I have this piece of code to generate the below plot:
f1 = figure(1);
patch(X,Y,stress_xx,'FaceColor','interp','LineStyle','none');
title('Distribution of stress xx','FontWeight', 'bold');
colormap jet;
axis equal;
How can I smooth the plot so that I won't see the lines in between? FaceColor interp doesn't seem to be working.
Related
Im trying to superimpose a trimesh-plot over a image imshow using hold on. This works fine so far. I'd additionally like to display a colorbar, which works too, but unfortunately it does not adjust to the range specified by caxis, does anyone have an idea how to fix this?
This is an example output: The colourbar should display a range from 1 to z, not from 0 to 60. If we remove imshow everything works fine.
Here my MCVE:
clc;clf;clear
T = [1,2,3;3,1,4]; % triangulation
X = [0,1,1,0]*300; % grid coordinates
Y = [0,0,1,1]*300;
for z = 2:20;
clf;
imshow(imread('board.tif')) % plot image (this is a built in matlab test image)
hold on
Z = [1,1,1,z];
trisurf(T,X,Y,Z) % superimpose plot
colormap hot
caxis([1,z])
colorbar
drawnow
pause(0.5)
end
This appears to be a bug in how older versions of MATLAB handled the colorbar (it's not present with HG2). The "correct" behavior would be that if you have any objects in the current axes that use scaled values, then the colorbar should respect your clims. It seems that MATLAB is using the first child in the current axes to determine whether to respect your clims or not. imshow does not use scaled CDataMapping so colorbar simply ignores your clims.
It looks like you have three options:
Use imagesc rather than imshow
clf;
imagesc(imread('board.tif'));
axis image
hold on
Z = [1,1,1,z];
trisurf(T,X,Y,Z) % superimpose plot
colormap hot
caxis([1,z])
drawnow
colorbar
drawnow
pause(0.5)
Call imshow after you've created your trisurf object
clf;
hold on
Z = [1,1,1,z];
trisurf(T,X,Y,Z) % superimpose plot
colormap hot
him = imshow(imread('board.tif'));
caxis([1,z])
drawnow
colorbar
drawnow
pause(0.5)
Set the CDataMapping property of the image object to 'scaled' (will be ignored when displaying the image since it's RGB but it will allow the colorbar to function properly)
clf;
him = imshow(imread('board.tif'));
set(him, 'CDataMapping', 'scaled')
hold on
Z = [1,1,1,z];
trisurf(T,X,Y,Z) % superimpose plot
colormap hot
caxis([1,z])
drawnow
colorbar
drawnow
pause(0.5)
I would like to plot a contour or contour3 with labeled levels over a surf plot with the same data using Matlab R2015b. Finally the figure is shown from above (the view in negative z-direction) to see the result.
My problem: The labels seem to disappear in the surf area - the product lacks the intended information.
My current test-code with the best result so far:
[X,Y,Z] = peaks;
v = -6:2:8;
hold on
surf(X,Y,Z)
shading interp
contour3(X,Y,Z,v,'k--','ShowText','on')
hold off
colormap default
caxis([-7,9])
view(0,90)
I am not yet allowed to post a picture of the result ..
Related questions in my consideration would be how to change contourf plots location on z-axis or shift the z-value of contour plot in Matlab 2014b to change the z-axis-property of a normal contour plot but they were no solution to my problem or did not work at all.
I finally understood your problem, you can solve it by doing all in 2D like so
[X,Y,Z] = peaks;
v = -6:2:8;
hold on
contourf(x,y,z,500,'LineStyle','none');
[C,h]=contour(x,y,z,v,'k--');
clabel(C,h,'FontSize',15);
caxis([-7,9])
view(0,90)
Could you tell me how to plot in Matlab figure such as below (smooth transition of colors)? Function countour allows only to create plot with contour lines which doesn't provide enough information to me.
You can use imagesc with the 'jet' colormap. Here's an example:
x = conv2( randn(600), fspecial('gaussian',200,20), 'valid'); %// example 2D smooth data
imagesc(x)
colormap(jet)
colorbar
grid
That is not a contour plot!
try imagesc, surf and all of their variants:
http://uk.mathworks.com/help/matlab/surface-and-mesh-plots-1.html
http://uk.mathworks.com/help/matlab/image-file-operations.html
I would like to have a 2D plot along with a 3D surface or mesh plot - shown by the blue line I drew on the surface plot below. How do I get it?
UPDATE: Natan's Solution worked :-) But I now have a new Problem - How do I add 2 Y axis to my MATLAB Plot?
