def correct_words(classified_words, actual_words, dictionary_word_list, names_word_list, mode='single'):
corrected_words = classified_words[:]
for word_index in xrange(len(corrected_words)):
current_word = corrected_words[word_index]
lowercase_word = corrected_words[word_index].lower()
# Don't carry out correction for valid single letters
valid_single_letters = 'ai'
if not lowercase_word in valid_single_letters:
# Preserve capitalisation of first letter of each word
capitalised = current_word[0].isupper()
if not dictionary_word_list.word_match(lowercase_word) and not names_word_list.word_match(lowercase_word):
name_word = names_word_list.correct_word(lowercase_word, isCapitalised=capitalised, mode=mode)
dictionary_word = dictionary_word_list.correct_word(lowercase_word, isCapitalised=capitalised, mode=mode)
# Skip loop if no valid corrections were found
if name_word is None and dictionary_word is None:
continue
# If no name words were found, use the dictionary word
elif name_word is None and dictionary_word is not None:
current_word = dictionary_word
# If no dictionary words were found, use the name word
elif name_word is not None and dictionary_word is None:
current_word = name_word
# See if word is closer to a name or a dictionary word and correct it to the closer one
elif WordList.word_difference(current_word, name_word) < dictionary_word_list.word_difference(current_word, dictionary_word):
current_word = name_word
else:
current_word = dictionary_word
corrected_words[word_index] = current_word
return corrected_words
