docs: clarify lqe and dlqe error covariance wording#1219
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I don't think that the new wording is accurate. In particular, it uses the term "minimum covariance", but the covariance is (in general) a matrix and so the minimum depends on the norm that you use (eg, determinant or trace). As noted in #1183, I think that something like "minimizes the mean squared error" or perhaps "minimizes the mean of x - x_e" would be more accurate. |
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Thanks, updated this to avoid describing covariance as the scalar objective.
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Thanks, updated this to avoid describing covariance as the scalar objective.
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Closes #1183.
This updates the
lqeanddlqedocstrings to describe the steady-state estimation error covariance minimized by the estimator, instead of saying only that the state estimate minimizes expected squared error.I avoided adding a runtime behavior change or changing generated docs directly.
Validation:
python -m ruff check control/stochsys.pypython -m pytest control/tests/stochsys_test.py -q-> 25 passed, 2 skippedpython -m numpydoc render control.stochsys.lqepython -m numpydoc render control.stochsys.dlqe$env:PYTHONPATH='..'; python -m pytest test_sphinxdocs.py::test_config_defaults -q-> 1 passed, 4 warningsKnown unrelated local docs issues:
python -m numpydoc validate control.stochsys.lqe/control.stochsys.dlqereports pre-existing docstring style findings.