sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
68ed90011d534a282de172832a22b14208b5e7f6f8f59b10b4632e7806acccfc | Python | 7,115 | 238 | import torch
import torch.nn as nn
from torch.hub import load_state_dict_from_url
from torchvision.models import ResNet
def conv3x3(in_planes, out_planes, stride=1):
return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride, padding=1, bias=False)
class SELayer(nn.Module):
def __init__(self, chan... |
52316d871056cc12057df8d9e1400b8c882f71dd8f7eed37f0d4f926deedd08a | Python | 7,119 | 201 | # Inheritaed from open-mmlab/mmclassification
# Modified by Hangyu LIN
import sys
from collections.abc import Iterable
from multiprocessing import Pool
from shutil import get_terminal_size
from .timer import Timer
class ProgressBar:
"""A progress bar which can print the progress."""
def __init__(self, task... |
d3984173f219d348ae272d5f2c10f7e3c35e4a73e34577404ee884d44b388996 | Python | 7,120 | 230 | import numpy
import six
import cellprofiler_core.image
import cellprofiler_core.measurement
from cellprofiler_core.constants.measurement import COLTYPE_FLOAT
from cellprofiler_library.opts.measureimageareaoccupied import MeasurementType, Target
import cellprofiler.modules.measureimageareaoccupied
import cellprofiler... |
e3c93a8966fa2f6cb3524f48212942d4aea11aec45aa056ae1f3c5a7a559a2ac | Python | 7,126 | 199 | # study: .sqlite3
import sys
import os
import time
import subprocess
import sqlite3
import lib2nist
start_time = time.time()
__version__ = "0.1.1"
# class Thing:
# def __getitem__(self, key):
# return getattr(self, key)
# def __setitem__(self, key, value):
# setattr(self, key, value)
#
# S... |
f50b4756669c047bf17b94aa576b3caaef9236466d716b0a3b07e4a3610b8521 | Python | 7,127 | 149 | """
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:
This module provides f... |
bdf482e6fca64aa0272f1d75a01bd982b7b9cb0705f8a62fb32379c1f82490f3 | Python | 7,133 | 180 | import collections
import numpy
import imageio
from ..constants.image import MD_SIZE_S, MD_SIZE_C, MD_SIZE_Z, MD_SIZE_T, MD_SIZE_Y, MD_SIZE_X
from ..preferences import config_read_typed
from ..reader import Reader
SUPPORTED_EXTENSIONS = {'.png', '.bmp', '.jpeg', '.jpg', '.gif'}
# bioformats returns 2 for these, imag... |
061c2339f94fecad6a1352e4031fbefe5489812f62b1116162ce657b4f28889f | Python | 7,139 | 192 | from termios import VMIN
import matplotlib.pyplot as plt
import numpy as np
import os
os.environ['MNE_USE_NUMBA']='false'
import mne
from collections import OrderedDict
import utils
import settings
def plot_conventional_temporal_kernels_by_weight(Wconv, Wout, selected_channels, fs=250):
"""
y axis ... |
3c3850d8583cea23d7605ab37b8b02e9b764537a479b2abafb7e9de03e8a343d | Python | 7,142 | 198 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Thu Apr 26 14:18:33 2018
@author: saskiad
"""
import numpy as np
import scipy.stats as st
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.ticker as mtick
import seaborn as sns
areas = ['VISp', 'VISl', 'VISal', 'VISpm', 'VISam', '... |
0527beb2aa67a620425479fa09fa18dbf8ef311109a1de72e9df6d436ee7403b | Python | 7,145 | 244 | """
pysteps.cascade.bandpass_filters
================================
Bandpass filters for separating different spatial scales from two-dimensional
images in the frequency domain.
The methods in this module implement the following interface::
filter_xxx(shape, n, optional arguments)
where shape is the shape of ... |
2f8a117c915150d76ef6bf92d177e7ca102adb5c13e62868cd10a374e69162bd | Python | 7,149 | 189 | """ Bilinear-Attention-Transform and Non-Local Attention
Paper: `Non-Local Neural Networks With Grouped Bilinear Attentional Transforms`
- https://openaccess.thecvf.com/content_CVPR_2020/html/Chi_Non-Local_Neural_Networks_With_Grouped_Bilinear_Attentional_Transforms_CVPR_2020_paper.html
Adapted from original code:... |
c3b0c0319ad8b60d7e026e23a8d82c37c180ccfbf3d30aba94fcb9825f983485 | Python | 7,158 | 175 | """ Lambda Layer
Paper: `LambdaNetworks: Modeling Long-Range Interactions Without Attention`
- https://arxiv.org/abs/2102.08602
@misc{2102.08602,
Author = {Irwan Bello},
Title = {LambdaNetworks: Modeling Long-Range Interactions Without Attention},
Year = {2021},
}
Status:
This impl is a WIP. Code snippets in the... |
4b4028a37bc711896e9a09e000d28694cf3a7c4dd6d7945e696c666f82ad843f | Python | 7,165 | 194 | from torch.optim.lr_scheduler import (
LambdaLR,
CyclicLR,
ExponentialLR,
StepLR,
ReduceLROnPlateau,
CosineAnnealingWarmRestarts,
CosineAnnealingLR,
)
import math
def cyclical_lr(stepsize, min_lr, max_lr):
# Scaler : we can adapt this if we do not want the triangular LR
scaler = la... |
8ee49876137965a061955759c7b97a2a37598cc4f0003c879aae46980dfac7c9 | Python | 7,165 | 175 | # 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... |
9d83a37d6ed67560661998487e068db00803a542015c942ef983bff3e71e6000 | Python | 7,169 | 220 | # Created by: Deserno, M. et. al., 2023 for https://www.nature.com/articles/s41598-023-38213-7
