nsw-2016-storm-impact/notebooks/01_exploration.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data exploration\n",
    "This notebook provides an example how the data has been loaded and accessed for further analysis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-11-19T00:22:35.172482Z",
     "start_time": "2018-11-19T00:22:35.000206Z"
    }
   },
   "outputs": [],
   "source": [
    "# Enable autoreloading of our modules. \n",
    "# Most of the code will be located in the /src/ folder, \n",
    "# and then called from the notebook.\n",
    "\n",
    "%reload_ext autoreload\n",
    "%autoreload"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-11-19T00:22:50.594936Z",
     "start_time": "2018-11-19T00:22:35.173486Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "from IPython.core.debugger import set_trace\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "\n",
    "import plotly\n",
    "import plotly.graph_objs as go\n",
    "import plotly.plotly as py\n",
    "\n",
    "from ipywidgets import widgets\n",
    "from IPython.display import display, clear_output, Image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-11-19T00:51:58.002082Z",
     "start_time": "2018-11-19T00:51:45.127794Z"
    },
    "pixiedust": {
     "displayParams": {}
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\z5189959\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\numpy\\lib\\arraysetops.py:472: FutureWarning:\n",
      "\n",
      "elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
      "\n"
     ]
    }
   ],
   "source": [
    "data_folder = '../data/interim'\n",
    "df_waves = pd.read_csv(os.path.join(data_folder, 'waves.csv'), index_col=[0,1])\n",
    "df_tides = pd.read_csv(os.path.join(data_folder, 'tides.csv'), index_col=[0,1])\n",
    "df_profiles = pd.read_csv(os.path.join(data_folder, 'profiles.csv'), index_col=[0,1,2])\n",
    "df_sites = pd.read_csv(os.path.join(data_folder, 'sites.csv'),index_col=[0])\n",
    "df_profile_features = pd.read_csv(os.path.join(data_folder, 'profile_features.csv'),index_col=[0])\n",
    "df_impacts_compared = pd.read_csv(os.path.join(data_folder,'impacts_observed_vs_forecasted_mean_slope_sto06.csv'),index_col=[0])\n",
    "df_twl = pd.read_csv(os.path.join(data_folder,'twl_mean_slope_sto06.csv'),index_col=[0,1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-11-19T01:46:34.068613Z",
     "start_time": "2018-11-19T01:46:34.021932Z"
    }
   },
   "outputs": [
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   ],
   "source": [
    "df_twl.query(\"site_id=='NARRA0018'\").Hs0.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-11-19T04:00:27.734848Z",
     "start_time": "2018-11-19T04:00:26.097751Z"
    },
    "code_folding": [
     277
    ],
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3790264e7f4a4fb6b5838d18c50957dc",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>VBox</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
       "  likely means that the widgets JavaScript library is either not installed or\n",
       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
      ],
      "text/plain": [
