diff --git a/DESCRIPTION b/DESCRIPTION
index a6ceb5eb4245b0f6fcbb6b627bb43c3e27ff7d73..bb56081c41492df3752ffdbfd7ff6cf2a51a4e27 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
Package: airGR
Type: Package
Title: Suite of GR Hydrological Models for Precipitation-Runoff Modelling
-Version: 1.6.8.19
+Version: 1.6.8.20
Date: 2020-12-01
Authors@R: c(
person("Laurent", "Coron", role = c("aut", "trl"), comment = c(ORCID = "0000-0002-1503-6204")),
diff --git a/NAMESPACE b/NAMESPACE
index 7119024b0009bfe35e663a2b7907c5cf1d112a5a..698087fb5d45f0f0e19edf8f7c31168af3373ba7 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -65,6 +65,7 @@ export(TransfoParam_Lag)
export(plot)
export(plot.OutputsModel)
export(.ErrorCrit)
+export(.AggregConvertFunTable)
diff --git a/NEWS.md b/NEWS.md
index 83b55d04b2bd5444030795f48012588db2eced46..84a2383dae2cea6b48911a22aae1e975de65f2ee 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -2,12 +2,13 @@
-### 1.6.8.10 Release Notes (2020-11-21)
+### 1.6.8.20 Release Notes (2020-12-01)
#### New features
- Added <code>SeriesAggreg</code> S3 method with functions for `InputsModel`, `OutputsModel`, `list`, `data.frame` class objects. This new version of the <code>SeriesAggreg()</code> function allows to compute regimes.
-- Added<code>.AggregConvertFun()</code> private function in order to choose automatically the <code>ConvertFun</code> to apply on each element of <code>InputsModel</code> and <code>OutputsModel</code> objects.
+- Added <code>getAggregConvertFun()</code> private function in order to choose automatically the <code>ConvertFun</code> to apply on each element of objects used in <code>SeriesAggreg</code>.
+- Added <code>.AggregConvertFunTable</code> data.frame that allows the user to see what names of list items or data.frame column names are guessed and eventually customise this correspondence table.
#### Bug fixes
diff --git a/R/SeriesAggreg.data.frame.R b/R/SeriesAggreg.data.frame.R
index 502a2ba7a7b736f70b93021885d58148a64e4bd9..1b4c102035a213f18dc24f8c4b19d71fd4869192 100644
--- a/R/SeriesAggreg.data.frame.R
+++ b/R/SeriesAggreg.data.frame.R
@@ -1,6 +1,6 @@
SeriesAggreg.data.frame <- function(TabSeries,
Format,
- ConvertFun = .AggregConvertFun(names(TabSeries)[-1]),
+ ConvertFun = getAggregConvertFun(names(TabSeries)[-1]),
TimeFormat = NULL,
NewTimeFormat = NULL,
YearFirstMonth = 1,
diff --git a/R/SeriesAggreg.list.R b/R/SeriesAggreg.list.R
index 932840e73cc09912dc8bd9e84e6f5e4cd25bfa9e..806736634f1206c95a14370eb3ed034eb8ad7f71 100644
--- a/R/SeriesAggreg.list.R
+++ b/R/SeriesAggreg.list.R
@@ -68,7 +68,7 @@ SeriesAggreg.list <- function(TabSeries,
}
dfOut <- NULL
if (length(cols)) {
- ConvertFun2 <- .AggregConvertFun(names(cols))
+ ConvertFun2 <- getAggregConvertFun(names(cols))
if (is.null(recursive)) {
if (missing(ConvertFun)) {
stop("'ConvertFun' argument should provided if 'recursive = NULL'")
@@ -104,7 +104,7 @@ SeriesAggreg.list <- function(TabSeries,
listCols <- listCols[setdiff(names(listCols), names(dfCols))]
if (length(listCols) > 0) {
# Check for predefined ConvertFun for all sub-elements
- ConvertFun <- .AggregConvertFun(names(listCols))
+ ConvertFun <- getAggregConvertFun(names(listCols))
# Run SeriesAggreg for each embedded list
listRes <-
lapply(names(listCols),
@@ -143,7 +143,7 @@ SeriesAggreg.list <- function(TabSeries,
"), it will be ignored in the aggregation"
)
} else {
- ConvertFun <- rep(.AggregConvertFun(key), ncol(m))
+ ConvertFun <- rep(getAggregConvertFun(key), ncol(m))
res[[key]] <- SeriesAggreg(data.frame(DatesR, m),
Format = Format,
ConvertFun = ConvertFun)
diff --git a/R/Utils.R b/R/Utils.R
index 23eae05ef30aeb65e19164ce8ca7b3c9f62d475d..d1cde5eb0dc10d9f3f686ddf03dab9c24671d850 100644
--- a/R/Utils.R
+++ b/R/Utils.R
@@ -11,32 +11,6 @@
# }
# }
-
-
-## =================================================================================
-## function to manage Fortran outputs
-## =================================================================================
