def test_saw():
synth = Synth(44100)
synth.setParameter(SynthParameters.OSC_1_WAVEFORM, Waveform.SAW)
synth.setParameter(SynthParameters.OSC_2_WAVEFORM, Waveform.SAW)
synth.setParameter(SynthParameters.OSC_3_WAVEFORM, Waveform.SAW)
synth.noteOn(10)
out = []
for i in range(44100):
out.append(synth.getSample())
synth.noteOff(10)
def test_whiteNoise():
synth = Synth(44100)
synth.setParameter(SynthParameters.OSC_1_WAVEFORM, Waveform.WHITE_NOISE)
synth.setParameter(SynthParameters.OSC_2_WAVEFORM, Waveform.WHITE_NOISE)
synth.setParameter(SynthParameters.OSC_3_WAVEFORM, Waveform.WHITE_NOISE)
synth.noteOn(60)
out = []
for i in range(44100):
out.append(synth.getSample())
synth.noteOff(60)
def play_and_analyze(parameters, instrument_name, gesture, plot):
duration = len(parameters)/GESTURE_SAMPLING_FREQUENCY
my_synth = Synth(duration, instrument_name, None, GESTURE_SAMPLING_FREQUENCY)
output_analysis = []
for step_parameters in parameters:
my_synth.set_synthesis_parms(step_parameters)
errcode = my_synth.step_synth()
output_analysis.append(my_synth.get_analysis_values())
output_analysis = np.stack(output_analysis)
my_synth.cleanup()
if plot:
x = np.arange(len(parameters))
gesture_plot_height = int(np.ceil(gesture.shape[1]/2))
total_plot_height = int(gesture_plot_height + 4)
# Find the most similar
simils = []
for g_axis in gesture.T:
simils.append([ mse(g_axis, feature) for feature in output_analysis.T ])
most_simil = [ np.argmin(s) for s in simils ]
# Plot gesture
iv, jv = np.meshgrid(np.arange(gesture_plot_height), np.arange(2), indexing='ij')
plot_coords = list(zip(np.ndarray.flatten(iv), np.ndarray.flatten(jv)))
plot_shape = (total_plot_height, 2)
for k, g_axis in enumerate(gesture.T):
ax = plt.subplot2grid(plot_shape, plot_coords[k])
ax.plot(x, g_axis, label='gesture axis {}'.format(k), color=colors[k])
ax.legend(loc='upper right')
ax.set_ylim(0,1)
# Plot audio features
iv, jv = np.meshgrid(np.arange(gesture_plot_height, total_plot_height),
np.arange(2), indexing='ij')
plot_coords = list(zip(np.ndarray.flatten(iv), np.ndarray.flatten(jv)))
for k, feature in enumerate(output_analysis.T):
color = 'b'
if k in most_simil:
if most_simil.count(k) > 1:
color = 'k'
else:
color = colors[most_simil.index(k)]
audio_features = ['amp', 'env_crest', 'pitch', 'centroid',
'flatness', 's_crest', 'flux', 'mfcc_diff']
ax = plt.subplot2grid(plot_shape, plot_coords[k])
ax.plot(x, feature, color=color, label=audio_features[k])
ax.legend(loc='upper right')
ax.set_ylim(0,1)
similarity = np.sum([ min(s) for s in simils ])
plt.savefig('/shape/sounds/{}.png'.format(my_synth.filename), dpi=300)
plt.close()
return (my_synth.filename, similarity)
def getSynth(self,
samplerate,
melodyToPad = 0.5,
calmToExciting = 0.5,
brightToDark = 0.5,
softToHard = 0.5,
clearToRich = 0.5,
):
"""This method returns a Synth matching the requirements.
It uses REALLY COOL algorithms to embed the parameters into the Synth.
Python's random module is used to generate random parameters. Therefore, a seed can be used to
generate the exact same song twice. That seed needs to be fed to the Composer instance.
The beta-distribution is used a lot in this code as its density function can be centered
very easily and it naturally yields values in [0.0, 1.0].
More on the beta distribution in the misc.additionalmath module.
"""
"""Set up synth."""
synth = Synth(samplerate)
"""Waveforms"""
synth.setParameter(SynthParameters.OSC_ALL_WAVEFORM, Waveform.SAW)
"""Oscillator gain"""
#synth.setParameter(SynthParameters.OSC_ALL_GAIN, 1.0)
synth.setParameter(SynthParameters.OSC_1_GAIN, 1.0)
synth.setParameter(SynthParameters.OSC_2_GAIN, 1.0)
synth.setParameter(SynthParameters.OSC_3_GAIN, 1.0)
"""Oscillator detune
Depends on
- brightToDark
- clearToRich
"""
for i in range(SynthParameters.NUM_OSCILLATORS):
mode = (brightToDark + 2.0 * clearToRich) / 3.0
steepness = 1000 # high steepness, we dont want to much detune
maxDetune = 50.0 # 50 cents
detune = 2.0 * maxDetune * beta(mode, steepness) - maxDetune
synth.setParameter(SynthParameters.OSC_1_DETUNE + i, detune)
"""Volume envelope
Depends on:
- melodyToPad
- calmToExciting
- softToHard
"""
maxAttack = 4.0
maxDecay = 3.0
maxRelease = 10.0
for i in range(SynthParameters.NUM_OSCILLATORS):
mode = (5.0 * melodyToPad + (1.0 - calmToExciting) + (1.0 - softToHard)) / 7.0
steepness = 40
attack = maxAttack * beta(mode, steepness) ** 1.5
decay = maxDecay * beta(mode, steepness) ** 1.5
mode = (3.0 * melodyToPad + (1.0 - calmToExciting) + (1.0 - softToHard)) / 5.0
steepness = 40
release = maxRelease * beta(mode, steepness)
synth.setParameter(SynthParameters.OSC_1_VOLUME_ENEVELOPE_ATTACK + i, attack)
synth.setParameter(SynthParameters.OSC_1_VOLUME_ENEVELOPE_DECAY + i, decay)
synth.setParameter(SynthParameters.OSC_1_VOLUME_ENEVELOPE_RELEASE + i, release)
"""Cutoff + Resonance
Depend on:
- melodyToPad (resonance not)
- calmToExciting
- softToHard
"""
# for i in range(SynthParameters.NUM_OSCILLATORS):
# cutoff
mode = ((1.0 - melodyToPad) + calmToExciting + 3.0 * softToHard) / 5.0
steepness = 20
cutoff = beta(mode, steepness) ** 3.0
# resonance
mode = (calmToExciting + softToHard) / 2.0
steepness = 2
resonance = beta(mode, steepness) ** 1.5
synth.setParameter(SynthParameters.OSC_ALL_CUTOFF, cutoff)
synth.setParameter(SynthParameters.OSC_ALL_RESONANCE, resonance)
"""LFO
Depend on
- calmToExciting
- softToHard
"""
mode = calmToExciting
steepness = 3
frequency = beta(mode, steepness) ** 2.0
mode = (calmToExciting + softToHard) / 2.0
steepness = 20
lfoToVolume = beta(mode, steepness) ** 6.0
mode = (calmToExciting + softToHard) / 2.0
steepness = 20
lfoToFilter = beta(mode, steepness) ** 6.0
synth.setParameter(SynthParameters.LFO_FREQUENCY, frequency)
synth.setParameter(SynthParameters.LFO_TO_VOLUME, lfoToVolume)
synth.setParameter(SynthParameters.LFO_TO_FILTER, lfoToFilter)
return synth