v1.0.9.26 many typo revisions in documentation

DESCRIPTION

 Package: airGR
 Type: Package
 Title: Suite of GR Hydrological Models for Precipitation-Runoff Modelling
-Version: 1.0.9.25
+Version: 1.0.9.26
 Date: 2017-08-18
 Authors@R: c(
   person("Laurent", "Coron", role = c("aut", "trl")),

NEWS.html

@@ -121,7 +121,7 @@ $(document).ready(function () {
 <div id="release-notes-2017-08-18" class="section level3">
-<h3>1.0.9.25 Release Notes (2017-08-18)</h3>
+<h3>1.0.9.26 Release Notes (2017-08-18)</h3>
 <div id="new-features" class="section level4">
 <h4>New features</h4>
 <ul>

NEWS.md

@@ -3,7 +3,7 @@
 
 
 
-### 1.0.9.25 Release Notes (2017-08-18) 
+### 1.0.9.26 Release Notes (2017-08-18) 
 
 #### New features
 

NEWS.rmd

@@ -8,7 +8,7 @@ output:
 
 
 
-### 1.0.9.25 Release Notes (2017-08-18) 
+### 1.0.9.26 Release Notes (2017-08-18) 
 
 #### New features
 

man/CreateRunOptions.Rd

@@ -87,7 +87,7 @@ The actual length of this warm-up might be shorter depending on data availabilit
 \itemize{
 \item \code{IndPeriod_WarmUp} can be used to specify the indices of the warm-up period (within the time series prepared in InputsModel). \cr
 - remark 1:	for most common cases, indices corresponding to one or several years preceding \code{IndPeriod_Run} are used (e.g. \code{IndPeriod_WarmUp = 1000:1365} and \code{IndPeriod_Run = 1366:5000)}. \cr
-However, it is also possible to perform a long-term initialisation if other indices than the warm-up ones are set in \code{IndPeriod_WarmUp} (e.g. \code{IndPeriod_WarmUp <- c(1:5000, 1:5000, 1:5000, 1000:1365)}). \cr
+However, it is also possible to perform a long-term initialisation if other indices than the warm-up ones are set in \code{IndPeriod_WarmUp} (e.g. \code{IndPeriod_WarmUp = c(1:5000, 1:5000, 1:5000, 1000:1365)}). \cr
 - remark 2:	it is also possible to completely disable the warm-up period when using \code{IndPeriod_WarmUp = 0L}. This is necessary if you want \code{IniStates} and / or \code{IniResLevels} to be the actual initial values of the model variables from your simulation (e.g. to perform a forecast form a given initial state). 
 
 \item \code{IniStates} and \code{IniResLevels} can be used to specify the initial model states. \cr
@@ -95,7 +95,7 @@ However, it is also possible to perform a long-term initialisation if other indi
 - remark 2:	if \code{IniStates} is used, two possibilities are offered:
    - \code{IniStates} can be set to the \code{$StateEnd} output of a previous \code{RunModel} call, as \code{$StateEnd} already respects the correct format; \cr
    -  \code{IniStates} can be created with the \code{\link{CreateIniStates}} function.
-- remark 3:	in addition to \code{IniStates}, \code{IniResLevels} allows to set the filling rate of the production and routing stores for the GR models. For instance for GR4J and , GR5J: \code{IniResLevels <- c(0.3, 0.5)} should be used to obtain initial fillings of 30\% and 50\% for the production and routing stores, respectively. For GR6J, \code{IniResLevels <- c(0.3, 0.5, 0)} shold be use to obtain initial fillings of 30\% and 50\% for the production, routing stores and 0 mm for the exponential store, respectively. \code{IniResLevels} is optional and can only be used if \code{IniStates} is also defined (the state values corresponding to these two other stores in \code{IniStates} are not used in such case). \cr \cr
+- remark 3:	in addition to \code{IniStates}, \code{IniResLevels} allows to set the filling rate of the production and routing stores for the GR models. For instance for GR4J and , GR5J: \code{IniResLevels = c(0.3, 0.5)} should be used to obtain initial fillings of 30 \% and 50 \% for the production and routing stores, respectively. For GR6J, \code{IniResLevels = c(0.3, 0.5, 0)} shold be use to obtain initial fillings of 30 \% and 50 \% for the production, routing stores and 0 mm for the exponential store, respectively. \code{IniResLevels} is optional and can only be used if \code{IniStates} is also defined (the state values corresponding to these two other stores in \code{IniStates} are not used in such case). \cr \cr
 }
 }
 

man/DataAltiExtrapolation_Valery.Rd

@@ -55,11 +55,11 @@ Function which extrapolates the precipitation and air temperature series for dif
 
