/// <summary>
/// Applies the specified inputs.
/// </summary>
/// <param name="inputs">The inputs.</param>
/// <param name="featureBuckets">The feature buckets.</param>
/// <param name="priors">The priors.</param>
/// <param name="results">The results.</param>
/// <param name="mode">The mode.</param>
/// <param name="showFactorGraph">if set to <c>true</c> [show factor graph].</param>
/// <exception cref="System.NotImplementedException">Not implemented for this model</exception>
public virtual void Apply(Inputs inputs, FeatureSet featureBuckets, Priors priors, ref Results results, InputMode mode, bool showFactorGraph = false)
{
this.Engine.ShowFactorGraph = showFactorGraph;
if (mode.HasFlag(InputMode.Validation))
{
this.SetObservedValues(inputs.Validation.Instances, featureBuckets, InputMode.Validation, priors);
results.Validation = new Results.ResultsSet {
IsRepliedTo = this.Engine.Infer <Bernoulli[]>(this.RepliedTo)
};
}
if (mode.HasFlag(InputMode.Testing))
{
this.SetObservedValues(inputs.Test.Instances, featureBuckets, InputMode.Testing, priors);
results.Test = new Results.ResultsSet {
IsRepliedTo = this.Engine.Infer <Bernoulli[]>(this.RepliedTo)
};
}
if (mode.HasFlag(InputMode.TrainAndValidation))
{
this.SetObservedValues(inputs.TrainAndValidation.Instances, featureBuckets, InputMode.TrainAndValidation, priors);
results.Validation = new Results.ResultsSet {
IsRepliedTo = this.Engine.Infer <Bernoulli[]>(this.RepliedTo)
};
}
this.Engine.ShowFactorGraph = this.ShowFactorGraph;
}
internal override void RemoveKey(IEntityKey key)
{
base.RemoveKey(key);
var job = key as JobKey;
if (job != null && Priors != null)
{
Priors.Remove(job);
}
var res = key as ResourceKey;
if (res != null && Resources != null)
{
Resources.Remove(res);
}
}
/// <summary>
/// The three player toy experiment.
/// </summary>
public void ThreePlayerToyExperiment()
{
var players = new[] { "Jill", "Fred", "Steve" };
var scores = new[] { new[] { 2, 1, 0 }, new[] { 1, 2, 0 } };
var outcomes =
scores.Select(s => players.Zip(s, (p, score) => new { p, score }).ToDictionary(ia => ia.p, ia => ia.score)).ToArray();
var inputs = Inputs <MultiPlayerGame> .CreateToyInputs(outcomes);
outputter.Out(inputs,
Contents.S4ExtensionsToTheCoreModel.NumberedName,
"ThreePlayerToyExperiment",
"Inputs");
// Rerun first game with different variances
var priors = new Priors
{
Skills =
{
{ "Jill", new Gaussian(120, 400) },
{ "Fred", new Gaussian(100, inputs.InitialVariance) },
{ "Steve", new Gaussian(140, inputs.InitialVariance) }
}
};
var model = new MultiPlayer(inputs.TrueSkillParameters, ShowFactorGraph);
var threePlayerToyExperiment = new[]
{
new ToyExperiment(model, inputs.Games[0], priors),
new ToyExperiment(model, inputs.Games[1], priors)
};
outputter.Out(threePlayerToyExperiment,
Contents.S4ExtensionsToTheCoreModel.NumberedName,
"ThreePlayerToyExperiment",
"Experiments");
}
private static void AgentIsRival_Postfix(Agent myAgent, StatusEffects __instance, ref bool __result)
{
// All custom Social traits with Rivalry & XP bonus
Agent otherAgent = __instance.agent;
if (MobDebt.AgentIsRival(myAgent, otherAgent) || BootLicker.AgentIsRival(myAgent, otherAgent) || Priors.AgentIsRival(myAgent, otherAgent))
{
__result = true;
}
}
/// <summary>
/// Sets the observed values.
