Low Discrepency sequences in arbitrary dimensions

sample.py

import numpy as np

class QuasiRandom():
    def __init__(self,dim=1,seed=None):
        self.dim = dim
        self.x = np.random.rand(dim) if seed is None else seed
        root_sys = [1] +[0 for i in range(dim-1)] + [-1,-1]
        self.const = sorted(np.roots(root_sys))[-1].real
        self.phi = np.array([1/(self.const)**(i+1) for i in range(dim)])
    def generate(self,n_points=1):
        res = np.zeros((n_points,self.dim))
        for i in range(n_points):
            res[i] = self.x = (self.x+self.phi)
        return np.squeeze(res%1)