Copy your original hanoi towers solution code to a new file (maybe 'complexity.py'). (use any hanoi towers program)

Modify your code to take the following command line arguments:

springsemester% python complexity.py USAGE: complexity.py   

Using the clock() method of the Python time module, measure the processor time required for function calls with min # rings <= rings <= max # rings; increment the number of rings by 1 each time you call the function.

At the end, your code will print a table reporting seconds of CPU time versus number of rings. You should have an upper limit on the number of rings that requires significant CPU time (say ~ 30 seconds).

It is suggested that you disable the print statements in the HanoiTowers function - they add an element of uncertainty that is irrelevant to measuring complexity.

Make a log plot of the data (log execution time VS number of rings) to answer these questions :

* Do you see evidence that the time complexity is exponential? Why so, or why not?

* If 'yes' to the above, what is your estimate of the base of the exponential function?