 
 \details{
-Elevation layers of equal surface are created the 101 elevation quantiles (\emph{HypsoData}) 
-and the number requested elevation layers (\emph{NLayers}). \cr
+Elevation layers of equal surface are created the 101 elevation quantiles (\code{HypsoData}) 
+and the number requested elevation layers (\code{NLayers}). \cr
 Forcing data (precipitation and air temperature) are extrapolated using gradients from Valery (2010).
-(e.g. gradP=0.0004 [m-1] for France and gradT=0.434 [°C/100m] for January, 1st). \cr
-This function is used by the \emph{CreateInputsModel} function.
+(e.g. gradP = 0.0004 [m-1] for France and gradT = 0.434 [°C/100m] for January, 1st). \cr
+This function is used by the \code{CreateInputsModel} function.
 }
 
 

man/ErrorCrit_KGE.Rd

@@ -33,7 +33,7 @@ ErrorCrit_KGE(InputsCrit, OutputsModel, warnings = TRUE, verbose = TRUE)
          \emph{$SubCritNames   }   \tab   [character] names of the components of the criterion \cr
          \emph{$CritBestValue  }   \tab   [numeric] theoretical best criterion value \cr
          \emph{$Multiplier     }   \tab   [numeric] integer indicating whether the criterion is indeed an error (+1) or an efficiency (-1) \cr
-         \emph{$Ind_notcomputed}   \tab   [numeric] indices of the time steps where InputsCrit$BoolCrit=FALSE or no data is available \cr
+         \emph{$Ind_notcomputed}   \tab   [numeric] indices of the time steps where \emph{InputsCrit$BoolCrit} = \code{FALSE} or no data is available \cr
          }
 }
 

man/ErrorCrit_KGE2.Rd

@@ -33,7 +33,7 @@ ErrorCrit_KGE2(InputsCrit, OutputsModel, warnings = TRUE, verbose = TRUE)
          \emph{$SubCritNames   }   \tab   [character] names of the components of the criterion \cr
          \emph{$CritBestValue  }   \tab   [numeric] theoretical best criterion value \cr
          \emph{$Multiplier     }   \tab   [numeric] integer indicating whether the criterion is indeed an error (+1) or an efficiency (-1) \cr
-         \emph{$Ind_notcomputed}   \tab   [numeric] indices of the time steps where InputsCrit$BoolCrit = FALSE or no data is available \cr
+         \emph{$Ind_notcomputed}   \tab   [numeric] indices of the time steps where \emph{InputsCrit$BoolCrit} = \code{FALSE} or no data is available \cr
          }
 }
 

man/ErrorCrit_NSE.Rd

@@ -31,7 +31,7 @@ ErrorCrit_NSE(InputsCrit, OutputsModel, warnings = TRUE, verbose = TRUE)
          \emph{$CritName       }   \tab   [character] name of the criterion \cr
          \emph{$CritBestValue  }   \tab   [numeric] theoretical best criterion value \cr
          \emph{$Multiplier     }   \tab   [numeric] integer indicating whether the criterion is indeed an error (+1) or an efficiency (-1) \cr
-         \emph{$Ind_notcomputed}   \tab   [numeric] indices of the time steps where InputsCrit$BoolCrit=FALSE or no data is available \cr
+         \emph{$Ind_notcomputed}   \tab   [numeric] indices of the time steps where \emph{InputsCrit$BoolCrit} = \code{FALSE} or no data is available \cr
          }
 }
 
@@ -43,7 +43,7 @@ Function which computes an error criterion based on the NSE formula proposed by
 
