{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Adding New Anomaly Detection Models\n", "\n", "This notebook provides a minimal example on how to add a new anomaly detection model to Merlion. We follow the instructions in [CONTRIBUTING.md](https://github.com/salesforce/Merlion/blob/main/CONTRIBUTING.md). We suggest you review this [notebook](1_AnomalyFeatures.ipynb) explaining how to use a Merlion anomaly detection model before reading this notebook.\n", "\n", "More specifically, let's implement an anomaly detection model whose anomaly score is just equal to the value of the time series metric (after mean and variance normalization). By default, we want the model to fire an alarm when the value of the time series metric is more than 3 standard deviations away from the mean value.\n", "\n", "Note that this is already implemented [here](https://github.com/salesforce/Merlion/blob/main/merlion/models/anomaly/stat_threshold.py) as the `StatThreshold` algorithm. For a more complete example, see our implementation of [Isolation Forest](https://github.com/salesforce/Merlion/blob/main/merlion/models/anomaly/isolation_forest.py)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Model Config Class\n", "\n", "The first step of creating a new model is defining an appropriate config class, which inherits from `DetectorConfig`:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "from merlion.models.anomaly.base import DetectorConfig\n", "from merlion.post_process.threshold import Threshold\n", "from merlion.transform.normalize import MeanVarNormalize\n", "\n", "class StatThresholdConfig(DetectorConfig):\n", " # If the transform argument is not provided when initializing the config,\n", " # we will pre-process the input by normalizing it to be zero mean (but\n", " # not unit variance!)\n", " _default_transform = MeanVarNormalize(normalize_scale=False)\n", "\n", " # When you call model.get_anomaly_label(), you will transform the model's\n", " # raw anomaly scores (returned by model.get_anomaly_score() into z-scores,\n", " # and you will apply a thresholding rule to suppress all anomaly scores\n", " # with magnitude smaller than the threshold. Here, we only wish to report\n", " # 3-sigma events.\n", " _default_threshold = Threshold(alm_threshold=3.0)\n", "\n", " def __init__(self, **kwargs):\n", " \"\"\"\n", " Provide model-specific config parameters here, with kwargs to capture any\n", " general-purpose arguments used by the base class. For DetectorConfig,\n", " these are transform and post_rule.\n", " \n", " We include the initializer here for clarity. In this case, it may be\n", " excluded, as it only calls the superclass initializer.\n", " \"\"\"\n", " super().__init__(**kwargs)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Model Class\n", "\n", "Next, we define the model itself, which must inherit from the `DetectorBase` base class and define all abstract methods. See the API docs for more details." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "from merlion.evaluate.anomaly import TSADMetric\n", "from merlion.models.anomaly.base import DetectorBase\n", "from merlion.utils import TimeSeries\n", "\n", "\n", "class StatThreshold(DetectorBase):\n", " # The config class for StatThreshold is StatThresholdConfig, defined above\n", " config_class = StatThresholdConfig\n", "\n", " # By default, we would like to train the model's post-rule (i.e. the threshold\n", " # at which we fire an alert) to maximize F1 score\n", " _default_post_rule_train_config = dict(metric=TSADMetric.F1)\n", " \n", " def __init__(self, config: StatThresholdConfig):\n", " \"\"\"\n", " Sets the model config and any other local variables. We include the\n", " initializer here for clarity. In this case, it may be excluded, as it\n", " only calls the superclass initializer.\n", " \n", " :param config: model configuration\n", " \"\"\"\n", " super().__init__(config)\n", "\n", "\n", " def train(self, train_data: TimeSeries,\n", " anomaly_labels: TimeSeries = None,\n", " train_config=None, post_rule_train_config=None) -> TimeSeries:\n", " # Apply standard pre-processing steps before training the model. Note\n", " # that this model can accept arbitrary time stamps, but it only works\n", " # for univariate time series, so we specify that.