`scipy.interpolate._bsplines:_handle_lhs_derivatives`

Signature

def _handle_lhs_derivatives(t, k, xval, ab, kl, ku, deriv_ords, offset = 0)

Fill in the entries of the colocation matrix corresponding to known derivatives at xval.

The colocation matrix is in the banded storage, as prepared by _coloc. No error checking.

t : ndarray, shape (nt + k + 1,): knots
k : int: B-spline order
xval : float: The value at which to evaluate the derivatives at.
ab : ndarray, shape(2*kl + ku + 1, nt), Fortran order: B-spline colocation matrix. This argument is modified in-place.
kl : int: Number of lower diagonals of ab.
ku : int: Number of upper diagonals of ab.
deriv_ords : 1D ndarray: Orders of derivatives known at xval
offset : int, optional: Skip this many rows of the matrix ab.