{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "nteract": {
     "transient": {
      "deleting": false
     }
    }
   },
   "source": [
    "# Make an Interactive Plot of NYC Noise with Bokeh\n",
    "Read in data from 1_calc_daily_noise.ipynb and plot using Bokeh."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "jupyter": {
     "outputs_hidden": false,
     "source_hidden": false
    },
    "nteract": {
     "transient": {
      "deleting": false
     }
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"https://bokeh.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"1001\">Loading BokehJS ...</span>\n",
       "    </div>"
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     "metadata": {},
     "output_type": "display_data"
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       "(function(root) {\n",
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       "\n",
       "  var force = true;\n",
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       "  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",
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       "\n",
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       "  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 != null && id in Bokeh.index) {\n",
       "      Bokeh.index[id].model.document.clear();\n",
       "      delete Bokeh.index[id];\n",
       "    }\n",
       "\n",
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       "      // 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 id = msg.content.text.trim();\n",
       "            if (id in Bokeh.index) {\n",
       "              Bokeh.index[id].model.document.clear();\n",
       "              delete Bokeh.index[id];\n",
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       "          }\n",
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       "      // Destroy server and session\n",
       "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
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       "\n",
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       "\n",
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       "      var bk_div = document.createElement(\"div\");\n",
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       "      // store reference to server id on output_area\n",
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       "  }\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",
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       "        EXEC_MIME_TYPE\n",
       "      );\n",
       "      this.keyboard_manager.register_events(toinsert);\n",
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       "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "      render(props, toinsert[toinsert.length - 1]);\n",
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       "    }\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",
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       "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
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       "\n",
       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
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       "\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(\"1001\");\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) {\n",
       "        if (callback != null)\n",
       "          callback();\n",
       "      });\n",
       "    } finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(css_urls, js_urls, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
       "    if (js_urls == null) js_urls = [];\n",
       "\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.debug(\"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.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
       "\n",
       "    function on_load() {\n",
       "      root._bokeh_is_loading--;\n",
       "      if (root._bokeh_is_loading === 0) {\n",
       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
       "        run_callbacks()\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function on_error() {\n",
       "      console.error(\"failed to load \" + url);\n",
       "    }\n",
       "\n",
       "    for (var i = 0; i < css_urls.length; i++) {\n",
       "      var url = css_urls[i];\n",
