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Martin Bubel 2023-10-06 18:52:02 +02:00
parent ef7d2f299c
commit 393f9938ea
1 changed files with 66 additions and 30 deletions
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GPy/testing/link_function_tests.py
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@ -3,11 +3,22 @@ import scipy
from scipy.special import cbrt from scipy.special import cbrt
from GPy.models import GradientChecker from GPy.models import GradientChecker
import random import random
_lim_val = np.finfo(np.float64).max _lim_val = np.finfo(np.float64).max
_lim_val_exp = np.log(_lim_val) _lim_val_exp = np.log(_lim_val)
_lim_val_square = np.sqrt(_lim_val) _lim_val_square = np.sqrt(_lim_val)
_lim_val_cube = cbrt(_lim_val) _lim_val_cube = cbrt(_lim_val)
from GPy.likelihoods.link_functions import Identity, Probit, Cloglog, Log, Log_ex_1, Reciprocal, Heaviside, ScaledProbit from GPy.likelihoods.link_functions import (
Identity,
Probit,
Cloglog,
Log,
Log_ex_1,
Reciprocal,
Heaviside,
ScaledProbit,
)
class LinkFunctionTests(np.testing.TestCase): class LinkFunctionTests(np.testing.TestCase):
def setUp(self): def setUp(self):
@ -21,48 +32,70 @@ class LinkFunctionTests(np.testing.TestCase):
def check_gradient(self, link_func, lim_of_inf, test_lim=False): def check_gradient(self, link_func, lim_of_inf, test_lim=False):
grad = GradientChecker(link_func.transf, link_func.dtransf_df, x0=self.mid_f) grad = GradientChecker(link_func.transf, link_func.dtransf_df, x0=self.mid_f)
self.assertTrue(grad.checkgrad(verbose=True)) self.assertTrue(grad.checkgrad(verbose=True))
grad2 = GradientChecker(link_func.dtransf_df, link_func.d2transf_df2, x0=self.mid_f) grad2 = GradientChecker(
link_func.dtransf_df, link_func.d2transf_df2, x0=self.mid_f
)
self.assertTrue(grad2.checkgrad(verbose=True)) self.assertTrue(grad2.checkgrad(verbose=True))
grad3 = GradientChecker(link_func.d2transf_df2, link_func.d3transf_df3, x0=self.mid_f) grad3 = GradientChecker(
link_func.d2transf_df2, link_func.d3transf_df3, x0=self.mid_f
)
self.assertTrue(grad3.checkgrad(verbose=True)) self.assertTrue(grad3.checkgrad(verbose=True))
grad = GradientChecker(link_func.transf, link_func.dtransf_df, x0=self.small_f) grad = GradientChecker(link_func.transf, link_func.dtransf_df, x0=self.small_f)
self.assertTrue(grad.checkgrad(verbose=True)) self.assertTrue(grad.checkgrad(verbose=True))
grad2 = GradientChecker(link_func.dtransf_df, link_func.d2transf_df2, x0=self.small_f) grad2 = GradientChecker(
link_func.dtransf_df, link_func.d2transf_df2, x0=self.small_f
)
self.assertTrue(grad2.checkgrad(verbose=True)) self.assertTrue(grad2.checkgrad(verbose=True))
grad3 = GradientChecker(link_func.d2transf_df2, link_func.d3transf_df3, x0=self.small_f) grad3 = GradientChecker(
link_func.d2transf_df2, link_func.d3transf_df3, x0=self.small_f
)
self.assertTrue(grad3.checkgrad(verbose=True)) self.assertTrue(grad3.checkgrad(verbose=True))
grad = GradientChecker(link_func.transf, link_func.dtransf_df, x0=self.zero_f) grad = GradientChecker(link_func.transf, link_func.dtransf_df, x0=self.zero_f)
self.assertTrue(grad.checkgrad(verbose=True)) self.assertTrue(grad.checkgrad(verbose=True))
grad2 = GradientChecker(link_func.dtransf_df, link_func.d2transf_df2, x0=self.zero_f) grad2 = GradientChecker(
link_func.dtransf_df, link_func.d2transf_df2, x0=self.zero_f
)
self.assertTrue(grad2.checkgrad(verbose=True)) self.assertTrue(grad2.checkgrad(verbose=True))
grad3 = GradientChecker(link_func.d2transf_df2, link_func.d3transf_df3, x0=self.zero_f) grad3 = GradientChecker(