\n", " train_data = self.train_pre_process(\n", " train_data, require_even_sampling=False, require_univariate=True)\n", " \n", " # Since this model's anomaly scores are just the values of the time\n", " # series metric (after any pre-processing), there is no model to train.\n", " # In general, you should train your model here, and determine its\n", " # anomaly scores on the training data. Note that this training should not\n", " # use anomaly_labels in any way!\n", " train_data = train_data.univariates[train_data.names[0]]\n", " train_anom_scores = TimeSeries({\"anom_score\": train_data})\n", " \n", " # We train the model's post-rule here, based on the training anomaly scores\n", " # and the anomaly labels (if none are given, an unsupervised threshold\n", " # selection strategy is used).\n", " self.train_post_rule(train_anom_scores, anomaly_labels, post_rule_train_config)\n", " \n", " # Return the model's predicted anomaly scores on the train data\n", " return train_anom_scores\n", "\n", " def get_anomaly_score(self, time_series: TimeSeries,\n", " time_series_prev: TimeSeries = None) -> TimeSeries:\n", " \n", " # Apply the data pre-processing transform on the input data.\n", " # Make sure to prepend time_series_prev to time_series if it is given.\n", " time_series, time_series_prev = self.transform_time_series(\n", " time_series, time_series_prev)\n", " \n", " # For this model, the anomaly scores are just the values of the time\n", " # time series metric. Make sure to return a time series with a single\n", " # variable named \"anom_score\".\n", " anom_scores = time_series.univariates[time_series.names[0]]\n", " return TimeSeries({\"anom_score\": anom_scores})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Running the Model: A Simple Example\n", "\n", "Let's try running this model on some actual data! This next part assumes you've installed `ts_datasets`. We'll begin by getting a time series from the NAB dataset & visualizing it." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Time series /Users/abhatnagar/Desktop/Merlion/data/nab/realKnownCause/ec2_request_latency_system_failure.csv (index 2) has timestamp duplicates. Kept first values.\n", "Time series /Users/abhatnagar/Desktop/Merlion/data/nab/realKnownCause/machine_temperature_system_failure.csv (index 3) has timestamp duplicates. Kept first values.\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "import numpy as np\n", "\n", "from merlion.plot import plot_anoms\n", "from merlion.utils import TimeSeries\n", "from ts_datasets.anomaly import NAB\n", "\n", "# This is a time series with anomalies in both the train and test split.\n", "# time_series and metadata are both time-indexed pandas DataFrames.\n", "time_series, metadata = NAB(subset=\"realKnownCause\")[3]\n", "\n", "# Visualize the full time series\n", "fig = plt.figure(figsize=(10, 6))\n", "ax = fig.add_subplot(111)\n", "ax.plot(time_series)\n", "\n", "# Label the train/test split with a dashed line & plot anomalies\n", "ax.axvline(metadata[metadata.trainval].index[-1], ls=\"--\", lw=2, c=\"k\")\n", "plot_anoms(ax, TimeSeries.from_pd(metadata.anomaly))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now, we'll split the data into train & test splits, and run our anomaly detection model on it." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "# Get training split\n", "train = time_series[metadata.trainval]\n", "train_data = TimeSeries.from_pd(train)\n", "train_labels = TimeSeries.from_pd(metadata[metadata.trainval].anomaly)\n", "\n", "# Get testing split\n", "test = time_series[~metadata.trainval]\n", "test_data = TimeSeries.from_pd(test)\n", "test_labels = TimeSeries.from_pd(metadata[~metadata.trainval].anomaly)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ " anom_score\n", "2013-12-02 21:15:00 -9.065700\n", "2013-12-02 21:20:00 -8.097140\n", "2013-12-02 21:25:00 -6.908860\n", "2013-12-02 21:30:00 -4.892315\n", "2013-12-02 21:35:00 -3.703186\n", "... ...\n", "2013-12-14 16:25:00 15.041999\n", "2013-12-14 16:30:00 14.494303\n", "2013-12-14 16:35:00 16.234568\n", "2013-12-14 16:40:00 15.160902\n", "2013-12-14 16:45:00 15.055357\n", "\n", "[3403 rows x 1 columns]" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Initialize a model & train it. The dataframe returned & printed\n", "# below is the model's anomaly scores on the training data.