From 71d5a6c1f14e2a053ac6fd48099577459efb079c Mon Sep 17 00:00:00 2001 From: Frank Dellaert Date: Thu, 26 Sep 2024 16:28:56 -0700 Subject: [PATCH] Fix more wrapper tests --- python/gtsam/tests/test_HybridBayesNet.py | 5 ++--- python/gtsam/tests/test_HybridFactorGraph.py | 4 ++-- 2 files changed, 4 insertions(+), 5 deletions(-) diff --git a/python/gtsam/tests/test_HybridBayesNet.py b/python/gtsam/tests/test_HybridBayesNet.py index bf2b6a033..57346d4d4 100644 --- a/python/gtsam/tests/test_HybridBayesNet.py +++ b/python/gtsam/tests/test_HybridBayesNet.py @@ -17,7 +17,7 @@ import numpy as np from gtsam.symbol_shorthand import A, X from gtsam.utils.test_case import GtsamTestCase -from gtsam import (DiscreteConditional, DiscreteKeys, DiscreteValues, +from gtsam import (DiscreteConditional, DiscreteValues, GaussianConditional, HybridBayesNet, HybridGaussianConditional, HybridValues, VectorValues, noiseModel) @@ -48,8 +48,7 @@ class TestHybridBayesNet(GtsamTestCase): bayesNet = HybridBayesNet() bayesNet.push_back(conditional) bayesNet.push_back( - HybridGaussianConditional([X(1)], [], Asia, - [conditional0, conditional1])) + HybridGaussianConditional(Asia, [conditional0, conditional1])) bayesNet.push_back(DiscreteConditional(Asia, "99/1")) # Create values at which to evaluate. diff --git a/python/gtsam/tests/test_HybridFactorGraph.py b/python/gtsam/tests/test_HybridFactorGraph.py index 3c63b9154..6d609deb0 100644 --- a/python/gtsam/tests/test_HybridFactorGraph.py +++ b/python/gtsam/tests/test_HybridFactorGraph.py @@ -35,7 +35,7 @@ class TestHybridGaussianFactorGraph(GtsamTestCase): jf1 = JacobianFactor(X(0), np.eye(3), np.zeros((3, 1)), model) jf2 = JacobianFactor(X(0), np.eye(3), np.ones((3, 1)), model) - gmf = HybridGaussianFactor([X(0)], (C(0), 2), [(jf1, 0), (jf2, 0)]) + gmf = HybridGaussianFactor((C(0), 2), [(jf1, 0), (jf2, 0)]) hfg = HybridGaussianFactorGraph() hfg.push_back(jf1) @@ -60,7 +60,7 @@ class TestHybridGaussianFactorGraph(GtsamTestCase): jf1 = JacobianFactor(X(0), np.eye(3), np.zeros((3, 1)), model) jf2 = JacobianFactor(X(0), np.eye(3), np.ones((3, 1)), model) - gmf = HybridGaussianFactor([X(0)], (C(0), 2), [(jf1, 0), (jf2, 0)]) + gmf = HybridGaussianFactor((C(0), 2), [(jf1, 0), (jf2, 0)]) hfg = HybridGaussianFactorGraph() hfg.push_back(jf1)