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I have a problem creating a variable with normal distribution in JS, I know the option math.random()
is limited and that the chance of each value between 0 and 1 is equal (rectangular distribution), I saw some codes on the Internet that can transform rectangular distribution as is the case of math.random()
in normal distribution. I am accepting library tips and similar for Javascript, I know that in Python it is possible to solve with a Numpy library since there is a method called np.random.normal()
. There is something similar in JS?
I know that using a Box-Muller transform is possible, but I would like to optimize the code to have the mean and standard deviation as a parameter, so I could determine which standard deviation and mean I would like to use in this transformation. Can someone help me?
I’ll leave the code of the Box-Muller transform, maybe it will help to understand my problem
function random() {
var u = 0, v = 0;
while(u === 0) u = Math.random(); //Converting [0,1) to (0,1)
while(v === 0) v = Math.random();
return Math.sqrt( -2.0 * Math.log( u ) )*Math.cos( 2.0 * Math.PI * v);
}
random();
See if the helping. PS: See the source code of this page.
– Augusto Vasques