sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
97d6b19ae4799856ed77a11737e1a9de8de53580e40408ba4c025ce67145c635 | Python | 2,339 | 74 | '''
Plots
'''
from matplotlib import cm
from mpl_toolkits.axes_grid1.anchored_artists import AnchoredSizeBar
import matplotlib.pyplot as plt
from brian2 import second, ms
from pylab import *
__all__ = ['plot_curves', 'prepare_panel', 'scale_bar', 'plot_fits']
def plot_fits(data, fits, metrics=None, vars=None):
''... |
abf43a13641e00feddf6dfc51cc15c2c0739dda9715cf29424f0a9e657faab3d | Python | 2,339 | 72 | """Cortical surface meshes.
Mid-thickness, inflated and very inflated surfaces for the left and right
hemispheres, on the 32k_fs_LR grid. These are used to render brain maps on the
cortical surface, either with HCP Workbench (see
:py:mod:`osl_dynamics.utils.workbench`) or directly from the vertices and
triangles retur... |
c6578ccd629c2307ed5070a94677ddc9d01231000c0c76c6fe60ec394ac1e859 | Python | 2,340 | 61 | import json
import logging
import unittest
from oaklib.implementations.pronto.pronto_implementation import ProntoImplementation
from oaklib.resource import OntologyResource
from oaklib.utilities.graph.relationship_walker import walk_up
from oaklib.utilities.obograph_utils import as_multi_digraph, graph_as_dict, graph_... |
15dee8d3d8710c82980e6876a7ea626b0795b06047d43104b35f95a4f5611f77 | Python | 2,342 | 72 | # Built-in
import os
from pathlib import Path
# Third-party
import pandas as pd
import pytest
# Local
from cxsystem2.core.exceptions import ParameterNotFoundError
from cxsystem2.core.tools import change_anat_file_header_value
@pytest.fixture
def setup_and_teardown():
# Create a dummy CSV file
dummy_data = [... |
7bab0ebf6fc7c7395d1a9a550308ad4c81805267a758f38472001922c97cfa45 | Python | 2,342 | 77 | #%%
import os
try:
os.chdir('/Volumes/GoogleDrive/My Drive/python_code/connectome_tools/')
print(os.getcwd())
except:
pass
#%%
import sys
sys.path.append("/Volumes/GoogleDrive/My Drive/python_code/connectome_tools/")
import pandas as pd
import numpy as np
import connectome_tools.process_matrix as promat... |
8b319d4559c333f5ec5a1fd39fb76916ac7fbb8fbcb4f1f5ac60f904564ae1b7 | Python | 2,343 | 63 | # 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... |
c896ee123d52526010f124c7aae1a94d8593880f2d606439d294b4e6736780d8 | Python | 2,343 | 90 | import csv
import os
import sys
def feature_to_index(cases, column_nb, offset=0):
feature_set = set()
for case in cases:
if len(case) > column_nb:
feature_set.add(case[column_nb])
l = list(feature_set)
index = {}
i = 0
for f in l:
if f != '':
index[f] = i... |
efc3e3a3ebec5cb5e9a55177c30222b2a1794d1c46d4d18eb4d3555a236c7ade | Python | 2,343 | 57 | ####################################################################################################
# Copyright (c) 2019 - 2021, 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 ... |
0052962a791706d450961b8acc8362ad1e2c34240bacd01a4efacad9e5714f9b | Python | 2,344 | 90 | import csv
import os
import sys
def feature_to_index(cases, column_nb, offset=0):
feature_set = set()
for case in cases:
if len(case) > column_nb:
feature_set.add(case[column_nb])
l = list(feature_set)
index = {}
i = 0
for f in l:
if f != '':
index[f] = i... |
528b4cb613921530e552fe5749bfc8a3ef2238ab41e43250a9f2d649cdd2155c | Python | 2,344 | 61 | from utils import Config
import nltk
class DataLoader:
def __init__(self, config: Config):
self.config = config
self.articles = {}
self.original_articles = {}
self.vocabulary = {}
self.frequency = {} # dict : keys Words et values : list of files where the words are from
... |
9c30d9f12787a9ba3a85eb202b79249c767ef334ce227909dba92356941308dd | Python | 2,344 | 58 | rule align_trome2trome:
input:
query='refs/{query}-all.fa.gz',
target='refs/{target}-all.mmidx'
output: 'refs-filtering/{query}-{target}.bam'
threads: 40
run:
if wildcards.query == wildcards.target:
shell('touch {output}')
else:
shell('minimap2 -a ... |
00bfa940cc34cd665d3c1072d3100c803a55ae7faf8ea562250902b7a9cad010 | Python | 2,346 | 89 | 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.datasets import load_drosophila_left, load_drosophila_right
from graspy.utils import binarize, symmetrize
from src.models import select_dcs... |
0b4f8844ba2f4ab583ca7f9d0d9e8bd33e6035435ade7c0e474003977cbdfd8e | Python | 2,346 | 89 | 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.datasets import load_drosophila_left, load_drosophila_right
