code test.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Root directory /home/giuseppe/src/cmans\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import pickle\n",
    "import numpy as np\n",
    "from core.population import archive\n",
    "from parameters import *\n",
    "from operator import itemgetter\n",
    "from scipy.spatial.distance import pdist, cdist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "exp_path = os.path.join(ROOT_DIR, 'experiment_data/Walker2D_CMA-NS')\n",
    "paths = [os.path.join(exp_path, d) for d in os.listdir(exp_path)]\n",
    "# paths = [os.path.join(exp_path, d) for d in ['2020_09_09_18:03_609206', '2020_09_09_18:02_983088']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:54_729562\n",
      "Loading parameters...\n",
      "Done\n",
      "Empty rew arch for 5\n",
      "Loading sigma 5\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:54_189100\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 4.5\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:38_058027\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 0.8\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_14_10:45_593495\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 0.002\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_18:03_609206\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 12\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:49_407128\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 3.5\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:54_729882\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 4\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:58_482796\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 8\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:34_273409\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 0.2\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_18:02_214148\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 10\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:58_070031\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 6\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:26_935521\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 0.01\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:58_363711\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 7.5\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:58_278778\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 6.5\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_14_10:45_057866\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 0.005\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_18:02_983088\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 11\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:46_852198\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 1.5\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:49_073367\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 3\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_18:01_160004\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 8.5\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:38_065074\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 0.7\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_14_10:45_591913\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 0.001\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:34_546982\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 0.5\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:26_208704\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 0.1\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:34_540236\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 0.3\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_14_10:44_540329\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 0.007\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:42_643332\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 1.1\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:57_867979\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 5.5\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:26_962012\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 0.05\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_18:02_516650\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 9.5\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:46_463596\n",
      "Loading parameters...\n",
      "Done\n",
      "Empty rew arch for 1.7\n",
      "Loading sigma 1.7\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:42_630328\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 1.2\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:39_114567\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 0.9\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:49_777611\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 2.5\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:46_441568\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 2\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:58_854628\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 7\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_18:02_816790\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 9\n",
