experiments-nivel-basico.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from Python.generator import Problem\n",
    "import pandas as pd\n",
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# seeds = [rand.randint(1, 1000000000) for _ in range(10)]\n",
    "seeds = [310294340,\n",
    " 481384238,\n",
    " 393948691,\n",
    " 54466310,\n",
    " 393844825,\n",
    " 607440463,\n",
    " 611846857,\n",
    " 836378547,\n",
    " 666002099,\n",
    " 639709340]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "carpeta_extension = 'Nivel basico'\n",
    "domain = 'nivel_basico'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def experiment(problem, seeds, n_rovers, suministros, personal, mars_map, warehouses, settlements, r_map, optim, comb_min_rover = 0, comb_max_rover= 0, comb =False, prio=False, pedidos_adicionales = 0):\n",
    "    results = []\n",
    "    reset_bases =  not warehouses and  not settlements\n",
    "    for seed in seeds:\n",
    "        if reset_bases:\n",
    "            warehouses = []\n",
    "            settlements = []\n",
    "\n",
    "        objects, init = problem.generate_problem(\n",
    "            n_rovers, suministros, personal, mars_map, warehouses, settlements, r_map, comb_min_rover, comb_max_rover, pedidos_adicionales, seed)\n",
    "\n",
    "        problem.write_problem(objects, init)\n",
    "        start     = time.time()\n",
    "        problem.execute(optim)\n",
    "        end       = time.time()\n",
    "        steps, times, result = problem.read_output(comb, prio)\n",
    "        result[1] = end - start\n",
    "        results.append(result)\n",
    "    return results\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def print_results(results, title):\n",
    "    mean = []\n",
    "\n",
    "    df = pd.DataFrame(results)\n",
    "    df = df.astype(float)\n",
    "    mean = df.mean()\n",
    "    print('------------------------------------------')\n",
    "    print(title)\n",
    "    print(f\"Step: {mean[0]}\")\n",
    "    print(f\"Time: {mean[1]}s\")\n",
    "    print(f\"easy actions: {mean[2]}\")\n",
    "    print(f\"hard actions: {mean[3]}\")\n",
    "    print(f\"facts: {mean[4]}\")\n",
    "    print(f\"actions: {mean[5]}\")\n",
    "    print(f\"relevant facts: {mean[6]}\")\n",
    "    print(f\"relevant fluents: {mean[7]}\")\n",
    "    print(f\"states: {mean[8]}\")\n",
    "    print(f\"depth: {mean[9]}\")\n",
    "    print('------------------------------------------')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Experimento 1 Nº Transportables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------------------------------------------\n",
      "Transportables:2\n",
      "Step: 6.0\n",
      "Time: 0.0757638931274414s\n",
      "easy actions: 60.0\n",
      "hard actions: 0.0\n",
      "facts: 22.0\n",
      "actions: 36.0\n",
      "relevant facts: 22.0\n",
      "relevant fluents: 0.0\n",
      "states: 10.0\n",
      "depth: 1.0\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Transportables:20\n",
      "Step: 48.0\n",
      "Time: 0.09921426773071289s\n",
      "easy actions: 348.0\n",
      "hard actions: 0.0\n",
      "facts: 112.0\n",
      "actions: 108.0\n",
      "relevant facts: 112.0\n",
      "relevant fluents: 0.0\n",
      "states: 157.0\n",
      "depth: 2.0\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Transportables:50\n",
      "Step: 108.0\n",
      "Time: 0.15076909065246583s\n",
      "easy actions: 828.0\n",
      "hard actions: 0.0\n",
      "facts: 262.0\n",
      "actions: 228.0\n",
      "relevant facts: 262.0\n",
      "relevant fluents: 0.0\n",
      "states: 315.0\n",
      "depth: 2.0\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Transportables:100\n",
      "Step: 208.0\n",
      "Time: 0.28208341598510744s\n",
      "easy actions: 1628.0\n",
      "hard actions: 0.0\n",
      "facts: 512.0\n",
      "actions: 428.0\n",
      "relevant facts: 512.0\n",
      "relevant fluents: 0.0\n",
      "states: 599.0\n",
      "depth: 2.0\n",
      "------------------------------------------\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[1;32mIn [6], line 14\u001b[0m\n\u001b[0;32m     12\u001b[0m settlements \u001b[39m=\u001b[39m [\u001b[39m3\u001b[39m, \u001b[39m4\u001b[39m]\n\u001b[0;32m     13\u001b[0m r_map \u001b[39m=\u001b[39m \u001b[39m0.5\u001b[39m\n\u001b[1;32m---> 14\u001b[0m results \u001b[39m=\u001b[39m experiment(problem, seeds, n_rovers, suministros, personal, mars_map, warehouses, settlements, r_map, optim)\n\u001b[0;32m     15\u001b[0m print_results(results, title\u001b[39m=\u001b[39m\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mTransportables:\u001b[39m\u001b[39m{\u001b[39;00mvar \u001b[39m*\u001b[39m\u001b[39m2\u001b[39m\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m)\n",
