| # ------------------------------------------------------------- |
| # |
| # 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 random |
| |
| import numpy as np |
| from systemds.context import SystemDSContext |
| from systemds.matrix import Matrix |
| |
| np.random.seed(7) |
| |
| shape = (random.randrange(1, 25), random.randrange(1, 25)) |
| m = np.random.rand(shape[0], shape[1]) |
| mx = np.random.rand(1, shape[1]) |
| my = np.random.rand(shape[0], 1) |
| by = random.randrange(1, np.size(m, 1)+1) |
| |
| class TestOrder(unittest.TestCase): |
| |
| sds: SystemDSContext = None |
| |
| @classmethod |
| def setUpClass(cls): |
| cls.sds = SystemDSContext() |
| |
| @classmethod |
| def tearDownClass(cls): |
| cls.sds.close() |
| |
| def test_basic(self): |
| o = Matrix(self.sds, m).order(by=by, decreasing=False, index_return=False).compute() |
| s = m[np.argsort(m[:, by-1])] |
| self.assertTrue(np.allclose(o, s)) |
| |
| def test_index(self): |
| o = Matrix(self.sds, m).order(by=by, decreasing=False, index_return=True).compute() |
| s = np.argsort(m[:, by - 1]) + 1 |
| self.assertTrue(np.allclose(np.transpose(o), s)) |
| |
| def test_out_of_bounds(self): |
| by_max = np.size(m, 1) + 2 |
| with self.assertRaises(IndexError) as context: |
| Matrix(self.sds, m).order(by=by_max).compute() |
| |
| def test_decreasing(self): |
| o = Matrix(self.sds, m).order(by=by, decreasing=True, index_return=True).compute() |
| s = np.argsort(-m[:, by - 1]) + 1 |
| self.assertTrue(np.allclose(np.transpose(o), s)) |
| |
| |
| if __name__ == "__main__": |
| unittest.main(exit=False) |