code/01_trajectory_dataset_preparation.ipynb

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  {
   "cell_type": "markdown",
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   "source": [
    "# Trajectory dataset preparation\n",
    "Here we explore and create a dataset of RL trajectories from the previously trained RL agent. The trajectories are split in a train set and a test set.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dependencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# The following code was run on Python 3.9.7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "Requirement already satisfied: pandas==1.4.1 in /Users/Alberto/Code/love-emotional-framework/.venv/lib/python3.9/site-packages (1.4.1)\n",
      "Requirement already satisfied: pytz>=2020.1 in /Users/Alberto/Code/love-emotional-framework/.venv/lib/python3.9/site-packages (from pandas==1.4.1) (2024.1)\n",
      "Requirement already satisfied: python-dateutil>=2.8.1 in /Users/Alberto/Code/love-emotional-framework/.venv/lib/python3.9/site-packages (from pandas==1.4.1) (2.8.2)\n",
      "Requirement already satisfied: numpy>=1.18.5 in /Users/Alberto/Code/love-emotional-framework/.venv/lib/python3.9/site-packages (from pandas==1.4.1) (1.22.2)\n",
      "Requirement already satisfied: six>=1.5 in /Users/Alberto/Code/love-emotional-framework/.venv/lib/python3.9/site-packages (from python-dateutil>=2.8.1->pandas==1.4.1) (1.16.0)\n",
      "\u001b[33mWARNING: You are using pip version 21.2.4; however, version 24.0 is available.\n",
      "You should consider upgrading via the '/Users/Alberto/Code/love-emotional-framework/.venv/bin/python -m pip install --upgrade pip' command.\u001b[0m\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "Requirement already satisfied: numpy==1.22.2 in /Users/Alberto/Code/love-emotional-framework/.venv/lib/python3.9/site-packages (1.22.2)\n",
      "\u001b[33mWARNING: You are using pip version 21.2.4; however, version 24.0 is available.\n",
      "You should consider upgrading via the '/Users/Alberto/Code/love-emotional-framework/.venv/bin/python -m pip install --upgrade pip' command.\u001b[0m\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "Requirement already satisfied: bokeh==2.4.2 in /Users/Alberto/Code/love-emotional-framework/.venv/lib/python3.9/site-packages (2.4.2)\n",
      "Requirement already satisfied: Jinja2>=2.9 in /Users/Alberto/Code/love-emotional-framework/.venv/lib/python3.9/site-packages (from bokeh==2.4.2) (3.1.3)\n",
      "Requirement already satisfied: typing-extensions>=3.10.0 in /Users/Alberto/Code/love-emotional-framework/.venv/lib/python3.9/site-packages (from bokeh==2.4.2) (4.9.0)\n",
      "Requirement already satisfied: tornado>=5.1 in /Users/Alberto/Code/love-emotional-framework/.venv/lib/python3.9/site-packages (from bokeh==2.4.2) (6.4)\n",
      "Requirement already satisfied: packaging>=16.8 in /Users/Alberto/Code/love-emotional-framework/.venv/lib/python3.9/site-packages (from bokeh==2.4.2) (23.2)\n",
      "Requirement already satisfied: pillow>=7.1.0 in /Users/Alberto/Code/love-emotional-framework/.venv/lib/python3.9/site-packages (from bokeh==2.4.2) (10.2.0)\n",
      "Requirement already satisfied: numpy>=1.11.3 in /Users/Alberto/Code/love-emotional-framework/.venv/lib/python3.9/site-packages (from bokeh==2.4.2) (1.22.2)\n",
      "Requirement already satisfied: PyYAML>=3.10 in /Users/Alberto/Code/love-emotional-framework/.venv/lib/python3.9/site-packages (from bokeh==2.4.2) (6.0.1)\n",
      "Requirement already satisfied: MarkupSafe>=2.0 in /Users/Alberto/Code/love-emotional-framework/.venv/lib/python3.9/site-packages (from Jinja2>=2.9->bokeh==2.4.2) (2.1.5)\n",
      "\u001b[33mWARNING: You are using pip version 21.2.4; however, version 24.0 is available.\n",
      "You should consider upgrading via the '/Users/Alberto/Code/love-emotional-framework/.venv/bin/python -m pip install --upgrade pip' command.\u001b[0m\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "# Installation of libraries (in the specific versions used).\n",
    "%pip install pandas==1.4.1\n",
    "%pip install numpy==1.22.2\n",
    "%pip install bokeh==2.4.2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The autoreload extension is already loaded. To reload it, use:\n",
      "  %reload_ext autoreload\n"
     ]
    }
   ],
   "source": [
