I've a 3xN matrix W where N is 50
W(1,1) is x coordinate of a point
W(2,1) is y coordinate of same point
W(3,1) is z coordinate of same point
Similarly:
W(1,2) is x coordinate of another point
W(2,2) is y coordinate of same point
W(3,2) is z coordinate of same point
....
Now I want to 3d plot all these 3d points on same figure using matlab. How can I plot all these
points on same figure?
Is it possible to plot this matrix using a single function call(in matlab)?
I know that plot3 can be used but it can be used for one graph at a time.
So plot3(v(1,1),v(1,2),v(1,3)); is just a single point. But how do I plot all N points?
Is there an easier and better method?
I guess you can use plot3(w(1,:),w(2,:),w(3,:)).
Related
Given some function z = f(x,y), I'm interested in creating a (1D) line plot along an arbitrary cutting plane in x,y,z. How do I do this in Matlab? Slice, for example, provides a higher dimensional version (colormap of density data) but this is not what I'm looking for.
E.g.:
z = peaks(50);
surf(z);
%->plot z along some defined plane in x,y,z...
This has been asked before, e.g. here, but this is the answer given is for reducing 3D data to 2D data, and there is no obvious answer on googling. Thanks.
If the normal vector of the plane you want to slice your surface will always lay in the xy plane, then you can interpolate the data over your surface along the x,y coordinates that are in the slicing line, for example, let the plane be defined as going from the point (0,15) to the point (50,35)
% Create Data
z=peaks(50);
% Create x,y coordinates of the data
[x,y]=meshgrid(1:50);
% Plot Data and the slicing plane
surf(z);
hold on
patch([0,0,50,50],[15,15,35,35],[10,-10,-10,10],'w','FaceAlpha',0.7);
% Plot an arbitrary origin axis for the slicing plane, this will be relevant later
plot3([0,0],[15,15],[-10,10],'r','linewidth',3);
Since it is a plane, is relatively easy to obtain the x,y coordinates alogn the slicing plane with linspace, I'll get 100 points, and then interpolate those 100 points into the original data.
% Create x and y over the slicing plane
xq=linspace(0,50,100);
yq=linspace(15,35,100);
% Interpolate over the surface
zq=interp2(x,y,z,xq,yq);
Now that we have the values of z, we need against what to plot them against, that's where you need to define an arbitrary origin axis for your splicing plane, I defined mine at (0,15) for convenience sake, then calculate the distance of every x,y pair to this axis, and then we can plot the obtained z against this distance.
dq=sqrt((xq-0).^2 + (yq-15).^2);
plot(dq,zq)
axis([min(dq),max(dq),-10,10]) % to mantain a good perspective
I have 3D matrix (100*50*10) and I want to plot one specific point in all slices. Let us say point (10*6*:). The plot should be in 2D plane
Example (I have this coordinate for point that I want to plot)
x (10*6*1)
x (10*6*2)
x (10*6*3)
x (10*6*4)
x (10*6*5)
x (10*6*6)
x (10*6*7)
x (10*6*8)
x (10*6*9)
x (10*6*10)
I tried plot (x(10,6,:)) but I got error
plot(squeeze(x(10,6,:)))
see: https://www.mathworks.com/help/matlab/ref/squeeze.html
x(10,6,:) is still a 3D matrix, and needs to be reduced to a 1D form before plotting it. This is where the squeeze function comes in.
Given a matrix nx3 that represents n points in 3D space. All points lie on a plane. The plane is given by its normal and a point lying on it. Is there a Matlab function or any Matlabby way to find the area directly from the matrix?
What i was trying to do is write a function that first computes the centroid,c, of the n-gon. Then form triangles : (1,2,c),(2,3,c),...,(n,1,c). Compute their area and sum up. But then i had to organise the polygon points in a cyclic order as they were unordered which i figured was hard. Is there a easy way to do so?
Is there a easier way in Matlab to just call some function on the matrix?
Here is perhaps an easier method.
First suppose that your plane is not parallel to the z-axis.
Then project the polygon down to the xy-plane simply by removing the 3rd coordinate.
Now compute the area A' in the xy-plane by the usual techniques.
If your plane makes an angle θ with the xy-plane, then your 3D
area A = A' / cos θ.
If your plane is parallel to the z-axis, do the same computation
w.r.t. the y-axis instead, projecting to the xz-plane.
To project from 3D to the plane normal to N, take some non-parallel vector A and compute the cross products U = N x A and V = N x U. After normalizing U and V, the dot products P.U and P.V give you 2D coordinates in the plane.
Joseph's solution is even easier (I'd recommend to drop the coordinate with the smallest absolute cosine).
You said the points all lie on a plane and you have the normal. You should then be able to reproject the 3-D points into 2-D coordinates in a new 2-D basis. I am not aware of a canned function in Matlab to do this , but coding it should not be difficult, this answer from Math.SE and this Matlab Central post should help you.
If you already solved the problem of finding the coordinates of the points in the 2-D plane they are in, you could use the Matlab boundary or convex hull function to compute the area of the boundary or convex hull enclosing the points.
[k,v]= boundary(x,y)
or
[k,v] =convhull(x,y)
where k is the vector of indices into points x,y, that define the boundary or convex hull, v is the area enclosed, and x, y are vectors of the x and y coordinates of your points.
What you were describing with trying to find triangles with the points sounds like a first attempt toward Delaunay triangulation. I think more recent versions of Matlab have functions to do Delaunay triangulation as well.
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.
I've run simulations which have given me data points corresponding to X number of different radii, and Y number of angles each one was evaluated at. This means that I have X times Y data points which I need to plot.
I am currently plotting it in an non-ideal fashion: I am using the x and y axes as the r and theta axes. This means that my data appears as a sinusoidal trend which increases with radius on a Cartesian grid, not the circle which it physically represents. This is how I am currently plotting my data:
surf(r_val, th_val, v_val);
What I wish to do is plot my data on a cylindrical axis, such like that of the function polar(), but in R3 space. I would rather not download a toolbox, or modify the existing polar function; if there is no other solution then I will obviously end up doing this anyways.
Thanks for your help!
G.
Also, I am using Matlab 2012a
EDIT:
r_val = 1x8 vector containing unique radii
th_val = 1x16 vector containing unique angles
v_val = 8x16 matrix containing voltages corresponding to each position
NOTE: (after answered)
The truly ideal solution does not exist to this problem, as Matlab currently supports no true polar axes methods. Resource found here.
You should transform your coordinates to Cartesian coordinates before plotting them. MATLAB has builtin functions for perfroming coordiante transformations. See, for example pol2cart, which transforms polar or cylindrical coordinates to Cartesian coordinates. In your case you would simply use something like:
[x, y] = pol2cart(th_val, r_val);
surf(x, y, v_val);
Edit: Given that th_val and r_val are vectors of differing lengths it is necessary to first create a grid of points before calling pol2cart, along the lines of:
[R, T] = meshgrid(r_val, th_val);
[x, y] = pol2cart(T, R);
surf(x, y, v_val);