{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## cdasws Example IDL Jupyter Notebook\n", "This Jupyter [notebook](https://jupyter.org/) demonstates using the [cdasws](/WebServices/REST/CdasIdlLibrary.html) IDL library to access data from [cdaweb](https://cdaweb.gsfc.nasa.gov/) in the [IDL](https://www.l3harrisgeospatial.com/Software-Technology/IDL) programming language.\n", "\n", "**Note:** This notebook is for the IDL version of cdasws. Jupyter notebooks for the Python version of cdasws is available at [python cdasws notebooks](/WebServices/REST/#Jupyter_Notebook_Examples)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Installation\n", "The following contains the procedure to install the [cdasws](https://cdaweb.gsfc.nasa.gov/WebServices/REST/CdasIdlLibrary.html) IDL library into your IDL environment. There are different procedures for different versions of IDL." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### IDL 8.7.1 and higher\n", "If you have an old version of the SPDF_CDAS package already installed, remove the old version." ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
Package \"SPDF_CDAS\" was removed
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ipm, /remove, 'SPDF_CDAS'" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If the lastest version of the SPDF_CDAS package is not already installed, install it as shown below." ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\"https://cdaweb.gsfc.nasa.gov/WebServices/REST/SPDF_CDAS.zip\" does not appear to be a valid IPM package.
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ipm, /install, 'https://cdaweb.gsfc.nasa.gov/WebServices/REST/SPDF_CDAS.zip'" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You only need to install a particular version of the package once. You will need to restore the package everytime you restart your IDL session. Restore the package as shown below." ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
% RESTORE: Error opening file. Unit: 100, File: /home/btharris/.idl/idl/packages/SPDF_CDAS/spdfcdas.sav
No such file or directory
% Execution halted at: $MAIN$
\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "restore, !package_path + '/SPDF_CDAS/spdfcdas.sav'" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### IDL 8.4.0 and newer\n", "Download [spdfcdas.sav](https://cdaweb.gsfc.nasa.gov/WebServices/REST/spdfcdas.sav). You will need to restore the package everytime you restart your IDL session. Restore the package as shown below." ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [], "source": [ ";restore, getenv('HOME') + '/Downloads' + '/spdfcdas.sav'" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Setup\n", "Create an SpdfCdas object." ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [], "source": [ "cdas = obj_new('SpdfCdas')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Get Observatory Groups\n", "The following code demonstrates how to get the mission/observatory groups supported by cdaweb." ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
ACE\n",
       "AMPTE\n",
       "ARTEMIS\n",
       "Alouette
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "groups = cdas.getObservatoryGroups()\n", "foreach group, groups[0:3] do print, group.getName()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Get Intrument Types\n", "The following code demonstrates how to get the intrument types supported by cdaweb." ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
Activity Indices\n",
       "Electric Fields (space)\n",
       "Electron Precipitation Bremsstrahlung\n",
       "Energetic Particle Detector\n",
       "Engineering\n",
       "Ephemeris/Attitude/Ancillary\n",
       "Gamma and X-Rays\n",
       "Ground-Based HF-Radars\n",
       "Ground-Based Imagers\n",
       "Ground-Based Magnetometers, Riometers, Sounders\n",
       "Ground-Based VLF/ELF/ULF, Photometers\n",
       "Housekeeping\n",
       "Imaging and Remote Sensing (ITM/Earth)\n",
       "Imaging and Remote Sensing (Magnetosphere/Earth)\n",
       "Imaging and Remote Sensing (Sun)\n",
       "Magnetic Fields (Balloon)\n",
       "Magnetic Fields (space)\n",
       "Particles (space)\n",
       "Plasma and Solar Wind\n",
       "Pressure gauge (space)\n",
       "Radio and Plasma Waves (space)\n",
       "Radio and Plasma Waves (space), Electric Antennas\n",
       "Spacecraft Potential Control\n",
       "UV Imaging Spectrograph (Space)
