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This article mainly introduces "what is python Monte Carlo algorithm". In daily operation, I believe that many people have doubts about what is python Monte Carlo algorithm. The editor consulted all kinds of data and sorted out simple and easy-to-use operation methods. I hope it will be helpful for you to answer the doubts about "what is python Monte Carlo algorithm"! Next, please follow the editor to study!

1. Also known as statistical simulation, random numbers (or, more commonly, pseudorandom numbers) are used to solve many computational problems.

2. The use process is to construct or describe the probability process, to sample from the known probability distribution and to establish various estimators.

Example

Import mathimport randomm = 10000n = 0for i in range (m): # x, y is a random number between 0 and 1 x = random.random () y = random.random () # if point (x Y) the number of valid within the circle of 1 if math.sqrt + 1 is + 1: n + = calculation pipi = 4 * n / mprint ("pi = {}" .format (pi)) # pi = 3.1508 (the results are random and not necessarily the same). The study on "what is the python Monte Carlo algorithm" is over, hoping to solve everyone's doubts. The collocation of theory and practice can better help you learn, go and try it! If you want to continue to learn more related knowledge, please continue to follow the website, the editor will continue to work hard to bring you more practical articles!

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