API¶
Creation routines
Routines for creating NDSpline
objects.
make_lsq_spline (x, y, knots, degrees[, w, …]) |
Construct a least squares regression B-spline. |
make_interp_spline (x, y[, degrees]) |
Construct an interpolating B-spline. |
make_interp_spline_from_tidy (tidy_data, …) |
Construct an interpolating B-spline from a tidy data source. |
from_file (file) |
Create a NDSpline object from a NumPy archive containing the necessary attributes. |
Class methods
Methods of the NDSpline class.
NDSpline (knots, coefficients, degrees[, …]) |
Multivariate tensor-product spline in the B-spline basis. |
__call__ (x[, nus]) |
Evaluate the N-dimensional B-spline. |
derivative (dim[, nu]) |
Return NDSpline representing the nu-th derivative in the dim-th dimension. |
antiderivative (dim[, nu]) |
Return NDSpline representing the nu-th antiderivative in the dim-th dimension. |
to_file (file[, compress]) |
Save attributes of NDSpline object to binary file in NumPy .npz format so that the object can be re-created. |
copy () |
Return a deep copy of this NDSpline object. |
__eq__ (other) |
Check equality with another spline. |
allocate_workspace_arrays (num_points) |
Allocate workspace arrays for the N-dimensional B-spline evaluation. |
compute_basis_coefficient_selector (x[, nus]) |
Evaluate the N-dimensional B-spline basis functions and coefficient selectors. |
Knots
Utility function for constructing knot arrays.
_not_a_knot (x, k[, left, right]) |
Utility function to perform the knot portion of the not-a-knot procedure. |
Implementations
Selection and usage of the Cython or NumPy implementations for B-Spline evaluation.
set_impl (name) |
Set bspl implementation to either cython or numpy. |
_bspl |
Cython implementation for evaluating B-splines. |
_npy_bspl |
NumPy implementation for evaluating B-splines. |