Just add to the surf plot another plot using plot3 where the relevant axis has the limits of the surf plot.
For example:
z=peaks(100);
surface(z, 'EdgeColor', 'none');
colormap(hot)
view(30,30); camlight; axis vis3d
x1=linspace(0,100);
hold on
plot3(x1,0*ones(1,numel(x1)),4*sin(x1))
I have some data (a function of two parameters) stored in a matlab format, and I'd like to use matlab to plot it. Once I read the data in, I use mesh() to make a plot. My mesh() plot gives me the the value of the function as a color and a surface height, like this:
What matlab plotting function should I use to make a 2D mesh plot where the dependent variable is represented as only a color? I'm looking for something like pm3d map in gnuplot.
By default mesh will color surface values based on the (default) jet colormap (i.e. hot is higher). You can additionally use surf for filled surface patches and set the 'EdgeColor' property to 'None' (so the patch edges are non-visible).
[X,Y] = meshgrid(-8:.5:8);
R = sqrt(X.^2 + Y.^2) + eps;
Z = sin(R)./R;
% surface in 3D
figure;
surf(Z,'EdgeColor','None');
2D map: You can get a 2D map by switching the view property of the figure
% 2D map using view
figure;
surf(Z,'EdgeColor','None');
view(2);
... or treating the values in Z as a matrix, viewing it as a scaled image using imagesc and selecting an appropriate colormap.
% using imagesc to view just Z
figure;
imagesc(Z);
colormap jet;
The color pallet of the map is controlled by colormap(map), where map can be custom or any of the built-in colormaps provided by MATLAB:
Update/Refining the map: Several design options on the map (resolution, smoothing, axis etc.) can be controlled by the regular MATLAB options. As #Floris points out, here is a smoothed, equal-axis, no-axis labels maps, adapted to this example:
figure;
surf(X, Y, Z,'EdgeColor', 'None', 'facecolor', 'interp');
view(2);
axis equal;
axis off;
gevang's answer is great. There's another way as well to do this directly by using pcolor. Code:
[X,Y] = meshgrid(-8:.5:8);
R = sqrt(X.^2 + Y.^2) + eps;
Z = sin(R)./R;
figure;
subplot(1,3,1);
pcolor(X,Y,Z);
subplot(1,3,2);
pcolor(X,Y,Z); shading flat;
subplot(1,3,3);
pcolor(X,Y,Z); shading interp;
Output:
Also, pcolor is flat too, as show here (pcolor is the 2d base; the 3d figure above it is generated using mesh):
Note that both pcolor and "surf + view(2)" do not show the last row and the last column of your 2D data.
On the other hand, using imagesc, you have to be careful with the axes. The surf and the imagesc examples in gevang's answer only (almost -- apart from the last row and column) correspond to each other because the 2D sinc function is symmetric.
To illustrate these 2 points, I produced the figure below with the following code:
[x, y] = meshgrid(1:10,1:5);
z = x.^3 + y.^3;
subplot(3,1,1)
imagesc(flipud(z)), axis equal tight, colorbar
set(gca, 'YTick', 1:5, 'YTickLabel', 5:-1:1);
title('imagesc')
subplot(3,1,2)
surf(x,y,z,'EdgeColor','None'), view(2), axis equal tight, colorbar
title('surf with view(2)')
subplot(3,1,3)
imagesc(flipud(z)), axis equal tight, colorbar
axis([0.5 9.5 1.5 5.5])
set(gca, 'YTick', 1:5, 'YTickLabel', 5:-1:1);
title('imagesc cropped')
colormap jet
As you can see the 10th row and 5th column are missing in the surf plot. (You can also see this in images in the other answers.)
Note how you can use the "set(gca, 'YTick'..." (and Xtick) command to set the x and y tick labels properly if x and y are not 1:1:N.
Also note that imagesc only makes sense if your z data correspond to xs and ys are (each) equally spaced. If not you can use surf (and possibly duplicate the last column and row and one more "(end,end)" value -- although that's a kind of a dirty approach).
I also suggest using contourf(Z). For my problem, I wanted to visualize a 3D histogram in 2D, but the contours were too smooth to represent a top view of histogram bars.
So in my case, I prefer to use jucestain's answer. The default shading faceted of pcolor() is more suitable.
However, pcolor() does not use the last row and column of the plotted matrix. For this, I used the padarray() function:
pcolor(padarray(Z,[1 1],0,'post'))
Sorry if that is not really related to the original post