\n", "model = StatThreshold(StatThresholdConfig())\n", "model.train(train_data=train_data, anomaly_labels=train_labels)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " no post rule with post rule\n", "2013-12-14 16:50:00 14.520900 0.0\n", "2013-12-14 16:55:00 15.065935 0.0\n", "2013-12-14 17:00:00 15.825172 0.0\n", "2013-12-14 17:05:00 13.846644 0.0\n", "2013-12-14 17:10:00 15.050966 0.0\n", "... ... ...\n", "2014-02-19 15:05:00 15.152393 0.0\n", "2014-02-19 15:10:00 14.771146 0.0\n", "2014-02-19 15:15:00 14.102446 0.0\n", "2014-02-19 15:20:00 15.023830 0.0\n", "2014-02-19 15:25:00 13.870839 0.0\n", "\n", "[19280 rows x 2 columns]\n" ] } ], "source": [ "# Let's run the our model on the test data, both with and without\n", "# applying the post-rule. Notice that applying the post-rule filters out\n", "# a lot of entries!\n", "import pandas as pd\n", "anom_scores = model.get_anomaly_score(test_data).to_pd()\n", "anom_labels = model.get_anomaly_label(test_data).to_pd()\n", "print(pd.DataFrame({\"no post rule\": anom_scores.iloc[:, 0],\n", " \"with post rule\": anom_labels.iloc[:, 0]}))" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " anom_score\n", "2013-12-16 06:40:00 -3.024196\n", "2013-12-16 06:45:00 -3.012073\n", "2013-12-16 07:00:00 -3.468464\n", "2013-12-16 07:05:00 -3.124039\n", "2013-12-16 07:10:00 -3.491421\n", "... ...\n", "2014-02-09 11:35:00 -4.819248\n", "2014-02-09 11:40:00 -4.823173\n", "2014-02-09 11:45:00 -4.822201\n", "2014-02-09 11:50:00 -4.677379\n", "2014-02-09 11:55:00 -4.300280\n", "\n", "[721 rows x 1 columns]\n" ] } ], "source": [ "# Additionally, notice that the nonzero post-processed anomaly scores,\n", "# are interpretable as z-scores. This is due to the automatic calibration.\n", "print(anom_labels[anom_labels.iloc[:, 0] != 0])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Visualization\n", "\n", "Qualitatively, we can plot the anomaly score sequences to see the difference." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "no post rule\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "print(\"no post rule\")\n", "fig, ax = model.plot_anomaly(test_data, filter_scores=False)\n", "plot_anoms(ax, test_labels)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "with post rule\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "print(\"with post rule\")\n", "fig, ax = model.plot_anomaly(test_data, filter_scores=True)\n", "plot_anoms(ax, test_labels)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Customizing the Post-Rule\n", "\n", "The example above uses a simple threshold as the post-processing rule. As a result, the model is continuously firing alerts when the differenced time series value is far from 0. We support an alternative option which combines successive alerts into a single alert. We demonstrate this below." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from merlion.post_process.threshold import AggregateAlarms\n", "\n", "# We use a custom post-rule (AggegateAlarms instead of the default Threshold),\n", "# where we suppress all alarms for a day after the most recent one is fired.\n", "threshold = AggregateAlarms(alm_threshold=3.0, alm_suppress_minutes=24*60)\n", "model2 = StatThreshold(StatThresholdConfig(threshold=threshold))\n", "\n", "# Train the model as before\n", "model2.train(train_data, train_labels)\n", "\n", "# Visualize the model's anomaly scores with the new post-rule\n", "fig, ax = model2.plot_anomaly(test_data, filter_scores=True)\n", "plot_anoms(ax, test_labels)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Quantitative Evaluation\n", "\n", "Finally, you may quantitatively evaluate the performance of your model as well. Here, we compute precision, recall, and F1 score for `model2` above." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Model Evaluation\n", "Precision: 0.5000\n", "Recall: 1.0000\n", "F1 Score: 0.6667\n" ] } ], "source": [ "anom_labels2 = model2.get_anomaly_label(test_data)\n", "\n", "print(\"Model Evaluation\")\n", "print(f\"Precision: {TSADMetric.Precision.value(ground_truth=test_labels, predict=anom_labels2):.4f}\")\n", "print(f\"Recall: {TSADMetric.Recall.value(ground_truth=test_labels, predict=anom_labels2):.4f}\")\n", "print(f\"F1 Score: {TSADMetric.F1.value(ground_truth=test_labels, predict=anom_labels2):.4f}\")" ] } ], "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": "3.9.5" } }, "nbformat": 4, "nbformat_minor": 4 }