📄 nyarpca2d_matrixpca.java
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/*
* PROJECT: NyARToolkit
* --------------------------------------------------------------------------------
* This work is based on the original ARToolKit developed by
* Hirokazu Kato
* Mark Billinghurst
* HITLab, University of Washington, Seattle
* http://www.hitl.washington.edu/artoolkit/
*
* The NyARToolkit is Java version ARToolkit class library.
* Copyright (C)2008 R.Iizuka
*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* as published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this framework; if not, write to the Free Software
* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
*
* For further information please contact.
* http://nyatla.jp/nyatoolkit/
* <airmail(at)ebony.plala.or.jp>
*
*/
package jp.nyatla.nyartoolkit.core.pca2d;
import jp.nyatla.nyartoolkit.NyARException;
import jp.nyatla.nyartoolkit.core.NyARMat;
import jp.nyatla.nyartoolkit.core.NyARVec;
import jp.nyatla.nyartoolkit.core.types.NyARDoublePoint2d;
import jp.nyatla.nyartoolkit.core.types.matrix.NyARDoubleMatrix22;
/**
* NyARMatrixを利用した主成分分析
* ARToolKitと同じ処理をします。
*/
public class NyARPca2d_MatrixPCA implements INyARPca2d
{
private final NyARMat __pca_input = new NyARMat(1, 2);
private final NyARMat __pca_evec = new NyARMat(2, 2);
private final NyARVec __pca_ev = new NyARVec(2);
private final NyARVec __pca_mean = new NyARVec(2);
public void pca(double[] i_x,double[] i_y,int i_number_of_point,NyARDoubleMatrix22 o_evec, NyARDoublePoint2d o_ev,NyARDoublePoint2d o_mean) throws NyARException
{
final NyARMat input = this.__pca_input;// 次処理で初期化される。
// pcaの準備
input.realloc(i_number_of_point, 2);
final double[][] input_array=input.getArray();
for(int i=0;i<i_number_of_point;i++){
input_array[i][0]=i_x[i];
input_array[i][1]=i_y[i];
}
// 主成分分析
input.matrixPCA(this.__pca_evec, this.__pca_ev, this.__pca_mean);
final double[] mean_array = this.__pca_mean.getArray();
final double[][] evec_array = this.__pca_evec.getArray();
final double[] ev_array=this.__pca_ev.getArray();
o_evec.m00=evec_array[0][0];
o_evec.m01=evec_array[0][1];
o_evec.m10=evec_array[1][0];
o_evec.m11=evec_array[1][1];
o_ev.x=ev_array[0];
o_ev.x=ev_array[1];
o_mean.x=mean_array[0];
o_mean.y=mean_array[1];
return;
}
}
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