from graspy.utils import binarize, symmetrize
from src.models import select_dcs... |
83c025cda5bdb09136e6918e58910d7bc887616a0540fc22d69eeef049142bc3 | Python | 2,346 | 71 | """ Module for computing features """
import re
from collections import Counter, defaultdict
from typing import List, Optional, Tuple, Type
import functools
from spacy.tokens.token import Token as SpacyToken
import scicite.constants as constants
from scicite.constants import CITATION_TOKEN
from scicite.resources.lexi... |
c87d3260d6a21696146de0e5d86f6876b9c5ae8713bbcbd70a8f7df5db26c4b7 | Python | 2,346 | 73 | import pandas as pd
import numpy as np
import torch, torchvision
import torch.nn as nn
from torchvision import transforms
from PIL import Image
from torch.utils.data import Dataset
import argparse
from functools import partial
import moco.builder_infence
import moco.loader
import moco.optimizer
import torchvision.model... |
8f0e693eb4a74c623ed8ed01b112da4fbfcb0ccdca8ea244d58b55fc39b5880b | Python | 2,347 | 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... |
b465699033a94ad3e40ab8555b65d20d1e33335ac58aaa4c15eb1db8a1751308 | Python | 2,347 | 81 | __author__ = "Jianfeng Sun"
__version__ = "v1.0"
__copyright__ = "Copyright 2023"
__license__ = "GPL v3.0"
__email__ = "jianfeng.sunmt@gmail.com"
__maintainer__ = "Jianfeng Sun"
from typing import List
import pandas as pd
from tmkit.seqnetrr.combo.Param import Param
from tmkit.seqnetrr.combo.Separation import Separa... |
b0a58038c04d99a241ff0dc2a51e2a3fdf34c3dbe8ee1a9af6be0dd5398d4f19 | Python | 2,348 | 81 | """
Original source: https://www.datacamp.com/community/tutorials/matplotlib-3d-volumetric-data
"""
import matplotlib.pyplot as plt
import numpy as np
def update_title(title, ax, total_slice):
title_str = f' << Prev (J) - {viewer_title} {ax.index}/{total_slice-1} - Next (K) >>'
ax.set_title(title_str)
de... |
bd7ebeb69d283f433739b2e0aa878f64121d562a82dcb08853ca069b72ee5889 | Python | 2,348 | 54 | 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... |
ffe8d554e01f91f7ec281477b409c653dd061b11afc78ce5fae3f0f1127261a8 | Python | 2,348 | 89 | import csv
import os
import sys
import data_processing
def feature_to_index(cases, column_nb, offset=0):
feature_set = set()
for case in cases:
feature_set.add(case[column_nb])
l = list(feature_set)
index = {}
i = 0
for f in l:
if f != '':
index[f] = i + offset
... |
2f86f2e6e89a204b3be95c44daca3c9cafc771b1270d9fdf15efe0051e7c39af | Python | 2,349 | 51 | ####################################################################################################
# Copyright (c) 2019, 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 softwar... |
880b7b3455078b1107d6442bf5f8034db80d3800f350120e6f572170eb4be4e3 | Python | 2,349 | 61 | import tqdm
import argparse, sys, os
import random as rand
import torch
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
from graphxai.gnn_models.node_classification.testing impo... |
64536df5cf7aa13ebff355fe270bff70708ddbe46941b3895e550c9a34b583eb | Python | 2,350 | 39 | """Vehicle light states, front and rear 3/4 views at night (Cinematic)."""
import os, sys, queue, math
import numpy as np, carla
sys.path.insert(0, os.path.dirname(__file__)); import scene
OUT = sys.argv[1]; MODEL = sys.argv[2] if len(sys.argv) > 2 else "vehicle.lincoln.mkz"
os.makedirs(OUT, exist_ok=True)
c, w = scene... |
c0e0d6b198e03fbcae14a0fa27a71734c608d55c65963790d7fffbc97048b9a3 | Python | 2,350 | 76 | import torch
from torch import nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from maskrcnn_benchmark import _C
# TODO: Use JIT to replace CUDA implementation in the future.
class _SigmoidFocalLoss(Function):
@staticmethod
def forward(ctx, logits, targets, gamma... |
fa1b49be0915dc5d71cf5fb910609b7f2daea0fbf086402a22d1d5e0cc80f068 | Python | 2,350 | 72 | # 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
import os
import sys
from datetime import datetime, timezone
# -- Path setup ---------... |
0bec889f56e73ba754bb4a303a319172aa0b2e7b44f3a819102e66efd0d737fc | Python | 2,351 | 60 | # 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... |
c414cf59396dd5bd92d1d828d1b877528c1cf89b6845970374cf36abeb5491ef | Python | 2,351 | 60 | # 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... |
ff3fe9557ac1f51d6e0257de95973ee9d7fb8a05814462b5c9fa994e57203739 | Python | 2,352 | 74 | """
DeepSEA architecture (Zhou & Troyanskaya, 2015).
