{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Counterfactual explanation on time series anomaly detection"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is an example of our optimization-based counterfactual explainer `MACEExplainer` for time series data. This explainer only supports time series anomaly detection."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This default renderer is used for sphinx docs only. Please delete this cell in IPython.\n",
    "import plotly.io as pio\n",
    "pio.renderers.default = \"png\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from omnixai.data.timeseries import Timeseries\n",
    "from omnixai.explainers.timeseries import MACEExplainer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The time series data used here is a sythentic univariate time series dataset. We recommend using `Timeseries` to represent a time series dataset. `Timeseries` contains one univariate/multivariate time series, which can be constructed from a pandas dataframe (the index in the dataframe indicates the timestamps and the columns are the variables)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                       values\n",
      "timestamp                    \n",
      "1970-01-01 00:00:00  1.928031\n",
      "1970-01-01 00:05:00 -1.156620\n",
      "1970-01-01 00:10:00 -0.390650\n",
      "1970-01-01 00:15:00  0.400804\n",
      "1970-01-01 00:20:00 -0.874490\n",
      "...                       ...\n",
      "1970-02-04 16:55:00  0.362724\n",
      "1970-02-04 17:00:00  2.657373\n",
      "1970-02-04 17:05:00  1.472341\n",
      "1970-02-04 17:10:00  1.033154\n",
      "1970-02-04 17:15:00  2.950466\n",
      "\n",
      "[10000 rows x 1 columns]\n"
     ]
    }
   ],
   "source": [
    "# Load the time series dataset\n",
    "df = pd.read_csv(os.path.join(\"../data\", \"timeseries.csv\"))\n",
    "df[\"timestamp\"] = pd.to_datetime(df[\"timestamp\"], unit='s')\n",
    "df = df.rename(columns={\"horizontal\": \"values\"})\n",
    "df = df.set_index(\"timestamp\")\n",
    "df = df.drop(columns=[\"anomaly\"])\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Split the dataset into training and test splits\n",
    "train_df = df.iloc[:9150]\n",
    "test_df = df.iloc[9150:9300]\n",
    "# A simple threshold for detecting anomaly data points\n",
    "threshold = np.percentile(train_df[\"values\"].values, 90)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The outputs of the detector are anomaly scores instead of anomaly labels (0 or 1). A data point is more anomalous if it has a higher anomaly score. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# A simple detector for determining whether a window of time series is anomalous\n",
    "def detector(ts: Timeseries):\n",
    "    anomaly_scores = np.sum((ts.values > threshold).astype(int))\n",
    "    return anomaly_scores / ts.shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To initialize a MACEExplainer explainer, we need to set:\n",
    "  \n",
    "  - `training_data`: The data used to initialize a MACEExplainer explainer. ``training_data`` can be the training dataset for training the machine learning model.\n",
    "  - `predict_function`: The prediction function corresponding to the model to explain. The input of ``predict_function`` should be an `Timeseries` instance. The outputs of ``predict_function`` are anomaly scores (higher scores imply more anomalous) for anomaly detection.\n",
    "  - `threshold`: The threshold to determine whether an instance is anomalous, e.g., anomaly score > threshold."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "explainer = MACEExplainer(\n",
    "    training_data=Timeseries.from_pd(train_df),\n",
    "    predict_function=detector,\n",
    "    mode=\"anomaly_detection\",\n",
    "    threshold=0.001\n",
    ")\n",
    "test_x = Timeseries.from_pd(test_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " |███████████████████████████████████████-| 98.0% "
     ]
    },
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "explanations = explainer.explain(test_x)\n",
    "explanations.ipython_plot()"
   ]
  }
 ],
 "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": "3.7.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}