Degree Corrected SBM

src/algorithms/__init__.py

@@ -7,3 +7,4 @@
 from .traditional.Spectral import Spectral
 from .traditional.SBM_em import SBM_em
 from .traditional.SBM_metropolis import SBM_metropolis
+from .traditional.DCSBM import DCSBM

src/algorithms/traditional/DCSBM.py

@@ -0,0 +1,39 @@
+import sys
+from graph import Graph
+from algorithms.Algorithm import Algorithm
+
+sys.path.append('..\\library\\')
+import pysbm
+
+
+class DCSBM(Algorithm):
+	"""Stochastic block model clustering algorithm
+	"""
+
+	def __init__(self, graph: Graph, num_clusters: int, iterations: int = 10000):
+		"""Constructor method
+		"""
+		super(DCSBM, self).__init__(graph)
+		self.iterations: int = iterations
+		self.num_clusters: int = num_clusters
+		self.graph = graph
+
+	def run(self) -> None:
+		"""Runs the algorithm
+		"""
+		degree_corrected_partition = pysbm.NxPartition(
+            graph=self.graph.nx_graph, 
+            number_of_blocks=self.num_clusters)
+		degree_corrected_objective_function = pysbm.DegreeCorrectedUnnormalizedLogLikelyhood(is_directed=False)
+		degree_corrected_inference = pysbm.PeixotoInference(self.graph.nx_graph, degree_corrected_objective_function, degree_corrected_partition)
+		degree_corrected_inference.infer_stochastic_block_model()
+
+		self.clusters = [node[1] for node in sorted(degree_corrected_inference.partition.partition.items())]
+
+	def __str__(self):
+		"""Returns the string representation of the algorithm object
+
+		:return: String representation of the algorithm object
+		:rtype: str
+		"""
+		return "SBM Metropolis algorithm object"

src/algorithms/traditional/__init__.py

@@ -4,3 +4,4 @@
 from .SBM_metropolis import SBM_metropolis
 from .SBM_em import SBM_em
 from .Spectral import Spectral
+from .DCSBM import DCSBM

src/main.py

@@ -5,7 +5,7 @@
 import numpy as np
 
 from graph import Graph
-from algorithms import GAE, ARGA, MVGRL, Markov, Louvain, Leiden, SBM_em, SBM_metropolis, Spectral
+from algorithms import GAE, ARGA, MVGRL, Markov, Louvain, Leiden, SBM_em, SBM_metropolis, Spectral, DCSBM
 
 
 def main():
@@ -85,6 +85,8 @@ def main():
 			algo = SBM_metropolis(graph, num_clusters=args.num_clusters, iterations=args.iterations)
 		case "sbm_em":
 			algo = SBM_em(graph, num_clusters=args.num_clusters, iterations=args.iterations)
+		case "dcsbm":
+			algo = DCSBM(graph, num_clusters=args.num_clusters, iterations=args.iterations)
 		case "spectral":
 			algo = Spectral(graph, num_clusters=args.num_clusters)
 		case _: