From 72000b329c54fbed64bd4c5b18ffa00738ec99be Mon Sep 17 00:00:00 2001
From: Yassin <aliyassin4@hotmail.com>
Date: Tue, 9 May 2023 22:53:59 +0200
Subject: [PATCH] Updating modularity
---
netbone/structural/modulairy_backbone.py | 9 ++-------
1 file changed, 2 insertions(+), 7 deletions(-)
diff --git a/netbone/structural/modulairy_backbone.py b/netbone/structural/modulairy_backbone.py
index c0a7228..4c2ccbd 100644
--- a/netbone/structural/modulairy_backbone.py
+++ b/netbone/structural/modulairy_backbone.py
@@ -1,6 +1,7 @@
import community.community_louvain as community
import heapq
import operator
+import math
import networkx as nx
import numpy as np
from scipy.sparse import csr_matrix
@@ -29,7 +30,6 @@ def orderCommunities(c):
return partition
-
def communityInfo(c, partition):
print('Number of partitions: ', len(partition))
l = list()
@@ -43,9 +43,6 @@ def communityInfo(c, partition):
print()
print()
-
-
-
def getSparseA(g):
return nx.to_scipy_sparse_matrix(g)
# return nx.to_scipy_sparse_array(g)
@@ -163,18 +160,16 @@ def get_top_k_best_nodes(dict_centrality, k):
return top_k, first_nodes
def modularity_backbone(data, node_fraction):
- is_graph=False
if isinstance(data, pd.DataFrame):
g = nx.from_pandas_edgelist(data, edge_attr='weight', create_using=nx.Graph())
elif isinstance(data, nx.Graph):
g = data.copy()
- is_graph=True
else:
print("data should be a panads dataframe or nx graph")
return
g1 = g.copy()
- k = len(g1)-round(len(g1)*node_fraction)
+ k = len(g1)-math.ceil(len(g1)*node_fraction)
communities = community.best_partition(g1, random_state=123)
modularity_value = community.modularity(communities, g1)
--
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