01_visualize_valfar.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>.container { width:100% !important; }</style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "from IPython.core.display import display, HTML\n",
    "display(HTML(\"<style>.container { width:100% !important; }</style>\"))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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baUci+lArb/nkMZ+JTGUkc/mWfPJoTnsG8SJn0Y+kytpKmZ8P27Y5z5fcsuXA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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ffb981a9eb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "np.set_printoptions(precision=3, suppress=True)\n",
    "import library.helpers as h\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from sklearn.metrics import auc\n",
    "from scipy.integrate import simps\n",
    "from scipy.interpolate import interp1d\n",
    "\n",
    "\n",
    "LOG_NAME = \"unix_forensic\"\n",
    "VIZUALIZATIONS_DIR = \"visualizations\"\n",
    "\n",
    "fig = plt.figure(figsize=(10,10))\n",
    "\n",
    "# TODO redo this one [ \n",
    "MODEL_NAMES = [ \"lstm-ae\", \"triplet-la\", \"triplet-jd-la-all-40-70-all-all\", \"triplet-jd-la-non-60-65-non-non\",  \"triplet-jd-la-00500-60-65-all-all-00001\", \n",
    "              \"triplet-jd-la-00500-60-65-all-00001-non\", \"triplet-jd-la-01000-60-65-all-all-00001\", \"triplet-jd-la-05000-60-65-all-all-00001\", \"jd-la-x05000-pt60-nt65-llall-lcall-ee00001-ep20\", \"jd-la-xnon-pt40-nt70-llall-lcall-ee00001-ep50\"] \n",
    "\n",
    "\n",
    "MODEL_NAMES_JD = [\n",
    "    \"triplet-jd-la-all-40-70-all-all\", # baseline, all labels\n",
    "    \"triplet-jd-la-non-60-65-non-non\",\"triplet-jd-la-non-40-70-non-non\",  # jd no labels, 10 ep\n",
    "    \"jd-la-xnon-pt60-nt65-llnon-lcnon-eenon-ep50\", \n",
    "    \"jd-la-xnon-pt30-nt75-llnon-lcnon-eenon-ep50\"\n",
    "    #\"jd-la-x02000-pt55-nt65-llnon-lc00003-ee00002-ep10\",\"jd-la-x02000-pt55-nt65-llnon-lc00003-ee00002-ep20\",\n",
    "    #\"triplet-jd-la-05000-60-65-all-all-00001\", \"jd-la-x05000-pt60-nt65-llall-lcall-ee00001-ep20\",\n",
    "] \n",
    "\n",
    "MODEL_NAMES_LA = [\n",
    "    \"triplet-jd-la-all-40-70-all-all\", # baseline, all labels\n",
    "    \"jd-la-x00500-pt30-nt70-llall-lcall-ee00002-ep30\", # 500 labels \n",
    "    \"jd-la-x01000-pt30-nt70-llall-lcall-ee00002-ep30\", # 1000 labels\n",
    "    \"jd-la-x02000-pt30-nt70-llall-lcall-ee00002-ep30\", # 2000 labels\n",
    "    \"jd-la-x02500-pt30-nt70-llall-lcall-ee00002-ep30\", # 2500 labels \n",
    "    \"jd-la-x05000-pt30-nt70-llall-lcall-ee00002-ep30\", # 5000 labels \n",
    "] \n",
    "\n",
    "MODEL_NAMES_NT60 = [\n",
    "    \"jd-la-xnon-pt10-nt60-llnon-lcnon-ee00002-ep30\", # \n",
    "    \"jd-la-xnon-pt20-nt60-llnon-lcnon-ee00002-ep30\", # \n",
    "    \"jd-la-xnon-pt30-nt60-llnon-lcnon-ee00002-ep30\", # \n",
    "    \"jd-la-xnon-pt40-nt60-llnon-lcnon-ee00002-ep30\", # \n",
    "    \"jd-la-xnon-pt50-nt60-llnon-lcnon-ee00002-ep30\",\n",
    "]\n",
    "\n",
    "MODEL_NAMES_NT70 = [\n",
    "    \"jd-la-xnon-pt10-nt70-llnon-lcnon-ee00002-ep30\", # \n",
    "    \"jd-la-xnon-pt20-nt70-llnon-lcnon-ee00002-ep30\", # \n",
    "    \"jd-la-xnon-pt30-nt70-llnon-lcnon-ee00002-ep30\", # \n",
    "    \"jd-la-xnon-pt40-nt70-llnon-lcnon-ee00002-ep30\", # \n",
    "    \"jd-la-xnon-pt50-nt70-llnon-lcnon-ee00002-ep30\",\n",
    "    \"jd-la-xnon-pt60-nt70-llnon-lcnon-ee00002-ep30\"\n",
    "]\n",
    "\n",
    "MODEL_NAMES_NT80 = [\n",
    "    \"jd-la-xnon-pt10-nt80-llnon-lcnon-ee00002-ep30\", # \n",
