Centralizing linear data generator and mllib regression tests to use it.

3 files changed, 16 insertions, 13 deletions

diff --git a/mllib/src/test/java/spark/mllib/regression/JavaLassoSuite.java b/mllib/src/test/java/spark/mllib/regression/JavaLassoSuite.java
index e26d7b385c..8d692c2d0d 100644
--- a/mllib/src/test/java/spark/mllib/regression/JavaLassoSuite.java
+++ b/mllib/src/test/java/spark/mllib/regression/JavaLassoSuite.java
@@ -27,6 +27,7 @@ import org.junit.Test;
 
 import spark.api.java.JavaRDD;
 import spark.api.java.JavaSparkContext;
+import spark.mllib.util.LinearDataGenerator;
 
 public class JavaLassoSuite implements Serializable {
   private transient JavaSparkContext sc;
@@ -61,10 +62,10 @@ public class JavaLassoSuite implements Serializable {
     double A = 2.0;
     double[] weights = {-1.5, 1.0e-2};
 
-    JavaRDD<LabeledPoint> testRDD = sc.parallelize(LassoSuite.generateLassoInputAsList(A,
-        weights, nPoints, 42), 2).cache();
+    JavaRDD<LabeledPoint> testRDD = sc.parallelize(LinearDataGenerator.generateLinearInputAsList(A,
+            weights, nPoints, 42), 2).cache();
     List<LabeledPoint> validationData =
-        LassoSuite.generateLassoInputAsList(A, weights, nPoints, 17);
+        LinearDataGenerator.generateLinearInputAsList(A, weights, nPoints, 17);
 
     LassoWithSGD svmSGDImpl = new LassoWithSGD();
     svmSGDImpl.optimizer().setStepSize(1.0)
@@ -82,10 +83,10 @@ public class JavaLassoSuite implements Serializable {
     double A = 2.0;
     double[] weights = {-1.5, 1.0e-2};
 
-    JavaRDD<LabeledPoint> testRDD = sc.parallelize(LassoSuite.generateLassoInputAsList(A,
+    JavaRDD<LabeledPoint> testRDD = sc.parallelize(LinearDataGenerator.generateLinearInputAsList(A,
         weights, nPoints, 42), 2).cache();
     List<LabeledPoint> validationData =
-        LassoSuite.generateLassoInputAsList(A, weights, nPoints, 17);
+        LinearDataGenerator.generateLinearInputAsList(A, weights, nPoints, 17);
 
     LassoModel model = LassoWithSGD.train(testRDD.rdd(), 100, 1.0, 0.01, 1.0);
 
diff --git a/mllib/src/test/java/spark/mllib/regression/JavaLinearRegressionSuite.java b/mllib/src/test/java/spark/mllib/regression/JavaLinearRegressionSuite.java
index 14d3d4ef39..d2d8a62980 100644
--- a/mllib/src/test/java/spark/mllib/regression/JavaLinearRegressionSuite.java
+++ b/mllib/src/test/java/spark/mllib/regression/JavaLinearRegressionSuite.java
@@ -27,6 +27,7 @@ import org.junit.Test;
 
 import spark.api.java.JavaRDD;
 import spark.api.java.JavaSparkContext;
+import spark.mllib.util.LinearDataGenerator;
 
 public class JavaLinearRegressionSuite implements Serializable {
     private transient JavaSparkContext sc;
@@ -61,10 +62,10 @@ public class JavaLinearRegressionSuite implements Serializable {
         double A = 2.0;
         double[] weights = {-1.5, 1.0e-2};
 
-        JavaRDD<LabeledPoint> testRDD = sc.parallelize(LinearRegressionSuite.generateLinearRegressionInputAsList(A,
+        JavaRDD<LabeledPoint> testRDD = sc.parallelize(LinearDataGenerator.generateLinearInputAsList(A,
                 weights, nPoints, 42), 2).cache();
         List<LabeledPoint> validationData =
-                LinearRegressionSuite.generateLinearRegressionInputAsList(A, weights, nPoints, 17);
+                LinearDataGenerator.generateLinearInputAsList(A, weights, nPoints, 17);
 
