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Sector Generation

Browse source 
Fixed Laser cancelling bug
Fixed Turrets not activating
Added ability to bind player perspective to orbital entities
Added Markov Chain name generator + Australian place name dataset
Modified old "galaxy" shader to serve as sector background
Implemented Cem Yuksel's Weighted Sample Elimination for Poisson Disk Sample Sets
Created sector generator which places sectors using WSE
This commit is contained in:
Reinier Vens 2021-03-10 09:18:07 +00:00
commit 3f9af29843
108 changed files with 139298 additions and 13543 deletions
Download patch file Download diff file Expand all files Collapse all files

2
Assets/Scripts/ServerShared/Agents/Agent.cs
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@ -38,7 +38,7 @@ public class Agent
public void Transition(BaseState targetState, Action onTransition = null)
{
ItemManager.Log($"{Ship.Name} changing state from {_currentState.GetType().Name} to {targetState.GetType().Name}");
//ItemManager.Log($"{Ship.Name} changing state from {_currentState.GetType().Name} to {targetState.GetType().Name}");
_currentState.OnExitState();
_currentState = targetState;
onTransition?.Invoke();

2
Assets/Scripts/ServerShared/Agents/Minion.cs
View file

@ -8,7 +8,7 @@ public class Minion : Agent
{
var patrolState = new PatrolOrbitsState(this);
_rootState.AddTransition(patrolState,
() => Task is PatrolOrbitsTask,
() => Task is PatrolOrbitsTask,
() => patrolState.Task = Task as PatrolOrbitsTask);
Ship.VisibleHostiles.ObserveAdd().Where(_ => Ship.Target.Value == null).Subscribe(add => Ship.Target.Value = add.Value);

2
Assets/Scripts/ServerShared/Behaviors/LockWeapon.cs
View file

@ -69,7 +69,7 @@ public class LockWeapon : InstantWeapon
_target = Entity.Target.Value;
}
if (Entity.Target.Value != null)
if (Entity.Target.Value != null && Entity.Target.Value.IsHostileTo(Entity))
{
LockSpeed = Item.Evaluate(_data.LockSpeed);
SensorImpact = Item.Evaluate(_data.SensorImpact);

111
Assets/Scripts/ServerShared/MarkovNameGenerator.cs Normal file
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@ -0,0 +1,111 @@
/* 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 https://mozilla.org/MPL/2.0/. */
using System;
using System.Collections.Generic;
using Random = Unity.Mathematics.Random;
//Generates random names based on the statistical weight of letter sequences
//in a collection of sample names
public class MarkovNameGenerator
{
private Dictionary<string, List<char>> _chains = new Dictionary<string, List<char>>();
private List<string> _samples = new List<string>();
private static List<string> _used = new List<string>();
private int _order;
private int _minLength;
private int _maxLength;
private Random _random;
public MarkovNameGenerator(ref Random random, IEnumerable<string> sampleNames, int order, int minLength, int maxLength)
{
_random = random;
//fix parameter values
if (order < 1)
order = 1;
if (minLength < 1)
minLength = 1;
_order = order;
_minLength = minLength;
_maxLength = maxLength;
//split comma delimited lines
foreach (string line in sampleNames)
{
string[] tokens = line.Split(' ','-','\'','(',')');
foreach (string word in tokens)
{
string upper = word.Trim().ToLowerInvariant();
if (upper.Length < order + 1)
continue;
_samples.Add(upper + '|'); // Add end character
}
}
//Build chains
foreach (string word in _samples)
{
for (int letter = 0; letter < word.Length - order; letter++)
{
string token = word.Substring(letter, order);
List<char> entry = null;
if (_chains.ContainsKey(token))
entry = _chains[token];
else
{
entry = new List<char>();
_chains[token] = entry;
}
entry.Add(word[letter + order]);
}
}
}
//Get the next random name
public string NextName
{
get
{
string s = "";
do
{
int n = _random.NextInt(0,_samples.Count);
//int nameLength = _samples[n].Length;
//s = _samples[n].Substring(UnityEngine.Random.Range(0, _samples[n].Length - _order), _order);//get a random token somewhere in middle of sample word
s = _samples[n].Substring(0, _order);//get a random token at the start of a sample word
while (true)//(s.Length < nameLength)
{
string token = s.Substring(s.Length - _order, _order);
char c = GetLetter(token);
if (c != '?' && c != '|')
s += c;//GetLetter(token);
else
break;
}
s = s.Substring(0, 1) + s.Substring(1).ToLower();
}
while (_used.Contains(s) || s.Length < _minLength || s.Length > _maxLength);
_used.Add(s);
return s;
}
}
//Reset the used names
public void Reset()
{
_used.Clear();
}
//Get a random letter from the chain
private char GetLetter(string token)
{
if (!_chains.ContainsKey(token))
return '?';
List<char> letters = _chains[token];
int n = _random.NextInt(0,letters.Count);
return letters[n];
}
}

11
Assets/Scripts/ServerShared/MarkovNameGenerator.cs.meta Normal file
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8
Assets/Scripts/ServerShared/NIH/Heap.meta Normal file
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@ -0,0 +1,8 @@
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211
Assets/Scripts/ServerShared/NIH/Heap/BaseHeap.cs Normal file
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@ -0,0 +1,211 @@
/*MIT License
Copyright(c) 2018 Vili Volčini / viliwonka
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
*/
using System.Collections.Generic;
namespace DataStructures.ViliWonka.Heap {
// array start at index 1, optimisation reason
public abstract class BaseHeap {
protected int nodesCount;
protected int maxSize;
protected float[] heap;
protected BaseHeap(int initialSize) {
maxSize = initialSize;
heap = new float[initialSize + 1];
}
public int Count { get { return nodesCount; } }
public float HeadValue { get { return heap[1]; } }
public void Clear() {
nodesCount = 0;
}
protected int Parent(int index) { return (index >> 1); }
protected int Left (int index) { return (index << 1); }
protected int Right (int index) { return (index << 1) | 1; }
// bubble down, MaxHeap version
protected void BubbleDownMax(int index) {
int L = Left(index);
int R = Right(index);
// bubbling down, 2 kids
while (R <= nodesCount) {
// if heap property is violated between index and Left child
if(heap[index] < heap[L]) {
if (heap[L] < heap[R]) {
Swap(index, R); // left has bigger priority
index = R;
}
else {
Swap(index, L); // right has bigger priority
index = L;
}
}
else {
// if heap property is violated between index and R
if (heap[index] < heap[R]) {
Swap(index, R);
index = R;
}
else {
index = L;
L = Left(index);
break;
}
}
L = Left(index);
R = Right(index);
}
// only left & last children available to test and swap
if (L <= nodesCount && heap[index] < heap[L]) {
Swap(index, L);
}
}
// bubble up, MaxHeap version
protected void BubbleUpMax(int index) {
int P = Parent(index);
//swap, until Heap property isn't violated anymore
while (P > 0 && heap[P] < heap[index]) {
Swap(P, index);
index = P;
P = Parent(index);
}
}
// bubble down, MinHeap version
protected void BubbleDownMin(int index) {
int L = Left(index);
int R = Right(index);
// bubbling down, 2 kids
while(R <= nodesCount) {
// if heap property is violated between index and Left child
if(heap[index] > heap[L]) {
if(heap[L] > heap[R]) {
Swap(index, R); // right has smaller priority
index = R;
}
else {
Swap(index, L); // left has smaller priority
index = L;
}
}
else {
// if heap property is violated between index and R
if(heap[index] > heap[R]) {
Swap(index, R);
index = R;
}
else {
index = L;
L = Left(index);
break;
}
}
L = Left(index);
R = Right(index);
}
// only left & last children available to test and swap
if(L <= nodesCount && heap[index] > heap[L]) {
Swap(index, L);
}
}
// bubble up, MinHeap version
protected void BubbleUpMin(int index) {
int P = Parent(index);
//swap, until Heap property isn't violated anymore
while(P > 0 && heap[P] > heap[index]) {
Swap(P, index);
index = P;
P = Parent(index);
}
}
protected float tempHeap;
protected virtual void Swap(int A, int B) {
tempHeap = heap[A];
heap[A] = heap[B];
heap[B] = tempHeap;
}
protected virtual void UpsizeHeap() {
maxSize *= 2;
System.Array.Resize(ref heap, maxSize + 1);
}
public virtual void PushValue(float h) {
throw new System.NotImplementedException();
}
public virtual float PopValue() {
throw new System.NotImplementedException();
}
public void FlushHeapResult(List<float> heapList) {
for(int i = 1; i < Count; i++) {
heapList.Add(heap[i]);
}
}
}
}

