def test_int_indexer_short_14(self):
expected = [[(0.0, interval.Interval(note.Note('G3'), note.Note('G4')).name),
(0.0625, interval.Interval(note.Note('G3'), note.Note('G4')).name),
(0.125, u'Rest'),
(0.1875, u'Rest'),
(0.25, interval.Interval(note.Note('A3'), note.Note('G4')).name),
(0.3125, interval.Interval(note.Note('A3'), note.Note('G4')).name),
(0.375, u'Rest'),
(0.4375, u'Rest'),
(0.5, interval.Interval(note.Note('G3'), note.Note('G4')).name)]]
expected = {'0,1': pandas_maker(expected)[0]}
not_processed = [[(0.0, u'G4', 0.0625), (0.0625, u'G4', 0.0625),
(0.125, u'G4', 0.0625), (0.1875, u'G4', 0.0625),
(0.25, u'G4', 0.0625), (0.3125, u'G4', 0.0625),
(0.375, u'G4', 0.0625), (0.4375, u'G4', 0.0625),
(0.5, u'G4')],
[(0.0, u'G3', 0.125), (0.125, u'Rest', 0.125), (0.25, u'A3', 0.125),
(0.375, u'Rest', 0.0625), (0.4375, u'Rest', 0.0625), (0.5, u'G3')]]
test_in = pandas_maker(not_processed)
int_indexer = IntervalIndexer(test_in,
{u'quality': True, u'simple or compound': u'compound'})
actual = int_indexer.run()[u'interval.IntervalIndexer']
self.assertEqual(len(expected), len(actual.columns))
for key in expected.iterkeys():
self.assertTrue(key in actual)
self.assertSequenceEqual(list(expected[key].index), list(actual[key].index))
self.assertSequenceEqual(list(expected[key]), list(actual[key]))
def test_interval_indexer_1(self):
# BWV7.7: full soprano and bass parts
test_parts = pandas.concat([self.bwv77_soprano, self.bwv77_bass],
axis=1)
test_parts.columns = pandas.MultiIndex.from_product([('A', ),
('a', 'b')])
expected = make_series(TestIntervalIndexerLong.bwv77_S_B_basis)
setts = {'simple or compound': 'compound', 'quality': True}
actual = IntervalIndexer(test_parts, setts).run().iloc[:, 0]
self.assertTrue(actual.equals(expected))
def test_int_indexer_short_1(self):
expected = [(0.0, interval.Interval(note.Note('G3'), note.Note('G4')).name)]
expected = TestIntervalIndexerShort.pandas_maker([expected])[0]
not_processed = [[(0.0, u'G4')], [(0.0, u'G3')]]
test_in = TestIntervalIndexerShort.pandas_maker(not_processed)
int_indexer = IntervalIndexer(test_in,
{u'quality': True, u'simple or compound': u'compound'})
actual = int_indexer.run()[u'0,1']
self.assertSequenceEqual(list(expected.index), list(actual.index))
self.assertSequenceEqual(list(expected.values), list(actual.values))
def test_interval_indexer_4(self):
# BWV7.7: small soprano and bass parts; "simple" in settings, "quality" not
test_parts = pandas.concat([self.bwv77_s_small, self.bwv77_b_small],
axis=1)
test_parts.columns = pandas.MultiIndex.from_product([('A', ),
('a', 'b')])
expected = make_series(
TestIntervalIndexerLong.bwv77_S_B_small_simple_noqual)
setts = {'simple or compound': 'simple'}
actual = IntervalIndexer(test_parts, setts).run().iloc[:, 0]
self.assertTrue(actual.equals(expected))
def test_interval_indexer_4(self):
# BWV7.7: small soprano and bass parts; "simple" in settings, "quality" not
test_parts = [self.bwv77_s_small, self.bwv77_b_small]
expected = TestIntervalIndexerLong.bwv77_S_B_small_simple_noqual
setts = {u'simple or compound': u'simple'}
int_indexer = IntervalIndexer(test_parts, setts)
actual = int_indexer.run()[u'0,1']
self.assertEqual(len(expected), len(actual))
for i, ind in enumerate(list(actual.index)):
self.assertEqual(expected[i][0], ind)
self.assertEqual(expected[i][1], actual[ind])
def test_interval_indexer_1(self):
# BWV7.7: full soprano and bass parts
test_parts = [self.bwv77_soprano, self.bwv77_bass]
expected = TestIntervalIndexerLong.bwv77_S_B_basis
setts = {u'simple or compound': u'compound', u'quality': True}
int_indexer = IntervalIndexer(test_parts, setts)
actual = int_indexer.run()[u'0,1']
self.assertEqual(len(expected), len(actual))
for i, ind in enumerate(list(actual.index)):
self.assertEqual(expected[i][0], ind)
self.assertEqual(expected[i][1], actual[ind])
def test_interval_indexer_1(self):
# BWV7.7: full soprano and bass parts
test_parts = [self.bwv77_soprano, self.bwv77_bass]
