filterpy
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rlabbe
Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoothe...
Hi Roger, Just have a confusion between line 1180 and line 1132 in kalman_filter.py > def log_likelihood_of(self, z): """ log likelihood of the measurement `z`. This should only be called...
If possible can you guys please implement the expectation-maximization (EM) algorithm like it is in pykalman?https://pykalman.github.io/#pykalman.KalmanFilter
It's pretty embarrassing. Help(KalmanFilter) or KalmanFilter? give better documentation. I may want to look into a different way of generating documentation. The look and feel is quite outdated compared to...
KalmanFilter uses a 2d column vector for x, UKF uses a 1d array. This is inconsistent. the column vector is also very annoying. If len(x)==9, batch_filter will return the mean...
I'm not sure if I like this or not. The function signature implies that x,P are computed and returned in a list, but the kf states are also updated. Maybe...
Consider the typical workflow: mu, cov, _, _ = kf.batch_filter(zs[1:], saver=saver) rxs, Ps, Ks, pPs = kf.rts_smoother(mu, cov) We have typically initialized the KF with the first measurement or 2...
Saver should have a (optional?) time field. saver.save() # increments time by whatever delta time was assigned or saver.save(curr_time) # save this time Otherwise the data can be hard to...
Rounding errors can cause small negative values for the covariance. Ensure these are removed with the 0.5*(P + P.T) trick.
kinematic_kf creates the filter with dim_z=dim. I'm still working through it, I'm not sure if we should remove dim_z from the call, or use it. when dim> 1 I think...