11
Assets/Scripts/ServerShared/NIH/Heap/BaseHeap.cs.meta Normal file
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229
Assets/Scripts/ServerShared/NIH/Heap/KSmallest.cs Normal file
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@ -0,0 +1,229 @@
/*MIT License
Copyright(c) 2018 Vili Volčini / viliwonka
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
*/
using System.Collections.Generic;
namespace DataStructures.ViliWonka.Heap {
public class KSmallestHeap : BaseHeap {
public KSmallestHeap(int maxEntries) : base(maxEntries) {
}
public bool Full {
get {
return maxSize == nodesCount;
}
}
// in lots of cases, max head gets removed
public override void PushValue(float h) {
// if heap full
if(nodesCount == maxSize) {
// if Heads priority is smaller than input priority, then ignore that item
if(HeadValue < h) {
return;
}
else {
heap[1] = h; // remove top element
BubbleDownMax(1); // bubble it down
}
}
else {
nodesCount++;
heap[nodesCount] = h;
BubbleUpMax(nodesCount);
}
}
public override float PopValue() {
if(nodesCount == 0)
throw new System.ArgumentException("Heap is empty!");
float result = heap[1];
heap[1] = heap[nodesCount];
nodesCount--;
BubbleDownMax(1);
return result;
}
public void Print() {
//UnityEngine.Debug.Log("HeapPropertyHolds? " + HeapPropertyHolds(1));
}
//should remove
public bool HeapPropertyHolds(int index, int depth = 0) {
if (index > nodesCount)
return true;
//UnityEngine.Debug.Log(heap[index]);
int L = Left(index);
int R = Right(index);
bool bothHold = true;
if(L <= nodesCount) {
//UnityEngine.Debug.Log(heap[index] + " => " + heap[L]);
if (heap[index] < heap[L])
bothHold = false;
}
// if L <= nodesCount, then R <= nodesCount can also happen
if (R <= nodesCount) {
//UnityEngine.Debug.Log(heap[index] + " => " + heap[R]);
if (bothHold && heap[index] < heap[R])
bothHold = false;
}
return bothHold & HeapPropertyHolds(L, depth + 1) & HeapPropertyHolds(R, depth + 1);
}
}
// array start at index 1
// generic version
public class KSmallestHeap<T> : KSmallestHeap {
T[] objs; //objects
public KSmallestHeap(int maxEntries) : base(maxEntries) {
objs = new T[maxEntries + 1];
}
public T HeadHeapObject { get { return objs[1]; } }
T tempObjs;
protected override void Swap(int A, int B) {
tempHeap = heap[A];
tempObjs = objs[A];
heap[A] = heap[B];
objs[A] = objs[B];
heap[B] = tempHeap;
objs[B] = tempObjs;
}
public override void PushValue(float h) {
throw new System.ArgumentException("Use Push(T, float)!");
}
public void PushObj(T obj, float h) {
// if heap full
if(nodesCount == maxSize) {
// if Heads priority is smaller than input priority, then ignore that item
if(HeadValue < h) {
return;
}
else {
heap[1] = h; // remove top element
objs[1] = obj;
BubbleDownMax(1); // bubble it down
}
}
else {
nodesCount++;
heap[nodesCount] = h;
objs[nodesCount] = obj;
BubbleUpMax(nodesCount);
}
}
public override float PopValue() {
throw new System.ArgumentException("Use PopObj()!");
}
public T PopObj() {
if(nodesCount == 0)
throw new System.ArgumentException("Heap is empty!");
T result = objs[1];
heap[1] = heap[nodesCount];
objs[1] = objs[nodesCount];
nodesCount--;
BubbleDownMax(1);
return result;
}
public T PopObj(ref float heapValue) {
if(nodesCount == 0)
throw new System.ArgumentException("Heap is empty!");
heapValue = heap[1];
T result = PopObj();
return result;
}
//flush internal results, returns ordered data
public void FlushResult(List<T> resultList, List<float> heapList = null) {
int count = nodesCount + 1;
if(heapList == null) {
for(int i = 1; i < count; i++) {
resultList.Add(PopObj());
}
}
else {
float h = 0f;
for(int i = 1; i < count; i++) {
resultList.Add(PopObj(ref h));
heapList.Add(h);
}
}
}
}
}

11
Assets/Scripts/ServerShared/NIH/Heap/KSmallest.cs.meta Normal file
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205
Assets/Scripts/ServerShared/NIH/Heap/MaxHeap.cs Normal file
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@ -0,0 +1,205 @@
/*MIT License
Copyright(c) 2018 Vili Volčini / viliwonka
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
*/
using System.Collections.Generic;
namespace DataStructures.ViliWonka.Heap {
public class MaxHeap : BaseHeap {
public MaxHeap(int initialSize = 2048) : base(initialSize) {
}
public override void PushValue(float h) {
// if heap array is full
if(nodesCount == maxSize) {
UpsizeHeap();
}
nodesCount++;
heap[nodesCount] = h;
BubbleUpMax(nodesCount);
}
public override float PopValue() {
if(nodesCount == 0)
throw new System.ArgumentException("Heap is empty!");
float result = heap[1];
heap[1] = heap[nodesCount];
nodesCount--;
BubbleDownMax(1);
return result;
}
}
// generic version
public class MaxHeap<T> : MaxHeap {
T[] objs; // objects
private Dictionary<T, int> currentIndices;
public MaxHeap(int maxNodes) : base(maxNodes) {
objs = new T[maxNodes + 1];
currentIndices = new Dictionary<T, int>(maxNodes);
}
public T HeadHeapObject { get { return objs[1]; } }
T tempObjs;
protected override void Swap(int A, int B) {
tempHeap = heap[A];
tempObjs = objs[A];
heap[A] = heap[B];
objs[A] = objs[B];
currentIndices[objs[A]] = A;
heap[B] = tempHeap;
objs[B] = tempObjs;
currentIndices[objs[B]] = B;
}
public void BubbleUp(T obj)
{
BubbleUpMax(currentIndices[obj]);
}
public void BubbleDown(T obj)
{
BubbleDownMax(currentIndices[obj]);
}
public void SetValue(T obj, float h)
{
if(currentIndices.ContainsKey(obj))
{
var index = currentIndices[obj];
var previous = heap[index];
heap[index] = h;
if (h > previous) BubbleUpMax(index);
else BubbleDownMax(index);
}
}
public override void PushValue(float h) {
throw new System.ArgumentException("Use PushObj(T, float)!");
}
public override float PopValue() {
throw new System.ArgumentException("Use Push(T, float)!");
}
public void PushObj(T obj, float h) {
// if heap array is full
if(nodesCount == maxSize) {
UpsizeHeap();
}
nodesCount++;
heap[nodesCount] = h;
objs[nodesCount] = obj;
currentIndices[obj] = nodesCount;
BubbleUpMax(nodesCount);
}
public T PopObj() {
if(nodesCount == 0)
throw new System.ArgumentException("Heap is empty!");
T result = objs[1];
currentIndices.Remove(result);
heap[1] = heap[nodesCount];
objs[1] = objs[nodesCount];
currentIndices[objs[1]] = 1;
objs[nodesCount] = default(T);
nodesCount--;
BubbleDownMax(1);
return result;
}
public T PopObj(ref float heapValue) {
if(nodesCount == 0)
throw new System.ArgumentException("Heap is empty!");
heapValue = heap[1];
T result = PopObj();
return result;
}
protected override void UpsizeHeap() {
maxSize *= 2;
System.Array.Resize(ref heap, maxSize + 1);
System.Array.Resize(ref objs, maxSize + 1);
}
//flush internal results, returns ordered data
public void FlushResult(List<T> resultList, List<float> heapList = null) {
int count = nodesCount + 1;
if(heapList == null) {
for(int i = 1; i < count; i++) {
resultList.Add(PopObj());
}
}
else {
float h = 0f;
for(int i = 1; i < count; i++) {
resultList.Add(PopObj(ref h));
heapList.Add(h);
}
}
}
public IEnumerable<T> FlushResult()
{
int count = nodesCount + 1;
for(int i = 1; i < count; i++) {
yield return PopObj();
}
}
}
}