       "VBox(children=(VBox(children=(HTML(value='<b>Filter by observed and predicted impacts:</b>'), HBox(children=(SelectMultiple(description='Forecasted Impacts', index=(0, 1, 2), options=('overwash', 'collision', 'swash'), value=('overwash', 'collision', 'swash')), SelectMultiple(description='Observed Impacts', index=(0, 1), options=('swash', 'collision'), value=('swash', 'collision')))))), VBox(children=(HTML(value='<b>Filter by site_id:</b>'), HBox(children=(Dropdown(description='site_id:   ', index=943, options=('AVOCAn0001', 'AVOCAn0002', 'AVOCAn0003', 'AVOCAn0004', 'AVOCAn0005', 'AVOCAn0006', 'AVOCAn0007', 'AVOCAn0008', 'AVOCAn0009', 'AVOCAs0001', 'AVOCAs0002', 'AVOCAs0003', 'AVOCAs0004', 'AVOCAs0005', 'AVOCAs0006', 'AVOCAs0007', 'AVOCAs0008', 'BILG0001', 'BILG0002', 'BILG0003', 'BILG0004', 'BILG0005', 'BLUEYS0001', 'BLUEYS0002', 'BLUEYS0003', 'BLUEYS0004', 'BLUEYS0005', 'BLUEYS0006', 'BOAT0001', 'BOAT0002', 'BOAT0003', 'BOAT0004', 'BOAT0005', 'BOOM0001', 'BOOM0002', 'BOOM0003', 'BOOM0004', 'BOOM0005', 'BOOM0006', 'BOOM0007', 'BOOM0008', 'BOOM0009', 'BOOM0010', 'BOOM0011', 'BOOM0012', 'BOOM0013', 'BOOM0014', 'CATHIE0001', 'CATHIE0002', 'CATHIE0003', 'CATHIE0004', 'CATHIE0005', 'CATHIE0006', 'CATHIE0007', 'CATHIE0008', 'CATHIE0009', 'CATHIE0010', 'CATHIE0011', 'CATHIE0012', 'CATHIE0013', 'CATHIE0014', 'CATHIE0015', 'CATHIE0016', 'CATHIE0017', 'CATHIE0018', 'CATHIE0019', 'CATHIE0020', 'CATHIE0021', 'CATHIE0022', 'CATHIE0023', 'CATHIE0024', 'CATHIE0025', 'CATHIE0026', 'CATHIE0027', 'CATHIE0028', 'CATHIE0029', 'CRESn0001', 'CRESn0002', 'CRESn0003', 'CRESn0004', 'CRESn0005', 'CRESn0006', 'CRESn0007', 'CRESn0008', 'CRESn0009', 'CRESn0010', 'CRESn0011', 'CRESn0012', 'CRESn0013', 'CRESn0014', 'CRESn0015', 'CRESn0016', 'CRESn0017', 'CRESn0018', 'CRESn0019', 'CRESn0020', 'CRESn0021', 'CRESn0022', 'CRESn0023', 'CRESn0024', 'CRESn0025', 'CRESn0026', 'CRESn0027', 'CRESn0028', 'CRESn0029', 'CRESn0030', 'CRESn0031', 'CRESn0032', 'CRESn0033', 'CRESn0034', 'CRESn0035', 'CRESn0036', 'CRESn0037', 'CRESn0038', 'CRESn0039', 'CRESn0040', 'CRESn0041', 'CRESn0042', 'CRESn0043', 'CRESn0044', 'CRESn0045', 'CRESn0046', 'CRESn0047', 'CRESn0048', 'CRESn0049', 'CRESn0050', 'CRESn0051', 'CRESn0052', 'CRESn0053', 'CRESn0054', 'CRESn0055', 'CRESn0056', 'CRESn0057', 'CRESn0058', 'CRESn0059', 'CRESn0060', 'CRESn0061', 'CRESn0062', 'CRESn0063', 'CRESn0064', 'CRESn0065', 'CRESn0066', 'CRESn0067', 'CRESn0068', 'CRESn0069', 'CRESn0070', 'CRESn0071', 'CRESn0072', 'CRESn0073', 'CRESn0074', 'CRESn0075', 'CRESn0076', 'CRESn0077', 'CRESn0078', 'CRESn0079', 'CRESn0080', 'CRESn0081', 'CRESn0082', 'CRESn0083', 'CRESn0084', 'CRESn0085', 'CRESn0086', 'CRESn0087', 'CRESn0088', 'CRESn0089', 'CRESn0090', 'CRESn0091', 'CRESn0092', 'CRESn0093', 'CRESn0094', 'CRESn0095', 'CRESn0096', 'CRESn0097', 'CRESn0098', 'CRESn0099', 'CRESn0100', 'CRESn0101', 'CRESn0102', 'CRESn0103', 'CRESn0104', 'CRESn0105', 'CRESn0106', 'CRESn0107', 'CRESn0108', 'CRESn0109', 'CRESn0110', 'CRESn0111', 'CRESn0112', 'CRESn0113', 'CRESn0114', 'CRESn0115', 'CRESn0116', 'CRESn0117', 'CRESn0118', 'CRESn0119', 'CRESn0120', 'CRESn0121', 'CRESn0122', 'CRESn0123', 'CRESn0124', 'CRESn0125', 'CRESs0001', 'CRESs0002', 'CRESs0003', 'CRESs0004', 'CRESs0005', 'CRESs0006', 'CRESs0007', 'CRESs0008', 'CRESs0009', 'CRESs0010', 'CRESs0011', 'CRESs0012', 'CRESs0013', 'CRESs0014', 'DEEWHYn0001', 'DEEWHYn0002', 'DEEWHYn0003', 'DEEWHYn0004', 'DEEWHYn0005', 'DEEWHYn0006', 'DEEWHYn0007', 'DEEWHYn0008', 'DEEWHYn0009', 'DEEWHYn0010', 'DEEWHYn0011', 'DEEWHYn0012', 'DEEWHYs0001', 'DEEWHYs0002', 'DEEWHYs0003', 'DEEWHYs0004', 'DEEWHYs0005', 'DEEWHYs0006', 'DEEWHYs0007', 'DEEWHYs0008', 'DIAMONDn0001', 'DIAMONDn0002', 'DIAMONDn0003', 'DIAMONDn0004', 'DIAMONDn0005', 'DIAMONDn0006', 'DIAMONDn0007', 'DIAMONDn0008', 'DIAMONDn0009', 'DIAMONDn0010', 'DIAMONDn0011', 'DIAMONDn0012', 'DIAMONDn0013', 'DIAMONDn0014', 'DIAMONDn0015', 'DIAMONDn0016', 'DIAMONDn0017', 'DIAMONDn0018', 'DIAMONDn0019', 'DIAMONDn0020', 'DIAMONDn0021', 'DIAMONDn0022', 'DIAMONDn0023', 'DIAMONDn0024', 'DIAMONDn0025', 'DIAMONDn0026', 'DIAMONDn0027', 'DIAMONDn0028',
       "    'data': [{'name': 'Pre Storm Profile',\n",
       "              'type': 'scatter',\n",
       "              'uid': 'a7ef1527-c36f-4f59-9d62-64928b7b924f',\n",
       "              'x': [0],\n",
       "              'y': [0]},\n",
       "             {'name': 'Post Storm Profile',\n",
       "              'type': 'scatter',\n",
       "              'uid': '8f93d4ab-7ef5-4798-b76d-ea742faf88a5',\n",
       "              'x': [0],\n",
       "              'y': [0]},\n",
       "             {'marker': {'color': 'rgb(17, 157, 255)', 'size': 20},\n",
       "              'mode': 'markers',\n",
       "              'name': 'Pre-storm dune crest',\n",
       "              'type': 'scatter',\n",
       "              'uid': 'fd8574f3-f280-4ef6-9792-d1c14df1eb55',\n",
       "              'x': [0],\n",
       "              'y': [0]},\n",
       "             {'marker': {'color': 'rgb(231, 99, 250)', 'size': 20},\n",
       "              'mode': 'markers',\n",
       "              'name': 'Pre-storm dune toe',\n",
       "              'type': 'scatter',\n",
       "              'uid': '4e6d2022-7ff2-42e6-9334-d76411906808',\n",
       "              'x': [0],\n",
       "              'y': [0]}],\n",
       "    'layout': {'height': 300,\n",
       "               'legend': {'x': 0.5, 'y': 1},\n",
       "               'margin': {'b': 50, 'l': 20, 'r': 20, 't': 50},\n",
       "               'title': 'Bed Profiles',\n",
       "               'xaxis': {'autorange': True,\n",
       "                         'range': [0, 200],\n",
       "                         'showgrid': True,\n",
       "                         'showline': True,\n",
       "                         'title': 'x (m)',\n",
       "                         'zeroline': True},\n",
       "               'yaxis': {'autorange': False,\n",
       "                         'range': [-1, 20],\n",
       "                         'showgrid': True,\n",
       "                         'showline': True,\n",
       "                         'title': 'z (m)',\n",
       "                         'zeroline': True}}\n",
       "}), FigureWidget({\n",
       "    'data': [{'lat': array([-33.46381539, -33.46301835, -33.46221051, ..., -33.4279646 ,\n",
       "                            -33.42732743, -33.42671036]),\n",
       "              'lon': array([151.43639576, 151.43690633, 151.43738179, ..., 151.4501613 ,\n",
       "                            151.45092222, 151.45170635]),\n",
       "              'marker': {'size': 10},\n",
       "              'mode': 'markers',\n",
       "              'text': array(['AVOCAn0001', 'AVOCAn0002', 'AVOCAn0003', ..., 'WAMBE0025', 'WAMBE0026',\n",
       "                             'WAMBE0027'], dtype='<U12'),\n",
       "              'type': 'scattermapbox',\n",
       "              'uid': 'e77778d2-afdf-479f-9ecb-642bad6011db'},\n",
       "             {'lat': [0],\n",
       "              'lon': [0],\n",
