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: min.m
    path of file: ./repos/mtex/S1Fun/@S1FunHarmonic
    
    the code of the file until where you have to start completion: function [v,x] = min(fun,varargin)
% global, local and pointwise maxima of periodic functions
%
% Syntax
%   [v,pos] = min(sF) % the position where the minimum is atained
%
%   [v,pos] = min(sF,'numLocal',5) % the 5 largest local minima
%
%   sF = min(sF, c) % minimum of a spherical functions and a constant
%   sF = min(sF1, sF2) % minimum of two spherical functions
%   sF = min(sF1, sF2, 'bandwidth', bw) % specify the new bandwidth
%
%   % compute the minimum of a multivariate function along dim
%   sF = min(sFmulti,[],dim)
%
% Input
%  sF, sF1, sF2 - @S1Fun
%  sFmulti - a multivariate @S1Fun

    
function [v,x] = min(fun,varargin)
% global, local and pointwise maxima of periodic functions
%
% Syntax
%   [v,pos] = min(sF) % the position where the minimum is atained
%
%   [v,pos] = min(sF,'numLocal',5) % the 5 largest local minima
%
%   sF = min(sF, c) % minimum of a spherical functions and a constant
%   sF = min(sF1, sF2) % minimum of two spherical functions
%   sF = min(sF1, sF2, 'bandwidth', bw) % specify the new bandwidth
%
%   % compute the minimum of a multivariate function along dim
%   sF = min(sFmulti,[],dim)
%
% Input
%  sF, sF1, sF2 - @S1Fun
%  sFmulti - a multivariate @S1Fun
%  c       - double
%
% Output
%  v   - double
%  pos - double
%
% Options
%  kmax          - number of iterations
%  numLocal      - number of peaks to return
%  startingNodes - double
%  tolerance     - minimum distance between two peaks
%  resolution    - minimum step size 
%  maxStepSize   - maximm step size
%

% pointwise minimum of two functions
if ( nargin > 1 ) && ( isa(varargin{1}, 'S1Fun') )
  f = @(v) min(fun.eval(v), varargin{1}.eval(v));
  v = S1FunHarmonic.quadrature(f);

% pointwise minimum of function and constant
elseif ( nargin > 1 ) && ~isempty(varargin{1}) && ( isa(varargin{1}, 'double') )
  f = @(v) min(fun.eval(v), varargin{1});
  v = S1FunHarmonic.quadrature(f);
  
elseif length(fun) == 1

  [v, x] = steepestDescent(fun, varargin{:});
  
else
  s = size(fun);
  if nargin < 2
    d = find(s ~= 1); % first non-singelton dimension
  else
    d = varargin{2};
  end