{ "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$serie)" ] }, { "cell_type": "code", "execution_count": 5, "id": "e0c8a397", "metadata": {}, "outputs": [], "source": [ "# establishing change point method \n", " model <- hcp_pelt()" ] }, { "cell_type": "code", "execution_count": 6, "id": "9d0079cf", "metadata": {}, "outputs": [], "source": [ "# fitting the model\n", " model <- fit(model, dataset$serie)" ] }, { "cell_type": "code", "execution_count": 7, "id": "863506fd", "metadata": {}, "outputs": [], "source": [ "# making detections\n", " detection <- detect(model, dataset$serie)" ] }, { "cell_type": "code", "execution_count": 8, "id": "1241ed10", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " idx event type\n", "1 9 TRUE changepoint\n", "2 19 TRUE changepoint\n", "3 29 TRUE changepoint\n", "4 39 TRUE changepoint\n", "5 60 TRUE changepoint\n", "6 71 TRUE changepoint\n", "7 81 TRUE changepoint\n", "8 91 TRUE changepoint\n" ] } ], "source": [ "# filtering detected events\n", " print(detection |> dplyr::filter(event==TRUE))" ] }, { "cell_type": "code", "execution_count": 9, "id": "10456892", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " event \n", "detection TRUE FALSE\n", "TRUE 0 8 \n", "FALSE 1 92 \n" ] } ], "source": [ "# evaluating the detections\n", " evaluation <- evaluate(model, detection$event, dataset$event)\n", " print(evaluation$confMatrix)" ] }, { "cell_type": "code", "execution_count": 10, "id": "075f7d2f", "metadata": {}, "outputs": [ { "data": { "image/png": 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fp1Dw8P2nEAgHsajSYsLGzPnj2PugHeigUAU9Hr9XFxcSKRKDk5mXYWq+Do6Dh/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\n/4FiZ5e0Wq1KpeLH5stz7J15idzd3WmTWIpareYXSgDNm6fT6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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 }