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real_qz.cpp
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Fri, Feb 21, 23:58
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rDLMA Diffusion limited mixed aggregation
real_qz.cpp
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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2012 Alexey Korepanov <kaikaikai@yandex.ru>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#define EIGEN_RUNTIME_NO_MALLOC
#include "main.h"
#include <limits>
#include <Eigen/Eigenvalues>
template
<
typename
MatrixType
>
void
real_qz
(
const
MatrixType
&
m
)
{
/* this test covers the following files:
RealQZ.h
*/
using
std
::
abs
;
typedef
typename
MatrixType
::
Scalar
Scalar
;
Index
dim
=
m
.
cols
();
MatrixType
A
=
MatrixType
::
Random
(
dim
,
dim
),
B
=
MatrixType
::
Random
(
dim
,
dim
);
// Regression test for bug 985: Randomly set rows or columns to zero
Index
k
=
internal
::
random
<
Index
>
(
0
,
dim
-
1
);
switch
(
internal
::
random
<
int
>
(
0
,
10
))
{
case
0
:
A
.
row
(
k
).
setZero
();
break
;
case
1
:
A
.
col
(
k
).
setZero
();
break
;
case
2
:
B
.
row
(
k
).
setZero
();
break
;
case
3
:
B
.
col
(
k
).
setZero
();
break
;
default
:
break
;
}
RealQZ
<
MatrixType
>
qz
(
dim
);
// TODO enable full-prealocation of required memory, this probably requires an in-place mode for HessenbergDecomposition
//Eigen::internal::set_is_malloc_allowed(false);
qz
.
compute
(
A
,
B
);
//Eigen::internal::set_is_malloc_allowed(true);
VERIFY_IS_EQUAL
(
qz
.
info
(),
Success
);
// check for zeros
bool
all_zeros
=
true
;
for
(
Index
i
=
0
;
i
<
A
.
cols
();
i
++
)
for
(
Index
j
=
0
;
j
<
i
;
j
++
)
{
if
(
abs
(
qz
.
matrixT
()(
i
,
j
))
!=
Scalar
(
0.0
))
{
std
::
cerr
<<
"Error: T("
<<
i
<<
","
<<
j
<<
") = "
<<
qz
.
matrixT
()(
i
,
j
)
<<
std
::
endl
;
all_zeros
=
false
;
}
if
(
j
<
i
-
1
&&
abs
(
qz
.
matrixS
()(
i
,
j
))
!=
Scalar
(
0.0
))
{
std
::
cerr
<<
"Error: S("
<<
i
<<
","
<<
j
<<
") = "
<<
qz
.
matrixS
()(
i
,
j
)
<<
std
::
endl
;
all_zeros
=
false
;
}
if
(
j
==
i
-
1
&&
j
>
0
&&
abs
(
qz
.
matrixS
()(
i
,
j
))
!=
Scalar
(
0.0
)
&&
abs
(
qz
.
matrixS
()(
i
-
1
,
j
-
1
))
!=
Scalar
(
0.0
))
{
std
::
cerr
<<
"Error: S("
<<
i
<<
","
<<
j
<<
") = "
<<
qz
.
matrixS
()(
i
,
j
)
<<
" && S("
<<
i
-
1
<<
","
<<
j
-
1
<<
") = "
<<
qz
.
matrixS
()(
i
-
1
,
j
-
1
)
<<
std
::
endl
;
all_zeros
=
false
;
}
}
VERIFY_IS_EQUAL
(
all_zeros
,
true
);
VERIFY_IS_APPROX
(
qz
.
matrixQ
()
*
qz
.
matrixS
()
*
qz
.
matrixZ
(),
A
);
VERIFY_IS_APPROX
(
qz
.
matrixQ
()
*
qz
.
matrixT
()
*
qz
.
matrixZ
(),
B
);
VERIFY_IS_APPROX
(
qz
.
matrixQ
()
*
qz
.
matrixQ
().
adjoint
(),
MatrixType
::
Identity
(
dim
,
dim
));
VERIFY_IS_APPROX
(
qz
.
matrixZ
()
*
qz
.
matrixZ
().
adjoint
(),
MatrixType
::
Identity
(
dim
,
dim
));
}
EIGEN_DECLARE_TEST
(
real_qz
)
{
int
s
=
0
;
for
(
int
i
=
0
;
i
<
g_repeat
;
i
++
)
{
CALL_SUBTEST_1
(
real_qz
(
Matrix4f
())
);
s
=
internal
::
random
<
int
>
(
1
,
EIGEN_TEST_MAX_SIZE
/
4
);
CALL_SUBTEST_2
(
real_qz
(
MatrixXd
(
s
,
s
))
);
// some trivial but implementation-wise tricky cases
CALL_SUBTEST_2
(
real_qz
(
MatrixXd
(
1
,
1
))
);
CALL_SUBTEST_2
(
real_qz
(
MatrixXd
(
2
,
2
))
);
CALL_SUBTEST_3
(
real_qz
(
Matrix
<
double
,
1
,
1
>
())
);
CALL_SUBTEST_4
(
real_qz
(
Matrix2d
())
);
}
TEST_SET_BUT_UNUSED_VARIABLE
(
s
)
}
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