sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
9f0e032104b9ad286634ca0bac03645f1860bd90797278b7eb54b981f4bdd78e | Python | 1,189 | 32 | """General Linear Model (GLM) and permutation testing.
Modules
-------
- :py:mod:`~osl_dynamics.glm.base` — :py:class:`DesignConfig` for specifying
regressors/contrasts and :py:class:`GLM` for fitting the model.
- :py:mod:`~osl_dynamics.glm.ols` — Ordinary least squares implementation.
- :py:mod:`~osl_dynamics.glm.p... |
3cae990b1ce4b83ddf58530b6e2962c82b3b38f84e58636608105b6fda08f128 | Python | 1,191 | 31 | """Command line interface for Selene.
Why does this file exist, and why not put this in ``__main__``? You might be tempted to import things from ``__main__``
later, but that will cause problems--the code will get executed twice:
- When you run ``python3 -m selene_sdk`` python will execute``__main__.py`` as a script. ... |
96c5b77e40a619805d7ee3dd220b9fdc033c0c1827ca7d9b45283da578a098ef | Python | 1,191 | 53 | '''
fires_to_geojson.py
Convert JSON fires data from NASA FIRMS into GeoJSON format
This makes it a lot easier to work with and visualize
'''
import glob
import json
import os
input_dir = './fires_v2'
output_file = './fires_v2/bali_fires.geojson'
input_files = glob.glob(os.path.join(input_dir, '*.json'))
print('F... |
24e295ef7bb93723fdd39ba6a6f3e6d91470067afe9ea0802b36bff1343eb65b | Python | 1,192 | 39 | # %%
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from pymaid_creds import url, name, password, token
import pymaid
rm = pymaid.CatmaidInstance(url, token, name, password)
import connectome_tools.process_matrix as pm
import connectome_tools.celltype as ct
import navis
... |
2187fb37cc23d02862a8caaf05988c0aa3a3201c9cc08951b517af7a695d04a1 | Python | 1,193 | 47 | from abc import ABC
from dataclasses import dataclass
from typing import Optional
from oaklib.implementations.sparql.abstract_sparql_implementation import AbstractSparqlImplementation
from oaklib.interfaces.mapping_provider_interface import MappingProviderInterface
from oaklib.interfaces.obograph_interface import OboG... |
3eeb8a70ab8020ee5e77f3ae84d1eab3e51b078d89fd1fb9b9b8820dc1a1059b | Python | 1,193 | 41 | # Copyright (c) Open-MMLab. All rights reserved.
from collections import OrderedDict
import numpy as np
class LogBuffer:
def __init__(self):
self.val_history = OrderedDict()
self.n_history = OrderedDict()
self.output = OrderedDict()
self.ready = False
def clear(self):
... |
dc5efbccf36efefdb67805729c7081c97eb0b994811c2be0a91ec799297d7ad6 | Python | 1,193 | 46 | import lxml.etree as ET
import sys
import re
import os
def main():
#DEBUG
#import pydevd
#pydevd.settrace('10.211.55.3', port=4200, stdoutToServer=True, stderrToServer=True)
# Read XML
xml = ET.parse(sys.argv[1])
try:
# Get the xml schema version
schemaURI = xml.getroot().get... |
4b5b2fdf41c62adfa3d8d50d4ffc19c8531c7d698a02831c84e56a55d4bd959e | Python | 1,194 | 32 | 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')
parser.add_argument('Genotype_directory', help='Directory to downl... |
5e86242a7c8a5471d677f7ffe6e47eddb1d458f633e93616b7cc94234c41cfcd | Python | 1,195 | 36 | import pytest
import numpy as np
from numpy.testing import assert_almost_equal, assert_array_almost_equal
from pycpd import affine_registration
def test_2D():
B = np.array([[1.0, 0.5], [0, 1.0]])
t = np.array([0.5, 1.0])
Y = np.loadtxt('data/fish_target.txt')
X = np.dot(Y, B) + np.tile(t, (np.shape(Y)... |
c08e8cde029ecbf37336fd59f3daa6eaa6434ebd370d45c4bd155f7bad57c33d | Python | 1,196 | 35 | from functools import partial
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from pycpd import rigid_registration
import numpy as np
import time
def visualize(iteration, error, X, Y, ax):
plt.cla()
ax.scatter(X[:,0], X[:,1], X[:,2], color='red', label='Target')
ax.scatter(Y[:,0], ... |
805566a6ba90db2a7bdbb24a3d1782f4bc4f0c5b7775433439e691888005f6f3 | Python | 1,197 | 33 | '''
Plot geometry & output forces (exerted by cilia on the fluid) & velocities.
Visualizing forces and velocities is tricky:
We want to average over several nearby points, otherwise we have too many arrows
Right now, I just average over one-dimensional indices -> works for cilia.
Applying this code to other geometries... |
66bb7f9beee12ed82d1c0e62085f4fa4ce7eed8605c16eeb8308c66b87519a7a | Python | 1,198 | 38 | from PyQt5.QtCore import QThread, pyqtSignal
from PyQt5 import QtNetwork
# ----------------------------------------------------------------------------
class TcpServer(QThread):
""" Defines the thread listening to the go signal from MATLAB.
"""
tcpsignal = pyqtSignal(str)
def __init__(self, port=823... |
9f9b11840ed28414c6dffa407bd58ee992f8d43b4554755ec13ea4507f229976 | Python | 1,198 | 61 | __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
class Select:
"""
A class for selecting chains and pockets in PyMOL.
