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894 lines (823 loc) · 31.3 KB
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"""bdalg_test.py - test suite for block diagram algebra.
RMM, 30 Mar 2011 (based on TestBDAlg from v0.4a)
"""
import control as ctrl
import numpy as np
import pytest
from control.bdalg import _ensure_tf, append, connect, feedback
from control.lti import poles, zeros
from control.statesp import StateSpace
from control.tests.conftest import assert_tf_close_coeff
from control.xferfcn import TransferFunction
from numpy import sort
class TestFeedback:
"""Tests for the feedback function in bdalg.py."""
@pytest.fixture
def tsys(self):
class T:
pass
# Three SISO systems.
T.sys1 = TransferFunction([1, 2], [1, 2, 3])
T.sys2 = StateSpace([[1., 4.], [3., 2.]], [[1.], [-4.]],
[[1., 0.]], [[0.]])
T.sys3 = StateSpace([[-1.]], [[1.]], [[1.]], [[0.]]) # 1 state, SISO
# Two random scalars.
T.x1 = 2.5
T.x2 = -3.
return T
def testScalarScalar(self, tsys):
"""Scalar system with scalar feedback block."""
ans1 = feedback(tsys.x1, tsys.x2)
ans2 = feedback(tsys.x1, tsys.x2, 1.)
np.testing.assert_almost_equal(
ans1.num[0][0][0] / ans1.den[0][0][0], -2.5 / 6.5)
np.testing.assert_almost_equal(
ans2.num[0][0][0] / ans2.den[0][0][0], 2.5 / 8.5)
def testScalarSS(self, tsys):
"""Scalar system with state space feedback block."""
ans1 = feedback(tsys.x1, tsys.sys2)
ans2 = feedback(tsys.x1, tsys.sys2, 1.)
np.testing.assert_array_almost_equal(ans1.A, [[-1.5, 4.], [13., 2.]])
np.testing.assert_array_almost_equal(ans1.B, [[2.5], [-10.]])
np.testing.assert_array_almost_equal(ans1.C, [[-2.5, 0.]])
np.testing.assert_array_almost_equal(ans1.D, [[2.5]])
np.testing.assert_array_almost_equal(ans2.A, [[3.5, 4.], [-7., 2.]])
np.testing.assert_array_almost_equal(ans2.B, [[2.5], [-10.]])
np.testing.assert_array_almost_equal(ans2.C, [[2.5, 0.]])
np.testing.assert_array_almost_equal(ans2.D, [[2.5]])
# Make sure default arugments work as well
ans3 = feedback(tsys.sys2, 1)
ans4 = feedback(tsys.sys2)
np.testing.assert_array_almost_equal(ans3.A, ans4.A)
np.testing.assert_array_almost_equal(ans3.B, ans4.B)
np.testing.assert_array_almost_equal(ans3.C, ans4.C)
np.testing.assert_array_almost_equal(ans3.D, ans4.D)
def testScalarTF(self, tsys):
"""Scalar system with transfer function feedback block."""
ans1 = feedback(tsys.x1, tsys.sys1)
ans2 = feedback(tsys.x1, tsys.sys1, 1.)
np.testing.assert_array_almost_equal(ans1.num, [[[2.5, 5., 7.5]]])
np.testing.assert_array_almost_equal(ans1.den, [[[1., 4.5, 8.]]])
np.testing.assert_array_almost_equal(ans2.num, [[[2.5, 5., 7.5]]])
np.testing.assert_array_almost_equal(ans2.den, [[[1., -0.5, -2.]]])
