sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
ab9a0002dd3d848f6597d10728d6b6bb8ec73c12a0935edfa2c7e32562a1b549 | Python | 2,549 | 78 | # 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... |
f5882752da84524716f0e8713795e6568de8eb535ab789bb07b52a48073eaf85 | Python | 2,549 | 74 | import sys
import torch
from torch_geometric.datasets import TUDataset
from graphxai.explainers import GuidedBP
#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 import GCN_2... |
9af62fa4c3d8eda8d37bbd8ce7a5471423e7a709849d3335221eefbb7836e08f | Python | 2,550 | 97 | """
Title
-----
Other adaptive models
Description
-----------
Apart from the Adaptive Exponential integrate-and-fire model (AdEx), Dendrify
also supports other types of adaptive models, that can be preferred in some
cases. In this example, we compare the behavior of two different adaptive models:
- The Adaptive IF mo... |
7f549875df288d2a161d7f99d110eb81bd1515641e97b178ac20786f2cbb1440 | Python | 2,551 | 77 | # 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... |
c85f2471702a6a4e57c331628d51da4ded1330a3be7b81a453c08b83b5115c45 | Python | 2,551 | 88 | import matplotlib as mpl
mpl.rcParams['figure.dpi'] = 100
mpl.rcParams['font.family'] = 'serif'
mpl.rcParams['font.sans-serif'] = ['Lucida Console']
import networkx as nx
import matplotlib.pyplot as plt
from read_edgeind import degdist, get_edge_index
#plt.style.use('ggplot') # Use ggplot style
from graphxai.datasets... |
f445d1f01c3a2e7435799f324e38f935fa3e3d38bc7715d291d28fbfe05ca91b | Python | 2,551 | 59 | # 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... |
2a81ad723be1f67db68229a3608e4895d28b4609bf96a14df55e8f4b83c6e437 | Python | 2,552 | 91 | # Copyright 2021 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... |
e60e559e9409a8b6f432de46d6c3059cb5c7d20186b8ac1ac13f222573b8d599 | Python | 2,552 | 57 | from builtins import super
import numpy as np
from .expectation_maximization_registration import expectation_maximization_registration
class rigid_registration(expectation_maximization_registration):
def __init__(self, R=None, t=None, s=None, only_t=False, *args, **kwargs):
super().__init__(*args, **kwargs... |
13a807d4aa9091540bccbd6bb020d299c5566a9546932541655ea6cc5872a695 | Python | 2,553 | 63 | import os
from chemproppred.utils import *
from rdkit.Chem import PandasTools
def screen_poly(data_path, save_path, preds_path):
if not os.path.exists(save_path):
os.makedirs(save_path)
#load xgboost screen set and predictions from chemprop
xgb_df = pd.read_csv('{}/xgb_screen.csv'.for... |
3330bc63d23f164172513f5894ad23a76e037df2bc8f2eee3f68de680763fa53 | Python | 2,555 | 76 | # 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>.
import time
import carla
from . import SmokeTest
# The packaged build only ships Town10HD_Opt and... |
36548d107eaf06f9410331ba6f1615cfc51814cbf215ee1078c6a44742f35640 | Python | 2,555 | 74 | 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 train, test
from graphxai.gnn_models.graph_classification.gcn import G... |
8f03693f62e54d3d01bf4e8480284e68b87fa40167b18c34e0a2df833042c10d | Python | 2,555 | 99 | from os.path import basename
from pathlib import Path
import numpy as np
import pandas as pd
from joblib import Parallel, delayed
from sacred import Experiment
from sacred.observers import FileStorageObserver, SlackObserver
from graspy.datasets import load_drosophila_left
from graspy.utils import binarize, symmetrize, ... |
c3c44cd3974163e61e57d7641c5fff37c21811d76f0533cf439ec6119cad5a0d | Python | 2,555 | 74 | 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 train, test
from graphxai.gnn_models.graph_classification.gcn import G... |
dd06690158f87af8336474d452e28ad1b653382ef47612b010259093240ac375 | Python | 2,555 | 75 | ## Utils.py -- Some utility functions
##
## Copyright (C) 2018, IBM Corp
## Chun-Chen Tu <timtu@umich.edu>
## PaiShun Ting <paishun@umich.edu>
## Pin-Yu Chen <Pin-Yu.Chen@ibm.com>
##
## Licensed under the Apache License, Version 2.0 (the "License");
#... |
b90b5a492e579bba6fdbde7b7d547f3fa6c5ee80f41592f67f49c57b8ca2103c | Python | 2,556 | 74 | import sys
import torch
from torch_geometric.datasets import TUDataset
from graphxai.explainers import SubgraphX
#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 import GCN_... |
c88881ace2789ffe9479af3e8f44de816ed2c93e57f87067b56879ba8e1b7a0d | Python | 2,556 | 73 | # 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... |
d0b8d1c0a95565d834a89e4fb0d3da1b014f9f87034e65607cfa6a4d996794c4 | Python | 2,556 | 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 t... |
5921003a6ddc001bf4c430d9947744e7fbab8cd93bbb62553c563ba55948fc4b | Python | 2,558 | 98 | from os.path import basename
from pathlib import Path
import numpy as np
import pandas as pd
from joblib import Parallel, delayed
from sacred import Experiment
from sacred.observers import FileStorageObserver, SlackObserver
from graspy.datasets import load_drosophila_left
from graspy.utils import binarize, symmetrize, ... |
9b64e1e216fae2046103387cec52bde5e6b20b9ab005c91330f367cd51c7705a | Python | 2,558 | 75 | import torch
import torch.nn as nn
def get_loss_func(loss_name, reduction='mean'):
"""
Return the loss function.