11
Assets/Scripts/ServerShared/NIH/Heap/MaxHeap.cs.meta Normal file
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195
Assets/Scripts/ServerShared/NIH/Heap/MinHeap.cs Normal file
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@ -0,0 +1,195 @@
/*MIT License
Copyright(c) 2018 Vili Volčini / viliwonka
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
*/
using System.Collections.Generic;
namespace DataStructures.ViliWonka.Heap {
public class MinHeap : BaseHeap {
public MinHeap(int initialSize = 2048) : base(initialSize) {
}
public override void PushValue(float h) {
// if heap array is full
if(nodesCount == maxSize) {
UpsizeHeap();
}
nodesCount++;
heap[nodesCount] = h;
BubbleUpMin(nodesCount);
}
public override float PopValue() {
if(nodesCount == 0)
throw new System.ArgumentException("Heap is empty!");
float result = heap[1];
heap[1] = heap[nodesCount];
nodesCount--;
if(nodesCount != 0)
BubbleDownMin(1);
return result;
}
}
// generic version
public class MinHeap<T> : MinHeap {
T[] objs; // objects
private Dictionary<T, int> currentIndices;
public MinHeap(int maxNodes = 2048) : base(maxNodes) {
objs = new T[maxNodes + 1];
currentIndices = new Dictionary<T, int>(maxNodes);
}
public T HeadHeapObject { get { return objs[1]; } }
T tempObjs;
protected override void Swap(int A, int B) {
tempHeap = heap[A];
tempObjs = objs[A];
heap[A] = heap[B];
objs[A] = objs[B];
currentIndices[objs[A]] = A;
heap[B] = tempHeap;
objs[B] = tempObjs;
currentIndices[objs[B]] = B;
}
public void BubbleUp(T obj)
{
BubbleUpMin(currentIndices[obj]);
}
public void BubbleDown(T obj)
{
BubbleDownMin(currentIndices[obj]);
}
public override void PushValue(float h) {
throw new System.ArgumentException("Use Push(T, float)!");
}
public override float PopValue() {
throw new System.ArgumentException("Use Push(T, float)!");
}
public void PushObj(T obj, float h) {
// if heap array is full
if(nodesCount == maxSize) {
UpsizeHeap();
}
nodesCount++;
heap[nodesCount] = h;
objs[nodesCount] = obj;
currentIndices[obj] = nodesCount;
BubbleUpMin(nodesCount);
}
public T PopObj() {
if(nodesCount == 0)
throw new System.ArgumentException("Heap is empty!");
T result = objs[1];
heap[1] = heap[nodesCount];
objs[1] = objs[nodesCount];
currentIndices[objs[1]] = 1;
objs[nodesCount] = default(T);
nodesCount--;
if(nodesCount != 0)
BubbleDownMin(1);
return result;
}
public T PopObj(ref float heapValue) {
if(nodesCount == 0)
throw new System.ArgumentException("Heap is empty!");
heapValue = heap[1];
T result = PopObj();
return result;
}
protected override void UpsizeHeap() {
maxSize *= 2;
System.Array.Resize(ref heap, maxSize + 1);
System.Array.Resize(ref objs, maxSize + 1);
}
//flush internal array, returns ordered data
public void FlushResult(List<T> resultList, List<float> heapList = null) {
int count = nodesCount + 1;
if(heapList == null) {
for(int i = 1; i < count; i++) {
resultList.Add(PopObj());
}
}
else {
float h = 0f;
for(int i = 1; i < count; i++) {
resultList.Add(PopObj(ref h));
heapList.Add(h);
}
}
}
public IEnumerable<T> FlushResult()
{
int count = nodesCount + 1;
for(int i = 1; i < count; i++) {
yield return PopObj();
}
}
}
}

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56
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/*MIT License
Copyright(c) 2018 Vili Volčini / viliwonka
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
*/
using Unity.Mathematics;
namespace DataStructures.ViliWonka.KDTree {
public struct KDBounds {
public float2 min;
public float2 max;
public float2 size {
get {
return max - min;
}
}
public float2 ClosestPoint(float2 point) {
// X axis
if(point.x < min.x) point.x = min.x;
else
if(point.x > max.x) point.x = max.x;
// Y axis
if(point.y < min.y) point.y = min.y;
else
if(point.y > max.y) point.y = max.y;
return point;
}
}
}

13
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48
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/*MIT License
Copyright(c) 2018 Vili Volčini / viliwonka
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
*/
using System.Collections;
using System.Collections.Generic;
namespace DataStructures.ViliWonka.KDTree {
public class KDNode {
public float partitionCoordinate;
public int partitionAxis = -1;
public KDNode negativeChild;
public KDNode positiveChild;
public int start;
public int end;
public int Count { get { return end - start; } }
public bool Leaf { get { return partitionAxis == -1; } }
public KDBounds bounds;
};
}

