sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
93d9cf41eb228c649dfe7b5994cc10dc371bb40db264d7e94502e4124057fa8b | Python | 10,450 | 275 | """ Object Context Network for Scene Parsing"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from models.baselines.segbase import SegBaseModel
__all__ = ['OCNet']
class OCNet(SegBaseModel):
def __init__(self, classes=2, aux=True, backbone='resnet50', oc_arch='base', pretrained_base=True):
... |
1f5097d3d965c7012823dfb00fd80d1cf7724f488c87163d29bede859858fd1d | Python | 10,455 | 255 | # 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... |
118d094dc8277a8aa7e5038180308e6b9de9404a649dc448817bd696b55d9746 | Python | 10,460 | 338 | #!/usr/bin/env python3
"""
Signal analysis module for phys2cvr.
Attributes
----------
LGR :
Logger
"""
import logging
from pathlib import Path, PosixPath
import numpy as np
import scipy.interpolate as spint
import scipy.stats as sct
from scipy.signal import butter, sosfiltfilt
LGR = logging.getLogger(__name__)
... |
465947b39f18497b157f36066cc4cb23e5140b0609a06b65d156b43efa704bc6 | Python | 10,475 | 315 | import os
import math
import numpy as np
import pandas as pd
from sklearn.model_selection import StratifiedKFold
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import scale
from sklearn.preprocessing import StandardScaler
from sklearn.decomposition import PCA
import pickl... |
2edd6765ff2e02daa717e10478c04c3e886766e4c7ac966125896e7d136ce6d4 | Python | 10,477 | 256 | import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import xavier_init
from mmdet.core import (build_anchor_generator, build_assigner,
build_bbox_coder, build_sampler, multi_apply)
from ..builder import HEADS
from ..losses import smooth_l1_loss
from .anchor_head imp... |
de7842405389c01d24cd599ac23da9bf430fdac65ed5bc45fdcd4e7ceae2a468 | Python | 10,479 | 261 | """
This class is the abstract base class for all handlers, i.e. objects
that "handle" model predictions. Specifically, handlers should store
the model predictions or scores derived from those predictions and eventually
output them according to a user-specified output format.
"""
import os
from abc import ABCMeta, abst... |
57b86fa34457884b283fe7fd69f3ba76259f52df2d0bc3f5a402031a2924ce1a | Python | 10,492 | 233 | # -*- coding: utf-8 -*-
"""Preview
Code for 'Inf-Net: Automatic COVID-19 Lung Infection Segmentation from CT Scans'
submit to Transactions on Medical Imaging, 2020.
First Version: Created on 2020-05-13 (@author: Ge-Peng Ji)
"""
# ---- base lib -----
import os
import argparse
from datetime import datetime
import cv2
... |
702447b0654d904d521c9eadd208fc95eaec8e8b5dc748d3878a1ebb6ccaa0ea | Python | 10,496 | 268 | import os
import sys
import subprocess
import shlex
import configparser
import argparse
import re
import pysam
import yaml
def argument_parser():
parser = argparse.ArgumentParser()
parser.add_argument('-c', '--config', default='config.yml')
args = vars(parser.parse_args())
config = args['config']
... |
2d02814d858d49b16c81dc5e62f0b2e82eb9acfb149d097b0b76948cb4dc9429 | Python | 10,499 | 265 | # 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... |
7ef244ecfa7e99bdf72deb012f3434b66a8615daf94b8341b29061853b417dba | Python | 10,502 | 233 | import warnings
from functools import reduce
from utils.helpers import *
from utils.plotting import plot_dataframe
from constants.enumerates import StatMeasures
STATISTIC_MEASURES = {
StatMeasures.MEAN: pd_mean,
StatMeasures.MEDIAN: pd_median,
StatMeasures.STANDARD_DEVIATION: pd_std,
StatMeasures.MINIM... |
974404558349443ebe42c20786dfa6e1b465fcc19d93fdcd988c7a64aaeb5bd4 | Python | 10,507 | 233 | # 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... |
86da25b297ab2ac94b29eda7bfa48d17abb24cb6bc47373582e6e656a22e0840 | Python | 10,516 | 272 | # 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... |
5e86548b6acba79479247fc1fcf6360f5d3290da938ce22c91e4be7bc09187d4 | Python | 10,517 | 241 | # -*- coding: utf-8 -*-
"""Preview
Code for 'Inf-Net: Automatic COVID-19 Lung Infection Segmentation from CT Scans'
submit to Transactions on Medical Imaging, 2020.
