| # |
| # 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 pytest |
| |
| from pywy.dataquanta import WayangContext |
| from pywy.platforms.java import JavaPlugin |
| from pywy.platforms.spark import SparkPlugin |
| |
| # TODO: add functionality required for this test load_collection & collect |
| @pytest.mark.skip(reason="no way of currently testing this, since we are missing implementations for load_collection & collect") |
| def test_train_and_predict(): |
| ctx = WayangContext().register({JavaPlugin, SparkPlugin}) |
| |
| features = ctx.load_collection([[0.0, 1.0], [1.0, 0.0], [1.0, 1.0], [0.0, 0.0]]) |
| labels = ctx.load_collection([1.0, 1.0, 0.0, 0.0]) |
| |
| model = features.train_logistic_regression(labels) |
| predictions = model.predict(features) |
| |
| result = predictions.collect() |
| print("Predictions:", result) |
| |
| assert len(result) is 4, f"Expected len(result) to be 4, but got: {len(result)}" |
| for pred in result: |
| assert pred in [0.0, 1.0], f"Expected prediction to be in [0.0, 0.1], but got: {pred}" |