def test_execute_sample_size(self):
field = self.get_field(with_value=True, month_count=2)
grouping = ['month']
tgd = field.temporal.get_grouping(grouping)
mu = Mean(field=field,
tgd=tgd,
alias='my_mean',
calc_sample_size=True,
dtype=np.float64)
dvc = mu.execute()
dv = dvc['my_mean']
self.assertEqual(dv.name, 'my_mean')
self.assertEqual(dv.get_value().shape, (2, 2, 2, 3, 4))
self.assertNumpyAll(
np.mean(field['tmax'].get_value()[1, tgd.dgroups[1], 0, :, :],
axis=0),
dv.get_value()[1, 1, 0, :, :])
ret = dvc['n_my_mean']
self.assertNumpyAll(
ret.get_masked_value()[0, 0, 0],
np.ma.array(data=[[31, 31, 31, 31], [31, 31, 31, 31],
[31, 31, 31, 31]],
mask=[[False, False, False, False],
[False, False, False, False],
[False, False, False, False]],
fill_value=999999,
dtype=ret.dtype))
mu = Mean(field=field,
tgd=tgd,
alias='my_mean',
calc_sample_size=False)
dvc = mu.execute()
self.assertNotIn('n_my_mean', list(dvc.keys()))
def test_execute_units_are_maintained(self):
field = self.get_field(with_value=True, month_count=2)
units_kelvin = get_units_object('kelvin')
self.assertEqual(field['tmax'].cfunits, units_kelvin)
grouping = ['month']
tgd = field.temporal.get_grouping(grouping)
mu = Mean(field=field,
tgd=tgd,
alias='my_mean',
calc_sample_size=False,
dtype=np.float64)
dvc = mu.execute()
self.assertEqual(dvc['my_mean'].cfunits, units_kelvin)
def test_calculate(self):
rd = self.test_data.get_rd('cancm4_tas')
field = rd.get()
field = field.get_field_slice({'y': slice(0, 10), 'x': slice(0, 10)})
klasses = [IcclimTG, IcclimTN, IcclimTX]
for klass in klasses:
for calc_grouping in [['month'], ['month', 'year']]:
tgd = field.temporal.get_grouping(calc_grouping)
itg = klass(field=field, tgd=tgd)
ret_icclim = itg.execute()
mean = Mean(field=field, tgd=tgd)
ret_ocgis = mean.execute()
self.assertNumpyAll(ret_icclim[klass.key].get_value(), ret_ocgis['mean'].get_value())
def test_execute(self):
field = self.get_field(with_value=True, month_count=2)
self.assertIsInstance(field, Field)
grouping = ['month']
tgd = field.temporal.get_grouping(grouping)
mu = Mean(field=field, tgd=tgd, alias='my_mean', dtype=np.float64)
dvc = mu.execute()
dv = dvc['my_mean']
self.assertEqual(dv.name, 'my_mean')
self.assertEqual(dv.get_value().shape, (2, 2, 2, 3, 4))
self.assertNumpyAll(
np.mean(field['tmax'].get_value()[1, tgd.dgroups[1], 0, :, :],
axis=0),
dv.get_value()[1, 1, 0, :, :])
def test_execute_two_variables(self):
"""Test running a field with two variables through the mean calculation."""
field = self.get_field(with_value=True, month_count=2)
field.add_variable(Variable(value=field['tmax'].get_value() + 5,
name='tmin',
dimensions=field['tmax'].dimensions),
is_data=True)
grouping = ['month']
tgd = field.temporal.get_grouping(grouping)
mu = Mean(field=field, tgd=tgd, alias='my_mean', dtype=np.float64)
ret = mu.execute()
self.assertEqual(len(ret), 2)
self.assertAlmostEqual(
5.0,
abs(ret['my_mean_tmax'].get_value().mean() -
ret['my_mean_tmin'].get_value().mean()))
def test_execute_file_only(self):
rd = self.test_data.get_rd('cancm4_tas')
field = rd.get()
field = field.get_field_slice({
'time': slice(10, 20),
'y': slice(20, 30),
'x': slice(40, 50)
})
grouping = ['month']
tgd = field.temporal.get_grouping(grouping)
# Value should not be loaded at this point.
self.assertEqual(field['tas']._value, None)
mu = Mean(field=field, tgd=tgd, alias='my_mean', file_only=True)
ret = mu.execute()
# Value should still not be loaded.
self.assertIsNone(field['tas']._value)
# No value should be calculated for the calculation.
self.assertIsNone(ret['my_mean']._value)
def test_execute_two_variables_sample_size(self):
field = self.get_field(with_value=True, month_count=2)
field.add_variable(Variable(value=field['tmax'].get_value() + 5,
name='tmin',
dimensions=field['tmax'].dimensions),
is_data=True)
grouping = ['month']
tgd = field.temporal.get_grouping(grouping)
mu = Mean(field=field,
tgd=tgd,
alias='my_mean',
dtype=np.float64,
calc_sample_size=True)
ret = mu.execute()
self.assertEqual(len(ret), 4)
self.assertAlmostEqual(
5.0,
abs(ret['my_mean_tmax'].get_value().mean() -
ret['my_mean_tmin'].get_value().mean()))
self.assertEqual(
{
'my_mean_tmax', 'n_my_mean_tmax', 'my_mean_tmin',
'n_my_mean_tmin'
}, set(ret.keys()))