# Make sure default arugments work as well
ans3 = feedback(tsys.sys1, 1)
ans4 = feedback(tsys.sys1)
np.testing.assert_array_almost_equal(ans3.num, ans4.num)
np.testing.assert_array_almost_equal(ans3.den, ans4.den)
def testSSScalar(self, tsys):
"""State space system with scalar feedback block."""
ans1 = feedback(tsys.sys2, tsys.x1)
ans2 = feedback(tsys.sys2, tsys.x1, 1.)
np.testing.assert_array_almost_equal(ans1.A, [[-1.5, 4.], [13., 2.]])
np.testing.assert_array_almost_equal(ans1.B, [[1.], [-4.]])
np.testing.assert_array_almost_equal(ans1.C, [[1., 0.]])
np.testing.assert_array_almost_equal(ans1.D, [[0.]])
np.testing.assert_array_almost_equal(ans2.A, [[3.5, 4.], [-7., 2.]])
np.testing.assert_array_almost_equal(ans2.B, [[1.], [-4.]])
np.testing.assert_array_almost_equal(ans2.C, [[1., 0.]])
np.testing.assert_array_almost_equal(ans2.D, [[0.]])
def testSSSS1(self, tsys):
"""State space system with state space feedback block."""
ans1 = feedback(tsys.sys2, tsys.sys2)
ans2 = feedback(tsys.sys2, tsys.sys2, 1.)
np.testing.assert_array_almost_equal(ans1.A, [[1., 4., -1., 0.],
[3., 2., 4., 0.], [1., 0., 1., 4.], [-4., 0., 3., 2]])
np.testing.assert_array_almost_equal(ans1.B, [[1.], [-4.], [0.], [0.]])
np.testing.assert_array_almost_equal(ans1.C, [[1., 0., 0., 0.]])
np.testing.assert_array_almost_equal(ans1.D, [[0.]])
np.testing.assert_array_almost_equal(ans2.A, [[1., 4., 1., 0.],
[3., 2., -4., 0.], [1., 0., 1., 4.], [-4., 0., 3., 2.]])
np.testing.assert_array_almost_equal(ans2.B, [[1.], [-4.], [0.], [0.]])
np.testing.assert_array_almost_equal(ans2.C, [[1., 0., 0., 0.]])
np.testing.assert_array_almost_equal(ans2.D, [[0.]])
def testSSSS2(self, tsys):
"""State space system with state space feedback block, including a
direct feedthrough term."""
sys3 = StateSpace([[-1., 4.], [2., -3]], [[2.], [3.]], [[-3., 1.]],
[[-2.]])
sys4 = StateSpace([[-3., -2.], [1., 4.]], [[-2.], [-6.]], [[2., -3.]],
[[3.]])
ans1 = feedback(sys3, sys4)
ans2 = feedback(sys3, sys4, 1.)
np.testing.assert_array_almost_equal(ans1.A,
[[-4.6, 5.2, 0.8, -1.2], [-3.4, -1.2, 1.2, -1.8],
[-1.2, 0.4, -1.4, -4.4], [-3.6, 1.2, 5.8, -3.2]])
np.testing.assert_array_almost_equal(ans1.B,
[[-0.4], [-0.6], [-0.8], [-2.4]])
np.testing.assert_array_almost_equal(ans1.C, [[0.6, -0.2, -0.8, 1.2]])
np.testing.assert_array_almost_equal(ans1.D, [[0.4]])
np.testing.assert_array_almost_equal(ans2.A,
[[-3.57142857142857, 4.85714285714286, 0.571428571428571,
-0.857142857142857],
[-1.85714285714286, -1.71428571428571, 0.857142857142857,
-1.28571428571429],
[0.857142857142857, -0.285714285714286, -1.85714285714286,
-3.71428571428571],
[2.57142857142857, -0.857142857142857, 4.42857142857143,
-1.14285714285714]])
np.testing.assert_array_almost_equal(ans2.B, [[0.285714285714286],
[0.428571428571429], [0.571428571428571], [1.71428571428571]])
np.testing.assert_array_almost_equal(ans2.C, [[-0.428571428571429,
0.142857142857143, -0.571428571428571, 0.857142857142857]])
np.testing.assert_array_almost_equal(ans2.D, [[-0.285714285714286]])
def test_mimo_ss_scalar_feedback(self):
"""MIMO state space system with scalar feedback block."""