First Version: Created on 2020-05-05 (@author: Ge-Peng Ji)
Second Version: Fix some bugs and edit some parameters on 2020-05-15. (@author: Ge-Peng Ji)
""... |
c51227978918f388ff76dfca91d4302e14e3f09349d87cc4308ee0f7bcd679b3 | Python | 10,517 | 356 |
import os
import sys
import multiprocessing as mp
import numpy as np
import ndsvae as ndsv
from balloon_windkessel import balloon_windkessel
def normalize(w):
w = w/np.max(w)
return w
def tavg(x, window_len):
y = np.zeros((x.shape[0], x.shape[1], x.shape[2] // window_len))
for i in range(y.shape... |
36e8d4d0345294c9e8aea38622b6070b0bf3b727ab90bd1cb954704d876ad0e8 | Python | 10,522 | 241 | """Mask-out classes: name resolution, class recovery through the codec, dilation,
masked control videos and what the submit path does with them.
The fixtures are synthetic clips: a two-class semantic frame (road + car) encoded
with the real control encoder, so the tests exercise the actual palette recovery
rather than... |
8ebce88ca7ffee46cc74fc5595b90bdcf908d492504f3242e1105d2b5dcf6e26 | Python | 10,524 | 269 | import os
import sys
import shutil
import json, csv, glob
from tqdm import tqdm
from sklearn.model_selection import StratifiedShuffleSplit
import numpy as np
import random, re
sys.path.append("..")
def create_base_directory():
"""
The crawled folder has files divided by labels and dataset and all individual c... |
d0f3796e0f22123b2e9de545deba6b775565241933355f70b3080ddf0fd27086 | Python | 10,527 | 241 | # -*- coding: utf-8 -*-
"""Preview
Code for 'Inf-Net: Automatic COVID-19 Lung Infection Segmentation from CT Scans'
submit to Transactions on Medical Imaging, 2020.
First Version: Created on 2020-05-05 (@author: Ge-Peng Ji)
Second Version: Fix some bugs and edit some parameters on 2020-05-15. (@author: Ge-Peng Ji)
""... |
183e4933b1e7e7756b11f247c3405395a68302ebf177ecb651cb871c6ffe8f3a | Python | 10,529 | 315 | import types
import typing as tp
import pytest
from backend import training
from backend.app import App
class FakeModel:
def __init__(self, result:tp.Any=training.TrainingResult('completed')):
self.result = result
self.calls = []
self.cpu_calls = 0
self.stop_calls = 0
def st... |
50cedf96bb8e3e14ce06035050bd37dca90620889dca31edbfccf100a0d3dd33 | Python | 10,529 | 288 | ## Plots
import os
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import pandas as pd
import anndata
def plot_expressions_multiple(adata=None, X=None, obs=None, var=None,
logdir="", plot_tf=True,plot_target=True,**kwargs... |
e6cab0d13cf1f1b17b3b7489c82566a99b49c574c903d90dbe8bf07ee8e1fc88 | Python | 10,532 | 318 | import os
import math
import numpy as np
import pandas as pd
from sklearn.model_selection import StratifiedKFold
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import scale
from sklearn.preprocessing import StandardScaler
from sklearn.decomposition import PCA
import pickl... |
157d36ade46f9cd62e697cd0443270fbc66bc86e0ce80d0c740fdb02efad33f2 | Python | 10,539 | 254 | #!/usr/bin/env python3
"""
File: correlate_genes_with_cell_fractions.py
Created: 2022/05/03
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 ... |
a19cf8d9c3aa3d1201b37d379235bcb840fa424ff050414e95e2d7dc1cd6bac5 | Python | 10,542 | 286 | #!/usr/bin/env python
# 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>.
"""Open3D Lidar visualization example for CARLA"""
import sys
import argpars... |
946d80b501c45eee3b667af135fa3175ad2e799fc22a985bc3066d0b9b7d64c6 | Python | 10,544 | 254 | import paddle
import paddle.nn as nn
class FaceSwap(nn.Layer):
def __init__(self, use_gpu=True):
super().__init__()
self.swap_model = UNet()
def set_model_param(self, id_emb, id_feature_map, model_weight=None):
predict_model = BuildFaceSwap()
if model_weight is not None:
... |
bcc1ac5920277f4f8f9bb537dc8552eac140f46b348aa68dd6efa110285ddc6a | Python | 10,548 | 328 | # 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... |
08104c43743e8259476e687a2fa48bf3656f9ace141cd9c14b1f31bbfb29fc88 | Python | 10,553 | 329 | # Libraries
import yaml
import time
import json
import shutil
import numpy as np
import pandas as pd
from pathlib import Path
from types import MethodType
# Specific libraries
from sklearn.metrics import make_scorer
#from sklearn.impute import SimpleImputer
#from sklearn.impute import IterativeImputer
from sklearn.pr... |
6421e0270e99fc130b7340e55521b7cd19cab53585c8d4ad6f3c591dbd8f3f9f | Python | 10,554 | 251 | """
Copyright 2020 - by Jerome Tubiana (jertubiana@gmail.com)
All rights reserved
Permission is granted for anyone to copy, use, or modify this
software for any uncommercial purposes, provided this copyright
notice is retained, and note is made of any changes that have
been made. This softwar... |
21678bfb97cdc2f47c64273de72cf96e116e887939b047c9ded526979a53b1ae | Python | 10,558 | 222 | """CosmosClient / Job / Result against a real mock server (uvicorn subprocess).
