def test_create(self):
ens_size = 10
ens_mask = BoolVector( default_value = True , initial_size = ens_size )
data = MeasData( ens_mask )
self.assertEqual( len(data) , 0)
self.assertTrue( isinstance( data , MeasData ))
block1 = data.addBlock( "OBS1" , 10 , 5 )
block2 = data.addBlock( "OBS2" , 27 , 10 )
with self.assertRaises(TypeError):
data[1.782]
with self.assertRaises(KeyError):
data["NO-this-does-not-exist"]
with self.assertRaises(IndexError):
data[2]
last0 = data[-1]
last1 = data[1]
self.assertEqual( last0 , last1 )
self.assertTrue( "OBS1-10" in data )
self.assertTrue( "OBS2-27" in data )
self.assertEqual( len(data) , 2)
self.assertTrue( isinstance( block1 , MeasBlock ))
self.assertTrue( isinstance( block2 , MeasBlock ))
self.assertEqual( block1.getObsSize() , 5 )
self.assertEqual( block2.getObsSize() , 10 )
l = []
for b in data:
l.append(b)
self.assertEqual(len(l) , 2)
self.assertEqual(l[0] , block1)
self.assertEqual(l[1] , block2)
with self.assertRaises(ValueError):
S = data.createS()
for iens in range(ens_size):
block1[0,iens] = 5
block2[0,iens] = 10
block2[1,iens] = 15
self.assertEqual( 3 , data.activeObsSize() )
S = data.createS()
self.assertEqual( S.dims() , (3 , ens_size) )
for iens in range(ens_size):
self.assertEqual( S[0,iens] , 5 )
self.assertEqual( S[1,iens] , 10 )
self.assertEqual( S[2,iens] , 15 )
def test_create(self):
ens_size = 10
ens_mask = BoolVector(default_value=True, initial_size=ens_size)
data = MeasData(ens_mask)
self.assertEqual(len(data), 0)
self.assertTrue(isinstance(data, MeasData))
block1 = data.addBlock("OBS1", 10, 5)
block2 = data.addBlock("OBS2", 27, 10)
with self.assertRaises(TypeError):
data[1.782]
with self.assertRaises(KeyError):
data["NO-this-does-not-exist"]
with self.assertRaises(IndexError):
data[2]
last0 = data[-1]
last1 = data[1]
self.assertEqual(last0, last1)
self.assertTrue("OBS1-10" in data)
self.assertTrue("OBS2-27" in data)
self.assertEqual(len(data), 2)
self.assertTrue(isinstance(block1, MeasBlock))
self.assertTrue(isinstance(block2, MeasBlock))
self.assertEqual(block1.getObsSize(), 5)
self.assertEqual(block2.getObsSize(), 10)
l = []
for b in data:
l.append(b)
self.assertEqual(len(l), 2)
self.assertEqual(l[0], block1)
self.assertEqual(l[1], block2)
with self.assertRaises(ValueError):
S = data.createS()
for iens in range(ens_size):
block1[0, iens] = 5
block2[0, iens] = 10
block2[1, iens] = 15
self.assertEqual(3, data.activeObsSize())
S = data.createS()
self.assertEqual(S.dims(), (3, ens_size))
for iens in range(ens_size):
self.assertEqual(S[0, iens], 5)
self.assertEqual(S[1, iens], 10)
self.assertEqual(S[2, iens], 15)
def init_matrices(ens, mask, obs, rng):
state_size = 2
report_step = 5
meas_data = MeasData(mask)
meas_block = meas_data.addBlock("OBS", report_step, len(obs))
A = Matrix(state_size, mask.countEqual(True))
active_iens = 0
for iens, params in enumerate(ens):
if mask[iens]:
state = forward_model(params)
meas_block[0, iens] = measure(state)
A[0, active_iens] = params[0]
A[1, active_iens] = params[1]
active_iens += 1
S = meas_data.createS()
obs_data = ObsData()
obs_block = obs_data.addBlock("OBS", 1)
for iobs, obs_value in enumerate(obs):
obs_block[iobs] = obs_value
R = obs_data.createR()
dObs = obs_data.createDObs()
E = obs_data.createE(rng, meas_data.getActiveEnsSize())
D = obs_data.createD(E, S)
obs_data.scale(S, E=E, D=D, R=R, D_obs=dObs)
return (A, S, E, D, R, dObs)
def init_matrices(ens , mask , obs , rng):
state_size = 2
report_step = 5
meas_data = MeasData( mask )
meas_block = meas_data.addBlock("OBS" , report_step , len(obs) )
A = Matrix( state_size , mask.countEqual( True ))
active_iens = 0
for iens,params in enumerate( ens ):
if mask[iens]:
state = forward_model( params )
meas_block[0,iens] = measure( state )
A[0 , active_iens] = params[0]
A[1 , active_iens] = params[1]
active_iens += 1
S = meas_data.createS()
obs_data = ObsData()
obs_block = obs_data.addBlock("OBS" , 1)
for iobs,obs_value in enumerate(obs):
obs_block[iobs] = obs_value
R = obs_data.createR()
dObs = obs_data.createDObs()
E = obs_data.createE( rng , meas_data.getActiveEnsSize() )
D = obs_data.createD(E , S)
obs_data.scale(S , E = E , D = D , R = R , D_obs = dObs)
return (A , S , E , D , R , dObs)
