sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
be6cdb7df2280d0eb99801fd6ad4d6411e4f58403f79713d500df922a4aa4552 | Python | 5,852 | 167 | import numpy as np
import os
from matplotlib import pyplot as plt
from matplotlib.patches import Rectangle
from matplotlib import cm
from matplotlib.colors import Normalize
colors = cm.tab10(np.linspace(0,1,9))
NO_FLUX_BND = False # This is a boolean variable for no_flux or fixed boundary condition. The fixed boun... |
f74b8d423fb21facd964186cc41a2e9f4906d6727e54a06347f6e8eb72b205c1 | Python | 5,855 | 180 | #!/usr/bin/env python
import os
import sys
from argparse import ArgumentParser
import glfw
from OpenGL.GL import *
import numpy
import h5py
import pyrr
# Assure that python can find the deeprank files:
deeprank_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.insert(0, deeprank_root)
fro... |
5a7cc9d7988c56789b0fdc54c9723a0ef58f345506131e417e12ad8b21a50539 | Python | 5,857 | 162 | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision.models as models
from collections import namedtuple
class SSIMLoss(torch.nn.Module):
def __init__(self):
super(SSIMLoss, self).__init__()
self.register_buffer("kernel", self._cal_gaussian_kernel(11, 1.... |
e047d773b93ae767bf3d8d8f13db087aa7e49b23f9a7b8fbdad2c264a28f1497 | Python | 5,860 | 160 | '''
JHK
Python script for conducting bootstraping for AGMT trend
'''
import numpy as np
from netCDF4 import Dataset
#==========================================================
# Set main directory
#==========================================================
hdir = '/home/jhkim/model/deep_detection'
#=================... |
1500d2716823d2d96567f1016f5a1cd07a1bd73006167d39840a8b78330b586f | Python | 5,866 | 161 | ''' adapted from https://github.com/all-umass/ManifoldWarping '''
import numpy as np
from scipy.cluster.hierarchy import linkage
import pandas as pd
from sklearn import decomposition, preprocessing
import matplotlib
# matplotlib.use("tkagg")
# from matplotlib import pyplot
from matplotlib.backends.backend_pdf import P... |
69c7db3a0d4b0bdcc03e9c9c37cc36b9872e65f47d8318771477981f7c2b646a | Python | 5,867 | 200 | import functools
import numpy
from cellprofiler_core.constants.measurement import (
C_PATH_NAME,
C_FILE_NAME,
C_URL,
C_OBJECTS_FILE_NAME,
C_OBJECTS_PATH_NAME,
C_OBJECTS_URL,
COLTYPE_VARCHAR,
COLTYPE_FLOAT,
COLTYPE_INTEGER,
)
def header_to_column(field):
"""Convert the field n... |
9d2e0a2084f19548d4c0f3b84ebc1be509c0209dbf048643d8dbcda7d897a6d5 | Python | 5,869 | 152 | import os
import sys
import traceback
from ._reader import Reader
from ..constants.reader import ALL_READERS, builtin_readers, BAD_READERS, AVAILABLE_READERS
import logging
from ..preferences import config_read_typed
LOGGER = logging.getLogger(__name__)
def add_reader(reader_name, check_svn, class_name=None):
... |
4c120e898d3584a96ea2d16b0dfcdf38ac5f2096b86b3ad735e2381a0dee7614 | Python | 5,874 | 54 | from main import run
import sys
import subprocess
import argparse
from itertools import cycle
parser = argparse.ArgumentParser()
parser.add_argument('--cl_mode', type=str,
default='domain',
help='The CL paradigm (domain or class).',
choices=['domain', 'class'... |
0abfc964169847344fb71632fda0597e8b51f1182d756fe4d5b191ca1a4edcb9 | Python | 5,875 | 160 | '''
JHK
Python script for calculating internal variability range of AGMT trend
'''
import numpy as np
from netCDF4 import Dataset
#==========================================================
# Set main directory
#==========================================================
hdir = '/home/jhkim/model/deep_detection'
#===... |
35b01d553a07001c15e51bd3275616dfaed54d603b15fe610d536b1b2de9df64 | Python | 5,876 | 153 | #!/usr/bin/env python
import sys
from rdkit import Chem
from rdkit.Chem import Descriptors, Crippen, Lipinski
from rdkit.Chem import PandasTools
import pandas as pd
from sklearn.linear_model import LinearRegression
from collections import namedtuple
class ESOLCalculator:
def __init__(self):
self.aromatic... |
2891c8ca76f0296be04b9d060f434a1a62557842e61cd8674e255199270f040b | Python | 5,880 | 201 | #!/usr/bin/env python
import os
import subprocess as sp
import h5py
import numpy as np
import pdb2sql
from deeprank.tools import sparse
def visualize3Ddata(hdf5=None, mol_name=None, out=None):
"""This function can be used to generate cube files for the visualization
of the mapped data in VMD.