Parameters:
loss_name (str) -- the name of the loss function: BCE | MSE | L1 | CE
reduction (str) -- the reduction method applied to the loss function: sum | mean
"""
... |
f9080f50dfe2faad4749b89e74bd35a039f556cc1e54cc77454cdb5692544e1e | Python | 2,558 | 68 | #%%
import sys
sys.path.append("/Volumes/GoogleDrive/My Drive/python_code/connectome_tools/")
import pymaid
import pyoctree
from pymaid_creds import url, name, password, token
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import pandas as pd
rm = pymaid.CatmaidInstance(url, token, name, pas... |
66c627bbaf5e65ad69d4a262a3e46ea997275b654407ad1f799eb0d0bd655693 | Python | 2,559 | 93 | import torch
import torch.nn as nn
import torchvision
import torchvision.transforms as transforms
import os, random, sys, math
import numpy as np
import matplotlib.pyplot as plt
import networks
device = 'cuda'
batch_size = 1
Z = 128
T = 1
transform_train = transforms.Compose([
transforms.ToTensor(),
])
trainset ... |
4f508b6862db26eebaf34e2748612913aacb0456bb53d93f6c9cdc3b9ee1b279 | Python | 2,561 | 93 | import torch
import torch.nn as nn
import torchvision
import torchvision.transforms as transforms
import os, random, sys, math
import numpy as np
import matplotlib.pyplot as plt
import networks
device = 'cuda'
batch_size = 1
Z = 128
T = 1
transform_train = transforms.Compose([
transforms.ToTensor(),
])
trainset ... |
d5ce883725d438110cf469dc1b7fc099f0bec03e0d79bd9bfd4b6812fdd619e2 | Python | 2,561 | 78 | """
File: local_settings.py
Created: 2020/10/08
Last Changed:
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 by
the Free Software Foundation, either version 3 o... |
fd67109aec9f276a8fba55c750b7546205107888b9f5f3f81c9c9b63a75265d2 | Python | 2,561 | 70 | #######
# This code was written by Nino Verwei and Niek van Hilten at Leiden University, The Netherlands (23 August 2022)
#
# When using this code, please cite:
# Van Hilten, N.; Methorst, J.; Verwei, N.; Risselada, H.J., Science Advances. 2023, 9(11). DOI: 10.1126/sciadv.ade8839
#######
import numpy as np
... |
3f3bf57fc9713d49e01a4880d39199d1c01d11c0d3adeb61fec99f1e81e2bfa2 | Python | 2,562 | 88 | '''
@author: Mahbub Ul Alam (mahbub@dsv.su.se)
@version: 1.0+
@copyright: Copyright (c) Mahbub Ul Alam (mahbub@dsv.su.se)
@license : MIT License
'''
'''@file early_sepsis_detector.py
run this file to go through the complete neural net training, testing and evaluating procedures,
look at the 'early_sepsis_detector_con... |
117267ea5d9c327b3c460598badf7c05a29d451e991d85c02846c240f179bcba | Python | 2,563 | 66 | from __future__ import division
from math import sqrt as sqrt
from itertools import product as product
import torch
class PriorBox(object):
"""Compute priorbox coordinates in center-offset form for each source
feature map.
