music21.features.native

Original music21 feature extractors.

ChordBassMotionFeature

class music21.features.native.ChordBassMotionFeature(dataOrStream=None, **keywords)

A twelve element feature that reports the fraction of all chord motion of music21.harmony.Harmony objects that move up by i-half-steps. (a half-step motion down would be stored in i = 11). i = 0 is always 0.0 since consecutive chords on the same pitch are ignored (unless there are 0 or 1 harmonies, in which case it is 1)

Sample test on Dylan’s Blowing In The Wind (not included), showing all motion is 3rds, 6ths, or especially 4ths and 5ths.

s = corpus.parse(‘demos/BlowinInTheWind’) fe = features.native.ChordBassMotionFeature(s) fe.extract().vector

[0.0, 0.0, 0.0, 0.0416…, 0.0416…, 0.166…, 0.0, 0.54166…, 0.0, 0.0, 0.2083… 0.0]

For comparison, the Beatles Here Comes the Sun has more tone motion

[0.0, 0.05…, 0.14…, 0.03…, 0.06…, 0.3…, 0.008…, 0.303…,

0.0, 0.0, 0.07…, 0.008…]

Post 1990s music has a lot more semitone motion.

ChordBassMotionFeature bases

• FeatureExtractor

ChordBassMotionFeature methods

ChordBassMotionFeature.process()

Do processing necessary, storing result in feature.

Methods inherited from FeatureExtractor:

extract() fillFeatureAttributes()

getAttributeLabels() getBlankFeature()

prepareFeature() setData()

ComposerPopularity

class music21.features.native.ComposerPopularity(dataOrStream=None, **keywords)

REMOVED in v7 because Google’s repsonse no longer includes result counts. Empty class still here so that id won’t be reused, but it’s been removed from this module’s list of features.

ComposerPopularity bases

• FeatureExtractor

ComposerPopularity methods

Methods inherited from FeatureExtractor:

extract() fillFeatureAttributes() getAttributeLabels()

getBlankFeature() prepareFeature()

process() setData()

DiminishedSeventhSimultaneityPrevalence

class music21.features.native.DiminishedSeventhSimultaneityPrevalence(dataOrStream=None, **keywords)

Percentage of all simultaneities that are diminished seventh chords.

>>> s = corpus.parse('bwv66.6')
>>> fe = features.native.DiminishedSeventhSimultaneityPrevalence(s)
>>> fe.extract().vector
[0.0]

DiminishedSeventhSimultaneityPrevalence bases

• FeatureExtractor

DiminishedSeventhSimultaneityPrevalence methods

DiminishedSeventhSimultaneityPrevalence.process()

Do processing necessary, storing result in feature.

Methods inherited from FeatureExtractor:

extract() fillFeatureAttributes()

getAttributeLabels() getBlankFeature()

prepareFeature() setData()

DiminishedTriadSimultaneityPrevalence

class music21.features.native.DiminishedTriadSimultaneityPrevalence(dataOrStream=None, **keywords)

Percentage of all simultaneities that are diminished triads.

>>> s = corpus.parse('bwv66.6')
>>> fe = features.native.DiminishedTriadSimultaneityPrevalence(s)
>>> fe.extract().vector
[0.019...]

DiminishedTriadSimultaneityPrevalence bases

• FeatureExtractor

DiminishedTriadSimultaneityPrevalence methods

DiminishedTriadSimultaneityPrevalence.process()

Do processing necessary, storing result in feature.

Methods inherited from FeatureExtractor:

extract() fillFeatureAttributes()

getAttributeLabels() getBlankFeature()

prepareFeature() setData()

DominantSeventhSimultaneityPrevalence

class music21.features.native.DominantSeventhSimultaneityPrevalence(dataOrStream=None, **keywords)

Percentage of all simultaneities that are dominant seventh.

>>> s = corpus.parse('bwv66.6')
>>> fe = features.native.DominantSeventhSimultaneityPrevalence(s)
>>> fe.extract().vector
[0.076...]

DominantSeventhSimultaneityPrevalence bases

• FeatureExtractor

DominantSeventhSimultaneityPrevalence methods

DominantSeventhSimultaneityPrevalence.process()

Do processing necessary, storing result in feature.

Methods inherited from FeatureExtractor:

extract() fillFeatureAttributes()

getAttributeLabels() getBlankFeature()

prepareFeature() setData()

FirstBeatAttackPrevalence

class music21.features.native.FirstBeatAttackPrevalence(dataOrStream=None, **keywords)

NOT IMPLEMENTED!

