates a single response time from a Diffusion Decision process.
Parameters:
-----------
v ... |
bccd7c0e8655d1c0635fc34c3fe32946a77db9f701efba569110c70070932d32 | Python | 8,022 | 226 | from typing import Optional, Tuple
from pandas.util import hash_pandas_object
import torch
from torch.utils.data import DataLoader
from abc import ABC, abstractmethod
from dataclasses import dataclass
from GANDLF.models import get_model
from GANDLF.schedulers import get_scheduler
from GANDLF.optimizers import get_optim... |
a3f35065e3ea9e885c0ba563740f7542dff37d852190ff88ab5e77be7b028fae | Python | 8,047 | 177 | # -*- coding: utf-8 -*-
# Some code in this file is from https://github.com/jiesutd/LatticeLSTM
import torch
import torch.autograd as autograd
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
# from kblayer import GazLayer
... |
03bffb86be73e7c06e99e6a00c4332c8657ba195a092872fe51684e5ef831443 | Python | 8,048 | 180 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed May 27 10:43:05 2020
@author: nozais
"""
import os
import glob
import h5py
import nibabel as nib
import sys
import argparse
class MyParser(argparse.ArgumentParser): # Used to diplay the help if no argment is given
def error(self, message):
... |
f39d7baf2c3b32e1ae3ea9531b01a376322e92a1eca45e0ec7ecc61eb4a015fe | Python | 8,049 | 212 | from __future__ import annotations
import importlib.util
import json
import shutil
import sys
from pathlib import Path
import pytest
import yaml
ROOT = Path(__file__).resolve().parents[3]
TOOLS = ROOT / "tools"
if str(TOOLS) not in sys.path:
sys.path.insert(0, str(TOOLS))
SPEC = importlib.util.spec_from_file_loc... |
a74250a15340a5979a61e0db30c86f6e2b3791a68a310a3edf8659ced72f1ba9 | Python | 8,061 | 189 | # -*- 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... |
09695be610e50133c6be069109a2e5f8b0ea7546a9a11d9b748f70b0a7a49b39 | Python | 8,066 | 295 | import numpy
import pytest
import scipy.sparse.coo
import cellprofiler_core.image
import cellprofiler_core.measurement
import cellprofiler_core.module
import cellprofiler.modules.convertobjectstoimage
import cellprofiler_core.object
import cellprofiler_core.pipeline
import cellprofiler_core.workspace
OBJECTS_NAME =... |
b9f703cbeb99eee23bc965446d490fe7ddc56d8846f7477fd172e2698e3d113a | Python | 8,069 | 237 | import numpy
import cellprofiler_core.image
import cellprofiler_core.measurement
import cellprofiler.modules.invertforprinting
import cellprofiler_core.object
import cellprofiler_core.pipeline
import cellprofiler_core.workspace
I_RED_IN = "RedInput"
I_GREEN_IN = "GreenInput"
I_BLUE_IN = "BlueInput"
I_COLOR_IN = "Co... |
1539d08824093c250304436920f39eac51b3b350ce9403c7d10a42dcaef82e76 | Python | 8,083 | 216 | from __future__ import annotations
import bz2
import copy
import gzip
import hashlib
import json
from pathlib import Path
from typing import Any
import pandas as pd
import pytest
from conftest import CORPUS
from test_dm_index import dm_index, make_release, prepare_root
from datamonger import DatasetSplits, FetchResu... |
17221bdffe29eb0c25cef53e631356418d9bd9a997b67056ecb2308a751911ac | Python | 8,090 | 218 | import h5py
from unnatural_movie_analysis_lsn import unnatural_movie_analysis_lsn
from natural_movie_analysis import natural_movie_analysis
import os
import numpy as np
import sys
from gabor_wavelet_preprocessing_linquad import gabor_wavelet_preprocessing_linquad
from threshgrad import threshold_grad_desc_cv, lsq, dotd... |
e990585cdb75d09b8961e750dc7e3f776d7709d2145c7112083bc5ab354e4fcd | Python | 8,092 | 192 | """
File name: train_models.py
Author: Esra Zihni
Date created: 21.05.2018
This is the main script for training models. It reads the implementation and path
options from the config.yml script. It loads the dataset, splits the data into training
and test sets, creates the specified model(s), runs gridsearch to select ... |
18b46c5e35dfb2372d69a5268b9ea6277e6c96a6d703daaead9e4fc368a51bf8 | Python | 8,093 | 242 | import gzip
import numpy as np
from lib.datasets.download import maybe_download_and_extract
import math
import random
import numpy as np
from .dataset import Datasets, Dataset
