pyerrors: A python framework for error analysis of Monte Carlo data

We present the pyerrors python package for statistical error analysis of Monte Carlo data. Linear error propagation using automatic differentiation in an object oriented framework is combined with the Γ-method for a reliable estimation of autocorrelation times. Data from different sources can easily be combined, keeping the information on the origin of error components intact throughout the analysis. pyerrors can be smoothly integrated into the existing scientific python ecosystem which allows for efficient and compact analyses.我们推出了用于蒙特卡洛（Monte Carlo）数据统计误差分析的pyerrors Python软件包。该软件将面向对象框架下结合自动微分的线性误差传播方法，与用于可靠估计自相关时间的Γ方法相结合。其支持轻松整合来自不同数据源的数据，并可在整个分析过程中完整保留误差分量来源的相关信息。pyerrors可无缝集成至现有科学Python生态系统，从而实现高效且简洁的数据分析工作。