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fix(xferfcn): normalize real zpk coefficients #1226

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fix(xferfcn): normalize real zpk coefficients #1226

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16 changes: 16 additions & 0 deletions control/tests/xferfcn_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -52,6 +52,9 @@ def test_constructor_bad_input_type(self):

with pytest.raises(TypeError, match="unsupported data type"):
ct.tf([1j], [1, 2, 3])
for dtype in [np.complex64, np.complex128]:
with pytest.raises(TypeError, match="unsupported data type"):
ct.tf(np.array([1 + 1j], dtype=dtype), [1, 2, 3])

# good input
TransferFunction([[[0, 1], [2, 3]],
Expand Down Expand Up @@ -1550,6 +1553,19 @@ def test_zpk(zeros, poles, gain, args, kwargs):
if kwargs.get('name'):
assert sys.name == kwargs.get('name')


@pytest.mark.parametrize("dtype", [np.complex64, np.complex128])
def test_zpk_complex_dtype_real_coefficients(dtype):
zeros = np.array([1 + 1j, 1 - 1j], dtype=dtype)
poles = np.array([-1 + 1j, -1 - 1j], dtype=dtype)

sys = ct.zpk(zeros, poles, gain=1, dt=0)

assert sys.num_array[0, 0].dtype == float
assert sys.den_array[0, 0].dtype == float
assert "float32" not in str(sys)


@pytest.mark.parametrize("create, args, kwargs, convert", [
(StateSpace, ([-1], [1], [1], [0]), {}, ss2tf),
(StateSpace, ([-1], [1], [1], [0]), {}, ss),
Expand Down
25 changes: 18 additions & 7 deletions control/xferfcn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1960,7 +1960,7 @@ def _clean_part(data, name="<unknown>"):
if isinstance(data, np.ndarray) and data.ndim == 2 and \
data.dtype == object and isinstance(data[0, 0], np.ndarray):
# Data is already in the right format
return data
out = data
elif isinstance(data, ndarray) and data.ndim == 3 and \
isinstance(data[0, 0, 0], valid_types):
out = np.empty(data.shape[0:2], dtype=np.ndarray)
Expand Down Expand Up @@ -1995,15 +1995,26 @@ def _clean_part(data, name="<unknown>"):
"The numerator and denominator inputs must be scalars or vectors "
"(for\nSISO), or lists of lists of vectors (for SISO or MIMO).")

# Check for coefficients that are ints and convert to floats
# Check for real numeric coefficients and normalize floating arrays
for i in range(out.shape[0]):
for j in range(out.shape[1]):
for k in range(len(out[i, j])):
if isinstance(out[i, j][k], (int, np.integer)):
out[i, j][k] = float(out[i, j][k])
elif isinstance(out[i, j][k], unsupported_types):
coefficients = np.asarray(out[i, j])
convert_to_float = np.issubdtype(coefficients.dtype, np.floating)
if np.iscomplexobj(coefficients):
real_coefficients = coefficients.real
zero_tol = 1000 * np.finfo(float).eps * max(
1, np.max(np.abs(real_coefficients)))
if np.any(np.abs(coefficients.imag) > zero_tol):
raise TypeError(
f"unsupported data type: {type(out[i, j][k])}")
f"unsupported data type: {type(coefficients.flat[0])}")
coefficients = real_coefficients
convert_to_float = True
for k in range(len(coefficients)):
if isinstance(coefficients[k], unsupported_types):
raise TypeError(
f"unsupported data type: {type(coefficients[k])}")
out[i, j] = np.asarray(
coefficients, dtype=float) if convert_to_float else coefficients
return out


Expand Down