mirror of
https://gitlab.com/libeigen/eigen.git
synced 2025-01-30 17:40:05 +08:00
move most of results vectors/matrices inside respective classes.
This commit is contained in:
Thomas Capricelli
parent
38fc6c8553
commit
6c1a9703b1
@ -8,17 +8,11 @@ public:
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int solve(
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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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const Scalar tol = ei_sqrt(epsilon<Scalar>())
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);
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int solve(
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Matrix< Scalar, Dynamic, 1 > &x,
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Matrix< Scalar, Dynamic, 1 > &fvec,
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int &nfev,
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Matrix< Scalar, Dynamic, Dynamic > &fjac,
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Matrix< Scalar, Dynamic, 1 > &R,
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Matrix< Scalar, Dynamic, 1 > &qtf,
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Matrix< Scalar, Dynamic, 1 > &diag,
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const int mode=1,
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int nb_of_subdiagonals = -1,
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@ -30,6 +24,10 @@ public:
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const int nprint=0
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);
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Matrix< Scalar, Dynamic, 1 > fvec;
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Matrix< Scalar, Dynamic, Dynamic > fjac;
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Matrix< Scalar, Dynamic, 1 > R;
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Matrix< Scalar, Dynamic, 1 > qtf;
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private:
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const FunctorType &functor;
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};
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@ -39,14 +37,12 @@ private:
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template<typename FunctorType, typename Scalar>
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int HybridNonLinearSolverNumericalDiff<FunctorType,Scalar>::solve(
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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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const Scalar tol
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)
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{
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const int n = x.size();
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int info, nfev=0;
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Matrix< Scalar, Dynamic, 1> R, qtf, diag;
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Matrix< Scalar, Dynamic, 1> diag;
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/* check the input parameters for errors. */
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if (n <= 0 || tol < 0.) {
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@ -56,10 +52,9 @@ int HybridNonLinearSolverNumericalDiff<FunctorType,Scalar>::solve(
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diag.setConstant(n, 1.);
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info = solve(
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x, fvec,
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x,
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nfev,
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fjac,
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R, qtf, diag,
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diag,
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2,
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-1, -1,
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(n+1)*200,
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@ -73,11 +68,7 @@ int HybridNonLinearSolverNumericalDiff<FunctorType,Scalar>::solve(
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template<typename FunctorType, typename Scalar>
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int HybridNonLinearSolverNumericalDiff<FunctorType,Scalar>::solve(
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Matrix< Scalar, Dynamic, 1 > &x,
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Matrix< Scalar, Dynamic, 1 > &fvec,
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int &nfev,
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Matrix< Scalar, Dynamic, Dynamic > &fjac,
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Matrix< Scalar, Dynamic, 1 > &R,
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Matrix< Scalar, Dynamic, 1 > &qtf,
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Matrix< Scalar, Dynamic, 1 > &diag,
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const int mode,
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int nb_of_subdiagonals,
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@ -95,10 +86,10 @@ int HybridNonLinearSolverNumericalDiff<FunctorType,Scalar>::solve(
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if (nb_of_subdiagonals<0) nb_of_subdiagonals = n-1;
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if (nb_of_superdiagonals<0) nb_of_superdiagonals = n-1;
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fvec.resize(n);
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qtf.resize(n);
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R.resize( (n*(n+1))/2);
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fjac.resize(n, n);
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fvec.resize(n);
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/* Local variables */
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int i, j, l, iwa[1];
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@ -8,17 +8,11 @@ public:
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int solve(
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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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const Scalar tol = ei_sqrt(epsilon<Scalar>())
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);
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int solve(
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Matrix< Scalar, Dynamic, 1 > &x,
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Matrix< Scalar, Dynamic, 1 > &fvec,
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int &nfev, int &njev,
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Matrix< Scalar, Dynamic, Dynamic > &fjac,
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Matrix< Scalar, Dynamic, 1 > &R,
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Matrix< Scalar, Dynamic, 1 > &qtf,
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Matrix< Scalar, Dynamic, 1 > &diag,
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const int mode=1,
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const int maxfev = 1000,
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@ -27,6 +21,10 @@ public:
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const int nprint=0
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);
