//Utilizes BFS search algorithm to find all locations in the world which are reachable with the current item set
//In this algorithm, we want to check for items which have been removed from I but are still contained within R, so an initial search is done to collect items,
//then repeated iteratively until no new items are found, at which point the final reachability graph is returned.
public WorldGraph GetReachableLocationsAssumed(WorldGraph world, List <Item> owneditems)
{
WorldGraph copy = world.Copy(); //Used so items may be removed from world at will
List <Item> newitems = ItemSearch(copy, owneditems); //Find items within R
List <Item> combined = owneditems.ToList(); //Copy list
while (newitems.Count > 0)
{
combined.AddRange(newitems); //Add items to currently used items
newitems = ItemSearch(copy, combined); //Find items within R
}
return(GetReachableLocations(world, combined)); //Use that combined list to find final search result
}
//Calculate info about human-like playthrough and then return the score
public InterestingnessOutput CalcDistributionInterestingness(WorldGraph world)
{
PlaythroughInfo info = new PlaythroughInfo();
try
{
info = searcher.PlaythroughSearch(world.Copy());
}
catch
{
throw new Exception(); //Something went wrong, have calling code retry
}
BiasOutput biasinfo = CalcDistributionBias(world);
return(ScorePlaythrough(world, info, biasinfo));
}
//Experiment space
static void Main(string[] args)
{
Fill filler = new Fill();
Search searcher = new Search();
Statistics stats = new Statistics();
////Uncomment to test different complexity measures and generate many worlds with different parameters.
//double[] testaverages = new double[5];
//for (int regioncount = 10; regioncount <= 50; regioncount += 5)
//{
// for (int itemcount = 5; itemcount <= Math.Min(regioncount, 30); itemcount += 5)
// {
// List<TestComplexityOutput> complexity = AverageComplexity(regioncount, itemcount);
// Console.WriteLine("Regions: " + regioncount + ", Items: " + itemcount);
// Console.WriteLine("Sum: " + complexity.Average(x => x.sum));
// Console.WriteLine("Avg: " + complexity.Average(x => x.average));
// Console.WriteLine("Max: " + complexity.Average(x => x.max));
// Console.WriteLine("SOS: " + complexity.Average(x => x.sumofsquares));
// Console.WriteLine("Avg50: " + complexity.Average(x => x.top50));
// Console.WriteLine("Avg75: " + complexity.Average(x => x.top75));
// Console.Write(Environment.NewLine);
// }
//}
//Loop through each algorithm set to be used and each world in the list, performing specified algorithm on specified world and recording information about the result.
string[] algos = { "Random", "Forward", "Assumed" };
foreach (string worldname in testworlds)
{
DateTime expstart = DateTime.Now;
string jsontext = File.ReadAllText("../../../WorldGraphs/" + worldname + ".json");
WorldGraph world = JsonConvert.DeserializeObject <WorldGraph>(jsontext);
//Loop to perform fill algorithms
for (int i = 0; i < 3; i++) //0 = Random, 1 = Forward, 2 = Assumed
{
if (dotests[i])
{
int savecounter = 0;
int countofexp = db.Results.Count(x => x.Algorithm == algos[i] && x.World == worldname);
while (countofexp < trials) //Go until there are trial number of records in db
{
InterestingnessOutput intstat = new InterestingnessOutput();
double difference = -1;
while (true) //If something goes wrong in playthrough search, may need to retry
{
WorldGraph input = world.Copy(); //Copy so that world is not passed by reference and overwritten
List <Item> majoritempool = input.Items.Where(x => x.Importance == 2).ToList();
List <Item> minoritempool = input.Items.Where(x => x.Importance < 2).ToList();
WorldGraph randomizedgraph = new WorldGraph();
DateTime start = DateTime.Now; //Start timing right before algorithm
//Decide which algo to use based on i
switch (i)
{
case 0:
randomizedgraph = filler.RandomFill(input, majoritempool);
break;
case 1:
randomizedgraph = filler.ForwardFill(input, majoritempool);
break;
case 2:
randomizedgraph = filler.AssumedFill(input, majoritempool);
break;
}
randomizedgraph = filler.RandomFill(randomizedgraph, minoritempool); //Use random for minor items always since they don't matter
//Calculate metrics
DateTime end = DateTime.Now;
difference = (end - start).TotalMilliseconds;
try
{
intstat = stats.CalcDistributionInterestingness(randomizedgraph);
break; //Was successful, continue
}
catch { } //Something went wrong, retry fill from scratch
////Uncomment to print the spheres of the result.