      "Cell \u001b[1;32mIn [4], line 14\u001b[0m, in \u001b[0;36mexperiment\u001b[1;34m(problem, seeds, n_rovers, suministros, personal, mars_map, warehouses, settlements, r_map, optim)\u001b[0m\n\u001b[0;32m     12\u001b[0m problem\u001b[39m.\u001b[39mwrite_problem(objects, init)\n\u001b[0;32m     13\u001b[0m start     \u001b[39m=\u001b[39m time\u001b[39m.\u001b[39mtime()\n\u001b[1;32m---> 14\u001b[0m problem\u001b[39m.\u001b[39;49mexecute(optim)\n\u001b[0;32m     15\u001b[0m end       \u001b[39m=\u001b[39m time\u001b[39m.\u001b[39mtime()\n\u001b[0;32m     16\u001b[0m steps, times, result \u001b[39m=\u001b[39m problem\u001b[39m.\u001b[39mread_output()\n",
      "File \u001b[1;32mc:\\Users\\Noel Nathan\\Desktop\\Universidad\\3r Quadrimestre\\ABIA\\ABIA_PDDL_Project\\Python\\generator.py:218\u001b[0m, in \u001b[0;36mProblem.execute\u001b[1;34m(self, optim)\u001b[0m\n\u001b[0;32m    216\u001b[0m O \u001b[39m=\u001b[39m \u001b[39m\"\u001b[39m\u001b[39m -O \u001b[39m\u001b[39m\"\u001b[39m \u001b[39mif\u001b[39;00m optim \u001b[39melse\u001b[39;00m \u001b[39m\"\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m    217\u001b[0m cmd \u001b[39m=\u001b[39m \u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m{\u001b[39;00m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpaths[\u001b[39m\"\u001b[39m\u001b[39mexecutable\u001b[39m\u001b[39m\"\u001b[39m]\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m\u001b[39m \u001b[39m\u001b[39m{\u001b[39;00mO\u001b[39m}\u001b[39;00m\u001b[39m-o \u001b[39m\u001b[39m\"\u001b[39m\u001b[39m{\u001b[39;00m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpaths[\u001b[39m\"\u001b[39m\u001b[39mdomain\u001b[39m\u001b[39m\"\u001b[39m]\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m\u001b[39m -f \u001b[39m\u001b[39m\"\u001b[39m\u001b[39m{\u001b[39;00m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpaths[\u001b[39m\"\u001b[39m\u001b[39mproblem\u001b[39m\u001b[39m\"\u001b[39m]\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m\u001b[39m'\u001b[39m\n\u001b[1;32m--> 218\u001b[0m output \u001b[39m=\u001b[39m subprocess\u001b[39m.\u001b[39;49mrun(shlex\u001b[39m.\u001b[39;49msplit(cmd), capture_output\u001b[39m=\u001b[39;49m\u001b[39mTrue\u001b[39;49;00m)\u001b[39m.\u001b[39mstdout\n\u001b[0;32m    219\u001b[0m output \u001b[39m=\u001b[39m \u001b[39mstr\u001b[39m(output)\u001b[39m.\u001b[39mreplace(\u001b[39m'\u001b[39m\u001b[39m\\\\\u001b[39;00m\u001b[39mn\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39m\\n\u001b[39;00m\u001b[39m'\u001b[39m)\n\u001b[0;32m    221\u001b[0m \u001b[39mwith\u001b[39;00m \u001b[39mopen\u001b[39m(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpaths[\u001b[39m\"\u001b[39m\u001b[39moutput\u001b[39m\u001b[39m\"\u001b[39m], \u001b[39m'\u001b[39m\u001b[39mw\u001b[39m\u001b[39m'\u001b[39m) \u001b[39mas\u001b[39;00m f:\n",
      "File \u001b[1;32mc:\\Users\\Noel Nathan\\AppData\\Local\\Programs\\Python\\Python38\\lib\\subprocess.py:495\u001b[0m, in \u001b[0;36mrun\u001b[1;34m(input, capture_output, timeout, check, *popenargs, **kwargs)\u001b[0m\n\u001b[0;32m    493\u001b[0m \u001b[39mwith\u001b[39;00m Popen(\u001b[39m*\u001b[39mpopenargs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs) \u001b[39mas\u001b[39;00m process:\n\u001b[0;32m    494\u001b[0m     \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m--> 495\u001b[0m         stdout, stderr \u001b[39m=\u001b[39m process\u001b[39m.\u001b[39;49mcommunicate(\u001b[39minput\u001b[39;49m, timeout\u001b[39m=\u001b[39;49mtimeout)\n\u001b[0;32m    496\u001b[0m     \u001b[39mexcept\u001b[39;00m TimeoutExpired \u001b[39mas\u001b[39;00m exc:\n\u001b[0;32m    497\u001b[0m         process\u001b[39m.\u001b[39mkill()\n",
      "File \u001b[1;32mc:\\Users\\Noel Nathan\\AppData\\Local\\Programs\\Python\\Python38\\lib\\subprocess.py:1028\u001b[0m, in \u001b[0;36mPopen.communicate\u001b[1;34m(self, input, timeout)\u001b[0m\n\u001b[0;32m   1025\u001b[0m     endtime \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m\n\u001b[0;32m   1027\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m-> 1028\u001b[0m     stdout, stderr \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_communicate(\u001b[39minput\u001b[39;49m, endtime, timeout)\n\u001b[0;32m   1029\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mKeyboardInterrupt\u001b[39;00m:\n\u001b[0;32m   1030\u001b[0m     \u001b[39m# https://bugs.python.org/issue25942\u001b[39;00m\n\u001b[0;32m   1031\u001b[0m     \u001b[39m# See the detailed comment in .wait().\u001b[39;00m\n\u001b[0;32m   1032\u001b[0m     \u001b[39mif\u001b[39;00m timeout \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n",
