/// <summary>
/// This finds brains that are really close together, and turns them into sets (the rest of the brains become 1 item sets)
/// </summary>
internal static Set2D[] IOLinks_PreMergeBrains(Item2D[] brains, SortedList<Tuple<int, int>, double> links)
{
if (!IOPREMERGE_SHOULD)
{
return Enumerable.Range(0, brains.Length).Select(o => new Set2D(o, brains)).ToArray();
}
// Get the AABB of the brains, and use the diagonal as the size
var aabb = Math2D.GetAABB(brains.Select(o => o.Position));
double maxDistance = (aabb.Item2 - aabb.Item1).Length;
// Figure out the max distance allowed for a merge
double threshold = maxDistance * IOPREMERGE_DISTANCE;
// Find links that should be merged
var closePairs = links.
Where(o => o.Value <= threshold).
OrderBy(o => o.Value).
ToArray();
if (closePairs.Length == 0)
{
return Enumerable.Range(0, brains.Length).Select(o => new Set2D(o, brains)).ToArray();
}
// Combine any close pairs that share a point (turn pairs into triples)
List<List<int>> sets = IOLinks_PreMergeBrains_Sets(closePairs);
// Build the final list
return IOLinks_PreMergeBrains_Centers(sets, brains, links);
}
private static Set2D[] IOLinks_PreMergeBrains_Centers(List<List<int>> sets, Item2D[] brains, SortedList<Tuple<int, int>, double> links)
{
List<Set2D> retVal = new List<Set2D>();
// Multi brain sets
retVal.AddRange(sets.Select(o => new Set2D(o.Distinct(), brains)));
// Single brain sets
foreach (Tuple<int, int> key in links.Keys)
{
if (!retVal.Any(o => o.Indices.Contains(key.Item1)))
{
retVal.Add(new Set2D(key.Item1, brains));
}
if (!retVal.Any(o => o.Indices.Contains(key.Item2)))
{
retVal.Add(new Set2D(key.Item2, brains));
}
}
return retVal.ToArray();
}
public Set2D(IEnumerable<int> indices, Item2D[] all)
{
this.Indices = indices.ToArray();
this.Items = this.Indices.Select(o => all[o]).ToArray();
this.Positions = this.Items.Select(o => o.Position).ToArray();
if (this.Items.Length == 1)
{
this.Center = this.Items[0].Position;
}
else
{
this.Center = Math2D.GetCenter(this.Positions);
}
}
/// <summary>
/// Link brains to io
/// </summary>
private static LinkIO[] IOLinks(Item2D[] brains, Item2D[] io, SortedList<Tuple<int, int>, double> allBrainLinks)
{
if (brains.Length < 2)
{
throw new ArgumentException("This method requires at least two brains: " + brains.Length.ToString());
}
// Look for brains that are really close together, treat those as single brains
Set2D[] brainSets = IOLinks_PreMergeBrains(brains, allBrainLinks);
// Link IO to each brain set
VoronoiResult2D voronoi = Math2D.GetVoronoi(brainSets.Select(o => o.Center).ToArray(), true);
Tuple<int, int>[] initial = IOLinks_Initial(brainSets, io, voronoi);
//TODO: If a brain set is saturated, and there is an under used brainset nearby, transfer some links
Tuple<int, int>[] adjusted = IOLinks_PostAdjust(initial, brainSets, io);
return adjusted.Select(o => new LinkIO(brainSets[o.Item1], o.Item2, io)).ToArray();
}
public BrainBurden(int index, Set2D[] brainSets, Item2D[] io)
{
this.Index = index;
this.Brain = brainSets[index];
this.Size = this.Brain.Items.Sum(o => o.Size);
_io = io;
}
private static LinkIO[] IOLinks(Item2D[] brains, Item2D[] io, SortedList<Tuple<int, int>, double> allBrainLinks, IOLinkupPriority ioLinkupPriority, double brainLinkResistanceMult)
{
// Look for brains that are really close together, treat those as single brains
Set2D[] brainSets = Worker2D_Voronoi.IOLinks_PreMergeBrains(brains, allBrainLinks);
#region Brain-IO Distances
// Figure out the distances between io and brains
var distancesIO = Enumerable.Range(0, io.Length).
Select(o => new
{
IOIndex = o,
BrainDistances = Enumerable.Range(0, brainSets.Length).
