I have a 3D data set representing a grid of photosensors which unfortunately were not steady during use. I have estimated the pdf for the motion of the detector and I want to find the expectation value for each sensor. As I don't want to reflect my pdf (i.e. I want f(t) not f(t-tau)) I don't think I can use the matlab convolve function. Is there a function that will do what I want or should I just get on with it? I've found movavg but it seems to do something else or maybe I just haven't followed it correctly.
Also, as I'm faily new to matlab, from C, I tend to use for loops which I'm aware is not the way to use Matlab. Is there an easy way to convert my 1-D pdf to a 3D matrix that will only operate in one axis (z in this case). Something like repmat(i, j, pdf).
Thanks
The expected value of a pdf is the integral over the product of the grid values and the pdf values at the corresponding grid points.
To integrate over a 3D-Grid, use the Matlab function triplequad (doc). As an example, let us compute the expected x value:
expectedx = triplequad(pdfxfun,xmin,xmax,ymin,ymax,zmin,zmax)
pdfxfun in this call must be a function handle which for any (x,y,z) point it receives should return the product of the pdf value at that point and x. In your case, this could probably be achieved by interpolation over your grid data. I don't know a 3D-interpolation function in Matlab, so probably you have to work on this for yourself. Roughly, what you would do is:
function pdfvalue = pdfinterpolation(x,y,z,Xgrid,Ygrid,Zgrid,pdfdata)
% compute interpolated pdfvalue at (x,y,z) from griddata and pdfdata
Then, pdfxfun above can be defined as anonymous function in the call to triplequad:
pdfxfun = #(x,y,z) x*pdfinterpolation(x,y,z,myxgrid,myygrid,myzgrid,pdfdata)
expectedx = triplequad(pdfxfun,xmin,xmax,ymin,ymax,zmin,zmax)
Related
I am trying trying to graph the polynomial fit of a 2D dataset in Matlab.
This is what I tried:
rawTable = readtable('Test_data.xlsx','Sheet','Sheet1');
x = rawTable.A;
y = rawTable.B;
figure(1)
scatter(x,y)
c = polyfit(x,y,2);
y_fitted = polyval(c,x);
hold on
plot(x,y_fitted,'r','LineWidth',2)
rawTable.A and rawTable.A are randomly generated numbers. (i.e. the x dataset cannot be represented in the following form : x=0:0.1:100)
The result:
second-order polynomial
But the result I expect looks like this (generated in Excel):
enter image description here
How can I graph the second-order polynomial fit in MATLAB?
I sense some confusion regarding what the output of each of those Matlab function mean. So I'll clarify. And I think we need some details as well. So expect some verbosity. A quick answer, however, is available at the end.
c = polyfit(x,y,2) gives the coefficient vectors of the polynomial fit. You can get the fit information such as error estimate following the documentation.
Name this polynomial as P. P in Matlab is actually the function P=#(x)c(1)*x.^2+c(2)*x+c(3).
Suppose you have a single point X, then polyval(c,X) outputs the value of P(X). And if x is a vector, polyval(c,x) is a vector corresponding to [P(x(1)), P(x(2)),...].
Now that does not represent what the fit is. Just as a quick hack to see something visually, you can try plot(sort(x),polyval(c,sort(x)),'r','LineWidth',2), ie. you can first sort your data and try plotting on those x-values.
However, it is only a hack because a) your data set may be so irregularly spaced that the spline doesn't represent function or b) evaluating on the whole of your data set is unnecessary and inefficient.
The robust and 'standard' way to plot a 2D function of known analytical form in Matlab is as follows:
Define some evenly-spaced x-values over the interval you want to plot the function. For example, x=1:0.1:10. For example, x=linspace(0,1,100).
Evaluate the function on these x-values
Put the above two components into plot(). plot() can either plot the function as sampled points, or connect the points with automatic spline, which is the default.
(For step 1, quadrature is ambiguous but specific enough of a term to describe this process if you wish to communicate with a single word.)
So, instead of using the x in your original data set, you should do something like:
t=linspace(min(x),max(x),100);
plot(t,polyval(c,t),'r','LineWidth',2)
The figure shown above is the plot of cumulative distribution function (cdf) plot for relative error (attached together the code used to generate the plot). The relative error is defined as abs(measured-predicted)/(measured). May I know the possible error/interpretation as the plot is supposed to be a smooth curve.
