refactor(CreateInputsCrit_Lavenne): rename CreateInputsCrit_DeLavenne to CreateInputsCrit_Lavenne

Refs #111

DESCRIPTION

@@ -38,3 +38,4 @@ BugReports: https://gitlab.irstea.fr/HYCAR-Hydro/airgr/-/issues
 NeedsCompilation: yes
 Encoding: UTF-8
 VignetteBuilder: knitr
+RoxygenNote: 7.1.1

NAMESPACE

@@ -27,7 +27,7 @@ export(CreateCalibOptions)
 export(CreateErrorCrit_GAPX)
 export(CreateIniStates)
 export(CreateInputsCrit)
-export(CreateInputsCrit_DeLavenne)
+export(CreateInputsCrit_Lavenne)
 export(CreateInputsModel)
 export(CreateRunOptions)
 export(DataAltiExtrapolation_Valery)

R/CreateInputsCrit_DeLavenne.R → R/CreateInputsCrit_Lavenne.R

-CreateInputsCrit_DeLavenne <- function(FUN_CRIT = ErrorCrit_KGE,
+CreateInputsCrit_Lavenne <- function(FUN_CRIT = ErrorCrit_KGE,
                                       InputsModel,
                                       RunOptions,
                                       Obs,

man/CreateInputsCrit_DeLavenne.Rd → man/CreateInputsCrit_Lavenne.Rd

 \encoding{UTF-8}
 
 
-\name{CreateInputsCrit_DeLavenne}
-\alias{CreateInputsCrit_DeLavenne}
+\name{CreateInputsCrit_Lavenne}
+\alias{CreateInputsCrit_Lavenne}
 
 
 \title{Creation of the InputsCrit object for De Lavenne Criterion}
@@ -14,7 +14,7 @@ Creation of the \code{InputsCrit} object required to the \code{\link{ErrorCrit}}
 
 
 \usage{
-CreateInputsCrit_DeLavenne(FUN_CRIT = ErrorCrit_KGE,
+CreateInputsCrit_Lavenne(FUN_CRIT = ErrorCrit_KGE,
                            InputsModel,
                            RunOptions,
                            Obs,
@@ -55,7 +55,7 @@ CreateInputsCrit_DeLavenne(FUN_CRIT = ErrorCrit_KGE,
 
 \value{
 
-\code{CreateInputsCrit_DeLavenne} returns an object of class \emph{Compo} that is a list of lists such as the one described in \code{\link{CreateInputsCrit}}.
+\code{CreateInputsCrit_Lavenne} returns an object of class \emph{Compo} that is a list of lists such as the one described in \code{\link{CreateInputsCrit}}.
 
 Items \code{Weights} of the criteria are respectively equal to \code{k} and \code{k * max(0,AprCrit)}.
 
@@ -70,7 +70,7 @@ The parameters \code{FUN_CRIT}, \code{Obs}, \code{VarObs}, \code{BoolCrit}, \cod
 \code{\link{ErrorCrit_RMSE}} cannot be used in a composite criterion since it is not a unitless value.
 
 
-\code{CreateInputsCrit_DeLavenne} creates a composed criterion in respect with Equations 1 and 2 of de Lavenne et al. (2019).
+\code{CreateInputsCrit_Lavenne} creates a composed criterion in respect with Equations 1 and 2 of de Lavenne et al. (2019).
 }
 
 
@@ -101,7 +101,7 @@ OutputsModel <- RunModel_GR4J(InputsModel = InputsModel,
 AprParamR <- c(X1 = 157, X2 = 0.8, X3 = 100, X4 = 1.5)
 
 ## Single efficiency criterion: GAPX with a priori parameters
-IC_DL <- CreateInputsCrit_DeLavenne(InputsModel = InputsModel,
+IC_DL <- CreateInputsCrit_Lavenne(InputsModel = InputsModel,
                                     RunOptions = RunOptions,
                                     Obs = BasinObs$Qmm[Ind_Run],
                                     AprParamR = AprParamR)

tests/testthat/test-CreateInputsCrit_DeLavenne.R → tests/testthat/test-CreateInputsCrit_Lavenne.R

