DOI: 10.5281/zenodo.15411117
title: Supplemetary data for Advancing the Morphometric Analysis of Early Medieval Slavic Pottery: A Semi-Automated 3D Toolset for Virtual Sections

description: MeshSectionToolset Dataset

An open-source toolkit for archaeologists and researchers to explore 3D artifacts, especially pottery. This project simplifies morphometric analysis by leveraging Blender's Geometry Nodes and Python scripting.This code is part of the article: Košťál, M. - Nosek, V. - Macháček, J. 2025. Advancing the Morphometric Analysis of Early Medieval Slavic Pottery: A Semi-Automated 3D Toolset for Virtual Sections. Journal of Archaeological Science https://doi.org/10.1016/j.jas.2025.106314

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Description

MeshSectionToolset facilitates the semi-automated generation of virtual cross-sections for 3D models. Designed for non-standard, asymmetrical, handmade artifacts like pottery, it extracts morphometric data and exports it for further analysis. The toolset is optimized for speed, precision, and accessibility to researchers with minimal programming experience. It is based on the Blender 4.3 software. This archive contains two subfolders(ZIP archives):

Data_extraction_blend_files - `Slicing_tool_pottery.blend` - file with geometry nodes setup to perform 3D model to 2D sections (polylines) -` Extract_modd_data_v2.py` - python file for extraction of data from GeometryNodes spreadsheets into the .txt file table (use /t as separator). It is mandatory to run this  from the "Scripting" tab in the Blender software (see the one of the example files)  - `Vertical_att_only_extraction_example.blend` - example file with modifiers and preloaded "Extract_modd_data_v2.py", used to extract all the data for the article. In general it can be used without applycation of Slicing_tool_pottery modifier, but at a cost of slower performance (depends on your hardware). - `Slicing_tool_pottery_COHL_att_example.blend` - example file with possible extraction of COHL attribute together with Slicing_tool_pottery modifier and with preloaded "Extract_modd_data_v2.py"

R_code_and_visualization

 - `JASC24-639_PCoA_analysis_used.R` - the R code used for calculation of the PCoA based on the extracted datasets - `Folder data/JASC24-639_Data_PCoA_used.txt` - dataset used in the article: (article_doi) - `Folder data/Hindex dataset.csv` - results of PCoA analysis, that can be used for pots visualization in All_pots_decimated_for_PCoA_visualization.blend - `Folder data/Technology similarity.csv` - results of PCoA analysis, that can be used for pots visualization in All_pots_decimated_for_PCoA_visualization.blend - `All_pots_decimated_for_PCoA_visualization.blend` - example blend file with decimated 3D models (used only for visualizations) - `Load_CSV_file_with_coordinates.py` - python file for loading of the data from the datasets (in .txt format, extracted by "Extract_modd_data_v2.py"). It is mandatory to run this  from the "Scripting" tab in the Blender software (see the All_pots_decimated_for_PCoA_visualization.blend)   

**Note**: The Numpy and Pandas python libraries must be installed in the python libraries (look at the end of the README file for tips). Also, basic knowledge of 3D concepts and Blender software is recommended