EkfdPredict and GmekfPredict classes and tests #7
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…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.
keithalegrand
requested changes
Oct 29, 2025
pyest/filters/KalmanFilter.py
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| (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.
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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.