I have the following coordinate system of (x,y) and attached z value to each coordinate. I need to keep the coordinates the same without using some linear fit function to change it into a grid system of some sort. Is there a way i can create a contour of that data using that data only and not using griddata or something.
x=[0.2,0.2,0.05,1.1,0.8,0.9,1.8,1.9,2.05];
y=[0,1.1,2.1,0.1,1.1,2.2,0.15,1.1,2.05];
z=[0,1,0,0,2,1,0,1,0;];
plot(x,y, 'bo')
The reason is i have another model with 540 thousand coordinate points that is a weird shape and if i start using the other functions it loses its shape and goes rectangular.
One option you have is to use fitto create a fit surface of your data, and then directly plot it. This also has the advantage to give you extra parameters to control the interpolation between your points.
f=fit([x',y'],z','linearinterp')
plot(f,'Style','Contour')
Will create something like:
And
f=fit([x',y'],z','cubicinterp')
plot(f,'Style','Contour')
Will smooth the interpolation into:
Please look here for more information on fit and fit plotting options
https://www.mathworks.com/help/curvefit/fit.html#inputarg_fitType
https://www.mathworks.com/help/curvefit/plot.html
Related
I have 8 plots which I want to implement in my Matlab code. These plots originate from several research papers, hence, I need to digitize them first in order to be able to use them.
An example of a plot is shown below:
This is basically a surface plot with three different variables. I know how to digitize a regular plot with just X and Y coordinates. However, how would one digitize a graph like this? I am quite unsure, hence, the question.
Also, If I would be able to obtain the data from this plot. How would you be able to utilize it in your code? Maybe with some interpolation and extrapolation between the given data points?
Any tips regarding this topic are welcome.
Thanks in advance
Here is what I would suggest:
Read the image in Matlab using imread.
Manually find the pixel position of the left bottom corner and the upper right corner
Using these pixels values and the real numerical value, it is simple to determine the x and y value of every pixel. I suggest you use meshgrid.
Knowing that the curves are in black, then remove every non-black pixel from the image, which leaves you only with the curves and the numbers.
Then use the function bwareaopen to remove the small objects (the numbers). Don't forget to invert the image to remove the black instead of the white.
Finally, by using point #3 and the result of point #6, you can manually extract the data of the graph. It won't be easy, but it will be feasible.
You will need the data for the three variables in order to create a plot in Matlab, which you can get either from the previous research or by estimating and interpolating values from the plot. Once you get the data though, there are two functions that you can use to make surface plots, surface and surf, surf is pretty much the same as surface but includes shading.
For interpolation and extrapolation it sounds like you might want to check out 2D interpolation, interp2. The interp2 function can also do extrapolation as well.
You should read the documentation for these functions and then post back with specific problems if you have any.
Can anyone tell me how to generate a 3D surface model like CAD in Matlab ?
1.Input: Input is a collection of points with (x,y,z) where surface is present for an object(I'm using this for a 3D scanner where my inputs are (x,y,z) of surface)
2.Points should be displayed as a surface using some smooth interpolation.
3.More like surface generation from data points.
Thanks you.
In order to plot surfaces, you can use patch function. However, you need along with the points the faces information. In patch a surface consists of polygons that is specified using 3 point, which is the face information.
1
Since it seems like you will be inputting discrete points located on the surface of the object, you will first want to create a Nonconvex Polygon based on the data using Matlab's boundary function.
https://www.mathworks.com/help/matlab/ref/boundary.html
You can then use the trimesh function to create the figure
This question shows the input data and what was produced using this method: How do I create a 3D polygon/mesh over data points?
I would like to find residuals of my solutions. However, each solution uses a different grid, thus I would like to interpolate the solutions in 2D to a mesh grid for each solution such that I can easily find the residuals.
I used griddata which seems to work, but it doesn't work very well in regions of discontinuities and near edges. I would like to interpolate data of flow over a sphere for example. The area of the sphere should be confined to zero since that is outside of the grid boundaries; however, after using griddata, there's some non zero values in the sphere region. I also get a warning saying there were duplicate x and y points.
Does anyone know how to preserve the integrity of the sphere after using griddata? I've double checked the original x,y data, and the area of the sphere all have values of 0.
Thank you. I hope that made sense.
Best,
Yuki
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 formula that depends on theta and phi (spherical coordinates 0<=theta<=2*pi and 0<=phi<=pi). By inserting each engle, I obtained a quantity. Now I have a set of data for different angles and I need to plot the surface. My data is a 180*360 matrix, so I am not sure if I can use SURF or MESH or PLOT3. The figure should be a surface that include all data and the axes should be in terms of the quantity, not the quantity versus the angles. How can I plot such a surface?
I see no reason why you cannot use mesh or surf to plot such data. Another option I tend to use is that of density plots. You basically display the dependent variable (quantity) as an image and include the independent variables (angles) along the axis, much like you would with the aforementioned 3D plotting functions. This can be done with imagesc.
Typically you would want your axes to be the dependent variables. Could you elaborate more on this point?
If I understand you correctly you have calculated a function f(theta,phi) and now you want to plot the surface containing all the points with the polar coordinated (r,theta,phi) where r=f(theta,phi).
If this is what you want to do, the 2D version of such a plot is included in MATLAB under the name polar. Unfortunately, as you pointed out, polar3 on MatlabCentral is not the generalization you are looking for.
I have been able to plot a sphere with the following code, using constant r=1. You can give it a try with your function:
phi1=0:1/(3*pi):pi; %# this would be your 180 points
theta1=-pi:1/(3*pi):pi; % your 360 points
r=ones(numel(theta1),numel(phi1));
[phi,theta]=meshgrid(phi1,theta1);
x=r.*sin(theta).*cos(phi);
y=r.*sin(theta).*sin(phi);
z=r.*cos(theta);
tri=delaunay(x(:),y(:),z(:));
trisurf(tri,x,y,z);
From my tests it seems that delaunay also includes a lot of triangles which go through the volume of my sphere, so it seems this is not optimal. So maybe you can have a look at fill3 and construct the triangles it draws itself: as a first approximation, you could have the points [x(n,m) x(n+1,m) x(n,m+1)] combined into one triangle, and [x(n+1,m) x(n+1,m+1) x(n+1,m+1)] into another...?