void fill_row_q(int imin, int imax, int q,
std::vector< std::vector<ldouble> > & S,
std::vector< std::vector<size_t> > & J,
const std::vector<ldouble> & sum_x,
const std::vector<ldouble> & sum_x_sq,
const std::vector<ldouble> & sum_w,
const std::vector<ldouble> & sum_w_sq,
const enum DISSIMILARITY criterion)
{
// Assumption: each cluster must have at least one point.
for(int i=imin; i<=imax; ++i) {
S[q][i] = S[q-1][i-1];
J[q][i] = i;
int jmin = std::max(q, (int)J[q-1][i]);
for(int j=i-1; j>=jmin; --j) {
ldouble Sj(S[q-1][j-1] +
dissimilarity(criterion, j, i, sum_x, sum_x_sq, sum_w, sum_w_sq)
// ssq(j, i, sum_x, sum_x_sq, sum_w)
);
if(Sj < S[q][i]) {
S[q][i] = Sj;
J[q][i] = j;
}
}
}
}
int main(void){
take_input();
total_bigram();
printf("%d",dissimilarity());
return 0;
}
double operator()(data_point a, data_point b){
return dissimilarity(a, a + dim, b);
}
double operator()(data_point& a, data_point& b){
return dissimilarity(a.begin(), a.end(), b.begin());
}
