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Merged
sdahdah merged 2 commits into from
Dec 3, 2024
Merged

Add transfer matrix split #16

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71bfe6d
Add zeros and ones
sdahdah Dec 3, 2024
280001c
Add split function
sdahdah Dec 3, 2024
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112 changes: 112 additions & 0 deletions src/dkpy/utilities.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,10 @@
"_ensure_tf",
"_tf_close_coeff",
"_tf_combine",
"_tf_split",
"_tf_eye",
"_tf_zeros",
"_tf_ones",
"_auto_lmi_strictness",
]

Expand Down Expand Up @@ -192,6 +195,55 @@ def _tf_combine(
return G_tf


def _tf_split(tf: control.TransferFunction) -> np.ndarray:
"""Split MIMO transfer function into NumPy array of SISO tranfer functions.

Parameters
----------
tf : control.TransferFunction
MIMO transfer function to split.

Returns
-------
np.ndarray
NumPy array of SISO transfer functions.

Examples
--------
Split a MIMO transfer function

>>> G = control.TransferFunction(
... [
... [[87.8], [-86.4]],
... [[108.2], [-109.6]],
... ],
... [
... [[1, 1], [1, 1]],
... [[1, 1], [1, 1]],
... ],
... )
>>> dkpy._tf_split(G)
array([[TransferFunction(array([87.8]), array([1, 1])),
TransferFunction(array([-86.4]), array([1, 1]))],
[TransferFunction(array([108.2]), array([1, 1])),
TransferFunction(array([-109.6]), array([1, 1]))]], dtype=object)
"""
tf_split_lst = []
for i_out in range(tf.noutputs):
row = []
for i_in in range(tf.ninputs):
row.append(
control.TransferFunction(
tf.num[i_out][i_in],
tf.den[i_out][i_in],
dt=tf.dt,
)
)
tf_split_lst.append(row)
tf_split = np.array(tf_split_lst, dtype=object)
return tf_split


def _tf_eye(
n: int,
dt: Union[None, bool, float] = None,
Expand Down Expand Up @@ -219,6 +271,66 @@ def _tf_eye(
return eye


def _tf_zeros(
m: int,
n: int,
dt: Union[None, bool, float] = None,
) -> control.TransferFunction:
"""Transfer function matrix of zeros.

Parameters
----------
m : int
First dimension.
n : int
Second dimension.
dt : Union[None, bool, float]
Timestep (s). Based on the ``control`` package, ``True`` indicates a
discrete-time system with unspecified timestep, ``0`` indicates a
continuous-time system, and ``None`` indicates a continuous- or
discrete-time system with unspecified timestep.

Returns
-------
control.TransferFunction
Identity transfer matrix.
"""
num = np.zeros((m, n, 1))
den = np.ones((m, n, 1))
zeros = control.TransferFunction(num, den, dt=dt)
return zeros


def _tf_ones(
m: int,
n: int,
dt: Union[None, bool, float] = None,
) -> control.TransferFunction:
"""Transfer matrix of ones.

Parameters
----------
m : int
First dimension.
n : int
Second dimension.
dt : Union[None, bool, float]
Timestep (s). Based on the ``control`` package, ``True`` indicates a
discrete-time system with unspecified timestep, ``0`` indicates a
continuous-time system, and ``None`` indicates a continuous- or
discrete-time system with unspecified timestep.

Returns
-------
control.TransferFunction
Identity transfer matrix.
"""
num = np.ones((m, n, 1))
den = np.ones((m, n, 1))
zeros = control.TransferFunction(num, den, dt=dt)
return zeros


def _auto_lmi_strictness(
solver_params: Dict[str, Any],
scale: float = 10,
Expand Down
176 changes: 172 additions & 4 deletions tests/test_utilities.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -201,8 +201,8 @@ def test_error_ensure(self, arraylike_or_tf, dt, exception):
dkpy._ensure_tf(arraylike_or_tf, dt)


class TestTfCombine:
"""Test :func:`_tf_combine`."""
class TestTfCombineSplit:
"""Test :func:`_tf_combine` and :func:`_tf_split`."""

