blob: 85c1eec79e10498d2de1f9a050199443c43d3d2e [file] [log] [blame]
/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you 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.apache.sysds.test.functions.binary.matrix_full_cellwise;
import java.util.Arrays;
import java.util.HashMap;
import org.junit.Test;
import org.apache.sysds.api.DMLScript;
import org.apache.sysds.common.Types.ExecMode;
import org.apache.sysds.lops.LopProperties.ExecType;
import org.apache.sysds.runtime.matrix.data.MatrixValue.CellIndex;
import org.apache.sysds.runtime.meta.MatrixCharacteristics;
import org.apache.sysds.test.AutomatedTestBase;
import org.apache.sysds.test.TestConfiguration;
import org.apache.sysds.test.TestUtils;
/**
* TODO cleanup outer(X,Y,z) definition to take two column vectors instead of column and row vector.
*
*/
public class FullVectorVectorCellwiseCompareOperationTest extends AutomatedTestBase
{
private final static String TEST_NAME = "FullVectorVectorCellwiseOperation";
private final static String TEST_DIR = "functions/binary/matrix_full_cellwise/";
private final static String TEST_CLASS_DIR = TEST_DIR + FullVectorVectorCellwiseCompareOperationTest.class.getSimpleName() + "/";
private final static double eps = 1e-10;
private final static int rows1 = 1001;
private final static int rows2 = 1009;
private final static double sparsity1 = 0.7;
private final static double sparsity2 = 0.01;
private enum OpType{
LESS_THAN,
LESS_THAN_EQUALS,
GREATER_THAN,
GREATER_THAN_EQUALS,
EQUALS,
NOT_EQUALS
}
private enum SparsityType{
DENSE,
SPARSE,
EMPTY
}
@Override
public void setUp()
{
addTestConfiguration(TEST_NAME, new TestConfiguration(TEST_CLASS_DIR, TEST_NAME, new String[]{"C"}));
}
@Test
public void testLessThanDenseDenseCP()
{
runMatrixVectorCellwiseOperationTest(OpType.LESS_THAN, SparsityType.DENSE, SparsityType.DENSE, ExecType.CP);
}
@Test
public void testLessThanDenseSparseCP()
{
runMatrixVectorCellwiseOperationTest(OpType.LESS_THAN, SparsityType.DENSE, SparsityType.SPARSE, ExecType.CP);
}
@Test
public void testLessThanDenseEmptyCP()
{
runMatrixVectorCellwiseOperationTest(OpType.LESS_THAN, SparsityType.DENSE, SparsityType.EMPTY, ExecType.CP);
}
@Test
public void testLessThanSparseDenseCP()
{
runMatrixVectorCellwiseOperationTest(OpType.LESS_THAN, SparsityType.SPARSE, SparsityType.DENSE, ExecType.CP);
}
@Test
public void testLessThanSparseSparseCP()
{
runMatrixVectorCellwiseOperationTest(OpType.LESS_THAN, SparsityType.SPARSE, SparsityType.SPARSE, ExecType.CP);
}
@Test
public void testLessThanSparseEmptyCP()
{
runMatrixVectorCellwiseOperationTest(OpType.LESS_THAN, SparsityType.SPARSE, SparsityType.EMPTY, ExecType.CP);
}
@Test
public void testLessThanEmptyDenseCP()
{
runMatrixVectorCellwiseOperationTest(OpType.LESS_THAN, SparsityType.EMPTY, SparsityType.DENSE, ExecType.CP);
}
@Test
public void testLessThanEmptySparseCP()
{
runMatrixVectorCellwiseOperationTest(OpType.LESS_THAN, SparsityType.EMPTY, SparsityType.SPARSE, ExecType.CP);
}
@Test
public void testLessThanEmptyEmptyCP()
{
runMatrixVectorCellwiseOperationTest(OpType.LESS_THAN, SparsityType.EMPTY, SparsityType.EMPTY, ExecType.CP);
}
//-------------------------------------
@Test
