[SciPy-Dev] Bug in use of np.sign() function with sparse csc_matrix?

[Nils Wagner]

On Sun, 22 Jan 2012 11:52:13 -0600
  Warren Weckesser <warren.weckesser@enthought.com> wrote:
> In all the examples that I've tried with a sparse 
>csc_matrix `a`, `sign(a)`
> always returns 1.  I expect it to return the matrix of 
>element-wise signs
> of a.  For example:
> 
> In [1]: from scipy.sparse import csc_matrix
> 
> In [2]: a = csc_matrix([[0.0, 1.0, 2.0], [0.0, 0.0, 
>-3.0], [0.0, 0.0, 0.0]])
> 
> In [3]: a.todense()
> Out[3]:
> matrix([[ 0.,  1.,  2.],
>        [ 0.,  0., -3.],
>        [ 0.,  0.,  0.]])
> 
> In [4]: np.sign(a.todense())
> Out[4]:
> matrix([[ 0.,  1.,  1.],
>        [ 0.,  0., -1.],
>        [ 0.,  0.,  0.]])
> 
> In [5]: np.sign(a)   # Incorrect result?
> Out[5]: 1
> 
> In [6]: import scipy
> 
> In [7]: scipy.__version__
> Out[7]: '0.11.0.dev-81dc505'
> 
> In [8]: np.__version__
> Out[8]: '1.6.1'
> 
> 
> I think that's a bug, but if someone knows better, let 
>me know!
> 
> Warren

>>> from scipy.linalg import signm
>>> signm(a.todense())
array([[  1.00000000e+00,  -2.01948392e-28, 
 -1.80945759e-25],
        [  0.00000000e+00,   1.00000000e+00, 
  7.06819371e-28],
        [  0.00000000e+00,   0.00000000e+00, 
  1.00000000e+00]])


Nils