Usage
... |
b45375c200104cd12aab3b2c900e9b6cce913adc3beab608fc39f2258da32599 | Python | 5,882 | 140 | from collections import namedtuple
from typing import Any, Tuple
import os.path as osp
import struct
import warnings
import numpy as np
import numpy.typing as npt
import six
from ptsa.data.readers import BaseRawReader
from .params import ParamsReader
class BinaryRawReader(BaseRawReader):
def __init__(self, **k... |
3197996d00d05f253e6baee55d3997373580397710eb35737ae0636e1b95bfca | Python | 5,883 | 207 | # -*- coding: utf-8 -*-
#
# Early stopping"""
# pylint: disable= no-member, arguments-differ, invalid-name
import datetime
import torch
import copy
__all__ = ['EarlyStopping']
# pylint: disable=C0103
class EarlyStopping(object):
"""Early stop tracker
Save model checkpoint when observing a performance improveme... |
0471aa92d0e9e5ac34a296a8455289bff96acd118a0cd18fded7c9df96a28bc2 | Python | 5,884 | 54 | from main import run
import sys
import subprocess
import argparse
from itertools import cycle
parser = argparse.ArgumentParser()
parser.add_argument('--cl_mode', type=str,
default='domain',
help='The CL paradigm (domain or class).',
choices=['domain', 'class'... |
906358dd7ed08e5469e2254a076b27d81aa5e387c443cffc857be95c2cf56a0a | Python | 5,888 | 111 | from torch.utils.data import Dataset
class WrapperDataset(Dataset):
def __init__(self, dataloader_a, dataloader_b, device, dataset_len_to_use=None):
self.dataloader_a = dataloader_a
self.dataloader_b = dataloader_b
self.dataloader_a_iter = iter(self.dataloader_a)
self.dataloader_b_... |
18215630c21861bc35b65fde4134ce25bd12d7790dde09836e59f5640f6fc2ff | Python | 5,913 | 145 |
from pathlib import Path
from datetime import datetime
import torch
from pytorch_lightning.trainer import Trainer
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
import numpy as np
import torchio as tio
from breaststudies.data import BreastDataModule, BreastDataModuleLR, BreastDataModule2D... |
708e583f626f8307230fde32ffd4a4842040a7ec32953353ebce47bbb5341bb0 | Python | 5,914 | 99 | """Model class template
This module provides a template for users to implement custom models.
You can specify '--model template' to use this model.
The class name should be consistent with both the filename and its model option.
The filename should be <model>_dataset.py
The class name should be <Model>Dataset.py
It im... |
6e84e083e516507a25eca404ea84117cf1c6cdd43302ce5a93d306adc8893c78 | Python | 5,915 | 146 | import torch
from torch import nn
from functools import partial
from timm.models import register_model
from braincog.base.node.node import *
from braincog.base.encoder.encoder import *
from braincog.model_zoo.vgg_snn import *
from braincog.model_zoo.base_module import BaseModule, BaseConvModule
from braincog.datasets i... |
3937536dce3cfff5bf3da89e8045b1cfaecf29f32b64fc376637bb44dfe7c5f6 | Python | 5,917 | 192 | # pyunicorn documentation build configuration file, created by
# sphinx-quickstart on Thu Feb 23 19:15:07 2017.
#
# 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 configuration values ... |
d97ba0296b066846371e73856cba0b68eb1603f2c54443670431b0a45747c8ab | Python | 5,918 | 152 | #!/usr/bin/env python2
# written by Jin Lee, 2016
import os, sys
import json
import subprocess
import collections
import argparse
import xlwt
parser = argparse.ArgumentParser(prog='ENCODE_summary.json parser for ENCODE QC import', \
description='Recursively find ENCODE_summary.jso... |
5b5cbaa4e459d4a0b3d6d2ab0743fa92920f0f0308acac75a46c58d439adfd3e | Python | 5,922 | 121 | from .modelBase import ModelBase
import monai.networks.nets.dynunet as dynunet
def get_kernels_strides(sizes, spacings):
"""
More info: https://github.com/Project-MONAI/tutorials/blob/main/modules/dynunet_pipeline/create_network.py#L19
When refering this method for other tasks, please ensure that the pat... |
a2006980bcc7135afbd0c3a03e862716570a3d49ff4fb1d353fa3b4a7bc9359b | Python | 5,926 | 167 | """
Created Aug 28 2019
@author: Nikolai M Chapochnikov
This file generates the following results that are then for plotting the
model behavior on the ORN dataset:
NNC-Y_act-all.hdf
NNC-Z_act-all.hdf
NNC-W_act-all.hdf
The following takes a while, since there are many repetitions,
in the scale of tens of mins
W_NNC-4.... |
f12b1bc7e3d1a34e1a5d61b943b82c04226ccb2930af8cbf4d931288e283587c | Python | 5,926 | 169 | #!/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
from matplotlib import pyplot
import os
import mne
import pandas as pd
import pickle
import matplotlib
# Configure the matplotlib figure style
FONT = 'Helvetica Ne... |
dabe2595545a151f3d93dc3d2902b1a5b9315dae0458ac97206a2007637a948d | Python | 5,935 | 189 | #!usr/bin/env python
# -*- coding: utf-8 -*-
import logging
import os
import argparse
import ast
from typing import Optional
import yaml
import click
from deprecated import deprecated
from GANDLF.entrypoints import append_copyright_to_help
from GANDLF.utils import writeTrainingCSV
from GANDLF.cli import copyrightMess... |
a44f860e101947cebd76d6a1ff77796af387341dcb073af8e049c1bbc3b41ce7 | Python | 5,941 | 173 | import PyDSTool
import numpy as np
import pickle
import matplotlib.pyplot as plt
from matplotlib.ticker import FormatStrFormatter,ScalarFormatter
import matplotlib as mpl
from matplotlib.lines import Line2D
'''
This script runs the ODE model for different membrane potentials and ADP concentrations, and plots the
ATP s... |
8678b06e4a0221b2656a7358a469bd05cdd59021472a3b1d0ac0d9721f01eec9 | Python | 5,945 | 118 | """ Distribution-Balanced Loss
Paper: `Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets`
- Tong Wu, Qingqiu Huang, Ziwei Liu, Yu Wang, Dahua Lin, ECCV 2020 - https://arxiv.org/abs/2007.09654
Implemented from the paper formulation, numerically matching the DB configuration of the o... |
8c7a71227c57fed63cc21f3bde877d8a8e7150c42ff570622106491addadfe08 | Python | 5,948 | 158 | """
File name: dataset.py
Author: Esra Zihni
Date created: 21.05.2018
This file contains the ClinicalDataset class object that is used for working
with a given dataset.
