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* Licensed to the Apache Software Foundation (ASF) under one
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* 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,
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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.ExecMode;
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)
@net.jcip.annotations.NotThreadSafe
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(){
ExecMode platformOld = setExecMode(ExecMode.HYBRID);
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");
}
finally {
resetExecMode(platformOld);
}
}
}