{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create Timeline Plot of Deployments in the Coordinated Canyon Experiment\n",
    "*Use the events measured by the BED Platforms to set Event start and end times for the loading of ADCP data into STOQS*\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Executing this Notebook requires a personal STOQS server. Follow the [steps to build your own development or produciton system](https://github.com/stoqs/stoqs/blob/master/README.md).  The Docker instructions below will give you your own copy of the database and is the preferred method.\n",
    "\n",
    "#### Vagrant Instructions\n",
    "Once your server is up log into it (after a `cd ~/Vagrants/stoqsvm`) and activate your virtual environment with the usual commands:\n",
    "\n",
    "    vagrant ssh -- -X\n",
    "    export STOQS_HOME=/vagrant/dev/stoqsgit  # Use STOQS_HOME=/home/vagrant/dev/stoqsgit if not using NFS mount\n",
    "    cd $STOQS_HOME && source venv-stoqs/bin/activate\n",
    "    \n",
    "Connect to your Institution's STOQS database server using read-only credentials. (Note: firewalls typically limit unprivileged access to such resources.)\n",
    "\n",
    "    cd stoqs\n",
    "    ln -s mbari_campaigns.py campaigns.py\n",
    "    export DATABASE_URL=postgis://everyone:guest@kraken.shore.mbari.org:5432/stoqs\n",
    "    \n",
    "Launch Jupyter Notebook on your system with:\n",
    "\n",
    "    cd contrib/notebooks\n",
    "    ../../manage.py shell_plus --notebook\n",
    "    \n",
    "#### Docker Instructions\n",
    "With your stoqs server running in Docker as \n",
    "[detailed in the README](https://github.com/stoqs/stoqs#production-deployment-with-docker) load a copy of the cce_2015 database (from your `$STOQS_HOME/docker` directory) :\n",
    "\n",
    "    docker-compose exec stoqs createdb -U postgres stoqs_cce2015\n",
    "    curl -k https://stoqs.shore.mbari.org/media/pg_dumps/stoqs_cce2015.pg_dump | \\\n",
    "        docker exec -i stoqs pg_restore -Fc -U postgres -d stoqs_cce2015\n",
    "        \n",
    "This may take 30 minutes or more to complete - wait for the command prompt. Then launch the Jupyter Notebook server:\n",
    "\n",
    "    docker-compose exec stoqs stoqs/manage.py shell_plus --notebook\n",
    "\n",
    "A message is displayed giving a token for you to use in a browser on your host, e.g.:\n",
    "\n",
    "    http://localhost:8888/?token=<use_the_given_one-time_token>\n",
    "\n",
    "In the browser window navigate to this file (`stoqs/contrib/notebooks/timeline_plot_cce2015.ipynb`) and open it. You will then be able to execute the cells and experiment with this notebook.\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For the CCE campaign add up the hours and collect in a dictionary all the platform start and end times using Matplotlib mdate format and plot them:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Platform Name     # Deployments   Hours\n",
      "-------------     -------------   -----\n",
      "BED03                         5     0.4\n",
      "BED04                         2     0.2\n",
      "BED05                         5     0.2\n",
      "BED06                         8     0.2\n",
      "BED08                        14     0.5\n",
      "BED09                        15   161.8\n",
      "BED10                         2     0.1\n",
      "BED11                         6     0.1\n",
      "CCESIN                      198 66369.5\n",
      "MS0                          71 43899.8\n",
      "MS1                         139 70245.7\n",
      "MS2                          69 40272.2\n",
      "MS3                         133 53866.2\n",
      "MS4                          45 16096.9\n",
      "MS5                          78 63200.5\n",
      "MS7                          69 33730.2\n"
     ]
    }
   ],
   "source": [
    "from collections import defaultdict\n",
    "from datetime import timedelta\n",
    "import matplotlib.dates as mdates\n",
    "\n",
    "db = 'stoqs_cce2015'\n",
    "\n",
    "plat_start_ends = defaultdict(list)\n",
    "plat_depl_dur = {}\n",
