def zipSongs(songA, songB, outfile_name, battle_length = 8, random_order = False): """ alternates between a downbeat from songA and a downbeat from songB for battle_length number of bars from each, then play the remainder from songA. if random_order is True then songA will still always win but the playorder will be reversed approximately half the time. """ if random_order == True and random.sample([True, False], 1)[0]: firstSong = songB secondSong = songA flipped = True else: firstSong = songA secondSong = songB flipped = False onesA = firstSong.analysis.beats.that(fall_on_the(1)) onesB = secondSong.analysis.beats.that(fall_on_the(1)) lacedUp = audio.AudioData(shape= (int(1.2*len(firstSong.data)),2), numChannels=firstSong.numChannels, sampleRate=firstSong.sampleRate) overlap_time = 0 for bar_num in xrange(battle_length): lacedUp.append(audio.getpieces(firstSong, [onesA[bar_num]])) lacedUp.append(audio.getpieces(secondSong, [onesB[bar_num]])) overlap_time += onesA[bar_num].duration + onesB[bar_num].duration if flipped: lacedUp.append(audio.getpieces(firstSong, [onesA[battle_length]])) overlap_time += onesA[battle_length].duration lacedUp.append(audio.getpieces(songA,songA.analysis.bars[battle_length:])) lacedUp.encode(outfile_name) return overlap_time
def get_loops(fileobj, output_name="out.mp3", bars_count=8, bars_start=1):
print "analyzing"
audio_file = audio.LocalAudioFile(fileobj.name)
print "done"
print "%d bars" % len(audio_file.analysis.bars)
collect = audio.AudioQuantumList()
bars = audio_file.analysis.bars
repeats = 1
if len(bars)-bars_start < bars_count:
bars_count = 4
if len(bars)-bars_start < bars_count:
bars_count = 1
print "actual bar count was %d" % (bars_count)
for y in xrange(repeats):
for x in xrange(bars_count):
collect.append(audio_file.analysis.bars[bars_start+x])
out = audio.getpieces(audio_file, collect)
output_temp = tempfile.NamedTemporaryFile(mode="w+b", suffix=".mp3")
out.encode(output_temp.name)
# Do it again
new_one = audio.LocalAudioFile(output_temp.name)
analysis = json.loads(urllib.urlopen(new_one.analysis.pyechonest_track.analysis_url).read())
return (output_temp, analysis)
def main(infile, outfile, choices=4, bars=40):
audiofile = audio.LocalAudioFile(infile)
meter = audiofile.analysis.time_signature['value']
fade_in = audiofile.analysis.end_of_fade_in
fade_out = audiofile.analysis.start_of_fade_out
segments = audiofile.analysis.segments.that(are_contained_by_range(fade_in, fade_out))
beats = audiofile.analysis.beats.that(are_contained_by_range(segments[0].start, segments[-1].end))
outchunks = audio.AudioQuantumList()
b = []
segstarts = []
for m in range(meter):
b.append(beats.that(are_beat_number(m)))
segstarts.append(segments.that(overlap_starts_of(b[m])))
now = b[0][0]
for x in range(0, bars * meter):
beat = x % meter
next_beat = (x + 1) % meter
now_end_segment = segments.that(contain_point(now.end))[0]
next_candidates = segstarts[next_beat].ordered_by(timbre_distance_from(now_end_segment))
next_choice = next_candidates[random.randrange(min(choices, len(next_candidates)))]
next = b[next_beat].that(start_during(next_choice))[0]
outchunks.append(now)
print now.context_string()
now = next
out = audio.getpieces(audiofile, outchunks)
out.encode(outfile)
def main(units, inputFile, outputFile):
# This takes your input track, sends it to the analyzer, and returns the results.
audiofile = audio.LocalAudioFile(inputFile)
# This gets the overall key of the track
tonic = audiofile.analysis.key['value']
# This gets a list of all of the selected unit in the track.
chunks = audiofile.analysis.__getattribute__(units)
# This is a serious line!
# It means: "segments that have the tonic as the max pitch and that overlap the start of the <units>"
# Note the syntax: ".that(do_something)". These work just the way you think they should
# (That is, they act like list comprehensions for the given statement!)
# Also, note that have_pitch_max and overlap are imported from selection.py
segs = audiofile.analysis.segments.that(have_pitch_max(tonic)).that(overlap_starts_of(chunks))
# Using the same synatx as the above line:
# this line gets all rhythmic units that begin with the segment we found above
outchunks = chunks.that(overlap_ends_of(segs))
# This assembles the pieces of audio defined in collect from the analyzed audio file.
out = audio.getpieces(audiofile, outchunks)
# This writes the newly created audio to the given file.
out.encode(outputFile)
def saveChunk(self, chunk, chunkId):
audioChunk = audio.getpieces(self.audioFile, [chunk])
dir = self.filename + "_chunks"
if not os.path.exists(dir):
os.makedirs(dir)
filename = dir + "/chunk_" + chunkId + ".wav"
audioChunk.encode(filename)
def get_loops(fileobj, output_name="out.mp3", bars_count=8, bars_start=1):
print "analyzing"
audio_file = audio.LocalAudioFile(fileobj.name)
print "done"
print "%d bars" % len(audio_file.analysis.bars)
collect = audio.AudioQuantumList()
bars = audio_file.analysis.bars
repeats = 1
if len(bars)-bars_start < bars_count:
bars_count = 4
if len(bars)-bars_start < bars_count:
bars_count = 1
print "actual bar count was %d" % (bars_count)
for y in xrange(repeats):
for x in xrange(bars_count):
collect.append(audio_file.analysis.bars[bars_start+x])
out = audio.getpieces(audio_file, collect)
output_temp = tempfile.NamedTemporaryFile(mode="w+b", suffix=".mp3")
out.encode(output_temp.name)
# Do it again
new_one = audio.LocalAudioFile(output_temp.name)
analysis = json.loads(urllib.urlopen(new_one.analysis.pyechonest_track.analysis_url).read())
return (output_temp, analysis)
def main(units, inputFile, outputFile):
audiofile = audio.LocalAudioFile(inputFile)
tonic = audiofile.analysis.key['value']
chunks = audiofile.analysis.__getattribute__(units)
# Get the segments
all_segments = audiofile.analysis.segments
# Find tonic segments
tonic_segments = audio.AudioQuantumList(kind="segment")
for segment in all_segments:
pitches = segment.pitches
if pitches.index(max(pitches)) == tonic:
tonic_segments.append(segment)
# Find each chunk that matches each segment
out_chunks = audio.AudioQuantumList(kind=units)
for chunk in chunks:
for segment in tonic_segments:
if chunk.start >= segment.start and segment.end >= chunk.start:
out_chunks.append(chunk)
break
out = audio.getpieces(audiofile, out_chunks)
out.encode(outputFile)
def main() :
config.ECHO_NEST_API_KEY= "GG0IO4JU1FZQJ0IH1"
clips = file(sys.argv[1], "r")
dataList = []
rate = 12000
channels = 2
for line in clips:
detailArray = line.split('|')
songFile = detailArray[0]
startTime = float(detailArray[1])
duration = float(detailArray[2])
endTime = startTime + duration
n = numpy.array([])
e = echoAudio.AudioData(songFile, n, None, rate, channels)
q = echoAudio.AudioQuantumList(None, "segment", None, e)
a = echoAudio.AudioAnalysis(songFile)
segments = a.segments
finalSeg = segments[len(segments) - 1]
songLength = finalSeg.start + finalSeg.duration
complete = False
while(not complete):
for s in segments:
if((s.start >= startTime) & (s.start <= endTime)):
q.append(s)
if songLength >= endTime:
complete = True
else:
complete = False
endTime = endTime - songLength
p = echoAudio.getpieces(e, q)
dataList.append(p)
clips.close()
echoAudio.assemble(dataList, channels, rate).encode(sys.argv[2])
def inorder():
audio_file = audio.LocalAudioFile("../zambi.mp3")
parts = audio_file.analysis.segments
t = Tree()
for p in parts:
# start, duration, timbre, loudness_begin, loudness_max, time_loudness_max or loudness_end
t.add(p.loudness_max, p)
ordered = []
def visit(k, v):
ordered.append(v)
t.traverse('postorder', visit)
