Quickstart

We provide a few ways to load data, please see Data for a detailed explanation of the data formats and retrieval methods.

Get data with Speasy

Speasy.jl provides functions to load data from main Space Physics WebServices (CDA,SSC,AMDA,..).

It could be installed using using Pkg; Pkg.add("Speasy").

using Speasy: get_data
using SPEDAS

# da = get_data("amda/imf", "2016-6-2", "2016-6-5")
da = get_data("cda/OMNI_HRO_1MIN/Pressure", "2016-6-2", "2016-6-5")

SpeasyVariable{Float32, 2}: Pressure
  Time Range: 2016-06-02T00:00:00 to 2016-06-04T23:59:00
  Units: nPa
  Size: (4320, 1)
  Memory Usage: 85.365 KiB
  Metadata:
    FIELDNAM: Flow pressure
    VALIDMIN: Any[0.0]
    VALIDMAX: Any[100.0]
    SCALEMIN: Any[0.0]
    SCALEMAX: Any[100.0]
    UNITS: nPa
    FORMAT: F5.2
    FILLVAL: Any[99.98999786376953]
    VAR_TYPE: data
    CATDESC: Flow pressure (nPa)
    VAR_NOTES: Derived parameters are obtained from the following equations. Flow pressure = (2*10**-6)*Np*Vp**2 nPa (Np in cm**-3, Vp in km/s, subscript p for proton) 
    DISPLAY_TYPE: time_series
    DEPEND_0: Epoch
    LABLAXIS: Flow pressure
    BIN_LOCATION: 0.0

Plot the data

tplot(da)

Get data using Heliophysics Application Programmer's Interface (HAPI)

HAPIClient.jl provides functions to load data from HAPI-compliant servers.

It could be installed using using Pkg; Pkg.add("HAPIClient").

using HAPIClient: get_data

da = get_data("CDAWeb/AC_H0_MFI/Magnitude,BGSEc", "2001-1-2", "2001-1-2T12")

2-element Vector{HAPIClient.HAPIVariable{Float64, N, A, Vector{Dates.DateTime}} where {N, A<:AbstractArray{Float64, N}}}:
 Magnitude [Time Range: 2001-01-02T00:00:15 to 2001-01-02T11:59:58, Units: nT, Size: (2700,)]
 BGSEc [Time Range: 2001-01-02T00:00:15 to 2001-01-02T11:59:58, Units: nT, Size: (2700, 3)]

Plot the data

using SPEDAS

tplot(da)

Get data with PySPEDAS

PySPEDAS.jl provides a Julia interface to the PySPEDAS Python package, offering a similar API for Julia users to utilize the existing Python routines.

It could be installed using using Pkg; Pkg.add("https://github.com/JuliaSpacePhysics/PySPEDAS.jl").

using SPEDAS: tplot
using PySPEDAS.Projects
using DimensionalData
using CairoMakie

da = themis.fgm(["2020-04-20/06:00", "2020-04-20/08:00"], time_clip=true, probe="d");
keys(da)
# Same as more verbose `pyspedas.projects.themis.fgm(...)`

(:thd_fgs_btotal, :thd_fgs_gse, :thd_fgs_gsm, :thd_fgs_dsl, :thd_fgl_btotal, :thd_fgl_gse, :thd_fgl_gsm, :thd_fgl_dsl, :thd_fgl_ssl, :thd_fgh_btotal, :thd_fgh_gse, :thd_fgh_gsm, :thd_fgh_dsl, :thd_fgh_ssl, :thd_fge_btotal, :thd_fge_gse, :thd_fge_gsm, :thd_fge_dsl, :thd_fge_ssl)

Plot the data

f = Figure()
tplot(f[1,1], [da.thd_fgs_gsm, da.thd_fgs_btotal])
tplot(f[2,1], [DimArray(da.thd_fgl_gsm), DimArray(da.thd_fgl_btotal)])
f