from collections import defaultdict
import math
import pickle
import re

open_file = open('naive_base_model.pkl', 'rb')
pickle_loaded = pickle.load(open_file)
paranomal_class_logprob, skeptic_class_logprob, word_logprobs = pickle_loaded
def prediction(input,output):
    output_file = open(output,'w')
    with open(input,encoding='utf-8') as in_file:
        for line in in_file:
            temp_paranormal_logprob = paranomal_class_logprob
            temp_skeptic_logprob = skeptic_class_logprob
            text, timestamp = line.rstrip('\n').split('\t')
            text = text.lower()
            text = re.sub(r'\\n+', " ", text)
            text = re.sub(r'http\S+', " ", text)
            text = re.sub(r'\/[a-z]\/', " ", text)
            text = re.sub(r'[^a-z]', " ", text)
            text = re.sub(r'\s{2,}', " ", text)
            text = re.sub(r'\W\w{1,3}\W|\A\w{1,3}\W', " ", text)
            text = re.sub(r'\W\w{1,3}\W|\A\w{1,3}\W', " ", text)
            text = re.sub(r'\W\w{1,3}\W|\A\w{1,3}\W', " ", text)
            text = re.sub(r'^\s', "", text)
            tokens = text.split(' ')
            for token in tokens:
                if token not in word_logprobs['paranormal']:
                    word_logprobs['paranormal'][token] = -14.78
                if token not in word_logprobs['skeptic']:
                    word_logprobs['skeptic'][token] = -15.6

                temp_paranormal_logprob += paranomal_class_logprob + word_logprobs['paranormal'][token]
                temp_skeptic_logprob += skeptic_class_logprob + word_logprobs['skeptic'][token]

            if temp_paranormal_logprob > temp_skeptic_logprob:
                output_file.write('1\n')
            else:
                output_file.write('0\n')
##
def main():
    prediction('dev-0/in.tsv','dev-0/out.tsv')
    prediction('test-A/in.tsv/in.tsv','test-A/out.tsv')

main()