{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "344" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Load the larger test file and process it using the solution\n", "file_path = 'input'\n", "\n", "def process_large_file(file_path):\n", " with open(file_path, 'r') as file:\n", " lines = [line.rstrip('\\n') for line in file.readlines()]\n", " \n", " height = len(lines)\n", " width = len(lines[0]) if height > 0 else 0\n", "\n", " # Identify antennas and their frequencies\n", " freq_map = {}\n", " for y in range(height):\n", " for x in range(width):\n", " c = lines[y][x]\n", " if c != '.':\n", " if c not in freq_map:\n", " freq_map[c] = []\n", " freq_map[c].append((x, y))\n", "\n", " # A set to hold all unique antinode locations\n", " antinodes = set()\n", "\n", " # Candidate λ values based on derived equations\n", " lambdas = [2, -1, 1/3, 2/3]\n", "\n", " for freq, antennas in freq_map.items():\n", " n = len(antennas)\n", " if n < 2:\n", " continue\n", "\n", " for i in range(n):\n", " for j in range(i+1, n):\n", " x1, y1 = antennas[i]\n", " x2, y2 = antennas[j]\n", " dx = x2 - x1\n", " dy = y2 - y1\n", "\n", " for lam in lambdas:\n", " px = x1 + lam * dx\n", " py = y1 + lam * dy\n", "\n", " if abs(px - round(px)) < 1e-12 and abs(py - round(py)) < 1e-12:\n", " rx = round(px)\n", " ry = round(py)\n", "\n", " if 0 <= rx < width and 0 <= ry < height:\n", " antinodes.add((rx, ry))\n", "\n", " # Output the number of unique antinode locations\n", " return len(antinodes)\n", "\n", "process_large_file(file_path)\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1182" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "def process_part_two(file_path):\n", " with open(file_path, 'r') as file:\n", " lines = [line.rstrip('\\n') for line in file.readlines()]\n", "\n", " height = len(lines)\n", " width = len(lines[0]) if height > 0 else 0\n", "\n", " # Identify antennas and their frequencies\n", " freq_map = {}\n", " for y in range(height):\n", " for x in range(width):\n", " c = lines[y][x]\n", " if c != '.':\n", " if c not in freq_map:\n", " freq_map[c] = []\n", " freq_map[c].append((x, y))\n", "\n", " # A set to hold all unique antinode locations\n", " antinodes = set()\n", "\n", " # For each frequency group, consider all pairs of antennas\n", " for freq, antennas in freq_map.items():\n", " n = len(antennas)\n", " if n < 2:\n", " continue\n", "\n", " for i in range(n):\n", " for j in range(i + 1, n):\n", " x1, y1 = antennas[i]\n", " x2, y2 = antennas[j]\n", "\n", " # Calculate the collinearity condition\n", " for x in range(width):\n", " for y in range(height):\n", " if (x2 - x1) * (y - y1) == (y2 - y1) * (x - x1):\n", " antinodes.add((x, y))\n", "\n", " # Include the positions of all antennas as antinodes\n", " for freq, antennas in freq_map.items():\n", " for x, y in antennas:\n", " antinodes.add((x, y))\n", "\n", " # Return the number of unique antinode locations\n", " return len(antinodes)\n", "\n", "\n", "# Process the larger test file for part two\n", "process_part_two('input')\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.8" } }, "nbformat": 4, "nbformat_minor": 2 }