{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import madrigalWeb.madrigalWeb\n",
    "import pylab\n",
    "import matplotlib.cm\n",
    "import numpy\n",
    "import h5py\n",
    "import datetime\n",
    "import dateutil.parser\n",
    "import calendar\n",
    "import re\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#CHANGE ME\n",
    "user_fullname = \"Student Example\"\n",
    "user_email = \"isr.summer.school@gmail.com\"\n",
    "user_affiliation = \"ISR Summer School 2022\"\n",
    "\n",
    "maddat = madrigalWeb.madrigalWeb.MadrigalData('http://cedar.openmadrigal.org/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# instrument codes for Millstone Hill\n",
    "instcodes={'MHO':30}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "id: 100195498\n",
      "realUrl: http://cedar.openmadrigal.org/showExperiment/?experiment_list=100195498\n",
      "url: http://cedar.openmadrigal.org/madtoc/experiments5/2013/mlh/16mar13a\n",
      "name: DICE Overflight\n",
      "siteid: 10\n",
      "sitename: CEDAR\n",
      "instcode: 30\n",
      "instname: Millstone Hill IS Radar\n",
      "startyear: 2013\n",
      "startmonth: 3\n",
      "startday: 16\n",
      "starthour: 21\n",
      "startmin: 23\n",
      "startsec: 22\n",
      "endyear: 2013\n",
      "endmonth: 3\n",
      "endday: 16\n",
      "endhour: 22\n",
      "endmin: 34\n",
      "endsec: 25\n",
      "isLocal: True\n",
      "madrigalUrl: http://cedar.openmadrigal.org/\n",
      "PI: Phil Erickson\n",
      "PIEmail: perickson@haystack.mit.edu\n",
      "uttimestamp: 1594078627\n",
      "access: 2\n",
      "Madrigal version: 3.2\n",
      "\n",
      "id: 100195539\n",
      "realUrl: http://cedar.openmadrigal.org/showExperiment/?experiment_list=100195539\n",
      "url: http://cedar.openmadrigal.org/madtoc/experiments5/2013/mlh/15mar13\n",
      "name: DICE Overflight\n",
      "siteid: 10\n",
      "sitename: CEDAR\n",
      "instcode: 30\n",
      "instname: Millstone Hill IS Radar\n",
      "startyear: 2013\n",
      "startmonth: 3\n",
      "startday: 15\n",
      "starthour: 19\n",
      "startmin: 42\n",
      "startsec: 44\n",
      "endyear: 2013\n",
      "endmonth: 3\n",
      "endday: 16\n",
      "endhour: 0\n",
      "endmin: 40\n",
      "endsec: 58\n",
      "isLocal: True\n",
      "madrigalUrl: http://cedar.openmadrigal.org/\n",
      "PI: Phil Erickson\n",
      "PIEmail: perickson@haystack.mit.edu\n",
      "uttimestamp: 1594075820\n",
      "access: 2\n",
      "Madrigal version: 3.2\n",
      "\n",
      "id: 100195516\n",
      "realUrl: http://cedar.openmadrigal.org/showExperiment/?experiment_list=100195516\n",
      "url: http://cedar.openmadrigal.org/madtoc/experiments5/2013/mlh/17mar13\n",
      "name: DICE Overflight\n",
      "siteid: 10\n",
      "sitename: CEDAR\n",
      "instcode: 30\n",
      "instname: Millstone Hill IS Radar\n",
      "startyear: 2013\n",
      "startmonth: 3\n",
      "startday: 17\n",
      "starthour: 21\n",
      "startmin: 51\n",
      "startsec: 24\n",
      "endyear: 2013\n",
      "endmonth: 3\n",
      "endday: 17\n",
      "endhour: 22\n",
      "endmin: 35\n",
      "endsec: 56\n",
      "isLocal: True\n",
      "madrigalUrl: http://cedar.openmadrigal.org/\n",
      "PI: Phil Erickson\n",
      "PIEmail: perickson@haystack.mit.edu\n",
      "uttimestamp: 1594078688\n",
      "access: 2\n",
      "Madrigal version: 3.2\n",
      "\n",
      "id: 100195497\n",
      "realUrl: http://cedar.openmadrigal.org/showExperiment/?experiment_list=100195497\n",
      "url: http://cedar.openmadrigal.org/madtoc/experiments5/2013/mlh/18mar13\n",
      "name: Van Allen Conjunction CME\n",
