def test_estimation_all_args(self):
ga_opts = {'maxiter': 3, 'pop_size': 10, 'trm_size': 5, 'lhs': True}
ps_opts = {'maxiter': 3}
session = Estimation(self.tmpdir, self.fmu_path, self.inp,
self.known, self.est, self.ideal,
lp_n=2, lp_len=3600, lp_frame=(0, 3600),
vp=(20000, 40000), ic_param={'Tstart': 'T'},
methods=('GA', 'PS'),
ga_opts=ga_opts, ps_opts=ps_opts,
seed=1, ftype='NRMSE')
estimates = session.estimate()
err, res = session.validate() # Standard validation period
err2, res2 = session.validate(vp=(25000, 28600))
self.assertIsNotNone(estimates)
self.assertGreater(len(estimates), 0)
self.assertIsNotNone(err)
self.assertIsNotNone(res)
self.assertIsNotNone(err2)
self.assertIsNotNone(res2)
self.assertGreater(len(res.index), 1)
self.assertGreater(len(res.columns), 0)
self.assertGreater(len(res2.index), 1)
self.assertGreater(len(res2.columns), 0)
self.assertEqual(session.lp[0][0], 0)
self.assertEqual(session.lp[0][1], 3600)
# Enabling next line triggers the Matplotlib error (issue #20)
# raw_input('Continue...')
self.assertLess(err['tot'], 1.7) # NRMSE
def test_estimation_basic_parallel(self):
"""Will use default methods ('MODESTGA', 'PS')"""
modestga_opts = {
"generations": 2,
"workers": 2,
"pop_size": 16,
"trm_size": 3
}
ps_opts = {"maxiter": 2}
session = Estimation(
self.tmpdir,
self.fmu_path,
self.inp,
self.known,
self.est,
self.ideal,
modestga_opts=modestga_opts,
ps_opts=ps_opts,
default_log=False,
)
estimates = session.estimate()
err, res = session.validate()
self.assertIsNotNone(estimates)
self.assertGreater(len(estimates), 0)
self.assertIsNotNone(err)
self.assertIsNotNone(res)
self.assertGreater(len(res.index), 1)
self.assertGreater(len(res.columns), 0)
def test_estimation_rmse(self):
modestga_opts = {"generations": 8}
ps_opts = {"maxiter": 16}
session = Estimation(
self.tmpdir,
self.fmu_path,
self.inp,
self.known,
self.est,
self.ideal,
lp_n=1,
lp_len=3600,
lp_frame=(0, 3600),
vp=(20000, 40000),
ic_param={"Tstart": "T"},
methods=("MODESTGA", "PS"),
modestga_opts=modestga_opts,
ps_opts=ps_opts,
ftype="RMSE",
default_log=False,
)
estimates = session.estimate()
err, res = session.validate()
self.assertIsNotNone(estimates)
self.assertGreater(len(estimates), 0)
self.assertIsNotNone(err)
self.assertIsNotNone(res)
self.assertGreater(len(res.index), 1)
self.assertGreater(len(res.columns), 0)
self.assertLess(err["tot"], 1.48)
def test_estimation_rmse(self):
ga_opts = {'maxiter': 3, 'pop_size': 8, 'trm_size': 3}
ps_opts = {'maxiter': 3}
session = Estimation(self.tmpdir,
self.fmu_path,
self.inp,
self.known,
self.est,
self.ideal,
lp_n=1,
lp_len=3600,
lp_frame=(0, 3600),
vp=(20000, 40000),
ic_param={'Tstart': 'T'},
methods=('GA', 'PS'),
ga_opts=ga_opts,
ps_opts=ps_opts,
seed=1,
ftype='RMSE')
estimates = session.estimate()
err, res = session.validate()
self.assertIsNotNone(estimates)
self.assertGreater(len(estimates), 0)
self.assertIsNotNone(err)
self.assertIsNotNone(res)
self.assertGreater(len(res.index), 1)
self.assertGreater(len(res.columns), 0)
self.assertLess(err['tot'], 1.48)
def test_estimation_basic(self):
"""Will use default methods ('MODESTGA', 'PS')"""
modestga_opts = {
'generations': 2,
'workers': 1,
'pop_size': 8,
'trm_size': 3
}
ps_opts = {'maxiter': 2}
session = Estimation(self.tmpdir,
self.fmu_path,
self.inp,
self.known,
self.est,
self.ideal,
modestga_opts=modestga_opts,
ps_opts=ps_opts,
default_log=False)
estimates = session.estimate()
err, res = session.validate()
self.assertIsNotNone(estimates)
self.assertGreater(len(estimates), 0)
self.assertIsNotNone(err)
self.assertIsNotNone(res)
self.assertGreater(len(res.index), 1)
self.assertGreater(len(res.columns), 0)
