Use saturation-weighted effective sink in destination sampling

[FlxPo]

This PR aligns destination sampling with saturation dynamics already used in programme utility evaluation, and removes redundant remaning sink computations. See #266.

Changes

• state_initializer.py

  • Removed sink_available creation.
  • Sink schema now: ["to", "motive", "sink_capacity", "k_saturation_utility"].

• state_updater.py

  • Removed sink_available recomputation/output in get_new_sinks.
  • Kept saturation update via k_saturation_utility.

• destination_sequence_sampler.py

  • Replaced hard-availability logic with soft saturation-weighted mass:
    effective_sink = sink_capacity * k_saturation_utility * prob
  • Replaced all sampling opportunity uses:
    • p_to normalization now uses effective_sink
    • bin aggregation now sums effective_sink
    • radiation cumulative s_ij now uses effective_sink

• Updated related docstrings.

Notes

This keeps saturation active in both destination proposal and programme utility scoring.
No behavior change to external interfaces; this is an internal consistency cleanup.

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 70.42%. Comparing base (aacd80a) to head (84dc7d3).
⚠️ Report is 2 commits behind head on main.

Additional details and impacted files

@@           Coverage Diff           @@
##             main     #267   +/-   ##
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  Coverage   70.42%   70.42%           
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  Files          56       56           
  Lines        2424     2424           
=======================================
  Hits         1707     1707           
  Misses        717      717           

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