LOD_Quadric.h

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/*
 * $Id: LOD_Quadric.h 35147 2011-02-25 10:47:28Z jesterking $
 * ***** 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.
 *
 * 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