      "\n",
      "/home/giuseppe/src/cmans/experiment_data/Walker2D_CMA-NS/2020_09_09_17:41_919574\n",
      "Loading parameters...\n",
      "Done\n",
      "Loading sigma 1\n",
      "\n"
     ]
    }
   ],
   "source": [
    "rew_archives = []\n",
    "archives = []\n",
    "for path in paths:\n",
    "    try:\n",
    "        print(path)\n",
    "        params.load(os.path.join(path, '_params.json'))\n",
    "        arch = archive.Archive(params)\n",
    "        arch.sigma = params.cma_es_sigma\n",
    "        arch.load(os.path.join(path, 'rew_archive_final.pkl'))\n",
    "        if arch.size > 0:\n",
    "            rew_archives.append(arch)\n",
    "        else:\n",
    "           print(\"Empty rew arch for {}\".format(params.cma_es_sigma))\n",
    "            \n",
    "        arch = archive.Archive(params)\n",
    "        arch.sigma = params.cma_es_sigma\n",
    "        print(\"Loading sigma {}\".format(params.cma_es_sigma))\n",
    "        arch.load(os.path.join(path, 'archive_final.pkl'))\n",
    "        if arch.size > 0:\n",
    "            archives.append(arch)\n",
    "        print()\n",
    "    except:\n",
    "        print(\"No archive for {}\".format(path))\n",
    "        continue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "rew_arch_size = []\n",
    "rews = []\n",
    "rew_genomes = []\n",
    "for arch in rew_archives:\n",
    "    rew_arch_size.append([arch.sigma, arch.size])\n",
    "    rews.append([arch.sigma, np.stack(arch['reward'])])\n",
    "    rew_genomes.append([arch.sigma, arch['genome']])\n",
    "rew_arch_size = np.array(rew_arch_size)\n",
    "rew_arch_size = rew_arch_size[rew_arch_size[:,0].argsort()]\n",
    "rews = np.array(sorted(rews, key=itemgetter(0)), dtype=object)\n",
    "rew_genomes = np.array(sorted(rew_genomes, key=itemgetter(0)), dtype=object)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.001: 141\n",
      "0.002: 156\n",
      "0.005: 191\n",
      "0.007: 213\n",
      "0.01: 141\n",
      "0.05: 102\n",
      "0.1: 38\n",
      "0.2: 19\n",
      "0.3: 16\n",
      "0.5: 9\n",
      "0.7: 2\n",
      "0.8: 18\n",
      "0.9: 4\n",
      "1: 14\n",
      "1.1: 2\n",
      "1.2: 4\n",
      "1.5: 4\n",
      "2: 2\n",
      "2.5: 3\n",
      "3: 6\n",
      "3.5: 2\n",
      "4: 3\n",
      "4.5: 5\n",
      "5.5: 3\n",
      "6: 7\n",
      "6.5: 1\n",
      "7: 4\n",
      "7.5: 2\n",
      "8: 1\n",
      "8.5: 7\n",
      "9: 6\n",
      "9.5: 6\n",
      "10: 1\n",
      "11: 6\n",
      "12: 3\n"
     ]
    }
   ],
   "source": [
    "for gen in rew_genomes:\n",
    "    print(\"{}: {}\".format(gen[0], len(gen[1])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "arch_size = []\n",
    "genomes = []\n",
    "for arch in archives:\n",
    "    arch_size.append([arch.sigma, arch.size])\n",
    "    genomes.append([arch.sigma, arch['genome']])\n",
    "arch_size = np.array(arch_size)\n",
    "arch_size = arch_size[arch_size[:,0].argsort()]\n",
    "genomes = np.array(sorted(genomes, key=itemgetter(0)), dtype=object)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Distance')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x1152 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "figure, axes = plt.subplots(3,1, figsize=(20, 16))\n",
    "axes[0].plot(list(range(len(rew_arch_size[:, 0]))), rew_arch_size[:, 1],'ro')\n",
    "axes[0].plot(list(range(len(rew_arch_size[:, 0]))), rew_arch_size[:, 1])\n",
    "axes[0].set_title('Reward Archive size')\n",
    "axes[0].set_xticks(list(range(len(rew_arch_size[:, 0]))))\n",
    "axes[0].set_xticklabels(rew_arch_size[:, 0])\n",
    "axes[0].set_xlabel('Sigma')\n",
    "axes[0].set_ylabel('Rew archive size')\n",
    "\n",
    "axes[1].violinplot(rews[:, 1], positions=list(range(len(rews[:, 0]))), showmeans=True, showmedians=False,\n",
    "        showextrema=True)\n",
    "axes[1].scatter(list(range(len(rews[:, 0]))), [np.median(a) for a in rews[:, 1]], marker='o', color='black', s=30, zorder=3)\n",
    "axes[1].set_xticks(list(range(len(rews[:, 0]))))\n",
    "axes[1].set_xticklabels(rews[:, 0])\n",
    "axes[1].set_title('Rewards')\n",
    "axes[1].set_xlabel('Sigma')\n",
    "axes[1].set_ylabel('Rewards')\n",
    "\n",
    "limit_idx = np.where(genomes[:, 0] == 1)[0][0] + 1\n",
    "axes[2].plot(list(range(len(rew_genomes[:limit_idx, 0]))), [np.mean(pdist(gen[1])) for gen in rew_genomes[:limit_idx]])\n",
    "axes[2].plot(list(range(len(rew_genomes[:limit_idx, 0]))), [np.mean(pdist(gen[1])) for gen in rew_genomes[:limit_idx]], 'ro')\n",
    "axes[2].set_title('Avg archive distance in parameter space')\n",
    "axes[2].set_xticks(list(range(len(rew_genomes[:limit_idx, 0]))))\n",
    "axes[2].set_xticklabels(rew_genomes[:limit_idx, 0])\n",
    "axes[2].plot(list(range(len(genomes[:limit_idx, 0]))), [np.mean(pdist(gen[1])) for gen in genomes[:limit_idx]])\n",
    "axes[2].plot(list(range(len(genomes[:limit_idx, 0]))), [np.mean(pdist(gen[1])) for gen in genomes[:limit_idx]], 'bo')\n",
    "axes[2].set_xlabel('Sigma')\n",
    "axes[2].set_ylabel('Distance')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}