154 lines
4.7 KiB
C++
154 lines
4.7 KiB
C++
/*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*
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* Copyright 2015 Danny Robson <danny@nerdcruft.net>
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*/
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#if defined(__UTIL_NOISE_BASIS_PATCH_IPP)
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#error
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#endif
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#define __UTIL_NOISE_BASIS_PATCH_IPP
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#include "../../types.hpp"
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#include "../../vector.hpp"
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namespace util { namespace noise { namespace basis {
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///////////////////////////////////////////////////////////////////////////
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template <size_t S, typename T>
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patch<S,T>::patch (seed_t _seed, T _width):
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m_width (_width),
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m_power (exactly_zero (_width)
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? std::numeric_limits<T>::infinity ()
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: std::log (THRESHOLD) / std::log (1 - _width)),
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m_seed (_seed)
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{ ; }
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///////////////////////////////////////////////////////////////////////////
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template <size_t S, typename T>
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range<T>
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patch<S,T>::bounds (void) const
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{
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return { T{0}, T{1} };
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}
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///////////////////////////////////////////////////////////////////////////
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template <size_t S, typename T>
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T
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patch<S,T>::operator () (point<S,T> p) const noexcept
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{
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static const size_t COUNT = type::distance<S,2>::OFFSET_SIZE;
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// extract integer and fractional parts. be careful to always round down
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auto p_int = floor (p).template cast<intmax_t> ();
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auto p_rem = (p - p_int).template as<point> ();
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// find the distances to each neighbour's centroid.
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util::point<S,T> centres[COUNT];
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std::transform (std::begin (this->OFFSETS),
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std::end (this->OFFSETS),
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std::begin (centres),
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[this,p_int] (auto i) { return rand::coord<point,T> (m_seed, p_int + i) + i; });
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T distances[COUNT];
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std::transform (std::begin (centres),
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std::end (centres),
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std::begin (distances),
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[p_rem] (auto i) { return util::distance (p_rem, i); });
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// sort the distances using indices so we can reuse indices into
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// 'OFFSETS' to generate the random patch values
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unsigned indices[COUNT];
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std::iota (std::begin (indices), std::end (indices), 0);
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std::sort (std::begin (indices),
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std::end (indices),
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[&] (auto a, auto b) {
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return distances[a] < distances[b];
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});
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// setup normalisation for the distances to the nearest points. the
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// neighbourhood size is implicitly specified by the 1.5 unit maximum
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// distance.
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const size_t hi_off = pow(3,S);
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const auto lo = distances[indices[0 ]];
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const auto hi = distances[indices[hi_off]];
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T out = 0.f;
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T sumw = 0.f;
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// sum the weight values of each neighbour. weight by a function of
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// the distance. we use an power function which allows a known width
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// to blend.
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for (size_t i = 0; i < hi_off; ++i)
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{
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auto v = rand::scalar<T> (
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m_seed,
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p_int + this->OFFSETS[indices[i]]
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);
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auto d = (distances[indices[i]] - lo) / (hi - lo);
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auto w = std::pow (1 - d, m_power);
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sumw += w;
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out += v * w;
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}
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return out / sumw;
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}
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///////////////////////////////////////////////////////////////////////////
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template <size_t S, typename T>
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seed_t
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patch<S,T>::seed (void) const
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{
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return m_seed;
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}
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//-------------------------------------------------------------------------
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template <size_t S, typename T>
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seed_t
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patch<S,T>::seed (util::noise::seed_t _seed)
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{
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return m_seed = _seed;
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}
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///////////////////////////////////////////////////////////////////////////
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template <size_t S, typename T>
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T
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patch<S,T>::width (void) const
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{
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return m_width;
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}
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//-------------------------------------------------------------------------
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template <size_t S, typename T>
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T
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patch<S,T>::width (T _width)
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{
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m_width = _width;
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m_power = exactly_zero (_width)
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? std::numeric_limits<T>::infinity ()
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: std::log (THRESHOLD) / std::log (1 - _width);
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return m_width;
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}
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} } }
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