count.m

来自「麻省理工学院的人工智能工具箱,很珍贵,希望对大家有用!」· M 代码 · 共 39 行

function [hi,ob,fa,nob,fbo,fbp]=count(Obsr,Prdc,P)
P=P(1:end);
nP=length(P);
hi(nP,size(Prdc,2),size(Prdc,3))=0;
ob(1,size(Prdc,2),size(Prdc,3))=0;
fa(nP,size(Prdc,2),size(Prdc,3))=0;
nob(1,size(Prdc,2),size(Prdc,3))=0;
fbo(nP-1,size(Prdc,2),size(Prdc,3))=0;
fbp(nP-1,size(Prdc,2),size(Prdc,3))=0;

indn=~isnan(Obsr) & ~isnan(Prdc);
ind=find(indn);
i=find(sum(indn,1)==0);

o(size(Obsr,1),size(Obsr,2),size(Obsr,3))=0;
no(size(Obsr,1),size(Obsr,2),size(Obsr,3))=0;
h(size(Prdc,1),size(Prdc,2),size(Prdc,3))=0;

o(ind)=Obsr(ind)>0;
no(ind)=~o(ind);
nob(1,:,:)=sum(no,1);
ob(1,:,:)=sum(o,1);
for l=1:nP
   %縎e ha producido el evento con una probabilidad > P para
   % la observacion y la prediccion?
   h(ind)=Prdc(ind)>P(l) & o(ind);
   hi(l,:,:)=sum(h,1);
   
   h(ind)=Prdc(ind)>P(l) & no(ind);
   fa(l,:,:)=sum(h,1);
   if l>1
      h(ind)= Prdc(ind)>=P(l-1) & Prdc(ind)<P(l);
      %h(ind)= Prdc(ind).*h(ind);
      fbp(l-1,:,:)=sum(h,1);
      h(ind)= h(ind) & o(ind);
      fbo(l-1,:,:)=sum(h,1);
   end
 end