Powerlaws #18
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Powerlaws #18
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nwlandry
reviewed
Dec 10, 2023
lcs/generative.py
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| @@ -128,3 +123,31 @@ def clustered_unipartite(n_groups, n_ind, my_p_dist, my_g_dist, **kwargs): | |||
| B = bipartite_graph(edge_list) | |||
| U = nx.projected_graph(B, projected_nodes) # create unipartite projection | |||
| return nx.adjacency_matrix(U).todense() | |||
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| def truncated_power_law_configuration(n, x_min, x_max, r, seed=None): | |||
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I think because we're doing so much post-processing, we could probably just modify this algo a little bit.
nwlandry
reviewed
Dec 10, 2023
lcs/generative.py
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| G = nx.configuration_model(degree_sequence) | ||
| G = nx.Graph(G) | ||
| G.remove_edges_from(nx.selfloop_edges(G)) | ||
| return G |
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A new branch for testing PS on configuration models.