sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
258c751835b14097ab501f547f3455cdf6fd591ea16db6f75e31dd78994b79b6 | Python | 2,478 | 52 | import torch.nn as nn
import torch.nn.functional as F
from .base_model import BaseModel
#########################
####### BRATS #########
#########################
from .blocks import ConvBlock # for plain vgg like 3D network
from monai.networks.nets import densenet121 # for tumorsyn
class GeneNet(nn.Module):# [ba... |
e47cefb19aab7982a4551ff71620abb09f4c43cdb1145b293ca3ca7bceb5bb33 | Python | 2,478 | 87 | from os.path import basename
from pathlib import Path
import numpy as np
from sacred import Experiment
from sacred.observers import FileStorageObserver, SlackObserver
from graspy.models import SBMEstimator, DCSBMEstimator
from src.data import load_left, load_right
from graspy.utils import binarize, symmetrize
from src... |
f9a7d016edf787b251b2c7966a37f9b19db320454cb6e21f540269c760e14036 | Python | 2,478 | 75 | """
File: utilities.py
Created: 2020/11/09
Last Changed:
Author(s): M.Vochteloo
Copyright (C) 2020 M.Vochteloo
This program 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, either version 3 of the... |
779dd5b7dbe12664854ecfdc700288b3fe6bb0c3cf40f676ff659cbe95545824 | Python | 2,480 | 72 | import sys
import torch
from torch_geometric.datasets import TUDataset
from graphxai.explainers import RandomExplainer
#from graphxai.explainers.utils.visualizations import visualize_mol_explanation
from graphxai.gnn_models.graph_classification import train, test
from graphxai.gnn_models.graph_classification.gcn impor... |
93651310e9e33dfc61354f21b7c7ec1e37fde65a9bbbfefad97442fe052d246a | Python | 2,480 | 64 | # Copyright (c) 2016, Konstantinos Kamnitsas
# All rights reserved.
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the BSD license. See the accompanying LICENSE file
# or read the terms at https://opensource.org/licenses/BSD-3-Clause.
from __future__ import absolute_im... |
7fad9c76134380a0e9bf83a7e8cbec112d6e1f2538c3c571800322f565a1b97e | Python | 2,481 | 70 | import torch
import torch.nn as nn
class FocalLoss(nn.Module):
def __init__(self, gamma=2, alpha=None, ignore_index=255, reduction='mean'):
super(FocalLoss, self).__init__()
self.gamma = gamma
self.reduction = reduction
self.CE_loss = nn.CrossEntropyLoss(
reduction=redu... |
9993dd8e1301a04f72e76f92cf29d7fbc1322ce36e5be9e05e1666c4333dd3b3 | Python | 2,483 | 60 | import logging
import unittest
from oaklib.datamodels.association import Association, NegatedAssociation, ParserConfiguration
from oaklib.parsers import GAF
from oaklib.parsers.association_parser_factory import get_association_parser
from tests import INPUT_DIR
INPUT_GAF = INPUT_DIR / "test-uniprot.gaf"
class GafAs... |
9a9841523401e871821e6e3116e86a25d2ae9c517ceee2613a2330420114d89b | Python | 2,483 | 65 | # Copyright 2021 Huawei Technologies Co., Ltd
#
# 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 agreed to... |
d3330526f9e93b10741b05d86e75414f9c45bd1f120d8dd8c016863b68f5bbc8 | Python | 2,484 | 64 | """
Model derived from "Human 5′ UTR design and variant effect prediction from a massively parallel translation assay", https://doi.org/10.1101/310375
"""
import torch
import numpy
import torch.nn as nn
class UTRModel(nn.Module):
def __init__(self, sequence_length=50, n_targets=1):
super(UTRModel, self).... |
d0fcf43e6ddbbe662627e2e1da38ada7ce0850f0023f9ebe277b6ed74f06c445 | Python | 2,485 | 72 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
from __future__ import division
import torch
class ImageList(object):
"""
Structure that holds a list of images (of possibly
varying sizes) as a single tensor.
This works by padding the images to the same size,
and storing in... |
dc8d691664169153a630def5657908321a08f87529678e751511314f1b8289f6 | Python | 2,487 | 67 | import random
import torch
import matplotlib.pyplot as plt
from graphxai.explainers import GraphLIME
from graphxai.gnn_models.node_classification.testing import GCN_3layer_basic, GIN_3layer_basic, test, train
from graphxai.datasets.shape_graph import ShapeGGen
# Load dataset:
# Smaller graph is shown to work well wi... |
926657947ce5e040c28ca934a63562fb1a4e30750ac267fb585df07840566f16 | Python | 2,488 | 80 | from __future__ import annotations
import logging
import os
from palmari.processing.utils import get_values_as_in_dict
from abc import ABC, abstractmethod
import json
class PostProcessingParameters(ABC):
def __init__(self, params: dict = {}):
for key in params:
assert (
key in... |
bd9a27640aae5fef186f1820c48f94db469689c5985f4c4c2b9a19628cda9ba2 | Python | 2,488 | 62 | import copy
import warnings
def replace_ImageToTensor(pipelines):
"""Replace the ImageToTensor transform in a data pipeline to
DefaultFormatBundle, which is normally useful in batch inference.
