Generalized Smith-Kirby Iterated Learning Models in Python
It is recommended to install all dependencies and run skILMpy with uv. Instructions for downloading uv can be found here: https://docs.astral.sh/uv/ After uv is installed, and this repository has been cloned to your system set your working directory accordingly.
In the directory for skILMpy on your system run uv sync, in order to install all the required dependencies. Followed by uv run ilm.py to run the program.
Any commands must have uv run before the ilm.py script and its options and arguments are written.
relies heavily on, and absolutely requires, numpy as a prerequisite.
You should install numpy and these other dependencies through uv
numpy,pandas,ply,distance,sympy
ILMpy comes with an executable inside the bin subdirectory to the
installation source package, a UNIX-compatible script called ilm.py.
Try running the --help option to the executables after installation and
for a command-line example.
Programmers may use the executable in bin as a guide and template for how to program against the cmcpy API.
Some documentation of the cmcpy API
See CHANGES.txt for version-related changes.