org.datavec.api.records.reader.impl.csv.CSVRecordReader Java Examples

private void createDataSource() throws IOException, InterruptedException {
    //First: get the dataset using the record reader. CSVRecordReader handles loading/parsing
    int numLinesToSkip = 0;
    String delimiter = ",";
    RecordReader recordReader = new CSVRecordReader(numLinesToSkip, delimiter);
    recordReader.initialize(new InputStreamInputSplit(dataFile));

    //Second: the RecordReaderDataSetIterator handles conversion to DataSet objects, ready for use in neural network
    int labelIndex = 4;     //5 values in each row of the iris.txt CSV: 4 input features followed by an integer label (class) index. Labels are the 5th value (index 4) in each row
    int numClasses = 3;     //3 classes (types of iris flowers) in the iris data set. Classes have integer values 0, 1 or 2

    DataSetIterator iterator = new RecordReaderDataSetIterator(recordReader, batchSize, labelIndex, numClasses);
    DataSet allData = iterator.next();
    allData.shuffle();

    SplitTestAndTrain testAndTrain = allData.splitTestAndTrain(0.80);  //Use 80% of data for training

    trainingData = testAndTrain.getTrain();
    testData = testAndTrain.getTest();

    //We need to normalize our data. We'll use NormalizeStandardize (which gives us mean 0, unit variance):
    DataNormalization normalizer = new NormalizerStandardize();
    normalizer.fit(trainingData);           //Collect the statistics (mean/stdev) from the training data. This does not modify the input data
    normalizer.transform(trainingData);     //Apply normalization to the training data
    normalizer.transform(testData);         //Apply normalization to the test data. This is using statistics calculated from the *training* set
}
 

@Test
public void testRRDSIwithAsync() throws Exception {
    RecordReader csv = new CSVRecordReader();
    csv.initialize(new FileSplit(Resources.asFile("iris.txt")));

    int batchSize = 10;
    int labelIdx = 4;
    int numClasses = 3;

    RecordReaderDataSetIterator rrdsi = new RecordReaderDataSetIterator(csv, batchSize, labelIdx, numClasses);
    AsyncDataSetIterator adsi = new AsyncDataSetIterator(rrdsi, 8, true);
    while (adsi.hasNext()) {
        DataSet ds = adsi.next();

    }

}
 

private void createDataSource() throws IOException, InterruptedException {
    //First: get the dataset using the record reader. CSVRecordReader handles loading/parsing
    int numLinesToSkip = 0;
    String delimiter = ",";
    RecordReader recordReader = new CSVRecordReader(numLinesToSkip, delimiter);
    recordReader.initialize(new InputStreamInputSplit(dataFile));

    //Second: the RecordReaderDataSetIterator handles conversion to DataSet objects, ready for use in neural network
    int labelIndex = 11;

    DataSetIterator iterator = new RecordReaderDataSetIterator(recordReader, batchSize, labelIndex, labelIndex, true);
    DataSet allData = iterator.next();

    SplitTestAndTrain testAndTrain = allData.splitTestAndTrain(0.80);  //Use 80% of data for training

    trainingData = testAndTrain.getTrain();
    testData = testAndTrain.getTest();

    //We need to normalize our data. We'll use NormalizeStandardize (which gives us mean 0, unit variance):
    DataNormalization normalizer = new NormalizerStandardize();
    normalizer.fit(trainingData);           //Collect the statistics (mean/stdev) from the training data. This does not modify the input data
    normalizer.transform(trainingData);     //Apply normalization to the training data
    normalizer.transform(testData);         //Apply normalization to the test data. This is using statistics calculated from the *training* set
}
 

@Test(timeout = 60000)
public void runAdd(TestContext testContext) throws Exception {
    BatchInputArrowParserVerticle verticleRef = (BatchInputArrowParserVerticle) verticle;
    Schema irisInputSchema = TrainUtils.getIrisInputSchema();
    ArrowRecordWriter arrowRecordWriter = new ArrowRecordWriter(irisInputSchema);
    CSVRecordReader reader = new CSVRecordReader();
    reader.initialize(new FileSplit(new ClassPathResource("iris.txt").getFile()));
    List<List<Writable>> writables = reader.next(150);

