# Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. import numpy as np import pytest import fairlearn.metrics._input_manipulations as fmim class TestConvertToNDArrayAndSqueeze: def test_simple_list(self): X = [0, 1, 2] result = fmim._convert_to_ndarray_and_squeeze(X) assert isinstance(result, np.ndarray) assert result.shape == (3,) assert result[0] == 0 assert result[1] == 1 assert result[2] == 2 def test_multi_rows(self): X = [[0], [1]] result = fmim._convert_to_ndarray_and_squeeze(X) assert isinstance(result, np.ndarray) assert result.shape == (2,) assert result[0] == 0 assert result[1] == 1 def test_multi_columns(self): X = [[0, 1]] result = fmim._convert_to_ndarray_and_squeeze(X) assert isinstance(result, np.ndarray) assert result.shape == (2,) assert result[0] == 0 assert result[1] == 1 def test_single_element(self): X = [[[1]]] result = fmim._convert_to_ndarray_and_squeeze(X) assert isinstance(result, np.ndarray) assert result.shape == (1,) assert result[0] == 1 class TestConvertToNDArray1D: def test_simple_list(self): X = [0, 1, 2] result = fmim._convert_to_ndarray_1d(X) assert isinstance(result, np.ndarray) assert result.shape == (3,) assert result[0] == 0 assert result[1] == 1 assert result[2] == 2 def test_simple_nested_list(self): X = [[4, 5]] result = fmim._convert_to_ndarray_1d(X) assert isinstance(result, np.ndarray) assert result.shape == (2,) assert result[0] == 4 assert result[1] == 5 def test_simple_transposed_list(self): X = [[5], [7]] result = fmim._convert_to_ndarray_1d(X) assert isinstance(result, np.ndarray) assert result.shape == (2,) assert result[0] == 5 assert result[1] == 7 def test_2d_raises_exception(self): X = [[1, 2], [3, 4]] with pytest.raises(ValueError) as exception_context: _ = fmim._convert_to_ndarray_1d(X) expected = "Supplied input array has more than one non-trivial dimension" assert exception_context.value.args[0] == expected