sys_static = StateSpace([], [], [], [[1, 0], [0, 2]])
ans1 = feedback(sys_static)
ans2 = feedback(sys_static, np.eye(2))
np.testing.assert_array_almost_equal(ans1.D, ans2.D)
ans3 = feedback(sys_static, 2)
ans4 = feedback(sys_static, 2 * np.eye(2))
np.testing.assert_array_almost_equal(ans3.D, ans4.D)
sys_dynamic = StateSpace(
[[-1, 0], [0, -2]], [[1, 0], [0, 1]],
[[1, 0], [0, 1]], [[0, 0], [0, 0]])
ans5 = feedback(sys_dynamic)
ans6 = feedback(sys_dynamic, np.eye(2))
np.testing.assert_array_almost_equal(ans5.A, ans6.A)
np.testing.assert_array_almost_equal(ans5.B, ans6.B)
np.testing.assert_array_almost_equal(ans5.C, ans6.C)
np.testing.assert_array_almost_equal(ans5.D, ans6.D)
sys_nonsquare = StateSpace([], [], [], [[1, 2, 3], [4, 5, 6]])
with pytest.raises(ValueError, match="compatible inputs/outputs"):
feedback(sys_nonsquare)
def testSSTF(self, tsys):
"""State space system with transfer function feedback block."""
# This functionality is not implemented yet.
pass
def testTFScalar(self, tsys):
"""Transfer function system with scalar feedback block."""
ans1 = feedback(tsys.sys1, tsys.x1)
ans2 = feedback(tsys.sys1, tsys.x1, 1.)
np.testing.assert_array_almost_equal(ans1.num, [[[1., 2.]]])
np.testing.assert_array_almost_equal(ans1.den, [[[1., 4.5, 8.]]])
np.testing.assert_array_almost_equal(ans2.num, [[[1., 2.]]])
np.testing.assert_array_almost_equal(ans2.den, [[[1., -0.5, -2.]]])
def testTFSS(self, tsys):
"""Transfer function system with state space feedback block."""
# This functionality is not implemented yet.
pass
def testTFTF(self, tsys):
"""Transfer function system with transfer function feedback block."""
ans1 = feedback(tsys.sys1, tsys.sys1)
ans2 = feedback(tsys.sys1, tsys.sys1, 1.)
np.testing.assert_array_almost_equal(ans1.num, [[[1., 4., 7., 6.]]])
np.testing.assert_array_almost_equal(ans1.den,
[[[1., 4., 11., 16., 13.]]])
np.testing.assert_array_almost_equal(ans2.num, [[[1., 4., 7., 6.]]])
np.testing.assert_array_almost_equal(ans2.den,
[[[1., 4., 9., 8., 5.]]])
def testLists(self, tsys):
"""Make sure that lists of various lengths work for operations."""
sys1 = ctrl.tf([1, 1], [1, 2])
sys2 = ctrl.tf([1, 3], [1, 4])
sys3 = ctrl.tf([1, 5], [1, 6])
sys4 = ctrl.tf([1, 7], [1, 8])
sys5 = ctrl.tf([1, 9], [1, 0])
# Series
sys1_2 = ctrl.series(sys1, sys2)
np.testing.assert_array_almost_equal(sort(poles(sys1_2)), [-4., -2.])
np.testing.assert_array_almost_equal(sort(zeros(sys1_2)), [-3., -1.])
sys1_3 = ctrl.series(sys1, sys2, sys3)
np.testing.assert_array_almost_equal(sort(poles(sys1_3)),
[-6., -4., -2.])
np.testing.assert_array_almost_equal(sort(zeros(sys1_3)),
[-5., -3., -1.])
sys1_4 = ctrl.series(sys1, sys2, sys3, sys4)
np.testing.assert_array_almost_equal(sort(poles(sys1_4)),
[-8., -6., -4., -2.])
np.testing.assert_array_almost_equal(sort(zeros(sys1_4)),
[-7., -5., -3., -1.])
sys1_5 = ctrl.series(sys1, sys2, sys3, sys4, sys5)
np.testing.assert_array_almost_equal(sort(poles(sys1_5)),
[-8., -6., -4., -2., -0.])
np.testing.assert_array_almost_equal(sort(zeros(sys1_5)),
[-9., -7., -5., -3., -1.])
