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# File seasonalfunction.R
# Part of the hydroTSM R package, https://github.com/hzambran/hydroTSM ;
# https://CRAN.R-project.org/package=hydroTSM
# Copyright 2009-2017 Mauricio Zambrano-Bigiarini
# Distributed under GPL 2 or later
################################################################################
# seasonalfunction #
################################################################################
# Generic function for applying any R function to summarize the seasonal values#
# of a time series #
################################################################################
# Author : Mauricio Zambrano-Bigiarini #
################################################################################
# Started: 11-Sep-2009 #
################################################################################
# 'x ' : variable of type 'zoo' or 'data.frame'
# 'FUN' : Function that will be applied to ALL the values in 'x' belonging to each one of the 4 weather seasons
# (e.g., Fun can be some of c('mean', 'max', 'min', 'sd'))
# 'na.rm' : Logical. Should missing values be removed?
# TRUE : the monthly values are computed considering only those values in 'x' different from NA
# FALSE: if there is AT LEAST one NA within a month, the FUN and monthly values are NA
seasonalfunction <- function(x, ...) UseMethod("seasonalfunction")
################################################################################
# Author : Mauricio Zambrano-Bigiarini #
################################################################################
# Started: 11-Sep-2009 #
# Updates: 08-Aug-2011 #
# 21-May-2013 #
################################################################################
seasonalfunction.default <- function(x, FUN, na.rm=TRUE, type="default",...) {
# Checking that 'x' is a zoo object
if ( !is.zoo(x) ) stop("Invalid argument: 'class(x)' must be in c('zoo', 'xts')")
seasonalfunction.zoo(x=x, FUN=FUN, na.rm=na.rm, type=type, ...)
} # 'seasonalfunction.default' end
################################################################################
# Author : Mauricio Zambrano-Bigiarini #
################################################################################
# Started: 08-Aug-2011 #
# Updates: 08-Aug-2011 #
# 03-Abr-2013 #
# 29-Nov-2015 #
################################################################################
seasonalfunction.zoo <- function(x, FUN, na.rm=TRUE, type="default", ...) {
# Checking that the user provied a valid argument for 'FUN'
if (missing(FUN)) stop("Missing argument: 'FUN' must be provided")
# Checking the user provide a valid value for 'x'
if (is.na(match(sfreq(x), c("daily", "monthly"))))
stop(paste("Invalid argument: 'x' is not a daily or mothly ts, it is a ", sfreq(x), " ts", sep="") )
# Checking that the user provied a valid value for 'type'
valid.types <- c("default", "FrenchPolynesia")
if (length(which(!is.na(match(type, valid.types )))) <= 0)
stop("Invalid argument: 'type' must be in c('default', 'FrenchPolynesia')")
# Time index of 'x'
if (type=="default") {
seasons.lab <- c("DJF", "MAM", "JJA", "SON")
} else if (type=="FrenchPolynesia") {
seasons.lab <- c("DJFM", "AM", "JJAS", "ON")
} # ELSE end
dates <- time(x)
seasons <- factor( time2season( dates, type=type ), levels=seasons.lab )
# zoo::aggregate
s <- aggregate(x, by= seasons, FUN=FUN, na.rm= na.rm, ...)
# Replacing the NaNs by 'NA.
# NaN's are obtained when using the FUN=mean with complete NA values
nan.index <- which(is.nan(s))
if ( length(nan.index) > 0 ) s[ nan.index] <- NA
# Replacing all the Inf and -Inf by NA's
# min(NA:NA, na.rm=TRUE) == Inf ; max(NA:NA, na.rm=TRUE) == -Inf
inf.index <- which(is.infinite(s))
if ( length(inf.index) > 0 ) s[inf.index] <- NA
# Giving meaningful names to the output
if ( (is.matrix(x)) | (is.data.frame(x)) ) {
# Getting the name of the actual seasons in 's'
cnames <- time(s)
# Transformation needed in order to change the default names of the result
s <- coredata(s)
s <- t(s) # For having the season' names as column names
# Giving the name of the seasons
colnames(s) <- cnames
} # IF end
return(s)
