Raw_Data.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from os import listdir\n",
    "\n",
    "from bokeh.io import output_notebook, show\n",
    "from bokeh.layouts import column\n",
    "from bokeh.plotting import figure, show, output_file\n",
    "\n",
    "from sklearn import preprocessing\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.decomposition import PCA\n",
    "\n",
    "from waveform_processor import ABPWaveformProcessor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.io.pytables.HDFStore'>\n",
      "File path: raw/K2ICU_BED18-1447919424.hd5\n",
      "/Vitals               frame_table  (typ->appendable,nrows->4627,ncols->10,indexers->[index])   \n",
      "/Waveforms            frame_table  (typ->appendable,nrows->2217600,ncols->11,indexers->[index])\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AR1</th>\n",
       "      <th>AR2</th>\n",
       "      <th>AR3</th>\n",
       "      <th>I</th>\n",
       "      <th>II</th>\n",
       "      <th>III</th>\n",
       "      <th>V</th>\n",
       "      <th>SPO2</th>\n",
       "      <th>CVP1</th>\n",
       "      <th>CVP2</th>\n",
       "      <th>RR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015-11-19 02:50:25.000000000</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.029</td>\n",
       "      <td>0.005</td>\n",
       "      <td>-0.017</td>\n",
       "      <td>-0.034</td>\n",
       "      <td>13.299</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-19 02:50:25.004166667</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.022</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-0.022</td>\n",
       "      <td>-0.034</td>\n",
       "      <td>26.598</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-19 02:50:25.008333334</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.022</td>\n",
       "      <td>-0.005</td>\n",
       "      <td>-0.027</td>\n",
       "      <td>-0.039</td>\n",
       "      <td>26.598</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-19 02:50:25.012500001</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.022</td>\n",
       "      <td>-0.020</td>\n",
       "      <td>-0.039</td>\n",
       "      <td>-0.039</td>\n",
       "      <td>39.936</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-19 02:50:25.016666668</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.017</td>\n",
       "      <td>-0.029</td>\n",
       "      <td>-0.044</td>\n",
       "      <td>-0.037</td>\n",
       "      <td>39.936</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               AR1  AR2  AR3      I     II    III      V  \\\n",
       "2015-11-19 02:50:25.000000000  NaN  NaN  NaN  0.029  0.005 -0.017 -0.034   \n",
       "2015-11-19 02:50:25.004166667  NaN  NaN  NaN  0.022  0.000 -0.022 -0.034   \n",
       "2015-11-19 02:50:25.008333334  NaN  NaN  NaN  0.022 -0.005 -0.027 -0.039   \n",
       "2015-11-19 02:50:25.012500001  NaN  NaN  NaN  0.022 -0.020 -0.039 -0.039   \n",
       "2015-11-19 02:50:25.016666668  NaN  NaN  NaN  0.017 -0.029 -0.044 -0.037   \n",
       "\n",
       "                                 SPO2  CVP1  CVP2  RR  \n",
       "2015-11-19 02:50:25.000000000  13.299   NaN   NaN NaN  \n",
       "2015-11-19 02:50:25.004166667  26.598   NaN   NaN NaN  \n",
       "2015-11-19 02:50:25.008333334  26.598   NaN   NaN NaN  \n",
       "2015-11-19 02:50:25.012500001  39.936   NaN   NaN NaN  \n",
       "2015-11-19 02:50:25.016666668  39.936   NaN   NaN NaN  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "store = {}\n",
    "\n",
    "for raw in listdir('raw/'):\n",
    "    if (raw != '.DS_Store' and raw !='.ipynb_checkpoints'):\n",
    "        store[raw] = pd.HDFStore('raw/{0}'.format(raw))\n",
    "\n",
    "# Through Trial and Error, Good vs. Bad Raw\n",
    "\n",
    "# Good\n",
    "# 'K2ICU_BED18-1447919424.hd5' <-- Best of the bunch. Strong Waveforms and Vitals (AR2 data -- AR2_data.iloc[357000:1071000])\n",
    "# DELETED 'K2ICU_BED09-1438799806.hd5' <-- Waveform data, not vitals, summary is useless. Waveform data isn't ideal. Poor ecg\n",
    "# 'K2ICU_BED32-1487763686.hd5' <-- Waveforms data (decent) + vitals (poor) (NO AR DATA)\n",
    "\n",
    "# Bad\n",
    "# 'K2ICU_BED25-1458669700.hd5' <-- No vitals or waveform data\n",
    "# 'K2ICU_BED01-1485531766.hd5' <-- just Vital data, nothing else\n",
    "# 'K2ICU_BED13-1497121350.hd5' <-- just Vital data, decent heart rate data but not much else\n",
    "# 'K2ICU_BED07-1493859809.hd5' <-- just Vital data\n",
    "# 'K2ICU_BED17-1509145105.hd5' <-- just Vitals data, SPO2-% the only column with info\n",
    "# 'K2ICU_BED01-1472098497.hd5' <-- just Vitals data, Decent HR, ARS2-M might be useful\n",
    "\n",
    "file = 'K2ICU_BED18-1447919424.hd5'\n",
    "\n",
    "# print(store.keys())\n",
    "print(store[file])\n",
    "\n",
    "waveforms = store[file].select('Waveforms')\n",
    "vitals = store[file].select('Vitals')\n",
    "# summary = store[file].select('Summary')\n",
    "\n",
    "# waves=store.select('Waveforms')\n",
    "\n",
    "# vitals.head(5)\n",
    "# summary.head(100)\n",
    "waveforms.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2015-11-19 03:47:25.000000000    8.0\n",
      "2015-11-19 03:47:25.004166667    8.0\n",
      "2015-11-19 03:47:25.008333334    8.0\n",
      "2015-11-19 03:47:25.012500001    8.2\n",
      "2015-11-19 03:47:25.016666668    8.2\n",
      "2015-11-19 03:47:25.020833335    8.2\n",
      "2015-11-19 03:47:25.025000002    8.2\n",
      "2015-11-19 03:47:25.029166669    8.2\n",
      "2015-11-19 03:47:25.033333336    8.2\n",
      "2015-11-19 03:47:25.037500003    8.4\n",
      "Name: AR2, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "AR1_data = waveforms['AR1'].dropna()\n",
