sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
75fc6efc450a71169124f5d23850b26cf1818fe8b6e95ad56b23eb17a60a7b77 | Python | 809 | 29 | import setuptools
with open("README.md", "r") as fh:
long_description = fh.read()
setuptools.setup(
name="nirsimple",
version="0.1.6",
author="Johann Benerradi",
author_email="johann.benerradi@gmail.com",
description="fNIRS signal processing simplified",
long_description=long_description,
... |
039dcfc30f7c69e1dcc129ddbae0cb4afaf6dda36203335eda318d849feeb89e | Python | 810 | 31 | # %%
import os
import sys
try:
os.chdir('/Volumes/GoogleDrive/My Drive/python_code/connectome_tools/')
print(os.getcwd())
except:
pass
import pymaid
import numpy as np
import pandas as pd
A1 = pymaid.get_skids_by_annotation('mw A1 neurons')
A1_names = pymaid.get_names(A1)
A1_names_array = []
for skid in ... |
54b5eab82d7bfce1f3e3d015bb39ea2fc9cb0bde6f9774a7d27bb62d56b57657 | Python | 810 | 36 | import unittest
from alpamayo_nurec import NurecEpisodeComplete, _tick_and_capture
class _FinishedScenario:
def __init__(self):
self.running = True
def tick(self):
self.running = False
def is_running(self):
return self.running
class _NoFrames:
def has_complete_batch_after(... |
8eedc9008ff60e068420746da574adc0ae546dff7605bfa869fa3bd3951883c8 | Python | 810 | 45 | from darela import SUR
import autograd.numpy as anp
import matplotlib.pyplot as plt
release = {
"Vm": 4.8,
"Km": 0.2,
"DAp": 0.43,
"kS": 0.9,
"kE": 1.05,
"kads1": 0.035,
"kads2": 0.14,
"kads3": 0.09
}
kinetic = {
"ktypes": ["stf", "std", "ltd"],
"p": [0.0105, -0.003, -0.0011],... |
9cd5a0e0c01f1d6984b4c8012c5f55a9aaaaaaa7efde36981c0e87322d213f13 | Python | 810 | 36 | from abc import ABC
from typing import Dict, List, Iterable, Any
from oaklib.interfaces.basic_ontology_interface import BasicOntologyInterface
from oaklib.types import CURIE
class PatcherInterface(BasicOntologyInterface, ABC):
"""
Applies diffs
See `KGCL <https://github.com/cmungall/knowledge-graph-chan... |
e02635e1bed9157bd93547d6167bc99303e2ddfd02dda139ab4caeabaa7206cd | Python | 810 | 21 | #!/bin/bash
# Copyright 2022 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law ... |
40a7fe0a6eccb034b2e9ba180690fbae77b460747392b5b69d56c4aaa0cbe820 | Python | 811 | 23 | import tensorflow as tf
# Dispersion interaction based on Cn coefficients and the Becke-Johnson damping scheme proposed in
# https://aip.scitation.org/doi/10.1063/1.1949201
def BJ_dispersion(R2, C6, C8, C10):
Rvdw = get_Rvdw(C6, C8, C10)
Rvdw_2 = tf.square(Rvdw)
Rvdw_6 = tf.math.pow(Rvdw_2, 3)
Rvdw_8 =... |
d0cde36d340cee86731ea2e9651524c245ed4fb1fdc1a3e04e649a9206887e0b | Python | 811 | 13 | from .base_options import BaseOptions
class PredictOptions(BaseOptions):
def initialize(self, parser):
parser = BaseOptions.initialize(self, parser)
parser.add_argument('--pet_file', type=str, required=True, help='Which PET file shall be used?')
parser.add_argument('--prostate_contour', ty... |
648de48c9cd77749d869f4079c1bba893b1008fad67d77345e201303ad4e71e9 | Python | 812 | 40 | '''
Velocity vs. calcium concentration
'''
from pylab import *
width, height = 2, 2
K_electromotor = 1.4e-6 #2.4e-6 #.5e-6 # in uM
n_electromotor_coupling = 2 # 3.7
v_plus = .5
#v_plus = .55
#el0 = 1/(1+(1e-7/K_electromotor))
#v_plus = .5/(2*el0-1)
#print('v_plus =',v_plus)
v_minus = -v_plus
fig = figure('Angle', (w... |
a20116649e6bfe132b1e3085219e0ac047593ed1394c79e6376da9189608547f | Python | 812 | 39 | import gzip
import sys
## converts GTEx 1_10497_C_T_b37 ids to chr:pos
infile = sys.argv[1] # SNPs.txt.gz with GTEx ids
outfile = sys.argv[2] # Output filename prefix
fh = gzip.open(infile,'rt')
fho = gzip.open(outfile+".txt.gz",'wt')
fho2 = gzip.open(outfile+"-mappings.txt.gz", 'wt')
set = set()
for line in fh:
... |
b0cf80a846ef83092ba141d9e519522ce842b6006eaf38c54a757a24c4314928 | Python | 813 | 28 | import navis
import pytest
import tempfile
from pathlib import Path
@pytest.mark.parametrize("filename", ['', '{neuron.name}.swc',
'neurons.zip',
'{neuron.name}.swc@neurons.zip'])
def test_swc_io(filename):
with tempfile.TemporaryDirecto... |
2cb266dfba0575f13d46261463dfac25564d554ec8439e0430e5731b2b036320 | Python | 814 | 29 | """Shared fixtures. Unit tests need no CARLA server; tests marked
``integration`` run only when ``CARLA_COSMOS_TEST_PORT`` is set."""
