def test_model_io():
# get example data
data = np.genfromtxt(os.path.join(".", "data", "exampleData.csv"),
delimiter=',')
frequencies = data[:, 0]
Z = data[:, 1] + 1j * data[:, 2]
randles = CustomCircuit(
initial_guess=[None, .005, .1, .005, .1, 0.9, .001, None],
circuit='R0-p(R1,C1)-p(R1,CPE1)-Wo1',
constants={
'R0': 0.01,
'Wo1_1': 200
})
randles.save('./test_io.json')
randles2 = CustomCircuit()
randles2.load('./test_io.json')
assert randles == randles2
randles.fit(frequencies, Z)
randles.save('./test_io.json')
randles2 = CustomCircuit()
randles2.load('./test_io.json')
assert str(randles) == str(randles2)
assert randles == randles2
fitted_template = CustomCircuit()
fitted_template.load('test_io.json', fitted_as_initial=True)
def test_model_io():
# get example data
data = np.genfromtxt(os.path.join(".", "data", "exampleData.csv"),
delimiter=',')
frequencies = data[:, 0]
Z = data[:, 1] + 1j * data[:, 2]
randles = CustomCircuit(
initial_guess=[None, .005, .1, .005, .1, .001, 200],
circuit='R0-p(R1,C1)-p(R1,C1)-Wo1',
constants={'R0': 0.01})
randles.fit(frequencies, Z)
randles.save('./test_io.json')
randles2 = CustomCircuit()
randles2.load('./test_io.json')
print(randles2)
assert randles == randles2