    "AR2_data = waveforms['AR2'].dropna()\n",
    "AR3_data = waveforms['AR3'].dropna()\n",
    "\n",
    "AR2_data = AR2_data.drop(AR2_data[AR2_data.values < -5].index)\n",
    "AR2_data = AR2_data.drop(AR2_data[AR2_data.values > 180].index)\n",
    "\n",
    "# print(len(AR1_data))\n",
    "print(AR2_data.head(10))\n",
    "# print(AR3_data.head(5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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cmz/a4NLzS6oWpN33THe30zIWGAk3gZNfnESzkolP8U8JnBc4o23ptljZdaWtq0JERKmI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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a2a3667f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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GX9hTGgppRQ931r5B7+9r3bpohjQ+/2XLqJ3kK3qAaL2xUeIbcIA7f8AJlxtv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\niqIoiqK0af4fB8/EIvCxPLQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a2a38b080>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a2d0c9860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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BH3jvS+xXoiRHJIFWPQ+zr40uq4lJzs45dhDqEPzS5wtgUi844T745FtWVlq9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\n/0VjSsCXbzHuAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a2d09f240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "num = 5000\n",
    "\n",
    "waveform_data = waveforms.head(num)\n",
    "vitals_data = vitals.head(num)\n",
    "\n",
    "abp_signal_whole = AR2_data\n",
    "abp_signal_ideal = AR2_data.iloc[350860:1071000] #waveform_data['AR2'] 357000:1071000\n",
    "abp_signal_poor = AR2_data.iloc[:346700] #100000\n",
    "abp_signal_hectic = AR2_data.iloc[346700:360860]\n",
    "\n",
    "# abp_segment = pd.DataFrame({\"AR1\": AR2_data.values})\n",
    "# abp_segment = pd.DataFrame(AR2_data)\n",
    "# abp_segment.rename(index=str, columns={\"AR1\": \"AR2\"})\n",
    "# print(abp_segment.head(5))\n",
    "\n",
    "# vitals_signal = vitals_data['AR2-M'] #waveform_data['V']\n",
    "# ecg_signal = waveform_data['I']\n",
    "\n",
    "plt.figure(num=1, figsize=(14, 2))\n",
    "plt.plot(abp_signal_ideal, color='green')\n",
    "\n",
    "plt.figure(num=2, figsize=(14, 2))\n",
    "plt.plot(abp_signal_hectic, color='blue')\n",
    "\n",
    "plt.figure(num=3, figsize=(14, 2))\n",
    "plt.plot(abp_signal_poor, color='red')\n",
    "\n",
    "plt.figure(num=4, figsize=(14, 2))\n",
    "plt.plot(abp_signal_whole, color='orange')\n",
    "\n",
    "# print(isinstance(abp_signal_ideal, pd.Series))\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "waveform_processor = ABPWaveformProcessor()\n",
    "\n",
    "level=7\n",
    "window_size=1\n",
    "\n",
    "df_ideal = waveform_processor.processWaveform(abp_signal_ideal, level, window_size, \"AR2\")\n",
    "df_poor = waveform_processor.processWaveform(abp_signal_poor, level, window_size, \"AR2\")\n",
    "df_hectic = waveform_processor.processWaveform(abp_signal_hectic, level, window_size, \"AR2\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"https://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"911ffebd-2dfb-472e-8034-042dba2dd5f0\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "  var JS_MIME_TYPE = 'application/javascript';\n",
       "  var HTML_MIME_TYPE = 'text/html';\n",
       "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
       "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
       "\n",
       "  /**\n",
       "   * Render data to the DOM node\n",
       "   */\n",
       "  function render(props, node) {\n",
       "    var script = document.createElement(\"script\");\n",
       "    node.appendChild(script);\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when an output is cleared or removed\n",
       "   */\n",
       "  function handleClearOutput(event, handle) {\n",
       "    var cell = handle.cell;\n",
       "\n",
       "    var id = cell.output_area._bokeh_element_id;\n",
       "    var server_id = cell.output_area._bokeh_server_id;\n",
       "    // Clean up Bokeh references\n",
       "    if (id !== undefined) {\n",
       "      Bokeh.index[id].model.document.clear();\n",
       "      delete Bokeh.index[id];\n",
       "    }\n",
       "\n",
       "    if (server_id !== undefined) {\n",
       "      // Clean up Bokeh references\n",
       "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
       "      cell.notebook.kernel.execute(cmd, {\n",
       "        iopub: {\n",
       "          output: function(msg) {\n",
       "            var element_id = msg.content.text.trim();\n",
       "            Bokeh.index[element_id].model.document.clear();\n",
       "            delete Bokeh.index[element_id];\n",
       "          }\n",
       "        }\n",
       "      });\n",
       "      // Destroy server and session\n",
       "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
       "      cell.notebook.kernel.execute(cmd);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when a new output is added\n",
       "   */\n",
       "  function handleAddOutput(event, handle) {\n",
       "    var output_area = handle.output_area;\n",
       "    var output = handle.output;\n",
       "\n",
       "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
       "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
       "      return\n",
       "    }\n",
       "\n",
       "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
       "\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
       "      toinsert[0].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
       "      // store reference to embed id on output_area\n",
       "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
