Arjun P | 10a898b3 | 2020-07-02 19:18:18 +0530 | [diff] [blame] | 1 | //===- MatrixTest.cpp - Tests for Matrix ----------------------------------===// |
| 2 | // |
| 3 | // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. |
| 4 | // See https://llvm.org/LICENSE.txt for license information. |
| 5 | // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception |
| 6 | // |
| 7 | //===----------------------------------------------------------------------===// |
| 8 | |
| 9 | #include "mlir/Analysis/Presburger/Matrix.h" |
| 10 | #include <gmock/gmock.h> |
| 11 | #include <gtest/gtest.h> |
| 12 | |
| 13 | namespace mlir { |
| 14 | |
| 15 | TEST(MatrixTest, ReadWrite) { |
| 16 | Matrix mat(5, 5); |
| 17 | for (unsigned row = 0; row < 5; ++row) |
| 18 | for (unsigned col = 0; col < 5; ++col) |
| 19 | mat(row, col) = 10 * row + col; |
| 20 | for (unsigned row = 0; row < 5; ++row) |
| 21 | for (unsigned col = 0; col < 5; ++col) |
| 22 | EXPECT_EQ(mat(row, col), int(10 * row + col)); |
| 23 | } |
| 24 | |
| 25 | TEST(MatrixTest, SwapColumns) { |
| 26 | Matrix mat(5, 5); |
| 27 | for (unsigned row = 0; row < 5; ++row) |
| 28 | for (unsigned col = 0; col < 5; ++col) |
| 29 | mat(row, col) = col == 3 ? 1 : 0; |
| 30 | mat.swapColumns(3, 1); |
| 31 | for (unsigned row = 0; row < 5; ++row) |
| 32 | for (unsigned col = 0; col < 5; ++col) |
| 33 | EXPECT_EQ(mat(row, col), col == 1 ? 1 : 0); |
| 34 | |
| 35 | // swap around all the other columns, swap (1, 3) twice for no effect. |
| 36 | mat.swapColumns(3, 1); |
| 37 | mat.swapColumns(2, 4); |
| 38 | mat.swapColumns(1, 3); |
| 39 | mat.swapColumns(0, 4); |
| 40 | mat.swapColumns(2, 2); |
| 41 | |
| 42 | for (unsigned row = 0; row < 5; ++row) |
| 43 | for (unsigned col = 0; col < 5; ++col) |
| 44 | EXPECT_EQ(mat(row, col), col == 1 ? 1 : 0); |
| 45 | } |
| 46 | |
| 47 | TEST(MatrixTest, SwapRows) { |
| 48 | Matrix mat(5, 5); |
| 49 | for (unsigned row = 0; row < 5; ++row) |
| 50 | for (unsigned col = 0; col < 5; ++col) |
| 51 | mat(row, col) = row == 2 ? 1 : 0; |
| 52 | mat.swapRows(2, 0); |
| 53 | for (unsigned row = 0; row < 5; ++row) |
| 54 | for (unsigned col = 0; col < 5; ++col) |
| 55 | EXPECT_EQ(mat(row, col), row == 0 ? 1 : 0); |
| 56 | |
| 57 | // swap around all the other rows, swap (2, 0) twice for no effect. |
| 58 | mat.swapRows(3, 4); |
| 59 | mat.swapRows(1, 4); |
| 60 | mat.swapRows(2, 0); |
| 61 | mat.swapRows(1, 1); |
| 62 | mat.swapRows(0, 2); |
| 63 | |
| 64 | for (unsigned row = 0; row < 5; ++row) |
| 65 | for (unsigned col = 0; col < 5; ++col) |
| 66 | EXPECT_EQ(mat(row, col), row == 0 ? 1 : 0); |
| 67 | } |
| 68 | |
| 69 | TEST(MatrixTest, resizeVertically) { |
