Smooth edge contour plot - matlab

Question

Hello
I want to represent data with 2 variables (latitude and longitude) in 2D format. The value is represented by color and the 2 variables as the 2 axis and I am using the contourf function to plot my data. All the data comes from a xlsx file and I put it in a matrix.
Locations = xlsread('Availability results.xlsx');
column_numberloc = 1; % Column in the locations file containing the number of the locations
column_latitude = 2; % Column in the locations file containing the latitude of the locations
column_longitude = 3; % Column in the locations file containing the longitude of the locations
column_availability = 4; % Column in the locations file containing the availability of the locations
min_latitude = min(Locations(:,column_latitude));
max_latitude = max(Locations(:,column_latitude));
min_longitude = min(Locations(:,column_longitude));
max_longitude = max(Locations(:,column_longitude));
max_availability = max(Locations(:,column_availability));
min_availability = min(Locations(:,column_availability));
longitude = Locations(:,column_longitude);
latitude = Locations(:,column_latitude);
Contour = zeros(23,17);
for numerofile=1:204
[coord_x,coord_y] =transformation(Locations(numerofile,column_latitude),Locations(numerofile,column_longitude));
Contour(coord_x,coord_y) = Locations(numerofile,column_availability);
end
for i=1:23
for j=1:17
if Contour(i,j) == 0
Contour(i,j) = NaN;
end
end
end
cMap=jet(256);
figure(1);
x = linspace(min_longitude,max_longitude,17);
y = linspace(min_latitude,max_latitude,23);
newpoints = 100;
[xq,yq] = meshgrid(linspace(min(x),max(x),newpoints),linspace(min(y),max(y),newpoints ));
Contourq = interp2(x,y,Contour,xq,yq,'linear',max_availability);
[c,h]=contourf(xq,yq,Contourq,100);
%[c,h]=contourf(x,y,Contour,50);
set(h, 'edgecolor','none');
colormap(cMap);
cb=colorbar;
caxis([min_availability max_availability]);
The transformation function allows me to place all the data in the Contour matrix as it associate a longitude and a latitude to a row and a column.
I've putted a NaN for every data equal to zero to have a better look at my data and I obtained this :
interpolation_linear
Which is nice but I wanted this data to be close to :
Without interpolation
So, I decided to change the linear interpolation to a 'nearest' interpolation and I got this :
interpolation_nearest
I can see more data but the contour plot isn't as smooth as with the linear interpolation.
I've seen many posts about how to make smooth contour plot (that's how I found the function 'interp2') but I think that my problem comes from the NaN data which prevent me from having a smooth contour plot at the edge between NaN values and the rest like the first image but with enough data like the third image.
My question is : Do you know how can I get a smooth edge contour plot with enough data thanks to the nearest interpolation but with a nice visual like the first image ?
Thank you very much

Answer 1

Since you are doing an interpolation on a square grid, you could directly display a 2D image with imagesc.
The advantage is that you can access the AlphaData property of image objects, which can be used as a display mask.
r=rand(50); % random 50x50 array
r(11:20,11:20)=NaN; % some hole filled with NaN
imagesc(r) % show the image, with NaN considered as the lowest value in color scale
imagesc(r,'AlphaData',~isnan(r)) % show the image, with NaN values set as fully transparent
You may also then:
set a display mask first
replace zeros or NaN with some meaningful values (nearest non NaN value?)
interpolate with interp2, perhaps even with the 'cubic' parameter for improved smoothness
display only the meaningful part of the image thanks to the display mask set in AlphaData.