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "instrTypes = cdas.getInstrumentTypes()\n", "foreach instrType, instrTypes do print, instrType.getName()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Get Datasets\n", "The following code demonstrates how to find the datasets for a specific observatory group and instrument type." ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
AC_H0_MFI: H0 - ACE Magnetic Field 16-Second Level 2 Data - N. Ness (Bartol Research Institute)\n",
       "TimeInterval: 1997-09-02T00:00:12.000Z to 2022-02-26T23:59:49.000Z
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "datasets = cdas.getDatasets(observatoryGroups=[groups[0].getName()], instrumentTypes=[instrTypes[16].getName()])\n", "datasets[-1].print" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Get Inventory\n", "The following code demonstrates getting the available data inventory." ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
TimeInterval: 1997-09-02T00:00:12.000Z to 2022-02-26T23:59:49.000Z
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "inventory = cdas.getInventory(datasets[-1].getId())\n", "foreach interval, inventory.getTimeIntervals() do interval.print" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Get Variable Names\n", "The following code demonstrates how to a dataset's variable names." ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
Magnitude BGSEc BGSM dBrms SC_pos_GSE SC_pos_GSM
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "names = cdas.getVariableNames(datasets[-1].getId())\n", "print, names" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Get Data Example\n", "The following code demonstrates how to access magnetic field measurements from the [ACE mission dataset](https://cdaweb.gsfc.nasa.gov/misc/NotesA.html#AC_H1_MFI)." ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [], "source": [ "d = spdfgetdata('AC_H2_MFI', ['Magnitude' , 'BGSEc'], ['2009-06-01T00:00:00.000Z', '2009-06-03T00:00:00.000Z'])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Use the standard IDL PLOT procedure to display the data." ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [ { "data": { "image/png": "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" }, "metadata": { "image/png": { "height": "540", "width": "768" } }, "output_type": "display_data" } ], "source": [ "plot, d.magnitude.dat" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Print the values." ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
      3.52700      3.40500      2.88200      2.73000      3.54800      3.94800      3.73000      3.70300      3.67200      3.61600\n",
       "      3.58300      3.37000      3.51300      3.77700      3.21800      3.01400      3.19700      3.49900      3.10900      3.03900\n",
       "      2.99700      3.09500      3.15200      3.26500      3.25000      3.07000      2.75000      2.92400      2.82200      2.83700\n",
       "      3.02900      3.54900      3.67500      3.76300      4.02500      4.13600      3.85400      3.85700      3.68800      3.58300\n",
       "      3.85200      2.63600      3.01900      3.25700      3.09100      2.61900      1.92300      1.81800      1.99100
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "print, d.magnitude.dat" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Use the [cdawlib plotmaster function](https://spdf.gsfc.nasa.gov/CDAWlib.html#plotmaster) to plot the data." ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "data": { "image/png": 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" }, "metadata": { "image/png": { "height": "540", "width": "768" } }, "output_type": "display_data" } ], "source": [ "status=plotmaster(d,/auto, xsize=768)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Binning Example\n", "For analysis, it is often useful to place two datasets that have different timestamps on the same time grid (with optional spike removal). The following demonstrates doing this with cdasws and the datasets [AC_H0_SWE](/misc/NotesA.html#AC_H0_SWE) and [AC_H2_SWE](/misc/NotesA.html#AC_H2_SWE). For more information on binning, see [binning in cdaweb](/CDAWeb_Binning_readme.html)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Display Original Data\n", "Get and display the data." ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
   6.3053770e+13   6.3053770e+13   6.3053770e+13   6.3053770e+13   6.3053770e+13   6.3053770e+13   6.3053770e+13   6.3053770e+13\n",
       "   6.3053770e+13   6.3053770e+13   6.3053770e+13
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
 -1.00000e+31 -1.00000e+31 -1.00000e+31 -1.00000e+31 -1.00000e+31 -1.00000e+31 -1.00000e+31 -1.00000e+31 -1.00000e+31 -1.00000e+31\n",
       " -1.00000e+31
