sarp.snowprofile.alignment (version 1.0.2)

resampleSP: Resample snowprofile

Description

Resample an individual snow profile onto a new depth-grid (i.e., height-grid).

Usage

resampleSP(x, h = 0.5, n = NULL)

Arguments

x

snowprofile (or snowprofileLayers) object

h

Sampling rate (i.e. constant depth increment) in centimeters, if given as scalar (default is 0.5 cm). Layers smaller than the scalar h will not be resolved in the resampled profile. Can also be a vector specifying the desired height grid of the resampled profile (useful for non-constant increments). But, be WARNED, that a meaningless grid will produce colorful but senseless output!

n

Number of layers in resampled profile (optional). A given n will overrule a conflicting h!

Value

resampled snowprofile with the same metadata as x, but resampled "layers". Note that only the following layer properties will be resampled: height, hardness, gtype, ddate. If input was a snowprofileLayers object, the output will be, too.

Details

This routine alters how the layer information of snow profiles is stored without changing how the profiles appear. Note, however, that only layer properties that are constant within the individual layers will be resampled: i.e., height, hardness, gtype, ddate will be resampled. However, temperature, for example, will not be resampled, because it is not constant within layers.

See Also

resampleSPpairs, mergeIdentLayers

Examples

# NOT RUN {
## (1) constant sampling rate of 1 cm:
profileResampled <- resampleSP(SPpairs$A_modeled, h = 1.0)

## compare profile summary before and after resampling:
summary(SPpairs$A_modeled)[, c("hs", "nLayers")]
summary(profileResampled)[, c("hs", "nLayers", "changes")]
head(profileResampled$layers)

## compare profile plots before and after resampling (i.e., appear identical!)
opar <- par(no.readonly=TRUE)
par(mfrow = c(1, 2))
plot(SPpairs$A_modeled, main = "original", ylab = "Snow height")
plot(profileResampled, main = "resampled", ylab = "Snow height")
par(opar)

## (2) resample to 150 layers:
profileResampled <- resampleSP(SPpairs$A_manual, n = 150)
summary(profileResampled)[, c("hs", "nLayers", "changes")]
head(profileResampled$layers)


## (3) resample onto arbitrarily specified grid
## (issues a warning when the new-grid HS deviates too much from the original HS)
irregularGrid <- c(2 + cumsum(c(0, c(10, 15, 5, 1, 3, 30, 50))), 120)
profileResampled <- resampleSP(SPpairs$A_manual, h = irregularGrid)

# }