    "    \"jd-la-xnon-pt20-nt80-llnon-lcnon-ee00002-ep30\", # \n",
    "    \"jd-la-xnon-pt30-nt80-llnon-lcnon-ee00002-ep30\", # \n",
    "    \"jd-la-xnon-pt40-nt80-llnon-lcnon-ee00002-ep30\", # \n",
    "    \"jd-la-xnon-pt50-nt80-llnon-lcnon-ee00002-ep30\",\n",
    "    \"jd-la-xnon-pt60-nt80-llnon-lcnon-ee00002-ep30\",\n",
    "    \"jd-la-xnon-pt70-nt80-llnon-lcnon-ee00002-ep30\"\n",
    "]\n",
    "\n",
    "MODEL_NAMES_10 = [\n",
    "    #\"jd-la-xnon-pt10-nt90-llnon-lcnon-ee00002-ep20\",\n",
    "    #\"jd-la-xnon-pt20-nt90-llnon-lcnon-ee00002-ep20\",\n",
    "    #\"jd-la-xnon-pt30-nt90-llnon-lcnon-ee00002-ep20\",\n",
    "    #\"jd-la-xnon-pt40-nt90-llnon-lcnon-ee00002-ep20\",\n",
    "    \"jd-la-xnon-pt50-nt90-llnon-lcnon-ee00002-ep20\",\n",
    "    \"jd-la-xnon-pt52-nt70-llnon-lcnon-ee00002-ep30\",\n",
    "    #\"jd-la-xnon-pt60-nt90-llnon-lcnon-ee00002-ep20\",\n",
    "    #\"jd-la-xnon-pt70-nt90-llnon-lcnon-ee00002-ep20\",\n",
    "    #\"jd-la-xnon-pt80-nt90-llnon-lcnon-ee00002-ep20\",\n",
    "    \"jd-la-xnon-pt52-nt90-llnon-lcnon-ee00002-ep200\",\n",
    "    \n",
    "]\n",
    "\n",
    "\n",
    "\n",
    "MODEL_NAMES = MODEL_NAMES_LA\n",
    "\n",
    "# \"triplet-jd-la-2000-55-70-40\", \"lstm-ae\", \"triplet-la\", \"triplet-jd-la-3000-55-70-55-30\", \"triplet-jd-la-ma-1500\"\n",
    "# [\"triplet-jd-la-2000-55-70-40\",\"triplet-jd-la-3000-55-70-55-30\",\"triplet-jd-la-3000-50-70-55-30\"]\n",
    "# [ \"triplet-jd-la-1500-055-70-40\", \"triplet-jd-la-1500-55-75-40\"]\n",
    "# \"triplet-jd-la-1500-060-70-40\", \"triplet-jd-la-1500-055-70-40\", \"triplet-jd-la-1500-050-70-40\",\n",
    "# [\"triplet-jd-la-1500-050-065-25\", \"triplet-jd-la-1500-065-070-25\", \"triplet-jd-la-1500-060-060-25\"]\n",
    "\n",
    "#[\"triplet-jd-la-ma-500-02-03\",\"triplet-jd-la-ma-750\",\"triplet-jd-la-ma-1000\",  # \"#4169e1\",\n",
    "#               \"triplet-jd-la-ma-1500\",\n",
    "#               \"triplet-jaccard\",\"triplet-jaccard-margin\",\n",
    "#               \"triplet-label\", # all labels\n",
    "#               \"lstm-ae\"]\n",
    "COLORS = h.get_N_HexCol(len(MODEL_NAMES)+1)\n",
    "\n",
    "fac_n = np.arange(0, 1.0, 0.0005)\n",
    "\n",
    "baseline_valid_accepts = h.load_from_json(\"data/ji_%s_basline-jaccard_valid.json\"%LOG_NAME)\n",
    "baseline_false_accepts = [np.round(f,5) for f in h.load_from_json(\"data/ji_%s_basline-jaccard_false.json\"%LOG_NAME)]\n",
    "\n",
    "interpolated_vac = interp1d(baseline_false_accepts, baseline_valid_accepts)\n",
    "vac_n = interpolated_vac(fac_n)\n",
    "auc_score = auc(fac_n, vac_n)\n",
    "\n",
    "\n",
    "plt.plot( fac_n,  interpolated_vac(fac_n), color='r', label=\"%0.3f,baseline\"%auc_score)\n",
    "plt.xscale(\"log\")\n",
    "\n",
    "\n",
    "for i, model_name in enumerate(MODEL_NAMES):\n",
    "    #print(model_name)\n",
    "    valid_accepts = h.load_from_json(\"data/%s_%s_valid.json\"%(model_name, LOG_NAME))\n",
    "    false_accepts = h.load_from_json(\"data/%s_%s_false.json\"%(model_name, LOG_NAME))\n",
    "    interpolated_vac = interp1d(false_accepts, valid_accepts)\n",
    "    auc_score = auc(fac_n, interpolated_vac(fac_n))\n",
    "    plt.plot( fac_n, interpolated_vac(fac_n) , color=COLORS[i+1], label=\"%0.3f, %s\"%(auc_score,  model_name))\n",
    "\n",
    "plt.title(\"VAR/FAR (%s) LA\"%LOG_NAME)\n",
    "plt.xlabel('FAR')\n",
    "plt.ylabel('VAL')\n",
    "plt.legend(loc='lower right')\n",
    "plt.show()\n",
    "#plt.savefig(\"%s/roc_%s.png\"%(VIZUALIZATIONS_DIR, LOG_NAME))\n"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": []
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