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/** @file
* @brief Convex hull of a set of points
*//*
* Authors:
* Nathan Hurst <njh@mail.csse.monash.edu.au>
* Michael G. Sloan <mgsloan@gmail.com>
* Krzysztof Kosiński <tweenk.pl@gmail.com>
* Copyright 2006-2015 Authors
*
* This library is free software; you can redistribute it and/or
* modify it either under the terms of the GNU Lesser General Public
* License version 2.1 as published by the Free Software Foundation
* (the "LGPL") or, at your option, under the terms of the Mozilla
* Public License Version 1.1 (the "MPL"). If you do not alter this
* notice, a recipient may use your version of this file under either
* the MPL or the LGPL.
*
* You should have received a copy of the LGPL along with this library
* in the file COPYING-LGPL-2.1; if not, write to the Free Software
* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
* You should have received a copy of the MPL along with this library
* in the file COPYING-MPL-1.1
*
* The contents of this file are subject to the Mozilla Public License
* Version 1.1 (the "License"); you may not use this file except in
* compliance with the License. You may obtain a copy of the License at
* http://www.mozilla.org/MPL/
*
* This software is distributed on an "AS IS" basis, WITHOUT WARRANTY
* OF ANY KIND, either express or implied. See the LGPL or the MPL for
* the specific language governing rights and limitations.
*
*/
#include <2geom/convex-hull.h>
#include <2geom/exception.h>
#include <algorithm>
#include <map>
#include <iostream>
#include <cassert>
#include <boost/array.hpp>
/** Todo:
+ modify graham scan to work top to bottom, rather than around angles
+ intersection
+ minimum distance between convex hulls
+ maximum distance between convex hulls
+ hausdorf metric?
+ check all degenerate cases carefully
+ check all algorithms meet all invariants
+ generalise rotating caliper algorithm (iterator/circulator?)
*/
using std::vector;
using std::map;
using std::pair;
using std::make_pair;
using std::swap;
namespace Geom {
ConvexHull::ConvexHull(Point const &a, Point const &b)
: _boundary(2)
, _lower(0)
{
_boundary[0] = a;
_boundary[1] = b;
std::sort(_boundary.begin(), _boundary.end(), Point::LexLess<X>());
_construct();
}
ConvexHull::ConvexHull(Point const &a, Point const &b, Point const &c)
: _boundary(3)
, _lower(0)
{
_boundary[0] = a;
_boundary[1] = b;
_boundary[2] = c;
std::sort(_boundary.begin(), _boundary.end(), Point::LexLess<X>());
_construct();
}
ConvexHull::ConvexHull(Point const &a, Point const &b, Point const &c, Point const &d)
: _boundary(4)
, _lower(0)
{
_boundary[0] = a;
_boundary[1] = b;
_boundary[2] = c;
_boundary[3] = d;
std::sort(_boundary.begin(), _boundary.end(), Point::LexLess<X>());
_construct();
}
ConvexHull::ConvexHull(std::vector<Point> const &pts)
: _lower(0)
{
//if (pts.size() > 16) { // arbitrary threshold
// _prune(pts.begin(), pts.end(), _boundary);
//} else {
_boundary = pts;
std::sort(_boundary.begin(), _boundary.end(), Point::LexLess<X>());
//}
_construct();
}
bool ConvexHull::_is_clockwise_turn(Point const &a, Point const &b, Point const &c)
{
if (b == c) return false;
return cross(b-a, c-a) > 0;
}
void ConvexHull::_construct()
{
// _boundary must already be sorted in LexLess<X> order
if (_boundary.empty()) {
_lower = 0;
return;
}
if (_boundary.size() == 1 || (_boundary.size() == 2 && _boundary[0] == _boundary[1])) {
_boundary.resize(1);
_lower = 1;
return;
}
if (_boundary.size() == 2) {
_lower = 2;
return;
}
std::size_t k = 2;
for (std::size_t i = 2; i < _boundary.size(); ++i) {
while (k >= 2 && !_is_clockwise_turn(_boundary[k-2], _boundary[k-1], _boundary[i])) {
