I have a function f(v,z) and z = [0:0.01:1], v = [1:0.01:5].
I first create a cell, denoted by C, to record the coordinates of this (v,z), and from this C, I fill in a matrix of the value of f(v,z). So my cell C look like the following
C = (0,5), (0.01,5), (0.02,5),....., (1,5)
(0,4.99),(0.01,4.99),(0.02,4.99),...,(1,4.99)
...
(0,1), (0.01,1), (0.02,1),......,(1,1)
So when viewing cell C as the coordinates in the 2D space, the vertical axis (the column) is z and the horizontal axis (the row) is v. And the value f(v,z) is built up on these coordinates. So one can imagining plotting a 3D picture.
Then I fill matrix M, which contains the value of f(v,z) according to the cell C. Then I want to do the heat map (or contour would also be fine), but when I use colormap or contour, it seems that matlab just does not plot the figure according to my specific direction of v and z as specified by my cell C. Also, the range of the two axes does not look right. I wonder if there is good way to control the plotting directions of the axes?
Related
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
I have a set of data points, x, y, and z contained in a matrix, record.
In record, each row is a data-point where the first value is the x-coordinate, the second is the y-coordinate, and the third is the z-coordinate. I would like to represent this as a surface plot. I tried:
surf([record(:,1), record(:,2)], record(:,3))
But the results were not what I expected. Any advice?
Try this code for instance.
[x,y,z]=sphere(n);
surf(x,y,z);
axis equal
This code plots with 3 parameters surf the surface of a sphere. As far as I understood from your code you want to utilize the 2 parameters surf for your application.
According to surf help when utilizing 2 parameters surf:
surf(Z) and surf(Z,C) use x = 1:n and y = 1:m. In this case,
the height, Z, is a single-valued function, defined over a
geometrically rectangular grid.
where:
The color scaling is determined
by the range of C
It just doesn't look like you want to utilize C as the color scaling parameter. For better understanding, can you send the contents of record for reference?
I am trying to plot a 3D volume in MATLAB. I am using the slice command.
a(:,:,1)=[1,2; 3,4];
a(:,:,2)=[5,6; 9,8];
figure;
slice (a,0,0,1);
hold on
slice (a,0,0,2);
The figure I get has just one square (pixel). I am expecting 4 squares. How do I plot this? What am I doing wrong?
Relevant part of documentation:
slice(V,sx,sy,sz) draws slices along the x, y, z directions in the volume V at the points in the vectors sx, sy, and sz. V is an m-by-n-by-p volume array containing data values at the default location X = 1:n, Y = 1:m, Z = 1:p. Each element in the vectors sx, sy, and sz defines a slice plane in the x-, y-, or z-axis direction.
So, your command slice (a,0,0,1); is asking Matlab to produce three slices of the cube [1,2]×[1,2]×[1,2] (colored according to the values of your a array), by the following planes
x=0 plane (shown as empty square since it's outside of the cube)
y=0 plane (same story)
z=1 plane (dark blue square).
You could have avoided the extraneous x=0 and y=0 slices with slice(a,[],[],1). Also,
slice(a,[],[],[1,2]) would give you top and bottom
slice(a,[],[1,2],[]) would give two vertical sides
slice(a,[1,2],[],[]) would give two other vertical sides
Or you could just get all six at once with slice(a,[1,2],[1,2],[1,2]). If you don't want, e.g., top and bottom slices, then slice(a,[1,2],[1,2],[]).
Note that the entries of a are not coordinates, they are understood as values of a function of three variables, and are represented by colors.
I need to plot a 3D figure with each data point colored with the value of a 4th variable using a colormap. Lets say I have 4 variables X,Y,Z and W where W = f(X,Y,Z). I want a 3D plot with X, Y, and Z as the three axis. The statement scatter3(X,Y,Z,'filled','b') gives me a scatter plot in 3D but I want to incorporate the value of Z in the graph by representing the points as an extra parameter (either with different areas :bigger circles for data points with high value of Z and small circles for data points with low value of Z or by plotting the data points with different colors using a colormap). However, I am a novice in MATLAB and dont really know how to proceed. Any help will be highly appreciated.
Thanks in advance!
