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from ...extern.six.moves import cPickle as pickle
import numpy as np
from ...table import Table, Column, MaskedColumn, QTable
from ...table.table_helpers import simple_table
from ...units import Quantity, deg
from ...time import Time
from ...coordinates import SkyCoord
def test_pickle_column(protocol):
c = Column(data=[1, 2], name='a', format='%05d', description='col a', unit='cm', meta={'a': 1})
cs = pickle.dumps(c)
cp = pickle.loads(cs)
assert np.all(cp == c)
assert cp.attrs_equal(c)
assert cp._parent_table is None
assert repr(c) == repr(cp)
def test_pickle_masked_column(protocol):
c = MaskedColumn(data=[1, 2], name='a', format='%05d', description='col a', unit='cm',
meta={'a': 1})
c.mask[1] = True
c.fill_value = -99
cs = pickle.dumps(c)
cp = pickle.loads(cs)
assert np.all(cp._data == c._data)
assert np.all(cp.mask == c.mask)
assert cp.attrs_equal(c)
assert cp.fill_value == -99
assert cp._parent_table is None
assert repr(c) == repr(cp)
def test_pickle_multidimensional_column(protocol):
"""Regression test for https://github.com/astropy/astropy/issues/4098"""
a = np.zeros((3, 2))
c = Column(a, name='a')
cs = pickle.dumps(c)
cp = pickle.loads(cs)
assert np.all(c == cp)
assert c.shape == cp.shape
assert cp.attrs_equal(c)
assert repr(c) == repr(cp)
def test_pickle_table(protocol):
a = Column(data=[1, 2], name='a', format='%05d', description='col a', unit='cm', meta={'a': 1})
b = Column(data=[3.0, 4.0], name='b', format='%05d', description='col b', unit='cm',
meta={'b': 1})
for table_class in Table, QTable:
t = table_class([a, b], meta={'a': 1, 'b': Quantity(10, unit='s')})
t['c'] = Quantity([1, 2], unit='m')
t['d'] = Time(['2001-01-02T12:34:56', '2001-02-03T00:01:02'])
t['e'] = SkyCoord([125.0,180.0]*deg, [-45.0,36.5]*deg)
ts = pickle.dumps(t)
tp = pickle.loads(ts)
assert tp.__class__ is table_class
assert np.all(tp['a'] == t['a'])
assert np.all(tp['b'] == t['b'])
# test mixin columns
assert np.all(tp['c'] == t['c'])
assert np.all(tp['d'] == t['d'])
assert np.all(tp['e'].ra == t['e'].ra)
assert np.all(tp['e'].dec == t['e'].dec)
assert type(tp['c']) is type(t['c']) # nopep8
assert type(tp['d']) is type(t['d']) # nopep8
assert type(tp['e']) is type(t['e']) # nopep8
assert tp.meta == t.meta
assert type(tp) is type(t)
assert isinstance(tp['c'], Quantity if (table_class is QTable) else Column)
def test_pickle_masked_table(protocol):
a = Column(data=[1, 2], name='a', format='%05d', description='col a', unit='cm', meta={'a': 1})
b = Column(data=[3.0, 4.0], name='b', format='%05d', description='col b', unit='cm',
meta={'b': 1})
t = Table([a, b], meta={'a': 1}, masked=True)
t['a'].mask[1] = True
t['a'].fill_value = -99
ts = pickle.dumps(t)
tp = pickle.loads(ts)
for colname in ('a', 'b'):
for attr in ('_data', 'mask', 'fill_value'):
assert np.all(getattr(tp[colname], attr) == getattr(tp[colname], attr))
assert tp['a'].attrs_equal(t['a'])
assert tp['b'].attrs_equal(t['b'])
assert tp.meta == t.meta
def test_pickle_indexed_table(protocol):
"""
Ensure that any indices that have been added will survive pickling.
"""
t = simple_table()
t.add_index('a')
t.add_index(['a', 'b'])
ts = pickle.dumps(t)
tp = pickle.loads(ts)
assert len(t.indices) == len(tp.indices)
for index, indexp in zip(t.indices, tp.indices):
assert np.all(index.data.data == indexp.data.data)
assert index.data.data.colnames == indexp.data.data.colnames
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