// SPDX-License-Identifier: Apache-2.0 // // Copyright 2008-2016 Conrad Sanderson (http://conradsanderson.id.au) // Copyright 2008-2016 National ICT Australia (NICTA) // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. // ------------------------------------------------------------------------ //! \addtogroup fn_princomp //! @{ //! \brief //! principal component analysis -- 4 arguments version //! coeff_out -> principal component coefficients //! score_out -> projected samples //! latent_out -> eigenvalues of principal vectors //! tsquared_out -> Hotelling's T^2 statistic template inline bool princomp ( Mat& coeff_out, Mat& score_out, Col& latent_out, Col& tsquared_out, const Base& X, const typename arma_blas_type_only::result* junk = nullptr ) { arma_extra_debug_sigprint(); arma_ignore(junk); const bool status = op_princomp::direct_princomp(coeff_out, score_out, latent_out, tsquared_out, X); if(status == false) { coeff_out.soft_reset(); score_out.soft_reset(); latent_out.soft_reset(); tsquared_out.soft_reset(); arma_debug_warn_level(3, "princomp(): decomposition failed"); } return status; } //! \brief //! principal component analysis -- 3 arguments version //! coeff_out -> principal component coefficients //! score_out -> projected samples //! latent_out -> eigenvalues of principal vectors template inline bool princomp ( Mat& coeff_out, Mat& score_out, Col& latent_out, const Base& X, const typename arma_blas_type_only::result* junk = nullptr ) { arma_extra_debug_sigprint(); arma_ignore(junk); const bool status = op_princomp::direct_princomp(coeff_out, score_out, latent_out, X); if(status == false) { coeff_out.soft_reset(); score_out.soft_reset(); latent_out.soft_reset(); arma_debug_warn_level(3, "princomp(): decomposition failed"); } return status; } //! \brief //! principal component analysis -- 2 arguments version //! coeff_out -> principal component coefficients //! score_out -> projected samples template inline bool princomp ( Mat& coeff_out, Mat& score_out, const Base& X, const typename arma_blas_type_only::result* junk = nullptr ) { arma_extra_debug_sigprint(); arma_ignore(junk); const bool status = op_princomp::direct_princomp(coeff_out, score_out, X); if(status == false) { coeff_out.soft_reset(); score_out.soft_reset(); arma_debug_warn_level(3, "princomp(): decomposition failed"); } return status; } //! \brief //! principal component analysis -- 1 argument version //! coeff_out -> principal component coefficients template inline bool princomp ( Mat& coeff_out, const Base& X, const typename arma_blas_type_only::result* junk = nullptr ) { arma_extra_debug_sigprint(); arma_ignore(junk); const bool status = op_princomp::direct_princomp(coeff_out, X); if(status == false) { coeff_out.soft_reset(); arma_debug_warn_level(3, "princomp(): decomposition failed"); } return status; } template arma_warn_unused inline const Op princomp ( const Base& X, const typename arma_blas_type_only::result* junk = nullptr ) { arma_extra_debug_sigprint(); arma_ignore(junk); return Op(X.get_ref()); } //! @}