GeospaceLAB: Python package for managing and visualizing data in space physics
GeospaceLAB: Python package for managing and visualizing data in space physics
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DOI：
10.3389/fspas.2022.1023163
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发表时间：
2022-12
期刊：
影响因子：
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通讯作者：
L. Cai;A. Aikio;A. Kullen;Yue Deng;Yongliang Zhang;Shunrong Zhang;I. Virtanen;H. Vanhamäki
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文献类型：
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作者：
L. Cai;A. Aikio;A. Kullen;Yue Deng;Yongliang Zhang;Shunrong Zhang;I. Virtanen;H. Vanhamäki
在空间物理界，处理和合并来自各种来源的观测和建模数据是一项艰巨的任务，因为这些数据往往具有不同的格式，并使用不同的坐标系。Python包GeospaceLAB的开发旨在提供一个统一的标准化框架来处理数据。该软件包由六个核心模块组成，包括作为数据管理器的DataHub，用于生成出版质量数字的Visualization，用于DataHub和Visualization的高级接口的Express，用于坐标系转换的SpaceCoordinateSystem，用于各种实用程序的PLAN，以及用于首选项的Configuration。核心模块构成了空间物理数据下载、存储、后处理和可视化的标准化框架。采用面向对象的设计方法，使得GeospaceLAB的核心模块易于修改和扩展。到目前为止，GeospaceLAB可以处理来自9个数据库的20多种数据产品，未来的数量还将增加。数据源包括，例如，EISCAT非相干散射雷达，DMSP，SWARM和Grace卫星，OMNI太阳风数据和GITM模拟测量。此外，该软件包还为用户提供了一个添加自己的数据产品的接口。因此，研究人员可以很容易地收集，联合收割机，并查看多种数据，为他们的工作使用GeospaceLAB。将来自不同来源的数据结合起来，将有助于更好地理解所研究现象的物理学，并可能导致新的发现。GeospaceLAB是一个开源软件，托管在GitHub上。我们欢迎社会各界人士为其未来发展作出贡献。
In the space physics community, processing and combining observational and modeling data from various sources is a demanding task because they often have different formats and use different coordinate systems. The Python package GeospaceLAB has been developed to provide a unified, standardized framework to process data. The package is composed of six core modules, including DataHub as the data manager, Visualization for generating publication quality figures, Express for higher-level interfaces of DataHub and Visualization, SpaceCoordinateSystem for coordinate system transformations, Toolbox for various utilities, and Configuration for preferences. The core modules form a standardized framework for downloading, storing, post-processing and visualizing data in space physics. The object-oriented design makes the core modules of GeospaceLAB easy to modify and extend. So far, GeospaceLAB can process more than twenty kinds of data products from nine databases, and the number will increase in the future. The data sources include, e.g., measurements by EISCAT incoherent scatter radars, DMSP, SWARM, and Grace satellites, OMNI solar wind data, and GITM simulations. In addition, the package provides an interface for the users to add their own data products. Hence, researchers can easily collect, combine, and view multiple kinds of data for their work using GeospaceLAB. Combining data from different sources will lead to a better understanding of the physics of the studied phenomena and may lead to new discoveries. GeospaceLAB is an open source software, which is hosted on GitHub. We welcome everyone in the community to contribute to its future development.