evaluation of Essentia's PitchYin and PitchYinFFT on a stationary signal

PitchYin_vs_PitchYinFFT_stationary_signal_test.py

import numpy as np
import essentia.standard
import matplotlib.pyplot as plt

 
def sinewave(f0, nseconds, samplerate=44100):
    t = np.arange(1, samplerate * nseconds)
    sig = np.zeros_like(t)
    return sig + 0.5 * np.sin(2 * np.pi * f0 * t / samplerate)
 
 
def pitch(signal, samplerate=44100, framesize=2048, hopsize=512):
        audio = essentia.array(signal)
        spectrum = essentia.standard.Spectrum()
        pitchEstimateFFT = essentia.standard.PitchYinFFT(
            sampleRate=samplerate,
            frameSize=framesize
        )
        pitchEstimate = essentia.standard.PitchYin(
            sampleRate=samplerate,
            frameSize=framesize
        )

        w = essentia.standard.Windowing(type='hann')
 
        pitch = []
        pitchFFT = []
 
        for frame in essentia.standard.FrameGenerator(audio, frameSize=framesize, hopSize=hopsize, startFromZero=True):
            # -- PitchYin
            p, confidence = pitchEstimate(frame)
            pitch.append(p)

            # -- PitchYinFFT
            spec = spectrum(w(frame))
            p, confidence = pitchEstimateFFT(spec)
            pitchFFT.append(p)
            break

        # essentia array to np
        return np.array(pitch), np.array(pitchFFT)
 
 
if __name__ == "__main__":
    frange = np.arange(100, 2000, .5)

    e = np.zeros(len(frange))
    eFFT = np.zeros(len(frange))

    for i, f in enumerate(frange):
        estimate, estimateFFT = pitch(sinewave(f, 5))
        ground_truth = np.ones(len(estimate)) * f
        error = np.mean(ground_truth - estimate)
        errorFFT = np.mean(ground_truth - estimateFFT)
    
        print "Freq %f\tError Yin: %f\tError YinFFT: %f" % (f, error, errorFFT)
        e[i] = error
        eFFT[i] = errorFFT
 
    plt.plot(frange, e, label='PitchYin')
    plt.plot(frange, eFFT, label='PitchYinFFT')

    plt.axhline(0, linewidth=3, color='r')
    plt.xlabel('Frequency (Hz)')
    plt.ylabel('Error (Hz)')
    
    plt.legend(loc=4)
    plt.show()