www.pudn.com > maldicode.zip > dQuantifyNormals.m

 
%% 
close all; clear all;clc 
load maldi3class_binned 
load casecirr_3030_prepro 
load casecirr_249wind 
 
% 1-78    : class 1 
% 79-150  : class 2 
% 151-201 : class 3 
 
normals = Y(:,79:150) ; 
 
%% BASELINE CORRECT and NORMALIZE NORMALS (CONTROLS) 
Y = normals; 
 
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 = msbackadj(MZ,YB2,'QUANTILEVALUE',0,'WINDOWSIZE',50,'STEPSIZE',50,... 
    'REGRESSIONMETHOD','spline','SMOOTHMETHOD','rlowess'); 
 
% Normalization of Normals using parameters used to normalize case and 
% cirrhosis 
YN_Norm  = msnorm(MZ,YB,P); 
 
%% QUANTIFY PEAKS IN CONTROLS 
 
m  = size(YN_Norm,2); 
 
% TAKE THE MAXIMUM OF THE INTENSITIES IN THE IDENTIFIED WINDOW 
 
sample = YN_Norm; 
max_win = []; 
for i = 1: length(win_tick) 
    if win_tick(i,1) == win_tick(i,2) 
        a=sample(win_tick(i,1),:); 
    else 
        a = max(sample(win_tick(i,1):win_tick(i,2),: )); % sum/max 
    end 
    max_win = [max_win;  a]; 
end 
 
YNorm = max_win; 
 
save  Controls72 YNorm windows;