6fbef6a3631d94991ab02a9f7411e3b6fd954dfc,tests/unittests_estimators.py,TestConditionalDensityEstimators_2d_gaussian,test_NKDE_with_2d_gaussian,#TestConditionalDensityEstimators_2d_gaussian#,92
Before Change
model.fit(X, Y)
y = np.arange(-1, 5, 0.5)
x = np.asarray([2 for i in range(y.shape[0])])
p_est = model.pdf(x, y)
p_true = norm.pdf(y, loc=2, scale=1)
self.assertLessEqual(np.mean(np.abs(p_true - p_est)), 0.1)
After Change
def test_NKDE_with_2d_gaussian(self):
mu = 5
std = 2.0
X = np.random.normal(loc=mu, scale=std, size=(4000, 2))
Y = np.random.normal(loc=mu, scale=std, size=(4000, 2))
model = NeighborKernelDensityEstimation(epsilon=0.3)
model.fit(X, Y)
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 5
Instances
Project Name: freelunchtheorem/Conditional_Density_Estimation
Commit Name: 6fbef6a3631d94991ab02a9f7411e3b6fd954dfc
Time: 2019-01-12
Author: jonas.rothfuss@gmx.de
File Name: tests/unittests_estimators.py
Class Name: TestConditionalDensityEstimators_2d_gaussian
Method Name: test_NKDE_with_2d_gaussian
Project Name: freelunchtheorem/Conditional_Density_Estimation
Commit Name: 4f9f28da19466e18165feb5a3dab0e82f686b926
Time: 2019-01-13
Author: jonas.rothfuss@gmx.de
File Name: tests/unittests_estimators.py
Class Name: TestConditionalDensityEstimators_2d_gaussian
Method Name: test_LSCD_with_2d_gaussian
Project Name: IBM/adversarial-robustness-toolbox
Commit Name: b09284f6ba59659a9819e68244a7a785016c87c5
Time: 2020-05-24
Author: beat.buesser@ie.ibm.com
File Name: art/attacks/evasion/shadow_attack.py
Class Name: ShadowAttack
Method Name: generate