def seed():
filepath = "preprocessed_texts/english/alice-only-spaced.txt"
# lvu.initialize()
lv, lang_vectors, n_gram_frequencies = lvu.initialize_from_file()
vocab_vec, max_word_length = lvu.vocab_vector(lv, lang_vectors)
vocab = lvu.vocab(max_word_length)
filepath = "preprocessed_texts/english/alice-only-stream.txt" # a_christmas_carol.txt"
text = read_file(filepath)
processed_indices = dict_explain_away(vocab, max_word_length, text)
processed = tuples_to_text(processed_indices, text)
fwrite = open("intermediate/processed_dict_explain_away_results.txt", "w")
fwrite.write(processed)
fwrite.close()
# now for the em
# not necessary in seeding phase.
discovered_words = hard_em_discover_words(processed_indices, text, vocab, lv)
record_results(text, processed_indices, discovered_words, "output/explain_away_results.txt")
# save data to file
lvu.write_data_structures(
[lv, lang_vectors, n_gram_frequencies, vocab_vec, vocab],
[
"intermediate/lookup_lv",
"intermediate/lookup_lang_vectors",
"intermediate/lookup_n_gram_frequencies",
"intermediate/lookup_vocab_vec",
"intermediate/lookup_vocab",
],
)
def seed():
filepath = "preprocessed_texts/english/alice-only-spaced.txt"
#lvu.initialize()
lv, lang_vectors, n_gram_frequencies = lvu.initialize_from_file()
vocab_vec, max_word_length = lvu.vocab_vector(lv, lang_vectors)
vocab_dict = lvu.vocab_dict(max_word_length)
filepath = "preprocessed_texts/english/alice-only-stream.txt"#a_christmas_carol.txt"
aea = dict_explain_away(vocab_dict,max_word_length,filepath)
#file = open("intermediate/processing_array_explain_away_results","w")
#file.write(aea)
#file.close()
#now for the em
#not necessary in seeding phase.
#hed = hard_em_discover_words(aea, vocab_array, max_length, filepath)
#file = open("../output/processed_array_explain_away_results","w")
#file.write(hed)
#file.close()
# save data to file
lvu.write_data_structures([lv, lang_vectors, n_gram_frequencies, vocab_vec, vocab_dict], \
["intermediate/lookup_lv", "intermediate/lookup_lang_vectors", \
"intermediate/lookup_n_gram_frequencies", "intermediate/lookup_vocab_vec", \
"intermediate/lookup_vocab_dict"])
def seed():
filepath = "preprocessed_texts/english/alice-only-spaced.txt"
#lvu.initialize()
lv, lang_vectors, n_gram_frequencies = lvu.initialize_from_file()
vocab_vec, max_word_length = lvu.vocab_vector(lv, lang_vectors)
vocab = lvu.vocab(max_word_length)
filepath = "preprocessed_texts/english/alice-only-stream.txt" #a_christmas_carol.txt"
text = read_file(filepath)
processed_indices = dict_explain_away(vocab, max_word_length, text)
processed = tuples_to_text(processed_indices, text)
fwrite = open("intermediate/processed_dict_explain_away_results.txt", "w")
fwrite.write(processed)
fwrite.close()
# now for the em
# not necessary in seeding phase.
discovered_words = hard_em_discover_words(processed_indices, text, vocab,
lv)
record_results(text, processed_indices, discovered_words,
"output/explain_away_results.txt")
# save data to file
lvu.write_data_structures([lv, lang_vectors, n_gram_frequencies, vocab_vec, vocab], \
["intermediate/lookup_lv", "intermediate/lookup_lang_vectors", \
"intermediate/lookup_n_gram_frequencies", "intermediate/lookup_vocab_vec", \
"intermediate/lookup_vocab"])