cellmlmanip and chaste_codegen: automatic CellML to C++ code generation with fixes for singularities and automatically generated Jacobians

Hendrix, Maurice; Clerx, Michael; Tamuri, Asif U; Keating, Sarah M; Johnstone, Ross H; Cooper, Jonathan; Mirams, Gary R

Abstract

Hundreds of different mathematical models have been proposed for describing electrophysiology of various cell types. These models are quite complex (nonlinear systems of typically tens of ODEs and sometimes hundreds of parameters) and software packages such as the Cancer, Heart and Soft Tissue Environment (Chaste) C++ library have been designed to run simulations with these models in isolation or coupled to form a tissue simulation. The complexity of many of these models makes sharing and translating them to new simulation environments difficult. CellML is an XML format that offers a widely-adopted solution to this problem. This paper specifically describes the capabilities of two new Python tools: the cellmlmanip library for reading and manipulating CellML models; and chaste_codegen, a CellML to C++ converter. These tools provide a Python 3 replacement for a previous Python 2 tool (called PyCML) and they also provide additional new features that this paper describes. Most notably, they can generate analytic Jacobians without the use of proprietary software, and also find singularities occurring in equations and automatically generate and apply linear approximations to prevent numerical problems at these points.

Citation

Hendrix, M., Clerx, M., Tamuri, A. U., Keating, S. M., Johnstone, R. H., Cooper, J., & Mirams, G. R. (2022). cellmlmanip and chaste_codegen: automatic CellML to C++ code generation with fixes for singularities and automatically generated Jacobians. Wellcome Open Research, 6, Article 261. https://doi.org/10.12688/wellcomeopenres.17206.2

• Journal Article Type: Article
• Acceptance Date: Jun 15, 2022
• Online Publication Date: Jun 15, 2022
• Publication Date: Jun 15, 2022
• Deposit Date: Aug 10, 2022
• Publicly Available Date: Aug 17, 2022
• Journal: Wellcome Open Research
• Publisher: F1000 Research Ltd
• Peer Reviewed: Peer Reviewed
• Volume: 6
• Article Number: 261
• DOI: https://doi.org/10.12688/wellcomeopenres.17206.2
• Keywords: General Biochemistry, Genetics and Molecular Biology; Medicine (miscellaneous)
• Public URL: https://nottingham-repository.worktribe.com/output/8501563
• Publisher URL: https://wellcomeopenresearch.org/articles/6-261