# Parallel
sys1_2 = ctrl.parallel(sys1, sys2)
np.testing.assert_array_almost_equal(sort(poles(sys1_2)), [-4., -2.])
np.testing.assert_array_almost_equal(sort(zeros(sys1_2)),
sort(zeros(sys1 + sys2)))
sys1_3 = ctrl.parallel(sys1, sys2, sys3)
np.testing.assert_array_almost_equal(sort(poles(sys1_3)),
[-6., -4., -2.])
np.testing.assert_array_almost_equal(sort(zeros(sys1_3)),
sort(zeros(sys1 + sys2 + sys3)))
sys1_4 = ctrl.parallel(sys1, sys2, sys3, sys4)
np.testing.assert_array_almost_equal(sort(poles(sys1_4)),
[-8., -6., -4., -2.])
np.testing.assert_array_almost_equal(
sort(zeros(sys1_4)),
sort(zeros(sys1 + sys2 + sys3 + sys4)))
sys1_5 = ctrl.parallel(sys1, sys2, sys3, sys4, sys5)
np.testing.assert_array_almost_equal(sort(poles(sys1_5)),
[-8., -6., -4., -2., -0.])
np.testing.assert_array_almost_equal(
sort(zeros(sys1_5)),
sort(zeros(sys1 + sys2 + sys3 + sys4 + sys5)))
def testMimoSeries(self, tsys):
"""regression: bdalg.series reverses order of arguments."""
g1 = ctrl.ss([], [], [], [[1, 2], [0, 3]])
g2 = ctrl.ss([], [], [], [[1, 0], [2, 3]])
ref = g2 * g1
tst = ctrl.series(g1, g2)
np.testing.assert_array_equal(ref.A, tst.A)
np.testing.assert_array_equal(ref.B, tst.B)
np.testing.assert_array_equal(ref.C, tst.C)
np.testing.assert_array_equal(ref.D, tst.D)
def test_feedback_args(self, tsys):
# Added 25 May 2019 to cover missing exception handling in feedback()
# If first argument is not LTI or convertable, generate an exception
args = ([1], tsys.sys2)
with pytest.raises(TypeError):
ctrl.feedback(*args)
# If second argument is not LTI or convertable, generate an exception
args = (tsys.sys1, 'hello world')
with pytest.raises(TypeError):
ctrl.feedback(*args)
# Convert first argument to FRD, if needed
h = TransferFunction([1], [1, 2, 2])
omega = np.logspace(-1, 2, 10)
frd = ctrl.FRD(h, omega)
sys = ctrl.feedback(1, frd)
assert isinstance(sys, ctrl.FRD)
def testConnect(self, tsys):
sys = append(tsys.sys2, tsys.sys3) # two siso systems
with pytest.warns(FutureWarning, match="use interconnect()"):
# should not raise error
connect(sys, [[1, 2], [2, -2]], [2], [1, 2])
connect(sys, [[1, 2], [2, 0]], [2], [1, 2])
connect(sys, [[1, 2, 0], [2, -2, 1]], [2], [1, 2])
connect(sys, [[1, 2], [2, -2]], [2, 1], [1])
sys3x3 = append(sys, tsys.sys3) # 3x3 mimo
connect(sys3x3, [[1, 2, 0], [2, -2, 1], [3, -3, 0]], [2], [1, 2])
connect(sys3x3, [[1, 2, 0], [2, -2, 1], [3, -3, 0]], [1, 2, 3], [3])
connect(sys3x3, [[1, 2, 0], [2, -2, 1], [3, -3, 0]], [2, 3], [2, 1])
# feedback interconnection out of bounds: input too high
Q = [[1, 3], [2, -2]]
with pytest.raises(IndexError):
connect(sys, Q, [2], [1, 2])
# feedback interconnection out of bounds: input too low
Q = [[0, 2], [2, -2]]
with pytest.raises(IndexError):
connect(sys, Q, [2], [1, 2])
# feedback interconnection out of bounds: output too high
Q = [[1, 2], [2, -3]]
with pytest.raises(IndexError):
connect(sys, Q, [2], [1, 2])
