When you want to plot scatter points with fixed alpha value in Matlab, you may the patch function, like advised in this SO question. But when you want to plot a high number of individual points, you should use the plot function, as advised in this SO question.
Is it still possible to plot a high number of scatter points with fixed alpha value in Matlab ?
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I am trying to write a MATLAB script to give me a contour map. The contour map must be created from inputs that I generated from 100 images.
The story is like this:
I have 100 images on which I ran an image processing algorithm for optimization. Now, I got their energy curves. So, I have 100 energy curves. I want to create a contour map that will show me where the points are denser on the plot. (the energy curves are plotted as energy vs. iteration with fixed number of iterations)
The following is my variable:
energy(iteration,numImages)
Hope I explained it well.
Thanks in advance.
I interpret your question to boil down to how can I create a surface plot with colors according to the energy found in energy. I would solve this by using the contour function with a grid generated using meshgrid. If each image is described in 1000 data points with 100 files the plot can be generated as follows:
% using stuff as random junk instead of energy
numPoints = 1000;
numFiles = 100;
stuff = rand(1000,100); % replace with actual information
[X, Y] = meshgrid(1:numFiles, 1:numPoints);
contour(X,Y,stuff);
You can also create a 3D surface plot using surf and the same logic.
From what i see of you graph (and using the comments also), one possible way is to use plot3 to plot a line in 3D for every plot.
For doing so, you can use something like this code:
x=(0:0.01:1)';
aexp=zeros(100,numel(x));
hold on
for ii=1:100;
% aexp(ii,:)=exp((-x+ii/10)); %exponential
aexp(ii,:)=exp(-(x-ii/100).^2); %~gaussian
% aexp(ii,:)= x*ii; %linear increase
plot3(x,aexp(ii,:),ii*ones(1,numel(x)));
end
% set(gca,'yscale','log'); % uncomment if you need logscale.
giving
I have a few options of plot. It always plot from the XY view. I changed by hand, but you can use the view command. Notice that i used a simple counter to make the spacing in the z direction.
In a similar manner, you can plot using the contour. For my code, after the data have been generated in the for loop, remove/comment the plot3 and add:
contour(aexp) %outside the for loop,
giving
Notice that i have not really take care what i'm plotting. You can find more info on contour in the Matlab page .
You commented that the x-axis should be number of iterations, y-axis should be energy and z-axis should be the information containing how many lines are passing through from some areas. For this, make a qq variable, being it qq=number_of_lines(number of iterations,energy) . Make a discrete grid for the energy if you don't have one. Number of iterations is probably discrete anyway. The function is you who need to devise, but i would go for something which checks the number of lines for every energy and every iteration. In this case you will have the z-function that depends on y and x, that is the case to use contour or surface.
My function above make a line for every ii point, to have a 3d function. An edition for another extra loop is not hard. Just remember to have the same regular grid for every point, otherwise you will have trouble.
Is it possible to make a plot in matlab that does not actually take the logs of the values? I'm plotting wide ranges of values and when I try to make a log plot of them, those below 1 become negative. I would just like it to plot the values on a log scale without taking their logs.
Alternatively, set(gca,'XScale','log') if you have your plot already.
Yes, it is possible. Use the loglog command.
The example from the Mathworks website:
x = logspace(-1,2); % generate a sequence of points equally spaced logarithmically
loglog(x,exp(x),'-s')
grid on
If you do not want both axes to be log scale, use semilogx or semilogy.
So, you want to plot liner data on logarithmic axes? You can exponentiate you values before using the log plot. This way the point p=(10,3) will plot at the x=10 position.
I want to visualize 4 vectors of scattered data with a surface plot. 3 vectors should be the coordinates. In addition the 4th vector should represent a surface color.
