from wavetable.utils import normalize, trim
# Render a single sawtooth waveform generated by the StandardOscillator.
s = np.zeros(44100 * 4, dtype='d')
StandardOscillator(43.65, 0.0, 1.0).render(s)
wavfile.write('sounds/single.wav', 44100, s)
# Render a detuned pair generated by StandardOscillator.
sdp = np.zeros(44100 * 4, dtype='d')
StandardOscillator(43.65, 0.0, 0.5).render(sdp)
StandardOscillator(43.65, 3.0, 0.5).render(sdp)
wavfile.write('sounds/standard_detuned_pair.wav', 44100, sdp)
# Now a detuned pair using the ResamplingOscillator.
rdp = np.zeros(44100 * 4, dtype='d')
StandardOscillator(43.65, 0.0, 0.5).render(rdp)
ResamplingOscillator(43.65, 3.0, 0.5).render(rdp)
wavfile.write('sounds/resampling_detuned_pair.wav', 44100, rdp)
# Next, to isolate the phase artifacts introduced by using the resampling
# approach, we'll render the difference between the two previous approaches.
wavfile.write('sounds/standard_resampling_diff.wav', 44100,
normalize(trim(rdp - sdp, pow(2, 3 / 1200.0))))
# And to show that the RealTimeResamplingOscillator produces the same sound
# as the classic ResamplingOscillator, we'll render another detuned pair here.
rtdp = np.zeros(44100 * 4, dtype='d')
StandardOscillator(43.65, 0.0, 0.5).render(rtdp)
RealTimeResamplingOscillator(43.65, 3.0, 0.5).render(rtdp)
wavfile.write('sounds/realtime_detuned_pair.wav', 44100, rtdp)
plt.show() # Next, we'll show the difference in the waveform produced by using resampling # to apply detune when played next to a similar waveform vs. what I assume is # the standard method of applying detune, as described in the oscillators file. _x = np.linspace(0, 44100 * 4, 44100 * 4) ss = np.zeros(44100 * 4, dtype='d') StandardOscillator(43.65, 0.0, 0.5).render(ss) StandardOscillator(43.65, 3.0, 0.5).render(ss) rs = np.zeros(44100 * 4, dtype='d') StandardOscillator(43.65, 0.0, 0.5).render(rs) ResamplingOscillator(43.65, 3.0, 0.5).render(rs) plt.plot(_x, normalize(trim(rs - ss, pow(2, 3 / 1200.0)))) plt.show() # Now, to show that we can introduce the same artifacts in real time, we'll # show that the output of the ResamplingOscillator and the # RealTimeResamplingOscillator are actually the same. rs = np.zeros(44100 * 4, dtype='d') ResamplingOscillator(43.65, 3.0, 1.0).render(rs) rt = np.zeros(44100 * 4, dtype='d') RealTimeResamplingOscillator(43.65, 3.0, 1.0).render(rt) trim(rt, pow(2, 3 / 1200.0)) assert np.allclose(rs, rt) plt.plot(_x, rs - rt) plt.show()