       "    }\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
       "      var bk_div = document.createElement(\"div\");\n",
       "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "      var script_attrs = bk_div.children[0].attributes;\n",
       "      for (var i = 0; i < script_attrs.length; i++) {\n",
       "        toinsert[0].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
       "      }\n",
       "      // store reference to server id on output_area\n",
       "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function register_renderer(events, OutputArea) {\n",
       "\n",
       "    function append_mime(data, metadata, element) {\n",
       "      // create a DOM node to render to\n",
       "      var toinsert = this.create_output_subarea(\n",
       "        metadata,\n",
       "        CLASS_NAME,\n",
       "        EXEC_MIME_TYPE\n",
       "      );\n",
       "      this.keyboard_manager.register_events(toinsert);\n",
       "      // Render to node\n",
       "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "      render(props, toinsert[0]);\n",
       "      element.append(toinsert);\n",
       "      return toinsert\n",
       "    }\n",
       "\n",
       "    /* Handle when an output is cleared or removed */\n",
       "    events.on('clear_output.CodeCell', handleClearOutput);\n",
       "    events.on('delete.Cell', handleClearOutput);\n",
       "\n",
       "    /* Handle when a new output is added */\n",
       "    events.on('output_added.OutputArea', handleAddOutput);\n",
       "\n",
       "    /**\n",
       "     * Register the mime type and append_mime function with output_area\n",
       "     */\n",
       "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "      /* Is output safe? */\n",
       "      safe: true,\n",
       "      /* Index of renderer in `output_area.display_order` */\n",
       "      index: 0\n",
       "    });\n",
       "  }\n",
       "\n",
       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
       "  if (root.Jupyter !== undefined) {\n",
       "    var events = require('base/js/events');\n",
       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
       "\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  \n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    var el = document.getElementById(\"911ffebd-2dfb-472e-8034-042dba2dd5f0\");\n",
       "    if (el != null) {\n",
       "      el.textContent = \"BokehJS is loading...\";\n",
       "    }\n",
       "    if (root.Bokeh !== undefined) {\n",
       "      if (el != null) {\n",
       "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
       "      }\n",
       "    } else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "    }\n",
       "    finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.info(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(js_urls, callback) {\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = js_urls.length;\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var s = document.createElement('script');\n",
       "      s.src = url;\n",
       "      s.async = false;\n",
       "      s.onreadystatechange = s.onload = function() {\n",
       "        root._bokeh_is_loading--;\n",
       "        if (root._bokeh_is_loading === 0) {\n",
       "          console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "          run_callbacks()\n",
       "        }\n",
       "      };\n",
       "      s.onerror = function() {\n",
       "        console.warn(\"failed to load library \" + url);\n",
       "      };\n",
       "      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "    }\n",
       "  };var element = document.getElementById(\"911ffebd-2dfb-472e-8034-042dba2dd5f0\");\n",
       "  if (element == null) {\n",
       "    console.log(\"Bokeh: ERROR: autoload.js configured with elementid '911ffebd-2dfb-472e-8034-042dba2dd5f0' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.14.min.js\"];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "    },\n",
       "    function(Bokeh) {\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.css\");\n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i].call(root, root.Bokeh);\n",
       "      }if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"911ffebd-2dfb-472e-8034-042dba2dd5f0\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(js_urls, function() {\n",
       "      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
      "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(\"911ffebd-2dfb-472e-8034-042dba2dd5f0\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n    }\n    finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.info(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(js_urls, callback) {\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = js_urls.length;\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var s = document.createElement('script');\n      s.src = url;\n      s.async = false;\n      s.onreadystatechange = s.onload = function() {\n        root._bokeh_is_loading--;\n        if (root._bokeh_is_loading === 0) {\n          console.log(\"Bokeh: all BokehJS libraries loaded\");\n          run_callbacks()\n        }\n      };\n      s.onerror = function() {\n        console.warn(\"failed to load library \" + url);\n      };\n      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.getElementsByTagName(\"head\")[0].appendChild(s);\n    }\n  };var element = document.getElementById(\"911ffebd-2dfb-472e-8034-042dba2dd5f0\");\n  if (element == null) {\n    console.log(\"Bokeh: ERROR: autoload.js configured with elementid '911ffebd-2dfb-472e-8034-042dba2dd5f0' but no matching script tag was found. \")\n    return false;\n  }\n\n  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.14.min.js\"];\n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    \n    function(Bokeh) {\n      \n    },\n    function(Bokeh) {\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.css\");\n    }\n  ];\n\n  function run_inline_js() {\n    \n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(\"911ffebd-2dfb-472e-8034-042dba2dd5f0\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(js_urls, function() {\n      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"bk-root\">\n",
