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EkfdPredict and GmekfPredict classes and tests#7

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EkfdPredict and GmekfPredict classes and tests#7
bschneiderheinze wants to merge 4 commits into
scope-lab:mainfrom
bschneiderheinze:main

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@bschneiderheinze
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Added classes for EkfdPredict and GmekfPredict to filters, and respective tests to tests. The tests should be comprehensive and they fully pass.

…h both pass. EkfdPredict test checked against manual ekf update, checked that a diagonal H implies a diagonal W, and checked against KfdPredict for linear measurements. GmekfPredict test checked against EkfdPredict for single mixand, checked that weights get heavily scaled down for non-agreeing measurements, and checked against GmkfPredict for linear measurements.
Comment thread pyest/filters/KalmanFilter.py Outdated
Comment thread pyest/filters/KalmanFilter.py Outdated
Comment thread pyest/filters/KalmanFilter.py Outdated
Comment thread pyest/filters/KalmanFilter.py Outdated
Comment thread pyest/filters/KalmanFilter.py Outdated
Comment thread pyest/filters/KalmanFilter.py Outdated
Comment thread pyest/filters/KalmanFilter.py Outdated
Comment thread pyest/filters/KalmanFilter.py Outdated
Comment thread pyest/filters/KalmanFilter.py
Comment thread pyest/filters/Gmkf.py Outdated
Comment thread pyest/filters/KalmanFilter.py Outdated
Comment thread pyest/filters/KalmanFilter.py Outdated
(ny,ny) measurement noise covariance matrix
H : ndarray or callable
(nz,nx) measurement Jacobian matrix
z_k = H(tk, xk, *args) @ x. If provided an ndarray instead, H will
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Here, we may want to force the user to specify H as a callable to avoid user errors caused by using an incorrect constant Jacobian

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I changed it to be consistent with the handling of F in EkfdPredict, where it is documented as a callable but if provided an ndarray is still recast as a callable. I can add an error/warning if we want that though.

Comment thread pyest/filters/KalmanFilter.py Outdated
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