Lines Matching full:average

334   average = numpy.average(data)
348         'low': average + t_bounds[0] * stddev / sqrt(N),
349         'high': average + t_bounds[1] * stddev / sqrt(N)
353     ci = { 'abs': 0, 'low': average, 'high': average }
354   if abs(stddev) > 0.0001 and abs(average) > 0.0001:
355     ci['perc'] = t_bounds[1] * stddev / sqrt(N) / average * 100
358   return { 'samples': N, 'average': average, 'median': median,
440   # Sort by ascending/descending time average, then by ascending/descending
441   # count average, then by ascending name.
443     return (item[1]['time_stat']['average'],
444             item[1]['count_stat']['average'],
447     return (-item[1]['time_stat']['average'],
448             -item[1]['count_stat']['average'],
466       return "{:8.1f}{} +/- {:15s}".format(s['average'], units, conf)
612           entry.append(round(s['average'], 1))