      "siteid: 10\n",
      "sitename: CEDAR\n",
      "instcode: 30\n",
      "instname: Millstone Hill IS Radar\n",
      "startyear: 2013\n",
      "startmonth: 3\n",
      "startday: 18\n",
      "starthour: 18\n",
      "startmin: 1\n",
      "startsec: 0\n",
      "endyear: 2013\n",
      "endmonth: 3\n",
      "endday: 19\n",
      "endhour: 0\n",
      "endmin: 30\n",
      "endsec: 0\n",
      "isLocal: True\n",
      "madrigalUrl: http://cedar.openmadrigal.org/\n",
      "PI: Phil Erickson\n",
      "PIEmail: perickson@haystack.mit.edu\n",
      "uttimestamp: 1543545564\n",
      "access: 2\n",
      "Madrigal version: 3.2\n",
      "\n",
      "id: 100195503\n",
      "realUrl: http://cedar.openmadrigal.org/showExperiment/?experiment_list=100195503\n",
      "url: http://cedar.openmadrigal.org/madtoc/experiments5/2013/mlh/16mar13\n",
      "name: Van Allen Conjunction\n",
      "siteid: 10\n",
      "sitename: CEDAR\n",
      "instcode: 30\n",
      "instname: Millstone Hill IS Radar\n",
      "startyear: 2013\n",
      "startmonth: 3\n",
      "startday: 16\n",
      "starthour: 16\n",
      "startmin: 6\n",
      "startsec: 30\n",
      "endyear: 2013\n",
      "endmonth: 3\n",
      "endday: 19\n",
      "endhour: 4\n",
      "endmin: 0\n",
      "endsec: 9\n",
      "isLocal: True\n",
      "madrigalUrl: http://cedar.openmadrigal.org/\n",
      "PI: Phil Erickson\n",
      "PIEmail: perickson@haystack.mit.edu\n",
      "uttimestamp: 1594078550\n",
      "access: 2\n",
      "Madrigal version: 3.2\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# start time\n",
    "st=datetime.datetime(2013, 3, 16, 0,0)\n",
    "et=datetime.datetime(2013, 3, 19, 0,0)\n",
    "\n",
    "expList = maddat.getExperiments(instcodes['MHO'], \n",
    "                                st.year, st.month, st.day, st.hour, st.minute, st.second, \n",
    "                                et.year, et.month, et.day, et.hour, et.minute, et.second)\n",
    "for exp in expList:\n",
    "    print(exp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Selecting: Van Allen Conjunction\n"
     ]
    }
   ],
   "source": [
    "# select Van Allen Conjunction experiment (regular ion line parameters)\n",
    "for thisExp in expList:\n",
    "    if re.match(exp.name, 'Van Allen'):\n",
    "        break\n",
    "print('Selecting: %s' % (thisExp.name))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Combined basic parameters file - all antennas and modes\n",
      "Zenith single-pulse basic parameters\n",
      "Zenith alternating-code basic parameters\n",
      "MISA (steerable) single-pulse basic parameters\n",
      "MISA (steerable) alternating-code basic parameters\n",
      "Gridded data fitted to a uniform spatial and temporal grid - useful for modellers\n",
      "Derived vector ion velocities\n"
     ]
    }
   ],
   "source": [
    "# survey all experiment files available\n",
    "fileList = maddat.getExperimentFiles(thisExp.id)\n",
    "thisFile=None\n",
    "for file in fileList:\n",
    "    print(file.kindatdesc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using: name: /opt/cedar3/experiments5/2013/mlh/16mar13/mlh130316k.005.hdf5\n",
      "kindat: 3430\n",
      "kindatdesc: MISA (steerable) single-pulse basic parameters\n",
      "category: 1\n",
      "status: Final\n",
      "permission: 0\n",
      "expId: 100195503\n",
      "doi: https://w3id.org/cedar?experiment_list=experiments5/2013/mlh/16mar13&file_list=mlh130316k.005.hdf5\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Select the correct experiment file (MISA uncoded pulse)\n",
    "fileList = maddat.getExperimentFiles(thisExp.id)\n",