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/*MIT License
Copyright(c) 2018 Vili Volčini / viliwonka
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
*/
/*
The object used for querying. This object should be persistent - re-used for querying.
Contains internal array for pooling, so that it doesn't generate (too much) garbage.
The array never down-sizes, only up-sizes, so the more you use this object, less garbage will it make over time.
Should be used only by 1 thread,
which means each thread should have it's own KDQuery object in order for querying to be thread safe.
KDQuery can query different KDTrees.
*/
using System.Collections.Generic;
using System;
using Unity.Mathematics;
using static Unity.Mathematics.math;
namespace DataStructures.ViliWonka.KDTree {
public partial class KDQuery {
protected KDQueryNode[] queueArray; // queue array
protected Heap.MinHeap<KDQueryNode> minHeap; //heap for k-nearest
protected int count = 0; // size of queue
protected int queryIndex = 0; // current index at stack
/// <summary>
/// Returns initialized node from stack that also acts as a pool
/// The returned reference to node stays in stack
/// </summary>
/// <returns>Reference to pooled node</returns>
private KDQueryNode PushGetQueue() {
KDQueryNode node = null;
if (count < queueArray.Length) {
if (queueArray[count] == null)
queueArray[count] = node = new KDQueryNode();
else
node = queueArray[count];
}
else {
// automatic resize of pool
Array.Resize(ref queueArray, queueArray.Length * 2);
node = queueArray[count] = new KDQueryNode();
}
count++;
return node;
}
protected void PushToQueue(KDNode node, float2 tempClosestPoint) {
var queryNode = PushGetQueue();
queryNode.node = node;
queryNode.tempClosestPoint = tempClosestPoint;
}
protected void PushToHeap(KDNode node, float2 tempClosestPoint, float2 queryPosition) {
var queryNode = PushGetQueue();
queryNode.node = node;
queryNode.tempClosestPoint = tempClosestPoint;
float sqrDist = lengthsq(tempClosestPoint - queryPosition);
queryNode.distance = sqrDist;
minHeap.PushObj(queryNode, sqrDist);
}
protected int LeftToProcess {
get {
return count - queryIndex;
}
}
// just gets unprocessed node from stack
// increases queryIndex
protected KDQueryNode PopFromQueue() {
var node = queueArray[queryIndex];
queryIndex++;
return node;
}
protected KDQueryNode PopFromHeap() {
KDQueryNode heapNode = minHeap.PopObj();
queueArray[queryIndex]= heapNode;
queryIndex++;
return heapNode;
}
protected void Reset() {
count = 0;
queryIndex = 0;
minHeap.Clear();
}
public KDQuery(int queryNodesContainersInitialSize = 2048) {
queueArray = new KDQueryNode[queryNodesContainersInitialSize];
minHeap = new Heap.MinHeap<KDQueryNode>(queryNodesContainersInitialSize);
}
}
}

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/*MIT License
Copyright(c) 2018 Vili Volčini / viliwonka
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
*/
using Unity.Mathematics;
namespace DataStructures.ViliWonka.KDTree {
public class KDQueryNode {
public KDNode node;
public float2 tempClosestPoint;
public float distance;
public KDQueryNode() {
}
public KDQueryNode(KDNode node, float2 tempClosestPoint) {
this.node = node;
this.tempClosestPoint = tempClosestPoint;
}
}
}

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145
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/*MIT License
Copyright(c) 2018 Vili Volčini / viliwonka
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
*/
using System.Collections.Generic;
using System;
using Unity.Mathematics;
using static Unity.Mathematics.math;
namespace DataStructures.ViliWonka.KDTree {
using Heap;
public partial class KDQuery {
public void ClosestPoint(KDTree tree, float2 queryPosition, List<int> resultIndices, List<float> resultDistances = null) {
Reset();
float2[] points = tree.Points;
int[] permutation = tree.Permutation;
if (points.Length == 0) {
return;
}
int smallestIndex = 0;
/// Smallest Squared Radius
float SSR = Single.PositiveInfinity;
var rootNode = tree.RootNode;
float2 rootClosestPoint = rootNode.bounds.ClosestPoint(queryPosition);
PushToHeap(rootNode, rootClosestPoint, queryPosition);
KDQueryNode queryNode = null;
KDNode node = null;
int partitionAxis;
float partitionCoord;
float2 tempClosestPoint;
// searching
while(minHeap.Count > 0) {
queryNode = PopFromHeap();
if(queryNode.distance > SSR)
continue;
node = queryNode.node;
if(!node.Leaf) {
partitionAxis = node.partitionAxis;
partitionCoord = node.partitionCoordinate;
tempClosestPoint = queryNode.tempClosestPoint;
if((tempClosestPoint[partitionAxis] - partitionCoord) < 0) {
// we already know we are on the side of negative bound/node,
// so we don't need to test for distance
// push to stack for later querying
PushToHeap(node.negativeChild, tempClosestPoint, queryPosition);
// project the tempClosestPoint to other bound
tempClosestPoint[partitionAxis] = partitionCoord;
if(node.positiveChild.Count != 0) {
PushToHeap(node.positiveChild, tempClosestPoint, queryPosition);
}
}
else {
// we already know we are on the side of positive bound/node,
// so we don't need to test for distance
// push to stack for later querying
PushToHeap(node.positiveChild, tempClosestPoint, queryPosition);
// project the tempClosestPoint to other bound
tempClosestPoint[partitionAxis] = partitionCoord;
if(node.positiveChild.Count != 0) {
PushToHeap(node.negativeChild, tempClosestPoint, queryPosition);
}
}
}
else {
float sqrDist;
// LEAF
for(int i = node.start; i < node.end; i++) {
int index = permutation[i];
sqrDist = lengthsq(points[index] - queryPosition);
if(sqrDist <= SSR) {
SSR = sqrDist;
smallestIndex = index;
}
}
}
}
resultIndices.Add(smallestIndex);
if(resultDistances != null) {
resultDistances.Add(SSR);
}
}
}
}

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/*MIT License
Copyright(c) 2018 Vili Volčini / viliwonka
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
*/
using System.Collections.Generic;
using System;
using Unity.Mathematics;
using static Unity.Mathematics.math;
namespace DataStructures.ViliWonka.KDTree {
public partial class KDQuery {
public void Interval(KDTree tree, float2 min, float2 max, List<int> resultIndices) {
Reset();
float2[] points = tree.Points;
int[] permutation = tree.Permutation;
var rootNode = tree.RootNode;
PushToQueue(
rootNode,
rootNode.bounds.ClosestPoint((min + max) / 2)
);
KDQueryNode queryNode = null;
KDNode node = null;
// KD search with pruning (don't visit areas which distance is more away than range)
// Recursion done on Stack
while(LeftToProcess > 0) {
queryNode = PopFromQueue();
node = queryNode.node;
if(!node.Leaf) {
int partitionAxis = node.partitionAxis;
float partitionCoord = node.partitionCoordinate;
float2 tempClosestPoint = queryNode.tempClosestPoint;
if((tempClosestPoint[partitionAxis] - partitionCoord) < 0) {
// we already know we are inside negative bound/node,
// so we don't need to test for distance
// push to stack for later querying
// tempClosestPoint is inside negative side
// assign it to negativeChild
PushToQueue(node.negativeChild, tempClosestPoint);
tempClosestPoint[partitionAxis] = partitionCoord;
// testing other side
if(node.positiveChild.Count != 0
&& tempClosestPoint[partitionAxis] <= max[partitionAxis]) {
PushToQueue(node.positiveChild, tempClosestPoint);
}
}
else {
// we already know we are inside positive bound/node,
// so we don't need to test for distance
// push to stack for later querying
// tempClosestPoint is inside positive side
// assign it to positiveChild
PushToQueue(node.positiveChild, tempClosestPoint);
// project the tempClosestPoint to other bound
tempClosestPoint[partitionAxis] = partitionCoord;
// testing other side
if(node.negativeChild.Count != 0
&& tempClosestPoint[partitionAxis] >= min[partitionAxis]) {
PushToQueue(node.negativeChild, tempClosestPoint);
}
}
}
else {
// LEAF
// testing if node bounds are inside the query interval
if(node.bounds.min[0] >= min[0]
&& node.bounds.min[1] >= min[1]
&& node.bounds.min[2] >= min[2]
&& node.bounds.max[0] <= max[0]
&& node.bounds.max[1] <= max[1]
&& node.bounds.max[2] <= max[2]) {
for(int i = node.start; i < node.end; i++) {
resultIndices.Add(permutation[i]);
}
}
// node is not inside query interval, need to do test on each point separately
else {
for(int i = node.start; i < node.end; i++) {
int index = permutation[i];
float2 v = points[index];
if(v[0] >= min[0]
&& v[1] >= min[1]
&& v[2] >= min[2]
&& v[0] <= max[0]
&& v[1] <= max[1]
&& v[2] <= max[2]) {
resultIndices.Add(index);
}
}
}
}
}
}
}
}

