void CowichanSerial::winnow(IntMatrix matrix, BoolMatrix mask,
PointVector points) {
index_t r, c;
index_t len; // number of points
index_t stride; // selection stride
index_t i, j;
// count set cell
len = mask_count (mask, nr, nc);
if (len < n) {
not_enough_points();
}
WeightedPointVector weightedPoints = NULL;
try {
weightedPoints = NEW_VECTOR_SZ(WeightedPoint, len);
}
catch (...) {out_of_memory();}
// fill temporary vector
i = 0;
for (r = 0; r < nr; r++) {
for (c = 0; c < nc; c++) {
if (MATRIX_RECT(mask, r, c)) {
weightedPoints[i++] = WeightedPoint((real)c, (real)r,
MATRIX_RECT(matrix, r, c));
}
}
}
#ifdef SORT_TIME
INT64 start, end;
start = get_ticks ();
#endif
// sort
std::sort(weightedPoints, &weightedPoints[len]);
#ifdef SORT_TIME
end = get_ticks ();
#endif
// copy over points
stride = len / n;
for (i = n - 1, j = len - 1; i >= 0; i--, j -= stride) {
#ifdef WINNOW_OUTPUT
std::cout << weightedPoints[j].weight << "\n";
#endif
points[i] = weightedPoints[j].point;
}
#ifdef SORT_TIME
std::cout << "winnow sort: ";
print_elapsed_time(start, end);
std::cout << std::endl;
#endif
delete [] weightedPoints;
}
// weights are relative, i.e., they need not add up to n; a
// typical choice of weights is each weight equals the reciprocal
// of the variance of the measurement
void add(double x, double y, double weight = 1.0) {
INVARIANT(weight > 0, "weight should be > 0");
data.push_back(WeightedPoint(x, y, weight));
}
