multi-trace-stream.ipynb

{
 "metadata": {
  "name": "",
  "signature": "sha256:9a87a7292ffebc7785eb7f5f589adb94d1b6309faa4a6b6bfd11fcf21cb3dba3"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import plotly.plotly as py\n",
      "from plotly.graph_objs import *"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "token0 = py.get_credentials()['stream_ids'][0]  # make sure not to print tokens in plain text\n",
      "token1 = py.get_credentials()['stream_ids'][1]\n",
      "token2 = py.get_credentials()['stream_ids'][2]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fig = Figure()\n",
      "fig['data'].append(Scatter(x=[], y=[], stream=Stream(token=token0)))\n",
      "fig['data'].append(Scatter(x=[], y=[], stream=Stream(token=token1)))\n",
      "fig['data'].append(Scatter(x=[], y=[], stream=Stream(token=token2)))\n",
      "py.iplot(fig, filename='messin')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
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       "metadata": {},
       "output_type": "pyout",
       "png": 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NTPQFBG/f0IZAQPAGWII3xxK8ZTPBW6MTvLmb4M3NTPQFBG/f0IZAQPAGWII3xxK8ZTPB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\nmegLCN4tDL/1rW+Nm266aVx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       "prompt_number": 3,
       "svg": [
        "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" xml:space=\"preserve\" width=\"700\" height=\"500\"><rect x=\"0\" y=\"0\" width=\"700\" height=\"500\" style=\"fill: #ffffff; fill-opacity: 1;\"></rect><g class=\"subplot xy\"><rect x=\"80\" y=\"100\" width=\"540\" height=\"320\" style=\"stroke-width: 0px; fill: #ffffff; fill-opacity: 1;\"></rect><g transform=\"translate(80,100)\"><path class=\"xgrid crisp\" d=\"M0,0v320\" transform=\"translate(154.29,0)\" style=\"stroke: #eeeeee; stroke-opacity: 1; stroke-width: 1px;\"></path><path class=\"xgrid crisp\" d=\"M0,0v320\" transform=\"translate(231.43,0)\" style=\"stroke: #eeeeee; stroke-opacity: 1; stroke-width: 1px;\"></path><path class=\"xgrid crisp\" d=\"M0,0v320\" transform=\"translate(308.57,0)\" style=\"stroke: #eeeeee; stroke-opacity: 1; stroke-width: 1px;\"></path><path class=\"xgrid crisp\" d=\"M0,0v320\" transform=\"translate(385.71,0)\" style=\"stroke: #eeeeee; stroke-opacity: 1; stroke-width: 1px;\"></path><path class=\"xgrid crisp\" d=\"M0,0v320\" transform=\"translate(462.86,0)\" style=\"stroke: #eeeeee; 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font-size: 12px; fill: #444444;\"><tspan class=\"js-link-to-tool\"></tspan><tspan class=\"js-link-spacer\"></tspan><tspan class=\"js-sourcelinks\"></tspan></text></svg>"
       ],
       "text": [
        "<plotly.tools.PlotlyDisplay at 0x10b4d6310>"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import time\n",
      "s0 = py.Stream(token0)\n",
      "s1 = py.Stream(token1)\n",
      "s2 = py.Stream(token2)\n",
      "s0.open()\n",
      "s1.open()\n",
      "s2.open()\n",
      "for i in range(10):\n",
      "    s0.write(Scatter(x=i, y=i))\n",
      "    time.sleep(.1)\n",
      "    s1.write(Scatter(x=i, y=i+1))\n",
      "    time.sleep(.1)\n",
      "    s2.write(Scatter(x=10-i, y=-i))\n",
      "    time.sleep(.1)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}