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