import numpy

from util import load_binary_file
from stats import iqr_remove_outliers, iqr_cutoff

def compact_file(fname, scale=None, extend=1.5):
    data = load_binary_file(fname)

    if not scale is None:
        data *= scale

    data.sort()

    iqr_min, iqr_max = iqr_cutoff(data, extend)

    min_idx, max_idx = numpy.searchsorted(data, [iqr_min, iqr_max])

    samples = data[min_idx:max_idx]

    filtered = len(data) - len(samples)
    max = samples[-1]
    min = samples[0]
    med = numpy.median(samples)
    avg = numpy.mean(samples)

    std = numpy.std(samples)
    var = numpy.var(samples)

    return [len(samples), filtered, max, avg, min, med, std, var]