[Pysparse-users] can't assign from a dense matrix

[Rob S. <rs...@MI...>]

It's hard to tell from the Web, but it sounds like the right thing to
do when I encounter unexpected behavior in PySparse is to e-mail this
list, right?

I'm trying to assign to a slice of an ll_mat from another matrix. If
this other matrix is also an ll_mat, this works fine. However, it acts
very strange if the other matrix is a standard NumPy ndarray:

----------
In [1]: from pysparse.spmatrix import *

In [2]: sq = ll_mat(5,5)

In [3]: sq
Out[3]: <ll_mat object at 0x1d26bf0>

In [4]: print sq
------> print(sq)
ll_mat(general, [5,5]):
 --------  --------  --------  --------  --------
 --------  --------  --------  --------  --------
 --------  --------  --------  --------  --------
 --------  --------  --------  --------  --------
 --------  --------  --------  --------  --------

In [6]: import numpy as np

In [7]: sq[:,:] = np.arange(25).reshape((5,5))
In LHS=RHS, RHS has shape (2,27483600), LHS has shape (5,5)
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)

/Users/rspeer/python/src/pysparse/<ipython console> in <module>()

ValueError: Matrix shapes are different
-----------

There seems to be no other straightforward way to convert a small
dense matrix to a sparse one, either. Am I missing how to do this, or
is this a bug that should be fixed?

-- Rob