| /* |
| * 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.ArrayList; |
| import java.util.Arrays; |
| import java.util.Collection; |
| import java.util.HashMap; |
| import java.util.List; |
| |
| import org.junit.Test; |
| import org.junit.runner.RunWith; |
| import org.junit.runners.Parameterized; |
| import org.junit.runners.Parameterized.Parameters; |
| import org.apache.sysds.runtime.matrix.data.MatrixValue.CellIndex; |
| import org.apache.sysds.test.AutomatedTestBase; |
| import org.apache.sysds.test.TestUtils; |
| |
| @RunWith(value = Parameterized.class) |
| @net.jcip.annotations.NotThreadSafe |
| public class NaiveBayesTest extends AutomatedTestBase{ |
| |
| protected final static String TEST_DIR = "applications/naive-bayes/"; |
| protected final static String TEST_NAME = "naive-bayes"; |
| protected String TEST_CLASS_DIR = TEST_DIR + NaiveBayesTest.class.getSimpleName() + "/"; |
| |
| protected int numRecords, numFeatures, numClasses; |
| protected double sparsity; |
| |
| public NaiveBayesTest(int rows, int cols, int nc, double sp) { |
| numRecords = rows; |
| numFeatures = cols; |
| numClasses = nc; |
| sparsity = sp; |
| } |
| |
| @Parameters |
| public static Collection<Object[]> data() { |
| Object[][] data = new Object[][] { |
| //sparse tests (sparsity=0.01) |
| {100, 50, 10, 0.01}, // example running time: 3.5s (dml: .3s) |
| {1000, 500, 10, 0.01}, // example running time: 5s (dml: .8s) |
| {10000, 750, 10, 0.01}, // example running time: 32s (dml: .7s) |
| //{100000, 1000, 10, 0.01}, // example running time: 471s (dml: 3s) |
| //dense tests (sparsity=0.7) |
| {100, 50, 10, 0.7}, // example running time: 2s (dml: .2s) |
| {1000, 500, 10, 0.7}, // example running time: 6s (dml: .7s) |
| {10000, 750, 10, 0.7} // example running time: 61s (dml: 5.6s) |
| }; |
| return Arrays.asList(data); |
| } |
| |
| @Override |
| public void setUp() { |
| addTestConfiguration(TEST_CLASS_DIR, TEST_NAME); |
| } |
| |
| @Test |
| public void testNaiveBayes() |
| { |
| System.out.println("------------ BEGIN " + TEST_NAME + " TEST {" + numRecords + ", " |
| + numFeatures + ", " + numClasses + ", " + sparsity + "} ------------"); |
| |
| int rows = numRecords; |
| int cols = numFeatures; |
| int classes = numClasses; |
| double sparsity = this.sparsity; |
| double laplace_correction = 1; |
| |
| getAndLoadTestConfiguration(TEST_NAME); |
| |
| List<String> proArgs = new ArrayList<>(); |
| proArgs.add("-stats"); |
| proArgs.add("-nvargs"); |
| proArgs.add("X=" + input("X")); |
| proArgs.add("Y=" + input("Y")); |
| proArgs.add("classes=" + classes); |
| proArgs.add("laplace=" + laplace_correction); |
| proArgs.add("prior=" + output("prior")); |
| proArgs.add("conditionals=" + output("conditionals")); |
| proArgs.add("accuracy=" + output("accuracy")); |
| programArgs = proArgs.toArray(new String[proArgs.size()]); |
| |
| fullDMLScriptName = getScript(); |
| |
| rCmd = getRCmd(inputDir(), Integer.toString(classes), Double.toString(laplace_correction), expectedDir()); |
| |
| double[][] X = getRandomMatrix(rows, cols, 0, 1, sparsity, -1); |
| double[][] Y = getRandomMatrix(rows, 1, 0, 1, 1, -1); |
| for(int i=0; i<rows; i++){ |
| Y[i][0] = (int)(Y[i][0]*classes) + 1; |
| Y[i][0] = (Y[i][0] > classes) ? classes : Y[i][0]; |
| } |
| |
| writeInputMatrixWithMTD("X", X, true); |
| writeInputMatrixWithMTD("Y", Y, true); |
| |
| runTest(true, EXCEPTION_NOT_EXPECTED, null, -1); |
| |
| runRScript(true); |
| |
| HashMap<CellIndex, Double> priorR = readRMatrixFromFS("prior"); |
| HashMap<CellIndex, Double> priorSYSTEMDS= readDMLMatrixFromHDFS("prior"); |
| HashMap<CellIndex, Double> conditionalsR = readRMatrixFromFS("conditionals"); |
| HashMap<CellIndex, Double> conditionalsSYSTEMDS = readDMLMatrixFromHDFS("conditionals"); |
| TestUtils.compareMatrices(priorR, priorSYSTEMDS, Math.pow(10, -12), "priorR", "priorSYSTEMDS"); |
| TestUtils.compareMatrices(conditionalsR, conditionalsSYSTEMDS, Math.pow(10.0, -12.0), "conditionalsR", "conditionalsSYSTEMDS"); |
| } |
| } |