       "      const element = document.createElement(\"link\");\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.rel = \"stylesheet\";\n",
       "      element.type = \"text/css\";\n",
       "      element.href = url;\n",
       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
       "      document.body.appendChild(element);\n",
       "    }\n",
       "\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "  };var element = document.getElementById(\"1001\");\n",
       "  if (element == null) {\n",
       "    console.error(\"Bokeh: ERROR: autoload.js configured with elementid '1001' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  function inject_raw_css(css) {\n",
       "    const element = document.createElement(\"style\");\n",
       "    element.appendChild(document.createTextNode(css));\n",
       "    document.body.appendChild(element);\n",
       "  }\n",
       "\n",
       "  \n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.4.0.min.js\"];\n",
       "  var css_urls = [];\n",
       "  \n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    function(Bokeh) {\n",
       "    \n",
       "    \n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if (root.Bokeh !== undefined || force === true) {\n",
       "      \n",
       "    for (var i = 0; i < inline_js.length; i++) {\n",
       "      inline_js[i].call(root, root.Bokeh);\n",
       "    }\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(\"1001\")).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.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(css_urls, js_urls, function() {\n",
       "      console.debug(\"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(\"1001\");\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) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"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.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };var element = document.getElementById(\"1001\");\n  if (element == null) {\n    console.error(\"Bokeh: ERROR: autoload.js configured with elementid '1001' but no matching script tag was found. \")\n    return false;\n  }\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  \n  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.4.0.min.js\"];\n  var css_urls = [];\n  \n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    function(Bokeh) {\n    \n    \n    }\n  ];\n\n  function run_inline_js() {\n    \n    if (root.Bokeh !== undefined || force === true) {\n      \n    for (var i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\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(\"1001\")).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.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from datetime import datetime, timedelta\n",
    "import pandas as pd\n",
    "\n",
    "# Load modules for interactive plotting\n",
    "import bokeh\n",
    "from bokeh.models import Line, Span, ColumnDataSource, DatetimeTickFormatter, HoverTool, CustomJS\n",
    "from bokeh.plotting import figure, output_notebook, show, output_file\n",
    "from bokeh import events\n",
    "import time\n",
    "\n",
    "output_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "jupyter": {
     "outputs_hidden": false,
     "source_hidden": false
    },
    "nteract": {
     "transient": {
      "deleting": false
     }
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/russell/anaconda/lib/python3.5/site-packages/ipykernel/__main__.py:30: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>t_cent</th>\n",
       "      <th>disp_avg</th>\n",
       "      <th>daily_average</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-02-08 19:30:00</td>\n",
       "      <td>1.107801e-09</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-02-08 20:30:00</td>\n",
       "      <td>1.079529e-09</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-02-08 21:30:00</td>\n",
       "      <td>1.026666e-09</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-02-08 22:30:00</td>\n",
       "      <td>9.982165e-10</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-02-08 23:30:00</td>\n",
       "      <td>9.570202e-10</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               t_cent      disp_avg  daily_average\n",
       "0 2020-02-08 19:30:00  1.107801e-09            NaN\n",
