def phonotactic_probability_vitevitch(corpus_context, query,
probability_type = 'unigram',
stop_check = None, call_back = None):
"""Calculate the phonotactic_probability of a particular word using
the Vitevitch & Luce algorithm
Parameters
----------
corpus_context : CorpusContext
Context manager for a corpus
query : Word
The word whose neighborhood density to calculate.
probability_type : str
Either 'unigram' or 'bigram' probability
stop_check : callable or None
Optional function to check whether to gracefully terminate early
call_back : callable or None
Optional function to supply progress information during the function
Returns
-------
float
Phonotactic probability of the word
"""
ensure_context(corpus_context)
if probability_type == 'unigram':
gramsize = 1
elif probability_type == 'bigram':
gramsize = 2
prob_dict = corpus_context.get_phone_probs(gramsize = gramsize)
sequence = zip(*[getattr(query, corpus_context.sequence_type)[i:] for i in range(gramsize)])
totprob = 0
tot = 0
for i,s in enumerate(sequence):
try:
totprob += prob_dict[s,i]
except KeyError:
notfound = []
for seg in s:
if seg not in corpus_context.inventory:
notfound.append(seg)
if len(notfound):
raise(PhonoProbError("Segments not found in the corpus: {}".format(', '.join(notfound))))
else:
raise(PhonoProbError("Segments not found in the corpus: {} at position: {}".format(', '.join(s),i)))
tot += 1
try:
totprob = totprob / tot
except ZeroDivisionError:
pass
return totprob
def phonotactic_probability_all_words(corpus_context, algorithm,
probability_type = 'unigram',
num_cores = -1,
stop_check = None, call_back = None):
"""Calculate the phonotactic_probability of all words in the corpus and
adds them as attributes of the words.
Parameters
----------
corpus_context : CorpusContext
Context manager for a corpus
algorithm : str
Algorithm to use for calculating phonotactic probability (currently
only 'vitevitch')
probability_type : str
Either 'unigram' or 'bigram' probability
stop_check : callable, optional
Optional function to check whether to gracefully terminate early
call_back : callable, optional
Optional function to supply progress information during the function
"""
ensure_context(corpus_context)
if call_back is not None:
call_back('Calculating phonotactic probabilities...')
call_back(0,len(corpus_context))
cur = 0
num_cores = -1 # Multiprocessing not yet implemented
if num_cores == -1:
for w in corpus_context:
if stop_check is not None and stop_check():
break
if call_back is not None:
cur += 1
if cur % 20 == 0:
call_back(cur)
if algorithm == 'vitevitch':
res = phonotactic_probability_vitevitch(corpus_context, w,
probability_type = probability_type,
stop_check = stop_check)
setattr(w.original, corpus_context.attribute.name,res)
if stop_check is not None and stop_check():
corpus_context.corpus.remove_attribute(corpus_context.attribute)
