Documentation

This commit is contained in:
Roland Hollós 2020-05-28 09:23:37 +02:00
parent 7a8b1aa68b
commit 88d681fe65
22 changed files with 208 additions and 64 deletions

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@ -35,7 +35,7 @@ Imports:
LinkingTo: Rcpp
SystemRequirements: C++11
Maintainer: Roland Hollo's <hollorol@gmail.com>
RoxygenNote: 7.0.0
RoxygenNote: 7.1.0
Suggests: knitr,
rmarkdown,
VignetteBuilder: knitr

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@ -16,6 +16,7 @@ export(getyearlycum)
export(getyearlymax)
export(mtclim)
export(musoDate)
export(musoGlue)
export(musoMapping)
export(musoMappingFind)
export(musoMonte)

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@ -198,6 +198,13 @@ calcLikelihoodsAndRMSE <- function(dataVar, mod, mes, likelihoods, alignIndexes,
return(c(likelihoodRMSE[1,],likelihoodRMSE[2,]))
}
#' musoGlue
#'
#' This function calculates the -users specified- likelihood for random model input.
#'
#' @author Roland HOLLOS
#' @param plotName u
#' @export
musoGlue <- function(preservedCalib, w){
preservedCalib<- read.csv(preservedCalib)
preservedCalib <- preservedCalib[-1,] #original

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@ -4,9 +4,16 @@
\alias{alignData}
\title{alignData}
\usage{
alignData(mdata, dataCol, modellSettings = NULL, startDate = NULL,
endDate = NULL, formatString = "\%Y-\%m-\%d", leapYear = TRUE,
continious = FALSE)
alignData(
mdata,
dataCol,
modellSettings = NULL,
startDate = NULL,
endDate = NULL,
formatString = "\%Y-\%m-\%d",
leapYear = TRUE,
continious = FALSE
)
}
\description{
This function align the data to the model and the model to the data

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@ -4,8 +4,14 @@
\alias{changemulline}
\title{This is the function which is capable to change multiple specific lines to others using their row numbers.}
\usage{
changemulline(filePaths, calibrationPar, contents, fileOut, fileToChange,
modifyOriginal = FALSE)
changemulline(
filePaths,
calibrationPar,
contents,
fileOut,
fileToChange,
modifyOriginal = FALSE
)
}
\description{
The function uses the previous changspecline function to operate.

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@ -4,8 +4,12 @@
\alias{checkMeteoBGC}
\title{checkMeteoBGC}
\usage{
checkMeteoBGC(settings = NULL, skip = 4, numericReport = FALSE,
type = "normal")
checkMeteoBGC(
settings = NULL,
skip = 4,
numericReport = FALSE,
type = "normal"
)
}
\arguments{
\item{settings}{The output of setupMuso}

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@ -4,9 +4,15 @@
\alias{compareMuso}
\title{compareMuso}
\usage{
compareMuso(settings = NULL, parameters, variable = 1,
calibrationPar = NULL, fileToChange = "epc", skipSpinup = TRUE,
timeFrame = "day")
compareMuso(
settings = NULL,
parameters,
variable = 1,
calibrationPar = NULL,
fileToChange = "epc",
skipSpinup = TRUE,
timeFrame = "day"
)
}
\arguments{
\item{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.}

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@ -4,8 +4,10 @@
\alias{getConstMatrix}
\title{getConstMatrix}
\usage{
getConstMatrix(filetype = "epc",
version = as.character(getOption("RMuso_version")))
getConstMatrix(
filetype = "epc",
version = as.character(getOption("RMuso_version"))
)
}
\arguments{
\item{filetype}{It can be "epc" or "soil".}

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@ -4,10 +4,19 @@
\alias{getMeteoData1BGC}
\title{getMeteoData1BGC}
\usage{
getMeteoData1BGC(startYear = 2017, endYear = 2017, lon = 18.8,
lat = 47.3, timeOut = 7200, monthList = sprintf("\%02d", 1:12),
dayList = sprintf("\%02d", 1:31), hourList = sprintf("\%02d:00",
0:23), destDir = NULL, apiFile = NULL, fileDir = NULL)
getMeteoData1BGC(
startYear = 2017,
endYear = 2017,
lon = 18.8,
lat = 47.3,
timeOut = 7200,
monthList = sprintf("\%02d", 1:12),
dayList = sprintf("\%02d", 1:31),
hourList = sprintf("\%02d:00", 0:23),
destDir = NULL,
apiFile = NULL,
fileDir = NULL
)
}
\arguments{
\item{startYear}{Start year of the downloading data. It shall be greater than 1978.}

