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use unittest framework instead of pytest

release/4.3a0
John Lambert 2021-10-22 01:18:51 -04:00 committed by GitHub
parent 84d291003f
commit bc68ecb5ab
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1 changed files with 19 additions and 10 deletions
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python/gtsam/tests/test_lago.py
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@ -8,6 +8,8 @@ See LICENSE for the license information
Author: John Lambert (Python) Author: John Lambert (Python)
""" """
import unittest
import numpy as np import numpy as np
import gtsam import gtsam
@ -19,16 +21,23 @@ def vector3(x: float, y: float, z: float) -> np.ndarray:
return np.array([x, y, z], dtype=float) return np.array([x, y, z], dtype=float)
def test_lago() -> None: class TestLago(unittest.TestCase):
"""Smokescreen to ensure LAGO can be imported and run on toy data stored in a g2o file.""" """Test selected LAGO methods."""
g2oFile = gtsam.findExampleDataFile("noisyToyGraph.txt")
graph = gtsam.NonlinearFactorGraph() def test_initialize(self) -> None:
graph, initial = gtsam.readG2o(g2oFile) """Smokescreen to ensure LAGO can be imported and run on toy data stored in a g2o file."""
g2oFile = gtsam.findExampleDataFile("noisyToyGraph.txt")
# Add prior on the pose having index (key) = 0 graph = gtsam.NonlinearFactorGraph()
priorModel = gtsam.noiseModel.Diagonal.Variances(vector3(1e-6, 1e-6, 1e-8)) graph, initial = gtsam.readG2o(g2oFile)
graph.add(PriorFactorPose2(0, Pose2(), priorModel))
estimateLago: Values = gtsam.lago.initialize(graph) # Add prior on the pose having index (key) = 0
assert isinstance(estimateLago, Values) priorModel = gtsam.noiseModel.Diagonal.Variances(vector3(1e-6, 1e-6, 1e-8))
graph.add(PriorFactorPose2(0, Pose2(), priorModel))
estimateLago: Values = gtsam.lago.initialize(graph)
assert isinstance(estimateLago, Values)
if __name__ == "__main__":
unittest.main()