       "1 2020-02-08 20:30:00  1.079529e-09            NaN\n",
       "2 2020-02-08 21:30:00  1.026666e-09            NaN\n",
       "3 2020-02-08 22:30:00  9.982165e-10            NaN\n",
       "4 2020-02-08 23:30:00  9.570202e-10            NaN"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Set x-axis limits for plotting\n",
    "# datetime(YEAR, MONTH, DAY)\n",
    "tmin = datetime(2020, 2, 9)\n",
    "tmax = datetime(2020, 5, 15)\n",
    "fname = 'LD.CPNY.2020-02-09.2020-05-15.5_15Hz.BHZ'\n",
    "datadir = './Data/'\n",
    "\n",
    "df = pd.read_csv(datadir+fname+'.csv',parse_dates=['t_cent'])\n",
    "\n",
    "# NYC stay at home 2020/3/22 8pm EST (UTC - 4)\n",
    "nyc_SAH = datetime(2020,3,22,20,0) + timedelta(0,4*60*60)\n",
    "\n",
    "# NYC First COVID-19 death 2020/3/14 EST (UTC - 4)\n",
    "nyc_1st = datetime(2020,3,14,0,0)\n",
    "\n",
    "# NYC subway closed 1am-5am 2020/5/6 EST (UTC - 4)\n",
    "nyc_subway = datetime(2020,5,6,0,0)\n",
    "\n",
    "# Convert timestamps to NYC local time\n",
    "df = df.set_index('t_cent').tz_localize('UTC').tz_convert('America/New_York')\n",
    "df = df.reset_index()\n",
    "\n",
    "df\n",
    "\n",
    "# Manually shift timezone to NYC local time since Bokeh doesn't understand timezones\n",
    "dfnyc = df.copy()\n",
    "dfnyc['t_cent'] = dfnyc.t_cent.dt.tz_localize(None)\n",
    "for ii, f in enumerate(df):\n",
    "    hr_utcoffset = pd.Timestamp.utcoffset(df.t_cent[ii]).total_seconds()/60/60\n",
    "    dfnyc['t_cent'][ii] = df['t_cent'][ii] + pd.Timedelta(hours=hr_utcoffset)\n",
    "df = dfnyc\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define Bokeh Figure and plot hourly and daily noise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "jupyter": {
     "outputs_hidden": false,
     "source_hidden": false
    },
    "nteract": {
     "transient": {
      "deleting": false
     }
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/russell/anaconda/lib/python3.5/site-packages/bokeh/plotting/helpers.py:689: UserWarning: WheelZoomTool are being repeated\n",
      "  warnings.warn(\"%s are being repeated\" % \",\".join(repeated_tools))\n"
     ]
    }
   ],
   "source": [
    "# Build interactive plots using Bokeh\n",
    "\n",
    "# Define figure attributes\n",
    "p = figure(x_axis_type='datetime',plot_width=800, plot_height=500, sizing_mode = 'scale_width',\n",
    "           x_range=(df.t_cent.min(),df.t_cent.max()), y_range=([df.disp_avg.min()*1e9*0.7, df.disp_avg.max()*1e9*1.05]),\n",
    "           x_axis_label='Date', y_axis_label='Average Ground Displacement (nm)', title='NYC Seismic Noise (5-15 Hz)',\n",
    "           tools=['save','box_zoom','xwheel_zoom','ywheel_zoom','reset','crosshair','pan'])\n",
    "\n",
    "# Plot lines for hourly and daily displacement\n",
    "# create a datetime string for the hover tool\n",
    "df['t_centstr'] = df.t_cent.dt.strftime(\"%Y-%m-%d %H:%M\")\n",
    "source = ColumnDataSource(data={'t_cent':df.t_cent, 'disp_avg':df.disp_avg*1e9, \n",
    "                                'daily_average':df.daily_average*1e9, 't_centstr':df.t_centstr})\n",
    "\n",
    "# Plot hourly noise\n",
    "l1 = p.line('t_cent', 'disp_avg', source=source, line_color=\"lightsteelblue\",\n",
    "             line_width=2, legend_label=\"Hourly Noise\")\n",
    "p.add_tools(HoverTool(renderers=[l1], tooltips=[(\"Date\", \"@t_centstr\"),(\"Hourly Noise Level\",\"@disp_avg\")]))\n",
    "\n",
    "# Plot daily noise\n",
    "l2 = p.line('t_cent', 'daily_average', source=source, line_color=\"steelblue\",\n",
    "             line_width=4, legend_label=\"Daily Noise\")\n",
    "p.add_tools(HoverTool(renderers=[l2], tooltips=[(\"Date\", \"@t_centstr\"),(\"Daily Noise Level\",\"@daily_average\")]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add vertical lines marking important events"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "jupyter": {
     "outputs_hidden": false,
     "source_hidden": false
    },
    "nteract": {
     "transient": {
      "deleting": false
     }
    }
   },
   "outputs": [
    {
     "data": {
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       "(function() {\n",
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       "    for (var i = 0; i < rows.length; i++) {\n",
