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+"""
+
+Part of the BlackStar filesystem (bsfs) module.
+A copy of the license is provided with the project.
+Author: Matthias Baumgartner, 2022
+"""
+# 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 ##