Get yearly vegetation phenological metrics of a curve fitting method
get_pheno(x, ...)
# S3 method for class 'rfit'
get_pheno(x, TRS = c(0.2, 0.5), asymmetric = TRUE, ...)
# S3 method for class 'list'
get_pheno(
x,
method,
TRS = c(0.2, 0.5, 0.6),
analytical = FALSE,
smoothed.spline = FALSE,
IsPlot = FALSE,
show.title = TRUE,
...
)
# S3 method for class 'fFITs'
get_pheno(
x,
method,
TRS = c(0.2, 0.5),
analytical = FALSE,
smoothed.spline = FALSE,
IsPlot = FALSE,
title.left = "",
show.PhenoName = TRUE,
...
)
One of:
rfit
(rought fitting object), returned by brks2rfit()
.
fFITs
(fine fitting object), return by multiple curve fitting methods by curvefit()
for
a growing season.
list of fFITs()
object, for multiple growing seasons.
ignored.
Threshold for PhenoTrs
.
If true, background value in spring season and autumn season is regarded as different.
Which fine curve fitting method to be extracted?
If true, numDeriv
package grad
and hess
will be used; if false, D1
and D2
will be used.
Whether apply smooth.spline
first?
Boolean. Whether to plot figure?
Whether to show the name of fine curve fitting method in top title?
String of growing season flag.
Whether to show phenological methods names in the top panel?
fFITs
object returned by curvefits()
List of every year phenology metrics
library(phenofit)
# simulate vegetation time-series
FUN = doubleLog.Beck
par = c( mn = 0.1, mx = 0.7, sos = 50, rsp = 0.1, eos = 250, rau = 0.1)
t <- seq(1, 365, 8)
tout <- seq(1, 365, 1)
y <- FUN(par, t)
methods <- c("AG", "Beck", "Elmore", "Gu", "Zhang") # "Klos" too slow
fit <- curvefit(y, t, tout, methods) # `fFITs` (fine-fitting) object
fits <- list(`2001` = fit, `2002` = fit) # multiple years
l_param <- get_param(fits)
d_GOF <- get_GOF(fits)
d_fitting <- get_fitting(fits)
#> Warning: Unknown argument 'id' has been passed.
#> Warning: Unknown argument 'id' has been passed.
l_pheno <- get_pheno(fits, "AG", IsPlot=TRUE)