Light Clean up
This commit is contained in:
Tobias Kessels committed
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commit
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11 files changed
+403
-2394
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@@ -1,6 +0,0 @@
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@@ -1,18 +0,0 @@
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+28
-72
@@ -2,21 +2,20 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 336,
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"execution_count": 13,
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"metadata": {},
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"outputs": [],
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"source": [
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"input = r'''0 1 10 99 999'''\n",
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"input = r'''125 17'''\n",
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"#input = r'''0 1 10 99 999'''\n",
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"#input = r'''125 17'''\n",
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"input = r'''475449 2599064 213 0 2 65 5755 51149'''\n",
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"\n",
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"\n",
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"stones = {int(x):1 for x in input.split()}\n"
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"stones = {int(x):1 for x in input.split()}"
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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": null,
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"execution_count": 14,
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@@ -40,17 +39,29 @@
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},
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 15,
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"metadata": {},
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"outputs": [],
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"outputs": [
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{
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"data": {
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"text/plain": [
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"193269"
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},
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"execution_count": 15,
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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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"for i in range(75):\n",
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" stones=step(stones)\n"
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"for i in range(25):\n",
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" stones=step(stones)\n",
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"sum(stones.values())"
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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": 269,
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"execution_count": 16,
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"metadata": {},
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"outputs": [
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{
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@@ -59,77 +70,22 @@
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"228449040027793"
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]
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},
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"execution_count": 269,
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"execution_count": 16,
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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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"stones = {int(x):1 for x in input.split()}\n",
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"for i in range(75):\n",
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" stones=step(stones)\n",
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"sum(stones.values())"
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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": 459,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"defaultdict(<class 'int'>, {6072: 673206953446361827286, 4048: 2734962356528935214636, 14168: 1343031271242210938014, 12144: 2300399947749196772879, 32772608: 1863779202753698640740, 40: 1800617350854067786011, 48: 1963004354915731679509, 2024: 1901242329177217918652, 80: 2071514762314577986161, 96: 1909127758252913749300, 16192: 2830947128757671518126, 18216: 1268972356388161972299, 8096: 2899816988343294077917, 10120: 569045306257576076768, 1: 2887855190943409245055, 36869184: 835429087093576428724, 24579456: 1514487337123235977781, 28: 545640724430717426974, 67: 383253720369045854463, 60: 826473730693175762336, 32: 1191095444078885640165, 24: 1908139147880629965130, 57: 656448851778621933102, 94: 656448851778621838017, 56: 656448851778627848108, 3: 1022537248590681705286, 2: 4154202543052785522877, 7: 2039928642914626319453, 6: 3494049803451761028009, 77: 807841723709838053671, 26: 807841723709836079846, 8: 4299935420757677600191, 36: 362115363446705336479, 86: 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293: 2126708, 642: 1Line truncated
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"3811\n"
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]
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}
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],
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"source": [
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"print(stones)\n",
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"stones=step(stones)\n",
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" \n",
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"print(len(stones))"
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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": 271,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"defaultdict(<class 'int'>, {2: 1, 0: 1})\n"
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]
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}
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],
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"source": [
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"from collections import defaultdict\n",
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"\n",
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"def step(stones):\n",
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" output = defaultdict(int) # Use defaultdict with int, which defaults to 0\n",
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" for stone, count in stones.items(): # Iterate over the dictionary of stones with their counts\n",
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" if stone == 0:\n",
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" output[1] += count # Zero turns into 1, add the count to the 1 key\n",
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" elif (tx_stone := str(stone)) and len(tx_stone) % 2 == 0:\n",
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" half = len(tx_stone) // 2\n",
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" left = int(tx_stone[:half])\n",
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" right = int(tx_stone[half:])\n",
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" output[left] += count # Add the count to the left split part\n",
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" output[right] += count # Add the count to the right split part\n",
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" else:\n",
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" output[stone * 2024] += count # Multiply by 2024 and add to the count for that stone\n",
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" return output\n",
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"\n",
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"# Example usage:\n",
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"stones = {20: 1} # Example input: stone values and their counts\n",
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"result = step(stones)\n",
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"print(result)"
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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": "pdf",
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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@@ -143,7 +99,7 @@
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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": "3.12.7"
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"version": "3.8.10"
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@@ -2,12 +2,12 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 87,
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"#read lines from input and store each list of space separeted integers into left and right lists respectively.\n",
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"with open('4/input', 'r') as f:\n",
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"with open('input', 'r') as f:\n",
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" data=f.readlines()\n",
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"\n",
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"data = [line.strip() for line in data]\n"
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@@ -15,7 +15,7 @@
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@@ -24,7 +24,7 @@
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"421"
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]
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@@ -36,7 +36,7 @@
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@@ -45,7 +45,7 @@
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"463"
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@@ -57,7 +57,7 @@
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@@ -66,7 +66,7 @@
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"1640"
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"execution_count": 90,
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@@ -89,7 +89,7 @@
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"2524"
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"mask = pattern != '.'"
