60 lines
1.6 KiB
Python
60 lines
1.6 KiB
Python
# -*- coding: utf-8 -*-
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"""Copyright 2015 Roger R Labbe Jr.
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Code supporting the book
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Kalman and Bayesian Filters in Python
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https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python
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This is licensed under an MIT license. See the LICENSE.txt file
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for more information.
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"""
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from __future__ import (absolute_import, division, print_function,
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unicode_literals)
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import filterpy.stats as stats
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import matplotlib.pyplot as plt
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import numpy as np
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def plot1():
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P = np.array([[6, 2.5], [2.5, .6]])
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stats.plot_covariance_ellipse((10, 2), P, facecolor='g', alpha=0.2)
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def plot2():
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P = np.array([[6, 2.5], [2.5, .6]])
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circle1=plt.Circle((10,0),3,color='#004080',fill=False,linewidth=4, alpha=.7)
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ax = plt.gca()
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ax.add_artist(circle1)
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plt.xlim(0,10)
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plt.ylim(0,3)
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P = np.array([[6, 2.5], [2.5, .6]])
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stats.plot_covariance_ellipse((10, 2), P, facecolor='g', alpha=0.2)
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def plot3():
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P = np.array([[6, 2.5], [2.5, .6]])
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circle1=plt.Circle((10,0),3,color='#004080',fill=False,linewidth=4, alpha=.7)
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ax = plt.gca()
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ax.add_artist(circle1)
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plt.xlim(0,10)
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plt.ylim(0,3)
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plt.axhline(3, ls='--')
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stats.plot_covariance_ellipse((10, 2), P, facecolor='g', alpha=0.2)
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def plot4():
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P = np.array([[6, 2.5], [2.5, .6]])
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circle1=plt.Circle((10,0),3,color='#004080',fill=False,linewidth=4, alpha=.7)
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ax = plt.gca()
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ax.add_artist(circle1)
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plt.xlim(0,10)
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plt.ylim(0,3)
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plt.axhline(3, ls='--')
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stats.plot_covariance_ellipse((10, 2), P, facecolor='g', alpha=0.2)
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plt.scatter([11.4], [2.65],s=200)
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plt.scatter([12], [3], c='r', s=200)
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plt.show() |