X = load('measured.txt');
Xhat = load('predicted.txt');
idx = find(X>0);
x = X(idx);
xhat = Xhat(idx);
relativeError = abs(x-xhat)./(x);
cdfplot(relativeError);
The input data file is a 4x4 matrix with zeros on the diagonal and some unmeasured entries (represent with 0). Appreciate for your kind help. Thanks!
The plot should be a discontinuous one because you are using discrete data. You are not plotting an analytic function which has an explicit (or implicit) function that maps, say, x to y. Instead, all you have is at most 16 points that relates x and y.
The CDF only "grows" when new samples are counted; otherwise its value remains steady, just because there isn't any satisfying sample that could increase the "frequency".
You can check the example in Mathworks' `cdfplot1 documentation to understand the concept of "empirical cdf". Again, only when you observe a sample can you increase the cdf.
If you really want to "get" a smooth curve, either 1) add more points so that the discontinuous line looks smoother, or 2) find any statistical model of whatever you are working on, and plot the analytic function instead.
I have a matrix which is 1*1*10000, the slightly odd dimensions are the result of the matrix algebra used to calculate it.
I simply want to be able to plot the 10000 data points contained in it, but matlab seems unable to do it?
Can someone please tell me how I can plot the data?
Seems simple but I really can't figure out how to do it!
Baz
yes you need to reduce the dimensions to a vector:
A = zeros(1,1,100)
vector = squeeze(A(1,1,:))
as when you'd access the third dimension this would only return a 3D-Matrix again:
z = A(1,1,:)
would NOT work. So use squeeze() ;-) Then plot as usual.
Doc-Link: http://www.mathworks.de/de/help/matlab/ref/squeeze.html
And as Ander pointed out in comments, no need to give any dimensions, as it removes singleton-dimensions by itself. So just use vector = squeeze(A). MATLAB recognizes the way to go itself.
I'm new in matlab and I'm trying to find the intersection between a curve (from points) and a line.
I've some points and I've plot the interpolation between this points. Now I want to find the intersection between the interpolation (xi,yi) curve and another line.
x = [94.8;84.4;63.1;49.4;40.6;33.8;23.2;20.1;10.2;9.2;7.9];
y = [0; 11.4;29.7;41.6;47.5;50.1;52.9;50.6;32.2;28.1;0];
xi=94.8:-0.1:7.9;
yi=interp1(x,y,xi,'spline');
plot(x,y,'*');
hold on
plot(xi,yi);
I've researched but everything I've found needs a function. I already tried to convert the curve to a function using polyfit but the fit is not good enought.
It is posible to do this in matlab?
Thanks.
Basically, the error message ask you to input a function handle (similar to function pointer in other languages). It's not necessary to convert it into something that matches a mathematical definition of a function (e.g. polynom):
f=#(xi)(interp1(x,y,xi,'spline'))
This can be evaluated at every xi.
Usage like every other function:
f(1)
f(1:3)
If I have an RC circuit with transfer function 1/(1+sRC) how do I draw the transfer function using MATLAB?
Num2=[1];
Den2=[R*C 1];
RCcirc=tf(Num2,Den2);
How do I declare the R and the C so that there are no errors?
tf is the wrong tool for plotting the transfer function. Try these instead:
Use linspace to generate a range of values for s. Give R and C reasonable values of your choice.
Read up on arithmetic operations in MATLAB, especially ./
Look at how to use plot and familiarize yourself with the command using some simple examples from the docs.
With these you should be able to plot the transfer function in MATLAB :)
First of all you need to understand what transfer function you want. Without defined values of R and C you won't get any transfer function. Compare it to this, you want to plot a sine wave: x = sin(w*t), I hope you can agree with me that you cannot plot such a function (including axes) unless I specifically say e.g. t is the time, ranging from 0 seconds to 10 seconds and w is a pulsation of 1 rad/s. It's exactly the same with your RC network: without any values, it is impossible for numerical software such as MATLAB to come up with a plot.
If you fill in those values, you can use th tf function to display the transfer function in whatever way you like (e.g. a bode plot).
On the other hand, if you just want the expression 1/(1+s*R*C), take a look at the symbolic toolbox, you can do such things there. But to make a plot, you will still have to fill in the R and C value (and even a value for your Laplace variable in this case).