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stats.py
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stats.py
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# -*- coding: utf-8 -*-
#!/usr/bin/env python
from __future__ import print_function
import numpy as np
import os
import sys
import re
from operator import itemgetter
def initialize_n_grams_list(n):
alphabet = "abcdefghijklmnopqrstuvwxyz"
n_grams_table = []
if n == 1:
for i in alphabet:
n_grams_table.append(i)
return n_grams_table
else:
n_grams_table = initialize_n_grams_list(n-1)
n_grams_table2 = []
for i in n_grams_table:
for j in alphabet:
n_grams_table2.append(i+j)
return n_grams_table2
def cosine_distance(vec1, vec2):
return np.dot(vec1, vec2) / (np.linalg.norm(vec1) * np.linalg.norm(vec2))
def clean(string):
return re.sub("[^a-z\s]", "", string)
def get_n_grams_from_string(string, n_grams=3):
n_grams_list = []
for i in xrange(len(string)-n_grams+1):
n_grams_list.append(string[i:i+n_grams])
return n_grams_list
def count_n_grams(data, n_grams=3):
n_grams_map = {}
for word in data:
for gram in get_n_grams_from_string(word, n_grams):
if gram in n_grams_map:
n_grams_map[gram] += 1
else:
n_grams_map[gram] = 1
return n_grams_map
def count_stat_for_document(document, n_size=3):
stat_list = []
with open(document) as file:
data = file.read()
data2 = clean(data.lower()).split()
stat_map = count_n_grams(data2, n_size)
for key in initialize_n_grams_list(n_size):
if key not in stat_map:
stat_list.append(0)
else:
stat_list.append(stat_map[key])
return stat_list
def make_stats(directory, n_size=3):
stat_map = {}
for file in os.listdir(directory):
if file.endswith(".txt"):
print("Processing file: " + directory + "/" + file)
stat_map[file] = count_stat_for_document(directory + "/" + file, n_size)
return stat_map
def print_similarity_map(similarity_map):
print("######## RECOMENDATIONS ###########")
for item in sorted(similarity_map.items(), key=itemgetter(1), reverse=True):
print(item[0], " : ", item[1])
if __name__ == '__main__':
if len(sys.argv) == 4:
dir = sys.argv[1]
n_size = int(sys.argv[2])
user_file = sys.argv[3]
stats = make_stats(dir, n_size)
user_stats = count_stat_for_document(user_file, n_size)
similarity = {}
for key in stats:
similarity[key] = cosine_distance(stats[key], user_stats)
print_similarity_map(similarity)
else:
print("python stats.py [directory] [n-grams] [user_file]")