Contour plot of densities
Density estimation (PDE) [Ultsch, 2005] or "SDH" [Eilers/Goeman, 2004] used for a density contour plot.
DensityContour(X,Y, DensityEstimation="SDH", SampleSize, na.rm=FALSE,PlotIt=TRUE, NrOfContourLines=20,Plotter='ggplot', DrawTopView = TRUE, xlab, ylab, main="DensityContour", xlim, ylim, Legendlab_ggplot="value", AddString2lab="",NoBinsOrPareto=NULL,...)
The DensityContour function generates the density of the xy data as a z coordinate. Afterwards xyz will be plotted either as a contour plot or a 3d plot. It assumens that the cases of x and y are mapped to each other meaning that a cbind(x,y) operation is allowed. This function plots the Density on top of a scatterplot. Variances of x and y should not differ by extreme numbers, otherwise calculate the percentiles on both first. If DrawTopView=FALSE only the plotly option is currently available. If another option is chosen, the method switches automatically there.
PlotIt=FALSE is usefull if one likes to perform adjustements like axis scaling prior to plotting with ggplot2 or plotly.
X: Numeric vector [1:n], first feature (for x axis values)
Y: Numeric vector [1:n], second feature (for y axis values)
DensityEstimation: "SDH" is very fast but maybe not correct, "PDE" is slow but proably more correct, third alternativ is the typical R density estimation with "kde2d" which is sensitive to parameters
SampleSize: Numeric, positiv scalar, maximum size of the sample used for calculation. High values increase runtime significantly. The default is that no sample is drawn
na.rm: Function may not work with non finite values. If these cases should be automatically removed, set parameter TRUE
PlotIt: TRUE: plots with function call
FALSE: Does not plot, plotting can be done using the list element Handle
NrOfContourLines: Numeric, number of contour lines to be drawn. 20 by default.
Plotter: String, name of the plotting backend to use. Possible values are: "ggplot", "plotly". Default: ggplot
DrawTopView: Boolean, True means contur is drawn, otherwise a 3D plot is drawn. Default: TRUE
xlab: String, title of the x axis. Default: "X", see plot() function
ylab: String, title of the y axis. Default: "Y", see plot() function
main: string, the same as "main" in plot() function
xlim: see plot() function
ylim: see plot() function
Legendlab_ggplot: String, in case of Plotter="ggplot" label for the legend. Default: "value"
AddString2lab: adds the same string of information to x and y axis label, e.g. usefull for adding SI units
NoBinsOrPareto: Density specifc parameters, for PDEscatter(ParetoRadius) or SDH (nbins)) or kde2d(bins)
...: further plot arguments
MT contributed with several adjustments
List of: - X: Numeric vector [1:m],m<=n, first feature used in the plot or the kernels used
Y: Numeric vector [1:m],m<=n, second feature used in the plot or the kernels used
Densities: Number of points within the ParetoRadius of each point, i.e. density information
Handle: Handle of the plot object
[Thrun, 2018] Thrun, M. C.: Projection Based Clustering through Self-Organization and Swarm Intelligence, (Ultsch, A. & Huellermeier, E. Eds., 10.1007/978-3-658-20540-9), Doctoral dissertation, Heidelberg, Springer, ISBN: 978-3658205393, 2018.
[Thrun/Ultsch, 2018] Thrun, M. C., & Ultsch, A. : Effects of the payout system of income taxes to municipalities in Germany, in Papiez, M. & Smiech,, S. (eds.), Proc. 12th Professor Aleksander Zelias International Conference on Modelling and Forecasting of Socio-Economic Phenomena, pp. 533-542, Cracow: Foundation of the Cracow University of Economics, Cracow, Poland, 2018.
[Ultsch, 2005] Ultsch, A.: Pareto density estimation: A density estimation for knowledge discovery, In Baier, D. & Werrnecke, K. D. (Eds.), Innovations in classification, data science, and information systems, (Vol. 27, pp. 91-100), Berlin, Germany, Springer, 2005.
[Eilers/Goeman, 2004] Eilers, P. H., & Goeman, J. J.: Enhancing scatterplots with smoothed densities, Bioinformatics, Vol. 20(5), pp. 623-628. 2004.
#taken from [Thrun/Ultsch, 2018] data("ITS") data("MTY") Inds=which(ITS<900&MTY<8000) plot(ITS[Inds],MTY[Inds],main='Bimodality is not visible in normal scatter plot') DensityContour(ITS[Inds],MTY[Inds],DensityEstimation="SDH",xlab = 'ITS in EUR', ylab ='MTY in EUR' ,main='Smoothed Densities histogram indicates Bimodality' ) DensityContour(ITS[Inds],MTY[Inds],DensityEstimation="PDE",xlab = 'ITS in EUR', ylab ='MTY in EUR' ,main='PDE indicates Bimodality' )
Felix Pape