DEFAULT_SOURCE_URL="http://yann.lecun.com/exdb/mnist/"
def _read32(bytestream):
dt = np.dtype(np.uint32).newbyteorder('>')
return np.from... |
ecf683d141c4f9c77cafdfcb9694f5f07c1dc4940ef9665068814d71a2c3065a | Python | 8,094 | 173 | from cellprofiler_core.preferences import INTENSITY_MODE_HELP, INTERPOLATION_MODE_HELP
C_CHOOSER = 0
C_COLOR = 1
C_SHOW = 2
C_REMOVE = 3
WORKSPACE_VIEWER_HELP = f"""
The workspace viewer is a flexible tool that you can use to explore your
images, objects and measurements in test mode. To use the viewer, select
*View ... |
b93281944e52872ea20647534b2ccf596a1d58a7397a3cfb22d826e0efb0fb51 | Python | 8,115 | 193 | from enum import Enum
import centriole.zernike
def get_zernike_indexes():
"""The Zernike numbers measured by this module"""
return centriole.zernike.get_zernike_indexes(10)
class ObjectSizeShapeFeatures(str, Enum):
"""The category of the per-object measurements made by the MeasureObjectSizeShape module"""... |
cdec798e76457c90465e9919da50b6b5d268c0ef0cba917ed6164578db676a6c | Python | 8,115 | 119 | # -*- coding: utf-8 -*-
"""
------------------------------------------------------------------------------
Copyright (C) 2019 Université catholique de Louvain (UCLouvain), Belgium.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.... |
bf2aad82ed2ac2f257d3b8bde6265612041648b5b7a13f594169259029707419 | Python | 8,119 | 289 | import sys
from itertools import pairwise
import numpy as np
import pytest
from hypothesis import given, settings, strategies
import xgboost as xgb
from xgboost import testing as tm
from xgboost.testing import no_cupy
from xgboost.testing.data_iter import (
check_invalid_cat_batches,
check_iterator_gc,
ch... |
f29790cf7895d5e37d969576f82e43bf3976ca107270a2da171e44ba78ff972a | Python | 8,119 | 225 | """
This file implements a leaky intergrate-and-fire (LIF) model.
You can inject a step current or sinusoidal current into
neuron using LIF_Step() or LIF_Sinus() methods respectively.
Relevant book chapters:
- http://neuronaldynamics.epfl.ch/online/Ch1.S3.html
"""
# This file is part of the exercise code repository... |
bb8d466d1bafafec7317e4d3c46f3b58a3de16f0b23dc7309ea5d56b5e3ab021 | Python | 8,131 | 261 | # Evaluate segmentation results
import colorsys
import itertools
import json
import os
import pickle
import matplotlib.pyplot as plt
import numpy as np
import pycocotools.mask as mask
import scipy.ndimage as ndimage
from PIL import Image
RESULT_PKL = "./results.pkl" # path to results .pkl file
IMGS_PATH = "./csb-1/... |
20784f825614aa30e22e09d36c35f0ce33ad4dc1b5367b70bca86bdc3a2513cc | Python | 8,139 | 169 | """ Per-class loss weights derived from label frequencies
Class stats (per-class positive counts and the sample count, written by `class_weights.py` in the repo root)
are loaded with `load_class_stats()`. `compute_class_weights()` turns them into BCE / ASL `pos_weight` or
`class_weight` vectors, `load_class_weights()`... |
0adbc7cfc2cbae38e7a3de86fc3aa92553f24d58d77e2ec366ec369939cf8bd7 | Python | 8,149 | 224 | from rdkit.Chem import AllChem
import pandas as pd
import sys
from module.pair_generation_top import Generator
from module.pair_generation_all import Generator as Generator_all
from module.paired_dataset import Dataset
from torch.utils.data import DataLoader
from rdkit import DataStructs
from rdkit import Chem
import... |
99ec9cf208e3ee0db1600b97b2052006e34daa11f9c821c0028f080999006840 | Python | 8,159 | 202 | from __future__ import division
from unittest import TestCase
import numpy as np
from numpy.testing import assert_equal
import scipy.sparse as sp
from .coarsening import (coarsen_adj, _coarsen_adj, _coarsen_clustered_adj,
_compute_perms)
from .adjacency import points_to_adj
from .distortion ... |
e7f8495d76d3f1043bcd1d2ea445a5bcb5ca50417095e1382f64ba328687453f | Python | 8,162 | 253 | import sys
import functools
from typing import Any, cast
import numpy as np
from numpy.typing import DTypeLike
from .MatlabIO import *
# mapping from python type specification (scipy loadmat will report those) to numpy dtype string abbreviation
if sys.platform.startswith('win'):
numpy_type_dict = {
ty... |
