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118 lines
3.2 KiB
118 lines
3.2 KiB
import os, json, re
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from math import log, exp
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import nltk
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from nltk import sent_tokenize
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from nltk.tokenize import RegexpTokenizer
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tokenizer = RegexpTokenizer(r'\w+') # initialize tokenizer
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import pprint
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pp = pprint.PrettyPrinter(indent=4)
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def tfidf(query, words, corpus):
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# Term Frequency
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tf_count = 0
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for word in words:
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if query == word:
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tf_count += 1
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tf = tf_count/len(words)
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# Inverse Document Frequency
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idf_count = 0
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for words in corpus:
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if query in words:
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idf_count += 1
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idf = log(len(corpus)/idf_count)
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tfidf_value = tf * idf
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return tf_count, idf_count, tfidf_value
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def get_language(manifesto):
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language = re.search(r'\[.*\]', manifesto, flags=re.IGNORECASE).group().replace('[','').replace(']','').lower()
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return language
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def load_text_files():
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files = []
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corpus = {}
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sentences = {}
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wordlists = {}
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languages = {}
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dir = 'txt'
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for manifesto in sorted(os.listdir(dir)):
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manifesto = manifesto.replace('.txt','')
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language = get_language(manifesto)
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if language == 'en+de+nl+fr': # exception for OBN manifesto
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language = 'en'
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languages[manifesto] = language
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lines = open('{}/{}.txt'.format(dir, manifesto), "r").read() # list of lines in .txt file
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lines = lines.replace(' •', '. ') # turn custom linebreaks into full-stops to let the tokenizer recognize them as end-of-lines
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words = [word for word in tokenizer.tokenize(lines)] # all words of one manifesto, in reading order
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wordlists[manifesto] = words
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if not language in corpus.keys():
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corpus[language] = []
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corpus[language].append(words)
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s = sent_tokenize(lines)
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sentences[manifesto] = s
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files.append(manifesto) # list of filenames
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print('\n*txt files loaded*')
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return files, corpus, sentences, wordlists, languages
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def make_human_readable_name(manifesto):
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year = re.match(r'^\d\d\d\d', manifesto).group()
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name = manifesto.replace(year, '').replace('_', ' ').replace('-', ' ')
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humanreadablename = '{} ({})'.format(name, year)
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return humanreadablename
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def create_index():
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files, corpus, sentences, wordlists, languages = load_text_files()
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index = {}
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# index = {
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# Fem manifesto : {
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# 'tfidf' : {
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# 'aap': 39.2,
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# 'beer': 20.456,
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# 'citroen': 3.21
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# },
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# 'tf' : {
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# 'aap': 4,
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# 'beer': 6,
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# 'citroen': 2
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# },
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# 'name': 'Feminist Manifesto (2000)',
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# 'language': 'en'
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# }
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# }
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for manifesto in files:
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print('---------')
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print('Manifesto:', manifesto)
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index[manifesto] = {}
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index[manifesto]['sentences'] = sentences[manifesto]
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language = languages[manifesto]
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words = wordlists[manifesto]
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for word in words:
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tf_count, idf_count, tfidf_value = tfidf(word, words, corpus[language])
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if 'tfidf' not in index[manifesto]:
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index[manifesto]['tfidf'] = {}
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index[manifesto]['tfidf'][word] = tfidf_value
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if 'idf' not in index[manifesto]:
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index[manifesto]['idf'] = {}
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index[manifesto]['idf'][word] = idf_count
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if 'tf' not in index[manifesto]:
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index[manifesto]['tf'] = {}
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index[manifesto]['tf'][word] = tf_count
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index[manifesto]['name'] = make_human_readable_name(manifesto)
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index[manifesto]['language'] = language
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with open('index.json','w+') as out:
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out.write(json.dumps(index, indent=4, sort_keys=True))
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out.close()
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print('*index created*')
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if __name__ == '__main__':
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create_index()
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