splinepy.utils.data.make_matrix#
- splinepy.utils.data.make_matrix(values, supports, n_cols, as_array=False)[source]#
Create a matrix from values and supports.
Used for basis functions their derivatives and everything mapped. Uses scipy if available. If as_array is true, dense matrix (numpy) is enforced
This matrix can be used for approximations and IGA-applications. With given queries \(\pmb{\xi}\), control points \(\mathbf{C}\), associated to spline \(\mathcal{S}\), this function can be used to return matrix \(\mathbf{A}\), such that
\[\mathcal{S}(\pmb{\xi}) = A(\pmb{\xi}) \cdot \mathbf{C}\]- Parameters:
values (np.ndarray) – Values to be inserted into the matrix
supports (np.ndarray) – Column values corresponding to the given values
n_cols (int) – Number of columns of the matrix (matches n_ctps for basis-functions)
as_array (bool) – Return as numpy / dense type
- Returns:
matrix – Matrix
- Return type:
np.ndarray / scipy.sparse.csr_array