File gsl2-support.patch of Package kst
From a9d24f91057441bbd2e3ed9e7536b071121526cb Mon Sep 17 00:00:00 2001
From: "D. V. Wiebe" <dvw@ketiltrout.net>
Date: Thu, 10 Mar 2016 14:09:26 -0800
Subject: [PATCH] GSL-2.x support.
---
src/plugins/fits/non_linear.h | 67 +++++++++++++++++++++-------------
src/plugins/fits/non_linear_weighted.h | 66 ++++++++++++++++++++-------------
2 files changed, 82 insertions(+), 51 deletions(-)
diff --git a/src/plugins/fits/non_linear.h b/src/plugins/fits/non_linear.h
index 4506704..74e82e7 100644
--- a/src/plugins/fits/non_linear.h
+++ b/src/plugins/fits/non_linear.h
@@ -18,6 +18,7 @@
#include <gsl/gsl_blas.h>
#include <gsl/gsl_multifit_nlin.h>
#include <gsl/gsl_statistics.h>
+#include <gsl/gsl_version.h>
#include "common.h"
struct data {
@@ -100,6 +101,7 @@ bool kstfit_nonlinear(
gsl_multifit_function_fdf function;
gsl_vector_view vectorViewInitial;
gsl_matrix* pMatrixCovariance;
+ gsl_matrix *pMatrixJacobian;
struct data d;
double dXInitial[NUM_PARAMS];
double* pInputX;
@@ -177,37 +179,50 @@ bool kstfit_nonlinear(
}
iIterations++;
} while( iStatus == GSL_CONTINUE && iIterations < MAX_NUM_ITERATIONS );
- gsl_multifit_covar( pSolver->J, 0.0, pMatrixCovariance );
-
- //
- // determine the fitted values...
- //
- for( i=0; i<NUM_PARAMS; i++ ) {
- dXInitial[i] = gsl_vector_get( pSolver->x, i );
- }
-
- for( i=0; i<iLength; i++ ) {
- vectorOutYFitted->value()[i] = function_calculate( pInputX[i], dXInitial );
- vectorOutYResiduals->value()[i] = pInputY[i] - vectorOutYFitted->value()[i];
- }
+#if GSL_MAJOR_VERSION >= 2
+ pMatrixJacobian = gsl_matrix_alloc( iLength, NUM_PARAMS );
+#else
+ pMatrixJacobian = pSolver->J;
+#endif
+ if ( pMatrixJacobian != NULL) {
+#if GSL_MAJOR_VERSION >= 2
+ gsl_multifit_fdfsolver_jac( pSolver, pMatrixJacobian );
+#endif
+ gsl_multifit_covar( pMatrixJacobian, 0.0, pMatrixCovariance );
+
+ //
+ // determine the fitted values...
+ //
+ for( i=0; i<NUM_PARAMS; i++ ) {
+ dXInitial[i] = gsl_vector_get( pSolver->x, i );
+ }
- //
- // fill in the parameter values and covariance matrix...
- //
- for( i=0; i<NUM_PARAMS; i++ ) {
- vectorOutYParameters->value()[i] = gsl_vector_get( pSolver->x, i );
- for( j=0; j<NUM_PARAMS; j++ ) {
- vectorOutYCovariance->value()[(i*NUM_PARAMS)+j] = gsl_matrix_get( pMatrixCovariance, i, j );
+ for( i=0; i<iLength; i++ ) {
+ vectorOutYFitted->value()[i] = function_calculate( pInputX[i], dXInitial );
+ vectorOutYResiduals->value()[i] = pInputY[i] - vectorOutYFitted->value()[i];
}
- }
- //
- // determine the value of chi^2/nu
- //
- scalarOutChi->setValue(gsl_blas_dnrm2( pSolver->f ));
+ //
+ // fill in the parameter values and covariance matrix...
