Kalman-and-Bayesian-Filters-in-Python/code/nonlinear_plots.py

# -*- coding: utf-8 -*-
"""
Created on Sun May 18 11:09:23 2014

@author: rlabbe
"""

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


def plot_transfer_func(data, f, lims, num_bins=1000):
    ys = f(data)
    
    
    h = np.histogram(ys, num_bins, density=False)
   
    #plot output
    plt.subplot(2,2,1)
    plt.plot(h[0], h[1][1:], lw=4)
    plt.ylim(lims)
    plt.gca().xaxis.set_ticklabels([])
    plt.title('output')

    plt.axhline(np.mean(ys), ls='--', lw=2)

    # plot transfer function
    plt.subplot(2,2,2)
    x = np.arange(lims[0], lims[1],0.1)
    y = f(x)
    plt.plot (x,y)
    isct = f(0)
    plt.plot([0,0,lims[0]],[lims[0],isct,isct],c='r')
    plt.xlim(lims)
    plt.ylim(lims)
    plt.title('transfer function')

    # plot input
    h = np.histogram(data, num_bins, density=True)

    plt.subplot(2,2,4)
    plt.plot(h[1][1:], h[0], lw=4)
    plt.xlim(lims)
    plt.gca().yaxis.set_ticklabels([])
    plt.title('input')

    plt.show()



if __name__ == "__main__":
    from numpy.random import normal
    import numpy as np

    data = normal(loc=0.0, scale=1, size=500000)

    def g(x):
        return (np.cos(4*(x/2+0.7)))*np.sin(0.3*x)-1.6*x


    plot_transfer_func (data, g, lims=(-3,3), num_bins=100)