Select(p => Tuple.Create(p, (brainSets[p].Center - io[o].Position).Length)). //Item1=BrainIndex, Item2=DistanceToBrain
OrderBy(p => p.Item2). // first brain needs to be the shortest distance
ToArray()
});
switch (ioLinkupPriority)
{
case IOLinkupPriority.ShortestDistFirst:
distancesIO = distancesIO.OrderBy(o => o.BrainDistances.First().Item2);
break;
case IOLinkupPriority.LongestDistFirst:
distancesIO = distancesIO.OrderByDescending(o => o.BrainDistances.First().Item2);
break;
case IOLinkupPriority.RandomOrder:
//TODO: Come up with a less expensive way of doing this
//.Select(o => new { Orig=o, Key=Guid.NewGuid }).OrderBy(o => o.Key).Select(o => o.Orig)
Random rand = StaticRandom.GetRandomForThread();
distancesIO = distancesIO.
Select(o => new { Orig = o, Key = rand.Next(int.MaxValue) }).
OrderBy(o => o.Key).
Select(o => o.Orig);
break;
default:
throw new ApplicationException("Unknown IOLinkupPriority: " + ioLinkupPriority.ToString());
}
distancesIO = distancesIO.ToArray();
#endregion
// Brain-Brain Distances
var distancesBrain = BrainBrainDistances(brainSets, brainLinkResistanceMult);
// Link IO to brains
BrainBurden[] links = Enumerable.Range(0, brainSets.Length).Select(o => new BrainBurden(o, brainSets, io)).ToArray();
foreach (var distanceIO in distancesIO)
{
int ioIndex = distanceIO.IOIndex;
int closestBrainIndex = distanceIO.BrainDistances[0].Item1;
AddIOLink(links, ioIndex, io[ioIndex].Size, closestBrainIndex, distancesBrain[closestBrainIndex]);
}
// Build the return
List<LinkIO> retVal = new List<LinkIO>();
foreach (BrainBurden brain in links)
{
foreach (int ioIndex in brain.IOLinks)
{
retVal.Add(new LinkIO(brain.Brain, ioIndex, io));
}
}
return retVal.ToArray();
}
public void Recalc(Set2D[] brainSets, Item2D[] io)
{
this.BrainSize = brainSets[this.Index].Items.Sum(o => o.Size);
this.Burden = CalculateBurden(UtilityCore.Iterate(this.LinksOrig, this.LinksMoved).Sum(o => io[o].Size), this.BrainSize); // size of the links / size of the brain
}
private static bool IOLinks_PostAdjust_MoveNext(BrainBurden[] ioLinks, Tuple<int, double>[][] brainLinks, Set2D[] brainSets, Item2D[] io)
{
List<Tuple<BrainBurden, int, double, double>> candidates = new List<Tuple<BrainBurden, int, double, double>>();
// Find brains that have excess links to give away, and which ones to hand to
foreach (BrainBurden ioLink in ioLinks.Where(o => o.LinksOrig.Count > 0))
{
foreach (Tuple<int, double> brainLink in brainLinks[ioLink.Index])
{
double otherBurden = ioLinks.First(o => o.Index == brainLink.Item1).Burden;
if (ioLink.Burden > otherBurden + brainLink.Item2)
{
candidates.Add(Tuple.Create(ioLink, brainLink.Item1, ioLink.Burden - (otherBurden + brainLink.Item2), brainLink.Item2));
}
}
}
// Iterate over them with the largest distance first (can't just pull the top, because an individual io link may represent too big of a burden
// to be able to shift)
foreach (var candidate in candidates.OrderByDescending(o => o.Item3))
{
// Try to move a link
if (IOLinks_PostAdjust_MoveNext_Brain(candidate.Item1, ioLinks.First(o => o.Index == candidate.Item2), candidate.Item4, brainSets, io))
{
return true;
}
}
return false;
}
public LinkIO(IEnumerable<int> brains, int io, Item2D[] allBrains, Item2D[] allIO)
: this(new Set2D(brains, allBrains), io, allIO) { }
public LinkIO(Set2D brains, int io, Item2D[] allIO)
{
this.Brains = brains;
this.IOIndex = io;
this.IO = allIO[io];
}
public LinkIO(int brain, int io, Item2D[] allBrains, Item2D[] allIO)
: this(new Set2D(brain, allBrains), io, allIO) { }
public LinkBrain2D(IEnumerable<int> set1, IEnumerable<int> set2, Item2D[] all)
: this(new Set2D(set1, all), new Set2D(set2, all)) { }
public LinkBrain2D(int item1, int item2, Item2D[] all)
: this(new Set2D(item1, all), new Set2D(item2, all)) { }
private static Tuple<int, int>[] IOLinks_Initial(Set2D[] brains, Item2D[] io, VoronoiResult2D voronoi)
{
List<Tuple<int, int>> retVal = new List<Tuple<int, int>>();
List<int> remainingIO = Enumerable.Range(0, io.Length).ToList(); // store the remaining so that they can be removed as found (avoid unnecessary IsInside checks)
