function [node,sqnorm,rsqnorm,Maxerror]=webanal
global name gi bb E K F xx h D n weight u_exact du_exact xi xe step2 X CEVAP CEVAPP
ii=0;jj=length(gi);EE=[];
for i=1:length(bb),
    if bb(i)>1,ii=ii+1;EE=[EE E(:,ii)];
    elseif bb(i)==1,jj=jj+1;EE=[EE E(:,jj)];end,
end,
K(find(bb==0),:)=[];K(:,find(bb==0))=[];F(find(bb==0))=[];
cwd=pwd;cd('output');fid=fopen([name,'.out'], 'w');
fprintf(fid, 'OUTPUT INFORMATION FOR THE %s \n',name);
fprintf(fid, 'The degree: %d \n',n);
fprintf(fid, 'The grid width: %6.3f \n',h);
fprintf(fid, 'The position nodes: %6.2f \n',xx);

fprintf(fid, '\nFEM USING WEIGHTED B-SPLINES \n');
node=size(K,1);fprintf(fid, 'The number of nodes: %d \n',node);
% COND   Condition number with respect to inversion.
%    COND(X) returns the 2-norm condition number (the ratio of the largest 
%    singular value of X to the smallest).  Large condition numbers 
%    indicate a nearly singular matrix
fprintf(fid, 'The condition number: %e \n',cond(full(K)));
[M1,M2]=luinc(K,1e-5);[CC,er,iter,flag]=pbicgstab(K,sparse(size(F,1),1),F,M1*M2,20000,1e-20,M1,M2);
CC
if sum(sum(EE)==0)~=0,display('EE MATRISINDE HATA VAR');end
K2=EE*K*EE';F2=EE*F;clear K F;
node=[node size(K2,1)];
CC2=K2\F2;

CC2=EE'*CC2;clear EE
gk=find(bb>=1);
CEVAP=sparse(1,length(xx));CEVAPP=sparse(1,length(xx));

for i=1:length(gk)
    k=gk(i);ii=D(k,1);Dx1=D(k,2);
    
    xxx=Dx1:h:Dx1+(n+1)*h;ww=weight(xxx);
    bx1=bspline(Dx1:h:Dx1+(n+1)*h);bx1=fncmb(bx1,1/sqrt(h));
    CONS=ww.*ppval(bx1,xxx);
    CEVAP((ii-1)+1:(ii+n)+1)=CEVAP((ii-1)+1:(ii+n)+1)+CC(i)*CONS;
    CEVAPP((ii-1)+1:(ii+n)+1)=CEVAPP((ii-1)+1:(ii+n)+1)+CC2(i)*CONS;
end
RCEV=u_exact(xx);%Exact values of nodes
index=(xx-xi).*(xe-xx)<-eps;
RCEV(index)=NaN;CEVAP(index)=NaN;CEVAPP(index)=NaN;
grafikleme(xx,RCEV,CEVAPP);
Maxerror(2)=max(abs(RCEV(n+1:end-n)-CEVAPP(n+1:end-n)));
fprintf(fid, 'The error of nodes: %e \n',abs(RCEV(n+1:end-n)-CEVAP(n+1:end-n)));
fprintf(fid, 'The maximum error: %e \n',Maxerror(1));
cd(cwd);[enorm(1),sqnorm(1),renorm(1),rsqnorm(1)]=webnorm(xx,CC);%Error analysis
[enorm(2),sqnorm(2),renorm(2),rsqnorm(2)]=webnorm(xx,CC2);cd('output');

fprintf(fid, 'L2 error norm: %e \n',sqnorm(1));
fprintf(fid, 'H1 error norm: %e \n',enorm(1));
fprintf(fid, 'Relative L2 error norm: %e \n',rsqnorm(1));
fprintf(fid, 'Relative H1 error norm: %e \n',renorm(1));

fprintf(fid, '\nFEM USING WEIGHTED EXTENDED B-SPLINES \n');
fprintf(fid, 'The number of nodes: %d \n',node(2));
fprintf(fid, 'The condition number: %e \n',cond(full(K2)));
fprintf(fid, 'The error of nodes: %e \n',abs(RCEV(n+1:end-n)-CEVAPP(n+1:end-n)));
fprintf(fid, 'The maximum error: %e \n',Maxerror(2));
fprintf(fid, 'L2 error norm: %e \n',sqnorm(2));
fprintf(fid, 'H1 error norm: %e \n',enorm(2));
fprintf(fid, 'Relative L2 error norm: %e \n',rsqnorm(2));
fprintf(fid, 'Relative H1 error norm: %e \n',renorm(2));
fclose(fid);cd(cwd);