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plotting - Control parameters of different styles of DistributionChart


Using DistributionChart, you can choose among several styles aka ChartElementFunction:


ChartElementData["DistributionChart"]

{"Density", "DensityQuantile", "FadingQuantile",
 "GlassQuantile", "HistogramDensity", "LineDensity", "PointDensity", 
 "Quantile", "SmoothDensity"}

Is there a way to control their parameters? The documentation does not seem to say.




The problem is that the defaults are less than optimal for my data. Consider these:


Using SmoothDensity:


SmoothDensity


Using HistogramDensity:


HistogramDensity


Using LineDensity:


<code>LineDensity</code>


Clearly, SmoothDensity grossly misrepresents the data (just compare with the LineDensity version); the violins should all look like the ones for 2 and 9. HistogramDensity does a better job but its resolution is horrible; there are 100 data points per size, about 70 of which fall into the upper class -- that should be plenty of points to draw more bars.


I would like to tell HistogramDensity to use more/smaller bins, and/or SmoothDensity to smooth less. How is this possible?



Answer




To get the options available for various ChartElementDataFunctions you can use:


 {#, Column[ChartElementData[#, "Options"]]} & /@ 
   ChartElementData["DistributionChart"] // Grid[#, Frame -> All] &

enter image description here



For "HistogramDensity", any bin specification accepted by Histogram > MoreInformation can be used as the setting for the suboption "Bins":



enter image description here




data = Table[RandomVariate[NormalDistribution[RandomInteger[5], 1], 100], {3}];

Partition[Table[DistributionChart[data, ChartStyle -> "SolarColors",
ChartElementFunction -> (ChartElementDataFunction["HistogramDensity", "Bins" -> i]),
PlotLabel -> Row[{"\"Bins\"", "->", ToString@i}], ImageSize -> 200],
{i, {10, 5, {.3}, {0, 8, .5}, {{0, 1, 2, 5, 6, 8}},
 Automatic, "Sturges", "Scott", "FreedmanDiaconis", "Knuth", 
 "Wand", "Log",
 {"Log", "Sturges"}, {"Log", "Scott"}, {"Log", 
  "FreedmanDiaconis"}, {"Log", "Knuth"}}}], 4] //

Grid[#, Frame -> All, Spacings -> 5] &

enter image description here


... including custom bin specifications like


binFunc1 = Union[IntegerPart[#]] &;
binFunc2 = Quantile[#, {0, .05, .1, .25, .5, .75, .9, .95, 1.}] &;
binFunc3 = First[HistogramList[#, "FreedmanDiaconis"]] &;
binFunc4 = Sort@#[[RandomSample[Range@Length@#, 10]]] &;

Partition[Table[DistributionChart[data, ChartStyle -> "Rainbow",

 ChartElementFunction -> (ChartElementDataFunction[
   "HistogramDensity", "Bins" -> i]),
 PlotLabel -> Row[{"\"Bins\"", "->\n", ToString@i}], 
 ImageSize -> 300],
 {i, {binFunc1, binFunc2, binFunc3, binFunc4}}], 2] //
 Grid[#, Frame -> All, Spacings -> 5] &

enter image description here



For "Quantile", "FadingQuantile", "GlassQuantile" and "DensityQuantile", the settings for suboption "Quantile" can be either an integer n (short for the n-1 quantiles 100 i/n (i = 1, ... , n-1) or an explicit list of integers between 0 and 100. Furthermore, each of the explicitly specified quantiles can be styled individually using the suboption "QuantileStyle".



Partition[Table[DistributionChart[data, 
ChartElementFunction -> (ChartElementDataFunction["GlassQuantile",
   "Quantile" -> i,
   "QuantileStyle" -> (Directive[Thick, Hue[#/100]] & /@ i),
   "QuantileShading" -> True]),
PlotLabel -> Row[{"Quantiles:  ", ToString@i}], ImageSize -> 300],
{i, {4, {25, 50, 75}, {10, 90}, {5, 10, 25, 50, 75, 90, 95}}}], 2] //
Grid[#, Frame -> All, Spacings -> 5] &

enter image description here




The option setting for "Threshold" seems to control symmetric trimming at the two tails as the following examples suggest. (Perhaps, further fishing may reveal that it accepts additional values to control the bandwidths)


Row@Table[DistributionChart[data, 
 ChartElementFunction -> (ChartElementDataFunction["SmoothDensity", 
  "ColorScheme" -> "DeepSeaColors", "Threshold" -> i]), 
 ImageSize -> 300], {i, {.05, .1, .5}}]

enter image description here


Row@Table[DistributionChart[data, ChartStyle -> "SolarColors", 
 ChartElementFunction -> (ChartElementDataFunction["Density", "Threshold" -> i]),

 ImageSize -> 300], {i, {.05, .1, .5}}]

enter image description here


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