daviddoji/Kalman-and-Bayesian-Filters-in-Python
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Switching to interactive plots

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Roger Labbe
2016-02-27 18:55:34 -08:00
parent a6c2b0ccc9
commit 590af94807
5 changed files with 27137 additions and 349 deletions
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46
code/book_plots.py
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@@ -236,7 +236,6 @@ def plot_estimate_chart_3():
def create_predict_update_chart(box_bg = '#CCCCCC',
arrow1 = '#88CCFF',
arrow2 = '#88FF88'):
plt.close('all')
plt.figure(figsize=(4, 2.), facecolor='w')
#plt.figure(figsize=(14,12.5), facecolor='w')
ax = plt.axes((0, 0, 1, 1),
@@ -301,6 +300,50 @@ def create_predict_update_chart(box_bg = '#CCCCCC',
plt.savefig('../figs/gh_predict_update.png', pad_inches=0.1)
def show_residual_chart(show_eq=True, show_H=False):
plt.figure(figsize=(11, 3.), facecolor='w')
est_y = ((164.2-158)*.8 + 158)
ax = plt.axes(xticks=[], yticks=[], frameon=False)
ax.annotate('', xy=[1,159], xytext=[0,158],
arrowprops=dict(arrowstyle='->',
ec='r', lw=3, shrinkA=6, shrinkB=5))
ax.annotate('', xy=[1,159], xytext=[1,164.2],
arrowprops=dict(arrowstyle='-',
ec='k', lw=3, shrinkA=8, shrinkB=8))
ax.annotate('', xy=(1., est_y), xytext=(0.9, est_y),
arrowprops=dict(arrowstyle='->', ec='#004080',
lw=2,
shrinkA=3, shrinkB=4))
plt.scatter ([0,1], [158.0,est_y], c='k',s=128)
plt.scatter ([1], [164.2], c='b',s=128)
plt.scatter ([1], [159], c='r', s=128)
plt.text (1.05, 158.8, r"prior $(\bar{x}_t)$", ha='center',va='top',fontsize=18,color='red')
plt.text (0.5, 159.6, "prediction", ha='center',va='top',fontsize=18,color='red')
plt.text (1.0, 164.4, r"measurement ($z$)",ha='center',va='bottom',fontsize=18,color='blue')
plt.text (0, 157.8, r"posterior ($x_{t-1}$)", ha='center', va='top',fontsize=18)
plt.text (1.02, est_y-1.5, "residual($y$)", ha='left', va='center',fontsize=18)
if show_eq:
if show_H:
plt.text (1.02, est_y-2.2, r"$y=z-H\bar x_t$", ha='left', va='center',fontsize=18)
else:
plt.text (1.02, est_y-2.2, r"$y=z-\bar x_t$", ha='left', va='center',fontsize=18)
plt.text (0.9, est_y, "new estimate ($x_t$)", ha='right', va='center',fontsize=18)
plt.text (0.8, est_y-0.5, "(posterior)", ha='right', va='center',fontsize=18)
if show_eq:
plt.text (0.75, est_y-1.2, r"$\bar{x}_t + Ky$", ha='right', va='center',fontsize=18)
plt.xlabel('time')
ax.yaxis.set_label_position("right")
plt.ylabel('state')
plt.xlim(-0.5, 1.5)
plt.savefig('../figs/residual_chart.png', pad_inches=0.1)
def show_legend():
plt.legend(loc='center left', bbox_to_anchor=(1, 0.5))
@@ -545,6 +588,7 @@ if __name__ == "__main__":
plot_estimate_chart_2()
plot_estimate_chart_3()
create_predict_update_chart()
show_residual_chart()
plt.close('all')
'''p = [0.2245871, 0.06288015, 0.06109133, 0.0581008, 0.09334062, 0.2245871,

40
code/mkf_internal.py
View File

@@ -79,46 +79,6 @@ def plot_track_ellipses(N, zs, ps, cov, title):
plt.show()
def show_residual_chart(show_eq=True, show_H=False):
est_y = ((164.2-158)*.8 + 158)
ax = plt.axes(xticks=[], yticks=[], frameon=False)
ax.annotate('', xy=[1,159], xytext=[0,158],
arrowprops=dict(arrowstyle='->',
ec='r', lw=3, shrinkA=6, shrinkB=5))
ax.annotate('', xy=[1,159], xytext=[1,164.2],
arrowprops=dict(arrowstyle='-',
ec='k', lw=3, shrinkA=8, shrinkB=8))
ax.annotate('', xy=(1., est_y), xytext=(0.9, est_y),
arrowprops=dict(arrowstyle='->', ec='#004080',
lw=2,
shrinkA=3, shrinkB=4))
plt.scatter ([0,1], [158.0,est_y], c='k',s=128)
plt.scatter ([1], [164.2], c='b',s=128)
plt.scatter ([1], [159], c='r', s=128)
plt.text (1.05, 158.8, r"prior $(\bar{x}_t)$", ha='center',va='top',fontsize=18,color='red')
plt.text (0.5, 159.6, "prediction", ha='center',va='top',fontsize=18,color='red')
plt.text (1.0, 164.4, r"measurement ($z$)",ha='center',va='bottom',fontsize=18,color='blue')
plt.text (0, 157.8, r"posterior ($x_{t-1}$)", ha='center', va='top',fontsize=18)
plt.text (1.02, est_y-1.5, "residual($y$)", ha='left', va='center',fontsize=18)
if show_eq:
if show_H:
plt.text (1.02, est_y-2.2, r"$y=z-H\bar x_t$", ha='left', va='center',fontsize=18)
else:
plt.text (1.02, est_y-2.2, r"$y=z-\bar x_t$", ha='left', va='center',fontsize=18)
plt.text (0.9, est_y, "new estimate ($x_t$)", ha='right', va='center',fontsize=18)
plt.text (0.8, est_y-0.5, "(posterior)", ha='right', va='center',fontsize=18)
if show_eq:
plt.text (0.75, est_y-1.2, r"$\bar{x}_t + Ky$", ha='right', va='center',fontsize=18)
plt.xlabel('time')
ax.yaxis.set_label_position("right")
plt.ylabel('state')
plt.xlim(-0.5, 1.5)
plt.show()
def plot_gaussian_multiply():