simple noise for planet surface
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1688DA83D222D0B5
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@ -164,7 +164,8 @@ void Application::run()
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SDL_ShowCursor(SDL_DISABLE);
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Input::getInstance().setMouseCoords(m_width/2, m_height/2);
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Planet* pl = new Planet(glm::vec3(0.0f,0.0f,0.0f), 500.0f);
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PlanetNoiseParams noise{128.f, 10.f, 2.f, 0.5f};
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Planet* pl = new Planet(glm::vec3(0.0f,0.0f,0.0f), 500.0f, noise);
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// Create the shader and link them together
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Shader& chunkShader = Shader::createShader("data/shaders/chunk.vert", "data/shaders/chunk.frag");
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chunkShader.linkShaders();
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@ -191,8 +192,8 @@ void Application::run()
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// TEST CODE
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glEnable(GL_DEPTH_TEST);
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//glEnable(GL_CULL_FACE);
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//glCullFace(GL_BACK);
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glEnable(GL_CULL_FACE);
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glCullFace(GL_BACK);
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pl->tick(m_camera, deltaTime);
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@ -1,7 +1,8 @@
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#include "planet/Planet.h"
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#include "planet/PlanetFace.h"
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Planet::Planet(glm::vec3 position, float radius) : m_position(position), m_radius(radius)
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Planet::Planet(glm::vec3 position, float radius, PlanetNoiseParams &noiseParams) :
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m_position(position), m_radius(radius), m_noise(noiseParams.frequency, noiseParams.amplitude, noiseParams.lacunarity, noiseParams.persistence)
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{
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for (int i = 0; i < 6; i++)
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{
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@ -2,14 +2,22 @@
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#define __PLANET_H__
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#include "util/Common.h"
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#include "util/SimplexNoise.h"
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#include "Shader.h"
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#include "Camera.h"
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struct PlanetNoiseParams {
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float frequency;
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float amplitude;
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float lacunarity;
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float persistence;
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};
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class PlanetFace;
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class Planet
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{
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public:
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Planet(glm::vec3 position, float radius);
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Planet(glm::vec3 position, float radius, PlanetNoiseParams &noiseParams);
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~Planet();
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inline void setLightDirection(glm::vec3 lightDir) { m_lightDir = lightDir; }
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@ -21,8 +29,11 @@ class Planet
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void tick(Camera* camera, GLfloat dtime);
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void draw(Camera* camera, Shader* shader);
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SimplexNoise& getNoise() { return m_noise; }
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glm::mat4 getTransformation();
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private:
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SimplexNoise m_noise;
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glm::vec3 m_position;
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float m_radius;
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@ -51,20 +51,20 @@ void PlanetFaceNode::tick(Camera* camera, GLfloat dtime, bool& tickUpdatedLOD, b
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float divisionLevel = (float)pow(2, m_level);
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float splitDistance = m_planet->getRadius() / divisionLevel;
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if (camToOrigin < splitDistance * 1.5 and m_leaf)
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if (camToOrigin < splitDistance * 1.5 && m_leaf)
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tickUpdatedLOD = this->subdivide();
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else if (camToOrigin > splitDistance * 2 and !m_leaf)
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else if (camToOrigin > splitDistance * 2 && !m_leaf)
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tickUpdatedLOD = this->merge();
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if (tickUpdatedLOD)
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return;
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// TODO: fix weird missing meshes
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// TODO: fix weird vanishing meshes
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if (m_leaf && m_generated == false)
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{
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generate();
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tickGeneratedFace = true;
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generate();
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return;
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}
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@ -129,16 +129,18 @@ void PlanetFaceNode::generate()
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// Normalize and multiply by radius to create a spherical mesh
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glm::vec3 vertNormal = glm::normalize(vertex);
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glm::vec3 pos = vertNormal * radius;
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glm::vec3 pos = (m_planet->getNoise().fractal(m_level + 1, vertNormal.x, vertNormal.y, vertNormal.z) + radius) * vertNormal;
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// Add