--k;
}
std::swap(_boundary[k++], _boundary[i]);
}
_lower = k;
std::sort(_boundary.begin() + k, _boundary.end(), Point::LexGreater<X>());
_boundary.push_back(_boundary.front());
for (std::size_t i = _lower; i < _boundary.size(); ++i) {
while (k > _lower && !_is_clockwise_turn(_boundary[k-2], _boundary[k-1], _boundary[i])) {
--k;
}
std::swap(_boundary[k++], _boundary[i]);
}
_boundary.resize(k-1);
}
double ConvexHull::area() const
{
if (size() <= 2) return 0;
double a = 0;
for (std::size_t i = 0; i < size()-1; ++i) {
a += cross(_boundary[i], _boundary[i+1]);
}
a += cross(_boundary.back(), _boundary.front());
return fabs(a * 0.5);
}
OptRect ConvexHull::bounds() const
{
OptRect ret;
if (empty()) return ret;
ret = Rect(left(), top(), right(), bottom());
return ret;
}
Point ConvexHull::topPoint() const
{
Point ret;
ret[Y] = std::numeric_limits<Coord>::infinity();
for (UpperIterator i = upperHull().begin(); i != upperHull().end(); ++i) {
if (ret[Y] >= i->y()) {
ret = *i;
} else {
break;
}
}
return ret;
}
Point ConvexHull::bottomPoint() const
{
Point ret;
ret[Y] = -std::numeric_limits<Coord>::infinity();
for (LowerIterator j = lowerHull().begin(); j != lowerHull().end(); ++j) {
if (ret[Y] <= j->y()) {
ret = *j;
} else {
break;
}
}
return ret;
}
template <typename Iter, typename Lex>
bool below_x_monotonic_polyline(Point const &p, Iter first, Iter last, Lex lex)
{
typename Lex::Secondary above;
Iter f = std::lower_bound(first, last, p, lex);
if (f == last) return false;
if (f == first) {
if (p == *f) return true;
return false;
}
Point a = *(f-1), b = *f;
if (a[X] == b[X]) {
if (above(p[Y], a[Y]) || above(b[Y], p[Y])) return false;
} else {
// TODO: maybe there is a more numerically stable method
Coord y = lerp((p[X] - a[X]) / (b[X] - a[X]), a[Y], b[Y]);
if (above(p[Y], y)) return false;
}
return true;
}
bool ConvexHull::contains(Point const &p) const
{
if (_boundary.empty()) return false;
if (_boundary.size() == 1) {
if (_boundary[0] == p) return true;
return false;
}
// 1. verify that the point is in the relevant X range
if (p[X] < _boundary[0][X] || p[X] > _boundary[_lower-1][X]) return false;
// 2. check whether it is below the upper hull
UpperIterator ub = upperHull().begin(), ue = upperHull().end();
if (!below_x_monotonic_polyline(p, ub, ue, Point::LexLess<X>())) return false;
// 3. check whether it is above the lower hull
LowerIterator lb = lowerHull().begin(), le = lowerHull().end();
if (!below_x_monotonic_polyline(p, lb, le, Point::LexGreater<X>())) return false;
return true;
}
bool ConvexHull::contains(Rect const &r) const
{
for (unsigned i = 0; i < 4; ++i) {
if (!contains(r.corner(i))) return false;
}
return true;
}
bool ConvexHull::contains(ConvexHull const &ch) const
{
// TODO: requires interiorContains.
// We have to check all points of ch, and each point takes logarithmic time.
// If there are more points in ch that here, it is faster to make the check
// the other way around.
/*if (ch.size() > size()) {
for (iterator i = begin(); i != end(); ++i) {
if (ch.interiorContains(*i)) return false;
}
return true;
}*/
for (iterator i = ch.begin(); i != ch.end(); ++i) {
if (!contains(*i)) return false;
}
return true;
}
void ConvexHull::swap(ConvexHull &other)
{
_boundary.swap(other._boundary);
std::swap(_lower, other._lower);
}
void ConvexHull::swap(std::vector<Point> &pts)
{
_boundary.swap(pts);
_lower = 0;
std::sort(_boundary.begin(), _boundary.end(), Point::LexLess<X>());
_construct();
}
#if 0
/*** SignedTriangleArea
* returns the area of the triangle defined by p0, p1, p2. A clockwise triangle has positive area.
