/// <summary>
/// Produces an N x 2 array of strings showing the best match-up of two lists of strings.
/// Used to match schematic pins with SPICE pins, for example.
/// </summary>
/// <param name="firstPinNames">The first list of strings, typically schematic pin names.</param>
/// <param name="secondPinNames">The second list of strings, typically SPICE pin names.</param>
/// <returns>N x 2 array of strings, showing the best match-up between two lists of strings.
/// The first column of the array has strings from the first list in a sorted order.
/// The second column of the array has a permutation of strings from the second list, so that
/// strings on the same row will tend to be close matches.
/// If one list is longer than the other, the shorter one will be extended with "" strings.</returns>
/// <remarks>This method uses a modified Levenshtein algorithm to tell how close two strings
/// are to matching, and the Hungarian algorithm to optimize the overall matchup.</remarks>
/// <seealso cref="http://en.wikipedia.org/wiki/Levenshtein_distance"/>
/// <seealso cref="http://en.wikipedia.org/wiki/Hungarian_algorithm"/>
static public string[,] GetPinMatches(List <string> firstPinNames, List <string> secondPinNames)
{
int len1 = firstPinNames.Count;
int len2 = secondPinNames.Count;
int pinListSize = Math.Max(len1, len2);
// Copy the pin lists so the new lists can be extended, if needed, to the same size with empty strings.
List <string> newS1 = new List <string>(firstPinNames);
newS1.Sort();
while (newS1.Count < pinListSize)
{
newS1.Add("");
}
List <string> newS2 = new List <string>(secondPinNames);
newS2.Sort();
while (newS2.Count < pinListSize)
{
newS2.Add("");
}
// Now, both new lists of pins have the same length.
// Compute a square cost matrix for the pins based on their distances.
int[,] costMatrix = new int[pinListSize, pinListSize];
for (int rows = 0; rows < pinListSize; rows++)
{
for (int cols = 0; cols < pinListSize; cols++)
{
costMatrix[rows, cols] = Costs.CostBetweenTwoPins(newS1[rows], newS2[cols]);
}
}
// Find the least cost assignment of pins to pins
int[] pinMap = HungarianAlgorithm.FindAssignments(costMatrix);
Debug.Assert(pinMap.Count() == pinListSize);
// Create the output list of matched pin strings
string[,] rVal = new string[pinListSize, 2];
for (int i = 0; i < pinListSize; i++)
{
rVal[i, index1] = newS1[i];
rVal[i, index2] = newS2[pinMap[i]];
}
return(rVal);
}
public void test04HungarianAlgorithmCheck()
{
/* Example from Layman's Explanation, http://en.wikipedia.org/wiki/Hungarian_algorithm
*
* Clean bathroom Sweep floors Wash windows
* Jim $1 $3 $3
* Steve $3 $2 $3
* Alan $3 $3 $2
*/
int[,] costs =
{
{ 1, 3, 3 },
{ 3, 2, 3 },
{ 3, 3, 2 }
};
int[] expected = { 0, 1, 2 }; // Jim cleans the bathroom, Steve sweeps the floors and Alan washes the windows.
int[] results = HungarianAlgorithm.FindAssignments(costs);
Assert.Equal(expected, results);
}