def test_unsupported_mdtol(self):
# The VARIANCE aggregator supports lazy_aggregation but does
# not provide mdtol handling. Check that a TypeError is raised
# if this unsupported kwarg is specified.
array = biggus.NumpyArrayAdapter(np.arange(8))
msg = "unexpected keyword argument 'mdtol'"
with self.assertRaisesRegexp(TypeError, msg):
VARIANCE.lazy_aggregate(array, axis=0, mdtol=0.8)
def test_unsupported_mdtol(self):
# The VARIANCE aggregator supports lazy_aggregation but does
# not provide mdtol handling. Check that a TypeError is raised
# if this unsupported kwarg is specified.
array = biggus.NumpyArrayAdapter(np.arange(8))
msg = "unexpected keyword argument 'mdtol'"
with self.assertRaisesRegexp(TypeError, msg):
VARIANCE.lazy_aggregate(array, axis=0, mdtol=0.8)
def test(self):
self.assertIsNotNone(VARIANCE.units_func)
mul = mock.Mock(return_value=mock.sentinel.new_unit)
units = mock.Mock(__mul__=mul)
new_units = VARIANCE.units_func(units)
# Make sure the VARIANCE units_func tries to square the units.
mul.assert_called_once_with(units)
self.assertEqual(new_units, mock.sentinel.new_unit)
def test(self):
self.assertIsNotNone(VARIANCE.units_func)
mul = mock.Mock(return_value=mock.sentinel.new_unit)
units = mock.Mock(__mul__=mul)
new_units = VARIANCE.units_func(units)
# Make sure the VARIANCE units_func tries to square the units.
mul.assert_called_once_with(units)
self.assertEqual(new_units, mock.sentinel.new_unit)
def test_ddof_zero(self):
array = biggus.NumpyArrayAdapter(np.arange(8))
var = VARIANCE.lazy_aggregate(array, axis=0, ddof=0)
self.assertArrayAlmostEqual(var.ndarray(), np.array(5.25))
def test(self):
shape = ()
kwargs = dict()
self.assertTupleEqual(VARIANCE.aggregate_shape(**kwargs), shape)
kwargs = dict(bat='man', wonder='woman')
self.assertTupleEqual(VARIANCE.aggregate_shape(**kwargs), shape)
def test(self):
self.assertEqual(VARIANCE.name(), 'variance')
def test_ddof_zero(self):
array = biggus.NumpyArrayAdapter(np.arange(8))
var = VARIANCE.lazy_aggregate(array, axis=0, ddof=0)
self.assertArrayAlmostEqual(var.ndarray(), np.array(5.25))
def test_ddof_zero(self):
array = as_lazy_data(np.arange(8))
var = VARIANCE.lazy_aggregate(array, axis=0, ddof=0)
result = as_concrete_data(var)
self.assertArrayAlmostEqual(result, np.array(5.25))
def test(self):
shape = ()
kwargs = dict()
self.assertTupleEqual(VARIANCE.aggregate_shape(**kwargs), shape)
kwargs = dict(bat='man', wonder='woman')
self.assertTupleEqual(VARIANCE.aggregate_shape(**kwargs), shape)
def test(self):
self.assertEqual(VARIANCE.name(), 'variance')
