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List:       scilab-users
Subject:    Re: [Scilab-users] ?==?utf-8?q? Scilab checkerboard plot (grayplot)
From:       Ekin Akoglu <ekinakoglu () gmail ! com>
Date:       2017-04-21 12:27:03
Message-ID: da3d48d5-7349-0bf3-ac74-18eb33a0e8f6 () gmail ! com
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Dear Antoine,

Thank you very much for the resolution. It solves my problem by 
producing a graphically consistent plot. However, data-wise, the 
colorbar does not match the plot unless I rescale it to (1,32). I want 
to be able to infer the approximate value of the data from the colors. 
However, thank you.

Kind regards,

Ekin


On 21/04/17 14:25, Antoine Monmayrant wrote:
> Le Vendredi, Avril 21, 2017 11:19 CEST, Ekin Akoglu <ekinakoglu@gmail.com> a \
> écrit: 
> > Dear all,
> > 
> > I am producing a checkerboard plot with Scilab and the plot seems
> > erroneously colored. The matrix I plot is attached as well as the
> > scripts to plot and the plot produced by Scilab.
> > 
> > The problem is that the data at matrix(1,3) and matrix(1,4) are equal,
> > however, on the plot produced by Scilab it is represented by different
> > colors (plants vs det. feeders and plants vs carnivores on the plot).
> > Let me remind you that the plot is transposed form of the matrix.
> > 
> > I would appreciate any help on the matter.
> > 
> > Kind regards,
> > 
> > Ekin
> > 
> 
> Hello,
> 
> The default behavior for grayplot is to paint a given pixel (a given square) with \
>                 the color corresponding to its four corners.
> See: "help data_mapping"
> You can either change the data_mapping after calling grayplot or use Matplot.
> However, you'll have to rescale your data so that it ranges from 1 to nc where nc \
> is the number of colors in your color_map. See my modified function below.
> Does it solve your problem?
> 
> Cheers,
> 
> Antoine
> 
> function myMTIplot(data)
> 
> [nrows ncols] = size(data);
> 
> data = [zeros(1,ncols); data; zeros(1,ncols)];
> data = [zeros(1,nrows+2)' data zeros(1,nrows+2)'];
> 
> [nrows ncols] = size(data);
> 
> figure1 = scf();
> a = newaxes();
> 
> colorbar(-1, 1);
> grayplot(1:nrows, 1:ncols, data);
> 
> figure1.color_map = jetcolormap(32);
> 
> a.y_label.text = "Impacted Group";
> a.y_label.font_size = 4;
> a.x_label.text = "Impacting Group";
> a.x_label.font_size = 4;
> a.title.text = "Relative MTI";
> a.title.font_size = 5;
> a.font_size = 4;
> a.data_bounds = [1, 6, 1, 6];
> 
> a.x_ticks = tlist(["ticks", "locations", "labels"], (1.5:1:5.5), ["Plants", \
> "Bacteria", "Det. Feeders", "Carnivores", "Detritus"]); a.y_ticks = tlist(["ticks", \
> "locations", "labels"], (1.5:1:5.5), ["Plants", "Bacteria", "Det. Feeders", \
> "Carnivores", "Detritus"]); 
> 
> //new version without interpolation
> // we rescale the data so that is goes from 1 to 32
> dat=(data-min(data))/(max(data)-min(data))*31+1;
> figure2 = scf();
> a = newaxes();
> 
> colorbar(-1, 1);
> grayplot(1:nrows, 1:ncols, dat);
> e=gce();e.data_mapping="direct";//no interpolation
> 
> figure2.color_map = jetcolormap(32);
> 
> a.y_label.text = "Impacted Group";
> a.y_label.font_size = 4;
> a.x_label.text = "Impacting Group";
> a.x_label.font_size = 4;
> a.title.text = "Relative MTI";
> a.title.font_size = 5;
> a.font_size = 4;
> a.data_bounds = [1, 6, 1, 6];
> 
> a.x_ticks = tlist(["ticks", "locations", "labels"], (1.5:1:5.5), ["Plants", \
> "Bacteria", "Det. Feeders", "Carnivores", "Detritus"]); a.y_ticks = tlist(["ticks", \
> "locations", "labels"], (1.5:1:5.5), ["Plants", "Bacteria", "Det. Feeders", \
> "Carnivores", "Detritus"]); 
> 
> endfunction
> 
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