How to plot overlapping images with matlab - matlab

I have several dataset matrices x, y, andz, where z contains values at the positions x,y showing shifted (overlapping) parts of the same picture. x and y are rectangularly centered around different center positions for each dataset.
How can I combine the data in one plot using pcolor or similar? Note that it should be a rectangular plot in the end, but that not all data points are given due to the shift.

I now solved my own question by using the command hold on, which makes it possible to plot several times into the same figure. You just have to run it in between two plot commands.

Related

Filling area of multiple contour plots that satisfies a condition in MATLAB

I have a 3D data, the x and y axis are angles and the Z axis is output. so the data is like this: [angle1 x angle2 x Z] ... I have multiple Z values at different conditions as well. Let's assume different Z values for 10 different conditions.
I want to plot a 3D contour of all the Z values overlaid on top of each other and at the same time fill the areas of each contour where Z<=-1 with a desired color ... How is that possible in MATLAB?
I found a way to overlay all the Z values on top of each other using a single color and contour command but I cannot find any way to fill the areas of Z<=-1 ... I realized that in contour command, MATLAB actually fill the whole graph with colors, so "hold on" command does not work here!
Here is an example image I want to create
Below is the example I could create but I cannot create the colored plot

Matlab or Origin - Combining two sets of 3D data in one contour plot

I have two sets of 3D data with XYZ coordinates. I would like to know if there is a program that can combine the two, such that:
One set of data is represented by the colours of the plot, and the other set of data is represented by the height (in 3D) of the plot.
I am familiar with both Matlab and Origin.
Can be done with surf(Z,C).
a = randi(20,20,20);
b = randi(20,20,20);
figure;
subplot(2,2,1);
surf(a);
title('Height');
subplot(2,2,2);
surf(b);
title('Color');
subplot(2,2,[3,4]);
surf(a,b);
title('Mixed');
Not the best representations but you can see one matrix yields height and one yields color.
Color of mixed plot comes from right plot
Height of mixed plot comes from left plot
It is easy if you use scatter3 function.
w=100;
x1=rand(1,w);
y1=rand(1,w);
z1=rand(1,w)*100;
z2=ceil(rand(1,w)*255);
figure
h=scatter3(x1,y1,z1,ones(1,w)*50,z2,'filled');

Improve surface plot visualisation of scatter points

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])

matlab - plot inequality in 3d with surf

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.

How to set an arbitrary direction on a contour plot to perform operation in Matlab

I am looking for help for my particular problem.
I have a contour plot created from XYZ data. This plot contains 2 broad peaks with one more intense than the other.
When the most intense peak is aligned with the Y axis, I can perform a fitting of every YZ curve at each X values. I usually do a gaussian fit to plot the peak center on the same graph.
In some cases I need to perform the same fitting but no along the Y axis direction (in this case I just plot YZ scan at every different X values) but along another arbitrary direction.
For the moment the only way I found is the following:
-plot the contour plot and find for the position of the most intense peak
-if the position is not aligned with the Y axis, then rotate all the datas and plot again the contour
-perform the YZ gaussian fit for every X value
- Rotate the resulting XY position to go back to the original plot
-plot the XY position as a line on the original contour plot
this is quite long and requires a lot of memory. i would like ot know if there is a more elegant/faster way.
Thanks for your help
David
I take it you want to extract data from the (x,y,z) data along some arbitrary line in order to make a fit. A contour plot will show only part of the data, the full z(x,y) data can be shown with imagesc etc. Say you want the data along line defined by two points (x1,y1) -> (x2,y2). According to the eq of the line, the line y=a*x+b the slope a is (y2-y1)/(x2-x1) and b=y1-a*x1. For example, I'll select (x,y) coordinates in the following contour:
Create data and end points:
m=peaks(100);
x1=11 ; x2=97;
y1=66; y2=40;
Thus the line parameters are:
a=(y2-y1)/(x2-x1);
b=y1-a*x1;
and the line is:
x=x1:x2;
y=round(a*x+b);
select the proper (x,y) elements using linear indexing:
ind=sub2ind(size(m),y,x)
plot:
subplot(2,1,1)
contour(m,10); hold on
line([x1 x2],[y1 y2],'Color',[1 0 0]);
subplot(2,1,2)
plot(m(ind))
You can now use vec=m(ind) to fit your function.