Code for Paper "Structural Sculpting: Making Inverse Modelling Generate and Deal with Variable Structures"

This data repository contains the code that I used to generate the data for my paper "Structural Sculpting: Making Inverse Modelling Generate and Deal with Variable Structures" as well as the data used for the subsequent analysis.<br>The repository contains two files:"structural-sculpting.zip" containing the source code (.py), the edited NetLogo model (.nlogo, for NetLogo 6.1.1) used for the paper, and the jupyter notebook (.ipynb) used for the analysis. "history.zip" containing the data (.csv) generated through the source code. Each .csv file has the headers candidate_id, the actions before and after mutation, the mutation decided on, the fitness values, the parametrisation for the run and the run number, the observed variable "number_of_households_owning_product_1" and the error of the comparison of the observed variable with the data.本数据集仓库包含了我为论文《结构塑形：使逆建模（Inverse Modelling）能够生成并处理可变结构》（Structural Sculpting: Making Inverse Modelling Generate and Deal with Variable Structures）生成实验数据所用的代码，以及后续分析所需的数据集。<br>本仓库包含两个压缩文件：其一为`structural-sculpting.zip`，内含论文所用的源代码（.py格式）、编辑后的NetLogo模型（.nlogo格式，适配NetLogo 6.1.1版本），以及用于分析的Jupyter Notebook（.ipynb格式）；其二为`history.zip`，其中包含通过源代码生成的逗号分隔值（CSV）文件。每个CSV文件均包含以下表头字段：候选ID（candidate_id）、突变前后的操作、选定的突变方案、适应度值（fitness values）、本次运行的参数配置以及运行编号、观测变量‘拥有产品1的家庭数量’（number_of_households_owning_product_1），以及该观测变量与参考数据比对后的误差值。