How to generate uncorrelated samples with Numpy-CodePudding

I'd like to generate random samples on python, but each with their own standard deviation.

I thought I could use np.random.normal(0, scale=np.array(standard_deviation), size=(len(np.array(standard_deviation)), number_of_simulations)

However, bumpy seems not to work when I put an array for scale (which is contrary to what I understand from the documentation) and only wants a float as an argument.

My goal is to render an array of size (Number of standards deviations X Numbers of simulations) where each row is just np.random.normal(0, scale=np.array(standard_deviation)[i], size= (1,number_of_simulations)

I think I could do a loop and then concatenate each result but i don't want to do this if not necessary because you loose the interest of Numpy and Pandas by doing loops I believe.

I hope I was clear and thanks for your help !

CodePudding user response：

The NumPy random functions do accept arrays, but when you also give a size parameter, the shapes must be compatible.

Change this:

np.random.normal(0, scale=np.array(standard_deviation), size=(len(np.array(standard_deviation)), number_of_simulations)

np.random.normal(0, scale=standard_deviation, size=(number_of_simulations, len(standard_deviation)))

The result will have shape (number_of_simulations, len(standard_deviation)).

Here's a concrete example in an ipython session. Note that instead of using numpy.random.normal, I use the newer NumPy random API, in which I create a generator called rng and call its normal() method:

In [103]: rng = np.random.default_rng()

In [104]: standard_deviation = np.array([1, 5, 25])

In [105]: number_of_simulations = 6

In [106]: rng.normal(scale=standard_deviation, size=(number_of_simulations, len(standard_deviation)))
Out[106]: 
array([[ -0.31088926,   1.95005394,  -8.77983357],
       [  1.80907248,   4.27082827,  31.13457498],
       [ -0.27178958, -12.6589072 , -31.70729135],
       [  0.2848883 ,   1.71198071, -23.6336055 ],
       [  0.78457822,   2.78281586,  32.61089728],
       [ -0.7014944 ,   5.47845616,   5.34276638]])