# Experimental code to visualize tracking results.
import colorsys
import os
import pickle
import random
import cv2
import numpy as np
import pycocotools.mask as mask
from alive_progress import alive_bar
def generate_colo... |
16c6c25914dc280a140c61fd3b04e05b3d7f5de7a3a4d9632fe322d12e2c8bf7 | Python | 7,177 | 224 | #!/usr/bin/env python
from os.path import join, dirname, abspath
import inspect
from mrHARDI.base.application import MagicMonkeyConfigurable
from mrHARDI.main_app import MagicMonkeyApplication
from traitlets import Instance, Undefined, import_item
from collections import defaultdict
here = abspath(dirname(__file__))... |
e95319929a5db06ee1dc5f0ca61f261ccc7db07976af08aefe444810fcb3c891 | Python | 7,179 | 206 | import sentencepiece as spm
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.metrics import classification_report, accuracy_score, multilabel_confusion_matrix, mean_squared_error, r2_score
import tensorflow as tf
import pandas as pd
from glob import glob
import wandb
from w... |
03976d9afb05260c23a0d87a8deb517e8bb818f647849917037df2608c858719 | Python | 7,182 | 182 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Thu Apr 5 13:06:41 2018
@author: saskiad
"""
import numpy as np
import pandas as pd
import os, h5py
import scipy.stats as st
import core
# class event_analysis(object):
# def __init__(self, *args, **kwargs):
# for k,v in kwargs.iteritems():
... |
8169bad273147fc6533adce76eca7910e863a10ea0237456bfe03fc15978b18c | Python | 7,184 | 191 | import numpy as np
import matplotlib.pyplot as plt
import matplotlib.table
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d.art3d import Poly3DCollection
import matplotlib.patches as patches
from IPython import embed
def plotcubus(axis, pos, ext, color):
xs = pos[0]
ys = pos[1]
zs = pos[2... |
d3db85ae7ea8756c884faf3210a61f0e4fb5a8583b975592f20c37869671f3b5 | Python | 7,186 | 256 | """Helpers shared by the pytest suite in scripts/test (test_*.py).
Everything here is plain Python so that expected values in the tests can be
derived independently of bowtie2: references are generated from a fixed
seed, reads are cut from them at known positions, and SAM output is parsed
into records whose fields the... |
0376ad6128f05dcc2e8aeedcceedaa5b7e2c5e3e537e47a3e504cafbc2904d89 | Python | 7,188 | 210 | # -*- coding: utf-8 -*-
"""
molvs.validations
~~~~~~~~~~~~~~~~~
This module contains all the built-in :class:`Validations <molvs.validations.Validation>`.
"""
from __future__ import print_function
from __future__ import unicode_literals
from __future__ import division
import logging
from rdkit import Chem
from .er... |
ed89ec8302f8b5382c9b2b7dfc0b9da5c9358d0015df71984cc5320e83b076a7 | Python | 7,195 | 226 | import nibabel as nib
import numpy as np
from numpy import (concatenate,
ones_like,
ceil,
floor,
array,
dtype as datatype,
r_ as row)
from scipy.io import loadmat
from scipy.io.matlab.mio4 import MatFile4Wr... |
e54cffd1f12ea156ad2a60c3055f77450acd0fa323cf8774d179a4d26809a6b9 | Python | 7,200 | 224 | #!/usr/bin/env python3
"""Extract Gemma4 Vision Encoder weights from a full Gemma4 multimodal model.
Uses safetensors lazy loading to avoid loading the full model into memory.
Converts HF Transformers weight keys to timm format.
