minor inefficency in the statistics module

[lbaumbauer]

Bug report

Bug description:

cpython/Lib/statistics.py

Line 1217 in 22a6c51

j = i * m // n # rescale i to m/n

in the quantiles computation 'i * m' should be reused not recomputed ( #150326) changes not added here)

            i_m = i * m
            j =  i_m // n                               # rescale i to m/n
            j = 1 if j < 1 else ld-1 if j > ld-1 else j  # clamp to 1 .. ld-1
            delta = i_m - j*n 

CPython versions tested on:

3.13

Operating systems tested on:

No response

[picnixz]

If you believe there is a real improvement this should be backed by benchmarks. I do not think this matters though.

[lbaumbauer]

lol

`from timeit import timeit

a = 1.23456789

def test_a(ld, i, m):
n = 100
i_m = i * m
j = i_m // n # rescale i to m/n
j = 1 if j < 1 else ld-1 if j > ld-1 else j # clamp to 1 .. ld-1
delta = i_m - j*n

def test_b(ld, i, m):
n = 100
j = i * m // n # rescale i to m/n
j = 1 if j < 1 else ld-1 if j > ld-1 else j # clamp to 1 .. ld-1
delta = i * m - j*n

_ld = 234
_i = 3
_m = _ld + 1

x = timeit(lambda : test_a(_ld, _i, _m), number=10_000_000)
y = timeit(lambda : test_b(_ld, _i, _m), number=10_000_000)

print(f"{x / y}")
`

0.925

[picnixz]

This benchmark is neither correct nor relevant; I am closing this. Use pyperf for more robust checks and benchmark the entire function as well instead of just thjs arithmetic part. Timeit does not givr any information (and use PGO/LTO builds).