>>> from commonnn import cluster
>>> # 2D data points (list of lists, 12 points in 2 dimensions)
>>> data_points = [ # point index
... [0, 0], # 0
... [1, 1], # 1
... [1, 0], # 2
... [0, -1], # 3
... [0.5, -0.5], # 4
... [2, 1.5], # 5
... [2.5, -0.5], # 6
... [4, 2], # 7
... [4.5, 2.5], # 8
... [5, -1], # 9
... [5.5, -0.5], # 10
... [5.5, -1.5], # 11
... ]
>>> clustering = cluster.Clustering(data_points)
>>> clustering.fit(radius_cutoff=1.5, similarity_cutoff=1, v=False)
>>> clustering.labels
array([1, 1, 1, 1, 1, 0, 0, 0, 0, 2, 2, 2])