Needs the ``carla-cosmos-server`` package importable (installed from
``../server``); skipped otherwise.
"""
import importlib.util
import json
import pytest
from carla_cosmos import Clip, ControlInput, CosmosClient
from carla_cosmos.clie... |
770d3dc4dac1aa163a203e2e93e81535c034fd05a05aad3ec71ab6b71e7cc673 | Python | 10,560 | 274 | #!/usr/bin/env python3
"""
File: plot_cell_fraction_per_disease_state.py
Created: 2021/11/29
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
th... |
0aba11a69591009534e331cc545992937d33ea66373d2784068613a041c0bcaa | Python | 10,565 | 283 | import pydicom
import SimpleITK as sitk
import sys
import numpy as np
import cv2
import matplotlib.pyplot as plt
import os
import scipy.stats as sci
import pickle
from tqdm import tqdm
def read_sitk(data_directory, CT_type):
# Read the original series. First obtain the reg file directory, then series file names u... |
24a2281dd389d9980df12fe363bd216bb27b74327b49181791c969fee1abc208 | Python | 10,570 | 224 | """Populate the image's Hugging Face cache from ``artifacts.lock`` (build stage).
python prefetch.py --image nano --dest /models/hf [--from-cache /mnt/hf-cache]... [--no-hash]
python prefetch.py --image nano --plan --max-layer-gb 40 # shard plan for tools/bake_weights.sh
For every file of every artifact ... |
3749bd76ad366f96c5b4fc4a5645fcb19772e29f63369a82746ba8d0f7195feb | Python | 10,570 | 298 | import itertools
import pandas as pd
import numpy as np
from utils import maskPeaks
def histogramFitParams(conditions, pColumns=None):
if pColumns == None:
#default columns
pColumns = ['ROI', 'id', 'N', 'Pr/mu', 'Stat', 'statistic', 'P', 'type']
_a = [conditions, pColumns]
... |
2541c67c9bc46cafba2cce1093d349a5250a61af7600013733153a5142631a64 | Python | 10,571 | 294 | import re
import torch
import numpy as np
import matplotlib.pyplot as plt
from torch.nn import functional as F
class Plot:
"""
Plot object.
This class contains functions for reading, processing, and plotting
results of the meta-training.
"""
def __init__(self, res_dir, meta_param_size, ... |
6384aacadb1c92df2fd395e4c36c7ac93473454dd2c41cebcbd2c670ecea8323 | Python | 10,574 | 366 | import statsmodels.nonparametric.kernel_regression
from KDEpy import FFTKDE
from multiprocessing import Pool, Manager
from scipy import stats
import numpy as np
import os
import pandas as pd
import statsmodels.discrete.discrete_model
from anndata import AnnData
import scipy as sp
_EPS = np.finfo(float).eps
def robus... |
31277782e05f30357ca78936dcdd5d73f600bf5b10023f991d6b8f635973a6a8 | Python | 10,577 | 338 |
# coding: utf-8
# In[50]:
from __future__ import print_function
feature_count = 39
predict_column = -4
#column_vector = [1] * feature_count
#target_cluster = 1
def train_model(column_vector = [1] * feature_count, target_cluster = 0):
plot = False
import tensorflow as tf
import keras
from pandas i... |
b9907a8ebfc5c39c0700cd314e9e97d2bc138ec1ddd668bda44b494fa178efa4 | Python | 10,579 | 285 | import torch
import torch.nn.functional as F
from torch.autograd import grad
from .differentiation import FiniteDiff
# Set warning filter to show each warning only once
import warnings
warnings.filterwarnings("once", category=UserWarning)
class BurgersEqnLoss(object):
"""
Computes loss for Burgers' equati... |
3faf6a603240a5146567dc826ad07657b5e05adab174e2a472a7980cee2c1d17 | Python | 10,584 | 237 | import tqdm
import ipdb
import argparse, sys; sys.path.append('../..')
import random as rand
import torch
from metrics import *
from graphxai.explainers import *
from graphxai.datasets import load_ShapeGGen
from graphxai.datasets.shape_graph import ShapeGGen
from graphxai.utils.performance.load_exp import exp_exists
f... |
7efcc06185b4c71e749cf5aa462e578deb046a4c59ad59fa0815f38e548ed440 | Python | 10,584 | 248 | import torch.nn as nn
import torch.nn.functional as F
from .CapNet import CapsNet
from mmcv.cnn import ConvModule, xavier_init
from mmdet.core import auto_fp16
from ..builder import NECKS
@NECKS.register_module()
class Caps_FPN(nn.Module):
r"""Feature Pyramid Network.
