| /* |
| * 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.io.csv; |
| |
| import java.util.Arrays; |
| import java.util.Collection; |
| |
| import org.apache.sysds.common.Types.ExecMode; |
| import org.apache.sysds.runtime.meta.MatrixCharacteristics; |
| import org.apache.sysds.test.TestConfiguration; |
| import org.apache.sysds.test.TestUtils; |
| import org.junit.Test; |
| import org.junit.runner.RunWith; |
| import org.junit.runners.Parameterized; |
| import org.junit.runners.Parameterized.Parameters; |
| |
| @RunWith(value = Parameterized.class) |
| @net.jcip.annotations.NotThreadSafe |
| public class CSVParametersTest extends CSVTestBase { |
| |
| private final static String TEST_NAME = "csvprop_test"; |
| private final static String TEST_CLASS_DIR = TEST_DIR + CSVParametersTest.class.getSimpleName() + "/"; |
| |
| private final static int rows = 1200; |
| private final static int cols = 100; |
| private static double sparsity = 0.1; |
| |
| private boolean _header = false; |
| private String _delim = ","; |
| private boolean _sparse = true; |
| |
| public CSVParametersTest(boolean header, String delim, boolean sparse) { |
| _header = header; |
| _delim = delim; |
| _sparse = sparse; |
| } |
| |
| @Parameters |
| public static Collection<Object[]> data() { |
| Object[][] data = new Object[][] { |
| // header sep sparse |
| {false, ",", true}, {false, ",", false}, {true, ",", true}, {true, ",", false}, {false, "|.", true}, |
| {false, "|.", false}, {true, "|.", true}, {true, "|.", false}}; |
| |
| return Arrays.asList(data); |
| } |
| |
| private void setup() { |
| |
| TestConfiguration config = getTestConfiguration(TEST_NAME); |
| config.addVariable("w_header", _header); |
| config.addVariable("w_delim", _delim); |
| config.addVariable("w_sparse", _sparse); |
| |
| loadTestConfiguration(config); |
| } |
| |
| @Test |
| public void testCSVParametersSparseCP() { |
| setup(); |
| sparsity = 0.1; |
| |
| ExecMode old_platform = rtplatform; |
| |
| rtplatform = ExecMode.SINGLE_NODE; |
| csvParameterTest(rtplatform, sparsity); |
| |
| rtplatform = old_platform; |
| } |
| |
| @Test |
| public void testCSVParametersDenseCP() { |
| setup(); |
| sparsity = 1.0; |
| |
| ExecMode old_platform = rtplatform; |
| |
| rtplatform = ExecMode.SINGLE_NODE; |
| csvParameterTest(rtplatform, sparsity); |
| |
| rtplatform = old_platform; |
| } |
| |
| @Test |
| public void testCSVParametersSparseHybrid() { |
| setup(); |
| sparsity = 0.1; |
| |
| ExecMode old_platform = rtplatform; |
| |
| rtplatform = ExecMode.HYBRID; |
| csvParameterTest(rtplatform, sparsity); |
| |
| rtplatform = old_platform; |
| } |
| |
| @Test |
| public void testCSVParametersDenseHybrid() { |
| setup(); |
| sparsity = 1.0; |
| |
| ExecMode old_platform = rtplatform; |
| |
| rtplatform = ExecMode.HYBRID; |
| csvParameterTest(rtplatform, sparsity); |
| |
| rtplatform = old_platform; |
| } |
| |
| private void csvParameterTest(ExecMode platform, double sp) { |
| |
| // generate actual dataset |
| double[][] D = getRandomMatrix(rows, cols, 0, 1, sp, 7777); |
| MatrixCharacteristics mc = new MatrixCharacteristics(rows, cols, -1, -1); |
| writeInputMatrixWithMTD("D", D, true, mc); |
| D = null; |
| |
| String HOME = SCRIPT_DIR + TEST_DIR; |
| String txtFile = input("D"); |
| // String binFile = input("D.binary"); |
| String csvFile = output("D.csv"); |
| String scalarFile = output("diff.scalar"); |
| |
| String writeDML = HOME + "csvprop_write.dml"; |
| String[] writeArgs = new String[] {"-args", txtFile, csvFile, Boolean.toString(_header).toUpperCase(), _delim, |
| Boolean.toString(_sparse).toUpperCase()}; |
| |
| String readDML = HOME + "csvprop_read.dml"; |
| String[] readArgs = new String[] {"-args", txtFile, csvFile, Boolean.toString(_header).toUpperCase(), _delim, |
| Boolean.toString(_sparse).toUpperCase(), Double.toString(0.0), scalarFile}; |
| |
| // System.out.println("Text -> CSV"); |
| // Text -> CSV |
| fullDMLScriptName = writeDML; |
| programArgs = writeArgs; |
| runTest(true, false, null, -1); |
| |
| // Evaluate the written CSV file |
| // System.out.println("CSV -> SCALAR"); |
| fullDMLScriptName = readDML; |
| programArgs = readArgs; |
| // boolean exceptionExpected = (!_sparse && sparsity < 1.0); |
| runTest(true, false, null, -1); |
| |
| double dmlScalar = TestUtils.readDMLScalar(scalarFile); |
| TestUtils.compareScalars(dmlScalar, 0.0, eps); |
| } |
| |
| protected String getTestName() { |
| return TEST_NAME; |
| } |
| |
| protected String getTestClassDir() { |
| return TEST_CLASS_DIR; |
| } |
| } |