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   "source": [
    "## Interact\n",
    "Here is a simple example of using the `interact` decorator from ipywidgets to create a simple set of widgets to control the parameters of a plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.graph_objs as go\n",
    "import numpy as np\n",
    "from ipywidgets import interact"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we'll create an empty figure, and add an empty scatter trace to it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
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       "FigureWidget({\n",
       "    'data': [{'type': 'scatter', 'uid': '0e6538cc-a0d7-11e8-bd43-645aede86e5b'}], 'layout': {}\n",
       "…"
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   "source": [
    "fig = go.FigureWidget()\n",
    "scatt = fig.add_scatter()\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then, write an update function that inputs the frequency factor (`a`) and phase factor (`b`) and sets the `x` and `y` properties of the scatter trace.  This function is decorated with the `interact` decorator from the `ipywidgets` package. The decorator parameters are used to specify the ranges of parameters that we want to sweep over. See http://ipywidgets.readthedocs.io/en/latest/examples/Using%20Interact.html for more details."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
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       "interactive(children=(FloatSlider(value=3.6, description='a', max=4.0, min=1.0, step=0.01), FloatSlider(value=…"
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    "xs=np.linspace(0, 6, 100)\n",
    "\n",
    "@interact(a=(1.0, 4.0, 0.01), b=(0, 10.0, 0.01), color=['red', 'green', 'blue'])\n",
    "def update(a=3.6, b=4.3, color='blue'):\n",
    "    with fig.batch_update():\n",
    "        scatt.x=xs\n",
    "        scatt.y=np.sin(a*xs-b)\n",
    "        scatt.line.color=color"
   ]
  },
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   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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