有效地重塑稀疏矩阵，Python，SciPy 0.12 [英] Reshape sparse matrix efficiently, Python, SciPy 0.12

问题描述

在关于在SciPy中调整稀疏矩阵大小的另一篇文章中，当要分别使用scipy.sparse.vstack或hstack添加更多的行或列时，答案有效.在SciPy 0.12中， reshape 或

In another post regarding resizing of a sparse matrix in SciPy the accepted answer works when more rows or columns are to be added, using scipy.sparse.vstack or hstack, respectively. In SciPy 0.12 the reshape or set_shape methods are still not implemented.

是否有一些稳定的良好做法来重塑SciPy 0.12中的稀疏矩阵?进行一些时间比较会很好.

Are there some stabilished good practices to reshape a sparse matrix in SciPy 0.12? It would be nice to have some timing comparisons.

推荐答案

自 SciPy 1.1.0 ，即

As of SciPy 1.1.0, the reshape and set_shape methods have been implemented for all sparse matrix types. The signatures are what you would expect and are as identical to the equivalent methods in NumPy as feasible (e.g. you can't reshape to a vector or tensor).

签名:

reshape(self, shape: Tuple[int, int], order: 'C'|'F' = 'C', copy: bool = False) -> spmatrix

示例:

>>> from scipy.sparse import csr_matrix
>>> A = csr_matrix([[0,0,2,0], [0,1,0,3]])
>>> print(A)
  (0, 2)    2
  (1, 1)    1
  (1, 3)    3
>>> B = A.reshape((4,2))
>>> print(B)
  (1, 0)    2
  (2, 1)    1
  (3, 1)    3
>>> C = A.reshape((4,2), order='F')
>>> print(C)
  (0, 1)    2
  (3, 0)    1
  (3, 1)    3

完全公开:我写了实现.

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