Args:
pipelines (list[dict]): Data pipeline configs.
Returns:
list: The new pipeline list w... |
37c484923fe98600194a3785c458bfcfd94de84996fbc655c7a637cb25f4f47e | Python | 2,489 | 62 | import os, sys; sys.path.append('..')
import argparse
import torch
import numpy as np
from tqdm import trange
from torch_geometric.datasets import TUDataset
from graphxai.explainers import IntegratedGradExplainer
#from graphxai.explainers.utils.visualizations import visualize_mol_explanation
from graphxai.gnn_models.g... |
4a3640a5b83049c31b7035719806a7d6ee8ab27cc241f862540e0090b11422db | Python | 2,489 | 72 | #!/usr/bin/env python3
# Copyright 2020 Maxim Korenevsky (STC-innovations Ltd)
# Apache 2.0.
import argparse
import logging
import sys
import numpy as np
import kaldi_io
from scipy.spatial.distance import cosine, pdist, squareform
sys.path.insert(0, 'steps')
import libs.common as common_lib
def LoadReco2Utt(file)... |
5ef96e5f348fd200fbae599017aa24b8dd544a9339a80adda3e5341c6338519c | Python | 2,489 | 66 | # Copyright 2020 Huawei Technologies Co., Ltd
#
# 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 agreed to... |
c7e2d1459d53c13a5be792ee7f398dc32ca84bc1deada9a42bb4b5add173d24a | Python | 2,489 | 75 | """
File: utilities.py
Created: 2020/10/08
Last Changed: 2020/10/15
Author(s): M.Vochteloo
Copyright (C) 2020 M.Vochteloo
This program 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, either versi... |
e4b30ac5f290de85d3b952d029c978ff3eeffd917bab0e71d654b354b8ca1aef | Python | 2,489 | 82 | import argparse
import glob
import os
parser = argparse.ArgumentParser(description='Generate htseq job files.')
parser.add_argument('jobs_directory', help='Directory for jobs')
parser.add_argument('cram_base_directory', help='Directory with cramFiles')
parser.add_argument('ref_gtf', help='Reference gtf file location')... |
f298d142c87906d5948fff2e1cd9001e4735678e90a3e2e5b9387ea745b3b0ab | Python | 2,489 | 71 | import os
from pytorch_lightning import Trainer
from pytorch_lightning.callbacks import ModelCheckpoint
from argparse import ArgumentParser
from omegaconf import OmegaConf
from utils.utils import get_commit_hash
from cotatron import Cotatron
from utils.loggers import TacotronLogger
def main(args):
model = Cotatr... |
bcd7ed13a554c28e7108bdca6be3246337cfc35817ae87ac731c47f770e6a1bc | Python | 2,490 | 70 | import sys
import torch
from torch_geometric.datasets import TUDataset
from graphxai.explainers import CAM, GradCAM
from graphxai.explainers.utils.visualizations import visualize_mol_explanation
from graphxai.gnn_models.graph_classification import GIN, load_data, train, test
import matplotlib.pyplot as plt
dataset... |
09af1154a2b483f8050ac531b22742830d369bb5df2d85adacd0ea603444f180 | Python | 2,491 | 96 | #%%
import time
import matplotlib.pyplot as plt
import numpy as np
from giskard.hierarchy import BaseNetworkTree
from giskard.plot import plot_dendrogram
from src.data import load_maggot_graph, load_palette
from src.io import savefig
from src.visualization import adjplot, set_theme
t0 = time.time()
set_theme()
def ... |
2a812a5fd6bacf0ba6e373a2e4a986fe885fd53be427e61454f6443bf9842c88 | Python | 2,491 | 82 | """
Utilities for working with networkx
-----------------------------------
NetworkX is a popular python package for working with graphs
"""
from collections import defaultdict
from typing import Dict, Iterable, List, Tuple
import networkx as nx
from sssom_schema import Mapping
from oaklib.interfaces.basic_ontology... |
bdcefee4e91eb4e4fe30dc864e8dea6d0ecdd729527a519790792fbb8952edb9 | Python | 2,491 | 81 | #!/usr/bin/python
#
# Convert instances from png files to a dictionary
# This files is created according to https://github.com/facebookresearch/Detectron/issues/111
from __future__ import print_function, absolute_import, division
import os, sys
sys.path.append( os.path.normpath( os.path.join( os.path.dirname( __file_... |
312ba53ea39a2c7ae6069d711fcb97308369b14b95a411de05d2644b307b2d3d | Python | 2,493 | 60 | import tensorflow as tf
import tensorflow.keras.backend as K
import logging
import numpy as np
class RollingAverageWeighting(tf.keras.callbacks.Callback):
def __init__(self, weights: list, loss_names: list, ref_loss: str, epoch_update):
super(RollingAverageWeighting, self).__init__()
assert len(we... |
a67031437e86ac1ade2516e184b8e4f7f4facf862f97df41e242f25df823770f | Python | 2,494 | 70 | import sys
import torch
from torch_geometric.datasets import TUDataset
from graphxai.explainers import CAM, GradCAM
from graphxai.explainers.utils.visualizations import visualize_mol_explanation
from graphxai.gnn_models.graph_classification import GCN, load_data, train, test
import matplotlib.pyplot as plt
dataset... |
b3dfc7fadc1cf8c2f341e0c6aaf7d1f118a7973937b65dd8e1406f710f384333 | Python | 2,494 | 95 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd.function import once_differentiable
from mmcv.cnn import Scale
from ..utils import ext_loader
ext_module = ext_loader.load_ext(
'_ext', ['ca_forward', 'ca_backward', 'ca_map_forward', 'ca_map_backward'])
class CAWeightFunctio... |
79095ca52efa7fe869ef040362f80ded50b5973f6db97e5534675fe040c64505 | Python | 2,495 | 69 | # python 3.7
"""Contains the encoder class of StyleGAN inversion.
This class is derived from the `BaseEncoder` class defined in `base_encoder.py`.
"""
import numpy as np
import torch
from .base_encoder import BaseEncoder
from .stylegan_encoder_network import StyleGANEncoderNet
__all__ = ['StyleGANEncoder']
class... |
38bfa91cb75f6de703f608f307b4da59d3adff9d81984c350b5a76b616f261c9 | Python | 2,496 | 67 | import random
import torch
import matplotlib.pyplot as plt
from graphxai.explainers import GNN_LRP
from graphxai.gnn_models.node_classification.testing import GCN_3layer_basic, GIN_3layer_basic, test, train
from graphxai.datasets.shape_graph import ShapeGGen
# Load dataset:
# Smaller graph is shown to work well with... |
d00143e9938ef06c9fd26433fe6c795f0cdb578fb806b984c9c616049a3f3562 | Python | 2,497 | 94 | # %% [markdown]
# ##
from src.visualization import adjplot, matrixplot
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_context("talk")
n_rows = 100
n_cols = 200
data11 = np.random.normal(0, 1, size=(n_rows, n_cols))
data21 = np.random.normal(0, 2, size=(n_rows, n_... |
105066cc0aa5a0dbc703017dbf3a427de74dc973d165839459cc22510fc40954 | Python | 2,499 | 73 | # Copyright 2020 Google Research. All Rights Reserved.
#
# 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... |
e745fb6d509285907431562ff67fdc792ed459ab9a633da3eb78006b1991af21 | Python | 2,499 | 85 | import os.path as op
import os
import json
def write_json(fname, data):
"""
Write data to JSON file.
Parameters
----------
fname : str
Full path to the file to write.
data : dict
A dict containing the data to write.
Returns
-------
None
"""
with open(fnam... |
fb884dff231047a5d2c21d37821f926e8678733655cda68db2a35ba345e87308 | Python | 2,500 | 85 | #%%
import pymaid
from pymaid_creds import url, name, password, token
import numpy as np
import pandas as pd
import re
import datetime
#pymaid.clear_cache()
rm = pymaid.CatmaidInstance(url, token, name, password)
# %%
def timeTracing(user, interval, start_date, end_date=None):
time_interval = pd.Timestamp(year... |
292b2456ba8c89fec6671af21069239c24f98fb8f51f5902c52efd6eb9d91fe9 | Python | 2,501 | 76 | import multiprocessing
import argparse
import time
import logging
import json
import tqdm
from os.path import join, exists
from os import makedirs
def build_batches(args, file_name):
with open(join(args.data_dir, file_name)) as f:
return [(args, json.loads(line.strip())) for line in f]
def format_story(d... |
91f0d13588d2ac6cb086197391c2433f3e2122d875256a457aa6039017333f62 | Python | 2,501 | 86 | #!/usr/bin/env python3
# Copyright (c) 2026 Computer Vision Center (CVC) at the Universitat Autonoma de
# Barcelona (UAB).
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
"""Download big files from Google Drive."""
import argparse
import shutil
i... |
ece63f6dd722bcc44479e9c1d91089e9474d73a25fda27a4c330d7856a6497e8 | Python | 2,501 | 72 | import copy
import numpy as np
from ..builder import PIPELINES
from .compose import Compose
@PIPELINES.register_module()
class AutoAugment(object):
"""Auto augmentation.
This data augmentation is proposed in `Learning Data Augmentation
Strategies for Object Detection <https://arxiv.org/pdf/1906.11172>`... |
13edc493adc404b75617ff22b445dc3905f6916e9fe334d9a2b219d788e5aee6 | Python | 2,502 | 72 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
from torch import nn
from torch.nn import functional as F
from ..box_head.roi_box_feature_extractors import ResNet50Conv5ROIFeatureExtractor
from maskrcnn_benchmark.modeling import registry
from maskrcnn_benchmark.modeling.poolers import Pooler
fr... |
8d0efee0cc2c3cb9c91f25743088ff2b2c4141f78c928edd8e59c8a3f14cc29b | Python | 2,502 | 65 | from pathlib import Path
from os import chdir
import unittest
from math import sqrt
from nipype.interfaces.base import CommandLine
from qipype.commands import NewImage, Diff
from qipype.utils import PolyImage, PolyFit, Filter, RFProfile
vb = True
CommandLine.terminal_output = 'allatonce'
class Utils(unittest.TestCas... |
94938dc566e40848eeee5cbd8375259710fa0d4c1803907d0dcf9903f16add0e | Python | 2,502 | 80 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from imlib.dtype import *
import numpy as np
import scipy.misc
def rgb2gray(images):
if images.ndim == 4 or images.ndim == 3:
assert images.shape[-1] == 3, 'Channel size should be 3!'
else:
... |
e69e5d355b76014f2a0c6f8f5f8ae3411ba22ac2f61ee27670d645c7872c8dc9 | Python | 2,502 | 63 | #!/bin/bash
# Copyright 2022 Huawei Technologies Co., Ltd
#
# 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 ... |
e85270f8295a8b0723a7a0a9a93bea0e3f5810c83683cf5627032ac563f02828 | Python | 2,502 | 37 | """Plot the tuto_G_traffic_manager set_path routes on the road network (from the Map API)."""
import sys, carla, numpy as np
import matplotlib; matplotlib.use("Agg"); import matplotlib.pyplot as plt
OUT = sys.argv[1]
import json
D = json.load(open(sys.argv[2]))
R1S, R1 = D["r1"][0], D["r1"][1:]
R2S, R2 = D["r2"][0], D[... |
fb3ad6235aa3472fc36e07f9280598bb83a38840271cf8aaa525a618413e71b7 | Python | 2,502 | 55 | import os
import torch
from akt import AKT
# from sakt import SAKT
# from dkvmn import DKVMN
# from dkt import DKT
# from dktplus import DKTPlus
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
def try_makedirs(path_):
if not os.path.isdir(path_):
try:
os.makedirs(path_)
... |
b9115ee0a43bc8a774f21fee8dca15c1cc6157d062c1f2f1225bbfa63e799394 | Python | 2,504 | 65 | # Copyright 2021 Huawei Technologies Co., Ltd
#
# 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 agreed to... |
d862669bf376cce483d1b4b7db304e247f0423251b59863152c7cdf67de9574f | Python | 2,505 | 64 | # Merge FeatureCount count files (counts per sample) to matrix with rows genes, columns samples
# NOTE: Needs Python version 3.5+
import glob
import argparse
import gzip
import sys
parser = argparse.ArgumentParser(description='Calculate the fraction each transcript of a gene is expressed')
parser.add_argument('feature_... |
284bdfe5a6a44abc059c3cbb0c582ba0b450088cbe9667856439b8d51891c8d5 | Python | 2,506 | 74 | # Copyright 2023 Huawei Technologies Co., Ltd
#
# 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 agreed to... |
e6ea4ec0426effcea03e7357b5c506d65790d3b7ce4fbb93cc12dce0d4ab9f23 | Python | 2,506 | 68 | import torch.utils.data
from torch.utils.data.dataloader import default_collate
from batch import BatchSubstructContext, BatchMasking, BatchAE
class DataLoaderSubstructContext(torch.utils.data.DataLoader):
r"""Data loader which merges data objects from a
:class:`torch_geometric.data.dataset` to a mini-batch.
... |
6f811b39149cc65835af5f036f0fbf52f1706dc59940f80a6617945872383732 | Python | 2,507 | 100 | """Example script for training Single-Channel DyNeMo on simulated data.
This script should achieve a dice coefficient of ~0.8.
"""
import numpy as np
from osl_dynamics.data import Data
from osl_dynamics.inference import modes, metrics
from osl_dynamics.simulation import HMM
from osl_dynamics.models.sc_dynemo import C... |
1ae58a6f050b37174dfa65d6d81c155367254aac06debb19e238a450252cd309 | Python | 2,510 | 76 | # Copyright 2022 Huawei Technologies Co., Ltd
#
# 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 agreed to... |
7a44a949af07116054ac183037c29b4dd3181d94403f86296d74dbcbdb11e8eb | Python | 2,510 | 67 | import random
import torch
import matplotlib.pyplot as plt
from graphxai.explainers import GradCAM
from graphxai.gnn_models.node_classification.testing import GCN_3layer_basic, GIN_3layer_basic, test, train
from graphxai.datasets.shape_graph import ShapeGGen
# Load dataset:
# Smaller graph is shown to work well with... |
e30c7bf659a34058a33dec04fbf0e5da292377ea2e08cc229beb5db05e8089dc | Python | 2,510 | 103 | # -*- coding: utf-8 -*-
"""
Created on Mon Mar 16 09:22:57 2020
@author: Sandi
"""
import numpy as np
from matplotlib import pyplot as plt
import pickle
from sklearn import metrics
from sklearn.neural_network import MLPRegressor
data=np.loadtxt("dataset.csv", delimiter=",")
print(data)
data= data[data[:, 2].argsort... |
89371a78071919dd62066897d88b208e725ab8a1dd1c644b02f051cdcdeea913 | Python | 2,511 | 86 | import torch
import torch.nn as nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.utils import _pair
from ..utils import ext_loader
ext_module = ext_loader.load_ext('_ext',
['roi_pool_forward', 'roi_pool_backward'])
... |
15157a7ebcdb4631ba880f6ef54908406de086451d31a26875e324eb0c671e64 | Python | 2,512 | 66 | import random
import torch
import matplotlib.pyplot as plt
from graphxai.explainers import RandomExplainer
from graphxai.gnn_models.node_classification.testing import GCN_3layer_basic, test, train
from graphxai.datasets.shape_graph import ShapeGGen
from graphxai.utils import aggregate_explanations
# Load dataset:
# ... |
51b825e1dc1468672d8fc31f5fe553a8de55fb71ed76f8d32a71a3215debc506 | Python | 2,512 | 66 | import random
import torch
import matplotlib.pyplot as plt
from graphxai.explainers import IntegratedGradExplainer
from graphxai.gnn_models.node_classification.testing import GCN_3layer_basic, GIN_3layer_basic, test, train
from graphxai.datasets.shape_graph import ShapeGGen
# Load dataset:
# Smaller graph is shown t... |
6d7fe6b9b58c731e65d18a541a95af6dbc6a82de6b3c79e1f1a8b2b4a575975b | Python | 2,512 | 81 | import torch
from torch import nn
class Basic3DUNet(nn.Module):
def __init__(self, **kwargs):
super(Basic3DUNet, self).__init__(**kwargs)
self.output_layer = nn.Conv3d(16, 1, 1, padding="same")
self.bottom_layer = nn.Sequential(
nn.Conv3d(128, 128, (2, 3, 3), padding="same"),
... |
9a4339f002d61b0e7ec6954dbc63f6d0e6720aebaccce134a7781b79cdfb5b68 | Python | 2,512 | 64 | """ Estimating stability of macro model by root finding.
Here, we want to find a root of jw + Fe(w)*(I-alpha*C)/tauC
This becomes a multiplication of jw + Fe(w)*lambda_i(w)/tauC, multiplication over i where lambda_i are eigenvalues
Thus, we need to find roots of jw + lambda_i(w)/(tauC*(tau_e*jw+1)**2)
T... |
1587deebb57f658da1b043c2d7586e29792f8ee6d01eef955390076608d53892 | Python | 2,513 | 63 | # this code will generate a literal caption and a pragmatic caption (referring expression) for the first of the urls provided in the context of the rest
import matplotlib
matplotlib.use('Agg')
import re
import requests
import time
import pickle
import tensorflow as tf
import numpy as np
from keras.preprocessing import... |
4a25a0ee640bcdc21807900cd3638eb8e56f7851309aa680769733cf7eb80722 | Python | 2,515 | 100 | # Author: Christian Brodbeck <christianbrodbeck@nyu.edu>
import numpy as np
from eelbrain import datasets, plot, testnd
from eelbrain.plot._figure import Figure
from eelbrain.plot._utsnd import _ax_bfly_epoch
from eelbrain.testing import requires_mne_sample_data
from eelbrain._wxgui.testing import hide_plots
@hide_p... |
8402fd0ac7f1ddad5e5d7281d2a2e6d1dea66428d63f4cee0132697a6c7b36ad | Python | 2,517 | 103 | # -*- coding: utf-8 -*-
"""
Created on Mon Mar 16 09:22:57 2020
@author: Sandi
"""
import numpy as np
from matplotlib import pyplot as plt
import pickle
from sklearn import metrics
from sklearn.neural_network import MLPRegressor
data=np.loadtxt("dataset.csv", delimiter=",")
print(data)
data= data[data[:, 2].argsort... |
f6ebd7856b1e87603a81284e358461d21faa49f242e6d70d042150caf86da265 | Python | 2,518 | 68 | """
The build/compilations setup
>> pip install -r requirements.txt
>> python setup.py install
"""
import pip
import logging
import pkg_resources
try:
from setuptools import setup
except ImportError:
from distutils.core import setup
def _parse_requirements(file_path):
pip_ver = pkg_resources.get_distribu... |
568f2952ba22943e5bf3cb69618c7f49ff2ddd87ac1f13e62f1cbf92ba45b8c8 | Python | 2,519 | 100 | import pandas as pd
import os
import sys
def read_genome_BED():
'''
Read genome intron/exon coordinates (from parse_gft.R)
'''
genome_bed = pd.read_csv(
"/hpf/largeprojects/ccm_dccforge/dccdipg/Common/genomes/hg19_introns_exons.bed",
sep=" ",
skiprows=1,
low_memory=Fals... |
e42b75a48f4ce605475e17ce496188886356787aa3da4c0bd9a2955a78885ab7 | Python | 2,519 | 59 | ####################################################################################################
# Copyright (c) 2019 - 2023, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of VessMorphoVis <https://github.com/BlueBrain/VessMorphoVis>
#
# This program is free ... |
d07fb482847f8c4be7136af6ff70b730132b79dfd205798643e87948be6b9cde | Python | 2,520 | 85 | # Copyright 2020 The HuggingFace Team. All rights reserved.
#
# 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 applicabl... |
e284f2f458853067cf4ddf26a43be3f962c998223f652e1b1dd0cb4b099cd933 | Python | 2,520 | 85 | import abc
import numpy as np
import cPickle as pkl
from . import Tools
class SpikingModel:
"""
Abstract class defining an interface for a Spiking Neuron Model, a model that produces spikes.
Inherit from this class to generate a new Spiking Neuron Model.
To create a new model that explicitly descri... |
d013fa1da460ae14cb423e5f972bb0304b55888e2cae259580f34ee03df692d0 | Python | 2,522 | 60 | import unittest
import numpy as np
from selene_sdk.sequences.proteome import Proteome
from selene_sdk.sequences.proteome import _get_sequence_from_coords
class TestProteome(unittest.TestCase):
def setUp(self):
self.proteome = Proteome("selene_sdk/sequences/tests/files/small.faa")
self.fill_value... |
07b4e366129dc82b88131686d9b934a48b22dccfa99b27b4887c1abdd22d44f2 | Python | 2,524 | 64 | from dataclasses import dataclass
from typing import Any
from linkml_runtime import CurieNamespace
from oaklib.interfaces.obograph_interface import OboGraphInterface
from oaklib.interfaces.semsim_interface import SemanticSimilarityInterface
from oaklib.io.streaming_writer import StreamingWriter
from oaklib.utilities.... |
d0e520bc32fb9ad0a931ffff11f7aa59ea9d353ccbbf837d597ec80b3fcda147 | Python | 2,524 | 82 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import argparse
from keras.models import Model
from keras.models import load_model
import os
import cv2
def make_dir(dir_):
if not os.path.exists(dir_):
os.makedir... |
7e9277e948874c23537823a776b5da8d5ff4a9bd0de9a25fde2e041c3aba29b5 | Python | 2,525 | 66 | # Configuration file for the Sphinx documentation builder.
#
# For the full list of built-in configuration values, see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
import os
import sys
sys.path.insert(0, os.path.abspath('../..'))
sys.path.insert(0, os.path.abspath('../../..'))
#... |
6a03f421bdb45e761b2337166129e1c5bf9b0b021e21119889a61467e0891df9 | Python | 2,526 | 66 | """Latent inhibition task — the classical discriminator for RPE vs hybrid models.
Protocol (Jacob & Waddell 2022 style, adapted for our minimal setting):
Group: pre-exposed 1) Pre-exposure N_pre trials of CS+ alone (no reward)
2) Acquisition N_acq trials of CS+/CS- (CS+ paired)
G... |
8338906f0bb2115b2648d8fca0ce17cffbd96307b8ca74932395cb842057c440 | Python | 2,526 | 72 | # Copyright 2021 Huawei Technologies Co., Ltd
#
# 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 agreed to... |
389bef227da975d8ce0746d3747d10771e806ba5f1d42a21f3efaff5a52a20de | Python | 2,527 | 76 | #!/usr/bin/env python
# Interface to cluster_report.csv file produced by IsoSeq.
import os
import sys
import re # for regular expressions
from tt_log import logger
VERSION = '20141029.01'
logger.debug('version %s loaded' % VERSION)
class ClusterList (object):
def __init__ (self, filen... |
62bd5dd640dce5dff933edb732356df56f4a27cda06e1a915d0fc9597515b016 | Python | 2,528 | 79 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
phys2bids interface for txt files.
"""
import numpy as np
from phys2bids.physio_obj import BlueprintInput
def populate_phys_input(filename, chtrig):
"""
Populate object phys_input
for now this works only with labchart files
Input (Properties)
... |
3c1a8d0884c3849fb2745fea7bb9652353d76de7473d353700d1a5fbc7eb9e32 | Python | 2,529 | 85 | import logging
import sys
import warnings
from dataclasses import asdict
import chika
from imblearn.metrics import geometric_mean_score
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import cohen_kappa_score, roc_auc_score
from spikebench import load_allen, load_fcx1, load_retina
from spikebe... |
3fe10bff4f1249bc5153b643466d559586add9a14769d01002b023c24ba3ca48 | Python | 2,529 | 93 | import cv2
import numpy as np
def imnormalize(img, mean, std, to_rgb=True):
"""Normalize an image with mean and std.
Args:
img (ndarray): Image to be normalized.
mean (ndarray): The mean to be used for normalize.
std (ndarray): The std to be used for normalize.
to_rgb (bool): ... |
ed4d3600002d3b06a9b2b6e003789a00bc0793f30ee5139babb1d04fe59032bb | Python | 2,529 | 85 | import PIL
import io
import scipy.misc
import numpy as np
from PIL import Image
import base64
def label_colormap(N=256):
def bitget(byteval, idx):
return ((byteval & (1 << idx)) != 0)
cmap = np.zeros((N, 3))
for i in range(0, N):
id = i
r, g, b = 0, 0, 0
for j in range(0, ... |
3001c6def86be62bbcf069d74e9a2a5a9e58a68b2356638d9fd49511346b5125 | Python | 2,531 | 79 | # Author: Christian Brodbeck <christianbrodbeck@nyu.edu>
"""
Sample MneExperiment. This experiment can be used with a sample dataset that
treats different parts of the recording from the MNE sample dataset as different
subjects. To produce the data directory for this experiment use (make sure
that the directory you spe... |
3a70de6dbd9a103c21e1dc17fa50eceb5b6450228adab08be3b38361277dceb5 | Python | 2,531 | 61 | import torch.nn as nn
class BaseNetwork(nn.Module):
def __init__(self):
super(BaseNetwork, self).__init__()
def print_network(self):
if isinstance(self, list):
self = self[0]
num_params = 0
for param in self.parameters():
num_params += param.numel()
... |
1e931c08e66fa76288861c172a29b1f912bd58d7852049c4a5b2fa0a7d691141 | Python | 2,535 | 76 | # Copyright 2022 Huawei Technologies Co., Ltd
#
# 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 agreed to... |
15e342b3f41feefcbd29f3c00f0bbd061a70359ad4dd75a0a42f82e216ea386a | Python | 2,536 | 82 | """
StyleMapGAN
Copyright (c) 2021-present NAVER Corp.
This work is licensed under the Creative Commons Attribution-NonCommercial
4.0 International License. To view a copy of this license, visit
http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to
Creative Commons, PO Box 1866, Mountain View, CA 94042, U... |
27ceb0b515a3250299f435cc48b6d832d6e0345583a3b2a0956bc93955acb323 | Python | 2,538 | 79 |
import gzip
terms = []
count_term = {}
term_type = {}
print('count go')
with open('term_order.txt','w') as out:
out.write('term\torder\n')
x = 1
with gzip.open('2020-03-29-goa_human.gaf.gz','rt') as input_file:
for index, line in enumerate(input_file):
if line.startswith('!'):
... |
64d00706533ac773a2740e58e64bc7fa577f2cf0b57227dff5fddcfec3747339 | Python | 2,538 | 100 | from os.path import basename
from pathlib import Path
import numpy as np
import pandas as pd
from sacred import Experiment
from sacred.observers import FileStorageObserver, SlackObserver
from graspy.datasets import load_drosophila_left
from graspy.utils import binarize, symmetrize, is_fully_connected
from graspy.plot i... |
93d3cde13ba747a3b5608abd154e961d0154c8505c1a3e5d9ebb3b6728e044fb | Python | 2,538 | 82 | """
Title
-----
AMPA synapses
Description
-----------
AMPA receptors are the most common type of ionotropic glutamate receptors in the
brain. They have fast kinetics and are responsible for excitatory synaptic
transmission.
In this example we show:
- How to add and activate AMPA synapses at various model compartment... |
a25b451a292704e4485b5bf0f7bc6112b4e3d255d8babd7ed8d0ca3afc53728e | Python | 2,538 | 69 | from scipy.linalg import blas
import numpy as np
from dipy.data import default_sphere
from dipy.reconst.shm import anisotropic_power, sh_to_sf_matrix
__all__ = ["extract_odf", "anisotropic_index", "anisotropic_power"]
def extract_odf(odf, sphere=default_sphere, sh_order=8):
"""
Calculates spherical harmonic... |
d14dca8e753ceaa95a867920cc826b16184a60aa729d78163332ee230b75bfb0 | Python | 2,538 | 53 | ####################################################################################################
# Copyright (c) 2019 - 2023, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of VessMorphoVis <https://github.com/BlueBrain/VessMorphoVis>
#
# This program is free ... |
3cb835dfffebfaa5001d6a0254cebdab5fae68dd930874752fb217ca6bbb32b9 | Python | 2,539 | 82 | """
Title
-----
GABA synapses
Description
-----------
GABA receptors are the most common type of inhibitory ionotropic receptors in the
brain. They have fast kinetics and are responsible for inhibitory synaptic
transmission.
In this example we show:
- How to add and activate GABA synapses at various model compartmen... |
e795193991397766309077a8b80adf9e2b434799c512673ac3437c70bc983353 | Python | 2,539 | 87 | import contextlib
import os
from typing import Tuple
import albumentations as alb
import numpy as np
import tifffile as tf
from spotipy.utils import points_to_prob, normalize_fast2d
from cenfind.core.data import Dataset
def load_foci(path) -> np.ndarray:
"""
Load annotation file from text file given channel... |
583db1a905d0fa9228dbd8296df3c4f769c6d405f571b123af28ddfd522ef12e | Python | 2,541 | 103 | # -*- coding: utf-8 -*-
"""
Created on Mon Mar 16 09:22:57 2020
@author: Sandi
"""
import numpy as np
from matplotlib import pyplot as plt
import pickle
from sklearn import metrics
from sklearn.neural_network import MLPRegressor
data=np.loadtxt("dataset.csv", delimiter=",")
print(data)
data= data[data[:, 2].argsort... |
7de43e4c02e5985e7cc4a2f442dd1e8cc6b6f75954cf6faf3828711f0319f59c | Python | 2,541 | 82 | import time
import torch
import pandas as pd
import networkx as nx
import numpy as np
import matplotlib.pyplot as plt
from torch_geometric.utils import from_networkx
from sklearn.model_selection import train_test_split
from graphxai.datasets.utils.bound_graph import build_bound_graph
from graphxai.gnn_models.node_cla... |
dbbaf7057e0ed82be3b7402bd8f009be64a2617bb384e6b007707e702ce7eaf6 | Python | 2,541 | 63 | # Copyright 2020-2022 Huawei Technologies Co., Ltd
#
# 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 agre... |
440a79d13f3567c4c6c5a19a62ca390b87f78a94fa1e9fef067df0c48faa41bd | Python | 2,542 | 78 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
from keras.models import Model, load_model
import argparse
from util import load_avi_video, load_dcm_video, remove_info2, limited_equalize
def predict(args):
# predict probability
... |
e388e079b41b1581a90925ad615e1b7754acef49e18b26ddc02745a3201df03e | Python | 2,543 | 44 | #!/usr/bin/env python3
# -*- coding:utf-8 -*-
#############################################################
# File: logo_class.py
# Created Date: Tuesday June 29th 2021
# Author: Chen Xuanhong
# Email: chenxuanhongzju@outlook.com
# Last Modified: Monday, 11th October 2021 12:39:55 am
# Modified By: Chen Xuanhong
# Cop... |
dc8dd85613b6c452099d54219b8429c19d4123faf32e9cd259a4cae81be67c6a | Python | 2,544 | 89 | import os
import os.path as op
import numpy as np
import nibabel as nib
from dipy.reconst import fwdti
import AFQ.utils.models as ut
__all__ = ["fit_fwdti"]
def _fit(data, gtab, mask):
fwmodel = fwdti.FreeWaterTensorModel(gtab)
fwfit = fwmodel.fit(data, mask=mask)
return fwfit
def fit_fwdti(data_fi... |
43fd37213fabfb7969f2b88045de1fd008e531cdc678ccc45932e47b6696c15b | Python | 2,545 | 85 | import csv
from dataclasses import dataclass
from typing import Dict, Iterable, List, Set, Tuple, Union
from oaklib.types import CURIE
@dataclass
class ListPair:
set1_id: str = None
set2_id: str = None
list1: List = None
list2: List = None
list1_len: int = None
list2_len: int = None
inter... |
02a364018813c4bcd676340f7a989b21e5bffbf1bb6f730ddce8fced2585134d | Python | 2,546 | 63 | # Copyright 2020-2021 Huawei Technologies Co., Ltd
#
# 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 agre... |
71ac28b4546cf617b5f3453c63ff079f81a4aa43ed1eec2d780354f5f6d6efdc | Python | 2,546 | 66 | import random
import torch
import matplotlib.pyplot as plt
from graphxai.explainers import GradExplainer
from graphxai.gnn_models.node_classification.testing import GCN_3layer_basic, GIN_3layer_basic, test, train
from graphxai.datasets.shape_graph import ShapeGGen
from graphxai.utils import aggregate_explanations
# ... |
233430516213c40bd40da7a1823ab46571bd5a4538c034180fb089709260fc45 | Python | 2,547 | 95 | import sys
from bokeh.io import curdoc
from bokeh.layouts import column, row
from bokeh.models import CustomJS, Slider
from bokeh.plotting import ColumnDataSource, figure, output_file, show
from bokeh. palettes import Greens7, OrRd3
import numpy as np
from lib import File, segmentation, image_adjustments
def reverse... |
a6677e918b67db10f49f72ea0739737ebe50a1c0c0462133acee501332e92636 | Python | 2,547 | 69 | from collections import defaultdict
from dataclasses import dataclass
from functools import lru_cache
from typing import Any, List, Union
from oaklib.converters.data_model_converter import DataModelConverter
from oaklib.datamodels.obograph import Graph, GraphDocument, LogicalDefinitionAxiom
from oaklib.types import CU... |
3da3c4dfe72db26082ce4d83ee8e14cfcda4664f332668d63c2c04f4d73480ca | Python | 2,548 | 92 | import numpy as np
from .traverse import BaseTraverse
class RandomWalk(BaseTraverse):
def _choose_next(self):
node_transition_probs = self.transition_probs[self._active]
if np.isclose(np.sum(node_transition_probs), 1):
nxt = np.random.choice(self.n_verts, p=node_transition_probs)
... |
8a825b6d37c6c718b5c0e7db2e0ecb6875df25b584eb215165ddc5b076b030e9 | Python | 2,548 | 87 |
import math
import glob
import argparse
parser = argparse.ArgumentParser(description='Create slurm job to Concatenate gVCFs')
parser.add_argument('list_of_vcfs', help='.txt file with list of path of VCFs to Concatenate (only for chr15, this will be replaced for other chr numbers)')
parser.add_argument('jobs_dir', h... |
ef065f47b08259551720617e1cbd23e7d068af370daef71f782c5db795c2aad4 | Python | 2,548 | 67 | # Copyright 2022 Huawei Technologies Co., Ltd
#
# 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 agreed to... |
6156ee6c97ec49ffd16d2c66b624bd3547d1ffbabd927b0d08f82b02e4035ca7 | Python | 2,549 | 73 | """
Utilities for traversing Ontology Graphs
====================
"""
from copy import copy
from dataclasses import dataclass
from typing import List, Union, Dict, Iterable, Tuple
from oaklib.interfaces.basic_ontology_interface import RELATIONSHIP, BasicOntologyInterface
from oaklib.types import CURIE, PRED_CURIE
#... |
744f8854edce85b58fb20d8150ce4249e00d52b4e42e49b1d556a3b228aeaf15 | Python | 2,549 | 67 | #!/usr/bin/env python3
"""
File: artificial_bulk_deconvolution.py
Created: 2020/11/09
Last Changed: 2020/11/12
Author: M.Vochteloo
Copyright (C) 2020 M.Vochteloo
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published b... |
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