"""
import numpy as np
import torch
import torch.nn as nn
class DeepSEA(nn.Module):
def __init__(self, sequence_length, n_genomic_features):
"""
Parameters
----------
sequence_length : int
n_genomic_features : int
... |
4ae900a4a4b2ef9d50d525977abfada59f5da130792abd7d34c2c1c9e1b0edf6 | Python | 2,356 | 96 | import contextlib
import tempfile
from linkml.generators import PythonGenerator
from linkml_runtime import SchemaView
from linkml_runtime.dumpers import yaml_dumper
from linkml_runtime.loaders import yaml_loader
from linkml_runtime.utils.compile_python import compile_python
from src.oaklib.utilities.subsets.value_set... |
6b37f859e1e267913123eafadb3e0eb492947ec640d6ca0caaad17589b7fd973 | Python | 2,356 | 55 | # Author: Christian Brodbeck <christianbrodbeck@nyu.edu>
"""
.. _exa-impulse:
Impulse predictors for epochs
=============================
:func:`epoch_impulse_predictor` generates predictor variables for reverse
correlation in trial-based experiments with discrete events. The function
generates one impulse per trial, ... |
c6cc470e5dac9b8f2bd059f0fe62ff87505102d9bd521a6eeec759c1aaa0b373 | Python | 2,360 | 73 | import os
if os.getcwd().endswith("UnitTests"):
os.chdir("..")
import unittest
from Classes.QueryParser import QueryParser
class QueryParserTest(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.parser = QueryParser()
def test_results_are_distinct(self):
result = self.parse... |
5479695936c24600db9f54a2746ee05e954bfd7704a457d6cf06f712f4d5e628 | Python | 2,361 | 68 | #!/usr/bin/env python3
"""
File: matrix_preparation.py
Created: 2020/10/08
Last Changed: 2020/10/20
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 ... |
66f55f8a2e99f13c864828f48725bd453ff8a78d1bde3d6a1b3ab139470f6c7c | Python | 2,361 | 94 | # This script is part of navis (http://www.github.com/schlegelp/navis).
# Copyright (C) 2018 Philipp Schlegel
#
# 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... |
b73e01b2a5a9eb42a98763468235aca779de07580a94f9d5009d8a97b39cd033 | Python | 2,361 | 69 | # 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... |
d752fa83b22f6b6cf18748095254e8a036b104318cf56e13aab8f3e1900135a4 | Python | 2,362 | 61 | # 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... |
d96ff47c0e1e415bee12d3a383d68ff990275bb0a0007da0ba8ac26c54d6a479 | Python | 2,362 | 84 | #%%
import datetime
import time
import pandas as pd
from giskard.flow import rank_signal_flow, signal_flow
from src.data import join_node_meta, load_maggot_graph
t0 = time.time()
#%%
print("Loading data...")
mg = load_maggot_graph()
mg = mg.node_subgraph(mg.nodes[mg.nodes["selected_lcc"]].index)
mg = mg.sum
index ... |
47a0c52f7464fc95d46615ebf2081bfba4d315053713a733a4ac6c22479e76ab | Python | 2,363 | 55 | # %%
#
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import networkx as nx
from joblib import Parallel, delayed
from tqdm import tqdm
from contools import Analyze_Nx_G, Prograph, Promat, Celltype_Analyzer
from pymaid_creds import url, name, password, token
from data_sett... |
688a3d88221f60859f390464b35eeb58df6e1acdffd1702bfb87c0d0b2440ab5 | Python | 2,363 | 81 | from functools import cache
from class_resolver import ClassResolver
from oaklib.parsers.association_parser import AssociationParser
from oaklib.parsers.gaf_association_parser import GafAssociationParser
from oaklib.parsers.gencc_association_parser import GenCCAssociationParser
from oaklib.parsers.hpoa_association_pa... |
ed53d009fbbfe2a9ce00b381db96640d243829c1f4ae1ca8f5349afab5a164b1 | Python | 2,364 | 69 | """
extractPDB.py: Extract selected chains from a PDB and save the extracted chains to an output file.
