Evaluation of B-spline basis functions

Old implementation of Jacobian

* Get table of samples x-values, * i.e. table[i][j] is the value of variable i at sample j */

* Checks that the hessian is symmetric across the diagonal */

Setters

* The B-spline domain is the half-open domain [ knots.first(), knots.end() ). * The hack checks if x is at the right boundary (if x = knots.end()), i

Default constructor

Used to evaluate basis functions - alternative to the recursive deBoorCox

* Find coefficients of B-spline by solving: * min ||A*x - b||^2 + alpha*||R||^2, * where * A = mxn matrix of n basis functions evaluated at m sampl

Computes knot averages: assumes that basis is initialized!

Compute a single knot vector from sample grid and degree

Compute all knot vectors from sample data

Insert knots until all knots have multiplicity degree + 1. This ensures that the polynomial pieces are not overlapping.

NOTE: does not pass tests

* Getters */

* Description of function. */

Getters