    "print('Platform Name     # Deployments   Hours')\n",
    "print('-------------     -------------   -----')\n",
    "for plat in Platform.objects.using(db).all().order_by('name'):\n",
    "    time_diff_sum = timedelta(0)\n",
    "    for act in Activity.objects.using(db).filter(platform=plat):\n",
    "        time_diff = act.enddate - act.startdate\n",
    "        time_diff_sum += time_diff\n",
    "        plat_start_ends[plat].append((mdates.date2num(act.startdate), \n",
    "                                      mdates.date2num(act.enddate)))\n",
    "\n",
    "    plat_depl_dur[plat] = (len(plat_start_ends[plat]), \n",
    "                           time_diff_sum.total_seconds() / 3600)\n",
    "    print(f'{plat.name:20s} {plat_depl_dur[plat][0]:10d} {plat_depl_dur[plat][1]:7.1f}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import pylab\n",
    "from numpy import arange\n",
    "import operator\n",
    "\n",
    "def plot_platforms(ax):\n",
    "    plat_labels = []\n",
    "\n",
    "    # Plot in order by platformtype name and platform name\n",
    "    for ypos, plat in enumerate(\n",
    "                        sorted(plat_start_ends.keys(),\n",
    "                               key=operator.attrgetter('platformtype.name', 'name'))):\n",
    "        plat_labels.append(f'{plat.name} ({plat.platformtype.name})')    \n",
    "        for bdate, edate in plat_start_ends[plat]:\n",
    "            dd = edate - bdate\n",
    "            if dd < 1:\n",
    "                dd = 1\n",
    "            ax.barh(ypos+0.5, dd, left=bdate, height=0.8, \n",
    "                    align='center', color='#' + plat.color, alpha=1.0) \n",
    "\n",
    "    ax.set_title(Campaign.objects.using(db).get(id=1).description)\n",
    "    ax.set_ylim(-0.5, len(plat_labels) + 0.5)\n",
    "    ax.set_yticks(arange(len(plat_labels)) + 0.5)\n",
    "    ax.set_yticklabels(plat_labels)\n",
    "\n",
    "    ax.grid(True)\n",
    "    plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%B %Y'))\n",
    "    plt.gca().xaxis.set_major_locator(mdates.MonthLocator())\n",
    "    plt.gca().xaxis.set_minor_locator(mdates.DayLocator())\n",
    "    plt.gcf().autofmt_xdate()\n",
    "\n",
    "pylab.rcParams['figure.figsize'] = (15, 9)\n",
    "fig, ax = plt.subplots()\n",
    "plot_platforms(ax)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There appear to be 10 events measured by the Benthic Event Detectors. Let's find the start times for these events and use _k_-means clustering to group the BEDs event data start times into 10 clusters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from sklearn.cluster import KMeans\n",
    "bed_starts = np.array(Activity.objects.using(db)\n",
    "                              .filter(platform__name__contains='BED')\n",
    "                              .values_list('startdate', flat=True)\n",
    "                              .order_by('startdate'), dtype=np.datetime64)\n",
    "km = KMeans(n_clusters=10).fit(bed_starts.reshape(-1, 1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pick the earliest event start time and construct start and end times that we'll use to instruct the STOQS loader that these are the times when we want to load ADCP data from all the moorings into the database."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "events = {}\n",
    "for bed_start in bed_starts:\n",
    "    label = km.predict(bed_start.reshape(-1, 1))[0]\n",
    "    if label not in events.keys():\n",
    "        events[label] = bed_start\n",
    "    # Print the clusters of start times and tune n_clusters above to get the optimal set\n",
    "    ##print(bed_start, label)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Print `Event()` instances of begining and end times for use in [loadCCE_2015.py](https://github.com/stoqs/stoqs/blob/3a596e6791104054c676a0ba84e81ec02b7ca06b/stoqs/loaders/CCE/loadCCE_2015.py#L23-L32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lores_event_times = [\n",
      "        Event(datetime(2015, 11, 30, 15, 37, 45, 500000), datetime(2015, 12, 3, 15, 37, 45, 500000)),\n",
