From b2851066c88f5436e18877ee2eb337b522c08512 Mon Sep 17 00:00:00 2001
From: Tor Myklebust <tmyklebu@gmail.com>
Date: Mon, 21 Apr 2014 13:47:09 -0400
Subject: [PATCH] Clean up NNLS test cases.

---
 .../spark/mllib/optimization/NNLSSuite.scala  | 53 ++++++++++++-------
 1 file changed, 34 insertions(+), 19 deletions(-)

diff --git a/mllib/src/test/scala/org/apache/spark/mllib/optimization/NNLSSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/optimization/NNLSSuite.scala
index f6f054741721a..7f6e828a10b51 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/optimization/NNLSSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/optimization/NNLSSuite.scala
@@ -20,40 +20,55 @@ package org.apache.spark.mllib.optimization
 import scala.util.Random
 
 import org.scalatest.FunSuite
-import org.scalatest.matchers.ShouldMatchers
 
-import org.apache.spark.mllib.util.LocalSparkContext
+import org.jblas.{DoubleMatrix, SimpleBlas, NativeBlas}
 
-import org.jblas.DoubleMatrix
-import org.jblas.SimpleBlas
-
-class NNLSSuite extends FunSuite with LocalSparkContext with ShouldMatchers {
+class NNLSSuite extends FunSuite {
   test("NNLSbyPCG: exact solution case") {
-    val A = new DoubleMatrix(20, 20)
-    val b = new DoubleMatrix(20, 1)
+    val n = 20
+    val A = new DoubleMatrix(n, n)
+    val b = new DoubleMatrix(n, 1)
     val rand = new Random(12345)
-    for (i <- 0 until 20; j <- 0 until 20) {
+    for (i <- 0 until n; j <- 0 until n) {
       val aij = rand.nextDouble()
       A.put(i, j, aij)
       b.put(i, b.get(i, 0) + aij)
     }
 
-    val ata = new DoubleMatrix(20, 20)
-    val atb = new DoubleMatrix(20, 1)
-    for (i <- 0 until 20; j <- 0 until 20; k <- 0 until 20) {
-      ata.put(i, j, ata.get(i, j) + A.get(k, i) * A.get(k, j))
-    }
-    for (i <- 0 until 20; j <- 0 until 20) {
-      atb.put(i, atb.get(i, 0) + A.get(j, i) * b.get(j))
-    }
+    val ata = new DoubleMatrix(n, n)
+    val atb = new DoubleMatrix(n, 1)
+
+    NativeBlas.dgemm('T', 'N', n, n, n, 1.0, A.data, 0, n, A.data, 0, n, 0.0, ata.data, 0, n)
+    NativeBlas.dgemv('T', n, n, 1.0, A.data, 0, n, b.data, 0, 1, 0.0, atb.data, 0, 1)
 
     val x = NNLSbyPCG.solve(ata, atb, true)
-    assert(x.length == 20)
+    assert(x.length == n)
     var error = 0.0
-    for (i <- 0 until 20) {
+    for (i <- 0 until n) {
       error = error + (x(i) - 1) * (x(i) - 1)
       assert(Math.abs(x(i) - 1) < 1e-3)
     }
     assert(error < 1e-2)
   }
+
+  test("NNLSbyPCG: nonnegativity constraint active") {
+    val n = 5
+    val M = Array(
+      Array( 4.377, -3.531, -1.306, -0.139,  3.418, -1.632),
+      Array(-3.531,  4.344,  0.934,  0.305, -2.140,  2.115),
+      Array(-1.306,  0.934,  2.644, -0.203, -0.170,  1.094),
+      Array(-0.139,  0.305, -0.203,  5.883,  1.428, -1.025),
+      Array( 3.418, -2.140, -0.170,  1.428,  4.684, -0.636))
+    val ata = new DoubleMatrix(5, 5)
+    val atb = new DoubleMatrix(5, 1)
+    for (i <- 0 until 5; j <- 0 until 5) ata.put(i, j, M(i)(j))
+    for (i <- 0 until 5) atb.put(i, M(i)(5))
+
+    val goodx = Array(0.13025, 0.54506, 0.2874, 0.0, 0.028628)
+
+    val x = NNLSbyPCG.solve(ata, atb, true)
+    for (i <- 0 until 5) {
+      assert(Math.abs(x(i) - goodx(i)) < 1e-3)
+    }
+  }
 }