def test_it(self):
state_size = 10
with ErtTestContext("update", self.config_file) as tc:
analysis = self.createAnalysisModule()
ert = tc.getErt()
obs = ert.getObservations()
local_obsdata = obs.getAllActiveLocalObsdata()
fs = ert.getEnkfFsManager().getCurrentFileSystem()
state = EnkfStateType.FORECAST
mask = BoolVector(initial_size=ert.getEnsembleSize(),
default_value=True)
meas_data = MeasData(mask)
obs_data = ObsData()
obs.getObservationAndMeasureData(fs, local_obsdata, state,
mask.createActiveList(),
meas_data, obs_data)
update(self.rng, mask, analysis, ert, meas_data, obs_data,
state_size)
mask[0] = False
mask[4] = False
meas_data = MeasData(mask)
obs_data = ObsData()
obs.getObservationAndMeasureData(fs, local_obsdata, state,
mask.createActiveList(),
meas_data, obs_data)
update(self.rng, mask, analysis, ert, meas_data, obs_data,
state_size)
def test_it(self):
state_size = 10
with ErtTestContext("update" , self.config_file) as tc:
analysis = self.createAnalysisModule()
ert = tc.getErt()
obs = ert.getObservations()
local_obsdata = obs.createLocalObsdata("OBS")
fs = ert.getEnkfFsManager().getCurrentFileSystem()
state = EnkfStateType.FORECAST
mask = BoolVector( initial_size = ert.getEnsembleSize() , default_value = True)
meas_data = MeasData(mask)
obs_data = ObsData()
obs.getObservationAndMeasureData( fs , local_obsdata , state , mask.createActiveList() , meas_data , obs_data )
update( self.rng , mask , analysis , ert , meas_data , obs_data , state_size)
mask[0] = False
mask[4] = False
meas_data = MeasData(mask)
obs_data = ObsData()
obs.getObservationAndMeasureData( fs , local_obsdata , state , mask.createActiveList() , meas_data , obs_data )
update( self.rng , mask , analysis , ert , meas_data , obs_data , state_size)
def createActiveList(self, fs):
state_map = fs.getStateMap()
ens_mask = BoolVector(False, self.ert().getEnsembleSize())
state_map.selectMatching(ens_mask, RealizationStateEnum.STATE_HAS_DATA)
active_list = BoolVector.createActiveList(ens_mask)
return active_list
def createActiveList(ert, fs):
state_map = fs.getStateMap()
ens_mask = BoolVector(False, ert.getEnsembleSize())
state_map.selectMatching(ens_mask, RealizationStateEnum.STATE_HAS_DATA)
active_list = BoolVector.createActiveList(ens_mask)
return [iens for iens in active_list]
def createActiveList(ert, fs):
state_map = fs.getStateMap()
ens_mask = BoolVector(False, ert.getEnsembleSize())
state_map.selectMatching(
ens_mask, RealizationStateEnum.STATE_INITIALIZED
| RealizationStateEnum.STATE_HAS_DATA)
active_list = BoolVector.createActiveList(ens_mask)
return [iens for iens in active_list]
def realizationList(self, state_value):
"""
Will create a list of all realisations with state equal to state_value.
@type state_value: RealizationStateEnum
@rtype: ert.util.IntVector
"""
mask = BoolVector(False, len(self))
self.selectMatching(mask, state_value)
return BoolVector.createActiveList(mask)
def realizationList(self , state_value):
"""
Will create a list of all realisations with state equal to state_value.
@type state_value: RealizationStateEnum
@rtype: ert.util.IntVector
"""
mask = BoolVector(False, len(self))
self.selectMatching(mask, state_value)
return BoolVector.createActiveList(mask)
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 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 = BoolVector.createActiveList(ens_mask)
if len(active_list) > 0:
state = EnkfStateType.FORECAST
meas_data = MeasData(active_list)
obs_data = ObsData()
self.ert().getObservations().getObservationAndMeasureData(fs, local_obsdata, state, active_list, meas_data, obs_data)
meas_data.deactivateZeroStdSamples(obs_data)
active_size = len(obs_data)
if active_size > 0:
S = meas_data.createS(active_size)
D_obs = obs_data.createDobs(active_size)
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
