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It would be nice to be able to get the induced norm from a particular metric space (provided it has a vector-space structure on it). I'm not sure what the API would look like but perhaps evaluating a distance function on only one array runs the norm instead. Something like
v =rand(100)
@asserteuclidean(v) ==euclidean(v, zero(v))
Right now, running something like euclidean(v, zero(v)) is slower than LinearAlgebra.norm(v), and it would be good to have the possibility to use the Distances API consistently instead of swapping between norm(v) and evaluate(dist, v, 0) for euclidean and other metrics.
The text was updated successfully, but these errors were encountered:
It would be nice to be able to get the induced norm from a particular metric space (provided it has a vector-space structure on it). I'm not sure what the API would look like but perhaps evaluating a distance function on only one array runs the norm instead. Something like
Right now, running something like
euclidean(v, zero(v))
is slower thanLinearAlgebra.norm(v)
, and it would be good to have the possibility to use theDistances
API consistently instead of swapping betweennorm(v)
andevaluate(dist, v, 0)
for euclidean and other metrics.The text was updated successfully, but these errors were encountered: