def pickleAnalysisData(localAudioFiles):
beatList = [laf.analysis.beats for laf in localAudioFiles]
segmentList = [laf.analysis.segments for laf in localAudioFiles]
beatPitchesList = []
beatTimbreList = []
beatLoudnessList = []
for beats,segments in zip(beatList,segmentList):
beatPitches = []
for beat in beats:
segs = segments.that(selection.overlap(beat))
beatPitches.append(meanPitches(segs))
beatPitchesList.append(beatPitches)
for beats,segments in zip(beatList,segmentList):
beatTimbre = []
for beat in beats:
segs = segments.that(selection.overlap(beat))
beatTimbre.append(meanTimbre(segs))
beatTimbreList.append(beatTimbre)
for beats,segments in zip(beatList,segmentList):
beatLoudness = []
for beat in beats:
segs = segments.that(selection.overlap(beat))
beatLoudness.append(matlib.mean(segs.loudness_max))
beatLoudnessList.append(beatLoudness)
cPickle.dump(beatPitchesList, open('AmuInstPitches.pkl', 'w'))
cPickle.dump(beatTimbreList, open('AmuInstTimbre.pkl', 'w'))
cPickle.dump(beatLoudnessList, open('AmuInstLoudness.pkl', 'w'))
sectionFirstBeats = []
sections = [laf.analysis.sections for laf in localAudioFiles]
for sectionsList,bList in zip(sections,beatList):
temp = [bList.index(bList.that(selection.overlap(section))[0]) for section in sectionsList]
sectionFirstBeats.append(temp)
cPickle.dump(sectionFirstBeats, open('AmuInstSections.pkl', 'w'))
def meanLoudness(segments, beats):
"""
Returns a loudness vector that is the mean of the loudness values of any segments
that overlap this AudioQuantum.
"""
loudness = []
for beat in beats:
segs = segments.that(selection.are_contained_by(beat))
if(len(segs) == 0): segs = segments.that(selection.start_during(beat))
if(len(segs) == 0): segs = segments.that(selection.overlap(beat))
values = [seg.loudness_max for seg in segments.that(selection.are_contained_by
(beat))]
loudness.append([sum(values)/len(segs)]*6)
return loudness
"""
def meanTimbre(segments, beats):
"""
Returns a timbre vector that is the mean of the timbre vectors of any segments
that overlap this AudioQuantum.
"""
timbre = []
for beat in beats:
temp = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
segs = segments.that(selection.are_contained_by(beat))
if(len(segs) == 0): segs = segments.that(selection.start_during(beat))
if(len(segs) == 0): segs = segments.that(selection.overlap(beat))
for seg in segs:
for index, tim in enumerate(seg.pitches):
temp[index] = temp[index] + tim
timbre.append([float(tim / len(segs)) for tim in temp])
return timbre
def meanPitches(segments, beats):
"""
Returns a pitch vector that is the mean of the pitch vectors of any segments
that overlap this AudioQuantum.
"""
pitches = []
for beat in beats:
temp_pitches = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
segs = segments.that(selection.are_contained_by(beat))
if(len(segs) == 0): segs = segments.that(selection.start_during(beat))
if(len(segs) == 0): segs = segments.that(selection.overlap(beat))
for seg in segs:
for index, pitch in enumerate(seg.pitches):
temp_pitches[index] = temp_pitches[index] + pitch
pitches.append([float(pitch / len(segs)) for pitch in temp_pitches])
return pitches
def getBeatMarkers(loudnessMarkers,segments,beats):
return [(b.index(b.that(selection.overlap(segments[i][loudnessMarkers[i][0]]))[0]),
b.index(b.that(selection.overlap(segments[i][loudnessMarkers[i][1]]))[0]))
for i,b in enumerate(beats)]