From 41eb276c1774e3b149bdcb29f37c89a13bd19562 Mon Sep 17 00:00:00 2001
From: JohnBeckner <jbeckner3@gatech.edu>
Date: Wed, 15 Apr 2020 22:19:57 -0400
Subject: [PATCH] Added comments to quantize.ts

---
 src/util/quantize.ts | 50 ++++++++++++++++++++++++++++++--------------
 1 file changed, 34 insertions(+), 16 deletions(-)

diff --git a/src/util/quantize.ts b/src/util/quantize.ts
index bdf8420..db8983b 100644
--- a/src/util/quantize.ts
+++ b/src/util/quantize.ts
@@ -106,8 +106,13 @@ export function quantize(
   return { sprite, palette };
 }
 
-// Used to find index of colors for building sprite colorArray
-// This kills the imageArr (imageArr is destroyed by this function)
+/**
+ * Used to find the index of colors for building Palette of
+ * quantized image
+ * NOTE: This function destroys imageArr
+ * @param imageArr The image to quantize as a 2D array
+ * @param colorArr List of unique colors in the image
+ */
 function getColorIndex(imageArr: number[][], colorArr: number[]): number {
   for (let i = 0; i < imageArr.length; i++) {
     if (
@@ -122,7 +127,10 @@ function getColorIndex(imageArr: number[][], colorArr: number[]): number {
   return -1;
 }
 
-//converts imageObject into array of colors for k-means
+/**
+ * converst image into array of RGB color values
+ * @param image The image to convert to 2d array
+ */
 function imageToArr(image: Bitmap): number[][] {
   let imageArr = [];
   for (let y = 0; y < image.dimensions.height; y++) {
@@ -138,10 +146,14 @@ function imageToArr(image: Bitmap): number[][] {
   return imageArr;
 }
 
-//used to find clusters of similar points for image depth reduction (quantization)
-//arrayToProcess: number array of colors; [[r, g, b], [r, g, b], ...]
-//centroids: center point of clusters;
-//clusters: number of clusters to generate
+/**
+ * Used to find clusters of similar colors for image color quantization
+ * @param arrayToProcess 2D array of RGB color values for the image to quantize
+ * @param centroids List of center points for each color cluster
+ *  2D array of RGB values
+ * @param clusters 3D array of clusters for color quantization
+ * Each centroid is associated with a cluster
+ */
 function kmeans(
   arrayToProcess: number[][],
   centroids: number[][],
@@ -232,15 +244,13 @@ function kmeans(
   return { groups: Groups, centers: centroids };
 }
 
-//function to determine if there exists a group of centroids with specific
-//average distance between them
-//points: list of points to search
-//midDist: desired average distance
-//numCentroids: number of points to find
-//
-//returns:
-//possible (boolean)
-//centers (list of points with desired distance)
+/**
+ * Used to determine if there exists a group of points with a at most 
+ * minDist distance between them
+ * @param points list of points to search
+ * @param midDist average distance to check for
+ * @param numCentroids number of points to find
+ */
 function centroidPossible(
   points: number[][],
   midDist: number,
@@ -277,6 +287,14 @@ function centroidPossible(
 
 //binary search to find centroids, reutrn list of centroids with
 // average largest distance between them
+
+/**
+ * Used to find optimal centroids for kmeans
+ * Uses binary search to find the group of centroids with min average distance
+ * between them
+ * @param uniqueColors 2D array of unique RGB color values
+ * @param depth number of centroids to find
+ */
 function findCentroids(
   uniqueColors: number[][],
   depth: number