def testBijectorValues(self):
x = [-1., 0., 1.]
bij = tfb.GeneralizedPareto(loc=[1., 2., 3.],
scale=5.,
concentration=[[-4., -6., -1.],
[2., 4., 0.]],
validate_args=True)
y = self.evaluate(bij.forward(x))
self.assertAllClose(y[0],
self.evaluate(
bij._negative_concentration_bijector()(x)[0]),
rtol=1e-6,
atol=0)
self.assertAllClose(y[1],
self.evaluate(
bij._non_negative_concentration_bijector(x)),
rtol=1e-6,
atol=0)
y = [1.5, 2.5, 3.5]
ildj = self.evaluate(bij.inverse_log_det_jacobian(y, event_ndims=0))
self.assertAllClose(ildj[0],
self.evaluate(bij._negative_concentration_bijector(
).inverse_log_det_jacobian(y, event_ndims=0))[0],
rtol=1e-6,
atol=0)
self.assertAllClose(ildj[1],
self.evaluate(
bij._non_negative_concentration_bijector.
inverse_log_det_jacobian(y, event_ndims=0)),
rtol=1e-6,
atol=0)
def testScalarCongruencyNegativeConcentration(self):
bijector_test_util.assert_scalar_congruency(tfb.GeneralizedPareto(
loc=1., scale=3., concentration=-5., validate_args=True),
lower_x=-7.,
upper_x=7.,
eval_func=self.evaluate,
rtol=.1)
def testBijectiveAndFinitePositiveConcentration(self):
loc = 5.
x = np.linspace(-10., 20., 20).astype(np.float32)
y = np.linspace(loc + 1e-3, 20., 20).astype(np.float32)
bijector_test_util.assert_bijective_and_finite(tfb.GeneralizedPareto(
loc=loc, scale=2., concentration=1., validate_args=True),
x,
y,
eval_func=self.evaluate,
event_ndims=0,
atol=1e-2,
rtol=1e-2)
def testBijectiveAndFiniteNegativeConcentration(self):
x = np.linspace(-10., 10., 20).astype(np.float32)
eps = 1e-3
loc = 5.
scale = 4.
concentration = 1.
upper_bound = loc + scale / concentration
y = np.linspace(loc + eps, upper_bound - eps, 20).astype(np.float32)
bijector_test_util.assert_bijective_and_finite(tfb.GeneralizedPareto(
loc=loc,
scale=scale,
concentration=concentration,
validate_args=True),
x,
y,
eval_func=self.evaluate,
event_ndims=0,
atol=1e-2,
rtol=1e-2)