Usage:
python convert/convert_gemma4_vit.py \
--source google/gemma-4-4b-it \... |
134a5f1caf806975b448a3398a5ddf6ceaca0612d19fc857985ee7c4fcaa5a0b | Python | 7,206 | 180 | # -*- coding: utf-8 -*-
"""
Created on Thu Feb 8 15:21:16 2018
@author: saskiad
"""
import numpy as np
import pandas as pd
import os, h5py
import scipy.stats as st
import core
class event_analysis(object):
def __init__(self, *args, **kwargs):
for k,v in kwargs.iteritems():
setattr(self, k, ... |
00c3a9cee1d938b9c0f9fdd4fc36c205ad1c866e259e743e9795256868c46d7c | Python | 7,210 | 193 | import argparse
import configparser
import logging
import os
import queue
import threading
import tracemalloc
import flickrapi
import pandas as pd
import tensorflow as tf
# https://github.com/tensorflow/tensorflow/issues/29968
os.environ['OMP_NUM_THREADS'] = '2'
tf.config.threading.set_inter_op_parallelism_threads(2)... |
1f900cb178dc5720bb107329669b381f3d5f932bf6d7d9431625cb596d80d260 | Python | 7,218 | 191 | ##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
## Created by: Hang Zhang
## ECE Department, Rutgers University
## Email: zhang.hang@rutgers.edu
## Copyright (c) 2017
##
## This source code is licensed under the MIT-style license found in the
## LICENSE file in the root directory of this sou... |
ca4464448c806e376a22bbd4195f1653f711a5ce3e96a605a808ebe66e6be0c8 | Python | 7,219 | 247 | """
This file implements a type I and a type II model from
the abstract base class NeuronAbstract.
You can inject step currents and plot the responses,
as well as get firing rates.
Relevant book chapters:
- http://neuronaldynamics.epfl.ch/online/Ch4.S4.html
"""
# This file is part of the exercise code repository a... |
4824fc9a25d11b1b9f0ef6a076b4ab4954df3836d951cee1f48918d1d2c0eb3e | Python | 7,224 | 226 | # pylint: disable=too-many-locals
"""Tests for learning to rank."""
from types import ModuleType
from typing import Any, Optional
import numpy as np
import pytest
import xgboost as xgb
from xgboost import testing as tm
from .data import make_ltr
from .utils import Device
def run_ranking_qid_df(
impl: ModuleTy... |
290ac62dc898832c9856872fb4e1c8cfe0e84b65ffddb3219ef105e7dd3e18a6 | Python | 7,226 | 170 | # -*- 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.... |
57fdaf722b763cdadf5a595108aecdaabde91ad0e0a2177f7931722818619da9 | Python | 7,226 | 186 | import numpy as np
from .crop_zero_planes import CropExternalZeroplanes
from .non_zero_normalize import NonZeroNormalizeOnMaskedRegion
from .threshold_and_clip import threshold_transform, clip_transform
from .normalize_rgb import (
normalize_by_val_transform,
normalize_imagenet_transform,
normalize_standar... |
4ca8b135c3b0a517e246eb140e748b71e499494e210c7e6af2a7b42664a7091b | Python | 7,231 | 213 | import numpy as np
from netCDF4 import Dataset
#===========================================================================
# Function for converting from longitude to X-dimension
#===========================================================================
def lon_to_xdim(lon_st, lon_nd, lon_int=2.5, lon_init=0.0):
... |
369d67b66e4568802a0825543f7fc68f389a07c36929009e683563d86871909f | Python | 7,239 | 209 | import numpy as np
from scipy.linalg import cholesky_banded, solveh_banded
from .utils.linalg import diag_indices, band_matrix, unband_matrix
from .utils.time import get_arg, get_dt
class OUProcess:
"""
Class implementing an Ornstein Uhlenbeck process
Parameters
----------
mu : float
... |
8ef770f142a3c134a33a509446693e1b8ca61104f815ec65c26e8d7e05a1297a | Python | 7,243 | 191 | from operator import indexOf
import os
from typing import Any, Tuple
import numpy as np
import torch
import torch.nn.functional as F
from torchvision.datasets import VisionDataset
from torch.utils.data import Dataset
import data.mapping_utils as mapping_utils
import pandas as pd
import glob
from tabulate import tabulat... |
d2f2b9f38f129d95048e5195ce9df621d85e658189073d995e7a992b047fdc03 | Python | 7,246 | 197 | """Classification training task."""
import logging
from typing import Any, Callable, Dict, Optional, Union
import torch
import torch.nn as nn
from timm.loss import create_classification_loss
from .task import TrainingTask
_logger = logging.getLogger(__name__)
def resolve_classification_loss(
criterion: Op... |
4b97d78a8c34f5cb0c1c59ba01370a9b75e3ded40e485b4e1a88f5e6847a2136 | Python | 7,248 | 229 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on 2022/2
@author: Nikolai M Chapochnikov
This file creates plots to better understand the behavior of the cdf -
the cumulative density function, called
relative cumulative frequency in the paper.
Plots are not saved on the disk and need to be saved by hand
"... |
686274daad6b2709446c46f3c0cdbb64c4f79179b223d0855db0612b6edfa50c | Python | 7,254 | 168 | import numpy as np
def get_im2col_indices(x_shape, field_height, field_width, padding=1, stride=1):
N, C, H, W = x_shape
assert (H + 2 * padding - field_height) % stride == 0
assert (W + 2 * padding - field_height) % stride == 0
out_height = int((H + 2 * padding - field_height) / stride + 1)
out_w... |
a9f4a93170f33883a050faf03ec26ecc118d7ff7ee6176c5f8423db84f2dc305 | Python | 7,258 | 217 | # coding: utf-8
"""
ANVIL nowcast
=============
This example demonstrates how to use ANVIL and the advantages compared to
extrapolation nowcast and S-PROG.
