static void GenerateDatasetForTrainingCVAE()
{
const int N = 1 << 22;
StreamWriter writer = new StreamWriter("ScattersDataSet.ds");
Console.WriteLine("Generating file...");
GRandom rnd = new GRandom();
for (int i = 0; i < N; i++)
{
if (i % 1000 == 0)
{
Console.Write("\r ");
Console.Write("\rCompleted... " + (i * 100.0f / N).ToString("F2"));
}
var settings = GenerateNewSettings(rnd);
var r = Scattering.GetVPTSampleInSphere(settings, rnd);
// code path variables in a compact way
float3 zAxis = float3(0, 0, 1);
float3 xAxis = abs(r.x.z) > 0.999 ? float3(1, 0, 0) : normalize(cross(r.x, float3(0, 0, 1)));
float3 yAxis = cross(zAxis, xAxis);
float3x3 normR = transpose(float3x3(xAxis, yAxis, zAxis));
float3 normx = mul(r.x, normR);
float3 normw = mul(r.w, normR);
float3 normX = mul(r.X, normR);
float3 normW = mul(r.W, normR);
float3 B = float3(1, 0, 0);
float3 T = cross(normx, B);
float costheta = normx.z;
float beta = dot(normw, T);
float alpha = dot(normw, B);
writer.WriteLine("{0}, {1}, {2}, {3}, {4}, {5}, {6}, {7}, {8}, {9}, {10}, {11}, {12}",
settings.Sigma,
settings.G,
settings.Phi,
r.N,
costheta,
beta,
alpha,
normX.x,
normX.y,
normX.z,
normW.x,
normW.y,
normW.z
);
}
Console.WriteLine();
writer.Close();
Console.WriteLine("Done.");
}
static void GenerateDatasetForTabulationXMethod()
{
int total = 0;
Parallel.For(0, 8, file =>
{
BinaryWriter writer = new BinaryWriter(new FileStream("DataSet" + file + ".bin", FileMode.Create));
GRandom rnd = new GRandom(file);
int N = 1 << 24; // 16 million samples per file
while (N-- > 0)
{
var settings = GenerateSettingsForX(rnd);
var r = Scattering.GetVPTSampleInSphere(settings, rnd);
// code path variables in a compact way
float3 zAxis = float3(0, 0, 1);
float3 xAxis = abs(r.x.z) > 0.999 ? float3(1, 0, 0) : normalize(cross(r.x, float3(0, 0, 1)));
float3 yAxis = cross(zAxis, xAxis);
float3x3 normR = transpose(float3x3(xAxis, yAxis, zAxis));
float3 normx = mul(r.x, normR);
float3 normw = mul(r.w, normR);
float3 normX = mul(r.X, normR);
float3 normW = mul(r.W, normR);
float3 B = float3(1, 0, 0);
float3 T = cross(normx, B);
float costheta = normx.z;
float beta = dot(normw, T);
float alpha = dot(normw, B);
writer.Write(settings.Sigma);
writer.Write(settings.G);
writer.Write(r.N);
writer.Write(costheta);
writer.Write(beta);
writer.Write(alpha);
Interlocked.Add(ref total, 1);
if (total % 100000 == 0)
{
Console.WriteLine("Overall progress: {0}%", total * 100.0f / (8 * (1 << 24)));
}
}
writer.Close();
});
}
static void GenerateDatasetForTabulationMethod()
{
/*
* This method generates data samples and builds a table using
* the idea in Mueller et al 2016.
*/
float[] table = new float[BINS_G * BINS_SA * BINS_R * BINS_THETA];
float[,,] oneTimeScatteringAlbedo = new float[BINS_G, BINS_SA, BINS_R];
float[,,] multiTimeScatteringAlbedo = new float[BINS_G, BINS_SA, BINS_R];
int MAX_N = 200;
int P = 1 << 18; // one quarter million photons per setting.
Console.WriteLine("Process started.");
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
int TOTAL_NUMBER_OF_SETTINGS = BINS_G * BINS_R;
int solvedSettings = 0;
Parallel.For(0, BINS_G, binG =>
{
GRandom rnd = new GRandom(binG);
float g = (binG + rnd.random()) * 2.0f * 0.99f / BINS_G - 0.99f;
for (int binR = 0; binR < BINS_R; binR++)
{
float r = pow(2.0f, binR);
Console.WriteLine("Solved {0}%.", solvedSettings * 100.0f / TOTAL_NUMBER_OF_SETTINGS);
if (solvedSettings >= 1)
{
Console.WriteLine("ETA {0} ", stopwatch.Elapsed * (TOTAL_NUMBER_OF_SETTINGS / (float)solvedSettings - 1));
}
MediumSettings settings = new MediumSettings();
settings.Sigma = r;
settings.Phi = 1;
settings.G = g;
long[,] Hl = new long[BINS_THETA, MAX_N + 1];
for (int sample = 0; sample < P; sample++)
{
var summary = Scattering.GetVPTSampleInSphereOffcenter(settings, rnd);
int thetaBin = (int)min(BINS_THETA - 1, BINS_THETA * (summary.x.z * 0.5f + 0.5f));
int nBin = (int)min(MAX_N, summary.N);
Hl[thetaBin, nBin]++;
}
for (int binSA = 0; binSA < BINS_SA; binSA++)
{
float phi = binSA == BINS_SA - 1 ? 1.0f : 1 - exp(binSA * log(0.001f) / (BINS_SA - 1));
for (int binTheta = 0; binTheta < BINS_THETA; binTheta++)
{
int pos = STRIDE_G * binG + STRIDE_SA * binSA + STRIDE_R * binR + binTheta;
for (int n = 2; n <= MAX_N; n++)
{
table[pos] += pow(phi, n) * Hl[binTheta, n];
multiTimeScatteringAlbedo[binG, binSA, binR] += pow(phi, n) * Hl[binTheta, n];
}
oneTimeScatteringAlbedo[binG, binSA, binR] += phi * Hl[binTheta, 1];
}
// Sum and normalize table slice to create an empirical cdf
for (int binTheta = 0; binTheta < BINS_THETA; binTheta++)
{
int pos = STRIDE_G * binG + STRIDE_SA * binSA + STRIDE_R * binR + binTheta;
if (binTheta > 0)
{
table[pos] += table[pos - 1];
}
}
}
solvedSettings++;
}
});
Console.WriteLine("Finished generation in {0}", stopwatch.Elapsed);
Console.WriteLine("Saving table");
BinaryWriter bw = new BinaryWriter(new FileStream("stf.bin", FileMode.Create));
for (int binG = 0; binG < BINS_G; binG++)
{
for (int binSA = 0; binSA < BINS_SA; binSA++)
{
for (int binR = 0; binR < BINS_R; binR++)
{
bw.Write(oneTimeScatteringAlbedo[binG, binSA, binR] / P);
}
}
}
for (int binG = 0; binG < BINS_G; binG++)
{
for (int binSA = 0; binSA < BINS_SA; binSA++)
{
for (int binR = 0; binR < BINS_R; binR++)
{
bw.Write(multiTimeScatteringAlbedo[binG, binSA, binR] / P);
}
}
}
int index = 0;
for (int binG = 0; binG < BINS_G; binG++)
{
for (int binSA = 0; binSA < BINS_SA; binSA++)
{
for (int binR = 0; binR < BINS_R; binR++)
{
for (int binTheta = 0; binTheta < BINS_THETA; binTheta++)
{
bw.Write(table[index++] / P);
}
}
}
}
bw.Close();
Console.WriteLine("Done.");
}