"""
def __init__(self, cfg):
super(PriorBox, self).__init__()
s... |
51b906a010df0eed126d2255312cfdd4310cef9ef1dc4e60612d4132c5b45eb7 | Python | 2,563 | 68 | # 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... |
6197de1c34499e8aadf5bd38ac2cb48d6b702a205b5a47bbd87fc3fa2d9d02ca | Python | 2,563 | 67 | import random
import torch
import matplotlib.pyplot as plt
from graphxai.explainers import GuidedBP
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
# Load ... |
311983c5c32de30f7ad526e98c10f9c70c1243aa314ac12486d52fc7335c8953 | Python | 2,564 | 88 | #!/usr/bin/env python
# Read annotation file, print counts, plot transcript sizes;
import os
import sys
import optparse
import re # regular expressions
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import Annotations as anno
VERSION = '20140930.01'
DEF_OUTPUT = 'transcript_sizes.p... |
fcef3d49f759623dd1e02b6bd45d8bf297a2a6ccc67a7b27c3cbf3a6edd0e11f | Python | 2,564 | 77 | import os.path as op
import numpy as np
import numpy.testing as npt
import pytest
from bids.layout import BIDSLayout
import AFQ.definitions.image as afm
from AFQ.definitions.image import * # interprets images from eval
from AFQ.definitions.mapping import * # interprets mappings from eval
from AFQ.tests.test_api imp... |
0790e297527d314eeb1b4f51d6159c509c5244f4b56c680bd4a3f234bed1da7c | Python | 2,565 | 67 | # 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... |
509077c9161b72ed015a5c2fdfb094a92e7b8de3395ee95da1fb4a5860a7f4b2 | Python | 2,565 | 57 | from spike2calcium_linear_ALS import *
import os, sys
import warnings
warnings.filterwarnings('ignore')
from glob import glob
# get cell list information
# flist = sorted(glob('GCaMP8_exported_ROIs_s2f_full/dff_v00/*.npz'))
# new fit based on the clean-up data
flist = sorted(glob('GCaMP8_exported_ROIs_s2f_full/dff_v03... |
6882be55968de7ce21d00b4a1fa10125022a4f06632682aa364a7cdc025c8ea9 | Python | 2,566 | 74 | import sys
import torch
from torch_geometric.datasets import TUDataset
from graphxai.explainers import GradExplainer
#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 import ... |
cf611cb3423c507a92db5cf5ac528597318075370630b731062dc555d9dc022a | Python | 2,567 | 88 | """
Refer to https://github.com/rosinality/stylegan2-pytorch/blob/master/op/fused_act.py
"""
import os
import torch
from torch import nn
from torch.autograd import Function
from torch.utils.cpp_extension import load
module_path = os.path.dirname(__file__)
fused = load(
"fused",
sources=[
... |
3bf27ba327066a0e833f525f3cba3bc030eb629362368f677c2375fec10bc94e | Python | 2,568 | 64 | import random
import pandas as pd
import numpy as np
import os
def dir_check(thispath):
if not os.path.exists(thispath):
os.mkdir(thispath)
def create_subfolders(savepath):
# create classic subfolder structure (figures, DF, csv) in given folder
savepath_fig = os.path.join(savepath, 'figures')
... |
6c93b131b4f0d57e0caab4bfcba0b0b38229c7ff2d376397a92ee8f55e81bafa | Python | 2,568 | 65 | """verify_cache.py <artifacts.lock> <HF_HOME> <artifact_id>... — sha256-check every lock file present in a local HF cache.
Resolution follows prefetch.py: the pinned revision's snapshot first, then the sha256-named blob, then the same
path under any other revision (NVIDIA re-tags the same weight file across commits, s... |
21d97c2cade96fabfd5dbcd3f9736051cc5acca066acd5c3df9d43036a290d5c | Python | 2,569 | 79 | ##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
## Created by: Hang Zhang
## Email: zhanghang0704@gmail.com
## Copyright (c) 2018
##
## This source code is licensed under the MIT-style license found in the
## LICENSE file in the root directory of this source tree
##++++++++++++++++++++++++++... |
549a799bf1d9478cba1b32d66bcc2083548f4b338b9ff19029ad5c352d2cae56 | Python | 2,569 | 71 | import torch
import networkx as nx
from graphxai.utils.nx_conversion import khop_subgraph_nx
def motif_id_label(G, num_hops):
'''
Gets labels based on motif label in the neighborhood
'''
def get_label(node_idx):
nodes_in_khop = khop_subgraph_nx(node_idx, num_hops, G)
# For now, sum mot... |
67743d9c97f5dc908ff3785117adac4cb78c7a2a5f2dae657de423b8bd56c4a5 | Python | 2,569 | 66 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
