def runTranscribe(show=True, plot=True, useMic=True,
seconds=20.0, useScale=None, saveFile=True):
'''
runs all the methods to record from audio for `seconds` length (default 10.0)
and transcribe the resulting melody returning a music21.Score object
if `show` is True, show the stream.
if `plot` is True then a Tk graph of the frequencies will be displayed.
if `useMic` is True then use the microphone. If False it will load the file of `saveFile`
or the default temp file to run transcriptions from.
a different scale besides the chromatic scale can be specified by setting `useScale`.
See :ref:`moduleScale` for a list of allowable scales. (or a custom one can be given).
Microtonal scales are totally accepted, as are retuned scales where A != 440hz.
if `saveFile` is False then then the recorded audio is saved to disk. If
set to `True` then `environLocal.getRootTempDir() + os.path.sep + 'ex.wav'` is
used as the filename. If set to anything else then it will use that as the
filename.
'''
from music21 import audioSearch as audioSearchBase
if useScale is None:
useScale = scale.ChromaticScale('C4')
#beginning - recording or not
if saveFile != False:
if saveFile == True:
WAVE_FILENAME = environLocal.getRootTempDir() + os.path.sep + 'ex.wav'
else:
WAVE_FILENAME = saveFile
else:
WAVE_FILENAME = False
# the rest of the score
if useMic is True:
freqFromAQList = audioSearchBase.getFrequenciesFromMicrophone(length=seconds, storeWaveFilename=WAVE_FILENAME)
else:
freqFromAQList = audioSearchBase.getFrequenciesFromAudioFile(waveFilename=WAVE_FILENAME)
detectedPitchesFreq = audioSearchBase.detectPitchFrequencies(freqFromAQList, useScale)
detectedPitchesFreq = audioSearchBase.smoothFrequencies(detectedPitchesFreq)
(detectedPitchObjects, listplot) = audioSearchBase.pitchFrequenciesToObjects(detectedPitchesFreq, useScale)
(notesList, durationList) = audioSearchBase.joinConsecutiveIdenticalPitches(detectedPitchObjects)
myScore, unused_length_part = audioSearchBase.notesAndDurationsToStream(notesList, durationList, removeRestsAtBeginning=True)
if show == True:
myScore.show()
if plot == True:
try:
import matplotlib.pyplot # for find
except ImportError:
raise audioSearchBase.AudioSearchException("Cannot plot without matplotlib installed.")
matplotlib.pyplot.plot(listplot)
matplotlib.pyplot.show()
environLocal.printDebug("* END")
return myScore
def runTranscribe(show=True, plot=True, useMic=True,
seconds=20.0, useScale=None, saveFile=True):
'''
runs all the methods to record from audio for `seconds` length (default 10.0)
and transcribe the resulting melody returning a music21.Score object
if `show` is True, show the stream.
if `plot` is True then a Tk graph of the frequencies will be displayed.
if `useMic` is True then use the microphone. If False it will load the file of `saveFile`
or the default temp file to run transcriptions from.
a different scale besides the chromatic scale can be specified by setting `useScale`.
See :ref:`moduleScale` for a list of allowable scales. (or a custom one can be given).
Microtonal scales are totally accepted, as are retuned scales where A != 440hz.
if `saveFile` is False then then the recorded audio is saved to disk. If
set to `True` then `environLocal.getRootTempDir() + os.path.sep + 'ex.wav'` is
used as the filename. If set to anything else then it will use that as the
filename.
'''
from music21 import audioSearch as audioSearchBase
if useScale is None:
useScale = scale.ChromaticScale('C4')
#beginning - recording or not
if saveFile != False:
if saveFile == True:
WAVE_FILENAME = environLocal.getRootTempDir() + os.path.sep + 'ex.wav'
else:
WAVE_FILENAME = saveFile
else:
WAVE_FILENAME = False
# the rest of the score
if useMic is True:
freqFromAQList = audioSearchBase.getFrequenciesFromMicrophone(length=seconds, storeWaveFilename=WAVE_FILENAME)
else:
freqFromAQList = audioSearchBase.getFrequenciesFromAudioFile(waveFilename=WAVE_FILENAME)
detectedPitchesFreq = audioSearchBase.detectPitchFrequencies(freqFromAQList, useScale)
detectedPitchesFreq = audioSearchBase.smoothFrequencies(detectedPitchesFreq)
(detectedPitchObjects, listplot) = audioSearchBase.pitchFrequenciesToObjects(detectedPitchesFreq, useScale)
(notesList, durationList) = audioSearchBase.joinConsecutiveIdenticalPitches(detectedPitchObjects)
myScore, unused_length_part = audioSearchBase.notesAndDurationsToStream(notesList, durationList, removeRestsAtBeginning=True)
if show == True:
myScore.show()
if plot == True:
try:
import matplotlib.pyplot # for find
except ImportError:
raise audioSearchBase.AudioSearchException("Cannot plot without matplotlib installed.")
matplotlib.pyplot.plot(listplot)
matplotlib.pyplot.show()
environLocal.printDebug("* END")
return myScore
def monophonicStreamFromFile(fileName, useScale=None):
'''
Reads in a .wav file and returns a stream representing the transcribed, monophonic audio.
