I have a problem to plot a function with 2 variables:
if i do:
x= linspace(0,5);
y=linspace(0,5);
[x,y]=meshgrid(x,y);
z=log(x.*sqrt(y-x));
mesh(x,y,z);
I get this error:
Error using mesh (line 76) X, Y, Z, and C cannot be complex.
I think because I have some complex results in the computation.
How could I solve?
What kind of output do you expect? It's possible to plot the absolute value using mesh(x,y,abs(z));, but I'm not sure if this is what you want. quiver is another possibility to plot your data.
The reason you are getting complex results is the sqrt(y-x) part in your code. y is less than x at almost half of the points of your grid which leads to computing the square root of a negative number.
So, as Daniel suggested, you can use abs(z). Alternatively you could check if it is OK for the particular application to compute sqrt(abs(y-x)) to make sure you have a positive number under the square root
Related
I am new to matlab and I am having the difficulty: I would like to have a graph of a function plotted and 'r' signifies the parabolic equation and valueof 'y' varies and while adding to 'k' it is showing error.
the code is shown below`clear all;
x=[3,4,5,6,7,8,9,10,11,10,13,14,15,16,17,18,19,20,21,22,23];
a=(8.854.*(10.^-12).*(0.016));
y=-0.0925:0.01:0.0925
z=(0.03);
r=((7.3.*(y).^2)+(z));
k=((x.*10^-2))+((r))
c=(a./k);
plot(x,c);
and the error in command window is
Error using +
matrix dimensions must agree.
error in program(line 8)
k=((x.*10^-2))+((r))
how can I get around this problem ?
As people have pointed out in the comments, the matrix dimensions are the issue. If you make x the same dimensions as y (i.e., 1x19), as seen below, you will produce a graph, which is what it sounds like you want:
x=3:21;
a=(8.854.*(10.^-12).*(0.016));
y=-0.0925:0.01:0.0925
z=(0.03);
r=((7.3.*(y).^2)+(z));
k=((x.*10^-2))+((r))
c=(a./k);
plot(x,c);
From your comment: If you want it in 2-D, i.e., one value of k for every pair of x and r then in Matlab 2016a+, all you need is k=((x.*10^-2))+((r).'), i.e., one more transpose. In Pre-2016, you would use arrayfun for this:
[xr,rx] = meshgrid(x,r);
k = arrayfun(#(x,r) ((x.*10^-2))+((r)),xr,rx);
Btw, to plot a 2-D image you would not use plot but imagesc. This is what it looks like:
First: your variable k, second: your variable c. Is this what you were looking for?
As pointed out by Matlab and in the comments, the problem is indeed the difference in size of the vector.
you can either change x or a better solution is to use linspace , as :
y=linspace(-0.925,0.0915,21);
I've got to vectors called ttre and ttim which contain real and imaginary data over a frequency (from 1 to 64). The fields are looking like this:
ttim 64x10100 single
ttre 64x10100 single
I can easily make a 2D scatter plot of a certain row by using the command
scatter(ttim(40,:),ttre(40,:))
Now, I would like to display all data in a 3D scatter plot where X=real values, Y=imaginary values and Z=[1...64]
I created an array for Z with the number 1 to 64 and copied it to make it the same size as the other variables, by:
z=(1:64)'
z=repmat(z,1,10100)
result:
z 64x10100 double
When I try to plo a 3D scatter plot now, I get the error "Vectors x,yu,z must be of the same size"...however, as far as I understand, they are of the same size.
>> scatter3(ttim,ttre,z)
Error using scatter3 (line 64)
X, Y and Z must be vectors of the same length.
I hope that someone could point me into the right direction here.
Kind regards
scatter3 needs points to plot, so x,yand z should be 1xN , where N is the amount of points your are plotting. I dont know what your data is, so unfortunately I can not help more. Maybe scatter3(ttim(:),ttre(:),z(:)) works, but I do not recommend it for the huge amount of data you have, it may crash your computer.
However, maybe z=1:64 is not the best option. It means that you will have 64 layers (like floors from a building) of scattered data, not sure if that's what you want.
I have a 100 x 100 matrix and i have to use plot3 in MATLAB environment to graph this data. I tried plot3(matrix name) but I faced this error "not enough input arguments". I think plot3 needs 3 input arguments, but I only have this matrix of data. could anyone help me to solve this problem? Is there any alternative for plot3 when we don't have enough arguments?
I need a graph like this:
I think you want to plot the values in a figure as a sort of surface element. What you can do then is:
[X,Y] = size(matrix);
figure;
surface(1:X,1:Y,matrix);
What this does is that it creates a vector for both X and Y indices, as possible in surface. The X and Y indices are obtained by setting them as integers from 1:size, so basically you assign the location of each matrix element to an index.
Note that you can strictly speaking use surface(matrix) as well, but the former approach allows you to use custom indexing, as long as the lengths of the vectors X and Y are the same as the size of your matrix.
For the waterfall use:
figure;
waterfall(matrix);
Sample code:
A=rand(100);
figure;
waterfall(1:100,1:100,A);
Gives:
where you can play around with the name-value pairs, see the documentation on that.
