I'm having trouble resizing a matrix - the set_shape
function seems to have no effect:
>>> 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>
Anyone else come across this?
I also tried doing this by hand, ie
>>> M._shape = new_shape
>>> M.data = np.concatenate(M.data, np.empty((0,0), dtype=np.float32))
but that throws up an error:
*** TypeError: only length-1 arrays can be converted to Python scalars
or
>>> M.data = np.concatenate(M.data, [])
*** TypeError: an integer is required
For info:
If you just want to add a row of zeros at the end:
>>> 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>
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