Examples with MatrixMetadata org.apache.sysml.api.mlcontext.MatrixMetadata used on opensource projects

Example 56 with MatrixMetadata

use of org.apache.sysml.api.mlcontext.MatrixMetadata in project systemml by apache.

the class MLContextTest method testOutputBinaryBlocksDML.

@Test
public void testOutputBinaryBlocksDML() {
    System.out.println("MLContextTest - output binary blocks DML");
    String s = "M = matrix('1 2 3 4', rows=2, cols=2);";
    MLResults results = ml.execute(dml(s).out("M"));
    Matrix m = results.getMatrix("M");
    JavaPairRDD<MatrixIndexes, MatrixBlock> binaryBlocks = m.toBinaryBlocks();
    MatrixMetadata mm = m.getMatrixMetadata();
    MatrixCharacteristics mc = mm.asMatrixCharacteristics();
    JavaRDD<String> javaRDDStringIJV = RDDConverterUtils.binaryBlockToTextCell(binaryBlocks, mc);
    List<String> lines = javaRDDStringIJV.collect();
    Assert.assertEquals("1 1 1.0", lines.get(0));
    Assert.assertEquals("1 2 2.0", lines.get(1));
    Assert.assertEquals("2 1 3.0", lines.get(2));
    Assert.assertEquals("2 2 4.0", lines.get(3));
}

Example 57 with MatrixMetadata

use of org.apache.sysml.api.mlcontext.MatrixMetadata in project systemml by apache.

the class MLContextTest method testDataFrameSumDMLVectorWithIDColumn.

@Test
public void testDataFrameSumDMLVectorWithIDColumn() {
    System.out.println("MLContextTest - DataFrame sum DML, vector with ID column");
    List<Tuple2<Double, Vector>> list = new ArrayList<Tuple2<Double, Vector>>();
    list.add(new Tuple2<Double, Vector>(1.0, Vectors.dense(1.0, 2.0, 3.0)));
    list.add(new Tuple2<Double, Vector>(2.0, Vectors.dense(4.0, 5.0, 6.0)));
    list.add(new Tuple2<Double, Vector>(3.0, Vectors.dense(7.0, 8.0, 9.0)));
    JavaRDD<Tuple2<Double, Vector>> javaRddTuple = sc.parallelize(list);
    JavaRDD<Row> javaRddRow = javaRddTuple.map(new DoubleVectorRow());
    List<StructField> fields = new ArrayList<StructField>();
    fields.add(DataTypes.createStructField(RDDConverterUtils.DF_ID_COLUMN, DataTypes.DoubleType, true));
    fields.add(DataTypes.createStructField("C1", new VectorUDT(), true));
    StructType schema = DataTypes.createStructType(fields);
    Dataset<Row> dataFrame = spark.createDataFrame(javaRddRow, schema);
    MatrixMetadata mm = new MatrixMetadata(MatrixFormat.DF_VECTOR_WITH_INDEX);
    Script script = dml("print('sum: ' + sum(M));").in("M", dataFrame, mm);
    setExpectedStdOut("sum: 45.0");
    ml.execute(script);
}

Example 58 with MatrixMetadata

use of org.apache.sysml.api.mlcontext.MatrixMetadata in project systemml by apache.

the class MLContextTest method testRDDGoodMetadataPYDML.

@Test
public void testRDDGoodMetadataPYDML() {
    System.out.println("MLContextTest - RDD<String> good metadata PYDML");
    List<String> list = new ArrayList<String>();
    list.add("1,1,1");
    list.add("2,2,2");
    list.add("3,3,3");
    JavaRDD<String> javaRDD = sc.parallelize(list);
    RDD<String> rdd = JavaRDD.toRDD(javaRDD);
    MatrixMetadata mm = new MatrixMetadata(3, 3, 9);
    Script script = pydml("print('sum: ' + sum(M))").in("M", rdd, mm);
    setExpectedStdOut("sum: 18.0");
    ml.execute(script);
}

Example 59 with MatrixMetadata

use of org.apache.sysml.api.mlcontext.MatrixMetadata in project systemml by apache.

the class MLContextTest method testDataFrameSumPYDMLVectorWithNoIDColumn.

@Test
public void testDataFrameSumPYDMLVectorWithNoIDColumn() {
    System.out.println("MLContextTest - DataFrame sum PYDML, vector with no ID column");
    List<Vector> list = new ArrayList<Vector>();
    list.add(Vectors.dense(1.0, 2.0, 3.0));
    list.add(Vectors.dense(4.0, 5.0, 6.0));
    list.add(Vectors.dense(7.0, 8.0, 9.0));
    JavaRDD<Vector> javaRddVector = sc.parallelize(list);
    JavaRDD<Row> javaRddRow = javaRddVector.map(new VectorRow());
    List<StructField> fields = new ArrayList<StructField>();
    fields.add(DataTypes.createStructField("C1", new VectorUDT(), true));
    StructType schema = DataTypes.createStructType(fields);
    Dataset<Row> dataFrame = spark.createDataFrame(javaRddRow, schema);
    MatrixMetadata mm = new MatrixMetadata(MatrixFormat.DF_VECTOR);
    Script script = pydml("print('sum: ' + sum(M))").in("M", dataFrame, mm);
    setExpectedStdOut("sum: 45.0");
    ml.execute(script);
}

Example 60 with MatrixMetadata

use of org.apache.sysml.api.mlcontext.MatrixMetadata in project systemml by apache.

the class MLContextTest method testOutputBinaryBlocksPYDML.

@Test
public void testOutputBinaryBlocksPYDML() {
    System.out.println("MLContextTest - output binary blocks PYDML");
    String s = "M = full('1 2 3 4', rows=2, cols=2);";
    MLResults results = ml.execute(pydml(s).out("M"));
    Matrix m = results.getMatrix("M");
    JavaPairRDD<MatrixIndexes, MatrixBlock> binaryBlocks = m.toBinaryBlocks();
    MatrixMetadata mm = m.getMatrixMetadata();
    MatrixCharacteristics mc = mm.asMatrixCharacteristics();
    JavaRDD<String> javaRDDStringIJV = RDDConverterUtils.binaryBlockToTextCell(binaryBlocks, mc);
    List<String> lines = javaRDDStringIJV.collect();
    Assert.assertEquals("1 1 1.0", lines.get(0));
    Assert.assertEquals("1 2 2.0", lines.get(1));
    Assert.assertEquals("2 1 3.0", lines.get(2));
    Assert.assertEquals("2 2 4.0", lines.get(3));
}