Add a Python decomposition layer using NetworkX that partitions the
constraint graph into biconnected components (rigid clusters), orders
them via a block-cut tree, and solves each cluster independently.
Articulation-point bodies propagate as boundary conditions between
clusters.
New module kindred_solver/decompose.py:
- DOF table mapping BaseJointKind to residual counts
- Constraint graph construction (nx.MultiGraph)
- Biconnected component detection + articulation points
- Block-cut tree solve ordering (root-first from grounded cluster)
- Cluster-by-cluster solver with boundary body fix/unfix cycling
- Pebble game integration for per-cluster rigidity classification
Changes to existing modules:
- params.py: add unfix() for boundary body cycling
- solver.py: extract _monolithic_solve(), add decomposition branch
for assemblies with >= 8 free bodies
Performance: for k clusters of ~n/k params each, total cost drops
from O(n^3) to O(n^3/k^2).
220 tests passing (up from 207).
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