cProfile based python profiling an omega network perfect shuffle simulation

omega.py

#simulate omega network
import math
import sys
import cProfile, pstats

class simulate:
	def __init__(self):
    self.a = range(int(input('Enter number of inputs:')))
		self.b = self.a[:]
		self.count = int(math.log(len(self.a),2))
		self.var = 1

	def shuffle(self,list):
		print('call', str(self.var))
		self.var += 1
		return_list = []
		for x in list:
			if x == len(list)-1 or x == 0:
				return_list.append(x)
			else:
				return_list.append((x<<1) % (len(self.a) - 1))
		return return_list

	def sim(self):
		while(self.count):
			self.a = self.shuffle(self.a)
			self.count -= 1
		for x,y in zip(self.b,self.a):
			print(str(x), '\t=>\t', str(y))

if __name__ == '__main__':
	sim = simulate()
	profiler = cProfile.Profile()
	profiler.enable()		            #start collecting profiling data
	sim.sim()
	profiler.disable()		          #stop collecting profile data
	stats = pstats.Stats(profiler)	#generate stats
	stats.print_stats()		          #print stats

more features like profiling a function call with parameters etc. are documented here