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The JTS Topology Suite is an API for modelling and manipulating 2-dimensional linear geometry. It provides numerous geometric predicates and functions. JTS conforms to the Simple Features Specification for SQL published by the Open GIS Consortium.

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/*
* The JTS Topology Suite is a collection of Java classes that
* implement the fundamental operations required to validate a given
* geo-spatial data set to a known topological specification.
*
* Copyright (C) 2001 Vivid Solutions
*
* This library is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation; either
* version 2.1 of the License, or (at your option) any later version.
*
* This library is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with this library; if not, write to the Free Software
* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA
*
* For more information, contact:
*
*     Vivid Solutions
*     Suite #1A
*     2328 Government Street
*     Victoria BC  V8T 5G5
*     Canada
*
*     (250)385-6040
*     www.vividsolutions.com
 */
package com.vividsolutions.jts.algorithm;
import com.vividsolutions.jts.geom.*;
import com.vividsolutions.jts.util.Assert;

import java.util.*;
import com.vividsolutions.jts.util.UniqueCoordinateArrayFilter;

/**
 * Computes the convex hull of a {@link Geometry}.
 * The convex hull is the smallest convex Geometry that contains all the
 * points in the input Geometry.
 * 

* Uses the Graham Scan algorithm. * *@version 1.7 */ public class ConvexHull { private GeometryFactory geomFactory; private Coordinate[] inputPts; /** * Create a new convex hull construction for the input {@link Geometry}. */ public ConvexHull(Geometry geometry) { this(extractCoordinates(geometry), geometry.getFactory()); } /** * Create a new convex hull construction for the input {@link Coordinate} array. */ public ConvexHull(Coordinate[] pts, GeometryFactory geomFactory) { inputPts = pts; this.geomFactory = geomFactory; } private static Coordinate[] extractCoordinates(Geometry geom) { UniqueCoordinateArrayFilter filter = new UniqueCoordinateArrayFilter(); geom.apply(filter); return filter.getCoordinates(); } /** * Returns a {@link Geometry} that represents the convex hull of the input * geometry. * The returned geometry contains the minimal number of points needed to * represent the convex hull. In particular, no more than two consecutive * points will be collinear. * * @return if the convex hull contains 3 or more points, a {@link Polygon}; * 2 points, a {@link LineString}; * 1 point, a {@link Point}; * 0 points, an empty {@link GeometryCollection}. */ public Geometry getConvexHull() { if (inputPts.length == 0) { return geomFactory.createGeometryCollection(null); } if (inputPts.length == 1) { return geomFactory.createPoint(inputPts[0]); } if (inputPts.length == 2) { return geomFactory.createLineString(inputPts); } Coordinate[] reducedPts = inputPts; // use heuristic to reduce points, if large if (inputPts.length > 50) { reducedPts = reduce(inputPts); } // sort points for Graham scan. Coordinate[] sortedPts = preSort(reducedPts); // Use Graham scan to find convex hull. Stack cHS = grahamScan(sortedPts); // Convert stack to an array. Coordinate[] cH = toCoordinateArray(cHS); // Convert array to appropriate output geometry. return lineOrPolygon(cH); } /** * An alternative to Stack.toArray, which is not present in earlier versions * of Java. */ protected Coordinate[] toCoordinateArray(Stack stack) { Coordinate[] coordinates = new Coordinate[stack.size()]; for (int i = 0; i < stack.size(); i++) { Coordinate coordinate = (Coordinate) stack.get(i); coordinates[i] = coordinate; } return coordinates; } /** * Uses a heuristic to reduce the number of points scanned * to compute the hull. * The heuristic is to find a polygon guaranteed to * be in (or on) the hull, and eliminate all points inside it. * A quadrilateral defined by the extremal points * in the four orthogonal directions * can be used, but even more inclusive is * to use an octilateral defined by the points in the 8 cardinal directions. *

* Note that even if the method used to determine the polygon vertices * is not 100% robust, this does not affect the robustness of the convex hull. *

