function x=clean_data(data,CrtSTD,CrtCONV)
%Written by Valentin Chabaud. v3 - August 2015 NTNU
%Removes erroneous values and outsiders from time series

% GLORIA COMMENT:
% Increase CrtSTD a bit if small variations in the good data, typically yaw, sway, surge.
% Start with for example: 
% crtstd=8; this is clean data setting: Increase for more sensitivity, doublecheck by comparing with original 
% Crtconv=0.001;
% data = needs to be a 1*n row vector 

x=data';
sx=std(x);
mx=mean(x);
d=diff(x);
sd=std(d);
d=[d;d(end)];
% figure(3)
% plot([data';d])
std_prev=std(x)/CrtSTD;
N=10;
while abs((std(x)-std_prev)/std_prev)>CrtCONV
flag=0;
ind=[];
for i=1:length(x)
if abs(x(i)-mx)>sx*CrtSTD || abs(d(i))>sd*CrtSTD || abs(d(i))<sd/CrtSTD*0.1
if flag==0
flag=1;
ind=[ind;[i 0]];
end
else
if flag==1
ind(end,2)=i;
flag=0;
end
end
end
if(ind(end,end))==0
ind(end,end)=length(x);
end
y=[ones(N,1)*x(1);x;ones(N,1)*x(end)];
for i=1:size(ind,1)
inttot=(1:length(y))';
intrem=ind(i,1)+N:ind(i,2)+N;
intfit=setdiff(inttot,intrem);
z=y(intfit);
% f = fit(intfit, z, 'smoothingspline','SmoothingParam',0.1);
% y(intrem)=feval(f,intrem);
y(intrem)=interp1(intfit,y(intfit),intrem);
x=y(N+(1:length(x)));
end
std_prev=std(x);
end
x=x';