# -*- 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)

# -*- 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):
    a2, s2, n2, axis2 = dask_ndfourier._utils._norm_args(a, s, n=n, axis=axis)

    assert isinstance(a2, da.Array)
    assert isinstance(s2, da.Array)

Update the argument normalization test
Update the argument normalization test

Needs to make sure it unpacks the right number of return values. Also
since we are changing the input array, it is good to add a check to make
sure it is still of the expected type.
