AsaPy is a custom-made Python library designed to simplify and optimize the analysis of aerospace simulation data. Instead of introducing new methodologies, it excels in combining various established techniques, creating a unified, specialized platform. It offers a range of features, including the design of experiment methods, statistical analysis techniques, machine learning algorithms, and data visualization tools. AsaPy's flexibility and customizability make it a viable solution for engineers and researchers who need to quickly gain insights into aerospace simulations. AsaPy is built on top of popular scientific computing libraries, ensuring high performance and scalability. In this work, we provide an overview of the key features and capabilities of AsaPy, followed by an exposition of its architecture and demonstrations of its effectiveness through some use cases applied in military operational simulations. We also evaluate how other simulation tools deal with data science, highlighting AsaPy's strengths and advantages. Finally, we discuss potential use cases and applications of AsaPy and outline future directions for the development and improvement of the library.

翻译：AsaPy是一个定制的Python库，旨在简化和优化航空航天仿真数据的分析。它并非引入新方法，而是擅长整合多种成熟技术，构建统一的专用平台。该库提供一系列功能，包括实验设计方法、统计分析技术、机器学习算法和数据可视化工具。AsaPy的灵活性和可定制性使其成为需要快速洞察航空航天仿真结果的工程师和研究人员的可行解决方案。AsaPy构建于流行的科学计算库之上，确保了高性能和可扩展性。本文概述了AsaPy的关键特性与能力，随后阐述了其架构，并通过在军事作战仿真中的应用案例展示了其有效性。我们还评估了其他仿真工具如何处理数据科学问题，突出了AsaPy的优势。最后，我们讨论了AsaPy的潜在用例与应用，并概述了该库未来开发与改进的方向。