* To satisfy the requirements of the Graham Scan algorithm, * the returned array has at least 3 entries. * * @param pts the points to reduce * @return the reduced list of points (at least 3) */ private Coordinate[] reduce(Coordinate[] inputPts) { //Coordinate[] polyPts = computeQuad(inputPts); Coordinate[] polyPts = computeOctRing(inputPts); //Coordinate[] polyPts = null; // unable to compute interior polygon for some reason if (polyPts == null) return inputPts; // LinearRing ring = geomFactory.createLinearRing(polyPts); // System.out.println(ring); // add points defining polygon TreeSet reducedSet = new TreeSet(); for (int i = 0; i < polyPts.length; i++) { reducedSet.add(polyPts[i]); } /** * Add all unique points not in the interior poly. * CGAlgorithms.isPointInRing is not defined for points actually on the ring, * but this doesn't matter since the points of the interior polygon * are forced to be in the reduced set. */ for (int i = 0; i < inputPts.length; i++) { if (! CGAlgorithms.isPointInRing(inputPts[i], polyPts)) { reducedSet.add(inputPts[i]); } } Coordinate[] reducedPts = CoordinateArrays.toCoordinateArray(reducedSet); // ensure that computed array has at least 3 points (not necessarily unique) if (reducedPts.length < 3) return padArray3(reducedPts); return reducedPts; } private Coordinate[] padArray3(Coordinate[] pts) { Coordinate[] pad = new Coordinate[3]; for (int i = 0; i < pad.length; i++) { if (i < pts.length) { pad[i] = pts[i]; } else pad[i] = pts[0]; } return pad; } private Coordinate[] preSort(Coordinate[] pts) { Coordinate t; // find the lowest point in the set. If two or more points have // the same minimum y coordinate choose the one with the minimu x. // This focal point is put in array location pts[0]. for (int i = 1; i < pts.length; i++) { if ((pts[i].y < pts[0].y) || ((pts[i].y == pts[0].y) && (pts[i].x < pts[0].x))) { t = pts[0]; pts[0] = pts[i]; pts[i] = t; } } // sort the points radially around the focal point. Arrays.sort(pts, 1, pts.length, new RadialComparator(pts[0])); //radialSort(pts); return pts; } /** * Uses the Graham Scan algorithm to compute the convex hull vertices. * * @param c a list of points, with at least 3 entries * @return a Stack containing the ordered points of the convex hull ring */ private Stack grahamScan(Coordinate[] c) { Coordinate p; Stack ps = new Stack(); p = (Coordinate) ps.push(c[0]); p = (Coordinate) ps.push(c[1]); p = (Coordinate) ps.push(c[2]); for (int i = 3; i < c.length; i++) { p = (Coordinate) ps.pop(); while (CGAlgorithms.computeOrientation((Coordinate) ps.peek(), p, c[i]) > 0) { p = (Coordinate) ps.pop(); } p = (Coordinate) ps.push(p); p = (Coordinate) ps.push(c[i]); } p = (Coordinate) ps.push(c[0]); return ps; } /** *@return whether the three coordinates are collinear and c2 lies between * c1 and c3 inclusive */ private boolean isBetween(Coordinate c1, Coordinate c2, Coordinate c3) { if (CGAlgorithms.computeOrientation(c1, c2, c3) != 0) { return false; } if (c1.x != c3.x) { if (c1.x <= c2.x && c2.x <= c3.x) { return true; } if (c3.x <= c2.x && c2.x <= c1.x) { return true; } } if (c1.y != c3.y) { if (c1.y <= c2.y && c2.y <= c3.y) { return true; } if (c3.y <= c2.y && c2.y <= c1.y) { return true; } } return false; } private Coordinate[] computeOctRing(Coordinate[] inputPts) { Coordinate[] octPts = computeOctPts(inputPts); CoordinateList coordList = new CoordinateList(); coordList.add(octPts, false); // points must all lie in a line if (coordList.size() < 3) { return null; } coordList.closeRing(); return coordList.toCoordinateArray(); } private Coordinate[] computeOctPts(Coordinate[] inputPts) { Coordinate[] pts = new Coordinate[8]; for (int j = 0; j < pts.length; j++) { pts[j] = inputPts[0]; } for (int i = 1; i < inputPts.length; i++) { if (inputPts[i].x < pts[0].x) { pts[0] = inputPts[i]; } if (inputPts[i].x - inputPts[i].y < pts[1].x - pts[1].y) { pts[1] = inputPts[i]; } if (inputPts[i].y > pts[2].y) { pts[2] = inputPts[i]; } if (inputPts[i].x + inputPts[i].y > pts[3].x + pts[3].y) { pts[3] = inputPts[i]; } if (inputPts[i].x > pts[4].x) { pts[4] = inputPts[i]; } if (inputPts[i].x - inputPts[i].y > pts[5].x - pts[5].y) { pts[5] = inputPts[i]; } if (inputPts[i].y < pts[6].y) { pts[6] = inputPts[i]; } if (inputPts[i].x + inputPts[i].y < pts[7].x + pts[7].y) { pts[7] = inputPts[i]; } } return pts; } /* // MD - no longer used, but keep for reference purposes private Coordinate[] computeQuad(Coordinate[] inputPts) { BigQuad bigQuad = bigQuad(inputPts); // Build a linear ring defining a big poly. ArrayList bigPoly = new