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Parula color on matlab 2013a

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Asir Tushar
Asir Tushar le 8 Jan 2020
Commenté : DGM le 16 Jan 2023
I want to customize the parula color on meshplots.
I am using matlab 2013a. How can this be done ?

Réponses (2)

DGM
DGM le 16 Jan 2023
Modifié(e) : DGM le 16 Jan 2023
Hm. I don't know what parula() was originally interpolated in, but I gave it a shot in LAB just for fun. At least it's smooth enough that cubic interpolation behaves fairly well with few points. Of course, I didn't stop to think that lab2rgb() and parula() came out in the same version (R2014b). Still, there are other options.
% a rough trajectory in LAB
x0 = [0 0.07451 0.1294 0.1843 0.2431 0.3647 0.4902 0.5569 0.6039 0.6745 0.7373 0.7843 0.8314 0.8784 0.9412 1];
CT0 = [27 47 -66; 37 53 -80; 43 49 -82; 48 41 -80; 53 26 -73; 63 -9 -44; 69 -38 -12; ...
72 -47 9; 74 -52 26; 75 -41 52; 76 -19 69; 77 0 72; 80 12 68; 84 4 76; 90 -12 84; 96 -22 92];
% generate a new uniform table of desired length
N = 256; % length of new color table
xf = linspace(0,1,N);
CT1 = interp1(x0,CT0,xf,'pchip');
% IPT, R2014b+ (which has parula() anyway)
%CT1 = lab2rgb(CT1);
% IPT, R2010a+ (for WP adaptation option)
cform = makecform('lab2srgb','adaptedwhitepoint',whitepoint('D65'));
CT1 = applycform(CT1,cform);
% MIMT, legacy-friendly (see File Exchange)
%CT1 = ctflop(lch2rgb(lab2lch(ctflop(CT1)),'lab'));
% create test sweeps for comparison
% parula() on top, recreated on bottom
CT = parula(N);
testsweeps = cat(3,CT,CT1);
testsweeps = permute(testsweeps,[3 1 2]);
testsweeps = imresize(testsweeps,[128 256],'nearest');
% compare the results
imshow(testsweeps)
So the difference is noticeable if you have them next to each other, but it's not terrible for a short 16-point reference curve. I might have been able to get away with less in HSYn, but I was trying to stick with base/IPT tools.
EDIT: I went ahead and did it in HSYn. I probably could have placed some of the points better, but it's close enough for arm's length with only 11 points. It doesn't really save any time, but I guess that wasn't the goal. There aren't any base/IPT tools to do this though, you'd need MIMT to run this example.
x0 = [0 0.1647 0.2588 0.3412 0.4471 0.5412 0.6353 0.7608 0.8353 0.9451 1];
CT0 = [252 1.806 0.236; 236 1.488 0.4017; 219 1.376 0.4581; 204 1.217 0.5009; ...
187 1.422 0.5166; 170 1.213 0.5772; 128 1.023 0.6381; 57 1.901 0.7024; ...
41 2.418 0.756; 58 4.209 0.8334; 63 6.642 0.8788];
% generate a new uniform table of desired length
N = 256;
xf = linspace(0,1,N);
CT1 = interp1(x0,CT0,xf,'pchip');
% HSY conversions require MIMT
CT1 = ctflop(hsy2rgb(ctflop(CT1),'native'));
% create test sweeps for comparison
% parula() on top, recreated on bottom
CT = parula(N);
testsweeps = cat(3,CT,CT1);
testsweeps = permute(testsweeps,[3 1 2]);
testsweeps = imresize(testsweeps,[128 256],'nearest');
% compare the results
imshow(testsweeps)
There are other attempts that would work prior to R2014b, but both of the above are closer to the version of parula() that would be around in R2020x.
For comparison, R2017b parula() vs R2014b parula() vs paruly()

Image Analyst
Image Analyst le 16 Jan 2023
For anyone interested in the history and rationale of colormaps in MATLAB, see Steve Eddins's Image Processing blog:
Talks about how Parula came about and other "perceptually uniform" colormaps.
  1 commentaire
DGM
DGM le 16 Jan 2023
I didn't notice parula() had been adjusted. That explains the inconsistent clones.

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