def test_load_save(self):
rng = RandomNumberGenerator()
with self.assertRaises(IOError):
rng.loadState("does/not/exist")
with TestAreaContext("rng_state") as t:
rng.saveState("rng.txt")
val1 = rng.getInt()
val2 = rng.getInt()
rng.loadState("rng.txt")
self.assertEqual(rng.getInt(), val1)
self.assertEqual(rng.getInt(), val2)
def test_rng_state(self):
rng = RandomNumberGenerator()
with self.assertRaises(ValueError):
rng.setState("12")
rng.setState("0123456789ABCDEF")
val1 = rng.getInt()
val2 = rng.getInt()
self.assertFalse(val1 == val2)
rng.setState("0123456789ABCDEF")
self.assertEqual(rng.getInt(), val1)
self.assertEqual(rng.getInt(), val2)
def test_analysis_module(self):
rng = RandomNumberGenerator()
module = self.createAnalysisModule()
ens_size = 12
obs_size = 1
state_size = 2
true_params = [1.25, 0.75]
true_state = forward_model(true_params)
obs = [(measure(true_state), 0.75)]
A = Matrix(state_size, ens_size)
ens = []
for iens in range(ens_size):
param = [random.gauss(1.00, 1.00), random.gauss(1.00, 1.00)]
ens.append(param)
mask = BoolVector(default_value=True, initial_size=ens_size)
mask[2] = False
(A, S, E, D, R, dObs) = init_matrices(ens, mask, obs, rng)
module.initUpdate(mask, S, R, dObs, E, D, rng)
module.updateA(A, S, R, dObs, E, D, rng)
mask[10] = False
mask[5] = False
(A, S, E, D, R, dObs) = init_matrices(ens, mask, obs, rng)
self.assertEqual(S.dims(), (obs_size, mask.countEqual(True)))
self.assertEqual(E.dims(), (obs_size, mask.countEqual(True)))
self.assertEqual(D.dims(), (obs_size, mask.countEqual(True)))
module.initUpdate(mask, S, R, dObs, E, D, rng)
module.updateA(A, S, R, dObs, E, D, rng)
def setUp(self):
if sys.platform.lower() == 'darwin':
self.libname = os.path.join(res.res_lib_path, "rml_enkf.dylib")
else:
self.libname = os.path.join(res.res_lib_path, "rml_enkf.so")
self.config_file = self.createTestPath("Equinor/config/obs_testing2/config")
self.rng = RandomNumberGenerator(RngAlgTypeEnum.MZRAN, RngInitModeEnum.INIT_DEFAULT)
def test_load_save(self):
rng = RandomNumberGenerator()
with self.assertRaises(IOError):
rng.loadState("does/not/exist")
with TestAreaContext("rng_state") as t:
rng.saveState( "rng.txt" )
t.sync()
val1 = rng.getInt()
val2 = rng.getInt()
rng.loadState( "rng.txt" )
self.assertEqual( rng.getInt() , val1 )
self.assertEqual( rng.getInt() , val2 )
def test_rng_state(self):
rng = RandomNumberGenerator()
with self.assertRaises(ValueError):
rng.setState("12")
rng.setState("0123456789ABCDEF")
val1 = rng.getInt()
val2 = rng.getInt()
self.assertFalse( val1 == val2 )
rng.setState("0123456789ABCDEF")
self.assertEqual( rng.getInt() , val1)
self.assertEqual( rng.getInt() , val2)
def test_matrix_copy_column(self):
m = Matrix(10, 2)
rng = RandomNumberGenerator(RngAlgTypeEnum.MZRAN, RngInitModeEnum.INIT_DEFAULT)
m.randomInit(rng)
with self.assertRaises(ValueError):
m.copyColumn(0, 2)
with self.assertRaises(ValueError):
m.copyColumn(2, 0)
with self.assertRaises(ValueError):
m.copyColumn(-2, 0)
m.copyColumn(1, 0)
for i in range(m.rows()):
self.assertEqual(m[i, 0], m[i, 1])
def test_sub_copy(self):
m1 = Matrix(3, 3)
rng = RandomNumberGenerator(RngAlgTypeEnum.MZRAN, RngInitModeEnum.INIT_DEFAULT)
m1.randomInit(rng)
with self.assertRaises(ValueError):
m2 = m1.subCopy(0, 0, 4, 2)
with self.assertRaises(ValueError):
m2 = m1.subCopy(0, 0, 2, 4)
with self.assertRaises(ValueError):
m2 = m1.subCopy(4, 0, 1, 1)
with self.assertRaises(ValueError):
m2 = m1.subCopy(0, 2, 1, 2)
m2 = m1.subCopy(0, 0, 2, 2)
for i in range(2):
for j in range(2):
self.assertEqual(m1[i, j], m2[i, j])
def createAnalysisModule(self):
rng = RandomNumberGenerator(RngAlgTypeEnum.MZRAN,
RngInitModeEnum.INIT_DEFAULT)
return AnalysisModule(lib_name=self.libname)
def test_matrix_random_init(self):
m = Matrix(10, 10)
rng = RandomNumberGenerator(RngAlgTypeEnum.MZRAN,
RngInitModeEnum.INIT_DEFAULT)
m.randomInit(rng)
def test_rng_default(self):
rng = RandomNumberGenerator()
self.assertIsInstance(rng.getDouble(), float)
def test_rng_default(self):
rng = RandomNumberGenerator()
self.assertIsInstance(rng.getDouble(), float)