import numpy as np import pytest from pandas import MultiIndex import pandas._testing as tm def test_numeric_compat(idx): with pytest.raises(TypeError, match="cannot perform __mul__"): idx * 1 with pytest.raises(TypeError, match="cannot perform __rmul__"): 1 * idx div_err = "cannot perform __truediv__" with pytest.raises(TypeError, match=div_err): idx / 1 div_err = div_err.replace(" __", " __r") with pytest.raises(TypeError, match=div_err): 1 / idx with pytest.raises(TypeError, match="cannot perform __floordiv__"): idx // 1 with pytest.raises(TypeError, match="cannot perform __rfloordiv__"): 1 // idx @pytest.mark.parametrize("method", ["all", "any", "__invert__"]) def test_logical_compat(idx, method): msg = f"cannot perform {method}" with pytest.raises(TypeError, match=msg): getattr(idx, method)() def test_inplace_mutation_resets_values(): levels = [["a", "b", "c"], [4]] levels2 = [[1, 2, 3], ["a"]] codes = [[0, 1, 0, 2, 2, 0], [0, 0, 0, 0, 0, 0]] mi1 = MultiIndex(levels=levels, codes=codes) mi2 = MultiIndex(levels=levels2, codes=codes) # instantiating MultiIndex should not access/cache _.values assert "_values" not in mi1._cache assert "_values" not in mi2._cache vals = mi1.values.copy() vals2 = mi2.values.copy() # accessing .values should cache ._values assert mi1._values is mi1._cache["_values"] assert mi1.values is mi1._cache["_values"] assert isinstance(mi1._cache["_values"], np.ndarray) # Make sure level setting works new_vals = mi1.set_levels(levels2).values tm.assert_almost_equal(vals2, new_vals) # Doesn't drop _values from _cache [implementation detail] tm.assert_almost_equal(mi1._cache["_values"], vals) # ...and values is still same too tm.assert_almost_equal(mi1.values, vals) # Make sure label setting works too codes2 = [[0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0]] exp_values = np.empty((6,), dtype=object) exp_values[:] = [(1, "a")] * 6 # Must be 1d array of tuples assert exp_values.shape == (6,) new_mi = mi2.set_codes(codes2) assert "_values" not in new_mi._cache new_values = new_mi.values assert "_values" in new_mi._cache # Shouldn't change cache tm.assert_almost_equal(mi2._cache["_values"], vals2) # Should have correct values tm.assert_almost_equal(exp_values, new_values)