class StdEnKFTest(ResTest):
def setUp(self):
self.rng = RandomNumberGenerator(RngAlgTypeEnum.MZRAN, RngInitModeEnum.INIT_DEFAULT)
self.module = AnalysisModule(name = "STD_ENKF" )
def toggleKey(self, key):
self.assertTrue( self.module.hasVar( key ))
# check it is true
self.assertTrue( self.module.setVar( key , True ) )
self.assertTrue( self.module.getBool(key) )
# set it to false
self.assertTrue( self.module.setVar( key , False ) )
self.assertFalse( self.module.getBool(key) )
def test_EE_option(self):
self.toggleKey( 'USE_EE' )
def test_GE_option(self):
self.toggleKey( 'USE_GE' )
def test_scaledata_option(self):
self.toggleKey( 'ANALYSIS_SCALE_DATA' )
def setUp(self):
self.rng = RandomNumberGenerator(RngAlgTypeEnum.MZRAN,
RngInitModeEnum.INIT_DEFAULT)
if sys.platform.lower() == 'darwin':
self.libname = res.res_lib_path + "/std_enkf_debug.dylib"
else:
self.libname = res.res_lib_path + "/std_enkf_debug.so"
self.module = AnalysisModule(lib_name=self.libname)
def setUp(self):
self.rng = RandomNumberGenerator(RngAlgTypeEnum.MZRAN,
RngInitModeEnum.INIT_DEFAULT)
if sys.platform.lower() == 'darwin':
lib_name = "std_enkf_debug.dylib"
else:
lib_name = "std_enkf_debug.so"
self.libname = find_file(self.SOURCE_ROOT, lib_name)
if self.libname:
self.module = AnalysisModule(lib_name=self.libname)
else:
pytest.skip('Debug library not found')
def test_initX_enkf_linalg_lowrankCinv(self):
"""Test AnalysisModule.initX with EE=False and GE=False"""
mod = AnalysisModule(name="STD_ENKF")
A, S, R, dObs, E, D = self._n_identity_mcs()
self.assertFalse(mod.getBool("USE_EE"))
self.assertFalse(mod.getBool("USE_GE"))
elt_a, elt_b = 1.222, -0.111
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.rng)
self._matrix_close(X, expected)
class StdEnKFDebugTest(ResTest):
def setUp(self):
self.rng = RandomNumberGenerator(RngAlgTypeEnum.MZRAN,
RngInitModeEnum.INIT_DEFAULT)
if sys.platform.lower() == 'darwin':
self.libname = res.res_lib_path + "/std_enkf_debug.dylib"
else:
self.libname = res.res_lib_path + "/std_enkf_debug.so"
self.module = AnalysisModule(lib_name=self.libname)
def toggleKey(self, key):
self.assertTrue(self.module.hasVar(key))
# check it is true
self.assertTrue(self.module.setVar(key, True))
self.assertTrue(self.module.getBool(key))
# set it to false
self.assertTrue(self.module.setVar(key, False))
self.assertFalse(self.module.getBool(key))
def test_EE_option(self):
self.toggleKey('USE_EE')
def test_scaledata_option(self):
self.toggleKey('ANALYSIS_SCALE_DATA')
def test_prefix(self):
self.assertTrue(self.module.hasVar("PREFIX"))
self.assertTrue(self.module.setVar("PREFIX", "Path"))
class StdEnKFDebugTest(ResTest):
def setUp(self):
self.rng = RandomNumberGenerator(RngAlgTypeEnum.MZRAN,
RngInitModeEnum.INIT_DEFAULT)
if sys.platform.lower() == "darwin":
lib_name = "std_enkf_debug.dylib"
else:
lib_name = "std_enkf_debug.so"
self.libname = find_file(self.SOURCE_ROOT, lib_name)
if self.libname:
self.module = AnalysisModule(lib_name=self.libname)
else:
pytest.skip("Debug library not found")
def toggleKey(self, key):
self.assertTrue(self.module.hasVar(key))
# check it is true
self.assertTrue(self.module.setVar(key, True))
self.assertTrue(self.module.getBool(key))
# set it to false
self.assertTrue(self.module.setVar(key, False))
self.assertFalse(self.module.getBool(key))
def test_EE_option(self):
self.toggleKey("USE_EE")
def test_scaledata_option(self):
self.toggleKey("ANALYSIS_SCALE_DATA")
def test_prefix(self):
self.assertTrue(self.module.hasVar("PREFIX"))
self.assertTrue(self.module.setVar("PREFIX", "Path"))
def test_set_get_var(self):
mod = AnalysisModule(name="STD_ENKF")
with self.assertRaises(KeyError):
mod.setVar("NO-NOT_THIS_KEY", 100)
with self.assertRaises(KeyError):
mod.getInt("NO-NOT_THIS_KEY")
def test_set_get_var(self):
mod = AnalysisModule(100, AnalysisModeEnum.ENSEMBLE_SMOOTHER)
with self.assertRaises(KeyError):
mod.setVar("NO-NOT_THIS_KEY", 100)
with self.assertRaises(KeyError):
mod.getInt("NO-NOT_THIS_KEY")
def test_analysis_module(self):
am = AnalysisModule(100, AnalysisModeEnum.ITERATED_ENSEMBLE_SMOOTHER)
self.assertTrue(am.setVar("ITER", "1"))
self.assertEqual(am.name(), "IES_ENKF")
self.assertTrue(
am.checkOption(AnalysisModuleOptionsEnum.ANALYSIS_ITERABLE))
self.assertTrue(am.hasVar("ITER"))
self.assertIsInstance(am.getDouble("ENKF_TRUNCATION"), float)
self.assertIsInstance(am.getInt("ITER"), int)
def test_set_get_var():
mod = AnalysisModule(100, 1)
with pytest.raises(KeyError):
mod.setVar("NO-NOT_THIS_KEY", 100)
with pytest.raises(KeyError):
mod.getInt("NO-NOT_THIS_KEY")
def test_analysis_module():
am = AnalysisModule(100, 2)
assert am.setVar("ITER", "1")
assert am.name() == "IES_ENKF"
assert am.hasVar("ITER")
assert isinstance(am.getDouble("ENKF_TRUNCATION"), float)
assert isinstance(am.getInt("ITER"), int)
def test_initX_enkf_linalg_lowrank_EE(self):
"""Test AnalysisModule.initX with EE=True and GE=False"""
mod = AnalysisModule(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.rng)
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(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"))
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.rng)
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(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.rng)
self._matrix_close(X, expected)
def createAnalysisModule(self):
rng = RandomNumberGenerator(RngAlgTypeEnum.MZRAN,
RngInitModeEnum.INIT_DEFAULT)
return AnalysisModule(lib_name=self.libname)
def setUp(self):
self.rng = RandomNumberGenerator(RngAlgTypeEnum.MZRAN,
RngInitModeEnum.INIT_DEFAULT)
self.libname = res.res_lib_path + "/std_enkf_debug.so"
self.module = AnalysisModule(lib_name=self.libname)
def setUp(self):
self.rng = RandomNumberGenerator(RngAlgTypeEnum.MZRAN, RngInitModeEnum.INIT_DEFAULT)
self.module = AnalysisModule(name = "STD_ENKF" )
def test_create_internal(self):
with self.assertRaises(KeyError):
mod = AnalysisModule(name="STD_ENKFXXX")
mod = AnalysisModule(name="STD_ENKF")
def createAnalysisModule(self):
return AnalysisModule(lib_name=self.libname)
