# Compare GSt's filter with LS's one in a frequency response plot.
# filename = path and file name of the respective IR sample .dat file
# midi_cutoff = GSt's abstract filter cutoff value (range of 0 to 127)
function res = plotall2(filename, filter_type, midi_resonance, midi_cutoff)

    f1 = midi_cutoff * 0.0075279;

    f2 = f1 - 1 + \
        midi_resonance * midi_cutoff * (-5.5389e-5 + 1.1982e-7 * midi_cutoff);

    if (midi_resonance < 69) gain = 1.0;
    else gain = 1.598 - midi_resonance * 0.00877;
    endif

    if strcmp(filter_type, "lp") || strcmp(filter_type, "turbo")
      num = [f1 * f1, 0 ];
    elseif strcmp(filter_type, "hp")
      num = [-1, 1, 1, -1];
    elseif strcmp(filter_type, "bp")
      num = [f1, 0, -f1];
    elseif strcmp(filter_type, "br")
      num = [1, -1, f1 * f1 - 1,  1];
    else
      error("unknown filter type");
    endif

    den = [1,  f2, f1 * f1 - 1, -f2];

    ## the lowpass turbo is simply two identical lowpass filters in
    ## series, with half gain
    if strcmp(filter_type, "turbo")
      num = conv(num, num) / 2;
      den = conv(den, den);
    endif

    [fresp, frequencies] = freqz(num * gain, den, 44100);
    frequencies = frequencies .* (22050 / pi);
    title_redesign = [ ";f=", num2str(f1 * 22050 / pi), "Hz;" ];

    # and here the respective IR sample for comparison
    file = fopen(filename, "rb");
    res = fscanf(file, "%d") / 2057773824;
    fclose(file);
    y = fft(res);
    y(1) = [];
    len = length(y) / 2;
    y = y(1:len);
    x = (1:len) / len * 22050;
    title_file = [ ";", filename, ";" ];

    # finally plot and compare our designed filter against the original one
    axis([20, 23000]);
    xlabel("Frequency [Hz]");
    ylabel("Attenuation [dB]");
    semilogx(frequencies, 20 * log10(abs(fresp)), title_redesign, x, 20 * log10(abs(y)), title_file), grid;
endfunction;