def test_execute_no_units(self):
"""Test there are no units associated with a natual log."""
field = self.get_field(with_value=True, month_count=2)
ln = NaturalLogarithm(field=field, alias='ln')
dvc = ln.execute()
self.assertEqual(dvc['ln'].units, None)
def test_execute_no_units(self):
"""Test there are no units associated with a natual log."""
field = self.get_field(with_value=True, month_count=2)
ln = NaturalLogarithm(field=field, alias='ln')
dvc = ln.execute()
self.assertEqual(dvc['ln'].units, None)
def test_execute_spatial_aggregation(self):
field = self.get_field(with_value=True, month_count=2)
grouping = ['month']
tgd = field.temporal.get_grouping(grouping)
ln = NaturalLogarithm(field=field, tgd=tgd, calc_sample_size=True, spatial_aggregation=True)
ret = ln.execute()
self.assertEqual(ret['ln'].get_value().shape, (2, 2, 2, 3, 4))
self.assertEqual(ret['n_ln'].get_value().mean(), 30.0)
def test_NaturalLogarithm(self):
field = self.get_field(with_value=True,month_count=2)
ln = NaturalLogarithm(field=field)
ret = ln.execute()
self.assertEqual(ret['ln'].value.shape,(2, 60, 2, 3, 4))
self.assertNumpyAllClose(ret['ln'].value,np.log(field.variables['tmax'].value))
ln = NaturalLogarithm(field=field,calc_sample_size=True)
ret = ln.execute()
self.assertNotIn('n_ln',ret.keys())
def test_execute_spatial_aggregation(self):
field = self.get_field(with_value=True, month_count=2)
grouping = ['month']
tgd = field.temporal.get_grouping(grouping)
ln = NaturalLogarithm(field=field,
tgd=tgd,
calc_sample_size=True,
spatial_aggregation=True)
ret = ln.execute()
self.assertEqual(ret['ln'].get_value().shape, (2, 2, 2, 3, 4))
self.assertEqual(ret['n_ln'].get_value().mean(), 30.0)
def test_execute_temporally_grouped(self):
field = self.get_field(with_value=True, month_count=2)
grouping = ['month']
tgd = field.temporal.get_grouping(grouping)
ln = NaturalLogarithm(field=field, tgd=tgd)
ret = ln.execute()
self.assertEqual(ret['ln'].get_value().shape, (2, 2, 2, 3, 4))
to_test = np.log(field['tmax'].get_value())
to_test = np.ma.mean(to_test[0, tgd.dgroups[0], 0, :, :], axis=0)
to_test2 = ret['ln'].get_value()[0, 0, 0, :, :]
self.assertNumpyAllClose(to_test, to_test2)
ln = NaturalLogarithm(field=field, tgd=tgd, calc_sample_size=True)
ret = ln.execute()
self.assertEqual(ret['ln'].get_value().shape, (2, 2, 2, 3, 4))
self.assertEqual(ret['n_ln'].get_value().mean(), 30.0)
def test_execute(self):
field = self.get_field(with_value=True, month_count=2)
ln = NaturalLogarithm(field=field)
ret = ln.execute()
self.assertEqual(ret['ln'].get_value().shape, (2, 60, 2, 3, 4))
self.assertNumpyAllClose(ret['ln'].get_value(),
np.log(field['tmax'].get_value()))
ln = NaturalLogarithm(field=field, calc_sample_size=True)
ret = ln.execute()
self.assertNotIn('n_ln', list(ret.keys()))
def test_execute_temporally_grouped(self):
field = self.get_field(with_value=True, month_count=2)
grouping = ['month']
tgd = field.temporal.get_grouping(grouping)
ln = NaturalLogarithm(field=field, tgd=tgd)
ret = ln.execute()
self.assertEqual(ret['ln'].get_value().shape, (2, 2, 2, 3, 4))
to_test = np.log(field['tmax'].get_value())
to_test = np.ma.mean(to_test[0, tgd.dgroups[0], 0, :, :], axis=0)
to_test2 = ret['ln'].get_value()[0, 0, 0, :, :]
self.assertNumpyAllClose(to_test, to_test2)
ln = NaturalLogarithm(field=field, tgd=tgd, calc_sample_size=True)
ret = ln.execute()
self.assertEqual(ret['ln'].get_value().shape, (2, 2, 2, 3, 4))
self.assertEqual(ret['n_ln'].get_value().mean(), 30.0)
def test_NaturalLogarithm_units_dimensionless(self):
field = self.get_field(with_value=True,month_count=2)
ln = NaturalLogarithm(field=field,alias='ln')
dvc = ln.execute()
self.assertEqual(dvc['ln'].units,None)
