def test_optimize_works(self):
exe = os.path.join(datafiles_path, 'bernoulli' + EXTENSION)
stan = os.path.join(datafiles_path, 'bernoulli.stan')
model = Model(stan_file=stan, exe_file=exe)
jdata = os.path.join(datafiles_path, 'bernoulli.data.json')
jinit = os.path.join(datafiles_path, 'bernoulli.init.json')
fit = model.optimize(
data=jdata,
seed=1239812093,
inits=jinit,
algorithm='BFGS',
init_alpha=0.001,
iter=100,
)
# check if calling sample related stuff fails
with self.assertRaises(RuntimeError):
fit.summary()
with self.assertRaises(RuntimeError):
_ = fit.sample
with self.assertRaises(RuntimeError):
fit.diagnose()
# test numpy output
self.assertAlmostEqual(fit.optimized_params_np[0], -5, places=2)
self.assertAlmostEqual(fit.optimized_params_np[1], 0.2, places=3)
# test pandas output
self.assertEqual(
fit.optimized_params_np[0], fit.optimized_params_pd['lp__'][0]
)
self.assertEqual(
fit.optimized_params_np[1], fit.optimized_params_pd['theta'][0]
)
# test dict output
self.assertEqual(
fit.optimized_params_np[0], fit.optimized_params_dict['lp__']
)
self.assertEqual(
fit.optimized_params_np[1], fit.optimized_params_dict['theta']
)
def test_optimize_works_dict(self):
import json
exe = os.path.join(datafiles_path, 'bernoulli' + EXTENSION)
stan = os.path.join(datafiles_path, 'bernoulli.stan')
model = Model(stan_file=stan, exe_file=exe)
with open(os.path.join(datafiles_path, 'bernoulli.data.json')) as d:
data = json.load(d)
with open(os.path.join(datafiles_path, 'bernoulli.init.json')) as d:
init = json.load(d)
fit = model.optimize(
data=data,
seed=1239812093,
inits=init,
algorithm='BFGS',
init_alpha=0.001,
iter=100,
)
# test numpy output
self.assertAlmostEqual(fit.optimized_params_np[0], -5, places=2)
self.assertAlmostEqual(fit.optimized_params_np[1], 0.2, places=3)