r"""Wet days

    Return the total number of days during period with precipitation over threshold.

    Parameters
    ----------
    pr : xarray.DataArray
      Daily precipitation [mm]
    thresh : str
      Precipitation value over which a day is considered wet. Default: '1 mm/day'.
    freq : str, optional
      Resampling frequency defining the periods
      defined in http://pandas.pydata.org/pandas-docs/stable/timeseries.html#resampling.

    Returns
    -------
    xarray.DataArray
      The number of wet days for each period [day]

    Examples
    --------
    The following would compute for each grid cell of file `pr.day.nc` the number days
    with precipitation over 5 mm at the seasonal frequency, ie DJF, MAM, JJA, SON, DJF, etc.:

    >>> pr = xr.open_dataset('pr.day.nc')
    >>> wd = wetdays(pr, pr_min = 5., freq="QS-DEC")

def wetdays(pr, thresh='1.0 mm/day', freq='YS'):
    r"""Wet days

    Return the total number of days during period with precipitation over threshold.

    Parameters
    ----------
    pr : xarray.DataArray
      Daily precipitation [mm]
    thresh : str
      Precipitation value over which a day is considered wet. Default: '1 mm/day'.
    freq : str, optional
      Resampling frequency defining the periods
      defined in http://pandas.pydata.org/pandas-docs/stable/timeseries.html#resampling.

    Returns
    -------
    xarray.DataArray
      The number of wet days for each period [day]

    Examples
    --------
    The following would compute for each grid cell of file `pr.day.nc` the number days
    with precipitation over 5 mm at the seasonal frequency, ie DJF, MAM, JJA, SON, DJF, etc.:

    >>> pr = xr.open_dataset('pr.day.nc')
    >>> wd = wetdays(pr, pr_min = 5., freq="QS-DEC")
    """
    thresh = utils.convert_units_to(thresh, pr, 'hydro')

    wd = (pr >= thresh) * 1
    return wd.resample(time=freq).sum(dim='time')