nsa.m

否定选择算法

%% 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 ^^^^^^^^^^^^^^^^^^^^  %%