This is an implementation of paper `Fe... |
61b957a87e1aed6f911a3d979eff3cd590012cce1175c94b40baa4ff33d7f0ea | Python | 10,595 | 278 | import sys
import numpy as np
import torch
from torch.onnx.symbolic_opset9 import select, squeeze, unsqueeze
from mmcv.utils import deprecated_api_warning
from ..utils import ext_loader
ext_module = ext_loader.load_ext('_ext', ['nms', 'softnms', 'nms_match'])
# This function is modified from: https://github.com/py... |
48ba04f1d84142096b305950431d45b14dbb7b42540e7f5a5dbe012fcfd388bc | Python | 10,598 | 323 | # Eelbrain documentation build configuration file, created by
# sphinx-quickstart on Tue Mar 29 23:16:11 2011.
#
# This file is execfile()d with the current directory set to its containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All configuration values hav... |
61edf1a1cc889cef2338c2ccc33aa07b054992f00604b8746b00cf02691fe404 | Python | 10,600 | 276 | # Copyright 2021-2022 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... |
5f9694c9fad50ba3266c3b92544a6374a26c90d959117223916b06d343500387 | Python | 10,605 | 256 | """Loss Functions.
In this code, normalize loss by only dimension of units for gradient caliculation,
but normalize loss by dimension, num of sequence and sequence length when saving
loss due to comparing other conditions. In Reza-san's code, normalize loss by
dimension and sequence length when saving.
"""
import to... |
c201769c739675fcaff25b1ff85bb69ae21d6cfb21ceeef76056e221fcf90e6f | Python | 10,607 | 283 | #!/usr/bin/python
# -*- encoding: utf-8 -*-
import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision
from parsing_model.resnet import Resnet18
# from modules.bn import InPlaceABNSync as BatchNorm2d
class ConvBNReLU(nn.Module):
def __init__(self, in_chan, out_chan, ks=3, stride=1, p... |
dead317bcc47375bc2c3c411b2993f95e435eb7e176eca11425dbf526c0f7bce | Python | 10,610 | 207 | import os, time, json, sys, gc
import numpy as np
import nltk, pandas
import torch
from sklearn.metrics import f1_score, recall_score, precision_score, accuracy_score, classification_report
from scipy.sparse import csr_matrix, lil_matrix, save_npz, load_npz
from torch_geometric.data import Data, DataLoader, GraphSAINTR... |
6dfc6ead20bb6162f23bc43933dce44aa214488f670bb283b9e7495f884fd351 | Python | 10,612 | 238 | # 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... |
0d34c73032bdc369348598bce45122a6ee3074f0a2470df9b93475a136c0a1a8 | Python | 10,620 | 303 | ####################################################################################################
# Copyright (c) 2019 - 2022, 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 ... |
d4cee0b09ce7d957463709942caefff5b7d75824ed4634d6e656945bebd57d88 | Python | 10,622 | 200 | import argparse, time, datetime, shutil
import sys, os, glob, json, re
from pprint import pprint
import warnings
warnings.filterwarnings("ignore")
# from torchsummary import summary
import numpy as np
import pandas
import torch
import torchtext
from torch.utils.tensorboard import SummaryWriter
# from tensorboardX im... |
6ae1c58688d9ad92aba1b4de268ed6ada7b2b350f2d84ed1f1f32469ff92aa30 | Python | 10,623 | 263 | #!/usr/bin/env python3
"""Install the CARLA Python client (`carla`) into a chosen interpreter.
Commands:
detect what is installed, what sources exist, what matches
install [--source auto|local|pypi|egg] [--version X.Y.Z] [--dry-run]
install the client and veri... |
f9bea78d819f919d7d7127d4d95250957a0c1b362f0c34d1f2b365f97cfa22e4 | Python | 10,623 | 300 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Variational Animal Motion Embedding 1.0-alpha Toolbox
© K. Luxem & P. Bauer, Department of Cellular Neuroscience
Leibniz Institute for Neurobiology, Magdeburg, Germany
https://github.com/LINCellularNeuroscience/VAME
Licensed under GNU General Public License v3.0
"""
... |
771f309b706d3ceb569cea68282a5808e4ec57f421bb3279a9b67ed47c84ddd5 | Python | 10,624 | 214 | import streamlit as st
import pandas as pad
import numpy as np
from joblib import dump, load
from PIL import Image
import sklearn
import tensorflow as tf
from tensorflow import keras
import time
## TO DO #######
## PCA and TSNE representation
def main():
""" fonction principale de prédiction de c... |
bcff14f04bece7cc89e58d3fbef26634fefe6868cdca5ee40255bc8567d92026 | Python | 10,624 | 291 | import argparse
import ast
import glob
import os
import sys
import pandas as pd
import pathlib
import re
import subprocess
from collections import namedtuple
"""
Usage: python3 exome_reanalysis.py -f <input_sample.tsv> -d <absolute path to create directories>
Parses analyses request csv from Stager for exome re-anal... |
b9ede85a66ad360f1e819b48943828847c8029d195d7018f9186d3b6e3fa373a | Python | 10,627 | 237 | '''
collection of chemisorption models.
