Storing numpy sparse matrix in HDF5 (PyTables)

Question

I am having trouble storing a numpy csr_matrix with PyTables. I'm getting this error: ``` TypeError: objects of type ``csr_matrix`` are not supported in this context, sorry; supported objects are: NumPy array, record or scalar; homogeneous list or tuple, integer, float, complex or string ``` My code: ``` f = tables.openFile(path,'w') atom = tables.Atom.from_dtype(self.count_vector.dtype) ds = f.createCArray(f.root, 'count', atom, self.count_vector.shape) ds[:] = self.count_vector f.close() ``` Any ideas? Thanks

Accepted Answer

A CSR matrix can be fully reconstructed from its `data`, `indices` and `indptr` attributes. These are just regular numpy arrays, so there should be no problem storing them as 3 separate arrays in pytables, then passing them back to the constructor of `csr_matrix`. See the scipy docs.

Edit: Pietro's answer has pointed out that the `shape` member should also be stored

Storing numpy sparse matrix in HDF5 (PyTables)

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