    File tmpFile = new File(temporary.getRoot(), "tmp.arrow");
    FileSplit fileSplit = new FileSplit(tmpFile);
    arrowRecordWriter.initialize(fileSplit, new NumberOfRecordsPartitioner());
    arrowRecordWriter.writeBatch(writables);

    given().port(port)
            .multiPart("input1", tmpFile)
            .when().post("/")
            .then().statusCode(200);

    testContext.assertNotNull(verticleRef.getBatch(), "Inputs were null. This means parsing failed.");
    testContext.assertTrue(verticleRef.getBatch().length >= 1);
    testContext.assertNotNull(verticleRef.getBatch());
    testContext.assertEquals(150, verticleRef.getBatch().length);
}
 

public RecordReader dataPreprocess() throws IOException, InterruptedException {
    //Schema Definitions
    Schema schema = new Schema.Builder()
            .addColumnsString("RowNumber")
            .addColumnInteger("CustomerId")
            .addColumnString("Surname")
            .addColumnInteger("CreditScore")
            .addColumnCategorical("Geography", Arrays.asList("France","Spain","Germany"))
            .addColumnCategorical("Gender",Arrays.asList("Male","Female"))
            .addColumnsInteger("Age","Tenure","Balance","NumOfProducts","HasCrCard","IsActiveMember","EstimatedSalary","Exited").build();

    //Schema Transformation
    TransformProcess transformProcess = new TransformProcess.Builder(schema)
            .removeColumns("RowNumber","Surname","CustomerId")
            .categoricalToInteger("Gender")
            .categoricalToOneHot("Geography")
            .removeColumns("Geography[France]")
            .build();

    //CSVReader - Reading from file and applying transformation
    RecordReader reader = new CSVRecordReader(1,',');
    reader.initialize(new FileSplit(new ClassPathResource("Churn_Modelling.csv").getFile()));
    RecordReader transformProcessRecordReader = new TransformProcessRecordReader(reader,transformProcess);
    return transformProcessRecordReader;
}
 

public RecordReader dataPreprocess() throws IOException, InterruptedException {
    //Schema Definitions
    Schema schema = new Schema.Builder()
            .addColumnsString("RowNumber")
            .addColumnInteger("CustomerId")
            .addColumnString("Surname")
            .addColumnInteger("CreditScore")
            .addColumnCategorical("Geography", Arrays.asList("France","Spain","Germany"))
            .addColumnCategorical("Gender",Arrays.asList("Male","Female"))
            .addColumnsInteger("Age","Tenure","Balance","NumOfProducts","HasCrCard","IsActiveMember","EstimatedSalary","Exited").build();

    //Schema Transformation
    TransformProcess transformProcess = new TransformProcess.Builder(schema)
            .removeColumns("RowNumber","Surname","CustomerId")
            .categoricalToInteger("Gender")
            .categoricalToOneHot("Geography")
            .removeColumns("Geography[France]")
            .build();

    //CSVReader - Reading from file and applying transformation
    RecordReader reader = new CSVRecordReader(1,',');
    reader.initialize(new FileSplit(new ClassPathResource("Churn_Modelling.csv").getFile()));
    RecordReader transformProcessRecordReader = new TransformProcessRecordReader(reader,transformProcess);
    return transformProcessRecordReader;
}
 

public RecordReader dataPreprocess() throws IOException, InterruptedException {
    //Schema Definitions
    Schema schema = new Schema.Builder()
            .addColumnsString("RowNumber")
            .addColumnInteger("CustomerId")
            .addColumnString("Surname")
            .addColumnInteger("CreditScore")
            .addColumnCategorical("Geography",Arrays.asList("France","Spain","Germany"))
            .addColumnCategorical("Gender",Arrays.asList("Male","Female"))
            .addColumnsInteger("Age","Tenure","Balance","NumOfProducts","HasCrCard","IsActiveMember","EstimatedSalary","Exited").build();

    //Schema Transformation
    TransformProcess transformProcess = new TransformProcess.Builder(schema)
            .removeColumns("RowNumber","Surname","CustomerId")
            .categoricalToInteger("Gender")
            .categoricalToOneHot("Geography")
            .removeColumns("Geography[France]")
            .build();

    //CSVReader - Reading from file and applying transformation
    RecordReader reader = new CSVRecordReader(1,',');
    reader.initialize(new FileSplit(new ClassPathResource("Churn_Modelling.csv").getFile()));
    RecordReader transformProcessRecordReader = new TransformProcessRecordReader(reader,transformProcess);
    return transformProcessRecordReader;
}
 

