Reduce Leiden view memory during coarsening#31
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Avoid keeping a separate composed original-to-coarse mapping in ParallelLeidenView. CoarsenedGraphView can now build a new view from an existing coarsened view by composing the original-node mapping directly, so flattening can use the view's nodeMapping instead of a duplicated vector. Also replace dense per-thread cut-weight vectors with sparse unordered maps in move/refine phases. This avoids allocating storage sized to the full community upper bound for every worker when each node only touches a small subset of neighbor communities. Together these changes reduce peak memory use during iterative Leiden coarsening and refinement without changing the partitioning result.
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Avoid keeping a separate composed original-to-coarse mapping in ParallelLeidenView. CoarsenedGraphView can now build a new view from an existing coarsened view by composing the original-node mapping directly, so flattening can use the view's nodeMapping instead of a duplicated vector.
Also replace dense per-thread cut-weight vectors with sparse unordered maps in move/refine phases. This avoids allocating storage sized to the full community upper bound for every worker when each node only touches a small subset of neighbor communities.
Together these changes reduce peak memory use during iterative Leiden coarsening and refinement without changing the partitioning result.