My first approach was to plot this data (xk,yk,zk,ck) using
scatHand = scatter3(xk,yk,zk,'*');
set(scatHand, 'CData', ck);
caxis([min(ck), max(ck)])
As a result I get scattered points of different color. As these points lie on the surface of a hemisphere it ist possible to get colored faces instead of just points. I replace the scattered points by a surface using griddata to first build an approximation
xk2=sort(unique(xk));
yk2=sort(unique(yk));
[xxk, yyk]=meshgrid(xk2, yk2);
zzk=griddata(xk,yk,zk,xxk,yyk,'cubic');
cck=griddata(xk,yk,clr,xxk,yyk,'cubic');
surf(xxk,yyk,zzk,cck);
shading flat;
This is already nearly what I want except that the bottom of the hemisphere is ragged. Of course if I increase the interpolation point numbers it gets better but than the handling of the plot gets also slow. So I wonder if there is an easy way to force the interpolation function to do a clear break. In addition it seems that the ragged border is because the value of zzk gets 'NaN' outside the circle the hemisphere shares with the z=0-plane.
The red points at the top are the first several entries of the original scattered data.
You can set the ZLim option to slice the plotted values within a certain range.
set(gca, 'Zlim', [min_value max_value])
I want to plot an inequality in 3d using surf. My condition is
0<=x<=1
0<=y<=1
0<=z<=x/(1+y)
I can create a surface plot using the following commands
[x y]=meshgrid(0:0.01:1);
z=x./(1+y);
surf(x,y,z);
This plot gives me regions where z=x/(1+y) but I am interested in regions where 0<=z<=x/(1+y) over all values of x and y. However, I am unable to plot/color the region explicitly. Can you please help.
A similar question has been asked but there was no acceptable answer and my question is also different.
Using isosurface you can show the boundary. There are two options, first create the points
[X,Y,Z]=meshgrid(0:.01:1);
then plot the boundaries in the z-direction (i.e. Z=0 and Z=X./(1+Y))
isosurface(X,Y,Z,Z.*(X./(1+Y)-Z),0)
or plot all the boundaries (including X=0, X=1, Y=0 and Y=1)
isosurface(X,Y,Z,Z.*(X./(1+Y)-Z).*X.*(X-1).*Y.*(Y-1),0)
All you have to do is come up with a function that is constant on any boundary, its value inside or outside is irrelevant as long as it is not zero.
I have a formula that depends on theta and phi (spherical coordinates 0<=theta<=2*pi and 0<=phi<=pi). By inserting each engle, I obtained a quantity. Now I have a set of data for different angles and I need to plot the surface. My data is a 180*360 matrix, so I am not sure if I can use SURF or MESH or PLOT3. The figure should be a surface that include all data and the axes should be in terms of the quantity, not the quantity versus the angles. How can I plot such a surface?
I see no reason why you cannot use mesh or surf to plot such data. Another option I tend to use is that of density plots. You basically display the dependent variable (quantity) as an image and include the independent variables (angles) along the axis, much like you would with the aforementioned 3D plotting functions. This can be done with imagesc.
Typically you would want your axes to be the dependent variables. Could you elaborate more on this point?
If I understand you correctly you have calculated a function f(theta,phi) and now you want to plot the surface containing all the points with the polar coordinated (r,theta,phi) where r=f(theta,phi).
If this is what you want to do, the 2D version of such a plot is included in MATLAB under the name polar. Unfortunately, as you pointed out, polar3 on MatlabCentral is not the generalization you are looking for.
I have been able to plot a sphere with the following code, using constant r=1. You can give it a try with your function:
phi1=0:1/(3*pi):pi; %# this would be your 180 points
theta1=-pi:1/(3*pi):pi; % your 360 points
r=ones(numel(theta1),numel(phi1));
[phi,theta]=meshgrid(phi1,theta1);
x=r.*sin(theta).*cos(phi);
y=r.*sin(theta).*sin(phi);
z=r.*cos(theta);
tri=delaunay(x(:),y(:),z(:));
trisurf(tri,x,y,z);
From my tests it seems that delaunay also includes a lot of triangles which go through the volume of my sphere, so it seems this is not optimal. So maybe you can have a look at fill3 and construct the triangles it draws itself: as a first approximation, you could have the points [x(n,m) x(n+1,m) x(n,m+1)] combined into one triangle, and [x(n+1,m) x(n+1,m+1) x(n+1,m+1)] into another...?