def testRetinaScaling(self):
"""Test the CioEncoder for retina dimension scaling."""
cio = CioEncoder(retinaScaling=1.0,
fingerprintType=EncoderTypes.document)
cioScaled = CioEncoder(retinaScaling=0.5,
fingerprintType=EncoderTypes.document)
cioScaled2 = CioEncoder(retinaScaling=0.71,
fingerprintType=EncoderTypes.document)
self.assertAlmostEqual(int(0.5 * cio.width), cioScaled.width)
self.assertAlmostEqual(int(0.5 * cio.height), cioScaled.height)
self.assertAlmostEqual(int(0.71 * cio.height), cioScaled2.height)
response = cio.encode(self.text)
responseScaled = cioScaled.encode(self.text)
responseScaled2 = cioScaled2.encode(self.text)
# Each bit position should be scaled down by retinaScaling*retinaScaling
self.assertLessEqual(
responseScaled["fingerprint"]["positions"].sum(),
0.5 * 0.5 * response["fingerprint"]["positions"].sum())
self.assertLessEqual(
responseScaled2["fingerprint"]["positions"].sum(),
0.71 * 0.71 * response["fingerprint"]["positions"].sum())
# The number of on bits in scaled retina should normally be slightly less
# than the original, but can be equal in some cases
self.assertLessEqual(len(responseScaled["fingerprint"]["positions"]),
len(response["fingerprint"]["positions"]))
self.assertLessEqual(len(responseScaled["fingerprint"]["positions"]),
len(responseScaled2["fingerprint"]["positions"]))
# Check that encodeIntoArray works even with weird scaling
a = numpy.zeros(cioScaled2.width * cioScaled2.height)
cioScaled2.encodeIntoArray(self.text, a)
self.assertEqual(len(responseScaled2["fingerprint"]["positions"]),
a.sum())
def testRetinaScaling(self):
"""Test the CioEncoder for retina dimension scaling."""
cio = CioEncoder(
retinaScaling = 1.0, fingerprintType=EncoderTypes.document)
cioScaled = CioEncoder(
retinaScaling = 0.5, fingerprintType=EncoderTypes.document)
cioScaled2 = CioEncoder(
retinaScaling = 0.71, fingerprintType=EncoderTypes.document)
self.assertAlmostEqual(int(0.5*cio.width), cioScaled.width)
self.assertAlmostEqual(int(0.5*cio.height), cioScaled.height)
self.assertAlmostEqual(int(0.71*cio.height), cioScaled2.height)
response = cio.encode(self.text)
responseScaled = cioScaled.encode(self.text)
responseScaled2 = cioScaled2.encode(self.text)
# Each bit position should be scaled down by retinaScaling*retinaScaling
self.assertLessEqual(responseScaled["fingerprint"]["positions"].sum(),
0.5*0.5*response["fingerprint"]["positions"].sum())
self.assertLessEqual(responseScaled2["fingerprint"]["positions"].sum(),
0.71*0.71*response["fingerprint"]["positions"].sum())
# The number of on bits in scaled retina should normally be slightly less
# than the original, but can be equal in some cases
self.assertLessEqual(len(responseScaled["fingerprint"]["positions"]),
len(response["fingerprint"]["positions"]))
self.assertLessEqual(len(responseScaled["fingerprint"]["positions"]),
len(responseScaled2["fingerprint"]["positions"]))
# Check that encodeIntoArray works even with weird scaling
a = numpy.zeros(cioScaled2.width*cioScaled2.height)
cioScaled2.encodeIntoArray(self.text, a)
self.assertEqual(len(responseScaled2["fingerprint"]["positions"]),
a.sum())