import os
import sys
import pytest
sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
def pytest_collection_modifyitems(config, items):
if os.environ.get("CARLA_... |
4d7448afa14811038b2a8a49375a837b6c6251f06769f6ef0a4aff786b20b840 | Python | 814 | 18 | # 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... |
7ebd8ad6649461579701ae38c20c95159947f6b35f0d47fb1ec584720e018bfb | Python | 814 | 21 | from .darcy import DarcyDataset, load_darcy_flow_small
from .navier_stokes import NavierStokesDataset, load_navier_stokes_pt
from .pt_dataset import PTDataset
from .burgers import Burgers1dTimeDataset, load_mini_burgers_1dtime
from .dict_dataset import DictDataset
from .mesh_datamodule import MeshDataModule
from .car_c... |
eea1eb0dde736e334ebd9c52f55c77e48a5a8379353925d5cc045f054f8d0bf0 | Python | 814 | 34 | """
Basic tests of BFS.
Author: Mengye Ren (mren@cs.toronto.edu)
"""
import numpy as np
import unittest
from tensorflow_forward_ad.cbfs import bfs
class BFSTests(unittest.TestCase):
def test_bfs(self):
adj = np.array([[1, 1, 0], [0, 0, 1], [0, 0, 0]], dtype=np.int8)
self.assertTrue(bfs(adj, 0, 2, None))
... |
f0e8e79842bb1c4d1dfd0f3e98e581fc9a3cd66e45aa9b6e486a6ba5037f04c3 | Python | 814 | 24 | import numbers
import numpy as np
def check_random_state(seed):
"""Turn seed into a np.random.RandomState instance
Parameters
----------
seed : None, int or instance of RandomState
If seed is None, return the RandomState singleton used by np.random.
If seed is an int, return a new Ran... |
7b94e98c4d3cb047fd4a0f06a019a38399df4526e3e7e32058ce5fcc28a59e5b | Python | 815 | 37 | from typing import Any
from PyQt5.QtCore import QObject, Qt
from PyQt5.QtWidgets import QMenu
class SensorServiceItem(QObject):
# region Class Initializer
def __init__(self, parent: QObject = None):
super(SensorServiceItem, self).__init__(parent=parent)
# endregion
# region Abstract Insta... |
7d4cc1bc9e6af8e987f4c56eaee4c1bc38496144bb58218e3d4aae03fa6d25ef | Python | 815 | 18 | # 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... |
88cf331b8ab84c00ded57adb97fa41d2195915f8c8458622b128f0422e3d3bc0 | Python | 815 | 17 | # 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... |
cc5c473986dd1bf72c8675a60d8532eed7b4dc346873599a6e56cb5a6e62cd8d | Python | 815 | 28 | import torch
from cgtasknet.net import SNNlifadex
from norse.torch import LIFAdExParameters
def load_network(f: str, v_th: float, tau_a_inv: float, filter_parameter: float, hidden_size: int, feature_size: int,
output_size: int, save_states: bool = False, device: torch.device = torch.device('cpu')):
... |
28daadf093e810fc419ac0257b805069f512064e60a6b0ab83a81ebdd6f2636d | Python | 816 | 32 | import csv
import sys
from dataclasses import dataclass, field
from typing import Any
from linkml_runtime import CurieNamespace
from linkml_runtime.dumpers import yaml_dumper
from linkml_runtime.utils.enumerations import EnumDefinitionImpl
from linkml_runtime.utils.yamlutils import YAMLRoot
from oaklib.io.streaming_wr... |
13ca6e1daa84b8d432978914e39f463e94be08fc1facc277e79d1e499f534ed7 | Python | 817 | 23 | # 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... |
4a39918b90863e16f3cee2e56027578a869f08878001348ffb3d6a28fa78e198 | Python | 817 | 23 | from mmdet.models.detectors import SingleStageDetector
from mmdet.models.registry import DETECTORS
from mmdet.core import bbox2result
@DETECTORS.register_module
class SingleStageDetectorSearch(SingleStageDetector):
def __init__(self, **kwargs):
super(SingleStageDetectorSearch, self).__init__(**kwargs)
... |
7f19a6208209221d6c3f51cf45a2ecb844864334e3f0fb43cdc47734b06efe6c | Python | 818 | 29 | from datetime import datetime
from pathlib import Path
from spotipy.model import SpotNet
from cenfind.cli.train import fetch_all_fields
from cenfind.constants import datasets
from cenfind.core.data import Dataset
from cenfind.training.config import config_unet
PREFIX_REMOTE = Path("/data1/centrioles/canonical/")
d... |
2925fe9192258be2879e1502901e937e697f915cfd35a8d7a2f9e6cc06877eda | Python | 819 | 32 | __author__ = "Johannes Köster"