"""
import pickle
import numpy as np
import pandas as pd
from sklearn import preprocessing
from sklearn.model_selection import train_test_split
fr... |
e93606668c13f6f1e36a3c6f44dfeab24f415ba9c73896858455cd289cb19b93 | Python | 5,948 | 162 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Oct 5 15:58:38 2021
@author: filtsem
This script reads accuracies from Eelbrain output files, takes the average overall all brain sources after smoothing, combined them in pd sturcture and writes to a csv file
"""
from pathlib import Path
import nump... |
5c3e44c2d7d0c1e986152f266a76b32631167eff22b827c7317b347f87245d16 | Python | 5,952 | 188 | import logging
import warnings
from typing import List, Sequence
import pytorch_lightning as pl
from pytorch_lightning.loggers.base import LightningLoggerBase
import rich.syntax
import rich.tree
from omegaconf import DictConfig, OmegaConf
from pytorch_lightning.utilities import rank_zero_only
def get_logger(name=__na... |
34fd356cdd02b9a258c3a50b382afb1d47978730a10e8f0480571e8832aed20a | Python | 5,956 | 152 | import os
from tempfile import mkdtemp, mkstemp
from shutil import rmtree
import h5py
import numpy
import torch.optim as optim
from nose.tools import ok_, eq_
from deeprank.models.variant import PdbVariantSelection, VariantClass
from deeprank.generate.DataGenerator import DataGenerator
from deeprank.learn.DataSet imp... |
fd5b63a0cf892b7d9ecb9c3ec355a0b1775e11179edbb66155bc3d272aa0f997 | Python | 5,956 | 172 | """
Module for all Dataset and Generator/Discriminator Classes
"""
import torch
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import torch.nn as nn
from collections import OrderedDict
import torch.nn.functional as F
from torch.utils.data import DataLoader
import torch.optim as optim
import sea... |
56d7b814fcd4e724dc822b7a3a98e40151093ed0a617f374698bc699dbcffbaa | Python | 5,960 | 190 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Magnetic field computations.
"""
import numpy as np
from multiprocessing import Pool
from itertools import repeat
def dipfld_sph(Q, rQ, R, r0):
"""Compute magnetic field of current dipole in a conducting sphere.
Implementation of the Sarvas formula.
... |
600bd3071c49ec04aa689dfb2d9684b8fd0c90b81cd5218925888ab403461779 | Python | 5,967 | 162 | """
Optical flow
============
This tutorial offers a short overview of the optical flow routines available in
pysteps and it will cover how to compute and plot the motion field from a
sequence of radar images.
"""
from datetime import datetime
from pprint import pprint
import matplotlib.pyplot as plt
impo... |
16fe7f344cad11a2543c37b0f076d1fbfefa4e8002fdbe6b51932c35c5624310 | Python | 5,969 | 159 | #!/usr/bin/python
# EquiPPIS: E(3) equivariant graph neural network for PPI site prediction
#
# Copyright (C) Bhattacharya Laboratory 2022
#
# EquiPPIS is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, eit... |
43512ab18f21a4817c53c9c8af6a8d9bc72c5e66926ea756dc606a5674f833ea | Python | 5,971 | 181 | """ CBAM (sort-of) Attention
Experimental impl of CBAM: Convolutional Block Attention Module: https://arxiv.org/abs/1807.06521
WARNING: Results with these attention layers have been mixed. They can significantly reduce performance on
some tasks, especially fine-grained it seems. I may end up removing this impl.