Pablo Gainza - LPDI STI EPFL 2019
Released under an Apache License 2.0
"""
from Bio.PDB import *
from Bio.SeqUtils import IUPACData
PROTEIN_LETTERS = [x.upper() for x in IUPACData.protein_letters_3to1.keys()]
# Exc... |
b02fe67a482c9a665db21bf211271f42afe95566dfa81790f782d006b042e7e4 | Python | 2,365 | 97 | from numpyro.infer import MCMC, NUTS
from numpyro.infer import Predictive
from scipy.stats import zscore
import numpy as np
from typing import Optional
mcmc_defaults = {"num_warmup": 1000, "num_samples": 3000}
def run_inference(
x: np.ndarray,
y: np.ndarray,
use_model,
feature_indicator: Optional[np.... |
9a91d79b4a24386947cc6135f3f15f69d33de7d442bc8867abec6ec7f1be8934 | Python | 2,366 | 62 | # Copyright 2019 by Gorka Munoz-Gil under the MIT license.
# This file is part of the Anomalous diffusion challenge (AnDi), and is
# released under the "MIT License Agreement". Please see the LICENSE
# file that should have been included in the repository containing the file
# (github.com/gorkamunoz/ANDI)
import numpy... |
bc34cf38e03e665fa95e2442c377865e1576f4537d6a29cdc3a92bc67ecff0f9 | Python | 2,366 | 89 | # Copyright (c) Open-MMLab. All rights reserved.
import functools
import torch
def assert_tensor_type(func):
@functools.wraps(func)
def wrapper(*args, **kwargs):
if not isinstance(args[0].data, torch.Tensor):
raise AttributeError(
f'{args[0].__class__.__name__} has no att... |
e84b5e1f7d6221dc63d037a12da9cd1e9450b0c922b131b80f0ce31dd664bcd3 | Python | 2,366 | 60 | # 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... |
947e6d2c9726012ce0ebee5214c52b75a5719e6ce5fb3ad78dd1667545fa63c5 | Python | 2,367 | 58 | from utils import Config, load_glove_model
from utils.ArticlesProvider import ArticlesProvider
from utils.decomposition import Decomposition
import numpy as np
import torch
class GloVeDecomposition(Decomposition):
def __init__(self, config: Config, articles: ArticlesProvider):
super().__init__(config, art... |
ad1536f3b5432ecf0372e0cd8a30354e0fbedb553d3ed3be41dd48caef5ff1df | Python | 2,367 | 74 | # Copyright 2024 Chen Liang
#
# 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 in writing, ... |
43bb375d26f48ba007ec2aaafc0a01eca38fcba6902f97ceab615a33259ac2b2 | Python | 2,368 | 91 | """
Copyright Dejan Kostyszyn 2019
This method prints all key paths that are read
during reading the data. This method only exists
for controlling the functionality of the
ReadData.py
"""
import ReadData as rd
from options.test_data_reading_options import ReadOptions
import time, utils
from os.path import join
import... |
8ca2f671ada16107cd7c2d99700112254fa3dc97da779de711ec8fdc5b43f677 | Python | 2,368 | 63 | import torch
import numpy as np
from torch_geometric.loader import DataLoader
import sklearn.metrics as metrics
from sklearn.metrics import f1_score, precision_score, recall_score
def load_data(dataset, mol_num):
assert mol_num < len(dataset)
train_dataset = dataset[:150]
test_dataset = dataset[150:]
... |
74f4f189b09d9dfadd1c1a74c454ea6cc765c6027f397eab0c3c0a4356500e93 | Python | 2,369 | 74 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
For segmeinting 3D image stacks to 2D images. This would help to skip
a project step for analysing movies.
Created on Fri Apr 3 15:27:27 2020
@author: smithm3
"""
import click
import unetsl
import unetsl.model
import unetsl
@click.group(chain=True)
def three_to_tw... |
9246e096c3b98f07f1bf128b042bc3c2179dca4dcb2afd3d9dace7c9aa3e22b0 | Python | 2,369 | 75 | import numpy.testing as npt
import numpy as np
import nibabel as nib
import os.path as op
import AFQ.data.fetch as afd
import AFQ.recognition.curvature as abv
import AFQ.recognition.utils as abu
import AFQ.recognition.cleaning as abc
from dipy.io.stateful_tractogram import StatefulTractogram, Space
import dipy.data.... |
700f664a106e44bc47ee76a302573aa7425224c163085c3ba4c8ca1b6d0c04b4 | Python | 2,370 | 80 | import numpy as np
from cgtasknet.tasks.reduce import CtxDMTaskParameters, DMTaskParameters, DMTaskRandomModParameters, GoDlTaskParameters, \
GoDlTaskRandomModParameters, \
GoRtTaskParameters, \
GoRtTaskRandomModParameters, GoTaskParameters, GoTaskRandomModParameters, MultyReduceTasks, RomoTaskParameters, \... |
cae6feab1bb4ad4f14585877d05244bed3271726a20806baf2b53b37d52d080b | Python | 2,372 | 69 | # 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.poolers import Pooler
from maskrcnn_benchmark.layers import Conv2d
from m... |
b8c3d704512bbee1a3f6131fe1265718729882a8ca1a9c9f1daec3b821bb7066 | Python | 2,373 | 55 | ########################################
# UNCLASSIFIED #
########################################
"""
This generate_mock_detections.py file is used to create mock YOLO detection
output from AIS messages. This will be used to test the functionality of
ship pairing code.
"""
import os
... |
87af59c2828f413a79851ffc9adc33f39e7d09164f3eb03c57f23b83d4458a5b | Python | 2,374 | 89 | from dolfin import compile_cpp_code as compile_cpp
from dolfin import Mesh
code="""
#include <dolfin/mesh/Mesh.h>
#include <dolfin/mesh/MeshEditor.h>
#include <dolfin/mesh/CellType.h>
#include <dolfin/mesh/MeshTopology.h>
#include <dolfin/mesh/MeshConnectivity.h>
#include <dolfin/mesh/MeshValueCollection.h>
#include ... |
b5ae38ad2dd71584796a92ae243a0e0691cbb2344db5a21db8c2cd90adecd7d7 | Python | 2,374 | 58 | # 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... |
c4eb7c26f88e549103860ec3f61d81b80d490d95a1957fd1f5404c46932e353a | Python | 2,374 | 71 | import argparse
from tqdm import tqdm
import numpy as np
import pandas as pd
from lib import skel, compartment, u
def main(cellidfilename, mitotoskelfilename,
outputfilename, branchtype="full"):
ids = u.readids(cellidfilename)
mitotoskeldf = compartment.readmitotoskel(mitotoskelfilename)
celld... |
e61a699deb23639eaa9e6a5792c975ed8223d7bdae3b6e8af7bb74a7d6be718b | Python | 2,374 | 68 | # coding=utf-8
"""
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 a... |
a4bb1af9a2840650ff6adf0093d586250b357dcb243d10612ae828c155aca751 | Python | 2,375 | 71 | import argparse
import logging
import pandas as pd
from pathlib import Path
import seaborn as sns
from matplotlib import pyplot as plt
from cenfind.core.data import Dataset
logging.basicConfig(level=logging.ERROR)
def register_parser(parent_subparsers):
parser = parent_subparsers.add_parser(
"analyse",
... |
0117e73e15ec607385b60313a831eac11a9647b22fa8cf101070b23f37865d98 | Python | 2,377 | 66 | #!/usr/bin/env python3
#
# Expansion Hunter Denovo
# Copyright (c) 2017 Illumina, Inc.
#
# Author: Egor Dolzhenko <edolzhenko@illumina.com>,
# Sai Chen <schen6@illumina.com>
# Concept: Michael Eberle <meberle@illumina.com>
#
# This program is free software: you can redistribute it and/or modify
# it under the ... |
539dc631a69103d15180ce00d1b7a9ca94486d0c2ff745976adfa654f6d2fa85 | Python | 2,377 | 75 | import pandas as pd
from biopandas.pdb import PandasPdb
def create_atom_label(row):
residue = row['residue_name']
atom = row['atom_name']
if atom == 'OXT':
return '{}_{}'.format(residue, 'O')
else:
return '{}_{}'.format(residue, atom)
def create_atom_id_raw(chain_id, residue_number,... |
ff1a2282e5094bc44c2c43a56a07bb01bc64c92b43dfeef846692e9f14eff8df | Python | 2,377 | 94 | from builtins import object