link_func.d2transf_df2, link_func.d3transf_df3, x0=self.zero_f
)
self.assertTrue(grad3.checkgrad(verbose=True)) self.assertTrue(grad3.checkgrad(verbose=True))
#Do a limit test if the large f value is too large # Do a limit test if the large f value is too large
large_f = np.clip(self.large_f, -np.inf, lim_of_inf-1e-3) large_f = np.clip(self.large_f, -np.inf, lim_of_inf - 1e-3)
grad = GradientChecker(link_func.transf, link_func.dtransf_df, x0=large_f) grad = GradientChecker(link_func.transf, link_func.dtransf_df, x0=large_f)
self.assertTrue(grad.checkgrad(verbose=True)) self.assertTrue(grad.checkgrad(verbose=True))
grad2 = GradientChecker(link_func.dtransf_df, link_func.d2transf_df2, x0=large_f) grad2 = GradientChecker(
link_func.dtransf_df, link_func.d2transf_df2, x0=large_f
)
self.assertTrue(grad2.checkgrad(verbose=True)) self.assertTrue(grad2.checkgrad(verbose=True))
grad3 = GradientChecker(link_func.d2transf_df2, link_func.d3transf_df3, x0=large_f) grad3 = GradientChecker(
link_func.d2transf_df2, link_func.d3transf_df3, x0=large_f
)
self.assertTrue(grad3.checkgrad(verbose=True)) self.assertTrue(grad3.checkgrad(verbose=True))
if test_lim: if test_lim:
print("Testing limits") print("Testing limits")
#Remove some otherwise we are too close to the limit for gradcheck to work effectively # Remove some otherwise we are too close to the limit for gradcheck to work effectively
lim_of_inf = lim_of_inf - 1e-4 lim_of_inf = lim_of_inf - 1e-4
grad = GradientChecker(link_func.transf, link_func.dtransf_df, x0=lim_of_inf) grad = GradientChecker(
link_func.transf, link_func.dtransf_df, x0=lim_of_inf
)
self.assertTrue(grad.checkgrad(verbose=True)) self.assertTrue(grad.checkgrad(verbose=True))
grad2 = GradientChecker(link_func.dtransf_df, link_func.d2transf_df2, x0=lim_of_inf) grad2 = GradientChecker(
link_func.dtransf_df, link_func.d2transf_df2, x0=lim_of_inf
)
self.assertTrue(grad2.checkgrad(verbose=True)) self.assertTrue(grad2.checkgrad(verbose=True))
grad3 = GradientChecker(link_func.d2transf_df2, link_func.d3transf_df3, x0=lim_of_inf) grad3 = GradientChecker(
link_func.d2transf_df2, link_func.d3transf_df3, x0=lim_of_inf
)
self.assertTrue(grad3.checkgrad(verbose=True)) self.assertTrue(grad3.checkgrad(verbose=True))
def check_overflow(self, link_func, lim_of_inf): def check_overflow(self, link_func, lim_of_inf):
#Check that it does something sensible beyond this limit, # Check that it does something sensible beyond this limit,
#note this is not checking the value is correct, just that it isn't nan # note this is not checking the value is correct, just that it isn't nan
beyond_lim_of_inf = lim_of_inf + 100.0 beyond_lim_of_inf = lim_of_inf + 100.0
self.assertFalse(np.isinf(link_func.transf(beyond_lim_of_inf))) self.assertFalse(np.isinf(link_func.transf(beyond_lim_of_inf)))
self.assertFalse(np.isinf(link_func.dtransf_df(beyond_lim_of_inf))) self.assertFalse(np.isinf(link_func.dtransf_df(beyond_lim_of_inf)))
@ -78,14 +111,14 @@ class LinkFunctionTests(np.testing.TestCase):
np.testing.assert_almost_equal(np.exp(self.mid_f), link.transf(self.mid_f)) np.testing.assert_almost_equal(np.exp(self.mid_f), link.transf(self.mid_f))
assert np.isinf(np.exp(np.log(self.f_upper_lim))) assert np.isinf(np.exp(np.log(self.f_upper_lim)))
#Check the clipping works # Check the clipping works
np.testing.assert_almost_equal(link.transf(self.f_lower_lim), 0, decimal=5) np.testing.assert_almost_equal(link.transf(self.f_lower_lim), 0, decimal=5)
self.assertTrue(np.isfinite(link.transf(self.f_upper_lim))) self.assertTrue(np.isfinite(link.transf(self.f_upper_lim)))
