/****************************************************************************** * @file * @brief Implementation of the [Convex * Hull](https://en.wikipedia.org/wiki/Convex_hull) implementation using [Graham * Scan](https://en.wikipedia.org/wiki/Graham_scan) * @details * In geometry, the convex hull or convex envelope or convex closure of a shape * is the smallest convex set that contains it. The convex hull may be defined * either as the intersection of all convex sets containing a given subset of a * Euclidean space, or equivalently as the set of all convex combinations of * points in the subset. For a bounded subset of the plane, the convex hull may * be visualized as the shape enclosed by a rubber band stretched around the * subset. * * The worst case time complexity of Jarvis’s Algorithm is O(n^2). Using * Graham’s scan algorithm, we can find Convex Hull in O(nLogn) time. * * ### Implementation * * Sort points * We first find the bottom-most point. The idea is to pre-process * points be sorting them with respect to the bottom-most point. Once the points * are sorted, they form a simple closed path. * The sorting criteria is to use the orientation to compare angles without * actually computing them (See the compare() function below) because * computation of actual angles would be inefficient since trigonometric * functions are not simple to evaluate. * * Accept or Reject Points * Once we have the closed path, the next step is to traverse the path and * remove concave points on this path using orientation. The first two points in * sorted array are always part of Convex Hull. For remaining points, we keep * track of recent three points, and find the angle formed by them. Let the * three points be prev(p), curr(c) and next(n). If the orientation of these * points (considering them in the same order) is not counterclockwise, we * discard c, otherwise we keep it. * * @author [Lajat Manekar](https://github.com/Lazeeez) * *******************************************************************************/ #include /// for std::assert #include /// for IO Operations #include /// for std::vector #include "./graham_scan_functions.hpp" /// for all the functions used /******************************************************************************* * @brief Self-test implementations * @returns void *******************************************************************************/ static void test() { std::vector points = { {0, 3}, {1, 1}, {2, 2}, {4, 4}, {0, 0}, {1, 2}, {3, 1}, {3, 3}}; std::vector expected_result = { {0, 3}, {4, 4}, {3, 1}, {0, 0}}; std::vector derived_result; std::vector res; derived_result = geometry::grahamscan::convexHull(points, points.size()); std::cout << "1st test: "; for (int i = 0; i < expected_result.size(); i++) { assert(derived_result[i].x == expected_result[i].x); assert(derived_result[i].y == expected_result[i].y); } std::cout << "passed!" << std::endl; } /******************************************************************************* * @brief Main function * @returns 0 on exit *******************************************************************************/ int main() { test(); // run self-test implementations return 0; }