    "# Enable automatic reloading of external modules before executing code here.\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import packages.\n",
    "import os\n",
    "import sys\n",
    "import random\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import modules.\n",
    "module_path = os.path.abspath(os.path.join('modules'))\n",
    "if module_path not in sys.path:\n",
    "    sys.path.append(module_path)\n",
    "\n",
    "import time_series_tools as ts_tools"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Auxiliary code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Not required here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dataset preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Read and show recorded RL trajectories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "60 trajectories read.\n",
      "Example: \n",
      "Exp-04.01 (episode_4.txt)\n",
      "      Step    Reward      Value      Delta\n",
      "0        0  0.000000  68.453072   0.000000\n",
      "1        1  0.024697  69.105492  -0.013938\n",
      "2        2  3.130233  66.474655  -0.165350\n",
      "3        3 -0.359940  67.537750   0.027777\n",
      "4        4  0.162538  68.540581   0.479963\n",
      "...    ...       ...        ...        ...\n",
      "996    996  1.919042  73.464653   1.825211\n",
      "997    997  1.628644  74.439430   1.859027\n",
      "998    998 -1.728141  75.311012  -1.609669\n",
      "999    999 -1.635396  74.080360  -3.606851\n",
      "1000  1000  1.657513   0.000000 -72.422848\n",
      "\n",
      "[1001 rows x 4 columns]\n"
     ]
    }
   ],
   "source": [
    "# Create all the 'Trajectory' instances.\n",
    "path_to_series = os.path.join(os.path.dirname(os.getcwd()), 'data', 'original', 'trajectories', 'test_series_s*') + os.sep\n",
    "experiment_id = 'Exp-04.01'\n",
    "columns=['Step', 'Reward', 'Value', 'Delta']\n",
    "\n",
    "traj_list = ts_tools.read_all_trajectories_in_path(\n",
    "    path_to_series,\n",
    "    experiment_id=experiment_id,\n",
    "    columns=columns\n",
    ")\n",
    "print(f\"{len(traj_list)} trajectories read.\")\n",
    "print(f\"Example: \\n{traj_list[0]}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
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Application\",\"version\":\"2.4.2\"}};\n  const render_items = [{\"docid\":\"641eeeae-8b35-424e-a288-1c40892708c8\",\"root_ids\":[\"1002\"],\"roots\":{\"1002\":\"28797e19-6e73-43f2-bf5d-0fb2b6027d30\"}}];\n  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n\n  }\n  if (root.Bokeh !== undefined) {\n    embed_document(root);\n  } else {\n    let attempts = 0;\n    const timer = setInterval(function(root) {\n      if (root.Bokeh !== undefined) {\n        clearInterval(timer);\n        embed_document(root);\n      } else {\n        attempts++;\n        if (attempts > 100) {\n          clearInterval(timer);\n          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n        }\n      }\n    }, 10, root)\n  }\n})(window);",
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "1002"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Exploration of the recorded trajectories\n",
    "t = traj_list[0]\n",
    "t.plot(plot_width=700, plot_height=400)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Create the train and test datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train set: 48, test set: 12\n"
     ]
    }
   ],
   "source": [
    "# Split train and test sets:\n",
    "random.seed(10)\n",
    "random.shuffle(traj_list)\n",
    "\n",
    "train_vs_test_rate = 0.8\n",
    "train_size = int(0.8 * len(traj_list))\n",
    "\n",
    "train_dataset = traj_list[:train_size]\n",
    "test_dataset = traj_list[train_size:]\n",
    "\n",
    "print(f\"train set: {len(train_dataset)}, test set: {len(test_dataset)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save train / test files lists:\n",
    "output_path = os.path.join(os.path.dirname(os.getcwd()), 'data', 'new_runs') + os.sep\n",
    "with open(output_path + 'train_set_files.txt', 'w') as f:\n",
    "    for t in train_dataset:\n",
    "        f.write(f\"{os.path.join(t.path_to_log.split(os.sep)[-2], t.log_file)}\\n\")\n",
    "\n",
    "with open(output_path + 'test_set_files.txt', 'w') as f:\n",
    "    for t in test_dataset:\n",
    "        f.write(f\"{os.path.join(t.path_to_log.split(os.sep)[-2], t.log_file)}\\n\")"
   ]
  }
 ],
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