Q = [[1, 2], [2, 4]]
with pytest.raises(IndexError):
connect(sys, Q, [2], [1, 2])
# input/output index testing
Q = [[1, 2], [2, -2]] # OK interconnection
# input index is out of bounds: too high
with pytest.raises(IndexError):
connect(sys, Q, [3], [1, 2])
# input index is out of bounds: too low
with pytest.raises(IndexError):
connect(sys, Q, [0], [1, 2])
with pytest.raises(IndexError):
connect(sys, Q, [-2], [1, 2])
# output index is out of bounds: too high
with pytest.raises(IndexError):
connect(sys, Q, [2], [1, 3])
# output index is out of bounds: too low
with pytest.raises(IndexError):
connect(sys, Q, [2], [1, 0])
with pytest.raises(IndexError):
connect(sys, Q, [2], [1, -1])
@pytest.mark.parametrize(
"op, nsys, ninputs, noutputs, nstates", [
(ctrl.series, 2, 1, 1, 4),
(ctrl.parallel, 2, 1, 1, 4),
(ctrl.feedback, 2, 1, 1, 4),
(ctrl.append, 2, 2, 2, 4),
(ctrl.negate, 1, 1, 1, 2),
])
def test_bdalg_update_names(op, nsys, ninputs, noutputs, nstates):
syslist = [ctrl.rss(2, 1, 1), ctrl.rss(2, 1, 1)]
inputs = ['in1', 'in2']
outputs = ['out1', 'out2']
states = ['x1', 'x2', 'x3', 'x4']
newsys = op(
*syslist[:nsys], name='newsys', inputs=inputs[:ninputs],
outputs=outputs[:noutputs], states=states[:nstates])
assert newsys.name == 'newsys'
assert newsys.ninputs == ninputs
assert newsys.input_labels == inputs[:ninputs]
assert newsys.noutputs == noutputs
assert newsys.output_labels == outputs[:noutputs]
assert newsys.nstates == nstates
assert newsys.state_labels == states[:nstates]
def test_bdalg_udpate_names_errors():
sys1 = ctrl.rss(2, 1, 1)
sys2 = ctrl.rss(2, 1, 1)
with pytest.raises(ValueError, match="number of inputs does not match"):
ctrl.series(sys1, sys2, inputs=2)
with pytest.raises(ValueError, match="number of outputs does not match"):
ctrl.series(sys1, sys2, outputs=2)
with pytest.raises(ValueError, match="number of states does not match"):
ctrl.series(sys1, sys2, states=2)
with pytest.raises(ValueError, match="number of states does not match"):
ctrl.series(ctrl.tf(sys1), ctrl.tf(sys2), states=2)
with pytest.raises(TypeError, match="unrecognized keywords"):
ctrl.series(sys1, sys2, dt=1)
class TestEnsureTf:
"""Test `_ensure_tf`."""
@pytest.mark.parametrize(
"arraylike_or_tf, dt, tf",
[
(
ctrl.TransferFunction([1], [1, 2, 3]),
None,
ctrl.TransferFunction([1], [1, 2, 3]),
),
(
ctrl.TransferFunction([1], [1, 2, 3]),
0,
ctrl.TransferFunction([1], [1, 2, 3]),
),
(
2,
None,
ctrl.TransferFunction([2], [1]),
),
(
np.array([2]),
None,
ctrl.TransferFunction([2], [1]),
),
(
np.array([[2]]),
None,
ctrl.TransferFunction([2], [1]),
),
(
np.array(
[
[2, 0, 3],
[1, 2, 3],
]
),
None,
ctrl.TransferFunction(
[
[[2], [0], [3]],
[[1], [2], [3]],
],
[
[[1], [1], [1]],
[[1], [1], [1]],
],
),
),
(
np.array([2, 0, 3]),
None,
ctrl.TransferFunction(
[
[[2], [0], [3]],
],
[
[[1], [1], [1]],
],
),
),
],
)
def test_ensure(self, arraylike_or_tf, dt, tf):
"""Test nominal cases."""
ensured_tf = _ensure_tf(arraylike_or_tf, dt)
assert_tf_close_coeff(tf, ensured_tf)
@pytest.mark.parametrize(
"arraylike_or_tf, dt, exception",
[
(
ctrl.TransferFunction([1], [1, 2, 3]),
0.1,
ValueError,
),
(
ctrl.TransferFunction([1], [1, 2, 3], 0.1),
0,
ValueError,
),
(
np.ones((1, 1, 1)),
None,
ValueError,
),
(
np.ones((1, 1, 1, 1)),
None,
ValueError,
),
],
)
def test_error_ensure(self, arraylike_or_tf, dt, exception):
"""Test error cases."""
with pytest.raises(exception):
_ensure_tf(arraylike_or_tf, dt)
class TestTfCombineSplit:
"""Test `combine_tf` and `split_tf`."""
@pytest.mark.parametrize(
"tf_array, tf",
[
# Continuous-time
(
[
[ctrl.TransferFunction([1], [1, 1])],
[ctrl.TransferFunction([2], [1, 0])],
],
ctrl.TransferFunction(
[
[[1]],
[[2]],
],
[
[[1, 1]],
[[1, 0]],
],
),
),
# Discrete-time
(
[
[ctrl.TransferFunction([1], [1, 1], dt=1)],
[ctrl.TransferFunction([2], [1, 0], dt=1)],
],
ctrl.TransferFunction(
[
[[1]],
[[2]],
],
[
[[1, 1]],
[[1, 0]],
],
dt=1,
),
),
# Scalar
(
[
[2],
[ctrl.TransferFunction([2], [1, 0])],
],
ctrl.TransferFunction(
[
[[2]],
[[2]],
],
[
[[1]],
[[1, 0]],
],
),
),
# Matrix
(
[
[np.eye(3)],
[
ctrl.TransferFunction(
[
[[2], [0], [3]],
[[1], [2], [3]],
],
[
[[1], [1], [1]],
[[1], [1], [1]],
],
)
],
],
ctrl.TransferFunction(
[
[[1], [0], [0]],
[[0], [1], [0]],
[[0], [0], [1]],
[[2], [0], [3]],
[[1], [2], [3]],
],
[
[[1], [1], [1]],
[[1], [1], [1]],
[[1], [1], [1]],
[[1], [1], [1]],
[[1], [1], [1]],
],
),
),
# Inhomogeneous
(
[
[np.eye(3)],
[
ctrl.TransferFunction(
[
[[2], [0]],
[[1], [2]],
],
[
[[1], [1]],
[[1], [1]],
],
),
ctrl.TransferFunction(
[
[[3]],
[[3]],
],
[
[[1]],
[[1]],
],
),
],
],
ctrl.TransferFunction(
[
[[1], [0], [0]],
[[0], [1], [0]],
[[0], [0], [1]],
[[2], [0], [3]],
[[1], [2], [3]],
],
[
[[1], [1], [1]],
[[1], [1], [1]],
[[1], [1], [1]],
[[1], [1], [1]],
[[1], [1], [1]],
],
),
),
# Discrete-time
(
[
[2],
[ctrl.TransferFunction([2], [1, 0], dt=0.1)],
],
ctrl.TransferFunction(
[
[[2]],
[[2]],
],
[
[[1]],
[[1, 0]],
],
dt=0.1,
),
),
],
)
def test_combine_tf(self, tf_array, tf):
"""Test combining transfer functions."""
