I have files stored using Matlab's sparse format (HDF5, csc I
believe), and I'm trying to use Pytables to operate on them directly,
but haven't succeeded yet. Using h5py I can do the following:
# Method 1: uses h5py (WORKS)
f1 = h5py.File(fname)
data = f1['M']['data]
ir = f1['M]['ir']
jc = f1['M']['jc']
M = scipy.sparse.csc_matrix( (data,ir,jc) )
but if I try to do the equivalent in Pytables:
# Method 2: uses pyTables (DOESN'T WORK)
f2 = tables.openFile(fname)
data = f2.root.M.data
ir = f2.root.M.ir
jc = f2.root.M.jc
M = scipy.sparse.csc_matrix( (data,ir,jc) )
this fails (after a long wait) with the error:
TypeError Traceback (most recent call last)
/home/tdiethe/BMJ/<ipython console> in <module>()
/usr/lib/python2.6/dist-packages/scipy/sparse/compressed.pyc in
__init__(self, arg1, shape, dtype, copy, dims, nzmax)
56 self.indices = np.array(indices, copy=copy)
57 self.indptr = np.array(indptr, copy=copy)
---> 58 self.data = np.array(data, copy=copy,
dtype=getdtype(dtype, data))
59 else:
60 raise ValueError, "unrecognized %s_matrix
constructor usage" %\
/usr/lib/python2.6/dist-packages/scipy/sparse/sputils.pyc in
getdtype(dtype, a, default)
69 canCast = False
70 else:
---> 71 raise TypeError, "could not interpret data type"
72 else:
73 newdtype = np.dtype(dtype)
TypeError: could not interpret data type
I have two questions:
- how do I load this file in
- do I need to perform the conversion to a scipy sparse matrix in
order to be able to perform operations on it, or can I perform
operations directly on the disk files (matrix multiplication etc)?
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