expected = {'0,1': make_series(TestIntervalIndexerLong.bwv77_S_B_basis)}
setts = {u'simple or compound': u'compound', u'quality': True}
int_indexer = IntervalIndexer(test_parts, setts)
actual = int_indexer.run()[u'interval.IntervalIndexer']
self.assertEqual(len(expected), len(actual.columns))
for key in expected.iterkeys():
self.assertTrue(key in actual)
self.assertSequenceEqual(list(expected[key].index), list(actual[key].index))
self.assertSequenceEqual(list(expected[key]), list(actual[key]))
def test_interval_indexer_3(self):
# BWV7.7: small soprano and bass parts; "simple" and "quality" not in settings, and the
# settings are in fact not specified
test_parts = pandas.concat([self.bwv77_s_small, self.bwv77_b_small],
axis=1)
test_parts.columns = pandas.MultiIndex.from_product([('A', ),
('a', 'b')])
expected = make_series(
TestIntervalIndexerLong.bwv77_S_B_small_compound_noqual)
# setts = {}
actual = IntervalIndexer(test_parts).run().iloc[:, 0]
self.assertTrue(actual.equals(expected))
def test_interval_indexer_4(self):
# BWV7.7: small soprano and bass parts; "simple" in settings, "quality" not
test_parts = [self.bwv77_s_small, self.bwv77_b_small]
expected = {'0,1': make_series(TestIntervalIndexerLong.bwv77_S_B_small_simple_noqual)}
setts = {u'simple or compound': u'simple'}
int_indexer = IntervalIndexer(test_parts, setts)
actual = int_indexer.run()[u'interval.IntervalIndexer']
self.assertEqual(len(expected), len(actual.columns))
for key in expected.iterkeys():
self.assertTrue(key in actual)
self.assertSequenceEqual(list(expected[key].index), list(actual[key].index))
self.assertSequenceEqual(list(expected[key]), list(actual[key]))
def test_interval_indexer_3(self):
# BWV7.7: small soprano and bass parts; "simple" and "quality" not in settings, and the
# settings are in fact not specified
test_parts = [self.bwv77_s_small, self.bwv77_b_small]
expected = TestIntervalIndexerLong.bwv77_S_B_small_compound_noqual
#setts = {}
int_indexer = IntervalIndexer(test_parts)
actual = int_indexer.run()[u'0,1']
self.assertEqual(len(expected), len(actual))
for i, ind in enumerate(list(actual.index)):
self.assertEqual(expected[i][0], ind)
self.assertEqual(expected[i][1], actual[ind])
def test_interval_indexer_2(self):
# BWV7.7: small soprano and bass parts; "simple" in settings
test_parts = pandas.concat([self.bwv77_s_small, self.bwv77_b_small], axis=1)
expected = {'0,1': make_series(TestIntervalIndexerLong.bwv77_S_B_small_simple_qual)}
setts = {'simple or compound': 'simple', 'quality': True}
int_indexer = IntervalIndexer(test_parts, setts)
actual = int_indexer.run()['interval.IntervalIndexer']
self.assertEqual(len(expected), len(actual.columns))
for key in six.iterkeys(expected):
self.assertTrue(key in actual)
self.assertSequenceEqual(list(expected[key].index), list(actual[key].index))
self.assertSequenceEqual(list(expected[key]), list(actual[key]))
def test_int_indexer_short_3(self):
expected = pandas.Series(['P8', 'Rest'], index=[0.0, 0.25], name='0,1')
not_processed = [[(0.0, 'G4')], [(0.0, 'G3'), (0.25, 'Rest')]]
test_in = pandas_maker(not_processed)
test_in.columns = pandas.MultiIndex.from_product([('notes', ),
('0', '1')])
setts = {
'quality': True,
'simple or compound': 'compound',
'directed': True
}
actual = IntervalIndexer(test_in, settings=setts).run().iloc[:, 0]
self.assertTrue(actual.equals(expected))
def test_int_indexer_short_1(self):
expected = pandas.Series('P8', name='0,1')
test_in = pandas.concat(
[pandas.Series('G4'), pandas.Series('G3')], axis=1)
test_in.columns = pandas.MultiIndex.from_product([('notes', ),
('0', '1')])
setts = {
'quality': True,
'simple or compound': 'compound',
'directed': True
}
actual = IntervalIndexer(test_in, settings=setts).run().iloc[:, 0]
self.assertTrue(actual.equals(expected))
def test_interval_indexer_3(self):
# BWV7.7: small soprano and bass parts; "simple" and "quality" not in settings, and the
# settings are in fact not specified
test_parts = [self.bwv77_s_small, self.bwv77_b_small]