# Code is copy-pasted exactly as in torch.utils.data.distributed.
# FIXME remove this once c10d fixes the bug it has
import math
import torch
import torch.distributed as dist
from torch.utils.data.sampler import Sampler
class DistributedSampler(S... |
82ab3629d3634663f6e252ed7d5558bd98feec20d898ba9b1759cc774d098ba1 | Python | 2,571 | 68 | # # Introduction
# This example illustrate a very simple linear regression couple with a cross validation mechanism.This example uses the only the first feature of the `diabetes` dataset, in order to illustrate a two-dimensional plot of this regression technique. The
# straight line can be seen in the plot, showing how... |
698f392189bda6415210d514613d9fc24307d052f8ff69f98d697c57db295fe5 | Python | 2,573 | 77 | import numpy as np
from mip.mip_nn import MIP_NN
from globals import CONT, TARGET_ERROR, MARGIN
class MIN_HINGE(MIP_NN):
def __init__(self, data, architecture, bound, reg, fair):
MIP_NN.__init__(self, data, architecture, bound, reg, fair)
self.init_output()
self.add_output_constraints()
if reg:
... |
dc99b7bd44d7154bd3809b58ab46791f443316ae357275fa2625e9dd96f1dc37 | Python | 2,573 | 70 | """Visualize atomic attention and save similarity map."""
from typing import Union
import numpy as np
from tqdm import tqdm
from chemprop.args import PredictArgs, TrainArgs
from chemprop.data import get_data, MoleculeDataLoader, MoleculeDataset
from chemprop.utils import load_args, load_checkpoint, update_prediction_a... |
ee69aba983728c8af1670d45332327e8bf7f9d4ee3bd66c4f2c9099555492eee | Python | 2,573 | 52 | from pathlib import Path
from matplotlib import pyplot as plt
from metrics import calculate_lateral_errors, read_frames_driving
def draw_error_plot(ax, model_frames, expert_frames, title=None):
lat_errors = calculate_lateral_errors(model_frames, expert_frames, only_autonomous=True)
autonomous_df = model_fr... |
17bdeab15db84d993c54cae8383efe3d3152bd7359d696f2ed159aaa712c40e2 | Python | 2,574 | 80 | import gzip
import sys
import argparse
parser = argparse.ArgumentParser(description='Merge (gzipped) matrices by column')
parser.add_argument('outfile', help='File to write output to')
parser.add_argument('type', help='type of event')
parser.add_argument('input_files', help='files to merge', nargs='+')
args = parser.... |
4360d8362f7b377b37a58f2640ff49a98ecc85bf3797e8e3baa1b730da534ad5 | Python | 2,574 | 77 | import numpy as np
from torch.utils.data import DataLoader
from torch.utils.data.dataloader import default_collate
from torch.utils.data.sampler import SubsetRandomSampler, WeightedRandomSampler
import torch
class BaseDataLoader(DataLoader):
"""
Base class for all data loaders
"""
def __init__(self, da... |
987817d8dfadb76b5828c9c7708165d1392eb9a7faea9386bfaabed1ab1ff8f1 | Python | 2,576 | 82 | import numpy as np
import matplotlib.pyplot as plt
from scipy import signal
plt.style.use('seaborn-whitegrid')
class Butterworth:
"""Creates an IIR Butterworth filter in second-order sections format.
Attrs:
order (int): filter order
ftype (str): the type of filter, one of:
... |
5771c308c4a5d9165e1badf1bc22bc379cf9af4425f756579ed5d00d7045227c | Python | 2,577 | 74 | # 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... |
b54c4e61505c658c1cc331312252d53d7b40990453fcc557d982820c893ec446 | Python | 2,577 | 66 | # 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... |
f660ba9212227387c5f6ea092f5bd71fcb0d041705deb056ed2f0ac6b5c10ce0 | Python | 2,577 | 110 | '''
Simulates 200 trajectories in a chemical gradient.
'''
from brian2 import *
from behavior import *
import imageio
from plotting import cell_mask, cell_indices
movie = True
C = paramecium_constants()['C']
N = 200
duration = 50*second
tau_noise = 20*ms
sigma_noise = .009*nA # .09*nA
size = 25000 # in um # observat... |
017a7868cc0f6ae3eca8d0898e38523c46fb5659283e951396d0449694d0dc11 | Python | 2,578 | 76 | import torch
import torch.nn as nn
import torchvision
import torchvision.transforms as transforms
# Hyper-parameters
input_size = 28 * 28 # 784
num_classes = 10
num_epochs = 5
batch_size = 100
learning_rate = 0.001
# MNIST dataset (images and labels)
train_dataset = torchvision.datasets.MNIST(root='../../data', ... |
7553b3f17a59866991385abf07c5eeff7689c9956df893df87981a99ba76318e | Python | 2,578 | 88 | import argparse
import datetime
import os
from pathlib import Path
import tensorflow as tf
import yaml
from multi_phase.networks.models import get_model
from multi_phase.trainingloops.build_training_loop import get_training_loop
from multi_phase.utils.build_dataloader import get_train_dataloader
# ------------------... |
de0d17fbacf1653148b5c29730e16dea85e0a56776bf77b34ffbdc435aee7bc6 | Python | 2,578 | 72 | # 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... |
4990d37e910dc6f7736eaf93100a35e71f6df738be6e4e401ef2cecd42d885ba | Python | 2,579 | 66 | # Copyright 2020-21 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... |
1eb6cf6103d8d07305c716bfc2729d3755acf1ade3a58004bf3aab47fd2c822a | Python | 2,580 | 75 | 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 train, test
from graphxai.gnn_models.graph_classification.gcn import G... |
3ca390fc3e2da67bdc8a0032a3dcc63dd466775e93d01eb2b8d31528d059b797 | Python | 2,580 | 68 | import numpy as np
from cenfind.core.structures import Centriole, Nucleus
def test_centriole_centre_xy_swaps_row_col(make_field):
field = make_field(shape=(2, 100, 100))
centriole = Centriole(field=field, channel=0, centre=(7, 3))
assert centriole.centre_xy == (3, 7)
def test_centriole_intensity_sums_n... |
0f0f8d8ff2358fdedaa7784c06180ff9e98e8a974097c90f915ce0efbb500f70 | Python | 2,581 | 68 | # Taken from : https://github.com/jindongwang/transferlearning/blob/master/code/distance/mmd_pytorch.py
# Compute MMD distance using pytorch
import torch
import torch.nn as nn
class MMD_loss(nn.Module):
def __init__(
self, kernel_type="rbf", kernel_mul=2.0, kernel_num=5, fix_sigma: float = None
):
... |
74f9450bbae8fa923e258d42798c769137a1be7f4b5a7388f154085ff4c48521 | Python | 2,583 | 77 | import pandas as pd
# from tqdm import tqdm
# import os
# import inspect
# import AIS_parameters
# import numpy as np
# import AIS_harvest
# import datetime
# import AIS_description
# import matplotlib.pyplot as plt
# from skimage import data, util, measure
# from scipy.ndimage.measurements import label
imp... |
bf5fe04075a5cf72cccd9ff298ac78719405427132e14830b4eba874f9a48edf | Python | 2,583 | 74 | import os.path as osp
from mmcv.runner import Hook
from torch.utils.data import DataLoader
class EvalHook(Hook):
"""Evaluation hook.
Attributes:
dataloader (DataLoader): A PyTorch dataloader.
interval (int): Evaluation interval (by epochs). Default: 1.
"""
def __init__(self, dataloa... |
116d22a003d7263976cb4fa6c213eb2e4ea7be2c463b3568e40af8171ba2b5b8 | Python | 2,584 | 83 | import unittest
import numpy as np
import numpy.testing as npt
from grr import Trace
class TestFilterTimesByROI(unittest.TestCase):
def testIntegerTimes(self):
unfilteredTimes = [1, 5, 7, 110, 111, 150]
ROI = [5, 111]
expectedFilteredTimes = [5, 7, 110]
npt.assert_array_equal(
... |
a3832e91c356d4aca3a181bc6b4eb6c296dedc8900a5e42799cfcb5a0e94bba0 | Python | 2,584 | 64 | # Copyright (c) 2015-present, Facebook, Inc.
# All rights reserved.
import torch
import torch.distributed as dist
import math
class RASampler(torch.utils.data.Sampler):
"""Sampler that restricts data loading to a subset of the dataset for distributed,
with repeated augmentation.
It ensures that different ... |
71aa5c3b712a71e836a4bce3885294e401251fc4cabdcc5cbf9bb6ae45c024d0 | Python | 2,586 | 82 | """
Utilities for working with networkx
-----------------------------------
NetworkX is a popular python package for working with graphs
"""
import logging
from typing import Dict, Tuple, List
import sssom
from oaklib.types import PRED_CURIE, CURIE
try:
# Python <= 3.9
from collections import Iterable, defau... |
e123cd9c2bc8a1acde3f988cd42e8f1d51aab1ed0cc0012969f122f7052269cd | Python | 2,587 | 100 | import argparse
import json
import os
import os.path as op
import sys
from glob import glob
from shutil import copyfile
import matplotlib.image as mpimg
import nibabel as nib
import numpy as np
import pandas as pd
from matplotlib import pyplot
from nilearn import image, masking, plotting
def _get_parser():
parse... |
1e1a53e6a9a6b993ab609a6a27ff033b1cbe2ea3278e0798f9ed43148a8d7178 | Python | 2,589 | 78 | #!/usr/bin/env python3
"""
File: diverging_cmap.py
Created: 2020/06/19
Last Changed:
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 by
the Free Software Founda... |
d58fa9ad1173645c9ac15ac23d7e677382615f0f0dcabae3457af29d77524423 | Python | 2,589 | 81 | # Copyright (c) Open-MMLab. All rights reserved.
