def test_errors():
if not matplotlib:
skip("Matplotlib not the default backend")
# Invalid `system` check
tfm = TransferFunctionMatrix([[tf6, tf5], [tf5, tf6]])
expr = 1 / (s**2 - 1)
raises(NotImplementedError, lambda: pole_zero_plot(tfm))
raises(NotImplementedError, lambda: pole_zero_numerical_data(expr))
raises(NotImplementedError, lambda: impulse_response_plot(expr))
raises(NotImplementedError, lambda: impulse_response_numerical_data(tfm))
raises(NotImplementedError, lambda: step_response_plot(tfm))
raises(NotImplementedError, lambda: step_response_numerical_data(expr))
raises(NotImplementedError, lambda: ramp_response_plot(expr))
raises(NotImplementedError, lambda: ramp_response_numerical_data(tfm))
raises(NotImplementedError, lambda: bode_plot(tfm))
# More than 1 variables
tf_a = TransferFunction(a, s + 1, s)
raises(ValueError, lambda: pole_zero_plot(tf_a))
raises(ValueError, lambda: pole_zero_numerical_data(tf_a))
raises(ValueError, lambda: impulse_response_plot(tf_a))
raises(ValueError, lambda: impulse_response_numerical_data(tf_a))
raises(ValueError, lambda: step_response_plot(tf_a))
raises(ValueError, lambda: step_response_numerical_data(tf_a))
raises(ValueError, lambda: ramp_response_plot(tf_a))
raises(ValueError, lambda: ramp_response_numerical_data(tf_a))
raises(ValueError, lambda: bode_plot(tf_a))
# lower_limit > 0 for response plots
raises(ValueError, lambda: impulse_response_plot(tf1, lower_limit=-1))
raises(ValueError, lambda: step_response_plot(tf1, lower_limit=-0.1))
raises(ValueError, lambda: ramp_response_plot(tf1, lower_limit=-4 / 3))
# slope in ramp_response_plot() is negative
raises(ValueError, lambda: ramp_response_plot(tf1, slope=-0.1))
# incorrect frequency or phase unit
raises(ValueError, lambda: bode_plot(tf1, freq_unit='hz'))
raises(ValueError, lambda: bode_plot(tf1, phase_unit='degree'))
def ramp_res_tester(sys, num_points, expected_value, slope=1):
x, y = _to_tuple(*ramp_response_numerical_data(
sys, slope=slope, adaptive=False, nb_of_points=num_points))
x_check = check_point_accuracy(x, expected_value[0])
y_check = check_point_accuracy(y, expected_value[1])
return x_check and y_check