*/
double
SignedTriangleArea(Point p0, Point p1, Point p2) {
return cross((p1 - p0), (p2 - p0));
}
class angle_cmp{
public:
Point o;
angle_cmp(Point o) : o(o) {}
#if 0
bool
operator()(Point a, Point b) {
// not remove this check or std::sort could crash
if (a == b) return false;
Point da = a - o;
Point db = b - o;
if (da == -db) return false;
#if 1
double aa = da[0];
double ab = db[0];
if((da[1] == 0) && (db[1] == 0))
return da[0] < db[0];
if(da[1] == 0)
return true; // infinite tangent
if(db[1] == 0)
return false; // infinite tangent
aa = da[0] / da[1];
ab = db[0] / db[1];
if(aa > ab)
return true;
#else
//assert((ata > atb) == (aa < ab));
double aa = atan2(da);
double ab = atan2(db);
if(aa < ab)
return true;
#endif
if(aa == ab)
return L2sq(da) < L2sq(db);
return false;
}
#else
bool operator() (Point const& a, Point const& b)
{
// not remove this check or std::sort could generate
// a segmentation fault because it needs a strict '<'
// but due to round errors a == b doesn't mean dxy == dyx
if (a == b) return false;
Point da = a - o;
Point db = b - o;
if (da == -db) return false;
double dxy = da[X] * db[Y];
double dyx = da[Y] * db[X];
if (dxy > dyx) return true;
else if (dxy < dyx) return false;
return L2sq(da) < L2sq(db);
}
#endif
};
//Mathematically incorrect mod, but more useful.
int mod(int i, int l) {
return i >= 0 ?
i % l : (i % l) + l;
}
//OPT: usages can often be replaced by conditions
/*** ConvexHull::add_point
* to add a point we need to find whether the new point extends the boundary, and if so, what it
* obscures. Tarjan? Jarvis?*/
void
ConvexHull::merge(Point p) {
std::vector<Point> out;
int len = boundary.size();
if(len < 2) {
if(boundary.empty() || boundary[0] != p)
boundary.push_back(p);
return;
}
bool pushed = false;
bool pre = is_left(p, -1);
for(int i = 0; i < len; i++) {
bool cur = is_left(p, i);
if(pre) {
if(cur) {
if(!pushed) {
out.push_back(p);
pushed = true;
}
continue;
}
else if(!pushed) {
out.push_back(p);
pushed = true;
}
}
out.push_back(boundary[i]);
pre = cur;
}
boundary = out;
}
//OPT: quickly find an obscured point and find the bounds by extending from there. then push all points not within the bounds in order.
//OPT: use binary searches to find the actual starts/ends, use known rights as boundaries. may require cooperation of find_left algo.
/*** ConvexHull::is_clockwise
* We require that successive pairs of edges always turn right.
* We return false on collinear points
* proposed algorithm: walk successive edges and require triangle area is positive.
*/
bool
ConvexHull::is_clockwise() const {
if(is_degenerate())
return true;
Point first = boundary[0];
Point second = boundary[1];
for(std::vector<Point>::const_iterator it(boundary.begin()+2), e(boundary.end());
it != e;) {
if(SignedTriangleArea(first, second, *it) > 0)
return false;
first = second;
second = *it;
++it;
}
return true;
}
/*** ConvexHull::top_point_first
* We require that the first point in the convex hull has the least y coord, and that off all such points on the hull, it has the least x coord.
* proposed algorithm: track lexicographic minimum while walking the list.
*/
bool
ConvexHull::top_point_first() const {
if(size() <= 1) return true;
std::vector<Point>::const_iterator pivot = boundary.begin();
for(std::vector<Point>::const_iterator it(boundary.begin()+1),
e(boundary.end());
it != e; it++) {
if((*it)[1] < (*pivot)[1])
pivot = it;
else if(((*it)[1] == (*pivot)[1]) &&
((*it)[0] < (*pivot)[0]))
pivot = it;
}
return pivot == boundary.begin();
}
//OPT: since the Y values are orderly there should be something like a binary search to do this.
bool
ConvexHull::meets_invariants() const {
return is_clockwise() && top_point_first();
}
/*** ConvexHull::is_degenerate
* We allow three degenerate cases: empty, 1 point and 2 points. In many cases these should be handled explicitly.
*/
bool
ConvexHull::is_degenerate() const {
return boundary.size() < 3;
}
int sgn(double x) {
if(x == 0) return 0;
return (x<0)?-1:1;
}
bool same_side(Point L[2], Point xs[4]) {
int side = 0;
for(int i = 0; i < 4; i++) {
int sn = sgn(SignedTriangleArea(L[0], L[1], xs[i]));
if(sn && !side)
side = sn;
else if(sn != side) return false;
}
return true;
}
/** find bridging pairs between two convex hulls.
