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Iterative, not recursive, version of the Douglas-Peucker-Ramer algorithm

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based on the work by @fuchstraumer
https://github.com/slic3r/Slic3r/pull/3825
https://gist.github.com/fuchstraumer/9421573fc281b946e5f561758961212a
which was based on
http://anis-moussa.blogspot.com/2014/03/ramer-douglas-peucker-algorithm-for.html
This commit is contained in:
bubnikv 2018-12-14 19:29:58 +01:00
parent 780b5667f3
commit 77d37f108c
3 changed files with 58 additions and 49 deletions
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78
src/libslic3r/MultiPoint.cpp
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@ -162,45 +162,51 @@ bool MultiPoint::first_intersection(const Line& line, Point* intersection) const
return found;
}
//FIXME This is very inefficient in term of memory use.
// The recursive algorithm shall run in place, not allocating temporary data in each recursion.
Points
MultiPoint::_douglas_peucker(const Points &points, const double tolerance)
std::vector<Point> MultiPoint::_douglas_peucker(const std::vector<Point>& pts, const double tolerance)
{
assert(points.size() >= 2);
Points results;
double dmax = 0;
size_t index = 0;
Line full(points.front(), points.back());
for (Points::const_iterator it = points.begin() + 1; it != points.end(); ++it) {
// we use shortest distance, not perpendicular distance
double d = full.distance_to(*it);
if (d > dmax) {
index = it - points.begin();
dmax = d;
std::vector<Point> result_pts;
if (! pts.empty()) {
const Point *anchor = &pts.front();
size_t anchor_idx = 0;
const Point *floater = &pts.back();
size_t floater_idx = pts.size() - 1;
result_pts.reserve(pts.size());
result_pts.emplace_back(*anchor);
if (anchor_idx != floater_idx) {
assert(pts.size() > 1);
std::vector<size_t> dpStack;
dpStack.reserve(pts.size());
dpStack.emplace_back(floater_idx);
for (;;) {
double max_distSq = 0.0;
size_t furthest_idx = anchor_idx;
// find point furthest from line seg created by (anchor, floater) and note it
for (size_t i = anchor_idx + 1; i < floater_idx; ++ i) {
double dist = Line::distance_to_squared(pts[i], *anchor, *floater);
if (dist > max_distSq) {
max_distSq = dist;
furthest_idx = i;
}
}
// remove point if less than tolerance
if (max_distSq <= tolerance) {
result_pts.emplace_back(*floater);
anchor_idx = floater_idx;
anchor = floater;
assert(dpStack.back() == floater_idx);
dpStack.pop_back();
if (dpStack.empty())
break;
floater_idx = dpStack.back();
} else {
floater_idx = furthest_idx;
dpStack.emplace_back(floater_idx);
}
floater = &pts[floater_idx];
}
}
}
if (dmax >= tolerance) {
Points dp0;
dp0.reserve(index + 1);
dp0.insert(dp0.end(), points.begin(), points.begin() + index + 1);
// Recursive call.
Points dp1 = MultiPoint::_douglas_peucker(dp0, tolerance);
results.reserve(results.size() + dp1.size() - 1);
results.insert(results.end(), dp1.begin(), dp1.end() - 1);
dp0.clear();
dp0.reserve(points.size() - index);
dp0.insert(dp0.end(), points.begin() + index, points.end());
// Recursive call.
dp1 = MultiPoint::_douglas_peucker(dp0, tolerance);
results.reserve(results.size() + dp1.size());
results.insert(results.end(), dp1.begin(), dp1.end());
} else {
results.push_back(points.front());
results.push_back(points.back());
}
return results;
return result_pts;
}
// Visivalingam simplification algorithm https://github.com/slic3r/Slic3r/pull/3825