[Pysparse-users] Adding a column of a sparse matrix to a dense vector

[Artur P. <art...@gm...>]

Hi to you all, I hope someone can help me.

I am trying to do the following with pysparse but I am having problems doing it.

I have a dense vector, say:

x = numpy.arange(0,10)

and a sparse matrix:

A = pysparse.spmatrix.ll_mat(10,10)

What I wish to do is:

x = x + A[:, 2]

But this gives the following error:
TypeError: unsupported operand type(s) for +: 'float' and 'll_mat'

Then I tried like this:

x = numpy.arange(0,10)

A = pysparse.sparray.sparray((10,10))

With this it works ok but then, when I try to do a slice:

A_reduced = A[0:5, 0:5]

It gives an error:
TypeError: unsupported operand type(s) for +: 'int' and 'slice'

Anybody can give a help?

Also, what is the main difference between spmatrix and sparray?

Thanking in advance

Best regards

-artur palha