{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "1d0d0503", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Loading required package: daltoolbox\n", "\n", "Registered S3 method overwritten by 'quantmod':\n", " method from\n", " as.zoo.data.frame zoo \n", "\n", "\n", "Attaching package: ‘daltoolbox’\n", "\n", "\n", "The following object is masked from ‘package:base’:\n", "\n", " transform\n", "\n", "\n", "Loading required package: harbinger\n", "\n" ] } ], "source": [ "# Harbinger Package\n", "# version 1.0.777\n", "\n", "source(\"https://raw.githubusercontent.com/cefet-rj-dal/harbinger/master/jupyter.R\")\n", "\n", "#loading Harbinger\n", "load_library(\"daltoolbox\") \n", "load_library(\"harbinger\") " ] }, { "cell_type": "code", "execution_count": 2, "id": "c0d41422", "metadata": {}, "outputs": [], "source": [ "#loading the example database\n", "data(examples_changepoints)" ] }, { "cell_type": "code", "execution_count": 3, "id": "9a12bab2", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A data.frame: 6 × 2
serieevent
<dbl><lgl>
10.00FALSE
20.25FALSE
30.50FALSE
40.75FALSE
51.00FALSE
61.25FALSE
\n" ], "text/latex": [ "A data.frame: 6 × 2\n", "\\begin{tabular}{r|ll}\n", " & serie & event\\\\\n", " & & \\\\\n", "\\hline\n", "\t1 & 0.00 & FALSE\\\\\n", "\t2 & 0.25 & FALSE\\\\\n", "\t3 & 0.50 & FALSE\\\\\n", "\t4 & 0.75 & FALSE\\\\\n", "\t5 & 1.00 & FALSE\\\\\n", "\t6 & 1.25 & FALSE\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A data.frame: 6 × 2\n", "\n", "| | serie <dbl> | event <lgl> |\n", "|---|---|---|\n", "| 1 | 0.00 | FALSE |\n", "| 2 | 0.25 | FALSE |\n", "| 3 | 0.50 | FALSE |\n", "| 4 | 0.75 | FALSE |\n", "| 5 | 1.00 | FALSE |\n", "| 6 | 1.25 | FALSE |\n", "\n" ], "text/plain": [ " serie event\n", "1 0.00 FALSE\n", "2 0.25 FALSE\n", "3 0.50 FALSE\n", "4 0.75 FALSE\n", "5 1.00 FALSE\n", "6 1.25 FALSE" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Using the simple time series \n", "dataset <- examples_changepoints$simple\n", "head(dataset)" ] }, { "cell_type": "code", "execution_count": 4, "id": "b744a3ad", "metadata": {}, "outputs": [ { "data": { "image/png": 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v8oqvndBkUistjcj4uQvW/2sTn/ufup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\nKHWGU+hcpKyMm9l80gRApj978YBKX0T1LdKa6xMYq00YACjtSo5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"text/plain": [ "plot without title" ] }, "metadata": { "image/png": { "height": 420, "width": 420 } }, "output_type": "display_data" } ], "source": [ "#ploting the time series\n", "plot_ts(x = 1:length(dataset$serie), y = dataset$serie)" ] }, { "cell_type": "code", "execution_count": 5, "id": "e0c8a397", "metadata": {}, "outputs": [], "source": [ "# establishing change finder ets method \n", " model <- hcp_cf_ets()" ] }, { "cell_type": "code", "execution_count": 6, "id": "9d0079cf", "metadata": {}, "outputs": [], "source": [ "# fitting the model\n", " model <- fit(model, dataset$serie)" ] }, { "cell_type": "code", "execution_count": 7, "id": "863506fd", "metadata": {}, "outputs": [], "source": [ "# making detections\n", " detection <- detect(model, dataset$serie)" ] }, { "cell_type": "code", "execution_count": 8, "id": "1241ed10", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " idx event type\n", "1 35 TRUE anomaly\n", "2 51 TRUE changepoint\n", "3 58 TRUE anomaly\n", "4 87 TRUE changepoint\n" ] } ], "source": [ "# filtering detected events\n", " print(detection |> dplyr::filter(event==TRUE))" ] }, { "cell_type": "code", "execution_count": 9, "id": "10456892", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " event \n", "detection TRUE FALSE\n", "TRUE 0 4 \n", "FALSE 1 96 \n" ] } ], "source": [ "# evaluating the detections\n", " evaluation <- evaluate(model, detection$event, dataset$event)\n", " print(evaluation$confMatrix)" ] }, { "cell_type": "code", "execution_count": 10, "id": "075f7d2f", "metadata": {}, "outputs": [ { "data": { "image/png": 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UKIxo0bv/nmm+fOnfvkk09ktwBQGoYd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\nANAIhh0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"text/plain": [ "plot without title" ] }, "metadata": { "image/png": { "height": 420, "width": 420 } }, "output_type": "display_data" } ], "source": [ "# ploting the results\n", " grf <- har_plot(model, dataset$serie, detection, dataset$event)\n", " plot(grf)" ] }, { "cell_type": "code", "execution_count": null, "id": "07c53f34", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "R", "language": "R", "name": "ir" }, "language_info": { "codemirror_mode": "r", "file_extension": ".r", "mimetype": "text/x-r-source", "name": "R", "pygments_lexer": "r", "version": "4.4.0" } }, "nbformat": 4, "nbformat_minor": 5 }