digraphTCC2 = ga.Graph.from_networkx(digraphTCC)
clus = nx.square_clustering(digraphTCC2)
print(clus)

for i in clus:
print(i)

I've just found graphblas-algorithms as a way to speed up computations on a networkx graph, and I've integrated it into my work for finding the square clustering coefficient of a graph. The speedup is immense, but I'm not sure how to interpret the result.

Based on the code snippet above (digraphTCC is a valid networkx graph), the result of the function, clus prints out as
<graphblas_algorithms.classes.nodemap.NodeMap object at 0x00000206BC590550>.

I'm unaware how to interact with a NodeMap object, but when I iterate through it, the values seem to just be node labels. How should I interpret this result, and transform it into the dictionary of {node:clustering} that you would expect from the slow networkx version?

Thank you for your time!