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v1.0.9.26 many typo revisions in documentation

parent 3ac14d8c
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")),
......
......@@ -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>
......
......@@ -3,7 +3,7 @@
### 1.0.9.25 Release Notes (2017-08-18)
### 1.0.9.26 Release Notes (2017-08-18)
#### New features
......
......@@ -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
......
......@@ -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
}
}
......
......@@ -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.
}
......
......@@ -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$BoolCrit} = \code{FALSE} or no data is available \cr
}
}
......
......@@ -33,7 +33,7 @@ ErrorCrit_KGE2(InputsCrit, OutputsModel, warnings = TRUE, verbose = TRUE)
\emph{$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
}
}
......
......@@ -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$BoolCrit} = \code{FALSE} or no data is available \cr
}
}
......@@ -43,7 +43,7 @@ Function which computes an error criterion based on the NSE formula proposed by
\details{
In addition to the criterion value, the function outputs include a multiplier (-1 or +1) which allows
the use of the function for model calibration: the product CritValue*Multiplier is the criterion to be minimised
the use of the function for model calibration: the product CritValue * Multiplier is the criterion to be minimised
(Multiplier = -1 for NSE).
}
......
......@@ -29,7 +29,7 @@ ErrorCrit_RMSE(InputsCrit, OutputsModel, warnings = TRUE, verbose = TRUE)
\emph{$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).
}
......
......@@ -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}})}
}
......
......@@ -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)
}
......
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