`scipy.interpolate._ndbspline:make_ndbspl`

Signature

def make_ndbspl(points, values, k = 3, *, solver = <function gcrotmk at 0x0000>, **solver_args)

Construct an interpolating NdBspline.

points : tuple of ndarrays of float, with shapes (m1,), ... (mN,): The points defining the regular grid in N dimensions. The points in each dimension (i.e. every element of the points tuple) must be strictly ascending or descending.
values : ndarray of float, shape (m1, ..., mN, ...): The data on the regular grid in n dimensions.
k : int, optional: The spline degree. Must be odd. Default is cubic, k=3
solver : a `scipy.sparse.linalg` solver (iterative or direct), optional.: An iterative solver from scipy.sparse.linalg or a direct one, sparse.sparse.linalg.spsolve. Used to solve the sparse linear system design_matrix @ coefficients = rhs for the coefficients. Default is scipy.sparse.linalg.gcrotmk
solver_args : dict, optional: Additional arguments for the solver. The call signature is solver(csr_array, rhs_vector, **solver_args)

Boundary conditions are not-a-knot in all dimensions.