def METHOD_NAME(nodata, use_dask):
    band_1 = np.random.randint(0, 100, size=(10, 100, 200)).astype(type(nodata))
    band_2 = np.random.randint(0, 100, size=(10, 100, 200)).astype(type(nodata))
    band_1[np.random.random(size=band_1.shape) > 0.5] = nodata
    band_2[np.random.random(size=band_1.shape) > 0.5] = nodata
    true_results = dict()
    true_results["band_1"] = np.stack(
        [np_percentile(band_1, 0.2, nodata), np_percentile(band_1, 0.6, nodata)], axis=0
    )
    true_results["band_2"] = np.stack(
        [np_percentile(band_2, 0.2, nodata), np_percentile(band_2, 0.6, nodata)], axis=0
    )
    if use_dask:
        band_1 = da.from_array(band_1, chunks=(2, 20, 20))
        band_2 = da.from_array(band_2, chunks=(2, 20, 20))
    attrs = {"test": "attrs"}
    coords = {
        "x": np.linspace(10, 20, band_1.shape[2]),
        "y": np.linspace(0, 5, band_1.shape[1]),
        "t": np.linspace(0, 5, band_1.shape[0]),
    }
    data_vars = {
        "band_1": xr.DataArray(band_1, dims=("t", "y", "x"), attrs={"test_attr": 1}),
        "band_2": xr.DataArray(band_2, dims=("t", "y", "x"), attrs={"test_attr": 2}),
    }
    dataset = xr.Dataset(data_vars=data_vars, coords=coords, attrs=attrs)
    output = xr_quantile(dataset, [0.2, 0.6], nodata).compute()
    for band in output.keys():
        np.testing.assert_equal(output[band], true_results[band])