Method test_upsample_nd

xarray/tests/test_groupby.py:2115–2171

(self)

        assert_identical(expected, actual)

    def test_upsample_nd(self) -> None:
        # Same as before, but now we try on multi-dimensional DataArrays.
        xs = np.arange(6)
        ys = np.arange(3)
        times = pd.date_range("2000-01-01", freq="6h", periods=5)
        data = np.tile(np.arange(5), (6, 3, 1))
        array = DataArray(data, {"time": times, "x": xs, "y": ys}, ("x", "y", "time"))

        # Forward-fill
        actual = array.resample(time="3h").ffill()
        expected_data = np.repeat(data, 2, axis=-1)
        expected_times = times.to_series().resample("3h").asfreq().index
        expected_data = expected_data[..., : len(expected_times)]
        expected = DataArray(
            expected_data,
            {"time": expected_times, "x": xs, "y": ys},
            ("x", "y", "time"),
        )
        assert_identical(expected, actual)

        # Backward-fill
        actual = array.resample(time="3h").ffill()
        expected_data = np.repeat(np.flipud(data.T).T, 2, axis=-1)
        expected_data = np.flipud(expected_data.T).T
        expected_times = times.to_series().resample("3h").asfreq().index
        expected_data = expected_data[..., : len(expected_times)]
        expected = DataArray(
            expected_data,
            {"time": expected_times, "x": xs, "y": ys},
            ("x", "y", "time"),
        )
        assert_identical(expected, actual)

        # As frequency
        actual = array.resample(time="3h").asfreq()
        expected_data = np.repeat(data, 2, axis=-1).astype(float)[..., :-1]
        expected_data[..., 1::2] = np.nan
        expected_times = times.to_series().resample("3h").asfreq().index
        expected = DataArray(
            expected_data,
            {"time": expected_times, "x": xs, "y": ys},
            ("x", "y", "time"),
        )
        assert_identical(expected, actual)

        # Pad
        actual = array.resample(time="3h").pad()
        expected_data = np.repeat(data, 2, axis=-1)
        expected_data[..., 1::2] = expected_data[..., ::2]
        expected_data = expected_data[..., :-1]
        expected_times = times.to_series().resample("3h").asfreq().index
        expected = DataArray(
            expected_data,
            {"time": expected_times, "x": xs, "y": ys},
            ("x", "y", "time"),
        )
        assert_identical(expected, actual)