add testcases

java/xgboost4j/src/main/java/org/dmlc/xgboost4j/Booster.java

@@ -76,14 +76,16 @@ public Booster(Iterable<Entry<String, Object>> params, DMatrix[] dMatrixs) throw
      * @throws org.dmlc.xgboost4j.util.XGBoostError
      */
     public Booster(Iterable<Entry<String, Object>> params, String modelPath) throws XGBoostError {
-        long[] out = new long[1];
         init(null);
+        if(modelPath == null) {
+            throw new NullPointerException("modelPath : null");
+        }
         loadModel(modelPath);
         setParam("seed","0");
         setParams(params);
     }
 
-  
+
 
 
     private void init(DMatrix[] dMatrixs) throws XGBoostError {

java/xgboost4j/src/main/java/org/dmlc/xgboost4j/DMatrix.java

@@ -55,6 +55,9 @@ public static enum SparseType {
      * @throws org.dmlc.xgboost4j.util.XGBoostError 
      */
     public DMatrix(String dataPath) throws XGBoostError {
+        if(dataPath == null) {
+            throw new NullPointerException("dataPath: null");
+        }
         long[] out = new long[1];
         ErrorHandle.checkCall(XgboostJNI.XGDMatrixCreateFromFile(dataPath, 1, out));
         handle = out[0];

java/xgboost4j/src/test/java/org/dmlc/xgboost4j/BoosterTest.java

@@ -0,0 +1,108 @@
+/*
+ Copyright (c) 2014 by Contributors 
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+    
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ */
+package org.dmlc.xgboost4j;
+
+import java.util.AbstractMap;
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.Map.Entry;
+import junit.framework.TestCase;
+import org.apache.commons.logging.Log;
+import org.apache.commons.logging.LogFactory;
+import org.dmlc.xgboost4j.util.Trainer;
+import org.dmlc.xgboost4j.util.XGBoostError;
+import org.junit.Test;
+
+/**
+ * test cases for Booster
+ * @author hzx
+ */
+public class BoosterTest {
+    public static class EvalError implements IEvaluation {
+        private static final Log logger = LogFactory.getLog(EvalError.class);
+
+        String evalMetric = "custom_error";
+
+        public EvalError() {
+        }
+
+        @Override
+        public String getMetric() {
+            return evalMetric;
+        }
+
+        @Override
+        public float eval(float[][] predicts, DMatrix dmat) {
+            float error = 0f;
+            float[] labels;
+            try {
+                labels = dmat.getLabel();
+            } catch (XGBoostError ex) {
+                logger.error(ex);
+                return -1f;
+            }
+            int nrow = predicts.length;
+            for(int i=0; i<nrow; i++) {
+                if(labels[i]==0f && predicts[i][0]>0) {
+                    error++;
+                }
+                else if(labels[i]==1f && predicts[i][0]<=0) {
+                    error++;
+                }
+            }
+
+            return error/labels.length;
+        }
+    }
+
+    @Test
+    public void testBoosterBasic() throws XGBoostError {
+        DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
+        DMatrix testMat = new DMatrix("../../demo/data/agaricus.txt.test");
+
+        //set params
+        Map<String, Object> paramMap = new HashMap<String, Object>() {
+            {
+                put("eta", 1.0);
+                put("max_depth", 2);
+                put("silent", 1);
+                put("objective", "binary:logistic");
+            }
+        };
+        Iterable<Entry<String, Object>> param = paramMap.entrySet();
+
+        //set watchList
+        List<Entry<String, DMatrix>> watchs =  new ArrayList<>();
+        watchs.add(new AbstractMap.SimpleEntry<>("train", trainMat));
+        watchs.add(new AbstractMap.SimpleEntry<>("test", testMat));
+
+         //set round
+        int round = 2;
+
+        //train a boost model
+        Booster booster = Trainer.train(param, trainMat, round, watchs, null, null);
+
+         //predict raw output
+        float[][] predicts = booster.predict(testMat, true);
+
+        //eval
+        IEvaluation eval = new EvalError();
+        //error must be less than 0.1
+        TestCase.assertTrue(eval.eval(predicts, testMat)<0.1f);
+    }
+}

java/xgboost4j/src/test/java/org/dmlc/xgboost4j/DMatrixTest.java

@@ -0,0 +1,102 @@
+/*
+ Copyright (c) 2014 by Contributors 
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+    
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ */
+package org.dmlc.xgboost4j;
+
+import java.util.Arrays;
+import java.util.Random;
+import junit.framework.TestCase;
+import org.dmlc.xgboost4j.util.XGBoostError;
+import org.junit.Test;
+
+/**
+ * test cases for DMatrix
+ * @author hzx
+ */
+public class DMatrixTest {
+
+    @Test
+    public void testCreateFromFile() throws XGBoostError {
+         //create DMatrix from file
+        DMatrix dmat = new DMatrix("../../demo/data/agaricus.txt.test");
+        //get label
+        float[] labels = dmat.getLabel();
+        //check length
+        TestCase.assertTrue(dmat.rowNum()==labels.length);
+        //set weights
+        float[] weights = Arrays.copyOf(labels, labels.length);
+        dmat.setWeight(weights);
+        float[] dweights = dmat.getWeight();
+        TestCase.assertTrue(Arrays.equals(weights, dweights));
+    }
+
+    @Test
+    public void testCreateFromCSR() throws XGBoostError {
+        //create Matrix from csr format sparse Matrix and labels
+        /**
+         * sparse matrix
+         * 1 0 2 3 0
+         * 4 0 2 3 5
+         * 3 1 2 5 0
+         */
+        float[] data = new float[] {1, 2, 3, 4, 2, 3, 5, 3, 1, 2, 5};
+        int[] colIndex = new int[] {0, 2, 3, 0, 2, 3, 4, 0, 1, 2, 3};
+        long[] rowHeaders = new long[] {0, 3, 7, 11};
+        DMatrix dmat1 = new DMatrix(rowHeaders, colIndex, data, DMatrix.SparseType.CSR);
+        //check row num
+        System.out.println(dmat1.rowNum());
+        TestCase.assertTrue(dmat1.rowNum()==3);
+        //test set label
+        float[] label1 = new float[] {1, 0, 1};
+        dmat1.setLabel(label1);
+        float[] label2  = dmat1.getLabel();
+        TestCase.assertTrue(Arrays.equals(label1, label2));
+    }
+
+    @Test
+    public void testCreateFromDenseMatrix() throws XGBoostError {
+         //create DMatrix from 10*5 dense matrix
+        int nrow = 10;
+        int ncol = 5;
+        float[] data0 = new float[nrow*ncol];
+        //put random nums
+        Random random = new Random();
+        for(int i=0; i<nrow*ncol; i++) {
+            data0[i] = random.nextFloat();
+        }
+
+        //create label
+        float[] label0 = new float[nrow];
+        for(int i=0; i<nrow; i++) {
+            label0[i] = random.nextFloat();
+        }
+
+        DMatrix dmat0 = new DMatrix(data0, nrow, ncol);
+        dmat0.setLabel(label0);
+
+        //check
+        TestCase.assertTrue(dmat0.rowNum()==10);
+        TestCase.assertTrue(dmat0.getLabel().length==10);
+
+        //set weights for each instance
+        float[] weights = new float[nrow];
+        for(int i=0; i<nrow; i++) {
+            weights[i] = random.nextFloat();
+        }
+        dmat0.setWeight(weights);
+
+        TestCase.assertTrue(Arrays.equals(weights, dmat0.getWeight()));
+    }
+}