       "              'marker': {'color': 'rgb(255, 0, 0)', 'opacity': 0.5, 'size': 20},\n",
       "              'mode': 'markers',\n",
       "              'text': array(['AVOCAn0001', 'AVOCAn0002', 'AVOCAn0003', ..., 'WAMBE0025', 'WAMBE0026',\n",
       "                             'WAMBE0027'], dtype='<U12'),\n",
       "              'type': 'scattermapbox',\n",
       "              'uid': 'e9d1a48c-46d8-4783-b50c-81ff73913f8a'}],\n",
       "    'layout': {'autosize': True,\n",
       "               'height': 300,\n",
       "               'hovermode': 'closest',\n",
       "               'mapbox': {'accesstoken': ('pk.eyJ1IjoiY2hyaXNsZWFtYW4iLCJ' ... 'Hp5bCJ9.U2dwFg2c7RFjUNSayERUiw'),\n",
       "                          'bearing': 0,\n",
       "                          'center': {'lat': -33.7, 'lon': 151.3},\n",
       "                          'pitch': 0,\n",
       "                          'style': 'satellite-streets',\n",
       "                          'zoom': 12},\n",
       "               'margin': {'b': 50, 'l': 20, 'r': 20, 't': 50},\n",
       "               'showlegend': False}\n",
       "}))), FigureWidget({\n",
       "    'data': [{'name': 'Hs0', 'type': 'scatter', 'uid': 'f4c191f6-fd4f-41f5-b779-95260f23f281', 'x': [0, 1], 'y': [0, 1]},\n",
       "             {'name': 'Tp',\n",
       "              'type': 'scatter',\n",
       "              'uid': '6f12399d-6b75-40f7-b713-893f7c353f38',\n",
       "              'x': [0, 2],\n",
       "              'y': [0, 2],\n",
       "              'yaxis': 'y2'},\n",
       "             {'name': 'beta',\n",
       "              'type': 'scatter',\n",
       "              'uid': 'd8212fc8-5399-4c1f-8623-ba5ade277599',\n",
       "              'x': [0, 3],\n",
       "              'y': [0, 3],\n",
       "              'yaxis': 'y3'}],\n",
       "    'layout': {'height': 200,\n",
       "               'margin': {'b': 50, 'l': 50, 'r': 50, 't': 50},\n",
       "               'title': 'Hydro/Morpho Parameters',\n",
       "               'xaxis': {'domain': [0.0, 0.9], 'title': 'time', 'zeroline': False},\n",
       "               'yaxis': {'title': 'Hs0 (m)'},\n",
       "               'yaxis2': {'overlaying': 'y', 'side': 'right', 'title': 'Tp (s)'},\n",
       "               'yaxis3': {'overlaying': 'y', 'position': 0.97, 'side': 'right', 'title': 'beta (-)'}}\n",
       "}), FigureWidget({\n",
       "    'data': [{'line': {'color': 'rgb(91,220,229)', 'width': 2},\n",
       "              'name': 'R High',\n",
       "              'type': 'scatter',\n",
       "              'uid': '0aa45aab-f418-4273-b898-080a738dd57a',\n",
       "              'x': [0, 1],\n",
       "              'y': [0, 1]},\n",
       "             {'line': {'color': 'rgb(13,174,186)', 'width': 2},\n",
       "              'name': 'R Low',\n",
       "              'type': 'scatter',\n",
       "              'uid': 'd874630e-6006-4d4e-a962-a95e817855fb',\n",
       "              'x': [0, 2],\n",
       "              'y': [0, 2]},\n",
       "             {'line': {'color': 'rgb(214, 117, 14)', 'dash': 'dot', 'width': 2},\n",
       "              'name': 'Dune Crest',\n",
       "              'type': 'scatter',\n",
       "              'uid': '0042b440-e49a-4d54-8ac2-fac51d6b67e1',\n",
       "              'x': [0, 3],\n",
       "              'y': [0, 3]},\n",
       "             {'line': {'color': 'rgb(142, 77, 8)', 'dash': 'dash', 'width': 2},\n",
       "              'name': 'Dune Toe',\n",
       "              'type': 'scatter',\n",
       "              'uid': '996ee70f-9f12-4670-b771-d1c01ee1cdff',\n",
       "              'x': [0, 3],\n",
       "              'y': [0, 3]},\n",
       "             {'line': {'color': 'rgb(8,51,137)', 'dash': 'dot', 'width': 2},\n",
       "              'name': 'Tide+Surge WL',\n",
       "              'type': 'scatter',\n",
       "              'uid': '0331b331-b34a-4bd2-befe-3ef7d9c71b65',\n",
       "              'x': [0, 4],\n",
       "              'y': [0, 4]}],\n",
       "    'layout': {'height': 200,\n",
       "               'margin': {'b': 50, 'l': 50, 'r': 50, 't': 50},\n",
       "               'title': 'Water Level & Dune Toe/Crest',\n",
       "               'xaxis': {'domain': [0.0, 0.95], 'title': 'time', 'zeroline': False},\n",
       "               'yaxis': {'title': 'Water Level (m)'}}\n",
       "})))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create widgets for filtering by observed and forecasted impacts\n",
    "\n",
    "filter_title = widgets.HTML(\n",
    "    value=\"<b>Filter by observed and predicted impacts:</b>\",\n",
    ")\n",
    "\n",
    "observed_impact_select = widgets.SelectMultiple(\n",
    "    options=df_impacts_compared.storm_regime_observed.dropna().unique(),\n",
    "    value=df_impacts_compared.storm_regime_observed.dropna().unique().tolist(),\n",
    "    description='Observed Impacts',\n",
    "    disabled=False\n",
    ")\n",
    "\n",
    "forecasted_impact_select = widgets.SelectMultiple(\n",
    "    options=df_impacts_compared.storm_regime_forecasted.dropna().unique(),\n",
    "    value=df_impacts_compared.storm_regime_forecasted.dropna().unique().tolist(),\n",
    "    description='Forecasted Impacts',\n",
    "    disabled=False\n",
    ")\n",
    "\n",
    "filter_container = widgets.VBox(children=[filter_title,widgets.HBox(children=[forecasted_impact_select,observed_impact_select])])\n",
    "\n",
    "\n",
    "# Create widgets for selecting site_id\n",
    "\n",
    "site_id_title = widgets.HTML(\n",
    "    value=\"<b>Filter by site_id:</b>\",\n",
    ")\n",
    "\n",
    "site_id_select = widgets.Dropdown(\n",
    "    description='site_id:   ',\n",
    "    value='NARRA0001',\n",
    "    options=df_profiles.index.get_level_values('site_id').unique().sort_values().tolist()\n",
    ")\n",
    "site_id_container = widgets.VBox(children=[site_id_title,widgets.HBox(children=[site_id_select])])\n",
    "\n",
    "\n",
    "\n",
    "# Add panel for pre/post storm profiles\n",
    "trace1 = go.Scatter(\n",
    "    x = [0],\n",
    "    y = [0],\n",
    "    name='Pre Storm Profile'\n",
    ")\n",
    "trace2 = go.Scatter(\n",
    "    x = [0],\n",
    "    y = [0],\n",
    "    name='Post Storm Profile'\n",
    ")\n",
    "trace3 = go.Scatter(\n",
    "    x = [0],\n",
    "    y = [0],\n",
    "    name='Pre-storm dune crest',\n",
    "    mode = 'markers',\n",
    "    marker = dict(\n",
    "          color = 'rgb(17, 157, 255)',\n",
    "          size = 20,\n",
    "        ),\n",
    ")\n",
    "trace4 = go.Scatter(\n",
    "    x = [0],\n",
    "    y = [0],\n",
    "    name='Pre-storm dune toe',\n",
    "    mode = 'markers',\n",
    "        marker = dict(\n",
    "          color = 'rgb(231, 99, 250)',\n",
    "          size = 20,\n",
    "         ),\n",
