sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
1598a67c399874cfe52da7098a188fbabbf70bcd259c13014a0a4274e9ec852a | Python | 1,461 | 44 | #!/usr/bin/env python3
# Copyright 2020 Audio, Speech and Language Processing Group (ASLP@NPU), Northwestern Polytechnical University (Authors: Zhuoyuan Yao, Xiong Wang, Jingyong Hou, Lei Xie)
# 2020 AIShell-Foundation (Author: Bengu WU)
# 2020 Beijing Shell Shell Tech. Co. Ltd. (Author: Hui BU)
#... |
2fbdc6a8aa8225c76e6ba6c4c47ad37f4c6617f7febc3753b3b89ec6aef277a6 | Python | 1,461 | 54 | from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import Callable, Optional
import curies
from oaklib.datamodels.ontology_metadata import Any
from oaklib.types import CURIE
@dataclass(eq=False)
class DataModelConverter(ABC):
"""
Base class for all inter-data model converters.... |
4daedacb949ba5d0eda9d643fc19893002aace70a6bc1f59c740e8bcf7ccd23c | Python | 1,462 | 47 | import torch
import torch.nn as nn
from mol_tree import Vocab, MolTree
from nnutils import create_var
from dfs import Motif_Generation_dfs
from bfs import Motif_Generation_bfs
from chemutils import enum_assemble, set_atommap, copy_edit_mol, attach_mols, atom_equal, decode_stereo
import rdkit
import rdkit.Chem as Chem
f... |
ebac9acd767a339d3bb298649c9642fc2d14919b20f220bd41e5bbc033b9a26e | Python | 1,462 | 54 | #!/usr/bin/python
# This script appends utterances dumped out from XML to a Kaldi datadir
import sys, re
from xml.sax.saxutils import unescape
basename=sys.argv[1]
outdir = sys.argv[2]
if len(sys.argv) > 3:
mer_thresh=float(sys.argv[3])
else:
mer_thresh = None
# open the output files in append mode
#segmen... |
e2ae003c66fed07c9792138f91b74d02119b55a61f370f32ff53f680c2058555 | Python | 1,463 | 57 | import numpy as np
import numpy.testing as npt
import pytest
import nibabel as nib
from dipy.io.stateful_tractogram import Space
from dipy.io.streamline import StatefulTractogram
import AFQ.utils.volume as afv
import AFQ.data.fetch as afd
def test_patch_up_roi():
roi_bad = np.zeros((10, 10, 10))
roi_good =... |
e2e9c82f69e1b9cd2cf1540ce868eeeaaf6f62df2aa939b0809ed1ad48819afa | Python | 1,463 | 37 | import unittest
import curies
from linkml_runtime.loaders import json_loader
from oaklib import OntologyResource
from oaklib.converters.obo_graph_to_rdf_owl_converter import OboGraphToRdfOwlConverter
from oaklib.datamodels.obograph import GraphDocument
from oaklib.implementations import SparqlImplementation
from oakl... |
402a455f1cae185bcee81f0d220b96cdd0c9349734412744072bd358457c76c2 | Python | 1,467 | 47 | """Example code for plotting power maps from the state/mode covariances inferred
on time-delay embedded training data.
"""
import os
import numpy as np
from osl_dynamics.analysis import power, post_hoc
def get_data(name, output_dir):
if os.path.exists(output_dir):
print(f"{output_dir} already downloaded... |
aaae531cd76fd918a5fe4934cf80c5d309bc3a41a85b8116dd59684f9c2c9366 | Python | 1,467 | 44 | #! /usr/bin/env python3
# -*- coding:utf-8 -*-
# @Author: Vincent (Qing Wang)
# @Date: 2021-7-12 12:00:00
"""
======================================================
Using correcting the inconsistent studyUIDs of dicom files, if there are any, change them to match the first one.
