csem-midl 0.3.0

Python client for the MIDL solar wind dataset

midl

Python client for the MIDL solar wind dataset.

Install

pip install csem-midl

Quickstart

import midl

ds = midl.load("2005-01-01 00:00", "2005-01-01 01:00", 32)
print(ds)

<xarray.Dataset> Size: 4kB
Dimensions:  (time: 61)
Coordinates:
  * time     (time) datetime64[ns] 488B 2005-01-01 ... 2005-01-01T01:00:00
Data variables:
    Bx       (time) float64 488B -6.05 -3.94 -3.7 -3.75 ... -2.01 -1.78 -2.08
    By       (time) float64 488B 3.84 3.5 3.12 2.94 3.2 ... 4.97 5.3 5.29 5.2
    Bz       (time) float64 488B -0.93 -4.06 -4.83 -4.92 ... 1.25 2.04 2.05 2.11
    Ux       (time) float64 488B -422.3 -429.9 -433.6 ... -437.4 -441.8 -441.8
    Uy       (time) float64 488B -13.38 -12.91 -9.05 ... -28.15 -27.06 -26.68
    Uz       (time) float64 488B 26.93 47.59 54.86 54.99 ... 0.46 1.42 0.92
    rho      (time) float64 488B 5.169 5.439 5.481 5.359 ... 6.131 6.363 6.323
    T        (time) float64 488B 1.33e+05 1.321e+05 ... 1.159e+05 1.159e+05
Attributes:
    source:             MIDL
    url:                https://csem.engin.umich.edu/MIDL/
    target:             32Re
    midl_propagation:   {'method': 'ballistic', 'target_re': 32.0}

# 14Re and 32Re Ballistically-propagated data are available for direct download
midl.load("2024-05-10 00:00", "2024-05-11 01:00", 14, method="ballistic")
midl.load("2024-05-10 00:00", "2024-05-11 01:00", 32,method="ballistic") 

# [-70,70]Re MHD-propagated data are available for direct download
midl.load("2024-05-10 00:00", "2024-05-11 01:00", 30, method="mhd")

# Any value can be ballistically propagated client-side
midl.load("2024-05-10 00:00", "2024-05-11 01:00", 20.25,method="ballistic") 

# Data at L1 can be downloaded directly as well 
midl.load("2024-05-10 00:00", "2024-05-11 01:00", "l1")

Client-side MHD propagation is not supported.

Saving to file:

midl.to_csv(ds, "storm.csv")
midl.to_dat(ds, "storm.dat")

Data is cached locally after the first download.

See also

• MIDL-Pipeline — the code that produces the MIDL dataset