//SphereSearchInfo output = searcher.SphereSearch(randomizedgraph);
//Print_Spheres(output);
}
//Store result in database
Result result = new Result();
result.Algorithm = algos[i];
result.World = worldname;
result.Completable = intstat.completable;
result.ExecutionTime = difference;
result.Bias = intstat.bias.biasvalue;
result.BiasDirection = intstat.bias.direction;
result.Interestingness = intstat.interestingness;
result.Fun = intstat.fun;
result.Challenge = intstat.challenge;
result.Satisfyingness = intstat.satisfyingness;
result.Boredom = intstat.boredom;
db.Entry(result).State = EntityState.Added;
savecounter++;
if (savecounter >= 1000) //Save every 1000 results processed
{
db.SaveChanges();
savecounter = 0;
}
countofexp++;
}
db.SaveChanges(); //Save changes when combo of algo and world is done
}
}
DateTime expend = DateTime.Now;
double expdifference = (expend - expstart).TotalMinutes;
Console.WriteLine("Time to perform " + trials + " iterations for world " + worldname + ": " + expdifference + " minutes"); //Print how long this world took to do
}
Console.ReadLine();
}
//Experiment space
static void Main(string[] args)
{
Fill filler = new Fill();
Search searcher = new Search();
Statistics stats = new Statistics();
//string testjsontext = File.ReadAllText("../../../WorldGraphs/World3.json");
//WorldGraph testworld = JsonConvert.DeserializeObject<WorldGraph>(testjsontext);
//double[] testaverages = new double[5];
//for (int regioncount = 10; regioncount <= 50; regioncount += 5)
//{
// for (int itemcount = 5; itemcount <= Math.Min(regioncount, 30); itemcount += 5)
// {
// List<TestComplexityOutput> complexity = AverageComplexity(regioncount, itemcount);
// Console.WriteLine("Regions: " + regioncount + ", Items: " + itemcount);
// Console.WriteLine("Sum: " + complexity.Average(x => x.sum));
// Console.WriteLine("Avg: " + complexity.Average(x => x.average));
// Console.WriteLine("Max: " + complexity.Average(x => x.max));
// Console.WriteLine("SOS: " + complexity.Average(x => x.sumofsquares));
// Console.WriteLine("Avg50: " + complexity.Average(x => x.top50));
// Console.WriteLine("Avg75: " + complexity.Average(x => x.top75));
// Console.Write(Environment.NewLine);
// }
//}
//string generatedjson = GenerateWorld(50, 30);
//string jsontest = File.ReadAllText("../../../WorldGraphs/World5.json");
//WorldGraph testworld = JsonConvert.DeserializeObject<WorldGraph>(jsontest);
//int testlocationcount = testworld.GetLocationCount();
//Search testsearcher = new Search();
//testsearcher.PathsToRegion(world, world.Regions.First(x => x.Name == "Waterfall"));
//Parser testparse = new Parser();
//string result = testparse.Simplify("(Sword and Bow and Bow) or Has(Key,2)"); //Should be simplified to something like (Sword and Bow) or Has(Key,2)
//string result2 = testparse.Simplify("Sword or Sword and Bow"); //Should be simplified to Sword
////majoritempool.RemoveAt(8);
////majoritempool.RemoveAt(0);
//bool result = testparse.RequirementsMet("(Sword and Bow) or Has(Key,2)", majoritempool);
//string testjsontext = File.ReadAllText("../../../WorldGraphs/TestWorldOriginal.json");
//WorldGraph testworld = JsonConvert.DeserializeObject<WorldGraph>(testjsontext);
//SphereSearchInfo testoutput = searcher.SphereSearch(testworld);
//Print_Spheres(testoutput);
string[] algos = { "Random", "Forward", "Assumed" };
foreach (string worldname in testworlds)
{
DateTime expstart = DateTime.Now;
string jsontext = File.ReadAllText("../../../WorldGraphs/" + worldname + ".json");
WorldGraph world = JsonConvert.DeserializeObject <WorldGraph>(jsontext);
int l = world.GetLocationCount();
//Loop to perform fill
for (int i = 0; i < 3; i++) //0 = Random, 1 = Forward, 2 = assumed
{
if (dotests[i])
{
//List<InterestingnessOutput> intstats = new List<InterestingnessOutput>();
//double totaltime = 0;
int savecounter = 0;
int countofexp = db.Results.Count(x => x.Algorithm == algos[i] && x.World == worldname);