for (int brainCntr = 0; brainCntr < brains.Length; brainCntr++)
{
Edge2D[] edges = voronoi.EdgesByControlPoint[brainCntr].Select(o => voronoi.Edges[o]).ToArray();
if (edges.Length == 1)
{
throw new ApplicationException("finish this");
}
foreach (int ioIndex in remainingIO.ToArray())
{
if (Edge2D.IsInside(edges, io[ioIndex].Position))
{
retVal.Add(Tuple.Create(brainCntr, ioIndex));
remainingIO.Remove(ioIndex);
}
}
}
return retVal.ToArray();
}
public static void GetLinks(out LinkBrain2D[] brainLinks, out LinkIO[] ioLinks, Item2D[] brains, Item2D[] io)
{
if (brains == null || brains.Length == 0)
{
brainLinks = null;
ioLinks = null;
return;
}
else if (brains.Length == 1)
{
brainLinks = null;
ioLinks = Enumerable.Range(0, io.Length).Select(o => new LinkIO(0, o, brains, io)).ToArray();
return;
}
// Link brains:brains
SortedList<Tuple<int, int>, double> allBrainLinks;
BrainLinks(out allBrainLinks, out brainLinks, brains);
// Link brains:io
ioLinks = IOLinks(brains, io, allBrainLinks);
}
private static Tuple<int, int>[] IOLinks_PostAdjust(Tuple<int, int>[] initial, Set2D[] brainSets, Item2D[] io)
{
// Get the links and distances between brain sets
Tuple<int, double>[][] brainLinks = IOLinks_PostAdjust_BrainBrainLinks(brainSets);
// Turn the initial links into something more usable (list of links by brain)
BrainBurden[] ioLinks = initial.
GroupBy(o => o.Item1).
Select(o => new BrainBurden(o.Key, o.Select(p => p.Item2))).
ToArray();
// Make sure there is an element in ioLinks for each brainset (the groupby logic above only grabs brainsets that have links)
int[] missing = Enumerable.Range(0, brainLinks.Length).Where(o => !ioLinks.Any(p => p.Index == o)).ToArray();
ioLinks = UtilityCore.Iterate(ioLinks, missing.Select(o => new BrainBurden(o, Enumerable.Empty<int>()))).ToArray();
// Move one link at a time
while (true)
{
// Figure out how burdened each brain set is
foreach (BrainBurden brain in ioLinks)
{
brain.Recalc(brainSets, io);
}
// Find the best link to move
if (!IOLinks_PostAdjust_MoveNext(ioLinks, brainLinks, brainSets, io))
{
break;
}
}
// Just build it manually
//return ioLinks.Select(o => new { BrainIndex = o.Index, UtilityCore.Iterate(o.LinksOrig, o.LinksMoved)
//var test = ioLinks.
// Select(o => new { BrainIndex = o.Index, Links = UtilityCore.Iterate(o.LinksOrig, o.LinksMoved).ToArray() }).
// ToArray();
List<Tuple<int, int>> retVal = new List<Tuple<int, int>>();
foreach (BrainBurden brain in ioLinks)
{
foreach (int ioIndex in UtilityCore.Iterate(brain.LinksOrig, brain.LinksMoved))
{
retVal.Add(Tuple.Create(brain.Index, ioIndex));
}
}
return retVal.ToArray();
//return initial;
}
/// <summary>
/// Link brains to each other (delaunay graph, then prune thin triangles)
/// </summary>
internal static void BrainLinks(out SortedList<Tuple<int, int>, double> all, out LinkBrain2D[] pruned, Item2D[] brains)
{
if (brains.Length < 2)
{
throw new ArgumentException("This method requires at least two brains: " + brains.Length.ToString());
}
else if (brains.Length == 2)
{
all = GetLengths(new[] { Tuple.Create(0, 1) }, brains);
pruned = all.Keys.Select(o => new LinkBrain2D(o.Item1, o.Item2, brains)).ToArray();
return;
}
TriangleIndexed[] triangles = Math2D.GetDelaunayTriangulation(brains.Select(o => o.Position).ToArray(), brains.Select(o => o.Position.ToPoint3D()).ToArray());
all = GetLengths(TriangleIndexed.GetUniqueLines(triangles), brains);
// Prune links that don't make sense
pruned = PruneBrainLinks(triangles, all, brains);
}
private static bool IOLinks_PostAdjust_MoveNext_Brain(BrainBurden from, BrainBurden to, double linkBurden, Set2D[] brainSets, Item2D[] io)
{
// Cache the sizes of the current io links
double fromIOSize = UtilityCore.Iterate(from.LinksOrig, from.LinksMoved).Sum(o => io[o].Size);
double toIOSize = UtilityCore.Iterate(to.LinksOrig, to.LinksMoved).Sum(o => io[o].Size);
// See what the new burdens would be for from and to for each io link
var newBurdens = from.LinksOrig.Select(o => new
{
IOIndex = o,
FromBurden = BrainBurden.CalculateBurden(fromIOSize - io[o].Size, from.BrainSize),
ToBurden = BrainBurden.CalculateBurden(toIOSize + io[o].Size, to.BrainSize),
}).
