1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
|
# -----------------------------------------------------------------------
# Copyright: 2010-2018, iMinds-Vision Lab, University of Antwerp
# 2013-2018, 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
import six
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
|