@pytest.mark.parametrize(
"tf_array, tf",
Expand Down Expand Up @@ -362,6 +362,102 @@ def test_combine(self, tf_array, tf):
tf_combined = dkpy._tf_combine(tf_array)
assert dkpy._tf_close_coeff(tf_combined, tf)

@pytest.mark.parametrize(
"tf_array, tf",
[
(
np.array(
[
[control.TransferFunction([1], [1, 1])],
],
dtype=object,
),
control.TransferFunction(
[
[[1]],
],
[
[[1, 1]],
],
),
),
(
np.array(
[
[control.TransferFunction([1], [1, 1])],
[control.TransferFunction([2], [1, 0])],
],
dtype=object,
),
control.TransferFunction(
[
[[1]],
[[2]],
],
[
[[1, 1]],
[[1, 0]],
],
),
),
(
np.array(
[
[control.TransferFunction([1], [1, 1], dt=1)],
[control.TransferFunction([2], [1, 0], dt=1)],
],
dtype=object,
),
control.TransferFunction(
[
[[1]],
[[2]],
],
[
[[1, 1]],
[[1, 0]],
],
dt=1,
),
),
(
np.array(
[
[control.TransferFunction([2], [1], dt=0.1)],
[control.TransferFunction([2], [1, 0], dt=0.1)],
],
dtype=object,
),
control.TransferFunction(
[
[[2]],
[[2]],
],
[
[[1]],
[[1, 0]],
],
dt=0.1,
),
),
],
)
def test_split(self, tf_array, tf):
"""Test splitting transfer functions."""
tf_split = dkpy._tf_split(tf)
# Test entry-by-entry
for i in range(tf_split.shape[0]):
for j in range(tf_split.shape[1]):
assert dkpy._tf_close_coeff(
tf_split[i, j],
tf_array[i, j],
)
# Test combined
assert dkpy._tf_close_coeff(
dkpy._tf_combine(tf_split),
dkpy._tf_combine(tf_array),
)

@pytest.mark.parametrize(
"tf_array, exception",
[
Expand Down Expand Up @@ -431,7 +527,7 @@ class TestTfEye:
),
),
(
2,
3,
1e-3,
control.TransferFunction(
[
Expand All @@ -452,7 +548,79 @@ class TestTfEye:
def test_tf_eye(self, n, dt, tf_exp):
"""Test :func:`_tf_eye`."""
tf = dkpy._tf_eye(n, dt)
assert dkpy._tf_close_coeff(tf, tf)
assert dkpy._tf_close_coeff(tf, tf_exp)


class TestTfZeros:
"""Test :func:`_tf_zeros`."""

@pytest.mark.parametrize(
"m, n, dt, tf_exp",
[
(
1,
1,
None,
control.TransferFunction([0], [1], dt=None),
),
(
2,
3,
None,
control.TransferFunction(
[
[[0], [0], [0]],
[[0], [0], [0]],
],
[
[[1], [1], [1]],
[[1], [1], [1]],
],
dt=None,
),
),
],
)
def test_tf_zeros(self, m, n, dt, tf_exp):
"""Test :func:`_tf_zeros`."""
tf = dkpy._tf_zeros(m, n, dt)
assert dkpy._tf_close_coeff(tf, tf_exp)


class TestTfOnes:
"""Test :func:`_tf_ones`."""

@pytest.mark.parametrize(
"m, n, dt, tf_exp",
[
(
1,
1,
None,
control.TransferFunction([1], [1], dt=None),
),
(
2,
3,
None,
control.TransferFunction(
[
[[1], [1], [1]],
[[1], [1], [1]],
],
[
[[1], [1], [1]],
[[1], [1], [1]],
],
dt=None,
),
),
],
)
def test_tf_ones(self, m, n, dt, tf_exp):
"""Test :func:`_tf_ones`."""
tf = dkpy._tf_ones(m, n, dt)
assert dkpy._tf_close_coeff(tf, tf_exp)


class TestAutoLmiStrictness:
Expand Down
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