Load the libraries.
"""
from datetime import datetime, timedelta
import warnings
warnings.simplefilter("ignore")
import matplotlib.pyplot as plt
import numpy a... |
798f3e8bb4828641b075fd5b57fc824b5ad1086652eab050aa15ddf6d42dfe06 | Python | 7,261 | 222 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Jun 1 08:19:50 2021
@author: Manuel
Execute from terminal with both of the following arguments:
1. "/path/to/files"
2. "/path/to/output"
"""
import pathlib, os, sys
import numpy as np
from PIL import Image
from PIL.ExifTags import TAGS, GPSTAGS
from ... |
f282c1ec58586ec094980fe710e1f28e179326f782ddd3d67dd04e4160f77613 | Python | 7,267 | 181 | import os
import pytest
from click.testing import CliRunner
from GANDLF.entrypoints.construct_csv import new_way, old_way
from . import CliCase, run_test_case, TmpDire, TmpFile, TmpNoEx
# This function is a place where a real logic is executed.
# For tests, we replace it with mock up, and check if this fu... |
89da8a88a7f8bffea8358da1960d1419e60fc9398f9cc2c4b82504d38f164ac8 | Python | 7,279 | 278 | import os
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
##############################################################################
# Constants
dataset = "hcp"
parcellation = "schaefer200x17"
idiff_path_combined_bins = os.path.join(
"..",
"..",
"..",
... |
9f5f72722663f607bad7abf6a3e7307ccfd9089314e20821cfe56830949b9b78 | Python | 7,279 | 177 | import copy
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
import sys
sys.path.append("..")
from molformer.tr_spe import Embeddings, FeedForward
from molformer.tr_spe import LayerNorm, SublayerConnection, clones, Generator3D
_NUM_RESIDUE_TYPES = 22
_MAX_SEQUENCE_LENGTH ... |
9e71dfc14127c79920e5543c0783ab6ac15b72453bff5a195f297a7ae5647054 | Python | 7,283 | 227 | import numpy as np
import pandas as pd
import statsmodels.api as sm
from etspredict.data import load_struct_connectomes
from etspredict.data.hcp_aging.load import HCPAgingTimeseries
from etspredict.data.hcp_ya.load import HCPTimeseries
from .. import selective_connectomes as sc
def load_timeseries(
dataset, sub... |
5d64ee935b9a048216750fcd1e6f86695849110204f550576a3ec4bed47ac9c5 | Python | 7,286 | 202 | #!/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 os
import mne
import pandas as pd
from mne.stats import (spatio_temporal_cluster_test, f_threshold_mway_rm, f_mway_rm)
from mne impo... |
fdf132c47fb5b88cc88bd8e7d2e08e85749a6c3585ff9f245d715ccd482efeea | Python | 7,296 | 187 | #!/usr/bin/env python3
"""
Runs wb_command -surface-geodesic-rois to make rois on left and right surfaces then combines
them into one dscalar file.
Usage:
ciftify_surface_rois [options] <inputcsv> <radius> <L.surf.gii> <R.surf.gii> <output.dscalar.nii>
Arguments:
<inputcsv> csv to read vertex list ... |
5a740237bb120bbbc8321cbf116cc494bc8702d6a6b8dc74e356e3f5322ed8ce | Python | 7,298 | 155 | """
@author: Johanna Rahm
Research group Heilemann
Institute for Physical and Theoretical Chemistry, Goethe University Frankfurt a.M.
ImageBinner functionalities.
"""
import numpy as np
import pandas as pd
import random
import matplotlib.pyplot as plt
import seaborn as sns
from tqdm.notebook import tqdm
def get_di... |
3ea0a6395fc9bed4d002b0fb9cd70df5b8b266c1e79deef9c43e45f6b3c8df55 | Python | 7,300 | 295 | """Information Retrieval metrics.
Useful Resources:
http://www.cs.utexas.edu/~mooney/ir-course/slides/Evaluation.ppt
http://www.nii.ac.jp/TechReports/05-014E.pdf
http://www.stanford.edu/class/cs276/handouts/EvaluationNew-handout-6-per.pdf
http://hal.archives-ouvertes.fr/docs/00/72/67/60/PDF/07-busa-fekete.pdf
Learning... |
1cf80333d76a04673888d0ce788984c1b0ea90d2771347014ce17c3a1d54cb4e | Python | 7,307 | 240 | # TODO Sep 08 version
"""This module contains simple helper functions """
from __future__ import print_function
import torch
import numpy as np
from PIL import Image
import os
import math
def tensor2im(input_image, imtype=np.uint16):
""""Converts a Tensor array into a numpy image array.