# And render the list as a new audio file!
audio.getpieces(audio_file, ordered).encode("../inorder.mp3")
def main(input_filename, output_filename):
audiofile = audio.LocalAudioFile(input_filename)
bars = audiofile.analysis.bars
collect = audio.AudioQuantumList()
for bar in bars:
collect.append(bar.children()[0])
out = audio.getpieces(audiofile, collect)
out.encode(output_filename)
def main(input_filename, output_filename):
audiofile = audio.LocalAudioFile(input_filename)
bars = audiofile.analysis.bars
collect = audio.AudioQuantumList()
for bar in bars:
collect.append(bar)
collect.append(bar)
out = audio.getpieces(audiofile, collect)
out.encode(output_filename)
def split_file_into_bars(track_name, bar_list):
i = 0
for bars in bar_list:
four_bar_chunk = audio.AudioQuantumList()
for bar in bars:
four_bar_chunk.append(bar)
audiofile = audio.LocalAudioFile("music/tracks/"+track_name+".mp3")
out = audio.getpieces(audiofile, four_bar_chunk)
i = i + 1
out.encode("music/output/"+track_name+"-chunk-"+str(i))
def main(input_filename, output_filename, break_filename, break_parts, measures, mix):
audiofile = audio.LocalAudioFile(input_filename)
sample_rate = audiofile.sampleRate
breakfile = audio.LocalAudioFile(break_filename)
if breakfile.numChannels == 1:
breakfile = mono_to_stereo(breakfile)
num_channels = audiofile.numChannels
drum_data = split_break(breakfile, break_parts)
hits_per_beat = int(break_parts / (4 * measures))
bars = audiofile.analysis.bars
out_shape = (len(audiofile) + 100000, num_channels)
out = audio.AudioData(shape=out_shape, sampleRate=sample_rate, numChannels=num_channels)
if not bars:
print "Didn't find any bars in this analysis!"
print "No output."
sys.exit(-1)
for bar in bars[:-1]:
beats = bar.children()
for i in range(len(beats)):
try:
break_index = ((bar.local_context()[0] % measures) * 4) + (i % 4)
except ValueError:
break_index = i % 4
tats = range((break_index) * hits_per_beat, (break_index + 1) * hits_per_beat)
drum_samps = sum([len(drum_data[x]) for x in tats])
beat_samps = len(audiofile[beats[i]])
beat_shape = (beat_samps, num_channels)
tat_shape = (float(beat_samps / hits_per_beat), num_channels)
beat_data = audio.AudioData(shape=beat_shape, sampleRate=sample_rate, numChannels=num_channels)
for j in tats:
tat_data = audio.AudioData(shape=tat_shape, sampleRate=sample_rate, numChannels=num_channels)
if drum_samps > beat_samps / hits_per_beat:
# truncate drum hits to fit beat length
tat_data.data = drum_data[j].data[: len(tat_data)]
elif drum_samps < beat_samps / hits_per_beat:
# space out drum hits to fit beat length
# temp_data = add_fade_out(drum_data[j])
tat_data.append(drum_data[j])
tat_data.endindex = len(tat_data)
beat_data.append(tat_data)
del (tat_data)
# account for rounding errors
beat_data.endindex = len(beat_data)
mixed_beat = audio.mix(beat_data, audiofile[beats[i]], mix=mix)
del (beat_data)
out.append(mixed_beat)
finale = bars[-1].start + bars[-1].duration
last = audio.AudioQuantum(
audiofile.analysis.bars[-1].start, audiofile.analysis.duration - audiofile.analysis.bars[-1].start
)
last_data = audio.getpieces(audiofile, [last])
out.append(last_data)
out.encode(output_filename)
def main(toReverse, inputFilename, outputFilename):
audioFile = audio.LocalAudioFile(inputFilename)
if toReverse == 'beats' :
chunks = audioFile.analysis.beats
elif toReverse == 'segments' :
chunks = audioFile.analysis.segments
else :
print usage
return
chunks.reverse()
reversedAudio = audio.getpieces(audioFile, chunks)
reversedAudio.encode(outputFilename)
def main(input_filename, output_filename, index):
audio_file = audio.LocalAudioFile(input_filename)
beats = audio_file.analysis.beats
collect = audio.AudioQuantumList()
for beat in beats:
tata = beat.children()
if len(tata)>1:
tat = tata[index]
else:
tat = tata[0]
collect.append(tat)
out = audio.getpieces(audio_file, collect)
out.encode(output_filename)
def main(username):
auds=[]
p = re.compile("mix")
files = os.listdir("f")
for file in files:
m = p.findall(file)
if m:
print "processing f/"+file
try:
auds.append(audio.LocalAudioFile("f/"+file))
except:
print "failed to include "+file
auds.sort(key=keysig)
mixed = []
end = None
previous = None
for aud in auds:
bars = aud.analysis.bars
try:
if end != None and previous != None:
mix = audio.mix(audio.getpieces(previous, [end]), audio.getpieces(aud, [bars[0]]), 0.5)
mixed.append(mix)
else:
mixed.append(audio.getpieces(aud, [bars[0]]))
except:
print "failed to create mix bar"
try:
mixed.append(audio.getpieces(aud, bars[1:-5]))
end = bars[-5]
previous = aud
except:
print "unable to append bars"
out = audio.assemble(mixed, numChannels=2)
out.encode(username+".mp3")
def main(input_filename1, input_filename2, output_filename):
audiofile1 = audio.LocalAudioFile(input_filename1)
audiofile2 = audio.LocalAudioFile(input_filename2)
beats1 = audiofile1.analysis.beats
beats2 = audiofile2.analysis.beats
l = min([len(beats1), len(beats2)])
collect = audio.AudioQuantumList()
out = None
for i in xrange(l):
if i % 2 == 1:
beat = beats1[i - offset]
next = audio.getpieces(audiofile1, [beat])
else:
beat = beats2[i]
next = audio.getpieces(audiofile2, [beat])
if out == None:
out = next
else:
out.append(next)
out.encode(output_filename)
def main(units, inputFile, outputFile):
audiofile = audio.LocalAudioFile(inputFile)
tonic = audiofile.analysis.key['value']
chunks = audiofile.analysis.__getattribute__(units)
