# -*- coding: utf-8 -*-
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# Copyright (C) Laboratory of Imaging technologies,
# Faculty of Electrical Engineering,
# University of Ljubljana.
#
# This file is part of PyXOpto.
#
# PyXOpto 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 the License, or
# (at your option) any later version.
#
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
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################################# End license ##################################
import os
import os.path
from typing import List
import numpy as np
import jinja2
from xopto.dataset import DATASET_PATH, MCVOX_TEMPLATE_PATH
from xopto.dataset.render import common
from xopto.dataset.render.mcml import DEFAULT_WAVELENGTH, RI_DIGITS
DEFAULT_WAVELENGTH = common.DEFAULT_WAVELENGTH
RI_DIGITS = common.RI_DIGITS
RI_WATER = round(common.RI_WATER(DEFAULT_WAVELENGTH), RI_DIGITS)
CONFIG = {
'materials': {
'surrounding': {'mua': 0.0001e2, 'mus': 1.0000e2, 'g': 1.0, 'n': RI_WATER},
'epidermis': {'mua': 16.5724e2, 'mus': 375.9398e2, 'g': 0.9, 'n': RI_WATER},
'dermis': {'mua': 0.4585e2, 'mus': 356.5406e2, 'g': 0.9, 'n': RI_WATER},
'blood': {'mua': 230.5427e2, 'mus': 93.9850e2, 'g': 0.9, 'n': RI_WATER}
},
'voxelization': {'nx': 201, 'ny': 201, 'nz': 200, 'voxel_size': 5.0e-6},
'epidermis_thickness': 100e-6,
'vessel_depth': 'np.round(np.linspace(200e-6, 800e-6, 25), 6)',
'vessel_diameter': 200e-6,
'num_packets': 1000e6,
'batch_packets': 10e6,
'rmax': 25e-3,
'root_storage_dir': os.path.join(DATASET_PATH, 'data'),
}
[docs]def render_mcvox_fluence(target_dir: str = None, config: dict = None,
method: str = None, cache: bool = False,
cl_device: str = None, cl_index: int = 0,
cl_build_options: List[str] = None,
test: bool = False, verbose: bool = False):
'''
Render templates with the given configuration.
Parameters
----------
target_dir: str
Root directory for the dataset. The scripts will be rendered into
"run" subdirectory and the dataset data will be saved into the data
subdirectory. If None, the parent directory of this file will serve
as the root directory.
config: dict
Configuration / context to use when rendering the run scripts. If None,
the default configuration will be used.
method: str
Monte Carlo stepping method. One of "ar" "aw" or "mbl".
cache: bool
Enables fluence accumulator cache.
cl_device: str
Default OpenCL device name or None. The value can be also set through
the CL_DEVICE environment variable.
cl_index: int
OpenCL device index (if multiple OpenCL devices of the same kind
are installed). The value can be also set through the CL_INDEX
environment variable.
cl_build_options: List[str]
A list of OpenCL build options.
See :py:class:`~xopto.cl.cloptions.ClBuildOption` for more details.
test: bool
Do a test run. The run scripts will be rendered but not saved. This
option will automatically enable the verbose mode.
verbose: bool
Enables verbose reporting.
'''
if verbose:
print('Rendering run scripts for MCVOX.')
if config is None:
config = CONFIG
if target_dir is None:
target_dir = os.getcwd()
if test:
verbose = True
if cl_build_options is None:
cl_build_options = []
else:
cl_build_options = [str(item) for item in cl_build_options]
root_dataset_dir = os.path.join(target_dir, 'data')
run_script_dir = os.path.join(target_dir, 'run', 'mcvox')
if verbose:
print('Root dataset directory set to "{}".'.format(target_dir))
print('Rendering run scripts into "{}".'.format(run_script_dir))
with open(os.path.join(MCVOX_TEMPLATE_PATH,
'fluence_skin_vessel.template.py'), 'r') as fid:
sv_template = fid.read()
T_sv = jinja2.Template(sv_template)
if verbose:
print('Rendering: fluence-skin-vessel')
config = dict(config)
config['cl_device'] = cl_device
config['cl_index'] = cl_index
config['method'] = method
config['cache'] = cache
config['root_dataset_dir'] = root_dataset_dir
rendered_template = T_sv.render(**config)
filename = os.path.join(run_script_dir, 'fluence-skin-vessel.py')
if verbose:
print('Creating output directory "{}".'.format(
run_script_dir))
print('Saving run script to "{}"'.format(filename))
if not test:
os.makedirs(run_script_dir, exist_ok=True)
with open(filename, 'w') as fid:
fid.write(rendered_template)
if verbose:
print('The run scripts will save data into "{}".'.format(
root_dataset_dir))
if __name__ == '__main__':
parser = common.prepare_cli('Render run scripts for optical '
'fiber reflectance Sampling Volume datasets')
# no additional command line arguments are required
kwargs = common.process_cli(parser)
render_mcvox_fluence(**kwargs)