    ")\n",
    "\n",
    "layout = go.Layout(\n",
    "    title = 'Bed Profiles',\n",
    "    height=300,\n",
    "    legend=dict(x=0.5, y=1),\n",
    "    margin=dict(t=50,b=50,l=20,r=20),\n",
    "    xaxis=dict(\n",
    "        title = 'x (m)',\n",
    "        autorange=True,\n",
    "        showgrid=True,\n",
    "        zeroline=True,\n",
    "        showline=True,\n",
    "        range=[0, 200]\n",
    "    ),\n",
    "    yaxis=dict(\n",
    "        title = 'z (m)',\n",
    "        autorange=False,\n",
    "        showgrid=True,\n",
    "        zeroline=True,\n",
    "        showline=True,\n",
    "        range=[-1, 20]\n",
    "    )\n",
    ")\n",
    "\n",
    "g1 = go.FigureWidget(data=[trace1, trace2, trace3, trace4],\n",
    "                    layout=layout)\n",
    "\n",
    "\n",
    "# Add panel for google maps\n",
    "mapbox_access_token = 'pk.eyJ1IjoiY2hyaXNsZWFtYW4iLCJhIjoiY2pvNTY1MzZpMDc2OTN2bmw5MGsycHp5bCJ9.U2dwFg2c7RFjUNSayERUiw'\n",
    "\n",
    "data = [\n",
    "    go.Scattermapbox(\n",
    "        lat=df_sites['lat'],\n",
    "        lon=df_sites['lon'],\n",
    "        mode='markers',\n",
    "        marker=dict(\n",
    "            size=10\n",
    "        ),\n",
    "        text=df_sites.index.get_level_values('site_id'),\n",
    "    ),\n",
    "    go.Scattermapbox(\n",
    "        lat=[0],\n",
    "        lon=[0],\n",
    "        mode='markers',\n",
    "        marker=dict(\n",
    "            size=20,\n",
    "            color='rgb(255, 0, 0)',\n",
    "            opacity = 0.5,\n",
    "        ),\n",
    "        text=df_sites.index.get_level_values('site_id'),\n",
    "    ),\n",
    "]\n",
    "\n",
    "layout = go.Layout(\n",
    "    autosize=True,\n",
    "    height=300,\n",
    "    hovermode='closest',\n",
    "    showlegend=False,\n",
    "    margin=dict(t=50,b=50,l=20,r=20),\n",
    "    mapbox=dict(\n",
    "        accesstoken=mapbox_access_token,\n",
    "        bearing=0,\n",
    "        center=dict(\n",
    "            lat=-33.7,\n",
    "            lon=151.3\n",
    "        ),\n",
    "        pitch=0,\n",
    "        zoom=12,\n",
    "        style='satellite-streets'\n",
    "    ),\n",
    ")\n",
    "\n",
    "fig = dict(data=data, layout=layout)\n",
    "g2 = go.FigureWidget(data=data,layout=layout)\n",
    "\n",
    "\n",
    "# Add panel for time series\n",
    "\n",
    "trace_Hs0 = go.Scatter(\n",
    "    x = [0,1],\n",
    "    y = [0,1],\n",
    "    name='Hs0'\n",
    ")\n",
    "trace_Tp = go.Scatter(\n",
    "    x = [0,2],\n",
    "    y = [0,2],\n",
    "    name='Tp',\n",
    "    yaxis='y2'\n",
    ")\n",
    "trace_beta = go.Scatter(\n",
    "    x = [0,3],\n",
    "    y = [0,3],\n",
    "    name='beta',\n",
    "    yaxis='y3'\n",
    ")\n",
    "data=[trace_Hs0, trace_Tp, trace_beta]\n",
    "\n",
    "layout = go.Layout(\n",
    "    title = 'Hydro/Morpho Parameters',\n",
    "    height=200,\n",
    "    margin=dict(t=50,b=50,l=50,r=50),\n",
    "    xaxis=dict(\n",
    "        title='time',\n",
    "        domain=[0.0, 0.9],\n",
    "        zeroline=False,\n",
    "    ),\n",
    "    yaxis=dict(\n",
    "        title = 'Hs0 (m)',\n",
    "    ),\n",
    "    yaxis2=dict(\n",
    "        title='Tp (s)',\n",
    "        overlaying='y',\n",
    "        side='right'\n",
    "    ),\n",
    "    yaxis3=dict(\n",
    "        title='beta (-)',\n",
