| /* |
| * 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.component.compress.colgroup; |
| |
| import java.util.ArrayList; |
| import java.util.Collection; |
| |
| import org.apache.sysds.runtime.compress.colgroup.ColGroup.CompressionType; |
| import org.apache.sysds.runtime.matrix.data.MatrixBlock; |
| import org.apache.sysds.runtime.util.DataConverter; |
| import org.apache.sysds.test.TestUtils; |
| import org.apache.sysds.test.component.compress.CompressibleInputGenerator; |
| import org.junit.runner.RunWith; |
| import org.junit.runners.Parameterized; |
| import org.junit.runners.Parameterized.Parameters; |
| |
| @RunWith(value = Parameterized.class) |
| public class JolEstimateOLETest extends JolEstimateTest { |
| |
| @Parameters |
| public static Collection<Object[]> data() { |
| ArrayList<Object[]> tests = new ArrayList<>(); |
| |
| MatrixBlock mb; |
| // base tests |
| mb = DataConverter.convertToMatrixBlock(new double[][] {{1}}); |
| tests.add(new Object[] {mb, new int[]{1, 2, 2, 1}, 0}); |
| mb = DataConverter.convertToMatrixBlock(new double[][] {{0}}); |
| tests.add(new Object[] {mb, new int[]{0, 1, 0, 0}, 0}); |
| mb = DataConverter.convertToMatrixBlock(new double[][] {{0, 0, 0, 0, 0}}); |
| tests.add(new Object[] {mb, new int[]{0, 1, 0, 0}, 0}); |
| |
| // The size of the compression increase at repeated values. |
| mb = DataConverter.convertToMatrixBlock(new double[][] {{0, 0, 0, 0, 5, 0}}); |
| tests.add(new Object[] {mb, new int[]{1, 2, 2, 1}, 0}); |
| mb = DataConverter.convertToMatrixBlock(new double[][] {{0, 0, 0, 0, 5, 5, 0}}); |
| tests.add(new Object[] {mb, new int[]{1, 2, 3, 1}, 0}); |
| mb = DataConverter.convertToMatrixBlock(new double[][] {{0, 0, 0, 0, 5, 5, 5, 0}}); |
| tests.add(new Object[] {mb, new int[]{1, 2, 4, 1}, 0}); |
| mb = DataConverter.convertToMatrixBlock(new double[][] {{0, 0, 0, 0, 5, 5, 5, 5, 5, 5}}); |
| tests.add(new Object[] {mb, new int[]{1, 2, 7, 1}, 0}); |
| |
| // all values grow by 1 if new value is introduced |
| mb = DataConverter.convertToMatrixBlock(new double[][] {{0, 0, 0, 0, 5, 7, 0}}); |
| tests.add(new Object[] {mb, new int[]{2, 3, 4, 2}, 0}); |
| mb = DataConverter.convertToMatrixBlock(new double[][] {{0, 0, 0, 0, 5, 2, 1, 0}}); |
| tests.add(new Object[] {mb, new int[]{3, 4, 6, 3}, 0}); |
| mb = DataConverter.convertToMatrixBlock(new double[][] {{0, 0, 0, 0, 5, 2, 1, 3, 6, 7}}); |
| tests.add(new Object[] {mb, new int[]{6, 7, 12, 6}, 0}); |
| |
| // Dense random... Horrible compression |
| mb = DataConverter.convertToMatrixBlock(TestUtils.generateTestMatrix(1, 100, 0, 100, 1.0, 7)); |
| tests.add(new Object[] {mb, new int[]{100, 100 + 1, 200, 100}, 0}); |
| mb = DataConverter.convertToMatrixBlock(TestUtils.generateTestMatrix(1, 1000, 0, 100, 1.0, 7)); |
| tests.add(new Object[] {mb, new int[]{1000, 1000 + 1, 2000, 1000}, 0}); |
| mb = DataConverter.convertToMatrixBlock(TestUtils.generateTestMatrix(1, 10000, 0, 100, 1.0, 7)); |
| tests.add(new Object[] {mb, new int[]{10000, 10000 + 1, 20000, 10000}, 0}); |