>>> s = corpus.parse('bwv66.6')
>>> fe = features.native.FirstBeatAttackPrevalence(s)
>>> f = fe.extract()
>>> f.vector
[0]

TODO: Implement!

FirstBeatAttackPrevalence bases

• FeatureExtractor

FirstBeatAttackPrevalence methods

Methods inherited from FeatureExtractor:

extract() fillFeatureAttributes() getAttributeLabels()

getBlankFeature() prepareFeature()

process() setData()

IncorrectlySpelledTriadPrevalence

class music21.features.native.IncorrectlySpelledTriadPrevalence(dataOrStream=None, **keywords)

Percentage of all triads that are spelled incorrectly.

example:

Mozart k155 movement 2 has a single instance of an incorrectly spelled triad (m. 17, where the C# of an A-major chord has a lower neighbor B# thus temporarily creating an incorrectly spelled A-minor chord).

We would expect highly chromatic music such as Reger or Wagner to have a higher percentage, or automatically rendered MIDI transcriptions (which don’t distinguish between D# and Eb).

>>> s = corpus.parse('bwv66.6')
>>> fe = features.native.IncorrectlySpelledTriadPrevalence(s)
>>> fe.extract().vector
[0.02...]

IncorrectlySpelledTriadPrevalence bases

• FeatureExtractor

IncorrectlySpelledTriadPrevalence methods

IncorrectlySpelledTriadPrevalence.process()

Do processing necessary, storing result in feature.

Methods inherited from FeatureExtractor:

extract() fillFeatureAttributes()

getAttributeLabels() getBlankFeature()

prepareFeature() setData()

LandiniCadence

class music21.features.native.LandiniCadence(dataOrStream=None, **keywords)

Return a boolean if one or more Parts end with a Landini-like cadential figure.

LandiniCadence bases

• FeatureExtractor

LandiniCadence methods

LandiniCadence.process()

Do processing necessary, storing result in feature.

Methods inherited from FeatureExtractor:

extract() fillFeatureAttributes()

getAttributeLabels() getBlankFeature()

prepareFeature() setData()

LanguageFeature

class music21.features.native.LanguageFeature(dataOrStream=None, **keywords)

language of text as a number the number is the index of text.LanguageDetector.languageCodes + 1 or 0 if there is no language.

Detect that the language of a Handel aria is Italian.

>>> s = corpus.parse('handel/rinaldo/lascia_chio_pianga')
>>> fe = features.native.LanguageFeature(s)
>>> fe.extract().vector
[3]

LanguageFeature bases

• FeatureExtractor

LanguageFeature methods

LanguageFeature.process()

Do processing necessary, storing result in feature.

Methods inherited from FeatureExtractor:

extract() fillFeatureAttributes()

getAttributeLabels() getBlankFeature()

prepareFeature() setData()

MajorTriadSimultaneityPrevalence

class music21.features.native.MajorTriadSimultaneityPrevalence(dataOrStream=None, **keywords)

Percentage of all simultaneities that are major triads.

>>> s = corpus.parse('bwv66.6')
>>> fe = features.native.MajorTriadSimultaneityPrevalence(s)
>>> fe.extract().vector
[0.46...]

MajorTriadSimultaneityPrevalence bases

• FeatureExtractor

MajorTriadSimultaneityPrevalence methods

MajorTriadSimultaneityPrevalence.process()

Do processing necessary, storing result in feature.

Methods inherited from FeatureExtractor:

extract() fillFeatureAttributes()

getAttributeLabels() getBlankFeature()

prepareFeature() setData()

MinorTriadSimultaneityPrevalence

class music21.features.native.MinorTriadSimultaneityPrevalence(dataOrStream=None, **keywords)

Percentage of all simultaneities that are minor triads.

>>> s = corpus.parse('bwv66.6')
>>> fe = features.native.MinorTriadSimultaneityPrevalence(s)
>>> fe.extract().vector  # same as major in this work
[0.211...]

MinorTriadSimultaneityPrevalence bases

• FeatureExtractor

MinorTriadSimultaneityPrevalence methods

MinorTriadSimultaneityPrevalence.process()

Do processing necessary, storing result in feature.

Methods inherited from FeatureExtractor:

extract() fillFeatureAttributes()

getAttributeLabels() getBlankFeature()

prepareFeature() setData()

MostCommonNoteQuarterLength

class music21.features.native.MostCommonNoteQuarterLength(dataOrStream=None, **keywords)

>>> s = corpus.parse('bwv66.6')
>>> fe = features.native.MostCommonNoteQuarterLength(s)
>>> fe.extract().vector
[1.0]

MostCommonNoteQuarterLength bases

• FeatureExtractor

MostCommonNoteQuarterLength methods

MostCommonNoteQuarterLength.process()

Do processing necessary, storing result in feature.