Attributes
----------
Non... |
cf1a5bf5c155e42bb3c95e0089e9c357e0bdca65fce618f279f0ba9e92a98117 | Python | 1,199 | 35 | """
© 2022, ETH Zurich
"""
from rescoss_logp_ml.predict_with_trained_model import predict_with_trained_model
from rescoss_logp_ml.utils import ROOT_PATH, DATA_PATH, MODEL_FILENAMES
import os
import pandas as pd
import numpy as np
import pytest
import itertools
TEST_FIRST_N = 10 # faster tests and just want to check... |
ed2cda93c310b623f581da7dc6fc1fadfb558d3c5eabdf90d543630422176abe | Python | 1,199 | 38 | import sys, numpy as np
#from matplotlib import pyplot as plt
infile = sys.argv[1]
outfile = sys.argv[2]
tr = {}
rec = []
with open(infile) as f:
for i in f:
i = i.strip().split("\t")
if any(s in i for s in ['motif', 'zscore', 'end', 'start']):
header = i
else:
de... |
5d55be17ea844ba91577f8ae105596ba45d88e78538cc8c3ab76a2cca8c9120f | Python | 1,200 | 42 | import os.path
import tempfile
from unittest import TestCase
from drugex.data.corpus.corpus import SequenceCorpus
from drugex.data.corpus.vocabulary import VocGraph
from drugex.molecules.converters.standardizers import DefaultStandardizer
from drugex.molecules.suppliers import StandardizedSupplier
class CorpusTest(T... |
14dee3badd47e975704d4595488be0720b99f0f016b6c506c93a036d2250178a | Python | 1,201 | 54 | """Get inferred parameters.
"""
from sys import argv
if len(argv) != 3:
print("Please pass the number of states and run id, e.g. python 3_get_inf_params.py 8 1")
exit()
n_states = int(argv[1])
run = int(argv[2])
#%% Import packages
import os
import pickle
import numpy as np
from glob import glob
from osl_d... |
a6aaa411241615a8abdf4fdbaa1de0c6a2e0446f8cad52111f629dd23a9df8bd | Python | 1,202 | 30 | import sys
import torch
from torch_geometric.datasets import TUDataset
from graphxai.explainers import PGMExplainer
#from graphxai.explainers.utils.visualizations import visualize_mol_explanation
from graphxai.gnn_models.graph_classification import train, test
from graphxai.gnn_models.graph_classification.gcn import G... |
bc4f3c9443c44205bc7102904da068bef37f6cca2cc10dd2d327d5d294c78f87 | Python | 1,203 | 48 | __author__ = "Dennis Kao"
__copyright__ = "Copyright 2020, Dennis Kao"
__email__ = "dennis.kao@sickkids.ca"
__license__ = "BSD"
from snakemake.shell import shell
from os import path
import shutil
import tempfile
shell.executable("bash")
luascript = snakemake.params.get("lua_script")
if luascript:
luascriptprefi... |
e4454b622cd530f0c364a816da395792e588cd22435f2c0b1094ebadf4cfcd61 | Python | 1,203 | 24 | ####################################################################################################
# Copyright (c) 2019 - 2023, 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 ... |
068fa299006e83817e121e37c0a2bd3b725b1abdbffe87b8580e48873b24a22c | Python | 1,204 | 55 | """
Contain some simple helper functions
"""
import os
import shutil
import torch
import random
import numpy as np
def mkdir(path):
"""
Create a empty directory in the disk if it didn't exist
Parameters:
path(str) -- a directory path we would like to create
"""
if not os.path.exists(path)... |
46e7bb4d7382ee4c2599c49be3ad0394c8fcc5ffa29814894d40fdbc3ebc7495 | Python | 1,204 | 54 | """Plot results.
"""
#%% 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 5_plot_results.py 1")
exit()
id = int(argv[1])
# Check results directory exists
results_dir = f"results/run{i... |
a461d7d5df191156566558e4fd1c4d701eb7e161ee5d01763f4704fc36f3b336 | Python | 1,204 | 36 | import torch
from torch import nn
class IOULoss(nn.Module):
def forward(self, pred, target, weight=None):
pred_left = pred[:, 0]
pred_top = pred[:, 1]
pred_right = pred[:, 2]
pred_bottom = pred[:, 3]
target_left = target[:, 0]
target_top = target[:, 1]
targ... |
e0b83f83d0609a12d8a462624546ed049770c7591aeb41a2c443c609a57beafe | Python | 1,204 | 49 | #%%
import numpy as np
import pandas as pd
from pathlib import Path
# %%
decon_results = Path("./res/")
# %%
dfs={}
for file in decon_results.glob("decon*.csv"):
dfs[file.stem] = pd.read_csv(file,index_col=0)
