Hi all, Indeed it seems to work as I wanted it to. Thanks alot for the help :) Per On Thu, Dec 1, 2011 at 23:36, Aronne Merrelli <aronne.merrelli@gmail.com>wrote:
On Wed, Nov 30, 2011 at 3:01 AM, Per Nielsen <evilper@gmail.com> wrote:
Hi all
I am trying to create a subclass of the sparse matrix class in scipy, to add some extra methods I need.
I have tried to follow the guide on: http://www.scipy.org/Subclasses but without much luck, the view method does not exist for the sparse matrix class. Below is a script I have created
Hi,
It appears that sparse matrices do not inherit from numpy.ndarray:
In [5]: sparse_mat = csr_matrix( np.ones(3) ) In [7]: isinstance( sparse_mat, np.ndarray ) Out[7]: False
So much of the numpy - specific information on that page at scipy.org is not relevant for a sparse matrix subclass. I would assume subclassing csr_matrix would essentially look more like plain python subclassing. However, playing around with this, I quickly found what appears to be a sparse matrix-specific aspect. The sparse matrix format is based on the name of the class - so if you want this to work you have to name the subclass with the same 3 letters as the desired subclass ("csr" in this case). Here is a minimal example that works - note the fail_matrix doesn't work, and causes an attribute error just because of the name:
from scipy.sparse.csr import csr_matrix
class csr_matrix_alt(csr_matrix): def __init__(self, *args, **kwargs): csr_matrix.__init__(self, *args, **kwargs) def square_spmat(self): return self ** 2
class fail_matrix(csr_matrix): pass
x = np.array( [[1, 0], [1, 3]] ) xsparse = csr_matrix_alt(x) xsparse_sq = xsparse.square_spmat()
print xsparse.todense() print xsparse_sq.todense()
xfail = fail_matrix(x)
Here is the output I get, running from ipython:
In [2]: execfile('spsub_example.py') [[1 0] [1 3]] [[1 0] [4 9]] --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) <snip> AttributeError: tofai not found
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