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rMUSPECTRE µSpectre
test_goodies.hh
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/**
* @file test_goodies.hh
*
* @author Till Junge <till.junge@epfl.ch>
*
* @date 27 Sep 2017
*
* @brief helpers for testing
*
* Copyright © 2017 Till Junge
*
* µSpectre 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, or (at
* your option) any later version.
*
* µSpectre 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 GNU Emacs; see the file COPYING. If not, write to the
* Free Software Foundation, Inc., 59 Temple Place - Suite 330,
* Boston, MA 02111-1307, USA.
*/
#ifndef TEST_GOODIES_H
#define TEST_GOODIES_H
#include "common/tensor_algebra.hh"
#include <boost/mpl/list.hpp>
#include <random>
#include <type_traits>
namespace
muSpectre
{
namespace
testGoodies
{
template
<
Dim_t
Dim
>
struct
dimFixture
{
constexpr
static
Dim_t
dim
{
Dim
};
};
using
dimlist
=
boost
::
mpl
::
list
<
dimFixture
<
oneD
>
,
dimFixture
<
twoD
>
,
dimFixture
<
threeD
>>
;
/* ---------------------------------------------------------------------- */
template
<
typename
T
>
class
RandRange
{
public
:
RandRange
()
:
rd
(),
gen
(
rd
())
{}
template
<
typename
dummyT
=
T
>
std
::
enable_if_t
<
std
::
is_floating_point
<
dummyT
>::
value
,
dummyT
>
randval
(
T
&&
lower
,
T
&&
upper
)
{
static_assert
(
std
::
is_same
<
T
,
dummyT
>::
value
,
"SFINAE"
);
auto
distro
=
std
::
uniform_real_distribution
<
T
>
(
lower
,
upper
);
return
distro
(
this
->
gen
);
}
template
<
typename
dummyT
=
T
>
std
::
enable_if_t
<
std
::
is_integral
<
dummyT
>::
value
,
dummyT
>
randval
(
T
&&
lower
,
T
&&
upper
)
{
static_assert
(
std
::
is_same
<
T
,
dummyT
>::
value
,
"SFINAE"
);
auto
distro
=
std
::
uniform_int_distribution
<
T
>
(
lower
,
upper
);
return
distro
(
this
->
gen
);
}
private
:
std
::
random_device
rd
;
std
::
default_random_engine
gen
;
};
/**
* explicit computation of linearisation of PK1 stress for an
* objective Hooke's law. This implementation is not meant to be
* efficient, but te reflect exactly the formulation in Curnier
* 2000, "Méthodes numériques en mécanique des solides" for
* reference and testing
*/
template
<
Dim_t
Dim
>
decltype
(
auto
)
objective_hooke_explicit
(
Real
lambda
,
Real
mu
,
const
Matrices
::
Tens2_t
<
Dim
>&
F
)
{
using
namespace
Matrices
;
using
T2
=
Tens2_t
<
Dim
>
;
using
T4
=
Tens4_t
<
Dim
>
;
T2
P
;
T2
I
=
P
.
Identity
();
T4
K
;
// See Curnier, 2000, "Méthodes numériques en mécanique des
// solides", p 252, (6.95b)
Real
Fjrjr
=
(
F
.
array
()
*
F
.
array
()).
sum
();
T2
Fjrjm
=
F
.
transpose
()
*
F
;
P
.
setZero
();
for
(
Dim_t
i
=
0
;
i
<
Dim
;
++
i
)
{
for
(
Dim_t
m
=
0
;
m
<
Dim
;
++
m
)
{
P
(
i
,
m
)
+=
lambda
/
2
*
(
Fjrjr
-
Dim
)
*
F
(
i
,
m
);
for
(
Dim_t
r
=
0
;
r
<
Dim
;
++
r
)
{
P
(
i
,
m
)
+=
mu
*
F
(
i
,
r
)
*
(
Fjrjm
(
r
,
m
)
-
I
(
r
,
m
));
}
}
}
// See Curnier, 2000, "Méthodes numériques en mécanique des solides", p 252
Real
Fkrkr
=
(
F
.
array
()
*
F
.
array
()).
sum
();
T2
Fkmkn
=
F
.
transpose
()
*
F
;
T2
Fisjs
=
F
*
F
.
transpose
();
K
.
setZero
();
for
(
Dim_t
i
=
0
;
i
<
Dim
;
++
i
)
{
for
(
Dim_t
j
=
0
;
j
<
Dim
;
++
j
)
{
for
(
Dim_t
m
=
0
;
m
<
Dim
;
++
m
)
{
for
(
Dim_t
n
=
0
;
n
<
Dim
;
++
n
)
{
get
(
K
,
i
,
m
,
j
,
n
)
=
(
lambda
*
((
Fkrkr
-
Dim
)
/
2
*
I
(
i
,
j
)
*
I
(
m
,
n
)
+
F
(
i
,
m
)
*
F
(
j
,
n
))
+
mu
*
(
I
(
i
,
j
)
*
Fkmkn
(
m
,
n
)
+
Fisjs
(
i
,
j
)
*
I
(
m
,
n
)
-
I
(
i
,
j
)
*
I
(
m
,
n
)
+
F
(
i
,
n
)
*
F
(
j
,
m
)));
}
}
}
}
return
std
::
make_tuple
(
P
,
K
);
}
}
// testGoodies
}
// muSpectre
#endif
/* TEST_GOODIES_H */
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