{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "%matplotlib inline"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Auto-update plot\n\nThis demo shows two possibilities of how to create an auto\nupdating plot, when the data does not come from a device allowing a live plot.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "from numpy import random\nimport time\nfrom itom import dataObject\nfrom itom import plot1"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Option 1: open plot with fixed interval, the plot shares its values\nfrom a given ``dataObject``, update the ``dataObject`` regularily and call\nthe replot slot of the plot to force an update of the canvas (without that\nslot, the canvas is updated once the user makes a zoom, clicks somewhere...)\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "d = dataObject.zeros([1, 3], \"float64\")\n[i, h] = plot1(d, properties={\"yAxisInterval\": (0, 1)})\n\nt = time.time()\nfor i in range(0, 50):\n    d[0, :] = random.rand(3)\n    h.call(\"replot\")\n    time.sleep(0.1)\nprint(\"finished in %.2f s using replot\" % (time.time() - t))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Option 2: similar to option 1, but the plot is continously given the same\nobject again as source. Some caching mechanism provides a quick replot\nof the data. This option makes an automatic bounds-check of the new source\nand can therefore automatically reset automatic axes intervals\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "[i, h] = plot1(d)\n\nt = time.time()\nfor i in range(0, 50):\n    d[0, :] = random.rand(3)\n    h[\"source\"] = d\n    time.sleep(0.1)\nprint(\"finished in %.2f s using autoupdate\" % (time.time() - t))"
      ]
    }
  ],
  "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": "3.8.10"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}