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Unit tests for vector databases.
$Id: testvectordb.py,v 1.3 2005/06/28 03:00:28 jp Exp $
"""
import unittest
import pickle
from plastk import rand
from plastk.fnapprox.vectordb import *
from plastk.utils import *
from Numeric import array,arange
class TestVectorDB(unittest.TestCase):
dim = 2
N = 1000
probes = [array((x,y)) for x in arange(0,1.25,0.25) for y in arange(0,1.25,0.25)]
def setUp(self):
rand.seed(0,0)
self.data = [(rand.uniform(0,1,(self.dim,)),None) for i in range(self.N)]
for x,y in self.data:
self.db.add(x,y)
def testKNearest(self):
k = 10
def probe_cmp(a,b,probe):
ax,ay = a
bx,by = b
diff = norm(ax-probe)-norm(bx-probe)
return int(diff/abs(diff))
for p in self.probes:
k_nearest,dists = self.db.k_nearest(p,k)
self.data.sort(lambda a,b:probe_cmp(a,b,p))
assert k_nearest == self.data[:k]
def testFindInRadius(self):
r = 0.1
for p in self.probes:
found,dists = self.db.find_in_radius(p,r)
dists = [norm(p-x) for x,y in self.data]
truth = [(x,y) for d,(x,y) in zip(dists,self.data) if d <= r]
for pair in truth:
assert pair in found
for pair in found:
assert pair in truth
class TestFlatVectorDB(TestVectorDB):
def setUp(self):
self.db = FlatVectorDB()
TestVectorDB.setUp(self)
class TestVectorTree(TestVectorDB):
def setUp(self):
self.db = VectorTree()
TestVectorDB.setUp(self)
class TestPickleVectorTree(TestVectorTree):
def setUp(self):
TestVectorTree.setUp(self)
s = pickle.dumps(self.db)
self.orig_db = self.db
self.db = pickle.loads(s)
def testContents(self):
for xo,vo in self.orig_db.all():
(x,v),d = self.db.nearest(xo)
self.assertEqual(x,xo)
cases = [TestFlatVectorDB,
TestVectorTree,
TestPickleVectorTree,
]
suite = unittest.TestSuite()
suite.addTests([unittest.makeSuite(case) for case in cases])
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