} # 'seasonalfunction.zoo' end
################################################################################
# Author : Mauricio Zambrano-Bigiarini #
################################################################################
# Started: 11-Sep-2009 #
# Updates: 08-Aug-2011 #
# 03-Jun-2013 #
################################################################################
# 'dates' : "numeric", "factor", "Date" indicating how to obtain the
# dates for correponding to the 'sname' station
# If 'dates' is a number, it indicates the index of the column in
# 'x' that stores the dates
# If 'dates' is a factor, it have to be converted into 'Date' class,
# using the date format specified by 'date.fmt'
# If 'dates' is already of Date class, the following line verifies that
# the number of days in 'dates' be equal to the number of element in the
# time series corresponding to the 'st.name' station
# 'date.fmt': format in which the dates are stored in 'dates'.
# ONLY required when class(dates)=="factor" or "numeric"
# 'out.type': string that define the desired type of output. Possible values are
# -) "data.frame": a data.frame, with as many columns as stations
# are included in 'x', and an additional column indicating the Year
# -) "db" : a data.frame, with 3 colums will be produced.
# The first column will store the Year,
# The second column will store the ID of the station,
# The third column will contain the seasonal
# value corresponding to that year and that station.
# 'verbose' : logical; if TRUE, progress messages are printed
seasonalfunction.data.frame <- function(x, FUN, na.rm=TRUE, type="default",
dates=1, date.fmt="%Y-%m-%d",
out.type="data.frame",
verbose=TRUE,...) {
# Checking that the user provied a valid argument for 'out.type'
if (is.na(match( out.type, c("data.frame", "db") ) ) )
stop("Invalid argument: 'out.type' must be in c('data.frame', 'db'")
# Checking that the user provied a valid argument for 'FUN'
if (missing(FUN))
stop("Missing argument: 'FUN' must be provided")
# Checking that the user provied a valid value for 'type'
valid.types <- c("default", "FrenchPolynesia")
if (length(which(!is.na(match(type, valid.types )))) <= 0)
stop("Invalid argument: 'type' must be in c('default', 'FrenchPolynesia')")
# Defining 'seasons.lab'
if (type=="default") {
seasons.lab <- c("DJF", "MAM", "JJA", "SON")
} else if (type=="FrenchPolynesia") {
seasons.lab <- c("DJFM", "AM", "JJAS", "ON")
} # ELSE end
# Checking that the user provied a valid argument for 'dates'
if (is.na(match(class(dates), c("numeric", "factor", "Date"))))
stop("Invalid argument: 'dates' must be of class 'numeric', 'factor', 'Date'")
# If 'dates' is a number, it indicates the index of the column of 'x' that stores the dates
# The column with dates is then substracted form 'x' for easening the further computations
if ( class(dates) == "numeric" ) {
tmp <- dates
dates <- as.Date(x[, dates], format= date.fmt)
x <- x[-tmp]
} # IF end
# If 'dates' is a factor, it have to be converted into 'Date' class,
# using the date format specified by 'date.fmt'
if ( class(dates) == "factor" ) dates <- as.Date(dates, format= date.fmt)
# If 'dates' is already of Date class, the following line verifies that
# the number of days in 'dates' be equal to the number of element in the
# time series corresponding to the 'st.name' station
if ( ( class(dates) == "Date") & (length(dates) != nrow(x) ) )
stop("Invalid argument: 'length(dates)' must be equal to 'nrow(x)'")
# Transforming 'x' into zoo
x <- zoo(x, dates)
##############################################################################
if (out.type == "data.frame") {
z <- seasonalfunction.zoo(x=x, FUN=FUN, na.rm=na.rm, type=type, ...)
snames <- colnames(x)
rownames(z) <- snames
colnames(z) <- seasons.lab
} else if (out.type == "db") {
if (verbose) message("[Starting the computations...]")
# Amount of stations in 'x'
nstations <- ncol(x)
# ID of all the stations in 'x'
snames <- colnames(x)
# Computing the Starting and Ending Year of the analysis
Starting.Year <- as.numeric(format(range(dates)[1], "%Y"))
Ending.Year <- as.numeric(format(range(dates)[2], "%Y"))
# Amount of Years belonging to the desired period
nyears <- Ending.Year - Starting.Year + 1
# Amount of months belonging to the desired period
nmonths <- 12*nyears
# Creating a vector with the names of the field that will be used for storing the results
field.names <- c("StationID", "Season", "Value" )
# Creating the data.frame that will store the computed averages for each subcatchment
z <- as.data.frame(matrix(data = NA, nrow = 4*nstations, ncol = 3,
byrow = TRUE, dimnames = NULL) )
for (j in 1:nstations) {
if (verbose) message( paste("[ Station: ", format(snames[j], width=10, justify="left"),
" : ", format(j, width=3, justify="left"), "/",
nstations, " => ",
format(round(100*j/nstations,2), width=6, justify="left"),
"% ]", sep="") )
# Computing the annual values
tmp <- seasonalfunction.default(x= tmp, FUN=FUN, na.rm=na.rm, type=type)
# Putting the annual/monthly values in the output data.frame
# The first column of 'x' corresponds to the Year
row.ini <- (j-1)*4 + 1
row.fin <- j*4
z[row.ini:row.fin, 1] <- snames[j] # it is automatically repeted 4 times
z[row.ini:row.fin, 2] <- seasons.lab
z[row.ini:row.fin, 3] <- tmp
} # FOR end
colnames(z) <- field.names
} # IF end
return( z )
} #'seasonalfunction.data.frame' END
################################################################################
# Author : Mauricio Zambrano-Bigiarini #
################################################################################
# Started: 11-Sep-2009 #
# Updates: 08-Aug-2011 #
################################################################################
seasonalfunction.matrix <- function(x, FUN, na.rm=TRUE, type="default",
dates=1, date.fmt="%Y-%m-%d",
out.type="data.frame",
verbose=TRUE,...) {
x <- as.data.frame(x)
#NextMethod("daily2annual")
seasonalfunction.data.frame(x=x, FUN=FUN, na.rm=na.rm, type=type,
dates=dates, date.fmt=date.fmt,
out.type=out.type,
verbose=verbose,...)
} # 'seasonalfunction.matrix ' END
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