Why did I get an error like ''Subscript indices must either be real positive integers or logicals. Error in bcfcn (line 7) qr = Ds*J(t,1)'' when I used pdepe matlab solver to solve diffusion equation on spherical coordinate. The Ds is just an constant but J is actually a vector with respect to time which has both very large positive and negative integers. I cannot change these value to all positive since it is a boundary condition given.
Is that because I need to change the J vector to some function with respect to time?? Actually I have tried to change all J to positive to figure out how does it work, but it doesn't work either.
Thank you very much!
Lu
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this a question that envolves both programming and mathematics. So, I'm trying to write a code that computes the general solution of a system of linear ODEs described by . The mathematical formula it's shown above:
where the greek symbol \PHI that appers in the equation is the expm(A*t)
clear all
A=[-2]; %system matrix
t0=1; %initial time of simulation
tf=2; %final time of simulation
syms t x_0
x0=x_0;
hom=expm(A*t); %hom means "homogeneous solution"
hom_initialcond=hom*x0;%this is the homogeneous solution multiplied by the initial conditon
invhom=inv(hom); %this is the inverse of the greek letter at which, multiplied by the input of the system, composes the integrand of the integral
g=5*cos(2*t); %system input
integrand=invhom*g; %computation of the integrand
integral=int(integrand,t0,t); %computation of the definite integral from t0 to t, as shown by the math formula
partsol=hom*integral; %this is the particular solution
gen_sol=partsol+hom_initialcond %this is the general solution
x_0=1; %this is the initial condition
t=linspace(t0,tf); %vector of time from t0 to tf
y=double(subs(gen_sol)); %here I am evaluating my symbolic expression
plot(t,y)
The problem is that my plot of the ODE's solution it's not looking well, as you can see:
The solution it's wrong because the curve shown in the graph doesnt start at the initial value equals 1. But the shape it's very similar from the plot gave by the MATLAB ODE solver:
However, if I set t0=0 then the plot gave by my code and by MATLAB solver it's exacly equal to each other. So, my code it's fine for t0=0 but with any other values my code goes wrong.
The general solution in terms of fundamental matrices is
or more often seen as
But since the initial time is often taken to be zero, the inverse of the fundamental matrix is often omitted since it is the identity for linear, constant coefficient problems at zero (i.e., expm(zeros(n)) == eye(n)) and the c vector is equivalent to the initial condition vector.
Swapping some of the lines around near your symbolic declaration to this
syms t x_0 c_0
hom = expm(A*t) ;
invhom = inv(hom) ;
invhom_0 = subs(invhom,t,sym(t0)) ;
c_0 = invhom_0 * x_0 ;
hom_initialcond = hom * c_0 ;
should provide the correct solution for non-zero initial time.
I have an integration function which does not have indefinite integral expression.
Specifically, the function is f(y)=h(y)+integral(#(x) exp(-x-1/x),0,y) where h(y) is a simple function.
Matlab numerically computes f(y) well, but I want to compute the following function.
g(w)=w*integral(1-f(y).^(1/w),0,inf) where w is a real number in [0,1].
The problem for computing g(w) is handling f(y).^(1/w) numerically.
How can I calculate g(w) with MATLAB? Is it impossible?
Expressions containing e^(-1/x) are generally difficult to compute near x = 0. Actually, I am surprised that Matlab computes f(y) well in the first place. I'd suggest trying to compute g(w)=w*integral(1-f(y).^(1/w),epsilon,inf) for epsilon greater than zero, then gradually decreasing epsilon toward 0 to check if you can get numerical convergence at all. Convergence is certainly not guaranteed!
You can calculate g(w) using the functions you have, but you need to add the (ArrayValued,true) name-value pair.
The option allows you to specify a vector-valued w and allows the nested integral call to receive a vector of y values, which is how integral naturally works.
f = #(y) h(y)+integral(#(x) exp(-x-1/x),0,y,'ArrayValued',true);
g = #(w) w .* integral(1-f(y).^(1./w),0,Inf,'ArrayValued',true);
At least, that works on my R2014b installation.
Note: While h(y) may be simple, if it's integral over the positive real line does not converge, g(w) will more than likely not converge (I don't think I need to qualify that, but I'll hedge my bets).
I have to calculate:
gamma=(I-K*A^-1)*OLS;
where I is the identity matrix, K and A are diagonal matrices of the same size, and OLS is the ordinary least squares estimate of the parameters.
I do this in Matlab using:
gamma=(I-A\K)*OLS;
However I then have to calculate:
gamma2=(I-K^2*A-2)*OLS;
I calculate this in Matlab using:
gamma2=(I+A\K)*(I-A\K)*OLS;
Is this correct?
Also I just want to calculate the variance of the OLS parameters:
The formula is simple enough:
Var(B)=sigma^2*(Delta)^-1;
Where sigma is a constant and Delta is a diagonal matrix containing the eigenvalues.
