def analysis(compositions):
midi_intervals = utils.get_music_data_attrib(compositions, 'intervals_midi', 'extend')
nested_midi_intervals = utils.get_music_data_attrib(compositions, 'intervals_midi', 'append')
simple_intervals = [abs(x) % 12 for x in midi_intervals]
chromatic_intervals = utils.get_music_data_attrib(compositions, 'intervals')
adjacent_intervals = []
for seq in nested_midi_intervals:
adjacent_intervals.extend(get_adjacent_intervals(seq))
basic_stats = utils.aux_basic_stats(midi_intervals, 'Intervals number', False)
categorized_midi_intervals = list(map(get_category, midi_intervals))
categorized_nested_midi_intervals = [list(map(get_category, s)) for s in nested_midi_intervals]
coll_freq_dic = utils.special_counter(categorized_midi_intervals, True)
if midi_intervals and chromatic_intervals:
args = {
'frequency_scatter': frequency_scatter(midi_intervals),
'frequency_basic_scatter': frequency_scatter(simple_intervals),
'basic_stats': basic_stats,
'frequency_pie': frequency_pie(midi_intervals),
'chromatic_frequency_pie': frequency_pie(chromatic_intervals),
'chromatic_leaps_frequency_pie': chromatic_leaps_frequency_pie(chromatic_intervals),
'histogram': utils.histogram(midi_intervals, 10, ['Intervals', 'Ocurrences'], False, True),
'distribution_amount': utils.distribution(midi_intervals, basic_stats, True),
'category_frequency_pie': frequency_pie(list(map(get_category, midi_intervals))),
'adjacent_frequency_pie': frequency_pie(adjacent_intervals),
'adjacent_frequency_bubble': make_adjacent_chart(adjacent_intervals),
'pitch_class_distance': utils.frequency_distance_scatter(compositions, categorized_nested_midi_intervals, coll_freq_dic),
}
else:
args = {}
return args
def analysis(compositions):
durations = utils.get_music_data_attrib(compositions, 'durations', 'extend')
nested_durations = utils.get_music_data_attrib(compositions, 'durations', 'append')
piece_durations = utils.get_music_data_attrib(compositions, 'total_duration', 'append')
basic_stats_duration = utils.aux_basic_stats(durations, 'Durations number', False)
basic_stats_piece_duration = utils.aux_basic_stats(piece_durations, 'Durations number', False)
coll_freq_dic = utils.special_counter(durations, True)
if durations and piece_durations:
args = {
'basic_stats_duration': basic_stats_duration,
'note_frequency_scatter': frequency_scatter(durations),
'note_frequency_pie': frequency_pie(durations),
'note_histogram': utils.histogram(durations, 10, ['Durations', 'Ocurrences'], False, True),
'note_distribution_amount': utils.distribution(durations, basic_stats_duration, True),
'basic_stats_piece_duration': basic_stats_piece_duration,
'piece_frequency_scatter': frequency_scatter(piece_durations),
'piece_frequency_pie': frequency_pie(piece_durations),
'piece_histogram': utils.histogram(piece_durations, 10, ['Durations', 'Ocurrences'], False, True),
'piece_distribution_amount': utils.distribution(piece_durations, basic_stats_duration, True),
'frequency_distance': utils.frequency_distance_scatter(compositions, nested_durations, coll_freq_dic),
}
else:
args = {}
return args
def analysis(compositions):
# intervals
midi_intervals = utils.get_music_data_attrib(compositions, 'intervals_midi', 'extend')
nested_midi_intervals = utils.get_music_data_attrib(compositions, 'intervals_midi', 'append')
# durations
dur = utils.get_music_data_attrib(compositions, 'durations', 'extend')
nested_dur = utils.get_music_data_attrib(compositions, 'durations', 'append')
# contour
contour_list = utils.get_music_data_attrib(compositions, 'contour', 'append')
tests = [midi_intervals,
nested_midi_intervals,
dur,
nested_dur,
contour_list]
if all(tests):
# intervals
cat_intervals = list(map(intervals.get_category, midi_intervals))
cat_nested_intervals = [list(map(intervals.get_category, s)) for s in nested_midi_intervals]
coll_freq_intervals = utils.special_counter(cat_intervals, True)
# durations
coll_freq_durations = utils.special_counter(dur, True)
# contour
freq_dist_args = {}
for size in range(2, 5):
split_seq = list(map(tuple, contour.split_and_translate_nested(contour_list, size)))
split_seq_nested = [list(map(tuple, contour.split_and_translate(c, size))) for c in contour_list]
coll_freq_dic = contour.get_frequency(split_seq, size)
freq_dist_sc = utils.frequency_distance_scatter(compositions, split_seq_nested, coll_freq_dic, True)
freq_dist_args.update({'contour_{}_distance'.format(size): freq_dist_sc})
freq_data = [
['Duration', nested_dur, coll_freq_durations],