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Assets/Scripts/ServerShared/NIH/KDTree/KDQuery/QueryKNearest.cs Normal file
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/*MIT License
Copyright(c) 2018 Vili Volčini / viliwonka
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
*/
#define KDTREE_VISUAL_DEBUG
using System.Collections.Generic;
using System;
using Unity.Mathematics;
using static Unity.Mathematics.math;
namespace DataStructures.ViliWonka.KDTree {
using Heap;
public partial class KDQuery {
SortedList<int, KSmallestHeap<int>> _heaps = new SortedList<int, KSmallestHeap<int>>();
/// <summary>
/// Returns indices to k closest points, and optionaly can return distances
/// </summary>
/// <param name="tree">Tree to do search on</param>
/// <param name="queryPosition">Position</param>
/// <param name="k">Max number of points</param>
/// <param name="resultIndices">List where resulting indices will be stored</param>
/// <param name="resultDistances">Optional list where resulting distances will be stored</param>
public void KNearest(KDTree tree, float2 queryPosition, int k, List<int> resultIndices, List<float> resultDistances = null) {
// pooled heap arrays
KSmallestHeap<int> kHeap;
_heaps.TryGetValue(k, out kHeap);
if(kHeap == null) {
kHeap = new KSmallestHeap<int>(k);
_heaps.Add(k, kHeap);
}
kHeap.Clear();
Reset();
float2[] points = tree.Points;
int[] permutation = tree.Permutation;
///Biggest Smallest Squared Radius
float BSSR = Single.PositiveInfinity;
var rootNode = tree.RootNode;
float2 rootClosestPoint = rootNode.bounds.ClosestPoint(queryPosition);
PushToHeap(rootNode, rootClosestPoint, queryPosition);
KDQueryNode queryNode = null;
KDNode node = null;
int partitionAxis;
float partitionCoord;
float2 tempClosestPoint;
// searching
while(minHeap.Count > 0) {
queryNode = PopFromHeap();
if(queryNode.distance > BSSR)
continue;
node = queryNode.node;
if(!node.Leaf) {
partitionAxis = node.partitionAxis;
partitionCoord = node.partitionCoordinate;
tempClosestPoint = queryNode.tempClosestPoint;
if((tempClosestPoint[partitionAxis] - partitionCoord) < 0) {
// we already know we are on the side of negative bound/node,
// so we don't need to test for distance
// push to stack for later querying
PushToHeap(node.negativeChild, tempClosestPoint, queryPosition);
// project the tempClosestPoint to other bound
tempClosestPoint[partitionAxis] = partitionCoord;
if(node.positiveChild.Count != 0) {
PushToHeap(node.positiveChild, tempClosestPoint, queryPosition);
}
}
else {
// we already know we are on the side of positive bound/node,
// so we don't need to test for distance
// push to stack for later querying
PushToHeap(node.positiveChild, tempClosestPoint, queryPosition);
// project the tempClosestPoint to other bound
tempClosestPoint[partitionAxis] = partitionCoord;
if(node.positiveChild.Count != 0) {
PushToHeap(node.negativeChild, tempClosestPoint, queryPosition);
}
}
}
else {
float sqrDist;
// LEAF
for(int i = node.start; i < node.end; i++) {
int index = permutation[i];
sqrDist = lengthsq(points[index] - queryPosition);
if(sqrDist <= BSSR) {
kHeap.PushObj(index, sqrDist);
if(kHeap.Full) {
BSSR = kHeap.HeadValue;
}
}
}
}
}
kHeap.FlushResult(resultIndices, resultDistances);
}
}
}

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/*MIT License
Copyright(c) 2018 Vili Volčini / viliwonka
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
*/
using System.Collections.Generic;
using System;
using Unity.Mathematics;
using static Unity.Mathematics.math;
namespace DataStructures.ViliWonka.KDTree {
public partial class KDQuery {
/// <summary>
/// Search by radius method.
/// </summary>
/// <param name="tree">Tree to do search on</param>
/// <param name="queryPosition">Position</param>
/// <param name="queryRadius">Radius</param>
/// <param name="resultIndices">Initialized list, cleared.</param>
public void Radius(KDTree tree, float2 queryPosition, float queryRadius, List<int> resultIndices, List<float> resultSqrDistances) {
Reset();
float2[] points = tree.Points;
int[] permutation = tree.Permutation;
float squaredRadius = queryRadius * queryRadius;
var rootNode = tree.RootNode;
PushToQueue(rootNode, rootNode.bounds.ClosestPoint(queryPosition));
KDQueryNode queryNode = null;
KDNode node = null;
// KD search with pruning (don't visit areas which distance is more away than range)
// Recursion done on Stack
while(LeftToProcess > 0) {
queryNode = PopFromQueue();
node = queryNode.node;
if(!node.Leaf) {
int partitionAxis = node.partitionAxis;
float partitionCoord = node.partitionCoordinate;
float2 tempClosestPoint = queryNode.tempClosestPoint;
if((tempClosestPoint[partitionAxis] - partitionCoord) < 0) {
// we already know we are inside negative bound/node,
// so we don't need to test for distance
// push to stack for later querying
// tempClosestPoint is inside negative side
// assign it to negativeChild
PushToQueue(node.negativeChild, tempClosestPoint);
tempClosestPoint[partitionAxis] = partitionCoord;
float sqrDist = lengthsq(tempClosestPoint - queryPosition);
// testing other side
if(node.positiveChild.Count != 0
&& sqrDist <= squaredRadius) {
PushToQueue(node.positiveChild, tempClosestPoint);
}
}
else {
// we already know we are inside positive bound/node,
// so we don't need to test for distance
// push to stack for later querying
// tempClosestPoint is inside positive side
// assign it to positiveChild
PushToQueue(node.positiveChild, tempClosestPoint);
// project the tempClosestPoint to other bound
tempClosestPoint[partitionAxis] = partitionCoord;
float sqrDist = lengthsq(tempClosestPoint - queryPosition);
// testing other side
if(node.negativeChild.Count != 0
&& sqrDist <= squaredRadius) {
PushToQueue(node.negativeChild, tempClosestPoint);
}
}
}
else {
// LEAF
for(int i = node.start; i < node.end; i++) {
int index = permutation[i];
if(lengthsq(points[index] - queryPosition) <= squaredRadius) {
resultIndices.Add(index);
}
}
}
}
}
/// <summary>
/// Search by radius method.
/// </summary>
/// <param name="tree">Tree to do search on</param>
/// <param name="queryPosition">Position</param>
/// <param name="queryRadius">Radius</param>
/// <param name="resultIndices">Initialized list, cleared.</param>
public IEnumerable<(int index, float sqrDistance)> Radius(KDTree tree, float2 queryPosition, float queryRadius) {
Reset();
float2[] points = tree.Points;
int[] permutation = tree.Permutation;
float squaredRadius = queryRadius * queryRadius;
var rootNode = tree.RootNode;
PushToQueue(rootNode, rootNode.bounds.ClosestPoint(queryPosition));
KDQueryNode queryNode = null;
KDNode node = null;
// KD search with pruning (don't visit areas which distance is more away than range)
// Recursion done on Stack
while(LeftToProcess > 0) {
queryNode = PopFromQueue();
node = queryNode.node;
if(!node.Leaf) {
int partitionAxis = node.partitionAxis;
float partitionCoord = node.partitionCoordinate;
float2 tempClosestPoint = queryNode.tempClosestPoint;
if((tempClosestPoint[partitionAxis] - partitionCoord) < 0) {
// we already know we are inside negative bound/node,
// so we don't need to test for distance
// push to stack for later querying
// tempClosestPoint is inside negative side
// assign it to negativeChild
PushToQueue(node.negativeChild, tempClosestPoint);
tempClosestPoint[partitionAxis] = partitionCoord;
float sqrDist = lengthsq(tempClosestPoint - queryPosition);
// testing other side
if(node.positiveChild.Count != 0
&& sqrDist <= squaredRadius) {
PushToQueue(node.positiveChild, tempClosestPoint);
}
}
else {
// we already know we are inside positive bound/node,
// so we don't need to test for distance
// push to stack for later querying
// tempClosestPoint is inside positive side
// assign it to positiveChild
PushToQueue(node.positiveChild, tempClosestPoint);
// project the tempClosestPoint to other bound
tempClosestPoint[partitionAxis] = partitionCoord;
float sqrDist = lengthsq(tempClosestPoint - queryPosition);
// testing other side
if(node.negativeChild.Count != 0
&& sqrDist <= squaredRadius) {
PushToQueue(node.negativeChild, tempClosestPoint);
}
}
}
else {
// LEAF
for(int i = node.start; i < node.end; i++) {
int index = permutation[i];
var lengthSq = lengthsq(points[index] - queryPosition);
if(lengthSq <= squaredRadius) {
yield return (index, lengthSq);
}
}
}
}
}
}
}