8060aacded4370684dba503b0810438f643fb596c2525ac5df1444a228510f86 | Python | 8,177 | 178 | import time
import numpy as np
from scipy.linalg import solveh_banded
class NewtonMethod:
def __init__(self, theta0=None, g_log_prior=None, h_log_prior=None, gh_log_prior=None, gh_log_likelihood=None,
banded_h=False, theta_independent_h=False, learning_rate=1e-1, initial_learning_rate=1e-2,
... |
ddaeae9e1fd9ad4e4767c690cf7ca56a1e72aaf405cedb7405499670fa789a59 | Python | 8,184 | 199 | import numpy as np
import torch
import ttach as tta
from typing import Callable, List, Tuple
from pytorch_grad_cam.activations_and_gradients import ActivationsAndGradients
from pytorch_grad_cam.utils.svd_on_activations import get_2d_projection
from pytorch_grad_cam.utils.image import scale_cam_image
from pytorch_grad_c... |
3e38efb531230e3377951c0149e1cfa63825883bf27ecbe947f73ebcd30095d3 | Python | 8,202 | 215 | # unrefined: .features
# filter_by: score mcrl_score dot revdot prob percentile
# equivalence_by: inchikey inchik name mzrt
# FDR: True False
# MAX_FDR: 100
# IF_NO_FDR_WHAT_MIN_SCORE: 900
# RT_TOL: 2.0
# PPM: 20.0
# MatchPolarity: True False
# Keep_Decoy_Hits: False True
# output: .features
import sys
import time
imp... |
ca3b800fd2415e81fe7ae10d22187e25cc820292dbfc4cff247efbfb530f84c0 | Python | 8,203 | 238 | from glob import glob
from os import path
import os
from time import sleep
import numpy as np
from tensorflow.keras.optimizers import Adam, RMSprop
from tensorflow.keras.utils import get_custom_objects
from tensorflow.keras.models import load_model
from config import *
from dbx import download_and_extract
... |
9c01672607a848bc73d748156d204bab40e6ce9cad139d4be9cbfed308f53611 | Python | 8,210 | 170 | """
ClinicalASL - Clinical Arterial Spin Labeling processing pipeline
DICOM to NIfTI conversion 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:
Function for conve... |
2ebfa869c14aa5aaf38e185bd57f557907c33df3d79df3af35e1d00166a04b68 | Python | 8,216 | 274 | # -- coding: utf-8 --
"""
pysteps.verification.ensscores
==============================
Evaluation and skill scores for ensemble forecasts.
.. autosummary::
:toctree: ../generated/
ensemble_skill
ensemble_spread
rankhist
rankhist_init
rankhist_accum
rankhist_compute
"""
import numpy as n... |
978421f49e04ca18b25d9e6773e4cd5385e1280bb59c3b14a51c133f5042788c | Python | 8,231 | 214 | #!/usr/bin/env python3
"""
A collection of functions used by ciftifies report generation functions
i.e. ciftify_peaktable and ciftify_dlabel_report
"""
import os
from ciftify.utils import run
import ciftify.config
import numpy as np
import pandas as pd
import logging
import logging.config
def define_atlas_settings()... |
c31d1d6d75ecf9c2f91aeb1af4ee96541dab86748d996c6c510de401edd1995a | Python | 8,233 | 220 | # -*- 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... |
5b4d844f6d793d324a02688d7fe4131005a1bc2542158423922a4cf3f432b8b5 | Python | 8,238 | 230 | """ ConvMixer
Papers:
* `Patches Are All You Need?` - https://arxiv.org/abs/2201.09792
"""
from typing import List, Optional, Tuple, Type, Union
import torch
import torch.nn as nn
from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
from timm.layers import SelectAdaptivePool2d, get_device_dtype
from ._r... |
eeea0b65433e1b4ae6fcabe730164b64a0c0608304dbcce3c2ada3d7499d9295 | Python | 8,240 | 220 | # -*- 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... |
c66cc09fb3f492a25dfc671fd7b9cc715efce29a16daaa62dc0638f374e4da4a | Python | 8,247 | 235 | import hashlib, os
from typing import Any, Dict, Optional, Tuple
import torch
from ..version import __version__
from .generic import get_unique_timestamp, get_git_hash
# these are the base keys for the model dictionary to save
model_dict_full = {
"epoch": 0,
"model_state_dict": None,
"optimizer_state_dic... |
edcc7fc76f4731cf454c50726e7d9751bf66f3c5aedaa87354f7a0e87c97d3e7 | Python | 8,251 | 191 | #!/usr/bin/env python3
"""
Takes a atlas or cluster map ('dlabel.nii') and output a nifti image in a particular participants space
Usage:
ciftify_dlabel_to_vol [options] --input-dlabel <input.dlabel.nii> --left-mid-surface <input.L.surf.gii> --volume-template <voltemplate.nii.gz> --output-nifti <output.nii.gz>
