MMS Fast Plasma Instrument: Difference between revisions

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Prior to using these data, please read the FPI Release Notes:
Prior to using these data, please read the FPI Release Notes:


https://lasp.colorado.edu/mms/sdc/public/datasets/fpi/ ([https://lasp.colorado.edu/mms/sdc/public/datasets/fpi/mms-FPIReleaseNotes-290216-1820-98.pdf FPI Release Notes])
https://lasp.colorado.edu/mms/sdc/public/datasets/fpi/ ([https://lasp.colorado.edu/mms/sdc/public/datasets/fpi/mms-FPIReleaseNotes-220217.pdf FPI Release Notes])





Revision as of 15:45, 5 May 2017

FPI summary plot in SPEDAS

SPEDAS provides command line and GUI access to the MMS FPI data.


Prior to using these data, please read the FPI Release Notes:

https://lasp.colorado.edu/mms/sdc/public/datasets/fpi/ (FPI Release Notes)


FPI Moments

For more complete examples, see the FPI crib sheets located in the /mms/examples/ folder.

Examples

Electron Moments Data

To load and plot the MMS1 FPI electron moments data on March 7, 2016:

MMS> mms_load_fpi, datatype='des-moms', trange=['2016-03-07', '2016-03-08'], probe=1

MMS> tplot, 'mms1_des_numberdensity_dbcs_fast'

MMS> tplot, ['mms1_des_energyspectr_omni_avg', 'mms1_des_pitchangdist_avg']


Ion Moments Data

To load and plot the ion density, along with the omni-directional spectra on March 7, 2016:

MMS> mms_load_fpi, datatype='dis-moms', trange=['2016-03-07', '2016-03-08'], probe=1

MMS> tplot, ['mms1_dis_numberdensity_dbcs_fast', 'mms1_dis_energyspectr_omni_avg']


FPI Distributions

SPEDAS can also be used to load and generate spectra from the FPI distribution functions.

Examples

Electron Distribution Data

To load the FPI electron data:

MMS> mms_load_fpi, probe=1, trange=['2015-10-16/13:02:30', '2015-10-16/13:07:30'], data_rate='brst', datatype='des-dist'


To generate the pitch angle distributions (PADs), we also need spacecraft position and magnetic field data covering the time range:

MMS> mms_load_state, probes=1, trange=['2015-10-16/13:01:30', '2015-10-16/13:08:30']

MMS> mms_load_fgm, probe=1, trange=['2015-10-16/13:01:30', '2015-10-16/13:08:30']


Generate and plot the electron energy spectra and PAD:

MMS> mms_part_products, 'mms1_des_dist_brst', trange=['2015-10-16/13:02:30', '2015-10-16/13:07:30'], mag_name='mms1_fgm_b_dmpa_srvy_l2_bvec', pos_name='mms1_defeph_pos', outputs=['energy','pa']

MMS> tdegap, '*_des_dist_brst_*', /overwrite ; be sure not to interpolate through data gaps

MMS> tplot, ['mms1_des_dist_brst_energy', 'mms1_des_dist_brst_pa']



Ion Distribution Data

To load the FPI ion data:

MMS> mms_load_fpi, probe=1, trange=['2015-10-16/13:02:30', '2015-10-16/13:07:30'], data_rate='brst', datatype='dis-dist'


To generate the pitch angle distributions (PADs), we also need spacecraft position and magnetic field data covering the time range:

MMS> mms_load_state, probes=1, trange=['2015-10-16/13:01:30', '2015-10-16/13:08:30']

MMS> mms_load_fgm, probe=1, trange=['2015-10-16/13:01:30', '2015-10-16/13:08:30']


Generate and plot the ion energy spectra and PAD:

MMS> mms_part_products, 'mms1_dis_dist_brst', trange=['2015-10-16/13:02:30', '2015-10-16/13:07:30'], mag_name='mms1_fgm_b_dmpa_srvy_l2_bvec', pos_name='mms1_defeph_pos', outputs=['energy','pa']

MMS> tdegap, '*_dis_dist_brst_*', /overwrite ; be sure not to interpolate through data gaps

MMS> tplot, ['mms1_dis_dist_brst_energy', 'mms1_dis_dist_brst_pa']



FPI 2D Slices

Examples

Basic 2D Slices

Load the FPI ion distribution data:

MMS> mms_load_fpi, data_rate='brst', datatype='dis-dist', probe=1, trange=['2015-10-16/13:06', '2015-10-16/13:07']


Reformat the data for ploting using spd_slice2d:

MMS> dist = mms_get_dist('mms1_dis_dist_brst', trange=['2015-10-16/13:06', '2015-10-16/13:07'])

MMS> slice = spd_slice2d(dist, time='2015-10-16/13:06') ;3D interpolation


Now plot the slice:

MMS> spd_slice2d_plot, slice


Visualizing 3D Distribution Functions

SPEDAS can also be used for visualizing MMS 3D distribution functions from FPI using the ISEE3D tool, developed by the Institute for Space-Earth Environmental Research (ISEE), Nagoya University, Japan.


Load data into tplot

MMS> mms_load_fpi, probe=1, trange=['2015-10-20/05:56:30', '2015-10-20/05:56:34'], data_rate='brst', datatype='dis-dist'


Load the data into standard structures

MMS> dist = mms_get_fpi_dist('mms1_dis_dist_brst' , trange=['2015-10-20/05:56:30', '2015-10-20/05:56:34'])

MMS> data = spd_dist_to_hash(dist) ;convert structures to isee_3d data model


Load the magnetic field (cyan vector) and velocity (yellow vector) support data

MMS> mms_load_fgm, probe=1, trange=['2015-10-20/05:55:30', '2015-10-20/05:57:34'], level='l2'

MMS> mms_load_fpi, data_rate='brst', datatype='dis-moms', probe=1, trange=['2015-10-20/05:56:30', '2015-10-20/05:56:34']

MMS> join_vec, 'mms1_dis_bulk' + ['x','y','z'] +'_dbcs_brst', 'mms1_dis_bulk' ;combine separate velocity components


Once the GUI is opened, select PSD from Units menu

MMS> isee_3d, data=data, trange=['2015-10-20/05:56:30', '2015-10-20/05:56:34'], bfield='mms1_fgm_b_gse_srvy_l2_bvec', velocity='mms1_dis_bulk'