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Matrix< Scalar, Dynamic, 1 > fvec;
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Matrix< Scalar, Dynamic, Dynamic > fjac;
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Matrix< Scalar, Dynamic, 1 > R;
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Matrix< Scalar, Dynamic, 1 > qtf;
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private:
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const FunctorType &functor;
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};
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@ -36,14 +34,12 @@ private:
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template<typename FunctorType, typename Scalar>
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int HybridNonLinearSolver<FunctorType,Scalar>::solve(
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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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const Scalar tol
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)
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{
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const int n = x.size();
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int info, nfev=0, njev=0;
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Matrix< Scalar, Dynamic, 1> R, qtf, diag;
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Matrix< Scalar, Dynamic, 1> diag;
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/* check the input parameters for errors. */
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if (n <= 0 || tol < 0.) {
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@ -53,10 +49,9 @@ int HybridNonLinearSolver<FunctorType,Scalar>::solve(
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diag.setConstant(n, 1.);
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info = solve(
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x, fvec,
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x,
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nfev, njev,
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fjac,
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R, qtf, diag,
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diag,
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2,
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(n+1)*100,
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100.,
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@ -70,12 +65,8 @@ int HybridNonLinearSolver<FunctorType,Scalar>::solve(
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template<typename FunctorType, typename Scalar>
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int HybridNonLinearSolver<FunctorType,Scalar>::solve(
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Matrix< Scalar, Dynamic, 1 > &x,
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Matrix< Scalar, Dynamic, 1 > &fvec,
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int &nfev,
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int &njev,
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Matrix< Scalar, Dynamic, Dynamic > &fjac,
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Matrix< Scalar, Dynamic, 1 > &R,
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Matrix< Scalar, Dynamic, 1 > &qtf,
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Matrix< Scalar, Dynamic, 1 > &diag,
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const int mode,
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const int maxfev,
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@ -91,6 +82,7 @@ int HybridNonLinearSolver<FunctorType,Scalar>::solve(
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qtf.resize(n);
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R.resize( (n*(n+1))/2);
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fjac.resize(n, n);
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fvec.resize(n);
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/* Local variables */
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int i, j, l, iwa[1];
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@ -8,18 +8,13 @@ public:
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int minimize(
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Matrix< Scalar, Dynamic, 1 > &x,
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Matrix< Scalar, Dynamic, 1 > &fvec,
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const Scalar tol = ei_sqrt(epsilon<Scalar>())
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);
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int minimize(
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Matrix< Scalar, Dynamic, 1 > &x,
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Matrix< Scalar, Dynamic, 1 > &fvec,
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int &nfev,
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int &njev,
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Matrix< Scalar, Dynamic, Dynamic > &fjac,
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VectorXi &ipvt,
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Matrix< Scalar, Dynamic, 1 > &qtf,
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Matrix< Scalar, Dynamic, 1 > &diag,
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const int mode=1,
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const Scalar factor = 100.,
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@ -30,6 +25,10 @@ public:
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const int nprint=0
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);
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Matrix< Scalar, Dynamic, 1 > fvec;
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Matrix< Scalar, Dynamic, Dynamic > fjac;
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VectorXi ipvt;
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Matrix< Scalar, Dynamic, 1 > qtf;
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private:
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const FunctorType &functor;
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};
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@ -38,11 +37,11 @@ private:
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template<typename FunctorType, typename Scalar>
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int LevenbergMarquardt<FunctorType,Scalar>::minimize(
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Matrix< Scalar, Dynamic, 1 > &x,
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Matrix< Scalar, Dynamic, 1 > &fvec,
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const Scalar tol
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)
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{
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const int n = x.size(), m=fvec.size();
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const int n = x.size();
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const int m = functor.nbOfFunctions();
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int info, nfev=0, njev=0;
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Matrix< Scalar, Dynamic, Dynamic > fjac(m, n);
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Matrix< Scalar, Dynamic, 1> diag, qtf;
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@ -55,9 +54,9 @@ int LevenbergMarquardt<FunctorType,Scalar>::minimize(
