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zjpoh opened this issue Sep 11, 2019 · 3 comments
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Unexpected behavior with csr matrices #14487

zjpoh opened this issue Sep 11, 2019 · 3 comments
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57 - Close? Issues which may be closable unless discussion continued component: numpy._core

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@zjpoh
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zjpoh commented Sep 11, 2019

I also have unexpected behavior with csr matrices:

import numpy as np
from scipy.sparse import csr_matrix

a = np.array([[1, 0, 2, 2], [1, 4, 2, 4]])
m = csr_matrix(a)

m.shape
Out: (2, 4)

m.todense()
Out:
matrix([[1, 0, 2, 2],
        [1, 4, 2, 4]])

m_2 = np.asarray(m)
# weird shape
m_2.shape
Out: ()

# whereas it seems to be conserved somehow
m_2
Out:
array(<2x4 sparse matrix of type '<type 'numpy.int64'>'
	with 7 stored elements in Compressed Sparse Row format>, dtype=object)


m_2.todense()
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-12-3ca00cd97e3f> in <module>()
----> 1 m_2.todense()

AttributeError: 'numpy.ndarray' object has no attribute 'todense'

versions:
1.17.1 3.7.2 (default, Feb 12 2019, 08:16:38)
[Clang 10.0.0 (clang-1000.11.45.5)]

 python: 3.7.2 
 scipy: 1.3.1

Originally posted by @leonardbinet in #14221 (comment)
@rgommers
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So what's happening here is that np.asarray(sparse_matrix) returns an object array:

In [28]: m_2.shape                                                                 
Out[28]: ()

In [29]: type(m_2)                                                                 
Out[29]: numpy.ndarray

In [30]: m_2.dtype                                                                 
Out[30]: dtype('O')

With the sparse array being contained inside:

In [31]: m_2[()]                                                                   
Out[31]: 
<2x4 sparse matrix of type '<class 'numpy.int64'>'
        with 7 stored elements in Compressed Sparse Row format>

So m_2.todense() giving an AttributeError is expected, since m_2 is a numpy.ndarray. tl;dr not a bug but highly annoying. Two separate ways forward:

  • NumPy may change its behavior regarding creating object arrays at some point, or at least start giving warnings for such cases.
  • SciPy could decide to raise a TypeError here via an added __array__ method on all sparse matrices.

@seberg
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seberg commented Sep 16, 2019

I actually think the second option in scipy is probably the best thing. Raise an error and ask to use todense specifically.

@seberg seberg added the 57 - Close? Issues which may be closable unless discussion continued label Sep 16, 2019
@mattip
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mattip commented Dec 3, 2019

Closing. Please reopen with new information if needed.

@mattip mattip closed this as completed Dec 3, 2019
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