def test_estimation_rmse(self):
modestga_opts = {'generations': 8}
ps_opts = {'maxiter': 16}
session = Estimation(self.tmpdir,
self.fmu_path,
self.inp,
self.known,
self.est,
self.ideal,
lp_n=1,
lp_len=3600,
lp_frame=(0, 3600),
vp=(20000, 40000),
ic_param={'Tstart': 'T'},
methods=('MODESTGA', 'PS'),
modestga_opts=modestga_opts,
ps_opts=ps_opts,
ftype='RMSE',
default_log=False)
estimates = session.estimate()
err, res = session.validate()
self.assertIsNotNone(estimates)
self.assertGreater(len(estimates), 0)
self.assertIsNotNone(err)
self.assertIsNotNone(res)
self.assertGreater(len(res.index), 1)
self.assertGreater(len(res.columns), 0)
self.assertLess(err['tot'], 1.48)
def test_estimation_all_args(self):
modestga_opts = {
"generations": 2,
"workers": 2,
"pop_size": 16,
"trm_size": 3
}
ps_opts = {"maxiter": 3}
session = Estimation(
self.tmpdir,
self.fmu_path,
self.inp,
self.known,
self.est,
self.ideal,
lp_n=2,
lp_len=3600,
lp_frame=(0, 3600),
vp=(20000, 40000),
ic_param={"Tstart": "T"},
methods=("MODESTGA", "PS"),
modestga_opts=modestga_opts,
ps_opts=ps_opts,
ftype="NRMSE",
default_log=False,
)
estimates = session.estimate()
err, res = session.validate() # Standard validation period
err2, res2 = session.validate(vp=(25000, 28600))
self.assertIsNotNone(estimates)
self.assertGreater(len(estimates), 0)
self.assertIsNotNone(err)
self.assertIsNotNone(res)
self.assertIsNotNone(err2)
self.assertIsNotNone(res2)
self.assertGreater(len(res.index), 1)
self.assertGreater(len(res.columns), 0)
self.assertGreater(len(res2.index), 1)
self.assertGreater(len(res2.columns), 0)
self.assertEqual(session.lp[0][0], 0)
self.assertEqual(session.lp[0][1], 3600)
self.assertLess(err["tot"], 1.7) # NRMSE
def test_estimation_all_args(self):
modestga_opts = {
'generations': 2,
'workers': 2,
'pop_size': 16,
'trm_size': 3
}
ps_opts = {'maxiter': 3}
session = Estimation(self.tmpdir,
self.fmu_path,
self.inp,
self.known,
self.est,
self.ideal,
lp_n=2,
lp_len=3600,
lp_frame=(0, 3600),
vp=(20000, 40000),
ic_param={'Tstart': 'T'},
methods=('MODESTGA', 'PS'),
modestga_opts=modestga_opts,
ps_opts=ps_opts,
ftype='NRMSE',
default_log=False)
estimates = session.estimate()
err, res = session.validate() # Standard validation period
err2, res2 = session.validate(vp=(25000, 28600))
self.assertIsNotNone(estimates)
self.assertGreater(len(estimates), 0)
self.assertIsNotNone(err)
self.assertIsNotNone(res)
self.assertIsNotNone(err2)
self.assertIsNotNone(res2)
self.assertGreater(len(res.index), 1)
self.assertGreater(len(res.columns), 0)
self.assertGreater(len(res2.index), 1)
self.assertGreater(len(res2.columns), 0)
self.assertEqual(session.lp[0][0], 0)
self.assertEqual(session.lp[0][1], 3600)
self.assertLess(err['tot'], 1.7) # NRMSE
def test_estimation_basic(self):
ga_opts = {'maxiter': 3}
ps_opts = {'maxiter': 3}
session = Estimation(self.tmpdir, self.fmu_path, self.inp,
self.known, self.est, self.ideal,
ga_opts=ga_opts, ps_opts=ps_opts)
estimates = session.estimate()
err, res = session.validate()
self.assertIsNotNone(estimates)
self.assertGreater(len(estimates), 0)
self.assertIsNotNone(err)
self.assertIsNotNone(res)
self.assertGreater(len(res.index), 1)
self.assertGreater(len(res.columns), 0)
# MODEL IDENTIFICATION ==========================================
session = Estimation(workdir,
fmu_path,
inp,
known,
est,
ideal,
lp_n=2,
lp_len=50000,
lp_frame=(0, 50000),
vp=(0, 50000),
ic_param={'Tstart': 'T'},
methods=('GA', 'PS'),
ga_opts={
'maxiter': 5,
'tol': 0.001,
'lhs': True
},
ps_opts={
'maxiter': 500,
'tol': 1e-6
},
scipy_opts={},
ftype='RMSE',
seed=1,
default_log=True,
logfile='simple.log')
estimates = session.estimate()
err, res = session.validate()