daviddoji/Kalman-and-Bayesian-Filters-in-Python
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Start of IMM section, lots left to do

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Roger Labbe 2015-08-22 12:22:09 -07:00
parent cf740e4d16
commit 43b55214a8
2 changed files with 184 additions and 57 deletions
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179
14-Adaptive-Filtering.ipynb
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62
code/adaptive_internal.py
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@ -17,6 +17,7 @@ from __future__ import (absolute_import, division, print_function,
unicode_literals)
import book_plots as bp
from matplotlib.patches import Circle, Rectangle, Polygon, Arrow, FancyArrow
import matplotlib.pyplot as plt
@ -37,3 +38,64 @@ def plot_track_and_residuals(t, xs, z_xs, res):
plt.ylabel('residual')
plt.title('residuals')
plt.show()
def plot_markov_chain():
plt.figure(figsize=(4,4), facecolor='w')
ax = plt.axes((0, 0, 1, 1),
xticks=[], yticks=[], frameon=False)
#ax.set_xlim(0, 10)
#ax.set_ylim(0, 10)
box_bg = '#DDDDDD'
kf1c = Circle((4,5), 0.5, fc=box_bg)
kf2c = Circle((6,5), 0.5, fc=box_bg)
ax.add_patch (kf1c)
ax.add_patch (kf2c)
plt.text(4,5, "KF\nStraight",ha='center', va='center', fontsize=14)
plt.text(6,5, "KF\nTurn",ha='center', va='center', fontsize=14)
#btm
plt.text(5, 3.9, ".05", ha='center', va='center', fontsize=18)
ax.annotate('',
xy=(4.1, 4.5), xycoords='data',
xytext=(6, 4.5), textcoords='data',
size=10,
arrowprops=dict(arrowstyle="->",
ec="k",
connectionstyle="arc3,rad=-0.5"))
#top
plt.text(5, 6.1, ".03", ha='center', va='center', fontsize=18)
ax.annotate('',
xy=(6, 5.5), xycoords='data',
xytext=(4.1, 5.5), textcoords='data',
size=10,
arrowprops=dict(arrowstyle="->",
ec="k",
connectionstyle="arc3,rad=-0.5"))
plt.text(3.5, 5.6, ".97", ha='center', va='center', fontsize=18)
ax.annotate('',
xy=(3.9, 5.5), xycoords='data',
xytext=(3.55, 5.2), textcoords='data',
size=10,
arrowprops=dict(arrowstyle="->",
ec="k",
connectionstyle="angle3,angleA=150,angleB=0"))
plt.text(6.5, 5.6, ".95", ha='center', va='center', fontsize=18)
ax.annotate('',
xy=(6.1, 5.5), xycoords='data',
xytext=(6.45, 5.2), textcoords='data',
size=10,
arrowprops=dict(arrowstyle="->",
fc="0.2", ec="k",
connectionstyle="angle3,angleA=-150,angleB=2"))
plt.axis('equal')
plt.show()