      "File \u001b[1;32mc:\\Users\\Noel Nathan\\AppData\\Local\\Programs\\Python\\Python38\\lib\\subprocess.py:1399\u001b[0m, in \u001b[0;36mPopen._communicate\u001b[1;34m(self, input, endtime, orig_timeout)\u001b[0m\n\u001b[0;32m   1395\u001b[0m \u001b[39m# Wait for the reader threads, or time out.  If we time out, the\u001b[39;00m\n\u001b[0;32m   1396\u001b[0m \u001b[39m# threads remain reading and the fds left open in case the user\u001b[39;00m\n\u001b[0;32m   1397\u001b[0m \u001b[39m# calls communicate again.\u001b[39;00m\n\u001b[0;32m   1398\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mstdout \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m-> 1399\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mstdout_thread\u001b[39m.\u001b[39;49mjoin(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_remaining_time(endtime))\n\u001b[0;32m   1400\u001b[0m     \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mstdout_thread\u001b[39m.\u001b[39mis_alive():\n\u001b[0;32m   1401\u001b[0m         \u001b[39mraise\u001b[39;00m TimeoutExpired(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39margs, orig_timeout)\n",
      "File \u001b[1;32mc:\\Users\\Noel Nathan\\AppData\\Local\\Programs\\Python\\Python38\\lib\\threading.py:1011\u001b[0m, in \u001b[0;36mThread.join\u001b[1;34m(self, timeout)\u001b[0m\n\u001b[0;32m   1008\u001b[0m     \u001b[39mraise\u001b[39;00m \u001b[39mRuntimeError\u001b[39;00m(\u001b[39m\"\u001b[39m\u001b[39mcannot join current thread\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m   1010\u001b[0m \u001b[39mif\u001b[39;00m timeout \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m-> 1011\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_wait_for_tstate_lock()\n\u001b[0;32m   1012\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m   1013\u001b[0m     \u001b[39m# the behavior of a negative timeout isn't documented, but\u001b[39;00m\n\u001b[0;32m   1014\u001b[0m     \u001b[39m# historically .join(timeout=x) for x<0 has acted as if timeout=0\u001b[39;00m\n\u001b[0;32m   1015\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_wait_for_tstate_lock(timeout\u001b[39m=\u001b[39m\u001b[39mmax\u001b[39m(timeout, \u001b[39m0\u001b[39m))\n",
      "File \u001b[1;32mc:\\Users\\Noel Nathan\\AppData\\Local\\Programs\\Python\\Python38\\lib\\threading.py:1027\u001b[0m, in \u001b[0;36mThread._wait_for_tstate_lock\u001b[1;34m(self, block, timeout)\u001b[0m\n\u001b[0;32m   1025\u001b[0m \u001b[39mif\u001b[39;00m lock \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:  \u001b[39m# already determined that the C code is done\u001b[39;00m\n\u001b[0;32m   1026\u001b[0m     \u001b[39massert\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_is_stopped\n\u001b[1;32m-> 1027\u001b[0m \u001b[39melif\u001b[39;00m lock\u001b[39m.\u001b[39;49macquire(block, timeout):\n\u001b[0;32m   1028\u001b[0m     lock\u001b[39m.\u001b[39mrelease()\n\u001b[0;32m   1029\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_stop()\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "\n",
    "for var in [1, 10, 25, 50, 75, 100, 125, 150, 175, 200, 225, 250, 275, 300, 325, 350, 375, 400, 425]:\n",
    "    problem = Problem(carpeta_extension, domain, 'custom')\n",
    "\n",
    "    n_rovers = 2\n",
    "    suministros = var\n",
    "    personal = var\n",
    "    optim = False\n",
    "\n",
    "    mars_map    = [(1, 2), (2, 3), (1, 3), (3, 4), (4, 5), (4, 6), (5, 6)]\n",
    "    warehouses  = [1, 2, 5, 6]\n",
    "    settlements = [3, 4]\n",
    "    r_map = 0.5\n",
    "    results = experiment(problem, seeds, n_rovers, suministros, personal, mars_map, warehouses, settlements, r_map, optim)\n",
    "    print_results(results, title=f'Transportables:{var *2}')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Experimento 2: Nº de rovers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------------------------------------------\n",
      "Rovers:1\n",
      "Step: 207.3\n",
      "Time: 0.22799270153045653s\n",
      "easy actions: 814.0\n",
      "hard actions: 0.0\n",
      "facts: 406.0\n",
      "actions: 214.0\n",
      "relevant facts: 406.0\n",
      "relevant fluents: 0.0\n",
      "states: 443.5\n",
      "depth: 2.0\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Rovers:2\n",
      "Step: 208.1\n",
      "Time: 0.315733003616333s\n",
      "easy actions: 1628.0\n",
      "hard actions: 0.0\n",
      "facts: 512.0\n",
      "actions: 428.0\n",
      "relevant facts: 512.0\n",
      "relevant fluents: 0.0\n",
      "states: 569.4\n",
      "depth: 2.0\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Rovers:3\n",
      "Step: 210.9\n",
      "Time: 0.35064945220947263s\n",
      "easy actions: 2442.0\n",
      "hard actions: 0.0\n",
      "facts: 618.0\n",
      "actions: 642.0\n",
      "relevant facts: 618.0\n",
      "relevant fluents: 0.0\n",
      "states: 771.4\n",
      "depth: 2.4\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Rovers:4\n",
      "Step: 214.1\n",
      "Time: 0.7546263933181763s\n",
      "easy actions: 3256.0\n",
      "hard actions: 0.0\n",
      "facts: 724.0\n",
      "actions: 856.0\n",
      "relevant facts: 724.0\n",
      "relevant fluents: 0.0\n",
      "states: 1302.0\n",
      "depth: 2.7\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Rovers:5\n",
