Difference between revisions of "Monte Carlo Calculation of Pi"
From WLCS
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'''Resources:''' | '''Resources:''' | ||
− | * [Media:PythonWhileLoops.pptx] | + | * [[Media:PythonWhileLoops.pptx]] |
* [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://bkm.billking.io/projects/pi/ Monte Carlo Pi simulator] |
Revision as of 09:29, 16 December 2016
Objective:
- To become well-learned in the way of the while loop
Resources:
- Media:PythonWhileLoops.pptx
- HTTLACS: Ch 6 - Iteration
- Monte Carlo Pi simulator
- Monte Carlo Pi
- Monte Carlo method
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