louvain -> leiden (modern)

.gitignore

@@ -160,3 +160,5 @@ cython_debug/
 .notebooks/figure/
 
 output/
+
+/notebooks/figures/

README.md

@@ -1,6 +1,6 @@
 # Advanced Graph Clustering 
 
-This project focuses on the study and implementation of various graph clustering techniques, covering traditional techniques such as Spectral Clustering and Louvain Method, as well as deep graph clustering methods like Graph Autoencoders. The project aims to provide a comprehensive overview of graph clustering algorithms and their applications in network analysis.
+This project focuses on the study and implementation of various graph clustering techniques, covering traditional techniques such as Spectral Clustering and Leiden Method, as well as deep graph clustering methods like Graph Autoencoders. The project aims to provide a comprehensive overview of graph clustering algorithms and their applications in network analysis.
 
 ## Table of Contents
 
@@ -49,10 +49,10 @@ py main.py --help
 
 ## Implemented Techniques
 - Traditional Clustering Techniques:
-  - Louvain Method
-  - Markov Clustering Algorithm
   - Spectral Clustering
   - Stochastic Block Models
+  - Markov Clustering Algorithm
+  - Leiden Method
 - Deep Graph Clustering:
   - Graph Autoencoder (GAE)
   - Adversarially Regularized Graph Autoencoder (ARGA)

src/algorithms/__init__.py

@@ -3,6 +3,6 @@
 from .deep.GAE import GAE
 from .deep.ARGA import ARGA
 from .traditional.Markov import Markov
-from .traditional.Louvain import Louvain
+from .traditional.Leiden import Leiden
 from .traditional.Spectral import Spectral
 from .traditional.SBM import SBM

src/algorithms/traditional/Louvain.py → src/algorithms/traditional/Leiden.py

@@ -1,17 +1,17 @@
-from cdlib.algorithms import louvain
+from cdlib.algorithms import leiden
 
 from algorithms.Algorithm import Algorithm
 from .utils import extract_clusters_from_communities_list
 
 
-class Louvain(Algorithm):
+class Leiden(Algorithm):
 	"""Louvain clustering algorithm
 	"""
 
 	def run(self) -> None:
 		"""Runs the algorithm
 		"""
-		clustering = louvain(self.graph.nx_graph)
+		clustering = leiden(self.graph.nx_graph)
 		self.clusters = extract_clusters_from_communities_list(clustering.communities)
 
 	def __str__(self):
@@ -20,4 +20,4 @@ def __str__(self):
 		:return: String representation of the algorithm object
 		:rtype: str
 		"""
-		return "Louvain algorithm object"
+		return "Louvain algorithm object"

src/algorithms/traditional/__init__.py

@@ -1,4 +1,4 @@
-from .Louvain import Louvain
+from .Leiden import Leiden
 from .Markov import Markov
 from .SBM import SBM
 from .Spectral import Spectral

src/main.py

@@ -5,7 +5,7 @@
 import numpy as np
 
 from graph import Graph
-from algorithms import AdaGAE, GAE, ARGA, Markov, Louvain, SBM, Spectral
+from algorithms import AdaGAE, GAE, ARGA, Markov, Leiden, SBM, Spectral
 
 
 def main():
@@ -66,7 +66,7 @@ def main():
 	elif args.algorithm == "markov":
 		algo = Markov(graph, expansion=args.expansion, inflation=args.inflation, iterations=args.iterations)
 	elif args.algorithm == "louvain":
-		algo = Louvain(graph)
+		algo = Leiden(graph)
 	elif args.algorithm == "sbm":
 		algo = SBM(graph)
 	elif args.algorithm == "spectral":