      "Step: 212.5\n",
      "Time: 0.7004779815673828s\n",
      "easy actions: 4070.0\n",
      "hard actions: 0.0\n",
      "facts: 830.0\n",
      "actions: 1070.0\n",
      "relevant facts: 830.0\n",
      "relevant fluents: 0.0\n",
      "states: 1229.1\n",
      "depth: 2.6\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Rovers:6\n",
      "Step: 213.5\n",
      "Time: 0.6777768135070801s\n",
      "easy actions: 4884.0\n",
      "hard actions: 0.0\n",
      "facts: 936.0\n",
      "actions: 1284.0\n",
      "relevant facts: 936.0\n",
      "relevant fluents: 0.0\n",
      "states: 1241.4\n",
      "depth: 2.9\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Rovers:7\n",
      "Step: 217.2\n",
      "Time: 0.47634966373443605s\n",
      "easy actions: 5698.0\n",
      "hard actions: 0.0\n",
      "facts: 1042.0\n",
      "actions: 1498.0\n",
      "relevant facts: 1042.0\n",
      "relevant fluents: 0.0\n",
      "states: 1159.9\n",
      "depth: 2.9\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Rovers:8\n",
      "Step: 216.8\n",
      "Time: 0.5723157167434693s\n",
      "easy actions: 6512.0\n",
      "hard actions: 0.0\n",
      "facts: 1148.0\n",
      "actions: 1712.0\n",
      "relevant facts: 1148.0\n",
      "relevant fluents: 0.0\n",
      "states: 1286.0\n",
      "depth: 2.9\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Rovers:9\n",
      "Step: 218.6\n",
      "Time: 0.6423964738845825s\n",
      "easy actions: 7326.0\n",
      "hard actions: 0.0\n",
      "facts: 1254.0\n",
      "actions: 1926.0\n",
      "relevant facts: 1254.0\n",
      "relevant fluents: 0.0\n",
      "states: 1499.6\n",
      "depth: 2.9\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Rovers:10\n",
      "Step: 217.7\n",
      "Time: 0.5969735622406006s\n",
      "easy actions: 8140.0\n",
      "hard actions: 0.0\n",
      "facts: 1360.0\n",
      "actions: 2140.0\n",
      "relevant facts: 1360.0\n",
      "relevant fluents: 0.0\n",
      "states: 1410.0\n",
      "depth: 3.0\n",
      "------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "for var in [1,2,3,4,5,6,7,8,9, 10]:\n",
    "    problem = Problem(carpeta_extension, domain, 'custom')\n",
    "\n",
    "    n_rovers = var\n",
    "    suministros = 50\n",
    "    personal = 50\n",
    "    optim = False\n",
    "\n",
    "    mars_map    = [(1, 2), (2, 3), (1, 3), (3, 4), (4, 5), (4, 6), (5, 6)]\n",
    "    warehouses  = [1, 2, 5, 6]\n",
    "    settlements = [3, 4]\n",
    "    r_map = 0.5\n",
    "    results = experiment(problem, seeds, n_rovers, suministros, personal, mars_map, warehouses, settlements, r_map, optim)\n",
    "    print_results(results, title=f'Rovers:{var}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Experimento 3: Ratio de transportables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------------------------------------------\n",
      "Ratio transportables:99.66666666666667\n",
      "Step: 604.3\n",
      "Time: 2.0981489181518556s\n",
      "easy actions: 4828.0\n",
      "hard actions: 0.0\n",
      "facts: 1512.0\n",
      "actions: 1228.0\n",
      "relevant facts: 1512.0\n",
      "relevant fluents: 0.0\n",
      "states: 978.6\n",
      "depth: 2.0\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Ratio transportables:90.0\n",
      "Step: 608.1\n",
      "Time: 3.5546416282653808s\n",
      "easy actions: 4828.0\n",
      "hard actions: 0.0\n",
      "facts: 1512.0\n",
      "actions: 1228.0\n",
      "relevant facts: 1512.0\n",
      "relevant fluents: 0.0\n",
      "states: 1829.1\n",
      "depth: 2.0\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Ratio transportables:80.0\n",
      "Step: 608.1\n",
      "Time: 3.1650241136550905s\n",
      "easy actions: 4828.0\n",
      "hard actions: 0.0\n",
      "facts: 1512.0\n",
      "actions: 1228.0\n",
      "relevant facts: 1512.0\n",
      "relevant fluents: 0.0\n",
      "states: 1763.0\n",
      "depth: 2.0\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Ratio transportables:70.0\n",
      "Step: 608.1\n",
      "Time: 4.502266764640808s\n",
      "easy actions: 4828.0\n",
      "hard actions: 0.0\n",
      "facts: 1512.0\n",
      "actions: 1228.0\n",
      "relevant facts: 1512.0\n",
      "relevant fluents: 0.0\n",
      "states: 1764.5\n",
      "depth: 2.0\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Ratio transportables:60.0\n",
      "Step: 608.1\n",
      "Time: 2.3300180673599242s\n",
      "easy actions: 4828.0\n",
      "hard actions: 0.0\n",
      "facts: 1512.0\n",
      "actions: 1228.0\n",
      "relevant facts: 1512.0\n",
      "relevant fluents: 0.0\n",
      "states: 1712.4\n",
      "depth: 2.0\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Ratio transportables:50.0\n",
      "Step: 608.1\n",
      "Time: 1.7292858600616454s\n",
      "easy actions: 4828.0\n",
      "hard actions: 0.0\n",
