View source: R/methods_hydroGOF.R
NSE.HypeSingleVar | R Documentation |
Nash-Sutcliffe Efficiency calculation for imported HYPE outputs with single variables for several catchments, i.e. time and map files, optionally multiple model run iterations combined.
## S3 method for class 'HypeSingleVar'
NSE(sim, obs, na.rm = TRUE, progbar = TRUE, ...)
sim |
|
obs |
|
na.rm |
Logical. If |
progbar |
Logical, if |
... |
ignored |
NSE.HypeSingleVar
returns a 2-dimensional array of NSE performances for all SUBIDs and model iterations provided in
argument sim
, with values in the same order
as the second and third dimension in sim
, i.e. [subid, iteration]
.
# Create dummy data, discharge observations with added white noise as model simulations
te1 <- ReadObs(filename = system.file("demo_model", "Qobs.txt", package = "HYPEtools"))
te1 <- HypeSingleVar(x = array(data = unlist(te1[, -1]) +
runif(n = nrow(te1), min = -.5, max = .5),
dim = c(nrow(te1), ncol(te1) - 1, 1),
dimnames = list(rownames(te1), colnames(te1)[-1])),
datetime = te1$DATE, subid = obsid(te1), hype.var = "cout")
te2 <- ReadObs(filename = system.file("demo_model", "Qobs.txt", package = "HYPEtools"))
te2 <- HypeSingleVar(x = array(data = unlist(te2[, -1]),
dim = c(nrow(te2), ncol(te2) - 1, 1),
dimnames = list(rownames(te2), colnames(te2)[-1])),
datetime = te2$DATE, subid = obsid(te2), hype.var = "rout")
# Nash-Sutcliffe Efficiency
NSE(sim = te1, obs = te2, progbar = FALSE)
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