def test_scipy(self):
self.scipy = SCIPY(self.fmu_path,
self.inp,
self.known,
self.est,
self.ideal,
solver='L-BFGS-B')
self.estimates = self.scipy.estimate()
# Generate plots
self.scipy.plot_comparison(
os.path.join(self.tmpdir, 'scipy_comparison.png'))
self.scipy.plot_error_evo(
os.path.join(self.tmpdir, 'scipy_error_evo.png'))
self.scipy.plot_parameter_evo(
os.path.join(self.tmpdir, 'scipy_param_evo.png'))
# Make sure plots are created
self.assertTrue(
os.path.exists(os.path.join(self.tmpdir, 'scipy_comparison.png')))
self.assertTrue(
os.path.exists(os.path.join(self.tmpdir, 'scipy_error_evo.png')))
self.assertTrue(
os.path.exists(os.path.join(self.tmpdir, 'scipy_param_evo.png')))
# Make last error is lower than initial
errors = self.scipy.get_errors()
self.assertGreaterEqual(errors[0], errors[-1])
ideal = pd.read_csv(ideal_path).set_index('time')
# Load definition of estimated parameters (name, initial value, bounds)
with open(est_path) as f:
est = json.load(f)
# Load definition of known parameters (name, value)
with open(known_path) as f:
known = json.load(f)
# MODEL IDENTIFICATION ==========================================
# session = Estimation(workdir, fmu_path, inp, known, est, ideal,
# lp_n=3, lp_len=25000, lp_frame=(0, 25000),
# vp = (150000, 215940), ic_param={'Tstart': 'T'},
# ga_pop=20, ga_iter=20, ps_iter=30, ga_tol=0.001,
# ps_tol=0.0001, seed=1, ftype='RMSE', lhs=True)
# estimates = session.estimate()
# err, res = session.validate()
scipy = SCIPY(fmu_path, inp, known, est, ideal, ftype='RMSE')
par = scipy.estimate()
print(par)
res = scipy.res
res['ideal'] = ideal['T']
res.plot()
plt.show()
print('ERROR={}'.format(scipy.best_err))
class TestSCIPY(unittest.TestCase):
def setUp(self):
# Platform (win32, win64, linux32, linix64)
platform = get_sys_arch()
assert platform, 'Unsupported platform type!'
# Temp directory
self.tmpdir = tempfile.mkdtemp()
# Parent directory
parent = os.path.dirname(__file__)
# Resources
self.fmu_path = os.path.join(parent, 'resources', 'simple2R1C',
'Simple2R1C_{}.fmu'.format(platform))
inp_path = os.path.join(parent, 'resources', 'simple2R1C',
'inputs.csv')
ideal_path = os.path.join(parent, 'resources', 'simple2R1C',
'result.csv')
est_path = os.path.join(parent, 'resources', 'simple2R1C', 'est.json')
known_path = os.path.join(parent, 'resources', 'simple2R1C',
'known.json')
self.inp = pd.read_csv(inp_path).set_index('time')
self.ideal = pd.read_csv(ideal_path).set_index('time')
with open(est_path) as f:
self.est = json.load(f)
with open(known_path) as f:
self.known = json.load(f)
# PS settings
self.max_iter = 3
self.try_lim = 2
def tearDown(self):
shutil.rmtree(self.tmpdir)
def test_scipy(self):
self.scipy = SCIPY(self.fmu_path,
self.inp,
self.known,
self.est,
self.ideal,
solver='L-BFGS-B')
self.estimates = self.scipy.estimate()
# Generate plots
self.scipy.plot_comparison(
os.path.join(self.tmpdir, 'scipy_comparison.png'))
self.scipy.plot_error_evo(
os.path.join(self.tmpdir, 'scipy_error_evo.png'))
self.scipy.plot_parameter_evo(
os.path.join(self.tmpdir, 'scipy_param_evo.png'))
# Make sure plots are created
self.assertTrue(
os.path.exists(os.path.join(self.tmpdir, 'scipy_comparison.png')))
self.assertTrue(
os.path.exists(os.path.join(self.tmpdir, 'scipy_error_evo.png')))
self.assertTrue(
os.path.exists(os.path.join(self.tmpdir, 'scipy_param_evo.png')))
# Make last error is lower than initial
errors = self.scipy.get_errors()
self.assertGreaterEqual(errors[0], errors[-1])
class TestSCIPY(unittest.TestCase):
def setUp(self):
# Platform (win32, win64, linux32, linix64)
platform = get_sys_arch()
assert platform, "Unsupported platform type!"
