public void FunctionTest()
{
Sigmoid dense = new Sigmoid(3.6, 1);
SparseSigmoid target = new SparseSigmoid(3.6, 1);
double[] sx = { 1, -0.555556, 2, +0.250000, 3, -0.864407, 4, -0.916667 };
double[] sy = { 1, -0.666667, 2, -0.166667, 3, -0.864407, 4, -0.916667 };
double[] sz = { 1, -0.944444, 3, -0.898305, 4, -0.916667 };
double[] dx = { -0.555556, +0.250000, -0.864407, -0.916667 };
double[] dy = { -0.666667, -0.166667, -0.864407, -0.916667 };
double[] dz = { -0.944444, +0.000000, -0.898305, -0.916667 };
double expected, actual;
expected = dense.Function(dx, dy);
actual = target.Function(sx, sy);
Assert.AreEqual(expected, actual);
expected = dense.Function(dx, dz);
actual = target.Function(sx, sz);
Assert.AreEqual(expected, actual);
expected = dense.Function(dy, dz);
actual = target.Function(sy, sz);
Assert.AreEqual(expected, actual);
}
private IKernel getKernel()
{
IKernel kernel;
if (rbGaussian.Checked)
{
kernel = new Gaussian((double)numSigma.Value);
}
else if (rbPolynomial.Checked)
{
kernel = new Polynomial((int)numDegree.Value, (double)numSigAlpha.Value);
}
else if (rbLaplacian.Checked)
{
kernel = new Laplacian((double)numLaplacianSigma.Value);
}
else if (rbSigmoid.Checked)
{
kernel = new Sigmoid((double)numSigAlpha.Value, (double)numSigB.Value);
}
else throw new Exception();
return kernel;
}