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Ran all notebooks to use new css settings.

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This commit is contained in:
Roger Labbe 2016-01-17 20:44:23 -08:00
parent 0a41e78aeb
commit 5240944dd4
19 changed files with 825 additions and 545 deletions
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95
05-Multivariate-Gaussians.ipynb
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85
06-Multivariate-Kalman-Filters.ipynb
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07-Kalman-Filter-Math.ipynb
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08-Designing-Kalman-Filters.ipynb
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09-Nonlinear-Filtering.ipynb
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10-Unscented-Kalman-Filter.ipynb
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11-Extended-Kalman-Filters.ipynb
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12-Particle-Filters.ipynb
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13-Smoothing.ipynb
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14-Adaptive-Filtering.ipynb
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29
Appendix-A-Installation.ipynb
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25
Appendix-B-Symbols-and-Notations.ipynb
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Appendix-D-HInfinity-Filters.ipynb
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Appendix-E-Ensemble-Kalman-Filters.ipynb
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Appendix-G-Designing-Nonlinear-Kalman-Filters.ipynb
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Appendix-H-Least-Squares-Filters.ipynb
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Interactions.ipynb → Supporting_Notebooks/Interactions.ipynb
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"source": [
"#format the book\n",
"%matplotlib inline\n",
"from __future__ import division, print_function\n",
"import sys;sys.path.insert(0,'..')\n",
"from book_format import load_style;load_style('..')"
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4
code/pf_internal.py
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@ -17,7 +17,7 @@ from __future__ import (absolute_import, division, print_function,
unicode_literals)
from filterpy.monte_carlo import stratified_resample
from filterpy.monte_carlo import stratified_resample, residual_resample
import matplotlib as mpl
import matplotlib.pyplot as plt
@ -25,7 +25,7 @@ import numpy as np
from numpy.random import randn, random, uniform, multivariate_normal, seed
#from nonlinear_plots import plot_monte_carlo_mean
import scipy.stats
from RobotLocalizationParticleFilter import *
#from RobotLocalizationParticleFilter import *

4
table_of_contents.ipynb
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@ -124,6 +124,10 @@
"Describes how I implemented the plotting of various pdfs in the book.\n",
"\n",
"\n",
"[**Interactions**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/master/Supporting_Notebooks/Interactions.ipynb)\n",
"\n",
"Interactive simulations of various algorithms. Use sliders to change the output in real time.\n",
"\n",
"\n",
"[**Iterative Least Squares for Sensor Fusion**](http://nbviewer.ipython.org/urls/raw.github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/master/Supporting_Notebooks/Iterative-Least-Squares-for-Sensor-Fusion.ipynb)\n",
"\n",