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| author | A. Wilcox <AWilcox@Wilcox-Tech.com> | 2018-05-15 18:31:09 -0500 |
|---|---|---|
| committer | A. Wilcox <AWilcox@Wilcox-Tech.com> | 2018-05-15 18:31:09 -0500 |
| commit | 67279ceceea86972ce21921c838d4a7f7ba942dd (patch) | |
| tree | 7d7e4011f507f45094b9408dcb537743ef63950b /user/kst/kst-gsl2.patch | |
| parent | baa49d659f3a3d29210e54c4f1452f562556e730 (diff) | |
| download | packages-67279ceceea86972ce21921c838d4a7f7ba942dd.tar.gz packages-67279ceceea86972ce21921c838d4a7f7ba942dd.tar.bz2 packages-67279ceceea86972ce21921c838d4a7f7ba942dd.tar.xz packages-67279ceceea86972ce21921c838d4a7f7ba942dd.zip | |
user/kst: new package (finally)
Diffstat (limited to 'user/kst/kst-gsl2.patch')
| -rw-r--r-- | user/kst/kst-gsl2.patch | 154 |
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 ); |