def test_validation(self):
"""
Test input validation
"""
ds = xr.Dataset({
'first': (['lat', 'lon', 'time'], np.ones([45, 90, 24])),
'lat':
np.linspace(-88, 88, 45),
'lon':
np.linspace(-178, 178, 90)
})
ds = adjust_temporal_attrs(ds)
with self.assertRaises(ValueError) as err:
long_term_average(ds)
self.assertIn('normalize', str(err.exception))
ds = xr.Dataset({
'first': (['lat', 'lon', 'time'], np.ones([45, 90, 24])),
'lat':
np.linspace(-88, 88, 45),
'lon':
np.linspace(-178, 178, 90),
'time':
pd.date_range('2000-01-01', periods=24)
})
ds = adjust_temporal_attrs(ds)
with self.assertRaises(ValueError) as err:
long_term_average(ds)
self.assertIn('temporal aggregation', str(err.exception))
def test_nominal(self):
"""
Test nominal execution
"""
ds = xr.Dataset({
'first': (['lat', 'lon', 'time'], np.ones([45, 90, 24])),
'second': (['lat', 'lon', 'time'], np.ones([45, 90, 24])),
'lat': np.linspace(-88, 88, 45),
'lon': np.linspace(-178, 178, 90),
'time': pd.date_range('2000-01-01', freq='MS', periods=24)})
ds = adjust_temporal_attrs(ds)
# Test monitor
m = ConsoleMonitor()
actual = long_term_average(ds, monitor=m)
self.assertEqual(m._percentage, 100)
# Test CF attributes
self.assertEqual(actual['first'].attrs['cell_methods'],
'time: mean over years')
self.assertEqual(actual.dims, {'time': 12,
'nv': 2,
'lat': 45,
'lon': 90})
self.assertEqual(actual.time.attrs['climatology'],
'climatology_bounds')
# Test variable selection
actual = long_term_average(ds, var='first')
with self.assertRaises(KeyError):
actual['second']
def test_nominal(self):
"""
Test nominal execution
"""
ds = xr.Dataset({
'first': (['lat', 'lon', 'time'], np.ones([45, 90, 24])),
'second': (['lat', 'lon', 'time'], np.ones([45, 90, 24])),
'lat': np.linspace(-88, 88, 45),
'lon': np.linspace(-178, 178, 90),
'time': pd.date_range('2000-01-01', freq='MS', periods=24)})
ds = adjust_temporal_attrs(ds)
# Test monitor
m = ConsoleMonitor()
actual = long_term_average(ds, monitor=m)
self.assertEqual(m._percentage, 100)
# Test CF attributes
self.assertEqual(actual['first'].attrs['cell_methods'],
'time: mean over years')
self.assertEqual(actual.dims, {'time': 12,
'nv': 2,
'lat': 45,
'lon': 90})
self.assertEqual(actual.time.attrs['climatology'],
'climatology_bounds')
# Test variable selection
actual = long_term_average(ds, var='first')
with self.assertRaises(KeyError):
actual['second']
def test_general(self):
"""
Test creating a 'general' LTA dataset
"""
# Test seasonal
ds = xr.Dataset({
'first': (['lat', 'lon', 'time'], np.ones([45, 90, 5])),
'second': (['lat', 'lon', 'time'], np.ones([45, 90, 5])),
'lat':
np.linspace(-88, 88, 45),
'lon':
np.linspace(-178, 178, 90),
'time':
pd.date_range('1999-12-01', freq='QS-DEC', periods=5)
})
ds = adjust_temporal_attrs(ds)
actual = long_term_average(ds)
self.assertEqual(actual['first'].attrs['cell_methods'],
'time: mean over years')
self.assertEqual(actual.dims, {
'time': 4,
'nv': 2,
'lat': 45,
'lon': 90
})
self.assertEqual(actual.time.attrs['climatology'],
'climatology_bounds')
# Test irregular seasons
ds = xr.Dataset({
'first': (['lat', 'lon', 'time'], np.ones([45, 90, 6])),
'second': (['lat', 'lon', 'time'], np.ones([45, 90, 6])),
'lat':
np.linspace(-88, 88, 45),
'lon':
np.linspace(-178, 178, 90),
'time':
pd.date_range('2000-01-01', freq='5M', periods=6)
})
ds = adjust_temporal_attrs(ds)
with self.assertRaises(ValueError) as err:
long_term_average(ds)
self.assertIn('inconsistent seasons', str(err.exception))
# Test 8D
ds = xr.Dataset({
