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pythonnumpygreedy

Greedy algorithm, numpy, matrix, explantation

Distance

from 0 to 1 is 1.0

from 1 to 2 is 3.0

from 0 to 2 is 2.0

D = [

     [ 0, 1.0, 2.0],
     [ 1.0, 0, 3.0],
     [ 2.0, 3.0, 0]
]

So I've got a matrix which looks like one above.

But I can't quite see why those measures are like the ones given at the top of my post?

How is distance from 0 to 1 is 1.0?

Solution

  • Ah... this is a pre-loaded distance array.

    Say for instance that point 0 is (5,0), point 1 is (4,0), and point 2 is (7,0). Then D is preloaded with inter-point distances, ie D[from_point][to_point] = distance(from_point, to_point).

    Then you can refer to the matrix rather than having to recalculate distances.