I tried doing this by:
Var_B=Delta\sigma^2;
But it comes back saying matrix dimensions must agree?
Please can you tell me how to calculate Var(B) in Matlab, as well as confirming whether or not my other calculations are correct.
In general, matrix multiplication does not commute, which makes A^2 - B^2 not equal to (A+B)*(A-B). However your case is special, because you have an identity matrix in the equation. So your method for finding gamma2 is valid.
'Var_B=Delta\sigma^2' is not a valid mldivide expression. See the documentation. Try Var_B=sigma^2*inv(Delta). The function inv returns a matrix inverse. Although this function can also be applied in your expression to find gamma or gamma2, the use of the operator \ is more recommended for better accuracy and faster computation.
I am trying to find the 2 eignevectors of the 2 smallest eigenvalues of a laplacian. I do this by
[v,c]=eigs(L,M,2,'SM');
Where L is the lapalcian and M is the mass matrix.
As a result I get the error
Error using eigs/checkInputs/LUfactorAminusSigmaB (line 1041)
The shifted operator is singular. The shift is an eigenvalue.
Try to use some other shift please.
Error in eigs/checkInputs (line 855)
[L,U,pp,qq,dgAsB] = LUfactorAminusSigmaB;
Error in eigs (line 94)
[A,Amatrix,isrealprob,issymA,n,B,classAB,k,eigs_sigma,whch, ...
Does this mean I am doing something wrong, or is this just matlab choosing a bad initial guess for its iteration process?
The matrices I am using should have a descent condition number...
I ran into the same problem while implementing normalized cuts segmentation. The condition number is actually infinite because the smallest eigenvalue is 0, and this is basically what MATLAB's error message is about. It's running LU decomposition first.
I just added a multiple of I, 10*eps*speye, to the normalized Laplacian to improve conditioning and that fixed it.
I had the same problem with the eigs function. So I went the long (and maybe stupid) way but it did the job for me as my problem is not that big: (I will try to keep your notation)
% Solve the eigenvalue problem using the full matrices
[v,c]=eig(full(L),full(M));
% Sort out the eigenvalues using the sort function (the "-" sign is because you want the smallest real eigenvalues in magnitude)
[E,P] = sort(real(c),'descend'); % Here I am assuming you know all the eigenvalues have` negative real parts
% Now P is a vector that contains (in order) the indices of the row permutation operated by the % function sort.
% In order to obtain the two eigenvectors corresponding to the 2 smallest eigenvalues:
for k = 1:2
index = P(k);
lambda(k) = c(index,index); % use this to check if c(index,index)=E(k,k)
eigvec(:,k) = v(:,index); % corresponding eigenvector
end
Hope this helps
G
I am getting this error while running my code:
Error using ==> mldivide Matrix dimensions must agree.
Here is my code :
%make the plots of phase and group velocity vs discreteness of the grid
c=1;
a=input('Please enter the ratio cdt/dx : ')
figure(1)
R=2:40;
plot(R,phase_vel(R,a)/c)
xlabel('R=l/dx')
ylabel('u_phase/c')
%figure(2)
%plot(group_vel(R,a),R,0,40)
%xlabel('R=l/dx')
%ylabel('u_group/c')
and here are my functions :
function phase_velocity = phase_vel(R,a)
%numerical phase velocity of the discrete wave
c=1;
phase_velocity=(2*pi*c)/(R*knum(R,a));
end
function group_velocity =group_vel(R,a )
%numerical group velocity of the discrete wave
c=1;
group_velocity=(a*sin(knum(R,a)))/(sin(2*pi*a/R))
end
function knumber = knum(R,a)
%This is the k wave number
knumber=acos((1/a)^2*(cos(2*pi*a/R)-1)+1);
end
How can I resolve this error?
EDIT: I used . operator in every equation and i changed the limits of R=4:40
If your goal is to apply your formulas to each individual value in the vector R then you should be performing all of your computations using the element-wise arithmetic operators .*, ./, and .^ instead of the matrix operators *, /, and ^.
Your error is probably occurring in the first call to your function knum, specifically when you try to compute 2*pi*a/R. Since 2*pi*a is a single scalar value, you get an error when trying to perform matrix right division / using the row vector R. The really weird thing is the error message:
??? Error using ==> mldivide
Matrix dimensions must agree.
which implies you are using the matrix left division operator \, which you clearly aren't. I tested this in MATLAB R2010b and I get the same incorrect function name appearing in my message. I think this may just be a typo in the error message, and I've dropped a note to the MATLAB folks to take a look at it and clear it up.
I don't have the Symbolic Math Toolbox, but your problem seems to be that you are using plot, a function which can deal with arrays of numbers, and feeding it the result of a symbolic calculation. Have a look at the Matlab Help, where the Topic Creating Plots of Symbolic Functions suggests using ezplot(). Alternatively you need to evaluate your symbolic expression for certain input values to create an array of numbers that plot can deal with - but you can't use double() for that since it wouldn't know what numbers to plug into your variables.