TY - JOUR
T1 - The Space Physics Environment Data Analysis System in Python
AU - Grimes, Eric W.
AU - Harter, Bryan
AU - Hatzigeorgiu, Nick
AU - Drozdov, Alexander
AU - Lewis, James W.
AU - Angelopoulos, Vassilis
AU - Cao, Xin
AU - Chu, Xiangning
AU - Hori, Tomo
AU - Matsuda, Shoya
AU - Jun, Chae Woo
AU - Nakamura, Satoko
AU - Kitahara, Masahiro
AU - Segawa, Tomonori
AU - Miyoshi, Yoshizumi
AU - Le Contel, Olivier
N1 - Publisher Copyright:
Copyright © 2022 Grimes, Harter, Hatzigeorgiu, Drozdov, Lewis, Angelopoulos, Cao, Chu, Hori, Matsuda, Jun, Nakamura, Kitahara, Segawa, Miyoshi and Le Contel.
PY - 2022/10/6
Y1 - 2022/10/6
N2 - In this article, we describe the free, open-source Python-based Space Physics Environment Data Analysis System (PySPEDAS), a platform for multi-mission, multi-instrument retrieval, analysis, and visualization of Heliophysics data. PySPEDAS currently contains load routines for data from 23 space missions, as well as a variety of data from ground-based observatories. The load routines are built from a common set of general routines that provide access to datasets in different ways (e.g., downloading and caching CDF files or accessing data hosted on web services), making the process of adding additional datasets simple. In addition to load routines, PySPEDAS contains numerous analysis tools for working with the dataset once it is loaded. We describe how these load routines and analysis tools are built by utilizing other free, open-source Python projects (e.g., PyTplot, cdflib, hapiclient, etc.) to make tools for space and solar physicists that are extremely powerful, yet easy-to-use. After discussing the code in detail, we show numerous examples of code using PySPEDAS, and discuss limitations and future plans.
AB - In this article, we describe the free, open-source Python-based Space Physics Environment Data Analysis System (PySPEDAS), a platform for multi-mission, multi-instrument retrieval, analysis, and visualization of Heliophysics data. PySPEDAS currently contains load routines for data from 23 space missions, as well as a variety of data from ground-based observatories. The load routines are built from a common set of general routines that provide access to datasets in different ways (e.g., downloading and caching CDF files or accessing data hosted on web services), making the process of adding additional datasets simple. In addition to load routines, PySPEDAS contains numerous analysis tools for working with the dataset once it is loaded. We describe how these load routines and analysis tools are built by utilizing other free, open-source Python projects (e.g., PyTplot, cdflib, hapiclient, etc.) to make tools for space and solar physicists that are extremely powerful, yet easy-to-use. After discussing the code in detail, we show numerous examples of code using PySPEDAS, and discuss limitations and future plans.
KW - data analysis
KW - data visualization
KW - heliophysics
KW - magnetospherc physics
KW - python
KW - space physics
UR - https://www.scopus.com/pages/publications/85140438483
U2 - 10.3389/fspas.2022.1020815
DO - 10.3389/fspas.2022.1020815
M3 - Article
AN - SCOPUS:85140438483
SN - 2296-987X
VL - 9
JO - Frontiers in Astronomy and Space Sciences
JF - Frontiers in Astronomy and Space Sciences
M1 - 1020815
ER -