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DOI-USGS / streamMetabolizer

streamMetabolizer uses inverse modeling to estimate aquatic metabolism (photosynthesis and respiration) from time series data on dissolved oxygen, water temperature, depth, and light.
http://usgs-r.github.io/streamMetabolizer/
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improve plot_DO_preds for pi, oipi, and sim models #294

Open aappling-usgs opened 7 years ago

aappling-usgs commented 7 years ago

for y_var %in% c('conc', 'pctsat'), pi models should have prediction line segments that each start at a DO.obs value and progress toward the next one. what we have now is what might be called the DO.pure predictions - what we get if we extrapolate the daily metab params to DO.mod assuming no error. oipi models should have the state-space estimates in DO.mod, which are pi-corrected but don't need to be line segments starting at DO.obs values.

with bayesian models we can track inst estimates of err_obs_iid and err_proc_iid, which could help with both pi and oipi plotting.

aappling-usgs commented 7 years ago

may want to plot both DO_mod (the state, which is DO.obs for pi models) and DO_pure (aka DO_det for 'deterministic'?). And what about DO_mod_partial, which is deterministic based on the previous timestep's state?

aappling-usgs commented 5 years ago

This function could also use updating for GPP-process-error models (pp, err_proc_GPP=TRUE).