def test_get_model(self):
"""Test model getter function."""
for model_name in MODEL_DATA:
model = models.get_isotherm_model(model_name)
assert model.name == model_name
with pytest.raises(ParameterError):
models.get_isotherm_model('bad_model')
def test_models_default_guess(self, m_name):
"""Test each model's default guess function."""
model = models.get_isotherm_model(m_name)
exp_guess = MODEL_DATA[m_name]['initial_guess']
def_guess = model.initial_guess(1, 1)
for param in def_guess:
assert numpy.isclose(exp_guess[param], def_guess[param], 0.01)
def test_models_s_pressure(self, m_name):
"""Test each model's spreading pressure function."""
model = models.get_isotherm_model(m_name)
model.params = MODEL_DATA[m_name]['test_parameters']
test_values = MODEL_DATA[m_name]['test_values']
for i, p in enumerate(test_values['pressure']):
assert numpy.isclose(model.spreading_pressure(p),
test_values['spreading_pressure'][i], 0.001)
def test_models_fit_function(self, m_name):
model = models.get_isotherm_model(m_name)
test_values = MODEL_DATA[m_name]['test_values']
param_guess = model.initial_guess(
numpy.array(test_values['pressure']),
numpy.array(test_values['loading']),
)
# param_real = MODEL_DATA[m_name]['test_parameters']
model.fit(
numpy.array(test_values['pressure']),
numpy.array(test_values['loading']),
param_guess,
optimization_params=dict(max_nfev=1e6),
verbose=True,
)