Arase 0.0.2

A module for downloading and reading Arase spacecraft data.

Arase

A module for downloading and reading Arase spacecraft data.

Installation

Install from PyPI:

pip3 install Arase --user

or

python3 -m pip install Arase --user

Set the ARASE_PATH variable by placing the following at the end of ~/.bashrc:

export ARASE_PATH=/path/to/arase/data

Downloading Data

Most instrument data can be downloaded using the DownloadData function contained in the instruments submodule, e.g.:

Arase.XXX.DownloadData(L,prod,StartYear=StartYear,EndYear=EndYear,Overwrite=Overwrite)

where XXX can be replaced with the instrument names: HEP, LEPe, LEPi, MEPe, MEPi, MGF or XEP. L is an integer and prod is a string which correspond to the level and data product provided by the instrument, repsectively (see the table in "Current Progress"). StartYear and EndYear determine the range of years to download data for. Overwrite will force the routine to overwrite existing data.

This method will work for PWE data:

Arase.PWE.DownloadData(subcomp,L,prod,StartYear=StartYear,EndYear=EndYear,Overwrite=Overwrite)

where subcomp is the sub-component of the instrument (see table below).

To download the position data:

Arase.Pos.DownloadData(prod,StartYear=StartYear,EndYear=EndYear,Overwrite=Overwrite)

where prod is either 'l3' or 'def'. The 'def' option is needed for position-related functions elsewhere in the Arase module.

Position and tracing

1. Download position data:

Arase.Pos.DownloadData('def')

2. Convert to a binary format (this allows for quicker reading):

Arase.Pos.ConvertPos()

3. Save field traces

Arase.Pos.SaveFieldTraces(Model=Model,StartDate=StartDate,EndDate=EndDate)

where Model is either 'T89', 'T96', 'T01' or 'TS05' ('T96' by default). StartDate and EndDate are the start and end dates to perform traces for, both are integers of the format yyymmdd.

4. To read the position data :

pos = Arase.Pos.GetPos()

To read the traces:

tr = Arase.Pos.ReadFieldTraces(Date)

Reading Data

MGF data

data = Arase.MGF.ReadMGF(Date)

This returns a numpy.recarray object which contains the time-series data.

Particle Omni-directional Spectra

data = Arase.LEPe.ReadOmni(Date)

For other instruments, replace LEPe with one of the following: LEPi, MEPe, MEPi, HEP or XEP. data is a dictionary which will contain dates, times, energy bins and instances of the SpecCls object. The SpecCls object contains all of the spectral information stored within it, and is usually identified by the dictionary key containing 'Flux'. The SpecCls object has an in-built method for plotting the spectrograms, e.g.:

data['eFlux'].Plot()

will plot the electron flux spectrogram from the LEPe data loaded above. To list the keys of a dictionary, use list(data.keys())

3D Particle Spectra

These data are not currently placed into an object like SpecCls, this may change once I have access to PAD data. For instruments which provide 3D spectra, there is a function Read3D which will simply read the CDF file for a given date, and list all of the data and corresponding metadata into two dictionarys, e.g.:

data,meta = Arase.LEPe.Read3D(Date)

Combined Particle Spectra

Two functions are available which will load the data for multiple instruments at the same time.

For electrons:

E = Arase.Electrons.ReadOmni(Date)

and for ions:

H,He,O = Arase.Ions.ReadOmni(Date)

where E, H, He and O are all instances of SpecCls.

Current progress

Instrument	Subcomponent	Level	Product	Download	Read	Plot
HEP		2	omniflux	✔	✔	✔
LEPe		2	omniflux	✔	✔	✔
LEPe		2	3dflux	✔	✱	✖
LEPi		2	omniflux	✔	✔	✔
LEPi		2	3dflux	✔	✱	✖
MEPe		2	omniflux	✔	✔	✔
MEPe		2	3dflux	✔	✱	✱
MEPe		3	3dflux	✝	✱	✖
MEPi		2	omniflux	✔	✔	✔
MEPi		2	3dflux	✔	✱	✔
MEPi		3	3dflux	✝	✱	✖
MGF		2	8sec	✔	✔	✖
PWE	efd	2	spec	✔	✔	✔
PWE	hfa	2	high	✔	✔	✔
PWE	hfa	2	low	✔	✔	✔
PWE	hfa	3		✝	✔	✖
PWE	ofa	2	complex	✝	✖	✖
PWE	ofa	2	matrix	✝	✖	✖
PWE	ofa	2	spec	✔	✖	✖
XEP		2	omniflux	✔	✔	✔

• ✔ - Works
• ✖ - Not working yet. In the case of 3D data, a SpecCls3D object needs to be written. For MGF and level 3 hfa data, it's a simple case of plotting a line.
• ✝ - Probably works, but have no access to the data to be able to test it.
• ✱ - Currently 3D spectra can only be read into dictionaries as a SpecCls3D object is needed.