def test_custom_region(self):
"""
Test execution with a generic WKT poygon
"""
dataset = 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': ([datetime(2001, x, 1) for x in range(1, 13)] +
[datetime(2002, x, 1) for x in range(1, 13)])
})
lta = xr.Dataset({
'first': (['lat', 'lon', 'time'], np.ones([45, 90, 12])),
'second': (['lat', 'lon', 'time'], np.ones([45, 90, 12])),
'lat':
np.linspace(-88, 88, 45),
'lon':
np.linspace(-178, 178, 90),
'time': [x for x in range(1, 13)]
})
lta = 2 * lta
expected_time = ([datetime(2001, x, 1) for x in range(3, 13)] +
[datetime(2002, x, 1) for x in range(1, 11)])
expected = pd.DataFrame(
data=(np.ones([20]) * -1),
columns=[
'ENSO Index over POLYGON '
'((-141.15234375 3.513421045640057, -129.0234375 6.839169626342807,'
' -102.65625 6.489983332670652, -90.703125 -3.688855143147035, -110'
'.21484375 -13.06877673435769, -141.6796875 -6.31529853833002, -141'
'.15234375 3.513421045640057))'
],
index=expected_time)
region = str(
'POLYGON((-141.15234375 3.513421045640057,-129.0234375'
' 6.839169626342807,-102.65625 6.4899833326706515,-90.703125 '
'-3.6888551431470353,-110.21484375 -13.068776734357693,'
'-141.6796875 -6.31529853833002,-141.15234375 '
'3.513421045640057))')
with create_tmp_file() as tmp_file:
lta.to_netcdf(tmp_file)
actual = index.enso(dataset,
'first',
tmp_file,
region='custom',
custom_region=region)
self.assertTrue(expected.equals(actual))
# Test a situation where the user forgets to provide the custom region
with self.assertRaises(ValueError) as err:
index.enso(dataset, 'first', 'dummy/file.nc', region='custom')
self.assertIn('No region', str(err.exception))
def test_antimeridian(self):
"""
Test execution with N4 region that crosses the antimeridian
"""
dataset = 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': ([datetime(2001, x, 1) for x in range(1, 13)] +
[datetime(2002, x, 1) for x in range(1, 13)])
})
lta = xr.Dataset({
'first': (['lat', 'lon', 'time'], np.ones([45, 90, 12])),
'second': (['lat', 'lon', 'time'], np.ones([45, 90, 12])),
'lat':
np.linspace(-88, 88, 45),
'lon':
np.linspace(-178, 178, 90),
'time': [x for x in range(1, 13)]
})
lta = 2 * lta
expected_time = ([datetime(2001, x, 1) for x in range(3, 13)] +
[datetime(2002, x, 1) for x in range(1, 11)])
expected = pd.DataFrame(data=(np.ones([20]) * -1),
columns=['ENSO N4 Index'],
index=expected_time)
with create_tmp_file() as tmp_file:
lta.to_netcdf(tmp_file)
actual = index.enso(dataset, 'first', tmp_file, region='N4')
self.assertTrue(expected.equals(actual))
def test_antimeridian(self):
"""
Test execution with N4 region that crosses the antimeridian
"""
dataset = 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': ([datetime(2001, x, 1) for x in range(1, 13)]
+ [datetime(2002, x, 1) for x in range(1, 13)])})
lta = xr.Dataset({
'first': (['lat', 'lon', 'time'], np.ones([45, 90, 12])),
'second': (['lat', 'lon', 'time'], np.ones([45, 90, 12])),
'lat': np.linspace(-88, 88, 45),
'lon': np.linspace(-178, 178, 90),
'time': [x for x in range(1, 13)]})
lta = 2 * lta
expected_time = ([datetime(2001, x, 1) for x in range(3, 13)]
+ [datetime(2002, x, 1) for x in range(1, 11)])
expected = pd.DataFrame(data=(np.ones([20]) * -1),
columns=['ENSO N4 Index'],
index=expected_time)
with create_tmp_file() as tmp_file:
lta.to_netcdf(tmp_file)
actual = index.enso(dataset, 'first', tmp_file, region='N4')
self.assertTrue(expected.equals(actual))
def test_custom_region(self):
"""
Test execution with a generic WKT poygon
"""
dataset = 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': ([datetime(2001, x, 1) for x in range(1, 13)]
+ [datetime(2002, x, 1) for x in range(1, 13)])})
lta = xr.Dataset({
'first': (['lat', 'lon', 'time'], np.ones([45, 90, 12])),
'second': (['lat', 'lon', 'time'], np.ones([45, 90, 12])),
'lat': np.linspace(-88, 88, 45),
'lon': np.linspace(-178, 178, 90),
'time': [x for x in range(1, 13)]})
lta = 2 * lta
expected_time = ([datetime(2001, x, 1) for x in range(3, 13)]
+ [datetime(2002, x, 1) for x in range(1, 11)])
expected = pd.DataFrame(data=(np.ones([20]) * -1),
columns=['ENSO Index over POLYGON '
'((-141.15234375 3.513421045640057, -129.0234375 6.839169626342807,'
' -102.65625 6.489983332670652, -90.703125 -3.688855143147035, -110'
'.21484375 -13.06877673435769, -141.6796875 -6.31529853833002, -141'
'.15234375 3.513421045640057))'],
index=expected_time)
region = str('POLYGON((-141.15234375 3.513421045640057,-129.0234375'
' 6.839169626342807,-102.65625 6.4899833326706515,-90.703125 '
'-3.6888551431470353,-110.21484375 -13.068776734357693,'
'-141.6796875 -6.31529853833002,-141.15234375 '
'3.513421045640057))')
with create_tmp_file() as tmp_file:
lta.to_netcdf(tmp_file)
actual = index.enso(dataset, 'first', tmp_file, region='custom',
custom_region=region)
self.assertTrue(expected.equals(actual))
# Test a situation where the user forgets to provide the custom region
with self.assertRaises(ValueError) as err:
index.enso(dataset, 'first', 'dummy/file.nc', region='custom')
self.assertIn('No region', str(err.exception))