# break
# dfs.append(pd.
# %%
all_decon_df = pd.concat(dfs)
# %%
all_decon_df.index.names = ["fil... |
ca6cede6b9cae1d00d9eaeb8a3ee0df1b0dd23ebfec735913a89b3e4db16bf24 | Python | 1,206 | 62 | import json
import thulac
from sklearn.externals import joblib
class Predictor(object):
def __init__(self):
self.tfidf = joblib.load('predictor/model/tfidf.model')
self.law = joblib.load('predictor/model/law.model')
self.accu = joblib.load('predictor/model/accu.model')
self.time = joblib.load('predictor/mod... |
ab26a6b4c55c542efb7562844f8faa0e46e58af227d60d61f088d9b22023b035 | Python | 1,207 | 43 | import os
import nibabel as nb
import numpy as np
import zipfile
TEMP_UNZIP_PATH = '/mnt/EncryptedData1/Users/javier/ext_datasets/LITS17/temp'
NII_EXTENSION = '.nii'
def save_nifti(data, save_path, header=None, verbose=True):
if header is None:
data_nifti = nb.Nifti1Image(data, affine=np.eye(4))
els... |
42a41a9e58bd7160c31d910e3afc36a6cd10cbc754743759080fc5b0b692513f | Python | 1,208 | 34 | # Copyright 2021 Google Research. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law... |
9103aade06a097c203e14601785f5993127d496f8d6613031f90e34288098320 | Python | 1,208 | 30 | import AIS_neighbors
import AIS_geopandas_tagging
import pandas as pd
import import_AIS
import functions_basic_sak as funsak
import trajectory
from tqdm import tqdm
from skimage import data, util, measure
from scipy.ndimage.measurements import label
import AIS_parameters
pd.set_option('display.max_columns... |
2592fe022dceff0597f49c988f22d03693ad84d5ec9fd432e044e7984f87b7f2 | Python | 1,209 | 44 | import torch
import os
from graphxai.datasets.load_synthetic import load_ShapeGGen
from graphxai.datasets import ShapeGGen
from graphxai.utils.explanation import Explanation
#SG = load_ShapeGGen('data/ShapeGGen/new_unzipped/SG_homophilic.pickle', root = '/Users/owenqueen/Desktop/HMS_research/graphxai_project/GraphXAI'... |
b570173da003cba62951b413e2102393197aa051047e8b5e22ad1dcd0343684f | Python | 1,209 | 50 | from __future__ import print_function
import sys
import struct
def create_index(tfrecord_file: str, index_file: str) -> None:
"""Create index from the tfrecords file.
Stores starting location (byte) and length (in bytes) of each
serialized record.
Params:
-------
tfrecord_file: str
P... |
bd86d06efd2176c85abcbdb58e6b0c632d23194b3fbee06142bbad37fef6c827 | Python | 1,209 | 37 | import unittest
from linkml_runtime.dumpers import yaml_dumper
from linkml_runtime.utils.introspection import package_schemaview
import oaklib.datamodels.validation_datamodel as vdm
from tests import output_path
class TestValidationDatamodel(unittest.TestCase):
def test_create(self):
"""
Tests ... |
e676b1cd6dc3a9042c18854e4d8d121c0d9fcb65d51d65fe5dd18128561b7297 | Python | 1,209 | 35 | import torch
from norse.torch import LIFAdExState
def save_states(x, save_states: bool, layer, state, additional_current=None):
if additional_current is not None:
if additional_current.shape[0] == 1:
tmp_additional_current = torch.zeros(
(len(x), additional_current.shape[1])
... |
5f20d399489f94d91423a89c5729cd483db5d88858c498357b470f73f3bc0af1 | Python | 1,212 | 32 | import torch
from torch_geometric.data import Data
def train(model: torch.nn.Module, optimizer: torch.optim.Optimizer,
criterion: torch.nn.Module, data: Data, losses: list = None):
model.train()
optimizer.zero_grad() # Clear gradients.
out = model(data.x, data.edge_index) # Perform a single fo... |
46934d3361955c538fdc2135bbb4f0b2dd3d45b9afee84b8f06a8a515a7b6ce5 | Python | 1,213 | 34 | import json
import unittest
import curies
from linkml_runtime.loaders import json_loader
from ndex2 import create_nice_cx_from_file
from oaklib.converters.obo_graph_to_cx_converter import OboGraphToCXConverter
from oaklib.datamodels.obograph import GraphDocument
from oaklib.interfaces.basic_ontology_interface import ... |
a031da47a95bf5d94fff1b3f22c69021f76d52213c4fa02953ccb4ed5364d0d1 | Python | 1,213 | 28 | # 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... |
e58b157dd4c748dd54b5d4523defee9ae583d15d525f13a6f75cdf90947543c1 | Python | 1,213 | 31 | # 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... |
59e1f7efc935932ed698d66f147e140fbb78a05c3abdf03d179e776f22ec5098 | Python | 1,214 | 52 | import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
tasks = [
"RomoTask1",
"RomoTask2",
"DMTask1",
"DMTask2",
"CtxDMTask1",
"CtxDMTask2",
"GoTask1",
"GoTask2",
"GoRtTask1",
"GoRtTask2",
"GoDlTask1",
"GoDlTask2",
]
# cmap = sns.cm.magma
def main():... |
86050bd9113de33bebd43bf1735abcfc1536c6ae0fe5ffda1136ffb2ee3d36d7 | Python | 1,214 | 39 | import random
import torch
from graphxai.explainers import GraphLIME
from graphxai.explainers.utils.visualizations import visualize_subgraph_explanation
from graphxai.gnn_models.node_classification import BA_Houses, GCN, train, test
n = 300
m = 2
num_houses = 20
bah = BA_Houses(n, m)
data, inhouse = bah.get_data(nu... |
beb7c00a35a6c52c35e698a77f806515bcf48f576d77b6b34d13d55a1e904576 | Python | 1,214 | 44 | import torch
import os
from graphxai.datasets.load_synthetic import load_ShapeGGen
from graphxai.datasets import ShapeGGen
from graphxai.utils.explanation import Explanation
#SG = load_ShapeGGen('data/ShapeGGen/new_unzipped/SG_homophilic.pickle', root = '/Users/owenqueen/Desktop/HMS_research/graphxai_project/GraphXAI'... |
d76c50a7e9ebbb37b44a0a57ee62a8b605a6c7568863f26ec68a008223c1d40f | Python | 1,214 | 21 | # Copyright (c) Open-MMLab. All rights reserved.
