day11.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "TEST_INPUT = '''...#......\n",
    ".......#..\n",
    "#.........\n",
    "..........\n",
    "......#...\n",
    ".#........\n",
    ".........#\n",
    "..........\n",
    ".......#..\n",
    "#...#.....'''.splitlines()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(\"day11.txt\") as f:\n",
    "    input = f.read().splitlines()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "fulL_input = []\n",
    "for row in input: ## THING TO CHANGE INPUT IN\n",
    "    fulL_input.append([*row])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[7, 52, 70, 83, 85, 87, 90]"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "def add_expansion(list_of_lists):\n",
    "    added_rows = []\n",
    "    for row in list_of_lists:\n",
    "        if all(x == '.' for x in row):\n",
    "            added_rows.append(row)\n",
    "        added_rows.append(row)\n",
    "    return added_rows\n",
    "\n",
    "def note_expanded_rows(list_of_lists):\n",
    "    clear_rows = []\n",
    "    for i,row in enumerate(list_of_lists):\n",
    "        if all(x == '.' for x in row):\n",
    "            clear_rows.append(i)\n",
    "    return clear_rows\n",
    "\n",
    "clear_rows = note_expanded_rows(fulL_input)\n",
    "clear_rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "flipped = np.array(fulL_input).T.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[40, 47, 51, 56, 59, 78, 80, 88]"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clear_columns = note_expanded_rows(flipped)\n",
    "clear_columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
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      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "galaxies = []\n",
    "for row_number,row in enumerate(fulL_input):\n",
    "    for column_number,point in enumerate(row):\n",
    "        if point =='#':\n",
    "            galaxies.append((row_number,column_number))\n",
    "galaxies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "total = 0\n",
    "for i, galaxy in enumerate(galaxies):\n",
    "    for j in range(i+1,len(galaxies)):\n",
    "        num_clear_rows = len([r for r in clear_rows if (r>min(galaxy[0],galaxies[j][0]) and r<max(galaxy[0],galaxies[j][0]))])\n",
    "        num_clear_columns = len([c for c in clear_columns if (c>min(galaxy[1],galaxies[j][1]) and c<max(galaxy[1],galaxies[j][1]))])\n",
    "        extra_distance_rows = num_clear_rows*(1000000-1)\n",
    "        extra_distance_columns = num_clear_columns*(1000000-1)\n",
    "        total+= abs(galaxy[0]-galaxies[j][0])+abs(galaxy[1]-galaxies[j][1]) + extra_distance_columns + extra_distance_rows\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "707505470642\n"
     ]
    }
   ],
   "source": [
    "print(total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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