'first': (['lat', 'lon', 'time'], np.ones([45, 90, 137])),
'second': (['lat', 'lon', 'time'], np.ones([45, 90, 137])),
'lat':
np.linspace(-88, 88, 45),
'lon':
np.linspace(-178, 178, 90),
'time':
pd.date_range('2000-01-01', '2002-12-31', freq='8D')
})
ds = adjust_temporal_attrs(ds)
with self.assertRaises(ValueError) as err:
long_term_average(ds)
self.assertIn('inconsistent seasons', str(err.exception))
def test_validation(self):
"""
Test input validation
"""
ds = xr.Dataset({
'first': (['lat', 'lon', 'time'], np.ones([45, 90, 24])),
'lat': np.linspace(-88, 88, 45),
'lon': np.linspace(-178, 178, 90)})
ds = adjust_temporal_attrs(ds)
with self.assertRaises(ValueError) as err:
long_term_average(ds)
self.assertIn('normalize', str(err.exception))
def test_daily(self):
"""
Test creating a daily LTA dataset
"""
ds = xr.Dataset({
'first': (['lat', 'lon', 'time'], np.ones([45, 90, 730])),
'second': (['lat', 'lon', 'time'], np.ones([45, 90, 730])),
'lat':
np.linspace(-88, 88, 45),
'lon':
np.linspace(-178, 178, 90),
'time':
pd.date_range('2001-01-01', '2002-12-31')
})
ds = adjust_temporal_attrs(ds)
actual = long_term_average(ds)
# Test CF attributes
self.assertEqual(actual['first'].attrs['cell_methods'],
'time: mean over years')
self.assertEqual(actual.dims, {
'time': 365,
'nv': 2,
'lat': 45,
'lon': 90
})
self.assertEqual(actual.time.attrs['climatology'],
'climatology_bounds')
def test_general(self):
"""
Test creating a 'general' LTA dataset
"""
# Test seasonal
ds = xr.Dataset({
'first': (['lat', 'lon', 'time'], np.ones([45, 90, 5])),
'second': (['lat', 'lon', 'time'], np.ones([45, 90, 5])),
'lat': np.linspace(-88, 88, 45),
'lon': np.linspace(-178, 178, 90),
'time': pd.date_range('1999-12-01', freq='QS-DEC', periods=5)})
ds = adjust_temporal_attrs(ds)
actual = long_term_average(ds)
self.assertEqual(actual['first'].attrs['cell_methods'],
'time: mean over years')
self.assertEqual(actual.dims, {'time': 4,
'nv': 2,
'lat': 45,
'lon': 90})
self.assertEqual(actual.time.attrs['climatology'],
'climatology_bounds')
# Test irregular seasons
ds = xr.Dataset({
'first': (['lat', 'lon', 'time'], np.ones([45, 90, 6])),
'second': (['lat', 'lon', 'time'], np.ones([45, 90, 6])),
'lat': np.linspace(-88, 88, 45),
'lon': np.linspace(-178, 178, 90),
'time': pd.date_range('2000-01-01', freq='5M', periods=6)})
ds = adjust_temporal_attrs(ds)
with self.assertRaises(ValueError) as err:
long_term_average(ds)
self.assertIn('inconsistent seasons', str(err.exception))
# Test 8D
ds = xr.Dataset({
'first': (['lat', 'lon', 'time'], np.ones([45, 90, 137])),
'second': (['lat', 'lon', 'time'], np.ones([45, 90, 137])),
'lat': np.linspace(-88, 88, 45),
'lon': np.linspace(-178, 178, 90),
'time': pd.date_range('2000-01-01', '2002-12-31', freq='8D')})
ds = adjust_temporal_attrs(ds)
with self.assertRaises(ValueError) as err:
long_term_average(ds)
self.assertIn('inconsistent seasons', str(err.exception))
def test_daily(self):
"""
Test creating a daily LTA dataset
"""
ds = xr.Dataset({
'first': (['lat', 'lon', 'time'], np.ones([45, 90, 730])),
'second': (['lat', 'lon', 'time'], np.ones([45, 90, 730])),
'lat': np.linspace(-88, 88, 45),
'lon': np.linspace(-178, 178, 90),
'time': pd.date_range('2001-01-01', '2002-12-31')})
ds = adjust_temporal_attrs(ds)
actual = long_term_average(ds)
# Test CF attributes
self.assertEqual(actual['first'].attrs['cell_methods'],
'time: mean over years')
self.assertEqual(actual.dims, {'time': 365,
'nv': 2,
'lat': 45,
'lon': 90})
self.assertEqual(actual.time.attrs['climatology'],
'climatology_bounds')