Adapted by Qing Wang (Vincent) from htt... |
036de878eda77f0c409b649a9867869da48749b6c0555649b700d36836740726 | Python | 1,468 | 40 | import os, subprocess
BaseCase = __import__('base_case').BaseCase
class TestDownloadRootDetection(BaseCase):
def test_download_root_detection(self):
if not self.is_chromium() and not self.headed:
self.skipTest('xdotool does not work with headless firefox for some reason')
self.open_ma... |
5ef01953df7b7565dd860023a4508f159dde35ff574b00434a5868f6a4574236 | Python | 1,469 | 46 | import subprocess
import backend.startup as startup
def test_nvidia_detection_prefers_nvidia_smi(monkeypatch):
calls = []
def check_output(command, **_kwargs):
calls.append(command)
return b'NVIDIA GeForce RTX 3080\r\n'
monkeypatch.setattr(startup.subprocess, 'check_output', check_outpu... |
37d95c77094227e73957f16980e0b65fb66e1f2b22ce142315fdbca13ed81690 | Python | 1,470 | 37 | import os
from drugex import VERSION
from drugex.logs import logger
def getVocPaths(data_path, voc_files, mol_type):
voc_paths = []
for v in voc_files:
path = data_path + f"{v}_{mol_type}_voc.txt"
if not os.path.exists(path):
logger.warning(f'Reading {mol_type}_voc.txt instead of ... |
751ece206fd7c82d24d7e836793f387b97d0fba261726b0bfdfd64a88a64c873 | Python | 1,470 | 36 | import torch
import torch.nn as nn
from torchvision.transforms import transforms as tt
class Net(nn.Module):
def __init__(self, line, dropout):
# l1_in, l1_out = 900, 128
# l2_in, l2_out = 128, 1
# dropout = 0.5
l1_in, l1_out, l2_in, l2_out = line
super(Net, self).... |
75c729dfdf0f4e685df7583178f01de959cbc25de144629c5b5e4042bbe3b4db | Python | 1,470 | 45 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import random
import argparse
import glob
import os
parser = argparse.ArgumentParser()
parser.add_argument("--dir", type=str, required=True, help="path to folder containing images")
parser.add_argument("--tra... |
d6d671c9b89d23b987524f828c30ebcf7c2fcbbed466009974775693076a6583 | Python | 1,470 | 43 | import os
import sys
import numpy as np
class DatasetGenerator:
def __init__(self, data_dir, drop=True):
self.data = []
self.label = []
filelist = os.path.join(data_dir, "fea.lst")
labellist = os.path.join(data_dir, "label.lst")
with open(filelist, 'r') as fp:
fo... |
158d1f232ddec423cdf4e0384412fb6c2a00d1020b7decb28ec191d913a1b2a8 | Python | 1,472 | 29 | from functions import *
import numpy as np
import matplotlib.pyplot as plt
import pickle
starttime = datetime.now()
#Note that measurement is stochastic, results will differ slightly on each run
#Load dictionaries from pkl files to reproduce the plot as shown in the article
#Running this script required 0.6sec for nr... |
551f5d775d132d99a6d0f23dea9a8856191e81ed4f38675e5cb9e7134812b213 | Python | 1,473 | 42 | from experiment import setup_seed, stft_general_data, stft_general_test
from train import train
from utils.dataTrans import get_dataloader
from sklearn.model_selection import train_test_split
from model import Unquantified_2layer_CNN, Unquantified_2layer_CNN_sp, Unquantified_2layer_CNN_sp_test, VGG16_base, VGG16_no... |
b03b622da2bd23e2ec319e7b177e7f22bd492732cfb644d467e0a1e6f968349c | Python | 1,474 | 43 | import numpy as np
def load_mabe_data_task1(data_path):
"""
Load data for task 1:
Task 1 has multiple sequences
The vocaubulary denotes the behavior name to class number.
The vocabulary is all the same for all sequences in this task.
"""
data_dict = np.load(data_path, allow_pi... |
5fc89cfdcfa9dac037b4cd8b854961f20952b77c87eeb188af1f9056933d5532 | Python | 1,477 | 47 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
def tensors_filter(tensors, filters, combine_type='or'):
assert isinstance(tensors, (list, tuple)), '`tensors` shoule be a list or tuple!'
assert isinstance(filters, (str, list... |
682c895b29913b6d96a9b9b307f01246c608a9503a14c49d1c63bd3b474b2a2d | Python | 1,477 | 52 | # 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... |
74a1b4b4a403b983489baaaa577aeee7374c7ac0f76c76d13db8ce04829f2610 | Python | 1,478 | 52 | __author__ = "Johannes Köster"
__copyright__ = "Copyright 2018, Johannes Köster"
__email__ = "johannes.koester@protonmail.com"
__license__ = "MIT"
import os
from snakemake.shell import shell
extra = snakemake.params.get("extra", "")
java_opts = snakemake.params.get("java_opts", "")
def fmt_res(resname, resparams... |
42f64d3c95a8b4722fec42921c2274f84ba3e4d58f6b0aff9323667c7aa973d9 | Python | 1,479 | 36 | import torch
import pytest
import numpy as np
from ..spectral_projection import spectral_projection_divergence_free
@pytest.mark.parametrize("resolution", [(64, 64), (80, 60), (60, 80)])
@pytest.mark.parametrize("constraint_modes", [(64, 64), (50, 64), (72, 60)])
@pytest.mark.parametrize("dtype", [torch.float32, torch... |
724fd9a2fe417734f68e00c9d2ca990f0042cace106e7e5ab4e286d4c6e2ecba | Python | 1,479 | 33 | # 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... |
8e56cf9dc213444b1b4a442b36f46b4dd9b4ba729f4020402bc5f4081ba42f45 | Python | 1,480 | 41 | import numpy as np
import ddmr.utils.constants as C
class SummaryDictionary:
def __init__(self, model, batch_size, accumulative_gradients_step=None):
self.train_names = model.metrics_names