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// Add vertex
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vertices.push_back({ pos, vertNormal, glm::vec2(j * (1.0 / RESOLUTION), i * (1.0 / RESOLUTION)) });
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// Set center
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if ((i == RESOLUTION / 2 and j == RESOLUTION / 2))
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m_center = pos;
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}
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}
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// Create indices for mesh
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for (int gz = 0; gz < RESOLUTION - 1; gz++)
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{
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for (int gx = 0; gx < RESOLUTION - 1; gx++)
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@ -185,12 +187,13 @@ bool PlanetFaceNode::subdivide()
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glm::vec3 stepLeft = m_left * (radius / (float)pow(2, lv));
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glm::vec3 stepForward = m_forward * (radius / (float)pow(2, lv));
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m_leaf = false;
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m_children[0] = new PlanetFaceNode(m_planet, m_planetFace, m_pos + stepForward, lv);
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m_children[1] = new PlanetFaceNode(m_planet, m_planetFace, (m_pos + stepLeft) + stepForward, lv);
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m_children[2] = new PlanetFaceNode(m_planet, m_planetFace, m_pos, lv);
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m_children[3] = new PlanetFaceNode(m_planet, m_planetFace, (m_pos + stepLeft), lv);
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m_leaf = false;
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this->dispose();
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return true;
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@ -247,6 +250,7 @@ void PlanetFace::draw(Camera* camera, Shader* shader)
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void PlanetFace::tick(Camera* camera, GLfloat dtime)
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{
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// Do only one operation per tick, TODO: maybe allow more?
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bool tickUpdatedLOD = false;
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bool tickGeneratedFace = false;
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m_planetFace->tick(camera, dtime, tickUpdatedLOD, tickGeneratedFace);
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@ -0,0 +1,475 @@
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/**
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* @file SimplexNoise.cpp
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* @brief A Perlin Simplex Noise C++ Implementation (1D, 2D, 3D).
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*
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* Copyright (c) 2014-2018 Sebastien Rombauts (sebastien.rombauts@gmail.com)
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*
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* This C++ implementation is based on the speed-improved Java version 2012-03-09
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* by Stefan Gustavson (original Java source code in the public domain).
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* http://webstaff.itn.liu.se/~stegu/simplexnoise/SimplexNoise.java:
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* - Based on example code by Stefan Gustavson (stegu@itn.liu.se).
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* - Optimisations by Peter Eastman (peastman@drizzle.stanford.edu).
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* - Better rank ordering method by Stefan Gustavson in 2012.
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*
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* This implementation is "Simplex Noise" as presented by
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* Ken Perlin at a relatively obscure and not often cited course
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* session "Real-Time Shading" at Siggraph 2001 (before real
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* time shading actually took on), under the title "hardware noise".
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* The 3D function is numerically equivalent to his Java reference
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* code available in the PDF course notes, although I re-implemented
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* it from scratch to get more readable code. The 1D, 2D and 4D cases
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* were implemented from scratch by me from Ken Perlin's text.
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*
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* Distributed under the MIT License (MIT) (See accompanying file LICENSE.txt
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* or copy at http://opensource.org/licenses/MIT)
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*/
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#include "SimplexNoise.h"
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#include <cstdint> // int32_t/uint8_t
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/**
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* Computes the largest integer value not greater than the float one
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*
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* This method is faster than using (int32_t)std::floor(fp).
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*
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* I measured it to be approximately twice as fast:
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* float: ~18.4ns instead of ~39.6ns on an AMD APU),
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* double: ~20.6ns instead of ~36.6ns on an AMD APU),
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* Reference: http://www.codeproject.com/Tips/700780/Fast-floor-ceiling-functions
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*
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* @param[in] fp float input value
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*
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* @return largest integer value not greater than fp
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*/
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static inline int32_t fastfloor(float fp) {
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int32_t i = static_cast<int32_t>(fp);
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return (fp < i) ? (i - 1) : (i);
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}
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/**
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* Permutation table. This is just a random jumble of all numbers 0-255.
