public void Fit(int roughnessIndex, int thetaIndex, NelderMead fitter, IBRDF brdf)
{
// Compute the roughness and cosTheta for this sample
float roughness, cosTheta;
GetRoughnessAndAngle(roughnessIndex, thetaIndex, tableResolution, parametrization, out roughness, out cosTheta);
// Compute the matching view vector
Vector3 tsView = new Vector3(Mathf.Sqrt(1 - cosTheta * cosTheta), 0, cosTheta);
// Compute BRDF's magnitude and average direction
LTCData currentLTCData;
LTCDataUtilities.Initialize(out currentLTCData);
LTCDataUtilities.ComputeAverageTerms(brdf, ref tsView, roughness, sampleCount, ref currentLTCData);
// Otherwise use average direction as Z vector
int previousLTCDataIndex = (thetaIndex - 1) * tableResolution + roughnessIndex;
LTCData previousLTC = ltcData[previousLTCDataIndex];
currentLTCData.m11 = previousLTC.m11;
currentLTCData.m22 = previousLTC.m22;
currentLTCData.m13 = previousLTC.m13;
LTCDataUtilities.Update(ref currentLTCData);
// Find best-fit LTC lobe (scale, alphax, alphay)
if (currentLTCData.magnitude > 1e-6)
{
double[] startFit = LTCDataUtilities.GetFittingParms(in currentLTCData);
double[] resultFit = new double[startFit.Length];
int localSampleCount = sampleCount;
currentLTCData.error = (float)fitter.FindFit(resultFit, startFit, (double)k_FitExploreDelta, (double)k_Tolerance, k_MaxIterations, (double[] parameters) =>
{
LTCDataUtilities.SetFittingParms(ref currentLTCData, parameters, false);
return(ComputeError(currentLTCData, brdf, localSampleCount, ref tsView, roughness));
});
currentLTCData.iterationsCount = fitter.m_lastIterationsCount;
// Update LTC with final best fitting values
LTCDataUtilities.SetFittingParms(ref currentLTCData, resultFit, false);
}
// Store new valid result
int currentLTCDataIndex = thetaIndex * tableResolution + roughnessIndex;
ltcData[currentLTCDataIndex] = currentLTCData;
}
static public void FitInitial(BRDFGenerator brdfGenerator, NelderMead fitter, NativeArray <LTCData> ltcData, int roughnessIndex, int thetaIndex)
{
// Compute the roughness and cosTheta for this sample
float roughness, cosTheta;
GetRoughnessAndAngle(roughnessIndex, thetaIndex, brdfGenerator.tableResolution, brdfGenerator.parametrization, out roughness, out cosTheta);
// Compute the matching view vector
Vector3 tsView = new Vector3(Mathf.Sqrt(1 - cosTheta * cosTheta), 0, cosTheta);
// Compute BRDF's magnitude and average direction
LTCData currentLTCData;
LTCDataUtilities.Initialize(out currentLTCData);
LTCDataUtilities.ComputeAverageTerms(brdfGenerator.brdf, ref tsView, roughness, brdfGenerator.sampleCount, ref currentLTCData);
// if theta == 0 the lobe is rotationally symmetric and aligned with Z = (0 0 1)
currentLTCData.X.x = 1;
currentLTCData.X.y = 0;
currentLTCData.X.z = 0;
currentLTCData.Y.x = 0;
currentLTCData.Y.y = 1;
currentLTCData.Y.z = 0;
currentLTCData.Z.x = 0;
currentLTCData.Z.y = 0;
currentLTCData.Z.z = 1;
if (roughnessIndex == (brdfGenerator.tableResolution - 1))
{
// roughness = 1 or no available result
currentLTCData.m11 = 1.0f;
currentLTCData.m22 = 1.0f;
}
else
{
// init with roughness of previous fit
LTCData previousLTC = ltcData[roughnessIndex + 1];
currentLTCData.m11 = previousLTC.m11;
currentLTCData.m22 = previousLTC.m22;
}
currentLTCData.m13 = 0;
LTCDataUtilities.Update(ref currentLTCData);
// Find best-fit LTC lobe (scale, alphax, alphay)
if (currentLTCData.magnitude > 1e-6)
{
double[] startFit = LTCDataUtilities.GetFittingParms(in currentLTCData);
double[] resultFit = new double[startFit.Length];
currentLTCData.error = (float)fitter.FindFit(resultFit, startFit, k_FitExploreDelta, k_Tolerance, k_MaxIterations, (double[] parameters) =>
{
LTCDataUtilities.SetFittingParms(ref currentLTCData, parameters, true);
return(ComputeError(currentLTCData, brdfGenerator.brdf, brdfGenerator.sampleCount, ref tsView, roughness));
});
currentLTCData.iterationsCount = fitter.m_lastIterationsCount;
// Update LTC with final best fitting values
LTCDataUtilities.SetFittingParms(ref currentLTCData, resultFit, true);
}
// Store new valid result
ltcData[roughnessIndex] = currentLTCData;
}