| # ------------------------------------------------------------- |
| # |
| # 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 |
| import pandas as pd |
| from systemds.context import SystemDSContext |
| |
| df = pd.DataFrame( |
| { |
| "col1": ["col1_hello_3", "col1_world_3", "col1_hello_3"], |
| "col2": [6, 7, 8], |
| "col3": [0.6, 0.7, 0.8], |
| } |
| ) |
| |
| |
| class TestFederatedAggFn(unittest.TestCase): |
| |
| sds: SystemDSContext = None |
| |
| @classmethod |
| def setUpClass(cls): |
| cls.sds = SystemDSContext(capture_stdout=True, logging_level=50) |
| |
| @classmethod |
| def tearDownClass(cls): |
| cls.sds.close() |
| |
| def test_setup(self): |
| sm = self.sds.from_pandas(df) |
| sr = sm.compute() |
| self.assertTrue(isinstance(sr, pd.DataFrame)) |
| e = df |
| self.assertTrue((e.values == sr.values).all()) |
| |
| def test_slice_first_third_row(self): |
| sm = self.sds.from_pandas(df)[[0, 2]] |
| sr = sm.compute() |
| e = df.loc[[0, 2]] |
| self.assertTrue((e.values == sr.values).all()) |
| |
| def test_slice_single_row(self): |
| sm = self.sds.from_pandas(df)[[1]] |
| sr = sm.compute() |
| e = df.loc[[1]] |
| self.assertTrue((e.values == sr.values).all()) |
| |
| def test_slice_last_row(self): |
| with self.assertRaises(ValueError): |
| self.sds.from_pandas(df)[[-1]] |
| |
| # def test_slice_first_third_col(self): |
| # sm = self.sds.from_pandas(df)[:, [0, 2]] |
| # sr = sm.compute() |
| # e = pd.DataFrame( |
| # { |
| # "col1": ["col1_hello_3", "col1_world_3", "col1_hello_3"], |
| # "col3": [0.6, 0.7, 0.8], |
| # } |
| # ) |
| # self.assertTrue((e.values == sr.values).all()) |
| |
| # def test_slice_single_col(self): |
| # sm = self.sds.from_pandas(df)[:, [1]] |
| # sr = sm.compute() |
| # e = pd.DataFrame( |
| # { |
| # "col2": [6, 7, 8] |
| # } |
| # ) |
| # self.assertTrue((e.values == sr.values).all()) |
| |
| def test_slice_row_col_both(self): |
| with self.assertRaises(NotImplementedError): |
| self.sds.from_pandas(df)[[1, 2], [0, 2]] |
| |
| |
| if __name__ == "__main__": |
| unittest.main(exit=False) |