set NaN as another color than default using imagesc
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Hello, I have a matrix filled probability numbers (i.e. ranging from 0 to 1) or NaN when the probability is not computed. I would like to display this matrix as a color table (e.g. using imagesc), in order to have a quick visualisation of the result. The colorbar range is thus set as 0 to 1 since I am interested in probability values. However, I would like the NaN fields to appear with another color than the default "-inf" (here the color of 0 since the down limit for the color is set for value 0), for example gray. How can I do this? Thank you very much, Gaelle
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Charles Krzysik
2017-4-27
If you want to use imagesc rather than pcolor, you can set the AlphaData property to zero everywhere you have a NaN. This will show the background wherever there is no data; you can then additionally set the background colour, if you so choose. In this example I'm setting it to black:
imAlpha=ones(size(Data_Array));
imAlpha(isnan(Data_Array))=0;
imagesc(Data_Array,'AlphaData',imAlpha);
set(gca,'color',0*[1 1 1]);
4 个评论
JoeB
2017-9-13
This is a really nice answer. Reading in netCDF files with missing values yields NaNs in MATLAB, so this allows me to make quick maps with the NaNs masked out.
teng zhang
2018-1-12
It is so nice for your answer.
TheStranger
2021-6-2
编辑:TheStranger
2021-6-2
This is the most useful comment of this thread, yet not with the most votes!
Maria Cristina Araya Rodriguez
2023-11-17
I agree, many thanks, in fact this is a good solution when using a ".cpt" colour scale.
Lauren
2017-11-7
21 个投票
imagesc(data,'AlphaData',~isnan(data))
8 个评论
Huayan Wang
2018-2-20
编辑:Huayan Wang
2018-2-20
I have to say this is a genius solution!
Thank you so much! This helps me a lot!
Xiaowei Zhou
2019-1-11
Excellent idea.
Walter Roberson
2019-1-11
you might need double(~isnan(data)) as alphadata cannot be logical .
Shakir Hussain
2019-3-18
How to use it for array data, it is giving error for array data(3d)
Error using image
Bad property value found.
Object Name: image
Property Name: 'AlphaData'.
Error in imagesc (line 20)
hh = image(varargin{:},'CDataMapping','scaled');
Walter Roberson
2019-3-18
please show your code calling imagesc
jichong han
2021-12-1
perfect
zhou weiyan
2023-3-24
perfect
Walter Roberson
2023-11-17
If you have RGB data, some elements of which might be NaN, then
%with sufficiently new versions of MATLAB
scaled_data = rescale(YourRGBData, 0, 1);
alpha_data = 0 + ~any(isnan(YourRGBData), 3);
image(scaled_data, 'AlphaData', alpha_data);
%older versions of MATLAB
scaled_data = mat2gray(YourRGBData);
alpha_data = 0 + ~any(isnan(YourRGBData), 3);
image(scaled_data, 'AlphaData', alpha_data);
In practice if your RGB data is single or double precision data that uses only integral values 0 to 255, but also has some NaN, then you would probably use slightly different code,
scaled_data = uint8(YourRGBData);
alpha_data = 0 + ~any(isnan(YourRGBData), 3);
image(scaled_data, 'AlphaData', alpha_data);
You can use the isnan function to find the indices of all NaNs, then set those elements to another value:
Example:
>>A = [4 NaN 3;NaN 2 1];
>>A(isnan(A)) = 255
A =
4 255 3
255 2 1
6 个评论
It depends. You always run the risk of setting the pixels in question to a value that is already used if you don't know anything specific about your image data.
Are you just wanting to visualize where your data returns as NaN? If so, I would do one of two things: I would plot my "good" data as grayscale, then turn the NaN pixels to a easily noticeable color like red. Alternatively, if you must have or prefer your data in color, you could plot your image then overlay a scatter plot where your elements are NaN.
Here's an example showing the first way:
A = rand(50); %random data
for i = 1:10 %turn some random points into NaNs
A(randi(50),randi(50),:) = NaN;
end
R = A(:,:,1); % turn your data into a "pseudo-gray" rgb image.
G = A(:,:,1);
B = A(:,:,1);
R(isnan(A(:,:,1))) = 1; %turn NaNs red
G(isnan(A(:,:,1))) = 0;
B(isnan(A(:,:,1))) = 0;
A(:,:,1) = R; %combine color slices into A
A(:,:,2) = G;
A(:,:,3) = B;
imagesc(A)
Here's an example for the second:
A = rand(50); %random data
for i = 1:10 %turn some random points into NaNs
A(randi(50),randi(50),:) = NaN;
end
imagesc(A)
hold on
[ii jj] = find(isnan(A));
scatter(ii,jj,'ok','MarkerEdgeColor',[1 1 1],'MarkerFaceColor',[0 0 0],'LineWidth',2,'SizeData',100)
Adil Masood
2015-12-10
移动:DGM
2023-3-25
Thanks you for a smart solution. There is just one correction: Instead of
scatter(ii,jj,'ok','MarkerEdgeColor',[1 1 1],'MarkerFaceColor',[0 0 0],'LineWidth',2,'SizeData',100)
it should be
scatter(jj,ii,'ok','MarkerEdgeColor',[1 1 1],'MarkerFaceColor',[0 0 0],'LineWidth',2,'SizeData',100)
Its because imagesc() plots elements of matrix indexed as (row,column), while scatter() handles elements as (x,y).
If using pcolor, NaNs are set to the axis background color. So you can set your colormap to color non-NaNs, and set the axis background color to set the color for NaNs. For example, to set NaNs black you can use: set(gca,'color','k')
1 个评论
Walter Roberson
2017-1-20
For pcolor the nan are not exactly set to the axes background color: instead a hole is created that allows whatever is under to be visible. If nothing else is there that would be the axes background, but there could also be a different graphics object there.
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