Ar... |
f58f6b41a504553aa6a306bc39ed1b847cf3c9d54ec5207b3b26ba8a7bef3f92 | Python | 8,252 | 230 | import sys
from os import path
sys.path.append(path.dirname(path.dirname(path.abspath(__file__))))
from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay, classification_report
import matplotlib.pyplot as plt
from knn import *
from inference import *
import cv2
import time
from datetime import timedelt... |
4a1efa18bdbc4fa15076a7dae8b138593cfef882d9b4e08b1f89e532ac03a6c1 | Python | 8,254 | 243 | #################################
#
# Imports from useful Python libraries
#
#################################
import numpy
import os
import skimage
import subprocess
import uuid
import shutil
import logging
import sys
from your_dependency_with_a_long_and_improbable_name import somefunction
########... |
227d608fc5373c148506837839518a7290da0ece5cd6b4d0e56344fb2ca8c48b | Python | 8,263 | 252 | from typing import Tuple, Dict
import numpy as np
from scipy import linalg as LA
from functions import general as FG, olfactory as FO, nmf as nmf
def generate_samples(D: int = 50, N: int = 100, K: int = 10,
method: str = 'spiked_covariance', options: dict = {},
scale_data: ... |
142c765bab10eda8fabccaefa55a1aea2427e0c6d8c7ac40b9e1890a9adfee97 | Python | 8,272 | 182 | import warnings
warnings.filterwarnings("ignore")
import logging
import platform
import sys
import matplotlib
from argparse import ArgumentParser
import pytorch_lightning
import torch
from utils import load_state_dict_greedy
from pytorch_lightning.strategies import DDPStrategy
import numpy as np
from functools import ... |
34964de12efa44c2dee4c857a40e0e7c71effdf1ef67f368317d76139aa7c7dd | Python | 8,274 | 177 | import os.path as osp
from typing import Any, Tuple
import h5py
import numpy as np
import numpy.typing as npt
from ptsa.data.readers import BaseRawReader
__all__ = [
'H5RawReader',
]
class H5RawReader(BaseRawReader):
"""Class for reading raw EEG data stored in HDF5 format."""
def __init__(self, **kwarg... |
9adb46f653be719054ea93cd86d6033e9c4e7be497da7da3a40b10cccaefe634 | Python | 8,277 | 186 | """Configuration object for the substructure pipeline.
Every knob the pipeline uses lives here. `SubsConfig.from_rve_info()` is the only place that reads
`RveInfo`, so the pipeline modules themselves stay free of global state and are directly testable.
"""
import os
from dataclasses import dataclass, field, asdict
fro... |
da1b04f1de5765c4e968cc55b5fb28828efe563d248600c87acab760e7f92c30 | Python | 8,278 | 226 | 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 ... |
011c3645c970adbd3ee20b117e9d94d9194a16ba134f1cc89c4a6d3b041be0f9 | Python | 8,282 | 290 | """Utilities for generating AFIDs-related graphics"""
import plotly.graph_objects as go
from afidsvalidator.model import EXPECTED_DESCS
def gen_connecting_lines(ref_afids, user_afids):
"""Assemble points from each fcsv into pairs.
Parameters
----------
ref_afids : Afids
Reference AFiDs obje... |
cfce26328d5ca15b89036f17dcde49e12a6d883a902e56ec8b349564ac0e57f4 | Python | 8,283 | 247 | # -*- coding: utf-8 -*-
"""
pysteps.postprocessing.interface
====================
Interface for the postprocessing module.
Support postprocessing types:
- ensmeblestats
- diagnostics
.. currentmodule:: pysteps.postprocessing.interface
.. autosummary::
:toctree: ../generated/
get_method
"""
import ... |
4b99f376119ba7b2fee9a85bcf1f8cc5a02b79d937a5236ab28d7839d15c6ade | Python | 8,285 | 211 | """Write the substructured RVE back out as a DAMASK material.yaml + grid.vti.
One DAMASK material per block for substructure cells, one per grain for everything else, so each
block carries its own orientation. The phase definitions and the homogenization from the
material.yaml that dragen/generation/spectral.py alread... |
230e09af999e83c99971630d5c81cba360ac519fa46339715e490879b278b03e | Python | 8,290 | 185 | # -*- coding: utf-8 -*-
"""
@author: bartulem
Convert the labeled tracking .csv to .pkl for loading into the GUI.
The Jython GUI we use to visualize the behavior of the animal requires
the labeled .csv data to have a certain format (in order to be loaded).
