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- function colors = distinguishable_colors(n_colors,bg,func)
- % DISTINGUISHABLE_COLORS: pick colors that are maximally perceptually distinct
- %
- % When plotting a set of lines, you may want to distinguish them by color.
- % By default, Matlab chooses a small set of colors and cycles among them,
- % and so if you have more than a few lines there will be confusion about
- % which line is which. To fix this problem, one would want to be able to
- % pick a much larger set of distinct colors, where the number of colors
- % equals or exceeds the number of lines you want to plot. Because our
- % ability to distinguish among colors has limits, one should choose these
- % colors to be "maximally perceptually distinguishable."
- %
- % This function generates a set of colors which are distinguishable
- % by reference to the "Lab" color space, which more closely matches
- % human color perception than RGB. Given an initial large list of possible
- % colors, it iteratively chooses the entry in the list that is farthest (in
- % Lab space) from all previously-chosen entries. While this "greedy"
- % algorithm does not yield a global maximum, it is simple and efficient.
- % Moreover, the sequence of colors is consistent no matter how many you
- % request, which facilitates the users' ability to learn the color order
- % and avoids major changes in the appearance of plots when adding or
- % removing lines.
- %
- % Syntax:
- % colors = distinguishable_colors(n_colors)
- % Specify the number of colors you want as a scalar, n_colors. This will
- % generate an n_colors-by-3 matrix, each row representing an RGB
- % color triple. If you don't precisely know how many you will need in
- % advance, there is no harm (other than execution time) in specifying
- % slightly more than you think you will need.
- %
- % colors = distinguishable_colors(n_colors,bg)
- % This syntax allows you to specify the background color, to make sure that
- % your colors are also distinguishable from the background. Default value
- % is white. bg may be specified as an RGB triple or as one of the standard
- % "ColorSpec" strings. You can even specify multiple colors:
- % bg = {'w','k'}
- % or
- % bg = [1 1 1; 0 0 0]
- % will only produce colors that are distinguishable from both white and
- % black.
- %
- % colors = distinguishable_colors(n_colors,bg,rgb2labfunc)
- % By default, distinguishable_colors uses the image processing toolbox's
- % color conversion functions makecform and applycform. Alternatively, you
- % can supply your own color conversion function.
- %
- % Example:
- % c = distinguishable_colors(25);
- % figure
- % image(reshape(c,[1 size(c)]))
- %
- % Example using the file exchange's 'colorspace':
- % func = @(x) colorspace('RGB->Lab',x);
- % c = distinguishable_colors(25,'w',func);
- % Copyright 2010-2011 by Timothy E. Holy
- % Parse the inputs
- if (nargin < 2)
- bg = [1 1 1]; % default white background
- else
- if iscell(bg)
- % User specified a list of colors as a cell aray
- bgc = bg;
- for i = 1:length(bgc)
- bgc{i} = parsecolor(bgc{i});
- end
- bg = cat(1,bgc{:});
- else
- % User specified a numeric array of colors (n-by-3)
- bg = parsecolor(bg);
- end
- end
-
- % Generate a sizable number of RGB triples. This represents our space of
- % possible choices. By starting in RGB space, we ensure that all of the
- % colors can be generated by the monitor.
- n_grid = 30; % number of grid divisions along each axis in RGB space
- x = linspace(0,1,n_grid);
- [R,G,B] = ndgrid(x,x,x);
- rgb = [R(:) G(:) B(:)];
- if (n_colors > size(rgb,1)/3)
- error('You can''t readily distinguish that many colors');
- end
-
- % Convert to Lab color space, which more closely represents human
- % perception
- if (nargin > 2)
- lab = func(rgb);
- bglab = func(bg);
- else
- C = makecform('srgb2lab');
- lab = applycform(rgb,C);
- bglab = applycform(bg,C);
- end
- % If the user specified multiple background colors, compute distances
- % from the candidate colors to the background colors
- mindist2 = inf(size(rgb,1),1);
- for i = 1:size(bglab,1)-1
- dX = bsxfun(@minus,lab,bglab(i,:)); % displacement all colors from bg
- dist2 = sum(dX.^2,2); % square distance
- mindist2 = min(dist2,mindist2); % dist2 to closest previously-chosen color
- end
-
- % Iteratively pick the color that maximizes the distance to the nearest
- % already-picked color
- colors = zeros(n_colors,3);
- lastlab = bglab(end,:); % initialize by making the "previous" color equal to background
- for i = 1:n_colors
- dX = bsxfun(@minus,lab,lastlab); % displacement of last from all colors on list
- dist2 = sum(dX.^2,2); % square distance
- mindist2 = min(dist2,mindist2); % dist2 to closest previously-chosen color
- [~,index] = max(mindist2); % find the entry farthest from all previously-chosen colors
- colors(i,:) = rgb(index,:); % save for output
- lastlab = lab(index,:); % prepare for next iteration
- end
- end
- function c = parsecolor(s)
- if ischar(s)
- c = colorstr2rgb(s);
- elseif isnumeric(s) && size(s,2) == 3
- c = s;
- else
- error('MATLAB:InvalidColorSpec','Color specification cannot be parsed.');
- end
- end
- function c = colorstr2rgb(c)
- % Convert a color string to an RGB value.
- % This is cribbed from Matlab's whitebg function.
- % Why don't they make this a stand-alone function?
- rgbspec = [1 0 0;0 1 0;0 0 1;1 1 1;0 1 1;1 0 1;1 1 0;0 0 0];
- cspec = 'rgbwcmyk';
- k = find(cspec==c(1));
- if isempty(k)
- error('MATLAB:InvalidColorString','Unknown color string.');
- end
- if k~=3 || length(c)==1,
- c = rgbspec(k,:);
- elseif length(c)>2,
- if strcmpi(c(1:3),'bla')
- c = [0 0 0];
- elseif strcmpi(c(1:3),'blu')
- c = [0 0 1];
- else
- error('MATLAB:UnknownColorString', 'Unknown color string.');
- end
- end
- end
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