         LinearRegressionWithSGD svmSGDImpl = new LinearRegressionWithSGD();
         svmSGDImpl.optimizer().setStepSize(1.0)
@@ -82,10 +83,10 @@ public class JavaLinearRegressionSuite implements Serializable {
         double A = 2.0;
         double[] weights = {-1.5, 1.0e-2};
 
-        JavaRDD<LabeledPoint> testRDD = sc.parallelize(LinearRegressionSuite.generateLinearRegressionInputAsList(A,
+        JavaRDD<LabeledPoint> testRDD = sc.parallelize(LinearDataGenerator.generateLinearInputAsList(A,
                 weights, nPoints, 42), 2).cache();
         List<LabeledPoint> validationData =
-                LinearRegressionSuite.generateLinearRegressionInputAsList(A, weights, nPoints, 17);
+                LinearDataGenerator.generateLinearInputAsList(A, weights, nPoints, 17);
 
         LinearRegressionModel model = LinearRegressionWithSGD.train(testRDD.rdd(), 100, 1.0, 1.0);
 
diff --git a/mllib/src/test/java/spark/mllib/regression/JavaRidgeRegressionSuite.java b/mllib/src/test/java/spark/mllib/regression/JavaRidgeRegressionSuite.java
index 4f379b51d5..72ab875985 100644
--- a/mllib/src/test/java/spark/mllib/regression/JavaRidgeRegressionSuite.java
+++ b/mllib/src/test/java/spark/mllib/regression/JavaRidgeRegressionSuite.java
@@ -27,6 +27,7 @@ import org.junit.Test;
 
 import spark.api.java.JavaRDD;
 import spark.api.java.JavaSparkContext;
+import spark.mllib.util.LinearDataGenerator;
 
 public class JavaRidgeRegressionSuite implements Serializable {
     private transient JavaSparkContext sc;
@@ -61,10 +62,10 @@ public class JavaRidgeRegressionSuite implements Serializable {
         double A = 2.0;
         double[] weights = {-1.5, 1.0e-2};
 
-        JavaRDD<LabeledPoint> testRDD = sc.parallelize(RidgeRegressionSuite.generateRidgeRegressionInputAsList(A,
+        JavaRDD<LabeledPoint> testRDD = sc.parallelize(LinearDataGenerator.generateLinearInputAsList(A,
                 weights, nPoints, 42), 2).cache();
         List<LabeledPoint> validationData =
-                RidgeRegressionSuite.generateRidgeRegressionInputAsList(A, weights, nPoints, 17);
+                LinearDataGenerator.generateLinearInputAsList(A, weights, nPoints, 17);
 
         RidgeRegressionWithSGD svmSGDImpl = new RidgeRegressionWithSGD();
         svmSGDImpl.optimizer().setStepSize(1.0)
@@ -82,10 +83,10 @@ public class JavaRidgeRegressionSuite implements Serializable {
         double A = 2.0;
         double[] weights = {-1.5, 1.0e-2};
 
-        JavaRDD<LabeledPoint> testRDD = sc.parallelize(RidgeRegressionSuite.generateRidgeRegressionInputAsList(A,
+        JavaRDD<LabeledPoint> testRDD = sc.parallelize(LinearDataGenerator.generateLinearInputAsList(A,
                 weights, nPoints, 42), 2).cache();
         List<LabeledPoint> validationData =
-                RidgeRegressionSuite.generateRidgeRegressionInputAsList(A, weights, nPoints, 17);
+                LinearDataGenerator.generateLinearInputAsList(A, weights, nPoints, 17);
 
         RidgeRegressionModel model = RidgeRegressionWithSGD.train(testRDD.rdd(), 100, 1.0, 0.01, 1.0);