Created
January 18, 2022 08:13
-
-
Save raeq/9d26969aaa8c20964b5aa375f8b5dcaf to your computer and use it in GitHub Desktop.
What is median...
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
from functools import lru_cache | |
from math import floor, ceil | |
from statistics import mean, median | |
def sum_c(pop: list[int], centroid: int) -> int: | |
@lru_cache | |
def gauss_sum(n: int) -> int: | |
return (n * (n + 1)) // 2 | |
return int(sum([gauss_sum(abs(x - centroid)) for x in pop])) | |
def sum_d(pop: list[int], centroid: int) -> int: | |
return int(sum([abs(x - centroid) for x in pop])) | |
def get_data(fn) -> list: | |
print(fn) | |
with open(fn) as f: | |
file_contents = f.read().rstrip() | |
return list(map(int, file_contents.split(','))) | |
if __name__ == '__main__': | |
file_data = get_data("day07.txt") | |
print(f"Day 7 Part 1: {sum_d(file_data, (median(file_data)))}") | |
# floor or ceil of mean? | |
m = mean(file_data) | |
fl = sum_c(file_data, floor(m)) | |
cl = sum_c(file_data, ceil(m)) | |
print(f"Day 7 Part 2: {fl if fl < cl else cl}") |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment