| # ------------------------------------------------------------- |
| # |
| # 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. |
| # |
| # ------------------------------------------------------------- |
| |
| |
| import unittest |
| |
| import numpy as np |
| from systemds.context import SystemDSContext |
| from systemds.matrix import Matrix |
| |
| dim = 5 |
| np.random.seed(7) |
| m1 = np.array(np.random.randint(100, size=dim * dim) + 1.01, dtype=np.double) |
| m1.shape = (dim, dim) |
| m2 = np.array(np.random.randint(5, size=dim * dim) + 1, dtype=np.double) |
| m2.shape = (dim, dim) |
| s = 3.02 |
| |
| |
| class TestBinaryOp(unittest.TestCase): |
| |
| sds: SystemDSContext = None |
| |
| @classmethod |
| def setUpClass(cls): |
| cls.sds = SystemDSContext() |
| |
| @classmethod |
| def tearDownClass(cls): |
| cls.sds.close() |
| |
| def test_plus(self): |
| self.assertTrue(np.allclose( |
| (Matrix(self.sds, m1) + Matrix(self.sds, m2)).compute(), m1 + m2)) |
| |
| def test_minus(self): |
| self.assertTrue(np.allclose( |
| (Matrix(self.sds, m1) - Matrix(self.sds, m2)).compute(), m1 - m2)) |
| |
| def test_mul(self): |
| self.assertTrue(np.allclose( |
| (Matrix(self.sds, m1) * Matrix(self.sds, m2)).compute(), m1 * m2)) |
| |
| def test_div(self): |
| self.assertTrue(np.allclose( |
| (Matrix(self.sds, m1) / Matrix(self.sds, m2)).compute(), m1 / m2)) |
| |
| # TODO arithmetic with numpy rhs |
| |
| # TODO arithmetic with numpy lhs |
| |
| def test_plus3(self): |
| self.assertTrue(np.allclose( |
| (Matrix(self.sds, m1) + s).compute(), m1 + s)) |
| |
| def test_minus3(self): |
| self.assertTrue(np.allclose( |
| (Matrix(self.sds, m1) - s).compute(), m1 - s)) |
| |
| def test_mul3(self): |
| self.assertTrue(np.allclose( |
| (Matrix(self.sds, m1) * s).compute(), m1 * s)) |
| |
| def test_div3(self): |
| self.assertTrue(np.allclose( |
| (Matrix(self.sds, m1) / s).compute(), m1 / s)) |
| |
| def test_matmul(self): |
| self.assertTrue(np.allclose( |
| (Matrix(self.sds, m1) @ Matrix(self.sds, m2)).compute(), m1.dot(m2))) |
| |
| # TODO arithmetic with scala lhs |
| |
| def test_lt(self): |
| self.assertTrue(np.allclose( |
| (Matrix(self.sds, m1) < Matrix(self.sds, m2)).compute(), m1 < m2)) |
| |
| def test_gt(self): |
| self.assertTrue(np.allclose( |
| (Matrix(self.sds, m1) > Matrix(self.sds, m2)).compute(), m1 > m2)) |
| |
| def test_le(self): |
| self.assertTrue(np.allclose( |
| (Matrix(self.sds, m1) <= Matrix(self.sds, m2)).compute(), m1 <= m2)) |
| |
| def test_ge(self): |
| self.assertTrue(np.allclose( |
| (Matrix(self.sds, m1) >= Matrix(self.sds, m2)).compute(), m1 >= m2)) |
| |
| def test_abs(self): |
| self.assertTrue(np.allclose( |
| Matrix(self.sds, m1).abs().compute(), np.abs(m1))) |
| |
| |
| if __name__ == "__main__": |
| unittest.main(exit=False) |