diff --git a/RBBGCMuso/R/plotMuso.R b/RBBGCMuso/R/plotMuso.R index dfaa167..db4de22 100644 --- a/RBBGCMuso/R/plotMuso.R +++ b/RBBGCMuso/R/plotMuso.R @@ -239,19 +239,19 @@ plotMuso <- function(settings=NULL, plotName = plotName) } -#'plot the BBGCMuso output with data +#'plot the Biome-BGCMuSo model output with observation data #' -#' This function runs the BBGC-MuSo model and reads in its outputfile in a very structured way, and after that plot the results automaticly along with a given measurement +#' This function runs the Biome-BGCMuSo model and reads its output file in a well structured way, and after that it plots the results automatically along with a given measurement dataset provided by the user. plotMusoWithData is a convenient and quick method to create nice graphs from Biome-BGCMuSo output which is quite painful in other environments. #' -#' @author Roland Hollos, Dora Hidy -#' @param settings You have to run the setupMuso function before rungetMuso. It is its output which contains all of the necessary system variables. It sets the whole environment -#' @param sep This is the separator used in the measurement file -#' @param savePlot It it is specified, the plot will be saved in a format specified with the immanent extension +#' @author Roland HOLLOS, Dora HIDY +#' @param settings RBBGCMuso uses variables that define the entire simulation environment. Those environment variables include the name of the INI files, the name of the meteorology files, the path to the model executable and its file name, the entire output list, the entire output variable matrix, the dependency rules for the EPC parameters etc. Using the runMuso function RBBGCMuso can automatically create those environment variables by inspecting the files in the working directory (this happens through the setupMuso function). It means that by default model setup is performed automatically in the background and the user has nothing to do. With this settings parameter we can force runMuso to skip automatic environment setup as we provide the environment settings to runMuso. In a typical situation the user can skip this option. +#' @param sep This is the separator symbol used in the measurement file (that is supposed to be a delimited text file) +#' @param savePlot It it is specified, the plot will be saved in a graphical format specified by the immanent extension. For example, it the savePlot is set to image01.png then a PNG graphics file will be created. #' @param variable The name of the output variable to plot #' @param NACHAR This is not implemented yet -#' @param csvFile The file of the measurement. It must contain a header. -#' @param calibrationPar documentation in setupMuso() -#' @param parameters documentation in calibMuso() +#' @param csvFile This specifies the filename of the measurements. It must contain a header. Typically this is a CSV file. +#' @param calibrationPar You might want to change some parameters in your EPC file before running the model. The function offers possibility for this without editing the EPC file. In this situation you have to select the appropirate model parameters first. You can refer to these parameters with the number of the line in the EPC file. Indexing of lines start from one. You should use a vector for this referencing like c(1,5,8) +#' @param parameters Using the function it is possible to change some of the EPC parameters prior to model execution. This can be achieved with this option. In the parameters variable you have set the row indices of the variables that you wish to change. In this parameters you can give an exact value for them in a vector form like c(1,2,3,4). #' @usage plotMuso(settings, variable, #' timee="d", silent=TRUE, #' debugging=FALSE, keepEpc=FALSE, @@ -300,14 +300,14 @@ plotMusoWithData <- function(csvFile, variable, NACHAR=NA, settings=NULL, sep=", #' compareMuso #' -#' This function runs the modell, change one of it's input, and plot both in one plot. +#' This function runs the model, then changes one of its input data, runs it again, and plots both results in one graph. #' -#' @author Roland Hollos -#' @param settings You have to run the setupMuso function before rungetMuso. It is its output which contains all of the necessary system variables. It sets the whole environment -#' @param parameters In the settings variable you have set the row indexes of the variables, you wish to change. In this parameter you can give an exact value for them in a vector like: c(1,2,3,4) +#' @author Roland HOLLOS +#' @param settings RBBGCMuso uses variables that define the entire simulation environment. Those environment variables include the name of the INI files, the name of the meteorology files, the path to the model executable and its file name, the entire output list, the entire output variable matrix, the dependency rules for the EPC parameters etc. Using the runMuso function RBBGCMuso can automatically create those environment variables by inspecting the files in the working directory (this happens through the setupMuso function). It means that by default model setup is performed automatically in the background and the user has nothing to do. With this settings parameter we can force runMuso to skip automatic environment setup as we provide the environment settings to runMuso. In a typical situation the user can skip this option. +#' @param parameters Using this function it is possible to change some of the EPC parameters prior to model execution. This can be achieved with this option. In the parameters variable you have set the row indices of the variables that you wish to change. In this parameters you can give an exact value for them in a vector form like c(1,2,3,4). #' @param variable The name of the output variable to plot -#' @param calibrationPar in the help of setupMuso function. -#' @param fileToChange You can change any line of the epc or the ini file, you just have to specify with this variable which file you van a change. Two options possible: "epc", "ini", "both" +#' @param calibrationPar You might want to change some parameters in your EPC file before running the model. This function offers possibility for this without editing the EPC file. In this situation you have to select the appropirate model parameters first. You can refer to these parameters with the number of the line in the EPC file. Indexing of lines start from one. You should use a vector for this referencing like c(1,5,8) +#' @param fileToChange You can change any line of the EPC or the INI file. Please choose "EPC", "INI" or "BOTH". This file will be used for the analysis, and the original parameter values will be changed according to the choice of the user. #' @import ggplot2 #' @export compareMuso <- function(settings=NULL,parameters, variable=1, calibrationPar=NULL, fileToChange="epc", skipSpinup=TRUE, timeFrame="day"){