nsa.m

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%% 该算法是NSA的编程实例，其中：sf是自己模式串；det是检测器集合； 
%% n是解测器检测器集合的个数； 
%% ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ 
%%  下面是检测器产生阶段 %% 
rs=0.04; 
rab=0.05; 
self=[0.2265 0.1423; 
     0.2871 0.2186; 
     0.273  0.1977; 
     0.265  0.2008; 
     0.1426 0.0567; 
     0.17   0.0797; 
     0.1772 0.087; 
     0.2773 0.2113; 
     0.2874 0.2288; 
     0.3045 0.2572]; 
 d=rand(250,2); 
 %for s=1:250 
     %plot(det(s,1),det(s,2),'b+');hold on; 
 %end 
 for n=1:250 
     for i=1:250 
        for j=1:10 
           affity(j)=sqrt((d(i,1)-self(j,1)).^2+(d(i,2)-self(j,2)).^2); 
           if affity(j)<=(rab+rs); 
               d(i,:)=rand(1,2); 
           else 
               d(i,:)=d(i,:); 
           end 
       end 
   end 
end 
d; 
for i=1:10 
    plot(self(i,1),self(i,2),'bo');hold on; 
end 
for i=1:250 
    plot(d(i,1),d(i,2),'b+');hold on; 
end 
%************************** the end  ******************** 
%%   下面是测试阶段  %% 
test=[0.3245 0.22; 
      0.2866 0.2279; 
      0.2308 0.1464; 
      0.2544 0.18; 
      0.151 0.068; 
      0.3179 0.2077; 
      0.3042 0.1989; 
      0.258 0.3477; 
      0.3327 0.2501; 
      0.214 0.139; 
      0.4524 0.31; 
      0.4401 0.30; 
      0.4782 0.36; 
      0.4633 0.357; 
      0.5687 0.898; 
      0.7245 0.987; 
      0.6333 0.96; 
      0.6929 0.983; 
      0.31 0.454; 
      0.344 0.568; 
      0.376 0.67; 
      0.284 0.563; 
      0.5501 0.1512; 
      0.2250 0.7821; 
      0.6543 0.2945]; 
  for j=1:25 
      plot(test(j,1),test(j,2),'r*'); hold on; % 标识当前的测试样本 
      for i=1:250 
          dir=norm(test(j,:)-d(i,:)); 
          d_test(i,1)=dir; 
          d_label(i,1)=i; % 标识当前是那个抗体和那个抗原在计算亲和力 
      end  %d(d_label(i,1) 
      for i=1:250 
          if d_test(i,1)<=rab 
              plot(d(d_label(i,1),1),d(d_label(i,1),2),'g^'); hold on; 
          end 
      end 
      min_dir=min(d_test); 
      %for i=1:245 
         % f=or(d_test(i,1)<=rab,d_test(i+1,1)<=rab); 
         % f=and(f,1); 
      %end 
      %f; 
      %if f==1 
      if min_dir<=rab 
          disp('This data is detected') 
      else 
          for p=1:10 
              dir2=norm(test(j,:)-self(p,:)); 
              test_self(p,1)=dir2; 
              self_label(p,1)=p; 
          end 
          for p=1:10 
              if test_self(p,1)<=rs 
                  plot(self(self_label(p,1),1),self(self_label(p,1),2),'g^'); hold on; 
              end 
          end 
          %for p=1:9 
              %ff=or(test_self(p,1)<=rs,test_self(p+1,1)<=rs); 
              %ff=and(ff,1); 
          %end 
          min_dir2=min(test_self); 
          %if ff==1 
          if min_dir2<=rs 
              disp('This data is self_data') 
          else 
               disp('This data is not detected and not a selfdata') 
          end 
      end 
  end 
%% ^^^^^^^^^^^^^^^^^  The end ^^^^^^^^^^^^^^^^^^^^  %%