def extract_chords_for_melodies(quantized_sequence, melodies):
"""Extracts a chord progression from the quantized NoteSequence for melodies.
This function will extract the underlying chord progression (encoded as text
annotations) from `quantized_sequence` for each monophonic melody in
`melodies`. Each chord progression will be the same length as its
corresponding melody.
Args:
quantized_sequence: A quantized NoteSequence object.
melodies: A python list of Melody instances.
Returns:
chord_progressions: A python list of ChordProgression instances, the same
length as `melodies`. If a progression fails to be extracted for a
melody, the corresponding list entry will be None.
stats: A dictionary mapping string names to `statistics.Statistic` objects.
"""
chord_progressions = []
stats = dict([('coincident_chords',
statistics.Counter('coincident_chords'))])
for melody in melodies:
try:
chords = ChordProgression()
chords.from_quantized_sequence(quantized_sequence,
melody.start_step, melody.end_step)
except CoincidentChordsError:
stats['coincident_chords'].increment()
chords = None
chord_progressions.append(chords)
return chord_progressions, list(stats.values())
def extract_chords(quantized_sequence,
max_steps=None,
all_transpositions=False):
"""Extracts a single chord progression from a quantized NoteSequence.
This function will extract the underlying chord progression (encoded as text
annotations) from `quantized_sequence`.
Args:
quantized_sequence: A quantized NoteSequence.
max_steps: An integer, maximum length of a chord progression. Chord
progressions will be trimmed to this length. If None, chord
progressions will not be trimmed.
all_transpositions: If True, also transpose the chord progression into all
12 keys.
Returns:
chord_progressions: If `all_transpositions` is False, a python list
containing a single ChordProgression instance. If `all_transpositions`
is True, a python list containing 12 ChordProgression instances, one
for each transposition.
stats: A dictionary mapping string names to `statistics.Statistic` objects.
"""
sequences_lib.assert_is_relative_quantized_sequence(quantized_sequence)
stats = dict([('chords_truncated', statistics.Counter('chords_truncated'))
])
chords = ChordProgression()
chords.from_quantized_sequence(quantized_sequence, 0,
quantized_sequence.total_quantized_steps)
if max_steps is not None:
if len(chords) > max_steps:
chords.set_length(max_steps)
stats['chords_truncated'].increment()
if all_transpositions:
chord_progressions = []
for amount in range(-6, 6):
transposed_chords = copy.deepcopy(chords)
transposed_chords.transpose(amount)
chord_progressions.append(transposed_chords)
return chord_progressions, stats.values()
else:
return [chords], stats.values()