void _update_cursor()
{
DrawGaussian(m_ProbabilityFunc, Color.white);
int x = (int)GetPosCursor().x;
m_ProbabilityFunc = Bayesian.Adapt(m_ProbabilityFunc.m_Mu, m_ProbabilityFunc.m_Sigma, x, m_SpeedElastic, m_SpeedTransition);
}
void _update_another_gaussian()
{
DrawSamples(m_Samples, Color.gray);
DrawGaussian(m_ProbabilityFunc, Color.white);
int x = (int)Bayesian.GetRandomXGaussinan(m_ProbabilityAnother.m_Mu, m_ProbabilityAnother.m_Sigma);
m_ProbabilityFunc = Bayesian.Adapt(m_ProbabilityFunc.m_Mu, m_ProbabilityFunc.m_Sigma, x, m_SpeedElastic, m_SpeedTransition);
DrawGaussian(m_ProbabilityAnother, Color.red);
}
void TakeSamples(Bayesian.Gaussian g)
{
const int num = 10000;
m_Samples = new float[m_Mat.width()];
for (int i = 0; i < num; ++i)
{
int x = (int)Bayesian.GetRandomXGaussinan(g.m_Mu, g.m_Sigma);
if (x < 0 || x >= m_Mat.width())
{
continue;
}
m_Samples[x] += 1f;
}
float max = m_Samples.Max();
for (int i = 0; i < m_Samples.Length; ++i)
{
m_Samples[i] /= max;
}
}
void DrawGaussian(Bayesian.Gaussian g, Color color)
{
float max_y = 0f;
for (int x = 0; x < m_SizeImage.x; ++x)
{
float y = Bayesian.GetYGaussian(g.m_Mu, g.m_Sigma, x);
if (y > max_y)
{
max_y = y;
}
}
for (int x = 0; x < m_SizeImage.x; ++x)
{
float y = Bayesian.GetYGaussian(g.m_Mu, g.m_Sigma, x);
y = m_SizeImage.y * y / max_y;
double[] pixel = new double[4]
{
color.r *255, color.g *255, color.b *255, 255
};
m_Mat.put((int)y, x, pixel);
}
}