/// </summary>
/// <param name="instances">The instances.</param>
/// <param name="featureSet">The feature buckets.</param>
/// <param name="mode">The mode.</param>
/// <param name="priors">The priors.</param>
/// <exception cref="System.InvalidOperationException">Data is null</exception>
public override void SetObservedValues(IList <Inputs.Instance> instances, FeatureSet featureSet, InputMode mode, Priors priors)
{
if (instances == null)
{
throw new InvalidOperationException("Data is null");
}
this.NumberOfMessages.ObservedValue = instances.Count;
this.FeatureValue.ObservedValue = instances.Select(ia => ia.FeatureValues.First().Value).ToArray();
this.NoiseVariance.ObservedValue = priors.NoiseVariance;
if (mode == InputMode.Training)
{
// No priors - this is training
this.RepliedTo.ObservedValue = instances.Select(ia => ia.Label).ToArray();
this.WeightPrior.ObservedValue = priors.Weights.First().Value;
this.ThresholdPrior.ObservedValue = priors.Threshold;
}
else
{
// This is testing, don't set isRepliedTo observed values
this.RepliedTo.ClearObservedValue();
this.WeightPrior.ObservedValue = priors.Weights.First().Value;
this.ThresholdPrior.ObservedValue = priors.Threshold;
}
}
private static void SetupRelationshipOriginal_Postfix(Agent otherAgent, Relationships __instance, ref Agent ___agent)
{
// Relationships defines how ___agent feels about otherAgent
// Don't delete this comment, it gets confusing-er-than-shit
if (GameController.gameController.levelType == nameof(InterfaceNameDB.rowIds.HomeBase))
{
__instance.SetRelInitial(otherAgent, nameof(relStatus.Aligned));
otherAgent.relationships.SetRelInitial(___agent, nameof(relStatus.Aligned));
return;
}
string currentRelationship = __instance.GetRel(otherAgent);
if (currentRelationship == null)
{
logger.LogWarning("SetupRelationshipOriginal - currentRelationship was null!");
return;
}
relStatus?newRelationship;
if (___agent.IsAgent(AgentNameDB.rowIds.ResistanceLeader) && otherAgent.isPlayer > 0)
{
newRelationship = relStatus.Aligned;
}
else
{
// Order matters here, the first non-Null relStatus will be used.
newRelationship =
MobDebt.SetupInitialRelationship(___agent, otherAgent, currentRelationship)
?? Domineering.SetupInitialRelationship(___agent, otherAgent, currentRelationship)
?? Domineering2.SetupInitialRelationship(___agent, otherAgent, currentRelationship)
?? Polarizing.SetupInitialRelationship(___agent, otherAgent, currentRelationship)
?? Polarizing2.SetupInitialRelationship(___agent, otherAgent, currentRelationship)
?? BootLicker.SetupInitialRelationship(___agent, otherAgent, currentRelationship)
?? Priors.SetupInitialRelationship(___agent, otherAgent, currentRelationship)
?? GenerallyUnpleasant.SetupInitialRelationship(___agent, otherAgent, currentRelationship)
?? ObjectivelyUnpleasant.SetupInitialRelationship(___agent, otherAgent, currentRelationship);
}
if (newRelationship != null)
{
string relationshipString = newRelationship.Value.ToString();
__instance.SetRelInitial(otherAgent, relationshipString);
otherAgent.relationships.SetRelInitial(___agent, relationshipString);
if (newRelationship.Value == relStatus.Annoyed)
{
otherAgent.relationships.SetStrikes(___agent, 2);
__instance.SetStrikes(otherAgent, 2);
}
else if (newRelationship.Value == relStatus.Hostile)
{
otherAgent.relationships.SetStrikes(___agent, 5);
__instance.SetStrikes(otherAgent, 5);
}
}
}
/// <summary>
/// Sets the observed values.
