Attachment #469558 for bug #574746

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            }
            iIterations++;
          } while( iStatus == GSL_CONTINUE && iIterations < MAX_NUM_ITERATIONS );
            
            
          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 );




          }
          while( iStatus == GSL_CONTINUE && iIterations < MAX_NUM_ITERATIONS );

          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 );

Return to bug 574746

Lines 177-213 Link Here

(-)a/src/plugins/fits/non_linear.h (-30 / +38 lines)
177	}	177	}
178	iIterations++;	178	iIterations++;
179	} while( iStatus == GSL_CONTINUE && iIterations < MAX_NUM_ITERATIONS );	179	} while( iStatus == GSL_CONTINUE && iIterations < MAX_NUM_ITERATIONS );
180	gsl_multifit_covar( pSolver->J, 0.0, pMatrixCovariance );	180
181		181
182	//	182	gsl_matrix *J = gsl_matrix_alloc(pSolver->fdf->n, pSolver->fdf->p);
183	// determine the fitted values...	183	if (J != NULL) {
184	//	184	gsl_multifit_fdfsolver_jac(pSolver, J);
185	for( i=0; i<NUM_PARAMS; i++ ) {	185
186	dXInitial[i] = gsl_vector_get( pSolver->x, i );	186	gsl_multifit_covar( J, 0.0, pMatrixCovariance );
187	}	187
188		188	//
189	for( i=0; i<iLength; i++ ) {	189	// determine the fitted values...
190	vectorOutYFitted->value()[i] = function_calculate( pInputX[i], dXInitial );	190	//
191	vectorOutYResiduals->value()[i] = pInputY[i] - vectorOutYFitted->value()[i];	191	for( i=0; i<NUM_PARAMS; i++ ) {
		192	dXInitial[i] = gsl_vector_get( pSolver->x, i );
		193	}
		194
		195	for( i=0; i<iLength; i++ ) {
		196	vectorOutYFitted->value()[i] = function_calculate( pInputX[i], dXInitial );
		197	vectorOutYResiduals->value()[i] = pInputY[i] - vectorOutYFitted->value()[i];
		198	}
		199
		200	//
		201	// fill in the parameter values and covariance matrix...
		202	//
		203	for( i=0; i<NUM_PARAMS; i++ ) {
		204	vectorOutYParameters->value()[i] = gsl_vector_get( pSolver->x, i );
		205	for( j=0; j<NUM_PARAMS; j++ ) {
		206	vectorOutYCovariance->value()[(i*NUM_PARAMS)+j] = gsl_matrix_get( pMatrixCovariance, i, j );
		207	}
		208	}
		209
		210	//
		211	// determine the value of chi^2/nu
		212	//
		213	scalarOutChi->setValue(gsl_blas_dnrm2( pSolver->f ));
		214
		215	bReturn = true;
		216
		217	gsl_matrix_free( J );
192	}	218	}
193
194	//
195	// fill in the parameter values and covariance matrix...
196	//
197	for( i=0; i<NUM_PARAMS; i++ ) {
198	vectorOutYParameters->value()[i] = gsl_vector_get( pSolver->x, i );
199	for( j=0; j<NUM_PARAMS; j++ ) {
200	vectorOutYCovariance->value()[(i*NUM_PARAMS)+j] = gsl_matrix_get( pMatrixCovariance, i, j );
201	}
202	}
203
204	//
205	// determine the value of chi^2/nu
206	//
207	scalarOutChi->setValue(gsl_blas_dnrm2( pSolver->f ));
208
209	bReturn = true;
210
211	gsl_matrix_free( pMatrixCovariance );	219	gsl_matrix_free( pMatrixCovariance );
212	}	220	}
213	gsl_multifit_fdfsolver_free( pSolver );	221	gsl_multifit_fdfsolver_free( pSolver );

Lines 193-229 Link Here

(-)a/src/plugins/fits/non_linear_weighted.h (-30 / +36 lines)
193	}	193	}
194	while( iStatus == GSL_CONTINUE && iIterations < MAX_NUM_ITERATIONS );	194	while( iStatus == GSL_CONTINUE && iIterations < MAX_NUM_ITERATIONS );
195		195
196	gsl_multifit_covar( pSolver->J, 0.0, pMatrixCovariance );	196	gsl_matrix *J = gsl_matrix_alloc(pSolver->fdf->n, pSolver->fdf->p);
197		197	if (J != NULL) {
198	//	198	gsl_multifit_fdfsolver_jac(pSolver, J);
199	// determine the fitted values...	199
200	//	200	gsl_multifit_covar( J, 0.0, pMatrixCovariance );
201	for( i=0; i<NUM_PARAMS; i++ ) {	201
202	dXInitial[i] = gsl_vector_get( pSolver->x, i );	202	//
203	}	203	// determine the fitted values...
204		204	//
205	for( i=0; i<iLength; i++ ) {	205	for( i=0; i<NUM_PARAMS; i++ ) {
206	vectorOutYFitted->value()[i] = function_calculate( pInputs[XVALUES][i], dXInitial );	206	dXInitial[i] = gsl_vector_get( pSolver->x, i );
207	vectorOutYResiduals->value()[i] = pInputs[YVALUES][i] - vectorOutYFitted->value()[i];	207	}
208	}	208
209		209	for( i=0; i<iLength; i++ ) {
210	//	210	vectorOutYFitted->value()[i] = function_calculate( pInputs[XVALUES][i], dXInitial );
211	// fill in the parameter values and covariance matrix...	211	vectorOutYResiduals->value()[i] = pInputs[YVALUES][i] - vectorOutYFitted->value()[i];
212	//	212	}
213	for( i=0; i<NUM_PARAMS; i++ ) {	213
214	vectorOutYParameters->value()[i] = gsl_vector_get( pSolver->x, i );	214	//
215	for( j=0; j<NUM_PARAMS; j++ ) {	215	// fill in the parameter values and covariance matrix...
216	vectorOutYCovariance->value()[(i*NUM_PARAMS)+j] = gsl_matrix_get( pMatrixCovariance, i, j );	216	//
217	}	217	for( i=0; i<NUM_PARAMS; i++ ) {
		218	vectorOutYParameters->value()[i] = gsl_vector_get( pSolver->x, i );
		219	for( j=0; j<NUM_PARAMS; j++ ) {
		220	vectorOutYCovariance->value()[(i*NUM_PARAMS)+j] = gsl_matrix_get( pMatrixCovariance, i, j );
		221	}
		222	}
		223
		224	//
		225	// determine the value of chi^2/nu
		226	//
		227	scalarOutChi->setValue(gsl_blas_dnrm2( pSolver->f ));
		228
		229	bReturn = true;
		230
		231	gsl_matrix_free( J );
218	}	232	}
219
220	//
221	// determine the value of chi^2/nu
222	//
223	scalarOutChi->setValue(gsl_blas_dnrm2( pSolver->f ));
224
225	bReturn = true;
226
227	gsl_matrix_free( pMatrixCovariance );	233	gsl_matrix_free( pMatrixCovariance );
228	}	234	}
229	gsl_multifit_fdfsolver_free( pSolver );	235	gsl_multifit_fdfsolver_free( pSolver );