/* * Licensed under the Apache License, Version 2.0 (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.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * * Copyright 2015-2018 Danny Robson */ #ifndef __UTIL_GEOM_SAMPLE_HPP #define __UTIL_GEOM_SAMPLE_HPP #include "../coord/fwd.hpp" #include "../extent.hpp" #include "ops.hpp" #include #include /////////////////////////////////////////////////////////////////////////////// namespace util::geom { /// a function object that selects a uniformly random point inside a shape /// using a provided random generator. the point will lie within the shape, /// inclusive of boundaries. /// /// may be specialised for arbitrary shapes but uses rejection sampling /// as a safe default. this implies that execution may not take a constant /// time. /// /// \tparam S coordinate type dimension /// \tparam T value type for the shape/coordinate /// \tparam K the shape type to test /// \tparam G a UniformRandomBitGenerator, eg std::min19937 template < size_t S, typename T, template class K, typename G > struct sampler { static point fn (K k, G &g) { auto b = bounds (k); while (true) { auto p = sample (b, g); if (intersects (k, p)) return p; } } }; /////////////////////////////////////////////////////////////////////////// /// a convenience function that calls sample::fn to select a random point /// in a provided shape. template < size_t S, typename T, template class K, typename G // random generator > point sample (K k, G &g) { return sampler::fn (k, g); } std::vector poisson_sample (util::extent2i, float distance, int samples); namespace surface { // a generator of samples that lie on the surface of a shape template class sampler; template sampler (ShapeT const&) -> sampler>; //--------------------------------------------------------------------- template class sampler> { public: sampler (util::extent _target): target (_target) { ; } template util::point operator() (GeneratorT &&gen) const noexcept { util::point p; for (size_t i = 0; i < S; ++i) { if constexpr (std::is_floating_point_v) { p[i] = std::uniform_real_distribution (0, target[i]) (gen); } else { CHECK_GE (target[i], T{1}); p[i] = std::uniform_int_distribution (0, target[i] - 1) (gen); } } return p; } private: util::extent target; }; /// approximate a poisson disc sampling through mitchell's best candidate. /// /// try to keep adding a new point to a set. each new point is the /// best of a set of candidates. the 'best' is the point that is /// furthest from all selected points. /// /// \return a vector of the computed points template auto poisson (SamplerT const &target, GeneratorT &&gen, DistanceT &&minimum_distance, size_t candidates_count) { using point_type = decltype (target (gen)); using value_type = typename point_type::value_type; std::vector selected; std::vector candidates; // prime the found elements list with an initial point we can // perform distance calculations on selected.push_back (target (gen)); // keep trying to add one more new point while (1) { // generate a group of candidate points candidates.clear (); std::generate_n ( std::back_inserter (candidates), candidates_count, [&] (void) { return target (gen); } ); // find the point whose minimum distance to the existing // points is the greatest (while also being greater than the // required minimum distance); auto best_distance2 = std::numeric_limits::lowest (); size_t best_index; for (size_t i = 0; i < candidates.size (); ++i) { auto const p = candidates[i]; auto d2 = std::numeric_limits::max (); // find the minimum distance from this candidate to the // selected points for (auto q: selected) d2 = util::min (d2, util::distance2 (p, q)); // record if it's the furthest away if (d2 > best_distance2 && d2 > util::pow (minimum_distance (p), 2)) { best_distance2 = d2; best_index = i; } } // if we didn't find a suitable point then we give up and // return the points we found, otherwise record the best point if (best_distance2 <= 0) break; selected.push_back (candidates[best_index]); } return selected; } } } #endif