    "thisFile=None\n",
    "for file in fileList:\n",
    "    if re.match('MISA \\(steerable\\) single-pulse',file.kindatdesc):\n",
    "        print('Using: %s' % (file))\n",
    "        thisFile=file\n",
    "        break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Download the file (should end up in this folder)       \n",
    "filename=thisFile.name\n",
    "outfilename=thisFile.name.split('/')[-1]\n",
    "result = maddat.downloadFile(filename,outfilename, user_fullname, user_email, user_affiliation, 'hdf5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load file and get data table\n",
    "hz = h5py.File(outfilename,'r')\n",
    "hztl = hz['Data']['Table Layout']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Unique pulse lengths in sec: [0.002, 0.00048]\n"
     ]
    }
   ],
   "source": [
    "# Survey the radar pulse lengths in this experiment\n",
    "print('Unique pulse lengths in sec: %s' % (list(set(hztl['pl']))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[('year', '<f8'), ('month', '<f8'), ('day', '<f8'), ('hour', '<f8'), ('min', '<f8'), ('sec', '<f8'), ('recno', '<f8'), ('kindat', '<f8'), ('kinst', '<f8'), ('ut1_unix', '<f8'), ('ut2_unix', '<f8'), ('range', '<f8'), ('pl', '<f8'), ('mdtyp', '<f8'), ('az1', '<f8'), ('az2', '<f8'), ('el1', '<f8'), ('el2', '<f8'), ('systmp', '<f8'), ('pnrmd', '<f8'), ('power', '<f8'), ('pulf', '<f8'), ('dtau', '<f8'), ('ipp', '<f8'), ('tfreq', '<f8'), ('vtx', '<f8'), ('dvtx', '<f8'), ('scntyp', '<f8'), ('cycn', '<f8'), ('posn', '<f8'), ('mresl', '<f8'), ('sn', '<f8'), ('wchsq', '<f8'), ('gfit', '<f8'), ('fpi_dataqual', '<f8'), ('ti', '<f8'), ('dti', '<f8'), ('tr', '<f8'), ('dtr', '<f8'), ('popl', '<f8'), ('dpopl', '<f8'), ('ph+', '<f8'), ('dph+', '<f8'), ('fa', '<f8'), ('dfa', '<f8'), ('co', '<f8'), ('dco', '<f8'), ('pm', '<f8'), ('dpm', '<f8'), ('vo', '<f8'), ('dvo', '<f8'), ('vdopp', '<f8'), ('dvdopp', '<f8'), ('tibf', '<f8'), ('dtibf', '<f8'), ('trbf', '<f8'), ('dtrbf', '<f8'), ('fit_type', '<f8'), ('cctitr', '<f8'), ('cctiph', '<f8'), ('cctico', '<f8'), ('cctrph', '<f8'), ('gdlat', '<f8'), ('glon', '<f8'), ('gdalt', '<f8'), ('ne', '<f8'), ('dne', '<f8')]\n"
     ]
    }
   ],
   "source": [
    "# List variables available\n",
    "print(hztl.dtype)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# antenna codes for Millstone Hill\n",
    "antcodes={'Zenith':32,\n",
    "           'MISA':31}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define time subset\n",
    "t1 = calendar.timegm(dateutil.parser.parse('2013-03-17T19:41:00').timetuple())\n",
    "t2 = calendar.timegm(dateutil.parser.parse('2013-03-17T19:57:00').timetuple())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Select the 2000 usec uncoded pulse from the MISA at the desired times\n",
    "indx = numpy.where(numpy.logical_and(hztl['pl'] >= 1900e-6,\n",
    "                                    hztl['kinst'] == antcodes['MISA']))[0]\n",
    "hztl = hztl[indx]\n",
    "indx = numpy.where(numpy.logical_and(hztl['ut1_unix'] >= t1,\n",
    "                                     hztl['ut2_unix'] <= t2))[0]\n",
    "hztl = hztl[indx]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Build a time array\n",
    "ut = 0.5*(hztl['ut1_unix'] + hztl['ut2_unix'])\n",
    "dut = numpy.array([datetime.datetime.utcfromtimestamp(uut) for uut in ut])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Electron density:\n",
    "# Construct X and Y meshgrid arrays for 2D plot and extract data for plotting\n",
    "tcount = len(set(ut))\n",
    "X = numpy.array(hztl['gdalt'])\n",
    "X = X.reshape(tcount,-1)\n",
    "Y = numpy.array(dut)\n",
