/// <summary>
/// 重畳加算法でsamplesとインパルス応答との畳み込みを計算する
/// </summary>
public void Convolution(float[] samples)
{
Debug.Assert(samples.Length == blockSamples);
Buffer.BlockCopy(samples, 0, convolutionBuf1X, 0, SizeofFloat * samples.Length);
Array.Clear(convolutionBuf1X, samples.Length, blockSize - samples.Length);
Array.Clear(convolutionBuf1Y, 0, blockSize);
fft.Forward(convolutionBuf1X, convolutionBuf1Y);
ComplexMultiple(convolutionBuf2X, convolutionBuf2Y, convolutionBuf1X, convolutionBuf1Y, frequencyResponseX, frequencyResponseY);
fft.Inverse(convolutionBuf2X, convolutionBuf2Y);
for (int i = blockSamples, j = 0; i < blockSize; ++i, ++j)
{
convolutionBuf2X[j] += overlap[j];
overlap[j] = convolutionBuf2X[i];
}
Buffer.BlockCopy(convolutionBuf2X, 0, convolutionResult, 0, SizeofFloat * blockSamples);
}
/// <summary>
/// FFTテスト
/// </summary>
private void FftTest()
{
if (!fftTestFlg)
{
return;
}
debugButton.AddButton("FftTest", () =>
{
float[] x = new float[] { 1, 0, 0, 0 };
float[] y = new float[] { 0, 0, 0, 0 };
var t = new Fft(4);
t.Forward(x, y);
t.Inverse(x, y);
Debug.Log($"result =================================");
for (int i = 0; i < x.Length; ++i)
{
Debug.Log($"[{i}]:{x[i]:0.00} {y[i]:0.00}");
}
});
}