# "segments that have the tonic as the max pitch and that overlap the start of the <units>"
# (have_pitch_max() is imported from selection.py)
segs = audiofile.analysis.segments.that(have_pitch_max(tonic)).that(overlap_starts_of(chunks))
# "<units> that begin with the above-found segments"
outchunks = chunks.that(overlap_ends_of(segs))
out = audio.getpieces(audiofile, outchunks)
out.encode(outputFile)
def main(infile, outfile, choices=4):
audiofile = audio.LocalAudioFile(infile)
meter = audiofile.analysis.time_signature['value']
fade_in = audiofile.analysis.end_of_fade_in
fade_out = audiofile.analysis.start_of_fade_out
sections = audiofile.analysis.sections.that(overlap_range(fade_in, fade_out))
outchunks = audio.AudioQuantumList()
for section in sections:
print str(section) + ":"
beats = audiofile.analysis.beats.that(are_contained_by(section))
segments = audiofile.analysis.segments.that(overlap(section))
num_bars = len(section.children())
print "\t", len(beats), "beats,", len(segments), "segments"
if len(beats) < meter:
continue
b = []
segstarts = []
for m in range(meter):
b.append(beats.that(are_beat_number(m)))
segstarts.append(segments.that(overlap_starts_of(b[m])))
if not b:
continue
elif not b[0]:
continue
now = b[0][0]
for x in range(0, num_bars * meter):
beat = x % meter
next_beat = (x + 1) % meter
now_end_segment = segments.that(contain_point(now.end))[0]
next_candidates = segstarts[next_beat].ordered_by(timbre_distance_from(now_end_segment))
if not next_candidates:
continue
next_choice = next_candidates[random.randrange(min(choices, len(next_candidates)))]
next = b[next_beat].that(start_during(next_choice))[0]
outchunks.append(now)
print "\t" + now.context_string()
now = next
out = audio.getpieces(audiofile, outchunks)
out.encode(outfile)
def main(input_filename, output_filename):
# This takes your input track, sends it to the analyzer, and returns the results.
audiofile = audio.LocalAudioFile(input_filename)
# This gets a list of every bar in the track.
# You can manipulate this just like any other Python list!
bars = audiofile.analysis.bars
# This makes a new list of "AudioQuantums".
# Those are just any discrete chunk of audio: bars, beats, etc.
collect = audio.AudioQuantumList()
# This loop puts the first item in the children of each bar into the new list.
# A bar's children are beats! Simple as that.
for bar in bars:
collect.append(bar.children()[0])
# This assembles the pieces of audio defined in collect from the analyzed audio file.
out = audio.getpieces(audiofile, collect)
# This writes the newly created audio to the given file.
out.encode(output_filename)
def main(input_filename, output_filename):
# This takes your input track, sends it to the analyzer, and returns the results.
audiofile = audio.LocalAudioFile(input_filename)
# This gets a list of every bar in the track.
# You can manipulate this just like any other Python list!
bars = audiofile.analysis.bars
# This makes a new list of "AudioQuantums".
# Those are just any discrete chunk of audio: bars, beats, etc
collect = audio.AudioQuantumList()
# This loop puts the first item in the children of each bar into the new list.
# A bar's children are beats! Simple as that.
for bar in bars:
collect.append(bar.children()[0])
# This assembles the pieces of audio defined in collect out of the analyzed audio file.
out = audio.getpieces(audiofile, collect)
# This writes the newly created to the given file.
out.encode(output_filename)
def main(units, inputFile, outputFile):
audiofile = audio.LocalAudioFile(inputFile)
collect = audio.AudioQuantumList()
if not audiofile.analysis.bars:
print "No bars found in this analysis!"
print "No output."
sys.exit(-1)
for b in audiofile.analysis.bars[0:-1]:
# all but the last beat
collect.extend(b.children()[0:-1])
if units.startswith("tatum"):
# all but the last half (round down) of the last beat
half = -(len(b.children()[-1].children()) // 2)
collect.extend(b.children()[-1].children()[0:half])
# endings were rough, so leave everything after the start
# of the final bar intact:
last = audio.AudioQuantum(
audiofile.analysis.bars[-1].start, audiofile.analysis.duration - audiofile.analysis.bars[-1].start
)
collect.append(last)
out = audio.getpieces(audiofile, collect)
out.encode(outputFile)
def main(toReverse, inputFilename, outputFilename):
# This takes your input track, sends it to the analyzer, and returns the results.
audioFile = audio.LocalAudioFile(inputFilename)
# Checks what sort of reversing we're doing.
if toReverse == 'beats' :
# This gets a list of every beat in the track.
chunks = audioFile.analysis.beats
elif toReverse == 'segments' :
# This gets a list of every segment in the track.
# Segments are the smallest chunk of audio that Remix deals with
chunks = audioFile.analysis.segments
else :
print usage
return
# Reverse the list!
chunks.reverse()
# This assembles the pieces of audio defined in chunks from the analyzed audio file.
reversedAudio = audio.getpieces(audioFile, chunks)
# This writes the newly created audio to the given file.
reversedAudio.encode(outputFilename)
def main(toReverse, inputFilename, outputFilename):
# This takes your input track, sends it to the analyzer, and returns the results.
audioFile = audio.LocalAudioFile(inputFilename)
# Checks what sort of reversing we're doing.
if toReverse == 'beats':
# This gets a list of every beat in the track.
chunks = audioFile.analysis.beats
elif toReverse == 'segments':
