[Numpy-discussion] Sparse matrices in NumPy?

Jon Saenz jsaenz at wm.lc.ehu.es
Mon Jun 5 12:22:52 CDT 2000


I don't know if I am missing something, but:

Let's suppose you have A so that A.shape is (7731,). It is diagonal, so,
obviously, you don't need to save it all. Just a vector.

You also have B, shaped like this: (7731,220)

And you want to multiply A*B (the matrix way).

I would dare to say that what you really need is
C=A[:,NewAxis]*B
C will be shaped as (7731,220), which is what you probably need.

Jon Saenz.				| Tfno: +34 946012470
Depto. Fisica Aplicada II               | Fax:  +34 944648500
Facultad de Ciencias.   \\ Universidad del Pais Vasco \\
Apdo. 644   \\ 48080 - Bilbao  \\ SPAIN

On Mon, 5 Jun 2000, Paul Gettings wrote:

> > But memory is so cheap these days! ;-)
> I am a grad student, and have no money. :(
> 
> >  > However, the matrix is empty except for the main diagonal. 
> > Multiplying by a diagonalized matrix is just vectorized multiplication:
> > a 0 0 
> > 0 b 0   .  <x, y, z> = <az, by, cz>
> > 0 0 c
> My mistake - I need to multiply the 7731x7731 by a 7731x220 element matrix -
> square matrix times rectangular matrix, not just 2 diagonal matrices.
> Otherwise, the problem wouldn't be so hard. :)
> 
> --
>   That which does not kill you, didn't try hard enough.
> 
> 
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