I want to be able to simulate a hyperbolic equation on characteristic curves (lines). I will start with a basic one. u_{t}+2u_{x}=u^{2} with initial data u(x,0)=cos(x). The solution is u(x,t)=cos(x-2t)/(1-t*cos(x-2t)) where the charackteristic curve is x=2*t+x_{0}. So the solution is defined on characteristics (method of characteristics).
x=zeros(10,5);
u=zeros(10,5);
x0=linspace(0,10,10);
t=linspace(0,5,5);
for i=1:length(x0)
for j=1:length(t)
x(i,j)=2*t(j)+x0(i);
if t(j)*cos(x(i,j)-2*t(j))==1
u(i,j)=0;
else
u(i,j)=cos(x(i,j)-2*t(j))/(1-t(j)*cos(x(i,j)-2*t(j)));
end
end
end
mesh(u)
Apperently, the grid of characteristic lines and rectangular grid do not fit eachother. How can I plot the solutions on characteristics?
Firstly, you do not have a rectangular grid due to this line
x(i,j)=2*t(j)+x0(i);
I am not entirely sure what you are asking. I get the impression that you might want to plot the surface of u over the irregular mesh x. If this is indeed the case, you may find the following like enables you to do what you need - although it does look like you will need to do some tweaking of your code.
http://blogs.mathworks.com/videos/2007/11/02/advanced-matlab-surface-plot-of-nonuniform-data/
Alternatively, you could just redesign your code such that x results in a rectangular grid - I cannot say for sure as maybe there is a reason that you only consider these particular points.
If you get no better answers, the above link could enable you to get what you want (assuming I have understood your question correctly).
Related
I would like to follow a curve (with matlab or opencv) and to find the other end of it when it is cut by an empty space like this example, which is simplified to illustrate the problem:
Link to image of cut curve
Real images are more like this one: Link to real image to analyse
To follow the curve, I can use a skeleton and look at the neighbourhood. The problem is that I don't know how to find the other end efficiently.
I don't think that closing or opening operations could help because as shown on the previous image, there are other curves and the two parts of the curve are quite far from each other so it could lead to boundaries between the different curves instead of the two parts.
I was thinking about polynomial evaluation which could be a solution for simple curves but I am not sure about the precision I could get. If I use a skeleton, I have to find exactly the right pixel or to search in a reasonable neighbourhood which would take some time and once again, as there are other curves in the images, I have to be sure that I will find the good one.
That's why I am searching for an existing function which could estimate precisely the trajectory of the curve and give an usefull output to go further and find the second part of the curve.
If that kind of function doesn't exist, I'm open to any other way of analysing the problem if it can help.
I will start to explain with the first image you provided, you can implement common OpenCV function useful for detecting contour(black region in your case as you have binary image) known as cv2.findContours(), which returns the coordinates of the edges of the surface detected then you can plot each detected contour separately in a blank image to get the edge of your desired line.
Now coming to your 2nd image you have to be slightly careful while performing above analysis as there are many tiny lines. get back to me for further help
I am currently trying to use spectral-methods to analyse topographic landscapes.
When i FFT the landscape and plot the power-spectrum. From the power-spectrum an orientation of the structures in the landscape can be found.
2D power-spectrum:-
In this power-spectrum, i would like to make a cross-section.
This is easy when the peak amplitude orientation is along the x or y-axis.
But for this area (and others), this is not the case.
Cross-section from another area - orientated along the y-axis:-
My problem is i want to make a cross-section along the peaks in 1, and i just cant seem to figure it out how.
If anyone could point me towards some solution for this. Been stuck here for a couple of days now.
Edit 1
I would like the cross-section, to be a line along the peak orientation.
Edit 2
Improved the first image to show where i want my cross-section
My solution was, as GameOfThrows suggested:
Pick 2 (or more) points on the orientation i want
used Least squares on the points to create the line
Setup a meshgrid for the interpolation.
Use the interp2 function on the new line.
define a proper axis for the section
In my final cross section i ended up having multiple lines in it, that way i was sure to hit the max amplitudes.
i was a little with the answer to my question, but i have been busy :)
You can use ginput built-in matlab function to store 2 (x,y) coordinates of your power spectrum and then use this values to delimit a profile to be interpolated.
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.
Anyone have any starting tips for me? I want to learn from this (ie Don't want to be lazy and have someone answer this for me).
I would like to develop my understanding of mathematical 3D surfaces. My own personal project is to produce a 3D surface/graph of the concourse structure in MATLAB.
I found a link with good pictures of its geometry here. I am not expecting to get it 100% perfectly but I'd like to come close!
At the end of this exercise I would like to have a mathematical definition of the geometry as well as a visual representation of the surface. This can involve cartesian equations, parametric equations, matrices, etc.
Any help would be very much appreciated!
To give some specific advice for MATLAB:
I would load in the 'section' image from the web page you have linked, and display this in a MATLAB figure window. You can then try plotting lines over the top until you find one that fits nicely. So you might do something like:
A = imread('~/Desktop/1314019872-1244-n364-1000x707.jpg');
imshow(A)
hold on
axis on
%# my guess at the function - obviously not a good fit
x = [550:900];
plot(x, 0.0001*x.^2 + 300)
Of course, you might want to move the position of the origin or crop the picture and so on.
As an arguably better alternative to this trial-and-error method, you could trace the outline of the section (e.g by clicking points with something like ginput), and then use one of MATLAB's curve-fitting tools (e.g. fit) to fit a function to the data.
The final 3D shape looks to me (at a casual glance) to be a 3D revolution of the section shape around a central axis. Use of a cylindrical coordinate system could therefore be a good idea.
The final plotting of your 3D shape could be done with a function such as surf or mesh.
I would start by defining a function that defines for each x, y coordinate whether there is a point z, and if so with which altitude.
The shape reminds me a bit of a log or a square root.
I have 3D space. And I know for example N points in this space (x1,y1,z1), (x2,y2,z2)..., (xn,yn,zn). I want to interplolate points, that is different from this. How can I do this in Matlab?
interp3 may help you. Here is the documentation.
As always, there are questions left unanswered by your one line query.
If the data is of the form where there is a functional relationship z(x,y), (or y(x,z) or x(y,z)) then you might potentially be able to use one of the interpolation tools. Thus, suppose you have data that lies on a lattice in the (x,y) plane, thus some value of z at each point in that lattice. In this case, you can use interp2.
Alternatively, if the data is scattered, but there is some single valued functional relationship z(x,y) that you don't have, but it is some continuous function. Infinite first derivatives are a problem too here. In this case, assuming that you have data that at least fills some convex domain in the (x,y) plane, you can still interpolate a value of z. For this, use griddata, or TriScatteredInterp. Or you might use my own gridfit tool, as found on the file exchange.
Next, the way you describe the data, I'm not at all positive that you have something in one of the above forms. For example, if your data lies along some curved path in this 3D domain, and you wish to interpolate points along that curved arc can be done using my interparc tool, also found on the file exchange.
One last case that people often seem to have when they talk about interpolation of a spatial set like this, is just a general surface, that they wish to build a neatly interpolated, smooth surface. It might be something as simple as the surface of a sphere, or something wildly more complex. (These things are never simple.) For this, you might be able to use a convex hull to approximate something, if it is a closed convex surface. More complex surfaces might require a tool like CRUST, although I have no implementation of it I can offer to you. Google will help you there, if that is what you need.
The point of all this is, how you interpolate your data depends on what form the data is in, what it represents, and the shape of the relationship you will be interpolating.