import operator import numpy as np import pytest import pandas as pd import pandas._testing as tm from pandas.arrays import BooleanArray from pandas.tests.extension.base import BaseOpsUtil class TestLogicalOps(BaseOpsUtil): def test_numpy_scalars_ok(self, all_logical_operators): a = pd.array([True, False, None], dtype="boolean") op = getattr(a, all_logical_operators) tm.assert_extension_array_equal(op(True), op(np.bool_(True))) tm.assert_extension_array_equal(op(False), op(np.bool_(False))) def get_op_from_name(self, op_name): short_opname = op_name.strip("_") short_opname = short_opname if "xor" in short_opname else short_opname + "_" try: op = getattr(operator, short_opname) except AttributeError: # Assume it is the reverse operator rop = getattr(operator, short_opname[1:]) op = lambda x, y: rop(y, x) return op def test_empty_ok(self, all_logical_operators): a = pd.array([], dtype="boolean") op_name = all_logical_operators result = getattr(a, op_name)(True) tm.assert_extension_array_equal(a, result) result = getattr(a, op_name)(False) tm.assert_extension_array_equal(a, result) # FIXME: dont leave commented-out # TODO: pd.NA # result = getattr(a, op_name)(pd.NA) # tm.assert_extension_array_equal(a, result) def test_logical_length_mismatch_raises(self, all_logical_operators): op_name = all_logical_operators a = pd.array([True, False, None], dtype="boolean") msg = "Lengths must match to compare" with pytest.raises(ValueError, match=msg): getattr(a, op_name)([True, False]) with pytest.raises(ValueError, match=msg): getattr(a, op_name)(np.array([True, False])) with pytest.raises(ValueError, match=msg): getattr(a, op_name)(pd.array([True, False], dtype="boolean")) def test_logical_nan_raises(self, all_logical_operators): op_name = all_logical_operators a = pd.array([True, False, None], dtype="boolean") msg = "Got float instead" with pytest.raises(TypeError, match=msg): getattr(a, op_name)(np.nan) @pytest.mark.parametrize("other", ["a", 1]) def test_non_bool_or_na_other_raises(self, other, all_logical_operators): a = pd.array([True, False], dtype="boolean") with pytest.raises(TypeError, match=str(type(other).__name__)): getattr(a, all_logical_operators)(other) def test_kleene_or(self): # A clear test of behavior. a = pd.array([True] * 3 + [False] * 3 + [None] * 3, dtype="boolean") b = pd.array([True, False, None] * 3, dtype="boolean") result = a | b expected = pd.array( [True, True, True, True, False, None, True, None, None], dtype="boolean" ) tm.assert_extension_array_equal(result, expected) result = b | a tm.assert_extension_array_equal(result, expected) # ensure we haven't mutated anything inplace tm.assert_extension_array_equal( a, pd.array([True] * 3 + [False] * 3 + [None] * 3, dtype="boolean") ) tm.assert_extension_array_equal( b, pd.array([True, False, None] * 3, dtype="boolean") ) @pytest.mark.parametrize( "other, expected", [ (pd.NA, [True, None, None]), (True, [True, True, True]), (np.bool_(True), [True, True, True]), (False, [True, False, None]), (np.bool_(False), [True, False, None]), ], ) def test_kleene_or_scalar(self, other, expected): # TODO: test True & False a = pd.array([True, False, None], dtype="boolean") result = a | other expected = pd.array(expected, dtype="boolean") tm.assert_extension_array_equal(result, expected) result = other | a tm.assert_extension_array_equal(result, expected) # ensure we haven't mutated anything inplace tm.assert_extension_array_equal( a, pd.array([True, False, None], dtype="boolean") ) def test_kleene_and(self): # A clear test of behavior. a = pd.array([True] * 3 + [False] * 3 + [None] * 3, dtype="boolean") b = pd.array([True, False, None] * 3, dtype="boolean") result = a & b expected = pd.array( [True, False, None, False, False, False, None, False, None], dtype="boolean" ) tm.assert_extension_array_equal(result, expected) result = b & a tm.assert_extension_array_equal(result, expected) # ensure we haven't mutated anything inplace tm.assert_extension_array_equal( a, pd.array([True] * 3 + [False] * 3 + [None] * 3, dtype="boolean") ) tm.assert_extension_array_equal( b, pd.array([True, False, None] * 3, dtype="boolean") ) @pytest.mark.parametrize( "other, expected", [ (pd.NA, [None, False, None]), (True, [True, False, None]), (False, [False, False, False]), (np.bool_(True), [True, False, None]), (np.bool_(False), [False, False, False]), ], ) def test_kleene_and_scalar(self, other, expected): a = pd.array([True, False, None], dtype="boolean") result = a & other expected = pd.array(expected, dtype="boolean") tm.assert_extension_array_equal(result, expected) result = other & a tm.assert_extension_array_equal(result, expected) # ensure we haven't mutated anything inplace tm.assert_extension_array_equal( a, pd.array([True, False, None], dtype="boolean") ) def test_kleene_xor(self): a = pd.array([True] * 3 + [False] * 3 + [None] * 3, dtype="boolean") b = pd.array([True, False, None] * 3, dtype="boolean") result = a ^ b expected = pd.array( [False, True, None, True, False, None, None, None, None], dtype="boolean" ) tm.assert_extension_array_equal(result, expected) result = b ^ a tm.assert_extension_array_equal(result, expected) # ensure we haven't mutated anything inplace tm.assert_extension_array_equal( a, pd.array([True] * 3 + [False] * 3 + [None] * 3, dtype="boolean") ) tm.assert_extension_array_equal( b, pd.array([True, False, None] * 3, dtype="boolean") ) @pytest.mark.parametrize( "other, expected", [ (pd.NA, [None, None, None]), (True, [False, True, None]), (np.bool_(True), [False, True, None]), (np.bool_(False), [True, False, None]), ], ) def test_kleene_xor_scalar(self, other, expected): a = pd.array([True, False, None], dtype="boolean") result = a ^ other expected = pd.array(expected, dtype="boolean") tm.assert_extension_array_equal(result, expected) result = other ^ a tm.assert_extension_array_equal(result, expected) # ensure we haven't mutated anything inplace tm.assert_extension_array_equal( a, pd.array([True, False, None], dtype="boolean") ) @pytest.mark.parametrize( "other", [True, False, pd.NA, [True, False, None] * 3], ) def test_no_masked_assumptions(self, other, all_logical_operators): # The logical operations should not assume that masked values are False! a = pd.arrays.BooleanArray( np.array([True, True, True, False, False, False, True, False, True]), np.array([False] * 6 + [True, True, True]), ) b = pd.array([True] * 3 + [False] * 3 + [None] * 3, dtype="boolean") if isinstance(other, list): other = pd.array(other, dtype="boolean") result = getattr(a, all_logical_operators)(other) expected = getattr(b, all_logical_operators)(other) tm.assert_extension_array_equal(result, expected) if isinstance(other, BooleanArray): other._data[other._mask] = True a._data[a._mask] = False result = getattr(a, all_logical_operators)(other) expected = getattr(b, all_logical_operators)(other) tm.assert_extension_array_equal(result, expected)