| # ------------------------------------------------------------- |
| # |
| # 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 json |
| import os |
| import shutil |
| import sys |
| import unittest |
| |
| import numpy as np |
| import pandas as pd |
| from systemds.context import SystemDSContext |
| |
| |
| class TestTransformEncode(unittest.TestCase): |
| |
| sds: SystemDSContext = None |
| HOMES_PATH = "../../test/resources/datasets/homes/homes.csv" |
| HOMES_SCHEMA = '"int,string,int,int,double,int,boolean,int,int"' |
| JSPEC_PATH = "../../test/resources/datasets/homes/homes.tfspec_recode2.json" |
| |
| @classmethod |
| def setUpClass(cls): |
| cls.sds = SystemDSContext(capture_stdout=True, logging_level=50) |
| |
| @classmethod |
| def tearDownClass(cls): |
| cls.sds.close() |
| |
| def tearDown(self): |
| pass |
| |
| def test_encode_recode(self): |
| with open(self.JSPEC_PATH) as jspec_file: |
| JSPEC = json.load(jspec_file) |
| F1 = self.sds.read( |
| self.HOMES_PATH, |
| data_type="frame", |
| schema=self.HOMES_SCHEMA, |
| format="csv", |
| header=True, |
| ) |
| pd_F1 = F1.compute() |
| jspec = self.sds.read(self.JSPEC_PATH, data_type="scalar", value_type="string") |
| X, M = F1.transform_encode(spec=jspec).compute() |
| self.assertTrue(isinstance(X, np.ndarray)) |
| self.assertTrue(isinstance(M, pd.DataFrame)) |
| self.assertTrue(X.shape == pd_F1.shape) |
| self.assertTrue(np.all(np.isreal(X))) |
| for col_name in JSPEC["recode"]: |
| self.assertTrue(M[col_name].nunique() == pd_F1[col_name].nunique()) |
| |
| def test_encode_recode_and_use_matrix(self): |
| with open(self.JSPEC_PATH) as jspec_file: |
| JSPEC = json.load(jspec_file) |
| F1 = self.sds.read( |
| self.HOMES_PATH, |
| data_type="frame", |
| schema=self.HOMES_SCHEMA, |
| format="csv", |
| header=True, |
| ) |
| jspec = self.sds.read(self.JSPEC_PATH, data_type="scalar", value_type="string") |
| X, M = F1.transform_encode(spec=jspec) |
| xm = X.sum() + 1 |
| res = xm.compute() |
| self.assertTrue(isinstance(res, float)) |
| |
| |
| if __name__ == "__main__": |
| unittest.main(exit=False) |