Version 0.0.23
==============
* Restructured directories so source code is under filterpy/,
not filterpy/filterpy. If you have PYTHONPATH set to point
to some_dir/filterpy you will need to change it to some_dir.
Shouldn't affect you if you do a normal pip install. Let me
know.
* Allow KalmanFilter.B to be set to a scalar.
* let plot_covariance_ellipse use fc and ec for facecolor
and edgecolor. Just to make code shorter in book!
Version 0.0.22
==============
BREAKING CHANGE
Split statistical functions in filterpy.common into filterpy.stats
module. I did not add or change anything, just move functions.
If you get an import error, this is probably why! Switch import
from filterpy.common to filterpy.stats and everything should work.
Version 0.0.21
==============
Added monte_carlo module which contains routines for MCMC - mostly
for particle filtering.
Version 0.0.20
==============
Several important bug fixes and additions for the UKF filter. It is very
important to update your code to this release if you are using the UKF.
* You couldn't call update() more than once in a row or the covariance
matrix would be computed incorrectly,.
* Added way to specify subtract routine in the sigma point classes.
* Fixed bug in computation of weights for the Julier sigma points.
Version 0.0.19
===========
BREAKING CHANGES!!
The unscented kalman filter code has been significantly altered. Your
existing code will no longer run. Sorry, but it had to be done.
As of version 0.0.18 there were separate classes for the UKF (Julier's)
original formulation, and for the scaled UKF. But they are all the same thing,
basically, and there were differing levels of support - the scaled version didn't
have an RTS smoother, for example.
Now the sigma point and weight generation is done with a separate class,
and the UKF class just performs the algorithm. This is much more configurable
at perhaps the cost of being a bit harder to read and learn. But I didn't want to
keep writing batch_filter, rts_smoother, etc, for every possible sigma point
filter.
The best documentation on this is the chapter on the UKF in my Kalman filter
book:
https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python/blob/master/09_Unscented_Kalman_Filter.ipynb
Version 0.0.18
==============
* Added args parameters to Hx and HJacobian of the ExtendedKalmanFilter
class so you can pass additional data to them.
* Made an exception more human readable by including the size of the
matrix that caused the shape error.
Version 0.0.17
==============
* Fixed assert in UKF module that incorrectly required kappa
to be >= 0.
Version 0.0.16
==============
* Added multivariate_multiply to stats module.
* IMPORTANT: bug fix in the UKF RTS smoother routine.
* various typo fixes.
Version 0.0.15
==============
A bunch of small changes and bug fixes. Documentation improvements.
Version 0.0.14
==============
The change to _dt was stupid in 0.0.13 . I put it back to _dt, and
then added an optional dt parameter to the predict() function.
Version 0.0.13
==============
* BREAKING CHANGE: _dt in UKF is now named dt to allow users to
rename. You will get an exception if you try to use _dt for now.
* fixed bug in EKF.
Version 0.0.12
==============
* Mostly a change in the pypi install so that the pip install will
include the test directories, and include the changelog and license.
* a few small bug fixes.
Version 0.0.11
==============
* Breaking change - moved rts_smoother into the KalmanFilter class.
* added an rts_smoother method to the UnscentedKalmanFilter class
Version 0.0.10
==============
* Modified all filters to allow a 1D array for the state vector x.
That is, np.array([1,0]) is allowed, as well as np.array([[1],[0]])
This is a potentially breaking change to your scripts. I tried to test
all of the possibilities, but bug may remain.
* Added some tests for dimensionality of input to functions. It is far
from complete, as I don't want to go overboard running tests for every
function call. On the other hand, failures are obsucre. This will be
finalized in few releases.
Version 0.0.9
=============
* Added Ensemble Kalman filter
* bug fixes in UKF
Version 0.0.8
=============
Minor changes to Unscented filter, mainly naming of local variables.
Version 0.0.7
=============
Significant changes to Unscented filter. Now separate classes for the different
sigma computations, and predict/update split out. Provision for supplying your own
residual and unscented transform functions.
Version 0.0.6
=============
Version 0.0.5
=============
* Fixed and included the fixed lag smoother algorithm.
* name change - all Z and Zs to z and zs. They are vectors, not matrices.
* Optional H parameter in KalmanFilter.update() to override the H matrix. Useful if you have a variable number of measurements on each update.
Version 0.0.4
=============
* Tests and fixes for the ExtendedKalmanFilter
* Minor name changes for the methods that compute Q in common
Version 0.0.3
=============
* Reverted the name change of .x to .X in the various classes. I have no idea what I was thinking - x is a vector, so it should be lower case.
* Moved some code to a new /examples directory to reduce clutter. It is worth noting that the code in there does not run now - it is based on the old procedural unscented KF code, not the new OO based code. However, the test_UKF.py code basically implements this example as a test using the new code. This is more a change for the future.