# Unit tests for sima/ROI.py
# Tests follow conventions for NumPy/SciPy available at
# https://github.com/numpy/numpy/blob/master/doc/TESTS.rst.txt
# use assert_() and related functions over the built in assert to ensure tests
# run properly, regardless of how python is started.
from numpy.... |
0732596b5e89e12c4c62d2c00c66577d889deec84b8c74419d4f1a81d2eb12a9 | Python | 2,378 | 85 | 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=[
os.path.join(module_path, 'fused_bias_act.cpp'),
os.path.join(module_path, 'fused_bias_act_kernel.... |
1b4436c0137a0c47bdfdb56059f1086f105b41f248c87a99a0c6c2566e451591 | Python | 2,378 | 68 | import argparse
import descarteslabs as dl
import geopandas as gpd
from scripts import query_patch
DL_SYSTEM_PARAMS = {
'image': ('us.gcr.io/dl-ci-cd/images/tasks/public/' +
'py3.8:v2020.09.22-5-ga6b4e5fa'),
'cpus': 1,
'maximum_concurrency': 1,
'memory': '8Gi',
'retry_count': 4,
... |
252e9dd2a08edb46ec98bf85013aba3eb38000ebfade566cddc273afa74ec2f2 | Python | 2,378 | 64 | import pandas as pd
import numpy as np
from rl_analysis.util import count_transitions
from rl_analysis.info.util import dm_entropy
# takes a syllable-RLE time-series and spits out the number of
# times the current syllable happens over the next N timesteps
#
# e.g. if 45 50 45 45 37 37 50 happens, then
# counts_5 wou... |
49e8783358c500d5f9fabbbec5217abec2556341e1c0bfe152083b980c55c719 | Python | 2,380 | 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... |
ad7f8430daab99ce306f4fefd1c989bd5fe398f40759d00afcea03d859afe41c | Python | 2,381 | 63 | #!/usr/bin/env python
# coding=utf-8
# Copyright 2021 Huawei Technologies Co., Ltd
#
# Licensed under the BSD 3-Clause License (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://opensource.org/licenses/BSD-3-Clause
#
# Unless requi... |
611759e6b43515e03de1ca81a2d1c68f9b86c09ce6d9e81c3727a03327a5eee5 | Python | 2,382 | 104 | """Group-average evoked response analysis.
"""
from sys import argv
if len(argv) != 3:
print("Please pass the number of states and run id, e.g. python 6_evoked_response.py 8 1")
exit()
n_states = int(argv[1])
run = int(argv[2])
#%% Import packages
import os
import mne
import pickle
import numpy as np
from ... |
1915c780bfc9513b195d30273bde2445337cdf11b743dd635c7420e23a501893 | Python | 2,383 | 90 | # libraries
import pandas as pd
import numpy as np
from sklearn import preprocessing
import tensorflow as tf
from tensorflow.keras.models import Model, load_model
from tensorflow.keras import optimizers, regularizers
from tensorflow.keras.layers import Dense, Dropout, BatchNormalization, Conv1D, Flatten, Input, Leaky... |
4561b026e1029154ec76f55986b0713da86d274a06b85ff686b063d1c5ce835c | Python | 2,383 | 82 | """Wakeman-Henson: Preprocessing."""
from pathlib import Path
import matplotlib
matplotlib.use("Agg")
import mne
from osl_dynamics.meeg import parallel, preproc
# ----------------------------------------------------------------------------
rawdir = Path("data/ds117")
outdir = Path("data/preproc")
log_dir = Path("lo... |
ccd5ebf2810517688ce0b317262ccb94a75d0c69ed4e59369528ff7170340d8c | Python | 2,383 | 90 | import json
import os
import urllib
import urllib2
import subprocess
import time
class SPARQLDB:
def __init__(self):
self.EndPointUrl = "http://localhost:3030/NeuroMLOntology/query"
self.ServerUrl = "http://localhost:3030/"
# Check if fuseki server is up
self.CheckIfUpAndStar... |
8cb926752ef76ead349e30eb807e861ba04a0b671a54c924a5eed1b4ef49b918 | Python | 2,384 | 55 | # 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... |
0b5ed78058c6421b3a60ace32c560b25280d520bdd784b5dc8b516a8bd1f7195 | Python | 2,386 | 82 | 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... |
6ae9165de27de5062cab3b7999ce0e9b7a297579a0545e47df545da6476c6355 | Python | 2,386 | 70 | import os
import numpy as np
import pandas as pd
from PIL import Image
from torch.utils.data import Dataset
class NABirds(Dataset):
base_folder = "nabirds"
def __init__(self, root, split="train", transform=None):
assert split in ["train", "val", "test_unseen"]
super(NABirds, self).__init__(... |
a4baaad6a6a1848cbcb31bc6061fae977d804fc2a46f54ecfc508cd8e1700577 | Python | 2,386 | 63 | # 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... |
f84f5b9cee83e49e7a3eb9e8d6efe285e3712b084b12db79a7f1c9e1725f1948 | Python | 2,387 | 52 | #%%
from pymaid_creds import url, name, password, token
from data_settings import pairs_path, data_date_A1_brain
import pymaid
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from datetime import date
from contools import Promat, Celltype, Celltype_Analyzer, Analyze_Nx_G
#... |
5044631062ad0ff23b2981c9580e25ed7e97d14fe1a308e8d18b1717a205beec | Python | 2,392 | 25 | """Run in a fresh Unreal Python commandlet to check saved assembly references."""
import json,os
from pathlib import Path
import unreal
P=Path(os.environ.get('CARLA_MODEL3_WORKDIR',Path(__file__).resolve().parents[4]/'artifacts/tesla-model3'))
root='/Game/Carla/Static/Car/4Wheeled/TeslaModel3UE58';path='/Game/Carla/Blu... |
3534b460b832d44edb9a65ae3ab731eefa227ac4f6e35bf84e2168c02e957554 | Python | 2,393 | 64 | # This script is part of navis (http://www.github.com/schlegelp/navis).