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*
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* This produce a repeatable pattern of 256, but Ken Perlin stated
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* that it is not a problem for graphic texture as the noise features disappear
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* at a distance far enough to be able to see a repeatable pattern of 256.
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*
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* This needs to be exactly the same for all instances on all platforms,
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* so it's easiest to just keep it as static explicit data.
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* This also removes the need for any initialisation of this class.
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*
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* Note that making this an uint32_t[] instead of a uint8_t[] might make the
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* code run faster on platforms with a high penalty for unaligned single
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* byte addressing. Intel x86 is generally single-byte-friendly, but
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* some other CPUs are faster with 4-aligned reads.
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* However, a char[] is smaller, which avoids cache trashing, and that
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* is probably the most important aspect on most architectures.
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* This array is accessed a *lot* by the noise functions.
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* A vector-valued noise over 3D accesses it 96 times, and a
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* float-valued 4D noise 64 times. We want this to fit in the cache!
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*/
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static const uint8_t perm[256] = {
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151, 160, 137, 91, 90, 15,
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131, 13, 201, 95, 96, 53, 194, 233, 7, 225, 140, 36, 103, 30, 69, 142, 8, 99, 37, 240, 21, 10, 23,
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190, 6, 148, 247, 120, 234, 75, 0, 26, 197, 62, 94, 252, 219, 203, 117, 35, 11, 32, 57, 177, 33,
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88, 237, 149, 56, 87, 174, 20, 125, 136, 171, 168, 68, 175, 74, 165, 71, 134, 139, 48, 27, 166,
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77, 146, 158, 231, 83, 111, 229, 122, 60, 211, 133, 230, 220, 105, 92, 41, 55, 46, 245, 40, 244,
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102, 143, 54, 65, 25, 63, 161, 1, 216, 80, 73, 209, 76, 132, 187, 208, 89, 18, 169, 200, 196,
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135, 130, 116, 188, 159, 86, 164, 100, 109, 198, 173, 186, 3, 64, 52, 217, 226, 250, 124, 123,
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5, 202, 38, 147, 118, 126, 255, 82, 85, 212, 207, 206, 59, 227, 47, 16, 58, 17, 182, 189, 28, 42,
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223, 183, 170, 213, 119, 248, 152, 2, 44, 154, 163, 70, 221, 153, 101, 155, 167, 43, 172, 9,
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129, 22, 39, 253, 19, 98, 108, 110, 79, 113, 224, 232, 178, 185, 112, 104, 218, 246, 97, 228,
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251, 34, 242, 193, 238, 210, 144, 12, 191, 179, 162, 241, 81, 51, 145, 235, 249, 14, 239, 107,
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49, 192, 214, 31, 181, 199, 106, 157, 184, 84, 204, 176, 115, 121, 50, 45, 127, 4, 150, 254,
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138, 236, 205, 93, 222, 114, 67, 29, 24, 72, 243, 141, 128, 195, 78, 66, 215, 61, 156, 180
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};
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/**
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* Helper function to hash an integer using the above permutation table
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*
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* This inline function costs around 1ns, and is called N+1 times for a noise of N dimension.
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*
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* Using a real hash function would be better to improve the "repeatability of 256" of the above permutation table,
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* but fast integer Hash functions uses more time and have bad random properties.
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*
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* @param[in] i Integer value to hash
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*
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* @return 8-bits hashed value
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*/
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static inline uint8_t hash(int32_t i) {
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return perm[static_cast<uint8_t>(i)];
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}
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/* NOTE Gradient table to test if lookup-table are more efficient than calculs
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static const float gradients1D[16] = {
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-8.f, -7.f, -6.f, -5.f, -4.f, -3.f, -2.f, -1.f,
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1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f
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};
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*/
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/**
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* Helper function to compute gradients-dot-residual vectors (1D)
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*
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* @note that these generate gradients of more than unit length. To make
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* a close match with the value range of classic Perlin noise, the final
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* noise values need to be rescaled to fit nicely within [-1,1].
