int main() // THIS IS BASICALLY ADMIN MENU ONLY IT CURRENTLY DOES TWO JOBS 1. CALL WRITE_PRODUCT 2.CALL READALL_PRODUCT
{
char ans, ch;
printf("\n------------------------------------------");
printf("\n\t*Welcome To NesNas Supermarket*\t |\n");
printf("------------------------------------------");
printf("\n ADMIN MENU\t\t\t\t |\n");
do
{
printf("------------------------------------------");
printf("\n 1 For Accept \t\t\t\t |");
printf("\n 2 For Display \t\t\t\t |");
printf("\n 3 For Displaying Particular Record\t | ");
printf("\n 4 For Modificaton \t\t\t |");
printf("\n 5 For Deletion \t\t\t |");
printf("\n 6 EXIT.\t\t\t\t |");
printf("\n------------------------------------------");
printf("\n\n Select -> ");
scanf("%c",&ch);
switch(ch)
{
case '1': write_product();
break;
case '2': readall_product();
break;
case '3':part_prod();
break;
case '4':mod_rec();
break;
case '5':del_rec();
break;
default: printf("\n INVALID OPERATION \n");
} // END OF SWITCH
}while( ch != '6' );
}
/**
* Description not yet available.
* \param
\n\n The implementation of this algorithm was inspired by
"Numerical Recipes in C", 2nd edition,
Press, Teukolsky, Vetterling, Flannery, chapter xx
*/
df1b2matrix solve(const df1b2matrix& aa,const df1b2matrix& tz,
df1b2variable ln_unsigned_det,df1b2variable& sign)
{
RETURN_ARRAYS_INCREMENT();
int n = aa.colsize();
int lb = aa.colmin();
int ub = aa.colmax();
if (lb!=aa.rowmin()||ub!=aa.colmax())
{
cerr << "Error matrix not square in solve()"<<endl;
ad_exit(1);
}
df1b2matrix bb(lb,ub,lb,ub);
bb = aa;
ivector indx(lb,ub);
int One = 1;
indx.fill_seqadd(lb,One);
df1b2variable d;
df1b2variable big,dum,sum,temp;
df1b2vector vv(lb,ub);
d = 1.0;
for (int i = lb;i<=ub;i++)
{
big = 0.0;
for (int j = lb;j<=ub;j++)
{
temp = fabs(bb(i,j));
if (value(temp) > value(big))
{
big = temp;
}
}
if (value(big) == 0.0)
{
cerr <<
"Error in matrix inverse -- matrix singular in inv(df1b2matrix)\n";
}
vv[i] = 1.0/big;
}
for (int j = lb;j<=ub;j++)
{
for (int i = lb;i<j;i++)
{
sum = bb(i,j);
for (int k = lb;k<i;k++)
{
sum -= bb(i,k)*bb(k,j);
}
// a[i][j] = sum;
bb(i,j) = sum;
}
int imax = j;
big = 0.0;
for (int i = j;i<=ub;i++)
{
sum = bb(i,j);
for (int k = lb;k<j;k++)
{
sum -= bb(i,k)*bb(k,j);
}
bb(i,j) = sum;
dum = vv[i]*fabs(sum);
if (value(dum) >= value(big))
{
big = dum;
imax = i;
}
}
if (j != imax)
{
for (int k = lb;k<=ub;k++)
{
dum = bb(imax,k);
bb(imax,k) = bb(j,k);
bb(j,k) = dum;
}
d = -1.*d;
vv[imax] = vv[j];
// if (j<ub)
{
int itemp = indx(imax);
indx(imax) = indx(j);
indx(j) = itemp;
}
// cout << "indx= " <<indx<<endl;
}
if (value(bb(j,j)) == value(0.0))
{
bb(j,j) = TINY;
}
if (j != n)
{
dum = 1.0/bb(j,j);
for (int i = j+1;i<=ub;i++)
{
bb(i,j) = bb(i,j) * dum;
}
}
}
// get the determinant
sign = d;
df1b2vector part_prod(lb,ub);
part_prod(lb) = log(fabs(bb(lb,lb)));
if (value(bb(lb,lb))<0) sign=-sign;
for (int j = lb+1;j<=ub;j++)
{
if (value(bb(j,j))<0) sign=-sign;
part_prod(j) = part_prod(j-1)+log(fabs(bb(j,j)));
}
ln_unsigned_det = part_prod(ub);
df1b2matrix z = trans(tz);
int mmin = z.indexmin();
int mmax = z.indexmax();
df1b2matrix x(mmin,mmax,lb,ub);
// df1b2vector x(lb,ub);
df1b2vector y(lb,ub);
// int lb = rowmin;
// int ub = rowmax;
df1b2matrix& b = bb;
ivector indxinv(lb,ub);
for (int i = lb;i<=ub;i++)
{
indxinv(indx(i)) = i;
}
for (int kk = mmin;kk<=mmax;kk++)
{
for (int i = lb;i<=ub;i++)
{
y(indxinv(i)) = z(kk)(i);
}
for (int i = lb;i<=ub;i++)
{
sum = y(i);
for (int j = lb;j<=i-1;j++)
{
sum-=b(i,j)*y(j);
}
y(i) = sum;
}
for (int i = ub;i>=lb;i--)
{
sum = y(i);
for (int j = i+1;j<=ub;j++)
{
sum-=b(i,j)*x(kk)(j);
}
x(kk)(i) = sum/b(i,i);
}
}
RETURN_ARRAYS_DECREMENT();
return trans(x);
}