Where(o => o.FromBurden >= linkBurden + o.ToBurden). // throw out any moves that cause a reverse in burden
Select(o => new
{
IOIndex = o.IOIndex,
FromBurden = o.FromBurden,
ToBurden = o.ToBurden,
Distance = (brainSets[to.Index].Center - io[o.IOIndex].Position).Length,
//TODO: Other scoring criterea here
}).
ToArray();
if (newBurdens.Length == 0)
{
return false;
}
// Come up with the best io to move
//TODO: Things to consider
// Distance between io and to brain
// Types of IO that from and to have (try to specialize)
//
// When combining scores, can't just score things linearly, then add up the score. Average performers of multiple categories
// would win
var best = newBurdens.OrderBy(o => o.Distance).First();
// Move the link
to.LinksMoved.Add(best.IOIndex);
from.LinksOrig.Remove(best.IOIndex);
return true;
}
private static LinkBrain2D[] PruneBrainLinks(TriangleIndexed[] triangles, SortedList<Tuple<int, int>, double> all, Item2D[] brains)
{
List<Tuple<int[], int[]>> retVal = all.Keys.
Select(o => Tuple.Create(new[] { o.Item1 }, new[] { o.Item2 })).
ToList();
foreach (TriangleIndexed triangle in triangles)
{
Tuple<bool, TriangleEdge> changeEdge = PruneBrainLinks_LongThin(triangle, all);
if (changeEdge == null)
{
continue;
}
if (changeEdge.Item1)
{
PruneBrainLinks_Merge(triangle, changeEdge.Item2, retVal);
}
else
{
PruneBrainLinks_Remove(triangle, changeEdge.Item2, retVal);
}
}
return retVal.Select(o => new LinkBrain2D(o.Item1, o.Item2, brains)).ToArray();
}
public static void GetLinks(out LinkBrain2D[] brainLinks, out LinkIO[] ioLinks, Item2D[] brains, Item2D[] io, IOLinkupPriority ioLinkupPriority = IOLinkupPriority.ShortestDistFirst, double brainLinkResistanceMult = 10)
{
if (brains == null || brains.Length == 0)
{
brainLinks = null;
ioLinks = null;
return;
}
else if (brains.Length == 1)
{
brainLinks = null;
ioLinks = Enumerable.Range(0, io.Length).Select(o => new LinkIO(0, o, brains, io)).ToArray();
return;
}
// Link brains:brains
SortedList<Tuple<int, int>, double> allBrainLinks;
Worker2D_Voronoi.BrainLinks(out allBrainLinks, out brainLinks, brains);
// Link brains:io
ioLinks = IOLinks(brains, io, allBrainLinks, ioLinkupPriority, brainLinkResistanceMult);
}
//NOTE: This makes sure that key.item1 is less than key.item2
private static SortedList<Tuple<int, int>, double> GetLengths(Tuple<int, int>[] keys, Item2D[] brains)
{
SortedList<Tuple<int, int>, double> retVal = new SortedList<Tuple<int, int>, double>();
foreach (Tuple<int, int> key in keys.Select(o => o.Item1 < o.Item2 ? o : Tuple.Create(o.Item2, o.Item1)))
{
double distance = (brains[key.Item1].Position - brains[key.Item2].Position).Length;
retVal.Add(key, distance);
}
return retVal;
}
public void Add2DItem(Item2D item2D)
{
item2DList.Add(item2D);
}
public Set2D(int index, Item2D[] all)
: this(new[] { index }, all) { }
