/// <summary>
/// Returns similarity score for two N-dimensional double vectors.
/// </summary>
///
/// <param name="p">1st point vector.</param>
/// <param name="q">2nd point vector.</param>
///
/// <returns>Returns Euclidean similarity between two supplied vectors.</returns>
///
/// <exception cref="ArgumentException">Thrown if the two vectors are of different dimensions (if specified
/// array have different length).</exception>
///
public double GetSimilarityScore( double[] p, double[] q )
{
double distance = 0;
EuclideanDistance dist = new EuclideanDistance( );
distance = 1.0 / ( 1.0 + dist.GetDistance( p, q ) );
return distance;
}
/// <summary>
/// Returns similarity score for two N-dimensional double vectors.
/// </summary>
///
/// <param name="p">1st point vector.</param>
/// <param name="q">2nd point vector.</param>
///
/// <returns>Returns Euclidean similarity between two supplied vectors.</returns>
///
/// <exception cref="ArgumentException">Thrown if the two vectors are of different dimensions (if specified
/// array have different length).</exception>
///
public double GetSimilarityScore(double[] p, double[] q)
{
double distance = 0;
EuclideanDistance dist = new EuclideanDistance( );
distance = 1.0 / (1.0 + dist.GetDistance(p, q));
return(distance);
}
public void EuclideanDistanceTest( )
{
EuclideanDistance dist = new EuclideanDistance( );
Assert.Throws<ArgumentException>( ( ) => dist.GetDistance( p0, q4 ) );
double result = dist.GetDistance( p0, q0 );
Assert.AreApproximatelyEqual( result, .70711, 0.00001 );
result = dist.GetDistance( p1, q1 );
Assert.AreApproximatelyEqual( result, 1.11803, 0.00001 );
result = dist.GetDistance( p2, q2 );
Assert.AreEqual( result, 0 );
result = dist.GetDistance( p3, q3 );
Assert.AreEqual( result, 0 );
result = dist.GetDistance( p4, q4 );
Assert.AreApproximatelyEqual( result, 2.39792, 0.00001 );
result = dist.GetDistance( p5, q5 );
Assert.AreApproximatelyEqual( result, 4.24264, 0.00001 );
}