| |
| // Random rounded numbers dense |
| mb = DataConverter.convertToMatrixBlock(TestUtils.round(TestUtils.generateTestMatrix(1, 1523, 0, 99, 1.0, 7))); |
| tests.add(new Object[] {mb, new int[]{99, 100, 1616, 99}, 0}); |
| mb = DataConverter.convertToMatrixBlock(TestUtils.round(TestUtils.generateTestMatrix(1, 4000, 0, 255, 1.0, 7))); |
| tests.add(new Object[] {mb, new int[]{255, 256, 4250, 255}, 0}); |
| |
| // Sparse rounded numbers |
| mb = DataConverter.convertToMatrixBlock(TestUtils.round(TestUtils.generateTestMatrix(1, 1523, 0, 99, 0.1, 7))); |
| tests.add(new Object[] {mb, new int[]{76, 77, 225, 76}, 0}); |
| mb = DataConverter |
| .convertToMatrixBlock(TestUtils.round(TestUtils.generateTestMatrix(1, 1621, 0, 99, 0.1, 142))); |
| tests.add(new Object[] {mb, new int[]{81, 82, 238, 81}, 0}); |
| mb = DataConverter |
| .convertToMatrixBlock(TestUtils.round(TestUtils.generateTestMatrix(1, 2321, 0, 99, 0.1, 512))); |
| tests.add(new Object[] {mb, new int[]{92, 93, 332, 92}, 0}); |
| mb = DataConverter.convertToMatrixBlock(TestUtils.round(TestUtils.generateTestMatrix(1, 4000, 0, 255, 0.1, 7))); |
| tests.add(new Object[] {mb, new int[]{195, 196, 573, 195}, 0}); |
| |
| mb = DataConverter.convertToMatrixBlock(TestUtils.round(TestUtils.generateTestMatrix(1, 1523, 0, 99, 0.5, 7))); |
| tests.add(new Object[] {mb, new int[]{98, 99, 826, 99}, 0}); |
| mb = DataConverter |
| .convertToMatrixBlock(TestUtils.round(TestUtils.generateTestMatrix(1, 1621, 0, 99, 0.5, 142))); |
| tests.add(new Object[] {mb, new int[]{99, 100, 913, 99}, 0}); |
| mb = DataConverter |
| .convertToMatrixBlock(TestUtils.round(TestUtils.generateTestMatrix(1, 2321, 0, 99, 0.5, 512))); |
| tests.add(new Object[] {mb, new int[]{99, 100, 1292, 99}, 0}); |
| mb = DataConverter.convertToMatrixBlock(TestUtils.round(TestUtils.generateTestMatrix(1, 4000, 0, 255, 0.5, 7))); |
| tests.add(new Object[] {mb, new int[]{255, 256, 2208, 255}, 0}); |
| |
| // Paper |
| mb = DataConverter |
| .convertToMatrixBlock(new double[][] {{7, 3, 7, 7, 3, 7, 3, 3, 7, 3}, {6, 4, 6, 5, 4, 5, 4, 4, 6, 4}}); |
| tests.add(new Object[] {mb, new int[]{6, 4, 13, 3}, 0}); |
| |
| // Dream Inputs |
| int[] cols = new int[]{2,6,111}; |
| int[] rows = new int[]{10,121,513}; |
| int[] unique = new int[]{3,5}; |
| for(int y : cols){ |
| for (int x : rows){ |
| for (int u : unique){ |
| mb = CompressibleInputGenerator.getInput(x, y, CompressionType.OLE, u, 1.0, 5); |
| tests.add(new Object[] {mb, new int[]{u * y, u + 1, x + u , u}, 0}); |
| } |
| } |
| } |
| |
| // Sparse test. |
| mb = CompressibleInputGenerator.getInput(571, 1, CompressionType.OLE, 40, 0.6, 5); |
| tests.add(new Object[] {mb, new int[]{40 * 1, 40 + 1, ((571 + 40) / 10 ) * 6 ,40}, 0}); |
| |
| return tests; |
| } |
| |
| public JolEstimateOLETest(MatrixBlock mb, int[] sizes, int tolerance) { |
| super(mb, sizes, tolerance); |
| } |
| |
| @Override |
| public CompressionType getCT() { |
| return ole; |
| } |
| } |