__copyright__ = "Copyright 2018, Johannes Köster"
__email__ = "johannes.koester@protonmail.com"
__license__ = "MIT"
import os
from snakemake.shell import shell
known = snakemake.input.get("known", "")
if known:
known = "--dbsnp " + known
extra = snakemake.params.get("extra", "")
... |
a10d2a53b23a8fee6105c23960ff1d32e426b935b3897945b3e1349e110ba978 | Python | 819 | 24 | import argparse
import yaml
from wandb_utils import WandbLogger
WANDB_ARTIFACT_PREFIX = 'wandb-artifact://'
def create_dataset_artifact(opt):
with open(opt.data) as f:
data = yaml.load(f, Loader=yaml.SafeLoader) # data dict
logger = WandbLogger(opt, '', None, data, job_type='Dataset Creation')
i... |
a227abcc7e841c9eafd3b108087cd1dfb9af949f35fb00ebca2aab7c4b384be0 | Python | 819 | 32 | import unittest
import numpy as np
class TestImports(unittest.TestCase):
'''
Test import of various packages, needed for this project
'''
def test_various_imports(self):
import matplotlib
import pandas
def test_parallel_libs_import(self):
import threading
import ... |
24fc26605ad17bcd3dec29b4a133be6a99b21ed11228ff8e85f8a073e9e76cf1 | Python | 820 | 17 | # 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... |
dc4fdd4d7b3e4507e30a14120656707bda53a6b2c32a2261862ed5091747fdb5 | Python | 820 | 35 | from setuptools import find_packages, setup
setup(
name="tmkit",
version="0.0.6",
keywords=["pip", "tmkit"],
description="TMKit",
long_description="TMKit",
license="GNU GENERAL V3.0",
url="https://github.com/2003100127/tmkit",
author="Jianfeng Sun",
author_email="jianfeng.sun@ndorms... |
eecb89dfc41766f0a684b52031f176043fa5e743eaf9ae3ce8c0dcb3d45958e7 | Python | 822 | 29 | """
Tools for handling info in mitochondria tables
"""
def string2list(stringlist,targtype=int):
"""
In DataFrames that have been saved to .csv files,
lists are sometimes converted to string types.
In mitochondrial dataframes this is often the case.
This tool converts a list with the contents of a... |
950f5a90bfc974954c698bf995905c827db3e9c65ceafe500c63518312897682 | Python | 824 | 32 | import os
from setuptools import setup, find_packages
with open('README.md', 'r') as f:
long_description = f.read()
setup(
name="crossmapy",
version="0.0.1",
author="Peng Tao",
author_email="taopeng543@gmail.com",
url='https://github.com/PengTao-HUST/crossmapy',
description="causal inferen... |
3acde784916589027b33567143644159ffd18874ff58ad375a48f5f23ebf3cde | Python | 825 | 33 | import logging
from dataclasses import dataclass
from pathlib import Path
from typing import Type, Union
@dataclass
class OntologyResource:
"""
A representation of an ontology resource.
This may be a local or remote file, or an ontology name that is part of a remote service
"""
slug: str = None
... |
48dd2d7f19dbb3afca7dee5cde33b30bc3b130a29e599fb677d1e2c4327a8c48 | Python | 827 | 28 | import unittest
import pytest
from oaklib import get_adapter
from oaklib.interfaces.association_provider_interface import (
AssociationProviderInterface,
)
from oaklib.utilities.iterator_utils import chunk
# TODO: use mock tests
@pytest.mark.skip(reason="Network dependency")
class TestPantherDB(unittest.TestCas... |
0684ff1b1afffa2d19fbbb03471f1ac52919e2dab15071d97af2d9b0e0eb7fd0 | Python | 829 | 21 | import pandas as pd
dataPath = "C:/Users/Hamish/Desktop/InjectionsA1_AllenBrainAtlas/projection_search_results.csv" # has to be downloaded beforehand
df = pd.read_csv(dataPath)
from selenium import webdriver
from selenium.webdriver.common.by import By
from webdriver_manager.chrome import ChromeDriverManager
browser =... |
05fca3a06d79ff74a8b2cff7999c3b7cab83ab7ab47c19460740a48ca5fb4bd0 | Python | 831 | 22 | # 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... |
464017d7bd1164807a471518f5ce5565b130cebdf2952cec4b4de964464f3789 | Python | 831 | 26 | # Copyright (c) Open-MMLab. All rights reserved.
import torch.distributed as dist
from .hook import HOOKS, Hook
@HOOKS.register_module()
class SyncBuffersHook(Hook):
"""Synchronize model buffers such as running_mean and running_var in BN at
the end of each epoch.