self.val_names = ['val_'+n for n in self.train_names]
self.batch_size = batch_size
self.acc_gr... |
c6749f94d8eb6546c30a81f46d220147777ad0f8e41234e2a441f2495a67ae78 | Python | 1,480 | 46 | import mediapipe as mp
import cv2
import time
import numpy as np
import pandas as pd
import os
mpPose = mp.solutions.pose
pose = mpPose.Pose()
mpDraw = mp.solutions.drawing_utils # For drawing keypoints
points = mpPose.PoseLandmark # Landmarks
path = "Code/Sample Image" # enter dataset path
data = []
... |
d950a7b40aec10cd990dfc35df9ee7057a2bf3e63948c599a102fd67fcc30a6c | Python | 1,480 | 46 | import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
from sklearn.ensemble import RandomForestRegressor, RandomForestClassifier
from sklearn.metrics import mean_absolute_error, mean_squared_error, mean_absolute_error
from pandas.api.types import is_string_dtype, is_numeric_dtype,... |
37bce54233a69da3635ed86cf14be6501133aad0de1563f18a40a1f1f27039e5 | Python | 1,482 | 35 | from .anchor_free_head import AnchorFreeHead
from .anchor_head import AnchorHead
from .atss_head import ATSSHead
from .centripetal_head import CentripetalHead
from .corner_head import CornerHead
from .fcos_head import FCOSHead
from .fovea_head import FoveaHead
from .free_anchor_retina_head import FreeAnchorRetinaHead
f... |
34c814378788cb654bc2e5127a0a89ae2c7a8167f94bf60a6fb3bd01691977e1 | Python | 1,483 | 60 | #!/usr/bin/env python3
import json
import os
import shutil
import sys
import numpy as np
indir = sys.argv[1]
cwd = os.getcwd()
os.chdir(indir)
os.makedirs('fsleyes', exist_ok=True)
shutil.copy2('ica_components.nii.gz', os.path.join('fsleyes', 'melodic_IC.nii.gz'))
d = np.genfromtxt('ica_mixing.tsv', skip_header... |
6b1f7a0063eff28030f53e8e823553fa758d2f185a3807d2fc8b02b3a08b5809 | Python | 1,483 | 44 | # 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... |
036047aecd0709d0106b88d5334775313baa2bf72bd8aa4a373b22555285bed5 | Python | 1,484 | 43 | import setuptools
import codecs
from setuptools.command.install import install
from io import open
import os
def read(rel_path):
here = os.path.abspath(os.path.dirname(__file__))
with codecs.open(os.path.join(here, rel_path), "r") as fp:
return fp.read()
def get_version(rel_path):
for line in rea... |
15ee8d9e9ccf59d7734c70119f20533402ca3331858e38ad8fac2628f9c8fa05 | Python | 1,484 | 38 | import multiprocessing
import mne
def preprocess_EEG(raw: mne.io.Raw, high_pass=None, low_pass=None, notch_freq=None, reference=None):
"""Filter and re-reference given mne.io.Raw object based on input values using mne.
Args:
raw (mne.io.Raw): Raw object holding EEG data.
high_pass (float, op... |
1fdaed99673923789c8582a6dc196a5326a76ee6aacc17f1ff1356fbc80bcb91 | Python | 1,484 | 64 | import torch
import numpy as np
import networkx as nx
import matplotlib.pyplot as plt
from tqdm import trange
from graphxai.datasets import Mutagenicity
from graphxai.utils import aggregate_explanations
dataset = Mutagenicity(root = '../../../explainers/mutagenicity/data', test_debug=True)
# Iterate through dataset, ... |
1c9c06ee5fdbc5964fae056c6abddef859b9a60e569a949f6e1b5d5cbd54b1a1 | Python | 1,486 | 32 | import os, sys
currentdir = os.path.dirname(os.path.realpath(__file__))
parentdir = os.path.dirname(currentdir)
sys.path.append(parentdir) # PYTHON > 3.3 does not allow relative referencing
from Brain_study.Train_Baseline import launch_train
import argparse
TRAIN_DATASET = '/mnt/EncryptedData1/Users/javier/ext_datas... |
5bc5590fdbfa601a75b539ba7b6e79d46d34bb60ee0779355d1471fb5033c0ac | Python | 1,486 | 47 | import os
import sys
import numpy as np
import torch
import esm
from Bio.PDB import PDBParser
# refdir = "/bml/ccm3x/reference/"
# outdir = "/bml/ccm3x/dataset/attn/"
refdir = sys.argv[1]
outdir = sys.argv[2]
d3to1 = {'CYS': 'C', 'ASP': 'D', 'SER': 'S', 'GLN': 'Q', 'LYS': 'K',
'ILE': 'I', 'PRO': 'P', 'THR... |
a122f81d37d3c8aeef3a2b7d1422e41a74bbf6763cf807409081bbbc47b232f5 | Python | 1,486 | 47 | import copy
import numpy as np
import torch
from tqdm import tqdm
# maximum size of targets stored in-memory for validation metrics computation,
# value derived experimentally using data loader of size 2000, batch size 64,
# 194 cell types, and 201 target features
MAX_TOTAL_VAL_TARGET_SIZE = 2000 * 64 * 194 * 201
d... |
6af2fcc3edd34847e2c18fbac59c344b09b7225ee960c8485b2bc9407a861176 | Python | 1,487 | 45 | # Copyright (c) 2026 Computer Vision Center (CVC) at the Universitat Autonoma de
# Barcelona (UAB).
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
import unittest
import carla
class TestWalkersSpawn(unittest.TestCase):
def test_walker_spawn(s... |
3f6171ea2c7e115c95a10fe96a23b7c87587af11408d29a6ef8366822363144a | Python | 1,488 | 96 | import json
def init():
f = open('law.txt', 'r', encoding = 'utf8')
law = {}
lawname = {}
line = f.readline()
while line:
lawname[len(law)] = line.strip()
law[line.strip()] = len(law)
line = f.readline()
f.close()
f = open('accu.txt', 'r', encoding = 'utf8')
accu = {}
accuname = {}
line = f.readlin... |
6c061b02e510291e7d501e6e1ff85447e72a3a55ddcb99d810e3075380711130 | Python | 1,488 | 42 | """ running the ntf over a range of frequencies."""