    "        overlaying='y',\n",
    "        side='right',\n",
    "        position=0.97\n",
    "    )\n",
    ")\n",
    "\n",
    "g3 = go.FigureWidget(data=data, layout=layout)\n",
    "\n",
    "\n",
    "# Add panel for water level\n",
    "\n",
    "trace_R_high = go.Scatter(\n",
    "    x = [0,1],\n",
    "    y = [0,1],\n",
    "    name='R High',\n",
    "    line = dict(\n",
    "        color = ('rgb(91,220,229)'),\n",
    "        width = 2)\n",
    ")\n",
    "trace_R_low = go.Scatter(\n",
    "    x = [0,2],\n",
    "    y = [0,2],\n",
    "    name='R Low',\n",
    "    line = dict(\n",
    "        color = ('rgb(13,174,186)'),\n",
    "        width = 2)\n",
    ")\n",
    "trace_dune_crest = go.Scatter(\n",
    "    x = [0,3],\n",
    "    y = [0,3],\n",
    "    name='Dune Crest',\n",
    "    line = dict(\n",
    "        color = ('rgb(214, 117, 14)'),\n",
    "        width = 2,\n",
    "        dash = 'dot')\n",
    ")\n",
    "trace_dune_toe = go.Scatter(\n",
    "    x = [0,3],\n",
    "    y = [0,3],\n",
    "    name='Dune Toe',\n",
    "    line = dict(\n",
    "        color = ('rgb(142, 77, 8)'),\n",
    "        width = 2,\n",
    "        dash = 'dash')\n",
    ")\n",
    "trace_tide = go.Scatter(\n",
    "    x = [0,4],\n",
    "    y = [0,4],\n",
    "    name='Tide+Surge WL',\n",
    "    line = dict(\n",
    "        color = ('rgb(8,51,137)'),\n",
    "        width = 2,\n",
    "        dash = 'dot')\n",
    ")\n",
    "\n",
    "data=[trace_R_high, trace_R_low, trace_dune_crest, trace_dune_toe,trace_tide]\n",
    "\n",
    "layout = go.Layout(\n",
    "    title = 'Water Level & Dune Toe/Crest',\n",
    "    height=200,\n",
    "    margin=dict(t=50,b=50,l=50,r=50),\n",
    "    xaxis=dict(\n",
    "        title='time',\n",
    "        domain=[0.0, 0.95],\n",
    "        zeroline=False,\n",
    "    ),\n",
    "    yaxis=dict(\n",
    "        title = 'Water Level (m)',\n",
    "    ),\n",
    ")\n",
    "\n",
    "g4 = go.FigureWidget(data=data, layout=layout)\n",
    "\n",
    "\n",
    "def update_profile(change):\n",
    "    \n",
    "    site_id = site_id_select.value\n",
    "    site_profile = df_profiles.query('site_id == \"{}\"'.format(site_id))\n",
    "    prestorm_profile = site_profile.query('profile_type == \"prestorm\"')\n",
    "    poststorm_profile = site_profile.query('profile_type == \"poststorm\"')\n",
    "\n",
    "    poststorm_x = poststorm_profile.index.get_level_values('x').tolist()\n",
    "    poststorm_z = poststorm_profile.z.tolist()\n",
    "\n",
    "    prestorm_x = prestorm_profile.index.get_level_values('x').tolist()\n",
    "    prestorm_z = prestorm_profile.z.tolist()\n",
    "    \n",
    "    site_features = df_profile_features.query('site_id == \"{}\"'.format(site_id))\n",
    "    dune_crest_x = site_features.dune_crest_x\n",
    "    dune_crest_z = site_features.dune_crest_z\n",
    "    dune_toe_x = site_features.dune_toe_x\n",
    "    dune_toe_z = site_features.dune_toe_z\n",
    "    \n",
    "    # Update beach profile section plots\n",
    "    with g1.batch_update():\n",
    "        g1.data[0].x = prestorm_x\n",
    "        g1.data[0].y = prestorm_z\n",
    "        g1.data[1].x = poststorm_x\n",
    "        g1.data[1].y = poststorm_z\n",
    "        g1.data[2].x = dune_crest_x\n",
    "        g1.data[2].y = dune_crest_z\n",
    "        g1.data[3].x = dune_toe_x\n",
