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# -----------------------------------------------------------------------
# Copyright: 2010-2022, imec Vision Lab, University of Antwerp
# 2013-2022, CWI, Amsterdam
#
# Contact: astra@astra-toolbox.com
# Website: http://www.astra-toolbox.com/
#
# This file is part of the ASTRA Toolbox.
#
#
# The ASTRA Toolbox 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.
#
# The ASTRA Toolbox is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with the ASTRA Toolbox. If not, see <http://www.gnu.org/licenses/>.
#
# -----------------------------------------------------------------------
from __future__ import print_function
import astra
import numpy as np
# Define the plugin class (has to subclass astra.plugin.base)
# Note that usually, these will be defined in a separate package/module
class LandweberPlugin(astra.plugin.base):
"""Example of an ASTRA plugin class, implementing a simple 2D Landweber algorithm.
Options:
'Relaxation': relaxation factor (optional)
"""
# The astra_name variable defines the name to use to
# call the plugin from ASTRA
astra_name = "LANDWEBER-PLUGIN"
def initialize(self,cfg, Relaxation = 1.0):
self.W = astra.OpTomo(cfg['ProjectorId'])
self.vid = cfg['ReconstructionDataId']
self.sid = cfg['ProjectionDataId']
self.rel = Relaxation
def run(self, its):
v = astra.data2d.get_shared(self.vid)
s = astra.data2d.get_shared(self.sid)
tv = np.zeros(v.shape, dtype=np.float32)
ts = np.zeros(s.shape, dtype=np.float32)
W = self.W
for i in range(its):
W.FP(v,out=ts)
ts -= s # ts = W*v - s
W.BP(ts,out=tv)
tv *= self.rel / s.size
v -= tv # v = v - rel * W'*(W*v-s) / s.size
if __name__=='__main__':
vol_geom = astra.create_vol_geom(256, 256)
proj_geom = astra.create_proj_geom('parallel', 1.0, 384, np.linspace(0,np.pi,180,False))
# As before, create a sinogram from a phantom
phantom_id, P = astra.data2d.shepp_logan(vol_geom)
proj_id = astra.create_projector('cuda',proj_geom,vol_geom)
# construct the OpTomo object
W = astra.OpTomo(proj_id)
sinogram = W * P
sinogram = sinogram.reshape([180, 384])
# Register the plugin with ASTRA
# First we import the package that contains the plugin
import s018_plugin
# Then, we register the plugin class with ASTRA
astra.plugin.register(s018_plugin.LandweberPlugin)
# Get a list of registered plugins
print(astra.plugin.get_registered())
# To get help on a registered plugin, use get_help
print(astra.plugin.get_help('LANDWEBER-PLUGIN'))
# Create data structures
sid = astra.data2d.create('-sino', proj_geom, sinogram)
vid = astra.data2d.create('-vol', vol_geom)
# Create config using plugin name
cfg = astra.astra_dict('LANDWEBER-PLUGIN')
cfg['ProjectorId'] = proj_id
cfg['ProjectionDataId'] = sid
cfg['ReconstructionDataId'] = vid
# Create algorithm object
alg_id = astra.algorithm.create(cfg)
# Run algorithm for 100 iterations
astra.algorithm.run(alg_id, 100)
# Get reconstruction
rec = astra.data2d.get(vid)
# Options for the plugin go in cfg['option']
cfg = astra.astra_dict('LANDWEBER-PLUGIN')
cfg['ProjectorId'] = proj_id
cfg['ProjectionDataId'] = sid
cfg['ReconstructionDataId'] = vid
cfg['option'] = {}
cfg['option']['Relaxation'] = 1.5
alg_id_rel = astra.algorithm.create(cfg)
astra.algorithm.run(alg_id_rel, 100)
rec_rel = astra.data2d.get(vid)
# We can also use OpTomo to call the plugin
rec_op = W.reconstruct('LANDWEBER-PLUGIN', sinogram, 100, extraOptions={'Relaxation':1.5})
# ASTRA also comes with built-in plugins:
astra.plugin.register(astra.plugins.SIRTPlugin)
astra.plugin.register(astra.plugins.CGLSPlugin)
rec_sirt = W.reconstruct('SIRT-PLUGIN', sinogram, 100, extraOptions={'Relaxation':1.5})
rec_cgls = W.reconstruct('CGLS-PLUGIN', sinogram, 100)
import pylab as pl
pl.gray()
pl.figure(1)
pl.imshow(rec,vmin=0,vmax=1)
pl.figure(2)
pl.imshow(rec_rel,vmin=0,vmax=1)
pl.figure(3)
pl.imshow(rec_op,vmin=0,vmax=1)
pl.figure(4)
pl.imshow(rec_sirt,vmin=0,vmax=1)
pl.figure(5)
pl.imshow(rec_cgls,vmin=0,vmax=1)
pl.show()
# Clean up.
astra.projector.delete(proj_id)
astra.algorithm.delete([alg_id, alg_id_rel])
astra.data2d.delete([vid, sid, phantom_id])
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