Figure Properties - SERC

2lsqr
Purpose LSQR implementation of Conjugate Gradients on the Normal Equations
Syntax x = lsqr(A,b)
lsqr(A,b,tol)
lsqr(A,b,tol,maxit)
lsqr(A,b,tol,maxit,M)
lsqr(A,b,tol,maxit,M1,M2)
lsqr(A,b,tol,maxit,M1,M2,x0)
lsqr(afun,b,tol,maxit,m1fun,m2fun,x0,p1,p2,...)
[x,flag] = lsqr(A,b,...)
[x,flag,relres] = lsqr(A,b,...)
[x,flag,relres,iter] = lsqr(A,b,...)
[x,flag,relres,iter,resvec] = lsqr(A,b,...)
[x,flag,relres,iter,resvec,lsvec] = lsqr(A,b,...)
Description x = lsqr(A,b) attempts to solve the system of linear equations A*x=b for x if
A is consistent, otherwise it attempts to solve the least squares solution x that
minimizes norm(b-A*x). The m-by-n coefficient matrix A need not be square but
it should be large and sparse. The column vector b must have length m. A can
be a function afun such that afun(x) returns A*x and afun(x,'transp')
returns A'*x.
If lsqr converges, a message to that effect is displayed. If lsqr fails to converge
after the maximum number of iterations or halts for any reason, a warning
message is printed displaying the relative residual norm(b-A*x)/norm(b) and
the iteration number at which the method stopped or failed. You can suppress
these messages by calling lsqr with the syntax
[x,flag] = lsqr(A,b,...)
which returns an integer flag instead of the message, as described in the
following table.
lsqr(A,b,tol) specifies the tolerance of the method. If tol is [], then lsqr
uses the default, 1e-6.
lsqr(A,b,tol,maxit) specifies the maximum number of iterations. If maxit
is [], then lsqr uses the default, min([m,n,20]).
lsqr
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