array_nd<T> repmat(const array_nd<T>& a, const size_array& sz)
{
CHECK (sz.length() <= a.ndims(), eshape());
array_nd<T> c(a);
for (size_t i = 0; i < sz.length(); i++) {
array_nd<T> tmp(c);
for (size_t j = 0; j < sz[i]; j++)
c = cat<T>(i, c, tmp);
}
return c;
}
void eval(const array <pos>& nn, const nn_options& opt)
{
msg::in_line(info, "evaluating");
const size_array at = (0, _, opt.at_step, _, opt.at_max);
array <T> recall(at.length(), T());
T R = .95;
array <T> rat = (R, _, opt.rat_step, _, opt.rat_max);
array <T> freq(rat.length());
size_t FL = freq.length();
size_t N = nn.length(), C = dist.length(), J = dist[0].columns();
T rank = 0, lower = 0, upper = 0, approx = 0;
for (size_t n = 0; n < N; n++)
{
msg::progress(info, n, N);
pos quot = nn[n];
for (size_t c = 0; c < C; c++)
{
array <T> d = dist[c].as_rows()[n];
T dq = d[quot % J], dl = min(d);
T r = find(d < dq).length();
rank += r;
recall[r > at]++;
freq[(min(dq / dl, opt.rat_max) - R) / opt.rat_step]++;
lower += dl;
upper += max(d);
approx += dq;
quot /= J;
}
}
T S = C * N;
msg::done(info);
msg::rank(info, rank / S, J);
msg::bounds(info, lower / S, approx / S, upper / S);
if (opt.recall)
msg::recall(info, at, 1 - recall / S);
if (opt.ratio)
msg::ratio(info, rat, freq / S);
}