//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();
}
/*
* Score info about human-like playthrough
* Several considerations:
* 1. Number of locations collected for each region traversed
* 2. Number of regions traversed between finding major or helpful items
* 3. Number of regions traversed between finding major items
*/
public InterestingnessOutput ScorePlaythrough(WorldGraph world, PlaythroughInfo input, BiasOutput biasinfo)
{
//First, calculate fun metric, which desires a consistently high rate of checking item locations
Queue <int> RollingAvg = new Queue <int>();
List <double> avgs = new List <double>();
List <bool> highavg = new List <bool>();
foreach (int num in input.LocationsPerTraversal)
{
if (RollingAvg.Count == 5) //Rolling average of last 5 values
{
RollingAvg.Dequeue();
}
RollingAvg.Enqueue(num);
double avg = RollingAvg.Average();
highavg.Add(avg >= 1); //If average is above 1, considered high enough to be fun, so add true to list, else add false
avgs.Add(avg);
}
double fun = (double)highavg.Count(x => x) / highavg.Count(); //Our "Fun" score is the percentage of high values in the list
//Next calculate challenge metric, which desires rate at which items are found to be within some optimal range so that it is not too often or too rare
double LocationToItemRatio = (double)world.GetLocationCount() / world.Items.Where(x => x.Importance == 2).Count();
int low = (int)Math.Floor(LocationToItemRatio * .5);
int high = (int)Math.Ceiling(LocationToItemRatio * 1.5);
RollingAvg = new Queue <int>();
avgs = new List <double>();
List <bool> avginrange = new List <bool>();
foreach (int num in input.BetweenMajorList)
{
if (RollingAvg.Count == 3) //Tighter rolling average of last 3 values
{
RollingAvg.Dequeue();
}
RollingAvg.Enqueue(num);
double avg = RollingAvg.Average();
avginrange.Add(low <= avg && avg <= high); //If value is within range rather than too high or too low, add true to list to indicate it is within a good range
avgs.Add(avg);
}
double challenge = (double)avginrange.Count(x => x) / avginrange.Count(); //Our "Challenge" score is the percentage of values in the list within desirable range
//Next calculate satisfyingness metric based on how many locations are unlocked when an item is found
double LocationToItemRatioWithoutInitial = (double)(world.GetLocationCount() - input.InitialReachableCount) / world.Items.Where(x => x.Importance == 2).Count();
int satthreshold = (int)Math.Floor(LocationToItemRatioWithoutInitial); //Set threshold as number of not-immediately-accessible locations divided by number of major items
List <bool> SatisfyingReachesThreshold = new List <bool>();
foreach (int num in input.LocationsUnlockedPerMajorFound)
{
SatisfyingReachesThreshold.Add(num >= satthreshold);
}
double satisfyingness = (double)SatisfyingReachesThreshold.Count(x => x) / SatisfyingReachesThreshold.Count(); //Our "Satisfyingness" score is the percentage of values above the desired threshold
//Finally calculate boredom by observing regions which were visited more often than is expected
//First get a count of how many times each region was visited
List <int> visitcounts = new List <int>();
foreach (Region r in world.Regions)
{
visitcounts.Add(input.Traversed.Count(x => x.Name == r.Name));
}
//Calculate threshold with max number of times region should be visited being the number of traversals divided by number of regions
double TraversedToRegionRatio = (double)input.Traversed.Count() / world.Regions.Count();
int borethreshold = (int)Math.Ceiling(TraversedToRegionRatio);
List <bool> VisitsAboveThreshold = new List <bool>();
foreach (int num in visitcounts)
{
VisitsAboveThreshold.Add(num > borethreshold); //Again as before, add list of bool when value is above threshold
}
double boredom = (double)VisitsAboveThreshold.Count(x => x) / VisitsAboveThreshold.Count(); //Our "Boredom" score is the percentage of values above the desired threshold
//Add calculated stats to output. If a result is NaN (possible when not completable) save as -1
InterestingnessOutput output = new InterestingnessOutput();
output.bias = biasinfo;
output.fun = double.IsNaN(fun) ? -1 : fun;
output.challenge = double.IsNaN(challenge) ? -1 : challenge;
output.satisfyingness = double.IsNaN(satisfyingness) ? -1 : satisfyingness;
output.boredom = double.IsNaN(boredom) ? -1 : boredom;
//Use stats to calculate final interestingness score
//Each score is a double in the range [0, 1]
//Multiply each score (or its 1 - score if low score is desirable) by its percentage share of the total
double biasscore = (1 - output.bias.biasvalue) * .2;
double funscore = output.fun * .2;
double challengescore = output.challenge * .2;
double satscore = output.satisfyingness * .2;
double borescore = (1 - output.boredom) * .2;
double intscore = biasscore + funscore + challengescore + satscore + borescore;
//If any components are NaN, consider interestingness as NaN as well
if (double.IsNaN(fun) || double.IsNaN(challenge) || double.IsNaN(satisfyingness) || double.IsNaN(boredom))
{
output.interestingness = -1;
}
else
{
output.interestingness = intscore;
}
output.completable = input.Completable;
return(output);
}
//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();
}