newns_anderson:
'''
import torch
import numpy as np
class Chemisorption:
def __init__(self, model_name, **kwargs):
# Initialize the class
if model_name == 'gnn':
self.model_num_input = 1
if model_name == 'newns_anderson_semi':
... |
d8e3866f08e6010dfcf4b9a0ebe4e46411b9fe1146f515c2d3c52f235c078601 | Python | 10,629 | 297 | import logging
import unittest
from copy import deepcopy
import yaml
from linkml.utils.schema_builder import SchemaBuilder
from linkml_runtime.dumpers import yaml_dumper
from linkml_runtime.linkml_model import SlotDefinition
from linkml_runtime.utils.introspection import package_schemaview
import oaklib.datamodels.on... |
bafa7f9a57afdb7f0549d0defa3e2c7cf9cc8ca7c30612c30ae118b7218c0e90 | Python | 10,633 | 281 | #!/usr/bin/python
# -*- encoding: utf-8 -*-
import torch
import torch.nn as nn
import torch.nn.functional as F
from .resnet import Resnet18
# from modules.bn import InPlaceABNSync as BatchNorm2d
class ConvBNReLU(nn.Module):
def __init__(self, in_chan, out_chan, ks=3, stride=1, padding=1, *args, **kwargs):
... |
1efc0c2346b33200f3c5a3ca183523bb71449ecf2cc603773b22161f68323ef6 | Python | 10,640 | 283 | import os
import os.path as osp
import cv2
import numpy as np
import time
from tqdm import tqdm
import torch
import torch.nn.functional as F
import torch.multiprocessing as mp
from engine.logger import get_logger
from utils.pyt_utils import load_model, link_file, ensure_dir
from utils.img_utils import pad_image_to_sh... |
12109b5b4c82d51b75d1938cba70b68cf52f8b42fbbda1ba00a66fa3be332716 | Python | 10,646 | 263 | import numpy as np
import math
import os
import random
import cv2
import matplotlib.pyplot as plt
import torch
import torch.nn.functional as F
import torchvision.utils as vutils
import pathlib
def gradient_loss_abs(gt, pd, ch=4):
filter1x = torch.tensor([[1., 2., 1.], [0., 0., 0.], [-1., -2., -1.]])
filter1y =... |
6e4992529e8b63b58b7349258e6bfc936492dc5b480bae982bf82ac0264d4502 | Python | 10,646 | 316 | import re
import tqdm
import numpy as np
from typing import List
from rdkit import Chem
from rdkit.Chem.QED import qed
from rdkit.Chem.GraphDescriptors import BertzCT
from rdkit.Chem.Fraggle import FraggleSim
from rdkit.Chem import Descriptors as desc, Crippen, AllChem, Lipinski
from drugex.training.scorers.interfac... |
056ad7260f06c36bb9b2241b064609bec731e098155200d78ed1cd1c669d7b67 | Python | 10,650 | 300 |
import torch
import torch.nn as nn
import torch.nn.functional as F
from networks import EqualLinear, ConvLayer, ResBlock
import math
class Bottleneck(nn.Module):
expansion = 4
def __init__(self, in_planes, planes, stride=1):
super(Bottleneck, self).__init__()
self.conv1 = nn.Conv2d(in_plan... |
7c1de45062f9078cc02d61fe691990936e2c840823c0e703d4ed577d413949ea | Python | 10,656 | 319 | #%% [markdown]
## Modeling the distribution of neural networks
# > An attempt to characterize the distribution of neural network parameters that are learned on the same task
# - toc: true
# - badges: true
# - categories: [pedigo, graspologic]
# - hide: false
# - search_exclude: false
#%%
# collapse
import os
import m... |
4abbb4bbb3e7d9d09eecab77661643298f7476faf9d7eb5e134b837038894386 | Python | 10,658 | 286 | import os
from unittest import mock
import threading
from sync import get_settings_from_env, server_factory
import json
import pytest
import requests
# Data sets passed to server
DATA_INCORRECT_CHILDREN = {
"parent": {
"metadata": {
"labels": {
"pipelines.kubeflow.org/enabled":... |
24d3b571a12d651dc619f5a9791afaafde2ff1788268962d1c6af81e93b1bac1 | Python | 10,659 | 490 | # %% [markdown]
# # THE MIND OF A MAGGOT
# %% [markdown]
# ## Imports
import os
import time
import warnings
import colorcet as cc
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.transforms as transforms
import numpy as np
import pandas as pd
import seaborn as sns
from anytree import LevelOr... |
75a0777e0420ff9f8fbb0d11466c9f9c9aa27be8ed54ddaff4ea9ef77ae1dd22 | Python | 10,662 | 261 | # 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... |
8fac7be60ba28aa77e591ce35efe2009f4cb1ff5ae807485bdb6c9f6164f064d | Python | 10,665 | 304 | #
# Deep Knowledge Tracing (DKT) Implementation
# Mohammad M H Khajah <mohammad.khajah@colorado.edu>
# Copyright (c) 2016 all rights reserved.
#
# How to use:
# python dkt.py dataset.txt dataset_split.txt
#
# Script saves 3 files:
# dataset.txt.model_weights trained model weights
# dataset.t... |
da061814e397363066c4efbd048b3e5127bc9670646761a68db3bf6ce4fdb9a1 | Python | 10,673 | 233 | """Live check that the path-traced lens sensors show freshly spawned actors completely from the
FIRST delivered frame, in synchronous mode.