Methods inherited from FeatureExtractor:

extract() fillFeatureAttributes()

getAttributeLabels() getBlankFeature()

prepareFeature() setData()

MostCommonNoteQuarterLengthPrevalence

class music21.features.native.MostCommonNoteQuarterLengthPrevalence(dataOrStream=None, **keywords)

>>> s = corpus.parse('bwv66.6')
>>> fe = features.native.MostCommonNoteQuarterLengthPrevalence(s)
>>> fe.extract().vector
[0.60...]

MostCommonNoteQuarterLengthPrevalence bases

• FeatureExtractor

MostCommonNoteQuarterLengthPrevalence methods

MostCommonNoteQuarterLengthPrevalence.process()

Do processing necessary, storing result in feature.

Methods inherited from FeatureExtractor:

extract() fillFeatureAttributes()

getAttributeLabels() getBlankFeature()

prepareFeature() setData()

MostCommonPitchClassSetSimultaneityPrevalence

class music21.features.native.MostCommonPitchClassSetSimultaneityPrevalence(dataOrStream=None, **keywords)

Fraction of all pitch class simultaneities that are the most common simultaneity.

>>> s = corpus.parse('bwv66.6')
>>> fe = features.native.MostCommonPitchClassSetSimultaneityPrevalence(s)
>>> fe.extract().vector
[0.134...]

MostCommonPitchClassSetSimultaneityPrevalence bases

• FeatureExtractor

MostCommonPitchClassSetSimultaneityPrevalence methods

MostCommonPitchClassSetSimultaneityPrevalence.process()

Do processing necessary, storing result in feature.

Methods inherited from FeatureExtractor:

extract() fillFeatureAttributes()

getAttributeLabels() getBlankFeature()

prepareFeature() setData()

MostCommonSetClassSimultaneityPrevalence

class music21.features.native.MostCommonSetClassSimultaneityPrevalence(dataOrStream=None, **keywords)

Fraction of all set class simultaneities that the most common simultaneity occupies.

>>> s = corpus.parse('bwv66.6')
>>> fe = features.native.MostCommonSetClassSimultaneityPrevalence(s)
>>> fe.extract().vector
[0.653...]
>>> s2 = corpus.parse('schoenberg/opus19', 6)
>>> fe2 = features.native.MostCommonSetClassSimultaneityPrevalence(s2)
>>> fe2.extract().vector
[0.228...]

MostCommonSetClassSimultaneityPrevalence bases

• FeatureExtractor

MostCommonSetClassSimultaneityPrevalence methods

MostCommonSetClassSimultaneityPrevalence.process()

Do processing necessary, storing result in feature.

Methods inherited from FeatureExtractor:

extract() fillFeatureAttributes()

getAttributeLabels() getBlankFeature()

prepareFeature() setData()

QualityFeature

class music21.features.native.QualityFeature(dataOrStream=None, **keywords)

Extends the jSymbolic QualityFeature to automatically find mode.

Set to 0 if the key signature indicates that a recording is major, set to 1 if it indicates that it is minor. A Music21 addition: if no key mode is found in the piece, or conflicting modes in the keys, analyze the piece to discover what mode it is most likely in.

Example: Handel, Rinaldo Aria (musicxml) is explicitly encoded as being in Major:

>>> s = corpus.parse('handel/rinaldo/lascia_chio_pianga')
>>> fe = features.native.QualityFeature(s)
>>> f = fe.extract()
>>> f.vector
[0]

now we will try it with the last movement of Schoenberg’s opus 19 which has no mode explicitly encoded in the musicxml but which our analysis routines believe (having very little to go on) fits the profile of e minor best.

>>> schoenberg19mvmt6 = corpus.parse('schoenberg/opus19', 6)
>>> fe2 = features.native.QualityFeature(schoenberg19mvmt6)
>>> f2 = fe2.extract()
>>> f2.vector
[1]

QualityFeature bases

• FeatureExtractor

QualityFeature methods

QualityFeature.process()

Do processing necessary, storing result in feature.

Methods inherited from FeatureExtractor:

extract() fillFeatureAttributes()

getAttributeLabels() getBlankFeature()

prepareFeature() setData()

RangeOfNoteQuarterLengths

class music21.features.native.RangeOfNoteQuarterLengths(dataOrStream=None, **keywords)

Difference between the longest and shortest quarter lengths.

