Ejemplo n.º 1
0
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'))
Ejemplo n.º 2
0
 def impulse_res_tester(sys, expected_value):
     x, y = _to_tuple(*impulse_response_numerical_data(
         sys, adaptive=False, nb_of_points=10))
     x_check = check_point_accuracy(x, expected_value[0])
     y_check = check_point_accuracy(y, expected_value[1])
     return x_check and y_check