daviddoji/Kalman-and-Bayesian-Filters-in-Python
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Disable interactive plots for PDF.

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nbconvert cannot output interactive plots to PDF. I wrote code
to remove all of the %matplotlib notebook magic, rerun the notebooks,
and then create the PDF.
This commit is contained in:
Roger Labbe
2017-01-14 13:15:24 -08:00
parent e2405b23d5
commit 8463014958
12 changed files with 1234 additions and 1869 deletions
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52
code/mkf_internal.py
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@@ -17,7 +17,6 @@ from __future__ import (absolute_import, division, print_function,
unicode_literals)
import code.book_plots as bp
from code.book_plots import interactive_plot
import filterpy.stats as stats
from filterpy.stats import plot_covariance_ellipse
from matplotlib.patches import Ellipse
@@ -420,37 +419,36 @@ def plot_track(ps, actual, zs, cov, std_scale=1,
xlabel='time', ylabel='position',
title='Kalman Filter'):
with interactive_plot():
count = len(zs)
zs = np.asarray(zs)
count = len(zs)
zs = np.asarray(zs)
cov = np.asarray(cov)
std = std_scale*np.sqrt(cov[:,0,0])
std_top = np.minimum(actual+std, [count + 10])
std_btm = np.maximum(actual-std, [-50])
cov = np.asarray(cov)
std = std_scale*np.sqrt(cov[:,0,0])
std_top = np.minimum(actual+std, [count + 10])
std_btm = np.maximum(actual-std, [-50])
std_top = actual + std
std_btm = actual - std
std_top = actual + std
std_btm = actual - std
bp.plot_track(actual,c='k')
bp.plot_measurements(range(1, count + 1), zs)
bp.plot_filter(range(1, count + 1), ps)
bp.plot_track(actual,c='k')
bp.plot_measurements(range(1, count + 1), zs)
bp.plot_filter(range(1, count + 1), ps)
plt.plot(std_top, linestyle=':', color='k', lw=1, alpha=0.4)
plt.plot(std_btm, linestyle=':', color='k', lw=1, alpha=0.4)
plt.fill_between(range(len(std_top)), std_top, std_btm,
facecolor='yellow', alpha=0.2, interpolate=True)
plt.legend(loc=4)
plt.xlabel(xlabel)
plt.ylabel(ylabel)
if y_lim is not None:
plt.ylim(y_lim)
else:
plt.ylim((-50, count + 10))
plt.plot(std_top, linestyle=':', color='k', lw=1, alpha=0.4)
plt.plot(std_btm, linestyle=':', color='k', lw=1, alpha=0.4)
plt.fill_between(range(len(std_top)), std_top, std_btm,
facecolor='yellow', alpha=0.2, interpolate=True)
plt.legend(loc=4)
plt.xlabel(xlabel)
plt.ylabel(ylabel)
if y_lim is not None:
plt.ylim(y_lim)
else:
plt.ylim((-50, count + 10))
plt.xlim((0,count))
plt.title(title)
plt.show()
plt.xlim((0,count))
plt.title(title)
plt.show()
if plot_P:
ax = plt.subplot(121)