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specify axes parent #24

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specify axes parent #24

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22 changes: 12 additions & 10 deletions Violin.m
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Original file line number Diff line number Diff line change
Expand Up @@ -106,13 +106,13 @@
args = obj.checkInputs(data, pos, varargin{:});
data = data(not(isnan(data)));
if numel(data) == 1
obj.MedianPlot = scatter(pos, data, 'filled');
obj.MedianPlot = scatter(args.Parent, pos, data, 'filled');
obj.MedianColor = args.MedianColor;
obj.MedianPlot.MarkerEdgeColor = args.EdgeColor;
return
end

hold('on');
hold(args.Parent, 'on');

% calculate kernel density estimation for the violin
if isempty(data)
Expand All @@ -139,19 +139,19 @@
end
jitter = 2*(rand(size(data))-0.5);
obj.ScatterPlot = ...
scatter(pos + jitter.*jitterstrength, data, 'filled');
scatter(args.Parent, pos + jitter.*jitterstrength, data, 'filled');

% plot the violin
obj.ViolinPlot = ... % plot color will be overwritten later
fill([pos+density*width pos-density(end:-1:1)*width], ...
[value value(end:-1:1)], [1 1 1]);
[value value(end:-1:1)], [1 1 1], 'Parent', args.Parent);

% plot the mini-boxplot within the violin
quartiles = quantile(data, [0.25, 0.5, 0.75]);
obj.BoxPlot = ... % plot color will be overwritten later
fill(pos+[-1,1,1,-1]*args.BoxWidth, ...
[quartiles(1) quartiles(1) quartiles(3) quartiles(3)], ...
[1 1 1]);
[1 1 1], 'Parent', args.Parent);

% plot the data mean
meanValue = mean(data);
Expand All @@ -163,7 +163,7 @@
if meanDensityWidth<args.BoxWidth/2
meanDensityWidth=args.BoxWidth/2;
end
obj.MeanPlot = plot(pos+[-1,1].*meanDensityWidth, ...
obj.MeanPlot = plot(args.Parent, pos+[-1,1].*meanDensityWidth, ...
[meanValue, meanValue]);
obj.MeanPlot.LineWidth = 1;

Expand All @@ -173,15 +173,15 @@
hiwhisker = quartiles(3) + 1.5*IQR;
hiwhisker = min(hiwhisker, max(data(data < hiwhisker)));
if ~isempty(lowhisker) && ~isempty(hiwhisker)
obj.WhiskerPlot = plot([pos pos], [lowhisker hiwhisker]);
obj.WhiskerPlot = plot(args.Parent, [pos pos], [lowhisker hiwhisker]);
end
obj.MedianPlot = scatter(pos, quartiles(2), [], [1 1 1], 'filled');
obj.MedianPlot = scatter(args.Parent, pos, quartiles(2), [], [1 1 1], 'filled');

obj.NotchPlots = ...
scatter(pos, quartiles(2)-1.57*IQR/sqrt(length(data)), ...
scatter(args.Parent, pos, quartiles(2)-1.57*IQR/sqrt(length(data)), ...
[], [1 1 1], 'filled', '^');
obj.NotchPlots(2) = ...
scatter(pos, quartiles(2)+1.57*IQR/sqrt(length(data)), ...
scatter(args.Parent, pos, quartiles(2)+1.57*IQR/sqrt(length(data)), ...
[], [1 1 1], 'filled', 'v');

obj.EdgeColor = args.EdgeColor;
Expand All @@ -197,6 +197,7 @@
obj.ShowData = args.ShowData;
obj.ShowNotches = args.ShowNotches;
obj.ShowMean = args.ShowMean;
uistack(obj.ViolinPlot,'bottom');
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Why is the violin plot stacked to the bottom? I think I would generally expect the last plot to end up on top.

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It's mainly to help with selecting the scatter points using the data cursor or the select tool in the figure panel. With the violin plot on top, I can only select the violin plot and it is rather annoying to select the underlying scatter points.

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Then we should change the plot order and plot the scatter points last. But stacking the Violin to the bottom is counterintuitive and might break plots.

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Plot order is more of a visual feature, unless I am mistaken and you use the plot order for another function? I do not think it is that counterintuitive to stack Violin to the bottom using uistack since that is the purpose of that function.

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Imagine someone plotting first a few lines, then a Violin. The Violin should definitely be atop the lines. We can not mess with uistack.

end

function set.EdgeColor(obj, color)
Expand Down Expand Up @@ -338,6 +339,7 @@
p.addParameter('ShowData', true, isscalarlogical);
p.addParameter('ShowNotches', false, isscalarlogical);
p.addParameter('ShowMean', false, isscalarlogical);
p.addParameter('Parent', gca, @ishghandle);

p.parse(data, pos, varargin{:});
results = p.Results;
Expand Down
37 changes: 28 additions & 9 deletions violinplot.m
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
function violins = violinplot(data, cats, varargin)
function varargout = violinplot(data, cats, varargin)
%Violinplots plots violin plots of some data and categories
% VIOLINPLOT(DATA) plots a violin of a double vector DATA
%
Expand Down Expand Up @@ -46,17 +46,19 @@
% Defaults to false
% 'GroupOrder' Cell of category names in order to be plotted.
% Defaults to alphabetical ordering
% 'Parent' Axis handle to plot in
% Defaults to gca

% Copyright (c) 2016, Bastian Bechtold
% This code is released under the terms of the BSD 3-clause license

hascategories = exist('cats','var') && not(isempty(cats));

%parse the optional grouporder argument
%if it exists parse the categories order
% parse the optional grouporder argument
% if it exists parse the categories order
% but also delete it from the arguments passed to Violin
grouporder = {};
idx=find(strcmp(varargin, 'GroupOrder'));
idx = find(strcmp(varargin, 'GroupOrder'));
if ~isempty(idx) && numel(varargin)>idx
if iscell(varargin{idx+1})
grouporder = varargin{idx+1};
Expand All @@ -65,6 +67,19 @@
error('Second argument of ''GroupOrder'' optional arg must be a cell of category names')
end
end

% parse the optional axis handle
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AxisHandle = gca;
idx = find(strcmp(varargin, 'Parent'));
if ~isempty(idx) && numel(varargin)>idx
if ishghandle(varargin{idx+1})
AxisHandle = varargin{idx+1};
else
error('Second argument of ''Parent'' optional arg must be a valid axis handle')
end
end



% tabular data
if isa(data, 'dataset') || isstruct(data) || istable(data)
Expand All @@ -85,7 +100,7 @@
thisData = data.(catnames{n});
violins(n) = Violin(thisData, n, varargin{:});
end
set(gca, 'XTick', 1:length(catnames), 'XTickLabels', catnames);
set(AxisHandle, 'XTick', 1:length(catnames), 'XTickLabel', catnames);

% 1D data, one category for each data point
elseif hascategories && numel(data) == numel(cats)
Expand All @@ -104,24 +119,28 @@
thisData = data(cats == thisCat);
violins(n) = Violin(thisData, n, varargin{:});
end
set(gca, 'XTick', 1:length(catnames), 'XTickLabels', catnames_labels);
set(AxisHandle, 'XTick', 1:length(catnames), 'XTickLabel', catnames_labels);

% 1D data, no categories
elseif not(hascategories) && isvector(data)
violins = Violin(data, 1, varargin{:});
set(gca, 'XTick', 1);
set(AxisHandle, 'XTick', 1);

% 2D data with or without categories
elseif ismatrix(data)
for n=1:size(data, 2)
thisData = data(:, n);
violins(n) = Violin(thisData, n, varargin{:});
end
set(gca, 'XTick', 1:size(data, 2));
set(AxisHandle, 'XTick', 1:size(data, 2));
if hascategories && length(cats) == size(data, 2)
set(gca, 'XTickLabels', cats);
set(AxisHandle, 'XTickLabel', cats);
end

end

if nargout > 0
varargout{1} = violins;
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Why the change to varargout?

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Sometimes I run the function from the command line, and I don't want any output. This gives it the flexibility for that option in addition to the default output.

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That doesn't make sense to me. If you don't assign the return value, you don't receive it. Please revert this part of the change before merging.

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That was the point of this change. When I am running the function from the command line, sometimes I do not want to receive the return value.

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Please revert this change. If you do not want to receive the return value, put a semicolon at the end of the line.

end

end