from ..forward import network_transfer_onlymacro as nt
import numpy as np
def run_local_coupling_forward(brain, params, freqs):
"""run_forward. Function for running the forward model over the passed in range of frequencies,
for the handed set of parameters (w... |
ac3b1054493c35353170f7f172eb1ec9ee1d2f90b76a68a4a6c38d528ea7ba00 | Python | 1,488 | 44 | # 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... |
43870e1d14aa4eb56f8fe67d3be0b91c71710b54467ec64bb24747edb021ac52 | Python | 1,489 | 42 | ## Template for saving
import tensorflow as tf
def array_to_tfrecords(X, y, output_file):
feature = {
'X': tf.train.Feature(float_list=tf.train.FloatList(value=X.flatten())),
'y': tf.train.Feature(float_list=tf.train.FloatList(value=y.flatten()))
}
example = tf.train.Example(features=tf.t... |
c084969140dca089d1d2b4c8a4e5c220ce75323caf0eedaf9105ac52a937a6c6 | Python | 1,489 | 63 | import os
if os.getcwd().endswith("UnitTests"):
os.chdir("..")
import json
from Classes.SearchModule import SearchModule
__author__ = 'Justas Birgiolas'
import unittest
class SearchModuleTest(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.search = SearchModule()
def test_purkc... |
a1145b6e50e606569da8b2b7574eea83ef85222ac78b5c363075b5449cb6d9a7 | Python | 1,490 | 39 | from __future__ import print_function
import os
import sys
"""Hacky tool to convert file system layout of MCG boxes downloaded from
http://www.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/mcg/
so that it's consistent with those computed by Jan Hosang (see:
http://www.mpi-inf.mpg.de/departments/computer-visio... |
a47416b37160e0ccc00ccc9c656ec6a3a019338a9b7859ffd8e2595ff4d71681 | Python | 1,491 | 40 | # 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... |
ef3aea5f3a525305fb92023aebeb561dfbe8881fbd59973002f67fbf8363f936 | Python | 1,491 | 40 | # 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... |
28c5f0e2391608b575e6786ad7ec070bbbb5a02e83daf3a64f9adb4f1cfa704f | Python | 1,492 | 26 | """Third-person chase camera on an autopilot vehicle (what tuto_G_pygame renders in its window)."""
import os, sys, queue
import carla
sys.path.insert(0, os.path.dirname(__file__)); import scene
OUT = sys.argv[1]; os.makedirs(OUT, exist_ok=True)
c, w = scene.connect(); tm = c.get_trafficmanager(8000); lib = w.get_bluep... |
2837ef447081daad99543566eb4bb0b9b98186632dc49b2334b406067e3c388b | Python | 1,494 | 49 | """
====================================
How to segment out only some bundles
====================================
The pyAFQ software can be configured to find all of its default set of white
matter pathways, or bundles. Alternatively, it can be configured to find only
some bundles. This example shows how to track and... |
0c65ddbef8dcf5301d7a95d7c21c45c57f7ff39d13af45e4e7698cfb24022ced | Python | 1,495 | 45 | import torch
import torch.nn as nn
import torch.nn.functional as F
import math
def rot_img(x, rot_mat):
grid = F.affine_grid(rot_mat, x.size())
x = F.grid_sample(x, grid)
return x
class rotation_loss(nn.Module):
def __init__(self):
super(rotation_loss, self).__init__()
self.loss = nn... |
3f5132bb8b78a60d2e210cf1a8de2e8632e65eebe8f72ada2140bc624c6e3f59 | Python | 1,496 | 69 | """Dual estimation.
In this script we estimate subject-specific means and covariances
given the group-level model.
"""
#%% Run ID and output directories
import os
from sys import argv
# We get the run ID from the command line arguments
if len(argv) != 2:
print("Please pass a run id, e.g. python 4_dual_estimatio... |
19b0c24a2f3109fecbdf69b90eb9c514e4944d518c53c521a18302442d8167c9 | Python | 1,497 | 41 | import torch
from graphxai.datasets import load_ShapeGGen
from graphxai.datasets.shape_graph import ShapeGGen
from graphxai.gnn_models.node_classification.testing import train, test
from graphxai.gnn_models.node_classification.testing import GCN_3layer_basic, GIN_3layer_basic, GCN_4layer_basic, GAT_3layer_basic
from g... |
75d786875bb75eeac62d3435be34885d9b5c465b5c69aa9c4bc2f51d57cceff6 | Python | 1,497 | 69 | """Dual estimation.
In this script we estimate subject-specific means and covariances
given the group-level model.
