def test_remove(self):
fit_items = basico.get_fit_parameters()
self.assertIsNotNone(fit_items)
basico.remove_fit_parameters()
fit_items_2 = basico.get_fit_parameters()
self.assertIsNone(fit_items_2)
basico.set_fit_parameters(fit_items)
def test_change_bounds(self):
basico.set_fit_parameters([{
'name': '(R1).k2',
'lower': 1,
'upper': 0.01
}])
with self.assertLogs(level='ERROR') as cm:
sol = basico.as_dict(basico.run_parameter_estimation())
self.assertTrue(np.isnan(sol['sol']))
def test_set_fit_items(self):
old_fit_items = basico.get_fit_parameters().reset_index()
basico.set_fit_parameters(old_fit_items)
fit_items = basico.get_fit_parameters().reset_index()
old_first = old_fit_items.iloc[0].to_dict()
new_first = fit_items.iloc[0].to_dict()
self.assertEqual(old_first['name'], new_first['name'])
self.assertEqual(old_first['lower'], new_first['lower'])
self.assertEqual(old_first['upper'], new_first['upper'])
def test_expressions(self):
basico.new_model(name='Model 4', volume_unit='ml', quantity_unit='mmol')
basico.add_species('PGME', initial_concentration=20)
basico.add_species('7-ADCA', initial_concentration=10)
basico.add_species('CEX', initial_concentration=0)
basico.add_species('PG', initial_concentration=2)
params = ['K_s', 'k2', 'K_n', 'k3', 'k4', 'k5', 'k6', 'K_si', 'K_p', 'k_4b', 'e0', 'kd', 'K_p2i']
values = [14,25920,290,25020,4416000,29460,99600,20,39,547560,0.000198000000000000,0.0385800000000000,12]
for k, v in zip(params, values):
basico.add_parameter(k, initial_value=v)
basico.add_equation('A = k4 * [7-ADCA] / K_n + k5 * [7-ADCA] / K_n + k6 * [PGME] / K_si + k3')
basico.add_equation('e = e0 /(1 + [PGME]^2/ (K_s * K_si) + [7-ADCA] / K_n + ( k2 * [PGME] /(K_s * A))*( 1 + [7-ADCA]/K_n + [PGME]/K_si)+[CEX]/K_p+[PG]/K_p2i)*exp(-kd*t)')
basico.add_equation('B = (k2 * e * [PGME]/K_s)*(1/A) + (k_4b * e * [CEX]/K_p)*(1/A)')
dxdt_1 = '-k2 * e * [PGME]/K_s - k6 * B * [PGME]/K_si'
dxdt_4 = 'B * (k3 + k5*[7-ADCA]/K_n + k6* [PGME]/K_si)'
dxdt_3 = '-({0}) - ({1})'.format(dxdt_1, dxdt_4)
dxdt_2 = '-({0})'.format(dxdt_3)
basico.add_equation('d[PGME]/dt=' + dxdt_1)
basico.add_equation('d[PG]/dt=' + dxdt_4)
basico.add_equation('d[CEX]/dt=' + dxdt_3)
basico.add_equation('d[7-ADCA]/dt=' + dxdt_2)
template = basico.get_fit_item_template(include_global=True, default_lb=1e-2, default_ub=1e6)
to_remove = None
for d in template:
# set lower bound for the equilibrium constants
if 'Values[K_si' in d['name']:
d['upper'] = 50
continue
if 'Values[K' in d['name']:
d['upper'] = 1000
continue
if 'Values[k_d' in d['name']:
d['upper'] = 0.5
d['lower'] = 0.3
basico.set_fit_parameters(template)
self.assertTrue(True)
def test_get_data(self):
data = basico.get_experiment_data_from_model()
self.assertEqual(len(data), 5)
set_1 = data[0]
self.assertEqual(set_1.shape, (100, 3))
names = basico.get_experiment_names()
self.assertIn('Experiment', names)
files = basico.get_experiment_filenames()
self.assertEqual(len(files), len(names))
set_2 = basico.get_data_from_experiment('Experiment')
self.assertEqual(set_2.shape, (100, 3))
sol_before = basico.run_parameter_estimation(
method=basico.PE.CURRENT_SOLUTION)
# remove data
basico.remove_experiments()
# add data back
for exp, name in zip(data, names):
basico.add_experiment(name, exp)
# since we have affected experiments, reset them
basico.set_fit_parameters(basico.get_fit_parameters())
# save to temp file
main_file = tempfile.mktemp()
basico.save_model_and_data(main_file, delete_data_on_exit=True)
# ensure it still works
sol_after = basico.run_parameter_estimation(
method=basico.PE.CURRENT_SOLUTION)
self.assertListEqual(basico.as_dict(sol_before[['sol']]),
basico.as_dict(sol_after[['sol']]))