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Reading a graph from the web and running k-means clustering
Source code name: "graph_medusa_kmeans.py"
Programming language: Python
Topic: Data mining/Graphs
DMelt Version 1.8. Last modified: 01/29/2021. License: Pro
https://datamelt.org/code/cache/graph_medusa_kmeans_4824.py
To run this script using the DataMelt IDE,
copy the above URL link to the menu [File]→[Read script from URL] of the DMelt IDE.
from jhplot import *
http="https://datamelt.org/examples/data/"
print Web.get(http+"sample1_medusa.dat")
c=HMedusa()
c.loadFile("sample1_medusa.dat")
gg=c.getGraph()
c.visible() # show the graph
from medusa.georgios.ClusteringAlgorithms import KMeans2
num_of_clusters=6 # run k-means with 6 clusters
kmeans = KMeans2(num_of_clusters, gg)
kmeans.runKMeans();
nodes_clusters=kmeans.getClusterMap()
print kmeans.getReport()
from medusa.georgios.Layouts import Layouts
Layouts.Apply_Kmeans_Clustering(gg, c.getPanel(), num_of_clusters) # asks for 6 clusters
c.update()
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