close all; 
clear all;
clc
load maldi3class_binned;
% 1-78    : class 1
% 79-150  : class 2
% 151-201 : class 3

sample_tr = [Y(:,1:30) Y(:,151:180)];
label_tr = [labels(1:30) labels(151:180)];

sample_pr = [Y(:,31:78) Y(:,181:201)];
label_pr = [labels(31:78) labels(181:201)];

% Baseline correction Training dataset
Y = sample_tr;

YB1 = msbackadj(MZ,Y,'QUANTILEVALUE',0,'WINDOWSIZE',50,'STEPSIZE',50,...
    'REGRESSIONMETHOD','spline','SMOOTHMETHOD','rlowess');
YB2 = msbackadj(MZ,YB1,'QUANTILEVALUE',0,'WINDOWSIZE',50,'STEPSIZE',50,...
    'REGRESSIONMETHOD','spline','SMOOTHMETHOD','rlowess');
YB_tr = msbackadj(MZ,YB2,'QUANTILEVALUE',0,'WINDOWSIZE',50,'STEPSIZE',50,...
    'REGRESSIONMETHOD','spline','SMOOTHMETHOD','rlowess');

% Normalization Training dataset (AUC)
[YN_tr P] = msnorm(MZ,YB_tr,'MAX',100);

% Baseline correction Prediction dataset
YB3 = msbackadj(MZ,sample_pr,'QUANTILEVALUE',0,'WINDOWSIZE',50,'STEPSIZE',50,...
    'REGRESSIONMETHOD','spline','SMOOTHMETHOD','rlowess');
YB4 = msbackadj(MZ,YB3,'QUANTILEVALUE',0,'WINDOWSIZE',50,'STEPSIZE',50,...
    'REGRESSIONMETHOD','spline','SMOOTHMETHOD','rlowess');
YB_pr = msbackadj(MZ,YB4,'QUANTILEVALUE',0,'WINDOWSIZE',50,'STEPSIZE',50,...
    'REGRESSIONMETHOD','spline','SMOOTHMETHOD','rlowess');

% Normalization Prediction dataset(AUC)
YN_pr  = msnorm(MZ,YB_pr,P);

sample_tr = YN_tr;
sample_pr = YN_pr;

save casecirr_3030_prepro sample_tr label_tr sample_pr label_pr MZ P