{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\n# Plot subspaces to vivualize short/long and ectopic beats\n\nThe artefact detection is based on the method described in [1]_.\n\n.. [1] Lipponen, J. A., & Tarvainen, M. P. (2019). A robust algorithm for\n    heart rate variability time series artefact correction using novel beat\n    classification. Journal of Medical Engineering & Technology, 43(3),\n    173\u2013181. https://doi.org/10.1080/03091902.2019.1640306\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "# Author: Nicolas Legrand <nicolas.legrand@cfin.au.dk>\n# Licence: Apache-2.0"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Visualizing artefacts from RR time series\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "from systole import import_rr\nfrom systole.plots import plot_subspaces\nimport matplotlib.pyplot as plt\n\n# Import PPG recording as numpy array\nrr = import_rr().rr.to_numpy()\n\n_, axs = plt.subplots(ncols=2, figsize=(12, 6))\nplot_subspaces(rr, ax=axs);"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Visualizing artefacts from the `artefact` dictionary\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "from systole.detection import rr_artefacts\n\n# Use the rr_artefacts function to short/long and extra/missed intervals\nartefacts = rr_artefacts(rr)\n\n_, axs = plt.subplots(ncols=2, figsize=(12, 6))\nplot_subspaces(artefacts=artefacts, ax=axs)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Using Bokeh as plotting backend\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "from bokeh.io import output_notebook\nfrom bokeh.plotting import show\nfrom systole.detection import rr_artefacts\noutput_notebook()\n\nshow(\n    plot_subspaces(\n    artefacts=artefacts, backend=\"bokeh\", figsize=400\n    )\n)"
      ]
    }
  ],
  "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": "3.11.16"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}