So just use z for the size vector (4th input) as well as the color vector (5th input):
z = 10*(1:pi/50:10*pi);
y = z.*sin(z/10);
x = z.*cos(z/10);
figure(1)
scatter3(x,y,z,z,z)
view(45,10)
colorbar
The size vector needs to be greater 0, so you may need to adjust your z accordingly.
You are already nearly there... simply use
scatter3(X,Y,Z,s,W);
where s is the point size (scalar, e.g. 3) and W is a vector with your W values.
You might also want to issue an
set(gcf, 'Renderer','OpenGL');
where gcf gets your current figure you are plotting in to significantly increase responsiveness when scattering a lot of data.
G'day
I'm trying to program a smart way to find the closest grid points to the points along a contour.
The grid is a 2-dimensional grid, stored in x and y (which contain the x and y kilometre positions of the grid cells).
The contour is a line, made up of x and y locations, not necessarily regularly spaced.
This is shown below - the red dots are the grid, and the blue dots are the points on the contour. How do I find the indices of the red dot closest to each blue dot?
Edit - I should mention that the grid is a latitude/longitude grid, of an area fairly close to the south pole. So, the points (the red dots) are the position in metres from the south pole (using a polar stereographic representation). Since the grid is a geographic grid there is unequal grid spacing - with slightly different shaped cells (where the red dots define the vertices of the cells) due to the distortion at high latitudes.
The result is that I can't just find which row/column of the x and y matrix corresponds closest to the input point coordinates - unlike a regular grid from meshgrid, the values in the rows and columns vary...
Cheers
Dave
The usual method is to go:
for every blue point {
for every red point {
is this the closest so far
}
}
But a better way is to put the red data into a kd tree. This is a tree that splits the data along its mean, then splits the two data sets along their means etc until you have them separated into a tree structure.
This will change your searching effeciancy from O(n*m) to O(log(n)*m)
Here is a library:
http://www.mathworks.com.au/matlabcentral/fileexchange/4586-k-d-tree
This library will provide you the means to easily make a kd tree out of the data and to search for the closest point in it.
Alternatively you can use a quadtree, not as simple but the same idea. (you may have to write your own library for that)
Make sure the largest data set (in this case your red points) go into the tree as this will provide the greatest time reduction.
I think I've found a way to do it using the nearest flag of griddata.
I make a matrix that is the same size as the grid x and y matrices, but is filled with the linear indices of the corresponding matrix element. This is formed by reshaping a vector (which is 1:size(x,1)*size(x,2)) to the same dimensions as x.
I then use griddata and the nearest flag to find the linear index of the point closest to each point on my contour (blue dots). Then, simply converting back to subscript notation with ind2sub leaves me with a 2 row vectors describing the matrix subscripts for the points closest to each point on the blue-dotted contour.
This plot below shows the contour (blue dots), the grid (red dots) and the closest grid points (green dots).
This is the code snippet I used:
index_matrix1 = 1:size(x,1)*size(x,2);
index_matrix1 = reshape(index_matrix1,size(x));
lin_ind = griddata(x,y,index_matrix1,CX,CY,'nearest'); % where CX and CY are the coords of the contour
[sub_ind(1,:),sub_ind(2,:)] = ind2sub(size(x),lin_ind);
I suppose that in the stereographic representation, your points form a neat grid in r-theta coordinates. (I'm not too familiar with this, so correct me if I'm wrong. My suggestion may still apply).
For plotting you convert from the stereographic to latitude-longitude, which distorts the grid. However, for finding the nearest point, consider converting the latitude-longitude of the blue contour points into stereographic coordinates, where it is easy to determine the cell for each point using its r and theta values.
If you can index the cell in the stereographic representation, the index will be the same when you transform to another representation.
The main requirement is that under some transformation, the grid points are defined by two vectors, X and Y, so that for any x in X and y in Y, (x, y) is a grid point. Next transform both the grid and the contour points by that transformation. Then given an arbitrary point (x1, y1), we can find the appropriate grid cell by finding the closest x to x1 and the closest y to y1. Transform back to get the points in the desired coordinate system.
dsearchn: N-D nearest point search.
[k, d] = dsearchn(A,B) : returns the distances, d, to the closest points. d is a column vector of length p.
http://au.mathworks.com/help/matlab/ref/dsearchn.html?s_tid=gn_loc_drop