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


How can I put a numpy multidimensional array in a HDF5 file using PyTables?

From what I can tell I can't put an array field in a pytables table.

I also need to store some info about this array and be able to do mathematical computations on it.

Any suggestions?


Solution

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

    import numpy as np
    import tables
    
    # Generate some data
    x = 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[:] = x
    f.close()
    

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

    import numpy as np
    import tables
    
    # Generate some data
    x = 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[:] = x
    f.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)