chaste_codegen

chaste_codegen converts CellML models into C++ code for use in computational electrophysiology simulations.

Key Features:

• CellML parsing and manipulation: Uses the cellmlmanip Python library to read and manipulate CellML models.
• C++ code generation via templating: Employs templating techniques to generate C++ code for integration into the Chaste (Cancer, Heart, and Soft Tissue Environment) C++ library.
• Analytic Jacobian generation: Produces analytic Jacobians without relying on proprietary software to improve numerical solver performance.
• Singularity detection and handling: Identifies singularities in equations and applies automatic linear approximations to mitigate numerical issues.
• Nonlinear and stiff ODE support: Targets nonlinear systems comprising tens or hundreds of ordinary differential equations and numerous parameters.
• Chaste integration for tissue coupling: Generates code that can be run in isolation or as part of coupled tissue simulations within Chaste.
• Python 3 implementation: Redeveloped in Python 3 as the successor to PyCML.

Scientific Applications:

• Computational electrophysiology: Enables simulation of the electrical behavior of various cell types using CellML-derived models.
• Tissue and multicellular simulations: Supports incorporation of cellular models into coupled tissue-level simulations in Chaste.
• Stiff system simulation and stability: Improves simulation efficiency and stability for stiff electrophysiological models via analytic Jacobians and singularity handling.
• Model translation and reuse: Facilitates translation of CellML models into portable C++ implementations for reuse across simulation environments.

Methodology:

Reads and manipulates CellML models with the cellmlmanip Python library.
Applies templating techniques to generate C++ code targeted to the Chaste C++ library.
Generates analytic Jacobians and detects singularities, applying linear approximations where needed.
Implemented in Python 3 as a redevelopment of PyCML.