plots {tiger}R Documentation

Evaluation plots for temporal dynamics of model performance

Description

Create various plot to understand the temporal dynamics of model performance

Usage

box.plots(result, solution, show.measures = 1:num.measures,
             new.order = 1:solution, show.synthetic.peaks = FALSE,
             synthetic.peaks.col = c(2:8, 2:8), show.timestep = NA,
             show.cell = NA,
                 ref = NULL, ref.new.order = new.order, ref.solutions =
                 solution, col.best.match = "black",
                 clusterPalette = rainbow(solution))
errors.in.time(xval, result, solution, show.months = FALSE, new.order
                 = 1:solution, x.range = 1:length(xval), pmax =
                 max(c(result$measured, result$modelled), na.rm =
                 TRUE), data.colors = data.frame(measured = c("grey"),
                 modelled = c("black"), rain = c("black")),
                 clusterPalette = rainbow(solution), color.cut.off = 0,
                 frac.max = 0.7, frac.min = 0.4, legend.pos =
                 "topleft", ...)
peaks.in.clusters(result, solution,  new.order = 1:solution)
peaks.on.som(result, solution, clusterPalette=rainbow(solution), cell.size = 0.9, mfrow=c(2,ceiling(n.errors/2)), new.order=1:solution)
peaks.measures(result, show.measures = 1:num.measures,
                 synthetic.peaks.col = c(2:8, 2:8), mfrow = c(2, 3),
                 col.best.match = "black", do.out = rep(TRUE,
                 length(show.measures)))
scatterplot(measures, show.measures=1:num.measures)
p.validityIndex(result, validity.max)

Arguments

result object returned from tiger
measures data.frame from which to create a scatter plot. e.g. result$measures.uniform
solution number of clusters to use for further evaluations (see also validityIndex)
show.measures vector of indices indicating for which performance measures to show the plots
new.order New numbering to assign to clusters. See also change.order.clusters
show.synthetic.peaks Show values of the synthetic peaks on top of the box plots.
synthetic.peaks.col Colors to use for synthetic peaks.
do.out vector of booleans indicating whether to exclude outliers when showing the plot
cell.size fraction of the cell square to be filled with color
show.cell the scores for a certain cell on the SOM can be ploted as blue line on the box plot (see examples)
x.range Indizes of x-values to be plotted
pmax maximum discharge for definition of the plot range
frac.min minimum of the y-range covered by color bars for cluster occurence
frac.max maximum of the y-range covered by color bars for cluster occurence
clusterPalette colors to use for the clusters
color.cut.off Value of cluster occurence below which the color bar is set to transparent (for better readability)
legend.pos Position of the legend
data.colors Color definition for rainfall and runoff
show.timestep timestep for which the values for the performance measures are to be plotted as black lines in the box plot
xval Values to be plotted on the x-axis (e.g. POSIX-date)
show.months Boolean indicating whether to add month ticks to x axis
mfrow see par
ref Reference solution to be ploted in grey on the box plot
ref.new.order New numbering to assign to clusters for reference solution on the box plot
ref.solutions Number of clusters for reference solution for which to plot the box plot
validity.max Do not plot solutions with cluster numbers resulting above in a validty index above validity.max
col.best.match Color to use for plotting the line indicating the position of the best match
... additional parameters passed to plot

Details

box.plots: for each performance measure, a box plot is created showing the values for each cluster

errors.in.time: occurence of the errors cluster along the time dimension

peaks.in.clusters: table of the position of the synthetic peak errors in the clusters.

peaks.measures: responce of the performance measures to the synthetic peak errors.

scatterplot: scatter plot of the performance measures

See package vignette for further details about which plot does what.

Value

used for the side effect of plotting results

Author(s)

Dominik Reusser

References

Reusser, D. E., Blume, T., Schaefli, B., and Zehe, E.: Analysing the temporal dynamics of model performance for hydrological models, Hydrol. Earth Syst. Sci. Discuss., 5, 3169-3211, 2008.

See Also

The package vignette

Examples

data(tiger.example)

new.order <- c(6,3,2,5,4,1)
correlated <- correlated(tiger.single, keep=c("CE","RMSE" ))

opar <- par(mfrow=c(3,5))
box.plots(tiger.single, solution=6, new.order=new.order, show.synthetic.peaks=TRUE)
box.plots(tiger.single, solution=6, new.order=new.order, show.cell=data.frame(x=1,y=1))
par(opar)
errors.in.time(xval=d.dates, result= tiger.single, solution=6, show.months=TRUE, new.order=new.order)
peaks.in.clusters(tiger.single, solution=6, new.order=new.order)
peaks.measures(tiger.single, show.measures=correlated$measures.uniform$to.keep)
scatterplot(tiger.single$measures.uniform, show.measures=correlated$measures.uniform$to.keep)


[Package tiger version 0.2 Index]