paranormal-or-skeptic/predict.py
2020-03-29 13:39:47 +02:00

64 lines
2.0 KiB
Python
Executable File

#!/usr/bin/python3
import pickle
import math
import re
import sys
def calc_post_class(post, paranormal_class_logprob, sceptic_class_logprob, bigrams_logprobs):
text, timestap = post.rstrip('\n').split('\t')
text = clear_post(text)
tokens = text.lower().split(' ')
probs = {}
for class_ in bigrams_logprobs.keys():
product = 0
for index in range(len(tokens)-1):
# we handle bigrams not in models as neutral
bigram = tokens[index] + " " + tokens[index + 1]
#print(bigram)
try:
product += bigrams_logprobs[class_][bigram]
except KeyError:
product +=0
if class_ == 'sceptic':
product += sceptic_class_logprob
elif class_ == 'paranormal':
product += paranormal_class_logprob
probs[product] = class_
#print(probs)
return probs[min(probs.keys())]
def clear_post(post):
post = post.replace('\\n', ' ')
post = re.sub(r'(\(|)(http|https|www)[a-zA-Z0-9\.\:\/\_\=\&\;\-\?\+]+(\)|)', '', post)
post = re.sub(r'[\.\,]+', ' ', post)
post = re.sub(r'(&lt|&gt)','',post)
post = re.sub(r'[\'\(\)\?\*\"\`\;0-9\[\]\:\%]+', '', post)
post = re.sub(r' \- ', ' ', post)
post = re.sub(r' +', ' ', post)
post = post.rstrip(' ')
return post
def main():
if len(sys.argv) != 4:
print("syntax is ./predict.py in.tsv out.tsv model.pkl")
return
in_file = sys.argv[1]
out_file = sys.argv[2]
model = sys.argv[3]
with open(model, 'rb') as f:
pickle_list = pickle.load(f)
paranormal_class_logprob = pickle_list[0]
sceptic_class_logprob = pickle_list[1]
bigrams_logprobs = pickle_list[2]
with open(in_file) as in_f, open(out_file, 'w') as out_f:
for line in in_f:
hyp = calc_post_class(line, paranormal_class_logprob, sceptic_class_logprob, bigrams_logprobs)
if hyp == 'sceptic':
out_f.write(' S\n')
elif hyp == 'paranormal':
out_f.write(' P\n')
main()