def _interpolate_turbidity(lts, time):
<EOL>lts_concat = np.concatenate([[lts[-<NUM_LIT:1>]], lts, [lts[<NUM_LIT:0>]]])<EOL>try:<EOL><INDENT>isleap = time.is_leap_year<EOL><DEDENT>except AttributeError:<EOL><INDENT>year = time.year<EOL>isleap = _is_leap_year(year)<EOL><DEDENT>dayofyear = time.dayofyear<EOL>days_leap = _calendar_month_middles(<NUM_LIT>)<EOL>days_no_leap = _calendar_month_middles(<NUM_LIT>)<EOL>lt_leap = np.interp(dayofyear, days_leap, lts_concat)<EOL>lt_no_leap = np.interp(dayofyear, days_no_leap, lts_concat)<EOL>linke_turbidity = np.where(isleap, lt_leap, lt_no_leap)<EOL>linke_turbidity = pd.Series(linke_turbidity, index=time)<EOL>return linke_turbidity<EOL>
Interpolated monthly Linke turbidity onto daily values.

Parameters
----------
lts : np.array
    Monthly Linke turbidity values.
time : pd.DatetimeIndex
    Times to be interpolated onto.

Returns
-------
linke_turbidity : pd.Series
    The interpolated turbidity.