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/*MIT License
Copyright(c) 2018 Vili Volčini / viliwonka
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
*/
// change to !KDTREE_DUPLICATES
// if you know for sure you will not use duplicate coordinates (all unique)
#define KDTREE_DUPLICATES
using System.Collections;
using System.Collections.Generic;
using System;
using Unity.Mathematics;
using static Unity.Mathematics.math;
using float2 = Unity.Mathematics.float2;
namespace DataStructures.ViliWonka.KDTree {
public class KDTree {
public KDNode RootNode { get; private set; }
public float2[] Points { get { return points; } } // points on which kd-tree will build on. This array will stay unchanged when re/building kdtree!
private float2[] points;
public int[] Permutation { get { return permutation; } } // index aray, that will be permuted
private int[] permutation;
public int Count { get; private set; }
private int maxPointsPerLeafNode = 32;
private KDNode[] kdNodesStack;
private int kdNodesCount = 0;
public KDTree(int maxPointsPerLeafNode = 32) {
Count = 0;
points = new float2[0];
permutation = new int[0];
kdNodesStack = new KDNode[64];
this.maxPointsPerLeafNode = maxPointsPerLeafNode;
}
public KDTree(float2[] points, int maxPointsPerLeafNode = 32) {
this.points = points;
this.permutation = new int[points.Length];
Count = points.Length;
kdNodesStack = new KDNode[64];
this.maxPointsPerLeafNode = maxPointsPerLeafNode;
Rebuild();
}
public void Build(float2[] newPoints, int maxPointsPerLeafNode = -1) {
SetCount(newPoints.Length);
for(int i = 0; i < Count; i++) {
points[i] = newPoints[i];
}
Rebuild(maxPointsPerLeafNode);
}
public void Build(List<float2> newPoints, int maxPointsPerLeafNode = -1) {
SetCount(newPoints.Count);
for(int i = 0; i < Count; i++) {
points[i] = newPoints[i];
}
Rebuild(maxPointsPerLeafNode);
}
public void Rebuild(int maxPointsPerLeafNode = -1) {
for(int i = 0; i < Count; i++) {
permutation[i] = i;
}
if(maxPointsPerLeafNode > 0) {
this.maxPointsPerLeafNode = maxPointsPerLeafNode;
}
BuildTree();
}
public void SetCount(int newSize) {
Count = newSize;
// upsize internal arrays
if(Count > points.Length) {
Array.Resize(ref points, Count);
Array.Resize(ref permutation, Count);
}
}
void BuildTree() {
ResetKDNodeStack();
RootNode = GetKDNode();
RootNode.bounds = MakeBounds();
RootNode.start = 0;
RootNode.end = Count;
SplitNode(RootNode);
}
KDNode GetKDNode() {
KDNode node = null;
if(kdNodesCount < kdNodesStack.Length) {
if(kdNodesStack[kdNodesCount] == null) {
kdNodesStack[kdNodesCount] = node = new KDNode();
}
else {
node = kdNodesStack[kdNodesCount];
node.partitionAxis = -1;
}
}
else {
// automatic resize of KDNode pool array
Array.Resize(ref kdNodesStack, kdNodesStack.Length * 2);
node = kdNodesStack[kdNodesCount] = new KDNode();
}
kdNodesCount++;
return node;
}
void ResetKDNodeStack() {
kdNodesCount = 0;
}
/// <summary>
/// For calculating root node bounds
/// </summary>
/// <returns>Boundary of all Vector3 points</returns>
KDBounds MakeBounds() {
var max = float2(float.MinValue);
var min = float2(float.MaxValue);
int even = Count & ~1; // calculate even Length
// min, max calculations
// 3n/2 calculations instead of 2n
for (int i0 = 0; i0 < even; i0 += 2) {
int i1 = i0 + 1;
// X Coords
if (points[i0].x > points[i1].x) {
// i0 is bigger, i1 is smaller
if (points[i1].x < min.x)
min.x = points[i1].x;
if (points[i0].x > max.x)
max.x = points[i0].x;
}
else {
// i1 is smaller, i0 is bigger
if (points[i0].x < min.x)
min.x = points[i0].x;
if (points[i1].x > max.x)
max.x = points[i1].x;
}
// Y Coords
if (points[i0].y > points[i1].y) {
// i0 is bigger, i1 is smaller
if (points[i1].y < min.y)
min.y = points[i1].y;
if (points[i0].y > max.y)
max.y = points[i0].y;
}
else {
// i1 is smaller, i0 is bigger
if (points[i0].y < min.y)
min.y = points[i0].y;
if (points[i1].y > max.y)
max.y = points[i1].y;
}
}
// if array was odd, calculate also min/max for the last element
if(even != Count) {
// X
if (min.x > points[even].x)
min.x = points[even].x;
if (max.x < points[even].x)
max.x = points[even].x;
// Y
if (min.y > points[even].y)
min.y = points[even].y;
if (max.y < points[even].y)
max.y = points[even].y;
}
KDBounds b = new KDBounds();
b.min = min;
b.max = max;
return b;
}
/// <summary>
/// Recursive splitting procedure
/// </summary>
/// <param name="parent">This is where root node goes</param>
/// <param name="depth"></param>
///
void SplitNode(KDNode parent) {
// center of bounding box
KDBounds parentBounds = parent.bounds;
var parentBoundsSize = parentBounds.size;
// Find axis where bounds are largest
int splitAxis = 0;
float axisSize = parentBoundsSize.x;
if (axisSize < parentBoundsSize.y) {
splitAxis = 1;
axisSize = parentBoundsSize.y;
}
// Our axis min-max bounds
float boundsStart = parentBounds.min[splitAxis];
float boundsEnd = parentBounds.max[splitAxis];
// Calculate the spliting coords
float splitPivot = CalculatePivot(parent.start, parent.end, boundsStart, boundsEnd, splitAxis);
parent.partitionAxis = splitAxis;
parent.partitionCoordinate = splitPivot;
// 'Spliting' array to two subarrays
int splittingIndex = Partition(parent.start, parent.end, splitPivot, splitAxis);
// Negative / Left node
float2 negMax = parentBounds.max;
negMax[splitAxis] = splitPivot;
KDNode negNode = GetKDNode();
negNode.bounds = parentBounds;
negNode.bounds.max = negMax;
negNode.start = parent.start;
negNode.end = splittingIndex;
parent.negativeChild = negNode;
// Positive / Right node
float2 posMin = parentBounds.min;
posMin[splitAxis] = splitPivot;
KDNode posNode = GetKDNode();
posNode.bounds = parentBounds;
posNode.bounds.min = posMin;
posNode.start = splittingIndex;
posNode.end = parent.end;
parent.positiveChild = posNode;
// check if we are actually splitting it anything
// this if check enables duplicate coordinates, but makes construction a bit slower
#if KDTREE_DUPLICATES
if(negNode.Count != 0 && posNode.Count != 0) {
#endif
// Constraint function deciding if split should be continued
if(ContinueSplit(negNode))
SplitNode(negNode);
if(ContinueSplit(posNode))
SplitNode(posNode);
#if KDTREE_DUPLICATES
}
#endif
}
/// <summary>
/// Sliding midpoint splitting pivot calculation
/// 1. First splits node to two equal parts (midPoint)
/// 2. Checks if elements are in both sides of splitted bounds
/// 3a. If they are, just return midPoint
/// 3b. If they are not, then points are only on left or right bound.
/// 4. Move the splitting pivot so that it shrinks part with points completely (calculate min or max dependent) and return.
/// </summary>
/// <param name="start"></param>
/// <param name="end"></param>
/// <param name="boundsStart"></param>
/// <param name="boundsEnd"></param>
/// <param name="axis"></param>
/// <returns></returns>
float CalculatePivot(int start, int end, float boundsStart, float boundsEnd, int axis) {
//! sliding midpoint rule
float midPoint = (boundsStart + boundsEnd) / 2f;
bool negative = false;
bool positive = false;
float negMax = Single.MinValue;
float posMin = Single.MaxValue;
// this for loop section is used both for sorted and unsorted data
for (int i = start; i < end; i++) {
if (points[permutation[i]][axis] < midPoint)
negative = true;
else
positive = true;
if (negative == true && positive == true)
return midPoint;
}
if (negative) {
for (int i = start; i < end; i++)
if (negMax < points[permutation[i]][axis])
negMax = points[permutation[i]][axis];
return negMax;
}
else {
for (int i = start; i < end; i++)
if (posMin > points[permutation[i]][axis])
posMin = points[permutation[i]][axis];
return posMin;
}
}
/// <summary>
/// Similar to Hoare partitioning algorithm (used in Quick Sort)
/// Modification: pivot is not left-most element but is instead argument of function
/// Calculates splitting index and partially sorts elements (swaps them until they are on correct side - depending on pivot)
/// Complexity: O(n)
/// </summary>
/// <param name="start">Start index</param>
/// <param name="end">End index</param>
/// <param name="partitionPivot">Pivot that decides boundary between left and right</param>
/// <param name="axis">Axis of this pivoting</param>
/// <returns>
/// Returns splitting index that subdivides array into 2 smaller arrays
/// left = [start, pivot),
/// right = [pivot, end)
/// </returns>
int Partition(int start, int end, float partitionPivot, int axis) {
// note: increasing right pointer is actually decreasing!
int LP = start - 1; // left pointer (negative side)
int RP = end; // right pointer (positive side)
int temp; // temporary var for swapping permutation indexes
while (true) {
do {
// move from left to the right until "out of bounds" value is found
LP++;
}
while (LP < RP && points[permutation[LP]][axis] < partitionPivot);
do {
// move from right to the left until "out of bounds" value found
RP--;
}
while (LP < RP && points[permutation[RP]][axis] >= partitionPivot);
if (LP < RP) {
// swap
temp = permutation[LP];
permutation[LP] = permutation[RP];
permutation[RP] = temp;
}
else {
return LP;
}
}
}
/// <summary>
/// Constraint function. You can add custom constraints here - if you have some other data/classes binded to Vector3 points
/// Can hardcode it into
/// </summary>
/// <param name="node"></param>
/// <returns></returns>
bool ContinueSplit(KDNode node) {
return (node.Count > maxPointsPerLeafNode);
}
}
}