@Test(timeout = 60000)

    public void testArrowBinary() throws Exception {
        Schema irisInputSchema = TrainUtils.getIrisInputSchema();
        ArrowRecordWriter arrowRecordWriter = new ArrowRecordWriter(irisInputSchema);
        CSVRecordReader reader = new CSVRecordReader();
        reader.initialize(new FileSplit(new ClassPathResource("iris.txt").getFile()));
        List<List<Writable>> writables = reader.next(150);

        File tmpFile = new File(temporary.getRoot(), "tmp.arrow");
        FileSplit fileSplit = new FileSplit(tmpFile);
        arrowRecordWriter.initialize(fileSplit, new NumberOfRecordsPartitioner());
        arrowRecordWriter.writeBatch(writables);
        byte[] arrowBytes = FileUtils.readFileToByteArray(tmpFile);

        Buffer buffer = Buffer.buffer(arrowBytes);
        ArrowBinaryInputAdapter arrowBinaryInputAdapter = new ArrowBinaryInputAdapter();
        ArrowWritableRecordBatch convert = arrowBinaryInputAdapter.convert(buffer, ConverterArgs.builder().schema(irisInputSchema).build(), null);
        assertEquals(writables.size(), convert.size());
    }
 

@Test
public void testMnist() throws Exception {
    ClassPathResource cpr = new ClassPathResource("mnist_first_200.txt");
    CSVRecordReader rr = new CSVRecordReader(0, ',');
    rr.initialize(new FileSplit(cpr.getTempFileFromArchive()));
    RecordReaderDataSetIterator dsi = new RecordReaderDataSetIterator(rr, 10, 0, 10);

    MnistDataSetIterator iter = new MnistDataSetIterator(10, 200, false, true, false, 0);

    while (dsi.hasNext()) {
        DataSet dsExp = dsi.next();
        DataSet dsAct = iter.next();

        INDArray fExp = dsExp.getFeatures();
        fExp.divi(255);
        INDArray lExp = dsExp.getLabels();

        INDArray fAct = dsAct.getFeatures();
        INDArray lAct = dsAct.getLabels();

        assertEquals(fExp, fAct.castTo(fExp.dataType()));
        assertEquals(lExp, lAct.castTo(lExp.dataType()));
    }
    assertFalse(iter.hasNext());
}
 

@Test
public void simpleTransformTest() throws Exception {
    Schema schema = new Schema.Builder()
            .addColumnsDouble("%d", 0, 4)
            .build();
    TransformProcess transformProcess = new TransformProcess.Builder(schema).removeColumns("0").build();
    CSVRecordReader csvRecordReader = new CSVRecordReader();
    csvRecordReader.initialize(new FileSplit(new ClassPathResource("iris.dat").getFile()));
    TransformProcessRecordReader rr =
                    new TransformProcessRecordReader(csvRecordReader, transformProcess);
    int count = 0;
    List<List<Writable>> all = new ArrayList<>();
    while(rr.hasNext()){
        List<Writable> next = rr.next();
        assertEquals(4, next.size());
        count++;
        all.add(next);
    }
    assertEquals(150, count);

    //Test batch:
    assertTrue(rr.resetSupported());
    rr.reset();
    List<List<Writable>> batch = rr.next(150);
    assertEquals(all, batch);
}
 

@Test
public void test() throws Exception {

    CSVRecordReader rr = new CSVRecordReader(0, ',');
    rr.initialize(new FileSplit(new ClassPathResource("iris.dat").getFile()));

    CSVRecordReader rr2 = new CSVRecordReader(0, ',');
    rr2.initialize(new FileSplit(new ClassPathResource("iris.dat").getFile()));

    RecordReader rrC = new ConcatenatingRecordReader(rr, rr2);

    int count = 0;
    while(rrC.hasNext()){
        rrC.next();
        count++;
    }

    assertEquals(300, count);
}
 

@Test
public void testReset() throws Exception {
    CSVRecordReader rr = new CSVRecordReader(0, ',');
    rr.initialize(new FileSplit(new ClassPathResource("iris.dat").getFile()));

    int nResets = 5;
    for (int i = 0; i < nResets; i++) {

        int lineCount = 0;
        while (rr.hasNext()) {
            List<Writable> line = rr.next();
            assertEquals(5, line.size());
            lineCount++;
        }
        assertFalse(rr.hasNext());
        assertEquals(150, lineCount);
        rr.reset();
    }
}
 

