CONTOURF AS PATCH COMMAND

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Mooner Land
Mooner Land 2019-10-29
评论： Mooner Land 2019-11-1
Hello,
I have 3 column matrix. I want to plot contourf but plot shape is wrong. When i try with patch command shape is true. How can i do this with contourf? Here is example picture.
01.jpg
here is my patch figure code:
a=load('xyz.txt');
x=a(:,1);
y=a(:,2);
m1=a(:,3);
cor=[x y];
ff=reshape( 1:length(cor), 4, length(cor)/4)';
fig = figure;
pm=patch('Faces',ff,'Vertices',cor,'FaceVertexCData',m1,'FaceColor','interp','Selected','on');
colormap(flipud(jet(20)))
shading interp
colorbar
set(pm, 'edgecolor','black','LineWidth',0.5)
grid on
grid minor
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Mooner Land
Mooner Land 2019-10-29
here is my code for contourf:
xi=linspace(min(x),max(x),300);
yi=linspace(min(y),max(y),300);
[XI YI]=meshgrid(xi,yi);
M1I = griddata(x,y,m1,XI,YI);
figure
contourf(XI,YI,M1I,'edgecolor','none')
colormap(flipud(jet(10)))
shading interp
colorbar
title('X MOMENT','FontSize',14)
grid on
grid minor
this code plots out of boundaries of shape.
Mooner Land
Mooner Land 2019-10-30
Do you have any idea about this my friends?
I am looking forward to your help :)

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采纳的回答

Walter Roberson
Walter Roberson 2019-10-30
What you observe is expected for griddata() and other scattered interpolants. You do not have data in a number of areas, but you ask for the values in those areas, so griddata() interpolates from the existing points. By asking for data in those areas but wanting blanks there, you are implicitly saying that lack of data in an area should be treated as-if data were there and was NaN there -- but that somehow the system should know to insert those implicit nans locally, and be smart about it. For example in the place where you have two rectangles touching diagonally, you do not want interpolation between the two rectangles, even though some of those points are closer together than some of the points in the bounds that you do want to influence interpolation.
You will need to segment your data into distinct regions and grid them separately.
For the case you loaded the file for, probably the easiest would be to use an editor to divide into parts.
If you had a number of similar files to process, you can do some processing based upon clustering such as k-means, or using nearest-neighbor-with-cutoff approaches, but automatically dividing out touching diagonal boxes is probably going to take more thought.
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Walter Roberson
Walter Roberson 2019-11-1
You could do a morphological dilation on "isnan()" of the array in order to disconnect areas that barely touch.
Mooner Land
Mooner Land 2019-11-1
I am not really good at matlab, so its hard to do this thing. Thank you friend, you are so kind :)

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