* this code is based on Hormoz Pirzadeh's masters thesis. There is room for optimisation:
* 1. reduce recomputation
* 2. use more efficient angle code
* 3. write as iterator
*/
std::vector<pair<int, int> > bridges(ConvexHull a, ConvexHull b) {
vector<pair<int, int> > ret;
// 1. find maximal points on a and b
int ai = 0, bi = 0;
// 2. find first copodal pair
double ap_angle = atan2(a[ai+1] - a[ai]);
double bp_angle = atan2(b[bi+1] - b[bi]);
Point L[2] = {a[ai], b[bi]};
while(ai < int(a.size()) || bi < int(b.size())) {
if(ap_angle == bp_angle) {
// In the case of parallel support lines, we must consider all four pairs of copodal points
{
assert(0); // untested
Point xs[4] = {a[ai-1], a[ai+1], b[bi-1], b[bi+1]};
if(same_side(L, xs)) ret.push_back(make_pair(ai, bi));
xs[2] = b[bi];
xs[3] = b[bi+2];
if(same_side(L, xs)) ret.push_back(make_pair(ai, bi));
xs[0] = a[ai];
xs[1] = a[ai+2];
if(same_side(L, xs)) ret.push_back(make_pair(ai, bi));
xs[2] = b[bi-1];
xs[3] = b[bi+1];
if(same_side(L, xs)) ret.push_back(make_pair(ai, bi));
}
ai++;
ap_angle += angle_between(a[ai] - a[ai-1], a[ai+1] - a[ai]);
L[0] = a[ai];
bi++;
bp_angle += angle_between(b[bi] - b[bi-1], b[bi+1] - b[bi]);
L[1] = b[bi];
std::cout << "parallel\n";
} else if(ap_angle < bp_angle) {
ai++;
ap_angle += angle_between(a[ai] - a[ai-1], a[ai+1] - a[ai]);
L[0] = a[ai];
Point xs[4] = {a[ai-1], a[ai+1], b[bi-1], b[bi+1]};
if(same_side(L, xs)) ret.push_back(make_pair(ai, bi));
} else {
bi++;
bp_angle += angle_between(b[bi] - b[bi-1], b[bi+1] - b[bi]);
L[1] = b[bi];
Point xs[4] = {a[ai-1], a[ai+1], b[bi-1], b[bi+1]};
if(same_side(L, xs)) ret.push_back(make_pair(ai, bi));
}
}
return ret;
}
unsigned find_bottom_right(ConvexHull const &a) {
unsigned it = 1;
while(it < a.boundary.size() &&
a.boundary[it][Y] > a.boundary[it-1][Y])
it++;
return it-1;
}
/*** ConvexHull sweepline_intersection(ConvexHull a, ConvexHull b);
* find the intersection between two convex hulls. The intersection is also a convex hull.
* (Proof: take any two points both in a and in b. Any point between them is in a by convexity,
* and in b by convexity, thus in both. Need to prove still finite bounds.)
* This algorithm works by sweeping a line down both convex hulls in parallel, working out the left and right edges of the new hull.
*/
ConvexHull sweepline_intersection(ConvexHull const &a, ConvexHull const &b) {
ConvexHull ret;
unsigned al = 0;
unsigned bl = 0;
while(al+1 < a.boundary.size() &&
(a.boundary[al+1][Y] > b.boundary[bl][Y])) {
al++;
}
while(bl+1 < b.boundary.size() &&
(b.boundary[bl+1][Y] > a.boundary[al][Y])) {
bl++;
}
// al and bl now point to the top of the first pair of edges that overlap in y value
//double sweep_y = std::min(a.boundary[al][Y],
// b.boundary[bl][Y]);
return ret;
}
/*** ConvexHull intersection(ConvexHull a, ConvexHull b);
* find the intersection between two convex hulls. The intersection is also a convex hull.
* (Proof: take any two points both in a and in b. Any point between them is in a by convexity,
* and in b by convexity, thus in both. Need to prove still finite bounds.)
*/
ConvexHull intersection(ConvexHull /*a*/, ConvexHull /*b*/) {
ConvexHull ret;
/*
int ai = 0, bi = 0;
int aj = a.boundary.size() - 1;
int bj = b.boundary.size() - 1;
*/
/*while (true) {
if(a[ai]
}*/
return ret;
}
template <typename T>
T idx_to_pair(pair<T, T> p, int idx) {
return idx?p.second:p.first;
}
/*** ConvexHull merge(ConvexHull a, ConvexHull b);
* find the smallest convex hull that surrounds a and b.
*/
ConvexHull merge(ConvexHull a, ConvexHull b) {
ConvexHull ret;
std::cout << "---\n";
std::vector<pair<int, int> > bpair = bridges(a, b);
// Given our list of bridges {(pb1, qb1), ..., (pbk, qbk)}
// we start with the highest point in p0, q0, say it is p0.
// then the merged hull is p0, ..., pb1, qb1, ..., qb2, pb2, ...