import os
import random
import sys
import time
from getpass import getuser
from socket import gethostname
import numpy as np
import torch
import mmcv
def get_host_info():
return f'{getuser()}@{gethostname()}'
def get_time_str():
return time.strftime('%Y%m%d... |
7b6396a485e5b62bb45050a8abfb92c89ec18a20ccb6196c5f9f8d88d1f2d934 | Python | 2,590 | 75 | """
Generate data for testing the effects of linear and nonlinear models on
data with the linear label signal removed
"""
import argparse
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('out_file', help='T... |
143b1d24a4697694567d6e7ab0ff30c78767bf638aa09c8ec708a5d5defb78de | Python | 2,591 | 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... |
23cf767603481b3976cbe407d6fb3da2035910628019c64fea61c08bb8b53dce | Python | 2,591 | 77 | # 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... |
861b733e80df0558b89ad34d5b842ea1f1bc3cab8025bf37c280c16949071c73 | Python | 2,591 | 77 | import os, glob
import torch
import argparse
import numpy as np
#def aggregate_results(exp_method, metric, level, path):
# def aggregate_results(dataset, exp_method, metric, level):
# '''
# Metrics should match:
# {exp_method}_{metric}_{level}
# Also performs filtering for None's
# Assumes th... |
54f41b0ca7cad02e2b9eaa49a3abed0f37722f1a9a721b5a38bc019a3a47ad40 | Python | 2,592 | 90 | # -*- coding: utf-8 -*-
#!/usr/bin/env python3
import tensorflow
import numpy
import unetsl.data
import sys
def getGaussianKernel(sigma, N=128):
xi = numpy.repeat(
numpy.arange(N).reshape( (1, N) ),
axis=0,
repeats = N
)
yi = numpy.repeat( numpy.arange(N).resha... |
635fe2ccb80876af0b8573202b80d1ec9f3f7f98d3efa5cc5f44c79483c22e0f | Python | 2,592 | 67 | import random
import torch
import matplotlib.pyplot as plt
from graphxai.explainers import PGMExplainer
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
# L... |
64ad49850e165c0c87eab2f9ed0d6638937e7ed8b7bcb109ebe10872bc022261 | Python | 2,593 | 74 | # Copyright (c) Open-MMLab. All rights reserved.
import torch
from torch.nn.parallel._functions import _get_stream
def scatter(input, devices, streams=None):
"""Scatters tensor across multiple GPUs."""
if streams is None:
streams = [None] * len(devices)
if isinstance(input, list):
chunk_s... |
7bdce9fae78175de83322a1d46e827f7af4809858fbf353d771a79850f6ef3ff | Python | 2,594 | 71 | import os
import glob
import argparse
import pickle
import numpy as np
from openeye import oechem
from utils import generate_esp_grids
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description='Generate PfAbNet ESP grid input')
parser.add_argument('--input_mols_dir', type=str, default... |
d2a95a0642244f97f08588e08efeb2c4a318deb04222e6caa444c4e75b0755f9 | Python | 2,594 | 87 | import numpy as np
import polychrom.forcekits
import polychrom.forces
import polychrom.polymerutils
import polychrom.starting_conformations
from polychrom.hdf5_format import HDF5Reporter, list_URIs, load_URI
from polychrom.simulation import Simulation
def test_basic_simulation_and_hdf5(tmp_path):
data = polychro... |
b9615e390fe2eaa77fe8d7f35d3a4320f64d16d42e6c969894f5edd27985f657 | Python | 2,595 | 95 | import torch
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from maskrcnn_benchmark import _C
class DeformRoIPoolingFunction(Function):
@staticmethod
def forward(
ctx,
data,
rois,
offset,
spatial_scale,
out_size,
... |
c707304f118d1509f2683ddb5aacd1942e7421b65fe3a443fc3ec23c6b10c922 | Python | 2,595 | 80 | #%%
import numpy as np
from src.data import load_maggot_graph
from src.io import save_walks
from src.traverse import RandomWalk, to_markov_matrix
from tqdm import tqdm
from graspologic.utils import remove_loops
def get_nodes(meta, labels):
nodes = []
for i, (node, row) in enumerate(meta.iterrows()):
m... |
0de17312eef7cca3bf2131a4f567a525fd20aef6a2e5aab65d91d55faecaf457 | Python | 2,596 | 70 | # 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... |
df60028eaebfe047c31ec7de7f075b7814e3d661318f47021187f0d9f6cec654 | Python | 2,596 | 54 | # Copyright 2021 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... |
398613b8fc1232da0403084c8d706b5382d0fe10bac1f5550755eac8b25ba439 | Python | 2,597 | 74 | ###############################################################################
# Language Modeling on Penn Tree Bank
#
# This file generates new sentences sampled from the language model
#
###############################################################################
import argparse
import torch
from torch.autograd... |
e6ffc0d365cc3793e33c9df24758a4cff6dae25f13a1430fee373e00f55d7157 | Python | 2,599 | 91 | """
Title
-----
AdEx neuron + noise
Description
-----------
The Dendrify implementation of the Adaptive exponential integrate-and-fire model
(adapted from `Brian's examples <https://brian2.readthedocs.io/en/stable/examples/frompapers.Brette_Gerstner_2005.html>`_).
