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0.4.3_[2015-04-16.114824]
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DESCRIPTION

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@@ -2,7 +2,7 @@ Package: Luminescence
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Type: Package
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Title: Comprehensive Luminescence Dating Data Analysis
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Version: 0.4.3
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Date: 2015-XX-XX [upcoming]
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Date: 2015-04-17
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Author: Sebastian Kreutzer [aut, trl, cre],
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Michael Dietze [aut],
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Christoph Burow [aut],

NEWS

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NEWS for the R Package Luminescence
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Changes in version 0.4.3 (XXth, 2015):
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Changes in version 0.4.3 (17th, 2015):
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Bugfixes and changes:
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@@ -67,14 +67,51 @@ Changes in version 0.4.3 (XXth, 2015):
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• argument 'breaks' removed from the argument list,
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however, supported via the ‘'...'’ argument.
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• ‘plot_GrowthCurve()’
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• Error estimation using the Monte Carlo runs for the
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fitting function ‘fit.method = "EXP+LIN"’ and
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‘fit.method = "EXP+EXP"’ results in false values, as the
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Monte Carlo simulation was fed by mistake with wrong
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input variables (introduced in version 0.4.2 with the
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uniroot function) ... fixed,
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• the function brook if the uniroot algorithm was not able
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to find a solution within the given ranges, fixed. De
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will become NA instead and the function continues.
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• ‘plot_RLum.Data.Spectrum()’
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• Colour handing changed towards a more logical behaviour
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for ‘plot.type = 'single'’. The color now changes only
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the colour of the points and the argument ‘rug’ is now
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recognised also by this plot type. Automatic wavelength
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colouring for points for in this plot type has been
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removed.
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• same changes are made for ‘plot.type =
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'multiple.lines'’,
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• instead of just plotting a new x-axis when the argument
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‘xaxis.energy = TRUE’ is used, the spectrum (intensity)
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is now proper re-calculated (#192),
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• minor code polishing.
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• ‘plot_RLum.Anaysis()’
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• Setting the argument ‘combine = TRUE’ for 'OSL' and
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'IRSL' caused an error related to the missing argument
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'curve.transformation'; corrected.,
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• colour handling for setting ‘combine = TRUE’ improved.
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It now works as for ‘plot.default’.
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It now works as for ‘plot.default’,
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• support for ‘xlim’ and ‘ylim’ in the non-combined mode,
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• combine mode (‘combine = TRUE’) is no more limited to an
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input object of similar curves. Now the plot function
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tries to combine curves of similar type automatically.
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• ‘readBIN2R()’
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R/analyse_IRSAR.RF.R

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@@ -7,7 +7,7 @@ analyse_IRSAR.RF<- structure(function(# Analyse IRSAR RF measurements
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## Sebastian Kreutzer, IRAMAT-CRP2A, Universite Bordeaux Montaigne (France) \cr
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##section<<
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## version 0.3.1
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## version 0.3.2
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# ===========================================================================
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##TODO - keep fit.range in mind for De calculation
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### also on the regenerated curve? At least there should be a clever check.
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### - currently no feedback on the outlier removal are given
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### - CHECK ERROR CALCULATION!
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### - RETURN values are not sufficiently described.
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object,
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### \code{\linkS4class{RLum.Analysis}} (\bold{required}):
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values.residuals <- temp.sliding[[3]]
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temp.trend.fit <- temp.sliding[[4]]
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values.natural.limited.full <- temp.sliding[[5]]
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Trend.slope <- temp.sliding[[4]][2]
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# MC runs for error calculation ---------------------------------------------------------------
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if(!exists("De.error.lower")){De.error.lower <- NA}
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if(!exists("De.error.upper")){De.error.upper <- NA}
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if(!exists("De.status")){De.status <- NA}
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if(!exists("Trend.slope")){Trend.slope <- NA}
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if(!exists("fit")){fit <- NA}
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De.error.lower = De.error.lower,
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De.error.upper = De.error.upper,
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De.status = De.status,
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Trend.slope = Trend.slope,
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row.names=NULL)
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newRLumResults.analyse_IRSAR.RF <- set_RLum.Results(

R/calc_Statistics.R

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@@ -30,7 +30,7 @@ calc_Statistics <- structure(function(# Function to calculate statistic measures
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## Check input data
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if(is(data, "RLum.Results") == FALSE &
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is(data, "data.frame") == FALSE) {
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stop(paste("[calc_Statistics()] Error: Input data format is neither",
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stop(paste("[calc_Statistics()] Input data format is neither",
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"'data.frame' nor 'RLum.Results'"))
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} else {
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if(is(data, "RLum.Results") == TRUE) {
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} else if(weight.calc == "square") {
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S.weights <- 1 / data[,2]^2
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} else {
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stop ("[calc_Statistics] Error: Weight calculation type not supported!")
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stop ("[calc_Statistics()] Weight calculation type not supported!")
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}
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S.weights <- S.weights / sum(S.weights)

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