None or a two item tuple.
    Tuple of the percentages to cut on each side of the array, with respect
    to the number of unmasked data, as floats between 0. and 1. If ``n``
    is the number of unmasked data before trimming, then
    (``n * limits[0]``)th smallest data and (``n * limits[1]``)th
    largest data are masked.  The total number of unmasked data after
    trimming is ``n * (1. - sum(limits))``.
    The value of one limit can be set to None to indicate an open interval.

    Defaults to (0.2, 0.2).
inclusive : (2,) tuple of boolean, optional
    If relative==False, tuple indicating whether values exactly equal to
    the absolute limits are allowed.
    If relative==True, tuple indicating whether the number of data being
    masked on each side should be rounded (True) or truncated (False).

    Defaults to (True, True).
alpha : float, optional
    Confidence level of the intervals.

    Defaults to 0.05.
axis : int, optional
    Axis along which to cut. If None, uses a flattened version of `data`.

    Defaults to None.

Returns
-------
trimmed_mean_ci : (2,) ndarray
    The lower and upper confidence intervals of the trimmed data.

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