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-rw-r--r--polymatrix/polymatrix/impl.py2
-rw-r--r--polymatrix/polymatrix/init.py2
-rw-r--r--polymatrix/polymatrix/mixins.py20
3 files changed, 11 insertions, 13 deletions
diff --git a/polymatrix/polymatrix/impl.py b/polymatrix/polymatrix/impl.py
index 85f56bf..2ac4dc0 100644
--- a/polymatrix/polymatrix/impl.py
+++ b/polymatrix/polymatrix/impl.py
@@ -19,7 +19,7 @@ class BroadcastPolyMatrixImpl(BroadcastPolyMatrixMixin):
@dataclassabc.dataclassabc(frozen=True)
class PolyMatrixAsAffineExpressionImpl(PolyMatrixAsAffineExpressionMixin):
- data: PolyMatrixAsAffineExpressionMixin.MatrixType
+ affine_coefficients: PolyMatrixAsAffineExpressionMixin.MatrixType
shape: tuple[int, int]
slices: dict[MonomialIndex, PolyMatrixAsAffineExpressionMixin.MatrixType]
degree: int
diff --git a/polymatrix/polymatrix/init.py b/polymatrix/polymatrix/init.py
index 6fcdcb1..332977e 100644
--- a/polymatrix/polymatrix/init.py
+++ b/polymatrix/polymatrix/init.py
@@ -79,4 +79,4 @@ def to_affine_expression(p: PolyMatrixMixin) -> PolyMatrixAsAffineExpressionMixi
max_degree = max(m.degree for m in slices.keys())
return PolyMatrixAsAffineExpressionImpl(
- data=data, shape=p.shape, slices=slices, degree=max_degree)
+ affine_coefficients=data, shape=p.shape, slices=slices, degree=max_degree)
diff --git a/polymatrix/polymatrix/mixins.py b/polymatrix/polymatrix/mixins.py
index ce6d09b..c7a1b00 100644
--- a/polymatrix/polymatrix/mixins.py
+++ b/polymatrix/polymatrix/mixins.py
@@ -177,6 +177,11 @@ class PolyMatrixAsAffineExpressionMixin(
where each matrix :math:`A_\alpha \in \mathbf{R}^{n\times m}`. In the
context of this class we will call the :math:`A_\alpha` matrices
`affine coefficients`.
+
+ **Note:** In the example above, all monomials powers upt to degree 2 are
+ present, however in general some monomials may be missing. In that case
+ this class does not store those as they are all zeros. See also the code of
+ :py:meth:`affine_coefficient`.
"""
# Type of matrix that stores affifne coefficients
@@ -186,7 +191,7 @@ class PolyMatrixAsAffineExpressionMixin(
@property
@abc.abstractmethod
- def data(self) -> MatrixType:
+ def affine_coefficients(self) -> MatrixType:
r"""
The big matrix that store all :math:`A_\alpha` matrices:
@@ -197,9 +202,8 @@ class PolyMatrixAsAffineExpressionMixin(
\in
\mathbf{R}^{n \times mN},
\quad
- N = \sum_{k = 0}^d {q + k \choose k}
+ N \leq \sum_{k = 0}^d {q + k \choose k}
"""
- ...
@property
@abc.abstractmethod
@@ -344,12 +348,6 @@ class PolyMatrixAsAffineExpressionMixin(
# Sort the values by monomial index, which have a total order
return dict(sorted(monomial_values.items()))
- def affine_coefficients(self) -> MatrixType:
- r"""
- Get the large matrix
- :math:`A = \begin{bmatrix} A_{\alpha_1} & A_{\alpha_2} & \cdots & A_{\alpha_N} \end{bmatrix}`
- """
- return self.data
def affine_coefficient(self, monomial: MonomialIndex) -> MatrixType:
r""" Get the affine coefficient :math:`A_\alpha` associated to :math:`x^\alpha`. """
@@ -358,7 +356,7 @@ class PolyMatrixAsAffineExpressionMixin(
return np.zeros((nrows, 1))
columns = range(*self.slices[monomial])
- return self.data[:, columns]
+ return self.affine_coefficients[:, columns]
def affine_coefficients_by_degrees(self) -> Iterable[tuple[int, MatrixType]]:
"""
@@ -418,7 +416,7 @@ class PolyMatrixAsAffineExpressionMixin(
# Evaluate the affine expression
_, ncols = self.shape
- return self.data @ (np.kron(mvalues, np.eye(ncols)).T)
+ return self.affine_coefficients @ (np.kron(mvalues, np.eye(ncols)).T)
def affine_eval_fn(self) -> Callable[[MatrixType], MatrixType]:
r"""