Here's a traceback:

_________ test_thresholds_dask_compatibility[threshold_minimum-84-86] __________

thresholding = <function threshold_minimum at 0x7f3ada677b00>, lower = 84
upper = 86

    @pytest.mark.parametrize("thresholding, lower, upper", [
        (threshold_otsu, 101, 103),
        (threshold_yen, 145, 147),
        (threshold_isodata, 101, 103),
        (threshold_mean, 128, 130),
        (threshold_triangle, 41, 43),
        (threshold_minimum, 84, 86),
    ])
    def test_thresholds_dask_compatibility(thresholding, lower, upper):
        pytest.importorskip('dask', reason="dask python library is not installed")
        import dask.array as da
        dask_camera = da.from_array(data.camera(), chunks=(256, 256))
>       assert lower < float(thresholding(dask_camera)) < upper

scikit-image/skimage/filters/tests/test_thresholding.py:689: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
scikit-image/skimage/filters/thresholding.py:783: in threshold_minimum
    counts, bin_centers = _validate_image_histogram(image, hist, nbins)
scikit-image/skimage/filters/thresholding.py:280: in _validate_image_histogram
    image.ravel(), nbins, source_range='image'
scikit-image/skimage/exposure/exposure.py:131: in histogram
    hist, bin_centers = _bincount_histogram(image, source_range)
scikit-image/skimage/exposure/exposure.py:73: in _bincount_histogram
    hist = hist[idx:]
/opt/hostedtoolcache/Python/3.7.10/x64/lib/python3.7/site-packages/dask/array/core.py:1696: in __getitem__
    index2 = normalize_index(index, self.shape)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

idx = (slice(0, None, None),), shape = ()

    def normalize_index(idx, shape):
        """Normalize slicing indexes
    
        1.  Replaces ellipses with many full slices
        2.  Adds full slices to end of index
        3.  Checks bounding conditions
        4.  Replace multidimensional numpy arrays with dask arrays
        5.  Replaces numpy arrays with lists
        6.  Posify's integers and lists
        7.  Normalizes slices to canonical form
    
        Examples
        --------
        >>> normalize_index(1, (10,))
        (1,)
        >>> normalize_index(-1, (10,))
        (9,)
        >>> normalize_index([-1], (10,))
        (array([9]),)
        >>> normalize_index(slice(-3, 10, 1), (10,))
        (slice(7, None, None),)
        >>> normalize_index((Ellipsis, None), (10,))
        (slice(None, None, None), None)
        >>> normalize_index(np.array([[True, False], [False, True], [True, True]]), (3, 2))
        (dask.array<array, shape=(3, 2), dtype=bool, chunksize=(3, 2), chunktype=numpy.ndarray>,)
        """
        from .core import Array, from_array
    
        if not isinstance(idx, tuple):
            idx = (idx,)
    
        # if a > 1D numpy.array is provided, cast it to a dask array
        if len(idx) > 0 and len(shape) > 1:
            i = idx[0]
            if is_arraylike(i) and not isinstance(i, Array) and i.shape == shape:
                idx = (from_array(i), *idx[1:])
    
        idx = replace_ellipsis(len(shape), idx)
        n_sliced_dims = 0
        for i in idx:
            if hasattr(i, "ndim") and i.ndim >= 1:
                n_sliced_dims += i.ndim
            elif i is None:
                continue
            else:
                n_sliced_dims += 1
    
        idx = idx + (slice(None),) * (len(shape) - n_sliced_dims)
        if len([i for i in idx if i is not None]) > len(shape):
>           raise IndexError("Too many indices for array")
E           IndexError: Too many indices for array

/opt/hostedtoolcache/Python/3.7.10/x64/lib/python3.7/site-packages/dask/array/slicing.py:897: IndexError

Potential sources from scanning the release notes:

dask/dask#7321
dask/dask#7033
dask/dask#7326

Would be awesome if @GenevieveBuckley could investigate... 😬

Uh oh!

test_thresholding fails with last dask version (2021.3.0) #5266

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