from .colorspace import (bgr2gray, bgr2hls, bgr2hsv, bgr2rgb, bgr2ycbcr,
gray2bgr, gray2rgb, hls2bgr, hsv2bgr, imconvert,
rgb2bgr, rgb2gray, rgb2ycbcr, ycbcr2bgr, ycbcr2rgb)
from .geometric import (imcrop, imflip, imflip_... |
dd6d0f3079a24179be399192f19364dd137b7c386d6fa3e8063faaae89b1cdc1 | Python | 1,215 | 38 | # 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 ast
import os
import unittest
REPO_ROOT = os.path.abspath(
os.path.join(os.path.dirname(... |
ee6a5ee6a7b6055978e1b58a4fac0dcf51042e34d609f80b82e5a6267d798cf1 | Python | 1,216 | 28 | from snakemake.shell import shell
log = snakemake.log_fmt_shell(stdout=True, stderr=True)
with open(snakemake.log[0], "w") as f:
sys.stderr = sys.stdout = f
family = snakemake.wildcards.family
sample = snakemake.wildcards.sample
ref_cache_cmd = "export REF_CACHE={snakemake.params.ref_cache}; export... |
2d7fd89676ec579bad9fbbe5c6c37724243ee8c66b48dc3e1d6ab408aadf4989 | Python | 1,217 | 41 | '''
Fix anterior and posterior positions in the morphology file, based on PIV.
Anterior and posterior ends picked by eye are swapped to be consistent with swimming direction.
This requires prior PIV analysis.
'''
import numpy as np
from file_management import *
import sys
from scipy.stats import circmean
from os.path i... |
c56520e4e8b6856ad50e1dd20325ca8d64b9b1db67650707f175f7770f958d2c | Python | 1,217 | 37 | import torch
from norse.torch.functional.lif_refrac import LIFRefracParameters, LIFRefracState
from cgtasknet.net.lifrefrac import SNNLifRefrac
def test_init_lif_refrac():
input_s, hidden_s, output_s = 100, 100, 100
SNNLifRefrac(input_s, hidden_s, output_s)
def test_set_custom_params_lif_refrac():
inpu... |
be1321463a1622f3e1d592c49e7108fad51856a83160082ab3406ffc68126fa3 | Python | 1,218 | 40 |
import pandas as pd
import numpy as np
import os
results_path = 'results/'
ignore_folders = ['task1_hparams']
resultfolders = [rf for rf in os.listdir(results_path) if rf not in ignore_folders]
for rfolder in resultfolders:
exppath = os.path.join(results_path, rfolder)
endname = 'metrics_test.csv'
csvfi... |
3292e8d47eb71b59105ae9535296750d2058def4677d7b576146795940f84c4e | Python | 1,219 | 36 | import neighbors
import loitering
import old_ports
import elevation
import coast_distance
import shipping_routes
import pandas as pd
import functions_basic_sak as funsak
import trajectory
from tqdm import tqdm
from skimage import data, util, measure
from scipy.ndimage.measurements import label
pd.set_opti... |
3d213844cae5ae71898ff44a13f812e41ffd7cf6a3da7e113c5d3825646876bf | Python | 1,219 | 39 | #!/usr/bin/env python
# Copyright 2016 Allen Guo
# 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
#
# THIS CODE IS PROVIDED *AS IS* BASIS, WITH... |
61b4b6aaf03fefcfe61e51a6eafff66109d274d9cea0dd37315554ef4b476150 | Python | 1,220 | 28 | # 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... |
7b3b70459614a0020817d66a91acaeff091632179251bf071c89bf2f313cd004 | Python | 1,221 | 28 | from qiskit import *
from functions import *
from datetime import datetime
#Load dictionaries from pkl files to reproduce the plot as shown in the article
#Running this script required 1.3sec on a MacBook Pro with a 2.3GHz Quad-Core processor and 16 GB of RAM
starttime = datetime.now()
toymodelpath = "./toyBNQuantum.... |
45201b959c41b221ca09007b348a41b981d54642481992f37d31076e49ba3a79 | Python | 1,222 | 41 | import mne
import pandas as pd
def save_annotations_csv(raw: mne.io.Raw, save_file_path: str):
"""Saves annotations of given mne.io.Raw object to save_file_path as .csv file.
Args:
raw (mne.io.Raw): Raw object holding EEG data.
save_file_path (str): Path at which to save annotations file.