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* (The simplex noise functions as such also have different scaling.)
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* Note also that these noise functions are the most practical and useful
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* signed version of Perlin noise.
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*
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* @param[in] hash hash value
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* @param[in] x distance to the corner
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*
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* @return gradient value
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*/
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static float grad(int32_t hash, float x) {
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const int32_t h = hash & 0x0F; // Convert low 4 bits of hash code
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float grad = 1.0f + (h & 7); // Gradient value 1.0, 2.0, ..., 8.0
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if ((h & 8) != 0) grad = -grad; // Set a random sign for the gradient
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// float grad = gradients1D[h]; // NOTE : Test of Gradient look-up table instead of the above
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return (grad * x); // Multiply the gradient with the distance
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}
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/**
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* Helper functions to compute gradients-dot-residual vectors (2D)
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*
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* @param[in] hash hash value
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* @param[in] x x coord of the distance to the corner
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* @param[in] y y coord of the distance to the corner
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*
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* @return gradient value
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*/
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static float grad(int32_t hash, float x, float y) {
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const int32_t h = hash & 0x3F; // Convert low 3 bits of hash code
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const float u = h < 4 ? x : y; // into 8 simple gradient directions,
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const float v = h < 4 ? y : x;
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return ((h & 1) ? -u : u) + ((h & 2) ? -2.0f * v : 2.0f * v); // and compute the dot product with (x,y).
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}
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/**
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* Helper functions to compute gradients-dot-residual vectors (3D)
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*
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* @param[in] hash hash value
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* @param[in] x x coord of the distance to the corner
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* @param[in] y y coord of the distance to the corner
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* @param[in] z z coord of the distance to the corner
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*
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* @return gradient value
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*/
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static float grad(int32_t hash, float x, float y, float z) {
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int h = hash & 15; // Convert low 4 bits of hash code into 12 simple
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float u = h < 8 ? x : y; // gradient directions, and compute dot product.
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float v = h < 4 ? y : h == 12 || h == 14 ? x : z; // Fix repeats at h = 12 to 15
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return ((h & 1) ? -u : u) + ((h & 2) ? -v : v);
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}
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/**
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* 1D Perlin simplex noise
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*
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* Takes around 74ns on an AMD APU.
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*
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* @param[in] x float coordinate
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*
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* @return Noise value in the range[-1; 1], value of 0 on all integer coordinates.
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*/
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float SimplexNoise::noise(float x) {
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float n0, n1; // Noise contributions from the two "corners"
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// No need to skew the input space in 1D
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// Corners coordinates (nearest integer values):
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int32_t i0 = fastfloor(x);
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int32_t i1 = i0 + 1;
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// Distances to corners (between 0 and 1):
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float x0 = x - i0;
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float x1 = x0 - 1.0f;
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// Calculate the contribution from the first corner
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float t0 = 1.0f - x0*x0;
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// if(t0 < 0.0f) t0 = 0.0f; // not possible
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t0 *= t0;
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n0 = t0 * t0 * grad(hash(i0), x0);
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// Calculate the contribution from the second corner
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float t1 = 1.0f - x1*x1;
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// if(t1 < 0.0f) t1 = 0.0f; // not possible
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t1 *= t1;
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n1 = t1 * t1 * grad(hash(i1), x1);
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// The maximum value of this noise is 8*(3/4)^4 = 2.53125
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// A factor of 0.395 scales to fit exactly within [-1,1]
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return 0.395f * (n0 + n1);
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}
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/**
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* 2D Perlin simplex noise
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*
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* Takes around 150ns on an AMD APU.
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*
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* @param[in] x float coordinate
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* @param[in] y float coordinate
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*
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* @return Noise value in the range[-1; 1], value of 0 on all integer coordinates.
