[ENH] Cluster initialisation refactor

[chrisholder]

[ENH] Centralise clustering initialisation logic and refactor tests

Reference Issues/PRs

What does this implement/fix? Explain your changes.

This PR introduces a new file, _cluster_initialisation.py, which moves the initialisation logic out of the individual clusterers and into a centralised location. This refactoring makes the code easier to maintain and ensures consistency across different clustering algorithms.

In addition to centralising the logic, I have:

1. Updated Tests: Refactored and extended the tests for ElasticSOM and TimeSeriesKMedoids to ensure that the new centralised logic is working correctly and that all initialisation methods are fully tested.
2. Enhanced Functionality: Added support for value-based initialisation in TimeSeriesKMedoids (passing np.ndarray of values instead of indexes), which is now handled seamlessly by the new resolve_center_initialiser function.

Does your contribution introduce a new dependency? If yes, which one?

No.

Any other comments?

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I have added the following labels to this PR based on the title: [ enhancement ].
I have added the following labels to this PR based on the changes made: [ clustering ]. Feel free to change these if they do not properly represent the PR.

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[TonyBagnall]

need to tidy up the _initialisation file and a bit of the logic, but nice work