Parameters:
i... |
4900264a0b84ed2edb6c8f089d668d1aaee3115039732e9ddfd39d099e5532c2 | Python | 7,308 | 194 | """Prepare and validate the Rhee2006 dataset from Stanford HIVDB."""
from __future__ import annotations
import argparse
import csv
import hashlib
import json
import shutil
import subprocess
import sys
from datetime import UTC, datetime
from pathlib import Path
from urllib.request import urlopen
import yaml
ROOT = P... |
0840bdd375707ddb0c5a7b69acaca46089fbd353f7bf36e43b8600ca3a2d83e7 | Python | 7,309 | 193 | import os
import time
import numpy as np
import torch
from copy import deepcopy
import utils
class Appr(object):
""" Class implementing the Elastic Weight Consolidation approach described in http://arxiv.org/abs/1612.00796 """
def __init__(self, model, nlab, nepochs=100, sbatch=64, lr=0.05, lr_min=1... |
efaf5baf11f7df2a62889f1e28db00e42a78211eeb740a3012bbf79543d263ad | Python | 7,314 | 198 | import torch
import torch.nn as nn
from torch.nn.modules.loss import _Loss
from asteroid.losses import pairwise_neg_sisdr, PITLossWrapper, singlesrc_mse, pairwise_mse, singlesrc_neg_sisdr
class SingleSrcBCE(_Loss):
def forward(self, est_targets, targets):
if targets.size() != est_targets.size() or targets... |
573c63c9ad8ae5d4f35a3df6db10c49cece59790815b186130c49f2aa83481ce | Python | 7,321 | 226 | from __future__ import annotations
import csv
import json
import sys
from datetime import datetime
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple, Union
from dateutil.parser import parse
from imctools.data.acquisition import Acquisition, AcquisitionDict
from imctools.data.channel import... |
253e2b13cd3a2cb76b5dbd66d5ee7a504a5e01fd6e29ef0d44f60df54cc87544 | Python | 7,335 | 221 | import six.moves
from cellprofiler_core.constants.measurement import FF_COUNT, COLTYPE_INTEGER, M_NUMBER_OBJECT_NUMBER, \
M_LOCATION_CENTER_X, COLTYPE_FLOAT, M_LOCATION_CENTER_Y, FF_PARENT, FF_CHILDREN_COUNT, C_COUNT, C_CHILDREN, \
C_LOCATION, FTR_CENTER_X, FTR_CENTER_Y, C_PARENT, C_NUMBER, FTR_OBJECT_NUMBER
... |
a3a4d9a7bf034aac5734ef23ad57d5e149452929890efd58a4ffb49076e6bc9d | Python | 7,338 | 179 | """Differential Attention
Paper: 'Differential Transformer' - https://arxiv.org/abs/2410.05258
Reference impl: https://github.com/microsoft/unilm/tree/master/Diff-Transformer
Hacked together by / Copyright 2024, Ross Wightman
"""
import math
from typing import Optional, Type
import torch
import torch.nn as nn
impor... |
8e29880bde7935b1547a8396c2d8e52d1354ac8b05b6ef1284751efb2f03b5b1 | Python | 7,345 | 214 | import itertools
import warnings
import pdb2sql
from deeprank.features import FeatureClass
from deeprank import config
class ResidueDensity(FeatureClass):
def __init__(self, pdb_data, chain1='A', chain2='B'):
"""Compute the residue contacts between polar/apolar/charged residues.
Args:
... |
2c343fddda810399e1aa3e4e3d22892b0a1657b935bf0d1bb622449600961210 | Python | 7,353 | 194 | import centriole.filter
import centriole.kirsch
import centriole.otsu
import numpy
import cellprofiler_core.image
import cellprofiler_core.measurement
import cellprofiler.modules.enhanceedges
import cellprofiler_core.object
import cellprofiler_core.pipeline
import cellprofiler_core.workspace
from cellprofiler_librar... |
38088af9ea2949f8e5eec28dad6bd1295b610ccfb98d38584399009608ce377f | Python | 7,355 | 189 | #!/usr/bin/env python3
'''
these tools are for building the html pages in cifti-vis
'''
import os
import ciftify.utils
def write_index_pages(qc_dir, qc_config, page_subject, title="",
title_formatter = None, user_filter=None):
subjects = list(ciftify.utils.get_subj(qc_dir, user_filter=user_filter))
... |
e201345fce13c923219614d64466d36d22ce8fcfab0b67619553a098c0789107 | Python | 7,358 | 212 | """ reference from Harvard NLP: https://nlp.seas.harvard.edu/2018/04/03/attention.html"""
import copy
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
#######################################
## Transformer with only Encoder
###############... |
81605b6486ee373b9f5b08f555eaad1a0f32e3657e7d3fb7bb6160158af69680 | Python | 7,372 | 184 |
# This file is part of the exercise code repository accompanying
# the book: Neuronal Dynamics (see http://neuronaldynamics.epfl.ch)
# located at http://github.com/EPFL-LCN/neuronaldynamics-exercises.
# This free software: you can redistribute it and/or modify it under
# the terms of the GNU General Public License 2.... |
fb535ce5ad02f473a2d59b22f4d7dc634e2cf413ed8e4f190cdcc9c5648efad6 | Python | 7,380 | 211 | from netCDF4 import Dataset
import numpy as np
import os, pathlib
#==========================================================
# Script for computing Lanczos cosine filter
#
# Time filtering for sensitivity test
# f01: 10dy high pass filter
# f02: 10-30dy band pass filter
# f03: 30-90dy band pass filter
# f04: 90-365d... |
8daa6834088ce02bab35977f2badee51948bac6e922c7db460c7264fdb062cb7 | Python | 7,385 | 222 | """Test nimare.reports."""
import os.path as op
import subprocess
import sys
from pathlib import Path
import pytest
from nimare.correct import FWECorrector
from nimare.diagnostics import FocusCounter, Jackknife
from nimare.meta.cbma import ALESubtraction
from nimare.meta.ibma import FixedEffectsHedges, Stouffers
fro... |
9b4548a791f0a7534115e600387497ed105f7c2e7072186cc7603d50ef5ab866 | Python | 7,385 | 222 | import numpy
import numpy.random
import scipy.ndimage
import pytest
import cellprofiler_core.image
import cellprofiler_core.measurement
from cellprofiler_core.constants.measurement import COLTYPE_FLOAT
import cellprofiler.modules.measureobjectoverlap
import cellprofiler_core.object
import cellprofiler_core.pipeline
i... |
9b7c1346088fb6ba34a7f095440d7c8ded7ce5247e54d198569c83c0730039a0 | Python | 7,385 | 154 | from . import framework as fw
class State_machine():
# State machine behaviour is defined by passing state machine description object smd to
# State_machine __init__(). smd is a module which defines the states, events and
# functionality of the state machine object that is created (see examples).
... |
8db4f82612f43d6769a528cb760b4858771099d0a45a63a991011ae66e917c1a | Python | 7,388 | 213 | """
Author: Ran Liu <rliu20@stanford.edu>
Unit tests for functions in somata/pac/pac_model.py
"""
import numpy as np
from somata.pac.pac_model import (
fit_pac_regression,
kmod,
autocovariances,
block_toeplitz,
ar_parameters,
mvar_ssm,
optimize_arp,
)
def generate_pac_data():
""" Gen... |
e7a756ec4282ce9b311c501402e154bb2fb29af21557ac4723f9067ae40b415d | Python | 7,402 | 125 | import os
import numpy as np
import pandas as pd
import nibabel as nib
from os.path import join as pjoin
from nod_utils import save2cifti, _orthogonalize
from nilearn.glm.first_level import make_first_level_design_matrix, run_glm
from nilearn.glm.contrasts import compute_contrast
# change to path of current file
os.ch... |
e0b1545a1269826029b6b2ad9dda7582fb4a4d83c0b6b9819c499f17c3d54fdc | Python | 7,403 | 193 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable l... |
91d2a00e7e33416e44584041c61474f13ddd5e2246648ed0d0faadd045dd1cbb | Python | 7,409 | 187 | import numpy as np
def unit_normal(a, b, c):
# unit normal vector of plane defined by points a, b, and c
x = np.linalg.det([[1,a[1],a[2]],
[1,b[1],b[2]],
[1,c[1],c[2]]])
y = np.linalg.det([[a[0],1,a[2]],
[b[0],1,b[2]],
[c[0],1,c[2]]])
z = np.linalg.det([[a[0],a[1],1... |
af485bbec04e796367f5789e0731327f6644c5cdb7db15737f34556bcdee8690 | Python | 7,410 | 215 |
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
import math
from statistics import mean
from rdkit import DataStructs
from rdkit import Chem
impo... |
706a3f38b6f8e405cef6d30404d1ab4139ff17a5fa54c080124411f31c751108 | Python | 7,411 | 192 | from sklearn.model_selection import StratifiedShuffleSplit,StratifiedKFold
from sklearn.preprocessing import OneHotEncoder
from imblearn.over_sampling import RandomOverSampler
import numpy as np
import sys
from datetime import timedelta
import time
import torch
import torch.nn as nn
import torch.nn.functional as F
from... |
282c7766ac97bdd3c7255b21ba2263302a51ac926d8eb4d99d4174426d587d80 | Python | 7,420 | 215 |
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
import math
from statistics import mean
from rdkit import DataStructs
from rdkit import Chem
impo... |
513202c23b352acd90a2a99ab4e5bdd84a08e3b90b8763551b8539f7167a0a9b | Python | 7,429 | 151 | import os
import yaml
import random
import torch
import numpy as np
import torchvision
import argparse
from util import (seed_torch, prepare, normalize, log_args_and_backup_code,
SampleIoHandler, set_args)
def sample(args):
""" random sample some images from dataset
if chosen_class is "rando... |
e73d51a757dab4eafc111811a3b43713eac407cb15e400a62e12b6854326733a | Python | 7,434 | 193 | import pytest
import torch
from torch import nn
from timm.models._builder import load_pretrained
from timm.models._manipulate import adapt_input_conv
def _weights(channels, dtype=torch.float32):
return torch.arange(2 * channels * 3 * 3, dtype=dtype).reshape(2, channels, 3, 3) / 100
def _reference_channels(weig... |
b7a418416f57d71ee637f870a8928c364e26a2dd530c084d4c9e131b0c268fa3 | Python | 7,435 | 194 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable l... |
8872346e2f1c002b1e6a044fc09faa58e3081b7bc63098e6faebbc8b1dc40124 | Python | 7,436 | 195 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable l... |
7f7d437b6e60366f25709ea209fb7505bb8e138a0f4bcb2561bd37f77c2324ac | Python | 7,438 | 151 | import pyb
import math
from array import array
from micropython import schedule
import pyControl.hardware as _h
class _MCP():
