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
|
#
# This file is part of CasADi.
#
# CasADi -- A symbolic framework for dynamic optimization.
# Copyright (C) 2010-2023 Joel Andersson, Joris Gillis, Moritz Diehl,
# KU Leuven. All rights reserved.
# Copyright (C) 2011-2014 Greg Horn
#
# CasADi is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License as published by the Free Software Foundation; either
# version 3 of the License, or (at your option) any later version.
#
# CasADi 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
# Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public
# License along with CasADi; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
#
from casadi import *
import numpy
# Let's construct a block diagonal structure
A = diagcat(1,DM([[2,3],[3,4]]),DM([[5,6,7],[6,8,9],[7,9,10]]),11)
print(A)
A.sparsity().spy()
numpy.random.seed(2)
# We randomly permute this nice structure
perm = list(numpy.random.permutation(list(range(A.size1()))))
AP = A[perm,perm]
print(AP)
AP.sparsity().spy()
# And use scc to recover the blocks
n,p,r = AP.sparsity().scc()
APrestored = AP[p,p]
print(APrestored)
APrestored.sparsity().spy()
print("# blocks: ", n)
print("block boundaries: ", r[:n])
|