// In other words, either of the two polygons vertices are added in order until the vertex coincides with a bridge point, at which point we swap.
unsigned state = (a[0][Y] < b[0][Y])?0:1;
ret.boundary.reserve(a.size() + b.size());
ConvexHull chs[2] = {a, b};
unsigned idx = 0;
for(unsigned k = 0; k < bpair.size(); k++) {
unsigned limit = idx_to_pair(bpair[k], state);
std::cout << bpair[k].first << " , " << bpair[k].second << "; "
<< idx << ", " << limit << ", s: "
<< state
<< " \n";
while(idx <= limit) {
ret.boundary.push_back(chs[state][idx++]);
}
state = 1-state;
idx = idx_to_pair(bpair[k], state);
}
while(idx < chs[state].size()) {
ret.boundary.push_back(chs[state][idx++]);
}
return ret;
}
ConvexHull graham_merge(ConvexHull a, ConvexHull b) {
ConvexHull result;
// we can avoid the find pivot step because of top_point_first
if(b.boundary[0] <= a.boundary[0])
swap(a, b);
result.boundary = a.boundary;
result.boundary.insert(result.boundary.end(),
b.boundary.begin(), b.boundary.end());
/** if we modified graham scan to work top to bottom as proposed in lect754.pdf we could replace the
angle sort with a simple merge sort type algorithm. furthermore, we could do the graham scan
online, avoiding a bunch of memory copies. That would probably be linear. -- njh*/
result.angle_sort();
result.graham_scan();
return result;
}
ConvexHull andrew_merge(ConvexHull a, ConvexHull b) {
ConvexHull result;
// we can avoid the find pivot step because of top_point_first
if(b.boundary[0] <= a.boundary[0])
swap(a, b);
result.boundary = a.boundary;
result.boundary.insert(result.boundary.end(),
b.boundary.begin(), b.boundary.end());
/** if we modified graham scan to work top to bottom as proposed in lect754.pdf we could replace the
angle sort with a simple merge sort type algorithm. furthermore, we could do the graham scan
online, avoiding a bunch of memory copies. That would probably be linear. -- njh*/
result.andrew_scan();
return result;
}
//TODO: reinstate
/*ConvexCover::ConvexCover(Path const &sp) : path(&sp) {
cc.reserve(sp.size());
for(Geom::Path::const_iterator it(sp.begin()), end(sp.end()); it != end; ++it) {
cc.push_back(ConvexHull((*it).begin(), (*it).end()));
}
}*/
double ConvexHull::centroid_and_area(Geom::Point& centroid) const {
const unsigned n = boundary.size();
if (n < 2)
return 0;
if(n < 3) {
centroid = (boundary[0] + boundary[1])/2;
return 0;
}
Geom::Point centroid_tmp(0,0);
double atmp = 0;
for (unsigned i = n-1, j = 0; j < n; i = j, j++) {
const double ai = cross(boundary[j], boundary[i]);
atmp += ai;
centroid_tmp += (boundary[j] + boundary[i])*ai; // first moment.
}
if (atmp != 0) {
centroid = centroid_tmp / (3 * atmp);
}
return atmp / 2;
}
// TODO: This can be made lg(n) using golden section/fibonacci search three starting points, say 0,
// n/2, n-1 construct a new point, say (n/2 + n)/2 throw away the furthest boundary point iterate
// until interval is a single value
Point const * ConvexHull::furthest(Point direction) const {
Point const * p = &boundary[0];
double d = dot(*p, direction);
for(unsigned i = 1; i < boundary.size(); i++) {
double dd = dot(boundary[i], direction);
if(d < dd) {
p = &boundary[i];
d = dd;
}
}
return p;
}
// returns (a, (b,c)), three points which define the narrowest diameter of the hull as the pair of
// lines going through b,c, and through a, parallel to b,c TODO: This can be made linear time by
// moving point tc incrementally from the previous value (it can only move in one direction). It
// is currently n*O(furthest)
double ConvexHull::narrowest_diameter(Point &a, Point &b, Point &c) {
Point tb = boundary.back();
double d = std::numeric_limits<double>::max();
for(unsigned i = 0; i < boundary.size(); i++) {
Point tc = boundary[i];
Point n = -rot90(tb-tc);
Point ta = *furthest(n);
double td = dot(n, ta-tb)/dot(n,n);
if(td < d) {
a = ta;
b = tb;
c = tc;
d = td;
}
tb = tc;
}
return d;
}
#endif
};
/*
Local Variables:
mode:c++
c-file-style:"stroustrup"
c-file-offsets:((innamespace . 0)(inline-open . 0)(case-label . +))
indent-tabs-mode:nil
fill-column:99
End:
*/
// vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:fileencoding=utf-8:textwidth=99 :
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