def _set_model(self, **keywords):
"""
Define the sequence model for the calculation.
Parameters
----------
model : { None, Model } (default=None)
Specify the sound-class model to which the strings shall be
converted.
"""
defaults = dict(
model=rcParams['sca'],
stress=rcParams['stress'],
transform=rcParams['align_transform'])
for k in defaults:
if k not in keywords:
keywords[k] = defaults[k]
if isinstance(keywords['model'], (text_type, str)):
self.model = rcParams[keywords['model']]
else:
self.model = keywords['model']
self.classes = []
for clA, clB in map(
lambda x: (
tokens2class(x[0], self.model, stress=keywords['stress']),
tokens2class(x[1], self.model, stress=keywords['stress'])),
self.tokens
):
self.classes += [(clA, clB)]
self.weights = []
for prA, prB in self.prostrings:
self.weights += [(
prosodic_weights(prA, _transform=keywords['transform']),
prosodic_weights(prB, _transform=keywords['transform'])
)]
self.scoredict = self.model.scorer
def _set_model(self, **keywords):
"""
Define the sequence model for the calculation.
Parameters
----------
model : { None, Model } (default=None)
Specify the sound-class model to which the strings shall be
converted.
"""
defaults = dict(
model=rcParams['sca'],
stress=rcParams['stress'],
transform=rcParams['align_transform'])
for k in defaults:
if k not in keywords:
keywords[k] = defaults[k]
if isinstance(keywords['model'], (text_type, str)):
self.model = rcParams[keywords['model']]
else:
self.model = keywords['model']
self.classes = []
for clA, clB in map(
lambda x: (
tokens2class(x[0], self.model, stress=keywords['stress']),
tokens2class(x[1], self.model, stress=keywords['stress'])),
self.tokens
):
self.classes += [(clA, clB)]
self.weights = []
for prA, prB in self.prostrings:
self.weights += [(
prosodic_weights(prA, _transform=keywords['transform']),
prosodic_weights(prB, _transform=keywords['transform'])
)]
self.scoredict = self.model.scorer
def test_prosodic_weights(self):
seq = 'tʰ ɔ x t ə r'.split(' ')
assert prosodic_weights(prosodic_string(seq))[0] == 2
assert prosodic_weights(prosodic_string(seq))[-1] == 0.8
def test_prosodic_weights():
seq = 'tʰ ɔ x t ə r'.split(' ')
assert prosodic_weights(prosodic_string(seq))[0] == 2
assert prosodic_weights(prosodic_string(seq))[-1] == 0.8