# This gets a list of every segment in the track.
# Segments are the smallest chunk of audio that Remix deals with
chunks = audioFile.analysis.segments
else:
print usage
return
# Reverse the list!
chunks.reverse()
# This assembles the pieces of audio defined in chunks from the analyzed audio file.
reversedAudio = audio.getpieces(audioFile, chunks)
# This writes the newly created audio to the given file.
reversedAudio.encode(outputFilename)
def main(input_filename, output_filename):
choices = 0
song = audio.LocalAudioFile(input_filename)
meter = song.analysis.time_signature.values()[1]
meter_conf = song.analysis.time_signature.values()[0]
tempo_conf = song.analysis.tempo.values()[0]
sections = song.analysis.sections
last_segment = song.analysis.segments[len(song.analysis.segments) - 1]
sl = len(sections)
print "meter confidence"
print meter_conf
print "meter"
print song.analysis.time_signature
print "number of sections"
print sl
outchunks = audio.AudioQuantumList()
if (meter_conf > 0.2):
outchunks = strong_meter(choices, song, meter, sections, sl, outchunks)
else:
outchunks = weak_meter(choices, song, sections, sl, outchunks)
outchunks.append(last_segment)
out = audio.getpieces(song, outchunks)
out.encode(output_filename)
def main(input_filename, output_filename):
choices = 0
song = audio.LocalAudioFile(input_filename)
meter = song.analysis.time_signature.values()[1]
meter_conf = song.analysis.time_signature.values()[0]
tempo_conf = song.analysis.tempo.values()[0]
sections = song.analysis.sections
last_segment = song.analysis.segments[len(song.analysis.segments) - 1]
sl = len(sections)
print "meter confidence"
print meter_conf
print "meter"
print song.analysis.time_signature
print "number of sections"
print sl
outchunks = audio.AudioQuantumList()
if (meter_conf > 0.2):
outchunks = strong_meter(choices, song, meter, sections, sl, outchunks)
else:
outchunks = weak_meter(choices, song, sections, sl, outchunks)
outchunks.append(last_segment)
out = audio.getpieces(song, outchunks)
out.encode(output_filename)
def main(units, inputFile, outputFile):
# This takes your input track, sends it to the analyzer, and returns the results.
audiofile = audio.LocalAudioFile(inputFile)
# This makes a new list of "AudioQuantums".
# Those are just any discrete chunk of audio: bars, beats, etc
collect = audio.AudioQuantumList()
# If the analysis can't find any bars, stop!
# (This might happen with really ambient music)
if not audiofile.analysis.bars:
print "No bars found in this analysis!"
print "No output."
sys.exit(-1)
# This loop puts all but the last of each bar into the new list!
for b in audiofile.analysis.bars[0:-1]:
collect.extend(b.children()[0:-1])
# If we're using tatums instead of beats, we want all but the last half (round down) of the last beat
# A tatum is the smallest rhythmic subdivision of a beat -- http://en.wikipedia.org/wiki/Tatum_grid
if units.startswith("tatum"):
half = - (len(b.children()[-1].children()) // 2)
collect.extend(b.children()[-1].children()[0:half])
# Endings were rough, so leave everything after the start of the final bar intact:
last = audio.AudioQuantum(audiofile.analysis.bars[-1].start,
audiofile.analysis.duration -
audiofile.analysis.bars[-1].start)
collect.append(last)
# This assembles the pieces of audio defined in collect from the analyzed audio file.
out = audio.getpieces(audiofile, collect)
# This writes the newly created audio to the given file.
out.encode(outputFile)
def main(units, inputFile, outputFile):
# This takes your input track, sends it to the analyzer, and returns the results.
audiofile = audio.LocalAudioFile(inputFile)
# This makes a new list of "AudioQuantums".
# Those are just any discrete chunk of audio: bars, beats, etc
collect = audio.AudioQuantumList()
# If the analysis can't find any bars, stop!
# (This might happen with really ambient music)
if not audiofile.analysis.bars:
print "No bars found in this analysis!"
print "No output."
sys.exit(-1)
# This loop puts all but the last of each bar into the new list!
for b in audiofile.analysis.bars[0:-1]:
collect.extend(b.children()[0:-1])
# If we're using tatums instead of beats, we want all but the last half (round down) of the last beat
# A tatum is the smallest rhythmic subdivision of a beat -- http://en.wikipedia.org/wiki/Tatum_grid
if units.startswith("tatum"):
half = -(len(b.children()[-1].children()) // 2)
collect.extend(b.children()[-1].children()[0:half])
# Endings were rough, so leave everything after the start of the final bar intact:
last = audio.AudioQuantum(
audiofile.analysis.bars[-1].start,
audiofile.analysis.duration - audiofile.analysis.bars[-1].start)
collect.append(last)
# This assembles the pieces of audio defined in collect from the analyzed audio file.
out = audio.getpieces(audiofile, collect)
# This writes the newly created audio to the given file.
out.encode(outputFile)
def mashComponents(localAudioFiles, loudnessMarkers):
instSegments = localAudioFiles[0].analysis.segments# This is the base track
vocalSegments = localAudioFiles[1].analysis.segments# This is the overlay track
instBeats = localAudioFiles[0].analysis.beats[loudnessMarkers[0][0]:
loudnessMarkers[0][1]]
vocalBeats = localAudioFiles[1].analysis.beats[loudnessMarkers[1][0]:
loudnessMarkers[1][1]]
pitches = meanPitches(instSegments,instBeats)
timbre = meanTimbre(instSegments,instBeats)
sections = localAudioFiles[1].analysis.sections #This is the new lead vocal layer
sections = sections.that(selection.are_contained_by_range(
vocalBeats[0].start, vocalBeats[-1].start+vocalBeats[-1].duration))
if(len(sections)==0):sections = localAudioFiles[1].analysis.sections[2:-2]
pyplot.figure(0,(16,9))
image = numpy.array(pitches)
image = numpy.concatenate((image,numpy.array(timbre)),axis = 1)
image = numpy.concatenate((image,numpy.array(meanLoudness(instSegments,instBeats))),
axis = 1)
""" Now image contains chromatic, timbral, and loudness information"""
sectBeats = getSectBeats(sections[0]) # get beats that comprise a specific section
template = numpy.array(meanPitches(vocalSegments,sectBeats))
template = numpy.concatenate((template,numpy.array(
meanTimbre(vocalSegments,sectBeats))),axis=1)
template = numpy.concatenate((template,numpy.array(
meanLoudness(vocalSegments,sectBeats))),axis = 1)
im = feature.match_template(image,template,pad_input=True)
maxValues = [] #tuples of x coord, y coord, correlation, and section len(in secs)
ij = numpy.unravel_index(numpy.argmax(im), im.shape)
x, y = ij[::-1]
maxValues.append((numpy.argmax(im),x,y,sections[0].duration))
for i in range(len(sections)-1):
sectBeats = getSectBeats(sections[i+1])
template = numpy.array(meanPitches(vocalSegments,sectBeats))
template = numpy.concatenate((template,numpy.array(
meanTimbre(vocalSegments,sectBeats))), axis=1)
template = numpy.concatenate((template,numpy.array(
meanLoudness(vocalSegments,sectBeats))),axis = 1)
match = feature.match_template(image,template,pad_input=True)
ij = numpy.unravel_index(numpy.argmax(match), match.shape)
x, y = ij[::-1]
maxValues.append((numpy.argmax(match),
TEMPLATE_WIDTH*i+x,y,sections[i+1].duration))
im = numpy.concatenate((im,match),axis = 1)
maxValues.sort()
maxValues.reverse()
try:
count = 0
while(maxValues[count][3] < 10.0): # choose a section longer than 10 secs
count += 1
x = maxValues[count][1]
y = maxValues[count][2]
except:
print "exception in mashComponents..."
