Hello Everyone,

This is more of a request for clarification than an actual problem:

I have written a procedure that involves multiplication, inversion (using LinearSolve) and eigenvalues/vectors (using Eigenvectors) calculations. The matrices are large (~3600 x 3600), consist of floating point complex numbers, and on occasion I need to hold several in memory at once. Therefore, I want to make sure that all of the calculations (and storage of resulting matrices) are done using double precision, not arbitrary precision, in order to minimise the memory usage.

Dear All, I am enquiring as to how the "Eigenvectors" function in Maple (I am using version 10) orders the eigenvalues that it returns (and hence the eigenvectors). That is to say, if I input it with a matrix of complex floats, does it just return the eigenvalues it happens to find randomly, or is there some ordering in the vector of eigenvalues it returns? I ask this because if I input it with say a diagonal matrix that is symmetric about it's centre, then the vector of eignevalues returned is also symmetric. Is this just a coincidence in that maple happens to find the eigenvalues in that order, or does it choose to return them in that order? Otherwise, if there is no symmetry in the input matrix then there appears to be no symmetry in the returned vector of eigenvalues.

Hello everyone, I have written a procedure that makes some calculations for me, which I am calling repeatedly using a simple for loop. Basically what I am doing is using the for loop to change one of the several input parameters to the procedure and then use the result. Here is a quick example: > transmission0:=Matrix(1200,2): reflection0:=Matrix(1200,2): > for m from 1 to 1200 do > freq:=0.0416666666*m: > rcwa(31,0.0,0.2998/freq,6.0e-3,1.0,2234.950223+2237.186291*I,2.042123126+0.1633593958e-1*I,2234.950223+2237.186291*I,1.0,0.8333,18.0e-6,356.0e-6,18.0e-6): > transmission0[m,1]:=freq: >transmission0[m,2]:=te[M+1]:

Hello everyone, I am having problems using matrix constructions to augment/stack matrices together using Maple 9.0. The types of matrices I am combining are not huge, perhaps only 4 256x256 matrics into 1 512x512 matrix, although they do contain complex numbers that may be beyond hardware precision and therefore using arbitrary software precision. My main issue is with the speed this takes. If I use the old "augment" or "stackmatrix" constructors from the "linalg" package then this takes about 15 secs on my pc (1.4GHz 512MB) which seems unnecessarily long to me in the first place. Furthermore, if I use the new constructors from the "LinearAlgebra" package ("