60 lines
2.0 KiB
Python
Executable File
60 lines
2.0 KiB
Python
Executable File
#!/usr/bin/python3
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import pickle
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import math
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import re
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def clear_tokens(tokens):
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tokens = tokens.replace('\\n', ' ')
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tokens = re.sub(r'\(((http)|(https)).*((\.com)|(\.net)|(\.jpg)|(\.html))\)'," ", tokens)
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tokens = re.sub(r'[\n\&\"\?\\\'\*\[\]\,\;\.\=\+\(\)\!\/\:\`\~\%\^\$\#\@]+', ' ', tokens)
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tokens = re.sub(r'[\.\-][\.\-]+', ' ', tokens)
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tokens = re.sub(r'[0-9]+', ' ', tokens)
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tokens = re.sub(r' +', ' ', tokens)
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return tokens
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def calc_post_prob(post, paranormal_class_logprob, sceptic_class_logprob, word_logprobs):
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# dla kazdego tokenu z danego posta
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text, timestap = post.rstrip('\n').split('\t')
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text = clear_tokens(text)
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tokens = text.lower().split(' ')
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probs = {0.0 : 'sceptic', 0.0 : 'paranormal'}
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for class_ in word_logprobs.keys():
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product = 1
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for token in tokens:
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try:
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product += word_logprobs[class_][token]
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except KeyError:
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pass
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# tu wzoru uzyj
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if class_ == 'sceptic':
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product += sceptic_class_logprob
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elif class_ == 'paranormal':
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product += paranormal_class_logprob
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probs[abs(product)] = class_
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#print(probs)
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return probs[max(probs.keys())]
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def main():
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with open('naive_base_model.pkl', 'rb') as f:
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pickle_list = pickle.load(f)
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paranormal_class_logprob = pickle_list[0]
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sceptic_class_logprob = pickle_list[1]
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word_logprobs = pickle_list[2]
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in_file = "test-A/in.tsv"
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#in_file = "dev-0/in.tsv"
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out_file = "test-A/out.tsv"
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#out_file = "dev-0/out.tsv"
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print (f"in {in_file}")
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print (f"out {out_file}")
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with open(in_file) as in_f, open(out_file, 'w') as out_f:
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for line in in_f:
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hyp = calc_post_prob(line, paranormal_class_logprob, sceptic_class_logprob, word_logprobs)
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if hyp == 'sceptic':
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out_f.write(" S\n")
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elif hyp == 'paranormal':
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out_f.write(' P\n')
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main()
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