       "    <div class=\"bk-plotdiv\" id=\"70f8fc6f-ee14-4c6e-8bca-37364a32cbf4\"></div>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
       "  var docs_json = 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Application\",\"version\":\"0.12.14\"}};\n",
       "  var render_items = [{\"docid\":\"0926c59b-9b6f-44e5-b756-1c6261a4b0b6\",\"elementid\":\"70f8fc6f-ee14-4c6e-8bca-37364a32cbf4\",\"modelid\":\"a13b1871-4fd6-4145-a6b2-3b1daabddedb\",\"notebook_comms_target\":\"217381da-7cb7-4e05-82b3-2be7e94fa964\"}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        embed_document(root);\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "      attempts++;\n",
       "      if (attempts > 100) {\n",
       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\")\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "a13b1871-4fd6-4145-a6b2-3b1daabddedb"
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<p><code>&lt;Bokeh Notebook handle for <strong>In[6]</strong>&gt;</code></p>"
      ],
      "text/plain": [
       "<bokeh.io.notebook.CommsHandle at 0x1a2d02e470>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "colors = [\"red\", \"olive\", \"darkred\", \"goldenrod\", \"skyblue\", \"orange\", \"salmon\"]\n",
    "\n",
    "p1 = figure(plot_width=600, plot_height=300, title=\"Detail Number vs Energy Coefficients\")\n",
    "p2 = figure(plot_width=600, plot_height=300, title=\"Average Number vs Energy Coefficients\")\n",
    "\n",
    "for color, data in zip([\"red\", \"goldenrod\", \"skyblue\"], [df_ideal, df_poor, df_hectic]):\n",
    "    data = data.head(5)\n",
    "#    print(data)\n",
    "    for i, coeffs in enumerate(data):\n",
    "#         print(coeffs)\n",
    "        for value in data[coeffs]:\n",
    "#             print(value)\n",
    "            y = value\n",
    "            #color = colors[i % len(colors)]\n",
    "\n",
    "            if \"cD\" in coeffs: \n",
    "                p1.circle(x=i, y=y, color=color)\n",
    "            else:\n",
    "                p2.circle(x=i, y=y, color=color)\n",
    "                #{'value': i, 'transform': Jitter(width=1)}\n",
    "\n",
    "# output_file(\"jitter.html\")\n",
    "\n",
    "output_notebook()\n",
    "\n",
    "show(column(p1,p2), notebook_handle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a2d09f668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a2e65e5f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a2e66b278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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Pr4HzP4cVT8LJf7bELDcLDu+0xCvvILzWxkZKTKsH7c6LPjZteQ8adYUmPcq/fyme97Dm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\n/0VjSsCXbzHuAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a2e6186d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "level = 7\n",
    "\n",
    "df_whole = waveform_processor.processWaveform(abp_signal_whole, level, 1, \"AR2\")\n",
    "\n",
    "min_max_scaler = preprocessing.MinMaxScaler()\n",
    "abp_train_minmax = min_max_scaler.fit_transform(df_whole)\n",
    "\n",
    "n_samples, n_features = abp_train_minmax.shape #1622, 10\n",
    "n_digits = 2\n",
    "n_targets = ['0', '1']\n",
    "\n",
    "cluster_data = KMeans(n_clusters=n_digits).fit_predict(abp_train_minmax)\n",
    "\n",
    "reduced_data = PCA(n_components=2).fit_transform(abp_train_minmax)\n",
    "\n",
    "pca_kmeans = KMeans(init='k-means++', n_clusters=n_digits, n_init=10).fit_predict(reduced_data)\n",
    "\n",
    "plt.figure(1)\n",
    "plt.plot(reduced_data[:, 0], reduced_data[:, 1], 'k.', markersize=2)\n",
    "\n",
    "plt.figure(2, figsize=(14, 2))\n",
    "plt.scatter(waveform_processor.segmenter(abp_signal_whole, level)[1:], cluster_data, color='red')\n",
    "\n",
    "plt.figure(3, figsize=(14, 2))\n",
    "plt.scatter(waveform_processor.segmenter(abp_signal_whole, level)[1:], pca_kmeans, color='blue')\n",
    "\n",
    "plt.figure(num=4, figsize=(14, 2))\n",
    "plt.plot(abp_signal_whole, color='orange')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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HmzHNoCSLwPOAzwKnVNX9zdTXgFOmlJam4x3AHwA/GBizJmbXduAo8LfNaY7XJDkJa2Im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\nswAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a2d09feb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAzIAAACPCAYAAAAhie4bAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nn3T73AomWgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a35c5b0f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Test on poor signal\n",
    "\n",
    "min_max_scaler = preprocessing.MinMaxScaler()\n",
    "abp_train_poor = min_max_scaler.fit_transform(waveform_processor.processWaveform(abp_signal_poor, 7, 1))\n",
    "\n",
    "reduced_data_poor = PCA(n_components=2).fit_transform(abp_train_poor)\n",
    "\n",
    "reduced_kmeans = KMeans(init='k-means++', n_clusters=n_digits, n_init=10).fit(reduced_data)\n",
    "reduced_kmeans_poor = reduced_kmeans.predict(reduced_data_poor)\n",
    "\n",
    "plt.figure(5, figsize=(14, 2))\n",
    "plt.scatter(np.arange(0,len(reduced_kmeans_poor)), reduced_kmeans_poor, color='blue')\n",
    "\n",
