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: ft_prepare_vol_sens.m
    path of file: ./repos/bspm/thirdparty/spm12/external/fieldtrip/forward
    
    the code of the file until where you have to start completion: function [headmodel, sens] = ft_prepare_vol_sens(headmodel, sens, varargin)

% FT_PREPARE_VOL_SENS does some bookkeeping to ensure that the volume
% conductor model and the sensor array are ready for subsequent forward
% leadfield computations. It takes care of some pre-computations that can
% be done efficiently prior to the leadfield calculations.
%
% Use as
%   [headmodel, sens] = ft_prepare_vol_sens(headmodel, sens, ...)
% with input arguments
%   headmodel  structure with volume conductor definition
%   sens       structure with gradiometer or electrode definition
%
% The headmodel structure represents a volume conductor model of the head,
% its contents depend on the type of model. The sens structure represents a
% sensor array, i.e. EEG electrodes or MEG gradiometers.
%
% Additional options should be specified in key-va
    
function Ppr = pointproj(P,plane)
% projects a point on a plane
% plane(1:3) is a point on the plane
% plane(4:6) is the ori of the plane
Ppr  = [];
ori  = plane(4:6);
line = [P ori];
% get indices of line and plane which are parallel
par = abs(dot(plane(4:6), line(:,4:6), 2))<1e-14;
% difference between origins of plane and line
dp = plane(1:3) - line(:, 1:3);
% Divide only for non parallel vectors (DL)
t = dot(ori(~par,:), dp(~par,:), 2)./dot(ori(~par,:), line(~par,4:6), 2);
% compute coord of intersection point
Ppr(~par, :) = line(~par,1:3) + repmat(t,1,3).*line(~par,4:6);

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function serves as a replacement for the dist function in the Neural
% Networks toolbox.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [d] = dist(x)
n = size(x,2);
d = zeros(n,n);
for i=1:n
  for j=(i+1):n
    d(i,j) = sqrt(sum((x(:,i)-x(:,j)).^2));
    d(j,i) = d(i,j);
  end