| 70 | Matrix mat(5, 5); |
| 71 | EXPECT_EQ(mat.getNumRows(), 5u); |
| 72 | EXPECT_EQ(mat.getNumColumns(), 5u); |
| 73 | for (unsigned row = 0; row < 5; ++row) |
| 74 | for (unsigned col = 0; col < 5; ++col) |
| 75 | mat(row, col) = 10 * row + col; |
| 76 | |
| 77 | mat.resizeVertically(3); |
Arjun P | c605dfc | 2021-07-01 20:12:56 +0530 | [diff] [blame] | 78 | ASSERT_TRUE(mat.hasConsistentState()); |
Arjun P | 10a898b3 | 2020-07-02 19:18:18 +0530 | [diff] [blame] | 79 | EXPECT_EQ(mat.getNumRows(), 3u); |
| 80 | EXPECT_EQ(mat.getNumColumns(), 5u); |
| 81 | for (unsigned row = 0; row < 3; ++row) |
| 82 | for (unsigned col = 0; col < 5; ++col) |
| 83 | EXPECT_EQ(mat(row, col), int(10 * row + col)); |
| 84 | |
| 85 | mat.resizeVertically(5); |
Arjun P | c605dfc | 2021-07-01 20:12:56 +0530 | [diff] [blame] | 86 | ASSERT_TRUE(mat.hasConsistentState()); |
Arjun P | 10a898b3 | 2020-07-02 19:18:18 +0530 | [diff] [blame] | 87 | EXPECT_EQ(mat.getNumRows(), 5u); |
| 88 | EXPECT_EQ(mat.getNumColumns(), 5u); |
| 89 | for (unsigned row = 0; row < 5; ++row) |
| 90 | for (unsigned col = 0; col < 5; ++col) |
| 91 | EXPECT_EQ(mat(row, col), row >= 3 ? 0 : int(10 * row + col)); |
| 92 | } |
| 93 | |
Arjun P | c605dfc | 2021-07-01 20:12:56 +0530 | [diff] [blame] | 94 | TEST(MatrixTest, insertColumns) { |
| 95 | Matrix mat(5, 5, 5, 10); |
| 96 | EXPECT_EQ(mat.getNumRows(), 5u); |
| 97 | EXPECT_EQ(mat.getNumColumns(), 5u); |
| 98 | for (unsigned row = 0; row < 5; ++row) |
| 99 | for (unsigned col = 0; col < 5; ++col) |
| 100 | mat(row, col) = 10 * row + col; |
| 101 | |
| 102 | mat.insertColumns(3, 100); |
| 103 | ASSERT_TRUE(mat.hasConsistentState()); |
| 104 | EXPECT_EQ(mat.getNumRows(), 5u); |
| 105 | EXPECT_EQ(mat.getNumColumns(), 105u); |
| 106 | for (unsigned row = 0; row < 5; ++row) { |
| 107 | for (unsigned col = 0; col < 105; ++col) { |
| 108 | if (col < 3) |
| 109 | EXPECT_EQ(mat(row, col), int(10 * row + col)); |
| 110 | else if (3 <= col && col <= 102) |
| 111 | EXPECT_EQ(mat(row, col), 0); |
| 112 | else |
| 113 | EXPECT_EQ(mat(row, col), int(10 * row + col - 100)); |
| 114 | } |
| 115 | } |
| 116 | |
| 117 | mat.removeColumns(3, 100); |
| 118 | ASSERT_TRUE(mat.hasConsistentState()); |
| 119 | mat.insertColumns(0, 0); |
| 120 | ASSERT_TRUE(mat.hasConsistentState()); |
| 121 | mat.insertColumn(5); |
| 122 | ASSERT_TRUE(mat.hasConsistentState()); |
| 123 | |
| 124 | EXPECT_EQ(mat.getNumRows(), 5u); |
| 125 | EXPECT_EQ(mat.getNumColumns(), 6u); |
| 126 | for (unsigned row = 0; row < 5; ++row) |
| 127 | for (unsigned col = 0; col < 6; ++col) |
| 128 | EXPECT_EQ(mat(row, col), col == 5 ? 0 : 10 * row + col); |
