PDimClass

import scipy as sp

class PDimClass:
    """
    A p-dimensional class, which takes a list of Normal distribution parameters, 
    each of which defines a dimension
    """
    #a list of normal distribution parameter tuples, for N(mean, sd)
    params = [(0,1), (0,1)]

    def __init__(self, params=None):
        if params:
            self.params = params

    def generate(self):
        point = []
        for dimension in self.params:
            #the dimension value = (random number from standard normal distribution * sd) + mean
            value = (sp.randn()*dimension[1]) + dimension[0]
            point.append(value)
        return tuple(point)