I have a matrix called 'totalAverage' with this size:
size(totalAverage)
ans =
65 110
When I run surf(totalAverage)) it shows a 3d-surf plot.
However I want X-values of surf plot be mapped with special values brought from a matrix called time_matrix_filtered. Currently surf plot is labeled from (1-110) according to matrix size in AXIS-X.
How can I plot the same surf but have X-Values brought from time_matrix_filtered? I tried something like surf(time_matrix_filtered,totalAverage) which works for plot but I don't know the right notation for this special case?
Size of time_matrix_filtered is as below:
size(time_matrix_filtered)
ans =
110 1
You need Y values too:
surf(time_matrix_filtered, 1:65, totalAverage)
Related
I'm doing a project that involves making a 3D model of the cornea in matlab. I have 6 plot3 in the same graph to draw one cornea
but now i want a surface plot.
Don't mind the curve orientation.
Note that all the plot3 have x, y and z that are vectors
Thanks in advance
If I were you I would use the Surf command doku surf. It is used to display [x,y,z] data. Since you have not have as many touples of data (just 6) you will have to interpolate all the other values. Therefore I would use the scattered interpolant function doku scattered interpolant.
!!!!!!!!!!!!!!Take care all this is pseudocode!!!!!!!!!!!!!!!!
F = scatteredInterpolant(x_existing,y_existing,z_existing);
generates a scattered interpolant object. You do already feed your already existing data in there. Afterwards you generate the points at which you want to interpolate:
%generates samples from -4 t0 4 in 0.05 steps
[x_sample,y_sample] = meshgrid(-4:0.05:4,-4:0.05:4);
Now you calculate the fitted z values using the scattered interpolant obj
z_interpolated=F(x_sample,y_sample) %interpolates
surf(x_sample,y_sample,z_interpolated) %plots with surf between -4 and 4
!!!!!!!!!!!!!!!From here working code!!!!!!!!!!!!!!!!!!!!!
%serialiasation of data (special for this usecase)
x_data=[h0(30:632,6);(a30(28:408,3))+0.527;(a60(276:632,3));(a90(26:575,3))+3.417;(a120(188:586,3))-0.6625;(a150(16:380,3))+1.173];
y_data=[(h0(30:632,5));((a30(28:408,2))-0.9128);(a60(276:632,2));(a90(26:575,2));(a120(188:586,2))-0.3825;((a150(16:380,2))+2.032)];
z_data=[yA0;yA30+0.162;yA60;yA90+0.837;yA120+0.135;yA150+0.135];
% cleaning the data of nan values
x_data=x_data(~isnan(z_data));
y_data=y_data(~isnan(z_data));
z_data=z_data(~isnan(z_data));%random for the looks
%interpolating
F=scatteredInterpolant(x_data,y_data,z_data);
%read yourself what this does
F.Method = 'natural';
F.ExtrapolationMethod = 'none';
%choosing sample points
[x_sample,y_sample] = meshgrid(-6:0.05:6,-6:0.05:6);
%interpolation
z_interpolated=F(x_sample,y_sample);
%plot
surf(x_sample,y_sample,z_interpolated)
I hope I was able to help you. If you try it and it works it would be very nice of you to post the working code here so that in the future here stands a working solution.
Part of an assignment of mine is to provide a 2D visualisation (plots) of some of my data points that are stored in a matrix. I'm slightly confused because the data is actually in 6D space (i.e. each row has 6 columns like 0 1 0 8 8 2).
Is there something I'm missing or does this genuinely not make sense? Is this something MATLAB can do?
Edit: Is something like this possible?
Though I wouldn't consider it visualizing 6D data, you can get the linked plot with a simple call to plot:
A = rand(6);
x = 1:6;
plot(x,A'); % Transpose A to plot rows since it's square, see plot documentation
Which produces the following:
From the documentation:
If one of X or Y is a vector and the other is a matrix, then the
matrix must have dimensions such that one of its dimensions equals the
vector length. If the number of matrix rows equals the vector length,
then the plot function plots each matrix column versus the vector. If
the number of matrix columns equals the vector length, then the
function plots each matrix row versus the vector. If the matrix is
square, then the function plots each column versus the vector.
Simply use:
surf(2Dmatrix)
You can read more here: http://uk.mathworks.com/help/matlab/ref/surf.html
If your matrix is 2D image, simply use
figure; imshow(2Dmatrix, [])
If you leave the square bracket empty, the limit will be automatic. When the figure is displayed you can change it to different colormap by Edit > Colormap.
I have a 25000x3-matrix, with each row containing a x-, a y- and a z-value. Now I wanted to do a graphical plot out of these. But for using for example surf(Z) I have to use a mxn-matrix as Z with m equal the size of x and n equal the size of y. How can I reshape the matrix I have to the needed mxn-matrix? The problem is that my x- and y-values are no ints, but floats, so I assume that I have to do a interpolation first. Is that true? My data plotted with plot3 looks like:
The fact that your x- and y- values are not integers is not a problem at all. The real question is: are your (x,y) points forming a grid, or not ?
