def test_initX_enkf_linalg_lowrank_EE(self):
"""Test AnalysisModule.initX with EE=True and GE=False"""
mod = AnalysisModule(self.rng, name="STD_ENKF")
A, S, R, dObs, E, D = self._n_identity_mcs()
mod.setVar('USE_EE', True)
self.assertTrue(mod.getBool('USE_EE'))
self.assertFalse(mod.getBool('USE_GE'))
elt_a, elt_b = 1.33, -0.167
vals = (elt_a, elt_b, elt_b, elt_b, elt_a, elt_b, elt_b, elt_b, elt_a)
expected = self.construct_matrix(3, vals)
X = mod.initX(A, S, R, dObs, E, D)
self._matrix_close(X, expected)
def test_initX_enkf_linalg_lowrank_EE(self):
"""Test AnalysisModule.initX with EE=True and GE=False"""
mod = AnalysisModule( self.rng , name = "STD_ENKF" )
A, S, R, dObs, E, D = self._n_identity_mcs()
mod.setVar('USE_EE', True)
self.assertTrue(mod.getBool('USE_EE'))
self.assertFalse(mod.getBool('USE_GE'))
elt_a, elt_b = 1.33, -0.167
vals = (elt_a, elt_b, elt_b,
elt_b, elt_a, elt_b,
elt_b, elt_b, elt_a)
expected = self.construct_matrix(3, vals)
X = mod.initX(A, S, R, dObs, E, D)
self._matrix_close(X, expected)
def test_initX_subspace_inversion_algorithm(self):
"""Test AnalysisModule.initX with EE=True and GE=True, the subspace inversion algorithm"""
mod = AnalysisModule(self.rng, name="STD_ENKF")
A, S, R, dObs, E, D = self._n_identity_mcs()
mod.setVar('USE_EE', True)
mod.setVar('USE_GE', True)
self.assertTrue(mod.getBool('USE_EE'))
self.assertTrue(mod.getBool('USE_GE'))
vals = (1.39, -0.111, -0.278, -0.111, 1.39, -0.278, -0.278, -0.278,
1.56)
expected = self.construct_matrix(3, vals)
X = mod.initX(A, S, R, dObs, E, D)
self._matrix_close(X, expected)
def test_initX_subspace_inversion_algorithm(self):
"""Test AnalysisModule.initX with EE=True and GE=True, the subspace inversion algorithm"""
mod = AnalysisModule( self.rng , name = "STD_ENKF" )
A, S, R, dObs, E, D = self._n_identity_mcs()
mod.setVar('USE_EE', True)
mod.setVar('USE_GE', True)
self.assertTrue(mod.getBool('USE_EE'))
self.assertTrue(mod.getBool('USE_GE'))
vals = ( 1.39, -0.111, -0.278,
-0.111, 1.39, -0.278,
-0.278, -0.278, 1.56 )
expected = self.construct_matrix(3, vals)
X = mod.initX(A, S, R, dObs, E, D)
self._matrix_close(X, expected)