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_vb_ppm_anova.m
    path of file: ./repos/spm
    
    the code of the file until where you have to start completion: function spm_vb_ppm_anova(SPM)
% Bayesian ANOVA using model comparison
% FORMAT spm_vb_ppm_anova(SPM)
%
% SPM    -  Data structure corresponding to a full model (ie. one
%           containing all experimental conditions).
%           
% This function creates images of differences in log evidence
% which characterise the average effect, main effects and interactions
% in a factorial design. 
%
% The factorial design is specified in SPM.factor. For a one-way ANOVA 
% the images 
%
%   avg_effect.<ext>
%   main_effect.<ext>
%
% are produced. For a two-way ANOVA the following images are produced
%

    
function spm_vb_ppm_anova(SPM)
% Bayesian ANOVA using model comparison
% FORMAT spm_vb_ppm_anova(SPM)
%
% SPM    -  Data structure corresponding to a full model (ie. one
%           containing all experimental conditions).
%           
% This function creates images of differences in log evidence
% which characterise the average effect, main effects and interactions
% in a factorial design. 
%
% The factorial design is specified in SPM.factor. For a one-way ANOVA 
% the images 
%
%   avg_effect.<ext>
%   main_effect.<ext>
%
% are produced. For a two-way ANOVA the following images are produced
%
%   avg_effect.<ext>
%   main_effect_'factor1'.<ext>
%   main_effect_'factor2'.<ext>
%   interaction.<ext>
%
% These images can then be thresholded. For example a threshold of 4.6 
% corresponds to a posterior effect probability of [exp(4.6)] = 0.999. 
% See paper VB4 for more details.
%__________________________________________________________________________

% Will Penny
% Copyright (C) 2005-2022 Wellcome Centre for Human Neuroimaging


if numel(SPM.Sess) > 1
    warning('spm_vb_ppm_anova only works for single session data.');
end

model = spm_vb_models(SPM,SPM.factor);

analysis_dir = pwd;
for m=1:length(model)-1
    model_subdir = ['model_',int2str(m)];
    mkdir(analysis_dir,model_subdir);
    SPM.swd = fullfile(analysis_dir,model_subdir);
    SPM.Sess(1).U = model(m).U;
    SPM.Sess(1).U = spm_get_ons(SPM,1);
    SPM = spm_fMRI_design(SPM,0); % 0 = don't save SPM.mat
    SPM.PPM.update_F = 1; % Compute evidence for each model
    SPM.PPM.compute_det_D = 1; 
    spm_spm_vb(SPM);
end