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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.28957 |
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Table of Contents:
- Informative data visualization methods are key to the clear and efficient communication of myriad forms of data. The PASTA Collaboration has made substantial contributions to the field of data visualization through $\mathtt{pastamarkers}$, a Python-based package that utilizes various types of pasta as data markers to create engaging plots. This work introduces $\mathtt{GF \ pastamarkers}$, an extension of $\mathtt{pastamarkers}$ that utilizes the tenuous structure of gluten free (GF) pasta to meet the needs of the GF population. The implementation of $\mathtt{GF \ pastamarkers}$ employs an exponential crumbling factor ($CF$), which benefits authors by encouraging clearer and more concise scientific articles, thereby leading to more effective manuscripts and proposals.