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Changing the colour intensity of a 2D plot

Asked by John on 25 Dec 2012

Hi,

I'm plotting lat long data on a map like this.

I'm using the plotm() function:

plotm(x,y,'LineStyle','none','Marker','o','MarkerSize',20);

I'm trying to change the colours so that areas with more data are a different colour. I would like the intensity of the colour to change with the amount of data points.

Would anybody know how I could achieve this?

Thanks

0 Comments

John

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2 Answers

Answer by Walter Roberson on 26 Dec 2012

plotm() cannot have different colors within any one line (column of data).

There are tricks for using patch() for drawing very narrow lines.

It appears to me that your data is sufficiently dense that you could use scatterm() and have the output look relatively continuous. scatterm() accepts a matrix of colors, one RGB row per point.

11 Comments

John on 14 Jan 2013

Hello Walter and Image Analyst,

Walter, thanks for your help, the change you suggested to rgbarray changed the color intensity slightly but the majority of the points are black with a bit more dark blue. I was hoping to get the colors more variable as it is difficult to distinguish between he two.

Image Analyst, thanks for your suggestion, I will try your code and will post later with the results.

All the best

Walter Roberson on 14 Jan 2013

What I think I would suggest at this point is to use interp1() on relative_counts, using a look-up table that emphasized the low values but still had high values. For example,

mapval = interp1( 0:.1:1, [0 .3 .5 .7 .725 .75 .775 .8 .825 .9 1], relative_counts);
rgbarray = [zeros(length(x), 2), mapval(:)];

You would adjust the first parameter (possibly unevenly) according to where you wanted the intensity boundaries to be, and would adjust the second parameter according to the percentage blue you wanted each range to show up with.

John on 17 Jan 2013

Hello Walter,

I tried your new suggestion. Unfortunately the points were all black, similar to the image posted below on Image Analyst's post. When you say 'adjust the first parameter', do mean, 0:.1:1? What would you suggest I change it to? Apologies for all the questions but I don't really understand the code and I'm not sure on how to proceed.

Thank you

Walter Roberson
Answer by Image Analyst on 26 Dec 2012
Edited by Image Analyst on 13 Jan 2013

If you treat it as an image you could do that, with some work. You could run the thing through a convolution, conv2(). This would give you a higher signal where the roads are more dense. Essentially that is an indexed image. Then you apply a colormap to it, and call ind2rgb to turn it into a color image. Then you use the roads as a mask over the color image so that roads in concentrated areas show up as a different color than roads in sparse areas. Hopefully that described it enough for you to carry out the code. Though I think this representation would be very confusing and distracting to look at.

for k = 1 : length(x)
  yourImage(round(y(k)), round(x(k)) = 1;
end
densityImage = conv2(yourImage, ones(5)/25, 'same');
imshow(densityImage, []);
colormap(jet(256));

6 Comments

Image Analyst on 14 Jan 2013

Can you upload the image? The fig file is no good to me. But I'm not sure how the x,y would correspond to pixels. I don't have the mapping toolbox so I'd probably have to calibrate the x,y to pixel row,column locations.

John on 16 Jan 2013

Hello Image Analyst,

I am not using the mapping toolbox to source the image. I am using this file on the file exchange to retrieve the map and then I just overlay the data on it. I code I use is below:

http://www.mathworks.com/matlabcentral/fileexchange/27627

 latlim = [53.0 53.6];
 lonlim = [-6.5 -6];
  figure
  axis([lonlim, latlim])
  axis image
  plot_google_map
  hold on
  plot(x,y,'LineStyle','none','Marker','.','MarkerSize',3);

The x and y data (GPS) is in this file.

https://dl.dropbox.com/u/54057365/All/gpsdata.mat

Would your method be possible with this setup?

Thank you

An example:

John on 19 Jan 2013

Hello Walter and Image Analyst,

Just wondering if you have had any further thoughts on this?

Thanks

Image Analyst

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