ij = numpy.unravel_index(numpy.argmax(im), im.shape)
x, y = ij[::-1]
pyplot.imshow(im, cmap = pyplot.get_cmap('gray'), aspect = 'auto')
pyplot.plot(x,y,'o',markeredgecolor='r',markerfacecolor='none',markersize=15)
pyplot.show()
sectionBeats = getSectBeats(sections[x/TEMPLATE_WIDTH])
print "len(sectionBeats): ", len(sectionBeats)
print "len(instBeats): ", len(instBeats)
print "y: ", y
y = instBeats[y].absolute_context()[0]
instBeats = localAudioFiles[0].analysis.beats
matchingBeats = instBeats[(y-len(sectionBeats)/2):(y+len(sectionBeats)/2)]
print"len(matchingBeats): ", len(matchingBeats)
matchingBeats = matchingBeats[-len(sectionBeats):]
print"len(matchingBeats): ", len(matchingBeats)
""" Check to make sure lengths of beat lists are equal... """
if len(matchingBeats) != len(sectionBeats):
print "len(matchingBeats) != len(sectionBeats). For now, I will just truncate..."
print "len(matchingBeats): ", len(matchingBeats)
print "len(sectionBeats): ", len(sectionBeats)
if len(matchingBeats) > len(sectionBeats):matchingBeats = matchingBeats[
:len(sectionBeats)]
else: sectionBeats = sectionBeats[:len(matchingBeats)]
""" I have to make sure sectionBeats and matchingBeats are similarly aligned
within their group, aka bar of four beats. I will add a beat to the beginning
of matchingBeats until that condition is met. I re-initialize instBeats and
vocalBeats, because now I want to include the areas outside of those marked
off by AutomaticDJ for fade ins and fade outs."""
vocalBeats = localAudioFiles[1].analysis.beats
while(matchingBeats[0].local_context()[0] != sectionBeats[0].local_context()[0]):
matchingBeats.insert(0,instBeats[matchingBeats[0].absolute_context()[0]-1])
sectionBeats.append(vocalBeats[sectionBeats[-1].absolute_context()[0]+1])
""" Check to make sure lengths of beat lists are equal... """
if len(matchingBeats) != len(sectionBeats):
print "len(matchingBeats) != len(sectionBeats) at the second checkpoint."
print "This should not be the case. The while loop must not be adding beats"
print "to both lists equally."
print "len(matchingBeats): ", len(matchingBeats)
print "len(sectionBeats): ", len(sectionBeats)
sys.exit()
""" Next, I will use the beats around the designated beats above to transition into
and out of the mashup. """
XLEN = 4 # number of beats in crossmatch
if(matchingBeats[0].absolute_context()[0] < XLEN or
len(instBeats) - matchingBeats[-1].absolute_context()[0] - 1 < XLEN or
sectionBeats[0].absolute_context()[0] < XLEN or
len(vocalBeats) - sectionBeats[-1].absolute_context()[0] - 1 < XLEN):
XLEN -= 1
BUFFERLEN = 12 # number of beats before and after crossmatches
while(matchingBeats[0].absolute_context()[0] < BUFFERLEN+XLEN or
len(instBeats) - matchingBeats[-1].absolute_context()[0] - 1 < BUFFERLEN+XLEN or
sectionBeats[0].absolute_context()[0] < BUFFERLEN+XLEN or
len(vocalBeats) - sectionBeats[-1].absolute_context()[0] - 1 < BUFFERLEN+XLEN):
BUFFERLEN -= 1
try:
""" These are the 4 beats before matchingBeats. These are the four beats of the
instrumental track that preclude the mashed section. """
b4beatsI = instBeats[matchingBeats[0].absolute_context()[0]-XLEN:
matchingBeats[0].absolute_context()[0]]
""" These are the 4 beats after matchingBeats. These are the four beats of the
instrumental track that follow the mashed section. """
afterbeatsI = instBeats[matchingBeats[-1].absolute_context()[0]+1:
matchingBeats[-1].absolute_context()[0]+1+XLEN]
if(len(b4beatsI) != len(afterbeatsI)):
print "The lengths of b4beatsI and afterbeatsI are not equal."
""" These are the 16 beats before the 4-beat crossmatch into matchingBeats. """
preBufferBeats = instBeats[matchingBeats[0].absolute_context()[0]-BUFFERLEN-XLEN:
matchingBeats[0].absolute_context()[0]-XLEN]
""" These are the 16 beats before the 4-beat crossmatch into matchingBeats. """
postBufferBeats = instBeats[matchingBeats[-1].absolute_context()[0]+1+XLEN:
matchingBeats[-1].absolute_context()[0]+1+XLEN+BUFFERLEN]
if(len(preBufferBeats) != len(postBufferBeats)):
print "The lengths of preBufferBeats and postBufferBeats are not equal."
print "len(preBufferBeats): ", len(preBufferBeats)
print "len(postBufferBeats): ", len(postBufferBeats)
print matchingBeats[-1].absolute_context()[0]
print len(instBeats)
sys.exit()
""" These are the 4 beats before matchingBeats. These are the four beats of the
new vocal track that preclude the mashed section. """
b4beatsV = vocalBeats[sectionBeats[0].absolute_context()[0]-XLEN:
sectionBeats[0].absolute_context()[0]]
""" These are the 4 beats after matchingBeats. These are the four beats of the
new vocal track that follow the mashed section. """
afterbeatsV = vocalBeats[sectionBeats[-1].absolute_context()[0]+1:
sectionBeats[-1].absolute_context()[0]+1+XLEN]
if(len(b4beatsV) != len(afterbeatsV)):
print "The lengths of b4beatsI and afterbeatsI are not equal."
sys.exit()
except:
print "exception in 4 beat try block."
sys.exit()
""" vocData: An AudioData object for the new vocal data that will be overlaid.
instData: An AudioData object for the base instrumental track.
originalVocData: An AudioData object of the original vocal to accompany
the new one.
vocalMix: An AudioData of both vocal tracks mixed together, in order to
keep the overall vocal loudness approximately constant.
mix: An AudioData of the instrumental track and combined vocals
mixed together. """
vocData = audio.getpieces(localAudioFiles[3],b4beatsV+sectionBeats+afterbeatsV)
instData = audio.getpieces(localAudioFiles[2],b4beatsI+matchingBeats+afterbeatsI)
if instData.data.shape[0] >= vocData.data.shape[0]:
mix = audio.megamix([instData, vocData])
else:
mix = audio.megamix([vocData, instData]) # the longer data set has to go first.
mix.encode('mix.mp3')
vocData.encode('vocData.mp3')
""" Now, make a similar mix for before the mashed sections..."""
instData = audio.getpieces(localAudioFiles[2], preBufferBeats + b4beatsI)
vocData = audio.getpieces(localAudioFiles[4], preBufferBeats + b4beatsI)
premix = audio.megamix([instData, vocData])
""" ...and another mix for after the mashed sections."""