... |
5f7a41314dcd5181daae744457659df1dfe1a2abdcb089872408522bfeed0ed6 | Python | 1,222 | 31 | import torch
from os.path import join
import glob
from gssc.train.DataManage import PSGDataSet
### basic example of how to make a PSG Dataset object for use in training, etc.
# define where the MNE -raw.fif files are, and also where the resulting output
# files will be saved.
proc_dir = "/your/directory/path" # where... |
8d2579d1cedb7d21f080bf49e75d0df1e562b1b0b9631cce47f4e894ac5c2de8 | Python | 1,222 | 39 | import logging
import unittest
from oaklib.implementations import SqlImplementation
from oaklib.resource import OntologyResource
from oaklib.utilities.mapping.cross_ontology_diffs import (
calculate_pairwise_relational_diff,
)
from tests import EXTERNAL_DB_DIR
DB_FOLDER = EXTERNAL_DB_DIR / "unreciprocated-mapping... |
c22594172dfd88bc660a9eb6ca3db5ceb49ba69d955d23ba250cf565994ba457 | Python | 1,222 | 27 | ####################################################################################################
# Copyright (c) 2019 - 2023, 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 ... |
285ba881bf9c7300f5540ae826cd1d1bb52df239522811a9263cd1269a3ec459 | Python | 1,223 | 43 | #!/usr/bin/env python
import unreal
import argparse
import json
import os
import subprocess
"""Generic function for running a commandlet with its arguments."""
ue4_path = os.environ["UE4_ROOT"]
uproject_path = unreal.Paths.project_dir() + ("CarlaUnreal.uproject")
run = "-run=%s" % ("GenerateTileCommandlet")
print("B... |
c84012af5b9efdebc6c6dc18957aa2db52a3514dcba028c9527ac07c94ab3026 | Python | 1,223 | 39 | from __future__ import print_function
#!/usr/bin/env py
# Converts a romanized ECA word list (symbol table) to
# a version in the arabic script
import sys
import codecs
if len(sys.argv) < 3:
print("USAGE: local/convert_symtable_to_utf.py [SYMTABLE] [ECA-LEXICON]")
print("E.g., local/convert_symtable_to_utf.p... |
d73794901173aa7a197350223ffbae9256330a02ac623f9868cc21259d121bc0 | Python | 1,223 | 30 | from ddmr.utils.nifti_utils import save_nifti
from tqdm import tqdm
import os
import h5py
import ddmr.utils.constants as C
DATASET_LOCATION = '/mnt/EncryptedData1/Users/javier/vessel_registration/3Dirca/dataset/EVAL'
DATASET_NAMES = ['Affine', 'None', 'Translation']
DATASET_FILENAME = 'volume'
if __name__ == '__main... |
1eb83bcc5e03a8a6a818893e6f2a1f3622a17cad2a6a348b8a514a245076ce6e | Python | 1,224 | 32 | from Bio.PDB import *
# Exclude disordered atoms.
class NotDisordered(Select):
def accept_atom(self, atom):
return not atom.is_disordered() or atom.get_altloc() == 'A'
def extractHelix(helix, infilename, outfilename, chain_ids=None, includeWaters=False,\
invert=False):
pa... |
3b20aaa431a8cf6bb38199175fe46ae7fe31456815770f2378863489e980b5c0 | Python | 1,224 | 43 | import torch.nn as nn
class GramMatrix(nn.Module):
def __init__(self):
super(GramMatrix, self).__init__()
def forward(self, x):
b, c, h, w = x.size()
feature = x.view(b, c, h * w)
feature_t = feature.transpose(1, 2)
gram = feature.bmm(feature_t)
b, h, w = gram.... |
abd4bf61ed3ef2655cb92d472bea3189a0aa6d12a256bd86ef26de9c78acb602 | Python | 1,224 | 33 | from setuptools import setup
setup(name='hd_gliomouse',
version='1.1',
packages=["hd_gliomouse"],
description='Tool for brain tumor segmentation in mice. This is the result of a joint project between the Department of '
'Neuroradiology at the Heidelberg University Hospital and the ... |
eb007123339f3b269579ca73c4d452aae49ee76673fa5c3948631f054154c3a9 | Python | 1,224 | 43 | import os
import numpy as np
import sys
from SBI.structure import PDB
from default_config.masif_opts import masif_opts
in_fields = sys.argv[1].split("_")
pdb_id = in_fields[0]
if not os.path.exists(masif_opts["ligand"]["ligand_coords_dir"]):
os.mkdir(masif_opts["ligand"]["ligand_coords_dir"])
# Ligands of inter... |
f6e330fd506db69e912114288565809c6b28350ca5e94888630a3a329310c6eb | Python | 1,224 | 29 | ###
# #%L
# Triangulated surface for deforming in 3D.
# %%
# Copyright (C) 2013 - 2023 University College London
# %%
# 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, incl... |
2235863c97156bdae9e3c5862b2e4d2192dfe55b04b0d738ce732c4dec8a2a8a | Python | 1,225 | 36 | import unittest
from linkml_runtime.dumpers import yaml_dumper
from linkml_runtime.utils.introspection import package_schemaview
from oaklib.datamodels import obograph
from oaklib.datamodels.vocabulary import IS_A
from tests import output_path
class TestOboGraphDatamodel(unittest.TestCase):
def test_create(self... |
929a93630b0aeed6026ba480071bdd981f15aa8614fb4f54e77fda41c5a664bf | Python | 1,225 | 41 | from typing import Any, List, Optional
from zencfg import ConfigBase
from ..distributed import DistributedConfig
from ..models import ModelConfig, FNO_Medium3d
from ..opt import OptimizationConfig, PatchingConfig
from ..wandb import WandbConfig
class MHD64OptConfig(OptimizationConfig):
n_epochs: int = 600
le... |
d184e84fdd3c4eaf7c6a5cd84e057135b936521295f0734ee086bc4dac68a7aa | Python | 1,226 | 48 | import argparse
import os.path as op
from glob import glob
import pandas as pd
def _get_parser():
parser = argparse.ArgumentParser(description="Get subjects to download")
parser.add_argument(
"--dset",
dest="dset",
required=True,
help="Path to fMRIPrep directory",
)
pa... |
e612ac33a5fb8ea0ccd3af65df48dc0f49b3176ea692b19e52dda61beb5672a6 | Python | 1,226 | 36 | # python 3.7
"""Helper functions."""