| 129 | } |
| 130 | |
| 131 | TEST(MatrixTest, insertRows) { |
| 132 | Matrix mat(5, 5, 5, 10); |
| 133 | ASSERT_TRUE(mat.hasConsistentState()); |
| 134 | EXPECT_EQ(mat.getNumRows(), 5u); |
| 135 | EXPECT_EQ(mat.getNumColumns(), 5u); |
| 136 | for (unsigned row = 0; row < 5; ++row) |
| 137 | for (unsigned col = 0; col < 5; ++col) |
| 138 | mat(row, col) = 10 * row + col; |
| 139 | |
| 140 | mat.insertRows(3, 100); |
| 141 | ASSERT_TRUE(mat.hasConsistentState()); |
| 142 | EXPECT_EQ(mat.getNumRows(), 105u); |
| 143 | EXPECT_EQ(mat.getNumColumns(), 5u); |
| 144 | for (unsigned row = 0; row < 105; ++row) { |
| 145 | for (unsigned col = 0; col < 5; ++col) { |
| 146 | if (row < 3) |
| 147 | EXPECT_EQ(mat(row, col), int(10 * row + col)); |
| 148 | else if (3 <= row && row <= 102) |
| 149 | EXPECT_EQ(mat(row, col), 0); |
| 150 | else |
| 151 | EXPECT_EQ(mat(row, col), int(10 * (row - 100) + col)); |
| 152 | } |
| 153 | } |
| 154 | |
| 155 | mat.removeRows(3, 100); |
| 156 | ASSERT_TRUE(mat.hasConsistentState()); |
| 157 | mat.insertRows(0, 0); |
| 158 | ASSERT_TRUE(mat.hasConsistentState()); |
| 159 | mat.insertRow(5); |
| 160 | ASSERT_TRUE(mat.hasConsistentState()); |
| 161 | |
| 162 | EXPECT_EQ(mat.getNumRows(), 6u); |
| 163 | EXPECT_EQ(mat.getNumColumns(), 5u); |
| 164 | for (unsigned row = 0; row < 6; ++row) |
| 165 | for (unsigned col = 0; col < 5; ++col) |
| 166 | EXPECT_EQ(mat(row, col), row == 5 ? 0 : 10 * row + col); |
| 167 | } |
| 168 | |
Arjun P | f263ea1 | 2021-09-17 13:14:50 +0530 | [diff] [blame] | 169 | TEST(MatrixTest, resize) { |
| 170 | Matrix mat(5, 5); |
| 171 | EXPECT_EQ(mat.getNumRows(), 5u); |
| 172 | EXPECT_EQ(mat.getNumColumns(), 5u); |
| 173 | for (unsigned row = 0; row < 5; ++row) |
| 174 | for (unsigned col = 0; col < 5; ++col) |
| 175 | mat(row, col) = 10 * row + col; |
| 176 | |
| 177 | mat.resize(3, 3); |
| 178 | ASSERT_TRUE(mat.hasConsistentState()); |
| 179 | EXPECT_EQ(mat.getNumRows(), 3u); |
| 180 | EXPECT_EQ(mat.getNumColumns(), 3u); |
| 181 | for (unsigned row = 0; row < 3; ++row) |
| 182 | for (unsigned col = 0; col < 3; ++col) |
| 183 | EXPECT_EQ(mat(row, col), int(10 * row + col)); |
| 184 | |
| 185 | mat.resize(7, 7); |
| 186 | ASSERT_TRUE(mat.hasConsistentState()); |
| 187 | EXPECT_EQ(mat.getNumRows(), 7u); |
| 188 | EXPECT_EQ(mat.getNumColumns(), 7u); |
| 189 | for (unsigned row = 0; row < 7; ++row) |
| 190 | for (unsigned col = 0; col < 7; ++col) |
| 191 | EXPECT_EQ(mat(row, col), row >= 3 || col >= 3 ? 0 : int(10 * row + col)); |
| 192 | } |
| 193 | |
Arjun P | 10a898b3 | 2020-07-02 19:18:18 +0530 | [diff] [blame] | 194 | } // namespace mlir |