Hack... |
40a655b26723daa6984d303e89b5dbec60f5eadc915ee7130181fbf11d45ab91 | Python | 5,976 | 166 | """
Tests for csv2nidm -derivative
The derivative activity's software agent must be typed rdf:type
prov:SoftwareAgent, because Query.GetDerivativesDataForSubject only follows
derivative activities associated with such an agent. Both ways of running
csv2nidm are covered: writing a new file (-out) and adding to an exist... |
69d149e91dceb8c234b9ff4e4208a3aa3bdfd8b022097f5a17dd46b57bfa34b3 | Python | 5,976 | 155 | import json
from scipy.stats import f_oneway, ttest_rel
import matplotlib.pyplot as plt
import numpy as np
from statistics import mean
def get_anova_p_value(wd_645_1400, wd_1400_2500, wd_2500_645):
anova_result = f_oneway(wd_645_1400, wd_1400_2500, wd_2500_645)
return anova_result[1]
def get_t_values(wd_645... |
907b37751c14e7f1b79b14169dbb995e29be331fb4de50a365c4234d1082c255 | Python | 5,982 | 145 | import numpy as np
import torch
from tests.utils import reset_seed, reset_layers, run_forward_pass
from networks.dfc_layer import DFCLayer
from networks.dfc_network import DFCNetwork
eps = 1e-20
torch.set_default_dtype(torch.float64)
def reset_layer(layer):
layer._weights.data = torch.randn(*layer.weights.shape)... |
8154808552130f34e81408d81ba667760afd18e61560cf68dd8db28ab5353df8 | Python | 5,985 | 190 | import os
import re
import sys
import tempfile
from .hdf5_dict import get_top_level_group
from .hdf5_dict import VERSION
def get_length_from_varchar(x):
"""Retrieve the length of a varchar column from its coltype def"""
m = re.match(r"^varchar\(([0-9]+)\)$", x)
if m is None:
return None
retur... |
f9df6de17b6b0a650cdc77efeb66d4d06f84933c83da66f7cdb9f16207e9d2b6 | Python | 5,991 | 184 | """ Distributed training/validation utils
Hacked together by / Copyright 2020 Ross Wightman
"""
import logging
import os
from typing import Optional
import torch
from torch import distributed as dist
from .model import unwrap_model
_logger = logging.getLogger(__name__)
def reduce_tensor(tensor, n):
rt = tenso... |
44d2bd4b37e02c7cdce39b2f38093a880dff62005d3e8f1c8c600d5c766324bb | Python | 5,994 | 182 | import numpy as np
from traitlets import Enum, Integer, default, Float, Bool, Unicode, List
from mrHARDI.base.application import (mrHARDIConfigurable,
convert_enum,
ChoiceList)
from mrHARDI.base.dwi import Direction, AcquisitionType... |
97b7e3240dab64cabeef658ee468ab80bd246e5a268944b372f4cb1b90c27b50 | Python | 5,995 | 153 | #!/usr/bin/env python3
""" Checkpoint Averaging Script
This script averages all model weights for checkpoints in specified path that match
the specified filter wildcard. All checkpoints must be from the exact same model.
For any hope of decent results, the checkpoints should be from the same or child
(via resumes) tr... |
c37345a3c8a189cc291223726b80ec7a95fa7aed228bb2f354c7d87fd7cfe489 | Python | 6,003 | 147 | import gc
import numpy as np
import torch
import torch.nn as nn
from BaseModel.basemodel import BaseModel
from DCiPatho_config import Config
config = Config()
class ResidualBlock(nn.Module):
def __init__(self, input_dim, hidden_dim):
super(ResidualBlock, self).__init__()
self.linear1 = nn.Linear... |
bc8a12e79da1e5caf9a4e53c8288a2a68df5bcc79257d89f6de6db6bf71ddbea | Python | 6,004 | 155 | import json
from scipy.stats import f_oneway, ttest_rel
import matplotlib.pyplot as plt
import numpy as np
from statistics import mean
def get_anova_p_value(wd_645_1400, wd_1400_2500, wd_2500_645):
anova_result = f_oneway(wd_645_1400, wd_1400_2500, wd_2500_645)
return anova_result[1]
def get_t_values(wd_645... |
a2ee5a73cdaf03a9668bdd9b50199ff20e74fd9e86f93827d7ce1d1ec9645a3d | Python | 6,005 | 217 | from abc import abstractmethod
from traitlets import Float, Integer
from traitlets.config import Bool, Enum, List, Unicode, default
from mrHARDI.base.application import mrHARDIConfigurable
def _format_response_names(responses):
return ["{}_response".format(r) for r in responses]
class SphericalDeconvAlgorithm... |
74e4ae3a710539c0369cf791b94ba7487233eb979aef0fa2bf7553769f04e2c1 | Python | 6,009 | 153 | import os
from typing import Optional
import numpy as np
import openslide
from GANDLF.data.patch_miner.opm.utils import get_patch_size_in_microns, tissue_mask
from skimage.transform import resize
from torch.utils.data.dataset import Dataset
def get_tissue_mask(image: np.ndarray) -> np.ndarray:
"""
This functi... |
156e8c3221201a8164c63c315f19bd7080a5eaf34f0ff94968eb9eb2f935d927 | Python | 6,015 | 168 | # -*- coding: utf-8 -*-
import matplotlib as mpl
from matplotlib.testing.compare import compare_images
from tempfile import NamedTemporaryFile, TemporaryDirectory
import os.path
import pygenometracks.plotTracks
mpl.use('agg')
ROOT = os.path.join(os.path.dirname(os.path.abspath(__file__)),
"test_dat... |
70e06298d6c9be1d98bb9cc98825db8a612ba9e526f1e2d6fefec08c4efe7b10 | Python | 6,022 | 149 | """ Selective Kernel Convolution/Attention
Paper: Selective Kernel Networks (https://arxiv.org/abs/1903.06586)
Hacked together by / Copyright 2020 Ross Wightman
"""