from .model_settings import MODEL_POOL
from .stylegan_generator import StyleGANGenerator
from .stylegan_encoder import StyleGANEncoder
from .perceptual_model import PerceptualModel
__all__ = ['build_generator', 'build_encoder', 'build_perceptual']
def build_generator(model_name,... |
fc3cd58105ef89ad5584890e7f4e135722de78941d3b6dc851d789e8ad4b0323 | Python | 1,226 | 37 | import torch.nn as nn
from tools.utils import parse_net_config, sort_net_config
from .operations import OPS, conv_bn
class Block(nn.Module):
def __init__(self, in_ch, block_ch, ops, stride, use_se=False, bn_params=[True, True]):
super(Block, self).__init__()
layers = []
for i, op in enum... |
1da217cea720eb44e197e59ca737f0f1a67dfea5aa19795d578469747cde7031 | Python | 1,229 | 34 | # -*- coding: utf-8 -*-
"""Preview
Code for 'Inf-Net: Automatic COVID-19 Lung Infection Segmentation from CT Scans'
submit to Transactions on Medical Imaging, 2020.
First Version: Created on 2020-05-13 (@author: Ge-Peng Ji)
"""
from PIL import Image
import os
import numpy as np
def split_class(pred_path, img_name,... |
ad356d66b69f3bdd7de399315a0f69fd53e2f3f61c2f93c6450fa6a32d77aae8 | Python | 1,229 | 50 | '''
2021-03-12: separate geometry and physics in order to have 1 geometry file for different frequqncies sets
'''
import numpy as np
import carpet
import carpet.lattice.triangular as lattice
## Parameters
# Geometry
nx = 16
ny = 16 # even number
N = nx * ny
a = 18 # [um] lattice spacing
## Initialize
# Geometry
d... |
32c80b2079f41c7ea54bcd86905a4b9c30587b0dc6be255c9bba6cc04854e111 | Python | 1,230 | 47 | from setuptools import find_packages, setup
setup(
name="rl_analysis",
packages=find_packages(),
version="1.0.0",
platforms=["mac", "unix"],
description='Python package and notebooks corresponding to "Spontaneous behavior is structured by reinforcement without explicit reward"',
author="wingill... |
aabe0ced3abf8d1115da0a7c8f8e4b67b1f7417fb5341df5e879bb95612f4f5a | Python | 1,230 | 40 | import os
import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)
import numpy as np
from subprocess import Popen, PIPE
from IPython.core.debugger import *
import sys
from Bio.PDB import *
import pyflann
# Go to directory
struct_dir = 'pdbs/'
trans_output_bin = "/home/gainza/lpdi_fs/seeder/data... |
15031b0102651df9ba883df74624e82e566d04feb1b31ad402dbe7bf3a2b3d94 | Python | 1,231 | 40 | from typing import Any, List, Optional
from zencfg import ConfigBase
from .distributed import DistributedConfig
from .models import ModelConfig, FNO_Medium2d
from .opt import OptimizationConfig, PatchingConfig
from .wandb import WandbConfig
class NavierStokesOptConfig(OptimizationConfig):
n_epochs: int = 600
... |
ac44682f01e36c3fc0155ec315c5d8c3898fbef984529edff44638e56179efc2 | Python | 1,231 | 30 | import numpy as np
from scipy.stats import beta, chi2
from scipy.stats import combine_pvalues as scipy_combine_pvalues
from scipy.stats import ks_1samp, uniform
def combine_pvalues(pvalues, method="fisher"):
pvalues = np.array(pvalues)
scipy_methods = ["fisher", "pearson", "tippett", "stouffer", "mudholkar_g... |
ad1a4a9e6cc791c34ba7d6a2555f3355603caf18abea6a40784915accf6b1193 | Python | 1,231 | 28 | from setuptools import setup
long_description = """A library that provides feature importances, based upon
the permutation importance strategy, for general scikit-learn
models and implementations specifically for random forest out-of-bag scores.
Built by Terence Parr and Kerem Turgutlu.
