| /* |
| * 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.builtin; |
| |
| import java.util.Arrays; |
| import java.util.Collection; |
| import java.util.HashMap; |
| |
| import org.junit.Test; |
| import org.apache.sysds.common.Types; |
| import org.apache.sysds.lops.LopProperties; |
| 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.runtime.meta.MatrixCharacteristics; |
| import org.apache.sysds.test.AutomatedTestBase; |
| import org.apache.sysds.test.TestConfiguration; |
| import org.apache.sysds.test.TestUtils; |
| |
| @RunWith(value = Parameterized.class) |
| public class BuiltinArimaTest extends AutomatedTestBase { |
| private final static String TEST_NAME = "arima"; |
| private final static String TEST_DIR = "functions/builtin/"; |
| private static final String TEST_CLASS_DIR = TEST_DIR + BuiltinArimaTest.class.getSimpleName() + "/"; |
| |
| protected int max_func_invoc, p, d, q, P, D, Q, s, include_mean, useJacobi; |
| |
| public BuiltinArimaTest(int m, int p, int d, int q, int P, int D, int Q, int s, int include_mean, int useJacobi){ |
| this.max_func_invoc = m; |
| this.p = p; |
| this.d = d; |
| this.q = q; |
| this.P = P; |
| this.D = D; |
| this.Q = Q; |
| this.s = s; |
| this.include_mean = include_mean; |
| this.useJacobi = useJacobi; |
| } |
| |
| @Parameters |
| public static Collection<Object[]> data() { |
| return Arrays.asList(new Object[][] { |
| {20, 1, 0, 0, 0, 0, 0, 24, 1, 1}, |
| {20, 0, 0, 1, 0, 0, 0, 24, 1, 1}, |
| {20, 2, 0, 1, 0, 0, 0, 24, 1, 1}, |
| |
| //TODO fix remaining configurations (e.g., differencing) |
| //{10, 1, 0, 10, 0, 0, 0, 24, 1, 1} |
| // {10, 1, 1, 2, 0, 0, 0, 24, 1, 1}, |
| // {10, 0, 1, 2, 0, 0, 0, 24, 1, 1}, |
| // {10, 0, 0, 0, 1, 1, 0, 24, 1, 1}, |
| // {10, 0, 0, 0, 1, 1, 2, 24, 1, 1}, |
| // {10, 0, 0, 0, 0, 1, 2, 24, 1, 1}} |
| }); |
| } |
| |
| @Override |
| public void setUp() { |
| addTestConfiguration(TEST_NAME, new TestConfiguration(TEST_CLASS_DIR, TEST_NAME, new String[]{"B"})); |
| } |
| |
| @Test |
| public void testArima(){ |
| Types.ExecMode platformOld = setExecMode(LopProperties.ExecType.CP); |
| try { |
| loadTestConfiguration(getTestConfiguration(TEST_NAME)); |
| String HOME = SCRIPT_DIR + TEST_DIR; |
| fullDMLScriptName = HOME + TEST_NAME + ".dml"; |
| fullRScriptName = HOME + TEST_NAME + ".R"; |
| |
| programArgs = new String[]{ |
| "-nvargs", "X=" + input("col.mtx"), "max_func_invoc=" + max_func_invoc, |
| "p=" + p, "d=" + d, "q=" + q, "P=" + P, "D=" + D, "Q=" + Q, |
| "s=" + s, "include_mean=" + include_mean, "useJacobi=" + useJacobi, |
| "model=" + output("learnt.model"),}; |
| |
| rCmd = getRCmd(input("col.mtx"), Integer.toString(max_func_invoc), Integer.toString(p), |
| Integer.toString(d), Integer.toString(q), Integer.toString(P), Integer.toString(D), |
| Integer.toString(Q), Integer.toString(s), Integer.toString(include_mean), |
| Integer.toString(useJacobi), expected("learnt.model")); |
| |
| int timeSeriesLength = 3000; |
| double[][] timeSeries = getRandomMatrix(timeSeriesLength, 1, 1, 5, 0.9, 54321); |
| |
| MatrixCharacteristics mc = new MatrixCharacteristics(timeSeriesLength,1,-1,-1); |
| writeInputMatrixWithMTD("col", timeSeries, true, mc); |
| |
| runTest(true, false, null, -1); |
| runRScript(true); |
| |
| double tol = Math.pow(10, -14); |
| HashMap<CellIndex, Double> arima_model_R = readRMatrixFromExpectedDir("learnt.model"); |
| HashMap<CellIndex, Double> arima_model_SYSTEMDS= readDMLMatrixFromOutputDir("learnt.model"); |
| TestUtils.compareMatrices(arima_model_R, arima_model_SYSTEMDS, tol, "arima_R", "arima_SYSTEMDS"); |
| } |
| catch(Exception ex) { |
| ex.printStackTrace(); |
| } |
| finally { |
| rtplatform = platformOld; |
| } |
| } |
| } |