/// <summary>
/// Creates an instantiated factor in this graph, with neighborIndices representing the neighbor variables by integer
/// index.
/// </summary>
/// <param name="featureTable">the feature table to use to drive the value of the factor</param>
/// <param name="neighborIndices">the indices of the neighboring variables, in order</param>
/// <returns>a reference to the created factor. This can be safely ignored, as the factor is already saved in the model</returns>
public virtual GraphicalModel.Factor AddFactor(ConcatVectorTable featureTable, int[] neighborIndices)
{
System.Diagnostics.Debug.Assert((featureTable.GetDimensions().Length == neighborIndices.Length));
GraphicalModel.Factor factor = new GraphicalModel.Factor(featureTable, neighborIndices);
factors.Add(factor);
return(factor);
}
/// <summary>Duplicates this factor.</summary>
/// <returns>a copy of the factor</returns>
public virtual GraphicalModel.Factor CloneFactor()
{
GraphicalModel.Factor clone = new GraphicalModel.Factor();
clone.neigborIndices = neigborIndices.MemberwiseClone();
clone.featuresTable = featuresTable.CloneTable();
clone.metaData.PutAll(metaData);
return(clone);
}
public static GraphicalModel.Factor ReadFromProto(GraphicalModelProto.Factor proto)
{
GraphicalModel.Factor factor = new GraphicalModel.Factor();
factor.featuresTable = ConcatVectorTable.ReadFromProto(proto.GetFeaturesTable());
factor.metaData = GraphicalModel.ReadMetaDataFromProto(proto.GetMetaData());
factor.neigborIndices = new int[proto.GetNeighborCount()];
for (int i = 0; i < factor.neigborIndices.Length; i++)
{
factor.neigborIndices[i] = proto.GetNeighbor(i);
}
return(factor);
}
/// <summary>
/// Check that two models are deeply value-equivalent, down to the concat vectors inside the factor tables, within
/// some tolerance.
/// </summary>
/// <remarks>
/// Check that two models are deeply value-equivalent, down to the concat vectors inside the factor tables, within
/// some tolerance. Mostly useful for testing.
/// </remarks>
/// <param name="other">the graphical model to compare against.</param>
/// <param name="tolerance">the tolerance to accept when comparing concat vectors for value equality.</param>
/// <returns>whether the two models are tolerance equivalent</returns>
public virtual bool ValueEquals(GraphicalModel other, double tolerance)
{
if (!modelMetaData.Equals(other.modelMetaData))
{
return(false);
}
if (!variableMetaData.Equals(other.variableMetaData))
{
return(false);
}
// compare factor sets for equality
ICollection <GraphicalModel.Factor> remaining = new HashSet <GraphicalModel.Factor>();
Sharpen.Collections.AddAll(remaining, factors);
foreach (GraphicalModel.Factor otherFactor in other.factors)
{
GraphicalModel.Factor match = null;
foreach (GraphicalModel.Factor factor in remaining)
{
if (factor.ValueEquals(otherFactor, tolerance))
{
match = factor;
break;
}
}
if (match == null)
{
return(false);
}
else
{
remaining.Remove(match);
}
}
return(remaining.Count <= 0);
}
/// <summary>Does a deep comparison, using equality with tolerance checks against the vector table of values.</summary>
/// <param name="other">the factor to compare to</param>
/// <param name="tolerance">the tolerance to accept in differences</param>
/// <returns>whether the two factors are within tolerance of one another</returns>
public virtual bool ValueEquals(GraphicalModel.Factor other, double tolerance)
{
return(Arrays.Equals(neigborIndices, other.neigborIndices) && metaData.Equals(other.metaData) && featuresTable.ValueEquals(other.featuresTable, tolerance));
}