    "plt.figure(num=6, figsize=(14, 2))\n",
    "plt.plot(abp_signal_poor, color='orange')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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NY2AariJJ21gRQkpn9oU+TFiGw2xWq21xh22HQ+DgwUBU7WO2qLrC/eSTwKlT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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a2e921ef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Test clustering on good signal\n",
    "# abp_signal_ideal\n",
    "\n",
    "plt.figure(1)\n",
    "plt.plot(np.arange(0, len(df_ideal)), df_ideal[\"cD5\"], 'k.', markersize=2, color='red')\n",
    "\n",
    "plt.figure(1)\n",
    "plt.plot(np.arange(0, len(df_ideal)), df_ideal[\"cD6\"], 'k.', markersize=2, color='blue')\n",
    "\n",
    "plt.figure(1)\n",
    "plt.plot(np.arange(0, len(df_ideal)), df_ideal[\"cD7\"], 'k.', markersize=2, color='green')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"https://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"a06774eb-6263-4836-ac70-cd0dbc45b0c7\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "  var JS_MIME_TYPE = 'application/javascript';\n",
       "  var HTML_MIME_TYPE = 'text/html';\n",
       "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
       "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
       "\n",
       "  /**\n",
       "   * Render data to the DOM node\n",
       "   */\n",
       "  function render(props, node) {\n",
       "    var script = document.createElement(\"script\");\n",
       "    node.appendChild(script);\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when an output is cleared or removed\n",
       "   */\n",
       "  function handleClearOutput(event, handle) {\n",
       "    var cell = handle.cell;\n",
       "\n",
       "    var id = cell.output_area._bokeh_element_id;\n",
       "    var server_id = cell.output_area._bokeh_server_id;\n",
       "    // Clean up Bokeh references\n",
       "    if (id !== undefined) {\n",
       "      Bokeh.index[id].model.document.clear();\n",
       "      delete Bokeh.index[id];\n",
       "    }\n",
       "\n",
       "    if (server_id !== undefined) {\n",
       "      // Clean up Bokeh references\n",
       "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
       "      cell.notebook.kernel.execute(cmd, {\n",
       "        iopub: {\n",
       "          output: function(msg) {\n",
       "            var element_id = msg.content.text.trim();\n",
       "            Bokeh.index[element_id].model.document.clear();\n",
       "            delete Bokeh.index[element_id];\n",
       "          }\n",
       "        }\n",
       "      });\n",
       "      // Destroy server and session\n",
       "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
       "      cell.notebook.kernel.execute(cmd);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when a new output is added\n",
       "   */\n",
       "  function handleAddOutput(event, handle) {\n",
       "    var output_area = handle.output_area;\n",
       "    var output = handle.output;\n",
       "\n",
       "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
       "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
       "      return\n",
       "    }\n",
       "\n",
       "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
       "\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
       "      toinsert[0].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
       "      // store reference to embed id on output_area\n",
       "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
       "    }\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
       "      var bk_div = document.createElement(\"div\");\n",
       "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "      var script_attrs = bk_div.children[0].attributes;\n",
       "      for (var i = 0; i < script_attrs.length; i++) {\n",
       "        toinsert[0].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
       "      }\n",
       "      // store reference to server id on output_area\n",
       "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function register_renderer(events, OutputArea) {\n",
       "\n",
       "    function append_mime(data, metadata, element) {\n",
       "      // create a DOM node to render to\n",
       "      var toinsert = this.create_output_subarea(\n",
       "        metadata,\n",
       "        CLASS_NAME,\n",
       "        EXEC_MIME_TYPE\n",
       "      );\n",
       "      this.keyboard_manager.register_events(toinsert);\n",
       "      // Render to node\n",
       "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "      render(props, toinsert[0]);\n",
       "      element.append(toinsert);\n",
       "      return toinsert\n",
       "    }\n",
       "\n",
       "    /* Handle when an output is cleared or removed */\n",
       "    events.on('clear_output.CodeCell', handleClearOutput);\n",
       "    events.on('delete.Cell', handleClearOutput);\n",
       "\n",
       "    /* Handle when a new output is added */\n",
       "    events.on('output_added.OutputArea', handleAddOutput);\n",
       "\n",
       "    /**\n",
       "     * Register the mime type and append_mime function with output_area\n",
       "     */\n",
       "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "      /* Is output safe? */\n",
       "      safe: true,\n",
       "      /* Index of renderer in `output_area.display_order` */\n",
       "      index: 0\n",
       "    });\n",
       "  }\n",
       "\n",
       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
       "  if (root.Jupyter !== undefined) {\n",
       "    var events = require('base/js/events');\n",
