forked from a1batross/Paranoia2_original
117 lines
3.6 KiB
C++
117 lines
3.6 KiB
C++
/* -----------------------------------------------------------------------------
|
|
|
|
Copyright (c) 2006 Simon Brown si@sjbrown.co.uk
|
|
|
|
Permission is hereby granted, free of charge, to any person obtaining
|
|
a copy of this software and associated documentation files (the
|
|
"Software"), to deal in the Software without restriction, including
|
|
without limitation the rights to use, copy, modify, merge, publish,
|
|
distribute, sublicense, and/or sell copies of the Software, and to
|
|
permit persons to whom the Software is furnished to do so, subject to
|
|
the following conditions:
|
|
|
|
The above copyright notice and this permission notice shall be included
|
|
in all copies or substantial portions of the Software.
|
|
|
|
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
|
|
OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
|
|
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
|
|
IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
|
|
CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
|
|
TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
|
|
SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
|
|
|
|
-------------------------------------------------------------------------- */
|
|
|
|
/*! @file
|
|
|
|
The symmetric eigensystem solver algorithm is from
|
|
http://www.geometrictools.com/Documentation/EigenSymmetric3x3.pdf
|
|
*/
|
|
|
|
#include "maths.h"
|
|
#include "simd.h"
|
|
#include <cfloat>
|
|
|
|
namespace squish {
|
|
|
|
Sym3x3 ComputeWeightedCovariance( int n, Vec3 const* points, float const* weights, Vec3::Arg metric )
|
|
{
|
|
// compute the centroid
|
|
float total = 0.0f;
|
|
Vec3 centroid( 0.0f );
|
|
int i;
|
|
|
|
for( i = 0; i < n; ++i )
|
|
{
|
|
total += weights[i];
|
|
centroid += weights[i]*points[i];
|
|
}
|
|
if( total > FLT_EPSILON )
|
|
centroid /= total;
|
|
|
|
// accumulate the covariance matrix
|
|
Sym3x3 covariance( 0.0f );
|
|
for( i = 0; i < n; ++i )
|
|
{
|
|
Vec3 a = (points[i] - centroid) * metric;
|
|
Vec3 b = weights[i]*a;
|
|
|
|
covariance[0] += a.X()*b.X();
|
|
covariance[1] += a.X()*b.Y();
|
|
covariance[2] += a.X()*b.Z();
|
|
covariance[3] += a.Y()*b.Y();
|
|
covariance[4] += a.Y()*b.Z();
|
|
covariance[5] += a.Z()*b.Z();
|
|
}
|
|
|
|
// return it
|
|
return covariance;
|
|
}
|
|
|
|
static Vec3 EstimatePrincipleComponent( Sym3x3 const& matrix )
|
|
{
|
|
Vec3 const row0(matrix[0], matrix[1], matrix[2]);
|
|
Vec3 const row1(matrix[1], matrix[3], matrix[4]);
|
|
Vec3 const row2(matrix[2], matrix[4], matrix[5]);
|
|
|
|
float r0 = Dot(row0, row0);
|
|
float r1 = Dot(row1, row1);
|
|
float r2 = Dot(row2, row2);
|
|
|
|
if (r0 > r1 && r0 > r2) return row0;
|
|
if (r1 > r2) return row1;
|
|
return row2;
|
|
}
|
|
|
|
#define POWER_ITERATION_COUNT 8
|
|
|
|
Vec3 ComputePrincipleComponent( Sym3x3 const& matrix )
|
|
{
|
|
Vec4 const row0( matrix[0], matrix[1], matrix[2], 0.0f );
|
|
Vec4 const row1( matrix[1], matrix[3], matrix[4], 0.0f );
|
|
Vec4 const row2( matrix[2], matrix[4], matrix[5], 0.0f );
|
|
#if 1
|
|
Vec3 v3 = EstimatePrincipleComponent( matrix );
|
|
Vec4 v( v3.X(), v3.Y(), v3.Z(), 0.0f );
|
|
#else
|
|
Vec4 v = VEC4_CONST( 1.0f );
|
|
#endif
|
|
for( int i = 0; i < POWER_ITERATION_COUNT; ++i )
|
|
{
|
|
// matrix multiply
|
|
Vec4 w = row0*v.SplatX();
|
|
w = MultiplyAdd(row1, v.SplatY(), w);
|
|
w = MultiplyAdd(row2, v.SplatZ(), w);
|
|
|
|
// get max component from xyz in all channels
|
|
Vec4 a = Max(w.SplatX(), Max(w.SplatY(), w.SplatZ()));
|
|
|
|
// divide through and advance
|
|
v = w*Reciprocal(a);
|
|
}
|
|
return v.GetVec3();
|
|
}
|
|
|
|
} // namespace squish
|