Description
import numpy as np import matplotlib.pyplot as plt import scipy.stats as ss import random as r import datetime
def monte ( parameters , samples ) :
tau_1 , beta_1 , tau_2 , beta_2 = parameters
# Here we create 2 distributions x and y
# They are normally distributed but correlated according to the covariance matrix ' cov '
mean = [ 0 , 0 ]
cov = [ [ 1 , 0.95 ] , [ 0.95 , 1 ] ] # diagonal covariance
x , y = np. random. multivariate_normal(mean , cov , samples ).T
# Here we change the normally distributed numbers to uniformly distributed numbers
# between 0 and 1
x = ss . norm.cdf ( x )
y = ss . norm.cdf ( y )
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54 line pyhton code .
https://matlab1.com/interaction-of-beta-particles-with-matter/
https://en.wikipedia.org/wiki/Monte_Carlo_method
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