       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
       "\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  \n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    var el = document.getElementById(\"a06774eb-6263-4836-ac70-cd0dbc45b0c7\");\n",
       "    if (el != null) {\n",
       "      el.textContent = \"BokehJS is loading...\";\n",
       "    }\n",
       "    if (root.Bokeh !== undefined) {\n",
       "      if (el != null) {\n",
       "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
       "      }\n",
       "    } else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "    }\n",
       "    finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.info(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(js_urls, callback) {\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = js_urls.length;\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var s = document.createElement('script');\n",
       "      s.src = url;\n",
       "      s.async = false;\n",
       "      s.onreadystatechange = s.onload = function() {\n",
       "        root._bokeh_is_loading--;\n",
       "        if (root._bokeh_is_loading === 0) {\n",
       "          console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "          run_callbacks()\n",
       "        }\n",
       "      };\n",
       "      s.onerror = function() {\n",
       "        console.warn(\"failed to load library \" + url);\n",
       "      };\n",
       "      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "    }\n",
       "  };var element = document.getElementById(\"a06774eb-6263-4836-ac70-cd0dbc45b0c7\");\n",
       "  if (element == null) {\n",
       "    console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'a06774eb-6263-4836-ac70-cd0dbc45b0c7' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.14.min.js\"];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "    },\n",
       "    function(Bokeh) {\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.css\");\n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i].call(root, root.Bokeh);\n",
       "      }if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"a06774eb-6263-4836-ac70-cd0dbc45b0c7\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(js_urls, function() {\n",
       "      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
      "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(\"a06774eb-6263-4836-ac70-cd0dbc45b0c7\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n    }\n    finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.info(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(js_urls, callback) {\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = js_urls.length;\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var s = document.createElement('script');\n      s.src = url;\n      s.async = false;\n      s.onreadystatechange = s.onload = function() {\n        root._bokeh_is_loading--;\n        if (root._bokeh_is_loading === 0) {\n          console.log(\"Bokeh: all BokehJS libraries loaded\");\n          run_callbacks()\n        }\n      };\n      s.onerror = function() {\n        console.warn(\"failed to load library \" + url);\n      };\n      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.getElementsByTagName(\"head\")[0].appendChild(s);\n    }\n  };var element = document.getElementById(\"a06774eb-6263-4836-ac70-cd0dbc45b0c7\");\n  if (element == null) {\n    console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'a06774eb-6263-4836-ac70-cd0dbc45b0c7' but no matching script tag was found. \")\n    return false;\n  }\n\n  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.14.min.js\"];\n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    \n    function(Bokeh) {\n      \n    },\n    function(Bokeh) {\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.css\");\n    }\n  ];\n\n  function run_inline_js() {\n    \n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(\"a06774eb-6263-4836-ac70-cd0dbc45b0c7\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(js_urls, function() {\n      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"bk-root\">\n",
       "    <div class=\"bk-plotdiv\" id=\"fca55549-d6d5-434d-8a29-dae49dda8052\"></div>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
       "  var docs_json = 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Application\",\"version\":\"0.12.14\"}};\n",
       "  var render_items = [{\"docid\":\"20c5984e-893c-4055-aeb9-a19eb1d31dd2\",\"elementid\":\"fca55549-d6d5-434d-8a29-dae49dda8052\",\"modelid\":\"adc0593f-3537-4dc8-bfa2-4d4723f8496e\",\"notebook_comms_target\":\"be2c3c42-470c-47ba-9815-0971410dd1e6\"}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        embed_document(root);\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "      attempts++;\n",
       "      if (attempts > 100) {\n",
       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\")\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "adc0593f-3537-4dc8-bfa2-4d4723f8496e"
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<p><code>&lt;Bokeh Notebook handle for <strong>In[7]</strong>&gt;</code></p>"
      ],
      "text/plain": [
       "<bokeh.io.notebook.CommsHandle at 0x1a2d0509e8>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p = figure(plot_width=900, plot_height=400)\n",
    "\n",
    "# add a circle renderer with a size, color, and alpha\n",
    "p.circle(np.arange(0, len(df_ideal)), df_ideal[\"cD7\"], size=5, color=\"olive\", alpha=0.5)\n",
    "p.circle(np.arange(0, len(df_ideal)), df_ideal[\"cD6\"], size=5, color=\"red\", alpha=0.5)\n",
    "p.circle(np.arange(0, len(df_ideal)), df_ideal[\"cD5\"], size=5, color=\"navy\", alpha=0.5)\n",
    "\n",
    "output_notebook()\n",
    "# show the results\n",
    "show(p, notebook_handle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"https://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"b3e3866c-b4da-41b9-b2da-00fd2306a91f\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "  var JS_MIME_TYPE = 'application/javascript';\n",
       "  var HTML_MIME_TYPE = 'text/html';\n",
       "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
       "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
       "\n",
       "  /**\n",
       "   * Render data to the DOM node\n",
       "   */\n",
       "  function render(props, node) {\n",
       "    var script = document.createElement(\"script\");\n",
       "    node.appendChild(script);\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when an output is cleared or removed\n",
       "   */\n",
       "  function handleClearOutput(event, handle) {\n",
       "    var cell = handle.cell;\n",
       "\n",
       "    var id = cell.output_area._bokeh_element_id;\n",
       "    var server_id = cell.output_area._bokeh_server_id;\n",
       "    // Clean up Bokeh references\n",
       "    if (id !== undefined) {\n",
       "      Bokeh.index[id].model.document.clear();\n",
       "      delete Bokeh.index[id];\n",
       "    }\n",
       "\n",
       "    if (server_id !== undefined) {\n",
       "      // Clean up Bokeh references\n",
       "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
       "      cell.notebook.kernel.execute(cmd, {\n",
       "        iopub: {\n",
       "          output: function(msg) {\n",
       "            var element_id = msg.content.text.trim();\n",
       "            Bokeh.index[element_id].model.document.clear();\n",
       "            delete Bokeh.index[element_id];\n",
       "          }\n",
       "        }\n",
       "      });\n",
       "      // Destroy server and session\n",
       "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
       "      cell.notebook.kernel.execute(cmd);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when a new output is added\n",
       "   */\n",
       "  function handleAddOutput(event, handle) {\n",
       "    var output_area = handle.output_area;\n",
       "    var output = handle.output;\n",
       "\n",
       "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
       "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
       "      return\n",
       "    }\n",
       "\n",
       "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
       "\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
       "      toinsert[0].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
       "      // store reference to embed id on output_area\n",
       "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
       "    }\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
       "      var bk_div = document.createElement(\"div\");\n",
       "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "      var script_attrs = bk_div.children[0].attributes;\n",
       "      for (var i = 0; i < script_attrs.length; i++) {\n",
       "        toinsert[0].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
       "      }\n",
       "      // store reference to server id on output_area\n",
       "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function register_renderer(events, OutputArea) {\n",
       "\n",
       "    function append_mime(data, metadata, element) {\n",
       "      // create a DOM node to render to\n",
       "      var toinsert = this.create_output_subarea(\n",
       "        metadata,\n",
       "        CLASS_NAME,\n",
       "        EXEC_MIME_TYPE\n",
       "      );\n",
       "      this.keyboard_manager.register_events(toinsert);\n",
       "      // Render to node\n",
       "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "      render(props, toinsert[0]);\n",
       "      element.append(toinsert);\n",
       "      return toinsert\n",
       "    }\n",
       "\n",
       "    /* Handle when an output is cleared or removed */\n",
       "    events.on('clear_output.CodeCell', handleClearOutput);\n",
       "    events.on('delete.Cell', handleClearOutput);\n",
       "\n",
       "    /* Handle when a new output is added */\n",
       "    events.on('output_added.OutputArea', handleAddOutput);\n",
       "\n",
       "    /**\n",
       "     * Register the mime type and append_mime function with output_area\n",
       "     */\n",
       "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "      /* Is output safe? */\n",
       "      safe: true,\n",
       "      /* Index of renderer in `output_area.display_order` */\n",
       "      index: 0\n",
       "    });\n",
       "  }\n",
       "\n",
       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
       "  if (root.Jupyter !== undefined) {\n",
       "    var events = require('base/js/events');\n",
       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
       "\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  \n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    var el = document.getElementById(\"b3e3866c-b4da-41b9-b2da-00fd2306a91f\");\n",
       "    if (el != null) {\n",
       "      el.textContent = \"BokehJS is loading...\";\n",
       "    }\n",
       "    if (root.Bokeh !== undefined) {\n",
       "      if (el != null) {\n",
       "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
       "      }\n",
       "    } else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "    }\n",
       "    finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.info(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(js_urls, callback) {\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = js_urls.length;\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var s = document.createElement('script');\n",
