<NME> RegressionSynthesizerTest.java
<BEF> ADDFILE
<MSG> add RegressionSynthesizer

<DFF> @@ -0,0 +1,39 @@
+package edu.neu.ccs.pyramid.simulation;
+
+import edu.neu.ccs.pyramid.dataset.RegDataSet;
+import edu.neu.ccs.pyramid.eval.MSE;
+import edu.neu.ccs.pyramid.regression.regression_tree.RegTreeConfig;
+import edu.neu.ccs.pyramid.regression.regression_tree.RegTreeTrainer;
+import edu.neu.ccs.pyramid.regression.regression_tree.RegressionTree;
+
+import java.util.stream.IntStream;
+
+import static org.junit.Assert.*;
+
+public class RegressionSynthesizerTest {
+    public static void main(String[] args) {
+        test1();
+    }
+
+
+    private static void test1(){
+        RegDataSet dataSet = RegressionSynthesizer.univarStepFunction();
+        int[] activeFeatures = IntStream.range(0, dataSet.getNumFeatures()).toArray();
+        int[] activeDataPoints = IntStream.range(0, dataSet.getNumDataPoints()).toArray();
+        RegTreeConfig regTreeConfig = new RegTreeConfig();
+        regTreeConfig.setActiveFeatures(activeFeatures);
+
+        regTreeConfig.setMaxNumLeaves(2);
+        regTreeConfig.setMinDataPerLeaf(5);
+        regTreeConfig.setActiveDataPoints(activeDataPoints);
+
+        regTreeConfig.setNumSplitIntervals(1000);
+        RegressionTree tree = RegTreeTrainer.fit(regTreeConfig,dataSet);
+        System.out.println(tree.toString());
+
+        RegDataSet testSet = RegressionSynthesizer.univarStepFunction();
+        System.out.println("training mse = "+ MSE.mse(tree,dataSet));
+        System.out.println("test mse = "+ MSE.mse(tree,testSet));
+    }
+
+}
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add RegressionSynthesizer