instData = audio.getpieces(localAudioFiles[2], afterbeatsI + postBufferBeats)
vocData = audio.getpieces(localAudioFiles[4], afterbeatsI + postBufferBeats)
postmix = audio.megamix([instData, vocData])
""" Now, I have three AudioData objects, mix, premix, and postmix, that overlap by
four beats. I will build Crossmatch objects from the overlapping regions, and three
Playback objects for the areas that are not in transition. """
action.make_stereo(premix)
action.make_stereo(mix)
action.make_stereo(postmix)
preBuffdur = sum([p.duration for p in preBufferBeats]) # duration of preBufferBeats
playback1 = action.Playback(premix,0.0,preBuffdur)
b4dur = sum([p.duration for p in b4beatsI]) # duration of b4beatsI
crossfade1 = action.Crossfade((premix,mix),(preBuffdur,0.0),b4dur)
abdur = sum([p.duration for p in afterbeatsI])
playback2 = action.Playback(mix,b4dur,mix.duration - b4dur - abdur)
crossfade2 = action.Crossfade((mix,postmix),(mix.duration - abdur,0.0),abdur)
playback3 = action.Playback(postmix,abdur,sum([p.duration for p in postBufferBeats]))
action.render([playback1,crossfade1,playback2,crossfade2,playback3], 'mashup.mp3')
"""Reverse a song by playing its beats forward starting from the end of the song"""
import echonest.audio as audio
# Easy wrapper around mp3 decoding and Echo Nest analysis
audio_file = audio.LocalAudioFile("Haiti.mp3")
# You can manipulate the beats in a song as a native python list
beats = audio_file.analysis.beats
beats.reverse()
# And render the list as a new audio file!
audio.getpieces(audio_file, beats).encode("Haiti_modded.mp3")
def compileIntro(self):
"""
Compiles the dubstep introduction. Returns an AudioData of the first 8 bars.
(8 bars at 140 bpm = ~13.71 seconds of audio)
If song is not 4/4, tries to even things out by speeding it up by the appropriate amount.
Pattern:
first 4 bars of song
first beat of 1st bar x 4 (quarter notes)
first beat of 2nd bar x 4 (quarter notes)
first beat of 3rd bar x 8 (eighth notes)
first beat of 4th bar x 8 (sixteenth notes)
third beat of 4th bar x 8 (sixteenth notes)
"""
out = audio.AudioQuantumList()
intro = audio.AudioData(self.sample_path + self.template['intro'], sampleRate=44100, numChannels=2, verbose=False)
# First 4 bars of song
custom_bars = []
if not self.beats or len(self.beats) < 16:
# Song is not long or identifiable enough
# Take our best shot at making something
self.tempo = 60.0 * 16.0 / self.original.duration
for i in xrange(0, 4):
bar = []
for j in xrange(0, 4):
length = self.original.duration / 16.0
start = ((i * 4) + j) * length
bar.append(audio.AudioQuantum(start, length, None, 0, self.original.source))
custom_bars.append(bar)
else:
for i in xrange(0, 4):
custom_bars.append(self.beats[i*4:(i*4)+4])
out.extend([x for bar in custom_bars for x in bar])
# First beat of first bar x 4
for i in xrange(0, 4):
out.append(custom_bars[0][0])
# First beat of second bar x 4
for i in xrange(0, 4):
out.append(custom_bars[1][0])
beatone = custom_bars[2][0]
beattwo = custom_bars[3][0]
beatthree = custom_bars[3][2]
# First beat of third bar x 8
for x in xrange(0, 8):
out.append(audio.AudioQuantum(beatone.start, beatone.duration/2, None, beatone.confidence, beatone.source))
# First beat of fourth bar x 8
for x in xrange(0, 8):
out.append(audio.AudioQuantum(beattwo.start, beattwo.duration/4, None, beattwo.confidence, beattwo.source))
# Third beat of fourth bar x 8
for x in xrange(0, 8):
out.append(audio.AudioQuantum(beatthree.start, beatthree.duration/4, None, beatthree.confidence, beatthree.source))
if self.original.analysis.time_signature == 4:
shifted = self.st.shiftTempo(audio.getpieces(self.original, out), self.template['tempo']/self.tempo)
else:
shifted1 = audio.getpieces(self.original, out)
shifted = self.st.shiftTempo(shifted1, len(shifted1) / ((44100 * 16 * 2 * 60.0)/self.template['tempo']))
shifted1.unload()
if shifted.numChannels == 1:
shifted = self.mono_to_stereo(shifted)
return self.truncatemix(intro, shifted, self.mixfactor(out))
def compileSection(self, j, section, hats):
"""
Compiles one "section" of dubstep - that is, one section (verse/chorus) of the original song,
but appropriately remixed as dubstep.
Chooses appropriate samples from the section of the original song in three keys (P1, m3, m7)
then plays them back in order in the generic "dubstep" pattern (all 8th notes):
| | :|
|: 1 1 1 1 1 1 1 1 | m3 m3 m3 m3 m7 m7 m7 m7 :| x2
| | :|
On the first iteration, the dubstep bar is mixed with a "splash" sound - high-passed percussion or whatnot.
On the second iteration, hats are mixed in on the offbeats and the wubs break on the last beat to let the
original song's samples shine through for a second, before dropping back down in the next section.
If samples are missing of one pitch, the searchSamples algorithm tries to find samples
a fifth from that pitch that will sound good. (If none exist, it keeps trying, in fifths up the scale.)
If the song is not 4/4, the resulting remix is sped up or slowed down by the appropriate amount.
(That can get really wonky, but sounds cool sometimes, and fixes a handful of edge cases.)
