12345qiupeng
/
gtsam
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Print estimated marginals and ratios!

release/4.3a0
Frank Dellaert 2023-01-01 11:48:08 -05:00
parent 7ab4c3e3fb
commit 64831300a5
1 changed files with 5 additions and 5 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

10
python/gtsam/tests/test_HybridFactorGraph.py
View File

@ -205,9 +205,9 @@ class TestHybridGaussianFactorGraph(GtsamTestCase):
# Estimate marginals using importance sampling.
marginals = self.estimate_marginals(bayesNet, sample)
# print(f"True mode: {sample.atDiscrete(M(0))}")
# print(f"P(mode=0; z0, z1) = {marginals[0]}")
# print(f"P(mode=1; z0, z1) = {marginals[1]}")
print(f"True mode: {sample.atDiscrete(M(0))}")
print(f"P(mode=0; z0, z1) = {marginals[0]}")
print(f"P(mode=1; z0, z1) = {marginals[1]}")
# Check marginals based on sampled mode.
if sample.atDiscrete(M(0)) == 0:
@ -251,8 +251,8 @@ class TestHybridGaussianFactorGraph(GtsamTestCase):
other.insert(measurements)
ratio = self.calculate_ratio(posterior, fg, other)
print(f"Ratio: {ratio}\n")
# if (ratio > 0):
# self.assertAlmostEqual(ratio, expected_ratio)
if (ratio > 0):
self.assertAlmostEqual(ratio, expected_ratio)
if __name__ == "__main__":
unittest.main()