Issue Plotting Array in Imagesc

I am trying to plot an array as an imagesc plot. The array is full of non-zero numbers, but imagesc plots them as zero. I think the issue is with scaling, but I don't know how to fix it. Screenshots attached to show what I mean. How do I scale my imagesc plot so that the numbers in the array are visible appropriately? Tried looking it up on the documentation but couldn't find a clear answer for my problem.

[Dyuman Joshi]

Try taking the log() of the absolute values of the data and see what the result is.

I suspect as most of the data (as seen in the image attached above), is around ~10^10, which is 0.001x10^13, thus the data looks closer to the 0.5x10^13 than to the max value.

If the problem still persists, please attach the data file using the paperclip button.

[DGM]

It might be worth looking at a histogram of the data to see if it would be prudent to pick colorscale limits other than the data extrema.

[Mathieu NOE]

hello @Rose

it would help if you could share your data (and code if you have one)

Answer 1

[Jatin Singh]

Hi,

This happens when “imagesc” automatically tries to scale the colormap based on the range of data in array. It makes it harder to visualise large range data using colormap if there are few outliers.

Few things that you might want to try are:

1. Remove outliers from the data, this will make the visualisation of data better using automatic colormap scaling.
2. Manually set the colormap limits using the “clim” property of the “imagesc” function, which allows you to define the range of data values that map to the colours.

For e.g.,

data = rand(10, 10) * 100; 
% Create the imagesc plot
figure;
imagesc(data);
colorbar; 
% Set the colour limits to the min and max of the data
clim([min(data(:)), max(data(:))]);

Kindly refer to “clim” documentation using link mentioned below:https://www.mathworks.com/help/releases/R2023b/matlab/ref/clim.html

[DGM]

Your example does the opposite of what your text describes. Using imagesc() already sets CDataMapping to 'scaled' and sets clim to the data extrema by default.

As you say, you either need to remove outliers, or simply pick different limits for clim().

% a bunch of data close to zero, but with very wide tails
A = 1E6./randn(1000);
histogram(A)

% default scaling
imagesc(A)

% pick better limits
pct = 10;
newrange = prctile(A,[pct 100-pct],'all');
imagesc(A)
clim(newrange)

[Jatin Singh]

Hi @DGM, I stated the example just to show how "clim" can be used, but you are right I could have used a better limit. Thanks for your informative example.