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: lintest.m
    path of file: ./repos/SuiteSparse/MATLAB_Tools/LINFACTOR
    
    the code of the file until where you have to start completion: function lintest (A,b)
%LINTEST test A*x=b, using linfactor, x=A\b, and (ack!) the explicit inv(A).
% The results printed include the breakeven point, which is the number of
% systems Ax=b that must be solved with the same A but different b for the
% inv(A) method to be faster than linfactor.  Using inv(A) is always
% numerically dubious, and typically slower.  However because of MATLAB's
% interpretive overhead, linfactor can be slightly slower in its
% forward/backsolves.  A true linfactor mexFunction would probably be just as
% fast as inv(A)*b when A is full.  You should never ever use inv(A) to solve
% a linear system.
%
% Example:
%   load west0479
%   b = rand (size (west0479,1), 1) ;
%   lintest (west0479, b) ;
%
% See also linfactor, lintests, mldivide

% LINFACTOR, Copyright (c) 2008, Timothy A Davis. All Rights Reserved.
% SPDX-License-Identifier: BSD-3-clause

%-------------------------------------------------------------------------------
% warmup, to make sure functions are loaded, for accurate timings
%-------------------------------------------------------------------------------

F = linfactor (1) ;
x = linfactor (F, 1) ;                                                      %#ok
F = linfactor (sparse (1)) ;
x = linfactor (F, 1) ;                                                      %#ok
F = linfactor (sparse (-1)) ;
x = linfactor (F, 1) ;                                                      %#ok
S = inv (1) ;
x = S*1 ;                                                                   %#ok
S = inv (sparse (1)) ;
x = S*1 ;                                                                   %#ok
S = inv (sparse (-1)) ;
x = S*1 ;                                                                   %#ok
x = rand (2) \ rand (2,1) ;                                                 %#ok
x = sparse (rand (2)) \ rand (2,1) ;                                        %#ok
clear x F S


    
function lintest (A,b)
%LINTEST test A*x=b, using linfactor, x=A\b, and (ack!) the explicit inv(A).
% The results printed include the breakeven point, which is the number of
% systems Ax=b that must be solved with the same A but different b for the
% inv(A) method to be faster than linfactor.  Using inv(A) is always
% numerically dubious, and typically slower.  However because of MATLAB's
% interpretive overhead, linfactor can be slightly slower in its
% forward/backsolves.  A true linfactor mexFunction would probably be just as
% fast as inv(A)*b when A is full.  You should never ever use inv(A) to solve
% a linear system.
%
% Example:
%   load west0479
%   b = rand (size (west0479,1), 1) ;
%   lintest (west0479, b) ;
%
% See also linfactor, lintests, mldivide

% LINFACTOR, Copyright (c) 2008, Timothy A Davis. All Rights Reserved.
% SPDX-License-Identifier: BSD-3-clause

%-------------------------------------------------------------------------------
% warmup, to make sure functions are loaded, for accurate timings
%-------------------------------------------------------------------------------

F = linfactor (1) ;
x = linfactor (F, 1) ;                                                      %#ok
F = linfactor (sparse (1)) ;
x = linfactor (F, 1) ;                                                      %#ok
F = linfactor (sparse (-1)) ;
x = linfactor (F, 1) ;                                                      %#ok
S = inv (1) ;
x = S*1 ;                                                                   %#ok
S = inv (sparse (1)) ;
x = S*1 ;                                                                   %#ok
S = inv (sparse (-1)) ;
x = S*1 ;                                                                   %#ok
x = rand (2) \ rand (2,1) ;                                                 %#ok
x = sparse (rand (2)) \ rand (2,1) ;                                        %#ok
clear x F S

%-------------------------------------------------------------------------------
% linfactor
%-------------------------------------------------------------------------------

% do this several times for accurate timings
t1 = 0 ;
trials = 0 ;
while (t1 < 1)
    [F, t] = linfactor (A) ;                % factorize A
    t1 = t1 + t ;
    trials = trials + 1 ;
end