Difference between revisions of "Monte Carlo Calculation of Pi"
From WLCS
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'''Resources:''' | '''Resources:''' | ||
* [http://openbookproject.net/thinkcs/python/english2e/ch06.html HTTLACS: Ch 6 - Iteration] | * [http://openbookproject.net/thinkcs/python/english2e/ch06.html HTTLACS: Ch 6 - Iteration] | ||
| + | * [http://bkm.billking.io/projects/pi/ Monte Carlo Pi simulator] | ||
| + | * [http://math.fullerton.edu/mathews/n2003/montecarlopimod.html Monte Carlo Pi] | ||
* [http://en.wikipedia.org/wiki/Monte_Carlo_method Monte Carlo method] | * [http://en.wikipedia.org/wiki/Monte_Carlo_method Monte Carlo method] | ||
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'''Directions:''' | '''Directions:''' | ||
Revision as of 15:18, 13 February 2015
Objective:
- To become well-learned in the way of the while loop
Resources:
Directions:
- Prompt the user for a number N (this will be our total number of test points)
- Create a variable for our numHits (this is *not* our loop counter)
- Write a loop that runs N times (you should use a loop counter variable like count and avoid using x because we will use x for something else)
- Generate random numbers for x and y between 0 and 1.0 by using random.random()
- Use the distance formula to calculate the distance from (0, 0) to (x, y)
- Increment (Increase by 1) numHits if the distance is less than 1
- Calculate an estimate of pi
- successProbability = numHits / N
- PI = successProbability * 4
- Print out your estimate of PI