# Parent class for MCP23017 and MCP23008 port expanders.
def __init__(self, I2C_bus, interrupt_pin, addr):
self.i2c = pyb.I2C(I2C_bus, mode=pyb.I2C.MASTER, baudrate=4... |
9c78e7472898892b02a8c5056380e5177e6fb0a9ffaef8689ec96ef74a048f79 | Python | 7,439 | 203 | from typing import Optional, Type
import torch
import torch.nn as nn
import torch.nn.functional as F
from .attention import maybe_add_mask
from .config import use_fused_attn
from .mlp import Mlp
from .weight_init import trunc_normal_tf_
class AttentionPoolLatent(nn.Module):
""" Attention pooling w/ latent query... |
5d83ca26a2384fdb9e2a8ec19aa7be919141d5ac978b29a359aa4f00d5075265 | Python | 7,445 | 159 | # Pytorch Tabular
# Author: Manu Joseph <manujoseph@gmail.com>
# For license information, see LICENSE.TXT
"""AutomaticFeatureInteraction Config"""
from dataclasses import dataclass, field
from src.models.tabular.pytorch_tabular.repository.config import ModelConfig
@dataclass
class AutoIntConfig(ModelConfig):
"""... |
9c5278fb4d5b26d3699b245fbae6c1a89fcd1e8a51c2c72e0841006b2e70521c | Python | 7,445 | 243 | # -*- 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... |
a21288bedf038e53beccd443899f88c0e535b8edea7eaccc6066465544c8fd38 | Python | 7,447 | 186 | # -*- coding: utf-8 -*-
"""
Created on Thu Feb 8 15:21:16 2018
@author: saskiad
"""
import numpy as np
import pandas as pd
import os, h5py
import scipy.stats as st
import core
# class event_analysis(object):
# def __init__(self, *args, **kwargs):
# for k,v in kwargs.iteritems():
# setattr(s... |
b628ef5ed761a49d3dd826c83a0bb947d25e0bb97170cde89c90d8e0f97f43aa | Python | 7,455 | 218 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Thu Apr 26 14:18:33 2018
@author: saskiad
"""
import numpy as np
import scipy.stats as st
import matplotlib.pyplot as plt
import seaborn as sns
areas = ['VISp', 'VISl', 'VISal', 'VISpm', 'VISam', 'VISrl']
area_labels = ['V1','LM','AL','PM','AM','RL']
cres ... |
6e2668b5be20edfa3f8a8c56ee239af00d56c4831eb7a94115bae8014463557c | Python | 7,456 | 194 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable l... |
704472b9a1c4e00fbe51e94bfe8553343fe1038d6455e1ea005c503e23478e84 | Python | 7,458 | 194 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable l... |
5e73b0ec57d13b42b906cf1e5b2d1280bdb29ea86f530ac15f78240d46fae146 | Python | 7,459 | 194 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable l... |
cf8f37aceeddaf369c4f990ba28ba9c194fa998c262340f60df7ca18d0efc515 | Python | 7,459 | 194 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable l... |
e2943d8d07b5e2f2c734837cf3f7ca2532fd906909a32db80cdfaa2d5380e26a | Python | 7,460 | 195 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable l... |
f0234da68e73a05261fb3d20c7aaf66e98f57a0b291679be867e9d9cd83a39b4 | Python | 7,460 | 194 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable l... |
e225cb1d800419dfc42c28665da617b8bbea90a36173df3073db6ac5d4fa3c45 | Python | 7,461 | 194 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable l... |
400b6dc76bb1a6a4b972a4a607ba7382f12f9d71e9c9d6a3c9ff550029c489e6 | Python | 7,475 | 185 | '''
==========
Iteratively reweighted least squares (IRLS) procedure in CS-CORE
==========
'''
import numpy as np
import scipy.stats as stats
from scipy.sparse import issparse
def CSCORE_IRLS(X, seq_depth, post_process=True):
"""
This function implements the iteratively reweighted least squares algorithm of C... |
845f5c1faa6dc8f6608d361dbc74e0a4a54c37c2ee1d402c49938af656b2ab8e | Python | 7,480 | 197 | from typing import Any
from typing import Dict
from typing import Optional
from typing import Tuple
from typing import Union
import numpy as np
import torch
import functional as func
from base import BaseTransform
from utils import expand_tensor_dims
from utils import squeeze_tensor_dims
import random
class DualTra... |
791cf0f777b5b9a5e5dc88fea00403c6da4e4a1e7a98188223536143333ecea1 | Python | 7,481 | 224 | import six.moves
import cellprofiler_core.image
import cellprofiler_core.measurement
