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 test_create(self):
obs_data = ObsData()
obs_size = 10
block = obs_data.addBlock("OBS", obs_size)
self.assertTrue(isinstance(block, ObsBlock))
block[0] = (10, 10)
block[1] = (12, 12)
D = obs_data.createDObs()
self.assertTrue(isinstance(D, Matrix))
self.assertEqual(D.dims(), (2, 1))
self.assertEqual(D[0, 0], 10)
self.assertEqual(D[1, 0], 12)
obs_data.scaleMatrix(D)
self.assertEqual(D[0, 0], 1)
self.assertEqual(D[1, 0], 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, 10)
self.assertEqual(s, 10)
v, s = obs_data[1]
self.assertEqual(v, 12)
self.assertEqual(s, 12)
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 test_create(self):
obs_data = ObsData()
obs_size = 10
block = obs_data.addBlock("OBS" , obs_size)
self.assertTrue( isinstance( block , ObsBlock ))
block[0] = (10,10)
block[1] = (12,12)
D = obs_data.createDObs()
self.assertTrue( isinstance(D , Matrix ))
self.assertEqual( D.dims() , (2,1))
self.assertEqual( D[0,0] , 10 )
self.assertEqual( D[1,0] , 12 )
obs_data.scaleMatrix( D )
self.assertEqual( D[0,0] , 1 )
self.assertEqual( D[1,0] , 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 , 10 )
self.assertEqual( s , 10 )
v,s = obs_data[1]
self.assertEqual( v , 12 )
self.assertEqual( s , 12 )