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@ -4,8 +4,14 @@
\alias{musoDate}
\title{musoDate}
\usage{
musoDate(startYear, endYears = NULL, numYears, combined = TRUE,
leapYearHandling = FALSE, prettyOut = FALSE)
musoDate(
startYear,
endYears = NULL,
numYears,
combined = TRUE,
leapYearHandling = FALSE,
prettyOut = FALSE
)
}
\description{
This function generates MuSo compatibla dates for the data

17
RBBGCMuso/man/musoGlue.Rd Normal file
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@ -0,0 +1,17 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/calibration.R
\name{musoGlue}
\alias{musoGlue}
\title{musoGlue}
\usage{
musoGlue(preservedCalib, w)
}
\arguments{
\item{plotName}{u}
}
\description{
This function calculates the -users specified- likelihood for random model input.
}
\author{
Roland HOLLOS
}

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@ -4,12 +4,27 @@
\alias{musoMonte}
\title{musoMonte}
\usage{
musoMonte(settings = NULL, parameters = NULL, inputDir = "./",
outLoc = "./calib", iterations = 10, preTag = "mont-",
outputType = "moreCsv", fun = mean, varIndex = 1, outVars = NULL,
silent = TRUE, skipSpinup = TRUE, debugging = FALSE,
keepEpc = FALSE, constrains = NULL, skipZero = TRUE,
postProcString = NULL, ...)
musoMonte(
settings = NULL,
parameters = NULL,
inputDir = "./",
outLoc = "./calib",
iterations = 10,
preTag = "mont-",
outputType = "moreCsv",
fun = mean,
varIndex = 1,
outVars = NULL,
silent = TRUE,
skipSpinup = TRUE,
debugging = FALSE,
keepEpc = FALSE,
constrains = NULL,
skipZero = TRUE,
postProcString = NULL,
modifyOut = TRUE,
...
)
}
\arguments{
\item{settings}{A list of environmental variables for the Monte Carlo experiment. These settings are generated by the setupMuso function. By default the settings parameter is generated automatically.}

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@ -4,9 +4,19 @@
\alias{musoQuickEffect}
\title{musoQuickEffect}
\usage{
musoQuickEffect(settings = NULL, calibrationPar = NULL, startVal,
endVal, nSteps = 1, fileToChange = "epc", outVar,
parName = "parVal")
musoQuickEffect(
settings = setupMuso(),
calibrationPar = NULL,
startVal,
endVal,
nSteps = 1,
fileToChange = "epc",
modifyOriginal = TRUE,
outVar,
parName = "parVal",
yearNum = 1,
year = (settings$startYear + yearNum - 1)
)
}
\arguments{
\item{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.}

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@ -4,9 +4,7 @@
\alias{musoRand}
\title{musoRand}
\usage{
musoRand(parameters, iterations = 3000, fileType = "epc",
version = as.character(getOption("RMuso_version")),
constrains = getConstMatrix(fileType = fileType, version = version))
musoRand(parameters, iterations = 3000, fileType = "epc", constrains = NULL)
}
\arguments{
\item{parameters}{This is a dataframe (heterogeneous data-matrix), where the first column is the name of the parameter, the second is a numeric vector of the rownumbers of the given variable in the input EPC file, and the last two columns describe the minimum and the maximum of the parameter (i.e. the parameter ranges), defining the interval for the randomization.}

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@ -4,13 +4,27 @@
\alias{musoSensi}
\title{musoSensi}
\usage{
musoSensi(monteCarloFile = NULL, parameters = NULL, settings = NULL,
inputDir = "./", outLoc = "./calib", outVars = NULL,
iterations = 30, preTag = "mont-", outputType = "moreCsv",
fun = mean, varIndex = 1, outputFile = "sensitivity.csv",
plotName = "sensitivity.png", plotTitle = "Sensitivity",
skipSpinup = TRUE, skipZero = TRUE, postProcString = NULL,
dpi = 300)
musoSensi(
monteCarloFile = NULL,
parameters = NULL,
settings = NULL,
inputDir = "./",
outLoc = "./calib",
outVars = NULL,
iterations = 30,
preTag = "mont-",
outputType = "moreCsv",
fun = mean,
varIndex = 1,
outputFile = "sensitivity.csv",
plotName = "sensitivity.png",
plotTitle = "Sensitivity",
skipSpinup = TRUE,
skipZero = TRUE,
postProcString = NULL,
modifyOut = TRUE,
dpi = 300
)
}
\arguments{
\item{parameters}{This is a dataframe (heterogen data-matrix), which first column is the name of the parameters, the second is a numeric vector of the rownumbers of the given variable in the epc-fie, the last two column consist the endpont of the parameter-ranges, where the parameters will be randomized.}

