def test_basic_phonoprob(unspecified_test_corpus):
expected = {
'atema': 0.1011173499,
'enuta': 0.1011173499,
'ta': 0.4353651056,
'mata': 0.1881114313,
'nata': 0.1782478499
}
with CanonicalVariantContext(unspecified_test_corpus, 'transcription',
'token') as c:
for k, v in expected.items():
res = phonotactic_probability_vitevitch(
c, unspecified_test_corpus.find(k), 'unigram')
assert (abs(v - res) < 0.0001)
expected = {
'atema': 0.0798992942,
'enuta': 0.0798992942,
'ta': 0.1507780332,
'mata': 0.0626335622,
'nata': 0.0494821204
}
with CanonicalVariantContext(unspecified_test_corpus, 'transcription',
'token') as c:
for k, v in expected.items():
res = phonotactic_probability_vitevitch(
c, unspecified_test_corpus.find(k), 'bigram')
assert (abs(v - res) < 0.0001)
def run(self):
if self.name == 'functional_load':
try:
results = minpair_fl(self.kwargs['corpus'],
self.kwargs['segment_pair'],
stop_check=self.kwargs['stop_check'],
call_back=self.kwargs['call_back'])
self.dataReady.emit(results)
except Exception as e:
message = '{}:{}'.format(self.name, e)
self.errorEncountered.emit(message)
return
elif self.name == 'string_similarity':
try:
results = string_similarity(
self.kwargs['corpus'],
self.kwargs['query'],
self.kwargs['algorithm'],
stop_check=self.kwargs['stop_check'],
call_back=self.kwargs['call_back'])
self.dataReady.emit(results)
except Exception as e:
message = '{}:{}'.format(self.name, e)
self.errorEncountered.emit(message)
return
elif self.name == 'phonotactic_probability':
try:
results = phonotactic_probability_vitevitch(
self.kwargs['corpus'],
self.kwargs['query'],
self.kwargs['sequence_type'],
probability_type=self.kwargs['probability_type'],
stop_check=self.kwargs['stop_check'],
call_back=self.kwargs['call_back'])
self.dataReady.emit(results)
except Exception as e:
message = '{}:{}'.format(self.name, e)
self.errorEncountered.emit(message)
return
elif self.name == 'kullback_leibler':
try:
results = KullbackLeibler(self.kwargs['corpus'],
self.kwargs['seg1'],
self.kwargs['seg2'],
self.kwargs['side'],
stop_check=self.kwargs['stop_check'],
call_back=self.kwargs['call_back'])
self.dataReady.emit(results)
except Exception as e:
message = '{}:{}'.format(self.name, e)
self.errorEncountered.emit(message)
return
else:
raise UnLuckyException(
'No analysis function called {} could be found'.format(
self.name))
def test_basic_phonoprob(unspecified_test_corpus):
expected = {'atema':0.1011173499,
'enuta':0.1011173499,
'ta':0.4353651056,
'mata':0.1881114313,
'nata':0.1782478499}
with CanonicalVariantContext(unspecified_test_corpus, 'transcription', 'token') as c:
for k,v in expected.items():
res = phonotactic_probability_vitevitch(c, unspecified_test_corpus.find(k), 'unigram')
assert(abs(v - res) < 0.0001)
expected = {'atema':0.0798992942,
'enuta':0.0798992942,
'ta':0.1507780332,
'mata':0.0626335622,
'nata':0.0494821204}
with CanonicalVariantContext(unspecified_test_corpus, 'transcription', 'token') as c:
for k,v in expected.items():
res = phonotactic_probability_vitevitch(c, unspecified_test_corpus.find(k), 'bigram')
assert(abs(v - res) < 0.0001)
def run(self):
if self.name == 'functional_load':
try:
results = minpair_fl(self.kwargs['corpus'], self.kwargs['segment_pair'],
stop_check = self.kwargs['stop_check'],
call_back = self.kwargs['call_back'])
self.dataReady.emit(results)
except Exception as e:
message = '{}:{}'.format(self.name,e)
self.errorEncountered.emit(message)
return
elif self.name == 'string_similarity':
try:
results = string_similarity(self.kwargs['corpus'], self.kwargs['query'], self.kwargs['algorithm'],
stop_check = self.kwargs['stop_check'],
call_back = self.kwargs['call_back'])
self.dataReady.emit(results)
except Exception as e:
message = '{}:{}'.format(self.name,e)
self.errorEncountered.emit(message)
return
elif self.name == 'phonotactic_probability':
try:
results = phonotactic_probability_vitevitch(self.kwargs['corpus'],self.kwargs['query'],
self.kwargs['sequence_type'],
probability_type=self.kwargs['probability_type'],
stop_check = self.kwargs['stop_check'],
call_back = self.kwargs['call_back'])
self.dataReady.emit(results)
except Exception as e:
message = '{}:{}'.format(self.name,e)
self.errorEncountered.emit(message)
return
elif self.name == 'kullback_leibler':
try:
results = KullbackLeibler(self.kwargs['corpus'], self.kwargs['seg1'], self.kwargs['seg2'], self.kwargs['side'],
stop_check = self.kwargs['stop_check'],
call_back = self.kwargs['call_back'])
self.dataReady.emit(results)
except Exception as e:
message = '{}:{}'.format(self.name,e)
self.errorEncountered.emit(message)
return
else:
raise UnLuckyException('No analysis function called {} could be found'.format(self.name))