      "facts: 1512.0\n",
      "actions: 1228.0\n",
      "relevant facts: 1512.0\n",
      "relevant fluents: 0.0\n",
      "states: 1671.5\n",
      "depth: 2.0\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Ratio transportables:40.0\n",
      "Step: 608.1\n",
      "Time: 2.510051393508911s\n",
      "easy actions: 4828.0\n",
      "hard actions: 0.0\n",
      "facts: 1512.0\n",
      "actions: 1228.0\n",
      "relevant facts: 1512.0\n",
      "relevant fluents: 0.0\n",
      "states: 1625.5\n",
      "depth: 2.0\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Ratio transportables:30.0\n",
      "Step: 608.1\n",
      "Time: 3.3207629919052124s\n",
      "easy actions: 4828.0\n",
      "hard actions: 0.0\n",
      "facts: 1512.0\n",
      "actions: 1228.0\n",
      "relevant facts: 1512.0\n",
      "relevant fluents: 0.0\n",
      "states: 1579.7\n",
      "depth: 2.0\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Ratio transportables:20.0\n",
      "Step: 608.1\n",
      "Time: 2.9707005977630616s\n",
      "easy actions: 4828.0\n",
      "hard actions: 0.0\n",
      "facts: 1512.0\n",
      "actions: 1228.0\n",
      "relevant facts: 1512.0\n",
      "relevant fluents: 0.0\n",
      "states: 1520.4\n",
      "depth: 2.0\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Ratio transportables:10.0\n",
      "Step: 608.1\n",
      "Time: 2.3357992649078367s\n",
      "easy actions: 4828.0\n",
      "hard actions: 0.0\n",
      "facts: 1512.0\n",
      "actions: 1228.0\n",
      "relevant facts: 1512.0\n",
      "relevant fluents: 0.0\n",
      "states: 1474.8\n",
      "depth: 2.0\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Ratio transportables:0.33333333333333337\n",
      "Step: 608.9\n",
      "Time: 3.0343156337738035s\n",
      "easy actions: 4828.0\n",
      "hard actions: 0.0\n",
      "facts: 1512.0\n",
      "actions: 1228.0\n",
      "relevant facts: 1512.0\n",
      "relevant fluents: 0.0\n",
      "states: 1643.4\n",
      "depth: 2.2\n",
      "------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "for var in [1, 30, 60, 90, 120, 150, 180, 210, 240, 270, 299]:\n",
    "    problem = Problem(carpeta_extension, domain, 'custom')\n",
    "\n",
    "    n_rovers = 2\n",
    "    suministros = var\n",
    "    personal = 300 - var\n",
    "    optim = False\n",
    "\n",
    "    mars_map    = [(1, 2), (2, 3), (1, 3), (3, 4), (4, 5), (4, 6), (5, 6)]\n",
    "    warehouses  = [1, 2, 5, 6]\n",
    "    settlements = [3, 4]\n",
    "    r_map = 0.5\n",
    "    results = experiment(problem, seeds, n_rovers, suministros, personal, mars_map, warehouses, settlements, r_map, optim)\n",
    "    print_results(results, title=f'Ratio transportables:{(300 - var) / 300 * 100}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Experimento 4 Ratio & Distribution bases"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------------------------------------------\n",
      "Map:[(1, 2), (2, 3), (3, 4), (4, 5), (5, 6), (6, 7), (7, 8), (8, 9), (9, 1)]\n",
      "Step: 251.6\n",
      "Time: 0.23464787006378174s\n",
      "easy actions: 2636.0\n",
      "hard actions: 0.0\n",
      "facts: 518.0\n",
      "actions: 436.0\n",
      "relevant facts: 518.0\n",
      "relevant fluents: 0.0\n",
      "states: 3611.1\n",
      "depth: 4.4\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Map:[(1, 2), (2, 3), (3, 4), (4, 5), (5, 6), (6, 7), (7, 8), (8, 9)]\n",
      "Step: 273.7\n",
      "Time: 2.2582230806350707s\n",
      "easy actions: 2632.0\n",
      "hard actions: 0.0\n",
      "facts: 518.0\n",
      "actions: 432.0\n",
      "relevant facts: 518.0\n",
      "relevant fluents: 0.0\n",
      "states: 18176.1\n",
      "depth: 5.8\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Map:[(5, 1), (5, 2), (5, 3), (5, 4), (5, 6), (5, 7), (5, 8), (5, 9)]\n",
      "Step: 239.0\n",
      "Time: 1.1933164834976195s\n",
      "easy actions: 2632.0\n",
      "hard actions: 0.0\n",
      "facts: 518.0\n",
      "actions: 432.0\n",
      "relevant facts: 518.0\n",
      "relevant fluents: 0.0\n",
      "states: 7320.4\n",
      "depth: 3.3\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Map:[(1, 2), (1, 4), (2, 3), (2, 5), (3, 6), (4, 5), (4, 7), (5, 6), (5, 8), (6, 9), (7, 8), (8, 9)]\n",
      "Step: 315.9\n",
      "Time: 1.6200983285903932s\n",
      "easy actions: 2648.0\n",
      "hard actions: 0.0\n",
      "facts: 518.0\n",
      "actions: 448.0\n",
      "relevant facts: 518.0\n",
      "relevant fluents: 0.0\n",
      "states: 17348.2\n",
      "depth: 4.3\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Map:[(1, 2), (1, 3), (2, 4), (3, 4), (4, 5), (5, 6), (6, 7), (6, 8), (7, 9), (8, 9)]\n",
      "Step: 244.6\n",
      "Time: 4.443374443054199s\n",
      "easy actions: 2640.0\n",
      "hard actions: 0.0\n",
      "facts: 518.0\n",
      "actions: 440.0\n",
      "relevant facts: 518.0\n",
      "relevant fluents: 0.0\n",
