protected ClusterFit(ColourSet colours, SquishOptions flags)
: base(colours, flags)
{
// Set the iteration count.
_IterationCount = flags.HasFlag(SquishOptions.ColourIterativeClusterFit) ? MaxIterations : 1;
// Initialise the best error.
_BestError = new Vector4(float.MaxValue);
// Initialize the metric
var perceptual = flags.HasFlag(SquishOptions.ColourMetricPerceptual);
if (perceptual)
{
_Metric = new Vector4(0.2126f, 0.7152f, 0.0722f, 0.0f);
}
else
{
_Metric = new Vector4(1.0f);
}
// Get the covariance matrix.
var covariance = Sym3x3.ComputeWeightedCovariance(colours.Count, colours.Points, colours.Weights);
// Compute the principle component
_Principle = Sym3x3.ComputePrincipledComponent(covariance);
}
public static byte[] CompressBlockMasked(byte[] rgba, int mask, SquishOptions flags)
{
flags = flags.FixFlags();
ColourSet colours = new ColourSet(rgba, mask, flags);
if (colours.Count == 1)
{
// Always do a single colour fit
//SingleColourFit fit = new SingleColourFit(ref colours, flags);
}
else if (flags.HasFlag(SquishOptions.ColourRangeFit) || colours.Count == 0)
{
// Do a range fit
//RangeFit fit = new RangeFit(ref colours, flags, metric);
}
else
{
// Default to a cluster fit (could be iterative or not)
//ClusterFit fit = new ClusterFit(ref colours, flags, metric);
}
// Compress alpha separately if needed
if (flags.HasFlag(SquishOptions.DXT3))
{
//Alpha.CompressAlphaDxt3(rgba, mask, alphaBlock);
}
else if (flags.HasFlag(SquishOptions.DXT5))
{
//Alpha.CompressAlphaDxt5(rgba, mask, alphaBlock);
}
throw new NotImplementedException();
}
private SingleColourFit(ColourSet colours, SquishOptions flags)
: base(colours, flags)
{
Vector3 values = this._Colours.Points[0];
this.colour[0] = (byte)FloatToInt(255.0f * values.X, 255);
this.colour[1] = (byte)FloatToInt(255.0f * values.Y, 255);
this.colour[2] = (byte)FloatToInt(255.0f * values.Z, 255);
this.bestError = int.MaxValue;
}
