def runInstance(self,
input,
tempoHints=None,
useOnset=True,
useBands=True,
poolInit=False):
print(
'TestRhythmExtractor: Warning - these tests are evaluated with high tolerances for error, please review these tests'
)
gen = VectorInput(input)
if not tempoHints:
rhythm = RhythmExtractor(useOnset=useOnset, useBands=useBands)
else:
rhythm = RhythmExtractor(useOnset=useOnset,
useBands=useBands,
tempoHints=array(tempoHints))
p = Pool()
gen.data >> rhythm.signal
rhythm.bpm >> (p, 'rhythm.bpm')
rhythm.ticks >> (p, 'rhythm.ticks')
rhythm.estimates >> (p, 'rhythm.estimates')
#rhythm.rubatoStart >> (p, 'rhythm.rubatoStart')
#rhythm.rubatoStop >> (p, 'rhythm.rubatoStop')
rhythm.bpmIntervals >> (p, 'rhythm.bpmIntervals')
run(gen)
outputs = [
'rhythm.ticks',
'rhythm.estimates',
#'rhythm.rubatoStart', 'rhythm.rubatoStop',
'rhythm.bpmIntervals'
]
# in case ther was no output from rhythm extractor in any of the output
# ports, specially common for rubato start/stop:
for output in outputs:
if output not in p.descriptorNames():
p.add(output, [0])
if 'rhythm.bpm' not in p.descriptorNames():
p.set('rhythm.bpm', 0)
return [
p['rhythm.bpm'],
p['rhythm.ticks'],
p['rhythm.estimates'],
#p['rhythm.rubatoStart'],
#p['rhythm.rubatoStop'],
p['rhythm.bpmIntervals']
]
def testRegression(self):
loader = sMonoLoader(filename=join(testdata.audio_dir, 'recorded',
'techno_loop.wav'),
sampleRate=44100)
rhythm = RhythmExtractor()
p = Pool()
loader.audio >> rhythm.signal
loader.audio >> (p, 'audio.raw')
rhythm.bpm >> None
rhythm.bpmIntervals >> None
rhythm.estimates >> None
#rhythm.rubatoStart >> None
#rhythm.rubatoStop >> None
rhythm.ticks >> (p, 'beats.locationEstimates')
run(loader)
gen = VectorInput(p['audio.raw'])
beatsLoudness = BeatsLoudness(beats=p['beats.locationEstimates'],
frequencyBands=[20, 150])
gen.data >> beatsLoudness.signal
beatsLoudness.loudness >> (p, 'beats.loudness')
beatsLoudness.loudnessBandRatio >> (p, 'beats.loudnessBandRatio')
run(gen)
expectedLoudness = []
expectedLoudnessBandRatio = []
for beat in p['beats.locationEstimates']:
loudness, loudnessBandRatio = self.computeSingleBeatLoudness(
beat, p['audio.raw'], 44100)
expectedLoudness.append(loudness)
expectedLoudnessBandRatio.append(loudnessBandRatio)
# The values below where extracted from running essentia-1.0 cpp tests
# on some platform. This results cause the test to fail, and there is no
# way to be sure they are correct. Therefore a new test has been done
# where we compare the results of the algorithm with a manually passing
# the beats to singlebeatloudness std:
# expectedLoudness = [0.428758, 0.291341, 0.633762, 0.26555, 0.425245, 0.277024, 0.495149, 0.242385, 0.357601, 0.334, 0.323821, 0.232946, 0.528381, 0.200571, 0.437708, 0.167769, 0.584228, 0.392591, 0.530719, 0.296724, 0.550218, 0.332743, 0.501887, 0.310001, 0.403775, 0.29342, 0.578137, 0.306543, 0.470718, 0.690108, 0.0089495, 0.372516, 0.180331, 0.253785, 0.298147, 0.290077, 0.447453, 0.536407, 0.257739, 0.587473, 0.526467, 0.415834, 0.259945, 0.48784, 0.440733, 0.462674, 0.279204]
# expectedLoudnessBass = [0.928696, 0.127746, 0.681139, 0.0506813, 0.947531, 0.0654974, 0.822909, 0.0516866, 0.781132, 0.134502, 0.74214, 0.0559918, 0.870337, 0.0795841, 0.825638, 0.0935618, 0.875636, 0.11054, 0.515007, 0.0459782, 0.681463, 0.0269587, 0.755229, 0.0620431, 0.711997, 0.127048, 0.713851, 0.0255558, 0.700511, 0.754544, 0.452143, 0.745394, 0.0926197, 0.113369, 0.0516325, 0.0871752, 0.00407939, 0.779901, 0.0498086, 0.677019, 0.0714908, 0.368265, 0.0453059, 0.51892, 0.0210914, 0.63086, 0.069424]
self.assertAlmostEqualVector(p['beats.loudness'], expectedLoudness)
self.assertAlmostEqualVector(p['beats.loudnessBandRatio'],
expectedLoudnessBandRatio)