def test_step_pole_cancellation(self, tsystem):
# confirm that pole-zero cancellation doesn't perturb results
# https://github.com/python-control/python-control/issues/440
step_info_no_cancellation = step_info(tsystem[0].sys)
step_info_cancellation = step_info(tsystem[1].sys)
self.assert_step_info_match(tsystem[0].sys, step_info_no_cancellation,
step_info_cancellation)
def test_step_pole_cancellation(self, pole_cancellation,
no_pole_cancellation):
# confirm that pole-zero cancellation doesn't perturb results
# https://github.com/python-control/python-control/issues/440
step_info_no_cancellation = step_info(no_pole_cancellation)
step_info_cancellation = step_info(pole_cancellation)
for key in step_info_no_cancellation:
np.testing.assert_allclose(step_info_no_cancellation[key],
step_info_cancellation[key], rtol=1e-4)
def test_step_pole_cancellation(self, pole_cancellation,
no_pole_cancellation):
# confirm that pole-zero cancellation doesn't perturb results
# https://github.com/python-control/python-control/issues/440
step_info_no_cancellation = step_info(no_pole_cancellation)
step_info_cancellation = step_info(pole_cancellation)
for key in step_info_no_cancellation:
if key == 'Overshoot':
# skip this test because these systems have no overshoot
# => very sensitive to parameters
continue
np.testing.assert_allclose(step_info_no_cancellation[key],
step_info_cancellation[key], rtol=1e-4)
def test_step_info(self):
# From matlab docs:
sys = TransferFunction([1, 5, 5], [1, 1.65, 5, 6.5, 2])
Strue = {
'RiseTime': 3.8456,
'SettlingTime': 27.9762,
'SettlingMin': 2.0689,
'SettlingMax': 2.6873,
'Overshoot': 7.4915,
'Undershoot': 0,
'Peak': 2.6873,
'PeakTime': 8.0530,
'SteadyStateValue': 2.50
}
S = step_info(sys)
Sk = sorted(S.keys())
Sktrue = sorted(Strue.keys())
assert Sk == Sktrue
# Very arbitrary tolerance because I don't know if the
# response from the MATLAB is really that accurate.
# maybe it is a good idea to change the Strue to match
# but I didn't do it because I don't know if it is
# accurate either...
rtol = 2e-2
np.testing.assert_allclose([S[k] for k in Sk],
[Strue[k] for k in Sktrue],
rtol=rtol)
def test_step_info_invalid(self):
"""Call step_info with invalid parameters."""
with pytest.raises(ValueError, match="time series data convention"):
step_info(["not numeric data"])
with pytest.raises(ValueError, match="time series data convention"):
step_info(np.ones((10, 15))) # invalid shape
with pytest.raises(ValueError, match="matching time vector"):
step_info(np.ones(15), T=np.linspace(0, 1, 20)) # time too long
with pytest.raises(ValueError, match="matching time vector"):
step_info(np.ones((2, 2, 15))) # no time vector
def test_step_info(self, tsystem, systype, time_2d, yfinal):
"""Test step info for SISO systems."""
step_info_kwargs = tsystem.kwargs.get('step_info', {})
if systype == "time response":
# simulate long enough for steady state value
tfinal = 3 * tsystem.step_info['SettlingTime']
if np.isnan(tfinal):
pytest.skip("test system does not settle")
t, y = step_response(tsystem.sys, T=tfinal, T_num=5000)
sysdata = y
step_info_kwargs['T'] = t[np.newaxis, :] if time_2d else t
else:
sysdata = tsystem.sys
if yfinal:
step_info_kwargs['yfinal'] = tsystem.step_info['SteadyStateValue']
info = step_info(sysdata, **step_info_kwargs)
self.assert_step_info_match(tsystem.sys, info, tsystem.step_info)
def test_step_info_mimo(self, tsystem, systype, yfinal):
"""Test step info for MIMO systems."""
step_info_kwargs = tsystem.kwargs.get('step_info', {})
if systype == "time response":
tfinal = 3 * max([S['SettlingTime']
for Srow in tsystem.step_info for S in Srow])
t, y = step_response(tsystem.sys, T=tfinal, T_num=5000)
sysdata = y
step_info_kwargs['T'] = t
else:
sysdata = tsystem.sys
if yfinal:
step_info_kwargs['yfinal'] = [[S['SteadyStateValue']
for S in Srow]
for Srow in tsystem.step_info]
info_dict = step_info(sysdata, **step_info_kwargs)
for i, row in enumerate(info_dict):
for j, info in enumerate(row):
self.assert_step_info_match(tsystem.sys,
info, tsystem.step_info[i][j])
