diff options
| -rw-r--r-- | Lib/statistics.py | 34 |
1 files changed, 16 insertions, 18 deletions
diff --git a/Lib/statistics.py b/Lib/statistics.py index 07d1fd5..7d5d750 100644 --- a/Lib/statistics.py +++ b/Lib/statistics.py @@ -136,9 +136,9 @@ from fractions import Fraction from decimal import Decimal from itertools import count, groupby, repeat from bisect import bisect_left, bisect_right -from math import hypot, sqrt, fabs, exp, erf, tau, log, fsum +from math import hypot, sqrt, fabs, exp, erf, tau, log, fsum, sumprod from functools import reduce -from operator import mul, itemgetter +from operator import itemgetter from collections import Counter, namedtuple, defaultdict _SQRT2 = sqrt(2.0) @@ -496,28 +496,26 @@ def fmean(data, weights=None): >>> fmean([3.5, 4.0, 5.25]) 4.25 """ - try: - n = len(data) - except TypeError: - # Handle iterators that do not define __len__(). - n = 0 - def count(iterable): - nonlocal n - for n, x in enumerate(iterable, start=1): - yield x - data = count(data) if weights is None: + try: + n = len(data) + except TypeError: + # Handle iterators that do not define __len__(). + n = 0 + def count(iterable): + nonlocal n + for n, x in enumerate(iterable, start=1): + yield x + data = count(data) total = fsum(data) if not n: raise StatisticsError('fmean requires at least one data point') return total / n - try: - num_weights = len(weights) - except TypeError: + if not isinstance(weights, (list, tuple)): weights = list(weights) - num_weights = len(weights) - num = fsum(map(mul, data, weights)) - if n != num_weights: + try: + num = sumprod(data, weights) + except ValueError: raise StatisticsError('data and weights must be the same length') den = fsum(weights) if not den: |