{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import nbinteract as nbi\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "548dd8f32f5444c1b044f27eee98aca2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(interactive(children=(IntSlider(value=5, description='mean', max=10), FloatSlider(value=1.0, de…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def hist_function(mean, sd, size=1000):\n",
    "    '''\n",
    "    Returns 1000 values picked at random from the normal\n",
    "    distribution with the Mean value and SD given.\n",
    "    '''\n",
    "    return np.random.normal(loc=mean, scale=sd, size=1000)\n",
    "\n",
    "\n",
    "options = {\n",
    "    'title': 'Histogram',\n",
    "    'xlabel': 'Mean value (mean)',\n",
    "    'ylabel': 'Standard Deviation (sd)',\n",
    "    'bins': 10\n",
    "}\n",
    "\n",
    "layouts = {\n",
    "    'plot_height': '480px',\n",
    "    'plot_width': '800px',\n",
    "}\n",
    "\n",
    "hist_chart = nbi.hist(\n",
    "    hist_function,\n",
    "    mean=(0, 10),\n",
    "    sd=(0.2, 2.0, 0.2),\n",
    "    options=options,\n",
    "    layouts=layouts\n",
    ")\n",
    "\n",
    "hist_chart"
   ]
  }
 ],
 "metadata": {
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   "language": "python",
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   "codemirror_mode": {
    "name": "ipython",
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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