      "states: 25903.3\n",
      "depth: 4.5\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Map:[(1, 2), (1, 3), (1, 4), (1, 5), (1, 6), (1, 7), (1, 8), (1, 9), (2, 3), (2, 4), (2, 5), (2, 6), (2, 7), (2, 8), (2, 9), (3, 4), (3, 5), (3, 6), (3, 7), (3, 8), (3, 9), (4, 5), (4, 6), (4, 7), (4, 8), (4, 9), (5, 6), (5, 7), (5, 8), (5, 9), (6, 7), (6, 8), (6, 9), (7, 8), (7, 9), (8, 9)]\n",
      "Step: 223.5\n",
      "Time: 0.46197261810302737s\n",
      "easy actions: 2744.0\n",
      "hard actions: 0.0\n",
      "facts: 518.0\n",
      "actions: 544.0\n",
      "relevant facts: 518.0\n",
      "relevant fluents: 0.0\n",
      "states: 2752.2\n",
      "depth: 2.9\n",
      "------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "for var in [\n",
    "        [(1, 2), (2, 3), (3, 4), (4, 5), (5, 6), (6, 7), (7, 8), (8, 9), (9, 1)],                           # Circulo\n",
    "        [(1, 2), (2, 3), (3, 4), (4, 5), (5, 6), (6, 7), (7, 8), (8, 9)],                                   # Linea\n",
    "        [(5, 1), (5, 2), (5, 3), (5, 4), (5, 6), (5, 7), (5, 8), (5, 9)],                                   # Punto central\n",
    "        [(1, 2), (1, 4), (2, 3), (2, 5), (3, 6), (4, 5), (4, 7), (5, 6), (5, 8), (6, 9), (7, 8), (8, 9)],   # Manhattan \n",
    "        [(1, 2), (1, 3), (2, 4), (3, 4), (4, 5), (5, 6), (6, 7), (6, 8), (7, 9), (8, 9)],                   # Dos cuadrados unidos por un vertice\n",
    "        [\n",
    "            (1, 2), (1, 3), (1, 4), (1, 5), (1, 6), (1, 7), (1, 8), (1, 9),                                 # Todos con todos\n",
    "            (2, 3), (2, 4), (2, 5), (2, 6), (2, 7), (2, 8), (2, 9),\n",
    "            (3, 4), (3, 5), (3, 6), (3, 7), (3, 8), (3, 9),\n",
    "            (4, 5), (4, 6), (4, 7), (4, 8), (4, 9),\n",
    "            (5, 6), (5, 7), (5, 8), (5, 9),\n",
    "            (6, 7), (6, 8), (6, 9),\n",
    "            (7, 8), (7, 9),\n",
    "            (8, 9)\n",
    "        ]\n",
    "    ]:\n",
    "    for r in [0.1, 0.5, 0.9]:\n",
    "\n",
    "        problem = Problem(carpeta_extension, domain, 'custom')\n",
    "\n",
    "        n_rovers = 2\n",
    "        suministros = 50\n",
    "        personal = 50\n",
    "        optim = False\n",
    "\n",
    "        mars_map = var\n",
    "        warehouses  = [1, 3, 5, 7, 9]\n",
    "        settlements = [2, 4, 6, 8]\n",
    "        r_map = 0.5\n",
    "        results = experiment(problem, seeds, n_rovers, suministros, personal, mars_map, warehouses, settlements, r_map, optim)\n",
    "        print_results(results, title=f'Ratio: {r} Map:{var}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Experiment 5 Nº Bases"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[1;32mIn [9], line 30\u001b[0m\n\u001b[0;32m     28\u001b[0m settlements \u001b[39m=\u001b[39m []\n\u001b[0;32m     29\u001b[0m r_map \u001b[39m=\u001b[39m \u001b[39m0.5\u001b[39m\n\u001b[1;32m---> 30\u001b[0m results \u001b[39m=\u001b[39m experiment(problem, seeds, n_rovers, suministros, personal, var, warehouses, settlements, r_map, optim)\n\u001b[0;32m     31\u001b[0m print_results(results, title\u001b[39m=\u001b[39m\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mMap:\u001b[39m\u001b[39m{\u001b[39;00mvar\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m)\n",
      "Cell \u001b[1;32mIn [8], line 14\u001b[0m, in \u001b[0;36mexperiment\u001b[1;34m(problem, seeds, n_rovers, suministros, personal, mars_map, warehouses, settlements, r_map, optim, comb_min_rover, comb_max_rover, comb, prio, pedidos_adicionales)\u001b[0m\n\u001b[0;32m     12\u001b[0m problem\u001b[39m.\u001b[39mwrite_problem(objects, init)\n\u001b[0;32m     13\u001b[0m start     \u001b[39m=\u001b[39m time\u001b[39m.\u001b[39mtime()\n\u001b[1;32m---> 14\u001b[0m problem\u001b[39m.\u001b[39;49mexecute(optim)\n\u001b[0;32m     15\u001b[0m end       \u001b[39m=\u001b[39m time\u001b[39m.\u001b[39mtime()\n\u001b[0;32m     16\u001b[0m steps, times, result \u001b[39m=\u001b[39m problem\u001b[39m.\u001b[39mread_output(comb, prio)\n",
      "File \u001b[1;32mc:\\Users\\Noel Nathan\\Desktop\\Universidad\\3r Quadrimestre\\ABIA\\ABIA_PDDL_Project\\Python\\generator.py:218\u001b[0m, in \u001b[0;36mProblem.execute\u001b[1;34m(self, optim)\u001b[0m\n\u001b[0;32m    216\u001b[0m O \u001b[39m=\u001b[39m \u001b[39m\"\u001b[39m\u001b[39m -O \u001b[39m\u001b[39m\"\u001b[39m \u001b[39mif\u001b[39;00m optim \u001b[39melse\u001b[39;00m \u001b[39m\"\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m    217\u001b[0m cmd \u001b[39m=\u001b[39m \u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m{\u001b[39;00m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpaths[\u001b[39m\"\u001b[39m\u001b[39mexecutable\u001b[39m\u001b[39m\"\u001b[39m]\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m\u001b[39m \u001b[39m\u001b[39m{\u001b[39;00mO\u001b[39m}\u001b[39;00m\u001b[39m-o \u001b[39m\u001b[39m\"\u001b[39m\u001b[39m{\u001b[39;00m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpaths[\u001b[39m\"\u001b[39m\u001b[39mdomain\u001b[39m\u001b[39m\"\u001b[39m]\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m\u001b[39m -f \u001b[39m\u001b[39m\"\u001b[39m\u001b[39m{\u001b[39;00m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpaths[\u001b[39m\"\u001b[39m\u001b[39mproblem\u001b[39m\u001b[39m\"\u001b[39m]\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m\u001b[39m'\u001b[39m\n\u001b[1;32m--> 218\u001b[0m output \u001b[39m=\u001b[39m subprocess\u001b[39m.