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)