@Test
public void testResetWithSkipLines() throws Exception {
    CSVRecordReader rr = new CSVRecordReader(10, ',');
    rr.initialize(new FileSplit(new ClassPathResource("iris.dat").getFile()));
    int lineCount = 0;
    while (rr.hasNext()) {
        rr.next();
        ++lineCount;
    }
    assertEquals(140, lineCount);
    rr.reset();
    lineCount = 0;
    while (rr.hasNext()) {
        rr.next();
        ++lineCount;
    }
    assertEquals(140, lineCount);
}
 

@Test(expected = NoSuchElementException.class)
public void testCsvSkipAllLines() throws IOException, InterruptedException {
    final int numLines = 4;
    final List<Writable> lineList = Arrays.asList((Writable) new IntWritable(numLines - 1),
                    (Writable) new Text("one"), (Writable) new Text("two"), (Writable) new Text("three"));
    String header = ",one,two,three";
    List<String> lines = new ArrayList<>();
    for (int i = 0; i < numLines; i++)
        lines.add(Integer.toString(i) + header);
    File tempFile = File.createTempFile("csvSkipLines", ".csv");
    FileUtils.writeLines(tempFile, lines);

    CSVRecordReader rr = new CSVRecordReader(numLines, ',');
    rr.initialize(new FileSplit(tempFile));
    rr.reset();
    assertTrue(!rr.hasNext());
    rr.next();
}
 

@Test
public void testStreamReset() throws Exception {
    CSVRecordReader rr = new CSVRecordReader(0, ',');
    rr.initialize(new InputStreamInputSplit(new ClassPathResource("iris.dat").getInputStream()));

    int count = 0;
    while(rr.hasNext()){
        assertNotNull(rr.next());
        count++;
    }
    assertEquals(150, count);

    assertFalse(rr.resetSupported());

    try{
        rr.reset();
        fail("Expected exception");
    } catch (Exception e){
        e.printStackTrace();
    }
}
 

@Test
public void testCsvRecordReader() throws Exception {
    SerializerInstance si = sc.env().serializer().newInstance();
    assertTrue(si instanceof KryoSerializerInstance);

    RecordReader r1 = new CSVRecordReader(1,'\t');
    RecordReader r2 = serDe(r1, si);

    File f = new ClassPathResource("iris_tab_delim.txt").getFile();
    r1.initialize(new FileSplit(f));
    r2.initialize(new FileSplit(f));

    while(r1.hasNext()){
        assertEquals(r1.next(), r2.next());
    }
    assertFalse(r2.hasNext());
}
 

@Test
public void simpleTransformTest() throws Exception {
    Schema schema = new Schema.Builder()
            .addColumnsDouble("%d", 0, 4)
            .build();
    TransformProcess transformProcess = new TransformProcess.Builder(schema).removeColumns("0").build();
    CSVRecordReader csvRecordReader = new CSVRecordReader();
    csvRecordReader.initialize(new FileSplit(new ClassPathResource("datavec-api/iris.dat").getFile()));
    TransformProcessRecordReader rr =
                    new TransformProcessRecordReader(csvRecordReader, transformProcess);
    int count = 0;
    List<List<Writable>> all = new ArrayList<>();
    while(rr.hasNext()){
        List<Writable> next = rr.next();
        assertEquals(4, next.size());
        count++;
        all.add(next);
    }
    assertEquals(150, count);

    //Test batch:
    assertTrue(rr.resetSupported());
    rr.reset();
    List<List<Writable>> batch = rr.next(150);
    assertEquals(all, batch);
}
 

@Test
public void test() throws Exception {

    CSVRecordReader rr = new CSVRecordReader(0, ',');
    rr.initialize(new FileSplit(new ClassPathResource("datavec-api/iris.dat").getFile()));

    CSVRecordReader rr2 = new CSVRecordReader(0, ',');
    rr2.initialize(new FileSplit(new ClassPathResource("datavec-api/iris.dat").getFile()));

    RecordReader rrC = new ConcatenatingRecordReader(rr, rr2);

    int count = 0;
    while(rrC.hasNext()){
        rrC.next();
        count++;
    }

    assertEquals(300, count);
}
 

@Test
public void testNormalizerPrefetchReset() throws Exception {
    //Check NPE fix for: https://github.com/deeplearning4j/deeplearning4j/issues/4214
    RecordReader csv = new CSVRecordReader();
    csv.initialize(new FileSplit(Resources.asFile("iris.txt")));

    int batchSize = 3;

