2011/3/23 Adriano Vilela Barbosa <adriano.vil...@yahoo.com>
> This is not a bug, but rather a feature of NumPy. Look at this:
>
> >>> import numpy as np
> >>> a = np.array(['aa\x00\x00'])
> >>> a[0]
> 'aa' # hey! were have my trailing 0's gone?
> >>> a.data[:]
> 'aa\x00\x00' # yeah, they still are in the data area of the array
>
> I'd recommend you using the byte ('i1') type for achieving what you want:
>
> >>> a.view('i1')
> array([97, 97, 0, 0], dtype=int8)
>
> Thank you very much for your explanation, but I still don't get it.
>
> Let's forget numpy for a moment and just say I want to store the string
> 'aa\x00\x00' in a CArray. Each element of the CArray is a 4 element string.
> First, I create the CArray:
>
> >>> import tables
> >>> fid = tables.openFile("carray_test.hdf","w")
> >>> fid.createGroup("/", 'table', 'Binary table')
> >>> array_atom = tables.StringAtom(itemsize=4)
> >>> array_shape = (1,)
> >>> fid.createCArray(fid.root.table,'bin_table',array_atom,array_shape)
>
> Now, I store the string 'aa\x00\x00' in the first row (which is the only
> row in
> this example) of the CArray:
>
> >>> fid.root.table.bin_table[0] = 'aa\x00\x00'
>
> Now, I do
>
> >>> fid.root.table.bin_table[0].data[:]
> 'aa'
>
> So, it looks to me that the trailing \x00 elements of the string are not
> being
> stored in the CArray. From my side, there's no numpy involved; I'm just
> trying
> to store a string. What am I missing?
>
You cannot avoid NumPy because PyTables uses NumPy behind the scenes as an
intermediate buffer area. What you are seeing is probably a secondary
effect caused by the 'feature' I mentioned before. Any reason why you don't
want to use a byte type instead of a string?
--
Francesc Alted
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