Added animation of multivariate tracking.

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Roger Labbe 2014-09-18 13:43:16 -07:00
parent 68dea65432
commit fe9df8a482
5 changed files with 200 additions and 143 deletions

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@ -1,6 +1,6 @@
Introductory textbook for Kalman filters and Bayesian filters. All code is written in Python, and the book itself is written in Ipython Notebook so that you can run and modify the code in the book in place, seeing the results inside the book. What better way to learn?
![alt tag](https://raw.githubusercontent.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/master/Chapter05_Kalman_Filters/dog_track.gif)
![alt tag](https://raw.githubusercontent.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/master/Chapter06_Multivariate_Kalman_Filter/track1.gif)
Reading Online

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@ -226,7 +226,7 @@ def is_inside_ellipse(x,y, ex, ey, orientation, width, height):
def plot_covariance_ellipse(mean, cov=None, variance = 1.0,
ellipse=None, title=None, axis_equal=True,
facecolor='none', edgecolor='#004080',
alpha=1.0):
alpha=1.0, xlim=None, ylim=None):
""" plots the covariance ellipse where
mean is a (x,y) tuple for the mean of the covariance (center of ellipse)
@ -277,6 +277,11 @@ def plot_covariance_ellipse(mean, cov=None, variance = 1.0,
lw=2)
ax.add_patch(e)
plt.scatter(mean[0], mean[1], marker='+') # mark the center
if xlim is not None:
ax.set_xlim(xlim)
if ylim is not None:
ax.set_ylim(ylim)
def _to_cov(x,n):