implement Mairca

Author: jbytecode

src/main/scala/mairca.scala

@@ -0,0 +1,50 @@
+package org.expr.mcdm
+
+
+
+case class MaircaResult(
+    T: Mat,
+    A: Mat,
+    S: Mat,
+    scores: Vec,
+    orderings: VecInt,
+    bestIndex: Int,
+) extends MCDMResult
+
+def mairca(
+    decmat: Mat,
+    weights: Vec,
+    directions: Array[Direction],
+    normalization: NormalizationFunction =
+      Normalization.MaxMinRangeNormalization,
+    options: Map[String, Any] = Map.empty 
+): MaircaResult = 
+
+    val (row, col) = Matrix.size(decmat)
+
+    var T = Matrix.zeros(row, col)
+
+    for (i <- 0 until col) {
+        for (j <- 0 until row) {
+            T(j)(i) = weights(i) * (1.0 / row)
+        }
+    }
+
+    val A = Matrix.elementwiseMultiply(normalization(decmat, weights, directions), T)
+
+    val S = Matrix.subtract(T, A)
+
+    val scores = S.map(row => row.sum)
+
+    val orderings = scores.zipWithIndex.sortBy(-_._1).map(_._2)
+
+    val bestIndex = orderings.last
+
+    MaircaResult(
+        T = T,
+        A = A,
+        S = S,
+        scores = scores,
+        orderings = orderings,
+        bestIndex = bestIndex,
+    )

src/main/scala/matrix.scala

@@ -153,4 +153,9 @@ object Matrix:
 
   def solve(A: Mat, b: Vec): Vec = mul(inverse(A), b)
 
+  def elementwiseMultiply(a: Mat, b: Mat): Mat =
+    a.zip(b).map((rowa, rowb) => rowa.zip(rowb).map((x, y) => x * y))
+
+
+
 

src/test/scala/testmairca.scala

@@ -0,0 +1,27 @@
+import munit.Assertions as A
+
+import org.expr.mcdm.mairca
+import org.expr.mcdm.Direction.{Maximize, Minimize}
+import org.expr.mcdm.Matrix
+
+class TestMairca extends munit.FunSuite {
+  test("Mairca Example - 1") {
+
+    val decmat = Array(
+        Array(6.952, 8.000, 6.649, 7.268, 8.000, 7.652, 6.316),
+        Array(7.319, 7.319, 6.604, 7.319, 8.000, 7.652, 5.313),
+        Array(7.000, 7.319, 7.652, 6.952, 7.652, 6.952, 4.642),
+        Array(7.319, 6.952, 6.649, 7.319, 7.652, 6.649, 5.000))
+
+    val weights = Array(0.172, 0.165, 0.159, 0.129, 0.112, 0.122, 0.140)
+
+    val fns = Array(Maximize, Maximize, Maximize, Maximize, Maximize, Maximize, Minimize)
+
+    val expected_scores = Array(0.1206454, 0.0806646, 0.1458627, 0.1454237)
+
+    val result = mairca(decmat, weights, fns)
+
+    A.assert(Matrix.elementwise_equal(result.scores, expected_scores, 0.001))
+
+  }
+}

src/test/scala/testmatrix.scala

@@ -414,6 +414,25 @@ class TestMatrix extends munit.FunSuite {
 
     A.assert(Matrix.elementwise_equal(result, expected, 1e-5))
   }
+  test("Elementwise matrix multiplication"){
+    val Amat = Array(
+      Array(1.0, 2.0, 3.0),
+      Array(4.0, -5.0, 6.0),
+      Array(7.0, 8.0, 9.0)
+    )
+    val Bmat = Array(
+      Array(1.0, 2.0, 3.0),
+      Array(4.0, -5.0, 6.0),
+      Array(7.0, 8.0, 9.0)
+    )
+    val result = Matrix.elementwiseMultiply(Amat, Bmat)
+    val expected = Array(
+      Array(1.0, 4.0, 9.0),
+      Array(16.0, 25.0, 36.0),
+      Array(49.0, 64.0, 81.0)
+    )
+    A.assert(Matrix.elementwise_equal(result, expected, 1e-03))
+  }
   test("Equation solve 1"){
     val Amat = Array(Array(2.0, 4.0), Array(6.0, 5.0))
     val bvec = Array(12.0, 60.0)