tf_combined = ctrl.combine_tf(tf_array)
assert_tf_close_coeff(tf_combined, tf)
@pytest.mark.parametrize(
"tf_array, tf",
[
(
np.array(
[
[ctrl.TransferFunction([1], [1, 1])],
],
dtype=object,
),
ctrl.TransferFunction(
[
[[1]],
],
[
[[1, 1]],
],
),
),
(
np.array(
[
[ctrl.TransferFunction([1], [1, 1])],
[ctrl.TransferFunction([2], [1, 0])],
],
dtype=object,
),
ctrl.TransferFunction(
[
[[1]],
[[2]],
],
[
[[1, 1]],
[[1, 0]],
],
),
),
(
np.array(
[
[ctrl.TransferFunction([1], [1, 1], dt=1)],
[ctrl.TransferFunction([2], [1, 0], dt=1)],
],
dtype=object,
),
ctrl.TransferFunction(
[
[[1]],
[[2]],
],
[
[[1, 1]],
[[1, 0]],
],
dt=1,
),
),
(
np.array(
[
[ctrl.TransferFunction([2], [1], dt=0.1)],
[ctrl.TransferFunction([2], [1, 0], dt=0.1)],
],
dtype=object,
),
ctrl.TransferFunction(
[
[[2]],
[[2]],
],
[
[[1]],
[[1, 0]],
],
dt=0.1,
),
),
],
)
def test_split_tf(self, tf_array, tf):
"""Test splitting transfer functions."""
tf_split = ctrl.split_tf(tf)
# Test entry-by-entry
for i in range(tf_split.shape[0]):
for j in range(tf_split.shape[1]):
assert_tf_close_coeff(
tf_split[i, j],
tf_array[i, j],
)
# Test combined
assert_tf_close_coeff(
ctrl.combine_tf(tf_split),
ctrl.combine_tf(tf_array),
)
@pytest.mark.parametrize(
"tf_array, exception",
[
# Wrong timesteps
(
[
[ctrl.TransferFunction([1], [1, 1], 0.1)],
[ctrl.TransferFunction([2], [1, 0], 0.2)],
],
ValueError,
),
(
[
[ctrl.TransferFunction([1], [1, 1], 0.1)],
[ctrl.TransferFunction([2], [1, 0], 0)],
],
ValueError,
),
# Too few dimensions
(
[
ctrl.TransferFunction([1], [1, 1]),
ctrl.TransferFunction([2], [1, 0]),
],
ValueError,
),
# Too many dimensions
(
[
[[ctrl.TransferFunction([1], [1, 1], 0.1)]],
[[ctrl.TransferFunction([2], [1, 0], 0)]],
],
ValueError,
),
# Incompatible dimensions
(
[
[
ctrl.TransferFunction(
[
[
[1],
]
],
[
[
[1, 1],
]
],
),
ctrl.TransferFunction(
[
[[2], [1]],
[[1], [3]],
],
[
[[1, 0], [1, 0]],
[[1, 0], [1, 0]],
],
),
],
],
ValueError,
),
(
[
[
ctrl.TransferFunction(
[
[[2], [1]],
[[1], [3]],
],
[
[[1, 0], [1, 0]],
[[1, 0], [1, 0]],
],
),
ctrl.TransferFunction(
[
[
[1],
]
],
[
[
[1, 1],
]
],
),
],
],
ValueError,
),
(
[
[
ctrl.TransferFunction(
[
[[2], [1]],
[[1], [3]],
],
[
[[1, 0], [1, 0]],
[[1, 0], [1, 0]],
],
),
ctrl.TransferFunction(
[
[[2], [1]],
[[1], [3]],
],
[
[[1, 0], [1, 0]],
[[1, 0], [1, 0]],
],
),
],
[
ctrl.TransferFunction(
[
[[2], [1], [1]],
[[1], [3], [2]],
],
[
[[1, 0], [1, 0], [1, 0]],
[[1, 0], [1, 0], [1, 0]],
],
),
ctrl.TransferFunction(
[
[[2], [1]],
[[1], [3]],
],
[
[[1, 0], [1, 0]],
[[1, 0], [1, 0]],
],
),
],
],
ValueError,
),
],
)
def test_error_combine_tf(self, tf_array, exception):
"""Test error cases."""
with pytest.raises(exception):
ctrl.combine_tf(tf_array)