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fn_optimize.cc
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Created
Mon, Aug 26, 14:19
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2 KB
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text/x-c++
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Wed, Aug 28, 14:19 (2 d)
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rAKA akantu
fn_optimize.cc
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/**
* @file fn_optimize.cc
*
* @author Alejandro M. Aragón <alejandro.aragon@epfl.ch>
*
* @date Thu May 22 14:12:00 2014
*
* @brief File used to show how to use the NLopt optimizator to find the
* minimum of a function
*
* @section LICENSE
*
* Copyright (©) 2010-2011 EPFL (Ecole Polytechnique Fédérale de Lausanne)
* Laboratory (LSMS - Laboratoire de Simulation en Mécanique des Solides)
*
* Akantu 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.
*
* Akantu 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 Akantu. If not, see <http://www.gnu.org/licenses/>.
*
*/
#include <vector>
#include <math.h>
#include "aka_optimize.hh"
typedef
struct
{
double
a
,
b
;
}
my_constraint_data
;
//! Functor used for the evaluation of the function and its gradient
class
Functor
{
int
count_
;
//!< Function evaluation counter
public
:
//! Default constructor
Functor
()
:
count_
()
{}
//! Return function evaluation counter
int
count
()
const
{
return
count_
;
}
double
operator
()(
const
std
::
vector
<
double
>
&
x
,
std
::
vector
<
double
>
&
grad
)
{
++
count_
;
if
(
!
grad
.
empty
())
{
grad
[
0
]
=
0.0
;
grad
[
1
]
=
0.5
/
sqrt
(
x
[
1
]);
}
return
sqrt
(
x
[
1
]);
}
static
double
wrap
(
const
std
::
vector
<
double
>
&
x
,
std
::
vector
<
double
>
&
grad
,
void
*
data
)
{
return
(
*
reinterpret_cast
<
Functor
*>
(
data
))(
x
,
grad
);
}
};
double
myvconstraint
(
const
std
::
vector
<
double
>
&
x
,
std
::
vector
<
double
>
&
grad
,
void
*
data
)
{
my_constraint_data
*
d
=
reinterpret_cast
<
my_constraint_data
*>
(
data
);
double
a
=
d
->
a
,
b
=
d
->
b
;
if
(
!
grad
.
empty
())
{
grad
[
0
]
=
3
*
a
*
(
a
*
x
[
0
]
+
b
)
*
(
a
*
x
[
0
]
+
b
);
grad
[
1
]
=
-
1.0
;
}
return
((
a
*
x
[
0
]
+
b
)
*
(
a
*
x
[
0
]
+
b
)
*
(
a
*
x
[
0
]
+
b
)
-
x
[
1
]);
}
int
main
(
int
argc
,
char
*
argv
[])
{
my_constraint_data
data
[
2
]
=
{
{
2
,
0
},
{
-
1
,
1
}
};
std
::
vector
<
double
>
x
(
2
);
x
[
0
]
=
1.234
;
x
[
1
]
=
5.678
;
Functor
fn
;
akantu
::
Optimizator
ofn
(
x
,
fn
);
ofn
.
add_inequality_constraint
(
myvconstraint
,
&
data
[
0
],
1e-8
);
ofn
.
add_inequality_constraint
(
myvconstraint
,
&
data
[
1
],
1e-8
);
ofn
.
result
();
std
::
cout
<<
"
\n
Total function evaluations: "
<<
fn
.
count
()
<<
std
::
endl
;
return
0
;
}
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