Repository: scipy/scipy
File: scipy/stats/_morestats.py (Python)

Code before:
    ----------
    samples : array_like
        Input array of angle observations.  The value of a full angle is
        equal to ``(high - low)``.
    high : float, optional
        Upper boundary of the principal value of an angle.  Default is ``2*pi``.
    low : float, optional
        Lower boundary of the principal value of an angle.  Default is ``0``.
    axis : int or None, default: None
        If an int, the axis of the input along which to compute the statistic.
        The statistic of each axis-slice (e.g. row) of the input will appear in a
        corresponding element of the output.
        If ``None``, the input will be raveled before computing the statistic.
    nan_policy : {'propagate', 'omit', 'raise'}
        Defines how to handle input NaNs.

        - ``propagate``: if a NaN is present in the axis slice (e.g. row) along
        which the  statistic is computed, the corresponding entry of the output
        will be NaN.
        - ``omit``: NaNs will be omitted when performing the calculation.
        If insufficient data remains in the axis slice along which the
        statistic is computed, the corresponding entry of the output will be
        NaN.
        - ``raise``: if a NaN is present, a ``ValueError`` will be raised.
    normalize : boolean, optional
        If ``False`` (the default), the return value is computed from the
        above formula with the input scaled by ``(2*pi)/(high-low)`` and
        the output scaled (back) by ``(high-low)/(2*pi)``.  If ``True``,
        the output is not scaled and is returned directly.

    Returns
    -------
    circstd : float
        Circular standard deviation, optionally normalized.

        If the input array is empty, ``np.nan`` is returned.

    See Also
    --------
    circmean : Circular mean.
    circvar : Circular variance.

    Notes
    -----
    In the limit of small angles, the circular standard deviation is close
    to the 'linear' standard deviation if ``normalize`` is ``False``.

    References
    ----------
    .. [1] Mardia, K. V. (1972). 2. In *Statistics of Directional Data*
       (pp. 18-24). Academic Press. :doi:`10.1016/C2013-0-07425-7`.

Review comment (suggestion):
Looks like these are new - did it complain about parameters being out of order because there were some missing?
```suggestion

    normalize : boolean, optional
```
I don't think it's syntactically required, but I've gotten it in my head that it's preferred to include whitespace after the list, too.

Code after:
    ----------
    samples : array_like
        Input array of angle observations.  The value of a full angle is
        equal to ``(high - low)``.
    high : float, optional
        Upper boundary of the principal value of an angle.  Default is ``2*pi``.
    low : float, optional
        Lower boundary of the principal value of an angle.  Default is ``0``.
    axis : int or None, default: None
        If an int, the axis of the input along which to compute the statistic.
        The statistic of each axis-slice (e.g. row) of the input will appear in a
        corresponding element of the output.
        If ``None``, the input will be raveled before computing the statistic.
    nan_policy : {'propagate', 'omit', 'raise'}
        Defines how to handle input NaNs.

        - ``propagate``: if a NaN is present in the axis slice (e.g. row) along
        which the  statistic is computed, the corresponding entry of the output
        will be NaN.
        - ``omit``: NaNs will be omitted when performing the calculation.
        If insufficient data remains in the axis slice along which the
        statistic is computed, the corresponding entry of the output will be
        NaN.
        - ``raise``: if a NaN is present, a ``ValueError`` will be raised.

    normalize : boolean, optional
        If ``False`` (the default), the return value is computed from the
        above formula with the input scaled by ``(2*pi)/(high-low)`` and
        the output scaled (back) by ``(high-low)/(2*pi)``.  If ``True``,
        the output is not scaled and is returned directly.

    Returns
    -------
    circstd : float
        Circular standard deviation, optionally normalized.

        If the input array is empty, ``np.nan`` is returned.

    See Also
    --------
    circmean : Circular mean.
    circvar : Circular variance.

    Notes
    -----
    In the limit of small angles, the circular standard deviation is close
    to the 'linear' standard deviation if ``normalize`` is ``False``.

    References
    ----------
    .. [1] Mardia, K. V. (1972). 2. In *Statistics of Directional Data*