commit42fc3fccad6918c9bc395c900d4e6e16d9824917parent27a578641f255001ee97eddc804b0c29e1abb81bAuthor:Eamon Caddigan <eamon.caddigan@gmail.com>Date:Tue, 7 Dec 2021 15:22:07 -0500 Solution to day 7, part 2Diffstat:

A | day07_part2.py | | | 56 | ++++++++++++++++++++++++++++++++++++++++++++++++++++++++ |

1 file changed, 56 insertions(+), 0 deletions(-)diff --git a/day07_part2.py b/day07_part2.py@@ -0,0 +1,56 @@ +#!/usr/bin/env python +"""Advent of Code 2021, day 7 (part 2): optimize 'crab submarine' alignment to +minimize fuel""" + +# Well the actual code I wrote for part 1 isn't very useful here, but the +# general approach works so that's cool I guess. It's probably faster to +# evaluate the fuel use at every position than it is to deploy an optimizer to +# solve the problem. HOWEVER, I'm using AoC to learn, so today I'm learning how +# to use `scipy.optimize.minimize()`. + +from scipy.optimize import minimize +from utils import get_puzzle_input, convert_int_line_to_series + +def find_minimum_fuel_use(positions): + """Given the positions of the 'crab submarines', find the minimum fuel use + to line them up""" + # Unlike part 1, we need to actually work to find the solution. What's + # interesting is that an optimization procedure found that, for the example + # input, a position of 4.7 had better fuel use (167.55) than the example + # solution of 5 (168). The problem doesn't explicitly state that only + # integer solutions are allowed, but we'll round the result. Knowing this, + # we can loose up the tolerances quite a bit, which gives us a nice + # speed boost. + best_position_solution = minimize( + lambda x: calculate_fuel_use_to(positions, x[0]), + 0, method='nelder-mead', options={'xatol': 0.1, 'fatol': 0.01} + ) + if not best_position_solution.success: + raise RuntimeError('optimizer failed to find solution') + return calculate_fuel_use_to(positions, + float(best_position_solution.x[0].round())) + +def calculate_fuel_use_to(start_positions, end_position): + """Given a series that represents the (1-D) positions of a collection of 'crab + submarines', find the fuel used to move to the given end position""" + # \sum_{i=1}^{n}i=\frac{n(n+1)}{2} + return ( + start_positions + .sub(end_position) + .abs() + .apply(lambda n: n*(n+1)/2) + .sum() + ) + +def solve_puzzle(input_string): + """Return the numeric solution to the puzzle""" + return find_minimum_fuel_use(convert_int_line_to_series(input_string)) + +def main(): + """Run when the file is called as a script""" + assert solve_puzzle("16,1,2,0,4,2,7,1,2,14\n") == 168.0 + print("Actual fuel spent to align crabs:", + f"{solve_puzzle(get_puzzle_input(7)):.0f}") + +if __name__ == "__main__": + main()