标题： AstronomyCalc: 用于教学天文学计算和数据分析方法的 Python 工具包 显示英文标题

标题： AstronomyCalc: A python toolkit for teaching Astronomical Calculations and Data Analysis methods

摘要： 理解天体物理和宇宙学过程因其复杂性以及缺乏直观类比而具有挑战性。 为了解决这一问题，我们介绍了\texttt{天文学计算}，这是一个专门设计用于通过整合理论物理学与实际天文学数据分析方法来辅助大学教学的Python软件包。 该软件包使学生能够解决关键的宇宙学计算（例如弗里德曼方程），探索各种模型，并可视化参数变化如何影响宇宙动力学。 它包括生成合成天文数据（如Ia型超新星测量）的工具，并支持对公开可用的数据集（包括Pantheon+和SPARC星系数据库）进行分析。 高级算法的简化实现（如蒙特卡罗马尔可夫链）允许学生参与当代研究中使用的数据分析技术。 此外，\texttt{天文学计算}将持续更新更多工具和更用户友好的Jupyter笔记本，使其成为不断发展的一个教育资源，以培养天体物理学和宇宙学的概念理解和实践技能。 显示英文摘要

摘要： Understanding astrophysical and cosmological processes can be challenging due to their complexity and lack of intuitive analogies. To address this, we present \texttt{AstronomyCalc}, a Python package specifically designed to aid university-level teaching by integrating theoretical physics with practical astronomical data analysis methods. The package enables students to solve key cosmological calculations, such as the Friedmann equations, and explore various models while visualizing how parameter variations affect cosmic dynamics. It includes tools for generating synthetic astronomical data, such as Type Ia supernova measurements, and supports analysis of publicly available datasets, including Pantheon+ and the SPARC galaxy database. Simplified implementations of advanced algorithms, such as Monte Carlo Markov Chains, allow students to engage with data analysis techniques used in contemporary research. Additionally, \texttt{AstronomyCalc} will be consistently updated with more tools and user-friendly Jupyter notebooks, making it a continually evolving educational resource for developing conceptual understanding and practical skills in astrophysics and cosmology.