void Tensor4d::tensorize(const Matrix & mat) {
assert( dims_[1] * dims_[2] * dims_[3] == mat.width());
assert( dims_[0] == mat.height() );
for(UINT i = 0; i < dims_[0]; ++i)
for(UINT j = 0; j < dims_[1]; ++j)
for(UINT m = 0; m < dims_[2]; ++m)
for(UINT n = 0; n < dims_[3]; ++n)
set_elt(i, j, m, n, mat.get_elt(i, j * dims_[2] * dims_[3] + m * dims_[3] + n));
}
/* This is the function you need to optimize. It takes one
square matrix as input
*/
void verfunc(smat_t *a)
{
int i, j;
double x,x2;
// i is the column of a we're computing right now
for(i = 0; i < a->n; i++)
{
// j is the row of a we're computing right now
for(j = 0; j < a->n; j++)
{
// First, compute f(A) for the element of a in question
x = get_elt(a, i, j);
x = ver_f(x, i, j);
// Add this to the value of a we're computing and store it
x2 = get_elt(a, i, j);
x = x * x2;
set_elt(a, i, j, x);
}
}
}
