def test_ref_val(self):
"""checks that we pick the correct reference value for all lon points."""
x = q.DiurnalLocalTimeStatistics(self.test_data, self.time_axis,
self.timestep, self.lons)
lsf = q.LongitudeSamplingFunction(24 * u.hour / self.timestep,
13 * u.hour)
i_lons = lsf.get_index(self.lons) + 4
result = np.empty((len(i_lons), ))
for i in range(len(i_lons)):
result[i] = self.test_data[i, i_lons[i]]
self.assertTrue(np.all(result == x.ref_val()))
# now switch test data so that there's more land points than time points
# and the axes are reversed
self.test_data = np.arange(100 * 16).reshape(16, 100)
self.time_axis = 0
self.lons = np.arange(100) * 2 * u.deg - 135 * u.deg
x = q.DiurnalLocalTimeStatistics(self.test_data, self.time_axis,
self.timestep, self.lons)
lsf = q.LongitudeSamplingFunction(24 * u.hour / self.timestep,
13 * u.hour)
i_lons = lsf.get_index(self.lons) + 4
result = np.empty((len(i_lons), ))
for i in range(len(i_lons)):
result[i] = self.test_data[i_lons[i], i]
self.assertTrue(np.all(result == x.ref_val()))
def test_noon(self):
samp_fn = q.LongitudeSamplingFunction(4., 12 * u.hour)
lons = np.arange(-180, 180, 30) * u.deg
test_ind = samp_fn.get_index(lons)
delta_hours = (c.Angle(180 * u.deg - lons).wrap_at(360 * u.deg) /
(15 * (u.deg / u.hour)))
ind = np.trunc(
(delta_hours / (6 * u.hour)).to(u.dimensionless_unscaled))
self.assertTrue(np.all(test_ind == ind.astype(int)))
def test_preceeding_day(self):
"""tests to ensure the correct data is returned"""
x = q.DiurnalLocalTimeStatistics(self.test_data, self.time_axis,
self.timestep, self.lons)
lsf = q.LongitudeSamplingFunction(24 * u.hour / self.timestep,
13 * u.hour)
i_lons = lsf.get_index(self.lons)
result = np.empty((len(i_lons), 4))
for i in range(len(i_lons)):
result[i, :] = self.test_data[i, i_lons[i] + 1:i_lons[i] + 5]
self.assertTrue(np.all(result == x.get_preceeding_day()))
def test_mask(self):
"""test initialization of mask"""
x = q.DiurnalLocalTimeStatistics(self.test_data, self.time_axis,
self.timestep, self.lons)
lsf = q.LongitudeSamplingFunction(24 * u.hour / self.timestep,
13 * u.hour)
i_lons = lsf.get_index(self.lons)
afternoon = i_lons[0]
self.assertTrue(afternoon == 3)
mask_test = [
not ((i > afternoon) and (i <= afternoon + 4)) for i in range(8)
]
self.assertTrue(np.all(x.mask[0, :] == mask_test))
def test_index_units(self):
samp_fn = q.LongitudeSamplingFunction(4, 12 * u.hour)
lons = np.arange(-180, 180, 30) * u.deg
test_ind = samp_fn.get_index(lons)
self.assertEqual(test_ind.unit, u.dimensionless_unscaled)