# Copyright (C) 2018 Philipp Schlegel
#
# 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... |
3aec75906cdf37a33c7501cb88351056e5d91648a2801b6d36b9b141a49c3f29 | Python | 2,393 | 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... |
67fa2f3640ba5d6afbbfd81022afd926d4596d6c664e6eb15017f31352814418 | Python | 2,393 | 73 | import random, os
import torch
import numpy as np
import pandas as pd
from pprint import pprint
from torch.utils.data._utils.collate import default_collate
import torch.nn.functional as F
import SimpleITK as sitk
from torch.cuda.amp import autocast
def seed_torch(seed):
random.seed(seed)
os.environ["PYTHONHAS... |
a0c3ddc8f6edbf4e3170854e63741a740eca5ec327bc5cc15b8683ab753e7a64 | Python | 2,393 | 72 | import logging
import numpy as np
from matplotlib.pyplot import figure
from skimage.filters import threshold_local
from skimage import io
from lib import File, SegmentedFile, utils
logger = logging.getLogger(__name__)
def segment_stack(
channel_file: File, threshold_method: str, min_vox_size: int = 3,
max... |
a24991952ea24b6a81faf5ee7ed7beb2d5553f3a09732ea0020632c8d656764b | Python | 2,393 | 60 | # 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... |
5e4600c39df0882f432486952193ad17f1f11640279c25f5da01cf607e99600d | Python | 2,395 | 64 | import unittest
import json
from bds_api.dumps.bds_queries import IndividualDetailsQuery, ListAllAllenIndividuals, GetOntologyMetadata, ListAllTaxonomies
class QueriesTest(unittest.TestCase):
def test_individual_details_query(self):
individual_details_query = IndividualDetailsQuery()
result = ind... |
ef4f785f2153c664a986245426c748b87e412612465d331efa5fa59a3ead4b91 | Python | 2,396 | 69 | import pandas as pd
import numpy as np
import networkx as nx
def create_proximity_model(g, locs, avg_th=10):
# get connection vs dist stats
conn_p_dist = []
for source_node in g.nodes():
for target_node in g.nodes():
if source_node == target_node: continue
distance = np.sqrt... |
c1c9cc2b0d3f04ac30a325e324639199e13ff99517a40355c9da941177878584 | Python | 2,397 | 94 | from abc import ABC
from monai.networks.nets import UNet
from monai.networks.layers import Norm
import pytorch_lightning as pl
class LowResBrainmaskModel(pl.LightningModule, ABC):
def __init__(self):
super().__init__()
# initialize network architecture
self.model = UNet(
spatia... |
bd9488d2f4eebcb0dfb24e206a940a35bf5a7bee705dfb6c0013dffd3c037e1c | Python | 2,398 | 70 | """
This is a sample simulation that does not represent any particular biological system. It is just a showcase
of how create a Simulation object, add forces, and initialize the reporter.
In this simulation, a simple polymer chain of 10,000 monomers is simulated.
"""
import os
import sys
import openmm
import polych... |
3cc4733b8e27936f0110ffe0247500f29554e8a3c5bf74d75ba7681ecca5e03a | Python | 2,399 | 69 | # 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... |
a7d6cab0c9e184199815653f14017490e805968f648f54e3feb70884071915b8 | Python | 2,399 | 78 | import numpy as np
import tensorflow as tf
class DataGenerator(tf.keras.utils.Sequence):
"""Initialization"""
def __init__(self, list_ids, dataset, dim, batch_size, n_classes=1, iterator=1, shuffle=True):
self.list_ids = list_ids
self.dataset = dataset
self.batch_size = batch_size
... |
f82ef171d85ebb218d6df810ebc4c1b0741c4911c4d5cbc884f9e52387016df7 | Python | 2,399 | 70 | import torch
from typing import Callable
def graph_build_zero_filling(x: torch.Tensor, edge_index: torch.Tensor,
node_mask: torch.Tensor):
"""
Subgraph building through masking the unselected nodes with zero features.
"""
ret_x = x * node_mask.unsqueeze(1)
return ret_... |
b22cd3d1ffcb967801ab295ab8b85f126f90cf2a0d7f35e72f28901dbca81bea | Python | 2,401 | 72 | import argparse
from pathlib import Path
import numpy as np
import pandas as pd
from tqdm import tqdm
import trajectory
from dataloading.model import Camera
from dataloading.nvidia import NvidiaValidationDataset, NvidiaTrainDataset
def parse_arguments():
argparser = argparse.ArgumentParser()
argparser.add_... |
3362fd49d6c1fd10473ee7da8f5b73ed911f1de209ac3eef633b06956bde53bb | Python | 2,402 | 56 | # 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 a... |
3c0e8501cf38ac7b5866aa7c009ba1b39e5c789aa4ba73ebc7377a125a308b4e | Python | 2,402 | 83 | import inspect
import re
from .registry import PLUGIN_LAYERS
def infer_abbr(class_type):
"""Infer abbreviation from the class name.
