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Add unit test for optimization a factor graph

release/4.3a0
Fan Jiang 2021-06-05 01:18:02 -04:00
parent 22ddab7921
commit 56faf3c4a8
1 changed files with 48 additions and 4 deletions
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52
python/gtsam/tests/test_custom_factor.py
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@ -75,7 +75,7 @@ class TestCustomFactor(GtsamTestCase):
key0 = this.keys()[0] key0 = this.keys()[0]
key1 = this.keys()[1] key1 = this.keys()[1]
gT1, gT2 = v.atPose2(key0), v.atPose2(key1) gT1, gT2 = v.atPose2(key0), v.atPose2(key1)
error = Pose2(0, 0, 0).localCoordinates(gT1.between(gT2)) error = expected.localCoordinates(gT1.between(gT2))
if H is not None: if H is not None:
result = gT1.between(gT2) result = gT1.between(gT2)
@ -89,7 +89,7 @@ class TestCustomFactor(GtsamTestCase):
v.insert(0, gT1) v.insert(0, gT1)
v.insert(1, gT2) v.insert(1, gT2)
bf = gtsam.BetweenFactorPose2(0, 1, Pose2(0, 0, 0), noise_model) bf = gtsam.BetweenFactorPose2(0, 1, expected, noise_model)
gf = cf.linearize(v) gf = cf.linearize(v)
gf_b = bf.linearize(v) gf_b = bf.linearize(v)
@ -136,7 +136,7 @@ class TestCustomFactor(GtsamTestCase):
key0 = this.keys()[0] key0 = this.keys()[0]
key1 = this.keys()[1] key1 = this.keys()[1]
gT1, gT2 = v.atPose2(key0), v.atPose2(key1) gT1, gT2 = v.atPose2(key0), v.atPose2(key1)
error = Pose2(0, 0, 0).localCoordinates(gT1.between(gT2)) error = expected.localCoordinates(gT1.between(gT2))
self.assertTrue(H is None) # Should be true if we only request the error self.assertTrue(H is None) # Should be true if we only request the error
@ -152,12 +152,56 @@ class TestCustomFactor(GtsamTestCase):
v.insert(0, gT1) v.insert(0, gT1)
v.insert(1, gT2) v.insert(1, gT2)
bf = gtsam.BetweenFactorPose2(0, 1, Pose2(0, 0, 0), noise_model) bf = gtsam.BetweenFactorPose2(0, 1, expected, noise_model)
e_cf = cf.error(v) e_cf = cf.error(v)
e_bf = bf.error(v) e_bf = bf.error(v)
np.testing.assert_allclose(e_cf, e_bf) np.testing.assert_allclose(e_cf, e_bf)
def test_optimization(self):
"""Tests if a factor graph with a CustomFactor can be properly optimized"""
gT1 = Pose2(1, 2, np.pi / 2)
gT2 = Pose2(-1, 4, np.pi)
expected = Pose2(2, 2, np.pi / 2)
def error_func(this: CustomFactor, v: gtsam.Values, H: List[np.ndarray]):
"""
Error function that mimics a BetweenFactor
:param this: reference to the current CustomFactor being evaluated
:param v: Values object
:param H: list of references to the Jacobian arrays
:return: the non-linear error
"""
key0 = this.keys()[0]
key1 = this.keys()[1]
gT1, gT2 = v.atPose2(key0), v.atPose2(key1)
error = expected.localCoordinates(gT1.between(gT2))
if H is not None:
result = gT1.between(gT2)
H[0] = -result.inverse().AdjointMap()
H[1] = np.eye(3)
return error
noise_model = gtsam.noiseModel.Unit.Create(3)
cf = CustomFactor(noise_model, [0, 1], error_func)
fg = gtsam.NonlinearFactorGraph()
fg.add(cf)
fg.add(gtsam.PriorFactorPose2(0, gT1, noise_model))
v = Values()
v.insert(0, Pose2(0, 0, 0))
v.insert(1, Pose2(0, 0, 0))
params = gtsam.LevenbergMarquardtParams()
optimizer = gtsam.LevenbergMarquardtOptimizer(fg, v, params)
result = optimizer.optimize()
self.gtsamAssertEquals(result.atPose2(0), gT1, tol=1e-5)
self.gtsamAssertEquals(result.atPose2(1), gT2, tol=1e-5)
if __name__ == "__main__": if __name__ == "__main__":
unittest.main() unittest.main()