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 calculatePrincipalComponent(self,
fs,
local_obsdata,
truncation_or_ncomp=3):
pc = Matrix(1, 1)
pc_obs = Matrix(1, 1)
singular_values = DoubleVector()
state_map = fs.getStateMap()
ens_mask = BoolVector(False, self.ert().getEnsembleSize())
state_map.selectMatching(ens_mask, RealizationStateEnum.STATE_HAS_DATA)
active_list = ens_mask.createActiveList()
if len(ens_mask) > 0:
meas_data = MeasData(ens_mask)
obs_data = ObsData()
self.ert().getObservations().getObservationAndMeasureData(
fs, local_obsdata, active_list, meas_data, obs_data)
meas_data.deactivateZeroStdSamples(obs_data)
active_size = len(obs_data)
if active_size > 0:
S = meas_data.createS()
D_obs = obs_data.createDObs()
truncation, ncomp = self.truncationOrNumberOfComponents(
truncation_or_ncomp)
obs_data.scale(S, D_obs=D_obs)
EnkfLinalg.calculatePrincipalComponents(
S, D_obs, truncation, ncomp, pc, pc_obs, singular_values)
if self.__prior_singular_values is None:
self.__prior_singular_values = singular_values
else:
for row in range(pc.rows()):
factor = singular_values[
row] / self.__prior_singular_values[row]
pc.scaleRow(row, factor)
pc_obs.scaleRow(row, factor)
return PcaPlotData(local_obsdata.getName(), pc, pc_obs,
singular_values)
return None
def test_create(self):
obs_data = ObsData()
obs_size = 10
block = obs_data.addBlock("OBS" , obs_size)
self.assertTrue( isinstance( block , ObsBlock ))
block[0] = (100,10)
block[1] = (120,12)
D = obs_data.createDObs()
self.assertTrue( isinstance(D , Matrix ))
self.assertEqual( D.dims() , (2,2))
self.assertEqual( D[0,0] , 100 )
self.assertEqual( D[1,0] , 120 )
self.assertEqual( D[0,1] , 10 )
self.assertEqual( D[1,1] , 12 )
obs_data.scaleMatrix( D )
self.assertEqual( D[0,0] , 10 )
self.assertEqual( D[1,0] , 10 )
self.assertEqual( D[0,1] , 1 )
self.assertEqual( D[1,1] , 1 )
R = obs_data.createR()
self.assertEqual( (2,2) , R.dims() )
with self.assertRaises(IndexError):
obs_data[10]
v,s = obs_data[0]
self.assertEqual( v , 100 )
self.assertEqual( s , 10 )
v,s = obs_data[1]
self.assertEqual( v , 120 )
self.assertEqual( s , 12 )