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feat: add include_bias option to Polynomial basis function #193 #197

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feat: add include_bias option to Polynomial basis function #193 #197

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9 changes: 9 additions & 0 deletions sysidentpy/basis_function/_polynomial.py
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Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,8 @@ class Polynomial(BaseBasisFunction):
----------
degree : int (max_degree), default=2
The maximum degree of the polynomial features.
include_bias : bool, default=True
Whether to include the bias (constant) term in the output feature matrix.

Notes
-----
Expand All @@ -37,8 +39,10 @@ class Polynomial(BaseBasisFunction):
def __init__(
self,
degree: int = 2,
include_bias: bool = True,
):
self.degree = degree
self.include_bias = include_bias

def fit(
self,
Expand Down Expand Up @@ -94,6 +98,11 @@ def fit(
]
)
psi = psi[max_lag:, :]

if self.include_bias:
bias_column = np.ones((psi.shape[0], 1))
psi = np.hstack((bias_column, psi))

return psi

def transform(
Expand Down
32 changes: 27 additions & 5 deletions sysidentpy/basis_function/tests/test_basis_functions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,29 @@


def test_fit_polynomial():
basis_function = Polynomial(degree=2)
basis_function = Polynomial(degree=2, include_bias=True)
data = np.array(([1, 1, 1], [2, 3, 4], [3, 3, 3]))
max_lag = 1
output = np.array([[1, 4, 6, 8, 9, 12, 16], [1, 9, 9, 9, 9, 9, 9]])

r = basis_function.fit(data=data, max_lag=max_lag)

assert_array_equal(output, r)


def test_fit_polynomial_with_bias():
basis_function = Polynomial(degree=2, include_bias=True)
data = np.array(([1, 1, 1], [2, 3, 4], [3, 3, 3]))
max_lag = 1
output = np.array([[1, 4, 6, 8, 9, 12, 16], [1, 9, 9, 9, 9, 9, 9]])

r = basis_function.fit(data=data, max_lag=max_lag)

assert_array_equal(output, r)


def test_fit_polynomial_without_bias():
basis_function = Polynomial(degree=2, include_bias=False)
data = np.array(([1, 1, 1], [2, 3, 4], [3, 3, 3]))
max_lag = 1
output = np.array([[4, 6, 8, 9, 12, 16], [9, 9, 9, 9, 9, 9]])
Expand All @@ -16,11 +38,11 @@ def test_fit_polynomial():


def test_fit_polynomial_predefined():
basis_function = Polynomial(degree=2)
basis_function = Polynomial(degree=2, include_bias=True)
data = np.array(([1, 1, 1], [2, 3, 4], [3, 3, 3]))
max_lag = 1
predefined_regressors = np.array([0, 2, 4])
output = np.array([[4, 8, 12], [9, 9, 9]])
output = np.array([[1, 4, 8, 12], [1, 9, 9, 9]])

r = basis_function.fit(
data=data, max_lag=max_lag, predefined_regressors=predefined_regressors
Expand All @@ -30,10 +52,10 @@ def test_fit_polynomial_predefined():


def test_transform_polynomial():
basis_function = Polynomial(degree=2)
basis_function = Polynomial(degree=2, include_bias=True)
data = np.array(([1, 1, 1], [2, 3, 4], [3, 3, 3]))
max_lag = 1
output = np.array([[4, 6, 8, 9, 12, 16], [9, 9, 9, 9, 9, 9]])
output = np.array([[1, 4, 6, 8, 9, 12, 16], [1, 9, 9, 9, 9, 9, 9]])

r = basis_function.transform(data=data, max_lag=max_lag)

Expand Down