>>> s = corpus.parse('bwv66.6')
>>> fe = features.native.RangeOfNoteQuarterLengths(s)
>>> fe.extract().vector
[1.5]

RangeOfNoteQuarterLengths bases

• FeatureExtractor

RangeOfNoteQuarterLengths methods

RangeOfNoteQuarterLengths.process()

Do processing necessary, storing result in feature.

Methods inherited from FeatureExtractor:

extract() fillFeatureAttributes()

getAttributeLabels() getBlankFeature()

prepareFeature() setData()

TonalCertainty

class music21.features.native.TonalCertainty(dataOrStream=None, **keywords)

>>> s = corpus.parse('bwv66.6')
>>> fe = features.native.TonalCertainty(s)
>>> f = fe.extract()
>>> f.vector
[1.26...]

>>> pitches = [56, 55, 56, 57, 58, 57, 58, 59, 60, 59, 60, 61, 62, 61,
...            62, 63, 64, 63, 64, 65, 66, 65, 66, 67]
>>> s = stream.Stream()
>>> for pitch in pitches:
...   s.append(note.Note(pitch))
>>> features.native.TonalCertainty(s).extract().vector
[0.0]

TonalCertainty bases

• FeatureExtractor

TonalCertainty methods

TonalCertainty.process()

Do processing necessary, storing result in feature.

Methods inherited from FeatureExtractor:

extract() fillFeatureAttributes()

getAttributeLabels() getBlankFeature()

prepareFeature() setData()

TriadSimultaneityPrevalence

class music21.features.native.TriadSimultaneityPrevalence(dataOrStream=None, **keywords)

Gives the proportion of all simultaneities which form triads (major, minor, diminished, or augmented)

>>> s = corpus.parse('bwv66.6')
>>> fe = features.native.TriadSimultaneityPrevalence(s)
>>> fe.extract().vector
[0.692...]
>>> s2 = corpus.parse('schoenberg/opus19', 2)
>>> fe2 = features.native.TriadSimultaneityPrevalence(s2)
>>> fe2.extract().vector
[0.021739...]

TriadSimultaneityPrevalence bases

• FeatureExtractor

TriadSimultaneityPrevalence methods

TriadSimultaneityPrevalence.process()

Do processing necessary, storing result in feature.

Methods inherited from FeatureExtractor:

extract() fillFeatureAttributes()

getAttributeLabels() getBlankFeature()

prepareFeature() setData()

UniqueNoteQuarterLengths

class music21.features.native.UniqueNoteQuarterLengths(dataOrStream=None, **keywords)

>>> s = corpus.parse('bwv66.6')
>>> fe = features.native.UniqueNoteQuarterLengths(s)
>>> fe.extract().vector
[3]

UniqueNoteQuarterLengths bases

• FeatureExtractor

UniqueNoteQuarterLengths methods

UniqueNoteQuarterLengths.process()

Do processing necessary, storing result in feature.

Methods inherited from FeatureExtractor:

extract() fillFeatureAttributes()

getAttributeLabels() getBlankFeature()

prepareFeature() setData()

UniquePitchClassSetSimultaneities

class music21.features.native.UniquePitchClassSetSimultaneities(dataOrStream=None, **keywords)

Number of unique pitch class simultaneities.

>>> s = corpus.parse('bwv66.6')
>>> fe = features.native.UniquePitchClassSetSimultaneities(s)
>>> fe.extract().vector
[27]

UniquePitchClassSetSimultaneities bases

• FeatureExtractor

UniquePitchClassSetSimultaneities methods

UniquePitchClassSetSimultaneities.process()

Do processing necessary, storing result in feature.

Methods inherited from FeatureExtractor:

extract() fillFeatureAttributes()

getAttributeLabels() getBlankFeature()

prepareFeature() setData()

UniqueSetClassSimultaneities

class music21.features.native.UniqueSetClassSimultaneities(dataOrStream=None, **keywords)

Number of unique set class simultaneities.

>>> s = corpus.parse('bwv66.6')
>>> fe = features.native.UniqueSetClassSimultaneities(s)
>>> fe.extract().vector
[14]

UniqueSetClassSimultaneities bases

• FeatureExtractor

UniqueSetClassSimultaneities methods

UniqueSetClassSimultaneities.process()

Do processing necessary, storing result in feature.

Methods inherited from FeatureExtractor:

extract() fillFeatureAttributes()

getAttributeLabels() getBlankFeature()

prepareFeature() setData()