This script performs those modifications and when the proce... |
8059b82deaa1f9e16d421ae89a397d34ac9a93f110d79cc3a54b7f43bda15997 | Python | 8,290 | 226 | import os
import numpy
from deeprank.models.variant import PdbVariantSelection
from deeprank.tools import sparse
from deeprank.domain.amino_acid import amino_acids
def get_variant_group_name(variant):
"""
Args:
variant (PdbVariantSelection): a variant object
Returns (str): an unique n... |
33b6f42b2a2377e28d4446434236b499fd35e98d819a7dd77ad344e0d9336191 | Python | 8,291 | 234 | # encoding: utf-8
# Author : Floyed<Floyed_Shen@outlook.com>
# Datetime : 2022/7/26 18:56
# User : Floyed
# Product : PyCharm
# Project : BrainCog
# File : vgg_snn.py
# explain :
from functools import partial
from torch.nn import functional as F
import torchvision
from timm.models impor... |
2367e41b46c1f20682823a82461a249048158559dae936efb52bd5d28b422a93 | Python | 8,300 | 185 | # Fundamental libraries
import os
import sys
import time
import glob
import copy
import random
import datetime
import warnings
import itertools
import numpy as np
import pandas as pd
import pickle as cp
import seaborn as sns
import multiprocessing
from scipy import stats
from pathlib import Path
from ast import literal... |
9529e097a30f833589bd621931cfdc515c55e7f072a44b38392987f73c7fc8ff | Python | 8,310 | 181 | """
ClinicalASL - Clinical Arterial Spin Labeling processing pipeline
DICOM parameter extraction 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:
Function for extr... |
1f58453f3fce965596430db582ccf158032cfea6ae19f6c1da659c2cde4d0207 | Python | 8,319 | 211 | # -*- 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... |
a6e57da83f1e460b717cd630266b252d37a12f249a139b435d620da4092bda48 | Python | 8,324 | 154 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import sys, os
import tensorflow.compat.v1 as tf
tf.disable_v2_behavior()
import tensorflow_probability as tfp
from tensorflow.python.framework import constant_op
from tensorflow.python.fram... |
cc45b7052ef34f34835ba075c10ab4c4d8db7626a3f132abc2fa62d94cf579ac | Python | 8,332 | 227 | import json
import math
import os
import numpy as np
import matplotlib.pyplot as plt
from sklearn.cluster import KMeans
from sklearn.metrics import silhouette_score
from utils import timer
from distance_calculation import get_mds
def get_dataset(datafile):
with open(datafile, "r") as json_file:
return np... |
c2e8637665be4420b5b5677e03add592518eed816fef4096dde2421c6aeae399 | Python | 8,348 | 203 | from typing import Any
import os
import numpy as np
import torch
import yaml
def set_args(args):
config_name = f"config_{args.dataset}.yaml"
with open(config_name, 'r', encoding='UTF-8') as f:
config = yaml.safe_load(f.read())
args.prefix = config['prefix']
args.ratios = config['ratios']
... |
3ddf6aa5a7f37a5acecb88bd0071844442e3a5ec39647ceee348c6fca8f7f395 | Python | 8,350 | 230 | """Numerical-correctness tests for ButterworthFilter and ResampleFilter.
Hand-coded ground-truth tests complementing the regression suite in
``tests/test_regression.py``. Asserts mathematical properties that
hold for any correct implementation: stopband attenuation, passband
flatness, zero-phase (filtfilt), frequency ... |
50f83f386651015f76d0954c9c6e0c63a14f8c882d0eb5b90c0b4e3083cb912b | Python | 8,351 | 243 | import centriole.cpmorphology
import centriole.outline
import numpy
import cellprofiler_core.image
import cellprofiler_core.measurement
import cellprofiler_core.module
import cellprofiler.modules.expandorshrinkobjects
import cellprofiler_core.object
import cellprofiler_core.pipeline
import cellprofiler_core.workspac... |
d55685193f57f7e6fef605143e26fbec672cf259b984cc80c5a1c3ba673c8a63 | Python | 8,351 | 199 |
ASSIGN_ALL = "All images"
ASSIGN_GUESS = "Try to guess image assignment"
ASSIGN_RULES = "Images matching rules"
LOAD_AS_GRAYSCALE_IMAGE = "Grayscale image"
LOAD_AS_COLOR_IMAGE = "Color image"
LOAD_AS_MASK = "Binary mask"
LOAD_AS_MASK_V5A = "Mask"
LOAD_AS_ILLUMINATION_FUNCTION = "Illumination function"
LOAD_AS_OBJECTS... |
3b3c73773ff79f1bb4d208243a210f383ce4ba43973f0a3f29dce4300a146c61 | Python | 8,352 | 223 | # -*- coding: utf-8 -*-
from . GenomeTrack import GenomeTrack
from . BedGraphTrack import BedGraphTrack
from matplotlib.patches import Rectangle
from matplotlib.collections import PatchCollection
from matplotlib.path import Path
import matplotlib.patches as patches
import numpy as np
DEFAULT_NARROWPEAK_COLOR = '#FF0... |
0b3f4662c0537a776eb6c7caa52c1c7f14a4c4a4a8845c91c5a0c691bfad6e3d | Python | 8,353 | 288 | #!/usr/bin/env python3
# coding: utf-8
"""
MIT License
Copyright (c) 2022 Pawan Goyal
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... |
26d4aad2fddd9c312d9fa1d65c750286dd5d937537833dc3d049bf718f919eb8 | Python | 8,355 | 196 | """Current model traits and construction arguments, separate from source checkpoint metadata."""
