{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "9cd3261f",
   "metadata": {},
   "source": [
    "## Performance testing of serialization\n",
    "\n",
    "This test checks the performance improvement of scene setup with serialization feature."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ee2ef520",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-22T11:45:24.646038Z",
     "iopub.status.busy": "2021-10-22T11:45:24.645378Z",
     "iopub.status.idle": "2021-10-22T11:45:24.740266Z",
     "shell.execute_reply": "2021-10-22T11:45:24.741130Z"
    }
   },
   "outputs": [],
   "source": [
    "import lmenv\n",
    "env = lmenv.load('.lmenv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2de699c0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-22T11:45:24.744932Z",
     "iopub.status.busy": "2021-10-22T11:45:24.743858Z",
     "iopub.status.idle": "2021-10-22T11:45:25.266207Z",
     "shell.execute_reply": "2021-10-22T11:45:25.265765Z"
    }
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import imageio\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import timeit\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.axes_grid1 import make_axes_locatable\n",
    "import lmscene\n",
    "import lightmetrica as lm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7bea8e47",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-22T11:45:25.271406Z",
     "iopub.status.busy": "2021-10-22T11:45:25.270268Z",
     "iopub.status.idle": "2021-10-22T11:45:25.277299Z",
     "shell.execute_reply": "2021-10-22T11:45:25.276408Z"
    }
   },
   "outputs": [],
   "source": [
    "%load_ext lightmetrica_jupyter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "528687ec",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-22T11:45:25.282024Z",
     "iopub.status.busy": "2021-10-22T11:45:25.281494Z",
     "iopub.status.idle": "2021-10-22T11:45:25.284081Z",
     "shell.execute_reply": "2021-10-22T11:45:25.284474Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[I|0.000] Lightmetrica -- Version 3.0.0 (rev. 70601db) Linux x64\n"
     ]
    }
   ],
   "source": [
    "lm.init()\n",
    "lm.log.init('jupyter')\n",
    "lm.progress.init('jupyter')\n",
    "lm.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "a73fab98",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-22T11:45:25.287461Z",
     "iopub.status.busy": "2021-10-22T11:45:25.286776Z",
     "iopub.status.idle": "2021-10-22T11:45:25.290465Z",
     "shell.execute_reply": "2021-10-22T11:45:25.290067Z"
    }
   },
   "outputs": [],
   "source": [
    "scene_names = lmscene.scenes_small()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "41bd7493",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-22T11:45:26.853486Z",
     "iopub.status.busy": "2021-10-22T11:45:25.702841Z",
     "iopub.status.idle": "2021-10-22T11:45:28.092898Z",
     "shell.execute_reply": "2021-10-22T11:45:28.093277Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[I|0.018] Loading asset [name='film_output']\n",
      "[I|0.096] Loading asset [name='accel']\n",
      "[I|0.096] Loading asset [name='scene']\n",
      "[I|0.096] Loading asset [name='camera_main']\n",
      "[I|0.096] Loading asset [name='model_obj']\n",
      "[I|0.096] .. Loading OBJ file [path='fireplace_room.obj']\n",
      "[I|0.096] .. Loading MTL file [path='fireplace_room.mtl']\n",
      "[I|0.422] .. Loading texture [path='wood.ppm']\n",
      "[I|0.512] .. Loading texture [path='leaf.ppm']\n",
      "[I|0.514] .. Loading texture [path='picture8.ppm']\n",
      "[I|0.546] .. Loading texture [path='wood5.ppm']\n",
      "[I|1.572] Loading asset [name='film_output']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[I|1.651] Loading asset [name='accel']\n",
      "[I|1.651] Loading asset [name='scene']\n",
      "[I|1.651] Loading asset [name='camera_main']\n",
      "[I|1.651] Loading asset [name='model_obj']\n",
      "[I|1.651] .. Loading OBJ file [path='CornellBox-Sphere.obj']\n",
      "[I|1.651] .. Loading MTL file [path='CornellBox-Sphere.mtl']\n",
      "[I|2.189] Loading asset [name='film_output']\n",
      "[I|2.266] Loading asset [name='accel']\n",
      "[I|2.267] Loading asset [name='scene']\n",
      "[I|2.267] Loading asset [name='camera_main']\n",
      "[I|2.267] Loading asset [name='model_obj']\n",
      "[I|2.267] .. Loading OBJ file [path='cube.obj']\n",
      "[I|2.267] .. Loading MTL file [path='default.mtl']\n",
      "[I|2.267] .. Loading texture [path='default.png']\n"
     ]
    }
   ],
   "source": [
    "scene_setup_time_df = pd.DataFrame(\n",
    "    columns=['scene loading', 'serialization', 'deserialization'],\n",
    "    index=scene_names)\n",
    "for scene_name in scene_names:\n",
    "    lm.reset()\n",
    "    \n",
    "    lm.load_film('film_output', 'bitmap', {\n",
    "        'w': 1920,\n",
    "        'h': 1080\n",
    "    })\n",
    "    \n",
    "    # Load the scene without serialization\n",
    "    def load_scene():\n",
    "        accel = lm.load_accel('accel', 'sahbvh', {})\n",
    "        scene = lm.load_scene('scene', 'default', {\n",
    "            'accel': accel.loc()\n",
    "        })\n",
    "        lmscene.load(scene, env.scene_path, scene_name)\n",
    "    loading_time_without_serialization = timeit.timeit(stmt=load_scene, number=1)\n",
    "    scene_setup_time_df['scene loading'][scene_name] = loading_time_without_serialization\n",
    "    \n",
    "    # Export the internal state to a file\n",
    "    def serialize_scene():\n",
    "        lm.save_state_to_file('lm.serialized')\n",
    "    serialization_time = timeit.timeit(stmt=serialize_scene, number=1)\n",
    "    scene_setup_time_df['serialization'][scene_name] = serialization_time\n",
    "    \n",
    "    # Import the internal state from the serialized file\n",
    "    lm.reset()\n",
    "    def deserialize_scene():\n",
    "        lm.load_state_from_file('lm.serialized')\n",
    "    deserialization_time = timeit.timeit(stmt=deserialize_scene, number=1)\n",
    "    scene_setup_time_df['deserialization'][scene_name] = deserialization_time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2f4129f2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-22T11:45:28.103855Z",
     "iopub.status.busy": "2021-10-22T11:45:28.101328Z",
     "iopub.status.idle": "2021-10-22T11:45:28.108639Z",
     "shell.execute_reply": "2021-10-22T11:45:28.109025Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>scene loading</th>\n",
       "      <th>serialization</th>\n",
       "      <th>deserialization</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>fireplace_room</th>\n",
       "      <td>0.502106</td>\n",
       "      <td>0.605808</td>\n",
       "      <td>0.358062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cornell_box_sphere</th>\n",
       "      <td>0.00285</td>\n",
       "      <td>0.292031</td>\n",
       "      <td>0.238252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cube</th>\n",
       "      <td>0.011338</td>\n",
       "      <td>0.289647</td>\n",
       "      <td>0.237782</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   scene loading serialization deserialization\n",
       "fireplace_room          0.502106      0.605808        0.358062\n",
       "cornell_box_sphere       0.00285      0.292031        0.238252\n",
       "cube                    0.011338      0.289647        0.237782"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scene_setup_time_df"
   ]
  }
 ],
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