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@ -4,14 +4,26 @@
\alias{optiMuso}
\title{optiMuso}
\usage{
optiMuso(measuredData, parameters = NULL, startDate = NULL,
endDate = NULL, formatString = "\%Y-\%m-\%d",
leapYearHandling = TRUE, dataVar, outLoc = "./calib",
preTag = "cal-", settings = NULL, outVars = NULL,
iterations = 30, skipSpinup = TRUE, constrains = NULL,
plotName = "calib.jpg", likelihood = function(x, y) {
exp(-sqrt(mean((x - y)^2))) }, continious, modelVar = 3009,
naVal = NULL, postProcString = NULL)
optiMuso(
measuredData,
parameters = NULL,
startDate = NULL,
endDate = NULL,
formatString = "\%Y-\%m-\%d",
dataVar,
outLoc = "./calib",
preTag = "cal-",
settings = setupMuso(),
outVars = NULL,
iterations = 30,
skipSpinup = TRUE,
plotName = "calib.jpg",
modifyOriginal = TRUE,
likelihood,
naVal = NULL,
postProcString = NULL,
w = NULL
)
}
\arguments{
\item{parameters}{b}
@ -30,8 +42,6 @@ optiMuso(measuredData, parameters = NULL, startDate = NULL,
\item{skipSpinup}{a}
\item{constrains}{d}
\item{plotName}{u}
\item{likelihood}{d}
@ -50,6 +60,8 @@ optiMuso(measuredData, parameters = NULL, startDate = NULL,
\item{calPar}{a}
\item{constrains}{d}
\item{leapYear}{b}
}
\description{

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@ -4,9 +4,14 @@
\alias{paramSweep}
\title{paramSweep}
\usage{
paramSweep(inputDir = "./", parameters = NULL, outputDir = NULL,
iterations = 10, outVar = "daily_gpp",
htmlOutName = "paramsweep.html")
paramSweep(
inputDir = "./",
parameters = NULL,
outputDir = NULL,
iterations = 10,
outVar = "daily_gpp",
htmlOutName = "paramsweep.html"
)
}
\arguments{
\item{inputDir}{The directory which contains the MuSo model's ini files}

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@ -4,8 +4,13 @@
\alias{randEpc}
\title{randEpc}
\usage{
randEpc(parameterFile = "parameters.csv", location = "./epcDir",
sourceEpc = "maize.epc", iterations = 1000, constrains = NULL)
randEpc(
parameterFile = "parameters.csv",
location = "./epcDir",
sourceEpc = "maize.epc",
iterations = 1000,
constrains = NULL
)
}
\arguments{
\item{parameterFile}{parameters.csv file location}

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@ -4,11 +4,19 @@
\alias{readObservedData}
\title{readMeasuredMuso}
\usage{
readObservedData(inFile, naString = NULL, sep = ",",
leapYearHandling = TRUE, convert.var = NULL, convert.scalar = 1,
readObservedData(
inFile,
naString = NULL,
sep = ",",
leapYearHandling = TRUE,
convert.var = NULL,
convert.scalar = 1,
convert.fun = (function(x) { x * convert.scalar }),
convert.file = NULL, filterCol = NULL, filterVal = 1,
selVar = NULL)
convert.file = NULL,
filterCol = NULL,
filterVal = 1,
selVar = NULL
)
}
\description{
MuSo data reader

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@ -4,9 +4,15 @@
\alias{saveAllMusoPlots}
\title{saveAllMusoPlots}
\usage{
saveAllMusoPlots(settings = NULL, plotName = ".png", silent = TRUE,
type = "line", outFile = "annual.csv", colour = NULL,
skipSpinup = FALSE)
saveAllMusoPlots(
settings = NULL,
plotName = ".png",
silent = TRUE,
type = "line",
outFile = "annual.csv",
colour = NULL,
skipSpinup = FALSE
)
}
\arguments{
\item{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.}

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@ -4,8 +4,15 @@
\alias{stampAndDir}
\title{stampAndCopy}
\usage{
stampAndDir(outputLoc, names, stampDir, wrongDir, type = "output",
errorsign, logfiles)
stampAndDir(
outputLoc,
names,
stampDir,
wrongDir,
type = "output",
errorsign,
logfiles
)
}
\arguments{
\item{outputLoc}{This is the location of the output files.}

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@ -4,8 +4,7 @@
\alias{updateMusoMapping}
\title{updateMusoMapping}
\usage{
updateMusoMapping(excelName, dest = "./",
version = getOption("RMuso_version"))
updateMusoMapping(excelName, dest = "./", version = getOption("RMuso_version"))
}
\arguments{
\item{excelName}{Name of the excelfile which contains the parameters}