Regression test for the "actors appear several ticks late" defect: the renderer compiles a new
ray tracing material pipeline in the background whenever an actor with materials it ... |
12d0acd1c8a62b097b981ae681b104901bfa914794ad36f44864f8905f4d0eea | Python | 10,677 | 190 | import ship_pairing_analysis
import collections
import pandas as pd
import inspect
import re
import os
import numpy as np
import itertools
import tqdm
import AIS_interp
import functions_basic_sak as funsak
from sklearn.cluster import DBSCAN
from scipy.interpolate import interp1d
import AIS_infer_mmsi
... |
65a92fa42dcdf87ccb3e59e519f0cefc7142985a8e27083a447f2c45bc2a42c9 | Python | 10,677 | 254 | # 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... |
3e05329211b21425f6e4e3227ad7c82c5de9d7d7353eed66047ad19000356a18 | Python | 10,678 | 286 | import os
from unittest import mock
import threading
from sync import get_settings_from_env, server_factory
import json
import pytest
import requests
# Data sets passed to server
DATA_INCORRECT_CHILDREN = {
"parent": {
"metadata": {
"labels": {
"pipelines.kubeflow.org/enabled":... |
0cdc0b4c671a84e4bb633f9f8c99d8e02854451b480b7a8c96b1eb5971895004 | Python | 10,679 | 286 | import os
from unittest import mock
import threading
from sync import get_settings_from_env, server_factory
import json
import pytest
import requests
# Data sets passed to server
DATA_INCORRECT_CHILDREN = {
"parent": {
"metadata": {
"labels": {
"pipelines.kubeflow.org/enabled":... |
541582eadaf017cacb1c150aa76d7ca236eb60ea19437d3b01f2340170f9100e | Python | 10,680 | 264 | """A module for querying the Finnish parliament open data API."""
import re
from typing import Any
from typing import Dict
from typing import List
from typing import Optional
from typing import Tuple
import requests
from lxml import etree
class Query:
"""Query template for fetching data from the API."""
def... |
c329c1feb0a5010f431e71072930d9c5e9710949976ceaee341eb722f0199215 | Python | 10,681 | 343 | # %%
import time
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from mpl_toolkits.axes_grid1 import make_axes_locatable
from giskard.utils import powerset
from src.data import load_maggot_graph
from src.io import savefig
from src.visualization import set_theme
from graspol... |
6898ff2cf14ff14a1d0b888c003834fc983a7db1eafd1744cf4a90ba8f37fa5d | Python | 10,682 | 322 | import torch_geometric.transforms as Transforms
from torch_geometric.data import Dataset
import numpy as np
from ..simulation.diffusion_models import generators, params_sampler
from ..simulation.traj_tools import *
from ..data.data import TrajData
import matplotlib.pyplot as plt
import numpy as np
from scipy.stats impo... |
7dce04647df25aea2eeeb3eac7ec52ed9e75b4da688f17f48839269bb662d940 | Python | 10,684 | 281 |
from nibabel import load
import os
import numpy as np
import scipy
import csv
import math
import scipy.stats
import glob
from scipy import ndimage
import copy
import random
#Function to get the indices of target value within given list
def findInd(List,Value):
return [i for i, x in enumerate(List) if x == Value]
... |
f0df27b45182e2bf3b44a7840bc8c1525574291738cd5767670055fe59e7992c | Python | 10,694 | 373 | import logging
from collections import ChainMap
from collections.abc import Callable
from pathlib import Path
from typing import Any
import numpy as np
from tqdm import tqdm # type: ignore[import-untyped]
from ppqm import chembridge, constants, units
from ppqm.calculator import BaseCalculator
from ppqm.chembridge im... |
705e92a3685ffd523bd556d7bc50348ceeccad5d006ad25a0e388ef6c4a12440 | Python | 10,700 | 249 | # %%
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from pymaid_creds import url, name, password, token
from data_settings import data_date, pairs_path
import pymaid
rm = pymaid.CatmaidInstance(url, token, name, password)
from contools import Celltype, Celltype_Analyzer, P... |
3f4a279126b447e26c953c89148e82f08e910552a2acee1ffc090ed97fb77a8e | Python | 10,701 | 284 | # 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... |
8054edda94b30c0653ef2b5616cb46d84df751abe6c0e7636719a34c3d81dd5f | Python | 10,704 | 321 | # -*- coding: utf-8 -*-
"""
Created on Wed Jul 7 18:47:46 2021
@author: Sleepymouse
"""
import glob
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import sys
import os
from scipy import signal
import csv
import math
import statistics
#mac
#path = glob.glob... |
c1c105b7e5c2fa5883516bf2bc05b588da5f45939d37f3fe281abca4579e7616 | Python | 10,707 | 268 | # Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and rel... |
283fb61f0555913bf91043f3e4f372ecb47bfa3f8094f0fed830140c07e8a75d | Python | 10,708 | 224 | import core.settings as CoreSettings
import user.usersettings as UserSettings
def gmx(bQuiet, bNocopyright, bNobackup):
command = "gmx"
if bQuiet:
command += " -quiet"
if bNocopyright:
command += " -nocopyright"
if bNobackup:
command += " -nobackup"
return command
def appe... |
abaaeae2480b67df0cf69876de26f4534583f61e0525229a7d94ac9da8497007 | Python | 10,710 | 255 | #!/usr/bin/env python3
"""Move the CARLA spectator camera, frame an actor, or follow one.