ArrayList(); bigPoly.add(bigQuad.westmost); if (! bigPoly.contains(bigQuad.northmost)) { bigPoly.add(bigQuad.northmost); } if (! bigPoly.contains(bigQuad.eastmost)) { bigPoly.add(bigQuad.eastmost); } if (! bigPoly.contains(bigQuad.southmost)) { bigPoly.add(bigQuad.southmost); } // points must all lie in a line if (bigPoly.size() < 3) { return null; } // closing point bigPoly.add(bigQuad.westmost); Coordinate[] bigPolyArray = CoordinateArrays.toCoordinateArray(bigPoly); return bigPolyArray; } private BigQuad bigQuad(Coordinate[] pts) { BigQuad bigQuad = new BigQuad(); bigQuad.northmost = pts[0]; bigQuad.southmost = pts[0]; bigQuad.westmost = pts[0]; bigQuad.eastmost = pts[0]; for (int i = 1; i < pts.length; i++) { if (pts[i].x < bigQuad.westmost.x) { bigQuad.westmost = pts[i]; } if (pts[i].x > bigQuad.eastmost.x) { bigQuad.eastmost = pts[i]; } if (pts[i].y < bigQuad.southmost.y) { bigQuad.southmost = pts[i]; } if (pts[i].y > bigQuad.northmost.y) { bigQuad.northmost = pts[i]; } } return bigQuad; } private static class BigQuad { public Coordinate northmost; public Coordinate southmost; public Coordinate westmost; public Coordinate eastmost; } */ /** *@param vertices the vertices of a linear ring, which may or may not be * flattened (i.e. vertices collinear) *@return a 2-vertex LineString if the vertices are * collinear; otherwise, a Polygon with unnecessary * (collinear) vertices removed */ private Geometry lineOrPolygon(Coordinate[] coordinates) { coordinates = cleanRing(coordinates); if (coordinates.length == 3) { return geomFactory.createLineString(new Coordinate[]{coordinates[0], coordinates[1]}); // return new LineString(new Coordinate[]{coordinates[0], coordinates[1]}, // geometry.getPrecisionModel(), geometry.getSRID()); } LinearRing linearRing = geomFactory.createLinearRing(coordinates); return geomFactory.createPolygon(linearRing, null); } /** *@param vertices the vertices of a linear ring, which may or may not be * flattened (i.e. vertices collinear) *@return the coordinates with unnecessary (collinear) vertices * removed */ private Coordinate[] cleanRing(Coordinate[] original) { Assert.equals(original[0], original[original.length - 1]); ArrayList cleanedRing = new ArrayList(); Coordinate previousDistinctCoordinate = null; for (int i = 0; i <= original.length - 2; i++) { Coordinate currentCoordinate = original[i]; Coordinate nextCoordinate = original[i+1]; if (currentCoordinate.equals(nextCoordinate)) { continue; } if (previousDistinctCoordinate != null && isBetween(previousDistinctCoordinate, currentCoordinate, nextCoordinate)) { continue; } cleanedRing.add(currentCoordinate); previousDistinctCoordinate = currentCoordinate; } cleanedRing.add(original[original.length - 1]); Coordinate[] cleanedRingCoordinates = new Coordinate[cleanedRing.size()]; return (Coordinate[]) cleanedRing.toArray(cleanedRingCoordinates); } /** * Compares {@link Coordinate}s for their angle and distance * relative to an origin. * * @author Martin Davis * @version 1.7 */ private static class RadialComparator implements Comparator { private Coordinate origin; public RadialComparator(Coordinate origin) { this.origin = origin; } public int compare(Object o1, Object o2) { Coordinate p1 = (Coordinate) o1; Coordinate p2 = (Coordinate) o2; return polarCompare(origin, p1, p2); } /** * Given two points p and q compare them with respect to their radial * ordering about point o. First checks radial ordering. * If points are collinear, the comparison is based * on their distance to the origin. *

* p < q iff *

    *
  • ang(o-p) < ang(o-q) (e.g. o-p-q is CCW) *
  • or ang(o-p) == ang(o-q) && dist(o,p) < dist(o,q) *
* * @param o the origin * @param p a point * @param q another point * @return -1, 0 or 1 depending on whether p is less than, * equal to or greater than q */ private static int polarCompare(Coordinate o, Coordinate p, Coordinate q) { double dxp = p.x - o.x; double dyp = p.y - o.y; double dxq = q.x - o.x; double dyq = q.y - o.y; /* // MD - non-robust int result = 0; double alph = Math.atan2(dxp, dyp); double beta = Math.atan2(dxq, dyq); if (alph < beta) { result = -1; } if (alph > beta) { result = 1; } if (result != 0) return result; //*/ int orient = CGAlgorithms.computeOrientation(o, p, q); if (orient == CGAlgorithms.COUNTERCLOCKWISE) return 1; if (orient == CGAlgorithms.CLOCKWISE) return -1; // points are collinear - check distance double op = dxp * dxp + dyp * dyp; double oq = dxq * dxq + dyq * dyq; if (op < oq) { return -1; } if (op > oq) { return 1; } return 0; } } }




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