# -*- coding: utf-8 -*-

# -*- coding: utf-8 -*-


import pytest

import numpy as np

import dask.array as da
import dask.array.utils as dau

import dask_ndfourier._utils


@pytest.mark.parametrize(
    "a, s, n, axis", [
        (da.ones((3, 4), chunks=(3, 4)), da.ones((2,), chunks=(2,)), -1, -1),
    ]
)
def test_norm_args(a, s, n, axis):
    s2, n2, axis2 = dask_ndfourier._utils._norm_args(a, s, n=n, axis=axis)

    assert isinstance(s2, da.Array)

Test that `s` as a Dask Array is preserved
Test that `s` as a Dask Array is preserved

Ensure that if `s` is a Dask Array, it will still be a Dask Array after
type normalization is done on the input arguments of the Fourier
filters. This allows Fourier filters to construct a computation around
an unknown `s` in addition to an unknown input array.
