python(scipy):调整稀疏矩阵的大小

Question

我在调整矩阵大小时遇到​​了麻烦 - set_shape函数似乎没有效果:

>>> M
<14x3562 sparse matrix of type '<type 'numpy.float32'>'
   with 6136 stored elements in LInked List format>
>>> new_shape = (15,3562)
>>> M.set_shape(new_shape)
>>> M
<14x3562 sparse matrix of type '<type 'numpy.float32'>'
   with 6136 stored elements in LInked List format>

有人遇到过这个吗？

我也尝试过这样做,即

>>> M._shape = new_shape
>>> M.data = np.concatenate(M.data, np.empty((0,0), dtype=np.float32))

但是这引发了一个错误:

*** TypeError: only length-1 arrays can be converted to Python scalars

要么

>>> M.data = np.concatenate(M.data, [])
*** TypeError: an integer is required

有关信息:

• Python 2.6.5(r265:79063,2010年4月16日,13:57:41)
• scipy 0.11.0.dev-03f9e4a

Answer 1

如果你只想在最后添加一行零:

>>> M = sp.lil_matrix((14, 3562))
>>> sp.vstack([M, sp.lil_matrix((1, 3562))])
<15x3562 sparse matrix of type '<type 'numpy.float64'>'
        with 0 stored elements in COOrdinate format>