Function test_weather_data_resample

xarray/tests/test_groupby.py:2921–2954

(use_flox)

@pytest.mark.parametrize("use_flox", [True, False])
def test_weather_data_resample(use_flox):
    # from the docs
    times = pd.date_range("2000-01-01", "2001-12-31", name="time")
    annual_cycle = np.sin(2 * np.pi * (times.dayofyear.values / 365.25 - 0.28))

    base = 10 + 15 * annual_cycle.reshape(-1, 1)
    tmin_values = base + 3 * np.random.randn(annual_cycle.size, 3)
    tmax_values = base + 10 + 3 * np.random.randn(annual_cycle.size, 3)

    ds = xr.Dataset(
        {
            "tmin": (("time", "location"), tmin_values),
            "tmax": (("time", "location"), tmax_values),
        },
        {
            "time": ("time", times, {"time_key": "time_values"}),
            "location": ("location", ["IA", "IN", "IL"], {"loc_key": "loc_value"}),
        },
    )

    with xr.set_options(use_flox=use_flox):
        actual = ds.resample(time="1MS").mean()
    assert "location" in actual._indexes

    gb = ds.groupby(time=TimeResampler(freq="1MS"), location=UniqueGrouper())
    with xr.set_options(use_flox=use_flox):
        actual = gb.mean()
        expected = ds.resample(time="1MS").mean().sortby("location")
    assert_allclose(actual, expected)
    assert actual.time.attrs == ds.time.attrs
    assert actual.location.attrs == ds.location.attrs

    assert expected.time.attrs == ds.time.attrs
    assert expected.location.attrs == ds.location.attrs


@pytest.mark.parametrize("as_dataset", [True, False])