Args:
distributed (bool): Whethe... |
780b0be60745fbe8ba76f649e1566e93e8e5588e8f4652ddb896905f7a8e3586 | Python | 833 | 33 | import math
import torch
from torch.nn import Linear
from torch.nn import init
class XavierLinear(torch.nn.Module):
"""
Linear transform initialized with Xavier uniform
"""
def __init__(self, input_dim, output_dim, bias=True):
super(XavierLinear, self).__init__()
self.input_dim = in... |
cda01f86c873fc69e0a3c6e7e89a55bab6263639c30ad964b8fa8a6bc9cd154f | Python | 833 | 22 | from benchnirs.load import load_dataset
from benchnirs.viz import epochs_viz
ALL_DATA_PATH = '../../data/dataset_' # path to the datasets
DATASETS = {'herff_2014_nb': ['1-back', '2-back', '3-back'],
'shin_2018_nb': ['0-back', '2-back', '3-back'],
'shin_2018_wg': ['baseline', 'word generation'... |
d9dedc9692617a7ef9f788932d02426d983a59f86cfca846297ab47a37b13257 | Python | 833 | 35 | '''
Calculates spontaneous avoiding response frequency vs. standard deviation of noise
'''
from brian2 import *
from behavior import *
from pylab import *
movie = True
C = paramecium_constants()['C']
N = 200
duration = 120*second
tau_noise = 20*ms
eqs= paramecium_equations() + Equations('''
dv/dt = (IL+ICa_cilia+IK... |
1691a15798c36845ee1796f8d4f4d8f72a5835b0c2e1a80bf7a5c0c839400cbe | Python | 834 | 41 | import numpy as np
from sympy import *
import mpmath as mp
def local_stability(parameters):
tau_e = parameters["tau_e"]
tau_i = parameters["tau_i"]
gei = parameters[
"gei"
] # excitatory-inhibitory synaptic conductance as ratio of E-E syn
gii = parameters[
"gii"
] # inhibito... |
93afb04efbd53ce4bb0694b5bd1878e6f35432e558e2589ea301a3f3489e48af | Python | 834 | 32 | import argparse
import torch
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description="Extract factor/eigenvectors of latent spaces using closed form factorization"
)
parser.add_argument(
"--out", type=str, default="factor.pt", help="name of the result factor file"
)
... |
a0204144ddb662a083bb4cb74a3fdc1f09892f167dd4e7086ff21c930d4c4bb2 | Python | 834 | 38 | __author__ = "Jianfeng Sun"
__version__ = "v1.0"
__copyright__ = "Copyright 2023"
__license__ = "GPL v3.0"
__email__ = "jianfeng.sunmt@gmail.com"
__maintainer__ = "Jianfeng Sun"
from Bio import SeqIO
class EmptyFastaError(Exception):
"""Error raised if FASTA file does not contain sequence"""
def get(fasta_fpn... |
ac18f60ecb23b99cf1c02ad425f09d911e2f473fc866a40b19bd5cd5e91fd157 | Python | 834 | 36 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon May 25 10:31:51 2020
@author: smithm3
"""
import click
import unetsl.model
from tensorflow import keras
@click.command()
@click.argument("model_file")
@click.option("--layer", default=None)
def main(model_file, layer):
model = unetsl.model.loadMo... |
0f7bf3726bea3a7998ad937fe3bb0ecaaab14b5aa5c4ff563cc38d6f002d151e | Python | 835 | 16 | # 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... |
2d2d6c29d75769367646d2409488b8ae73c92aeaf591c9767052fd73a17a2306 | Python | 835 | 30 | from setuptools import setup
requirements = [
"numpy",
"scanpy",
"numba",
"pandas",
"scikit-learn",
"scipy",
"seaborn",
"matplotlib",
"pytest", #TODO: For simplicity adding it to requirements.
]
gpu = ["torch"]
setup(
name="scPrisma",
version="0.0.5",
... |
748f5219d45b2326829ffbc8bfd655450316fd40755ab29595114fa272ef98d2 | Python | 835 | 29 | # -*- coding: utf-8 -*-
# File : unittest.py
# Author : Jiayuan Mao
# Email : maojiayuan@gmail.com
# Date : 27/01/2018
#
# This file is part of Synchronized-BatchNorm-PyTorch.
# https://github.com/vacancy/Synchronized-BatchNorm-PyTorch
# Distributed under MIT License.
import unittest
import numpy as np
from tor... |
ad30302cf26ec8fc7c08f8bcbc8017ab1d5a5388ffe4d20207a91d55d23db899 | Python | 835 | 17 | import subprocess as sp
from .logger import get_logger
LOGGER = get_logger()
def run_model(fixed_path=None, moving_path=None, fixed_seg_path=None, moving_seg_path=None, output_path=None, task="B"):
if (fixed_seg_path is None) or (moving_seg_path is None):
# LOGGER.info("The fixed or moving segmentation... |
03c18617a56f1f7181379741febaef44cc0976b58cdc3fa4d9f2e543edca9195 | Python | 836 | 35 | __author__ = "Johannes Köster"
__copyright__ = "Copyright 2018, Johannes Köster"
__email__ = "johannes.koester@protonmail.com"
__license__ = "MIT"
import os
from snakemake.shell import shell
known = snakemake.input.get("known", "")
if known:
known = "--dbsnp " + known
extra = snakemake.params.get("extra", "")
... |
c6f083c3ee3033663133f7a1a019e544abd5b642cb62c552acfe4b2d66979456 | Python | 836 | 23 | import logging
import logging.config
from pathlib import Path
from .util import read_json
from datetime import datetime
def setup_logging(save_dir, log_config='utils/logger_config.json', default_level=logging.INFO):
"""
Setup logging configuration
"""
log_config = Path(log_config)
if log_config.is... |
a8f16ee59f047d80c3caf6c9f67793a3798077fc1ea0dc780b44e1d493ab38d9 | Python | 837 | 20 | from easydict import EasyDict