from cellprofiler_core.constants.measurement import M_SITE, M_ROW, M_COLUMN, M_PLATE, M_WELL
import cellprofiler.modules.labelimages
import cellprofiler_core.object
import cellprofiler_core.pipeline
import cellprofiler_core.workspac... |
a728b966d138da833324013adf07ccc3829c752f7cc6376d8d83ae77fd1f6f4a | Python | 7,481 | 206 | from os import cpu_count
from traitlets import Float, Integer
from traitlets.config import Bool, Enum, default
from traitlets.config.loader import ConfigError
from mrHARDI.base.application import mrHARDIConfigurable
from mrHARDI.traits.diamond import BoundingBox, Stick
_flags = {
"mose-tensor": (
{'Diamo... |
5c57df9b4979cfdb1a1e5ab4b4b09f298323bc5d2d0da6ea83c2aabba9feaa42 | Python | 7,482 | 163 | # -*- coding: utf-8 -*-
import os
import pickle
import subprocess
import sys
import numpy as np
import scipy.io.wavfile as wav
import torch
from python_speech_features import fbank
from sklearn.preprocessing import normalize
from torch.utils.data import Dataset
from torchvision import datasets, transforms
... |
a4d2c5a03bddc27c16fd57470c1d6e1171002dad046a0a8e04f390c92becb9bd | Python | 7,482 | 222 | '''
JHK
Python script for calculating internal variability range of the ratio between dSTD and dClim. of the HF PRCP.
'''
import numpy as np
from netCDF4 import Dataset
#==========================================================
# Set main directory
#==========================================================
hdir = '/... |
edd18372e071171d4e8adbbab377726f9651ba1d11044f81470d59dce75e91a0 | Python | 7,482 | 195 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable l... |
469511c45dc77b5aa37db801f1d36d7c128d7ea2e6568f0104397fa973a8b32f | Python | 7,485 | 196 | import numpy as np
import math
from braincog.base.brainarea.PFC import PFC
from Modal.synapse import Synapse
from Modal.titlelayer import TitleLayer
from Modal.composerlayer import ComposerLayer
from Modal.genrelayer import GenreLayer
class PFC(PFC):
'''
This area is used to store the sub-Goal of the task
... |
2a81f902f27906a37e744095bb63748d8c6d8a427ef299507088532fd267b2f3 | Python | 7,505 | 195 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable l... |
11211a74d925e680f73f69be7e28b8427b14dbc9a2d4e78984a65057752c24a3 | Python | 7,506 | 195 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable l... |
d7a66e15e248216779b76d9d713aae035003eebf0fd431bc44f6676391bcb731 | Python | 7,507 | 195 | #!/usr/bin/env python3
# Copyright 2019 Christian Henning
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable l... |
7da6c29d8304be1bb2d6ee1710af1057889073763b1d0c08e17ea43b4ada05d5 | Python | 7,509 | 214 | """
LabelImages
===========
**LabelImages** assigns plate metadata to image sets.
**LabelImages** assigns a plate number, well and site number to each
image set based on the order in which they are processed. You can use
**Label Images** to add plate and well metadata for images loaded using
*Order* for “Image set ma... |
8fb0bec595c9c4e6568a240cab849209b9bfd1f8e7175811d0b7c676826902b9 | Python | 7,510 | 232 | import os
import json
import argparse
import datetime
import pickle
import numpy as np
from sklearn.model_selection import train_test_split
from model import *
from betaVAE import *
from read_data import *
from utils import *
parser = argparse.ArgumentParser(description='betaVAE disantangle generation of RNA-Seq dat... |
6ba7a06b960090f3c3389fcba41dd96ec497b10cb9e3f0528395dc8a530ca456 | Python | 7,512 | 177 | from __future__ import annotations
from typing import Union
import numpy as np
import numpy.typing as npt
import traits.api
import xarray as xr
from . import BaseFilter
from ptsa.data.timeseries import TimeSeries
# An ``events`` recarray-or-ndarray; some callers pass a structured
# ``np.ndarray``, others pass an ``... |
741a8aef5e371442a5f7f1413ee5a9198eb171396648e31afc173d8cc3dd6ba9 | Python | 7,513 | 231 | # 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... |
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