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       "      el.style.display = expanded ? \"none\" : \"table-row\";\n",
       "    }\n",
       "    ellipsis.innerHTML = expanded ? \"&hellip;)\" : \"&lsaquo;&lsaquo;&lsaquo;\";\n",
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       "  });\n",
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       "</script>\n"
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      "text/plain": [
       "GlyphRenderer(id='1154', ...)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "# Plot vertical lines marking stay at home and first nyc death\n",
    "# First need to convert datetime to milliseconds for some reason...\n",
    "nyc_SAH_ms = time.mktime(nyc_SAH.timetuple())*1000\n",
    "nyc_1st_ms = time.mktime(nyc_1st.timetuple())*1000\n",
    "nyc_subway_ms = time.mktime(nyc_subway.timetuple())*1000\n",
    "\n",
    "# Add vertical line for first NYC fatality\n",
    "nyc_1st_start = Span(location=nyc_1st_ms, dimension='height', line_color='firebrick',\n",
    "                     line_dash='solid', line_width=3)\n",
    "p.add_layout(nyc_1st_start)\n",
    "# Add a phantom line for legend purposes since Span does not have legend property\n",
    "p.line([], [], legend_label=\"First NYC COVID-19 fatality\", line_color='firebrick', line_dash='solid', line_width=3)\n",
    "\n",
    "# Add vertical line for stay at home order\n",
    "nyc_SAH_start = Span(location=nyc_SAH_ms, dimension='height', line_color='firebrick',\n",
    "                     line_dash='dashed', line_width=3)\n",
    "p.add_layout(nyc_SAH_start)\n",
    "p.line([], [], legend_label=\"NYC stay at home order\", line_color='firebrick', line_dash='dashed', line_width=3)\n",
    "\n",
    "# Add vertical line when NYC subway closes\n",
    "nyc_subway_start = Span(location=nyc_subway_ms, dimension='height', line_color='firebrick',\n",
    "                        line_dash='dotted', line_width=3)\n",
    "p.add_layout(nyc_subway_start)\n",
    "p.line([], [], legend_label=\"Subway closes overnight\", line_color='firebrick', line_dash='dotted', line_width=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add Legend and Plot!\n",
    "\n",
    "Tip: Double click to toggle legend on/of"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "jupyter": {
     "outputs_hidden": false,
     "source_hidden": false
    },
    "nteract": {
     "transient": {
      "deleting": false
     }
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "BokehDeprecationWarning: 'from_py_func' is deprecated and will be removed in an eventual 2.0 release. Use CustomJS directly instead.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"d74ef346-cd85-4355-8b94-e6568f4f57ac\" data-root-id=\"1002\"></div>\n"
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     },
     "metadata": {},
     "output_type": "display_data"
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     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
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       "  var docs_json = {\"a303220b-6594-4066-853a-c2b305561c0d\":{\"roots\":{\"references\":[{\"attributes\":{},\"id\":\"1023\",\"type\":\"SaveTool\"},{\"attributes\":{\"line_alpha\":0.1,\"line_color\":\"#1f77b4\",\"line_width\":2,\"x\":{\"field\":\"t_cent\"},\"y\":{\"field\":\"disp_avg\"}},\"id\":\"1041\",\"type\":\"Line\"},{\"attributes\":{\"line_color\":\"lightsteelblue\",\"line_width\":2,\"x\":{\"field\":\"t_cent\"},\"y\":{\"field\":\"disp_avg\"}},\"id\":\"1040\",\"type\":\"Line\"},{\"attributes\":{\"base\":60,\"mantissas\":[1,2,5,10,15,20,30],\"max_interval\":1800000.0,\"min_interval\":1000.0,\"num_minor_ticks\":0},\"id\":\"1051\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"text\":\"NYC Seismic Noise (5-15 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\",\"dtype\":\"float64\",\"shape\":[2304]},\"disp_avg\":{\"__ndarray__\":\"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19:30\"]},\"selected\":{\"id\":\"1090\",\"type\":\"Selection\"},\"selection_policy\":{\"id\":\"1089\",\"type\":\"UnionRenderers\"}},\"id\":\"1038\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"1045\",\"type\":\"DatetimeTickFormatter\"},{\"attributes\":{\"label\":{\"value\":\"Hourly Noise\"},\"renderers\":[{\"id\":\"1042\",\"type\":\"GlyphRenderer\"}]},\"id\":\"1063\",\"type\":\"LegendItem\"},{\"attributes\":{\"label\":{\"value\":\"NYC