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*/
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float SimplexNoise::noise(float x, float y) {
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float n0, n1, n2; // Noise contributions from the three corners
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// Skewing/Unskewing factors for 2D
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static const float F2 = 0.366025403f; // F2 = (sqrt(3) - 1) / 2
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static const float G2 = 0.211324865f; // G2 = (3 - sqrt(3)) / 6 = F2 / (1 + 2 * K)
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// Skew the input space to determine which simplex cell we're in
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const float s = (x + y) * F2; // Hairy factor for 2D
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const float xs = x + s;
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const float ys = y + s;
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const int32_t i = fastfloor(xs);
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const int32_t j = fastfloor(ys);
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// Unskew the cell origin back to (x,y) space
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const float t = static_cast<float>(i + j) * G2;
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const float X0 = i - t;
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const float Y0 = j - t;
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const float x0 = x - X0; // The x,y distances from the cell origin
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const float y0 = y - Y0;
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// For the 2D case, the simplex shape is an equilateral triangle.
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// Determine which simplex we are in.
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int32_t i1, j1; // Offsets for second (middle) corner of simplex in (i,j) coords
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if (x0 > y0) { // lower triangle, XY order: (0,0)->(1,0)->(1,1)
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i1 = 1;
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j1 = 0;
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} else { // upper triangle, YX order: (0,0)->(0,1)->(1,1)
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i1 = 0;
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j1 = 1;
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}
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// A step of (1,0) in (i,j) means a step of (1-c,-c) in (x,y), and
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// a step of (0,1) in (i,j) means a step of (-c,1-c) in (x,y), where
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// c = (3-sqrt(3))/6
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const float x1 = x0 - i1 + G2; // Offsets for middle corner in (x,y) unskewed coords
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const float y1 = y0 - j1 + G2;
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const float x2 = x0 - 1.0f + 2.0f * G2; // Offsets for last corner in (x,y) unskewed coords
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const float y2 = y0 - 1.0f + 2.0f * G2;
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// Work out the hashed gradient indices of the three simplex corners
|
||||
const int gi0 = hash(i + hash(j));
|
||||
const int gi1 = hash(i + i1 + hash(j + j1));
|
||||
const int gi2 = hash(i + 1 + hash(j + 1));
|
||||
|
||||
// Calculate the contribution from the first corner
|
||||
float t0 = 0.5f - x0*x0 - y0*y0;
|
||||
if (t0 < 0.0f) {
|
||||
n0 = 0.0f;
|
||||
} else {
|
||||
t0 *= t0;
|
||||
n0 = t0 * t0 * grad(gi0, x0, y0);
|
||||
}
|
||||
|
||||
// Calculate the contribution from the second corner
|
||||
float t1 = 0.5f - x1*x1 - y1*y1;
|
||||
if (t1 < 0.0f) {
|
||||
n1 = 0.0f;
|
||||
} else {
|
||||
t1 *= t1;
|
||||
n1 = t1 * t1 * grad(gi1, x1, y1);
|
||||
}
|
||||
|
||||
// Calculate the contribution from the third corner
|
||||
float t2 = 0.5f - x2*x2 - y2*y2;
|
||||
if (t2 < 0.0f) {
|
||||
n2 = 0.0f;
|
||||
} else {
|
||||
t2 *= t2;
|
||||
n2 = t2 * t2 * grad(gi2, x2, y2);
|
||||
}
|
||||
|
||||
// Add contributions from each corner to get the final noise value.
|
||||
// The result is scaled to return values in the interval [-1,1].
|
||||
return 45.23065f * (n0 + n1 + n2);
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* 3D Perlin simplex noise
|
||||
*
|
||||
* @param[in] x float coordinate
|
||||
* @param[in] y float coordinate
|
||||
* @param[in] z float coordinate
|
||||
*
|
||||
* @return Noise value in the range[-1; 1], value of 0 on all integer coordinates.