expected = {'0,1': make_series(TestIntervalIndexerLong.bwv77_S_B_small_compound_noqual)}
# setts = {}
int_indexer = IntervalIndexer(test_parts)
actual = int_indexer.run()[u'interval.IntervalIndexer']
self.assertEqual(len(expected), len(actual.columns))
for key in expected.iterkeys():
self.assertTrue(key in actual)
self.assertSequenceEqual(list(expected[key].index), list(actual[key].index))
self.assertSequenceEqual(list(expected[key]), list(actual[key]))
def test_int_indexer_short_1(self):
expected = [[(0.0, interval.Interval(note.Note('G3'), note.Note('G4')).name)]]
expected = {'0,1': pandas_maker(expected)[0]}
not_processed = [[(0.0, 'G4')], [(0.0, 'G3')]]
test_in = pandas_maker(not_processed)
int_indexer = IntervalIndexer(test_in,
{'quality': True, 'simple or compound': 'compound', 'directed': True})
actual = int_indexer.run()['interval.IntervalIndexer']
self.assertEqual(len(expected), len(actual.columns))
for key in six.iterkeys(expected):
self.assertTrue(key in actual)
self.assertSequenceEqual(list(expected[key].index), list(actual[key].index))
self.assertSequenceEqual(list(expected[key]), list(actual[key]))
def test_int_ind_indexer_init_13(self):
int_indexer_1 = IntervalIndexer([], {
'quality': True,
'simple or compound': 'compound',
'directed': False
})
int_indexer_2 = IntervalIndexer(
[], {
'quality': 'diatonic with quality',
'simple or compound': 'compound',
'directed': False
})
self.assertEqual(int_indexer_1._indexer_func.__name__,
'indexer_dwq_und_com')
self.assertEqual(int_indexer_2._indexer_func.__name__,
'indexer_dwq_und_com')
def test_int_ind_indexer_init_4(self):
int_indexer_1 = IntervalIndexer([], {
'quality': False,
'simple or compound': 'simple',
'directed': False
})
int_indexer_2 = IntervalIndexer(
[], {
'quality': 'diatonic no quality',
'simple or compound': 'simple',
'directed': False
})
self.assertEqual(int_indexer_1._indexer_func.__name__,
'indexer_dnq_und_sim')
self.assertEqual(int_indexer_2._indexer_func.__name__,
'indexer_dnq_und_sim')
def test_int_ind_indexer_init_7(self):
int_indexer = IntervalIndexer(
[], {
'quality': 'interval class',
'simple or compound': 'simple',
'directed': False
})
self.assertEqual(int_indexer._indexer_func.__name__,
'indexer_icl_und_sim')
def test_int_ind_indexer_init_14(self):
int_indexer = IntervalIndexer(
[], {
'quality': 'chromatic',
'simple or compound': 'compound',
'directed': False
})
self.assertEqual(int_indexer._indexer_func.__name__,
'indexer_chr_und_com')
def test_int_indexer_short_17(self):
expected = pandas.Series(
['P8', 'P8', 'M10', 'Rest', 'Rest', 'm7', 'M6'],
index=[.0, .5, .75, 1.125, 1.25, 1.375, 2.0],
name='0,1')
not_processed = [[(0.0, 'G4'), (0.5, 'A4', 0.75), (1.25, 'F4', 0.75),
(2.0, 'E4')],
[(0.0, 'G3'), (0.5, 'A3'), (0.75, 'F3', 0.375),
(1.125, 'Rest'), (1.375, 'G3', 0.625), (2.0, 'G3')]]
test_in = pandas_maker(not_processed)
test_in.columns = pandas.MultiIndex.from_product([('notes', ),
('0', '1')])
setts = {
'quality': True,
'simple or compound': 'compound',
'directed': True
}
actual = IntervalIndexer(test_in, settings=setts).run().iloc[:, 0]
self.assertTrue(actual.equals(expected))
def run_my_task(self, inputs, settings, outputs):
# Set execution settings.
wrapper_settings = dict( [(k, settings[k]) for k in ('Simple or Compound Intervals', 'Interval Quality')] )
execution_settings = dict()
if wrapper_settings['Simple or Compound Intervals'] == 0:
execution_settings['simple or compound'] = 'simple'
else:
execution_settings['simple or compound'] = 'compound'
execution_settings['quality'] = wrapper_settings['Interval Quality']
execution_settings['mp'] = False
execution_settings['directed'] = True
# Run.
infile = inputs['NoteRest Interval Indexer Result'][0]['resource_path']
outfile = outputs['Vertical Interval Indexer Result'][0]['resource_path']
data = DataFrame.from_csv(infile, header = [0, 1]) # We know the first two rows constitute a MultiIndex
vertical_intervals = IntervalIndexer(data, execution_settings).run()
vertical_intervals.to_csv(outfile)
return True