Source code for astropy.table.ndarray_mixin
# 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
[docs]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)