['Interval', cat_nested_intervals, coll_freq_intervals],
]
args = {
'intervals_distance': utils.frequency_distance_scatter(compositions, cat_nested_intervals, coll_freq_intervals, True),
'durations_distance': utils.frequency_distance_scatter(compositions, nested_dur, coll_freq_durations, True),
'id_distance': utils.frequency_distance_scatter_group(compositions, freq_data, True),
}
args.update(freq_dist_args)
else:
args = {}
return args
def analysis(compositions, size=2):
duration_ambitus = cluster_duration_ambitus.get_duration_ambitus(compositions, True, False)
contour_list = utils.get_music_data_attrib(compositions, 'contour', 'append')
a = numpy.array(duration_ambitus[1:])
b = cluster_contour.get_contour_frequency(contour_list, size, True)
c = cluster_intervals_frequency.get_interval_frequency(compositions)
d = cluster_durations_frequency.get_duration_frequency(compositions)
array = numpy.column_stack((a, b, c, d))
min_pts = 10
if array.shape[0] < 10:
min_pts = 0
reachability_plot = utils.make_reachability_plot(array, min_pts)
cluster_table = utils.make_clusters(compositions, array, min_pts)
if array.any():
args = {
'reachability_plot': reachability_plot,
'cluster_table': cluster_table,
'size': size,
}
else:
args = {}
return args
def make_general_chain(compositions, attrib, order=1):
nested_seq = utils.get_music_data_attrib(compositions, attrib, 'append')
if nested_seq:
spl = split_nested_sequences(nested_seq, order)
chain_str, map_str = markov_print(*make_markov_chain(spl))
args = {
'chain': chain_str,
'map': map_str,
}
else:
args = {}
return args
def generate_contour_chain(compositions, order=1):
contour_list = utils.get_music_data_attrib(compositions, 'contour', 'append')
if contour_list:
cseg_map, cseg_chain = markov_chain_contour(contour_list, order, True)
args = {
'cseg_map': cseg_map,
'cseg_chain': cseg_chain,
}
else:
args = {}
return args
def analysis(compositions):
ambitus_list = utils.get_music_data_attrib(compositions, 'ambitus', 'append')
if ambitus_list:
basic_stats = utils.aux_basic_stats(ambitus_list, 'Pieces number', False)
dist_value = utils.distribution(ambitus_list, basic_stats, False)
args = {
'basic_stats': basic_stats,
'frequency': frequency(ambitus_list),
'histogram': utils.histogram(ambitus_list, 10, ['Ambitus', 'Pieces'], False, True),
'distribution_value': dist_value,
'distribution_amount': utils.distribution(ambitus_list, basic_stats, True),
'frequency_pie': frequency_pie(ambitus_list),
'boxplot': utils.boxplot(basic_stats),
}
return args
else:
return {}
def analysis(compositions, size=2):
contour_list = utils.get_music_data_attrib(compositions, 'contour', 'append')
array = get_contour_frequency(contour_list, size, True)
min_pts = 10
if array.shape[0] < 10:
min_pts = 0
reachability_plot = utils.make_reachability_plot(array, min_pts)
cluster_table = utils.make_clusters(compositions, array, min_pts)
if array.any():
args = {
'reachability_plot': reachability_plot,
'cluster_table': cluster_table,
'size': size,
}
else:
args = {}
return args
def analysis(compositions):
size = 4
contour_list = utils.get_music_data_attrib(compositions, 'contour', 'append')
if contour_list:
basic_stats = utils.aux_basic_stats(contour_list, 'Contour number', True)
repetition_scatter_data = repetition_scatter(contour_list)
repetition_seq = repetition_index(contour_list)
repetition_stats = utils.aux_basic_stats(repetition_seq, 'Pieces Number', False)
dist_value = utils.distribution(repetition_seq, repetition_stats, False)
dist_amount = utils.distribution(repetition_seq, repetition_stats, True)
freq_dist_args = {}
for size in range(2, 5):
split_seq = list(map(tuple, split_and_translate_nested(contour_list, size)))
split_seq_nested = [list(map(tuple, split_and_translate(c, size))) for c in contour_list]
coll_freq_dic = get_frequency(split_seq, size)
freq_dist_sc = utils.frequency_distance_scatter(compositions, split_seq_nested, coll_freq_dic)
freq_dist_args.update({'frequency_distance_{}'.format(size): freq_dist_sc})
args = {
'basic_stats': basic_stats,
'repetition_stats': repetition_stats,
'frequency_pie_2': frequency_pie(contour_list, 2),
'frequency_pie_3': frequency_pie(contour_list, 3),
'frequency_pie_4': frequency_pie(contour_list, 4),
'repetition_scatter': repetition_scatter_data,
'distribution_value': dist_value,
'distribution_amount': dist_amount,
'histogram': utils.histogram(repetition_seq, 10, ['Index', 'Pieces'], False, True),
}
args.update(freq_dist_args)
else:
args = {}
return args
