def test_output(self):
"""Simple output is correct."""
df = DataFrame(dict(
vowel=['fleece', 'fleece', 'trap', 'trap'],
f1=[300., 350., 400., 450.],
f2=[500., 550., 600., 650.]
))
expected = DataFrame(dict(
f1=[325., 425.],
f2=[525., 625.]
), index=['fleece', 'trap'])
expected.index.name = 'vowel'
actual = _get_apice_formants(
df, dict(fleece='fleece', trap='trap'), 'vowel', ['f1', 'f2'])
self.assertIsNone(assert_frame_equal(actual, expected))
def test_apice_spec(self):
"""Non-defualt points processed correctly."""
df = DataFrame(dict(
hvd=['heed', 'heed', 'had', 'had'],
f1=[300., 350., 400., 450.],
f2=[500., 550., 600., 650.]
))
expected = DataFrame(dict(
f1=[325., 425.],
f2=[525., 625.]
), index=['fleece', 'trap'])
expected.index.name = 'hvd'
actual = _get_apice_formants(
df, dict(fleece='heed', trap='had'), 'hvd', ['f1', 'f2'])
self.assertIsNone(assert_frame_equal(
actual.sort_index(), expected.sort_index()))
def setUp(self):
self.df = DataFrame(dict(
speaker=['S1'] * 6 + ['S2'] * 6,
vowel=['kit', 'goose', 'fleece', 'start', 'thought', 'trap'] * 2,
f1=[200., 210., 220., 230., 240., 250.,
300., 310., 320., 330., 340., 350.],
f2=[500., 510., 520., 530., 540., 550.,
600., 610., 620., 630., 640., 650.]
))
df = self.df[self.df['speaker'] == 'S1'].copy()
self.s1_centroid = dict(
f1=(df[df['vowel'] == 'kit']['f1'].values +
df[df['vowel'] == 'fleece']['f1'].values +
df[df['vowel'] == 'start']['f1'].values / 2 +
df[df['vowel'] == 'thought']['f1'].values / 2 +
df[df['vowel'] == 'trap']['f1'].values) / 4,
f2=(df[df['vowel'] == 'fleece']['f2'].values +
df[df['vowel'] == 'goose']['f2'].values +
df[df['vowel'] == 'start']['f2'].values / 2 +
df[df['vowel'] == 'thought']['f2'].values / 2 +
df[df['vowel'] == 'trap']['f2'].values) / 4)
self.formants = ['f1', 'f2']
self.kwargs = dict(formants=self.formants)
def test_get_centroid(self):
"""Test the get_centroid method."""
df = DataFrame(dict(
speaker=['s1', 's1'],
vowel=['e', 'e'],
f1=[100., 200.],
f2=[400., 500.]
))
actual = self.normalizer.get_centroid(
df, dict(letter='e'), vowel='vowel', formants=['f1', 'f2'])
expected = Series(
dict(
f1=(100. + 200.) / 2,
f2=(400. + 500.) / 2),
dtype=actual.dtype)
assert_series_equal(actual, expected)
def test_get_centroid(self):
"""Test get_centroid method."""
df = DataFrame(dict(
speaker=['s1', 's1', 's1', 's1'],
vowel=['fleece', 'fleece', 'trap', 'trap'],
f1=[100., 200., 200., 300.],
f2=[400., 500., 500., 600.]
))
actual = self.normalizer.get_centroid(
df, dict(fleece='fleece', trap='trap'),
vowel='vowel', formants=['f1', 'f2'])
expected = Series(
dict(
f1=(150. + 250. + 150.) / 3,
f2=(450. + 550. + 150.) / 3),
dtype=actual.dtype)
assert_series_equal(actual, expected)
class TestBighamNormalizer(TestWattFabriciusNormalizer):
"""Tests for the BighamNormalizer Class. """
normalizer = BighamNormalizer
def setUp(self):
self.df = DataFrame(dict(
speaker=['S1'] * 6 + ['S2'] * 6,
vowel=['kit', 'goose', 'fleece', 'start', 'thought', 'trap'] * 2,
f1=[200., 210., 220., 230., 240., 250.,
300., 310., 320., 330., 340., 350.],
f2=[500., 510., 520., 530., 540., 550.,
600., 610., 620., 630., 640., 650.]
))
df = self.df[self.df['speaker'] == 'S1'].copy()
self.s1_centroid = dict(
f1=(df[df['vowel'] == 'kit']['f1'].values +
df[df['vowel'] == 'fleece']['f1'].values +
df[df['vowel'] == 'start']['f1'].values / 2 +
df[df['vowel'] == 'thought']['f1'].values / 2 +
df[df['vowel'] == 'trap']['f1'].values) / 4,
f2=(df[df['vowel'] == 'fleece']['f2'].values +
df[df['vowel'] == 'goose']['f2'].values +
df[df['vowel'] == 'start']['f2'].values / 2 +
df[df['vowel'] == 'thought']['f2'].values / 2 +
df[df['vowel'] == 'trap']['f2'].values) / 4)
self.formants = ['f1', 'f2']
self.kwargs = dict(formants=self.formants)
def test_fx_spec(self):
"""
Specify formants using individual keys.
"""
df = self.df.copy()
normalizer = self.normalizer()
normalizer.normalize(
df, f1='f1', f2='f2', **self.kwargs)
self.assertListEqual(
normalizer.params['formants'],
['f1', 'f2'])
def test_fx_list_spec(self):
"""
Specify formants using individual keys as list.
"""
df = self.df.copy()
normalizer = self.normalizer()
normalizer.normalize(
df, f1=['f1'], f2=['f2'], **self.kwargs)
self.assertListEqual(
normalizer.params['formants'],
['f1', 'f2'])
def test_get_centroid(self):
"""Test get_centroid method."""
df = self.df.copy()
df = df[df['speaker'] == 'S1']
actual = self.normalizer.get_centroid(
df,
dict(
fleece='fleece',
goose='goose',
kit='kit',
start='start',
thought='thought',
trap='trap'),
vowel='vowel',
f1='f1', f2='f2')
expected = self.s1_centroid
self.assertEqual(actual['f1'], expected['f1'])
self.assertEqual(actual['f2'], expected['f2'])