{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\n# Plot raw physiological signal\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\n\n\nfrom bokeh.io import output_notebook\nfrom bokeh.plotting import show\nfrom systole.plots import plot_raw\n\nfrom systole import import_dataset1, import_ppg"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Plot raw ECG signal\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "# Import PPG recording as pandas data frame\nphysio_df = import_dataset1(modalities=['ECG', 'Respiration'])\n\n# Only use the first 60 seconds for demonstration\necg = physio_df[physio_df.time.between(60, 90)].ecg\nplot_raw(ecg, modality='ecg', sfreq=1000, detector='sleepecg')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Plot raw PPG signal\nImport Respiration recording as pandas data frame\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "rsp = import_dataset1(modalities=['Respiration'])\n\n# Only use the first 90 seconds for demonstration\nrsp = physio_df[physio_df.time.between(500, 600)].respiration\nplot_raw(rsp, sfreq=1000, modality=\"respiration\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Plot raw respiratory signal\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "# Import PPG recording as pandas data frame\nppg = import_ppg()\n\n# Only use the first 60 seconds for demonstration\nplot_raw(ppg[ppg.time<60], sfreq=75)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Using Bokeh as plotting backend\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "output_notebook()\n\nshow(\n    plot_raw(ppg, backend=\"bokeh\", show_heart_rate=True, show_artefacts=True)\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
}