def sonorities_segment_by_measure(df):
"""
If a set (bar) contains more than 10 different pitch
classes, the bar is divided into beats and the beats are treated as new
segments. If a set contains less than 2 pitch classes, this set is added to the
set that is constructed from the next bar, forming a new segment. (HONINGH;
BOD, 2010, p. 2).
"""
def make_row(frame, composer, name, opus, measure, notes12, nf, iv, categ):
row = {'composer': composer, 'name': name, 'opus': opus,
"measure": measure, 'notes_base12': notes12,
"normal_form": nf, "interval_vector": iv,
"sonority_category": categ}
return frame.append([row], ignore_index=True)
df2 = pandas.DataFrame(columns=["composer", "name", "opus", "measure",
"notes_base12", "normal_form", "interval_vector",
"sonority_category"])
previous_measure = None
# Group sonorities by measure.
for (composer, name, opus, measure), frame in df.groupby(['composer', 'name', 'opus', 'measure']):
print " - ", composer, opus, measure
son12 = tuple(set(flatten(frame['notes_base12'].tolist())))
# If we have some sonority from the previous measure, i.e. a sonority
# with less than 3 elements, we merge to this sonority
if previous_measure:
son12 += previous_measure
previous_measure = None
# If sonority has less than 3 elements, we save to merge in the next measure
if len(son12) < 3:
previous_measure = son12
# If a sonority has more than 9 elementes, we split by beat and merge beats with
# less than 3 elements.
elif len(son12) > 9:
for item in _split_sonorities_by_beat(frame):
nf = tuple(music.normal_form0(item))
iv = tuple(music.interval_vector(item))
categ = music.sonority_category(item)
df2 = make_row(df2, composer, name, opus, measure, item, nf, iv, categ)
else:
nf = tuple(music.normal_form0(son12))
iv = tuple(music.interval_vector(son12))
categ = music.sonority_category(son12)
df2 = make_row(df2, composer, name, opus, measure, son12, nf, iv, categ)
return df2
def test_interval_vector_of_01457_should_be_212221(self):
iv = interval_vector([0, 1, 4, 5, 7])
self.assertEqual(iv, [2, 1, 2, 2, 2, 1])
