Matvec Users’ Guide

3.4. COMPUTATION 29
sort
If A is a matrix, A.sort() sorts each column of A in an ascending order.
If A is a vector, A.sort() sorts the vector in an ascending order.
If you want to sort it in descending order, the following will do the job:
> a = Vector(3,2,4);
> b = a.sort()
i = 1 i = 2 i = 3
2 3 4
> b(3:1:-1) # sort it in descending order
i = 1 i = 2 i = 3
4 3 2
std
A.std() returns a vector containing the standard deviations for each column of A.
This member function is a user-defined function, it’s loaded automatically into memory whenever you
launch Matvec.
For example,
> A = [3,2,1;4,5,6;9,8,7];
> A.std()
sum
i = 1 i = 2 i = 3
3.21455 3 3.21455
A.sum() returns a vector containing sum values for each column of A. If A is a one-row or one-column matrix,
then the returned value would be a scalar.
sumsq
A.sumsq() returns a vector containing sum square values for each column of A. If A is a one-row or one-column
matrix, then the returned value would be a scalar.
svd
The singular value decomposition of an m-by-n matrix A is a decomposition
A = U*W*V’
where U is m-by-n with U’*U = I, W is an n-by-n diagonal matrix and V is an n-by-n orthogonal matrix.
Both A.svd() and A.svd(U,V) returns a vector containing diagonals in W, but the latter has U and V
which must be declared as matrix objects before calling.
If A is a scalar, then it will be treated as a 1-by-1 matrix.
For example,
> a=[1,2,3;2,9,4;2,1,8];
> u=[]; v=[];
> a.svd(u,v)
i = 1 i = 2 i = 3
12.0953 0.0538603 6.14008