Heron is a Python package for producing surrogate models for computationally intensive functions, such as numerical relativity waveforms.
This version of heron is implemented slightly differently to older versions, and should allow for a greater degree of flexibility for using different GP libraries for the modelling, and to fit into analysis pipelines better than the earlier development versions.
This documentation is still being written, and you may find a few places either where documentation is missing, or where the formatting isn’t good. If you spot something which has clearly been missed in the documentation please open an issue on the git repository.
This package contains a number of different pre-baked waveform models, and the data which is required to reproduce them. It’s also fairly easy to use the existing framework to implement a new model, using the same training data as pre-supplied models, or using new training data.