self.check_overflow(link, lim_of_inf) self.check_overflow(link, lim_of_inf)
#Check that it would otherwise fail # Check that it would otherwise fail
beyond_lim_of_inf = lim_of_inf + 10.0 beyond_lim_of_inf = lim_of_inf + 10.0
old_err_state = np.seterr(over='ignore') old_err_state = np.seterr(over="ignore")
self.assertTrue(np.isinf(np.exp(beyond_lim_of_inf))) self.assertTrue(np.isinf(np.exp(beyond_lim_of_inf)))
np.seterr(**old_err_state) np.seterr(**old_err_state)
@ -93,21 +126,24 @@ class LinkFunctionTests(np.testing.TestCase):
link = Log_ex_1() link = Log_ex_1()
lim_of_inf = _lim_val_exp lim_of_inf = _lim_val_exp
np.testing.assert_almost_equal(scipy.special.log1p(np.exp(self.mid_f)), link.transf(self.mid_f)) np.testing.assert_almost_equal(
scipy.special.log1p(np.exp(self.mid_f)), link.transf(self.mid_f)
)
assert np.isinf(scipy.special.log1p(np.exp(np.log(self.f_upper_lim)))) assert np.isinf(scipy.special.log1p(np.exp(np.log(self.f_upper_lim))))
#Check the clipping works # Check the clipping works
np.testing.assert_almost_equal(link.transf(self.f_lower_lim), 0, decimal=5) np.testing.assert_almost_equal(link.transf(self.f_lower_lim), 0, decimal=5)
#Need to look at most significant figures here rather than the decimals # Need to look at most significant figures here rather than the decimals
np.testing.assert_approx_equal(link.transf(self.f_upper_lim), scipy.special.log1p(_lim_val), significant=5) np.testing.assert_approx_equal(
link.transf(self.f_upper_lim), scipy.special.log1p(_lim_val), significant=5
)
self.check_overflow(link, lim_of_inf) self.check_overflow(link, lim_of_inf)
#Check that it would otherwise fail # Check that it would otherwise fail
beyond_lim_of_inf = lim_of_inf + 10.0 beyond_lim_of_inf = lim_of_inf + 10.0
old_err_state = np.seterr(over='ignore') old_err_state = np.seterr(over="ignore")
self.assertTrue(np.isinf(scipy.special.log1p(np.exp(beyond_lim_of_inf)))) self.assertTrue(np.isinf(scipy.special.log1p(np.exp(beyond_lim_of_inf))))
np.seterr(**old_err_state) np.seterr(**old_err_state)
def test_log_gradients(self): def test_log_gradients(self):
# transf dtransf_df d2transf_df2 d3transf_df3 # transf dtransf_df d2transf_df2 d3transf_df3
link = Log() link = Log()
@ -117,14 +153,14 @@ class LinkFunctionTests(np.testing.TestCase):
def test_identity_gradients(self): def test_identity_gradients(self):
link = Identity() link = Identity()
lim_of_inf = _lim_val lim_of_inf = _lim_val
#FIXME: Should be able to think of a way to test the limits of this # FIXME: Should be able to think of a way to test the limits of this
self.check_gradient(link, lim_of_inf, test_lim=False) self.check_gradient(link, lim_of_inf, test_lim=False)
def test_probit_gradients(self): def test_probit_gradients(self):
link = Probit() link = Probit()
lim_of_inf = _lim_val lim_of_inf = _lim_val
self.check_gradient(link, lim_of_inf, test_lim=True) self.check_gradient(link, lim_of_inf, test_lim=True)
def test_scaledprobit_gradients(self): def test_scaledprobit_gradients(self):
link = ScaledProbit(nu=random.random()) link = ScaledProbit(nu=random.random())
lim_of_inf = _lim_val lim_of_inf = _lim_val
@ -144,5 +180,5 @@ class LinkFunctionTests(np.testing.TestCase):
def test_reciprocal_gradients(self): def test_reciprocal_gradients(self):
link = Reciprocal() link = Reciprocal()
lim_of_inf = _lim_val lim_of_inf = _lim_val
#Does not work with much smaller values, and values closer to zero than 1e-5 # Does not work with much smaller values, and values closer to zero than 1e-5
self.check_gradient(link, lim_of_inf, test_lim=True) self.check_gradient(link, lim_of_inf, test_lim=True)