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Assets/Scripts/ServerShared/SampleElimination.cs Normal file
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@ -0,0 +1,164 @@
using System;
using System.Collections.Generic;
using System.Linq;
using DataStructures.ViliWonka.Heap;
using DataStructures.ViliWonka.KDTree;
using Unity.Mathematics;
using static Unity.Mathematics.math;
using float2 = Unity.Mathematics.float2;
public static class WeightedSampleElimination
{
private static float2 boundsMin = float2.zero; // The minimum bounds of the sampling domain
private static float2 boundsMax = float2(1); // The maximum bounds of the sampling domain
// Returns the minimum bounds of the sampling domain.
// The sampling domain boundaries are used for tiling and computing the maximum possible
// Poisson disk radius for the sampling domain. The default boundaries are between 0 and 1.
public static float2 BoundsMin => boundsMin;
// Returns the maximum bounds of the sampling domain.
// The sampling domain boundaries are used for tiling and computing the maximum possible
// Poisson disk radius for the sampling domain. The default boundaries are between 0 and 1.
public static float2 BoundsMax => boundsMax;
// This is the main method that uses weighted sample elimination for selecting a subset of samples
// with blue noise (Poisson disk) characteristics from a given input sample set (inputPoints).
// The selected samples are copied to outputPoints. The output size must be smaller than the input size.
//
// If the progressive parameter is true, the output sample points are ordered for progressive sampling,
// such that when the samples are introduced one by one in this order, each subset in the sequence
// exhibits blue noise characteristics.
//
// The d_max parameter defines radius within which the weight function is non-zero.
//
// The weight function is the crucial component of weighted sample elimination. It computes the weight
// of a sample point based on the placement of its neighbors within d_max radius. The weight function
// must have the following form:
//
// float weightFunction( float2 p0, float2 p1, float dist2, float dmax )
//
// The arguments p0 and p1 are the two neighboring points, dist2 is the square of the Euclidean distance
// between these two points, and d_max is the current radius for the weight function.
// Note that if the progressive parameter is on, the d_max value sent to the weight function can be
// different than the d_max value passed to this method.
public static void Eliminate (
float2[] inputPoints,
float2[] outputPoints,
Func<float2, float2, float, float, float> weightFunction,
float d_max = 0)
{
if ( d_max < .001f ) d_max = 2 * GetMaxPoissonDiskRadius( outputPoints.Length );
DoEliminate( inputPoints, outputPoints, d_max, weightFunction );
}
public static void Eliminate(
float2[] inputPoints,
float2[] outputPoints,
float d_max = 0,
float alpha = 8,
float beta = 0.65f,
float gamma = 1.5f)
{
if ( d_max < .001f ) d_max = 2 * GetMaxPoissonDiskRadius( outputPoints.Length );
float d_min = d_max * GetWeightLimitFraction( inputPoints.Length, outputPoints.Length, beta, gamma );
Eliminate( inputPoints, outputPoints, (p0, p1, d2, dmax) =>
{
float d = sqrt(d2);
if ( d < d_min ) d = d_min;
return pow( 1f / (d / dmax + .01f), alpha );
}, d_max);
}
// Returns the maximum possible Poisson disk radius in the given dimensions for the given sampleCount
// to spread over the given domainSize. If the domainSize argument is zero or negative, it is computed
// as the area or N-dimensional volume of the box defined by the minimum and maximum bounds.
// This method is used for the default weight function.
static float GetMaxPoissonDiskRadius( int sampleCount )
{
var domainSize = boundsMax[0] - boundsMin[0];
domainSize *= domainSize;
float sampleArea = domainSize / sampleCount;
return sqrt( sampleArea / ( 2 * sqrt(3) ) );
}
// This is the method that performs weighted sample elimination.
static void DoEliminate(
float2[] inputPoints,
float2[] outputPoints,
float d_max,
Func<float2, float2, float, float, float> weightFunction
)
{
// Build a k-d tree for samples
var kdtree = new KDTree(inputPoints);
var query = new KDQuery();
var dmax2 = d_max * d_max;
// Assign weights to each sample
float[] weights = new float[inputPoints.Length];
for (int i = 0; i < inputPoints.Length; i++)
{
var p = inputPoints[i];
// for (int qi = 0; qi < inputPoints.Length; qi++)
// {
// var d2 = lengthsq(inputPoints[i] - inputPoints[qi]);
// if (i != qi && d2 < dmax2)
// {
// var p2 = inputPoints[qi];
// weights[i] += weightFunction(p, p2, d2, d_max);
// }
// }
foreach (var (qi, d2) in query.Radius(kdtree, inputPoints[i], d_max))
{
var p2 = inputPoints[qi];
weights[i] += weightFunction(p, p2, d2, d_max);
}
}
// Build a heap for the samples using their weights
MaxHeap<int> heap = new MaxHeap<int>(inputPoints.Length);
for (int i = 0; i < inputPoints.Length; i++)
heap.PushObj(i, weights[i]);
// While the number of samples is greater than desired
int sampleCount = inputPoints.Length;
while (sampleCount > outputPoints.Length)
{
// Pull the top sample from heap
var i = heap.PopObj();
var p = inputPoints[i];
// For each sample around it, remove its weight contribution and update the heap
// for (int qi = 0; qi < inputPoints.Length; qi++)
// {
// var d2 = lengthsq(inputPoints[i] - inputPoints[qi]);
// if (i != qi && d2 < dmax2)
// {
// var p2 = inputPoints[qi];
// weights[qi] -= weightFunction(p, p2, d2, d_max);
// heap.SetValue(qi, weights[qi]);
// }
// }
foreach (var (qi, d2) in query.Radius(kdtree, p, d_max))
{
var p2 = inputPoints[qi];
weights[qi] -= weightFunction(p, p2, d2, d_max);
heap.SetValue(qi, weights[qi]);
}
sampleCount--;
}
var outputIndex = 0;
foreach (var i in heap.FlushResult())
{
outputPoints[outputIndex++] = inputPoints[i];
}
}
// Returns the minimum radius fraction used by the default weight function.
static float GetWeightLimitFraction( int inputSize, int outputSize, float beta, float gamma )
{
float ratio = (float) outputSize / inputSize;
return ( 1 - pow( ratio, gamma ) ) * beta;
}
}