+ //
+ for( i=0; i<NUM_PARAMS; i++ ) {
+ vectorOutYParameters->value()[i] = gsl_vector_get( pSolver->x, i );
+ for( j=0; j<NUM_PARAMS; j++ ) {
+ vectorOutYCovariance->value()[(i*NUM_PARAMS)+j] = gsl_matrix_get( pMatrixCovariance, i, j );
+ }
+ }
- bReturn = true;
+ //
+ // determine the value of chi^2/nu
+ //
+ scalarOutChi->setValue(gsl_blas_dnrm2( pSolver->f ));
+ bReturn = true;
+
+#if GSL_MAJOR_VERSION >= 2
+ gsl_matrix_free( pMatrixJacobian );
+#endif
+ }
gsl_matrix_free( pMatrixCovariance );
}
gsl_multifit_fdfsolver_free( pSolver );
diff --git a/src/plugins/fits/non_linear_weighted.h b/src/plugins/fits/non_linear_weighted.h
index 6ca7d6f..347ae9d 100644
--- a/src/plugins/fits/non_linear_weighted.h
+++ b/src/plugins/fits/non_linear_weighted.h
@@ -18,6 +18,7 @@
#include <gsl/gsl_blas.h>
#include <gsl/gsl_multifit_nlin.h>
#include <gsl/gsl_statistics.h>
+#include <gsl/gsl_version.h>
#include "common.h"
struct data {
@@ -101,6 +102,7 @@ bool kstfit_nonlinear_weighted(
gsl_multifit_function_fdf function;
gsl_vector_view vectorViewInitial;
gsl_matrix* pMatrixCovariance;
+ gsl_matrix *pMatrixJacobian;
struct data d;
double dXInitial[NUM_PARAMS];
double* pInputs[3];
@@ -193,37 +195,51 @@ bool kstfit_nonlinear_weighted(
}
while( iStatus == GSL_CONTINUE && iIterations < MAX_NUM_ITERATIONS );
- gsl_multifit_covar( pSolver->J, 0.0, pMatrixCovariance );
-
- //
- // determine the fitted values...
- //
- for( i=0; i<NUM_PARAMS; i++ ) {
- dXInitial[i] = gsl_vector_get( pSolver->x, i );
- }
+#if GSL_MAJOR_VERSION >= 2
+ pMatrixJacobian = gsl_matrix_alloc( iLength, NUM_PARAMS );
+#else
+ pMatrixJacobian = pSolver->J;
+#endif
+
+ if ( pMatrixJacobian != NULL) {
+#if GSL_MAJOR_VERSION >= 2
+ gsl_multifit_fdfsolver_jac( pSolver, pMatrixJacobian );
+#endif
+ gsl_multifit_covar( pMatrixJacobian, 0.0, pMatrixCovariance );
+
+ //
+ // determine the fitted values...
+ //
+ for( i=0; i<NUM_PARAMS; i++ ) {
+ dXInitial[i] = gsl_vector_get( pSolver->x, i );
+ }
- for( i=0; i<iLength; i++ ) {
- vectorOutYFitted->value()[i] = function_calculate( pInputs[XVALUES][i], dXInitial );
- vectorOutYResiduals->value()[i] = pInputs[YVALUES][i] - vectorOutYFitted->value()[i];
- }
+ for( i=0; i<iLength; i++ ) {
+ vectorOutYFitted->value()[i] = function_calculate( pInputs[XVALUES][i], dXInitial );
+ vectorOutYResiduals->value()[i] = pInputs[YVALUES][i] - vectorOutYFitted->value()[i];
+ }
- //
- // fill in the parameter values and covariance matrix...
- //
- for( i=0; i<NUM_PARAMS; i++ ) {
- vectorOutYParameters->value()[i] = gsl_vector_get( pSolver->x, i );
- for( j=0; j<NUM_PARAMS; j++ ) {
- vectorOutYCovariance->value()[(i*NUM_PARAMS)+j] = gsl_matrix_get( pMatrixCovariance, i, j );
+ //
+ // fill in the parameter values and covariance matrix...
+ //
+ for( i=0; i<NUM_PARAMS; i++ ) {
+ vectorOutYParameters->value()[i] = gsl_vector_get( pSolver->x, i );
+ for( j=0; j<NUM_PARAMS; j++ ) {
+ vectorOutYCovariance->value()[(i*NUM_PARAMS)+j] = gsl_matrix_get( pMatrixCovariance, i, j );
+ }
}
- }
- //
- // determine the value of chi^2/nu
- //
- scalarOutChi->setValue(gsl_blas_dnrm2( pSolver->f ));
+ //
+ // determine the value of chi^2/nu
+ //
+ scalarOutChi->setValue(gsl_blas_dnrm2( pSolver->f ));
- bReturn = true;
+ bReturn = true;
+#if GSL_MAJOR_VERSION >= 2
+ gsl_matrix_free( pMatrixJacobian );
+#endif
+ }
gsl_matrix_free( pMatrixCovariance );
}
gsl_multifit_fdfsolver_free( pSolver );
