Gsm v2

[emuskardin]

TODO

add_labeled_sequence aggregates intermediate steps under unknown_output (DataHandler.py:100-110) and, when a later sequence resolves that output, only remaps transitions — the handler data is left alone. So count-based handlers on labeled_sequences split counts across two keys:

labeled: {'a': {<unknown_output>: 1, False: 1}}   vs   io_traces: {'a': {False: 2}}

shadow_pta keeps a stale unknown_output key the same way. Fixing it properly needs a "output resolved" hook on DataHandler (the remap is handler-specific), which is more than a minimal change, so I left it: it's captured as @unittest.expectedFailure in test_gsm_data_handler.py:46 with the cause in a comment. It flips to an unexpected success once fixed.

- GsmAlgorithms.py mealy sentinel leak: run_EDSM(..., automaton_type='mealy') on data that isn't prefix-closed (violates the documented precondition) doesn't raise — it silently produces a MealyMachine with unknown_output's sentinel object as a real transition's output. Low priority since it's already documented as unsupported, but corrupting silently instead of raising seems worth a guard.

Ensure, also in tests / run exaustive that I have added, that DFA and Moore learning works also with non-prefix closed data

[zwergziege]

regarding 1: since having counts for non-prefix-closed deterministic data is not all that useful, i suggest simply raising an exception if unknown_output is encountered in the data handler. if somebody really needs it, they can implement it themselves.

regarding 2: i think this behavior is perfectly fine. the classic RPNI version also does not raise on None outputs. a warning maybe.