I have some vector (matrix 2*64) points that I draw in a standard way on a compass plot.
compass(data)
This plot looks like this:
Now I'm doing kmeans clustering on my data. After clustering I have a vector of 8 center points (x,y) that I want to draw on the same compass plot like a circle with some diameter R.
First thing I did was creating new compass layer on that plot using command:
compass(centers(:,1), centers(:,2), "o")
"markersize" property doesn't work here. The result of that plot is:
there are some small center circles visible (along with some points describing default arrow), but that is not what I need.
I need something like this:
Is it possible to do that? Does octave (matlab) alows us to draw new objects of different types (circles) on existing plots?
If you instead use an ordinary plot when you want to plot your circles it works fine.
% # Random data in [-1,1]
x = 2*rand(1,10)-1;
y = 2*rand(1,10)-1;
compass(x,y)
hold on
plot(x,y,'ok','MarkerSize',15,'LineWidth',3)
Related
I need to plot the locations of 3 treasures on a contour map.The coordinates are in a matrix (3x2) called "treasures", the first column contains the y coordinates, and the second column the x coordinates.
Using an X marker I was asked to plot the treasures locations using a marker size of 15, a line width of 4 and a red color.
How could I do that? the image should look like this
It looks like you need to read a basic tutorial on matlab first before you take on this project.
plotting scattered points can be done in matlab using the command plot. Assuming your treasure locations is x and y (both can be a vector for multiple points), you can plot those using
plot(x,y,'rx','markersize',15)
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])
Suppose I have a dataset which consists of three vectors which represent a trajectory in 3D. This temporal data can be plotted in Matlab with the following command:
plot3(Data(:,1),Data(:,2),Data(:,3),'.r');
The output is a "cloud" of points:
I would like to visualize the trajectory, so my question is: How do I modify the plot so that the color of the points represent the index (time) of the temporal data?
Just to make my point a bit clearer, imagine a trajectory of points that change color "smoothly" from red to blue in a way that will enable me to visualize the trajectory.
I can think of two answers:
use the surface function on a 3D line like this:
color=1:length(Data(:,1));
surface([Data(:,1);Data(:,1)],[Data(:,2);Data(:,2)][Data(:,3);Data(:,3)],[color ;color],...
'facecol','no','edgecol','interp');
this is a very nice trick, but it plots a line.
If you want to plot points, you can define an RGB color and plot single points with hold on like this:
hold on
for i=1:length(Data(:,1))
plot3(Data(i,1),Data(i,2),Data(i,3),'Color',[(i/100*255)/255 0/255 (255-(i/100*255))/255],'LineWidth',2)
end
shg
I have a 3D data set of a surface that is not a function graph. The data is just a bunch of points in 3D, and the only thing I could think of was to try scatter3 in Matlab. Surf will not work since the surface is not a function graph.
Using scatter3 gave a not so ideal result since there is no perspective/shading of any sort.
Any thoughts? It does not have to be Matlab, but that is my go-to source for plotting.
To get an idea of the type of surface I have, consider the four images:
The first is a 3D contour plot, the second is a slice in a plane {z = 1.8} of the contour. My goal is to pick up all the red areas. I have a method to do this for each slice {z = k}. This is the 3rd plot, and I like what I see here a lot.
Iterating this over z give will give a surface, which is the 4th plot, which is a bit noisy (though I have ideas to reduce the noise...). If I plot just the black surface using scatter3 without the contour all I get is a black indistinguishable blob, but for every slice I get a smooth curve, and I have noticed that the curves vary pretty smoothly when I adjust z.
Some fine-tuning will give a much better 4th plot, but still, even if I get the 4th plot to have no noise at all, the result using scatter3 will be a black incomprehensible blob when plotted alone and not on top of the 3D contour. I would like to get a nice picture of the full surface that is not plotted on top of the 3D contour plot
In fact, just to compare and show how bad scatter3 is for surfaces, even if you had exact points on a sphere and used scatter3 the result would be a black blob, and wouldn't even look like a sphere
Can POV-Ray handle this? I've never used it...
If you have a triangulation of your points, you could consider using the trisurf function. I have used that before to generate closed surfaces that have no boundary (such as polyhedra and spheres). The downside is that you have to generate a triangulation of your points. This may not be ideal to your needs but it definitely an option.
EDIT: As #High Performance Mark suggests, you could try using delaunay to generate a triangulation in Matlab
just wanted to follow up on this question. A quick nice way to do this in Matlab is the following:
Consider the function d(x, y, z) defined as the minimum distance from (x, y, z) to your data set. Make sure d(x, y, z) is defined on some grid that contains the data set you're trying to plot.
Then use isosurface to plot a (some) countour(s) of d(x, y, z). For me plotting the contour 0.1 of d(x, y ,z) was enough: Matlab will plot a nice looking surface of all points within a distance 0.1 of the data set with good lighting and all.
In povray, a blob object could be used to display a very dense collection of points, if you make them centers of spheres.
http://www.povray.org/documentation/view/3.6.1/71/
If you want to be able to make slices of "space" and have them colored as per your data, then maybe the object pattern (based on a #declared blob object) might do the trick.
Povray also has a way to work with df3 files, which I've never worked with, but this user appears to have done something similar to your visualization.
http://paulbourke.net/miscellaneous/df3/
I have a 2D scatter plot in MATLAB. Is it possible to interpolate the scatter plot to create an area plot?
If you're simply trying to draw one large filled polygon around your entire set of scattered points, you can use the function CONVHULL to find the convex hull containing your points and the function PATCH to display the convex hull:
x = rand(1,20); %# 20 random x values
y = rand(1,20); %# 20 random y values
hullPoints = convhull(x,y); %# Find the points defining the convex hull
patch(x(hullPoints),y(hullPoints),'r'); %# Plot the convex hull in red
hold on; %# Add to the existing plot
scatter(x,y); %# Plot your scattered points (for comparison)
And here's the resulting figure:
Scatter is generally used to represent data where you can't use a line graph, i.e., where each x might have many different y values, so you can't convert directly to an area graph--it would be meaningless. If your data actually is representable as a line graph, then pass it to area directly.
So I'm not quite sure what you want, but here are some possibilities:
You could create a Voronoi diagram based on your points. This will show a region near your points showing which points are closer to a specific point: voronoi(x,y), or see the help.
You could bucket or quantize your data somehow, making it fit into a grid, and then plot the grid. This could also be considered a histogram, so read up on that.
You could just use larger scatter markers (scatter(x,y,scale) where scale is the same dimensions as x and y).