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fileFormatVersion: 2
guid: 21d7e3a015d3430db9ecf66f8e59de28
timeCreated: 1615344428

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using System.Collections.Generic;
using Unity.Mathematics;
public class Sector
{
public List<SectorZone> Zones = new List<SectorZone>();
}
public class SectorZone
{
public string Name;
public float2 Position;
public List<SectorZone> AdjacentZones = new List<SectorZone>();
}

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fileFormatVersion: 2
guid: 02eb0a6347a54bcebc359807207af96b
timeCreated: 1615343479

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@ -0,0 +1,38 @@
using System;
using Unity.Mathematics;
using static Unity.Mathematics.math;
using Random = Unity.Mathematics.Random;
public static class SectorGenerator
{
public static Sector GenerateSector(ref Random random, SectorGenerationSettings settings, MarkovNameGenerator nameGenerator)
{
var inputSamples = new float2[2048];
var sample = 0;
var accumulator = 0f;
while (sample < inputSamples.Length)
{
var v = random.NextFloat2();
accumulator += pow(settings.CloudDensity(v), 3f) * (.25f-lengthsq(v - float2(.5f))) * 4;
if (accumulator > .5f)
{
accumulator = 0;
inputSamples[sample++] = v;
}
}
// for (int i = 0; i < inputSamples.Length; i++)
// {
// inputSamples[i] = random.NextFloat2();
// }
var outputSamples = new float2[64];
//Array.Copy(inputSamples,outputSamples,32);
Func<float2, float2, float, float, float> weightFunc = (p1, p2, d2, dmax) =>
pow(1-sqrt(d2)/dmax, 1+settings.CloudDensity((p1 + p2) / 2)*8);
WeightedSampleElimination.Eliminate(inputSamples, outputSamples, 0f, 4, 0.0f);
var sector = new Sector();
foreach (var v in outputSamples) sector.Zones.Add(new SectorZone {Position = v, Name = nameGenerator.NextName});
return sector;
}
}

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fileFormatVersion: 2
guid: 6436908b41be47d98391eabca4e57167
timeCreated: 1615343010

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Assets/Scripts/ServerShared/Settings.cs
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@ -9,6 +9,7 @@ using MessagePack;
using Newtonsoft.Json;
using Unity.Mathematics;
using static Unity.Mathematics.math;
using static Unity.Mathematics.noise;
[Serializable, MessagePackObject(keyAsPropertyName:true), JsonObject]
public class PlanetSettings
@ -42,6 +43,40 @@ public class GalaxyShapeSettings
public float TwistExponent = 2;
}
[Serializable, MessagePackObject(keyAsPropertyName:true), JsonObject]
public class SectorGenerationSettings
{
public float NoisePosition;
public float CloudExponent;
public float CloudAmplitude;
public float NoiseAmplitude;
public float NoiseOffset;
public float NoiseGain;
public float NoiseLacunarity;
public float NoiseFrequency;
public float fBm(float2 p, int octaves)
{
float freq = NoiseFrequency, amp = .5f;
float sum = 0;
for(int i = 0; i < octaves; i++)
{
if(i<4)
sum += (1-abs(snoise(p * freq))) * amp;
else sum += abs(snoise(p * freq)) * amp;
freq *= NoiseLacunarity;
amp *= NoiseGain;
}
return (sum + NoiseOffset)*NoiseAmplitude;
}
public float CloudDensity(float2 uv)
{
float noise = fBm(uv + NoisePosition, 8);
return pow(noise, CloudExponent) * CloudAmplitude;
}
}
[Serializable, MessagePackObject(keyAsPropertyName:true), JsonObject]
public class ZoneGenerationSettings
{
@ -83,6 +118,8 @@ public class ZoneGenerationSettings
public float GasGiantBandAltColorChance = .25f;
public ExponentialLerp GasGiantBandSaturation;
public ExponentialLerp GasGiantBandBrightness;
public string[] NameData;
}
[Serializable, MessagePackObject(keyAsPropertyName: true), JsonObject]