Kalman-and-Bayesian-Filters.../gaussian_internal.py

57 lines
1.6 KiB
Python

# -*- coding: utf-8 -*-
"""
Created on Thu May 8 23:16:31 2014
@author: rlabbe
"""
import math
import matplotlib.pylab as pylab
import matplotlib.pyplot as plt
import numpy as np
import stats
def plot_gaussian (mu, variance,
mu_line=False,
xlim=None,
xlabel=None,
ylabel=None):
xs = np.arange(mu-variance*2,mu+variance*2,0.1)
ys = [stats.gaussian (x, mu, variance)*100 for x in xs]
plt.plot (xs, ys)
if mu_line:
plt.axvline(mu)
if xlim:
plt.xlim(xlim)
if xlabel:
plt.xlabel(xlabel)
if ylabel:
plt.ylabel(ylabel)
plt.show()
def display_stddev_plot():
figsize = pylab.rcParams['figure.figsize']
pylab.rcParams['figure.figsize'] = 12,6
xs = np.arange(10,30,0.1)
var = 8; stddev = math.sqrt(var)
p2, = plt.plot (xs,[stats.gaussian(x, 20, var) for x in xs])
x = 20+stddev
y = stats.gaussian(x, 20, var)
plt.plot ([x,x], [0,y],'g')
plt.plot ([20-stddev, 20-stddev], [0,y], 'g')
y = stats.gaussian(20,20,var)
plt.plot ([20,20],[0,y],'b')
ax = plt.axes()
ax.annotate('68%', xy=(20.3, 0.045))
ax.annotate('', xy=(20-stddev,0.04), xytext=(x,0.04),
arrowprops=dict(arrowstyle="<->",
ec="r",
shrinkA=2, shrinkB=2))
ax.xaxis.set_ticks ([20-stddev, 20, 20+stddev])
ax.xaxis.set_ticklabels(['$-\sigma$','$\mu$','$\sigma$'])
ax.yaxis.set_ticks([])
plt.show()
if __name__ == '__main__':
display_stddev_plot()