       "      s.src = url;\n",
       "      s.async = false;\n",
       "      s.onreadystatechange = s.onload = function() {\n",
       "        root._bokeh_is_loading--;\n",
       "        if (root._bokeh_is_loading === 0) {\n",
       "          console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "          run_callbacks()\n",
       "        }\n",
       "      };\n",
       "      s.onerror = function() {\n",
       "        console.warn(\"failed to load library \" + url);\n",
       "      };\n",
       "      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "    }\n",
       "  };var element = document.getElementById(\"b3e3866c-b4da-41b9-b2da-00fd2306a91f\");\n",
       "  if (element == null) {\n",
       "    console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'b3e3866c-b4da-41b9-b2da-00fd2306a91f' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.14.min.js\"];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "    },\n",
       "    function(Bokeh) {\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.css\");\n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i].call(root, root.Bokeh);\n",
       "      }if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"b3e3866c-b4da-41b9-b2da-00fd2306a91f\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(js_urls, function() {\n",
       "      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
      "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(\"b3e3866c-b4da-41b9-b2da-00fd2306a91f\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n    }\n    finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.info(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(js_urls, callback) {\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = js_urls.length;\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var s = document.createElement('script');\n      s.src = url;\n      s.async = false;\n      s.onreadystatechange = s.onload = function() {\n        root._bokeh_is_loading--;\n        if (root._bokeh_is_loading === 0) {\n          console.log(\"Bokeh: all BokehJS libraries loaded\");\n          run_callbacks()\n        }\n      };\n      s.onerror = function() {\n        console.warn(\"failed to load library \" + url);\n      };\n      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.getElementsByTagName(\"head\")[0].appendChild(s);\n    }\n  };var element = document.getElementById(\"b3e3866c-b4da-41b9-b2da-00fd2306a91f\");\n  if (element == null) {\n    console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'b3e3866c-b4da-41b9-b2da-00fd2306a91f' but no matching script tag was found. \")\n    return false;\n  }\n\n  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.14.min.js\"];\n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    \n    function(Bokeh) {\n      \n    },\n    function(Bokeh) {\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.css\");\n    }\n  ];\n\n  function run_inline_js() {\n    \n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(\"b3e3866c-b4da-41b9-b2da-00fd2306a91f\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(js_urls, function() {\n      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"bk-root\">\n",
       "    <div class=\"bk-plotdiv\" id=\"ff24a9f8-d804-4901-b1e7-0f11ec89e6d9\"></div>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
       "  var docs_json = 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       "  var render_items = [{\"docid\":\"e1682de8-2748-4fa7-ad22-2731b3e8c437\",\"elementid\":\"ff24a9f8-d804-4901-b1e7-0f11ec89e6d9\",\"modelid\":\"a9a667f9-e4c0-4cdc-9d28-88368a4901cb\",\"notebook_comms_target\":\"8b096101-d59d-49ca-b0dd-06c39bb850d5\"}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
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       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        embed_document(root);\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "      attempts++;\n",
       "      if (attempts > 100) {\n",
       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\")\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
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     },
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       "id": "a9a667f9-e4c0-4cdc-9d28-88368a4901cb"
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    {
     "data": {
      "text/html": [
       "<p><code>&lt;Bokeh Notebook handle for <strong>In[13]</strong>&gt;</code></p>"
      ],
      "text/plain": [
       "<bokeh.io.notebook.CommsHandle at 0x1a2a579940>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "p1 = figure(plot_width=900, plot_height=400)\n",
    "#p2 = figure(plot_width=900, plot_height=400, title=\"Detail Number vs Energy Coefficients\")\n",
    "\n",
    "# add a circle renderer with a size, color, and alpha\n",
    "p1.circle(np.arange(0, len(df_whole)), df_whole[\"cD7\"], size=5, color=\"olive\", alpha=0.5)\n",
    "p1.circle(np.arange(0, len(df_whole)), df_whole[\"cD6\"], size=5, color=\"red\", alpha=0.5)\n",
    "p1.circle(np.arange(0, len(df_whole)), df_whole[\"cD5\"], size=5, color=\"navy\", alpha=0.5)\n",
    "\n",
    "# Plot clusters\n",
    "# plt.figure(3, figsize=(14, 2))\n",
    "# plt.scatter(waveform_processor.segmenter(abp_signal_whole, level)[1:], pca_kmeans, color='blue')\n",
    "\n",
    "p2.circle(np.arange(0, len(cluster_data)), cluster_data, size=5, color=\"blue\",alpha=0.5)\n",
    "\n",
    "output_notebook()\n",
    "# show the results\n",
    "show(column(p1,p2), notebook_handle=True)"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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