use of org.apache.sysml.api.mlcontext.Script in project incubator-systemml by apache.
the class MLContextTest method testCreatePYDMLScriptBasedOnLocalFileAndExecute.
@Test
public void testCreatePYDMLScriptBasedOnLocalFileAndExecute() {
System.out.println("MLContextTest - create PYDML script based on local file and execute");
setExpectedStdOut("hello world");
File file = new File(baseDirectory + File.separator + "hello-world.pydml");
Script script = pydmlFromLocalFile(file);
ml.execute(script);
}
use of org.apache.sysml.api.mlcontext.Script in project incubator-systemml by apache.
the class MLContextTest method testInputScalaMapDML.
@Test
public void testInputScalaMapDML() {
System.out.println("MLContextTest - input Scala map DML");
List<String> list = new ArrayList<String>();
list.add("10,20");
list.add("30,40");
final JavaRDD<String> javaRDD = sc.parallelize(list);
Map<String, Object> inputs = new HashMap<String, Object>() {
private static final long serialVersionUID = 1L;
{
put("$X", 2);
put("M", javaRDD);
}
};
scala.collection.mutable.Map<String, Object> scalaMap = JavaConversions.mapAsScalaMap(inputs);
String s = "M = M + $X; print('sum: ' + sum(M));";
Script script = dml(s).in(scalaMap);
setExpectedStdOut("sum: 108.0");
ml.execute(script);
}
use of org.apache.sysml.api.mlcontext.Script in project incubator-systemml by apache.
the class MLContextTest method testPrintFormattingBooleanSubstitutionAlignment.
@Test
public void testPrintFormattingBooleanSubstitutionAlignment() {
System.out.println("MLContextTest - print formatting boolean substitution alignment");
Script script = dml("print(\"'%10b' '%-10b'\", TRUE, FALSE);");
setExpectedStdOut("' true' 'false '");
ml.execute(script);
}
use of org.apache.sysml.api.mlcontext.Script in project incubator-systemml by apache.
the class MLContextTest method testDataFrameSumDMLDoublesWithIDColumnNoFormatSpecified.
@Test
public void testDataFrameSumDMLDoublesWithIDColumnNoFormatSpecified() {
System.out.println("MLContextTest - DataFrame sum DML, doubles with ID column, no format specified");
List<String> list = new ArrayList<String>();
list.add("1,2,2,2");
list.add("2,3,3,3");
list.add("3,4,4,4");
JavaRDD<String> javaRddString = sc.parallelize(list);
JavaRDD<Row> javaRddRow = javaRddString.map(new CommaSeparatedValueStringToDoubleArrayRow());
List<StructField> fields = new ArrayList<StructField>();
fields.add(DataTypes.createStructField(RDDConverterUtils.DF_ID_COLUMN, DataTypes.DoubleType, true));
fields.add(DataTypes.createStructField("C1", DataTypes.DoubleType, true));
fields.add(DataTypes.createStructField("C2", DataTypes.DoubleType, true));
fields.add(DataTypes.createStructField("C3", DataTypes.DoubleType, true));
StructType schema = DataTypes.createStructType(fields);
Dataset<Row> dataFrame = spark.createDataFrame(javaRddRow, schema);
Script script = dml("print('sum: ' + sum(M));").in("M", dataFrame);
setExpectedStdOut("sum: 27.0");
ml.execute(script);
}
use of org.apache.sysml.api.mlcontext.Script in project incubator-systemml by apache.
the class MLContextTest method testOutputDataFrameDoublesWithIDColumnFromMatrixDML.
@Test
public void testOutputDataFrameDoublesWithIDColumnFromMatrixDML() {
System.out.println("MLContextTest - output DataFrame of doubles with ID column from matrix DML");
String s = "M = matrix('1 2 3 4', rows=2, cols=2);";
Script script = dml(s).out("M");
Dataset<Row> df = ml.execute(script).getMatrix("M").toDFDoubleWithIDColumn();
Dataset<Row> sortedDF = df.sort(RDDConverterUtils.DF_ID_COLUMN);
List<Row> list = sortedDF.collectAsList();
Row row1 = list.get(0);
Assert.assertEquals(1.0, row1.getDouble(0), 0.0);
Assert.assertEquals(1.0, row1.getDouble(1), 0.0);
Assert.assertEquals(2.0, row1.getDouble(2), 0.0);
Row row2 = list.get(1);
Assert.assertEquals(2.0, row2.getDouble(0), 0.0);
Assert.assertEquals(3.0, row2.getDouble(1), 0.0);
Assert.assertEquals(4.0, row2.getDouble(2), 0.0);
}
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