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"1873"
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@@ -173,9 +160,21 @@
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+1
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File renamed without changes.
File renamed without changes.
File renamed without changes.
@@ -1,164 +1,295 @@
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|
||||
"data": {
|
||||
"text/plain": [
|
||||
"344"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"execution_count": 2
|
||||
}
|
||||
],
|
||||
"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('input')\n"
|
||||
]
|
||||
},
|
||||
"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"
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"colab": {
|
||||
"base_uri": "https://localhost:8080/"
|
||||
},
|
||||
"id": "RvPJM8km9m1W",
|
||||
"outputId": "77731738-0776-46da-e8e5-4faf9e334515"
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "execute_result",
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"1182"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"execution_count": 3
|
||||
}
|
||||
],
|
||||
"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"
|
||||
]
|
||||
},
|
||||
"execution_count": 2,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
},
|
||||
{
|
||||
"source": [
|
||||
"# prompt: visualize the map\n",
|
||||
"\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"\n",
|
||||
"# 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",
|
||||
" # The line below was previously commented out and caused the error\n",
|
||||
" # because the variable 'antinodes' was not defined.\n",
|
||||
" # It has been uncommented and restored to its original functionality.\n",
|
||||
" return antinodes, width, height, lines # Return antinodes and dimensions\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"def visualize_map(antinodes, width, height, lines):\n",
|
||||
" # Create a 2D array to represent the map\n",
|
||||
" map_array = [['.' for _ in range(width)] for _ in range(height)]\n",
|
||||
"\n",
|
||||
" # Place antennas on the map\n",
|
||||
" for y in range(height):\n",
|
||||
" for x in range(width):\n",
|
||||
" map_array[y][x] = lines[y][x]\n",
|
||||
"\n",
|
||||
" # Mark antinodes on the map\n",
|
||||
" for x, y in antinodes:\n",
|
||||
" map_array[y][x] = '#'\n",
|
||||
"\n",
|
||||
" # Display the map using matplotlib\n",
|
||||
" plt.figure(figsize=(10, 10)) # Adjust figure size as needed\n",
|
||||
" plt.imshow([[ord(c) for c in row] for row in map_array], cmap='viridis')\n",
|
||||
" plt.colorbar()\n",
|
||||
" plt.show()\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"# Call the function and get the results\n",
|
||||
"antinodes, width, height, lines = process_large_file('testinput')\n",
|
||||
"visualize_map(antinodes, width, height, lines)"
|
||||
],
|
||||
"cell_type": "code",
|
||||
"metadata": {
|
||||
"colab": {
|
||||
"base_uri": "https://localhost:8080/",
|
||||
"height": 821
|
||||
},
|
||||
"id": "TbsEuRwx-giw",
|
||||
"outputId": "2b2f61ab-c2b5-40e5-bddc-2c191f6529aa"
|
||||
},
|
||||
"execution_count": null,
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "display_data",
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"<Figure size 1000x1000 with 2 Axes>"
|
||||
],
|
||||
"image/png": "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 truncated
|
||||
},
|
||||
"metadata": {}
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"source": [],
|
||||
"metadata": {
|
||||
"id": "yqLLsSep_F_j"
|
||||
},
|
||||
"execution_count": null,
|
||||
"outputs": []
|
||||
}
|
||||
],
|
||||
"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"
|
||||
},
|
||||
"colab": {
|
||||
"provenance": []
|
||||
}
|
||||
],
|
||||
"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
|
||||
}
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 0
|
||||
}
|
||||
Reference in new issue
Block a user