See <a href="http://explained.a... |
4fd4255565fb06acaeb46bf430f6848e5db7774be048c734d99a174a8898dfd2 | Python | 1,232 | 53 | #%% IMPORT MODULES
from __future__ import division
import os
import pickle
from grr.cell_class import Cell
from grr import MiniDetector
#%% LOAD DATA
DATA_PATH = os.path.join('data', 'raw', '5HT', 'GABA_synapses')
mIPSC_fnames = ['18o23003.abf', '18o23004.abf', '18o23005.abf']
mini_recs = Cell().read_ABF(
[o... |
cfde08a1ad836127ee3157e6ddb0b1c5fe036818ab6ec13c843c791a5a2a36c5 | Python | 1,233 | 28 | from argparse import ArgumentParser
from mmdet.apis import inference_detector, init_detector, show_result_pyplot
def main():
parser = ArgumentParser()
parser.add_argument('--img', help='Image file')
parser.add_argument('--config', help='Config file',default='./configs/mask_rcnn/mask_rcnn_r101_fpn_1x_coco... |
5aaa89ffc1022fb79a10584035eb021c9ae05c73ab35f8dd7861bfcdaeba4cf1 | Python | 1,236 | 50 | # 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... |
69d1bc0b5bb0d34bc98457bc170f8541270304f13ba25c5984243a831bd27b33 | Python | 1,237 | 41 | import torch
from torch.autograd import Variable
import numpy as np
import collections
__all__ = ['as_variable', 'as_numpy', 'mark_volatile']
def as_variable(obj):
if isinstance(obj, Variable):
return obj
if isinstance(obj, collections.Sequence):
return [as_variable(v) for v in obj]
elif i... |
d93550a7e0641172893aa058d3a8dbee40bc0d7d9a55f7ee7d9c84d85e8f31ee | Python | 1,237 | 32 | import torch.nn as nn
class ConvNorm(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size=1, stride=1,
padding=None, dilation=1, bias=True, w_init_gain='linear'):
super(ConvNorm, self).__init__()
if padding is None:
assert(kernel_size % 2 == 1)
... |
eaf07c342bc8342bc11d742b3c9cfc6ffb6bdce0744c7df1bb21382fb512baa8 | Python | 1,239 | 24 | from .base_roi_head import BaseRoIHead
from .bbox_heads import (BBoxHead, ConvFCBBoxHead, DoubleConvFCBBoxHead,
Shared2FCBBoxHead, Shared4Conv1FCBBoxHead)
from .cascade_roi_head import CascadeRoIHead
from .double_roi_head import DoubleHeadRoIHead
from .dynamic_roi_head import DynamicRoIHead
fro... |
0e04589476554a459cd6c3c82b3c203ce38f5981259002f11cf5e0dab5eb122e | Python | 1,240 | 30 | from snakemake.shell import shell
log = snakemake.log_fmt_shell(stdout=True, stderr=True,append=True)
family = snakemake.wildcards.family
outdir = snakemake.params.outdir
tool = snakemake.params.tool
pythonpath = tool.replace("bin", "")
python = " export PYTHONPATH={pythonpath}; "
# Temporary fix until mity fixes b... |
fc51b6d5f5764d394869fb19f35046dd6f2896773f6b56633adcad2c07868ff9 | Python | 1,240 | 41 | # -*- coding: utf-8 -*-
# @Author : WenHan
import numpy as np
from models.net_q import QMyFuseModel
from sklearn.metrics import accuracy_score, f1_score, confusion_matrix
from tqdm import tqdm
# This script should be only used for quantized performance evaluation!
# To test the inference speed, please use tst_keras_... |
21956c8444285f4e43646f63e6741367c5a4ce77f7542b87b88f7101b35ff31a | Python | 1,241 | 33 |
import argparse
import os
import torch
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Convert MoCo Pre-Traind Model to DEiT')
parser.add_argument('--input', default='', type=str, metavar='PATH', required=True,
help='path to moco pre-trained checkpoint')
... |
85f32696e8b90447323cb589d4bfae81165205922fbe3bb014d8d9c31c437373 | Python | 1,241 | 46 | # %%
#
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 pymaid_creds import url, name, password, token
import pymaid
import connectome_tools.cluster_analysis as clust
import connectome_too... |
a53f043fd893c6b73a7443c00ab1b9f1529bace4e468647803a7a655976b8004 | Python | 1,242 | 42 | from typing import Any, List, Optional
from zencfg import ConfigBase
from .distributed import DistributedConfig
from .models import ModelConfig, FNO_Small2d
from .opt import OptimizationConfig, PatchingConfig
from .wandb import WandbConfig
class DarcyOptConfig(OptimizationConfig):
n_epochs: int = 300
learnin... |
0b9becf01b38914a0d140573d0e403ec95199a7adad1ea2d7cb1441b9d9f79a7 | Python | 1,243 | 43 | import numpy as np
def cm2inch(*tupl):
"""
Convert centimeter tuple to inch tuple for setting figure size in matplotlib
"""
inch = 2.54
if isinstance(tupl[0], tuple):
return tuple(i/inch for i in tupl[0])
else:
return tuple(i/inch for i in tupl)
def remove_box(ax, type = 'vert... |
85b8ee3cce2a8645df84e1b567a4dede3788fa321927e933deddf742bd52c4db | Python | 1,245 | 38 | # 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... |
0a44f506c5015a3fc439d33fe455099f6c295afd681e7b9b3ea1d44288718d5b | Python | 1,246 | 45 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import unetsl.model
import unetsl.data
import skimage.draw
import sys
import numpy
if __name__=="__main__":
print("usage: box_detect_bristles.py model.h5 input.tif output.tif")
img, _ = unetsl.data.loadImage(sys.argv[2])
model = unetsl.model.loadModel(sys.ar... |
e3b8e34e112afb74099d4434fbe17025217d083c0d567f5585a7ff2eacd0b722 | Python | 1,246 | 42 | import lib
import numpy
import theano
import theano.tensor as T
import lasagne
# from theano.compile.nanguardmode import NanGuardMode
import math
import time
import locale
locale.setlocale(locale.LC_ALL, '')
def print_params_info(params):
"""Print information about the parameters in the given param set."""
