gtsam
3rdparty
Eigen
unsupported
Eigen
src
NonLinearOptimization
fdjac1.h
Go to the documentation of this file.
1
namespace
Eigen
{
2
3
namespace
internal
{
4
5
template
<
typename
FunctorType,
typename
Scalar>
6
DenseIndex
fdjac1
(
7
const
FunctorType &
Functor
,
8
Matrix< Scalar, Dynamic, 1 >
&
x
,
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Matrix< Scalar, Dynamic, 1 >
&fvec,
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Matrix< Scalar, Dynamic, Dynamic >
&fjac,
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DenseIndex
ml,
DenseIndex
mu
,
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Scalar
epsfcn)
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{
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using
std::sqrt
;
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using
std::abs
;
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typedef
DenseIndex
Index
;
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/* Local variables */
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Scalar
h
;
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Index
j
, k;
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Scalar
eps, temp;
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Index
msum;
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int
iflag;
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Index
start, length;
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/* Function Body */
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const
Scalar
epsmch =
NumTraits<Scalar>::epsilon
();
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const
Index
n
=
x
.
size
();
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eigen_assert
(fvec.size()==
n
);
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Matrix< Scalar, Dynamic, 1 >
wa1(
n
);
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Matrix< Scalar, Dynamic, 1 >
wa2(
n
);
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eps =
sqrt
((
std::max
)(epsfcn,epsmch));
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msum = ml +
mu
+ 1;
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if
(msum >=
n
) {
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/* computation of dense approximate jacobian. */
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for
(
j
= 0;
j
<
n
; ++
j
) {
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temp =
x
[
j
];
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h
= eps *
abs
(temp);
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if
(
h
== 0.)
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h
= eps;
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x
[
j
] = temp +
h
;
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iflag =
Functor
(
x
, wa1);
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if
(iflag < 0)
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return
iflag;
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x
[
j
] = temp;
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fjac.col(
j
) = (wa1-fvec)/
h
;
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}
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}
else
{
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/* computation of banded approximate jacobian. */
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for
(k = 0; k < msum; ++k) {
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for
(
j
= k; (msum<0) ? (
j
>
n
): (
j
<
n
);
j
+= msum) {
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wa2[
j
] =
x
[
j
];
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h
= eps *
abs
(wa2[
j
]);
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if
(
h
== 0.)
h
= eps;
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x
[
j
] = wa2[
j
] +
h
;
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}
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iflag =
Functor
(
x
, wa1);
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if
(iflag < 0)
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return
iflag;
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for
(
j
= k; (msum<0) ? (
j
>
n
): (
j
<
n
);
j
+= msum) {
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x
[
j
] = wa2[
j
];
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h
= eps *
abs
(wa2[
j
]);
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if
(
h
== 0.)
h
= eps;
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fjac.col(
j
).
setZero
();
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start = std::max<Index>(0,
j
-
mu
);
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length = (
std::min
)(
n
-1,
j
+ml) - start + 1;
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fjac.col(
j
).segment(start, length) = ( wa1.segment(start, length)-fvec.segment(start, length))/
h
;
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}
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}
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}
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return
0;
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}
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}
// end namespace internal
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}
// end namespace Eigen
Eigen
Namespace containing all symbols from the Eigen library.
Definition:
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mu
double mu
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h
const double h
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n
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static double epsilon
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Functor
Definition:
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j
std::ptrdiff_t j
Definition:
tut_arithmetic_redux_minmax.cpp:2
Eigen::internal::fdjac1
DenseIndex fdjac1(const FunctorType &Functor, Matrix< Scalar, Dynamic, 1 > &x, Matrix< Scalar, Dynamic, 1 > &fvec, Matrix< Scalar, Dynamic, Dynamic > &fjac, DenseIndex ml, DenseIndex mu, Scalar epsfcn)
Definition:
fdjac1.h:6
anyset::size
size_t size() const
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pytypes.h:2220
Eigen::DenseIndex
EIGEN_DEFAULT_DENSE_INDEX_TYPE DenseIndex
Definition:
Meta.h:66
min
#define min(a, b)
Definition:
datatypes.h:19
Eigen::Matrix< Scalar, Dynamic, 1 >
abs
#define abs(x)
Definition:
datatypes.h:17
internal
Definition:
BandTriangularSolver.h:13
Eigen::PlainObjectBase::setZero
EIGEN_DEVICE_FUNC Derived & setZero(Index size)
Definition:
CwiseNullaryOp.h:562
max
#define max(a, b)
Definition:
datatypes.h:20
ceres::sqrt
Jet< T, N > sqrt(const Jet< T, N > &f)
Definition:
jet.h:418
Scalar
SCALAR Scalar
Definition:
bench_gemm.cpp:46
Eigen::Index
EIGEN_DEFAULT_DENSE_INDEX_TYPE Index
The Index type as used for the API.
Definition:
Meta.h:74
gtsam
Author(s):
autogenerated on Sat Nov 16 2024 04:02:17