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authorA. Wilcox <AWilcox@Wilcox-Tech.com>2018-05-15 18:31:09 -0500
committerA. Wilcox <AWilcox@Wilcox-Tech.com>2018-05-15 18:31:09 -0500
commit67279ceceea86972ce21921c838d4a7f7ba942dd (patch)
tree7d7e4011f507f45094b9408dcb537743ef63950b /user/kst/kst-gsl2.patch
parentbaa49d659f3a3d29210e54c4f1452f562556e730 (diff)
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user/kst: new package (finally)
Diffstat (limited to 'user/kst/kst-gsl2.patch')
-rw-r--r--user/kst/kst-gsl2.patch154
1 files changed, 154 insertions, 0 deletions
diff --git a/user/kst/kst-gsl2.patch b/user/kst/kst-gsl2.patch
new file mode 100644
index 000000000..0edbfe7fd
--- /dev/null
+++ b/user/kst/kst-gsl2.patch
@@ -0,0 +1,154 @@
+--- Kst-2.0.8/src/plugins/fits/non_linear.h 2014-02-13 18:41:44.000000000 +0900
++++ Kst-2.0.8/src/plugins/fits/non_linear.h 2016-03-04 00:34:31.000000000 +0900
+@@ -177,37 +177,45 @@
+ }
+ 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];
++
++
++ gsl_matrix *J = gsl_matrix_alloc(pSolver->fdf->n, pSolver->fdf->p);
++ if (J != NULL) {
++ gsl_multifit_fdfsolver_jac(pSolver, J);
++
++ gsl_multifit_covar( 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];
++ }
++
++ //
++ // 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 ));
++
++ bReturn = true;
++
++ gsl_matrix_free( 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 ));
+-
+- bReturn = true;
+-
+ gsl_matrix_free( pMatrixCovariance );
+ }
+ gsl_multifit_fdfsolver_free( pSolver );
+--- Kst-2.0.8/src/plugins/fits/non_linear_weighted.h 2014-02-13 18:41:44.000000000 +0900
++++ Kst-2.0.8/src/plugins/fits/non_linear_weighted.h 2016-03-04 00:37:41.000000000 +0900
+@@ -193,37 +193,43 @@
+ }
+ 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( 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 );
+- }
++ gsl_matrix *J = gsl_matrix_alloc(pSolver->fdf->n, pSolver->fdf->p);
++ if (J != NULL) {
++ gsl_multifit_fdfsolver_jac(pSolver, J);
++
++ gsl_multifit_covar( 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( 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 );
++ }
++ }
++
++ //
++ // determine the value of chi^2/nu
++ //
++ scalarOutChi->setValue(gsl_blas_dnrm2( pSolver->f ));
++
++ bReturn = true;
++
++ gsl_matrix_free( J );
+ }
+-
+- //
+- // determine the value of chi^2/nu
+- //
+- scalarOutChi->setValue(gsl_blas_dnrm2( pSolver->f ));
+-
+- bReturn = true;
+-
+ gsl_matrix_free( pMatrixCovariance );
+ }
+ gsl_multifit_fdfsolver_free( pSolver );