... |
6334cad96e56916397932048ce2d4c86cce85c6d95c26ea3a050037b5fc1abda | Python | 1,247 | 40 | #!/usr/bin/env python
# coding: utf-8
#
# Author: Kazuto Nakashima
# URL: https://kazuto1011.github.io
# Date: 19 February 2019
from __future__ import absolute_import, print_function
import torch
import torch.nn as nn
import torch.nn.functional as F
from .resnet import _ResLayer, _Stem
class DeepLabV1(nn.Sequ... |
ae754d17213b3c6d374e18861a5bb8726f25958abeac23994c59091814a880d8 | Python | 1,247 | 48 | import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
tasks = [
"RomoTask1",
"RomoTask2",
"DMTask1",
"DMTask2",
"CtxDMTask1",
"CtxDMTask2",
"GoTask1",
"GoTask2",
"GoRtTask1",
"GoRtTask2",
"GoDlTask1",
"GoDlTask2",
]
# cmap = sns.cm.magma
def main():... |
5c58e2e7e6bf0c75c57126d288e30f652d76dcb16c4dbaf33b284dfff44ce2df | Python | 1,248 | 39 | import numpy as np
# import mpmath as mp
def ntf_laplace(C,L1,L2,Tau,nroi,alpha,tau_e,tau_i,tauC,gei,gee,gii,s,noisein,trange,nr,dt):
nroi = C.shape[0]
K = nroi
# Cortical model
Fe = np.divide(1 / tau_e ** 2, (s + 1 / tau_e) ** 2)
Fi = np.divide(1 / tau_i ** 2, (s + 1 / tau_i) ** 2)
Hed = (1... |
e4dd0a7c79cc9a319dd3ce654e44650759ef78664b177cd0e18d284b18589eb1 | Python | 1,248 | 50 | '''
Bring together data from multiple sessions with optogenetic testing
of vowel discrimination in noise by F1706_Mimi
Tested in white elephant with sounds in restricted noise only, varying vowel in level and thus SNR.
'''
from datetime import datetime
import pandas as pd
from pathlib import Path
parent_dir = P... |
7b7ef85ed28a3ef3848336f487c8bde350eda1daf34be62aa5f6d1035b411da5 | Python | 1,249 | 37 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import os
from maskrcnn_benchmark.utils.imports import import_file
def setup_environment():
"""Perform environment setup work. The default setup is a no-op, but this
function allows the user to specify a Python source file that performs
... |
b75394d758f22e8ad2ec51884e705958947a4d5c601a7c1a6428271dfe81589a | Python | 1,249 | 35 | import torch
import torch.nn as nn
class Dropped_Network(nn.Module):
def __init__(self, super_model):
super(Dropped_Network, self).__init__()
# static modules loading
self.output_indices = super_model.output_indices
self.sub_obj_list = super_model.sub_obj_list
self.alphas_n... |
8f2bfe61ab3a5ca927d66c4d49fab316c5d26d9eaf19690c42746645e4064a9e | Python | 1,250 | 37 | from dataclasses import dataclass
from ontoportal_client import BioPortalClient
from oaklib.implementations.ontoportal.ontoportal_implementation_base import (
OntoPortalImplementationBase,
)
@dataclass
class BioPortalImplementation(OntoPortalImplementationBase):
"""
A :ref:`OntoPortal` implementation th... |
a24706b6135d48f62a924f6353c339b2eddd55cea8621c67ff435d5c125ece1e | Python | 1,250 | 44 | #!/usr/bin/env python
# Keep track of the best value we're seen so far in a series of calls.
# This is pretty elaborate. But this way we're got all the gubbins in
# one place, and the calls to it in the main body of the program are
# simple. The parent script was starting to fill up with "find the
# best one" clutter... |
3b02850c499a00c64755d08bd5bcaf9fe320d11afde8c0b18d156c49e98d72c7 | Python | 1,251 | 24 | # 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... |
ed07dddef5d1920cfd3be9a55569fb4a0851483ff32e41c7c471ec1d2d18f036 | Python | 1,251 | 42 | # Copyright 2021 Xiaomi Corporation (Author: Junbo Zhang, Yongqing Wang)
# Apache 2.0
# This script does phone-level pronunciation scoring by GOP values.
import sys
import argparse
import pickle
import kaldi_io
from utils import round_score
def get_args():
parser = argparse.ArgumentParser(
description=... |
4d606a24fbcfe9ae7272a1f2c499881b45171b93a95c387d5d8a69dded2851af | Python | 1,252 | 28 | # 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... |
a4e098fa8ad8ca6a6decf74a4620f3961f81ab32d41a9bb6cc93e579cce552e3 | Python | 1,253 | 53 | # -*- coding: utf-8 -*-
"""
Created on Fri Feb 18 13:00:49 2022
@author: csb
"""
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
sns.set_theme(context='notebook', style='ticks',font='arial',font_scale=1.2)
#%% Bistable
data=pd.read_csv('Bistable.csv')
f, ax = plt.subplots(figsize=(5,4)... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.