matlab - Compression and Decompression of ECG Signal using HUFFMAN ALGORITHM -

i want compress , decompress ecg signal stored text message text file , find out file size, cr,prd ratio,and qs.

here code compression , decompression of ecg signal using huffman algorithm. i'm trying find out file size, compression ratio,prd ratio,qs.

but error i'm getting

the ecg file in text format.

        %clearing variables , screen          enter code here          clear all;          close all;          clc;          [file1]=uigetfile('*.txt');          %fprintf('enter ecg file name :%s',file1);          p=file1;          t=sprintf('%s',p);          b1=dlmread([file1]);          len=length(b1);          lead=input('enter lead number :');          %lead=str2double(lead);            col2=b1(1:end,lead);          e=fix(sqrt(len));         m=1;           i=1:e           j=1:e           g2(i,j)=fix(col2(m)*1000); %amplifying 1000           m=m+1;           end           end           g3=g2;            i=1:e           j=1:e            if(g3(i,j)<0)             g3(i,j)=(g3(i,j))*(-1);            end            end            end            max_term=g3(1,1);              i=1:e              j=1:e             if(g3(i,j)>max_term)            max_term=g3(i,j);            end            end            end            time=b1(1:end,1)*1000;             plot(time,col2);            xlabel('time / s'); ylabel('voltage / mv');            string=['input ecg signal :: ',t];             title(string);            %title('input ecg signal:t');            grid on;              %%%%%%%%%%%input file %%%%%%%%%%%%%           fid=fopen('inputfile.txt','w+');            cnt2=fwrite(fid,col2);            fclose(fid);            %%%%%%a%%%%%%%%%%%%%%%%%%%%%%%              a=g3;            i=a;            [m,n]=size(i);           totalcount=m*n;           %variables using find probability           cnt=1;              sigma=0;             %computing cumulative probability.            i=0:max_term           k=i==i;           count(cnt)=sum(k(:))            %pro array having probabilities            pro(cnt)=count(cnt)/totalcount;            sigma=sigma+pro(cnt);            cumpro(cnt)=sigma;           cnt=cnt+1;           end;          %symbols signal          symbols = [0:max_term];           %huffman code dictionary          dict = huffmandict(symbols,pro);             %function converts array vector           vec_size = 1;            p = 1:m            q = 1:n           newvec(vec_size) = i(p,q);           vec_size = vec_size+1;           end           end            %huffman encodig             hcode = huffmanenco(newvec,dict);             %huffman decoding             dhsig1 = huffmandeco(hcode,dict);             %convertign dhsig1 double dhsig uint8             dhsig = uint8(dhsig1);              %vector array conversion              dec_row=sqrt(length(dhsig));                dec_col=dec_row;              %variables using convert vector 2 array              arr_row = 1;              arr_col = 1;              vec_si = 1;                x = 1:m                y = 1:n               back(x,y)=dhsig(vec_si);               arr_col = arr_col+1;               vec_si = vec_si + 1;               end               arr_row = arr_row+1;               end               z=b1(1:end,1)*750;               %converting  grayscale rgb               [deco, map] = gray2ind(back,256);               rgb = ind2rgb(deco,map);                figure,subplot(1,2,1),title('original graph'),...               subplot(1,2,1),plot(b1,col2),xlabel('time / s');                  figure,subplot(1,2,1),plot(time,col2),xlabel('time / s');                       ylabel('voltage / mv'),grid on,title('decompressed graph');               % subplot(2,2,3),imshow((b1)),title('compressed graph');                 % k=imfinfo('original.jpg');               % size_of_file=k.filesize               %k=imfinfo('compressed.jpg');               %size_of_file=k.filesize                %k=imfinfo('fdr.jpg');               %size_of_file=k.filesize               disp('size of original ecg in bytes');                 disp(bytes(p));               disp('size of ecg after compression');                 fid=fopen('comp1.txt','w+'); % compressed file "comp.dat"                cnt=fwrite(fid,q);               fclose(fid);               disp(bytes('comp1.txt'));                 disp('size of decompressed ecg');                fid=fopen('recons1.txt','w+');               cnt1=fwrite(fid,pro);                fclose(fid);               disp(bytes(pro));                %  disp('size of ecg after re-construct in bytes');               %  fid=fopen('recons1.dat','w+');              %  cnt1=fwrite(fid,g13);              %  fclose(fid);              %  disp(bytes('recons1.dat'));               %%%%%%% prd calculation %%%%%%%%%%%%%              e=length(p);                i=1:e                y3(i)=ecg(i)- main_t(i);                y4(i)=(y3(i).^2);          %      y5=sum(y4(i));                y5(i)=(ecg(i).^2);                end               y6=sum(y4)/sum(y5);                 prd=sqrt(y6);                disp('after calculation prd:');                disp(prd);                 b0=bytes(p);                  b1=bytes('comp1.txt');                cr1=b0/b1;                cr=100/cr1;                disp('after calculation cr%:');                disp(cr);                disp('quality score');                 c=double(cr);                 d=double(prd);                   qs=double(c/(d*100));                   disp(qs);                   %end of huffman coding 

errors: code half executing , giving error in line no 189 in finding out size after compression error in line : cnt=fwrite(fid,q);

the code strangely executable if avoid moment lines

line#23    %g3=g2(i,j); line#31    %max_term=g3(1,1); 

but helpful if share more precise information problem , ecg file load. mean ecg data format.