Using your own custom data types

You can make your own data types by subclassing Table (or other PyTables types, such as tables.Leaf). This can be useful for storing a specialized type of data or presenting a customized API.

Here’s one way to do it, taken from http://sourceforge.net/mailarchive/message.php?msg_id=200805250042.50653.pgmdevlist%40gmail.com

from __future__ import print_function
import numpy as np
import numpy.ma as ma

import tables
from tables import File, Table
from tables.file import _checkfilters

from tables.parameters import EXPECTED_ROWS_TABLE

class MaskedTable(Table):
    _c_classId = 'MaskedTable'
    def __init__(self, parentNode, name, description=None,
                 title="", filters=None,

                 expectedrows=EXPECTED_ROWS_TABLE,
                 chunkshape=None, byteorder=None, _log=True):
        new = description is None
        if not new:
            maskedarray = description
            description = np.array(zip(maskedarray.filled().flat,

                                   ma.getmaskarray(maskedarray).flat),
                                   dtype=[('_data',maskedarray.dtype),
                                          ('_mask',bool)])
        Table.__init__(self, parentNode, name,
                       description=description, title=title,
                       filters=filters,

                       expectedrows=expectedrows,
                       chunkshape=chunkshape, byteorder=byteorder,
                       _log=_log)
        if not new:
            self.attrs.shape = maskedarray.shape

    def read(self, start=None, stop=None, step=None, field=None):
        data = Table.read(self, start=start, stop=stop, step=step,
                          field=field)
        newshape = self.attrs.shape
        return ma.array(data['_data'],
                        mask=data['_mask']).reshape(newshape)


def createMaskedTable(self, where, name, maskedarray, title="",
                      filters=None, expectedrows=10000,
                      chunkshape=None, byteorder=None,
                      createparents=False):
    parentNode = self._getOrCreatePath(where, createparents)

    _checkfilters(filters)
    return MaskedTable(parentNode, name, maskedarray,
                       title=title, filters=filters,
                       expectedrows=expectedrows,
                       chunkshape=chunkshape, byteorder=byteorder)


File.createMaskedTable = createMaskedTable


if __name__ == '__main__':
    x = ma.array(np.random.rand(100),mask=(np.random.rand(100) > 0.7))
    h5file = tables.openFile('tester.hdf5','w')
    mtab = h5file.createMaskedTable('/','random',x)

    h5file.flush()
    print(type(mtab))
    print(mtab.read())
    h5file.close()
    h5file = tables.openFile('tester.hdf5','r')
    mtab = h5file.root.random

    print(type(mtab))
    print(mtab.read())