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#'CST_Analogs
#'
#'@author Carmen Alvarez-Castro, \email{carmen.alvarez-castro@cmcc.it}
#' adapted version of the method of Yiou et al 2013
#'
#'@references Yiou, P., T. Salameh, P. Drobinski, L. Menut, R. Vautard, and M. Vrac, 2013 :
#' Ensemble reconstruction of the atmospheric column from surface pressure using analogues.
#' Clim. Dyn., 41, 1419-1437. \email{pascal.yiou@lsce.ipsl.fr}
#'
#'@description search for days with similar atmospheric conditions based on the large scale slp (or geopotential height)
# and the local scale (precipitation or Temperature)
#'
#'@param month month of the analog day
#' day day of the analog day
#' yr year of the analog day
#' mAnalog month or list of months to search for analogs
#'@import
#'
#'@return list best.corr.time.ana,best.dist.time.ana,selec.dist.time,selec.corr.time
#' list file.dat with a list of days with the format yyyymmdd ordered by best analog with the dist (minima) and corr (maxima)
#' plot preliminary plot of the best analog selected
#' yr1 first year of the total period of study
#' yr2 last year of the total period of study
#' ical number of days per year in the calendar (360,365,366)
#'@example
# Analogs <- function(exp, obs) {
# if (!all(c('member', 'sdate') %in% names(dim(exp)))) {
# stop("Parameter 'exp' must have the dimensions 'member' and 'sdate'.")
# }
#
# if (!all(c('sdate') %in% names(dim(obs)))) {
# stop("Parameter 'obs' must have the dimension 'sdate'.")
# }
#
# if (any(is.na(exp))) {
# warning("Parameter 'exp' contains NA values.")
# }
#
# if (any(is.na(obs))) {
# warning("Parameter 'obs' contains NA values.")
# }
#
# target_dims_obs <- 'sdate'
# if ('member' %in% names(dim(obs))) {
# target_dims_obs <- c('member', target_dims_obs)
# }
#
# Analogs <- Apply(data = list(var_obs = obs, var_exp = exp),
# target_dims = list(target_dims_obs, c('member', 'sdate')),
# fun = .select)$output1
#
# return(Analogs)
# }
time_obsL <- as.Date(c("2005-01-01", "2005-02-01", "2005-03-01",
"2005-04-01", "2005-05-01"))
Analogs <- function(expL, obsL, time_obsL, expVar = NULL, obsVar = NULL,
criteria = "Large_dist",
lon_local = NULL, lat_local = NULL, region = NULL,
nAnalogs = 1, return_list = FALSE) {
# checks
metric <- Select(expL = expL, obsL = obsL, expVar = expVar, obsVar = obsVar,
criteria = criteria, lon_local = lon_local, lat_local = lat_local,
region = region)
best <- Apply(list(metric), target_dims = 'time', fun = BestAnalog,
criteria = criteria, return = return_list)
}
#'@example
#'met <- Select(expL = expL, obsL = obsL)
#'pos <- BestAnalog(met)
BestAnalog <- function(metric, criteria = 'Large_dist', return_list = FALSE,
nAnalogs = 1)
if (criteria == 'Large_dist') {
metric1 <- metric$metric1
pos1 <- metric$pos1
if (return_list == FALSE) {
pos <- pos1[1]
} else {
pos <- pos1[1 : nAnalogs]
}
} else if (criteria== 'Local_dist') {
# pos1 <- c(7, 13, 5, 3, 6, 12, 10, 1, 8, 9, 11, 4, 2, 14)
# pos2 <- c(4, 8, 13, 6, 3, 1, 12, 5, 9, 7, 10, 2, 11, 14)
pos1 <- pos1[1 : nAnalogs]
pos2 <- pos2[1 : nAnalogs]
best <- match(pos1, pos2)
pos <- pos1[as.logical(best)]
pos <- pos[which(!is.na(pos))]
if (return_list == FALSE) {
pos <- pos[1]
}
} else if (criteria == 'Local_cor') {
pos1 <- pos1[1 : nAnalogs]
pos2 <- pos2[1 : nAnalogs]
best <- match(pos1, pos2)
pos <- pos1[as.logical(best)]