-context("CreateInputsCrit_DeLavenne")
+context("CreateInputsCrit_Lavenne")
 
 data(L0123001)
 InputsModel <- CreateInputsModel(FUN_MOD = RunModel_GR4J, DatesR = BasinObs$DatesR,
@@ -14,7 +14,7 @@ OutputsModel <- RunModel_GR4J(InputsModel = InputsModel,
                               RunOptions = RunOptions, Param = Param)
 
 k <- 0.15
-IC_DL <- CreateInputsCrit_DeLavenne(FUN_CRIT = ErrorCrit_KGE,
+IC_DL <- CreateInputsCrit_Lavenne(FUN_CRIT = ErrorCrit_KGE,
                                 InputsModel = InputsModel,
                                 RunOptions = RunOptions,
                                 Obs = BasinObs$Qmm[Ind_Run],
@@ -40,7 +40,7 @@ test_that("should return KGE*(1-k)+k with parameters matching a priori parameter
 
 test_that("should return proper error if mismatch number of parameters", {
   expect_error(
-    CreateInputsCrit_DeLavenne(FUN_CRIT = ErrorCrit_KGE,
+    CreateInputsCrit_Lavenne(FUN_CRIT = ErrorCrit_KGE,
                                InputsModel = InputsModel,
                                RunOptions = RunOptions,
                                Obs = BasinObs$Qmm[Ind_Run],

vignettes/V05_sd_model.Rmd

@@ -201,10 +201,10 @@ ParamDownTheo <- c(Velocity, OutputsCalibUp$ParamFinalR)
 The De Lavenne criterion is initialised with the a priori parameter set and the value of the KGE of the upstream basin.
 
 ```{r}
-IC_DeLavenne <- CreateInputsCrit_DeLavenne(InputsModel = InputsModelDown2, 
+IC_Lavenne <- CreateInputsCrit_Lavenne(InputsModel = InputsModelDown2,
                                     RunOptions = RunOptionsDown,
                                     Obs = QObsDown[Ind_Run],
-                                    AprParamR = ParamDownTheo, 
+                                    AprParamR = ParamDownTheo,
                                     AprCrit = OutputsCalibUp$CritFinal)
 ```
 
@@ -213,7 +213,7 @@ The De Lavenne criterion is used instead of the KGE for calibration with regular
 ```{r}
 OutputsCalibDown3 <- Calibration_Michel(InputsModel = InputsModelDown2,
                                         RunOptions = RunOptionsDown,
-                                        InputsCrit = IC_DeLavenne,
+                                        InputsCrit = IC_Lavenne,
                                         CalibOptions = CalibOptionsDown,
                                         FUN_MOD = RunModel_GR4J)
 ```
@@ -238,7 +238,7 @@ Both calibrations overestimate this parameter:
 ```{r}
 mVelocity <- matrix(c(Velocity,
                       OutputsCalibDown1$ParamFinalR[1],
-                      OutputsCalibDown2$ParamFinalR[1], 
+                      OutputsCalibDown2$ParamFinalR[1],
                       OutputsCalibDown3$ParamFinalR[1]),
                     ncol = 1,
                     dimnames = list(c("theoretical",
@@ -251,7 +251,7 @@ knitr::kable(mVelocity)
 
 ## Value of the performance criteria with theoretical calibration
 
-Theoretically, the parameters of the downstream GR4J model should be the same as the upstream one with the velocity as extra parameter : 
+Theoretically, the parameters of the downstream GR4J model should be the same as the upstream one with the velocity as extra parameter :
 
 ```{r}
 OutputsModelDownTheo <- RunModel(InputsModel = InputsModelDown2,