{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Print out Initial BED Rotation Rate from the cce_2015 database\n",
    "*Walk through all full resolution BED events and collect first non-zero ROT_RATE value*\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Executing this Notebook requires a personal STOQS server. Follow the [steps to build your own development system](https://github.com/stoqs/stoqs/blob/master/README.md) — this will take a few hours and depends on a good connection to the Internet.  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",
    "    cd /vagrant/dev/stoqsgit\n",
    "    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:5433/stoqs\n",
    "    \n",
    "Launch Jupyter Notebook on your system with:\n",
    "\n",
    "    cd contrib/notebooks\n",
    "    ../../manage.py shell_plus --notebook\n",
    "    \n",
    "navigate to this file 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 print the second ROT_RATE value (first non-zero value from backward difference) for all full resoltion BED events "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Activity Name                    Initial ROT_RATE (deg/sec) Initial A (g)\n",
      "-------------------------------- -------------------------- -------------\n",
      "40100037_full_traj.nc (stride=1)                     238.69         0.251\n",
      "30200078_full_traj.nc (stride=1)                      39.00         0.167\n",
      "60100068_full_traj.nc (stride=1)                     110.44         0.257\n",
      "80200014_full_traj.nc (stride=1)                      68.25         0.046\n",
      "90100156_full_traj.nc (stride=1)                     156.75         0.149\n",
      "80200015_full_traj.nc (stride=1)                      73.52         0.182\n",
      "80200016_full_traj.nc (stride=1)                      75.42         0.213\n",
      "90100157_full_traj.nc (stride=1)                      40.25         0.221\n",
      "80200017_full_traj.nc (stride=1)                     114.48         0.065\n",
      "90100158_full_traj.nc (stride=1)                       8.39         0.052\n",
      "80200019_full_traj.nc (stride=1)                      60.61         0.028\n",
      "80200020_full_traj.nc (stride=1)                      46.94         0.026\n",
      "90100159_full_traj.nc (stride=1)                      37.76         0.101\n",
      "90100160_full_traj.nc (stride=1)                      72.61         0.042\n",
      "90100161_full_traj.nc (stride=1)                      87.81         0.032\n",
      "90100162_full_traj.nc (stride=1)                      57.53         0.063\n",
      "90100164_full_traj.nc (stride=1)                      78.50         0.070\n",
      "90100165_full_traj.nc (stride=1)                      31.30         0.100\n",
      "90100196_full_traj.nc (stride=1)                     259.94         0.628\n",
      "80200039_full_traj.nc (stride=1)                     304.39         1.002\n",
      "B0100028_full_traj.nc (stride=1)                       6.35         0.251\n",
      "30400034_full_traj.nc (stride=1)                       2.43         0.080\n",
      "80200052_full_traj.nc (stride=1)                      98.02         0.088\n"
     ]
    }
   ],
   "source": [
    "db = 'stoqs_cce2015'\n",
    "\n",
    "print(f\"{'Activity Name':32s} {'Initial ROT_RATE (deg/sec)':26s} {'Initial A (g)'}\")\n",
    "print('-' * 32, '-' * 26, '-' * 13)\n",
    "for act in Activity.objects.using(db).filter(name__contains='full').order_by('startdate'):\n",
    "    mps = (MeasuredParameter.objects.using(db)\n",
    "                   .filter(measurement__instantpoint__activity=act)\n",
    "                   .order_by('measurement__instantpoint__timevalue'))\n",
    "    irr = mps.filter(parameter__name='ROT_RATE')\n",
    "    ia = mps.filter(parameter__name='A')\n",
    "\n",
    "    print(f'{act.name:32s} {irr[1].datavalue:26.2f} {ia[0].datavalue:13.3f}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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