      "        Event(datetime(2016, 1, 14, 21, 35, 52), datetime(2016, 1, 17, 21, 35, 52)),\n",
      "        Event(datetime(2016, 2, 16, 21, 53, 58), datetime(2016, 2, 19, 21, 53, 58)),\n",
      "        Event(datetime(2016, 3, 5, 9, 23, 36), datetime(2016, 3, 8, 9, 23, 36)),\n",
      "        Event(datetime(2016, 4, 6, 21, 28, 26), datetime(2016, 4, 9, 21, 28, 26)),\n",
      "        Event(datetime(2016, 8, 31, 1, 18, 57), datetime(2016, 9, 3, 1, 18, 57)),\n",
      "        Event(datetime(2016, 11, 23, 6, 36, 24), datetime(2016, 11, 26, 6, 36, 24)),\n",
      "        Event(datetime(2017, 1, 8, 5, 23, 5), datetime(2017, 1, 11, 5, 23, 5)),\n",
      "        Event(datetime(2017, 2, 2, 16, 14, 49), datetime(2017, 2, 5, 16, 14, 49)),\n",
      "        Event(datetime(2017, 2, 17, 16, 44, 47), datetime(2017, 2, 20, 16, 44, 47)),\n",
      "                    ]\n",
      "hires_event_times = [\n",
      "        Event(datetime(2015, 12, 1, 11, 37, 45, 500000), datetime(2015, 12, 2, 5, 37, 45, 500000)),\n",
      "        Event(datetime(2016, 1, 15, 17, 35, 52), datetime(2016, 1, 16, 11, 35, 52)),\n",
      "        Event(datetime(2016, 2, 17, 17, 53, 58), datetime(2016, 2, 18, 11, 53, 58)),\n",
      "        Event(datetime(2016, 3, 6, 5, 23, 36), datetime(2016, 3, 6, 23, 23, 36)),\n",
      "        Event(datetime(2016, 4, 7, 17, 28, 26), datetime(2016, 4, 8, 11, 28, 26)),\n",
      "        Event(datetime(2016, 8, 31, 21, 18, 57), datetime(2016, 9, 1, 15, 18, 57)),\n",
      "        Event(datetime(2016, 11, 24, 2, 36, 24), datetime(2016, 11, 24, 20, 36, 24)),\n",
      "        Event(datetime(2017, 1, 9, 1, 23, 5), datetime(2017, 1, 9, 19, 23, 5)),\n",
      "        Event(datetime(2017, 2, 3, 12, 14, 49), datetime(2017, 2, 4, 6, 14, 49)),\n",
      "        Event(datetime(2017, 2, 18, 12, 44, 47), datetime(2017, 2, 19, 6, 44, 47)),\n",
      "                    ]\n"
     ]
    }
   ],
   "source": [
    "from datetime import datetime, timedelta\n",
    "event_start_ends = defaultdict(list)\n",
    "def print_Events(events, before, after, type):\n",
    "    for start in events.values():\n",
    "        beg_dt = repr(start.astype(datetime) - before).replace('datetime.', '')\n",
    "        end_dt = repr(start.astype(datetime) + after).replace('datetime.', '')\n",
    "        event_start_ends[type].append((mdates.date2num(start.astype(datetime) - before),\n",
    "                                       mdates.date2num(start.astype(datetime) + after)))\n",
    "        print(f\"        Event({beg_dt}, {end_dt}),\")\n",
    "\n",
    "# Low-resolution region: 1 day before to 2 days after the start of each event\n",
    "before = timedelta(days=1)\n",
    "after = timedelta(days=2)\n",
    "print(\"lores_event_times = [\")\n",
    "print_Events(events, before, after, 'lores')\n",
    "print(\"                    ]\")\n",
    "\n",
    "# High-resolution region: 4 hours before to 14 hours after the start of each event\n",
    "before = timedelta(hours=4)\n",
    "after = timedelta(hours=14)\n",
    "print(\"hires_event_times = [\")\n",
    "print_Events(events, before, after, 'hires')\n",
    "print(\"                    ]\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot timeline again, but this time with events as shaded regions across all the Platforms."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_events(ax):\n",
    "    for type in ('lores', 'hires'):\n",
    "        for bdate, edate in event_start_ends[type]:\n",
    "            dd = edate - bdate\n",
    "            if dd < 1:\n",
    "                dd = 1\n",
    "            # Plot discovered events as gray lines across all platforms\n",
    "            ax.barh(0, dd, left=bdate, height=32, \n",
    "                    align='center', color='#000000', alpha=0.1) \n",
    "\n",
    "pylab.rcParams['figure.figsize'] = (15, 9)\n",
    "fig, ax2 = plt.subplots()\n",
    "plot_platforms(ax2)\n",
    "plot_events(ax2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Django Shell-Plus",
   "language": "python",
   "name": "django_extensions"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}