# Temp directory
self.tmpdir = tempfile.mkdtemp()
# Parent directory
parent = os.path.dirname(__file__)
# Resources
self.fmu_path = os.path.join(
parent, "resources", "simple2R1C", "Simple2R1C_{}.fmu".format(platform)
)
inp_path = os.path.join(parent, "resources", "simple2R1C", "inputs.csv")
ideal_path = os.path.join(parent, "resources", "simple2R1C", "result.csv")
est_path = os.path.join(parent, "resources", "simple2R1C", "est.json")
known_path = os.path.join(parent, "resources", "simple2R1C", "known.json")
# Assert there is an FMU for this platform
assert os.path.exists(
self.fmu_path
), "FMU for this platform ({}) doesn't exist.\n".format(
platform
) + "No such file: {}".format(
self.fmu_path
)
self.inp = pd.read_csv(inp_path).set_index("time")
self.ideal = pd.read_csv(ideal_path).set_index("time")
with open(est_path) as f:
self.est = json.load(f)
with open(known_path) as f:
self.known = json.load(f)
# PS settings
self.max_iter = 3
self.try_lim = 2
def tearDown(self):
shutil.rmtree(self.tmpdir)
def test_scipy(self):
self.scipy = SCIPY(
self.fmu_path, self.inp, self.known, self.est, self.ideal, solver="L-BFGS-B"
)
self.estimates = self.scipy.estimate()
# Generate plots
self.scipy.plot_comparison(os.path.join(self.tmpdir, "scipy_comparison.png"))
self.scipy.plot_error_evo(os.path.join(self.tmpdir, "scipy_error_evo.png"))
self.scipy.plot_parameter_evo(os.path.join(self.tmpdir, "scipy_param_evo.png"))
# Make sure plots are created
self.assertTrue(
os.path.exists(os.path.join(self.tmpdir, "scipy_comparison.png"))
)
self.assertTrue(
os.path.exists(os.path.join(self.tmpdir, "scipy_error_evo.png"))
)
self.assertTrue(
os.path.exists(os.path.join(self.tmpdir, "scipy_param_evo.png"))
)
# Make last error is lower than initial
errors = self.scipy.get_errors()
self.assertGreaterEqual(errors[0], errors[-1])
# Load definition of known parameters (name, value)
with open(known_path) as f:
known = json.load(f)
# MODEL IDENTIFICATION ==========================================
# session = Estimation(workdir, fmu_path, inp, known, est, ideal,
# lp_n=3, lp_len=25000, lp_frame=(0, 25000),
# vp = (150000, 215940), ic_param={'Tstart': 'T'},
# ga_pop=20, ga_iter=20, ps_iter=30, ga_tol=0.001,
# ps_tol=0.0001, ftype='RMSE', lhs=True)
# estimates = session.estimate()
# err, res = session.validate()
scipy = SCIPY(fmu_path,
inp,
known,
est,
ideal,
ftype="RMSE",
solver="SLSQP")
par = scipy.estimate()
print(par)
res = scipy.res
res["ideal"] = ideal["T"]
res.plot()
plt.show()
print("ERROR={}".format(scipy.best_err))
# Load definition of known parameters (name, value)
with open(known_path) as f:
known = json.load(f)
# MODEL IDENTIFICATION ==========================================
# session = Estimation(workdir, fmu_path, inp, known, est, ideal,
# lp_n=3, lp_len=25000, lp_frame=(0, 25000),
# vp = (150000, 215940), ic_param={'Tstart': 'T'},
# ga_pop=20, ga_iter=20, ps_iter=30, ga_tol=0.001,
# ps_tol=0.0001, ftype='RMSE', lhs=True)
# estimates = session.estimate()
# err, res = session.validate()
scipy = SCIPY(fmu_path,
inp,
known,
est,
ideal,
ftype='RMSE',
solver='SLSQP')
par = scipy.estimate()
print(par)
res = scipy.res
res['ideal'] = ideal['T']
res.plot()
plt.show()
print('ERROR={}'.format(scipy.best_err))