| # ------------------------------------------------------------- |
| # |
| # 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 |
| |
| m1 = np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12], [13, 14, 15, 16]]) |
| |
| m2 = np.random.random((10, 10)) |
| |
| |
| class TestTRIANGULAR(unittest.TestCase): |
| def setUp(self): |
| self.sds = SystemDSContext(capture_stdout=True, logging_level=50) |
| |
| def tearDown(self): |
| self.sds.close() |
| |
| def test_triu_basic1(self): |
| sds_input = self.sds.from_numpy(m1) |
| sds_result = sds_input.triu().compute() |
| np_result = np.triu(m1) |
| assert np.allclose(sds_result, np_result, 1e-9) |
| |
| def test_triu_basic2(self): |
| sds_input = self.sds.from_numpy(m1) |
| sds_result = sds_input.triu(include_diagonal=False).compute() |
| np_result = np.triu(m1, 1) |
| assert np.allclose(sds_result, np_result, 1e-9) |
| |
| def test_triu_basic3(self): |
| sds_input = self.sds.from_numpy(m1) |
| sds_result = sds_input.triu(return_values=False).compute() |
| np_result = np.triu(m1) > 0 |
| assert np.allclose(sds_result, np_result, 1e-9) |
| |
| def test_triu_basic4(self): |
| sds_input = self.sds.from_numpy(m1) |
| sds_result = sds_input.triu( |
| return_values=False, include_diagonal=False |
| ).compute() |
| np_result = np.triu(m1, 1) > 0 |
| assert np.allclose(sds_result, np_result, 1e-9) |
| |
| def test_triu_random(self): |
| sds_input = self.sds.from_numpy(m2) |
| sds_result = sds_input.triu().compute() |
| np_result = np.triu(m2) |
| assert np.allclose(sds_result, np_result, 1e-9) |
| |
| def test_tril_basic1(self): |
| sds_input = self.sds.from_numpy(m1) |
| sds_result = sds_input.tril().compute() |
| np_result = np.tril(m1) |
| assert np.allclose(sds_result, np_result, 1e-9) |
| |
| def test_tril_basic2(self): |
| sds_input = self.sds.from_numpy(m1) |
| sds_result = sds_input.tril(include_diagonal=False).compute() |
| np_result = np.tril(m1, -1) |
| assert np.allclose(sds_result, np_result, 1e-9) |
| |
| def test_tril_basic3(self): |
| sds_input = self.sds.from_numpy(m1) |
| sds_result = sds_input.tril(return_values=False).compute() |
| np_result = np.tril(m1) > 0 |
| assert np.allclose(sds_result, np_result, 1e-9) |
| |
| def test_tril_basic4(self): |
| sds_input = self.sds.from_numpy(m1) |
| sds_result = sds_input.tril( |
| return_values=False, include_diagonal=False |
| ).compute() |
| np_result = np.tril(m1, -1) > 0 |
| assert np.allclose(sds_result, np_result, 1e-9) |
| |
| def test_tril_random(self): |
| sds_input = self.sds.from_numpy(m2) |
| sds_result = sds_input.tril().compute() |
| np_result = np.tril(m2) |
| assert np.allclose(sds_result, np_result, 1e-9) |
| |
| |
| if __name__ == "__main__": |
| unittest.main() |