    "Y = Y.reshape(tcount,-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/fv/q7qf8rjn6zdd37k3vttxspjw0000gp/T/ipykernel_36972/328036491.py:10: UserWarning: The input coordinates to pcolor are interpreted as cell centers, but are not monotonically increasing or decreasing. This may lead to incorrectly calculated cell edges, in which case, please supply explicit cell edges to pcolor.\n",
      "  am = ax[0].pcolor(Y, X, Z, vmin=9, vmax=12, cmap='jet')\n",
      "/var/folders/fv/q7qf8rjn6zdd37k3vttxspjw0000gp/T/ipykernel_36972/328036491.py:19: UserWarning: The input coordinates to pcolor are interpreted as cell centers, but are not monotonically increasing or decreasing. This may lead to incorrectly calculated cell edges, in which case, please supply explicit cell edges to pcolor.\n",
      "  am = ax[1].pcolor(Y, X, Z, vmin=0, vmax=1000, cmap='jet')\n",
      "/var/folders/fv/q7qf8rjn6zdd37k3vttxspjw0000gp/T/ipykernel_36972/328036491.py:24: RuntimeWarning: invalid value encountered in log10\n",
      "  Z = numpy.log10(hztl['ne']*hztl['vo'])\n",
      "/var/folders/fv/q7qf8rjn6zdd37k3vttxspjw0000gp/T/ipykernel_36972/328036491.py:26: UserWarning: The input coordinates to pcolor are interpreted as cell centers, but are not monotonically increasing or decreasing. This may lead to incorrectly calculated cell edges, in which case, please supply explicit cell edges to pcolor.\n",
      "  am = ax[2].pcolor(Y, X, Z, vmin=12, vmax=15, cmap='jet')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Make triple panel figure:\n",
    "# Electron density, LOS velocity, density x velocity\n",
    "\n",
    "pylab.rcParams['figure.figsize']=(15,15)\n",
    "pylab.rcParams['font.size']=18\n",
    "f,ax = pylab.subplots(3,1,sharex=True)\n",
    "\n",
    "Z = numpy.log10(hztl['ne'])\n",
    "Z = Z.reshape(X.shape)\n",
    "am = ax[0].pcolor(Y, X, Z, vmin=9, vmax=12, cmap='jet')\n",
    "ax[0].set_ylim(150,600)\n",
    "f.colorbar(am, ax=ax[0], label='Log10([e-])')\n",
    "ax[0].set_ylabel('Altitude (km)')\n",
    "ax[0].set_title('Millstone Hill MISA %s El=%.0f' % (dut[0].strftime('%Y-%m-%d'),\n",
    "                                                    hztl['el1'][0]))\n",
    "\n",
    "Z = hztl['vo']\n",
    "Z = Z.reshape(X.shape)\n",
    "am = ax[1].pcolor(Y, X, Z, vmin=0, vmax=1000, cmap='jet')\n",
    "ax[1].set_ylim(150,600)\n",
    "f.colorbar(am, ax=ax[1], label='LOS Velocity (m/s)')\n",
    "ax[1].set_ylabel('Altitude (km)')\n",
    "\n",
    "Z = numpy.log10(hztl['ne']*hztl['vo'])\n",
    "Z = Z.reshape(X.shape)\n",
    "am = ax[2].pcolor(Y, X, Z, vmin=12, vmax=15, cmap='jet')\n",
    "ax[2].set_ylim(150,600)\n",
    "f.colorbar(am, ax=ax[2], label='Dens x veloc (m^-2 s^-1)')\n",
    "ax[2].set_ylabel('Altitude (km)')\n",
    "ax[2].set_xlabel('UT (Hours)')\n",
    "\n",
    "f.autofmt_xdate()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fixed plot of data from same time period in geographic form: 2D (latitude, longitude)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"images/mho_log_e-_2013-03-17T194125ut.png\" />"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"images/mho_vlos_2013-03-17T194125ut.png\" />"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Questions\n",
    "\n",
    "1. Why does the electron density rapidly increase to the west of Millstone at about 55 gdlat?\n",
    "\n",
    "2. Why does the line of sight velocity rapidly increase in the same region?\n",
    "\n",
    "3. This period was very magnetically disturbed.  What does the product of density and velocity gauge, and what does the measurement here tell you about dynamics in the subauroral region?"
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