"""
#%% Run ID and output directories
import os
from sys import argv
# We get the run ID from the command line arguments
if len(argv) != 2:
print("Please pass a run id, e.g. python 4_dual_estimatio... |
825a714420c825201c4da5a36d50a57af97ed59f13212f2d3879ebc49ad1c376 | Python | 1,497 | 35 | # Copyright 2020-2022 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agre... |
1f83ac26b7ad68b49fd4c3b160538092c335a7e40507dcb56d3297010fff453a | Python | 1,499 | 48 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import glob
import os.path
import torch
try:
from torch.utils.cpp_extension import load as load_ext
from torch.utils.cpp_extension import CUDA_HOME
except ImportError:
raise ImportError("The cpp layer extensions requires PyTorch 0.4 o... |
8588587bbb0a939eec3966f10ad065f3ecf99557852343162a12119040ba02dc | Python | 1,499 | 39 | #!/usr/bin/env python3
# Apache 2.0
# This script truncates the rttm file
# using UEM file and writes it to a new rttm file
#
from __future__ import print_function
from __future__ import unicode_literals
import argparse
from scorelib.turn import trim_turns
import scorelib.rttm as rttm_func
from scorelib.uem import loa... |
3a42ccab090da408f8eb935b6252b170b07bec2902e3f520a013bb5bf60d1041 | Python | 1,500 | 41 | import torch
from graphxai.datasets import load_ShapeGGen
from graphxai.datasets.shape_graph import ShapeGGen
from graphxai.gnn_models.node_classification.testing import train, test
from graphxai.gnn_models.node_classification.testing import GCN_3layer_basic, GIN_3layer_basic, GCN_4layer_basic, GAT_3layer_basic
from g... |
40bc9cf98ec2c581ee4e6f79a5ef7e1cd93e261fbcc789cfb8a121e5998c4176 | Python | 1,502 | 54 | from pathlib import Path
import pandas as pd
import pytest
import navis
@pytest.fixture
def data_dir():
return Path(__file__).resolve().parent.parent / "navis" / "data"
@pytest.fixture(
params=["Path", "pathstr", "swcstr", "textbuffer", "rawbuffer", "DataFrame"]
)
def swc_source(request, data_dir: Path):
... |
49e84ed2d63492c2fdb21ac65703aa4828dd9ef1acff6838c3ebc1f0b04ae001 | Python | 1,502 | 63 | import numpy as np
import matplotlib.pyplot as plt
import sys
ID_ROW=0
REAL_ROW=1
GUESS_ROW=2
SCORE_1=5
SCORE_0=6
path = sys.argv[1]
file_name = path.split('/')[-1].split('.')[0]
with open(path) as f:
data = f.readlines()
p = 1000
n = len(data)
Y = np.ndarray(shape=(n,1), dtype=int, order='F')
T = np.ndarray(s... |
16f0ae3ecfab79f5b895dbce47f272feed7336a839815cda9a4766030f9ce28d | Python | 1,503 | 47 | class str_gen:
def basic_str(self):
b_s = ""
params_list = [p for p in dir(self) if not p.startswith("__") and not callable(getattr(self, p))]
for p in params_list:
k = getattr(self, p)
if isinstance(k, str):
b_s += p + ":" + k
elif... |
8809a951c407bdbd1766a40372a137e88c8880fc1391a51b99269e2d85fceca5 | Python | 1,503 | 46 | # -*- 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)
""... |
f74a676ccc77662c9edbfd7914c771cb6ebd1e7fda043007837b480440ace2d5 | Python | 1,505 | 43 | import pandas as pd
from drugex.data.corpus.corpus import SequenceCorpus
from drugex.data.corpus.vocabulary import VocSmiles
from drugex.data.datasets import SmilesDataSet
from drugex.data.processing import Standardization, CorpusEncoder, RandomTrainTestSplitter
from ..settings import *
def main():
if not os.path... |
093d72b084bdf0cdd3372aa4c42bff5551907534d60d7edf0ea0a4c2ad0ec50f | Python | 1,506 | 84 | # Libraries
import pandas as pd
import numpy as np
# Columns to map
BOOLMAP = {
'N': False,
'Y': True,
'n': False,
'y': True,
'No': False,
'Yes': True,
'no': False,
'yes': True,
}
MAPPINGS = {
'Gender': {
'M': 0,
'F': 1
},
'Admitted': BOOLMAP,
'Cough': B... |
28d558aa7647110c2527ed324c8a7c1666d16e9f7a62314ff58af295d2c1cd95 | Python | 1,507 | 34 | # 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... |
1d851f7014093bb55c1097ed3f3a9deb30e032f1c182d7b98f5a6cad481eb19d | Python | 1,508 | 41 | import logging
import unittest
from oaklib import get_adapter
from oaklib.conf import CONF_DIR_PATH
from oaklib.parsers import HPOA_G2D
from oaklib.parsers.association_parser_factory import get_association_parser
from tests import INPUT_DIR
G2D_INPUT = INPUT_DIR / "example-hpoa-g2d.tsv"
class HpoaG2DAssociationPars... |
333cde30983e7f2dda5dcfb24c462b890d293c1036638b5f5740b47b6428299c | Python | 1,508 | 36 | # 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... |
aaf3baefdc676c4c87e072053cf9426145eea0d787894a6745002b563ffb83de | Python | 1,508 | 36 | # 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... |
2a9a2f332cb44fe1b348e853b30de4a429a839ea7ea4e369dbe4e420ba0546d3 | Python | 1,509 | 42 | import os.path
import os
import glob
import re
import argparse
parser = argparse.ArgumentParser(description='Make Molgenis Compute samplesheet for Brainseq.')
parser.add_argument('fastq_dir', help='directory containing fastq files')
parser.add_argument('phenotype_file', help='file with sample info')
parser.add_argumen... |
5bf90f9d45e325e4d0a159846510e6d8a5031013d1e2fd943d813aa89cbd8896 | Python | 1,509 | 61 | import argparse
import pickle
import pandas as pd
from grr.ThresholdModel import modelsToRecords
parser = argparse.ArgumentParser()
parser.add_argument(
'models', nargs='+', help='Paths to pickled lists of models.'
)
parser.add_argument(
'-o',
'--output',
type=str,
required=True,
help='Where... |
6324872660a2eb09a844f1809143b154a1438d9a492a2f04d5333d468f5b825c | Python | 1,510 | 41 | import pandas as pd
import os
from drugex.data.corpus.vocabulary import VocGraph
from drugex.data.datasets import GraphFragDataSet
from drugex.data.fragments import FragmentPairsSplitter, FragmentCorpusEncoder, GraphFragmentEncoder
from drugex.data.processing import Standardization
from drugex.molecules.converters.fra... |
10c55cce82df50f9ed85e1033770f4d121aa0ce8c639b5ca51384f4263d6fdcf | Python | 1,511 | 46 | #!/usr/bin/env python3
import argparse
####################################
### Parse command-line arguments ###
parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument("EH_filename", type=str)
parser.add_argument("disease_locus_filename", type=str)
args = parser.p... |
73ebeb7816810d560461ce059896eaa4c5b0d05766b973cd6d3b64881f7c0464 | Python | 1,511 | 54 | from math import exp, lgamma
from typing import Tuple
def log_binomial_coefficient(n: int, k: int) -> float:
"""
Binomial coefficient (n choose k).
n: number of successes in sample
:param n:
:param k:
:return:
"""
return lgamma(n + 1) - (lgamma(k + 1) + lgamma(n - k + 1))
def hyperg... |
74015d59f670f4110bc0744e24ac8aba4e3fa09b1189ac80e8b95f80a6d4911b | Python | 1,511 | 46 | import torch
import torch.nn.functional as F
from torch_geometric.nn import global_mean_pool
from torch_geometric.nn import GCNConv
class GCN_2layer(torch.nn.Module):
def __init__(self, in_channels, hidden_channels, out_channels):
super(GCN_2layer, self).__init__()
self.conv1 = GCNConv(in_channels,... |
3e0c6d4e3a0c67b93160df43e22ff246054958899f0e07ab9d45a93fa4fe213b | Python | 1,512 | 45 | import logging
import dipy.tracking.utils as dtu
import numpy as np
logger = logging.getLogger('AFQ')
def get_percentile_threshold(mask, threshold):
zero_mask = mask == 0
mask[zero_mask] = np.nan
new_threshold = np.nanpercentile(
mask,
100 - threshold)
mask[zero_mask] = 0
return ... |
9d811914e0d8c2014c0461698a16799d5bb2813aac393c5dedf695bf728402ae | Python | 1,512 | 46 | import os
from subprocess import Popen, PIPE
from input_output.read_msms import read_msms
from triangulation.xyzrn import output_pdb_as_xyzrn
from default_config.global_vars import msms_bin
from default_config.masif_opts import masif_opts
import random
# Pablo Gainza LPDI EPFL 2017-2019
# Calls MSMS and returns the ... |
b71b3b3aeb67eae7c18209cc58ac8c22842d31561d0e9ada51d1f9fe7bdf685a | Python | 1,512 | 49 | # 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
#
# less required by applicable law... |
d4ae95a9752095219053e66157825e5611b1be326b6f76117330f2afdf2f6daa | Python | 1,512 | 44 | """Base Model for Semantic Segmentation"""
import torch.nn as nn
from models.baselines.resnetv1b import resnet50_v1b, resnet101_v1b, resnet152_v1b
__all__ = ['SegBaseModel']
class SegBaseModel(nn.Module):
def __init__(self, classes=2, aux=False, backbone='resnet50', pretrained_base=True):
super(SegBaseMo... |
fb089a176ab6d2fe358fa4b9a58f0ff4e3a31dad8f7fe542bcb0ff1153b11ce3 | Python | 1,513 | 34 | # 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... |
562fa8da171c72ff3ae14afa5b3f5ad3e34a9f237951851cb975209056f03eef | Python | 1,516 | 51 | import os
import numpy as np
import scanpy as sc
from sklearn.model_selection import KFold
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--datadir',type=str, default='default')
parser.add_argument('--size_threshold', type=int, default=1000)
args = parser.parse_args()
datadir = args.datad... |
52c9efce9bcf4e7c720f32282825f114dc6a36d7aa93d7c42f5844df4e8ce6a8 | Python | 1,517 | 59 | import torch
from pathlib import Path
from utils.data import make_trees_dataset
from utils.nnet import get_device
from hebbcl.logger import LoggerFactory
from hebbcl.model import ModelFactory
from hebbcl.trainer import Optimiser, train_on_trees
from hebbcl.parameters import parser
from joblib import Parallel, delaye... |
a85507bf415215ecdc4c6e87bc86567971eeb93091b2790779a6443d667b9538 | Python | 1,518 | 44 | # Unit tests for sima/motion/dftreg.py
# Tests follow conventions for NumPy/SciPy avialble 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 future import standard_li... |
de8769d0258647b3e2b10fb4d5392f42123a34b7ab58f279fca7d90203719425 | Python | 1,518 | 61 | import matplotlib.pyplot as plt
import platform
import seaborn as sns
from rl_analysis.util import merge_dict
all_fig_dct = {
"pdf.fonttype": 42,
"font.sans-serif": "Arial",
"font.family": "sans-serif",
"mathtext.fontset": "custom",
"mathtext.rm": "Liberation Sans",
"mathtext.it": "Liberation Sans:italic",
"m... |
d9a75e7ddcba18cb26d55d25fa4827eced889227830a9ac81567784bc826b5b2 | Python | 1,520 | 40 | # 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... |
902d0aa834a69aa40191698637d0d4efe7688cba09b77889d41de403fa0e274e | Python | 1,521 | 35 | #!/usr/bin/env python3