If your points are forming a grid, then you have to reshape your columns to form m-by-n arrays. You may need to sort your data according to the first, then second column and then use the reshape function.
If your points are not forming a grid, then you will have to make an interpolation. By chance the scatterinterpolant class can nicely help you in doing so.
As you can see, the data you are providing is neither given in a gridded way, nor is the point cloud clean. You could however try to do the following:
Project the point cloud onto the x-y plane
Triangulate those points
Give the points their original z-coordinate back.
Plot the surface using trisurf
Here is a MATLAB code that does this:
%// Generate some points P
[X,Y] = ndgrid(0:30);
P = [X(:), Y(:), X(:).^2+Y(:)];
%%// Here the actual computation starts
[~,I] = unique(P(:,1:2),'rows'); %// Remove points with duplicate (x,y)-coords
P = P(I,:);
T = delaunay(P(:,1),P(:,2)); %// Triangulate the 2D-projection
surface = triangulation(T, P(:,1), P(:,2), P(:,3)); %// Project back to 3D
trisurf(surface); %// Plot
You may want to remove stray points first, though.
I need to be able to do a surface plot using data from 3 vectors. I found similar information, but no method seems to work with my data. My X and Y columns are evenly spaced, but not in increasing order. I tried different methods, but none of them seem to give me what I want, which is a simple surface linking close points together. I tried the following:
[X Y]=meshgrid(x,y);
Z=griddata(x,y,z, X,Y);
surf(X,Y,Z);
This is not exactly what I want, because it creates a surface at z=0 and makes it look more like a volume plot than just a surface. It also runs very slowly on my computer (probably from creating all the gridpoints). If I could get something that doesn't require as much memory it would be ideal (my vectors have about 20k values each), but this is not a necessity.
***Edit: I also tried using the scatteredInterpolant method found here,but the function doesn't seem to be recognized by MATLAB and I get this error:
Undefined function 'scatteredInterpolant' for input arguments of type 'double'.
Also here is an image of my problem:
You can see that we can't see under the surface, there is some z=0 plane blocking it.
If you have anything for me, any help is appreciated.
Thanks in advance.
**Edit 2: I added sample vectors, they're my x,y and z values from left to right.
***Edit 3: Here's an image of the triangulation I get. As you can see some points are being ignored for some reason, which gives those long and weird looking blue triangles.
Mike
As conventional methods seem to fail, I would suggest you to do it manually.
Create a Z matrix full of NaN values. The size of the matrix should be dependant on your x and y values.
Loop over all occuring x,y, pairs and put their (average?) z value in the right position of your Z matrix.
Loop over all NaN values and interpolate their value. Perhaps using filter2.
Use surf to plot the resulting surface
If you have points which are described by vectors, and you want to plot them you could always use a Delauny triangulation. The function in matlab is called Tri=delauny(X,Y,Z). The data generated by this function can be shown with either trimesh(Tri,X,Y,Z) or trisurf(Tri,X,Y,Z). Keep in mind trisurf is only for 3D data. If you want to adjust the transparancy of plots in your graph use the alpha setting.
I hope this helps
To me it looks like you just need to sort your data before plotting.
Here is an example which I believe is similar to your case (since I could not download your data).
x = [2 1 4 3 -1 -3 -4 -2];
y = [1 2 3 4 -1 -2 -3 -4];
z = 32 - x.*x - y.*y;
[X1 Y1] = meshgrid(x,y);
Z1 = 32 - X1.*X1 -Y1.*Y1;
surf(X1,Y1,Z1)
aux = sort([x;y],2);
x = aux(1,:);
y = aux(2,:);
[X2 Y2] = meshgrid(x,y);
Z2 = 32 - X.*X - Y.*Y;
figure()
surf(X2,Y2,Z2)
The first figure results in a very problematic surface:
The second figure contains the desired surface:
I have the following matlab code for approximating a differential equation via the Euler-method:
% Eulermethod
a=0;
b=0.6;
Steps=6;
dt=(b-a)/Steps;
x=zeros(Steps+1,1);
x(1,1)=1;
y=zeros(Steps+1,1);
for i=1:Steps
x(i+1,1)=x(i,1)+dt*(x(i,1)*x(i,1)+1);
end
plot(x)
I want to be able to plot the solution plot for several different values of Steps in one plot and have the x-axis go from 0 to 0.6 instead of from for example 1 to 100 000 etc. Can this be done?
If you use the hold on command this will allow you achieve multiple plots on the same figure. Similarly, if you separate your data into x and y vectors, you can plot them against eachother by passing 2 vectors to plot instead of just one. For example
figure
hold on
for i=1:m
x = [];
y = [];
%% code to populate your vectors
plot(x,y)
end
You should now see all your plots simultanesously on the same figure. If you want x to be composed of n equally spaced elements between 0 and 0.6, you could use the linspace command:
x = linspace(0.0,0.6,n);
In order to distinguish your plots, you can pass an extra paramter to the function .For example
plot(x,y,'r+')
will plot the data as a series of red + symbols.
Plot can take more arguments: plot(x_axis,values, modifiers);
If x-axis is a vector of M elements, values can be a matrix of MxN elements, each of which are drawn with a separate color.