def pca(pool, namespace=''):
llspace = 'lowlevel.'
if namespace: llspace = namespace + '.lowlevel.'
sccoeffs = pool[llspace + 'sccoeffs']
scvalleys = pool[llspace + 'scvalleys']
numFrames = len(sccoeffs)
poolSc = Pool()
merged = essentia.zeros(2 * len(sccoeffs[0]))
for frame in xrange(numFrames):
j = 0
for i in xrange(len(sccoeffs[frame])):
merged[j] = sccoeffs[frame][i]
merged[j + 1] = scvalleys[frame][i]
j += 2
poolSc.add('contrast', merged)
poolTransformed = standard.PCA(namespaceIn='contrast',
namespaceOut='contrast')(poolSc)
contrast = poolTransformed['contrast']
pool.set(llspace + 'spectral_contrast.mean', mean(contrast, axis=0))
pool.set(llspace + 'spectral_contrast.var', var(contrast, axis=0))
pool.remove(llspace + 'sccoeffs')
pool.remove(llspace + 'scvalleys')
def spectralContrastPCA(scPool, pool):
scCoeffs = scPool['lowlevel.sccoeffs']
scValleys = scPool['lowlevel.scvalleys']
frames = len(scCoeffs)
coeffs = len(scCoeffs[0])
# merged = numpy.zeros([frames, coeffs], dtype='f4')
merged = numpy.zeros(2 * coeffs, dtype='f4')
for i in range(frames):
k = 0
for j in range(coeffs):
merged[k] = scCoeffs[i][j]
merged[k + 1] = scValleys[i][j]
k += 2
scPool.add('contrast', merged)
pca = ess.PCA(namespaceIn='contrast', namespaceOut='contrast')(scPool)
pool.add(namespace + '.' + 'spectral_contrast', [c[:] for c in pca['contrast']])