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# standard imports
import typing
# external imports
import numpy as np
# bsfs imports
from bsfs.namespace import ns
# constants
EPS = 1e-9
# exports
__all__: typing.Sequence[str] = (
'DISTANCE_FU',
)
## code ##
def euclid(fst, snd) -> float:
"""Euclidean distance (l2 norm)."""
fst = np.array(fst)
snd = np.array(snd)
return float(np.linalg.norm(fst - snd))
def cosine(fst, snd) -> float:
"""Cosine distance."""
fst = np.array(fst)
snd = np.array(snd)
if (fst == snd).all():
return 0.0
nrm0 = np.linalg.norm(fst)
nrm1 = np.linalg.norm(snd)
return float(1.0 - np.dot(fst, snd) / (nrm0 * nrm1 + EPS))
def manhatten(fst, snd) -> float:
"""Manhatten (cityblock) distance (l1 norm)."""
fst = np.array(fst)
snd = np.array(snd)
return float(np.abs(fst - snd).sum())
# Known distance functions.
DISTANCE_FU = {
ns.bsfs.euclidean: euclid,
ns.bsfs.cosine: cosine,
ns.bsfs.manhatten: manhatten,
}
## EOF ##
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