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_preproc_bandstopfilter.m
    path of file: ./repos/bspm/thirdparty/MRtools_2015-08-21/Utilities
    
    the code of the file until where you have to start completion: function [filt] = ft_preproc_bandstopfilter(dat,Fs,Fbp,N,type,dir,instabilityfix)

% FT_PREPROC_BANDSTOPFILTER applies a band-stop filter to the data and thereby
% removes the spectral components in the specified frequency band
%
% Use as
%   [filt] = ft_preproc_bandstopfilter(dat, Fsample, Fbp, N, type, dir, instabilityfix)
% where
%   dat        data matrix (Nchans X Ntime)
%   Fsample    sampling frequency in Hz
%   Fbp        frequency band, specified as [Fhp Flp]
%   N          optional filter order, default is 4 (but) or dependent upon
%              frequency band and data length (fir/firls)
%   type       optional filter type, can be
%                'but' Butterworth IIR filter (default)
%                'fir' FIR filter using Matlab fir1 function
%                'firls' FIR filter using Matlab firls function (requires Matlab Signal Processing Toolbox)
%                'brickwall' Frequency-domain filter using Matlab FFT and iFFT function
%   dir        optional filter direction, can be
%                'onepass'         forward filter only
%                'onepass-reverse' reverse filter only, i.e. backward in time
%                'twopass'         zero-phase forward and reverse filter (default)
%                'twopass-reverse' zero-phase reverse and forward filter
%                'twopass-average' average of the twopass and the twopass-reverse
%   instabilityfix optional method to deal with filter instabilities
%                'no'       only detect and give error (default)
%                'reduce'   reduce the filter order
%                'split'    split the filter in two lower-order filters, apply sequentially
%
% Note that a one- or two-pass filter has consequences for the
% strength of the filter, i.e. a two-pass filter with the same filter
% order will attenuate the signal twice as strong.
%
% Further note that the filter type 'brickwall' filters in the frequency domain,
% but may have severe issues. For instance, it has the implication that the time
% domain signal is periodic. Another issue pertains to that frequencies are
% not well defined over short time intervals; particularly for low frequencies.
%
% See also PREPROC

% Copyright (c) 2003-2013, Robert Oostenveld, Arjen Stolk
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% for the documentation and details.
%
% 
    
function
%                'firls' FIR filter using Matlab firls function (requires Matlab Signal Processing Toolbox)
%                'brickwall' Frequency-domain filter using Matlab FFT and iFFT function
%   dir        optional filter direction, can be
%                'onepass'         forward filter only
%                'onepass-reverse' reverse filter only, i.e. backward in time
%                'twopass'         zero-phase forward and reverse filter (default)
%                'twopass-reverse' zero-phase reverse and forward filter
%                'twopass-average' average of the twopass and the twopass-reverse
%   instabilityfix optional method to deal with filter instabilities
%                'no'       only detect and give error (default)
%                'reduce'   reduce the filter order
%                'split'    split the filter in two lower-order filters, apply sequentially
%
% Note that a one- or two-pass filter has consequences for the
% strength of the filter, i.e. a two-pass filter with the same filter
% order will attenuate the signal twice as strong.
%
% Further note that the filter type 'brickwall' filters in the frequency domain,
% but may have severe issues. For instance, it has the implication that the time
% domain signal is periodic. Another issue pertains to that frequencies are
% not well defined over short time intervals; particularly for low frequencies.
%
% See also PREPROC

% Copyright (c) 2003-2013, Robert Oostenveld, Arjen Stolk
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% for the documentation and details.
%
%    FieldTrip is free software: you can redistribute it and/or modify
%    it under the terms of the GNU General Public License as published by
%    the Free Software Foundation, either version 3 of the License, or
%    (at your option) any later version.
%
%    FieldTrip is distributed in the hope that it will be useful,
%    but WITHOUT ANY WARRANTY; without even the implied warranty of
%    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
%    GNU General Public License for more details.
%
%    You should have received a copy of the GNU General Public License
%    along with FieldTrip. If not, see <http://www.gnu.org/licenses/>.
%
% $Id: ft_preproc_bandstopfilter.m 8335 2013-07-29 10:09:23Z arjsto $

% determine the size of the data
[nchans, nsamples] = size(dat);

% set the default filter order later
if nargin<4 || isempty(N)
  N = [];
end