#!/usr/bin/env python

from __future__ import division
import numpy as np
from scipy import interpolate
import matplotlib.pyplot as plt


def noise(nnodes, amplitude):
    x = np.linspace(0, 1, nnodes)
    y = amplitude * np.random.uniform(-1, +1, nnodes)
    return interpolate.interp1d(x, y, kind='cubic')


class Noise(object):
    def __init__(self, size, details=1):
        self._f = [noise(2**(size+n), 1/2**n) for n in range(details)]

    def __call__(self, x):
        return sum([f(x) for f in self._f])


f = Noise(3, 5)
x = np.linspace(0, 1, 1000)

with plt.style.context('ggplot'):
    plt.plot(x, f(x))
    plt.savefig('src02.png')