def compare_words(filename, word_bank):
histogram = make_histogram.make_histogram_from_file(filename)
word_bank = make_histogram.make_histogram_from_file(word_bank)
new_words = []
for keys in histogram:
if keys not in word_bank:
new_words.append(keys)
return new_words
def zipf_freq(filename):
histogram = make_histogram.make_histogram_from_file(filename)
by_keys, by_values = sort_histogram.sort_histogram(histogram)
x = []
y = []
for f in by_values:
y.append(log(f[0]))
for i in range(1, len(by_values)+1):
x.append(log(i))
simple_plot.simple_plot(x, y)
def compare_word(filename, word_bank):
histogram = make_histogram.make_histogram_from_file(filename)
word_bank = make_histogram.make_histogram_from_file(word_bank)
return set(histogram) - set(word_bank)
__author__ = 'QHe'
import make_histogram
import random
import bisect
#Choose from a list constructed based on cumulative distribution of words
#Input - histogram (dictionary), output - the randomly chosen word (string)
def choose_from_hist(hist):
selection_list = []
for keys, values in hist.items():
selection_list.extend([keys] * values)
return random.choice(selection_list)
#Choose a random word by constructing a cumulative distribution list of words
#Input - histogram (dictionary), output - the randomly chosen word (string)
def choose_from_cdf(hist):
word_list = hist.keys()
cdf = []
counter = 0
for keys in hist:
counter += hist[keys]
cdf.append(counter)
random_number = random.randint(0, counter-1)
index = bisect.bisect(cdf, random_number)
return word_list[index]
if __name__ == '__main__':
print choose_from_hist(make_histogram.make_histogram_from_file('words.txt'))
print choose_from_cdf(make_histogram.make_histogram_from_file('words.txt'))
