Python: how to store a numpy multidimensional array in PyTables?

There may be a simpler way, but this is how you'd go about doing it, as far as I know:

import numpy as npimport tables# Generate some datax = np.random.random((100,100,100))# Store "x" in a chunked array...f = tables.open_file('test.hdf', 'w')atom = tables.Atom.from_dtype(x.dtype)ds = f.createCArray(f.root, 'somename', atom, x.shape)ds[:] = xf.close()

If you want to specify the compression to use, have a look at tables.Filters. E.g.

import numpy as npimport tables# Generate some datax = np.random.random((100,100,100))# Store "x" in a chunked array with level 5 BLOSC compression...f = tables.open_file('test.hdf', 'w')atom = tables.Atom.from_dtype(x.dtype)filters = tables.Filters(complib='blosc', complevel=5)ds = f.createCArray(f.root, 'somename', atom, x.shape, filters=filters)ds[:] = xf.close()

There's probably a simpler way for a lot of this... I haven't used pytables for anything other than table-like data in a long while.

Note: with pytables 3.0, f.createCArray was renamed to f.create_carray. It can also accept the array directly, without specifying the atom,

f.create_carray('/', 'somename', obj=x, filters=filters)