/// </summary>
/// <param name="instances">The instances.</param>
/// <param name="featureSet">The feature set.</param>
/// <param name="mode">The mode.</param>
/// <param name="priors">The priors.</param>
/// <exception cref="System.InvalidOperationException">Data is null</exception>
public override void SetObservedValues(IList <Inputs.Instance> instances, FeatureSet featureSet, InputMode mode, Priors priors)
{
if (instances == null)
{
throw new InvalidOperationException("Data is null");
}
this.NumberOfMessages.ObservedValue = instances.Count;
this.NumberOfFeatures.ObservedValue = featureSet.FeatureVectorLength;
this.NoiseVariance.ObservedValue = priors.NoiseVariance;
if (mode == InputMode.Training)
{
this.RepliedTo.ObservedValue = instances.Select(ia => ia.Label).ToArray();
this.WeightPriors.ObservedValue = DistributionArrayHelpers.DistributionArray(priors.Weights.Values);
this.ThresholdPrior.ObservedValue = priors.Threshold;
}
else
{
// This is testing, don't set isRepliedTo observed values
this.RepliedTo.ClearObservedValue();
this.WeightPriors.ObservedValue = DistributionArrayHelpers.Copy(priors.Weights.Values);
this.ThresholdPrior.ObservedValue = priors.Threshold;
}
// Convert feature values to dense jagged array
var featureValues = new double[instances.Count][];
for (int i = 0; i < instances.Count; i++)
{
featureValues[i] = new double[featureSet.FeatureVectorLength];
foreach (var featureBucketValue in instances[i].FeatureValues)
{
int index = instances[i].FeatureSet.FeatureBuckets.IndexOf(featureBucketValue.Key);
if (index < 0)
{
throw new InvalidOperationException("Bucket index not found");
}
featureValues[i][index] = featureBucketValue.Value;
}
}
this.FeatureValue.ObservedValue = featureValues;
}
/// <summary> /// Sets the observed values. /// </summary> /// <param name="instances">The instances.</param> /// <param name="featureSet">The feature buckets.</param> /// <param name="mode">The mode.</param> /// <param name="priors">The priors.</param> public abstract void SetObservedValues(IList <Inputs.Instance> instances, FeatureSet featureSet, InputMode mode, Priors priors);
/// <summary>
/// Sets the observed values.
/// </summary>
/// <param name="instances">The instances.</param>
/// <param name="featureSet">The feature buckets.</param>
/// <param name="mode">The mode.</param>
/// <param name="priors">The priors.</param>
/// <exception cref="System.InvalidOperationException">Data is null</exception>
/// <exception cref="System.ArgumentNullException">parameters;@Mode expected in parameters</exception>
/// <exception cref="System.ArgumentException"></exception>
public override void SetObservedValues(IList <Inputs.Instance> instances, FeatureSet featureSet, InputMode mode, Priors priors)
{
if (instances == null)
{
throw new InvalidOperationException("Data is null");
}
this.NumberOfMessages.ObservedValue = instances.Count;
this.NumberOfFeatures.ObservedValue = featureSet.FeatureVectorLength;
this.NoiseVariance.ObservedValue = priors.NoiseVariance;
if (mode == InputMode.Training)
{
this.RepliedTo.ObservedValue = instances.Select(ia => ia.Label).ToArray();
this.WeightPriors.ObservedValue = DistributionArrayHelpers.DistributionArray(priors.Weights.Values);
}
else
{
// This is testing, don't set isRepliedTo observed values
this.WeightPriors.ObservedValue = DistributionArrayHelpers.Copy(priors.Weights.Values);
}
var featureIndices = featureSet.FeatureBuckets.Select((ia, i) => new { ia, i }).ToDictionary(anon => anon.ia, anon => anon.i);
this.FeatureIndices.ObservedValue =
instances.Select(ia => ia.FeatureValues.Select(fbv => featureIndices[fbv.Key]).ToArray()).ToArray();
this.FeatureValue.ObservedValue = instances.Select(ia => ia.FeatureValues.Select(fbv => fbv.Value).ToArray()).ToArray();
this.FeatureCounts.ObservedValue = this.FeatureIndices.ObservedValue.Select(ia => ia.Length).ToArray();
}