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}
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info = minimize(
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x, fvec,
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x,
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nfev, njev,
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fjac, ipvt, qtf, diag,
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diag,
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1,
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100.,
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(n+1)*100,
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@ -70,12 +69,8 @@ int LevenbergMarquardt<FunctorType,Scalar>::minimize(
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template<typename FunctorType, typename Scalar>
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int LevenbergMarquardt<FunctorType,Scalar>::minimize(
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Matrix< Scalar, Dynamic, 1 > &x,
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Matrix< Scalar, Dynamic, 1 > &fvec,
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int &nfev,
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int &njev,
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Matrix< Scalar, Dynamic, Dynamic > &fjac,
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VectorXi &ipvt,
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Matrix< Scalar, Dynamic, 1 > &qtf,
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Matrix< Scalar, Dynamic, 1 > &diag,
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const int mode,
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const Scalar factor,
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@ -86,9 +81,11 @@ int LevenbergMarquardt<FunctorType,Scalar>::minimize(
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const int nprint
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)
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{
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const int m = fvec.size(), n = x.size();
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Matrix< Scalar, Dynamic, 1 > wa1(n), wa2(n), wa3(n), wa4(m);
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const int n = x.size();
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const int m = functor.nbOfFunctions();
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Matrix< Scalar, Dynamic, 1 > wa1(n), wa2(n), wa3(n), wa4;
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fvec.resize(m);
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ipvt.resize(n);
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fjac.resize(m, n);
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diag.resize(n);
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@ -8,17 +8,12 @@ public:
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int minimize(
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Matrix< Scalar, Dynamic, 1 > &x,
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Matrix< Scalar, Dynamic, 1 > &fvec,
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const Scalar tol = ei_sqrt(epsilon<Scalar>())
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);
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int minimize(
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Matrix< Scalar, Dynamic, 1 > &x,
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Matrix< Scalar, Dynamic, 1 > &fvec,
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int &nfev,
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Matrix< Scalar, Dynamic, Dynamic > &fjac,
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VectorXi &ipvt,
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Matrix< Scalar, Dynamic, 1 > &qtf,
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Matrix< Scalar, Dynamic, 1 > &diag,
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const int mode=1,
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const Scalar factor = 100.,
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@ -30,6 +25,10 @@ public:
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const int nprint=0
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);
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Matrix< Scalar, Dynamic, 1 > fvec;
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Matrix< Scalar, Dynamic, Dynamic > fjac;
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VectorXi ipvt;
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Matrix< Scalar, Dynamic, 1 > qtf;
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private:
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const FunctorType &functor;
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};
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@ -38,11 +37,11 @@ private:
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template<typename FunctorType, typename Scalar>
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int LevenbergMarquardtNumericalDiff<FunctorType,Scalar>::minimize(
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Matrix< Scalar, Dynamic, 1 > &x,
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Matrix< Scalar, Dynamic, 1 > &fvec,
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const Scalar tol
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)
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{
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const int n = x.size(), m=fvec.size();
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const int n = x.size();
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const int m = functor.nbOfFunctions();
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int info, nfev=0;
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Matrix< Scalar, Dynamic, Dynamic > fjac(m, n);
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Matrix< Scalar, Dynamic, 1> diag, qtf;
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@ -55,9 +54,9 @@ int LevenbergMarquardtNumericalDiff<FunctorType,Scalar>::minimize(
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}
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info = minimize(
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x, fvec,
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x,
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nfev,
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fjac, ipvt, qtf, diag,
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diag,
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1,
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100.,
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(n+1)*200,
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@ -69,11 +68,7 @@ int LevenbergMarquardtNumericalDiff<FunctorType,Scalar>::minimize(
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template<typename FunctorType, typename Scalar>
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int LevenbergMarquardtNumericalDiff<FunctorType,Scalar>::minimize(
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Matrix< Scalar, Dynamic, 1 > &x,
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Matrix< Scalar, Dynamic, 1 > &fvec,
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int &nfev,
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Matrix< Scalar, Dynamic, Dynamic > &fjac,
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VectorXi &ipvt,
