cayleypy.create_graph

cayleypy.create_graph(*, generators_permutations: list[list[int]] | Tensor | ndarray | None = None, generators_matrices: list[MatrixGenerator | list | ndarray] | None = None, generator_names: list[str] | None = None, name: str = '', central_state=None, make_inverse_closed: bool = False, **kwargs) → CayleyGraph[source]

Creates CayleyGraph.

All arguments are optional, but one of these must be specified: generators_permutations, generators_matrices, name.

Additional arguments may be passed via kwargs:

  • when creating graph by name, other parameters of the graph (such as “n”) that will be passed to prepare_graph,

  • any arguments that are accepted by CayleyGraph constructor (e.g. verbose=2).r.

This function allows to create graphs in a uniform way. It is useful when you want to specify graph type and parameters in a config and have the same code handling different configs.

This is not recommended in most cases. Instead, create CayleyGraphDef using one of library classes and then pass it to CayleyGraph constructor.

Parameters:

  • generators_permutations – List of generating permutations.

  • generators_matrices – List of generating n*n matrices.

  • generator_names – Names of the generators.

  • name – the name of the graph. If generators are not explicitly specified, this will be used to create graph, see prepare_graph source for supported names.

  • central_state – central state of the graph.

  • make_inverse_closed – if generators are not inverse-closed and make_inverse_closed=True, adds inverse generators to make set of generators inverse-closed.

Returns:

created CayleyGraph.