(features_type)
| 771 | ids=['features_type=numpy.ndarray', 'features_type=pandas.DataFrame'] |
| 772 | ) |
| 773 | def test_pool_from_slices(features_type): |
| 774 | full_size = (100, 30) |
| 775 | subset_size = (20, 17) |
| 776 | |
| 777 | prng = np.random.RandomState(seed=20191120) |
| 778 | |
| 779 | for start_offsets in ((0, 0), (5, 3)): |
| 780 | full_features_data = np.round(prng.normal(size=full_size), decimals=3) |
| 781 | full_label = _generate_nontrivial_binary_target(full_size[0], prng=prng) |
| 782 | |
| 783 | subset_features_data = full_features_data[start_offsets[0]:subset_size[0], start_offsets[1]:subset_size[1]] |
| 784 | subset_label = full_label[start_offsets[0]:subset_size[0]] |
| 785 | |
| 786 | if features_type == 'numpy.ndarray': |
| 787 | pool = Pool(subset_features_data, subset_label) |
| 788 | else: |
| 789 | pool = Pool(pd.DataFrame(subset_features_data), subset_label) |
| 790 | assert _check_data(pool.get_features(), subset_features_data) |
| 791 | assert _check_data([float(value) for value in pool.get_label()], subset_label) |
| 792 | |
| 793 | |
| 794 | @pytest.mark.parametrize( |
nothing calls this directly
no test coverage detected