I was specifying the Neo-Euler font, which renders poorly
on nbviewer. This is a test to make sure it works before
checking in all notebooks. (I have to re-execute the notebook)
so that the script from the css file gets embedded into the
notebook).
A comment in a markdown cell inside a ```python ...``` block
was treated as a chapter header by nbconvert. I filled a bug
report with IPython and removed the comment.
Also found a mistake in the text about computing the residual
of angles that was duplicated in the EKF chapter, so I fixed the
error in that chapter as well.
I pulled out the 'track in a circle' example as it is the usual
sort of textbook nonsense problem that no one cares about. I created
an 'old-content' Notebook in case anyone still wants to see it; I
may put more content there as I continue to edit.
There is more than that here. I had a bad commit of a bunch of temporary
files, I had to reset back in time, and now I am doing a massive commit.
Sorry.
Too big a check in; got away from me. I rewrote a lot of the preface.
Added instructions for cloud.sagemath install. Removed import of
set_figsize and figsize in first cell because the first cell gets
deleted for the pdf.
All these changes are to make the book easier to run from
cloud.sagemath.org. You can share individual notebooks there,
but not entire projects.By putting everything under code at the
user only needs to grab that one directory.
More on sagemath later, if I decide to pursue that as a delivery
mechanism...
I split multivariate chapter into two as it was running 60+
pages. This required renumbering. While I was doing this
I changed names from using underscores to dashes; this seems
to help with line breaks when displaying links.
I plan to reorder the design so that the prediction is
fully implemented and I show an example. The chapter just goes
on and on with no examples. Plus, talking about Q just after
discussion Fx makes the most sense.
I made the source code more concise.
I added a lot of text to help clarify the relationship to Bayes
and the g-h filter.
Added an interaction for computing Gaussian products.
I used plt.show() to elimiante the <Matplotlib....> messages
on the output line, but using a ; on the last statement also
suppresses this data. Shorter code is better.
I made a separate filterpy.stats module becuase it made
little sense to import filterpy.common for stats
functions. This required a lot of changes in the notebooks
and supporting code.
Roger Labbe