def test_lcth_algorithm_nan_neighbor(self):
lcthalgo = LowCloudHeightAlgorithm(**self.testinput)
elev = np.empty((3, 3))
elev[:] = np.nan
lcthalgo.elev = elev
ret, mask = lcthalgo.run()
self.assertEqual(lcthalgo.ir108.shape, (3, 3))
self.assertEqual(ret.shape, (3, 3))
self.assertEqual(lcthalgo.shape, (3, 3))
self.assertEqual(np.ma.is_mask(lcthalgo.mask), True)
self.assertEqual(np.isnan(np.nanmax(lcthalgo.dz)), True)
self.assertEqual(np.isnan(np.nanmax(lcthalgo.cth)), True)
def lcth_ok():
alg = LowCloudHeightAlgorithm()
alg.elev = np.zeros((5, 5))
alg.ir108 = np.arange(260, 265, 0.2).reshape(5, 5)
alg.ccl = np.ones((5, 5))
alg.clusters = np.array([[0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 1, 1, 0, 0],
[0, 1, 1, 1, 0], [1, 1, 0, 0, 0]],
dtype="i4")
alg.dz = np.zeros((5, 5))
alg.cth = np.zeros((5, 5))
alg.nlapse = 0
return alg