This method will infer the abbreviation to map class types to
abbreviations.
Rule 1: If the class has the property "abbr", return the property.
Rule 2: Otherwise, ... |
7866bb0c24f631f1bb91a5cdb8459dbd04762367f9db7fe7e62e3cde574ba784 | Python | 2,402 | 63 | # -*- coding: utf-8 -*-
import numpy as np
import homcloud.interface as hc
import matplotlib.pyplot as plt
from os import mkdir
from os.path import exists
def peristent_homology_sublevel_cubic(
image,
filename,
save_path,
plot_persistence_diagrams=False):
"""Calculate sublevel set cubical homology ... |
86dea7ad0fbcbac0991f4e704e74183acf36a3662921b163fe56dee2201d2763 | Python | 2,402 | 65 | #!/usr/bin/env python
# fpkm_to_tpm.py
# convert a file with an arbitrary number of columns to tpm using the following formula:
# TPM_i = FPKM_i * 1e6 / sum(FPKM_g for all genes g)
# formula based on a Lynch paper http://lynchlab.uchicago.edu/publications/Wagner,%20Kin,%20and%20Lynch%20%282012%29.pdf
import sy... |
44763eefc1ee44b61b02b95fd5ff9de3b0eeb78919a045ba4d576a646ed461f9 | Python | 2,403 | 84 | from seaborn import boxplot, kdeplot, violinplot
import pandas as pd
from matplotlib import pyplot as plt
from math import fabs
buckets = []
folder = "results/runs/5-final"
with open(f"{folder}/random_forest/crossval.txt", "r") as fin:
buckets.append(("decision tree", [float(l) for l in fin]))
with open(f"{folde... |
b705c336cb84e307343896959f11455376243d65e989ad613f3e3e382c811c08 | Python | 2,404 | 79 | import sys
import numpy as np
import torch
from torch_geometric.datasets import TUDataset
from torch_geometric.data import DataLoader, Data
from torch_geometric.nn import global_mean_pool, GCNConv
import torch.nn.functional as F
#from explainers.guidedbp import GuidedBP
from graphxai.gnn_models.graph_classification i... |
b9aad8b0a5db55a81a791e13ecc655551503a134b826d792b98dda81b6013d0d | Python | 2,404 | 83 | 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... |
443d9993b83b2aa4b14f596f109e1dc0c8367ed3af5d4fee4037120162b10a40 | Python | 2,405 | 76 | import pyBigWig
import numpy as np
from .target import Target
class qSeqGenomicFeatures(Target):
"""
Stores the dataset specifying sequence regions and features.
Accepts a path to directory containing bigWig files with feature values
Parameters
----------
features : list(str)
non-redu... |
5d62857d52725b948c8188aa4593c89c73b9af99e6509ca4455989754d767f6d | Python | 2,405 | 91 | """
From https://github.com/wanghao14/Stain_Normalization
Normalize a patch stain to the target image using the method of:
E. Reinhard, M. Adhikhmin, B. Gooch, and P. Shirley, ‘Color transfer between images’, IEEE Computer Graphics and Applications, vol. 21, no. 5, pp. 34–41, Sep. 2001.
"""
from __future__ import div... |
679aaa200452d0e819b3f153394f4150f276afbb100280c2a214ef6f0a1e7da9 | Python | 2,406 | 61 | """Registry mapping (patient_status, crop_method) pairs to crop strategy executors.
This decouples the algorithm dispatch from ``croppingControllerClass`` so new
crop strategies can be registered without editing the controller's branching
logic. Each registered executor is called with the controller instance as its
so... |
7e32fb6a7ccf1138fd56c88cabcc4ec754b3e7121367700d8e1bd12748af984c | Python | 2,407 | 65 | import sys
import torch
from torch_geometric.datasets import TUDataset
from torch_geometric.utils import remove_self_loops
from graphxai.explainers import GNN_LRP
from graphxai.explainers.utils.visualizations import visualize_mol_explanation
from graphxai.gnn_models.graph_classification import GCN, load_data, train, ... |
f4de0f2b04ecef269613c35d83487d0b4ba0fc2676c4e680da7cb42f61d4a54a | Python | 2,407 | 68 | #!/usr/bin/env python
"""Import ImageJ ROIs
To identify and import ZIP files within all SIMA directories:
>> python import_ImageJ_rois.py /path/to/sima/datasets rois
For help and additional arguments:
>> python import_ImageJ_rois.py --help
"""
import argparse
import os
import sima
def remove_empty_ROIs(rois, im_... |
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