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Kalman-and-Bayesian-Filters-in-Python
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Added instructions for cloning the book

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Roger Labbe 2018-04-29 08:08:40 -07:00 committed by GitHub
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@ -95,7 +95,12 @@ The PDF will usually lag behind what is in github as I don't update it for every
However, this book is intended to be interactive and I recommend using it in that form. It's a little more effort to set up, but worth it. If you install IPython and some supporting libraries on your computer and then clone this book you will be able to run all of the code in the book yourself. You can perform experiments, see how filters react to different data, see how different filters react to the same data, and so on. I find this sort of immediate feedback both vital and invigorating. You do not have to wonder "what happens if". Try it and see!
Instructions for installation can be found in the Installation appendix, found [here](http://nbviewer.ipython.org/github/rlabbe/Kalman-and-Bayesian-Filters-in-Python/blob/master/Appendix-A-Installation.ipynb).
The book and supporting software can be downloaded from GitHub by running this command on the command line:
git clone --depth=1 https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python.git
pip install filterpy
Instructions for installation of the IPython ecosystem can be found in the Installation appendix, found [here](http://nbviewer.ipython.org/github/rlabbe/Kalman-and-Bayesian-Filters-in-Python/blob/master/Appendix-A-Installation.ipynb).
Once the software is installed you can navigate to the installation directory and run Juptyer notebook with the command line instruction