# Licensed under a 3-clause BSD style license - see LICENSE.rst

import numpy as np

from astropy.utils.data_info import ParentDtypeInfo

class NdarrayMixinInfo(ParentDtypeInfo):

_represent_as_dict_primary_data = "data"

def _represent_as_dict(self):

"""Represent Column as a dict that can be serialized."""

col = self._parent

out = {"data": col.view(np.ndarray)}

return out

def _construct_from_dict(self, map):

"""Construct Column from ``map``."""

data = map.pop("data")

out = self._parent_cls(data, **map)

return out

class NdarrayMixin(np.ndarray):

"""

Mixin column class to allow storage of arbitrary numpy

ndarrays within a Table. This is a subclass of numpy.ndarray

and has the same initialization options as ``np.array()``.

"""

info = NdarrayMixinInfo()

def __new__(cls, obj, *args, **kwargs):

self = np.array(obj, *args, **kwargs).view(cls)

if "info" in getattr(obj, "__dict__", ()):

self.info = obj.info

return self

def __array_finalize__(self, obj):

if obj is None:

return

if callable(super().__array_finalize__):

super().__array_finalize__(obj)

# Self was created from template (e.g. obj[slice] or (obj * 2))

# or viewcast e.g. obj.view(Column). In either case we want to

# init Column attributes for self from obj if possible.

if "info" in getattr(obj, "__dict__", ()):

self.info = obj.info

def __reduce__(self):

# patch to pickle NdArrayMixin objects (ndarray subclasses), see

# http://www.mail-archive.com/numpy-discussion@scipy.org/msg02446.html

object_state = list(super().__reduce__())

object_state[2] = (object_state[2], self.__dict__)

return tuple(object_state)

def __setstate__(self, state):

# patch to unpickle NdarrayMixin objects (ndarray subclasses), see

# http://www.mail-archive.com/numpy-discussion@scipy.org/msg02446.html

nd_state, own_state = state

super().__setstate__(nd_state)

self.__dict__.update(own_state)