# Baseline config - Convolution 1D
task1_baseline_config = {"seed": 42,
"val_size": 0.2,
"split_videos": False,
"normalize": True,
"past_frames": 100,
"future_frame... |
ff12822301c612d35009af302bccbbfc549746f4cafe7f06a156f67ce9fba152 | Python | 837 | 32 | import numpy as np
import os
from machemer import num_phases, shapes_data_path
def get_colors(num, cmap):
'''
:param num: How many colors to return
:param cmap: e.g. 'jet' 'viridis' 'RdBu_r' 'hsv'
:return:
'''
import matplotlib.cm as mcm
cm = getattr(mcm, cmap)
return cm(np.linspace(0,... |
34f59c549ec48023709460ffb4b7a59c5d183c6919fc96bae6dfc6c912ca12bc | Python | 838 | 30 | #!/usr/bin/env python
import sys
import codecs
romanToScript = {}
lexiconLocation = sys.argv[1]
wordLexiconLoc = sys.argv[2]
outLexiconLoc = sys.argv[3]
# First create a map from the romanized to the script version
lexicon = codecs.open(lexiconLocation + "callhome_arabic_lexicon_991012/ar_lex.v07", \
encoding="... |
64f5dfc76fffb45092ef6944a548cca7060f6167b7340ce167d2aa379ad03292 | Python | 838 | 19 | from .heuristics import MiddleDistCentroid,MiddleWingAngleMinIntruder,MiddleWingAngleMaxIntruder,MiddleAxisRatioResident,MiddleAxisRatioIntruder, MiddleAngleSocialIntruder, MiddleSpeedResident, MiddleWingAngleMaxResident, MiddleSpeedIntruder,MiddleWingAngleMinResident, MiddleAngularSpeedResident, MiddleAngularSpeedIntr... |
9d74035b1735931c4a82517da745b4733817175059346458c75f86c4f2b689e3 | Python | 839 | 33 | def _no_tqdm(iterable, *args, **kwargs):
"""
replacement for tqdm that just passes back the iterable to silence `tqdm`
"""
return iterable
def _no_progressbar(progress, total_length):
"""
no-op calls to update the `fetcher` progress bar
"""
return
def reset_progressbars(gallery_conf,... |
d358a164338c51717cde95017fbe0f31d93f467433b36707e8ed2dd462b5149f | Python | 841 | 27 | import importlib
import os
from collections import namedtuple
import torch
if torch.__version__ != 'parrots':
def load_ext(name, funcs):
ext = importlib.import_module('mmcv.' + name)
for fun in funcs:
assert hasattr(ext, fun), f'{fun} miss in module {name}'
return ext
else:
... |
519c7df99d6537ddfd12eeffcd0a52d43c339ab41b75ffccb7119c934b6c61f2 | Python | 842 | 40 | """
scHumanNet: Construction of cell-type-specific functional gene network
This package provides tools for constructing cell-type-specific functional gene networks
using SCINET and HumanNetv3, with functions for downstream analysis including hub gene
identification and differential network analysis.
"""
__version__ =... |
74bc935e318a953547c94fd35cc5b24a3782c3db0f1101833eed4d627eb90b9c | Python | 842 | 37 | #!/usr/bin/env python3
# Copyright 2017 Bengu Wu
# Apache 2.0.
# This script splits the test set utt2spk into enroll set and eval set
# For each speaker, 3 utterances are randomly selected as enroll samples,
# and the others are used as eval samples for evaluation
# input: test utt2spk
# output: enroll utt2spk, eval ... |
7a54f8b6142051858c37c2dd2943f39b4a9640a9859946dd6023539d62ddde19 | Python | 842 | 21 | from .._widget import PalmariWidget
from ..data_structure.acquisition import Acquisition
from ..data_structure.experiment import Experiment
from ..processing.image_pipeline import ImagePipeline
from glob import glob
import numpy as np
# make_napari_viewer is a pytest fixture that returns a napari viewer object
# capsy... |
b9f6acd15cf605dd88df0c19fa5d00afa8b219e2a8884e120cd1c90bea6653e9 | Python | 843 | 26 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import torch
from .batch_norm import FrozenBatchNorm2d
from .misc import Conv2d
from .misc import ConvTranspose2d
from .misc import BatchNorm2d
from .misc import interpolate
from .nms import nms
from .roi_align import ROIAlign
from .roi_align impo... |
ec4592a5cffa1742fd10f55f9ce19b305912c8d6d13a669325561cc0b20b24e7 | Python | 843 | 23 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import torch
if torch._six.PY3:
import importlib
import importlib.util
import sys
# from https://stackoverflow.com/questions/67631/how-to-import-a-module-given-the-full-path?utm_medium=organic&utm_source=google_rich_qa&utm_campai... |
755cf03f100ee810199f760b9517ff3c3f39674aab0d981e64ddce14eb2da248 | Python | 844 | 31 | #%%
from src.data import load_metagraph
mg = load_metagraph("G")
meta = mg.meta
#%%
mbin = meta[meta["class1"] == "MBIN"]
mbin
mbin.loc[[4381377, 10673895]]["name"]
#%%
from src.visualization import simple_plot_neurons
from src.pymaid import start_instance
from src.visualization import CLASS_COLOR_DICT as palette... |
f38fb7202d12dcc6912a562056d3fc1073efeda83ee2c571ec1df07d0e976d79 | Python | 844 | 31 | from typing import Any, Tuple
import torch
class SNNOneState:
def __init__(self, model) -> None:
self.model = model
def one_state(self, x: torch.tensor, state: Any) -> Tuple[torch.Tensor, Any]:
out, new_state = self.model(x, state=state)
return out, new_state
class SNNStates(SNNOne... |
91f8e92cc309458c580cb21cbbf74d6bcd74acff28a88a5818d4ad07d1dc18c5 | Python | 846 | 15 |
