Sample from an empirical cdf specified by a set of points

ecdf.py

import numpy as np
import numpy.random as random
from scipy.stats import rv_continuous

class custom_distribution:
    def __init__(self, rng, xp, fp):
        """takes x, y points of cdf"""
        np.all(np.diff(xp) > 0)
        self.rng = rng
        self.xp = xp
        self.fp = fp
    def sample(self, size=1):
        sampled_prob = self.rng.uniform(0, 1, size)
        # use interp func to find x given y
        sampled_x = [np.interp(prob, self.fp, self.xp) for prob in sampled_prob]
        return sampled_x

if __name__ == "__main__":
    xp =[0, 10000, 20000, 30000, 50000, 80000, 200000, 1e+06, 2e+06, 5e+06, 1e+07, 3e+07]
    fp = [0, 0.15, 0.2, 0.3, 0.4, 0.53, 0.6, 0.7, 0.8, 0.9, 0.97, 1]
    rng = random.RandomState(seed=1)
    custom_d = custom_distribution(rng, xp, fp)
    sampled_points = custom_d.sample(size=10000)
    print np.percentile(sampled_points, 20)
    print np.percentile(sampled_points, 40)
    print np.percentile(sampled_points, 80)
    # 19978.8514227
    # 50131.0919101
    # 1964479.08035