libcruft-util/geom/sample/surface.hpp

106 lines
3.4 KiB
C++

/*
* This Source Code Form is subject to the terms of the Mozilla Public
* License, v. 2.0. If a copy of the MPL was not distributed with this
* file, You can obtain one at http://mozilla.org/MPL/2.0/.
*
* Copyright 2015-2018 Danny Robson <danny@nerdcruft.net>
*/
#pragma once
#include "volume.hpp"
#include "../ops.hpp"
#include "../../coord/fwd.hpp"
#include "../../extent.hpp"
#include "../../random.hpp"
#include <cstddef>
#include <random>
///////////////////////////////////////////////////////////////////////////////
namespace cruft::geom::sample {
/// Approximate a poisson disc sampling through the "Mitchell's Best
/// Candidate" algorithm.
///
/// 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 <typename SamplerT, typename DistanceT, typename GeneratorT>
auto
poisson (SamplerT const &target,
GeneratorT &&gen,
DistanceT &&minimum_distance,
size_t candidates_count)
{
using point_type = decltype (target.eval (gen));
using value_type = typename point_type::value_type;
std::vector<point_type> selected;
std::vector<point_type> candidates;
// prime the found elements list with an initial point we can
// perform distance calculations on
selected.push_back (target.eval (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.eval (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<value_type>::lowest ();
size_t best_index = 0;
for (size_t i = 0; i < candidates.size (); ++i) {
auto const p = candidates[i];
auto d2 = std::numeric_limits<value_type>::max ();
// find the minimum distance from this candidate to the
// selected points
for (auto q: selected)
d2 = cruft::min (d2, cruft::distance2 (p, q));
// record if it's the furthest away
if (d2 > best_distance2 && d2 > cruft::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;
}
/// A surface sampler specialisation for 2d extents.
///
/// The actual work is handed off to the volume sampler, as it's
/// equivalent in 2 dimensions.
template <typename T>
class surface<extent<2,T>> :
public volume<extent<2,T>>
{ using volume<extent<2,T>>::volume; };
}