From 58f1d7b6f2632e00451cf4becf2486cbc9650d03 Mon Sep 17 00:00:00 2001
From: Feynman Liang <fliang@databricks.com>
Date: Tue, 21 Jul 2015 11:16:31 -0700
Subject: [PATCH] Fix from review feedback

---
 .../org/apache/spark/mllib/clustering/LDAOptimizer.scala  | 8 ++++----
 .../org/apache/spark/mllib/clustering/LDASuite.scala      | 2 +-
 2 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAOptimizer.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAOptimizer.scala
index bc20f75133509..b2f3a2538d0b0 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAOptimizer.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAOptimizer.scala
@@ -95,7 +95,7 @@ final class EMLDAOptimizer extends LDAOptimizer {
    * Compute bipartite term/doc graph.
    */
   override private[clustering] def initialize(docs: RDD[(Long, Vector)], lda: LDA): LDAOptimizer = {
-    val docConcentration = breeze.stats.mean(lda.getDocConcentration.toBreeze)
+    val docConcentration = lda.getDocConcentration(0)
     require({
       lda.getDocConcentration.toArray.forall(_ == docConcentration)
     }, "EMLDAOptimizer currently only supports symmetric document-topic priors")
@@ -349,13 +349,13 @@ final class OnlineLDAOptimizer extends LDAOptimizer {
     this.alpha = if (lda.getDocConcentration.size == 1) {
       if (lda.getDocConcentration(0) == -1) Vectors.dense(Array.fill(k)(1.0 / k))
       else {
-        require(lda.getDocConcentration(0) >= 0, "all entries in alpha must be >=0")
+        require(lda.getDocConcentration(0) >= 0, s"all entries in alpha must be >=0, got: $alpha")
         Vectors.dense(Array.fill(k)(lda.getDocConcentration(0)))
       }
     } else {
-      require(lda.getDocConcentration.size == k, "alpha must have length k")
+      require(lda.getDocConcentration.size == k, s"alpha must have length k, got: $alpha")
       lda.getDocConcentration.foreachActive { case (_, x) =>
-        require(x >= 0, "all entries in alpha must be >= 0")
+        require(x >= 0, s"all entries in alpha must be >= 0, got: $alpha")
       }
       lda.getDocConcentration
     }
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/clustering/LDASuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/clustering/LDASuite.scala
index c6f6d2a73c4b0..da70d9bd7c790 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/clustering/LDASuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/clustering/LDASuite.scala
@@ -148,7 +148,7 @@ class LDASuite extends SparkFunSuite with MLlibTestSparkContext {
 
   test("initializing with elements in alpha < 0 fails") {
     intercept[IllegalArgumentException] {
-      val lda = new LDA().setK(2).setAlpha(Vectors.dense(-1, 2, 3, 4))
+      val lda = new LDA().setK(4).setAlpha(Vectors.dense(-1, 2, 3, 4))
       val corpus = sc.parallelize(tinyCorpus, 2)
       lda.run(corpus)
     }