"""
onebar = audio.AudioQuantumList()
s1 = self.searchSamples(j, self.tonic)
s2 = self.searchSamples(j, (self.tonic + 3) % 12)
s3 = self.searchSamples(j, (self.tonic + 9) % 12)
biggest = max([s1, s2, s3]) #for music that's barely tonal
if not biggest:
for i in xrange(0, 12):
biggest = self.searchSamples(j, self.tonic + i)
if biggest:
break
if not biggest:
raise Exception('Missing samples in section %s of the song!' % j+1)
if not s1: s1 = biggest
if not s2: s2 = biggest
if not s3: s3 = biggest
if self.template['target'] == "tatums":
f = 4
r = 2
elif self.template['target'] == "beats":
f = 2
r = 2
elif self.template['target'] == "bars":
f = 1
r = 1
for k in xrange(0, r):
for i in xrange(0, 4*f):
onebar.append(s1[i % len(s1)])
for i in xrange(4*f, 6*f):
onebar.append( s2[i % len(s2)] )
for i in xrange(6*f, 8*f):
onebar.append( s3[i % len(s3)] )
if self.original.analysis.time_signature == 4:
orig_bar = self.st.shiftTempo(audio.getpieces(self.original, onebar), self.template['tempo']/self.tempo)
else:
orig_bar = audio.getpieces(self.original, onebar)
orig_bar = self.st.shiftTempo(orig_bar, len(orig_bar) / ((44100 * 16 * 2 * 60.0)/self.template['tempo']))
if orig_bar.numChannels == 1:
orig_bar = self.mono_to_stereo(orig_bar)
mixfactor = self.mixfactor(onebar)
a = self.truncatemix(
audio.mix(
audio.AudioData(
self.sample_path + self.template['wubs'][self.tonic],
sampleRate=44100,
numChannels=2,
verbose=False
),
audio.AudioData(
self.sample_path + self.template['splashes'][(j+1) % len(self.template['splashes'])],
sampleRate=44100,
numChannels=2,
verbose=False
)
),
orig_bar,
mixfactor
)
b = self.truncatemix(
audio.mix(
audio.AudioData(
self.sample_path + self.template['wub_breaks'][self.tonic],
sampleRate=44100,
numChannels=2,
verbose=False
),
hats
),
orig_bar,
mixfactor
)
return (a, b)
def compileIntro(self):
"""
Compiles the dubstep introduction. Returns an AudioData of the first 8 bars.
(8 bars at 140 bpm = ~13.71 seconds of audio)
If song is not 4/4, tries to even things out by speeding it up by the appropriate amount.
Pattern:
first 4 bars of song
first beat of 1st bar x 4 (quarter notes)
first beat of 2nd bar x 4 (quarter notes)
first beat of 3rd bar x 8 (eighth notes)
first beat of 4th bar x 8 (sixteenth notes)
third beat of 4th bar x 8 (sixteenth notes)
"""
out = audio.AudioQuantumList()
intro = audio.AudioData(self.sample_path + self.template['intro'],
sampleRate=44100,
numChannels=2,
verbose=False)
# First 4 bars of song
custom_bars = []
if not self.beats or len(self.beats) < 16:
# Song is not long or identifiable enough
# Take our best shot at making something
self.tempo = 60.0 * 16.0 / self.original.duration
for i in xrange(0, 4):
bar = []
for j in xrange(0, 4):
length = self.original.duration / 16.0
start = ((i * 4) + j) * length
bar.append(
audio.AudioQuantum(start, length, None, 0,
self.original.source))
custom_bars.append(bar)
else:
for i in xrange(0, 4):
custom_bars.append(self.beats[i * 4:(i * 4) + 4])
out.extend([x for bar in custom_bars for x in bar])
# First beat of first bar x 4
for i in xrange(0, 4):
out.append(custom_bars[0][0])
# First beat of second bar x 4
for i in xrange(0, 4):
out.append(custom_bars[1][0])
beatone = custom_bars[2][0]
beattwo = custom_bars[3][0]
beatthree = custom_bars[3][2]
# First beat of third bar x 8
for x in xrange(0, 8):
out.append(
audio.AudioQuantum(beatone.start, beatone.duration / 2, None,
beatone.confidence, beatone.source))
# First beat of fourth bar x 8
for x in xrange(0, 8):
out.append(
audio.AudioQuantum(beattwo.start, beattwo.duration / 4, None,
beattwo.confidence, beattwo.source))
# Third beat of fourth bar x 8
for x in xrange(0, 8):
out.append(
audio.AudioQuantum(beatthree.start, beatthree.duration / 4,
None, beatthree.confidence,
beatthree.source))
if self.original.analysis.time_signature == 4:
shifted = self.st.shiftTempo(audio.getpieces(self.original, out),
self.template['tempo'] / self.tempo)
else:
shifted1 = audio.getpieces(self.original, out)
shifted = self.st.shiftTempo(
shifted1,
len(shifted1) /
((44100 * 16 * 2 * 60.0) / self.template['tempo']))
shifted1.unload()
if shifted.numChannels == 1:
shifted = self.mono_to_stereo(shifted)
return self.truncatemix(intro, shifted, self.mixfactor(out))
def output(self, fn, prefix):
out = audio.getpieces(self.audioFile, self.chunks.ordered_by(fn))
out.encode(self.filename + "_" + prefix + ".wav")
def compileSection(self, j, section, hats):
"""
Compiles one "section" of dubstep - that is, one section (verse/chorus) of the original song,
but appropriately remixed as dubstep.
Chooses appropriate samples from the section of the original song in three keys (P1, m3, m7)
then plays them back in order in the generic "dubstep" pattern (all 8th notes):
| | :|
|: 1 1 1 1 1 1 1 1 | m3 m3 m3 m3 m7 m7 m7 m7 :| x2
| | :|
On the first iteration, the dubstep bar is mixed with a "splash" sound - high-passed percussion or whatnot.
On the second iteration, hats are mixed in on the offbeats and the wubs break on the last beat to let the
original song's samples shine through for a second, before dropping back down in the next section.
If samples are missing of one pitch, the searchSamples algorithm tries to find samples
a fifth from that pitch that will sound good. (If none exist, it keeps trying, in fifths up the scale.)
If the song is not 4/4, the resulting remix is sped up or slowed down by the appropriate amount.
(That can get really wonky, but sounds cool sometimes, and fixes a handful of edge cases.)
"""
onebar = audio.AudioQuantumList()
s1 = self.searchSamples(j, self.tonic)
s2 = self.searchSamples(j, (self.tonic + 3) % 12)
s3 = self.searchSamples(j, (self.tonic + 9) % 12)
biggest = max([s1, s2, s3]) #for music that's barely tonal
if not biggest:
for i in xrange(0, 12):
biggest = self.searchSamples(j, self.tonic + i)
if biggest:
break
if not biggest:
raise Exception('Missing samples in section %s of the song!' % j +
1)
if not s1: s1 = biggest
if not s2: s2 = biggest
if not s3: s3 = biggest
if self.template['target'] == "tatums":
f = 4
r = 2
elif self.template['target'] == "beats":
f = 2
r = 2
elif self.template['target'] == "bars":
f = 1
r = 1
for k in xrange(0, r):
for i in xrange(0, 4 * f):
onebar.append(s1[i % len(s1)])
for i in xrange(4 * f, 6 * f):
onebar.append(s2[i % len(s2)])
for i in xrange(6 * f, 8 * f):
onebar.append(s3[i % len(s3)])
if self.original.analysis.time_signature == 4:
orig_bar = self.st.shiftTempo(
audio.getpieces(self.original, onebar),
self.template['tempo'] / self.tempo)
else:
orig_bar = audio.getpieces(self.original, onebar)
orig_bar = self.st.shiftTempo(
orig_bar,
len(orig_bar) /
((44100 * 16 * 2 * 60.0) / self.template['tempo']))
if orig_bar.numChannels == 1:
orig_bar = self.mono_to_stereo(orig_bar)
mixfactor = self.mixfactor(onebar)
a = self.truncatemix(
audio.mix(
audio.AudioData(self.sample_path +
self.template['wubs'][self.tonic],
sampleRate=44100,
numChannels=2,
verbose=False),
audio.AudioData(
self.sample_path +
self.template['splashes'][(j + 1) %
len(self.template['splashes'])],
sampleRate=44100,
numChannels=2,
verbose=False)), orig_bar, mixfactor)
b = self.truncatemix(
audio.mix(
audio.AudioData(self.sample_path +
self.template['wub_breaks'][self.tonic],
sampleRate=44100,
numChannels=2,
verbose=False), hats), orig_bar, mixfactor)
return (a, b)
def main(input_filename, output_filename, break_filename, break_parts,
measures, mix):
