One major challenge in science is to make all results potentially reproducible. Thus, along with the raw data, every step from basic processing of the data, evaluation, to the generation of the figures, has to be documented as clearly as possible. While there are many programming libraries that cover the basic processing and plotting steps (e.g. Matplotlib in Python), no library yet addresses the reproducible composing of single plots into meaningful figures for publication. Thus, up to now it is still state-of-the-art to generate publishable figures using image-processing or vector-drawing software leading to unwanted alterations of the presented data in the worst case and to figure quality reduction in the best case. Pylustrator a open source library based on the Matplotlib aims to fill this gap and provides a tool to easily generate the code necessary to compose publication figures from single plots. It provides a graphical user interface where the user can interactively compose the figures. All changes are tracked and converted to code that is automatically integrated into the calling script file. Thus, this software provides the missing link from raw data to the complete plot published in scientific journals and thus contributes to the transparency of the complete evaluation procedure.
翻译:科学方面的一个主要挑战是使所有结果都有可能复制。 因此,与原始数据一样,从数据的基本处理、评价到数据生成的每一个步骤都必须尽可能清楚地记录下来。 虽然有许多程序库覆盖基本处理和绘图步骤(例如Python的Matplotlib),但还没有一个图书馆能够解决将单个图块复制成有意义的数字的问题。因此,到目前为止,利用图像处理或矢量拖动软件生成可公布的数字,导致最坏情况中出现的数据的不必要改变和最佳情况中质量的下降,仍然是最先进的。根据Matplotlib 建立一个开放源库,以填补这一空白,并提供一个工具,方便地生成从单一图中编制出版数字所需的代码。它提供了一个图形用户界面,用户可以对数字进行互动式的配置。所有变化都跟踪并转换成自动纳入调用脚本文档的代码。 因此,该软件提供了从原始数据到科学期刊中公布的全部图案的完整图案的完整流程的缺失链接。