private static PartitionSet <T> FindBestPartition(T item, List <PartitionSet <T> > sets)
{
var bestSeen = double.MaxValue;
PartitionSet <T> targetSet = null;
foreach (var set in sets)
{
var candidate = set.Test(item);
if (candidate < bestSeen)
{
bestSeen = candidate;
targetSet = set;
}
}
return(targetSet);
}
///obviously impossible to test every possibility.
///Might be possible to iterate or do local hill climbing? order matters for all that.
///title length has weird transitivity; don't use that because it won't apply for other metrics.
///I could just do it 100 times with random starts, iterating adding members to the set which they are closest to.
///Then as a final step test each element to see if it belongs better in another set.
public PartitionData <T> GetPartitions(int partitionCount, List <T> Elements)
{
if (partitionCount < 2 || partitionCount > 100)
{
throw new Exception("Are you sure you want to generate that many partitions?");
}
var sets = new List <PartitionSet <T> >();
var ii = 0;
while (ii < partitionCount)
{
var px = new PartitionSet <T>(metrics, ii);
sets.Add(px);
ii++;
}
using (var db = new FusekiContext())
{
foreach (var el in Elements)
{
var targetSet = FindBestPartition(el, sets);
targetSet.Add(el);
}
}
//initial assignment done.
//now iterate over each item, removing it and then readding it where it belongs til we reach stability or N iterations.
var loopCt = 0;
var moveCt = 100;
var stats = new Dictionary <string, object>();
stats["InitialQuality"] = FindQuality(sets);
while (loopCt < 200)
{
moveCt = 0;
var PlannedMoves = new Dictionary <T, Tuple <PartitionSet <T>, PartitionSet <T> > >();
foreach (var set in sets)
{
foreach (var el in set.Items)
{
//remove it first so it has a free choice
var targetSet = FindBestPartition(el, sets);
if (targetSet != set)
{
moveCt++;
var data = new Tuple <PartitionSet <T>, PartitionSet <T> >(set, targetSet);
PlannedMoves[el] = data;
}
if (moveCt > 0)
{
break;
}
}
if (moveCt > 0)
{
break;
}
}
//problem: I am moving to favor the article, not to favor the overall quality of matches. i.e. if there is a linking article who is happier in a dedicated node, but removing him hurts the parent, how to do it?
foreach (var article in PlannedMoves.Keys)
{
var tup = PlannedMoves[article];
var old = tup.Item1;
var newset = tup.Item2;
old.Remove(article);
newset.Add(article);
}
loopCt++;
stats[$"quality:{loopCt} moved:{moveCt}"] = FindQuality(sets);
if (moveCt == 0)
{
break;
}
}
stats["moveCt"] = moveCt;
stats["loopCt"] = loopCt;
stats["Final quality"] = FindQuality(sets);
var pdata = new PartitionData <T>(sets, stats);
return(pdata);
}