# This takes the input tracks, sends them to the analyzer, and returns the results.
audiofile = audio.LocalAudioFile(input_filename)
sample_rate = audiofile.sampleRate
breakfile = audio.LocalAudioFile(break_filename)
# This converts the break to stereo, if it is mono
if breakfile.numChannels == 1:
breakfile = mono_to_stereo(breakfile)
# This gets the number of channels in the main file
num_channels = audiofile.numChannels
# This splits the break into each beat
drum_data = split_break(breakfile, break_parts)
hits_per_beat = int(break_parts / (4 * measures))
# This gets the bars from the input track
bars = audiofile.analysis.bars
# This creates the 'shape' of new array.
# (Shape is a tuple (x, y) that indicates the length per channel of the audio file)
out_shape = (len(audiofile) + 100000, num_channels)
# This creates a new AudioData array to write data to
out = audio.AudioData(shape=out_shape,
sampleRate=sample_rate,
numChannels=num_channels)
if not bars:
# If the analysis can't find any bars, stop!
# (This might happen with really ambient music)
print "Didn't find any bars in this analysis!"
print "No output."
sys.exit(-1)
# This is where the magic happens:
# For every beat in every bar except the last bar,
# map the tatums of the break to the tatums of the beat
for bar in bars[:-1]:
# This gets the beats in the bar, and loops over them
beats = bar.children()
for i in range(len(beats)):
# This gets the index of matching beat in the break
try:
break_index = ((bar.local_context()[0] %\
measures) * 4) + (i % 4)
except ValueError:
break_index = i % 4
# This gets the tatums from the beat of the break
tats = range((break_index) * hits_per_beat,
(break_index + 1) * hits_per_beat)
# This gets the number of samples in each tatum
drum_samps = sum([len(drum_data[x]) for x in tats])
# This gets the number of sample and the shape of the beat from the original track
beat_samps = len(audiofile[beats[i]])
beat_shape = (beat_samps, num_channels)
# This get the shape of each tatum
tat_shape = (float(beat_samps / hits_per_beat), num_channels)
# This creates the new AudioData that will be filled with chunks of the drum break
beat_data = audio.AudioData(shape=beat_shape,
sampleRate=sample_rate,
numChannels=num_channels)
for j in tats:
# This creates an audioData for each tatum
tat_data = audio.AudioData(shape=tat_shape,
sampleRate=sample_rate,
numChannels=num_channels)
# This corrects for length / timing:
# If the original is shorter than the break, truncate drum hits to fit beat length
if drum_samps > beat_samps / hits_per_beat:
tat_data.data = drum_data[j].data[:len(tat_data)]
# If the original is longer, space out drum hits to fit beat length
elif drum_samps < beat_samps / hits_per_beat:
tat_data.append(drum_data[j])
# This adds each new tatum to the new beat.
tat_data.endindex = len(tat_data)
beat_data.append(tat_data)
del (tat_data)
# This corrects for rounding errors
beat_data.endindex = len(beat_data)
# This mixes the new beat data with the input data, and appends it to the final file
mixed_beat = audio.mix(beat_data, audiofile[beats[i]], mix=mix)
del (beat_data)
out.append(mixed_beat)
# This works out the last beat and appends it to the final file
finale = bars[-1].start + bars[-1].duration
last = audio.AudioQuantum(
audiofile.analysis.bars[-1].start,
audiofile.analysis.duration - audiofile.analysis.bars[-1].start)
last_data = audio.getpieces(audiofile, [last])
out.append(last_data)
# This writes the newly created audio to the given file.
out.encode(output_filename)
def getpieces(video, segs):
a = audio.getpieces(video.audio, segs)
newv = EditableFrames(settings=video.video.settings)
for s in segs:
newv += video.video[s]
return SynchronizedAV(audio=a, video=newv)
def monoSignal(audioFile,chunk):
audioChunk = audio.getpieces(audioFile,[chunk])
arr = audioChunk.data
if arr.ndim==2:
return arr.mean(1)
return arr
def main(input_filename):
output_filename = input_filename.split('.')[0]
output_filename = ''.join(c for c in output_filename if c.isalnum())
if output_filename == "":
output_filename = "Untitled"
sounds = []
segments= []
bricks = []
audiofile = audio.LocalAudioFile(input_filename)
bars = audiofile.analysis.bars
segments = audiofile.analysis.segments
counter = 0
background = audio.AudioQuantumList()
for bar in bars:
# Check to see if we are loud enough to generate bricks
start = bar.start
duration = bar.duration
relevant_segment = None
for segment in segments:
if segment.start > start:
if segment.start > start + duration:
break # Last segment
else:
relevent_segment = segment
break
relevant_segment = segment
if relevant_segment.loudness_max < -25:
continue
counter += 1
if counter < 5:
background.append(bar)
collect = audio.AudioQuantumList()
collect.append(bar)
out = audio.getpieces(audiofile, collect)
this_filename = "%s%d.mp3" % (output_filename, counter)
sounds.append((bar, relevent_segment, "%s" % this_filename))
out.encode(this_filename)
if counter > 200:
break
bc = 0
extended_background = audio.AudioQuantumList()
while bc < 20:
bc +=1
for bar in background:
extended_background.append(bar)
background_out = audio.getpieces(audiofile, extended_background)
background_out.encode("%s_background.mp3" % output_filename)
luacode_output(output_filename, sounds, audiofile, background_out)
import sys, os
import echonest.audio as audio
import random
# Lib
def chunks(l, n):
""" Yield successive n-sized chunks from l.
"""
for i in xrange(0, len(l), n):
yield l[i:i+n]
# /Lib
subject = audio.LocalAudioFile(sys.argv[1])
beats = subject.analysis.beats
slices = list(chunks(beats, 10))
new_slices = []
while slices:
i = random.randint(0, len(slices))
for j in slices.pop(i-1):
new_slices.append(j)
audio.getpieces(subject, new_slices).encode("%s-improved.mp3" % os.path.basename(sys.argv[1][:-4]))
def getpieces(video, segs):
a = audio.getpieces(video.audio, segs)
newv = EditableFrames(settings=video.video.settings)
for s in segs:
newv += video.video[s]
return SynchronizedAV(audio=a, video=newv)
