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tryTests.asv
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tryTests.asv
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clear;
clc;
%t tests for TRY
numSamples=60;
load('tryCompareRestCue.mat',"tryBatch");
restMeanTime=tryBatch{1};
restStdTime=tryBatch{2};
cueMeanTime=tryBatch{3};
cueStdTime=tryBatch{4};
%% round 1 tests
% tests: Rest vs Cue
% rest1 vs rest2
% cue1 vs cue2
[subs,sessions]=size(cueMeanTime);
%test1: all rest vs all cue
rest=restMeanTime(:);
restsig=restStdTime(:);
cue=cueMeanTime(:);
cuesig=cueStdTime(:);
[h1,p1]=ttest2(cue,rest);
%test2: rest1 vs rest2
[h2,p2]=ttest2(restMeanTime(:,1),restMeanTime(:,2));
%test3: cue1 vs cue2
[h3,p3]=ttest2(cueMeanTime(:,1),cueMeanTime(:,2));
testR2C1=[];
testR1C2=[];
testR1C1=[];
testR2C2=[];
resid1=[];
resid2=[];
presid=[];
%% round 2 tests
%samples = mu + sigma.*randn(numSamples, 1);
ki=1;
X=linspace(1,numSamples,numSamples);
n=1; %order of model
for ki=1:subs
% initialize means
sess1c=cueMeanTime(ki,1);
sess1r=restMeanTime(ki,1);
sess2c=cueMeanTime(ki,2);
sess2r=restMeanTime(ki,2);
% stdevs
sig1c=cueStdTime(ki,1);
sig1r=restStdTime(ki,1);
sig2c=cueStdTime(ki,2);
sig2r=restStdTime(ki,2);
% generate
s1c = sess1c + sig1c.*randn(numSamples, 1);
s1r = sess1r + sig1r.*randn(numSamples, 1);
s2c = sess2c + sig2c.*randn(numSamples, 1);
s2r = sess2r + sig2r.*randn(numSamples, 1);
% ttests 2
[h21,p21]=ttest2(s1c,s2r);
[h22,p22]=ttest2(s1c,s1r);
[h23,p23]=ttest2(s2c,s2r);
[h24,p24]=ttest2(s2c,s1r);
testR2C1=[testR2C1; p21];
testR1C2=[testR1C2; p24];
testR1C1=[testR1C1; p22];
testR2C2=[testR1C2; p23];
ps1c = polyfit(X,s1c,n);
ps1r = polyfit(X,s1r,n);
ps2c = polyfit(X,s2c,n);
ps2r = polyfit(X,s2r,n);
% apply fitted poly
zs1c = polyval(ps1c,X);
zs1r = polyval(ps1r,X);
zs2c = polyval(ps2c,X);
zs2r = polyval(ps2r,X);
session1=zs1r-zs1c;
session2=zs2r-zs2c;
resid1(ki,:)=session1;
resid2(ki,:)=session2;
[hres,pres]=ttest2(session1,session2);
presid(ki)=pres;
end
tryBatch{5}=testR2C1;
tryBatch{6}=testR1C2;
tryBatch{7}=testR1C1;
tryBatch{8}=testR2C2;
tryBatch{8}=testR2C2;
%save('tryCompareRestCue.mat',"tryBatch");
%% residuals
% regress baseline out of cue
% lmfit each
% remove rest from cue
% plot sess 1 vs sess 2
% residual = data – fit