{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import madrigalWeb.madrigalWeb\n", "import pylab\n", "import numpy\n", "import h5py\n", "import datetime\n", "import dateutil.parser\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: 100194345\n", "realUrl: http://cedar.openmadrigal.org/showExperiment/?experiment_list=100194345\n", "url: http://cedar.openmadrigal.org/madtoc/experiments5/2018/mlh/04sep18p\n", "name: High resolution F2 Peak Density (From Plasma Line)\n", "siteid: 10\n", "sitename: CEDAR\n", "instcode: 30\n", "instname: Millstone Hill IS Radar\n", "startyear: 2018\n", "startmonth: 9\n", "startday: 4\n", "starthour: 10\n", "startmin: 38\n", "startsec: 7\n", "endyear: 2018\n", "endmonth: 9\n", "endday: 4\n", "endhour: 16\n", "endmin: 1\n", "endsec: 34\n", "isLocal: True\n", "madrigalUrl: http://cedar.openmadrigal.org/\n", "PI: Phil Erickson\n", "PIEmail: perickson@haystack.mit.edu\n", "uttimestamp: 1586213586\n", "access: 2\n", "Madrigal version: 3.2\n", "\n", "id: 100194374\n", "realUrl: http://cedar.openmadrigal.org/showExperiment/?experiment_list=100194374\n", "url: http://cedar.openmadrigal.org/madtoc/experiments5/2018/mlh/04sep18\n", "name: Rapid Plasma Line East\n", "siteid: 10\n", "sitename: CEDAR\n", "instcode: 30\n", "instname: Millstone Hill IS Radar\n", "startyear: 2018\n", "startmonth: 9\n", "startday: 4\n", "starthour: 8\n", "startmin: 0\n", "startsec: 17\n", "endyear: 2018\n", "endmonth: 9\n", "endday: 4\n", "endhour: 16\n", "endmin: 3\n", "endsec: 44\n", "isLocal: True\n", "madrigalUrl: http://cedar.openmadrigal.org/\n", "PI: Phil Erickson\n", "PIEmail: perickson@haystack.mit.edu\n", "uttimestamp: 1566865997\n", "access: 2\n", "Madrigal version: 3.2\n", "\n", "id: 100194399\n", "realUrl: http://cedar.openmadrigal.org/showExperiment/?experiment_list=100194399\n", "url: http://cedar.openmadrigal.org/madtoc/experiments5/2018/mlh/04sep18a\n", "name: Alternate processing using USRP receiver - not for science use\n", "siteid: 10\n", "sitename: CEDAR\n", "instcode: 30\n", "instname: Millstone Hill IS Radar\n", "startyear: 2018\n", "startmonth: 9\n", "startday: 4\n", "starthour: 8\n", "startmin: 0\n", "startsec: 17\n", "endyear: 2018\n", "endmonth: 9\n", "endday: 4\n", "endhour: 16\n", "endmin: 3\n", "endsec: 44\n", "isLocal: True\n", "madrigalUrl: http://cedar.openmadrigal.org/\n", "PI: Phil Erickson\n", "PIEmail: perickson@haystack.mit.edu\n", "uttimestamp: 1566865999\n", "access: 2\n", "Madrigal version: 3.2\n", "\n" ] } ], "source": [ "# start time\n", "st=datetime.datetime(2018, 9, 4, 0,0)\n", "et=datetime.datetime(2018, 9, 5, 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": [], "source": [ "# multiple experiments on this day; select the first one (plasma line)\n", "thisExp = expList[0]" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Using: name: /opt/cedar3/experiments5/2018/mlh/04sep18p/mlh_pl_20180904.002.hdf5\n", "kindat: 3415\n", "kindatdesc: Plasma line peak densities\n", "category: 1\n", "status: Final\n", "permission: 0\n", "expId: 100194345\n", "doi: https://w3id.org/cedar?experiment_list=experiments5/2018/mlh/04sep18p&file_list=mlh_pl_20180904.002.hdf5\n", "\n" ] } ], "source": [ "# Select the correct experiment file (Plasma line peak density)\n", "fileList = maddat.getExperimentFiles(thisExp.id)\n", "thisFile=None\n", "for file in fileList:\n", " if re.match('Plasma line',file.kindatdesc):\n", " print('Using: %s' % (file))\n", " thisFile=file\n", " break" ] }, { "cell_type": "code", "execution_count": 7, "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": 8, "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": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[('year', '" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "pylab.rcParams['figure.figsize']=(15,10)\n", "pylab.rcParams['font.size']=18\n", "pylab.figure()\n", "pylab.errorbar(dut_zenith, hztl_zenith['nemax'], hztl_zenith['dnemax'], color='b', label='Zenith')\n", "pylab.errorbar(dut_misa, hztl_misa['nemax'], hztl_misa['dnemax'], color='r', label='MISA')\n", "pylab.ylabel('[e-], m-3')\n", "pylab.xlabel('UT, Hours')\n", "pylab.title('Millstone Hill F2 Peak Plasma Line %s' % (dut_zenith[0].strftime('%Y-%m-%d')))\n", "pylab.grid()\n", "pylab.legend()\n", "pylab.gcf().autofmt_xdate()" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# which way was each antenna pointing?\n", "pylab.rcParams['figure.figsize']=(15,10)\n", "pylab.rcParams['font.size']=18\n", "\n", "pylab.figure()\n", "\n", "pylab.subplot(211)\n", "pylab.plot(dut_zenith, hztl_zenith['azm'], color='b', marker='*', label='Zenith')\n", "pylab.plot(dut_misa, hztl_misa['azm'], color='r', marker='*', label='MISA')\n", "pylab.ylabel('Azimuth, deg')\n", "pylab.title('Millstone Hill Plasma Line %s' % (dut_zenith[0].strftime('%Y-%m-%d')))\n", "pylab.grid()\n", "pylab.legend()\n", "\n", "pylab.subplot(212)\n", "pylab.plot(dut_zenith, hztl_zenith['elm'], color='b', marker='*', label='Zenith')\n", "pylab.plot(dut_misa, hztl_misa['elm'], color='r', marker='*', label='MISA')\n", "pylab.ylabel('Elevation, deg')\n", "pylab.xlabel('UT, Hours')\n", "pylab.grid()\n", "pylab.legend()\n", "pylab.gcf().autofmt_xdate()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Questions\n", "\n", "1. What is happening at 12 UT?\n", "\n", "2. Why are the two antennas showing different variations? What direction are they looking? Are the observed variations related in some way?\n", "\n", "3. This data is from the F2 peak but altitude information is not available for this experiment (examining 'hmax' variable will show all NaNs). How would you use other Millstone Hill data to find where that peak is?" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.12" } }, "nbformat": 4, "nbformat_minor": 4 }