//int countofexp = 0;
while (countofexp < trials) //Go until there are trial number of records in db
{
InterestingnessOutput intstat = new InterestingnessOutput();
double difference = -1;
while (true) //If something goes wrong in playthrough search, may need to retry
{
WorldGraph input = world.Copy(); //Copy so that world is not passed by reference and overwritten
List <Item> majoritempool = input.Items.Where(x => x.Importance == 2).ToList();
List <Item> minoritempool = input.Items.Where(x => x.Importance < 2).ToList();
WorldGraph randomizedgraph = new WorldGraph();
DateTime start = DateTime.Now; //Start timing right before algorithm
//Decide which algo to use based on i
switch (i)
{
case 0:
randomizedgraph = filler.RandomFill(input, majoritempool);
break;
case 1:
randomizedgraph = filler.ForwardFill(input, majoritempool);
break;
case 2:
randomizedgraph = filler.AssumedFill(input, majoritempool);
break;
}
randomizedgraph = filler.RandomFill(randomizedgraph, minoritempool); //Use random for minor items always since they don't matter
//Calculate metrics
DateTime end = DateTime.Now;
difference = (end - start).TotalMilliseconds;
//totaltime += difference;
//string randomizedjson = JsonConvert.SerializeObject(randomizedgraph);
//SphereSearchInfo output = searcher.SphereSearch(randomizedgraph);
//Print_Spheres(output);
try
{
intstat = stats.CalcDistributionInterestingness(randomizedgraph);
break; //Was successful, continue
}
catch { } //Something went wrong, retry fill from scratch
}
//intstats.Add(intstat);
//Store result in database
Result result = new Result();
result.Algorithm = algos[i];
result.World = worldname;
result.Completable = intstat.completable;
result.ExecutionTime = difference;
result.Bias = intstat.bias.biasvalue;
result.BiasDirection = intstat.bias.direction;
result.Interestingness = intstat.interestingness;
result.Fun = intstat.fun;
result.Challenge = intstat.challenge;
result.Satisfyingness = intstat.satisfyingness;
result.Boredom = intstat.boredom;
db.Entry(result).State = EntityState.Added;
savecounter++;
if (savecounter >= 1000) //Save every 1000 results processed
{
db.SaveChanges();
savecounter = 0;
}
countofexp++;
}
//double avgint = intstats.Where(x => x.completable).Average(x => x.interestingness);
//Console.WriteLine("Average interestingness for " + algos[i] + " Fill in world " + worldname + ": " + avgint);
//double avgbias = intstats.Where(x => x.completable).Average(x => x.bias.biasvalue);
//Console.WriteLine("Average bias for " + algos[i] + " Fill in world " + worldname + ": " + avgbias);
//double avgfun = intstats.Where(x => x.completable).Average(x => x.fun);
//Console.WriteLine("Average fun for " + algos[i] + " Fill in world " + worldname + ": " + avgfun);
//double avgchal = intstats.Where(x => x.completable).Average(x => x.challenge);
//Console.WriteLine("Average challenge for " + algos[i] + " Fill in world " + worldname + ": " + avgchal);
//double avgsat = intstats.Where(x => x.completable).Average(x => x.satisfyingness);
//Console.WriteLine("Average satisfyingness for " + algos[i] + " Fill in world " + worldname + ": " + avgsat);
//double avgbore = intstats.Where(x => x.completable).Average(x => x.boredom);
//Console.WriteLine("Average boredom for " + algos[i] + " Fill in world " + worldname + ": " + avgbore);
//double avgtime = totaltime / trials;
//Console.WriteLine("Average time to generate for " + algos[i] + " Fill in world " + worldname + ": " + avgtime + "ms");
db.SaveChanges(); //Save changes when combo of algo and world is done
}
//Console.Write(Environment.NewLine);
}
//Console.Write(Environment.NewLine);
//Console.Write(Environment.NewLine);
DateTime expend = DateTime.Now;
double expdifference = (expend - expstart).TotalMinutes;
Console.WriteLine("Time to perform " + trials + " iterations for world " + worldname + ": " + expdifference + " minutes");
}
Console.ReadLine();
}
