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import math
def _none_if_null_len(func):
def tmp(xs, *args, **kwargs):
if len(xs) == 0:
return None
return func(xs, *args, **kwargs)
return tmp
@_none_if_null_len
def mean(xs):
return sum(xs) / len(xs)
@_none_if_null_len
def std(xs):
xs_mean = mean(xs)
return math.sqrt(sum(
[(x - xs_mean) ** 2 for x in xs]) / (len(xs) - 1))
@_none_if_null_len
def _pick(xs, compar):
m = xs[0]
for t in xs[1:]:
if compar(t, m):
m = t
return m
def min(xs):
return _pick(xs, lambda x, y: x < y)
def max(xs):
return _pick(xs, lambda x, y: x > y)
def _qsort(xs):
if len(xs) < 2:
return xs
xs = list(xs)
pivot = xs[0]
body = xs[1:]
return (_qsort([x for x in body if x < pivot])
+ [pivot]
+ _qsort([x for x in body if x >= pivot]))
def _need_sorted(func):
return lambda xs, *args, **kwargs: func(_qsort(xs), *args, **kwargs)
@_none_if_null_len
@_need_sorted
def q25(xs):
return xs[len(xs) // 4]
@_none_if_null_len
@_need_sorted
def median(xs):
return xs[len(xs) // 2 ]
@_none_if_null_len
@_need_sorted
def q75(xs):
return xs[3 * (len(xs) // 4)]
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