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Loop Detection & Circular Economy Analysis

In system-wide (Leontief) mode, circular flows are represented implicitly. fastspa also supports explicit loop detection on the extracted path set.

Detect loops in extracted paths​

paths = spa.analyze(sector=42, depth=8)

loops = paths.loop_analysis()

print("Loop share:", loops.loop_share)
print("Top cycles:", loops.top_cycles(10))

Interpretation​

  • A loop is detected when a sector index repeats within a single path.
  • The analysis summarises each looping path using the first repeated sector encountered.

Feedback loop metrics​

loops.sector_participation provides a per-sector measure of participation in looping paths. This can be useful as a proxy for self-reinforcing circular dynamics.