function varargout = spm_bsplins(varargin)
% Sample a volume using B-spline interpolation - a compiled routine
% FORMAT [f,dfx,dfy,dfz] = spm_bsplins(c,x,y,z,d)
%   c - volume of B-spline coefficients (from spm_bsplinc)
%   x,y,z - coordinates of sampled points
%       d(1:3) - degree of B-spline (from 0 to 7) along different dimensions
%                - these must be same as used by spm_bsplinc
%       d(4:6) - 1/0 to indicate wrapping along the dimensions
%   f - sampled data
%   dfx,dfy,dfz - sampled first derivatives
%
% This function takes B-spline basis coefficients from spm_bsplinc,
% and re-convolves them with B-splines centred at the new sample points.
%
% Note that nearest neighbour interpolation is used instead of 0th
% degree B-splines, and the derivatives of trilinear interpolation are
% returned instead of those of 1st degree B-splines.  The difference is
% extremely subtle.
%__________________________________________________________________________
%
% References:
%   M. Unser, A. Aldroubi and M. Eden.
%   "B-Spline Signal Processing: Part I-Theory,"
%   IEEE Transactions on Signal Processing 41(2):821-832 (1993).
%
%   M. Unser, A. Aldroubi and M. Eden.
%   "B-Spline Signal Processing: Part II-Efficient Design and
%   Applications,"
%   IEEE Transactions on Signal Processing 41(2):834-848 (1993).
%
%   M. Unser.
%   "Splines: A Perfect Fit for Signal and Image Processing,"
%   IEEE Signal Processing Magazine, 16(6):22-38 (1999)
%
%   P. Thevenaz and T. Blu and M. Unser.
%   "Interpolation Revisited"
%   IEEE Transactions on Medical Imaging 19(7):739-758 (2000).
%__________________________________________________________________________

% John Ashburner
% Copyright (C) 2001-2022 Wellcome Centre for Human Neuroimaging


%-This is merely the help file for the compiled routine
error('spm_bsplins.c not compiled - see Makefile');
