From 39b09f144a3f197b86ad0ab38a06ba3fea04e116 Mon Sep 17 00:00:00 2001
From: neingeist <neingeist@bl0rg.net>
Date: Mon, 17 Nov 2014 23:02:10 +0100
Subject: [PATCH] Compute centroid means (unvectorized)

---
 ex7/computeCentroids.m | 27 ++++++++++++++++++---------
 1 file changed, 18 insertions(+), 9 deletions(-)

diff --git a/ex7/computeCentroids.m b/ex7/computeCentroids.m
index 606011e..2bd6095 100644
--- a/ex7/computeCentroids.m
+++ b/ex7/computeCentroids.m
@@ -1,7 +1,7 @@
 function centroids = computeCentroids(X, idx, K)
-%COMPUTECENTROIDS returs the new centroids by computing the means of the 
+%COMPUTECENTROIDS returs the new centroids by computing the means of the
 %data points assigned to each centroid.
-%   centroids = COMPUTECENTROIDS(X, idx, K) returns the new centroids by 
+%   centroids = COMPUTECENTROIDS(X, idx, K) returns the new centroids by
 %   computing the means of the data points assigned to each centroid. It is
 %   given a dataset X where each row is a single data point, a vector
 %   idx of centroid assignments (i.e. each entry in range [1..K]) for each
@@ -19,18 +19,27 @@ centroids = zeros(K, n);
 
 % ====================== YOUR CODE HERE ======================
 % Instructions: Go over every centroid and compute mean of all points that
-%               belong to it. Concretely, the row vector centroids(i, :)
+%               belong to it. Concretely, the row vector centroids(k, :)
 %               should contain the mean of the data points assigned to
-%               centroid i.
+%               centroid k.
 %
 % Note: You can use a for-loop over the centroids to compute this.
 %
 
-
-
-
-
-
+for k = 1:K
+  count = 0;
+
+  % XXX vectorize
+  for i = 1:m
+    if idx(i) == k
+      centroids(k, :) += X(i, :);
+      count += 1;
+    end
+  end
+  if count > 0
+    centroids(k, :) /= count;
+  end
+end
 
 
 % =============================================================