from typing import Any, Dict, Optional, Sequence, Tuple, Union
from torch import Tensor, nn
def _spatial_size(size: Union[int, Sequence[int]]) -> Tuple[int, int]:
if isinstance(size, int):
size = (size, size... |
6c20e6c2ba50c34a2624f9b9b0ddc37d680034d74b0ae805a80db9544cf40b22 | Python | 8,356 | 214 | import glob
import sys
import os.path
import logging
import jinja2
import importlib.resources
import wx
import wx.html2
from cellprofiler_core.preferences import set_startup_blurb
import cellprofiler.gui.help.content
import cellprofiler.gui.html
import cellprofiler.gui.html.utils
import cellprofiler.gui.utilities.ic... |
e4116bb8650332a8fd0fc2ac1e8f75729824fb8d60eb7ad2a796ced787e48465 | Python | 8,358 | 269 | import tensorflow as tf
import numpy as np
from lib.network import Network
from lib.pinn import PINN
import matplotlib.pyplot as plt
import pandas as pd
import os
from Helper import calcY
import math
import argparse
from itertools import product
import sys
SLRUM_ARRAY_TASK_ID = int(sys.argv[1])
nu_list = [1.4e-6,1.... |
c40e3ddde58b0dc37344380bf2d311b7917dea6301d632c842eb70f6117dad55 | Python | 8,367 | 251 |
"""
FindMaxima
==========
**FindMaxima** isolates local peaks of high intensity from an image.
The returned image will feature single pixels at each position where
a peak of intensity was found in the input image.
This can be useful for finding particular points of interest,
identifying very small objects or genera... |
b7d0e9711a6d1abfc86ecde64c23a988005663f60ba1621f7c68b8b2271ca986 | Python | 8,368 | 236 | """
DisplayHistogram
================
**DisplayHistogram** plots a histogram of the desired measurement.
A histogram is a bar plot depicting frequencies of items in each data range.
Here, each bar's value is created by binning measurement data for a set of
objects. A two-dimensional histogram can be created using the... |
1738fba7830b0b8a24d7297cf88e8548fd643e64740ab1da3f3a846dbe849aa9 | Python | 8,382 | 216 | from unittest import TestCase
import torch
from .losses import DCS, DiceLoss, FocalLoss, GeneralizedDiceLoss, DiceCoeff
from .evaluation import dice_coeff
import matplotlib.pyplot as plt
from torch import sigmoid
class DCS_mixed(object):
def __init__(self, pre_sigmoid=False):
self.pre_sigmoid = pre_sigm... |
e60eb8af21e584b4ea9f1d2d13773f057a06405ebcca270ec9fe12dd7d0a5776 | Python | 8,384 | 181 | # -*- coding: utf-8 -*-
import os
import pickle
import subprocess
import sys
import time
import numpy as np
import scipy.io as sio
import scipy.io.wavfile as wav
import torch
import torchvision
from python_speech_features import fbank
from sklearn import preprocessing
from sklearn.preprocessing import no... |
f31f1fb29707efa6d202827c0773239430bc8652cfcffa20394fca632d824927 | Python | 8,395 | 161 | import datetime
import logging
from copy import deepcopy
from os import makedirs
from os.path import join, exists
from posixpath import abspath
import argparse, math, random, sys, time
import numpy as np
#np.random.seed(0) # set random seed for keras neural nets
#import xgboost as xgb
import tensorflow as tf
from kera... |
7b810a9a9452390e69f0e2b55fb2828217ea86409bd31f02bee2557bdaabb06a | Python | 8,404 | 221 | import numpy as np
import pandas as pd
import torch
import lightgbm as lgb
import hydra
from omegaconf import DictConfig
from pytorch_lightning import seed_everything
from src.datamodules.tabular import TabularDataModule
from src.utils import utils
import matplotlib.pyplot as plt
import seaborn as sns
import xgboost as... |
b6eab12fd1b42d9ca440de4a2398dc1b3ad23369c68d9aa4060fad211f25a511 | Python | 8,404 | 143 |
from multiprocessing import Process, Queue, cpu_count
import pysam, sys
import getopt
import fileinput
from sys import argv # Used to bring in the feature argv, variables or arguments
def main(scriptname, argv):
vcf = '' ; tbam = '' ; nbam = '' ; slop = 1000; ## Default values
try:
opts, args ... |
2cd8ece29c805711294c2e0e83590dbd5d0b7a42cb9fade088c580699d9b176f | Python | 8,407 | 229 | import json
import math
import os
import numpy as np
import matplotlib.pyplot as plt
from sklearn.cluster import KMeans
from sklearn.metrics import silhouette_score
from utils import timer
from distance_calculation import get_mds
def get_dataset(datafile):
with open(datafile, "r") as json_file:
return np... |
fcb92636080015121ed4f74b459a0922f192f928dfdafbdc2875b0f8069af151 | Python | 8,410 | 162 | from tensorflow.keras.models import Model
from tensorflow.keras.layers import concatenate
from tensorflow.keras.layers import BatchNormalization, Activation, Conv2DTranspose
from tensorflow.keras.layers import Input, Dropout, Conv2D, MaxPooling2D, dot, add
import tensorflow as tf
# 3 res with 3*3 + true skip + tr... |
2a513d2754437fa0bd90ae01fac26413cf6f4b060d24260a8d72c04d519f20dd | Python | 8,417 | 274 | #!/usr/bin/env python3
import os
from itertools import product
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
# -------------------------------------------------------------------------- #
# Prepre input paths
dataset = "hcp"
model = "kernelridge_scik... |
d3f9409571bd1d1615464ff3351c92a7c771e7b5dbbad912c1028b661fef478f | Python | 8,424 | 248 | import re
from pathlib import Path
from typing import Any, Dict, List
import yaml
from bs4 import BeautifulSoup
from .context_url import CONTEXTFILE_URL
from .jsonldutils import get_context_version
from .models import Activity, Item, Protocol, write_obj_jsonld
PROTOCOL_KEYS_REQUIRED = [
"protocol_name",
"pro... |
c99eacbd56f6d34252e06a5aea2557c83b39f52f9cef494d642b1d74a7eab666 | Python | 8,428 | 175 | import os
from time import time
import torch
import torch.optim as opt
from sklearn.model_selection import train_test_split
from torch.utils.data import DataLoader, TensorDataset
from torch.nn.functional import l1_loss
from einops import rearrange
from model.egnn import EGNN_Network
from model.molformer import Molform... |
b7bdd15e51f2f0ecced2a46be29b255086148650d87d674d3d3864c46cae66c3 | Python | 8,432 | 242 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import logging
import os
import argparse
from typing import Optional
import click
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from pathlib import Path
from deprecated import deprecated
from GANDLF.cli import copyrightMessage
from GANDLF.entry... |
e867015478f38e3de30deeb342003625854eabe8c4002352507b04c67052b352 | Python | 8,443 | 193 | import pandas as pd
import numpy as np
from openslide import OpenSlide
from multiprocessing import Pool, Value, Lock
import os
from IPython.display import display
import matplotlib.pyplot as plt
from skimage.color import rgb2hsv
from skimage.filters import threshold_otsu
from skimage.io import imsave, imread
from skima... |
cac0a9c2b0405453fc930683c77c7b0f3e227ce897a742b1c9529878ef3e267b | Python | 8,445 | 266 | # -*- coding: utf-8 -*-
# All configuration values have a default; values that are commented out
# serve to show the default.
import os
import subprocess
import sys
from datetime import datetime
import json
from jsmin import jsmin
# If extensions (or modules to document with autodoc) are in another directory,
# add... |
f9e805829b3dd7676e80222b5a96b7378fd2e2b48e28ab82073569a4ad1125d3 | Python | 8,447 | 196 | import os
import uuid
from datetime import datetime, timezone
import xmltodict
from dateutil.parser import parse
import imctools.io.mcd.constants as const
from imctools import __version__
from imctools.data import Acquisition, Channel, Panorama, Session, Slide
from imctools.io.utils import sort_acquisition_channels
... |
00a0b01815178a318d86a112c014a5da9a21dd0369a510dda5197f8da7ffd29c | Python | 8,450 | 281 | # -*- 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... |
fddd9f6fdb7e5909e4a2ca3910f61d86894688e654c97ea3ff5f4cf9f15ff7a0 | Python | 8,454 | 150 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Oct 5 15:58:38 2021
@author: filtsem
"""
from pathlib import Path
import numpy as np
import eelbrain
import re
import utils
import os
ANOVA_results_path = '/project/3027007.02/Scripts_for_publication/TRFs/Weights_ANOVA/Dutch_part1/'
language = 'F... |
15618d4c19fada7c961426993e164d534cfb6aa6a036e2ab46f3d4f0766aca7c | Python | 8,462 | 272 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Feb 20 17:04:32 2020
@author: joshs
"""
# %%
df = pd.read_csv(os.path.join(os.getcwd(), 'data', 'unit_table.csv'), low_memory=False)
import matplotlib
matplotlib.rcParams['pdf.fonttype'] = 42
matplotlib.rcParams['ps.fonttype'] = 42
# %%
from scipy.... |
7eb8091bfd4dee6d286bdc801b4e639f418ec60f97761ceff844b0a101143206 | Python | 8,470 | 242 | # -*- 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... |
f2bc1b8841ae01ff782ffd768335d27f95ccf7e8ef1d1ad7e930e38580600e0b | Python | 8,471 | 260 | """ 'Fast' Normalization Functions
For GroupNorm and LayerNorm these functions bypass typical AMP upcast to float32.