first fatality\"},\"renderers\":[{\"id\":\"1098\",\"type\":\"GlyphRenderer\"}]},\"id\":\"1120\",\"type\":\"LegendItem\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"1049\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"label\":{\"value\":\"Daily Noise\"},\"renderers\":[{\"id\":\"1069\",\"type\":\"GlyphRenderer\"}]},\"id\":\"1091\",\"type\":\"LegendItem\"},{\"attributes\":{},\"id\":\"1019\",\"type\":\"BasicTicker\"},{\"attributes\":{\"source\":{\"id\":\"1151\",\"type\":\"ColumnDataSource\"}},\"id\":\"1155\",\"type\":\"CDSView\"},{\"attributes\":{\"below\":[{\"id\":\"1013\",\"type\":\"DatetimeAxis\"}],\"center\":[{\"id\":\"1017\",\"type\":\"Grid\"},{\"id\":\"1022\",\"type\":\"Grid\"},{\"id\":\"1062\",\"type\":\"Legend\"},{\"id\":\"1094\",\"type\":\"Span\"},{\"id\":\"1121\",\"type\":\"Span\"},{\"id\":\"1150\",\"type\":\"Span\"}],\"js_event_callbacks\":{\"doubletap\":[{\"id\":\"1183\",\"type\":\"CustomJS\"}]},\"left\":[{\"id\":\"1018\",\"type\":\"LinearAxis\"}],\"plot_height\":500,\"plot_width\":800,\"renderers\":[{\"id\":\"1042\",\"type\":\"GlyphRenderer\"},{\"id\":\"1069\",\"type\":\"GlyphRenderer\"},{\"id\":\"1098\",\"type\":\"GlyphRenderer\"},{\"id\":\"1125\",\"type\":\"GlyphRenderer\"},{\"id\":\"1154\",\"type\":\"GlyphRenderer\"}],\"sizing_mode\":\"scale_width\",\"title\":{\"id\":\"1003\",\"type\":\"Title\"},\"toolbar\":{\"id\":\"1030\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"1005\",\"type\":\"Range1d\"},\"x_scale\":{\"id\":\"1009\",\"type\":\"LinearScale\"},\"y_range\":{\"id\":\"1007\",\"type\":\"Range1d\"},\"y_scale\":{\"id\":\"1011\",\"type\":\"LinearScale\"}},\"id\":\"1002\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"data_source\":{\"id\":\"1122\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"1123\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1124\",\"type\":\"Line\"},\"selection_glyph\":null,\"view\":{\"id\":\"1126\",\"type\":\"CDSView\"}},\"id\":\"1125\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"1029\",\"type\":\"PanTool\"},{\"attributes\":{},\"id\":\"1011\",\"type\":\"LinearScale\"},{\"attributes\":{\"label\":{\"value\":\"NYC stay at home order\"},\"renderers\":[{\"id\":\"1125\",\"type\":\"GlyphRenderer\"}]},\"id\":\"1149\",\"type\":\"LegendItem\"},{\"attributes\":{},\"id\":\"1209\",\"type\":\"Selection\"},{\"attributes\":{\"data_source\":{\"id\":\"1095\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"1096\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1097\",\"type\":\"Line\"},\"selection_glyph\":null,\"view\":{\"id\":\"1099\",\"type\":\"CDSView\"}},\"id\":\"1098\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"source\":{\"id\":\"1095\",\"type\":\"ColumnDataSource\"}},\"id\":\"1099\",\"type\":\"CDSView\"},{\"attributes\":{},\"id\":\"1009\",\"type\":\"LinearScale\"},{\"attributes\":{\"callback\":null,\"data\":{\"x\":[],\"y\":[]},\"selected\":{\"id\":\"1209\",\"type\":\"Selection\"},\"selection_policy\":{\"id\":\"1208\",\"type\":\"UnionRenderers\"}},\"id\":\"1151\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"days\":[1,15]},\"id\":\"1056\",\"type\":\"DaysTicker\"},{\"attributes\":{},\"id\":\"1208\",\"type\":\"UnionRenderers\"}],\"root_ids\":[\"1002\"]},\"title\":\"Bokeh Application\",\"version\":\"1.4.0\"}};\n",
       "  var render_items = [{\"docid\":\"a303220b-6594-4066-853a-c2b305561c0d\",\"roots\":{\"1002\":\"d74ef346-cd85-4355-8b94-e6568f4f57ac\"}}];\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",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "1002"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "p.legend.location = \"top_right\"\n",
    "# p.legend.click_policy = \"hide\"\n",
    "\n",
    "# Set up double click toggle legend\n",
    "def show_hide_legend(legend=p.legend[0]):\n",
    "    legend.visible = not legend.visible\n",
    "p.js_on_event(events.DoubleTap, CustomJS.from_py_func(show_hide_legend))\n",
    "\n",
    "# Save local file\n",
    "output_file(fname+'.html')\n",
    "# Show plot in browser\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "display_name": "Python [default]",
   "language": "python",
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    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
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