In this example, we also explore:
- How to add gauss... |
f040e211ddc5c02e9a2362a68a8188887aadebda9da8f1aefca6b392bbc804e9 | Python | 2,599 | 98 | import torch
import torch.nn as nn
import torch.nn.functional as F
class MFMLP(nn.Module):
"""
Multi-class Field Multi Layer Perceptron
"""
def __init__(self, d_in, c_in, dropout, n_c):
super(MFMLP, self).__init__()
self.d_in = d_in
self.c_in = c_in
self.seq1 = nn.Seq... |
d758e487deb4809725843d429e8d888316f838ce82ec6dff382772bd324e6e88 | Python | 2,600 | 74 | import sys
import torch
from torch_geometric.datasets import TUDataset
from graphxai.explainers import PGMExplainer
#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 import G... |
1e31a841a1eaa2cce918661c70c0e806e4481355e8500b0fb8a26fce87646b48 | Python | 2,601 | 104 | 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... |
d958cbe48466f69d7620995e31216568ca276b3c4247a412c5c18e4cb5538861 | Python | 2,601 | 83 | import numpy as np
from mip.mip_nn import MIP_NN
from globals import EPSILON, BIN, TARGET_ERROR
class MAX_CORRECT(MIP_NN):
def __init__(self, data, architecture, bound, reg, fair):
MIP_NN.__init__(self, data, architecture, bound, reg, fair)
self.init_output()
self.add_output_constraints()
self.cuto... |
a785e4c5f8f91412820506f224b567ba458894e6be115c1efa5e9a356cfc7445 | Python | 2,602 | 97 | #%%
import os
try:
os.chdir('/Volumes/GoogleDrive/My Drive/python_code/connectome_tools/')
print(os.getcwd())
except:
pass
#%%
import csv
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import connectome_tools.process_matrix as promat
from tqdm import tqdm
from ... |
7c6447dd86d9289dd84457f1f3b68709ce8e290706bf1c94f89d59747e4a80fc | Python | 2,603 | 70 | # 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... |
cbb41efb9eeed0d7b67a5b7facd64a3aa2b67126a236aab009d9ff4166fe7754 | Python | 2,603 | 94 | import matplotlib.pyplot as plt
def calc_acc(matrix):
import numpy as np
diag = np.diag(matrix)
class_sample_sum = np.sum(matrix, axis=1)
return diag / class_sample_sum
def score_acc_each_class(y_true, y_pred):
"""
Parameters
----------
y_true : array-like
y_pred : array-like
... |
e46964cc2c71334392a58ec26d9cd7298ce7ff18187115975f55855e005d85f0 | Python | 2,604 | 64 | # -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
import numpy as np
import os
SET_DPI = 100
FIGSIZE = (18, 10)
def plot_channel(table, channel, filename, figsize=FIGSIZE, dpi=SET_DPI):
plt.figure(figsize=figsize, dpi=dpi)
plt.title(channel)
plt.plot(table.index.values, table[channel], '-')
plt... |
6b5dcca3eed26c480bef87167d4e3b70e10031fa755209fd911e0c14f27816ce | Python | 2,605 | 74 | import sys
import torch
from torch_geometric.datasets import TUDataset
from graphxai.explainers import IntegratedGradExplainer
#from graphxai.explainers.utils.visualizations import visualize_mol_explanation
from graphxai.gnn_models.graph_classification import train, test
from graphxai.gnn_models.graph_classification.g... |
f80b81bdb978a0c8a50313829eee1ade508cb74c2ce32496f14dc1fb850c493d | Python | 2,609 | 55 | from pathlib import Path
from matplotlib import pyplot as plt
from metrics import calculate_lateral_errors, read_frames_driving
def draw_error_plot(ax, model_frames, expert_frames, title=None):
lat_errors = calculate_lateral_errors(model_frames, expert_frames, only_autonomous=True)
autonomous_df = model_fr... |
1c545e047fb54259394bbbd3f068b3508f169cb9d159e97fafe9748546bd6b92 | Python | 2,611 | 66 | # 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... |
