plscmd_readme.txt

来自「国外的一个PLStoolbox,主要用于处理图象,也可以用来回归,欢迎使用」· 文本 代码 · 共 58 行

%  This document provides some simple guidelines for command-line PLS usage:
%
%  Usage: result = pls_analysis(datamat_lst, num_subj_lst, num_cond);
%	For details of input/output parameters, type: help pls_analysis
%
===========================================================================


%  Usually, the first thing to be checked is singular value, and
%  the percentage of eigenvalue. If the percentage is very low for 
%  certain LVs, simply discard those LVs
%
figure; bar(result.s);			% display singular value bar graph
pct=(result.s.^2/sum(result.s.^2));	% calculate eigenvalue percentage
figure; bar(pct);			% notice that sum(pct) should be 1


%  If permutation loop is applied, you can also check whether those LVs
%  can be trust by plot bar graph of the probability of permuted values
%  greater than observed values. If for certain LVs, the chance of permuted
%  values greater than observed values are very large, you also need to
%  discard those LVs
%
figure; bar(result.perm_result.sprob);


%  Next, for Task PLS, the outlier subjects should be checked for each
%  meaningful LV. If there is any outlier subjects, you may want to 
%  reconsider if you want to keep them or remove them. If you decide 
%  to remove them, you will have to run analysis again without those 
%  subjects.
%
LV = 1;					% just an example. can be 2,3, ...
figure; plot(result.vsc(:,LV),result.usc(:,LV),'*');


%  You also need to render the active area map "result.u" depending on
%  whether your data is a brain image or a brain wave. If it is a 
%  brain image, you must have a brain coordinates and dimensions handy.
%  Simply create a brain and put the result.u into the brain, and
%  then render the brain.


%  For Task PLS, Design LV can help you to interpret which condition
%  is distinguished by which LV
%
LV = 1;					% just an example. can be 2,3, ...
figure; bar(result.v(:,1));


%  If the bootstrap is applied, you can find which active area indicated
%  by result.u is reliable. Let's use 95 percentile as threshold, we can
%  find out the indices of the brain coordinate that are stable.
%
thresh = percentile(result.boot_result.compare_u(:,1), 95)
idx = find(abs(result.boot_result.compare_u(:,1)) > thresh);