    "        g1.data[3].y = dune_toe_z\n",
    "        \n",
    "    # Relocate plan of satellite imagery\n",
    "    site_coords = df_sites.query('site_id == \"{}\"'.format(site_id))\n",
    "    with g2.batch_update():\n",
    "        g2.layout.mapbox['center'] = {\n",
    "            'lat': site_coords['lat'].values[0],\n",
    "            'lon': site_coords['lon'].values[0]\n",
    "        }\n",
    "        g2.layout.mapbox['zoom'] = 15\n",
    "        g2.data[1].lat = [site_coords['lat'].values[0]]\n",
    "        g2.data[1].lon = [site_coords['lon'].values[0]]\n",
    "        g2.data[1].text = site_coords['lon'].index.get_level_values('site_id').tolist()\n",
    "\n",
    "    # Update time series plots \n",
    "    df_timeseries = df_twl.query(\"site_id=='{}'\".format(site_id))\n",
    "    times = df_timeseries.index.get_level_values('datetime').tolist()\n",
    "    with g3.batch_update():\n",
    "        g3.data[0].x = times\n",
    "        g3.data[1].x = times\n",
    "        g3.data[2].x = times\n",
    "        g3.data[0].y = df_timeseries.Hs0.tolist()\n",
    "        g3.data[1].y = df_timeseries.Tp.tolist()\n",
    "        g3.data[2].y = df_timeseries.beta.tolist()\n",
    "        \n",
    "    # Update water levels plot\n",
    "    df_timeseries = df_twl.query(\"site_id=='{}'\".format(site_id))\n",
    "    with g4.batch_update():\n",
    "        g4.data[0].x = times\n",
    "        g4.data[1].x = times\n",
    "        g4.data[2].x = [min(times), max(times)]\n",
    "        g4.data[3].x = [min(times), max(times)]\n",
    "        g4.data[4].x = times\n",
    "        g4.data[0].y = df_timeseries.R_high.tolist()\n",
    "        g4.data[1].y = df_timeseries.R_low.tolist()\n",
    "        g4.data[2].y = dune_crest_z.tolist()[0], dune_crest_z.tolist()[0],\n",
    "        g4.data[3].y = dune_toe_z.tolist()[0], dune_toe_z.tolist()[0],\n",
    "        g4.data[4].y = df_timeseries.tide.tolist()\n",
    "    \n",
    "        \n",
    "def update_filter(change):\n",
    "    \n",
    "    # Get filtered impacts\n",
    "    observed_impacts = observed_impact_select.value\n",
    "    forecasted_impacts = forecasted_impact_select.value\n",
    "    \n",
    "    # Get sites with these impacts \n",
    "    site_id_select.options = df_impacts_compared.loc[df_impacts_compared.storm_regime_forecasted.isin(forecasted_impacts) & \n",
    "                                                     df_impacts_compared.storm_regime_observed.isin(observed_impacts),].index.tolist()\n",
    "    \n",
    "    \n",
    "site_id_select.observe(update_profile, names=\"value\")\n",
    "observed_impact_select.observe(update_filter, names=\"value\")\n",
    "forecasted_impact_select.observe(update_filter, names=\"value\")\n",
    "\n",
    "widgets.VBox([filter_container,site_id_container,widgets.HBox([g1,g2]),g3,g4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
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    "ExecuteTime": {
     "end_time": "2018-11-19T03:23:37.582663Z",
     "start_time": "2018-11-19T03:23:37.577662Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([3.111490610630103, 3.111490610630103],)"
      ]
     },
     "execution_count": 178,
     "metadata": {},
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    }
   ],
   "source": [
    "g4.data[2].y"
   ]
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