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

Add unit test

release/4.3a0
Fan Jiang 2023-07-31 10:19:41 -07:00
parent d473cef470
commit 7f7acd7012
1 changed files with 33 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

33
gtsam/linear/tests/testNoiseModel.cpp
View File

@ -14,6 +14,7 @@
* @date Jan 13, 2010 * @date Jan 13, 2010
* @author Richard Roberts * @author Richard Roberts
* @author Frank Dellaert * @author Frank Dellaert
* @author Fan Jiang
*/ */
@ -504,6 +505,22 @@ TEST(NoiseModel, robustFunctionCauchy)
DOUBLES_EQUAL(0.490258914416017, cauchy->loss(error4), 1e-8); DOUBLES_EQUAL(0.490258914416017, cauchy->loss(error4), 1e-8);
} }
TEST(NoiseModel, robustFunctionAsymmetricCauchy)
{
const double k = 5.0, error1 = 1.0, error2 = 10.0, error3 = -10.0, error4 = -1.0;
const mEstimator::AsymmetricCauchy::shared_ptr cauchy = mEstimator::AsymmetricCauchy::Create(k);
DOUBLES_EQUAL(0.961538461538461, cauchy->weight(error1), 1e-8);
DOUBLES_EQUAL(0.2000, cauchy->weight(error2), 1e-8);
// Test negative value to ensure we take absolute value of error.
DOUBLES_EQUAL(10.0, cauchy->weight(error3), 1e-8);
DOUBLES_EQUAL(1.0, cauchy->weight(error4), 1e-8);
DOUBLES_EQUAL(0.490258914416017, cauchy->loss(error1), 1e-8);
DOUBLES_EQUAL(20.117973905426254, cauchy->loss(error2), 1e-8);
DOUBLES_EQUAL(50.0, cauchy->loss(error3), 1e-8);
DOUBLES_EQUAL(0.5, cauchy->loss(error4), 1e-8);
}
TEST(NoiseModel, robustFunctionGemanMcClure) TEST(NoiseModel, robustFunctionGemanMcClure)
{ {
const double k = 1.0, error1 = 1.0, error2 = 10.0, error3 = -10.0, error4 = -1.0; const double k = 1.0, error1 = 1.0, error2 = 10.0, error3 = -10.0, error4 = -1.0;
@ -551,6 +568,22 @@ TEST(NoiseModel, robustFunctionTukey)
DOUBLES_EQUAL(0.480266666666667, tukey->loss(error4), 1e-8); DOUBLES_EQUAL(0.480266666666667, tukey->loss(error4), 1e-8);
} }
TEST(NoiseModel, robustFunctionAsymmetricTukey)
{
const double k = 5.0, error1 = 1.0, error2 = 10.0, error3 = -10.0, error4 = -1.0;
const mEstimator::AsymmetricTukey::shared_ptr tukey = mEstimator::AsymmetricTukey::Create(k);
DOUBLES_EQUAL(0.9216, tukey->weight(error1), 1e-8);
DOUBLES_EQUAL(0.0, tukey->weight(error2), 1e-8);
// Test negative value to ensure we take absolute value of error.
DOUBLES_EQUAL(10.0, tukey->weight(error3), 1e-8);
DOUBLES_EQUAL(1.0, tukey->weight(error4), 1e-8);
DOUBLES_EQUAL(0.480266666666667, tukey->loss(error1), 1e-8);
DOUBLES_EQUAL(4.166666666666667, tukey->loss(error2), 1e-8);
DOUBLES_EQUAL(50.0, tukey->loss(error3), 1e-8);
DOUBLES_EQUAL(0.5, tukey->loss(error4), 1e-8);
}
TEST(NoiseModel, robustFunctionDCS) TEST(NoiseModel, robustFunctionDCS)
{ {
const double k = 1.0, error1 = 1.0, error2 = 10.0; const double k = 1.0, error1 = 1.0, error2 = 10.0;