`fileName` should be the complete path to a file on the disk.
a different scale besides the chromatic scale can be specified by setting `useScale`.
See :ref:`moduleScale` for a list of allowable scales. (or a custom one can be given).
Microtonal scales are totally accepted, as are retuned scales where A != 440hz.
We demonstrate with an audio file beginning with an ascending scale.
>>> import os #_DOCS_HIDE
>>> taw = 'test_audio.wav' #_DOCS_HIDE
>>> waveFile = str(common.getSourceFilePath() / 'audioSearch' / taw) #_DOCS_HIDE
>>> #_DOCS_SHOW waveFile = 'test_audio.wav'
>>> p = audioSearch.transcriber.monophonicStreamFromFile(waveFile)
>>> p
<music21.stream.Part ...>
>>> p.show('text')
{0.0} <music21.note.Note C>
{0.25} <music21.note.Note C>
{0.75} <music21.note.Note D>
{1.75} <music21.note.Note E>
{2.75} <music21.note.Note F>
{4.25} <music21.note.Note G>
{5.25} <music21.note.Note A>
{6.25} <music21.note.Note B>
{7.25} <music21.note.Note C>
...
'''
from music21 import audioSearch as audioSearchBase
freqFromAQList = audioSearchBase.getFrequenciesFromAudioFile(
waveFilename=fileName)
detectedPitchesFreq = audioSearchBase.detectPitchFrequencies(
freqFromAQList, useScale)
detectedPitchesFreq = audioSearchBase.smoothFrequencies(
detectedPitchesFreq)
(detectedPitchObjects,
unused_listplot) = audioSearchBase.pitchFrequenciesToObjects(
detectedPitchesFreq, useScale)
(notesList, durationList
) = audioSearchBase.joinConsecutiveIdenticalPitches(detectedPitchObjects)
myScore, unused_length_part = audioSearchBase.notesAndDurationsToStream(
notesList, durationList, removeRestsAtBeginning=True)
return myScore.parts.first()
def monophonicStreamFromFile(fileName, useScale=None):
'''
Reads in a .wav file and returns a stream representing the transcribed, monophonic audio.
`fileName` should be the complete path to a file on the disk.
a different scale besides the chromatic scale can be specified by setting `useScale`.
See :ref:`moduleScale` for a list of allowable scales. (or a custom one can be given).
Microtonal scales are totally accepted, as are retuned scales where A != 440hz.
We demonstrate with an audio file beginning with an ascending scale.
>>> import os #_DOCS_HIDE
>>> taw = 'test_audio.wav' #_DOCS_HIDE
>>> waveFile = os.path.join(common.getSourceFilePath(), 'audioSearch', taw) #_DOCS_HIDE
>>> #_DOCS_SHOW waveFile = 'test_audio.wav'
>>> p = audioSearch.transcriber.monophonicStreamFromFile(waveFile)
>>> p
<music21.stream.Part ...>
>>> p.show('text')
{0.0} <music21.note.Note C>
{0.25} <music21.note.Note C>
{0.75} <music21.note.Note D>
{1.75} <music21.note.Note E>
{2.75} <music21.note.Note F>
{4.25} <music21.note.Note G>
{5.25} <music21.note.Note A>
{6.25} <music21.note.Note B>
{7.25} <music21.note.Note C>
...
'''
from music21 import audioSearch as audioSearchBase
freqFromAQList = audioSearchBase.getFrequenciesFromAudioFile(waveFilename=fileName)
detectedPitchesFreq = audioSearchBase.detectPitchFrequencies(freqFromAQList, useScale)
detectedPitchesFreq = audioSearchBase.smoothFrequencies(detectedPitchesFreq)
(detectedPitchObjects,
unused_listplot) = audioSearchBase.pitchFrequenciesToObjects(detectedPitchesFreq, useScale)
(notesList,
durationList) = audioSearchBase.joinConsecutiveIdenticalPitches(detectedPitchObjects)
myScore, unused_length_part = audioSearchBase.notesAndDurationsToStream(
notesList, durationList, removeRestsAtBeginning=True)
return myScore.parts[0]