from typing import List, Optional, Tuple, Type, Union
import torch
from torch import nn as nn
from .conv_bn_act import ConvNormAct
from .helpers import... |
3a8f35b2c2f7eb286a3de5854417994d5e472657b080c582a6a617a2b7521d9b | Python | 6,032 | 161 | # # coding=utf-8
# #TODO: this file uselss until CellProfiler/CellProfiler#4684 is resolved
# """omerologin - dialog box to capture login credentials for Omero
# """
# from cellprofiler_core.bioformats import formatreader
# import wx
# from cellprofiler_core.preferences import (
# get_omero_server,
# get_omer... |
a6f777a0fff9651f9e42741eb9a4439c0ccdd2088bee825fd63de9e9cc0d6485 | Python | 6,037 | 161 | # coding=utf-8
# Copyright 2020 The SimCLR Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or... |
6e71a5f02c137cce01d3668925c69827ed4c1633e68f27c7dc02601ec2f9d914 | Python | 6,039 | 220 | from matplotlib import pyplot as plt
import ray
import os
import wntr
import numpy as np
import networkx as nx
import pdb
import os
from DT_for_WDN_leak_localization.generate_data import simulate_WDN
from DT_for_WDN_leak_localization.inference.prior import get_prior
from DT_for_WDN_leak_localization.network import WDN... |
79be7a8c38f9197c480315a80349ce7e1eea1e5662ebbb607acd03f9657afae1 | Python | 6,039 | 130 | #Created by P-NET https://github.com/marakeby/pnet_prostate_paper
#Modified by Yunjie Liu
import sys
from os.path import join, dirname, realpath
current_dir = dirname(realpath(__file__))
sys.path.insert(0, dirname(current_dir))
import os
import imp
import logging
import random
import timeit
import datetime
import numpy... |
f34775eaad77f0b816646f5995f606b92efce957af559f86d25dda64ba50b6ee | Python | 6,044 | 157 | import json
from scipy.stats import f_oneway, ttest_rel
import matplotlib.pyplot as plt
import numpy as np
from statistics import mean
def get_anova_p_value(wd_645_1400, wd_1400_2500, wd_2500_645):
anova_result = f_oneway(wd_645_1400, wd_1400_2500, wd_2500_645)
return anova_result[1]
def get_t_values(wd_645... |
b79d71ed8f83abaa083e33b4fe371280ffae7490d75082a70e658589842cf79c | Python | 6,046 | 193 | """Tests for the CUDA implementation of multi-target."""
# pylint: disable=too-many-positional-arguments,missing-function-docstring
from typing import Any, Callable, Dict, Optional
import numpy as np
import pytest
from hypothesis import given, note, settings, strategies
import xgboost as xgb
from xgboost import buil... |
1d83afaf38cec970becd2237a87b4923c00aa10daab5eb22ce2632227d6c5212 | Python | 6,047 | 231 | import os
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from load_transform_results import (
load_idiff_matrices_results,
load_transform_results_suppl_8,
)
##############################################################################
# C... |
5c6803df9aab0199867cd52cdd77b873fa382df7a82afd0ad80d1f0b44c31433 | Python | 6,064 | 153 | import numpy as np
from scipy.stats import halfnorm
from configuration import default_priors, default_lower_bounds, default_upper_bounds, default_points_of_jump
def sample_scale(alpha=default_priors["scale_alpha"], beta=default_priors["scale_beta"], rng=None):
"""Generates 3 random draws from a beta prior over th... |
d0da25fa5f89a2c2ee07cf3794d4a3823e96ba76a5b9525544fd325e17a13daf | Python | 6,067 | 175 | from enum import Enum
from traitlets import Integer, Float
from traitlets.config import Bool, Instance, default, List
from traitlets.config.loader import ConfigError
from mrHARDI.base.application import (BoundedInt,
DictInstantiatingInstance,
... |
70781529bb316b2f65f05ca2aa5c1e4552d64ef3b7a865422d97e41d89ce8a28 | Python | 6,073 | 184 | import torch
import torch.nn as nn
from einops import rearrange, repeat
from braincog.base.strategy.surrogate import GateGrad
class AutoEncoder(nn.Module):
def __init__(self, step, spike_output=True):
super(AutoEncoder, self).__init__()
self.step = step
self.spike_output = spike_output
... |
793f96f03ea4b522ebab2cc24342b4a26c6e7f7f3b1f27170f5a8a3aab97a411 | Python | 6,076 | 158 | # -*- 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... |
e852a0771f1592876f327335e637f57d0545439b738e12b6815d26db0c4512be | Python | 6,076 | 143 | import cv2
import numpy as np
import matplotlib.pyplot as plt
import torch
from torch.utils.data import TensorDataset, DataLoader
import pandas as pd
import matplotlib.pylab as plt
from matplotlib.collections import LineCollection
from pytorch_grad_cam import GradCAM
from vajiraGAN_original import Pulse2pulseDiscrimi... |
993ff5353e5b8208015906dd3f492ff6fc4ec3c0aaf702d26849dd717fd0804c | Python | 6,078 | 172 | import matplotlib
import matplotlib.backend_bases
import matplotlib.backends.backend_wxagg
import wx
import wx.lib.intctrl
from ..constants.figure import NAV_MODE_ZOOM
from ..constants.figure import NAV_MODE_MEASURE
from ..constants.figure import BMP_MEASURE
from ..constants.figure import NAV_MODE_PAN
from ..constants... |
9a03acd6d1a3157fceea9c984bc452b638062ef87486d0b40feaca0db9b0f0a7 | Python | 6,078 | 169 | """
This file is subject to the terms and conditions defined in
file 'LICENCE', which is part of this source code package.
Author: Leo Guignard (leo.guignard...@AT@...univ-amu.fr)
"""
import json
from sc3D import SpatialOmicArray
from qtpy.QtWidgets import QWidget, QVBoxLayout, QTabWidget, QPushButton
from magicgui im... |
aff3a6f0fe1fd641e824e45eeeafd9a75f97c48a75ce7e418e8c150e45dca057 | Python | 6,080 | 175 | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import os
import warnings
import pickle as pkl
from numbers import Number
import numpy as np
import torch
from apis import single_gpu_test
from datasets import build_dataloader, build_dataset
from models import build_model
from utils import (auto_select... |
d72f30b08af62fc25b0600e7d2ad0fe616182b073bcc337999f504d5cd275188 | Python | 6,080 | 161 | import json
from scipy.stats import f_oneway, ttest_rel
import matplotlib.pyplot as plt
import numpy as np
from statistics import mean
import argparse
from utils import timer
def get_anova_p_value(wd_645_1400, wd_1400_2500, wd_2500_645):
anova_result = f_oneway(wd_645_1400, wd_1400_2500, wd_2500_645)
return an... |
9b8ed3872131791bf32720dd685a3cc6ed3141e830fa86c8669fc8e576ed7299 | Python | 6,082 | 112 | """General-purpose training script for image-to-image translation.
This script works for various models (with option '--model': e.g., pix2pix) and
different datasets (with option '--dataset_mode': e.g., np_array_aligned, ).
You need to specify the dataset ('--dataroot'), experiment name ('--name'), and model ('--model... |
9eedfe791e1c4049193fed4a974e91a0536cf756a141cdc5caa190f47ddc565c | Python | 6,082 | 181 | import abc
import torch
from .event_handling import find_event
from .misc import _handle_unused_kwargs
class AdaptiveStepsizeODESolver(metaclass=abc.ABCMeta):
def __init__(self, dtype, y0, norm, **unused_kwargs):
_handle_unused_kwargs(self, unused_kwargs)
del unused_kwargs
self.y0 = y0
... |
1716d8e8bbbd2e3da471b394d86facb9d0d551b8a3d717373a712804f92703be | Python | 6,095 | 160 | # -*- 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... |
7fb08e03af0333ee3c6ce596978669861b299c8ca4b24d09764e7ff312d8014c | Python | 6,096 | 170 | import torch
import torch.optim as optim
import torch.nn.functional as F
from torch.autograd import Variable
from model import ADDSTCN
import random
import pandas as pd
import numpy as np
import heapq
import copy
import os
import sys
def preparedata(file, target):
"""Reads data from csv file and tran... |
950ceadaca62d5e592480549ff7316f18710cd31f6bca2f1bf2df73494e4c366 | Python | 6,098 | 134 | import tensorflow as tf
import tqdm.auto as tqdm
from .architecture import neurite_classifier
from .data import prepare_dataset
def train_wt_vs_cko(train_image_dir='TrainImages', validation_image_dir='ValidationImages'):
"""This method trains the model to distinguish between wild-type and C-KO images."""
tra... |
ac9dfc91d08b4014d1c79f1fba20e6595f7fa1f2931a3a0656f2a1be81f5e33b | Python | 6,104 | 213 | # -*- 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... |
e6d0ac03127cf2e69f3cf1f3f0d4cfadbc0b7f10852f5e6e885da72771e070fd | Python | 6,116 | 155 | import os
from pathlib import Path
from typing import Optional
import pandas as pd
import torch
from GANDLF.utils import get_unique_timestamp
import lightning.pytorch as pl
from GANDLF.models.lightning_module import GandlfLightningModule
from GANDLF.data.lightning_datamodule import GandlfInferenceDatamodule
def Infe... |
b094037a918c53184c134afd6fbd845ae9c598e82503b20b02edb46080eb7920 | Python | 6,121 | 178 | # -*- 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... |
f57b3580221e7ab1016ea86ea09026fcf2ec7bf2d4023ba9da203f2e1991e53a | Python | 6,132 | 191 | import matplotlib
matplotlib.use('Agg')
import numpy as np
from netCDF4 import Dataset
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
import os
#==========================================================
# Set main directory
#==========================================================
hdir = '... |
269fa588b7e06f15ced297766288b6f7b6690c20c0592cf3e70b4865bf3bc3fb | Python | 6,137 | 179 | """Run simple cell optimisation"""
"""
Copyright (c) 2016, EPFL/Blue Brain Project
This file is part of BluePyOpt <https://github.com/BlueBrain/BluePyOpt>
This library is free software; you can redistribute it and/or modify it under
the terms of the GNU Lesser General Public License version 3.0 as published
by t... |
7a55f0420ef87e585bcbace604c3b928c7a5257a276ab8b4e721e89646888787 | Python | 6,137 | 189 | #!/usr/bin/env python3
import sys
from mrHARDI.base.application import mrHARDIBaseApplication
def cast_unicode(s):
if isinstance(s, bytes):
return s.decode(sys.stdin.encoding, 'replace')
return s
class mrHARDIApplication(mrHARDIBaseApplication):
@classmethod
def launch_instance(cls, argv=N... |
b952ead5e05e2463f2573cb2e59e684289f6ed21842f9f3449f09331c85e10d1 | Python | 6,141 | 183 | import pickle
import sys
import nibabel as nib
import numpy as np
from dipy.segment.mask import crop
from scipy.linalg import qr, lu
from traitlets import Unicode, Any, Dict
from mrHARDI.compute.utils import voxel_to_world, world_to_voxel
from mrHARDI.base.application import (mrHARDIBaseApplication,
... |
625e9a37b74e205b643f88a05c915988f95a9b1ca4aab30b657291fdf42d7a5f | Python | 6,153 | 123 | """
Implements compartmental model of a passive cable. See Neuronal Dynamics
`Chapter 3 Section 2 <http://neuronaldynamics.epfl.ch/online/Ch3.S2.html>`_
"""
# This file is part of the exercise code repository accompanying
# the book: Neuronal Dynamics (see http://neuronaldynamics.epfl.ch)
# located at http://github.c... |
68f53c3c22513caaaaccd3ba85c4c07d1fb4d0cd4b9ec95e3ffc856f8187df7d | Python | 6,156 | 189 | from __future__ import annotations
from pathlib import Path
from click.testing import CliRunner
import pytest
from nidm.experiment.tools.nidm_linreg import linear_regression
def test_simple_model(brain_vol_files: list[str]) -> None:
runner = CliRunner()
with runner.isolated_filesystem():
r = runner.in... |
a1f71029aed55071b6a25249f16cdf660ebd029c788a07eb1c4b8312ced0b9cf | Python | 6,160 | 121 | import tensorflow as tf
import numpy as np
import tensorflow_probability as tfp
from tqdm import tqdm
def KL_annealing(step, reset_pos=10000, split=0.5, lower=0.0, upper=1.0, type='linear'):
# Fu, Hao, et al. "Cyclical annealing schedule: A simple approach to mitigating kl vanishing." arXiv preprint arXiv:1903.10... |
739fcef173fecf7a483a1cd8fdfda227ecdf3ea92f89e4c3fd3d49b181c32a5b | Python | 6,164 | 160 | import os
import shutil
import csv
import sys
# creates CSV with tidy CNN results
def findMax(line):
ind = 2
m = 0
for i in range(2, len(line)):
if(float(line[i]) > m):
ind = i
m = float(line[i])
return [ind, m]
def findMax_class(class_dict):
aa_class_name = ""
max_class_freq = 0 # max
... |
0196928089d3c9c02b4313923d756eccd66242b0f5ca289c5c3eb102086b6dc0 | Python | 6,166 | 146 |
# -*- coding: utf-8 -*-
"""Classes for data augmentation of SMILES.
Adapted from pysmilesutils
"""
from abc import abstractmethod
from random import shuffle
from typing import Any
from typing import Iterable
from typing import List
from typing import Union
import numpy as np
from rdkit import Chem
Mol = Chem.Mol... |
3720319155fcd66aaf57433110844f1f58b53c84580ebccf4003a514c4047b5a | Python | 6,169 | 203 |
import torch
import argparse
import torch.nn as nn
import torch.nn.functional as F
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 tqdm import tqdm
import sys
import numpy... |
991161a798af3a633eb27b74d39fb0744c4179123543c9d9cb378344a810d4b4 | Python | 6,170 | 124 | """ ONNX export script
Export PyTorch models as ONNX graphs.
This export script originally started as an adaptation of code snippets found at
https://pytorch.org/tutorials/advanced/super_resolution_with_onnxruntime.html
The default parameters work with PyTorch 1.6 and ONNX 1.7 and produce an optimal ONNX graph
for h... |
a072d92a178215a53e7fe14f47973ade300ba30dacad47661773e04dc637a1bd | Python | 6,170 | 167 | from os import listdir
from os.path import join, isfile
from scipy import misc
import numpy as np
import random
from ipdb import set_trace as st
from math import ceil
import copy
import time
from PIL import Image
class pet():
def __init__(self):
super(pet, self).__init__()
def name(self):
... |
b39d5cde2e784c57fa26ce7032390b1813b4b8d5290e7a2f3f63c45b529acf9d | Python | 6,171 | 203 |
import torch
import argparse
import torch.nn as nn
import torch.nn.functional as F
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 tqdm import tqdm
import sys
import numpy... |
f0b8615f46447d6b865e9df5c36843e9939305a336a573625c42ca06ac21fd5e | Python | 6,172 | 198 | """Tests related to the `DataIter` interface."""
from typing import Callable, Optional
import numpy as np
from xgboost import testing as tm
from ..compat import import_cudf, import_cupy
from ..core import DataIter, DMatrix, ExtMemQuantileDMatrix, QuantileDMatrix
from .utils import predictor_equal
def run_mixed_sp... |
e0dfead09d19afeef70446751fbf2cde0b2308cb176a8e84e80b431ad5798861 | Python | 6,173 | 155 | import sys
import numpy as np
import torch
import torch.nn as nn
from numpy import prod
from torch.distributions.beta import Beta
import torch.nn.functional as F
sys.path.append("..")
import utils
spike_args = {}
class Net(torch.nn.Module):
def __init__(self, args, inputsize, taskcla, nlab, nhid=... |
3e2ba0daf426783a0a2a11e7c6a00a795ff85f1865c29ddb9a2592fd75bd937e | Python | 6,175 | 197 | import logging
import os
from pathlib import Path
from typing import Optional, Sequence, Tuple, Type, Union
import numpy as np
import pandas as pd
from imctools.io.ometiff.ometiffparser import OmeTiffParser
logger = logging.getLogger(__name__)
def get_metals_from_panel(
panel_csv_file: Optional[Union[str, Path... |
c3fcad3629425728e83f54eb4f9c1d2dc1144c17b16d7438d9a33283ebf78f70 | Python | 6,180 | 152 | """
File name: evaluate_models_performance.py
Author: Esra Zihni
Date created: 21.05.2018
This is the main script to evaluate models performance. 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 the train... |
020c30c9763d770cbf1a0ed44f2ea6ff803473f725ef5d8ca0a1e7adc78058a4 | Python | 6,181 | 164 | import torch
from torch.autograd.functional import vjp
from .dopri5 import Dopri5Solver
from .bosh3 import Bosh3Solver
from .adaptive_heun import AdaptiveHeunSolver
from .fehlberg2 import Fehlberg2
from .fixed_grid import Euler, Midpoint, RK4
from .fixed_adams import AdamsBashforth, AdamsBashforthMoulton
from .dopri8 i... |
93e69998ab7d72ec6a9fa31aa434a512eb83cb0bb225d355733977edd345ab11 | Python | 6,186 | 195 | '''
JHK
Python script for generating ED figure 6.
'''
import matplotlib
matplotlib.use('Agg')
import numpy as np
from netCDF4 import Dataset
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
import os
#==========================================================
# Set main directory
#=============... |
14dc008acd3d33d5cbcdad2ca79e3d98dcea00b8b5781486eaa2ba4359e506c7 | Python | 6,191 | 147 | from pathlib import Path
import pytest
import torch
from timm.utils.checkpoint_saver import CheckpointSaver
# torch < 2.5 (no safe_globals) can't load training checkpoints (floats, argparse.Namespace) with weights_only=True
needs_checkpoint_load = pytest.mark.skipif(
not hasattr(torch.serialization, 'safe_global... |
e2bb889de77af3961ba079ab32c16931359a9f41718d02082090d18f105eae4e | Python | 6,196 | 192 | import os
import pickle
import time
import numpy as np
import torch
from torch.utils.data import Dataset
class Gesture_pre(Dataset):
def __init__(self, train_or_test, transform=None, target_transform=None):
super(Gesture_pre, self).__init__()
roots = '../../Dataset/DVSGesture'
... |
9a91953d1af1cbb0926a08e0716646b811b4d9a7663f97fed19f185ca24e34fe | Python | 6,198 | 156 | #!/usr/bin/env python2
# written by Jin Lee, 2016
import os, sys
import json
import subprocess
import collections
import argparse
parser = argparse.ArgumentParser(prog='ENCODE_summary.json parser for ENCODE accession', \
description='Recursively find ENCODE_summary.json, parse it ... |
06a92834269d23aae292cce8dc2d6755105a22e55eeee85442ee26cbbdd5f0be | Python | 6,200 | 183 | import numpy as np
import pandas as pd
from sklearn.preprocessing import OneHotEncoder, OrdinalEncoder
from ..data.hcp_aging_pheno.load import load_hcp_aging_pheno
from ..data.hcp_ya_pheno.get_data import load_behavioural_data, load_fd_data
def prepare_confound_names(dataset, target):
"""Name of confounds select... |
20fbf0a0181a9e2fc92244a08138b6a7ef8a13987e4b6f3b8ecf63f923676fee | Python | 6,201 | 130 | #!/usr/bin/env python
""" BIDS Terms -> NIDM-Exp Mappings
@author: David Keator <dbkeator@uci.edu>
"""
from . import Constants
# BIDS dataset_description -> NIDM constants mappings
dataset_description = {
"BIDSVersion": Constants.BIDS["BIDSVersion"],
"Name": Constants.NIDM_PROJECT_NAME,
"Procedure": Consta... |
f8d14cfe4a73924041a12701dda4e32a763dfafaf12ac6da7f336a1733092028 | Python | 6,201 | 204 | from torch import nn
from torch.autograd import Function
import torch.nn.functional as F
import torch
"""
Other possible implementations:
https://github.com/KrisKorrel/sparsemax-pytorch/blob/master/sparsemax.py
https://github.com/msobroza/SparsemaxPytorch/blob/master/mnist/sparsemax.py
https://github.com/vene/sparse-... |
94baa327d493792785e15b092d9a8ba561b9ce8f8e772f96203387f64016e8a0 | Python | 6,215 | 177 | import argparse
import os
import warnings
from pathlib import Path
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 options import Options
from utils impo... |
8c87f342f536215b49f653fbefcf4ca07247cca6f52a8321ed60254ac761f672 | Python | 6,221 | 175 | #!/usr/bin/env python3
"""
Tries to match the preprocessing described in "Functional connectome
fingerprinting: identifying individuals using patterns of brain connectivity".
i.e. generates an eroded white matter mask, eroded CSF mask, and calculates
mean time courses in the white matter and CSF. May also calulate the... |
d21fd8a62a3ce278e535c670b28af0e03d7d8bf45b39be4cb13a4ef010cf2863 | Python | 6,223 | 226 | from __future__ import division
from matplotlib.mlab import find
from scipy.stats import *
from scikits import bootstrap
import seaborn as sns
from matplotlib.pylab import *
from numpy import *
import numpy as np
import bz2
set_printoptions(precision=4)
sns.set_context("talk", font_scale=1.4)
sns.set_style("ticks")
... |
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