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
   6.3053770e+13   6.3053773e+13   6.3053777e+13   6.3053780e+13   6.3053784e+13   6.3053788e+13   6.3053791e+13   6.3053795e+13\n",
       "   6.3053798e+13   6.3053802e+13   6.3053806e+13
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
 -1.00000e+31 -1.00000e+31 -1.00000e+31 -1.00000e+31 -1.00000e+31 -1.00000e+31 -1.00000e+31 -1.00000e+31 -1.00000e+31 -1.00000e+31\n",
       " -1.00000e+31
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "dataset0 = 'AC_H0_SWE'\n", "variables = ['Np']\n", "time = ['1998-02-04T00:00:00Z', '1998-02-06T00:00:00Z']\n", "data0 = spdfgetdata(dataset0, variables, time)\n", "print, data0.epoch.dat[0:10]\n", "print, data0.np.dat[0:10]\n", "dataset1 = 'AC_H2_SWE'\n", "data1 = spdfgetdata(dataset1, variables, time)\n", "print, data1.epoch.dat[0:10]\n", "print, data1.np.dat[0:10]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Bin Data\n", "Bin the data with 60 second interval and interpolate any missing values." ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
   6.3053770e+13   6.3053770e+13   6.3053770e+13   6.3053770e+13   6.3053770e+13   6.3053770e+13   6.3053770e+13   6.3053770e+13\n",
       "   6.3053770e+13   6.3053770e+13   6.3053770e+13
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
      16.3343      16.3343      16.3343      16.3343      16.3343      16.3343      16.3343      16.3343      16.3343      16.3343\n",
       "      16.3343
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
   6.3053770e+13   6.3053773e+13   6.3053777e+13   6.3053780e+13   6.3053784e+13   6.3053788e+13   6.3053791e+13   6.3053795e+13\n",
       "   6.3053798e+13   6.3053802e+13   6.3053806e+13
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
      16.6551      16.6551      16.6551      16.6551      16.6551      16.6551      16.6551      16.6551      16.6551      16.6551\n",
       "      16.6551
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "data0 = spdfgetdata(dataset0, variables, time, $\n", " binInterval=60.0D, binInterpolateMissingValues=1, $\n", " binSigmaMultiplier=4)\n", "print, data0.epoch.dat[0:10]\n", "print, data0.np.dat[0:10]\n", "data1 = spdfgetdata(dataset1, variables, time, $\n", " binInterval=60.0D, binInterpolateMissingValues=1, $\n", " binSigmaMultiplier=4)\n", "print, data1.epoch.dat[0:10]\n", "print, data1.np.dat[0:10]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Compare Data\n", "Compare the binned data from the two datasets." ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [ { "data": { "image/png": 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}, "metadata": { "image/png": { "height": "540", "width": "768" } }, "output_type": "display_data" } ], "source": [ "plot, data0.np.dat" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "data": { "image/png": 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}, "metadata": { "image/png": { "height": "540", "width": "768" } }, "output_type": "display_data" } ], "source": [ "plot, data1.np.dat" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### DOI Example\n", "The following demonstrates the use of a dataset's [Digital Object Identifier](https://www.doi.org/) (DOI)." ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
ISEE2_60SEC_MFI, DOI: 10.21978/p8t923, spase://NASA/NumericalData/ISEE2/MAG/PT1M
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
BX BY BZ BTOT
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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" }, "metadata": { "image/png": { "height": "540", "width": "768" } }, "output_type": "display_data" } ], "source": [ "ds = cdas.getDatasets(idPattern='ISEE2_60SEC_MFI')\n", "print, ds[0].getId(), ', DOI: ', ds[0].getDoi(), ', ', ds[0].getResourceId()\n", "iseeVars = cdas.getVariableNames(ds[0].getId())\n", "print, iseeVars[0:3]\n", "iseeInventory = cdas.getInventory(ds[0].getId())\n", "iseeIntervals = iseeInventory.getTimeIntervals()\n", "iseeStop = iseeIntervals[-1].getStop()\n", "iseeStart = iseeStop - 1.0\n", "iseeData = spdfgetdata(ds[0].getDoi(), iseeVars[0:3], [iseeStart, iseeStop])\n", "status = plotmaster(iseeData, /auto, xsize=768)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Additional Documentation\n", "View the [cdasws API](https://cdaweb.gsfc.nasa.gov/WebServices/REST/idl/api/) for additional functions." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "IDL", "language": "IDL", "name": "idl" }, "language_info": { "codemirror_mode": "idl", "file_extension": ".pro", "mimetype": "text/x-idl", "name": "idl" } }, "nbformat": 4, "nbformat_minor": 4 }