From 89ecb3f79b83b58732a23b739b8c127eb915854a Mon Sep 17 00:00:00 2001
From: drake7707 <mijnbureauklok@gmail.com>
Date: Wed, 11 Sep 2019 17:17:35 +0200
Subject: [PATCH] bug fix for the broken LAB / HSL mode in clustering

---
 scripts/main.js                 | 6 +++++-
 src/colorreductionmanagement.ts | 8 +++++++-
 src/lib/clustering.ts           | 2 ++
 3 files changed, 14 insertions(+), 2 deletions(-)

diff --git a/scripts/main.js b/scripts/main.js
index f1146bc..7d643af 100644
--- a/scripts/main.js
+++ b/scripts/main.js
@@ -442,6 +442,7 @@ define("colorreductionmanagement", ["require", "exports", "common", "lib/cluster
                     // determine the weight (#pointsOfColor / #totalpoints) of each color
                     const weight = pointsByColor[color].length / (imgData.width * imgData.height);
                     const vec = new clustering_1.Vector(data, weight);
+                    vec.tag = rgb;
                     vectors[vIdx++] = vec;
                 }
                 const random = new random_1.Random(settings.randomSeed);
@@ -493,6 +494,8 @@ define("colorreductionmanagement", ["require", "exports", "common", "lib/cluster
                     else {
                         rgb = centroid.values;
                     }
+                    // remove decimals
+                    rgb = rgb.map(v => Math.floor(v));
                     if (restrictToSpecifiedColors) {
                         if (settings.kMeansColorRestrictions.length > 0) {
                             // there are color restrictions, for each centroid find the color from the color restrictions that's the closest
@@ -527,8 +530,9 @@ define("colorreductionmanagement", ["require", "exports", "common", "lib/cluster
                             }
                         }
                     }
+                    let pointRGB = v.tag;
                     // replace all pixels of the old color by the new centroid color
-                    const pointColor = `${v.values[0]},${v.values[1]},${v.values[2]}`;
+                    const pointColor = `${Math.floor(pointRGB[0])},${Math.floor(pointRGB[1])},${Math.floor(pointRGB[2])}`;
                     for (const pt of pointsByColor[pointColor]) {
                         const ptx = pt % imgData.width;
                         const pty = Math.floor(pt / imgData.width);
diff --git a/src/colorreductionmanagement.ts b/src/colorreductionmanagement.ts
index a4e1c98..9948bca 100644
--- a/src/colorreductionmanagement.ts
+++ b/src/colorreductionmanagement.ts
@@ -110,6 +110,7 @@ export class ColorReducer {
             const weight = pointsByColor[color].length / (imgData.width * imgData.height);
 
             const vec = new Vector(data, weight);
+            vec.tag = rgb;
             vectors[vIdx++] = vec;
         }
 
@@ -170,6 +171,9 @@ export class ColorReducer {
                     rgb = centroid.values;
                 }
 
+                 // remove decimals
+                 rgb = rgb.map(v => Math.floor(v));
+
                 if (restrictToSpecifiedColors) {
                     if (settings.kMeansColorRestrictions.length > 0) {
                         // there are color restrictions, for each centroid find the color from the color restrictions that's the closest
@@ -205,8 +209,10 @@ export class ColorReducer {
                     }
                 }
 
+                let pointRGB: number[] = v.tag;
+
                 // replace all pixels of the old color by the new centroid color
-                const pointColor = `${v.values[0]},${v.values[1]},${v.values[2]}`;
+                const pointColor = `${Math.floor(pointRGB[0])},${Math.floor(pointRGB[1])},${Math.floor(pointRGB[2])}`;
                 for (const pt of pointsByColor[pointColor]) {
                     const ptx = pt % imgData.width;
                     const pty = Math.floor(pt / imgData.width);
diff --git a/src/lib/clustering.ts b/src/lib/clustering.ts
index 0fc783b..cfda933 100644
--- a/src/lib/clustering.ts
+++ b/src/lib/clustering.ts
@@ -2,6 +2,8 @@ import { Random } from "../random";
 
 export class Vector {
 
+    public tag:any;
+    
     constructor(public values: number[], public weight: number = 1) { }
 
     public distanceTo(p: Vector): number {