11 """Define a metric on a list of floating point numbers based on their difference"""
13 def __init__(self, nums):
14 """Store the list of numbers to measure distances between"""
15 IMP.statistics.Metric.__init__(self,
"MyMetric%1%")
19 """Return the magnitude of the distance between the ith and jth number"""
20 return math.fabs(self.
_nums[i] - self.
_nums[j])
22 def get_number_of_items(self):
23 return len(self.
_nums)
26 mm =
MyMetric([random.uniform(0, 1)
for i
in range(0, 15)])
29 print cc.get_number_of_clusters()
PartitionalClustering * create_centrality_clustering(Embedding *d, double far, int k)
See IMP.statistics for more information.
Store data to be clustered for distance metric based algorithms.