public static double ApproximatelyEquals(this string firstWord, string secondWord, SimMetricType simMetricType = SimMetricType.Levenstein)
{
switch (simMetricType)
{
case SimMetricType.BlockDistance:
var sim2 = new BlockDistance();
return(sim2.GetSimilarity(firstWord, secondWord));
case SimMetricType.ChapmanLengthDeviation:
var sim3 = new ChapmanLengthDeviation();
return(sim3.GetSimilarity(firstWord, secondWord));
case SimMetricType.CosineSimilarity:
var sim4 = new CosineSimilarity();
return(sim4.GetSimilarity(firstWord, secondWord));
case SimMetricType.DiceSimilarity:
var sim5 = new DiceSimilarity();
return(sim5.GetSimilarity(firstWord, secondWord));
case SimMetricType.EuclideanDistance:
var sim6 = new EuclideanDistance();
return(sim6.GetSimilarity(firstWord, secondWord));
case SimMetricType.JaccardSimilarity:
var sim7 = new JaccardSimilarity();
return(sim7.GetSimilarity(firstWord, secondWord));
case SimMetricType.Jaro:
var sim8 = new Jaro();
return(sim8.GetSimilarity(firstWord, secondWord));
case SimMetricType.JaroWinkler:
var sim9 = new JaroWinkler();
return(sim9.GetSimilarity(firstWord, secondWord));
case SimMetricType.MatchingCoefficient:
var sim10 = new MatchingCoefficient();
return(sim10.GetSimilarity(firstWord, secondWord));
case SimMetricType.MongeElkan:
var sim11 = new MongeElkan();
return(sim11.GetSimilarity(firstWord, secondWord));
case SimMetricType.NeedlemanWunch:
var sim12 = new NeedlemanWunch();
return(sim12.GetSimilarity(firstWord, secondWord));
case SimMetricType.OverlapCoefficient:
var sim13 = new OverlapCoefficient();
return(sim13.GetSimilarity(firstWord, secondWord));
case SimMetricType.QGramsDistance:
var sim14 = new QGramsDistance();
return(sim14.GetSimilarity(firstWord, secondWord));
case SimMetricType.SmithWaterman:
var sim15 = new SmithWaterman();
return(sim15.GetSimilarity(firstWord, secondWord));
case SimMetricType.SmithWatermanGotoh:
var sim16 = new SmithWatermanGotoh();
return(sim16.GetSimilarity(firstWord, secondWord));
case SimMetricType.SmithWatermanGotohWindowedAffine:
var sim17 = new SmithWatermanGotohWindowedAffine();
return(sim17.GetSimilarity(firstWord, secondWord));
case SimMetricType.ChapmanMeanLength:
var sim18 = new ChapmanMeanLength();
return(sim18.GetSimilarity(firstWord, secondWord));
default:
var sim1 = new Levenstein();
return(sim1.GetSimilarity(firstWord, secondWord));
}
}
public static int GetMinTravelAptBlock(List <Block> blocks, List <string> requirements)
{
blockDistances = new List <BlockDistance>();
//forward pass
for (int i = 0; i < blocks.Count; i++)
{
var blockDistance = new BlockDistance()
{
BlockId = i, Gym = int.MaxValue, School = int.MaxValue, Office = int.MaxValue, Store = int.MaxValue, MaxTravel = int.MaxValue
};
if (blocks[i].Gym)
{
blockDistance.Gym = 0;
}
else if (i > 0 && blockDistances[i - 1].Gym != int.MaxValue)
{
blockDistance.Gym = Math.Min(blockDistances[i - 1].Gym + 1, blockDistance.Gym);
}
if (blocks[i].School)
{
blockDistance.School = 0;
}
else if (i > 0 && blockDistances[i - 1].School != int.MaxValue)
{
blockDistance.School = Math.Min(blockDistances[i - 1].School + 1, blockDistance.School);
}
if (blocks[i].Office)
{
blockDistance.Office = 0;
}
else if (i > 0 && blockDistances[i - 1].Office != int.MaxValue)
{
blockDistance.Office = Math.Min(blockDistances[i - 1].Office + 1, blockDistance.Office);
}
if (blocks[i].Store)
{
blockDistance.Store = 0;
}
