def test_lcth_algorithm_real(self):
# Compute cloud mask
cloudfilter = CloudFilter(self.input['ir108'], **self.input)
cloudfilter.apply()
snowfilter = SnowFilter(cloudfilter.result, **self.input)
snowfilter.apply()
icefilter = IceCloudFilter(snowfilter.result, **self.input)
icefilter.apply()
cirrusfilter = CirrusCloudFilter(icefilter.result, **self.input)
cirrusfilter.apply()
waterfilter = WaterCloudFilter(cirrusfilter.result,
cloudmask=cloudfilter.mask,
**self.input)
ret, mask = waterfilter.apply()
self.ccl = cloudfilter.ccl
self.input['ccl'] = self.ccl
self.input['cloudmask'] = ret.mask
lcthalgo = LowCloudHeightAlgorithm(**self.input)
ret, mask = lcthalgo.run()
self.assertEqual(lcthalgo.ir108.shape, (141, 298))
self.assertEqual(ret.shape, (141, 298))
self.assertEqual(lcthalgo.shape, (141, 298))
self.assertEqual(np.ma.is_mask(lcthalgo.mask), True)
self.assertLessEqual(round(np.nanmax(lcthalgo.dz), 2), 1524.43)
def test_lcth_algorithm_artificial_next(self):
lcthalgo = LowCloudHeightAlgorithm(**self.testnextinput)
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.nanmax(lcthalgo.dz), 12.)
self.assertEqual(np.around(lcthalgo.cth[1, 1], 2), 444.23)
def test_lcth_algorithm_artificial_complement(self):
lcthalgo = LowCloudHeightAlgorithm(**self.testinput2)
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.nanmax(lcthalgo.dz), 1300.)
self.assertEqual(np.nanmax(np.around(lcthalgo.cth, 2)), 6168.06)
def test_lcth_algorithm_artificial(self):
lcthalgo = LowCloudHeightAlgorithm(**self.testinput)
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.nanmax(lcthalgo.dz), 800.)
self.assertEqual(np.nanmax(lcthalgo.cth), 800.)
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 test_lcth_algorithm_linreg_cluster(self):
"""Test single cloud cluster linear regression interpolation"""
# Get cloud parameters
from fogpy.filters import CloudFilter
cloudfilter = CloudFilter(self.ir108, **self.input)
ret, mask = cloudfilter.apply()
input = {'ir108': self.ir108,
'elev': self.elev,
'ccl': cloudfilter.ccl,
'cloudmask': cloudfilter.mask,
'interpolate': False,
'single': True}
# Run LCTH algorithm
lcthalgo = LowCloudHeightAlgorithm(**input)
ret, mask = lcthalgo.run()
# lcthalgo.plot_result()
self.assertEqual(ret.shape, (141, 298))
self.assertEqual(lcthalgo.shape, (141, 298))
self.assertEqual(np.ma.is_mask(lcthalgo.mask), True)
self.assertLessEqual(round(np.nanmax(lcthalgo.dz), 2), 1900)