\u001b[39;49mrun(shlex\u001b[39m.\u001b[39;49msplit(cmd), capture_output\u001b[39m=\u001b[39;49m\u001b[39mTrue\u001b[39;49;00m)\u001b[39m.\u001b[39mstdout\n\u001b[0;32m    219\u001b[0m output \u001b[39m=\u001b[39m \u001b[39mstr\u001b[39m(output)\u001b[39m.\u001b[39mreplace(\u001b[39m'\u001b[39m\u001b[39m\\\\\u001b[39;00m\u001b[39mn\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39m\\n\u001b[39;00m\u001b[39m'\u001b[39m)\n\u001b[0;32m    221\u001b[0m \u001b[39mwith\u001b[39;00m \u001b[39mopen\u001b[39m(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpaths[\u001b[39m\"\u001b[39m\u001b[39moutput\u001b[39m\u001b[39m\"\u001b[39m], \u001b[39m'\u001b[39m\u001b[39mw\u001b[39m\u001b[39m'\u001b[39m) \u001b[39mas\u001b[39;00m f:\n",
      "File \u001b[1;32mc:\\Users\\Noel Nathan\\AppData\\Local\\Programs\\Python\\Python38\\lib\\subprocess.py:495\u001b[0m, in \u001b[0;36mrun\u001b[1;34m(input, capture_output, timeout, check, *popenargs, **kwargs)\u001b[0m\n\u001b[0;32m    493\u001b[0m \u001b[39mwith\u001b[39;00m Popen(\u001b[39m*\u001b[39mpopenargs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs) \u001b[39mas\u001b[39;00m process:\n\u001b[0;32m    494\u001b[0m     \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m--> 495\u001b[0m         stdout, stderr \u001b[39m=\u001b[39m process\u001b[39m.\u001b[39;49mcommunicate(\u001b[39minput\u001b[39;49m, timeout\u001b[39m=\u001b[39;49mtimeout)\n\u001b[0;32m    496\u001b[0m     \u001b[39mexcept\u001b[39;00m TimeoutExpired \u001b[39mas\u001b[39;00m exc:\n\u001b[0;32m    497\u001b[0m         process\u001b[39m.\u001b[39mkill()\n",
      "File \u001b[1;32mc:\\Users\\Noel Nathan\\AppData\\Local\\Programs\\Python\\Python38\\lib\\subprocess.py:1028\u001b[0m, in \u001b[0;36mPopen.communicate\u001b[1;34m(self, input, timeout)\u001b[0m\n\u001b[0;32m   1025\u001b[0m     endtime \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m\n\u001b[0;32m   1027\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m-> 1028\u001b[0m     stdout, stderr \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_communicate(\u001b[39minput\u001b[39;49m, endtime, timeout)\n\u001b[0;32m   1029\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mKeyboardInterrupt\u001b[39;00m:\n\u001b[0;32m   1030\u001b[0m     \u001b[39m# https://bugs.python.org/issue25942\u001b[39;00m\n\u001b[0;32m   1031\u001b[0m     \u001b[39m# See the detailed comment in .wait().\u001b[39;00m\n\u001b[0;32m   1032\u001b[0m     \u001b[39mif\u001b[39;00m timeout \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n",
      "File \u001b[1;32mc:\\Users\\Noel Nathan\\AppData\\Local\\Programs\\Python\\Python38\\lib\\subprocess.py:1399\u001b[0m, in \u001b[0;36mPopen._communicate\u001b[1;34m(self, input, endtime, orig_timeout)\u001b[0m\n\u001b[0;32m   1395\u001b[0m \u001b[39m# Wait for the reader threads, or time out.  If we time out, the\u001b[39;00m\n\u001b[0;32m   1396\u001b[0m \u001b[39m# threads remain reading and the fds left open in case the user\u001b[39;00m\n\u001b[0;32m   1397\u001b[0m \u001b[39m# calls communicate again.\u001b[39;00m\n\u001b[0;32m   1398\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mstdout \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m-> 1399\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mstdout_thread\u001b[39m.\u001b[39;49mjoin(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_remaining_time(endtime))\n\u001b[0;32m   1400\u001b[0m     \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mstdout_thread\u001b[39m.\u001b[39mis_alive():\n\u001b[0;32m   1401\u001b[0m         \u001b[39mraise\u001b[39;00m TimeoutExpired(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39margs, orig_timeout)\n",
      "File \u001b[1;32mc:\\Users\\Noel Nathan\\AppData\\Local\\Programs\\Python\\Python38\\lib\\threading.py:1011\u001b[0m, in \u001b[0;36mThread.join\u001b[1;34m(self, timeout)\u001b[0m\n\u001b[0;32m   1008\u001b[0m     \u001b[39mraise\u001b[39;00m \u001b[39mRuntimeError\u001b[39;00m(\u001b[39m\"\u001b[39m\u001b[39mcannot join current thread\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m   1010\u001b[0m \u001b[39mif\u001b[39;00m timeout \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m-> 1011\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_wait_for_tstate_lock()\n\u001b[0;32m   1012\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m   1013\u001b[0m     \u001b[39m# the behavior of a negative timeout isn't documented, but\u001b[39;00m\n\u001b[0;32m   1014\u001b[0m     \u001b[39m# historically .join(timeout=x) for x<0 has acted as if timeout=0\u001b[39;00m\n\u001b[0;32m   1015\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_wait_for_tstate_lock(timeout\u001b[39m=\u001b[39m\u001b[39mmax\u001b[39m(timeout, \u001b[39m0\u001b[39m))\n",
