Implements the Simulating Optimal FUNctioning framework for site-scale simulations of ecosystem processes, including model calibration. It contains Fortran 90 modules for the P-model, SPLASH, and BiomeE models.
BiomeE likelihood function was very basic, mainly a hardcoded proof-of-concept but not flexible enough to apply to multiple sites or multiple target variables.
This PR updates this.
This PR further serves as a opportunity to streamline the likelihoods/RMSE calculations and properly applying the DRY principle (reducing the repeated code).
[x] add tests for current behavior
[x] homogenize likelihoods for p-model and BiomeE-model
[x] split likelihood function in
[x] a first part that runs the model and generates an obs_pred_data.frame
[x] TODO: streamline pred_obs result from likelihoodHelper_combine_model_obs() into a single, long data.frame()
[x] and a second part that computes RMSE/likelihood/GoF between obs and pred
[ ] same as above for RMSE functions, too
[ ] add argument verbose=FALSE from PR: #217
[ ] update vignettes, tests etc. with the split-function-approach
BiomeE likelihood function was very basic, mainly a hardcoded proof-of-concept but not flexible enough to apply to multiple sites or multiple target variables. This PR updates this.
This PR further serves as a opportunity to streamline the likelihoods/RMSE calculations and properly applying the DRY principle (reducing the repeated code).
pred_obsresult fromlikelihoodHelper_combine_model_obs()into a single, long data.frame()verbose=FALSEfrom PR: #217This is not only relevant for BiomeE but also changing the calibration of p-model to use ET instead/in addition to GPP. Hence this is also related to: https://github.com/geco-bern/sofunCalVal/issues/5 and https://github.com/geco-bern/sofunCalVal/pull/17