IntegerCluster utility that implements a simplistic hierarchical clustering algorithm.
This class solves the problem; given a series of integers find the smallest number of clusters (of a given min-max inclusive range of values) such that no range is wider than a given max.
If all values are within the given max, one cluster is produces, and if no two values are closer than max, then there will be as many clusters as there are unique values in the observed set of values.
The algorithm orders the set of observed values into an set of clusters of 0 size (min = max = value), and searches for the two adjacent clusters that produce the smallest resulting cluster if merged. If the smallest available merge is bigger than the max, the work is done. If the range is smaller than the max, the merged cluster replaces the two inputs. The algorithm now loops back to check for the next two adjacent clusters with the smallest distance.
The implementation is primarily intended for a fairly small number of observations/clusters as the final step of mapping observations to clusters search (binary search) for a cluster per value. To use this class with larger data sets, it would be better to keep a map from observations to clusters.
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