src/test/java/org/apache/sysds/test/applications/BivariateScaleScaleTest.java

/*
 * 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.applications;

import java.util.HashMap;

import org.junit.Test;
import org.apache.sysds.runtime.matrix.data.MatrixValue.CellIndex;
import org.apache.sysds.test.AutomatedTestBase;
import org.apache.sysds.test.TestConfiguration;
import org.apache.sysds.test.TestUtils;


public class BivariateScaleScaleTest extends AutomatedTestBase 
{

	private final static String TEST_DIR = "applications/descriptivestats/";
	private final static String TEST_SCALE_SCALE = "ScaleScale";
	private final static String TEST_SCALE_SCALE_WEIGHTS = "ScaleScalePearsonRWithWeightsTest";
	private final static String TEST_CLASS_DIR = TEST_DIR + BivariateScaleScaleTest.class.getSimpleName() + "/";
	
	private final static double eps = 1e-10;
	
	private final static int rows = 100000;      // # of rows in each vector
	private final static double minVal=0;       // minimum value in each vector 
	private final static double maxVal=10000;    // maximum value in each vector 
	private int maxW = 1000;    // maximum weight
	
	@Override
	public void setUp() {
		addTestConfiguration(TEST_SCALE_SCALE, new TestConfiguration(TEST_CLASS_DIR,
				TEST_SCALE_SCALE, new String[] { "PearsonR" + ".scalar" }));
		addTestConfiguration(TEST_SCALE_SCALE_WEIGHTS, new TestConfiguration(
				TEST_CLASS_DIR, "ScaleScalePearsonRWithWeightsTest",
				new String[] { "PearsonR" + ".scalar" }));
	}
	
	@Test
	public void testPearsonR() {

		TestConfiguration config = getTestConfiguration(TEST_SCALE_SCALE);
		config.addVariable("rows", rows);
		loadTestConfiguration(config);
		
		/* This is for running the junit test the new way, i.e., construct the arguments directly */
		String SS_HOME = SCRIPT_DIR + TEST_DIR;
		fullDMLScriptName = SS_HOME + TEST_SCALE_SCALE + ".dml";
		programArgs = new String[]{"-args",  input("X"), 
			Integer.toString(rows), input("Y"), output("PearsonR") };
		
		fullRScriptName = SS_HOME + TEST_SCALE_SCALE + ".R";
		rCmd = "Rscript" + " " + fullRScriptName + " " + inputDir() + " " + expectedDir();

		long seed = System.currentTimeMillis();
		//System.out.println("Seed = " + seed);
        double[][] X = getRandomMatrix(rows, 1, minVal, maxVal, 0.1, seed);
        double[][] Y = getRandomMatrix(rows, 1, minVal, maxVal, 0.1, seed+1);

		writeInputMatrix("X", X, true);
		writeInputMatrix("Y", Y, true);

		boolean exceptionExpected = false;
		/*
		 * Expected number of jobs:
		 */
		// int expectedNumberOfJobs = 5; // This will cause failure
		runTest(true, exceptionExpected, null, -1);
		runRScript(true);
		
		for(String file: config.getOutputFiles())
		{
			/* NOte that some files do not contain matrix, but just a single scalar value inside */
			HashMap<CellIndex, Double> dmlfile;
			HashMap<CellIndex, Double> rfile;
			if (file.endsWith(".scalar")) {
				file = file.replace(".scalar", "");
				dmlfile = readDMLScalarFromHDFS(file);
				rfile = readRScalarFromFS(file);
			}
			else {
				dmlfile = readDMLMatrixFromHDFS(file);
				rfile = readRMatrixFromFS(file);
			}
			TestUtils.compareMatrices(dmlfile, rfile, eps, file+"-DML", file+"-R");
		}
	}
	
	@Test
	public void testPearsonRWithWeights() {

		TestConfiguration config = getTestConfiguration(TEST_SCALE_SCALE_WEIGHTS);
		config.addVariable("rows", rows);
		loadTestConfiguration(config);

		/* This is for running the junit test the new way, i.e., construct the arguments directly */
		String SS_HOME = SCRIPT_DIR + TEST_DIR;
		fullDMLScriptName = SS_HOME + TEST_SCALE_SCALE_WEIGHTS + ".dml";
		programArgs = new String[]{"-args",  input("X"),
			Integer.toString(rows), input("Y"), input("WM"), output("PearsonR") };
		
		fullRScriptName = SS_HOME + TEST_SCALE_SCALE_WEIGHTS + ".R";
		rCmd = "Rscript" + " " + fullRScriptName + " " + inputDir() + " " + expectedDir();

		double[][] X = getRandomMatrix(rows, 1, minVal, maxVal, 0.1, System.currentTimeMillis());
		double[][] Y = getRandomMatrix(rows, 1, minVal, maxVal, 0.1, System.currentTimeMillis());
		double[][] WM = getRandomMatrix(rows, 1, 1, maxW, 1, System.currentTimeMillis());
		TestUtils.floor(WM);

		writeInputMatrix("X", X, true);
		writeInputMatrix("Y", Y, true);
		writeInputMatrix("WM", WM, true);
		createHelperMatrix();
		
		boolean exceptionExpected = false;
		/*
		 * Expected number of jobs:
		 * Mean etc - 2 jobs (reblock & gmr)
		 * Cov etc - 2 jobs
		 * Final output write - 1 job
		 */
		//int expectedNumberOfJobs = 6;
		runTest(true, exceptionExpected, null, -1);
		runRScript(true);
		
		for(String file: config.getOutputFiles())
		{
			/* NOte that some files do not contain matrix, but just a single scalar value inside */
			HashMap<CellIndex, Double> dmlfile;
			HashMap<CellIndex, Double> rfile;
			if (file.endsWith(".scalar")) {
				file = file.replace(".scalar", "");
				dmlfile = readDMLScalarFromHDFS(file);
				rfile = readRScalarFromFS(file);
			}
			else {
				dmlfile = readDMLMatrixFromHDFS(file);
				rfile = readRMatrixFromFS(file);
			}
			TestUtils.compareMatrices(dmlfile, rfile, eps, file+"-DML", file+"-R");
		}

	}
	
}