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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#| hide\n",
    "!pip install -Uqq nixtla datasetsforecast utilsforecast"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#| hide \n",
    "from nixtla.utils import in_colab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#| hide \n",
    "IN_COLAB = in_colab()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#| hide\n",
    "if not IN_COLAB:\n",
    "    from nixtla.utils import colab_badge\n",
    "    from dotenv import load_dotenv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Long-horizon forecasting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Long-horizon forecasting refers to predictions far into the future, typically exceeding two seasonal periods. However, the exact definition of a 'long horizon' can vary based on the frequency of the data. For example, when dealing with hourly data, a forecast for three days into the future is considered long-horizon, as it covers 72 timestamps (calculated as 3 days × 24 hours/day). In the context of monthly data, a period exceeding two years would typically be classified as long-horizon forecasting. Similarly, for daily data, a forecast spanning more than two weeks falls into the long-horizon category.\n",
    "\n",
    "Of course, forecasting over a long horizon comes with its challenges. The longer the forecast horizon, the greater the uncertainty in the predictions. It is also possible to have unknown factors come into play in the long-term that were not expected at the time of forecasting.\n",
    "\n",
    "To tackle those challenges, use TimeGPT's specialized model for long-horizon forecasting by specifying `model='timegpt-1-long-horizon'` in your setup.\n",
    "\n",
    "For a detailed step-by-step guide, follow this tutorial on long-horizon forecasting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "[![](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Nixtla/nixtla/blob/main/nbs/docs/tutorials/04_longhorizon.ipynb)"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#| echo: false\n",
    "if not IN_COLAB:\n",
    "    load_dotenv()    \n",
    "    colab_badge('docs/tutorials/04_longhorizon')\n",
    "    import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Import packages\n",
    "First, we install and import the required packages and initialize the Nixtla client."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nixtla import NixtlaClient\n",
    "from datasetsforecast.long_horizon import LongHorizon\n",
    "from utilsforecast.losses import mae"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "nixtla_client = NixtlaClient(\n",
    "    # defaults to os.environ.get(\"NIXTLA_API_KEY\")\n",
    "    api_key = 'my_api_key_provided_by_nixtla'\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> 👍 Use an Azure AI endpoint\n",
    "> \n",
    "> To use an Azure AI endpoint, remember to set also the `base_url` argument:\n",
    "> \n",
    "> `nixtla_client = NixtlaClient(base_url=\"you azure ai endpoint\", api_key=\"your api_key\")`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#| hide\n",
    "if not IN_COLAB:\n",
    "    nixtla_client = NixtlaClient()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Load the data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's load the ETTh1 dataset. This is a widely used dataset to evaluate models on their long-horizon forecasting capabalities. \n",
    "\n",
    "The ETTh1 dataset monitors an electricity transformer from a region of a province of China including oil temperature and variants of load (such as high useful load and high useless load) from July 2016 to July 2018 at an hourly frequency.\n",
    "\n",
    "For this tutorial, let's only consider the oil temperature variation over time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 314M/314M [00:14<00:00, 21.3MiB/s] \n",
      "INFO:datasetsforecast.utils:Successfully downloaded datasets.zip, 314116557, bytes.\n",
      "INFO:datasetsforecast.utils:Decompressing zip file...\n",
      "INFO:datasetsforecast.utils:Successfully decompressed longhorizon\\datasets\\datasets.zip\n"
     ]
    },
    {
     "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",
       "        vertical-align: top;\n",
       "    }\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>unique_id</th>\n",
       "      <th>ds</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>OT</td>\n",
       "      <td>2016-07-01 00:00:00</td>\n",
       "      <td>1.460552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OT</td>\n",
       "      <td>2016-07-01 01:00:00</td>\n",
       "      <td>1.161527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>OT</td>\n",
       "      <td>2016-07-01 02:00:00</td>\n",
       "      <td>1.161527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>OT</td>\n",
       "      <td>2016-07-01 03:00:00</td>\n",
       "      <td>0.862611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>OT</td>\n",
       "      <td>2016-07-01 04:00:00</td>\n",
       "      <td>0.525227</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  unique_id                   ds         y\n",
       "0        OT  2016-07-01 00:00:00  1.460552\n",
       "1        OT  2016-07-01 01:00:00  1.161527\n",
       "2        OT  2016-07-01 02:00:00  1.161527\n",
       "3        OT  2016-07-01 03:00:00  0.862611\n",
       "4        OT  2016-07-01 04:00:00  0.525227"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#| eval: false\n",
    "Y_df, *_ = LongHorizon.load(directory='./', group='ETTh1')\n",
    "\n",
    "Y_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For this small experiment, let's set the horizon to 96 time steps (4 days into the future), and we will feed TimeGPT with a sequence of 42 days."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#| hide\n",
    "if not IN_COLAB:\n",
    "    Y_df = pd.read_parquet(\"../../assets/long_horizon_example_Y_df.parquet\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "test = Y_df[-96:]             # 96 = 4 days x 24h/day\n",
    "input_seq = Y_df[-1104:-96]   # Gets a sequence of 1008 observations (1008 = 42 days * 24h/day)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Forecasting for long-horizon"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we are ready to use TimeGPT for long-horizon forecasting. Here, we need to set the `model` parameter to `\"timegpt-1-long-horizon\"`. This is the specialized model in TimeGPT that can handle such tasks."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:nixtla.nixtla_client:Validating inputs...\n",
      "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n",
      "INFO:nixtla.nixtla_client:Inferred freq: H\n",
      "INFO:nixtla.nixtla_client:Calling Forecast Endpoint...\n"
     ]
    }
   ],
   "source": [
    "fcst_df = nixtla_client.forecast(\n",
    "    df=input_seq,\n",
    "    h=96,\n",
    "    level=[90],\n",
    "    finetune_steps=10,\n",
    "    finetune_loss='mae',\n",
    "    model='timegpt-1-long-horizon',\n",
    "    time_col='ds',\n",
    "    target_col='y'\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> 📘 Available models in Azure AI\n",
    ">\n",
    "> If you are using an Azure AI endpoint, please be sure to set `model=\"azureai\"`:\n",
    ">\n",
    "> `nixtla_client.forecast(..., model=\"azureai\")`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2400x350 with 1 Axes>"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nixtla_client.plot(Y_df[-168:], fcst_df, models=['TimeGPT'], level=[90], time_col='ds', target_col='y')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Evaluation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's now evaluate the performance of TimeGPT using the mean absolute error (MAE)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "test = test.copy()\n",
    "\n",
    "test.loc[:, 'TimeGPT'] = fcst_df['TimeGPT'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  unique_id   TimeGPT\n",
      "0        OT  0.145393\n"
     ]
    }
   ],
   "source": [
    "evaluation = mae(test, models=['TimeGPT'], id_col='unique_id', target_col='y')\n",
    "\n",
    "print(evaluation)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, TimeGPT achieves a MAE of 0.146."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "python3",
   "language": "python",
   "name": "python3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}