# Copyright 2019 Ashish Arora
# Apache 2.0.
import sys, io
import string
infile = io.TextIOWrapper(sys.stdin.buffer, encoding='utf-8')
output = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8')
spkorder_writer = open(sys.argv[1],'w', encoding='utf8')
array_id_error_dict={}
for line in in... |
1a53b562b42390479fb291f24376a8bf7c0827a20f91bd0acbbe561287c1c8d1 | Python | 1,522 | 55 | import os
import numpy as np
import pandas as pd
from sklearn.metrics import pairwise_distances
from src.data import load_metagraph
from src.io import savecsv
FNAME = os.path.basename(__file__)[:-3]
print(FNAME)
def stashcsv(df, name, **kws):
savecsv(df, name, foldername=FNAME, **kws)
mg = load_metagraph("G"... |
2f4d06a072cd218377fb1c4a01e9494797d39a4f457b47c4041c15634b9bc4b0 | Python | 1,523 | 50 | import torch.nn as nn
from collections import OrderedDict
class LeNet5(nn.Module):
"""
Input - 1x32x32
C1 - 6@28x28 (5x5 kernel)
tanh
S2 - 6@14x14 (2x2 kernel, stride 2) Subsampling
C3 - 16@10x10 (5x5 kernel, complicated shit)
tanh
S4 - 16@5x5 (2x2 kernel, stride 2) Subsampling
C5 ... |
d3d175520a9803df09c9e9e5430287a289c5f9e1cd8aa2fae397af33e38b9c1e | Python | 1,523 | 62 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Feb 22 20:54:01 2022
@author: th
"""
import numpy as np
def flatten_list_1d(act_ratio):
ph = np.empty((1,0))
ph = np.squeeze(ph)
for entry in act_ratio:
ph = np.concatenate((ph, entry))
return ph
def standardscal... |
1b719574362863a7c86a36074c3045ba536b22c141884f48753f15dde6813b16 | Python | 1,524 | 53 | import pymesh
import numpy
"""
read_ply.py: Read a ply file from disk using pymesh and load the attributes used by MaSIF.
Pablo Gainza - LPDI STI EPFL 2019
Released under an Apache License 2.0
"""
def read_ply(filename):
# Read a ply file from disk using pymesh and load the attributes used by MaSIF.
# filena... |
34d60d89cf64aa90d53e2b9d3e30dcbbf5620224388404fb8a8b91c4c7736c78 | Python | 1,524 | 41 | import torch
from torch_geometric.datasets import TUDataset
from graphxai.explainers import PGMExplainer
from graphxai.explainers.utils.visualizations import visualize_mol_explanation
from graphxai.gnn_models.graph_classification import GCN, load_data, train, test
dataset = TUDataset(root='data/TUDataset', name='MUT... |
3e45ee6273437db3da6338db1d9cf8cce76a4ccba1b4cf9b818d3aa7a289291f | Python | 1,524 | 41 | import pandas as pd
import os
from drugex.data.corpus.vocabulary import VocSmiles
from drugex.data.datasets import SmilesFragDataSet
from drugex.data.fragments import FragmentPairsSplitter, FragmentCorpusEncoder, SequenceFragmentEncoder
from drugex.data.processing import Standardization
from drugex.molecules.converter... |
41a57e9466071acdb18b4d25e2b779ac7fa6c7e6d061a3b79f4c16e365d6868e | Python | 1,525 | 43 | """Parser for GAF/HPOA and related association formats"""
from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import Iterable, Iterator, Optional, TextIO, Union
from oaklib.datamodels.association import (
Association,
NegatedAssociation,
ParserConfiguration,
)
from oaklib.par... |
dcf467e5efe26dee4c0bf1b074fcafba352848fe14941d2dc57f3fb1ef8b570a | Python | 1,529 | 36 | from utils.dataloaders import DataLoader
import csv
class CSVLoader(DataLoader):
def load(self):
with open(self.config.dataset.dataset_path, "rt", encoding='utf-8') as csv_file:
reader = csv.reader(csv_file)
data = next(reader)
print("Import csv...")
