A simple crib sheet for loading and plotting Arase satellite data

This notebook shows how to load and plot Arase satellite data with pySPEDAS and pyTplot.

Please refer to the following website for the details of the data.

https://ergsc.isee.nagoya-u.ac.jp/data_info/erg.shtml.en

Get started

It is assumed that you already have pySPEDAS and the latest version of ERG-SC plug-in installed on your python environment. The following commands import some necessary modules for loading and plotting the data.

You can import the ERG-SC plug-in from either the pyspedas module or the ergpyspedas module. The latter is kind of the bleeding-edge distribution: it always delivers the latest version of sub-modules some of which may still be in an experimental phase. The former, the main distribution of pySPEDAS, contains a stable version of the ERG-SC plug-in.

In this notebook, we use the bleeding-edge version of the ERG-SC plug-in. For example, the data-load module for the MGF data can be imported with the following command:

Basic commands of pyTplot and pySPEDAS

With MGF data, let us introduce some basic commands of pyTplot and pySPEDAS, which are used commonly for loading and visualizing data. Also see the official document of the pyTplot module at:

https://pytplot.readthedocs.io/en/latest/index.html

Load data and plot them with "tplot"

Plot multiple tplot variables verticaly in a row on a window

Limit the time range of a plot: timespan()

Change the vertical scale of a plot: ylim

Change the title of the vertical axis: options()

Change the contour scale for a spectrum-type plot: zlim()

Show the list of loaded tplot variables: tplot_names()

Remove tplot variables that have been loaded


Load Arase satellite data

Add some extra Xaxes to the bottom of the plot


Use the part_products library to obtain particle spectra

An experimental version of the part_products library has just been implemented to the ERG-SC plug-in. So far only the bleeding-edge distribution of the plug-in contains the part_products. In near future, after fully tested, the ERG part_products will be merged to the main distribution of pySPEDAS.

As of Mar., 2022, the following modules are released experimentally:

They can be used with common arguments and options, similar to those of the (original) IDL version. Several spectrum plots using part_products are demonstrated below to show how to use the library for Arase's particle data.

Generate a tplot variable containing energy-time spectra