From 4287637e81637dbc220351ad1726ed3d3c7125b3 Mon Sep 17 00:00:00 2001
From: "mhsatman@gmail.com" <mhsatman@gmail.com>
Date: Mon, 11 Dec 2023 20:11:53 +0300
Subject: [PATCH] more verbose aras edas waspas output with inner calculations

---
 CHANGELOG.md  |  7 ++++++-
 Project.toml  |  2 +-
 src/aras.jl   |  5 +++++
 src/edas.jl   | 26 +++++++++++++++++++++++++-
 src/waspas.jl | 12 +++++++++++-
 5 files changed, 48 insertions(+), 4 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index b2adb24..b6e0637 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,6 +1,11 @@
-### 0.7.11 (Upcoming release)
+### 0.7.12 (Upcoming release)
 
 
+
+### 0.7.11
+
+- ARAS, EDAS, and WASPAS results are now holding more inner-calculation results.
+
 ### 0.7.10 
 
 - Add LMAW (Logarithm Methodology of Additive Weights) as a new MCDM tool.
diff --git a/Project.toml b/Project.toml
index aecbce9..f3c25ab 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,7 +1,7 @@
 name = "JMcDM"
 uuid = "358108f5-d052-4d0a-8344-d5384e00c0e5"
 authors = ["Mehmet Hakan Satman (jbytecode) <mhsatman@gmail.com>", "Bahadir Fatih Yildirim <bahadirfyildirim@gmail.com>", "Ersagun Kuruca"]
-version = "0.7.10"
+version = "0.7.11"
 
 [deps]
 Requires = "ae029012-a4dd-5104-9daa-d747884805df"
diff --git a/src/aras.jl b/src/aras.jl
index e4e6ea5..9342b84 100755
--- a/src/aras.jl
+++ b/src/aras.jl
@@ -4,6 +4,8 @@ module ARAS
 import ..MCDMMethod, ..MCDMResult, ..MCDMSetting
 import ..Normalizations
 
+import ..Utilities: weightise
+
 using ..Utilities
 
 
@@ -18,6 +20,7 @@ struct ARASResult <: MCDMResult
     referenceRow::Vector
     extendMat::Matrix
     normalizedMat::Matrix
+    weightedNormalizedMat::Matrix
     optimalitydegrees::Vector
     scores::Vector
     orderings::Array{Int64,1}
@@ -100,6 +103,7 @@ function aras(
     end
 
     normalizedMat = normalization(extendMat, fs)
+    weightednormalizedmatrix = weightise(normalizedMat, w)
     
 
     optimality_degrees = Vector(undef, nrows + 1)
@@ -119,6 +123,7 @@ function aras(
         referenceRow,
         extendMat,
         normalizedMat,
+        weightednormalizedmatrix,
         optimality_degrees,
         utility_degrees,
         orderings,
diff --git a/src/edas.jl b/src/edas.jl
index e552df2..eb0c51a 100644
--- a/src/edas.jl
+++ b/src/edas.jl
@@ -3,6 +3,9 @@ module EDAS
 export edas, EdasMethod, EDASResult
 
 import ..MCDMMethod, ..MCDMResult, ..MCDMSetting
+
+import ..Utilities: weightise
+
 using ..Utilities
 
 
@@ -12,6 +15,12 @@ struct EdasMethod <: MCDMMethod end
 struct EDASResult <: MCDMResult
     decisionMatrix::Matrix
     weights::Array{Float64,1}
+    NDAMatrix::Matrix 
+    PDAMatrix::Matrix
+    weightedNDAMatrix::Matrix
+    weightedPDAMatrix::Matrix
+    SN::Vector 
+    SP::Vector
     scores::Vector
     ranking::Array{Int64,1}
     bestIndex::Int64
@@ -116,6 +125,10 @@ function edas(
         end
     end
 
+    weightedPDAMatrix = weightise(PDAMatrix, w)
+    weightedNDAMatrix = weightise(NDAMatrix, w)
+
+
     SP = zeros(eltype(df), row)
     SN = zeros(eltype(df), row)
 
@@ -133,7 +146,18 @@ function edas(
 
     bestIndex = rankings |> last
 
-    result = EDASResult(decisionMat, w, scores, rankings, bestIndex)
+    result = EDASResult(
+        decisionMat, 
+        w,
+        NDAMatrix,
+        PDAMatrix,
+        weightedNDAMatrix,
+        weightedPDAMatrix,
+        SN,
+        SP, 
+        scores, 
+        rankings, 
+        bestIndex)
 
     return result
 end
diff --git a/src/waspas.jl b/src/waspas.jl
index 0e224c0..e124350 100644
--- a/src/waspas.jl
+++ b/src/waspas.jl
@@ -12,6 +12,8 @@ struct WASPASResult <: MCDMResult
     decisionMatrix::Matrix
     normalizedDecisionMatrix::Matrix
     weights::Array{Float64,1}
+    scoresWPM::Vector
+    scoresWSM::Vector
     scores::Vector
     ranking::Array{Int64,1}
     bestIndex::Int64
@@ -132,7 +134,15 @@ function waspas(
     bestIndex = rankings |> last
 
     result =
-        WASPASResult(decisionMat, normalizedDecisionMat, w, scores, rankings, bestIndex)
+        WASPASResult(
+            decisionMat, 
+            normalizedDecisionMat,
+            w, 
+            scoresWPM, 
+            scoresWSM,
+            scores, 
+            rankings, 
+            bestIndex)
 
     return result
 end