pl/python circular quartiles function

gistfile1.txt

create type numeric_quartiles_plus as (
    min float,
    q05 float,
    q10 float,
    q25 float,
    q50 float,
    q75 float,
    q90 float,
    q95 float,
    max float,
    stddev float,
    mean float
);


create or replace function circular_quartiles_py (
    valarray float[], circ_size float default 360 )
returns numeric_quartiles_plus
language plpythonu
as $f$
    from scipy.stats.mstats import mquantiles
    from numpy import append, arange, array, diff, sort, all, repeat, mean, std
    #remove nulls from the incoming array
    samples = array([p for p in valarray if p is not None])
    n = len(samples)
    # check for the empty set
    if n == 0:
        return (None,) * 11
    # sort the raw data
    x = sort(samples % (circ_size))
    # find the single largest gap
    spacings = append(diff(x), x[0] - x[n-1] + circ_size)
    max_spacing = arange(n)[spacings == max(spacings)] + 1
    # take the first largest spacing and assume its the gap
    if max_spacing[0] == n:
        offset = 0
    else:
        offset = circ_size - x[max_spacing[0]]
    # adjust all values by the gap location
    xoffset = sort((x + offset) % (circ_size))
    # calculate percentiles
    quant = mquantiles(xoffset,
                    prob=[0, 0.05, 0.1, 0.25, 0.5, 0.75, 0.9, 0.95, 1],
                    alphap=1,
                    betap=1) - offset
    # add mean and stddev
    quant2 = append(append(quant, std(xoffset) - offset), mean(xoffset) - offset)
    rez = [val + circ_size if val < 0 else val for val in quant2]
    return tuple(rez)
    $f$;