calc_fit: Calculate model performance metrics

In aemon-j/LakeEnsemblR: Run Ensemble of Lake Models

Calculate model performance metrics

Description

Calculates model performace metrics from the netcdf file generated by running 'run_ensemble'

Usage

calc_fit(
  ncdf,
  list = NULL,
  model,
  var = "temp",
  dim = "model",
  dim_index = 1,
  qualfun = qual_fun,
  avfun = "mean"
)

Arguments

ncdf	Path to the netcdf file generated by running 'run_ensemble'
list	Alternatively to 'ncdf' a list of siimulated variables, as returned by 'run_ensemble()' when argument 'return_list = TRUE'
model	Vector of models for which to calculate the performance measures
var	Variable for which to calculate the performance measures. Defaults to "temp".
dim	character; NetCDF dimensions to extract. Must be either "member" or "model". Defaults to "model". Only used if using the netCDF file. Currently only works with "model".
dim_index	numeric; Index of dimension chosen to extract from. Defaults to 1. Only used if using the netCDF file.
qualfun	Function to calculate the performance measures. Per default calculates root mean suqared error (rmse), Nash-Shutcliff efficiency (nse), Pearson correlation (r), bias (bias), mean absolute error (mae), normalized mean absolute error (nmae), and bias. Can be any function that takes observed data as first, and simulated data at the same time and depth as the second argument.
avfun	Name of the function to calculate the ensemble average, defaults to "mean"

Author(s)

Johannes Feldbauer

Examples

## Not run: 
# using standard quality measures
calc_fit(ncdf = "output/ensemble_output.nc",
                   model = c("FLake", "GLM",  "GOTM", "Simstrat", "MyLake"),
                   var = "temp")
# using own performance measure
 calc_fit(ncdf = "output/ensemble_output.nc",
                  model = c("FLake", "GLM",  "GOTM", "Simstrat", "MyLake"),
                  var = "temp", qualfun = function(O, S) mean(O - S, na.rm = TRUE))

## End(Not run)

aemon-j/LakeEnsemblR documentation built on April 11, 2025, 10:09 p.m.