Matlab: Measurevaluefilter

Messwertfilter:

Verfahren:

(German) The Matlab function is used to exclude measurevalues with big variation in linear relation and to fit through the remaining values. This works equal to Matlab:errorlines. Therefor you can change the variation to exclude more or less measure values. If there is a measure value with oversized value the function excludes it and fit again a linear relation how in this figure seen:

 

In red the errorbox and excludes measure value.

Implementation:

This function is called in Matlab with:"[x,y,xerr,yerr,xaus,yaus,xerraus,yerraus] = filterfunc(x, y, xerr, yerr, scale, count)". Therefor "xaus,yaus" are the filtered x- and y-values. "x,y,xerr,yerr" are the values you measured.  "Scale" determines how the variation. For (scale = 1) the function takes "yerr".
As follows here are several approaches of this function:

If (count = 1) the function plots a errorbox.

Source code:

function [x,y,xerr,yerr,xaus,yaus,xerraus,yerraus] = filterfunc(x, y, xerr, yerr, scale, count)
%This function filters the values, which are imprecise. 'Scale' is a
%parameter for this imprecise. With 'scale=1' the imprecise is exacly your
%y-error. With count '1' this function plots the errorbox'.
%If the measured point is outside the area, this function will
%take the values out and give it back at 'xaus, yaus, xerraus, yerraus'.


l=numel(x);
if(xerr==0)
    xerr=zeros([l,1]);
endymax=y+scale*yerr
ymin=y-scale*yerr
fitmax=fit(x,ymax,@(a,b,x) a*x+b);
fitmin=fit(x,ymin,@(a,b,x) a*x+b);
fitVal=fit(x,y,@(a,b,x) a*x+b);

%Fit the maximal and the minimal errorlines through the mesured values with
%their deviations.
a=coeffvalues(fitmax);
b=coeffvalues(fitmin);

amax=a(1);
amin=b(1);
bmax=a(2);
bmin=b(2);

xaus=[];
yaus=[];
xerraus=[];
yerraus=[];

yp=x*amax+bmax;
ym=x*amin+bmin;
n=1;
%filter the values with a large imprecision
while(1==1)
    altamax=amax;
    altbmax=bmax;
    altamin=amin;
    altbmin=bmin;
    for i=1:1:l
        if (i>l)
            break;
        end
        if( (y(i)>(yp(i)+yerr(i)*(scale-1))) | (y(i)<(ym(i)-yerr(i)*(scale-1))) )
            xaus(n)=x(i);
            yaus(n)=y(i);
            xerraus(n)=xerr(i);
            yerraus(n)=yerr(i);
            x(i)=[];
            y(i)=[];
            yp(i)=[];
            ym(i)=[];
            xerr(i)=[];
            yerr(i)=[];
            i=i-1;
            l=l-1;
            n=n+1;
        end
    end
    if (numel(x)>1)
        fitmax=fit(x,y+yerr*scale,@(a,b,x) a*x+b);
        fitmin=fit(x,y-yerr*scale,@(a,b,x) a*x+b);
    end
    a=coeffvalues(fitmax);
    b=coeffvalues(fitmin);
    amax=a(1);
    amin=b(1);
    bmax=a(2);
    bmin=b(2);
    %if in this cycle the fits are equal, then close the function 
    if (abs(altamax-amax)<1e-6 & abs(altbmax-bmax)<1e-6 & abs(altamin-amin)<1e-6 & abs(altbmin-bmin)<1e-6)
        break;
    end
            
end
if (n==1)
    xaus=[];
    yaus=[];
    xerraus=[];
    yerraus=[];
end
l=numel(x)
if (l>=2)
    l=numel(x);

    %Declare the 4 corners of the box
    xlu=x(1)-xerr(1);
    xld=x(1)-xerr(1);
    xru=x(l)+xerr(1);
    xrd=x(l)+xerr(1);

ylu=amax*xlu+bmax;
yru=amax*xru+bmax;
yld=amin*xld+bmin;
yrd=amin*xrd+bmin;

%Declare the vectors of the corners.
xcorner=[xlu xru xrd xld xlu];
ycorner=[ylu yru yrd yld ylu];

if (count == 1)
    hold on;
    plot(xcorner,ycorner,'--','Color',[0.8 0 0.2]);
end
end

if (l==0)
    display('All measurpoint are acapetable');
end
if (numel(x)==0)
    display('No points are in that scale');
end
end