03642865655175768f83353da631ca9fbc7deb7f5fa1a7b06602053f671f3bf8 | Python | 2,612 | 104 | # %% [markdown]
# ##
import os
import time
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import scipy
import seaborn as sns
from joblib import Parallel, delayed
import pandas as pd
from graspy.match import GraphMatch
from graspy.plot import heatmap
from src.cluster import get_paired_inds... |
2b8ed82e977547852c164273dd746eba47983c18cbaf2474cfc11cdb8cb2b816 | Python | 2,612 | 89 | '''
Selection of data
'''
import yaml
import os
from brian2 import second
import numpy as np
from numpy import mean
__all__ = ['trim_data', 'stimulus_time', 'amplitudes', 'select_trials', 'merge_data', 'align_traces', 'subsample']
def subsample(data, n):
'''
Subsamples the data n times.
'''
data['t'] ... |
617dda2a957a2d9417733950abe9c0c34c0f5fd0e0714ffa173306bd8c824a40 | Python | 2,613 | 67 | # 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 a... |
7d7eaf69116aa59740731d175dd2ee0a42899a2352a9a92e05d04921afbc6d30 | Python | 2,613 | 64 | """
Closure ("multi-hot") encoding of ontology terms.
Each term is encoded as a binary vector over a vocabulary of terms, with a 1 at the
position of each of its reflexive ancestors. Under this encoding, classic set-based
semantic similarity measures become vector comparisons; e.g. Jaccard over closure
vectors is iden... |
59ec94cc3eaef709545aa68696a2116cb29da9daee681ae785cd9c47b03d039f | Python | 2,614 | 82 | import functools
import numpy as np
import scipy.stats
import sklearn.metrics as metrics
# Metric helpers which convert float values to binary (0/1).
# Regression metrics helper functions.
def _to_binary(x: np.ndarray, threshold=0.5) -> np.ndarray:
return np.where(x > threshold, 1, 0).astype(int)
def binary_i... |
1d0db3306c027bb2bbbbaadc5232837f8dd04a6cf15ddb0c24ea4cb1d3793754 | Python | 2,617 | 62 | # 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>.
import carla
import random
import time
from . import SyncSmokeTest
class TestSnapshot(SyncSmokeTe... |
3e3bc58623281ed5bfc1878c58b0612d79b558bc81c34fb65734bc4c0edc5226 | Python | 2,617 | 77 | # python 3.7
"""Utility functions for logging."""
import os
import sys
import logging
__all__ = ['setup_logger']
DEFAULT_WORK_DIR = 'results'
def setup_logger(work_dir=None, logfile_name='log.txt', logger_name='logger'):
"""Sets up logger from target work directory.
The function will sets up a logger with `DEB... |
2a4432726d0aa0968b81dca4156d692979bf86d4c47d869af973d007ba6da374 | Python | 2,618 | 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... |
101eabdb08217ed01334240264d1fe61aa9f80873510efa1812c0ddcc8d9fad3 | Python | 2,620 | 78 | '''
Experiment with current pulses.
'''
from __future__ import print_function
from clampy import *
#from .utils import *
from init_rig import *
import utils
import current_pulses_analysis
from numpy.random import shuffle
from os.path import join
default_parameters = dict(
name = 'current pulses',
ntrials = 10,... |
86d969bb2f64d1115a71f9b637bdecdeb86953cc8956f1585613551fc4c1b822 | Python | 2,620 | 82 | import numpy as np
import time
import carpet
import carpet.lattice.triangular as lattice
import carpet.visualize as vis
## Parameters
# Geometry
nx = 6
ny = 6 # even number
N = nx * ny
a = 18 # [um] lattice spacing
## Initialize
# Geometry
L1, L2 = lattice.get_domain_sizes(nx, ny, a)
coords, lattice_ids = lattice.... |
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