Index of Coincidence

import sys

'''
Returns a list of sorted tuples of the letter distribution.
'''
def count(text):
	letter_counts = dict()
	#~ for char in alphabet.alphabetstr:
		#~ letter_counts[char] = 0
	
	for char in text:
		if not char in letter_counts.keys():
			letter_counts[char] = 0
		letter_counts[char] += 1
	return letter_counts

def index_of_coincidence_chunked(text, length):
	chunks, chunk_size = len(text)/length, length
	rows = [ text[i:i+chunk_size] for i in range(0, chunks, chunk_size)]

	sum = 0.0	
	for i in xrange(length):
		# Grab column i of each row and join. Then compute index of that.
		# This is equal to checking for a shift cipher if that column
		# is using that 
		column = "".join([row[i] for row in rows])
		if(len(column) < 2):
			continue
		sum += index_of_coincidence(column)
		
	# Average
	return sum / length
	

def index_of_coincidence(text):	
	distrib = count(text)
	divisor = len(text) * (len(text) - 1)
	sum = 0.0	
	for c in distrib.keys():
		fi = distrib[c]
		sum += fi * (fi - 1)	
	return sum / divisor


if __name__ == "__main__":
	text = ""
	line = sys.stdin.readline()
	while line != "":
		text += line.strip()
		line = sys.stdin.readline()
	
	_min, _max = 1, 30
	if(len(sys.argv) > 2):
		_min, _max = int(sys.argv[1]), int(sys.argv[2])	
		
	#~ fig = figure()
	#~ ax = fig.add_subplot(111, autoscale_on=False)	
	x, y = list(),list()
	for i in range(_min, _max):
		val = index_of_coincidence_chunked(text, i)
		x.append(i)
		y.append(val)
	
	try:
		import numpy as np
		import matplotlib.pyplot as plt
		import matplotlib.lines as lines
		from pylab import figure, show
		plt.plot(x,y)
		plt.show()
	except:
		print zip(x,y)
	#~ ax.add_line(lines.Line2D(x,y, color='m'))
	#~ a=lines.Line2D([5,6],[7,8],color='m') 
	#~ ax.add_line(a)
	#~ print x
	#~ print y