pos <- pos[which(!is.na(pos))]
# pos3 <- c(6, 11, 14, 3, 13, 7, 2, 5, 1, 12, 10, 9, 8, 4)
pos3 <- pos3[1 : nAnalogs]
best <- match(pos, pos3)
pos <- pos[order(best, decreasing = F)]
pos <- pos[which(!is.na(pos))]
if (return_list == FALSE) {
pos[1]
}
return(pos)
}
expL <- (1 + 2): (4 * 3 * 2 + 2)
dim(expL) <- c(lat = 4, lon = 3, time = 2)
obsL <- 1 : c(4 * 3 * 5)
dim(obsL) <- c(lat = 4, lon = 3, time = 5)
res = Select(expL, obsL)
expL <- (1 + 2): (8 * 10 * 2 + 2)
dim(expL) <- c(lat = 8, lon = 10, time = 2)
obsL <- 1 : c(8 * 10 * 5)
dim(obsL) <- c(lat = 8, lon = 10, time = 5)
lat_local <- lat <- seq(0, 19, 2.5)
lon_local <- lon <- seq(0, 23, 2.5)
res = Select(expL, obsL, criteria = "Local_dist", lon_local = lon,
lat_local = lat,
region = c(lonmin = 0, lonmax = 5, latmin = 0, latmax = 5 ))
# probar mas ejemplos con diferentes criterios, latitudes, longitudes
Select <- function(expL, obsL, expVar = NULL, obsVar = NULL, criteria = "Large_dist",
lon_local = NULL, lat_local = NULL, region = NULL) {
#check expL
#check obsL
#check obsVar
metric1 <- Apply(list(obsL), target_dims = list(c('lat', 'lon')),
fun = .select, expL, metric = "dist",
output_dims = c('time_exp'))$output1
pos1 <- apply(metric1, 1, order)
metric1 <- apply(metric1, 1, sort)
if (criteria == "Large_dist") {
return(list(metric1 = metric1, pos1 = pos1))
}
if (criteria == "Local_dist" | criteria == "Local_cor") {
obs <- SelBox(obsL, lon = lon_local, lat = lat_local, region = region)$data
exp <- SelBox(expL, lon = lon_local, lat = lat_local, region = region)$data
metric2 <- Apply(list(obs), target_dims = list(c('lat', 'lon')),
fun = .select, exp, metric = "dist")$output1
pos2 <- apply(metric2, 1, order)
metric2 <- apply(metric2, 1, sort)
if (criteria == "Local_dist") {
return(list(metric1 = metric1, metric2 = metric2,
pos1 = pos1, pos2 = pos2))
}
}
if (criteria == "Local_cor") {
obs <- SelBox(obsVar, lon = lon_local, lat = lat_local, region = region)$data
exp <- SelBox(expVar, lon = lon_local, lat = lat_local, region = region)$data
metric3 <- Apply(list(obs), target_dims = list(c('lat', 'lon')),
fun = .select, exp, metric = "cor")$output1
pos3 <- apply(metric3, 1, order, decreasing = TRUE)
metric3 <- apply(metric3, 1, sort)
return(list(metric1 = metric1, metric2 = metric2, metric3 = metric3,
pos1 = pos1, pos2 = pos2, pos3 = pos3))
}
else {
stop("Parameter 'criteria' must to be one of the: 'Large_dist', ",
"'Local_dist','Local_cor'.")
}
}
# data <- 1:(20 * 3 * 2 * 4)
# dim(data) <- c(lon = 20, lat = 3, time = 2, model = 4)
# lon <- seq(2, 40, 2)
# lat <- c(1, 5, 10)
# a <- SelBox(data = data, lon = lon, lat = lat, region = c(2, 20, 1, 5),
# londim = 1, latdim = 2, mask = NULL)
# str(a)
#'@example
exp <- (1 + 2): (4 * 3 + 2)
dim(exp) <- c(lat = 4, lon = 3)
obs <- 1 : c(5 * 4 * 3)
dim(obs) <- c(time = 5, lat = 4, lon = 3)
res <- .select(exp, obs)
res
res <- .select(exp, obs, metric = 'cor')
dim(res)
.select <- function(exp, obs, metric = "dist") {
if (metric == "dist") {
#metric <- sum((obs - exp) ^ 2)
#metric <- apply(obs, "time", function(x) {sum((x - exp) ^ 2)})
result <- Apply(list(obs), target_dims = list(c('lat', 'lon')),
fun = function(x) {sum((x - exp) ^ 2)})$output1
} else if (metric == "cor") {
result <- Apply(list(obs), target_dims = list(c('lat', 'lon')),
fun = function(x) {cor(as.vector(x), as.vector(exp))})$output1
}
result
}