Commands:
actors [--filter PATTERN] list actors (basis for "the ego" etc.)
move --at X,Y,Z [--pitch P --yaw Y --roll R] set the spectator transform
look --view chase|first|top|front <selector... |
c588544f773b985bcd01f143c77c5a60b6131a3f1c0ab380bf760bbbbab8bb7e | Python | 10,713 | 301 | import argparse
import ast
import glob
import os
import sys
import pandas as pd
import pathlib
import re
import subprocess
from collections import namedtuple
from itertools import chain
"""
Usage: python3 genome_reanalysis.py -f <input_sample.tsv> -d <absolute path to create directories>
Parses analyses request csv ... |
15e45f371175619e151943446fcd52cd9ff142aacd657b58eb8f099224bdf2a6 | Python | 10,719 | 254 | #%%
from pymaid_creds import url, name, password, token
from data_settings import data_date, pairs_path
import pymaid
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import pandas as pd
import networkx as nx
from contools import Promat, Prograph
# allows text to be editable in Illustrator
plt... |
c4fd83a6822bc9643fc0911bf02f7dd782fa132b8bf86a08dfa0103c86e2a0bf | Python | 10,723 | 322 | # 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... |
48df16b215e819d472327c23086655722cfe7ede5fd3c3f5e1eedb3f70659343 | Python | 10,727 | 283 | from logging import Logger
import os
import pickle
from typing import Dict, List, Union
from pprint import pformat
import numpy as np
from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor
from sklearn.svm import SVC, SVR
from tqdm import trange, tqdm
from chemprop.args import SklearnTrainArgs
fro... |
901238916f4937b346d249b8d1496b1e07e2747e1e8493a06c3ad117be610ecb | Python | 10,728 | 249 | # 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... |
ede16e330dca089c8376c779f2df007088a10b3f96367875d111845a669dba27 | Python | 10,728 | 363 | # %%
import os
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from graspy.cluster import AutoGMMCluster, GaussianCluster
from graspy.embed import AdjacencySpectralEmbed
from graspy.plot import pairplot
from graspy.utils import pass_to_ranks
from sk... |
3124533d1d85af322dda1a79d3589877ca86a3c2fdbd54a00f6b09772d1a3931 | Python | 10,734 | 357 | #%% [markdown]
# # Density test
# Here, we compare the two unmatched networks by treating each as an Erdos-Renyi network
# and simply compare their estimated densities.
#%% [markdown]
# ## The Erdos-Renyi (ER) model
# The [**Erdos-Renyi (ER) model**
# ](https://en.wikipedia.org/wiki/Erd%C5%91s%E2%80%93R%C3%A9nyi_model... |
385edf4c3a44622cff7615cab8c2fe3507867d6fd03fe9a915ccc9cc798a0c5d | Python | 10,744 | 305 | """Different custom layers"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from maskrcnn_benchmark.layers.dcn_v2 import DCN
def conv3x3(in_planes, out_planes, stride=1, groups=1, bias=False, dilation=1):
"3x3 convolution with padding"
return nn.Conv2d(in_planes, out_planes, kernel_size=3... |
2a944dcf8e955efcfbd85a0a47dde7908b38fe396d6b938ef32371f9aa864540 | Python | 10,749 | 266 | #!/usr/bin/python3
from numpy import asarray
import numpy as np
from sklearn.tree import DecisionTreeClassifier
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score
from sklearn.metrics import precision_score
from sklearn.metrics import recall_score
from sklearn.tree import ex... |
53fffda6a19ae476fe4563b2a1317309cf0adda53a8de9fd120079fc5b1bae69 | Python | 10,753 | 400 | __author__ = "Jianfeng Sun"
__version__ = "v1.0"
__copyright__ = "Copyright 2023"
__license__ = "GPL v3.0"
__email__ = "jianfeng.sunmt@gmail.com"
__maintainer__ = "Jianfeng Sun"
from typing import Any, Dict, List, Tuple, Union
import gzip
import os
import re
import shutil
import urllib.request
def chainid(
prot... |
a7b960fa9b40b77f293b26e0f6c2957d49aa674454ef3e243bfb6c8d8ec74e46 | Python | 10,758 | 307 | """
Class for managing our data.