else if (i > 0 && blockDistances[i - 1].Store != int.MaxValue)
{
blockDistance.Store = Math.Min(blockDistances[i - 1].Store + 1, blockDistance.Store);
}
blockDistance.MaxTravel = MaxOfValues(new int[] { blockDistance.Gym, blockDistance.School, blockDistance.Office, blockDistance.Store });
blockDistances.Add(blockDistance);
}
//backward pass
for (int i = blocks.Count - 1; i >= 0; i--)
{
var blockDistance = blockDistances[i];
if (blocks[i].Gym)
{
blockDistance.Gym = 0;
}
else if (i < blocks.Count - 1 && blockDistances[i + 1].Gym != int.MaxValue)
{
blockDistance.Gym = Math.Min(blockDistances[i + 1].Gym + 1, blockDistance.Gym);
}
if (blocks[i].School)
{
blockDistance.School = 0;
}
else if (i < blocks.Count - 1 && blockDistances[i + 1].School != int.MaxValue)
{
blockDistance.School = Math.Min(blockDistances[i + 1].School + 1, blockDistance.School);
}
if (blocks[i].Office)
{
blockDistance.Office = 0;
}
else if (i < blocks.Count - 1 && blockDistances[i + 1].Office != int.MaxValue)
{
blockDistance.Office = Math.Min(blockDistances[i + 1].Office + 1, blockDistance.Office);
}
if (blocks[i].Store)
{
blockDistance.Store = 0;
}
else if (i < blocks.Count - 1 && blockDistances[i + 1].Store != int.MaxValue)
{
blockDistance.Store = Math.Min(blockDistances[i + 1].Store + 1, blockDistance.Store);
}
blockDistance.MaxTravel = MaxOfValues(new int[] { blockDistance.Gym, blockDistance.School, blockDistance.Office, blockDistance.Store });
}
Array.Sort(blockDistances.Select(b => b.MaxTravel).ToArray());
return(blockDistances[0].BlockId);
}
public double GetSimilarity(string str1, string str2, string type)
{
IStringMetric stringMetric;
switch (type)
{
case AlgorithmTypes.BlockDistance:
stringMetric = new BlockDistance();
break;
case AlgorithmTypes.ChapmanLengthDeviation:
stringMetric = new ChapmanLengthDeviation();
break;
case AlgorithmTypes.ChapmanMeanLength:
stringMetric = new ChapmanMeanLength();
break;
case AlgorithmTypes.CosineSimilarity:
stringMetric = new CosineSimilarity();
break;
case AlgorithmTypes.DiceSimilarity:
stringMetric = new DiceSimilarity();
break;
case AlgorithmTypes.EuclideanDistance:
stringMetric = new EuclideanDistance();
break;
case AlgorithmTypes.JaccardSimilarity:
stringMetric = new JaccardSimilarity();
break;
case AlgorithmTypes.Jaro:
stringMetric = new Jaro();
break;
case AlgorithmTypes.JaroWinkler:
stringMetric = new JaroWinkler();
break;
case AlgorithmTypes.Levenstein:
stringMetric = new Levenstein();
break;
case AlgorithmTypes.MatchingCoefficient:
stringMetric = new MatchingCoefficient();
break;
case AlgorithmTypes.MongeElkan:
stringMetric = new MongeElkan();
break;
case AlgorithmTypes.NeedlemanWunch:
stringMetric = new NeedlemanWunch();
break;
case AlgorithmTypes.OverlapCoefficient:
stringMetric = new OverlapCoefficient();
break;
case AlgorithmTypes.QGramsDistance:
stringMetric = new QGramsDistance();
break;
case AlgorithmTypes.SmithWaterman:
stringMetric = new SmithWaterman();
break;
case AlgorithmTypes.SmithWatermanGotoh:
stringMetric = new SmithWatermanGotoh();
break;
case AlgorithmTypes.SmithWatermanGotohWindowedAffine:
stringMetric = new SmithWatermanGotohWindowedAffine();
break;
default:
stringMetric = new SmithWatermanGotoh();
break;
}
var similarity = stringMetric.GetSimilarity(str1.Trim(), str2.Trim());
return(similarity);
}
// [SetUp]
public BlockDistanceUnitTests()
{
LoadData();
myBlockDistance = new BlockDistance();
}
