def test_SimpleMatchAbsoluteNeighbor(self):
points, dummy = Utils.getSimplePatterns()
pointsAsNpArray = np.array(points)
R = Utils.getRotationMatrix(35 + 180)
translation = np.array([[0.11, -0.03]])
points2 = Utils.transform(1.0, R, translation, pointsAsNpArray)
c = AbsoluteNeighborFitnessComputer(points2, 0.1)
m = SimulatedAnnealingPointMatcher2D(c)
Utils.addPointsToAnnealer(points, m)
m.setSlowMovementBreakpoint(0.75)
m.setInitialRotationSigma(360)
m.setInitialTranslationSigma(0.2)
m.setSlowTranslationSigma(0.1)
m.setStartTemperature(0.0)
m.setNumIterations(200)
scale, rotation, translation, fitness = m.match()
self.assertAlmostEqual(fitness[0, 0], 0.0)
self.assertAlmostEqual(scale[0, 0], 1.0)
numDigits = 1
self.assertMatrixAlmostEquals(rotation, R, numDigits)
self.assertMatrixAlmostEquals(translation, translation, numDigits)
def test_SimpleMatch(self):
refCloud = np.array([[0.0, 0.0], [0.0, 1.0], [1.0, 1.0]])
scale = 1.0
rotation = Utils.getRotationMatrix(90)
translation = np.array([[1.0, 2.0]])
matchCloud = Utils.transform(scale, rotation, translation, refCloud)
c = MeanShortestDistanceFitnessComputer(refCloud)
m = BruteForceMatcher(c, refCloud)
m.setCandidateKeepRatio(1)
scale, rotation, translation, fitness = m.match(matchCloud)
self.assertAlmostEqual(fitness[0, 0], 0.0)
self.assertEqual(scale[0, 0], 1.0)
self.assertAlmostEqual(rotation[0, 0], 0.0)
self.assertAlmostEqual(rotation[0, 1], 1.0)
self.assertAlmostEqual(rotation[1, 0], -1.0)
self.assertAlmostEqual(rotation[1, 1], 0.0)
