%***************************************************************************
%* Matlab Benchmark program version 5.0                                    *
%* Author : Stefan Steinhaus                                               *
%* EMAIL  : stefan@steinhaus-net.de                                        * 
%* This program is public domain. Feel free to copy it freely.             *
%***************************************************************************

clc
disp('The following benchmark program will print the average timings')
disp('to calculate the functions by 3 runs.')
disp(' ')
disp(' ')
disp('!!! MATLAB - Benchmarkprogram !!!')
disp('=================================')
disp(' ')

%* Misc. operation *

result=0; runs=3;
for i=1:runs;
   tic;
   datmat=importdata('d:\\mathematik\\ncrunch5\\currency2.txt',' ');
    Limits_Area=[1,261,522,784,1045,1305,1565,1827,2088,2349,2610,2871,3131,3158];
   for k=1:2000;
      for j=1:13;
         Year_Data=datmat.data(Limits_Area(j):Limits_Area(j+1)-1,4:37);
         Min_Year=min(Year_Data);
         Max_Year=max(Year_Data);
         Mean_Year=mean(Year_Data);
         GainLoss_Year=100-(Year_Data(1,:)+0.00000001)./(Year_Data(end,:)+0.00000001)*100;
     end;
   end;
   result=result+toc;
end;
result=result/runs;
disp(['IO test & descriptive statistics_____________________ : ' num2str(result) ' sec.'])

result=0; a=1;
for i=1:runs
   tic;
   for x=1:15000;
       for y=1:15000;
           a=a+x+y;
       end;
   end;
   result=result+toc;
end;
result=result/runs;
disp(['Loop testing_________________________________________ : ' num2str(result) ' sec.'])
result=0;
for i=1:runs
   for j=1:200
       b=1+(rand(2000,2000)/100);
       tic;
       a=b.^1000; 
       result=result+toc;
   end
end
result=result/runs;
disp(['2000x2000 normal distributed random matrix^1000______ : ' num2str(result) ' sec.'])
clear a; clear b; result=0; 
for i=1:runs
   for j=1:100
       a=rand(1000000,1);
       tic;
       b=sort(a); 
       result=result+toc;
   end
end
result=result/runs;
disp(['1000000 values sorted ascending______________________ : ' num2str(result) ' sec.'])

%* Analysis *

clear a; clear b; result=0;
for i=1:runs
   for j=1:100
       a=rand(1048576,1);
       tic;
       b=fft(a);
       result=result+toc;
   end
end
result=result/runs;
disp(['FFT over 1048576 values (2^20)_______________________ : ' num2str(result) ' sec.'])

%* Algebra *

clear a; clear b; result=0;
for i=1:runs
   for j=1:100
        a=rand(1500,1500);
        tic;
        b=det(a); 
        result=result+toc;
   end
end
result=result/runs;
disp(['Determinant of a 1500x1500 random matrix_____________ : ' num2str(result) ' sec.'])
clear a; clear b; result=0;
for i=1:runs
   for j=1:100
        a=rand(1500,1500);
        tic;
        b=inv(a); 
        result=result+toc;
   end
end
result=result/runs;
disp(['Inverse of a 1500x1500 uniform distr. random matrix__ : ' num2str(result) ' sec.'])
clear a; clear b; result=0;
for i=1:runs
   a=rand(1200,1200);
   tic; 
   c=eig(a); 
   result=result+toc;
end
result=result/runs;
disp(['Eigenval. of a normal distr. 1200x1200 randommatrix___ : ' num2str(result) ' sec.'])
clear a; clear b; result=0;
for i=1:runs
   for j=1:100
       a=rand(1500,1500);
       a=a'*a;
       tic;
       b=chol(a); 
       result=result+toc;
   end
end
result=result/runs;
disp(['Cholesky decomposition of a 1500x1500-matrix_________ : ' num2str(result) ' sec.'])
clear a; clear b; result=0;
for i=1:runs
   for j=1:100
       a=rand(1500,1500);
       tic;
       b=a'*a; 
       result=result+toc;
   end
end
result=result/runs;
disp(['1500x1500 cross-product matrix_______________________ : ' num2str(result) ' sec.'])

%* Number theory *

clear a; clear b;
phi = 1.6180339887498949; result=0;
for i=1:runs;
   a=floor(1000*rand(10000000,1));
   tic;
   b=(phi.^a-(-phi).^(-a))/sqrt(5);
   result=result+toc;
end
result=result/runs;
disp(['Calculation of 10000000 fibonacci numbers____________ : ' num2str(result) ' sec.'])

%* Stochastic-statistic *

result=0; a=0; b=0;
for i=1:runs;
    a=rand(10000,1000);
    tic;
	b=princomp(a);
    result=result+toc;
end;
result=result/runs;
disp(['Calc. of the principal components of a 10000x1000 matrix : ' num2str(result) ' sec.'])
clear a; clear b; result=0;
for i=1:runs
   for j=1:100
       a=rand(1500,1500);
       tic;
       b=gamma(a); 
       result=result+toc;
   end
end
result=result/runs;
disp(['Gamma function over a 1500x1500 matrix_______________ : ' num2str(result) ' sec.'])
clear a; clear b; result=0;
for i=1:runs
   for j=1:100
       a=rand(1500,1500);
       tic;
       b=erf(a); 
       result=result+toc;
   end
end
result=result/runs;
disp(['Gaussian error function over a 1500x1500 matrix______ : ' num2str(result) ' sec.'])
clear a; clear b; result=0;
for i=1:runs
   for j=1:100
       a=randn(1000,1000); 
       b=1:1000;
       tic;
       b=a\b'; 
       result=result+toc;
   end
end
result=result/runs;
disp(['Linear regression over a 1000x1000 matrix____________ : ' num2str(result) ' sec.'])