public void testLessThanEqualsDenseEmptyCP()
{
runMatrixVectorCellwiseOperationTest(OpType.LESS_THAN_EQUALS, SparsityType.DENSE, SparsityType.EMPTY, ExecType.CP);
}
@Test
public void testGreaterThanSparseDenseCP()
{
runMatrixVectorCellwiseOperationTest(OpType.GREATER_THAN, SparsityType.SPARSE, SparsityType.DENSE, ExecType.CP);
}
@Test
public void testGreaterThanEqualsSparseSparseCP()
{
runMatrixVectorCellwiseOperationTest(OpType.GREATER_THAN_EQUALS, SparsityType.SPARSE, SparsityType.SPARSE, ExecType.CP);
}
@Test
public void testEqualsSparseEmptyCP()
{
runMatrixVectorCellwiseOperationTest(OpType.EQUALS, SparsityType.SPARSE, SparsityType.EMPTY, ExecType.CP);
}
@Test
public void testNotEqualEmptyDenseCP()
{
runMatrixVectorCellwiseOperationTest(OpType.NOT_EQUALS, SparsityType.EMPTY, SparsityType.DENSE, ExecType.CP);
}
//-------------------------------------
/**
*
* @param sparseM1
* @param sparseM2
* @param instType
*/
private void runMatrixVectorCellwiseOperationTest( OpType type, SparsityType sparseM1, SparsityType sparseM2, ExecType instType)
{
//rtplatform for MR
ExecMode platformOld = rtplatform;
switch( instType ){
case SPARK: rtplatform = ExecMode.SPARK; break;
default: rtplatform = ExecMode.HYBRID; break;
}
boolean sparkConfigOld = DMLScript.USE_LOCAL_SPARK_CONFIG;
if( rtplatform == ExecMode.SPARK )
DMLScript.USE_LOCAL_SPARK_CONFIG = true;
try
{
String opcode = null;
String opcoder = null;
switch( type )
{
case LESS_THAN: opcode="<"; opcoder="lt"; break;
case LESS_THAN_EQUALS: opcode="<="; opcoder="le"; break;
case GREATER_THAN: opcode=">"; opcoder="gt"; break;
case GREATER_THAN_EQUALS: opcode=">="; opcoder="ge"; break;
case EQUALS: opcode="=="; opcoder="eq"; break;
case NOT_EQUALS: opcode="!="; opcoder="ne"; break;
}
getAndLoadTestConfiguration(TEST_NAME);
String HOME = SCRIPT_DIR + TEST_DIR;
fullDMLScriptName = HOME + TEST_NAME + ".dml";
programArgs = new String[]{"-stats", "-args",
input("A"), input("B"), opcode, output("C") };
fullRScriptName = HOME + TEST_NAME + ".R";
rCmd = "Rscript" + " " + fullRScriptName + " " +
inputDir() + " " + opcoder + " " + expectedDir();
//get sparsity
double lsparsity1 = 1.0, lsparsity2 = 1.0;
switch( sparseM1 ){
case DENSE: lsparsity1 = sparsity1; break;
case SPARSE: lsparsity1 = sparsity2; break;
case EMPTY: lsparsity1 = 0.0; break;
}
switch( sparseM2 ){
case DENSE: lsparsity2 = sparsity1; break;
case SPARSE: lsparsity2 = sparsity2; break;
case EMPTY: lsparsity2 = 0.0; break;
}
//generate actual dataset
double[][] A = getRandomMatrix(rows1, 1, 0, (lsparsity1==0)?0:1, lsparsity1, 7);
writeInputMatrixWithMTD("A", A, true);
double[][] B = getRandomMatrix(1, rows2, 0, (lsparsity2==0)?0:1, lsparsity2, 3);
Arrays.sort(B[0]);
writeInputMatrixWithMTD("B", B, true);
boolean exceptionExpected = false;
runTest(true, exceptionExpected, null, -1);
runRScript(true);
//compare matrices
HashMap<CellIndex, Double> dmlfile = readDMLMatrixFromHDFS("C");
HashMap<CellIndex, Double> rfile = readRMatrixFromFS("C");
TestUtils.compareMatrices(dmlfile, rfile, eps, "Stat-DML", "Stat-R");
checkDMLMetaDataFile("C", new MatrixCharacteristics(rows1,rows2,1,1));
}
finally
{
rtplatform = platformOld;
DMLScript.USE_LOCAL_SPARK_CONFIG = sparkConfigOld;
}
}
}