public void GetKernel_ZeroPointTwoNormalized()
{
float[] matrix = StandardDeviation.GetKernel(0.2f);
Assert.AreEqual(0.9999926f, matrix[1]);
Assert.AreEqual(3, matrix.Length);
ValidateNormalizedMatrixForm(matrix);
}
public void GetKernel_ZeroPointFiveNormalized()
{
float[] matrix = StandardDeviation.GetKernel(0.5f);
Assert.AreEqual(0.7865707f, matrix[2]);
Assert.AreEqual(5, matrix.Length);
ValidateNormalizedMatrixForm(matrix);
}
public void GetKernel_TwoNormalized()
{
float[] matrix = StandardDeviation.GetKernel(2);
Assert.AreEqual(0.0648251921f, matrix[3]);
Assert.AreEqual(13, matrix.Length);
ValidateNormalizedMatrixForm(matrix);
}
public void GetKernel_OneNormalized()
{
float[] matrix = StandardDeviation.GetKernel(1);
Assert.AreEqual(0.3990503f, matrix[3]);
Assert.AreEqual(7, matrix.Length);
ValidateNormalizedMatrixForm(matrix);
}
public void Symmetric_5x1SampleBlurringIsCorrect()
{
float[,] map = new float[, ]
{
{ 0, 0, 1, 0, 0 }
};
float[] kernel = StandardDeviation.GetKernel(0.5f);
float[,] blurredMap = Convolution.Symmetric(map, kernel);
Assert.AreEqual(0.0002075485f, blurredMap[0, 0], floatPrecision);
Assert.AreEqual(0.08373106f, blurredMap[0, 1], floatPrecision);
Assert.AreEqual(0.6186935f, blurredMap[0, 2], floatPrecision);
Assert.AreEqual(0.08373106f, blurredMap[0, 3], floatPrecision);
Assert.AreEqual(0.0002075485f, blurredMap[0, 4], floatPrecision);
}
public void GetKernel_NegativeOne()
{
Assert.Throws <ArgumentException>(() => StandardDeviation.GetKernel(-1));
}
public void GetKernel_Zero()
{
Assert.Throws <ArgumentException>(() => StandardDeviation.GetKernel(0));
}
