Method test_comparisons

xarray/tests/test_units.py:3036–3080

(self, func, variation, unit, dtype)

        ids=repr,
    )
    def test_comparisons(self, func, variation, unit, dtype):
        def is_compatible(a, b):
            a = a if a is not None else 1
            b = b if b is not None else 1
            quantity = np.arange(5) * a

            return a == b or quantity.check(b)

        data = np.linspace(0, 5, 10).astype(dtype)
        coord = np.arange(len(data)).astype(dtype)

        base_unit = unit_registry.m
        array = data * (base_unit if variation == "data" else 1)
        x = coord * (base_unit if variation == "dims" else 1)
        y = coord * (base_unit if variation == "coords" else 1)

        variations = {
            "data": (unit, 1, 1),
            "dims": (1, unit, 1),
            "coords": (1, 1, unit),
        }
        data_unit, dim_unit, coord_unit = variations[variation]

        data_array = xr.DataArray(data=array, coords={"x": x, "y": ("x", y)}, dims="x")

        other = attach_units(
            strip_units(data_array), {None: data_unit, "x": dim_unit, "y": coord_unit}
        )

        units = extract_units(data_array)
        other_units = extract_units(other)

        equal_arrays = all(
            is_compatible(units[name], other_units[name]) for name in units.keys()
        ) and (
            strip_units(data_array).equals(
                strip_units(convert_units(other, extract_units(data_array)))
            )
        )
        equal_units = units == other_units
        expected = equal_arrays and (func.name != "identical" or equal_units)

        actual = func(data_array, other)

        assert expected == actual

    @pytest.mark.parametrize(
        "unit",