# This recipe shows the current traffic rules affecting the vehicle.
# Shows the current lane type and if a lane change can be done in the actual lane or the surrounding ones.
# ...
waypoint = world.get_map().get_waypoint(vehicle.get_location(),project_to_road=True, lane_type=(carla.LaneType.Driving | carla.LaneType... |
c4c5b3dc673454fea7999ae8f4059031be64eb73ee9bcaa5ba5593b8db81794d | Python | 846 | 37 | import numpy as np
from cgtasknet.tasks.reduce import _generate_values
def test_generate_value_mode():
mode = "value"
values = [0, 1, 2, 3, 4]
size = 10
for value in values:
assert np.allclose(
np.ones(size, dtype=np.float64) * value, _generate_values(mode, size, value)
)
... |
d8f45a41cc55f375a296777065762e3f6769264dbb8d2107dc604ea2f6eca8e6 | Python | 847 | 35 | from moses.trans import (
TranslationModel,
TranslationTrainer,
translation_parser,
)
class ModelsStorage:
def __init__(self):
self._models = {}
self.add_model(
"translation",
TranslationModel,
TranslationTrainer,
translation_parser,
... |
24270402a4170aa36b69d6c40502544dd73d599b34214d2c256ce319301a07a3 | Python | 848 | 25 | # 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... |
965a23f2c2ce6a8a8c82920a11c855213010f88e7b4bd46effc6056ab8788582 | Python | 848 | 23 | # 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... |
a88a6a84dd895c594327bbfd6d4a00e9307437c07a4d890f2a7b040b73647a6d | Python | 848 | 29 | from collections import defaultdict
IMG_DATA_PATH="charpragcap/resources/visual_genome_data/"
REP_DATA_PATH="charpragcap/resources/resnet_reps/"
TRAINED_MODEL_PATH="data/models/"
WEIGHTS_PATH="charpragcap/resources/weights/"
S0_WEIGHTS_PATH="s0_weights"
S0_PRIME_WEIGHTS_PATH="s0_prime_weights"
caption,region = 0,1
star... |
4775c49e1294bfabe470423d82576cf4337c8106f9e97cb2c7cfba00d43f49d9 | Python | 850 | 27 | from typing import List, Tuple, Union
from linkml_runtime.linkml_model import SlotDefinitionName
from linkml_runtime.utils.yamlutils import YAMLRoot
from oaklib import BasicOntologyInterface
def add_labels_to_object(
oi: BasicOntologyInterface,
obj: YAMLRoot,
pairs: List[Tuple[Union[SlotDefinitionName, ... |
799221f40f74db2581f616d93ccda50fac0d76f60020656e168050e0ec434e43 | Python | 850 | 37 | from __future__ import print_function
import os
import torch
from torch.utils.ffi import create_extension
#this_file = os.path.dirname(__file__)
sources = []
headers = []
defines = []
with_cuda = False
if torch.cuda.is_available():
print('Including CUDA code.')
sources += ['src/nms_cuda.c']
headers += ['... |
81fc9e18b144324097ae0fac6087f7b5851dce1a6b07f6d717edc2cd1cb32bf2 | Python | 850 | 32 | ##Code by Isaac Arias S - YachayTech University
##Biomedical Engineer Student.
##School of Biological Sciences and Engineering.
import shutil
import os
import fnmatch
file = open("TrainHRF.txt","r")
f = file.readlines()
newList = []
for line in f:
newList.append(line.strip() + ".jpg") ##Add the c... |
8c2b471be52b92946883756b839a4be6c0994716814edfb8377075b380341b9e | Python | 850 | 25 | import unittest
from alpamayo_display import SimulationVideoClock
class SimulationVideoClockTest(unittest.TestCase):
def test_twenty_fps_duplicates_each_ten_hz_state(self):
clock = SimulationVideoClock(20.0)
self.assertEqual([clock.advance(0.1) for _ in range(4)], [2, 2, 2, 2])
def test_frac... |
d677e5d86e94b56183b7fac59dee7c0fade511380e94f4ec04ee58287ad0a29a | Python | 850 | 32 | from typing import Tuple, Union
import torch
import numpy as np
def get_device(
use_cuda: bool,
) -> Tuple[torch.device, Union[torch._C._CudaDeviceProperties, None]]:
"""retrieves information about device (CPU or CUDA)
Args:
use_cuda (bool): if cuda to be used
Returns:
Tuple[torch.de... |
424286c2426c5ef339dfbe4902117690702987a7390cc1ed8b1fb1887c77dc8a | Python | 851 | 28 | #%%
import os
import sys
try:
os.chdir('/Volumes/GoogleDrive/My Drive/python_code/connectome_tools/')
sys.path.append('/Volumes/GoogleDrive/My Drive/python_code/maggot_models/')
sys.path.append('/Volumes/GoogleDrive/My Drive/python_code/connectome_tools/')
except:
pass
import pandas as pd
from pymaid_... |
18b3905742baabbbd259c0f486e1e7b21066bd1a71b1e0a0f6dc28a49d257733 | Python | 852 | 28 | import os
import torch
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') # sets device for model and PyTorch tensors
