Computational analysis has become ubiquitous within the Space Physics community. Many scientists have devoted significant time to the development of quality data access, management, and analysis tools in an effort to address issues with research reproducibility and lower barriers to scientific collaboration. Python has become a particularly popular language for scientific analysis in the space physics community, as it is free to use, contains easily searchable repositories for publicly available tools, is designed to interface with popular computationally efficient compiled languages (C and Fortran), and can read data sets produced by other popular (but proprietary) scientific analysis tools.
The goals of this Frontiers Research Topic are:
1) to publish Python packages available for use within the space physics community, including packages aimed at research in planetary physics, solar physics, space weather, and the Earth’s thermosphere, ionosphere, and magnetosphere,
2) to highlight scientific advances made possible by established Python packages, and
3) demonstrate new techniques in Python that are potentially useful to the broader space physics community.
The scope of this collection aims to present the most recent advances, algorithms, and packages implemented in Python to support the Space Physics community. The articles may be either a full paper or a communication based on your own work in this area, a focused review on science highlights from a particular Python package, or a focused review article on another aspect of this subject. Submissions of any of the standard article types (https://www.frontiersin.org/journals/astronomy-and-space-sciences\#article-types) will be considered. We would like to draw authors attention to Methods and Technology and Code formats, which may be particularly appropriate for describing python - for these article types new scientific results are welcome but not required.
Computational analysis has become ubiquitous within the Space Physics community. Many scientists have devoted significant time to the development of quality data access, management, and analysis tools in an effort to address issues with research reproducibility and lower barriers to scientific collaboration. Python has become a particularly popular language for scientific analysis in the space physics community, as it is free to use, contains easily searchable repositories for publicly available tools, is designed to interface with popular computationally efficient compiled languages (C and Fortran), and can read data sets produced by other popular (but proprietary) scientific analysis tools.
The goals of this Frontiers Research Topic are:
1) to publish Python packages available for use within the space physics community, including packages aimed at research in planetary physics, solar physics, space weather, and the Earth’s thermosphere, ionosphere, and magnetosphere,
2) to highlight scientific advances made possible by established Python packages, and
3) demonstrate new techniques in Python that are potentially useful to the broader space physics community.
The scope of this collection aims to present the most recent advances, algorithms, and packages implemented in Python to support the Space Physics community. The articles may be either a full paper or a communication based on your own work in this area, a focused review on science highlights from a particular Python package, or a focused review article on another aspect of this subject. Submissions of any of the standard article types (https://www.frontiersin.org/journals/astronomy-and-space-sciences\#article-types) will be considered. We would like to draw authors attention to Methods and Technology and Code formats, which may be particularly appropriate for describing python - for these article types new scientific results are welcome but not required.
