sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
e4e5c8f78bb480be250845b0168cd7cab0c481882fdae88aa04f4b1911f75c13 | Python | 2,113 | 45 | import os
import ntpath
from . import util, utilBitDepth
def save_images(opt, webpage, visuals, image_path, aspect_ratio=1.0, width=256):
"""Save images to the disk.
Parameters:
opt -- stores all the experiment flags; need to be subclass of BaseOptions
webpage (the HTML cl... |
dfc3f74cfdb3ed478095102c0ba3592383b4eac7946b6bd11fa5a9c02d0e45f3 | Python | 2,114 | 63 | import os
import SimpleITK as sitk
import numpy as np
from torchio.data.image import ScalarImage
from .base import TemplateNormalizeBase
class HistogramMatching(TemplateNormalizeBase):
"""
This class performs histogram matching.
Args:
TemplateNormalizeBase (object): Base class
"""
def _... |
2de62ba4285666cf9fbf1b8b3d44e027323a0328398d146529a0f26265579440 | Python | 2,115 | 60 | import torch
from torch.autograd import Variable
from torch.utils.data import DataLoader
from DCiPatho_config import Config
config = Config()
class Trainer(object):
def __init__(self, model):
self._model = model
self._optimizer = torch.optim.Adam(self._model.parameters(), lr=config.lr,
... |
2b5140c0bcdccf801c6d058f682684c95992652280c4a6f4ce5122c3c299a678 | Python | 2,116 | 60 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
484078d96a28a7a74484b2c2aa551d0a4b3de2151516ef285da3991db6c12815 | Python | 2,119 | 66 | import h5py
import numpy as np
import pandas as pd
import pytest
from ptsa.io import hdf5
@pytest.fixture
def hfilename(tmpdir):
return str(tmpdir.join("test.h5"))
class TestHDF5IO:
def test_maxlen(self):
array = ["a", "bb", "ccc", "dddd"]
assert hdf5.maxlen(array) == 4
array = ["",... |
a3c9a9117d4e987925274ce534a86bb1b017a74677c91138a8047531c023c200 | Python | 2,119 | 58 | """Predictions module for SVAE model
Author: Hikari Sorensen - Vector Engineering Team (hsorense@broadinstitute.org)
Notes:
"""
import pandas as pd
import tensorflow as tf
mse = tf.keras.losses.MeanSquaredError()
"""
# -- predict --
Description: given a trained (supervised) VAE model and (one-hot encoded) inputs X... |
752bb0e915334b132a4b7ea8619c71e9525be6b38c4ead3dffd3ebbb9aaba1cd | Python | 2,123 | 69 | import tempfile
from pathlib import Path
import pytest
from ..convertutils import normalize_condition
from ..redcap2reproschema import process_csv
def test_process_csv():
csv_data = """Form Name,Variable / Field Name,Field Type,Field Label,Field Annotation,"Choices, Calculations, OR Slider Labels"
form1,field1,... |
09fb257ea024d9aab1a65959c598c44eaa93708362b826ac184c6aceab70ef5d | Python | 2,124 | 55 | import torch
class EventRepresentation:
def convert(self, x: torch.Tensor, y: torch.Tensor, pol: torch.Tensor, time: torch.Tensor):
raise NotImplementedError
class VoxelGrid(EventRepresentation):
def __init__(self, channels: int, height: int, width: int, normalize: bool):
self.voxel_grid = t... |
a241ee16b2e56e087024b29c587e5a0a67539b6f82ba84720529fac288dff7d7 | Python | 2,126 | 45 | import pytest
import requests
import shutil
from pathlib import Path
def _download_and_extract_asset(tmp_dir_path: Path, asset_url: str):
asset_file_path = tmp_dir_path / 'asset.tar.gz'
response = requests.get(asset_url, stream=True)
if response.status_code == 200:
with asset_file_path.open(mode='... |
40b709c4135c70b5b1d6ce13fd1acdc45e21ae824279e46ffafc5b22c318bea4 | Python | 2,127 | 46 | # Author: Mingjian He <mh1@stanford.edu>
from somata.oscillator_search import IterativeOscillatorModel as IterOsc
from somata.oscillator_search.helper_functions import innovations_wrapper
from somata import OscillatorModel as Osc
import numpy as np
# Simulate 10-s data with two oscillators, one slow and one alpha freq... |
8e69b072fdae311cb7d9d3aa8f8131fb742f88469c3ff919038fcfce0ed3bce7 | Python | 2,127 | 60 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
a5c7431e3e42df95333631c3c469701a0ca28819f070b7aaaf11912da34cad98 | Python | 2,127 | 58 | # /// script
# requires-python = ">=3.11"
# dependencies = ["openpyxl==3.1.5"]
# ///
"""Independently compare every CSV cell with the workbook using openpyxl."""
import argparse
import csv
import gzip
import hashlib
import struct
from pathlib import Path
from openpyxl import load_workbook
def verify(source: Path, d... |
125d568a4b4e2f782ec29589ef89f7b1bf4e0abe1510ae47357b0e2237cc9ac5 | Python | 2,128 | 59 | """Delimited-text version 1 decoding through datamonger-core."""
from __future__ import annotations
from collections.abc import Mapping
from pathlib import Path
from typing import Any, cast
import numpy.typing as npt
import pandas as pd
from datamonger import _native
from datamonger._decoder_options import delimite... |
ea609232d37ea502d72ca09f04bc357bb45bac4eb08981a09d182f1594d8dbdb | Python | 2,128 | 79 | from scipy.ndimage.filters import gaussian_filter1d
from scipy import stats
df = pd.read_csv(os.path.join(os.getcwd(), 'data', 'unit_table.csv'), low_memory=False)
# %%
areas = ('VISp','VISl','VISrl','VISal','VISpm','VISam','LGd', 'LP', 'HPC')
color_palette= 'seaborn'
key = 'specimen_id'
mice = df[key].unique()
... |
9c7baaae9f30f833fb16a9f19c486aa113c4834698d391f0f8e0838f419af5ec | Python | 2,129 | 44 | from src.models.tabular.widedeep.base import WDBaseModel
from pytorch_widedeep.models import TabPerceiver
class WDTabPerceiverModel(WDBaseModel):
def __init__(self, **kwargs):
super().__init__(**kwargs)
def build_network(self):
self.model = TabPerceiver(
column_idx=self.hparams.c... |
4ffc02acf8aa0050aa74aa3da482fd6434c502911bda96bf16aa5bc78428fdb6 | Python | 2,130 | 85 | """NiMARE: Neuroimaging Meta-Analysis Research Environment."""
import logging
import warnings
import lazy_loader as lazy
import numpy as np
from ._version import get_versions
logging.basicConfig(level=logging.INFO)
# Ask for float64's machine limits before anything can ask for long double's. NumPy caches
# finfo b... |
b930ea2d025a1dec164a1e501b077055594a884a65e7db1eb0b9dc214b96e50f | Python | 2,135 | 62 | from __future__ import absolute_import
import unittest
import numpy as np
from centriole.rankorder import rank_order
class TestRankOrder(unittest.TestCase):
def test_00_zeros(self):
"""Test rank_order on a matrix of all zeros"""
x = np.zeros((5, 5))
output = rank_order(x)[0]
self.a... |
9bf32ba0ac0c865eef304858a80087433f048c69a9b927ebb69f36b899fb8d20 | Python | 2,136 | 99 | #!/usr/bin/env python2
import sys,os
sys.path.append('/home/xzhou/subtleKnife/script/genescript')
import parseUcscgenestruct
if len(sys.argv)!=3:
print '<ucsc gene file> <tkname>'
sys.exit()
ucsc,tkname=sys.argv[1:]
symbol={}
desc={}
i=0
if os.path.exists('refLink.txt'):
'''
0 symbol
1 desc
2 name
3 name
'... |
f4136a95e63b5ca88823553a0ce7ed3dc714a82ac440c7f3b4fbbe71fed4dcbc | Python | 2,136 | 64 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
0fb9017712256e55b4eb4dc8abd953e50bbc0368d67c83040c650fd4f7f56d8e | Python | 2,138 | 41 | ##################################################################################
# Date created : 10/21/2022
# Date modified: 10/21/2022
# Purpose : Generate intermediate features from sequences and structures
##################################################################################
import optparse... |
36418dd44e2b23b4b7208e6c114eeb4b97e8f0b351ba2cf808b36e0e8c912e7d | Python | 2,138 | 60 | import nibabel as nib
import numpy as np
from traitlets import Bool, Dict
from mrHARDI.base.application import (mrHARDIBaseApplication,
output_prefix_argument,
required_file)
from mrHARDI.compute.utils import validate_affine
_aliases = {
... |
5de4910070eeecaf1798eadbaf71b647feddc85395ac50820f512ca3b5633fc3 | Python | 2,138 | 49 | from torch.nn import init
def init_weights(net, init_type='normal', init_gain=0.02):
'''
Initialize network weights.
Parameters:
net (network) -- network to be initialized
init_type (str) -- the name of an initialization method: normal | xavier | kaiming | orthogonal
init_... |
71ec30b79de05569244408873026102ec7f4d849774c960724b5a717911da5aa | Python | 2,139 | 72 | import numpy as np
def coincident_trues(mask1, mask2, max_shift):
"""
Given two n-dimensional masks returns an (n-1)-dimensional array with the number of coincident Trues arg apart on
axis 0. Used to calculate distances between Spike Trains
Parameters
----------
mask1: array_like
mask2: a... |
a18ce8774d70485b79d5e9183801d22fedb17615e038aa837608d5b7b813ac23 | Python | 2,139 | 56 |
import pandas as pd
import numpy as np
from sklearn.model_selection import KFold
kf = KFold(n_splits=5)
df = pd.read_csv('split.txt')
print(df.describe())
TRAIN_LEN=65
VAL_LEN = 6
TEST_LEN = 23
print(df['fold_1'])
print(df['CASES'])
fold_1 = df['fold_1']
train_val_indices = [ i for i, f in enumerate(df['fold_1']) if... |
6a859fe1318d02691bd40a7317b7eb6b904e8535401d31b6097b18ca2dbeda85 | Python | 2,142 | 67 | from traitlets import Bool, Integer, List, Float, default
from mrHARDI.base.application import mrHARDIConfigurable, BoundedInt
_aliases = dict(
seed="N4BiasCorrectionConfiguration.seed"
)
_flags = {
"rescale": (
{"N4BiasCorrectionConfiguration": {"rescale": False}},
"Rescale images to initia... |
59e0dd2f32a80def0970ead9d677c72481e49e211a8940acd2cdf28267dbd424 | Python | 2,146 | 76 | import os
from itertools import product
import numpy as np
import pandas as pd
import pkg_resources
def load_subject_list(dataset):
path = os.path.join("..", "etspredict", "data", f"{dataset}_subjects.txt")
stream = pkg_resources.resource_stream(__name__, path)
return list(np.loadtxt(stream, dtype=str)... |
66c848feecf9ddd8a219744aaade37fe5f78bb642f53bc83fbb375e5603422f7 | Python | 2,146 | 92 | import os
from . import FASTQ_File
class Library(object):
def __init__(self, name, id=0):
from . import Database as db
self._fastq_files = []
self._name = str(name)
self._metadata = {}
if id == 0:
db.add_library(self)
else:
self._id = id
... |
bd2169641a79f2fb9d112bb20db142b1b765a014d1348c83cace330c04de6f37 | Python | 2,149 | 63 | import os
import subprocess
from os.path import join as pjoin
from tqdm import tqdm
#%%
ncpu = input('Cpu num:')
# input path includes all subject folds
prj_dir = 'PATHtoDataset'
input_path = pjoin(prj_dir, 'derivatives/fmriprep')
# flags for selection
# set subjects, sessions, files that waiting for ci... |
47999d17ad56fcb7935432a45df468078cefcf787f4d7b4da9ee771104dfe960 | Python | 2,150 | 76 | from __future__ import annotations
from typing import TYPE_CHECKING, Sequence
import traits.api
from ptsa.filt import buttfilt
from ptsa.data.common import get_axis_index
from ptsa.data.filters import BaseFilter
if TYPE_CHECKING:
from ptsa.data.timeseries import TimeSeries
__all__ = ['ButterworthFilter']
cla... |
713e5a634b75c9cb5862d8467b11c691fd848a2dc37eaadaa20ba485f5164507 | Python | 2,150 | 56 | """
Move sliding window across images, get expression values in each window, expression values are arcsinh normalized
Author: Candace Liu
Date: 4/11/21
"""
import os
import numpy as np
from PIL import Image
import scipy.ndimage as ndimage
import pandas as pd
points = list(range(1,13))
step_size = 3
window_size = 6
m... |
91ace16a11e78cc4842804ec3ec0b6b5cc98bd54d957c07f6fb9535b4267df8e | Python | 2,152 | 61 | import numpy as np
import torch
import torchvision
class ClassifierOutputTarget:
def __init__(self, category):
self.category = category
def __call__(self, model_output):
if len(model_output.shape) == 1:
return model_output[self.category]
return model_output[:, self.category]... |
056555aa209f3add7bf4194692fd755a1b585462465f8a44d89584d0b25db529 | Python | 2,156 | 55 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
6dbfad421f06f72b558e15349f9cab7bd1e2da6393268c96cbe8b9c0302caca3 | Python | 2,156 | 68 | """ PyTorch Mixed Convolution
Paper: MixConv: Mixed Depthwise Convolutional Kernels (https://arxiv.org/abs/1907.09595)
Hacked together by / Copyright 2020 Ross Wightman
"""
from typing import List, Union
import torch
from torch import nn as nn
from .conv2d_same import create_conv2d_pad
def _split_channels(num_cha... |
d03409bffc9a8e27c21b0645b1639cf581862212d3ff3ae3d57153b727fc3a1c | Python | 2,156 | 96 | #!/usr/bin/env python2
import sys,os
sys.path.append('/home/xzhou/subtleKnife/script/genescript')
import parseUcscgenestruct
if len(sys.argv)!=3:
print '<ensGene.txt file> <tkname> knownToEnsembl.txt and kgXref.txt must be under current dir'
sys.exit()
aa={}
with open('knownToEnsembl.txt') as fin:
for line in fi... |
4fc9ead46c551c6cef648a94d3faadd447a8fb16f4231e266393e669ab900e23 | Python | 2,158 | 43 | """Transforms for classification targets."""
import torch
class MultiLabelTarget:
"""Encode a multi-label target as a float32 multi-hot tensor of length num_classes.
By default the target is a sequence of positive class indices: an empty sequence
means no positive labels, repeats are allowed, and negativ... |
f2247d4b9f2420c046207cde1acf6aba3d1c7f527be86d0f86af12d236dbce26 | Python | 2,158 | 71 | """
Create an RGB image with color-coded labels overlaid on a grayscale image.
"""
from cellprofiler_core.module import ImageProcessing
from cellprofiler_core.setting.subscriber import LabelSubscriber
from cellprofiler_core.setting.text import Float
from cellprofiler_library.modules import overlayobjects
from cellprof... |
90991c78308926d224986de932367ffddd5480d660e06798dea98423687b7557 | Python | 2,161 | 66 | ''' adapted from: https://github.com/letiantian/kmedoids '''
import numpy as np
import random
def kMedoids(D, k, tmax=100):
# determine dimensions of distance matrix D
m, n = D.shape
if k > n:
raise Exception('too many medoids')
# find a set of valid initial cluster medoid indices since we
... |
6b5c95e36e380463b9829e0eb8020a254660476d54d4e3dda2f2799c7d6e52bb | Python | 2,162 | 70 | import logging
import yaml
from pathlib import Path
from importlib import resources
import tempfile
from GANDLF.utils import get_unique_timestamp
import sys
def _create_tmp_log_file():
tmp_dir = Path(Path.home())
log_dir = Path.joinpath(tmp_dir, ".gandlf")
log_dir.mkdir(parents=True, exist_ok=True)
lo... |
9b9560d8a6d9012e1d0e65d350415511415e04c66a317591093476ebf6d7d42b | Python | 2,171 | 60 | import numpy
from numpy.typing import NDArray
import skimage.segmentation
from typing import Annotated, Tuple, Union, List, Any
from pydantic import Field, validate_call, ConfigDict, BaseModel
from cellprofiler_library.types import ImageGrayscale
from cellprofiler_library.opts.measureimageskeleton import TemplateMeasur... |
c7e2a186e90569aac87bd4685febcb902a3611e17f23c9cf70c6f57ced35e4bd | Python | 2,172 | 72 | # -*- coding: utf-8 -*-
import os
import numpy as np
import pytest
from numpy.testing import assert_array_almost_equal
import pysteps
from pysteps import nowcasts
from pysteps.cascade.bandpass_filters import filter_gaussian
from pysteps.cascade.bandpass_filters import filter_uniform
from pysteps.cascade.decompositio... |
17e3fe0bf6df05b23f2e86dc5cb655527d12a993877e87bd95e7ef75669d51b3 | Python | 2,173 | 78 | """ CUDA / AMP utils
Hacked together by / Copyright 2020 Ross Wightman
"""
import torch
try:
from apex import amp
has_apex = True
except ImportError:
amp = None
has_apex = False
from .clip_grad import dispatch_clip_grad
class ApexScaler:
state_dict_key = "amp"
def __call__(
sel... |
690142cf64100bea69f18dde20658151048deea23a1387e023c61db78c0e2a31 | Python | 2,177 | 74 | #!/usr/bin/env python3
import os
import pandas as pd
def configure_output_name(target, sampling_strat, sc_free):
if target in ["sex", "Gender"]:
name = f"sex_predictions_{sampling_strat}"
elif target in ["age", "Age_in_Yrs"]:
name = f"age_predictions_{sampling_strat}"
else:
name ... |
26c874bb19254e93f8b48b08bedbc78acbd7ef533e443e698b75868b94fdbf29 | Python | 2,179 | 57 | from cellprofiler_core.utilities.zmq.communicable._communicable import Communicable
from cellprofiler_core.utilities.zmq.communicable.reply._reply import Reply
class Request(Communicable):
"""A class for making requests and receiving replies across a zmq REQ
socket. When communicated through a socket, the cl... |
850ea9635d7dc58498df550a8219c8dd02b898e8234c23b9996a9cd2732eddf3 | Python | 2,179 | 59 | import torch.nn as nn
class IncDropout(nn.Module):
def __init__(
self,
input_channels: int,
output_channels: int,
Conv: nn.Module = nn.Conv2d,
Dropout: nn.Module = nn.Dropout2d,
InstanceNorm: nn.Module = nn.InstanceNorm2d,
dropout_p: float = 0.3,
lea... |
d186f5e656901a36d7ff0581ef777aab8e611bc1152a5f2aa38c07c7e3971442 | Python | 2,179 | 73 | import numpy as np
import torch
import torch.nn as nn
from tests.utils import reset_seed, reset_layers, run_forward_pass
from networks.dfc_network_utils import get_layer_sparsity, sparsifier
torch.set_default_dtype(torch.float64)
def test_get_layer_sparsity():
# test that layer sparsity is 0 at the start
ass... |
a67f298ea3825a5b4abca6581a4561256188fad1e22fe4864301177c30dc806e | Python | 2,180 | 58 | from __future__ import annotations
import copy
import json
from pathlib import Path
from typing import Any
import pytest
from test_dm_index import dm_index, manifest_template
from datamonger import Registry, _api, data_info, list_data
from datamonger.errors import UnsupportedRegistryError
CASES = json.loads(
(P... |
64515f02b80d93f36070df916e33ee01f0f272a99eaa9720975f044e0a6f43a0 | Python | 2,183 | 60 | #!/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
... |
6eaf1ef46e506ede66c5d415870a9abe43700359bb4e5c6b92df26bc6809e3b7 | Python | 2,183 | 76 | import numpy as np
import scipy.sparse as sp
import numpy_groupies as npg
def perm_adj(adj, perm):
"""Permute an adjacency matrix given a permutation. The permutation must
contain all existing nodes in an arbitrary order and can contain fake
nodes."""
n = perm.shape[0]
sorted_perm = np.argsort(pe... |
d3321688c9be79402097fc7a8de42da573c843cbddb732330ec460974971d6cd | Python | 2,190 | 83 | '''
Based on gen_gerber_and_drill_files_board.py in kicad/demos directory.
'''
import sys
from pcbnew import *
filename=sys.argv[1]
board = LoadBoard(filename)
plotDir = "plot/"
pctl = PLOT_CONTROLLER(board)
popt = pctl.GetPlotOptions()
popt.SetOutputDirectory(plotDir)
# Set some important plot options:
pop... |
9c2bd832f38ddc9501abe5258632a4e4cfedbcf405a1d9458f1689a1b253cf7d | Python | 2,191 | 49 | # -*- coding: utf-8 -*-
import torch
from torch.autograd import Function
from numpy import prod
import utils
class HookFunction(Function):
@staticmethod
def forward(ctx, input, labels, y, fixed_fb_weights, input_, train_mode):
if train_mode in ["DFA", "sDFA", "DRTP", "BRP"]:
ctx... |
a1368617c73b1d60f59b688ade7e100c11fb00e6392b0dbd4182d181b4ad93fb | Python | 2,191 | 76 | # -*- coding: utf-8 -*-
import os
import pytest
import pysteps
from pysteps.tests.helpers import smart_assert
pytest.importorskip("PIL")
root_path = pysteps.rcparams.data_sources["mch"]["root_path"]
filename = os.path.join(root_path, "20170131", "AQC170310945F_00005.801.gif")
precip, _, metadata = pysteps.io.impor... |
01de29b9858d323fedbda453ddb331acaaa5ab98d2c58dcd5ee69761f209dafe | Python | 2,200 | 65 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# http://www.sphinx-doc.org/en/master/config
# -- Path setup --------------------------------------------------------------
# If extensions (or module... |
3a2a51a5069d6046af2390090dbabe376ef42bf10366503f8d2a672087541895 | Python | 2,200 | 84 | # Basic Habituation state where hole 2 and 4 illuminated and poke will leads to reward and non illuminated hole poke does nothing
from pyControl.utility import *
import hardware_definition as hw
import random
states = ['choice',
'reward']
events = ['poke_1',
'poke_2',
'p... |
f8a54fba80cac2650f2eab1acca7f34731e760506cef49c2267bd2735e0a61bf | Python | 2,200 | 103 | import numpy
import numpy.testing
import pytest
import cellprofiler_core.image
import cellprofiler_core.measurement
import cellprofiler.modules.shrinktoobjectcenters
import cellprofiler_core.object
instance = cellprofiler.modules.shrinktoobjectcenters.ShrinkToObjectCenters()
@pytest.fixture(scope="module")
def imag... |
13aa862c777d8daec2c89f1d018335b4c3f49a6e436fc63c233393748e78f9e6 | Python | 2,202 | 58 | """ JIT scripting/tracing utils
Hacked together by / Copyright 2020 Ross Wightman
"""
import os
import torch
def set_jit_legacy():
""" Set JIT executor to legacy w/ support for op fusion
This is hopefully a temporary need in 1.5/1.5.1/1.6 to restore performance due to changes
in the JIT executor. These ... |
31735509e455a005c58cfc005ff92f02fd223b137644bb6a77b9f28f2ebf44c1 | Python | 2,204 | 132 | class TestWorkspace:
def test_refresh(self):
pass
def test_get_windows_used(self):
pass
def test_get_pipeline(self):
pass
def test_get_image_set(self):
pass
def test_set_image_set_for_testing_only(self):
pass
def test_get_image_set_list(self):
... |
741b69cfaf43f00ca62cc264c1ef3c5a0f3e79392a2c9a228e14470908d38f75 | Python | 2,205 | 73 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Nov 30 14:24:44 2017
@author: Nikolai M Chapochnikov
"""
file_L = 'data/Berck_2016/elife-14859-supp1-v2_no_blanks.xlsx'
file_R = 'data/Berck_2016/elife-14859-supp2-v2_no_blanks.xlsx'
# this is some information from the excel sheet
# not sure if it is ... |
4c04f36609f2b7f176c97685aef14e690ef558c76c244c4ec1f11ab868b45e95 | Python | 2,207 | 84 | """
Merge content of multiple hdf5 files.
Usage: {0} t01.hdf5 t02.hdf5 out.hdf5
Author: {1}
"""
import sys
import h5py
import numpy as np
__author__ = 'CunliangGeng'
USAGE = __doc__.format(sys.argv[0], __author__)
def check_input(args):
if len(args) <= 3:
sys.exit(USAGE)
def merge_hdf5(h5ins, h5out):
... |
e5eabf8fc05981c6eff442df9f4ce11dd7e31c5f79ab8155a7c40c011affaec5 | Python | 2,207 | 59 | import os.path as osp
import unittest
import numpy as np
import pytest
from ptsa.data.readers import BaseEventReader
from ptsa.data.filters.morlet import MorletWaveletFilter
from ptsa.data.readers.tal import TalReader
from ptsa.data.readers import EEGReader
from ptsa.data.filters import MonopolarToBipolarMapper
from t... |
7cb244adda39f0d7f61101bafcb5c4478bca062f9b7d8cf39db847702f2f5bae | Python | 2,209 | 71 | import argparse
import os
import sklearn.model_selection as model_selection
import xlrd
import config
import utils
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--class_num",
default=3,
type=int,
help... |
9434f6853b5c4504f6f40f5ac220bbd07476e13a0b370fbe83c1178c7ebb01e3 | Python | 2,209 | 43 | from monai.networks.nets.resnet import resnet50, resnet34, resnet18
from ptflops import get_model_complexity_info
res503d = resnet50(spatial_dims=3)
res343d = resnet34(spatial_dims=3)
res183d = resnet18(spatial_dims=3)
macs, params = get_model_complexity_info(res503d, (3, 224, 224, 224), as_strings=True,
... |
b802bf64362ad9d8bf3c62b23190435f8fb6b6476d9131e9fbd7da07e9708d66 | Python | 2,210 | 73 | from pynq import PL
from pynq import Overlay
from pynq import allocate
from pynq import MMIO
import numpy as np
import time
from firefly_utils import *
ol = Overlay('accel/sys_wrapper.bit')
input_channels = 32
output_channels = 64
time_step = 4
kernel_size = 3
parallel_channel = 16
width = 16
height = 16
threshold = ... |
255757b68af697a92fa1794025d55c6a009d76b10799baa57473f53455c88617 | Python | 2,216 | 46 | import torch
from asteroid.engine.system import System
from asteroid.losses import PITLossWrapper, pairwise_neg_sisdr
class GeneralSystem(System):
def __init__(
self,
model,
optimizer,
loss_func,
train_loader=None,
val_loader=None,
scheduler=None,
co... |
2ff05c4f464a1ed8169f260fa681fe294e70da1b218f09ecd0f857dc37184b08 | Python | 2,218 | 88 | # -*- coding: utf-8 -*-
#
# ioutil.py
#
"""
Results handling utility functions for model comparison experiments.
"""
import csv
import os
import shutil
from collections import OrderedDict
import numpy as np
import pandas as pd
def load_target_to_ndarray(path_to_file, index_col=0, classification=True):
"""Load ... |
a01f4689ab47c3c0f980ee5692c634c3a0da0be475c8f0bbc854bf0f77f29528 | Python | 2,218 | 70 | # written by Nathan Boley, from https://github.com/nboley/GGR_code
import sys
import gzip
VERBOSE = False
adapters = {
'Illumina': b'AGATCGGAAGAGC',
'Nextera ': b'CTGTCTCTTATA',
'smallRNA': b'TGGAATTCTCGG'
}
def detect_adapters_and_cnts(fname, max_n_lines=1000000):
adapter_cnts = {
'Illumina... |
42364afe4a31f1c30e38e84f4499277b7b60f3a8364cc9b19cfca83163b95598 | Python | 2,219 | 50 | import os
import numpy as np
import pytest
from numpy.testing import assert_allclose, assert_array_equal
from s2cloudless import S2PixelCloudDetector
DATA = np.load(os.path.join(os.path.dirname(__file__), "TestInputs", "input_arrays.npz"))
@pytest.fixture(name="cloud_detector")
def cloud_detector_fixture() -> S2Pi... |
234f6b7faf759c0c30e2e84483b20c358c1cc4c6f3c34af221f10b17c957ab8c | Python | 2,220 | 81 | from typing import Callable, Dict, List, Optional, Union, Tuple, Type
import torch
from torch import nn
try:
# NOTE we wrap torchvision fns to use timm leaf / no trace definitions
from torchvision.models.feature_extraction import create_feature_extractor as _create_feature_extractor
from torchvision.model... |
dc298483d4a48c980e154fa0a6f501eb67b49df4c93ba3c0f9fc518a62d35272 | Python | 2,223 | 73 | # -*- coding: utf-8 -*-
import os
from setuptools import setup, find_packages
here = os.path.abspath(os.path.dirname(__file__))
# To update the package version number, edit deeprank/__version__.py
version = {}
with open(os.path.join(here, 'deeprank', '__version__.py')) as f:
exec(f.read(), version)
with open('R... |
286619d368b9e427aa16a4feb15f4413841e98b0607811e20bb64f2a59edef81 | Python | 2,228 | 58 | # 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... |
9f8300c8d9b685184c01636019d3105aac5286ab3bb3fe32420d81b0bfd6dd6b | Python | 2,230 | 56 | #!/usr/bin/env python
"""Script to auto-generate our API docs.
"""
import os
import sys
pjoin = os.path.join
here = os.path.abspath(os.path.dirname(__file__))
sys.path.append(pjoin(os.path.abspath(here), 'sphinxext'))
from apigen import ApiDocWriter
source = pjoin(here, 'source')
#********************************... |
aa96f41b9be73db07de7ef48f9a70f7baf8bf3f7780f10babdf54133de288fd9 | Python | 2,231 | 64 | import prov.model as pm
from .Core import Core, getUUID
from ..core import Constants
class DerivativeObject(pm.ProvEntity, Core):
"""Class for NIDM-Experimenent DerivativeObject-Level Objects.
Default constructor uses empty graph with namespaces added from NIDM/Scripts/Constants.py.
Additional alternate ... |
59c549433cd1fe720b8cdc30fea8c665f1bcf00d4d874f32e7c31459787f65ec | Python | 2,235 | 69 | #emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
#ex: set sts=4 ts=4 sw=4 et:
### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
#
# See the COPYING file distributed along with the PTSA package for the
# copyright and license terms.
#
### ### ### ### ### ### ### #... |
f941cdf5610a165b861e564500d197484484527394e58a0c15a7fae3fd160abc | Python | 2,243 | 53 | import numpy as np
from matplotlib import pyplot as plt
import pandas as pd
import seaborn as sns
import matplotlib.cm as cm
linewidth = 4
fontsize = 15
font = {'family' : 'monospace',
'weight' : 'bold',
'size' : fontsize }
plt.rc('font', **font) # pass in the font dict as kwargs
Scs = np.arra... |
84462c891127dc461c9e86109851f9d3be3cb55bde8ef557d762654302323a2f | Python | 2,247 | 68 | import os
from tempfile import mkdtemp
from shutil import rmtree
import h5py
from nose.tools import ok_, eq_
from deeprank.features.neighbour_profile import (__compute_feature__, get_pssm_paths,
IC_FEATURE_NAME, WT_FEATURE_NAME, VAR_FEATURE_NAME, PSSM_FEATURE_NAME)
fro... |
f85f9d1d42929692ee5a5455e6e5213118f81102b56f8170c1331543591725f7 | Python | 2,247 | 68 | from typing import Dict
from deeprank.models.residue import Residue
from deeprank.models.secondary_structure import SecondaryStructure
from deeprank.domain.amino_acid import amino_acids, cysteine
def _is_dssp_header(line: str) -> bool:
# RESIDUE AA STRUCTURE BP1 BP2 ACC N-H-->O O-->H-N N-H-->O O--... |
9ca38197d654d0ed736a4316530bb96501a2556cfad34366a283e725057afad4 | Python | 2,254 | 62 | import numpy as np
import pickle
import matplotlib.pyplot as plt
from matplotlib.ticker import FormatStrFormatter,ScalarFormatter
'''
This script generates the average over 10 initial conditions
GCG
8.11.23
'''
seed_number = 10 #number of seeds
nv = 30
npoints = int(300000)#int(1e5) #time points available
arr = np.ze... |
7f29497e18beb6b04cb2d19372f9306034facc1557ae46a86cd236d48b5a8865 | Python | 2,255 | 79 | from warnings import warn
from typing import List, Union, Dict, Callable
from .wrap_torchio import (
mri_artifact,
motion,
affine,
elastic,
swap,
bias,
blur,
noise,
noise_var,
gamma,
flip,
anisotropy,
)
from .rotations import rotate_90, rotate_180
from .rgb_augs import ... |
8201d98ef0633b768afa8c0229db9d7237368fd5cf834997c6010b0a768c1018 | Python | 2,256 | 45 | """Regression test documenting a known bug: RveInfo doesn't fully reset between Run() calls.
dragen/run.py's Run.__init__ only reassigns RveInfo.n_pts_y/n_pts_z *conditionally* (inside
`if box_size_y:` / `if box_size_z:`), while RveInfo.box_size_y/box_size_z themselves are always
reset unconditionally. So a Run() with... |
3ac96fb8062dc0f844f81266df5d5ebda39ce953f791f152d5b903622d22d553 | Python | 2,266 | 51 | """
@author: Johanna Rahm
Research group Heilemann
Institute for Physical and Theoretical Chemistry, Goethe University Frankfurt a.M.
Save binned image results as localization file .csv in DeepSTORM2D format & tif.
"""
import pandas as pd
import tifffile
def merge_random_locs(random_locs):
"""
Convert into... |
5a10fdb4cdb049d182a90821306245f88eeb6e3b17afece5ba9a59ce317459ab | Python | 2,269 | 65 | import numpy as np
def sample_scale(a=1, b=25, rng=None):
"""Generates a single random draw from a beta prior over the
scale of the random walk. The artificial bounds are for comparability with bayesloop.
Parameters:
-----------
a : float, optional, default: 1
The first parameter of the... |
d001eb318a19fa51f983360d96b9d8ad049619e5ed3a614563cf9e2d44ceeb72 | Python | 2,271 | 67 | import os
import numpy as np
import caffe
import cv2
from caffe.proto import caffe_pb2
# config
ROOT = os.path.dirname(__file__)
ARCHITECTURE = os.path.join(ROOT, 'model', 'initModel.prototxt')
WEIGHTS = os.path.join(ROOT, 'model', 'initModel.caffemodel')
IMAGE_MEAN = os.path.join(ROOT, 'model', 'mean_AADB_regressio... |
3cc6231ffa6b04a99ae0b360531980e46cc5edf43a928d3d5eccca6ad4ee941e | Python | 2,274 | 45 | import numpy
from typing import Annotated, Optional, Tuple, Callable, Dict, Union
from pydantic import Field, validate_call, ConfigDict
from cellprofiler_library.opts.convertobjectstoimage import ImageMode
from cellprofiler_library.types import ImageBinary, ImageColor, ImageGrayscale, ObjectLabelSet, ImageAny, ImageInt... |
cd68bda3dcf94b5ddf39839192f96e5cec26ac60856303fd2091d66e14f6c7a1 | Python | 2,277 | 71 | from unittest import TestCase
import numpy as np
import torch
from .gsvessel import GSVESSEL
data = GSVESSEL()
class SVESSELTest(TestCase):
def test_init(self):
self.assertEqual(4040, data.train.num_examples)
self.assertEqual(1010, data.val.num_examples)
self.assertEqual(1010, data.tes... |
6e0b5c5d4567d97ac55ee69543ca885dddadf87edc9109262851ad91263fe13c | Python | 2,279 | 56 | """ Two-way Multi-Label Loss
Paper: `Two-way Multi-Label Loss` - Takumi Kobayashi, CVPR 2023
https://staff.aist.go.jp/takumi.kobayashi/publication/2023/CVPR2023.pdf
Implemented from the paper formulation, numerically matching the official (unlicensed) reference at
https://github.com/tk1980/TwoWayMultiLabelLoss
"""
im... |
a33da0f56551f439d4fd04474f769d65ef52859a55a5e24b7f5d8eda6b870797 | Python | 2,279 | 46 | import torch
import torch.nn as nn
import torch.nn.functional as F
from .layer import GradientLayer, BoundaryGradientLayer
class PINN(nn.Module):
def __init__(self, network, RADIALDIFFUSION, NO_FLUX_BND):
super(PINN, self).__init__()
self.network = network
self.grads = GradientLayer(networ... |
36f3fd28734a34351194b2a1f49d56c576b1f769da04cbd3b44f048d4c1340c2 | Python | 2,280 | 51 | #####################################################################################################################
# Date created : 10/21/2022
# Date modified: 10/21/2022
# Purpose : To generate (full) node feature set from temporary features
##################################################################... |
f8ce0478e4f3c5def8b5ce27e82be0dafdb6841d3c0da987254110de3cbbc8e1 | Python | 2,281 | 67 | #!/usr/bin/env python
# coding: utf-8
"""Code for Figure 3"""
# In[ ]:
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler, RobustScaler, QuantileTransformer
from sklearn.model_selection import train_test_split, KFold
from statistics import mean, stdev
from sklearn.linear_model impo... |
00f6295057d95757ebbc52443257e7168328ee9423807911f5015292a10f0afd | Python | 2,287 | 68 | import logging
import os
import tempfile
import h5py
import cellprofiler_core.measurement
import cellprofiler_core.pipeline
import cellprofiler_core.utilities.core.workspace
import cellprofiler_core.workspace
from cellprofiler_core.utilities.hdf5_dict import FILE_LIST_GROUP, TOP_LEVEL_GROUP_NAME
LOGGER = logging.ge... |
fa291a164c0ccc8ebbfded64e9efb33221766e319bfb2f2155778d94f58aade2 | Python | 2,292 | 82 | from torch.utils.data import DataLoader
from .ImagesFromDataFrame import ImagesFromDataFrame
from GANDLF.utils.write_parse import get_dataframe
from GANDLF.utils import populate_channel_keys_in_params
def get_train_loader(params):
"""
Get the training data loader.
Args:
params (dict): Dictionary... |
436a76d2b2a0e3eadffa7a7f132bc07d829140cc92815dcfdf83f8f2559e4ef1 | Python | 2,293 | 58 | import tensorflow as tf
from io import BytesIO
from zipfile import ZipFile
from sklearn.utils import shuffle
class DataLoader():
def __init__(self, csv_file='data/nyu2_train.csv', DEBUG=False):
self.shape_rgb = (480, 640, 3)
self.shape_depth = (240, 320, 1)
self.read_nyu_data(csv_file, DEB... |
4e6938388de66b399e4f8a89fa9b8e3111c2b8ccb1ebf9e57d4ec325674d760d | Python | 2,293 | 75 | # TODO SEP 08 version
"""A modified image folder class
We modify the official PyTorch image folder (https://github.com/pytorch/vision/blob/master/torchvision/datasets/folder.py)
so that this class can load images from both current directory and its subdirectories.
"""
import torch.utils.data as data
from PIL import ... |
896b6e0b8cbffd1af542970289fe328e9f2e6ae71f2b6ce402dd1ef52ece6f7c | Python | 2,293 | 94 |
from typing import Dict
import torch
import torch.nn as nn
import torch.nn.functional as F
ACTIVATION_LAYERS = {
'ReLU':nn.ReLU,
'LeakyReLU':nn.LeakyReLU,
'PReLU':nn.PReLU,
'RReLU':nn.RReLU,
'ReLU6':nn.ReLU6,
'ELU':nn.ELU,
'Sigmoid':nn.Sigmoid,
'Tanh':nn.Tanh,
}
class Clamp(nn.Mo... |
c5140ddcf8a86cc70134c24b105c5e3e36826c96d7580eaa0265f10cfdcb1a1a | Python | 2,298 | 57 | import os
import numpy as np
from glob import glob
from PIL import Image
import imageio
import time
from tensorflow.keras.callbacks import EarlyStopping, ModelCheckpoint, ReduceLROnPlateau
class U_Net():
def __init__(self):
self.height = 256
self.width = 256
self.channels = 3
... |
f80f998842888a407a1b5efc12acc25414b85d8f9f87af19be403bba1048b2f4 | Python | 2,300 | 58 | import torch
import numpy as np
from argparse import Namespace
from datahandlers.data_utils import generate_task
from networks.net_utils import generate_network
from utils.optimizer_utils import get_optimizers
from utils import math_utils as mutils
from utils import sim_utils
def reset_seed(seed=10):
torch.manual... |
7c7dc2393ca97ac612f2f35f3cba943284e5a89b40442c3093e4c92dfe25c18b | Python | 2,304 | 64 | import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
plt.rcParams.update({'font.size': 12})
def get_shot_res(drp, data):
path = f'../results/chemformer_snn/dropout{str(drp)}/{data}/tables/'
df = pd.read_csv(path + 'avg_res.csv')
df = df[df['cutoff'] == 0][1:]
return list(df['rmse']), ... |
fabb9e97b8d88f2a7f78e2065d08c8fde5d7b20f64d28871884dab0709599f1b | Python | 2,304 | 46 | import os
import shutil
import pytest
from dragen.utilities.InputInfo import RveInfo
REPO_ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..'))
OUTPUT_DATA_DIR = os.path.join(REPO_ROOT, 'OutputData')
@pytest.fixture(autouse=True)
def _cleanup_output_dir():
"""Delete whatever OutputData/<d... |
7095ba60f86d2c97c983ccad27497b70d733f6dfd0a7550153e6f2561f45d330 | Python | 2,308 | 91 | # -*- coding: utf-8 -*-
import numpy as np
import pytest
from numpy.testing import assert_array_almost_equal
from pysteps.postprocessing.ensemblestats import excprob, mean, banddepth
# CREATE DATASETS TO TEST
a = np.arange(9, dtype=float).reshape(3, 3)
b = np.tile(a, (4, 1, 1))
b1 = b.copy()
b1[3] = np.nan
a1 = a.c... |
ff764db3e83213d5e6e2c959a152692fdde9147353d2c8f1d2e398e326d7fc6b | Python | 2,308 | 74 | import os
import timm
import torch
import torch.nn as nn
from mmcv.runner import load_state_dict
def load_checkpoint(args, checkpoint_path: str, model: nn.Module) -> None:
"""
Input
args: args
checkpoint_path: str, path of saved model parameters
model: nn.Module
optimizer: tor... |
d5bbac22ed5d2cbccf0615dd5268db6f408d97d252c8c44cf54c257395e57e6b | Python | 2,309 | 68 | import numpy as np
import matplotlib.pyplot as plt
from ..utils.time import get_dt
def plot_mask(t, mask_spikes, ax, t0, tf, offset, lw, delta, color):
for sw in range(mask_spikes.shape[1]):
t_spikes_ = t[mask_spikes[:, sw]]
t_spikes_ = t_spikes_[(t_spikes_ >= t0) & (t_spikes_ < tf)]
t_s... |
2bdf961cc5075843e229849bbfa26b58ccd66d85a1267e54b3c3ee683d0ac664 | Python | 2,312 | 68 | import numpy as np
import matplotlib.pyplot as plt
from ..utils.time import get_dt
def plot_mask(t, mask_spikes, ax, t0, tf, offset, lw, delta, color):
for sw in range(mask_spikes.shape[1]):
t_spikes_ = t[mask_spikes[:, sw]]
t_spikes_ = t_spikes_[(t_spikes_ >= t0) & (t_spikes_ < tf)]
t_s... |
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