k = 0
... |
6a71a38a9a7aa7a79d26f9efc3fff23cd5f31815e28011100fa53bd7f6a69b48 | Python | 1,531 | 63 | __author__ = 'jieqing jiao'
__email__ = "jieqing.jiao@gmail.com"
# weighting scheme implementation based on https://www.ncbi.nlm.nih.gov/pubmed/16912378
from niftypad import kt
import numpy as np
def get_weight(dt, isotope='18F', a=1, t=None, r=None, tac=None):
if isotope == '12C':
half_life = 20.39 * ... |
78286d15c5a78566ab85eedfdec3f7eb794189b4cb0c313881caf1862a3a035f | Python | 1,531 | 40 | import argparse
import argparse, sys; sys.path.append('../..')
import random as rand
import torch
from metrics import *
import numpy as np
from graphxai.gnn_models.node_classification.testing import GIN_3layer_basic, GCN_3layer_basic, GSAGE_3layer
# ----------------------------
my_base_graphxai = '/home/owq978/GraphXA... |
e9455bce5d3665eb13ad935fbe2de8045cf6a2d507bb16befc202a988d3ab2e0 | Python | 1,531 | 23 | """Town stills with traffic: townshots.py OUTDIR W H name=x,y,z,yaw,pitch[,fov] ... (Cinematic, sunny afternoon)."""
import sys, os, queue, carla
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__))); import scene
out, W, H = sys.argv[1], sys.argv[2], sys.argv[3]; os.makedirs(out, exist_ok=True)
shots = [(a.sp... |
eac65c86c3926e16f4e0850ae2d0ea613163e705b7f63a18e467e6208ef0a87a | Python | 1,531 | 41 | from __future__ import division
from __future__ import print_function
from __future__ import absolute_import
import tflib as tl
import tensorflow as tf
import tensorflow.contrib.slim as slim
from functools import partial
conv = partial(slim.conv2d, activation_fn=None, weights_regularizer=slim.l2_regularizer(1e-4))
f... |
2b1c1f489c6a4cbbcc475fe3240d97a5fddd8c4e5a8d1bf7e8da96a0b35a1111 | Python | 1,532 | 45 | #!/usr/bin/env python
# Copyright 2015 Minhua Wu
# Apache 2.0
# convert acronyms in swbd decode result to fisher convention
# e.g. convert things like en_4156 B 414.26 0.65 u._c._l._a. to
# en_4156 B 414.26 0.16 u
# en_4156 B 414.42 0.16 c
# en_4156 B 414.58 0.16 l
# en_4156 B 414.74 0.17 a
from __future__ import d... |
6e0814f192e95a7e7be9ae758ebf366a61b77f7c91644b84862125f9cb9d040c | Python | 1,533 | 44 | # 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... |
ff2863f7bd115626a146930f7fac61d5573f05b6e0c7b5cf89eab0d87e4ad4c6 | Python | 1,533 | 41 | # Copyright 2020-2022 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agre... |
56376dd5f92d395a82e63fd490463596cfa1e94cff3871a6d46b3aa76b742e93 | Python | 1,535 | 50 | # Copyright 2021 Xiaomi Corporation (Author: Junbo Zhang, Yongqing Wang)
# Apache 2.0
# This script does phone-level pronunciation scoring by GOP-based features.
import sys
import argparse
import pickle
import kaldi_io
import numpy as np
from utils import round_score
def get_args():
parser = argparse.ArgumentP... |
9b8d4772b5dcd964c800901471bab4b4ae0c6d4547beb32f3da76da457112376 | Python | 1,536 | 48 | """Parser for GAF association formats"""
import csv
from dataclasses import dataclass
from typing import Iterator, Optional, TextIO
from oaklib.datamodels.association import Association, ParserConfiguration
from oaklib.parsers.xaf_association_parser import XafAssociationParser
@dataclass
class HpoaG2DAssociationPar... |
b181d7993f7258ffa9b817ee546698f1d41d394f7f3ebb24909d192e7d4df728 | Python | 1,537 | 36 | #!/usr/bin/env python3
#
# Copyright (c) 2018 Hyeshik Chang
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modi... |
6a1208214645c736828730d5b3e4174c2d3cdbffd4c1ded3d31a0c30da4c2bbe | Python | 1,538 | 42 | import torch
import torch.nn.functional as F
import numpy as np
import os, argparse
from scipy import misc
from lib.HarDMSEG import HarDMSEG
from utils.dataloader import test_dataset
parser = argparse.ArgumentParser()
parser.add_argument('--testsize', type=int, default=352, help='testing size')
parser.add_argument('--... |
b85e063ac28c8eaf85ffb80413dd1e2f82763995afb70d60612a1bec6eb94714 | Python | 1,539 | 27 | #!/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>.
"""Shared pytest CLI options for lens_validation/. pytest only picks up
pytes... |
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