"""
import csv
import numpy as np
import random
import glob
import os.path
import sys
import operator
import threading
from processor import process_image,process_image_aug
from keras.utils import to_categorical
import tensorflow as tf
from keras_preprocessing import image
import random... |
ff1c666671e62959dd11ca1ca325b6be490bcea278654fc9d1a06e8709ea066c | Python | 10,760 | 275 | """
File: main.py
Created: 2020/10/08
Last Changed: 2020/10/27
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 ... |
79bc92f5bd1dcb8a568e1285df9d09b869c549784931851bcc78f47daba10c3c | Python | 10,763 | 250 | from typing import List, Literal, Optional, Callable
import torch
from torch import nn
import torch.nn.functional as F
from .channel_mlp import LinearChannelMLP
from .integral_transform import IntegralTransform
from .neighbor_search import NeighborSearch
from .embeddings import SinusoidalEmbedding
class GNOBlock(nn... |
3bea4f39f663685fb3d4982ebd761d7ab2fc0d43387cc1d9b3cca147a053771b | Python | 10,770 | 286 | # 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... |
63baaa506c7bc7af28b2a6a7949358f9cc9987e320d375ad99ecde64864d17ef | Python | 10,773 | 309 | """Cells for MTRNN.
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
torch.set_printoptions(threshold=10000)
class MaskMaker(object):
@classmethod
def make_mask_matrix(cls,
h_dim,
mode='',
z_dim=0,
... |
15b4456873ce3bc39d69d501362f2b5ee7cb07fe341d0de5b643953d4a40fba8 | Python | 10,775 | 276 | from __future__ import division
from builtins import range
from distutils.version import LooseVersion
import numpy as np
from scipy import ndimage
from scipy.ndimage import measurements
# skimage renamed the 'filter' module to 'filters' in 0.11 and will remove
# 'filter' in 0.13
# Currently (August 2016) 0.13 dev buil... |
3cf37893e12f71d9aa0aed807012b154cb245ab5496b07e78421010ba9aab5ba | Python | 10,783 | 273 | #%%
from pymaid_creds import url, name, password, token
import pymaid
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import pandas as pd
from contools import Promat, Celltype, Celltype_Analyzer
import navis
# allows text to be editable in Illustrator
plt.rcParams['pdf.fonttype'] = 42
plt.rc... |
7ac3b2f1b9d93f9164257a9eb813bd50288ca3428defca533522eb64e025a4f9 | Python | 10,792 | 258 | from mmdet.datasets import PIPELINES
import copy
import cv2
import mmcv
import numpy as np
from ..builder import PIPELINES
from .compose import Compose
_MAX_LEVEL = 10
def level_to_value(level, max_value):
"""Map from level to values based on max_value."""
return (level / _MAX_LEVEL) * max_value
def enh... |
1a040556f32d8054c9af5094b271eb4ba7f3f92a8740deaae870054c02ef4615 | Python | 10,799 | 168 | # Form implementation generated from reading ui file 'picachooserTemplate.ui'
#
# Created by: PyQt6 UI code generator 6.6.0
#
# WARNING: Any manual changes made to this file will be lost when pyuic6 is
# run again. Do not edit this file unless you know what you are doing.
from PyQt6 import QtCore, QtGui, QtWidgets
... |
68b11a87940935eaa9bcb57c0105c29a383b91702b47535dcc7835aa386ce957 | Python | 10,799 | 404 | import torch
import networkx as nx
from torch_geometric.data import Data
from torch_geometric.utils import k_hop_subgraph, subgraph
from torch_geometric.utils.convert import to_networkx
# MUTAG notation: [C, N, O, ...]
# MUTAG notation:
# 0 C
# 1 O
# 2 Cl
# 3 H
# 4 N
# 5 F
# 6 Br
# 7 S
# 8 P
# 9 I
# 10 Na
# 11 K
# 1... |
a52c256c5f707c57f961c967b35b9a2d4b403b82a23b7dde6540fa4d906f45d8 | Python | 10,802 | 252 | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class DilatedParallelConvBlockD2(nn.Module):
def __init__(self, in_planes, out_planes):
super(DilatedParallelConvBlockD2, self).__init__()
self.conv0 = nn.Conv2d(in_planes, out_planes, 1, stride=1, padding=0, dilation=1... |
4ef4c990d74663a445ac7132c07ccf25dbee4d8fd25eb589d8551006907d7dd2 | Python | 10,804 | 280 | # 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... |
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