-
-.AggregConvertFun <- function(Outputs) {
- Table <- rbind(
- data.frame(ConvertFun = "mean",
- Outputs = c("Prod","Rout","Exp","SnowPack","ThermalState",
- "Gratio","Temp","Gthreshold","Glocalmax","LayerTempMean", "T")),
- data.frame(ConvertFun = "sum",
- Outputs = c("zzz","PotEvap","Precip","Pn","Ps","AE","Perc","PR","Q9",
- "Q1","Exch","AExch1","AExch2","AExch","QR","QRExp",
- "QD","Qsim","Pliq","Psol","PotMelt","Melt","PliqAndMelt",
- "LayerPrecip","LayerFracSolidPrecip", "Qmm", "Qls", "E", "P", "Qupstream"))
- )
- res <- sapply(Outputs, function(iOutputs) {
- iRes <- Table$ConvertFun[Table$Outputs == iOutputs]
- iRes <- ifelse(any(is.na(iRes)), NA, iRes)
- })
- return(res)
-}
-
-
-
## =================================================================================
## function to manage Fortran outputs
## =================================================================================
diff --git a/R/UtilsSeriesAggreg.R b/R/UtilsSeriesAggreg.R
index 397cfd076df5bdf0df5e218c18230938c4582b94..de72c97487b10ba15adfb74aaf36e0e08c15a64f 100644
--- a/R/UtilsSeriesAggreg.R
+++ b/R/UtilsSeriesAggreg.R
@@ -40,4 +40,24 @@ getSeriesAggregClass <- function(Format) {
m = "monthly",
Y = "yearly"
)
-}
\ No newline at end of file
+}
+
+.AggregConvertFunTable <- rbind(
+ data.frame(ConvertFun = "mean",
+ Outputs = c("Prod","Rout","Exp","SnowPack","ThermalState",
+ "Gratio","Temp","Gthreshold","Glocalmax","LayerTempMean", "T")),
+ data.frame(ConvertFun = "sum",
+ Outputs = c("zzz","PotEvap","Precip","Pn","Ps","AE","Perc","PR","Q9",
+ "Q1","Exch","AExch1","AExch2","AExch","QR","QRExp",
+ "QD","Qsim","Pliq","Psol","PotMelt","Melt","PliqAndMelt",
+ "LayerPrecip","LayerFracSolidPrecip", "Qmm", "Qls", "E", "P", "Qupstream"))
+ )
+
+getAggregConvertFun <- function(Outputs) {
+
+ res <- sapply(Outputs, function(iOutputs) {
+ iRes <- .AggregConvertFunTable$ConvertFun[.AggregConvertFunTable$Outputs == iOutputs]
+ iRes <- ifelse(any(is.na(iRes)), NA, iRes)
+ })
+ return(res)
+}
diff --git a/man/SeriesAggreg.Rd b/man/SeriesAggreg.Rd
index 156677816f5aece3523554bffe631d1ac7b20b7e..ff8f33da4fe35d00a6d1b4305e705981c4aa0184 100644
--- a/man/SeriesAggreg.Rd
+++ b/man/SeriesAggreg.Rd
@@ -24,13 +24,16 @@ Warning: on the aggregated outputs, the dates correspond to the beginning of the
\code{\link{SeriesAggreg.InputsModel}} and \code{\link{SeriesAggreg.OutputsModel}}
call \code{\link{SeriesAggreg.list}} which itself calls \code{\link{SeriesAggreg.data.frame}}.
So, all arguments passed to any \code{\link{SeriesAggreg}} method will be passed to \code{\link{SeriesAggreg.data.frame}}.
+
+ If \code{ConvertFun} is not provided, the operation to perform is guessed from the name of the list items or column
+ name dataframe in respect with the matching table \code{.AggregConvertFunTable}.
}
\usage{
\method{SeriesAggreg}{data.frame}(TabSeries,
Format,
- ConvertFun = .AggregConvertFun(names(TabSeries)[-1]),
+ ConvertFun = getAggregConvertFun(names(TabSeries)[-1]),
TimeFormat = NULL,
NewTimeFormat = NULL,
YearFirstMonth = 1,
@@ -61,7 +64,7 @@ Warning: on the aggregated outputs, the dates correspond to the beginning of the
\item{NewTimeFormat}{(deprecated) [character] output time step format (i.e. \code{"hourly"}, \code{"daily"}, \code{"monthly"} or \code{"yearly"}). Use the \code{TabSeries} argument instead}
-\item{ConvertFun}{[character] names of aggregation functions (e.g. for P[mm], T[degC], Q[mm]: \code{ConvertFun = c("sum", "mean", "sum"})) (Default: use the name of the column or "mean" for regime calculation)}
+\item{ConvertFun}{[character] names of aggregation functions (e.g. for P[mm], T[degC], Q[mm]: \code{ConvertFun = c("sum", "mean", "sum"})) (Default: use the name of the column (See details) or "mean" for regime calculation)}
\item{YearFirstMonth}{(optional) [numeric] integer used when \code{Format = "\%Y"} to set when the starting month of the year (e.g. 01 for calendar year or 09 for hydrological year starting in September)}