    DataSetIterator iter = new RecordReaderDataSetIterator(csv, batchSize, 4, 4, true);

    DataNormalization normalizer = new NormalizerMinMaxScaler(0, 1);
    normalizer.fit(iter);
    iter.setPreProcessor(normalizer);

    iter.inputColumns();    //Prefetch
    iter.totalOutcomes();
    iter.hasNext();
    iter.reset();
    iter.next();
}
 

@Test
public void testReset() throws Exception {
    CSVRecordReader rr = new CSVRecordReader(0, ',');
    rr.initialize(new FileSplit(new ClassPathResource("datavec-api/iris.dat").getFile()));

    int nResets = 5;
    for (int i = 0; i < nResets; i++) {

        int lineCount = 0;
        while (rr.hasNext()) {
            List<Writable> line = rr.next();
            assertEquals(5, line.size());
            lineCount++;
        }
        assertFalse(rr.hasNext());
        assertEquals(150, lineCount);
        rr.reset();
    }
}
 

@Test
public void testsBasicMeta() throws Exception {
    //As per testBasic - but also loading metadata
    RecordReader rr2 = new CSVRecordReader(0, ',');
    rr2.initialize(new FileSplit(Resources.asFile("iris.txt")));

    RecordReaderMultiDataSetIterator rrmdsi = new RecordReaderMultiDataSetIterator.Builder(10)
                    .addReader("reader", rr2).addInput("reader", 0, 3).addOutputOneHot("reader", 4, 3).build();

    rrmdsi.setCollectMetaData(true);

    int count = 0;
    while (rrmdsi.hasNext()) {
        MultiDataSet mds = rrmdsi.next();
        MultiDataSet fromMeta = rrmdsi.loadFromMetaData(mds.getExampleMetaData(RecordMetaData.class));
        assertEquals(mds, fromMeta);
        count++;
    }
    assertEquals(150 / 10, count);
}
 

@Test
public void testLoadBatchDataSet() throws Exception {
    int epochs = 2;

    RecordReader rr = new CSVRecordReader();
    rr.initialize(new FileSplit(new ClassPathResource("iris.txt").getFile()));
    DataSetIterator iter = new RecordReaderDataSetIterator(rr, 150, 4, 3);
    DataSet ds = iter.next(20);
    assertEquals(20, ds.getFeatures().size(0));
    MultipleEpochsIterator multiIter = new MultipleEpochsIterator(epochs, ds);

    while (multiIter.hasNext()) {
        DataSet path = multiIter.next(10);
        assertNotNull(path);
        assertEquals(10, path.numExamples(), 0.0);
    }

    assertEquals(epochs, multiIter.epochs);
}
 

@Test(expected = NoSuchElementException.class)
public void testCsvSkipAllLines() throws IOException, InterruptedException {
    final int numLines = 4;
    final List<Writable> lineList = Arrays.asList((Writable) new IntWritable(numLines - 1),
                    (Writable) new Text("one"), (Writable) new Text("two"), (Writable) new Text("three"));
    String header = ",one,two,three";
    List<String> lines = new ArrayList<>();
    for (int i = 0; i < numLines; i++)
        lines.add(Integer.toString(i) + header);
    File tempFile = File.createTempFile("csvSkipLines", ".csv");
    FileUtils.writeLines(tempFile, lines);

    CSVRecordReader rr = new CSVRecordReader(numLines, ',');
    rr.initialize(new FileSplit(tempFile));
    rr.reset();
    assertTrue(!rr.hasNext());
    rr.next();
}
 

@Test
public void testCsvSkipAllButOneLine() throws IOException, InterruptedException {
    final int numLines = 4;
    final List<Writable> lineList = Arrays.<Writable>asList(new Text(Integer.toString(numLines - 1)),
            new Text("one"), new Text("two"), new Text("three"));
    String header = ",one,two,three";
    List<String> lines = new ArrayList<>();
    for (int i = 0; i < numLines; i++)
        lines.add(Integer.toString(i) + header);
    File tempFile = File.createTempFile("csvSkipLines", ".csv");
    FileUtils.writeLines(tempFile, lines);