# Model parameters
image_w = 112
image_h = 112
channel = 3
emb_size = 512
# Training parameters
num_workers = 1 # for data-loading; right now, only 1 works with h5py
grad_clip =... |
30622c33751fdabdb1eca256e2f591a660208167b7155f72269e7a8c8f0601cc | Python | 852 | 25 | # -*- coding: utf-8 -*-
import numpy as np
from . import utils
from . import mi
from ._base import _ConventionCausality
class TransferEntropy(_ConventionCausality):
def fit(self, data, mi_kwargs=None):
self._preprocess(data)
self._fit_data(mi_kwargs)
def _fit_data(self, mi_kwargs=None):
... |
9bc05d5e927ef0fb66d430117ec51551366de7f41da0f884caa07b494d720de7 | Python | 852 | 33 | from dataclasses import dataclass
from enum import Enum
from pathlib import Path
import pandas as pd
# -----------------------------------------------------------------------------------------------------------
# Data paths across tasks
@dataclass
class Ferret():
""" Metadata associated with a specific subject "... |
045cd328128d4fef564ceb606f2ea40d5fe431af1539502296919d124f87e7e2 | Python | 854 | 25 | import urllib
import yaml
from urllib import request
TAXONOMY_DETAILS_YAML = "https://raw.githubusercontent.com/obophenotype/brain_data_standards_ontologies/pcl_migration/src/dendrograms/taxonomy_details.yaml"
species_mapping = {"mouse": "Mus musculus",
"human": "Homo sapiens",
... |
e66bdef8cb25f28a00c5378e3ee0cdf4cafa885d98ac850c2dbf8ddf2840ed49 | Python | 854 | 32 | import numpy as np
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
from matplotlib import colors as mcolors
folders = ['/clusterfs/lawrencium/yaningl/Research/DK3_duke_forest_1996_2005_041417/sim_'
+ str(i) for i in range(1, 11)]
year = 2005
col_num = 4
colors = ['red', 'green', 'b... |
62791930713aa245a3e3e4fdd4bc74d7fc33f988559b7e1bc14551dc11b6ba1d | Python | 856 | 22 | """
File: __init__.py
Created: 2020-04-29
Last Changed: 2020-04-29
Author(s): H.H.Wiersma
Code to create distribution plot and a mask image used in the research plan
Copyright (C) 2019 H.H.Wiersma
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Genera... |
b61bbaf51ac29d1734d52eb9f64c18481e12347d067f369a6e80b00d68859a3a | Python | 856 | 25 | from typing import List, Any, Optional
from zencfg import ConfigBase
class DistributedConfig(ConfigBase):
"""
DistributedConfig provides config options for multi-GPU
and multi-node settings. Our current setup depends on ``torchrun``-based
Elastic Launch and the ``nccl`` distributed backend for commun... |
835904b339c0244fcd9ee88d1ac10579506fc0803ebea4996f3d2f409dadd9c3 | Python | 857 | 36 | import ast
import numpy as np
import cloudvolume as cv
import json
from meshparty import skeleton_io
"""
Skeleton handling
Label conventions:
{1: 'axon',
2: 'basal dendrite',
3: 'apical dendrite',
4: 'ambiguous dendrite',
5: 'ambiguous',
0: 'soma'}
"""
SMOOTHED_SKELDIR = "data/smoothed_skels"
SMOOTHED_LABELDIR ... |
661d9eaa7eef0bb201b71b1884f7bad7e486adfe6746a81f87b53a7ea85dea6a | Python | 858 | 32 | #!/usr/bin/env python3
import os
import sys
import json
def main(argv):
fp = open(argv[1], encoding = "utf-8")
js = json.load(fp)
fp.close()
metas = {}
for ele in js:
fname = ele['file']
metas[fname] = ele
fWavScp = open(os.path.join(argv[2], 'wav.scp'), 'w')
fText = open(os.path.join(argv[2], '... |
fa4caff6284e25eace10fe436b8c0c1a214b84ed8d2793bbd3ed34b79b191128 | Python | 858 | 28 | import mmcv
from .version import __version__, short_version
def digit_version(version_str):
digit_version = []
for x in version_str.split('.'):
if x.isdigit():
digit_version.append(int(x))
elif x.find('rc') != -1:
patch_version = x.split('rc')
digit_version... |
13936ef4a542e38bcb2f2ec4d568609d01c7ddf3a303a83336b30c22bfee2195 | Python | 861 | 20 | """Test methods in data structures."""
from unittest import mock
from unittest.mock import MagicMock
from fi_parliament_tools.parsing.data_structures import Transcript
@mock.patch("fi_parliament_tools.parsing.data_structures.json.dump")
@mock.patch("fi_parliament_tools.parsing.data_structures.atomic_write")
def test... |
7719899ab4219fb8bfad9b7e2d99bc6515f69467cb6574456b3e832e8ce73adc | Python | 861 | 29 | def contrast_index(x1, x2, double=True):
"""
Calculate the contrast index between two arrays.
