You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: spm_affreg.m
    path of file: ./repos/malini/Codes/deconvolution - model/spm8
    
    the code of the file until where you have to start completion: function [M,scal] = spm_affreg(VG,VF,flags,M,scal)
% Affine registration using least squares.
% FORMAT [M,scal] = spm_affreg(VG,VF,flags,M0,scal0)
%
% VG        - Vector of template volumes.
% VF        - Source volume.
% flags     - a structure containing various options.  The fields are:
%             WG       - Weighting volume for template image(s).
%             WF       - Weighting volume for source image
%                        Default to [].
%             sep      - Approximate spacing between sampled points (mm).
%                        Defaults to 5.
%             regtype  - regularisation type.  Options are:
%                        'none'  - no regularisation
%                        'rigid' - almost rigid body
%
    
function error_message
% Display an error message for when things go wrong.
str = { 'There is not enough overlap in the images',...
    'to obtain a solution.',...
    ' ',...
    'Please check that your header information is OK.',...
    'The Check Reg utility will show you the initial',...
    'alignment between the images, which must be',...
    'within about 4cm and about 15 degrees in order',...
    'for SPM to find the optimal solution.'};
spm('alert*',str,mfilename,sqrt(-1));
error('insufficient image overlap')
%_______________________________________________________________________

%_______________________________________________________________________
function piccies(VF,VG,M,scal)
% This is for debugging purposes.
% It shows the linear combination of template images, the affine
% transformed source image, the residual image and a histogram of the
% residuals.
%_______________________________________________________________________

figure(2);
Mt = spm_matrix([0 0 (VG(1).dim(3)+1)/2]);
M  = (M*VF(1).mat)\VG(1).mat;
t  = zeros(VG(1).dim(1:2));
for i=1:length(VG);
    t  = t + spm_slice_vol(VG(i),  Mt,VG(1).dim(1:2),1)*scal(i);
end