public ClusterFit(ColourSet Colours, SquishFlags Flags) : base(Colours, Flags) {
//
// initialise the metric
//
bool isPerceptual = (flags & SquishFlags.ColourMetricPerceptual) != 0;
metric = isPerceptual ? new Vec3(0.2126f, 0.7152f, 0.0722f) : new Vec3(1.0f);
//
// initialise the best error
//
bestError = Single.MaxValue;
//
// cache some values
//
int count = colours.Count;
Vec3[] values = colours.Points;
float[] weights = colours.Weights;
//
// get the covariance matrix
//
Sym3x3 covariance = Maths.ComputeWeightedCovariance(count, values, weights);
//
// compute the principle component
//
Vec3 principle = Maths.ComputePrincipleComponent(covariance);
//
// get the min and max range as the codebook endpoints
//
Vec3 startTemp = new Vec3(0.0f);
Vec3 endTemp = new Vec3(0.0f);
if (count > 0) {
//
// compute the range
//
startTemp = endTemp = values[0];
float min = Vec3.Dot(values[0], principle);
float max = min;
for(int i = 1; i < count; ++i) {
float val = Vec3.Dot(values[i], principle);
if (val < min) {
startTemp = values[i];
min = val;
}
else {
if (val > max) {
endTemp = values[i];
max = val;
}
}
}
}
//
// clamp the output to [0, 1]
//
Vec3 one = new Vec3(1.0f);
Vec3 zero = new Vec3(0.0f);
startTemp = Vec3.Min(one, Vec3.Max(zero, startTemp));
endTemp = Vec3.Min(one, Vec3.Max(zero, endTemp));
//
// clamp to the grid and save
//
Vec3 grid = new Vec3(31.0f, 63.0f, 31.0f);
Vec3 gridrcp = new Vec3(1.0f / 31.0f, 1.0f / 63.0f, 1.0f / 31.0f);
Vec3 half = new Vec3(0.5f);
start = Vec3.Truncate(grid * startTemp + half) * gridrcp;
end = Vec3.Truncate(grid * endTemp + half) * gridrcp;
}
