amber: scores.compare.ensemble – R documentation

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scores.compare.ensemble

Summarize scores from multiple model runs in single figure.

Description

This function produces a figure that summarizes score values from multiple model runs. The figure has four columns, which give the multi-model mean scores, the total score range, the model with the lowest score and the model with the highest score. The respective inputs are created by the functions scores.fluxnet.csv or scores.fluxnet.nc, scores.grid.notime, scores.grid.time, and scores.runoff.

Usage

scores.compare.ensemble(mod.path.list = mod.path.list,
  modelIDs = modelIDs, myVariables = myVariables, plot.width = 10,
  plot.height = 10, myMargin = c(12, 0, 3, 0), outputDir = FALSE)

Arguments

`mod.path.list`	A list with paths for each model run, e.g. mod.path.list <- list(mod01.path, mod02.path, mod03.path)
`modelIDs`	An R object with the different model run IDs, e.g. c('CLASSIC.CRUJRAv2', 'CLASSIC.GSWP3W5E5', 'CLASSIC.CRUNCEP')
`myVariables`	An R object with variable names of variables that should be included in table, e.g. c('GPP', 'RECO', 'NEE')
`plot.width`	Number that gives the plot width, e.g. 6
`plot.height`	Number that gives the plot height, e.g. 5
`myMargin`	An R object that gives the figure margins, e.g. c(4, 13, 3, 4)
`outputDir`	A string that gives the output directory, e.g. '/home/project/study'. The output will only be written if the user specifies an output directory.

Value

A figure in PDF format that shows the ensemble scores, the total score range, the model with the lowest score and the model with the highest score.

Examples

library(amber)
library(classInt)
library(doParallel)
library(foreach)
library(Hmisc)
library(latex2exp)
library(ncdf4)
library(parallel)
library(raster)
library(rgdal)
library(rgeos)
library(scico)
library(sp)
library(stats)
library(utils)
library(viridis)
library(xtable)

mod01.path <- system.file('extdata/model01', package = 'amber')
mod02.path <- system.file('extdata/model02', package = 'amber')
mod.path.list <- list(mod01.path, mod02.path)
modelIDs <- c('CLASSIC.CRUJRAv2', 'CLASSIC.GSWP3W5E5')
myVariables <- c('GPP', 'BURNT')
#myVariables <- c('RNS', 'RSS', 'RLS', 'ALBS', 'HFLS', 'HFSS', 'HFG', 'GPP', 'RECO',
#'NEE', 'FIRE', 'AGB', 'CVEG', 'CSOIL', 'LAI', 'BURNT', 'SNW', 'MRSLL', 'MRRO')

scores.compare.ensemble(mod.path.list = mod.path.list, modelIDs = modelIDs,
myVariables = myVariables, plot.width = 9.3, plot.height = 10,
myMargin = c(12, 0, 3, 0), outputDir = FALSE)

amber

Automated Model Benchmarking R Package

v1.0.3

GPL-3

Authors

Christian Seiler [cre, aut]

Initial release