 \details{
 In addition to the criterion value, the function outputs include a multiplier (-1 or +1) which allows 
-the use of the function for model calibration: the product CritValue*Multiplier is the criterion to be minimised 
+the use of the function for model calibration: the product CritValue * Multiplier is the criterion to be minimised 
 (Multiplier = -1 for NSE).
 }
 

man/ErrorCrit_RMSE.Rd

@@ -29,7 +29,7 @@ ErrorCrit_RMSE(InputsCrit, OutputsModel, warnings = TRUE, verbose = TRUE)
          \emph{$CritName       }   \tab   [character] name of the criterion \cr
          \emph{$CritBestValue  }   \tab   [numeric] theoretical best criterion value \cr
          \emph{$Multiplier     }   \tab   [numeric] integer indicating whether the criterion is indeed an error (+1) or an efficiency (-1) \cr
-         \emph{$Ind_notcomputed}   \tab   [numeric] indices of the time steps where InputsCrit$BoolCrit=FALSE or no data is available \cr
+         \emph{$Ind_notcomputed}   \tab   [numeric] indices of the time steps where \emph{InputsCrit$BoolCrit} = \code{FALSE} or no data is available \cr
          }
 }
 
@@ -41,7 +41,7 @@ Function which computes an error criterion based on the root mean square error (
 
 \details{
 In addition to the criterion value, the function outputs include a multiplier (-1 or +1) which allows 
-the use of the function for model calibration: the product CritValue*Multiplier is the criterion to be minimised 
+the use of the function for model calibration: the product CritValue * Multiplier is the criterion to be minimised 
 (Multiplier = +1 for RMSE).
 }
 

man/RunModel.Rd

@@ -18,7 +18,7 @@ RunModel(InputsModel, RunOptions, Param, FUN_MOD)
 
 \item{Param}{[numeric] vector of model parameters}
 
-\item{FUN_MOD}{[function] hydrological model function (e.g. RunModel_GR4J, RunModel_CemaNeigeGR4J)}
+\item{FUN_MOD}{[function] hydrological model function (e.g. \code{\link{RunModel_GR4J}}, \code{\link{RunModel_CemaNeigeGR4J}})}
 }
 
 

man/TransfoParam.Rd

@@ -18,7 +18,7 @@ TransfoParam(ParamIn, Direction, FUN_TRANSFO)
 
 \item{Direction}{[character] direction of the transformation: use \code{"RT"} for Raw -> Transformed and \code{"TR"} for Transformed -> Raw}
 
-\item{FUN_TRANSFO}{[function] model parameters transformation function (e.g. \code{link{TransfoParam_GR4J}}, \code{link{TransfoParam_CemaNeigeGR4J}})}
+\item{FUN_TRANSFO}{[function] model parameters transformation function (e.g. \code{\link{TransfoParam_GR4J}}, \code{\link{TransfoParam_CemaNeigeGR4J}})}
 }
 \value{
 \emph{ParamOut} [numeric] matrix of parameter sets (sets in line, parameter values in column)
@@ -34,18 +34,18 @@ Function which transforms model parameters using the provided function (from raw
 library(airGR)
 
 ## transformation Raw->Transformed for the GR4J model
-    Xraw  <- matrix(c(+221.41, -3.63,  +30.00, +1.37,
-                      +347.23, -1.03,  +60.34, +1.76,
-                      +854.06, -0.10, +148.41, +2.34),
-                      ncol = 4, byrow = TRUE)
-    Xtran <- TransfoParam(ParamIn = Xraw, Direction = "RT", FUN_TRANSFO = TransfoParam_GR4J)
+Xraw  <- matrix(c(+221.41, -3.63,  +30.00, +1.37,
+                  +347.23, -1.03,  +60.34, +1.76,
+                  +854.06, -0.10, +148.41, +2.34),
+                  ncol = 4, byrow = TRUE)
+Xtran <- TransfoParam(ParamIn = Xraw, Direction = "RT", FUN_TRANSFO = TransfoParam_GR4J)
 
 ## transformation Transformed->Raw for the GR4J model
-    Xtran <- matrix(c(+3.60, -2.00, +3.40, -9.10,
-                      +3.90, -0.90, +4.10, -8.70,
-                      +4.50, -0.10, +5.00, -8.10),
-                      ncol = 4, byrow = TRUE)
-    Xraw  <- TransfoParam(ParamIn = Xtran, Direction = "TR", FUN_TRANSFO = TransfoParam_GR4J)
+Xtran <- matrix(c(+3.60, -2.00, +3.40, -9.10,
+                  +3.90, -0.90, +4.10, -8.70,
+                  +4.50, -0.10, +5.00, -8.10),
+                  ncol = 4, byrow = TRUE)
+Xraw  <- TransfoParam(ParamIn = Xtran, Direction = "TR", FUN_TRANSFO = TransfoParam_GR4J)
 }