Additionally, for LayerNorm, the APEX fused LN is used if available (which also does not upcast)
Hacked together by / Copyright 2022 Ross Wightman
"""
from typing import List, Optional
import torch
f... |
d47a24cae0ed1f3b2d20558e045a8acc794434d4d8275d8c3b898e1cdb78c75e | Python | 8,480 | 185 | import torch
import cv2
import numpy as np
from e2vid.model.model import *
from e2vid.utils.inference_utils import CropParameters, EventPreprocessor, IntensityRescaler, ImageFilter, ImageDisplay, \
ImageWriter, UnsharpMaskFilter
from e2vid.utils.inference_utils import upsample_color_image, \
merge_channels_into... |
68a61733c30b16878bd17c427213afa6a7346216f8132bd734b65b08eb108fe9 | Python | 8,482 | 234 | # -*- 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... |
a703e517f8fac4d5a6138616cf9c0241ae62105a3456126e0b6c25e183714968 | Python | 8,492 | 222 | #!/usr/bin/env python3
"""
Runs all posible ciftify functions on some test data
Usage:
run_ABIDE_NYU_tests [options] <testing_dir>
Arguments:
<testing_dir> The directory to run the tests inside
Options:
--outputs-dir PATH The directory to write the gerated outputs into
--stages LIST s... |
1e7f3ef53069c840aed02c6bab4097308f7fd43d75a7cf9d7f7ab482b09429eb | Python | 8,505 | 233 |
"""
Educational Use License
This software is provided solely for educational purposes.
Any use of this software for commercial or non-educational purposes is prohibited.
If you use this software in an academic setting, you must cite the following paper in any resulting publications or presentations:
[Sanaullah, Ko... |
74e80f6927746b90d73468632ae7fb6af892a6625773dcf8ae9ce56bbd488cc5 | Python | 8,505 | 235 | """Canonical-form version 1 encoder."""
from __future__ import annotations
import hashlib
import io
import struct
from collections.abc import Callable, Iterable
from typing import Any, cast
import numpy as np
import numpy.typing as npt
from datamonger._models import (
LogicalComponent,
LogicalDenseMatrix,
... |
e79c4a52cdb5b797e3404874a3bd05721128af3e6e21b3ffb8fb0264ffcc8386 | Python | 8,508 | 253 | #!/usr/bin/env python
# coding: utf-8
# In[1]:
import tensorflow.compat.v1 as tf
tf.disable_v2_behavior()
import numpy as np
import sys
from pandas_plink import read_plink#1_bin
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.decomposition import PCA
from sklearn.linear_model import LogisticRegressi... |
135d6eb90d7798e470da929345d4c189fe74930dce13550e01d9a690fb9baa67 | Python | 8,509 | 237 | # -*- coding: utf-8 -*-
"""
Implementation of TransUNet
"""
from GANDLF.models.seg_modules.DownsamplingModule import DownsamplingModule
from GANDLF.models.seg_modules.EncodingModule import EncodingModule
from GANDLF.models.seg_modules.InitialConv import InitialConv
from GANDLF.models.seg_modules.out_conv import out_co... |
330ae525d72a00e299c36ba5d83e30eacbb40d1bcd548d80576b01f8cd97a6a7 | Python | 8,510 | 232 | import pandas as pd
import pytorch_lightning as pl
import seaborn as sns
import torch
import torchmetrics
import wandb
from matplotlib import pyplot as plt
from utils import get_loss, get_model, get_optimizer, get_scheduler
class ClassifierLightning(pl.LightningModule):
def __init__(self, config):
super(... |
476a4668b867eaec591663fbb62bded3f5e92f57e11913389cd10d38fb6f6ee4 | Python | 8,510 | 250 | """ Res2Net and Res2NeXt
Adapted from Official Pytorch impl at: https://github.com/gasvn/Res2Net/
Papers:
* `Res2Net: A New Multi-scale Backbone Architecture` - https://arxiv.org/abs/1904.01169
"""
import math
from typing import Optional, Type
import torch
import torch.nn as nn
from timm.data import IMAGENET_DEFAULT... |
cb96003f4b607fa21461487f3cbf28de25bf18fab2488c74f26962b23b652a1f | Python | 8,513 | 287 | from __future__ import division
import pandas as pd
from matplotlib.mlab import find
from numpy import *
from matplotlib.mlab import *
from matplotlib.pylab import *
from scipy.io import savemat
import sys
from scipy.stats import *
from scikits import bootstrap
from scipy.stats import spearmanr
import seaborn as sns
fr... |
23d956c26bc78e970015a1be8d258f5d6eca7393719dd97331c87ab6ef516b73 | Python | 8,532 | 299 | # -*- coding: utf-8 -*-
"""
pysteps.visualization.basemaps
==============================
Methods for plotting geographical maps using Cartopy.
.. autosummary::
:toctree: ../generated/
plot_geography
plot_map_cartopy
"""
from matplotlib import gridspec
import matplotlib.pylab as plt
impo... |
890532a114b7797d7fdbbcfa2e1928d0ae10de249d2df836403b498c423f76ab | Python | 8,532 | 180 | from pydantic import Field, validate_call, ConfigDict
from typing import Optional, Tuple, Annotated, Any, Union
from ..functions.image_processing import (
get_adaptive_threshold,
get_global_threshold,
apply_threshold,
)
from ..opts.threshold import (
Scope,
Method,
Assignment,
AveragingMeth... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.