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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/>.
#
# -----------------------------------------------------------------------
import astra
import numpy as np
class CGLSPlugin(astra.plugin.base):
"""CGLS."""
astra_name = "CGLS-PLUGIN"
def initialize(self,cfg):
self.W = astra.OpTomo(cfg['ProjectorId'])
self.vid = cfg['ReconstructionDataId']
self.sid = cfg['ProjectionDataId']
try:
v = astra.data2d.get_shared(self.vid)
s = astra.data2d.get_shared(self.sid)
self.data_mod = astra.data2d
except Exception:
v = astra.data3d.get_shared(self.vid)
s = astra.data3d.get_shared(self.sid)
self.data_mod = astra.data3d
def run(self, its):
v = self.data_mod.get_shared(self.vid)
s = self.data_mod.get_shared(self.sid)
z = np.zeros(v.shape, dtype=np.float32)
p = np.zeros(v.shape, dtype=np.float32)
r = np.zeros(s.shape, dtype=np.float32)
w = np.zeros(s.shape, dtype=np.float32)
W = self.W
# r = s - W*v
W.FP(v, out=w)
r[:] = s
r -= w
# p = W'*r
W.BP(r, out=p)
# gamma = <p,p>
gamma = np.dot(p.ravel(), p.ravel())
for i in range(its):
# w = W * p
W.FP(p, out=w)
# alpha = gamma / <w,w>
alpha = gamma / np.dot(w.ravel(), w.ravel())
# v += alpha * p
z[:] = p
z *= alpha
v += z
# r -= alpha * w
w *= -alpha;
r += w
# z = W' * r
W.BP(r, out=z)
# beta = <z,z> / gamma
newgamma = np.dot(z.ravel(), z.ravel())
beta = newgamma / gamma
# gamma = <z,z>
gamma = newgamma
# p = z + beta * p
p *= beta
p += z
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