|
||||
*/
|
||||
float SimplexNoise::noise(float x, float y, float z) {
|
||||
float n0, n1, n2, n3; // Noise contributions from the four corners
|
||||
|
||||
// Skewing/Unskewing factors for 3D
|
||||
static const float F3 = 1.0f / 3.0f;
|
||||
static const float G3 = 1.0f / 6.0f;
|
||||
|
||||
// Skew the input space to determine which simplex cell we're in
|
||||
float s = (x + y + z) * F3; // Very nice and simple skew factor for 3D
|
||||
int i = fastfloor(x + s);
|
||||
int j = fastfloor(y + s);
|
||||
int k = fastfloor(z + s);
|
||||
float t = (i + j + k) * G3;
|
||||
float X0 = i - t; // Unskew the cell origin back to (x,y,z) space
|
||||
float Y0 = j - t;
|
||||
float Z0 = k - t;
|
||||
float x0 = x - X0; // The x,y,z distances from the cell origin
|
||||
float y0 = y - Y0;
|
||||
float z0 = z - Z0;
|
||||
|
||||
// For the 3D case, the simplex shape is a slightly irregular tetrahedron.
|
||||
// Determine which simplex we are in.
|
||||
int i1, j1, k1; // Offsets for second corner of simplex in (i,j,k) coords
|
||||
int i2, j2, k2; // Offsets for third corner of simplex in (i,j,k) coords
|
||||
if (x0 >= y0) {
|
||||
if (y0 >= z0) {
|
||||
i1 = 1; j1 = 0; k1 = 0; i2 = 1; j2 = 1; k2 = 0; // X Y Z order
|
||||
} else if (x0 >= z0) {
|
||||
i1 = 1; j1 = 0; k1 = 0; i2 = 1; j2 = 0; k2 = 1; // X Z Y order
|
||||
} else {
|
||||
i1 = 0; j1 = 0; k1 = 1; i2 = 1; j2 = 0; k2 = 1; // Z X Y order
|
||||
}
|
||||
} else { // x0<y0
|
||||
if (y0 < z0) {
|
||||
i1 = 0; j1 = 0; k1 = 1; i2 = 0; j2 = 1; k2 = 1; // Z Y X order
|
||||
} else if (x0 < z0) {
|
||||
i1 = 0; j1 = 1; k1 = 0; i2 = 0; j2 = 1; k2 = 1; // Y Z X order
|
||||
} else {
|
||||
i1 = 0; j1 = 1; k1 = 0; i2 = 1; j2 = 1; k2 = 0; // Y X Z order
|
||||
}
|
||||
}
|
||||
|
||||
// A step of (1,0,0) in (i,j,k) means a step of (1-c,-c,-c) in (x,y,z),
|
||||
// a step of (0,1,0) in (i,j,k) means a step of (-c,1-c,-c) in (x,y,z), and
|
||||
// a step of (0,0,1) in (i,j,k) means a step of (-c,-c,1-c) in (x,y,z), where
|
||||
// c = 1/6.
