def generate_dataframes(preprocessed_dir):
composers = os.listdir(preprocessed_dir)
feature_names = features_lib.FEATURES
examples_train = []
examples_test = []
for composer in composers:
examples_temp = []
composer_dir = os.path.join(preprocessed_dir, composer)
pieces = os.listdir(composer_dir)
for piece_name in pieces:
filename = os.path.join(composer_dir, piece_name)
piece_obj = music21.converter.parse(filename)
item = {"composer": composer, "filename": piece_name}
# skip piece_obj's that are too short
num_notes = len(util.get_notes(piece_obj))
if num_notes < MIN_NOTES:
continue
for feature in feature_names:
feature_func = getattr(features_lib, feature)
item[feature] = feature_func(piece_obj)
examples_temp.append(item)
# Split examples_temp into training and testing set
temp1, temp2 = split_arr(examples_temp)
examples_train += temp1
examples_test += temp2
return pandas.DataFrame(examples_train), pandas.DataFrame(examples_test)
def generate_dataframes(preprocessed_dir):
composers = os.listdir(preprocessed_dir)
feature_names = features_lib.FEATURES
examples_train = []
examples_test = []
for composer in composers:
examples_temp = []
composer_dir = os.path.join(preprocessed_dir, composer)
pieces = os.listdir(composer_dir)
for piece_name in pieces:
filename = os.path.join(composer_dir, piece_name)
piece_obj = music21.converter.parse(filename)
item = {"composer": composer, "filename": piece_name}
# skip piece_obj's that are too short
num_notes = len(util.get_notes(piece_obj))
if num_notes < MIN_NOTES:
continue
for feature in feature_names:
feature_func = getattr(features_lib, feature)
item[feature] = feature_func(piece_obj)
examples_temp.append(item)
# Split examples_temp into training and testing set
temp1, temp2 = split_arr(examples_temp)
examples_train += temp1
examples_test += temp2
return pandas.DataFrame(examples_train), pandas.DataFrame(examples_test)
def chromaticism(piece):
notes = util.get_notes(piece)
note_values = list(map(lambda x: x.midi, notes))
is_chromatic = 0
for i in range(len(note_values)-2):
if ((note_values[i]-note_values[i+1] == 1) and (note_values[i+1]-note_values[i+2] == 1)) or ((note_values[i+2]-note_values[i+1] == 1) and (note_values[i+1]-note_values[i] == 1)):
is_chromatic = 1
return is_chromatic
def Low_notes(piece):
notes = util.get_notes(piece)
note_values = list(map(lambda x: x.midi, notes))
high = 0
low = 0
for i in range(len(note_values)):
if note_values[i] > 64:
high += 1
else:
low +=1
return low/(low+high)
def Low_notes(piece):
notes = util.get_notes(piece)
note_values = list(map(lambda x: x.midi, notes))
high = 0
low = 0
for i in range(len(note_values)):
if note_values[i] > 64:
high += 1
else:
low += 1
return low / (low + high)
def chromaticism(piece):
notes = util.get_notes(piece)
note_values = list(map(lambda x: x.midi, notes))
is_chromatic = 0
for i in range(len(note_values) - 2):
if ((note_values[i] - note_values[i + 1] == 1) and
(note_values[i + 1] - note_values[i + 2] == 1)) or (
(note_values[i + 2] - note_values[i + 1] == 1) and
(note_values[i + 1] - note_values[i] == 1)):
is_chromatic = 1
return is_chromatic
def leaps_ratio(piece):
notes = util.get_notes(piece)
note_values = list(map(lambda x: x.midi, notes))
leaps = 0
steps = 0
for i in range(len(note_values)-1):
distance = abs(note_values[i+1]-note_values[i])
if distance > 2:
leaps += 1
else:
steps += 1
return leaps/(leaps+steps)
def leaps_ratio(piece):
notes = util.get_notes(piece)
note_values = list(map(lambda x: x.midi, notes))
leaps = 0
steps = 0
for i in range(len(note_values) - 1):
distance = abs(note_values[i + 1] - note_values[i])
if distance > 2:
leaps += 1
else:
steps += 1
return leaps / (leaps + steps)
def range_melody(piece):
notes = util.get_notes(piece)
note_values = list(map(lambda x: x.midi, notes))
return max(note_values)-min(note_values)
def repeated_notes(piece):
notes = util.get_notes(piece)
note_values = list(map(lambda x: x.midi, notes))
return stats.mode(note_values)[1][0]
def rhythmic_variety(piece):
notes = util.get_notes(piece)
durations = list(map(lambda x: float(x.duration.quarterLength), notes))
num_durations = len(set(durations))
return 10 * num_durations / len(notes)
def rhythmic_variance(piece):
notes = util.get_notes(piece)
durations = list(map(lambda x: float(x.duration.quarterLength), notes))
mean = numpy.mean(durations)
sq_diff = reduce(lambda acc, x: acc + (x - mean) * (x - mean), durations)
return sq_diff / len(notes)
def num_notes(piece):
return len(util.get_notes(piece))
def repeated_notes(piece):
notes = util.get_notes(piece)
note_values = list(map(lambda x: x.midi, notes))
return stats.mode(note_values)[1][0]
def rhythmic_variety(piece):
notes = util.get_notes(piece)
durations = list(map(lambda x: float(x.duration.quarterLength), notes))
num_durations = len(set(durations))
return 10 * num_durations / len(notes)
def rhythmic_variance(piece):
notes = util.get_notes(piece)
durations = list(map(lambda x: float(x.duration.quarterLength), notes))
mean = numpy.mean(durations)
sq_diff = reduce(lambda acc, x: acc + (x - mean) * (x - mean), durations)
return sq_diff / len(notes)
def num_notes(piece):
return len(util.get_notes(piece))
def range_melody(piece):
notes = util.get_notes(piece)
note_values = list(map(lambda x: x.midi, notes))
return max(note_values) - min(note_values)