LOD_Quadric.h

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/*
 * ***** BEGIN GPL LICENSE BLOCK *****
 *
 * 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 program; if not, write to the Free Software Foundation,
 * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
 *
 * The Original Code is Copyright (C) 2001-2002 by NaN Holding BV.
 * All rights reserved.
 *
 * The Original Code is: all of this file.
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 * Contributor(s): none yet.
 *
 * ***** END GPL LICENSE BLOCK *****
 */

#ifndef NAN_INCLUDED_LOD_Quadric_h
#define NAN_INCLUDED_LOD_Quadric_h

#include "MT_Vector3.h"
#include "MT_Matrix3x3.h"


class LOD_Quadric {

private:
    MT_Scalar a2, ab, ac, ad;
    MT_Scalar     b2, bc, bd;
    MT_Scalar         c2, cd;
    MT_Scalar             d2;

    void init(MT_Scalar a, MT_Scalar b, MT_Scalar c, MT_Scalar d);

public:

    LOD_Quadric(
    ) {
        Clear();
    };

    LOD_Quadric(
        const MT_Vector3 & vec,
        const MT_Scalar & offset
    ) {
        a2 = vec[0] *vec[0];
        b2 = vec[1] *vec[1];
        c2 = vec[2] *vec[2];

        ab = vec[0]*vec[1];
        ac = vec[0]*vec[2];
        bc = vec[1]*vec[2];

        MT_Vector3 temp = vec*offset;
        ad = temp[0];
        bd = temp[1];
        cd = temp[2];

        d2 = offset*offset;
    };

        MT_Matrix3x3 
    Tensor(
    ) const {
        // return a symmetric matrix 

        return MT_Matrix3x3(
            a2,ab,ac,
            ab,b2,bc,
            ac,bc,c2
        );
    };


        MT_Vector3
    Vector(
    ) const {
        return MT_Vector3(ad, bd, cd);
    };

        void 
    Clear(
        MT_Scalar val=0.0
    ) {
        a2=ab=ac=ad=b2=bc=bd=c2=cd=d2=val;
    };

        LOD_Quadric & 
    operator=(
        const LOD_Quadric& Q
    ) {

        a2 = Q.a2;  ab = Q.ab;  ac = Q.ac;  ad = Q.ad;
                    b2 = Q.b2;  bc = Q.bc;  bd = Q.bd;
                                c2 = Q.c2;  cd = Q.cd;  
                                            d2 = Q.d2;
        return *this;
    };
        
        LOD_Quadric& 
    operator+=(
        const LOD_Quadric& Q
    ) {
        a2 += Q.a2; ab += Q.ab;  ac += Q.ac;  ad += Q.ad;
                    b2 += Q.b2;  bc += Q.bc;  bd += Q.bd;
                                 c2 += Q.c2;  cd += Q.cd;  
                                              d2 += Q.d2;
        return *this;
    };

        LOD_Quadric& 
    operator*=(
        const MT_Scalar & s
    ) {
        a2 *= s; ab *= s;  ac *= s;  ad *= s;
                    b2 *= s;  bc *= s;  bd *= s;
                                 c2 *= s;  cd *= s;  
                                              d2 *= s;
        return *this;
    };


        MT_Scalar 
    Evaluate(
        const MT_Vector3 &v
    ) const {
        // compute the LOD_Quadric error

        return v[0]*v[0]*a2 + 2*v[0]*v[1]*ab + 2*v[0]*v[2]*ac + 2*v[0]*ad
              +v[1]*v[1]*b2 + 2*v[1]*v[2]*bc + 2*v[1]*bd
              +v[2]*v[2]*c2   + 2*v[2]*cd
              + d2;
    };
        
        bool 
    Optimize(
        MT_Vector3& v
    ) const {
        
        MT_Scalar det = Tensor().determinant();
        if (MT_fuzzyZero(det)) {
            return false;
        }
        
        v = -((Tensor().inverse()) * Vector());
        return true;
    }; 

};

#endif