|
||||
float x1 = x0 - i1 + G3; // Offsets for second corner in (x,y,z) coords
|
||||
float y1 = y0 - j1 + G3;
|
||||
float z1 = z0 - k1 + G3;
|
||||
float x2 = x0 - i2 + 2.0f * G3; // Offsets for third corner in (x,y,z) coords
|
||||
float y2 = y0 - j2 + 2.0f * G3;
|
||||
float z2 = z0 - k2 + 2.0f * G3;
|
||||
float x3 = x0 - 1.0f + 3.0f * G3; // Offsets for last corner in (x,y,z) coords
|
||||
float y3 = y0 - 1.0f + 3.0f * G3;
|
||||
float z3 = z0 - 1.0f + 3.0f * G3;
|
||||
|
||||
// Work out the hashed gradient indices of the four simplex corners
|
||||
int gi0 = hash(i + hash(j + hash(k)));
|
||||
int gi1 = hash(i + i1 + hash(j + j1 + hash(k + k1)));
|
||||
int gi2 = hash(i + i2 + hash(j + j2 + hash(k + k2)));
|
||||
int gi3 = hash(i + 1 + hash(j + 1 + hash(k + 1)));
|
||||
|
||||
// Calculate the contribution from the four corners
|
||||
float t0 = 0.6f - x0*x0 - y0*y0 - z0*z0;
|
||||
if (t0 < 0) {
|
||||
n0 = 0.0;
|
||||
} else {
|
||||
t0 *= t0;
|
||||
n0 = t0 * t0 * grad(gi0, x0, y0, z0);
|
||||
}
|
||||
float t1 = 0.6f - x1*x1 - y1*y1 - z1*z1;
|
||||
if (t1 < 0) {
|
||||
n1 = 0.0;
|
||||
} else {
|
||||
t1 *= t1;
|
||||
n1 = t1 * t1 * grad(gi1, x1, y1, z1);
|
||||
}
|
||||
float t2 = 0.6f - x2*x2 - y2*y2 - z2*z2;
|
||||
if (t2 < 0) {
|
||||
n2 = 0.0;
|
||||
} else {
|
||||
t2 *= t2;
|
||||
n2 = t2 * t2 * grad(gi2, x2, y2, z2);
|
||||
}
|
||||
float t3 = 0.6f - x3*x3 - y3*y3 - z3*z3;
|
||||
if (t3 < 0) {
|
||||
n3 = 0.0;
|
||||
} else {
|
||||
t3 *= t3;
|
||||
n3 = t3 * t3 * grad(gi3, x3, y3, z3);
|
||||
}
|
||||
// Add contributions from each corner to get the final noise value.
|
||||
// The result is scaled to stay just inside [-1,1]
|
||||
return 32.0f*(n0 + n1 + n2 + n3);
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Fractal/Fractional Brownian Motion (fBm) summation of 1D Perlin Simplex noise
|
||||
*
|
||||
* @param[in] octaves number of fraction of noise to sum
|
||||
* @param[in] x float coordinate
|
||||
*
|
||||
* @return Noise value in the range[-1; 1], value of 0 on all integer coordinates.
|
||||
*/
|
||||
float SimplexNoise::fractal(size_t octaves, float x) const {
|
||||
float output = 0.f;
|
||||
float denom = 0.f;
|
||||
float frequency = mFrequency;
|
||||
float amplitude = mAmplitude;
|
||||
|
||||
for (size_t i = 0; i < octaves; i++) {
|
||||
output += (amplitude * noise(x * frequency));
|
||||
denom += amplitude;
|
||||
|
||||
frequency *= mLacunarity;
|
||||
amplitude *= mPersistence;
|
||||
}
|
||||
|
||||
return (output / denom);
|
||||
}
|
||||
|
||||
/**
|
||||
* Fractal/Fractional Brownian Motion (fBm) summation of 2D Perlin Simplex noise
|
||||
*
|
||||
* @param[in] octaves number of fraction of noise to sum
|
||||
* @param[in] x x float coordinate
|
||||
* @param[in] y y float coordinate
|
||||
*
|
||||
* @return Noise value in the range[-1; 1], value of 0 on all integer coordinates.
|
||||
*/
|
||||
float SimplexNoise::fractal(size_t octaves, float x, float y) const {
|
||||
float output = 0.f;
|
||||
float denom = 0.f;
|
||||
float frequency = mFrequency;
|
||||
float amplitude = mAmplitude;
|
||||
|
||||
for (size_t i = 0; i < octaves; i++) {
|
||||
output += (amplitude * noise(x * frequency, y * frequency));
|
||||
denom += amplitude;
|
||||
|
||||
frequency *= mLacunarity;
|
||||
amplitude *= mPersistence;
|
||||
}
|
||||
|
||||
return (output / denom);
|
||||
}
|
||||
|
||||
/**
|
||||
* Fractal/Fractional Brownian Motion (fBm) summation of 3D Perlin Simplex noise
|
||||
*
|
||||
* @param[in] octaves number of fraction of noise to sum
|
||||
* @param[in] x x float coordinate
|
||||
* @param[in] y y float coordinate
|
||||
* @param[in] z z float coordinate
|
||||
*
|
||||
* @return Noise value in the range[-1; 1], value of 0 on all integer coordinates.