    CSVRecordReader rr = new CSVRecordReader(numLines - 1, ',');
    rr.initialize(new FileSplit(tempFile));
    rr.reset();
    assertTrue(rr.hasNext());
    assertEquals(rr.next(), lineList);
}
 

@Test
    public void testStreamReset() throws Exception {
        CSVRecordReader rr = new CSVRecordReader(0, ',');
        rr.initialize(new InputStreamInputSplit(new ClassPathResource("datavec-api/iris.dat").getInputStream()));

        int count = 0;
        while(rr.hasNext()){
            assertNotNull(rr.next());
            count++;
        }
        assertEquals(150, count);

        assertFalse(rr.resetSupported());

        try{
            rr.reset();
            fail("Expected exception");
        } catch (Exception e){
            String msg = e.getMessage();
            String msg2 = e.getCause().getMessage();
            assertTrue(msg, msg.contains("Error during LineRecordReader reset"));
            assertTrue(msg2, msg2.contains("Reset not supported from streams"));
//            e.printStackTrace();
        }
    }
 

@Test
public void testNextAndReset() throws Exception {
    int epochs = 3;

    RecordReader rr = new CSVRecordReader();
    rr.initialize(new FileSplit(Resources.asFile("iris.txt")));
    DataSetIterator iter = new RecordReaderDataSetIterator(rr, 150);
    MultipleEpochsIterator multiIter = new MultipleEpochsIterator(epochs, iter);

    assertTrue(multiIter.hasNext());
    while (multiIter.hasNext()) {
        DataSet path = multiIter.next();
        assertFalse(path == null);
    }
    assertEquals(epochs, multiIter.epochs);
}
 

@Test
public void testCsvRecordReader() throws Exception {
    SerializerInstance si = sc.env().serializer().newInstance();
    assertTrue(si instanceof KryoSerializerInstance);

    RecordReader r1 = new CSVRecordReader(1,'\t');
    RecordReader r2 = serDe(r1, si);

    File f = new ClassPathResource("iris_tab_delim.txt").getFile();
    r1.initialize(new FileSplit(f));
    r2.initialize(new FileSplit(f));

    while(r1.hasNext()){
        assertEquals(r1.next(), r2.next());
    }
    assertFalse(r2.hasNext());
}
 

@Test
public void testCsvSkipAllButOneLine() throws IOException, InterruptedException {
    final int numLines = 4;
    final List<Writable> lineList = Arrays.<Writable>asList(new Text(Integer.toString(numLines - 1)),
            new Text("one"), new Text("two"), new Text("three"));
    String header = ",one,two,three";
    List<String> lines = new ArrayList<>();
    for (int i = 0; i < numLines; i++)
        lines.add(Integer.toString(i) + header);
    File tempFile = File.createTempFile("csvSkipLines", ".csv");
    FileUtils.writeLines(tempFile, lines);

    CSVRecordReader rr = new CSVRecordReader(numLines - 1, ',');
    rr.initialize(new FileSplit(tempFile));
    rr.reset();
    assertTrue(rr.hasNext());
    assertEquals(rr.next(), lineList);
}
 

@Override
public RecordReader createReader(InputSplit split) throws IOException, InterruptedException {
    CSVRecordReader ret = new CSVRecordReader();
    ret.initialize(split);
    return ret;

}
 

@Test
public void testAnalysisBasic() throws Exception {

    RecordReader rr = new CSVRecordReader();
    rr.initialize(new FileSplit(new ClassPathResource("iris.txt").getFile()));

    Schema s = new Schema.Builder()
            .addColumnsDouble("0", "1", "2", "3")
            .addColumnInteger("label")
            .build();

    DataAnalysis da = AnalyzeLocal.analyze(s, rr);

    System.out.println(da);

    //Compare:
    List<List<Writable>> list = new ArrayList<>();
    rr.reset();
    while(rr.hasNext()){
        list.add(rr.next());
    }

    INDArray arr = RecordConverter.toMatrix(DataType.DOUBLE, list);
    INDArray mean = arr.mean(0);
    INDArray std = arr.std(0);

    for( int i=0; i<5; i++ ){
        double m = ((NumericalColumnAnalysis)da.getColumnAnalysis().get(i)).getMean();
        double stddev = ((NumericalColumnAnalysis)da.getColumnAnalysis().get(i)).getSampleStdev();
        assertEquals(mean.getDouble(i), m, 1e-3);
        assertEquals(std.getDouble(i), stddev, 1e-3);
    }

}