I think what you need is mesh or surf instead of plot3.
plot3 draws a line in 3d-space, so it will need three vectors of the same length (one for each dimension).
When you have a matrix, one reasonable way of displaying it is as a surface in 3d space, which is done by the functions mesh and surf.
Try it out! I hope i helps!
I know there are many plotting documents for Matlab online and I am pretty sure that it has been asked many times. I aplogize in advance for any inconvenience.
I am dealing with a new distribution and I need to draw 3D plot for different values of parameters (I can do it with Excel or any other programs, however, since my other graphs is drawn with MATLAB, and I need to put this 3D in Matlab, too, to publish it as an article). I calculated the result using MATLAB loops, however, plotting gives me the hardest time. I had no other choice but to ask for your assistance. I have these equations for different alphas and betas with a constant sigma and calculate Galton's Skewness and Moor's Kurtosis given with the last two equations.
median=sqrt(2*(sigma^2)*beta*gammaincinv(0.5,alpha));
q1=sqrt(2*(sigma^2)*beta*gammaincinv((6/8),alpha));
q3=sqrt(2*(sigma^2)*beta*gammaincinv((2/8),alpha));
q4=sqrt(2*(sigma^2)*beta*gammaincinv((7/8),alpha));
q5=sqrt(2*(sigma^2)*beta*gammaincinv((5/8),alpha));
q6=sqrt(2*(sigma^2)*beta*gammaincinv((3/8),alpha));
q7=sqrt(2*(sigma^2)*beta*gammaincinv((1/8),alpha));
galtonskewness=(q1-2*median+q3)/(q1-q3);
moorskurtosis=(q4-q5+q6-q7)/(q1-q3);
Let's assume that,
sigma=1
beta=[0.1 0.2 0.5 1 2 5];
alpha=[0.1 0.2 0.5 1 2 5];
I have used mesh(X,Y,Z) for the same range of alphas and betas with the same increment but I take the error "these values cannot be complex". I just want to draw something like the one below.
It must be something easy that I am missing out, but I do not understand where the mistake is. I appreciate any help. Thank you!
I ran the above code for a 2D mesh of points for alpha and beta between 0.1 and 5 for both dimensions and I got results for both.
I suspect it's due to your alpha and beta declaration. You are only providing a few points, and if you try to use mesh, it won't get good results. Therefore, define a meshgrid of points for both alpha and beta, then vectorize your MATLAB code to produce the kurotsis and skewness curves. Only under certain situations should you use for loops. In general, you should avoid using them whenever possible.
How meshgrid works is that given a range of X and Y values, it will produce two (or three if you want 3D co-ordinates) arrays where each location in each array gives you the spatial co-ordinate at that particular location. Therefore, if we did something like:
[X,Y] = meshgrid(1:3, 1:3);
This is what we get:
X =
1 2 3
1 2 3
1 2 3
Y =
1 1 1
2 2 2
3 3 3
Notice that in a 2D grid, for the top-left corner, (x,y) = (1,1), and so for the corresponding location in X, we get 1 and Y we get 1. If you do the same logic for any other position in the 2D grid, you simply look at the X and Y values in each array and it will tell you what the component is for each dimension.
As such, instead of looping through all possible points in your grid, generate them all using meshgrid, then vectorize the computation by calculating your values all at once rather than individually. Once you do this, you have the right structure to be able to put this into mesh.
Therefore, try doing this instead:
%// Define meshgrid of points
[alpha,beta] = meshgrid(0.1:0.1:5, 0.1:0.1:5);
%// From your code
sigma = 1;
%// Calculate quantities - Notice that this is all vectorized
med=sqrt(2*(sigma^2)*beta.*gammaincinv(0.5,alpha));
q1=sqrt(2*(sigma^2)*beta.*gammaincinv((6/8),alpha));
q3=sqrt(2*(sigma^2)*beta.*gammaincinv((2/8),alpha));
q4=sqrt(2*(sigma^2)*beta.*gammaincinv((7/8),alpha));
q5=sqrt(2*(sigma^2)*beta.*gammaincinv((5/8),alpha));
q6=sqrt(2*(sigma^2)*beta.*gammaincinv((3/8),alpha));
q7=sqrt(2*(sigma^2)*beta.*gammaincinv((1/8),alpha));
galtonskewness=(q1-2*med+q3)./(q1-q3);
moorskurtosis=(q4-q5+q6-q7)./(q1-q3);
%// Show our meshes
figure;
mesh(alpha, beta, galtonskewness);
figure;
mesh(alpha, beta, moorskurtosis);
Also take note that I renamed your median variable to med. MATLAB has a function called median and so you don't want to unintentionally shadow over this function with a variable of the same name.
This is what I get:
Take note that I'm not getting the plots that you have placed in your post. It may be because I'm choosing the wrong variables to define the mesh, or perhaps your equations may be incorrect. Double check what you know in theory to what you have here in code and try again.
This should hopefully give you enough to start with though!
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.