      "File \u001b[1;32mc:\\Users\\Noel Nathan\\AppData\\Local\\Programs\\Python\\Python38\\lib\\threading.py:1027\u001b[0m, in \u001b[0;36mThread._wait_for_tstate_lock\u001b[1;34m(self, block, timeout)\u001b[0m\n\u001b[0;32m   1025\u001b[0m \u001b[39mif\u001b[39;00m lock \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:  \u001b[39m# already determined that the C code is done\u001b[39;00m\n\u001b[0;32m   1026\u001b[0m     \u001b[39massert\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_is_stopped\n\u001b[1;32m-> 1027\u001b[0m \u001b[39melif\u001b[39;00m lock\u001b[39m.\u001b[39;49macquire(block, timeout):\n\u001b[0;32m   1028\u001b[0m     lock\u001b[39m.\u001b[39mrelease()\n\u001b[0;32m   1029\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_stop()\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "from maps_generator import * \n",
    "# 6 bases\n",
    "l6 = line(1, 6)\n",
    "c6 = circle(1, 6)\n",
    "a6 = all_connected(6)\n",
    "_2b6 = two_blocks(6)\n",
    "\n",
    "# 12 bases\n",
    "l12 = line(1, 12)\n",
    "c12 = circle(1, 12)\n",
    "a12 = all_connected(12)\n",
    "_2b12 = two_blocks(12)\n",
    "# 18 bases\n",
    "\n",
    "l18 = line(1, 18)\n",
    "c18 = circle(1, 18)\n",
    "a18 = all_connected(18)\n",
    "_2b18 = two_blocks(18)\n",
    "\n",
    "for var in [l6, c6, a6, _2b6, l12, c12, a12, _2b12, l18, c18, a18, _2b18]:\n",
    "    problem = Problem(carpeta_extension, domain, 'custom')\n",
    "    n_rovers = 2\n",
    "    suministros = 50\n",
    "    personal = 50\n",
    "    optim = False\n",
    "\n",
    "    warehouses  = []\n",
    "    settlements = []\n",
    "    r_map = 0.5\n",
    "    results = experiment(problem, seeds, n_rovers, suministros, personal, var, warehouses, settlements, r_map, optim)\n",
    "    print_results(results, title=f'Map:{var}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Experimento 6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------------------------------------------\n",
      "Map:10\n",
      "Step: 235.9\n",
      "Time: 0.17234251499176026s\n",
      "easy actions: 1824.0\n",
      "hard actions: 0.0\n",
      "facts: 522.0\n",
      "actions: 438.0\n",
      "relevant facts: 519.0\n",
      "relevant fluents: 0.0\n",
      "states: 1115.7\n",
      "depth: 3.6\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Map:20\n",
      "Step: 232.7\n",
      "Time: 0.17762067317962646s\n",
      "easy actions: 1824.0\n",
      "hard actions: 0.0\n",
      "facts: 532.0\n",
      "actions: 449.4\n",
      "relevant facts: 524.7\n",
      "relevant fluents: 0.0\n",
      "states: 1099.5\n",
      "depth: 3.6\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Map:30\n",
      "Step: 236.1\n",
      "Time: 0.2041555643081665s\n",
      "easy actions: 1824.0\n",
      "hard actions: 0.0\n",
      "facts: 542.0\n",
      "actions: 461.8\n",
      "relevant facts: 530.9\n",
      "relevant fluents: 0.0\n",
      "states: 1273.3\n",
      "depth: 3.7\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Map:40\n",
      "Step: 237.3\n",
      "Time: 0.22320146560668946s\n",
      "easy actions: 1824.0\n",
      "hard actions: 0.0\n",
      "facts: 552.0\n",
      "actions: 473.6\n",
      "relevant facts: 536.8\n",
      "relevant fluents: 0.0\n",
      "states: 1302.2\n",
      "depth: 3.8\n",
      "------------------------------------------\n",
      "------------------------------------------\n",
      "Map:50\n",
      "Step: 243.7\n",
      "Time: 0.2220985174179077s\n",
      "easy actions: 1824.0\n",
      "hard actions: 0.0\n",
      "facts: 562.0\n",
      "actions: 485.4\n",
      "relevant facts: 542.7\n",
      "relevant fluents: 0.0\n",
      "states: 1188.7\n",
      "depth: 3.8\n",
      "------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "from maps_generator import * \n",
    "c6 = circle(1, 6)\n",
    "\n",
    "\n",
    "for var in [0, 10, 20, 30, 40, 50]:\n",
    "    problem = Problem(carpeta_extension, domain, 'custom')\n",
    "    n_rovers = 2\n",
    "    suministros = 50\n",
    "    personal = 50\n",
    "    optim = False\n",
    "    mars_map = c6\n",
    "    warehouses  = [1,2,3]\n",
    "    settlements = [4,5,6]\n",
    "    r_map = 0.5\n",
    "    results = experiment(problem, seeds, n_rovers, suministros, personal, mars_map, warehouses, settlements, r_map, optim, pedidos_adicionales = var)\n",
    "    print_results(results, title=f'Map:{var}')"
   ]
  }
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