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Matrix< Scalar, Dynamic, 1 > &qtf,
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Matrix< Scalar, Dynamic, 1 > &diag,
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const int mode,
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const Scalar factor,
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@ -85,9 +80,11 @@ int LevenbergMarquardtNumericalDiff<FunctorType,Scalar>::minimize(
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const int nprint
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)
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{
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const int m = fvec.size(), n = x.size();
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const int n = x.size();
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const int m = functor.nbOfFunctions();
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Matrix< Scalar, Dynamic, 1 > wa1(n), wa2(n), wa3(n), wa4(m);
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fvec.resize(m);
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ipvt.resize(n);
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fjac.resize(m, n);
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diag.resize(n);
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@ -8,18 +8,13 @@ public:
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int minimize(
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Matrix< Scalar, Dynamic, 1 > &x,
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Matrix< Scalar, Dynamic, 1 > &fvec,
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const Scalar tol = ei_sqrt(epsilon<Scalar>())
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);
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int minimize(
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Matrix< Scalar, Dynamic, 1 > &x,
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Matrix< Scalar, Dynamic, 1 > &fvec,
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int &nfev,
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int &njev,
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Matrix< Scalar, Dynamic, Dynamic > &fjac,
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VectorXi &ipvt,
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Matrix< Scalar, Dynamic, 1 > &qtf,
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Matrix< Scalar, Dynamic, 1 > &diag,
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const int mode=1,
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const Scalar factor = 100.,
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@ -30,6 +25,10 @@ public:
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const int nprint=0
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);
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Matrix< Scalar, Dynamic, 1 > fvec;
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Matrix< Scalar, Dynamic, Dynamic > fjac;
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VectorXi ipvt;
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Matrix< Scalar, Dynamic, 1 > qtf;
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private:
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const FunctorType &functor;
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};
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@ -38,11 +37,11 @@ private:
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template<typename FunctorType, typename Scalar>
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int LevenbergMarquardtOptimumStorage<FunctorType,Scalar>::minimize(
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Matrix< Scalar, Dynamic, 1 > &x,
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Matrix< Scalar, Dynamic, 1 > &fvec,
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const Scalar tol
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)
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{
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const int n = x.size(), m=fvec.size();
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const int n = x.size();
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const int m = functor.nbOfFunctions();
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int info, nfev=0, njev=0;
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Matrix< Scalar, Dynamic, Dynamic > fjac(m, n);
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Matrix< Scalar, Dynamic, 1> diag, qtf;
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@ -55,9 +54,9 @@ int LevenbergMarquardtOptimumStorage<FunctorType,Scalar>::minimize(
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}
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info = minimize(
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x, fvec,
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x,
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nfev, njev,
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fjac, ipvt, qtf, diag,
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diag,
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1,
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100.,
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(n+1)*100,
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@ -69,12 +68,8 @@ int LevenbergMarquardtOptimumStorage<FunctorType,Scalar>::minimize(
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template<typename FunctorType, typename Scalar>
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int LevenbergMarquardtOptimumStorage<FunctorType,Scalar>::minimize(
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Matrix< Scalar, Dynamic, 1 > &x,
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Matrix< Scalar, Dynamic, 1 > &fvec,
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int &nfev,
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int &njev,
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Matrix< Scalar, Dynamic, Dynamic > &fjac,
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VectorXi &ipvt,
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Matrix< Scalar, Dynamic, 1 > &qtf,
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Matrix< Scalar, Dynamic, 1 > &diag,
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const int mode,
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const Scalar factor,
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@ -85,9 +80,11 @@ int LevenbergMarquardtOptimumStorage<FunctorType,Scalar>::minimize(
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const int nprint
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)
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{
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const int m = fvec.size(), n = x.size();
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const int n = x.size();
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const int m = functor.nbOfFunctions();
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Matrix< Scalar, Dynamic, 1 > wa1(n), wa2(n), wa3(n), wa4(m);
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fvec.resize(m);
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ipvt.resize(n);
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fjac.resize(m, n);
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diag.resize(n);
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