The contrast index is symmetrical with respect to
the choice of the baseline for comparison
Parameters
----------
x1 : ndarray of floats
An ndarray to compare. The contrast index will have ... |
0b310f1ba56e3440d511ca7637f9871df8bfbc4deafd8ac71ef097aedffaaf61 | Python | 862 | 26 | from setuptools import find_packages, setup
VERSION = '1.0.5'
DESCRIPTION = 'A package for adding dendrites to SNNs'
LONG_DESCRIPTION = 'A package for adding dendrites to SNNs in Brian 2'
# Setting up
setup(
name="dendrify",
version=VERSION,
author="Michalis Pagkalos",
author_email="<mpagkalos93@gmail... |
eaf3dc56abbed90c4c07785d2d9c5fac52e5bf1f5328376f43853d865153c502 | Python | 862 | 34 | from __future__ import absolute_import
import numpy as np
import torch
def nms_cpu(dets, thresh):
dets = dets.numpy()
x1 = dets[:, 0]
y1 = dets[:, 1]
x2 = dets[:, 2]
y2 = dets[:, 3]
scores = dets[:, 4]
areas = (x2 - x1 + 1) * (y2 - y1 + 1)
order = scores.argsort()[::-1]
keep = []... |
9f8ccde20594d7a330f731e6e7f376701cd5d9b2f5a94461c17582d6f6dc9af8 | Python | 863 | 28 | from flask import Flask, Blueprint
from bds_api import settings
from bds_api.restplus import api
from bds_api.endpoints.search_service import ns as api_namespace
from werkzeug.middleware.proxy_fix import ProxyFix
app = Flask(__name__)
# added for https bugfix https://github.com/noirbizarre/flask-restplus/issues/565
ap... |
ce4fd7186e0cef3ede47116b459e0251ea92d3e7aefa4ae7fae4ac98c7b41900 | Python | 863 | 35 | __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
def Palette(
chains: List[str], prot_c: str = "rainbow", sm_c: str = "blue_green"
) -> None:
"""
Apply... |
4644b7489e2f092cca335a3a26d13fdfb552e7176ccfe39d294f5882db4e0078 | Python | 864 | 16 | # 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... |
abd9dc623f1e42d16de54ad2a1de054fda8df323cbc8b42f38ba81124b0e66c6 | Python | 864 | 33 | """Figures for custom plots"""
from ._base import EelFigure, Layout, XAxisMixin
class Figure(EelFigure):
"""Empty figure
Parameters
----------
nax : int (optional)
Create this many axes (default is to not create any axes).
...
Also accepts :ref:`general-layout-parameters`.
aut... |
bf6365ffda3b263bb218671512b994968854bfcb897fe32d6ea27f85d178b73f | Python | 864 | 37 | # This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
""" This module contains the different parameters sets for each behavior. """
class Cautious:
"""Class for Cautious agent."""
max_speed = 40
speed_lim_dist = 6
speed_decrease = 12
... |
971221e284a5583a09c51457dafe083fb2d69b15c171f4052b3a7adb998a0ff9 | Python | 865 | 25 | #!/usr/bin/env python3
# encoding: utf-8
# @Time : 2017/12/16 下午8:41
# @Author : yuchangqian
# @Contact : changqian_yu@163.com
# @File : camvid.py
import numpy as np
from datasets.BaseDataset import BaseDataset
class CamVid(BaseDataset):
@classmethod
def get_class_colors(*args):
return [[128, ... |
aae9eec196d325860dd40de0d08b35f2dce1f59bcd2e53282cb7db1c78d303c4 | Python | 865 | 19 | # 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... |
98f451fa4adca4b490258c15f5de1afbd0f1dc2c353ff7e68e223b48ccb6874e | Python | 868 | 26 | import os
import synapseclient
import synapseutils
import argparse
import getpass
parser = argparse.ArgumentParser(description='Download RNAseq and genotypes of CMC.')
parser.add_argument('RNAseq_directory', help='Directory to download RNAseq data to')
args = parser.parse_args()
user = input("Synapse username:")
pas... |
b8b0b4fa4886b0dce2121bfffc9cd17b297b61e86f33428bfc54a7529a4e00df | Python | 871 | 22 | # 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... |
4d43ce842227d6c4b27a41fdfe993493a990fe0168b7e111b4ba65c29cc23e2e | Python | 872 | 40 | '''
@author: Mahbub Ul Alam (mahbub@dsv.su.se)
@version: 1.0+
@copyright: Copyright (c) Mahbub Ul Alam (mahbub@dsv.su.se)
@license : MIT License
'''
from abc import ABC, abstractmethod
class ModelTrainer(ABC):
def __init__(self, model, args=None):
self.model = model
self.id = 0
self.ar... |
50e81378c6fb849173f5c3284be0e5870759a0389b77d89370027d76e63d4c48 | Python | 872 | 26 | from unittest import TestCase
from drugex.molecules.converters.standardizers import DefaultStandardizer
from drugex.molecules.mol import DrExMol
from drugex.molecules.suppliers import StandardizedSupplier, ListSupplier
class TestStandardizer(TestCase):
def test_default(self):
"""
Tests whether t... |
35637b3547a673bd4125aef268c73ea08a1b455af5ef482b3973acdfe3d10ce5 | Python | 873 | 40 | class RSA_World:
def __init__(
self,
target,
speaker,
rationality="DEFAULTBAD",
):
self.target=target
self.rationality=rationality
self.speaker=speaker
def __hash__(self):
return hash((self.target,self.speaker,self.rationality))
def __eq__(self,other):
return self.target==other.target and sel... |
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