Content is largely the same, but I reduced the number of functions
that the code uses to minimize the amount of scrolling back and
forth. I move the dog simulation back into the notebook so that
it is easily inspected - people have been confused about what it
is doing.
This code did not work for Python 2.x becaus I was not
importing from future. While I was altering all the files
I updated the header to include license information.
I was saying 'blue curve' 'green curve', but those have no meaning,
especially if printed in black and white. Switched to explicit
$\sigma=0.2$.
Also added second std in the chart showing the 68-95-99.7 rule.
User ulenka on gitter suggest changing the color for the
residual line. I found my changes garish, so I switched
to a thicker black line and changed the grids to dotted.
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).
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.
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 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.
I made a lot of changes so that each chapter makes clear that
they are all implementing the same basic bayesian algorithm.
This required a lot of editting, and it doesn't make sense to
try to do that atomically, hence this huge check in.
I made a lot of edits, and haven't copy editted anything. i'm
sure I introduced a lot of problems and discontinuities.
Most of the text is wrong, but changed code to use the
renamed ScaledUnscentedKalmanFilter.
Checking in with bad text because I am in the process of changing
FilterPy to use a class for the sigma points to make it easier
to change the sigma point generation, leaving us with one
UKF class instead of several.
Added better explanation of P = FPF' + Q.
Moved conversion of multivariate equations to univariate eqs. to the
math chapter.
Moved the walkthrough of KalmanFilter to an appendix.
Let this check in get away from me. Bunch of small formatting sttuf
in the various chapters, some experimental animations and code, etc.
Not a clearly delineated check in.
I had information on these rather buried, and did not have a single example
of how to compute them. Now the first part of the chapter covers this much
more thoroughly.
Also added a section on plotting exponentials. Not sure I want to retain
it; it is a bit 'light'.
