observable.py 2.31 KB
Newer Older
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program.  If not, see <http://www.gnu.org/licenses/>.
#
# Copyright(C) 2013-2017 Max-Planck-Society
#
# IMAGINE is being developed at the Max-Planck-Institut fuer Astrophysik
# and financially supported by the Studienstiftung des deutschen Volkes.
18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42

from nifty import Field, FieldArray


class Observable(Field):
    def __init__(self, domain=None, val=None, dtype=None,
                 distribution_strategy=None, copy=False):

        super(Observable, self).__init__(
                                domain=domain,
                                val=val,
                                dtype=dtype,
                                distribution_strategy=distribution_strategy,
                                copy=copy)

        assert(len(self.domain) == 2)
        assert(isinstance(self.domain[0], FieldArray))

    def ensemble_mean(self):
        try:
            self._ensemble_mean
        except(AttributeError):
            self._ensemble_mean = self.mean(spaces=0)
        finally:
            return self._ensemble_mean
43 44

    def _to_hdf5(self, hdf5_group):
45
        if hasattr(self, '_ensemble_mean'):
46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62
            return_dict = {'ensemble_mean': self._ensemble_mean}
        else:
            return_dict = {}
        return_dict.update(
                   super(Observable, self)._to_hdf5(hdf5_group=hdf5_group))
        return return_dict

    @classmethod
    def _from_hdf5(cls, hdf5_group, repository):
        new_field = super(Observable, cls)._from_hdf5(hdf5_group=hdf5_group,
                                                      repository=repository)
        try:
            observable_mean = repository.get('ensemble_mean', hdf5_group)
            new_field._observable_mean = observable_mean
        except(KeyError):
            pass
        return new_field