|
||||
*/
|
||||
float SimplexNoise::fractal(size_t octaves, float x, float y, float z) const {
|
||||
float output = 0.f;
|
||||
float denom = 0.f;
|
||||
float frequency = mFrequency;
|
||||
float amplitude = mAmplitude;
|
||||
|
||||
for (size_t i = 0; i < octaves; i++) {
|
||||
output += (amplitude * noise(x * frequency, y * frequency, z * frequency));
|
||||
denom += amplitude;
|
||||
|
||||
frequency *= mLacunarity;
|
||||
amplitude *= mPersistence;
|
||||
}
|
||||
|
||||
return (output / denom);
|
||||
}
|
||||
|
|
@ -0,0 +1,55 @@
|
|||
/**
|
||||
* @file SimplexNoise.h
|
||||
* @brief A Perlin Simplex Noise C++ Implementation (1D, 2D, 3D).
|
||||
*
|
||||
* Copyright (c) 2014-2018 Sebastien Rombauts (sebastien.rombauts@gmail.com)
|
||||
*
|
||||
* Distributed under the MIT License (MIT) (See accompanying file LICENSE.txt
|
||||
* or copy at http://opensource.org/licenses/MIT)
|
||||
*/
|
||||
#pragma once
|
||||
|
||||
#include <cstddef> // size_t
|
||||
|
||||
/**
|
||||
* @brief A Perlin Simplex Noise C++ Implementation (1D, 2D, 3D, 4D).
|
||||
*/
|
||||
class SimplexNoise {
|
||||
public:
|
||||
// 1D Perlin simplex noise
|
||||
static float noise(float x);
|
||||
// 2D Perlin simplex noise
|
||||
static float noise(float x, float y);
|
||||
// 3D Perlin simplex noise
|
||||
static float noise(float x, float y, float z);
|
||||
|
||||
// Fractal/Fractional Brownian Motion (fBm) noise summation
|
||||
float fractal(size_t octaves, float x) const;
|
||||
float fractal(size_t octaves, float x, float y) const;
|
||||
float fractal(size_t octaves, float x, float y, float z) const;
|
||||
|
||||
/**
|
||||
* Constructor of to initialize a fractal noise summation
|
||||
*
|
||||
* @param[in] frequency Frequency ("width") of the first octave of noise (default to 1.0)
|
||||
* @param[in] amplitude Amplitude ("height") of the first octave of noise (default to 1.0)
|
||||
* @param[in] lacunarity Lacunarity specifies the frequency multiplier between successive octaves (default to 2.0).
|
||||
* @param[in] persistence Persistence is the loss of amplitude between successive octaves (usually 1/lacunarity)
|
||||
*/
|
||||
explicit SimplexNoise(float frequency = 1.0f,
|
||||
float amplitude = 1.0f,
|
||||
float lacunarity = 2.0f,
|
||||
float persistence = 0.5f) :
|
||||
mFrequency(frequency),
|
||||
mAmplitude(amplitude),
|
||||
mLacunarity(lacunarity),
|
||||
mPersistence(persistence) {
|
||||
}
|
||||
|
||||
private:
|
||||
// Parameters of Fractional Brownian Motion (fBm) : sum of N "octaves" of noise
|
||||
float mFrequency; ///< Frequency ("width") of the first octave of noise (default to 1.0)
|
||||
float mAmplitude; ///< Amplitude ("height") of the first octave of noise (default to 1.0)
|
||||
float mLacunarity; ///< Lacunarity specifies the frequency multiplier between successive octaves (default to 2.0).
|
||||
float mPersistence; ///< Persistence is the loss of amplitude between successive octaves (usually 1/lacunarity)
|
||||
};
|
||||
Loading…
Reference in New Issue