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migrate likelihood_tests to pytest

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Martin Bubel 2023-10-06 18:50:21 +02:00
parent 4df152048c
commit 58f61d5a5c
1 changed files with 14 additions and 47 deletions
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61
GPy/testing/likelihood_tests.py
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@ -121,15 +121,12 @@ def dparam_checkgrad(
return gradchecking return gradchecking
from nose.tools import with_setup class TestNoiseModels:
class TestNoiseModels(object):
""" """
Generic model checker Generic model checker
""" """
def setUp(self): def setup(self):
np.random.seed(fixed_seed) np.random.seed(fixed_seed)
self.N = 15 self.N = 15
self.D = 3 self.D = 3
@ -418,13 +415,8 @@ class TestNoiseModels(object):
""" """
model[regex].constrain_bounded(lower, upper) model[regex].constrain_bounded(lower, upper)
def tearDown(self):
self.Y = None
self.f = None
self.X = None
def test_scale2_models(self): def test_scale2_models(self):
self.setUp() self.setup()
for name, attributes in self.noise_models.items(): for name, attributes in self.noise_models.items():
model = attributes["model"] model = attributes["model"]
@ -503,12 +495,12 @@ class TestNoiseModels(object):
yield self.t_dexp_dmu, model, Y, Y_metadata yield self.t_dexp_dmu, model, Y, Y_metadata
yield self.t_dexp_dvar, model, Y, Y_metadata yield self.t_dexp_dvar, model, Y, Y_metadata
self.tearDown() # TODO: how to now run all of the tests?
############# #############
# dpdf_df's # # dpdf
# _df's #
############# #############
@with_setup(setUp, tearDown)
def t_logpdf(self, model, Y, f, Y_metadata): def t_logpdf(self, model, Y, f, Y_metadata):
print("\n{}".format(inspect.stack()[0][3])) print("\n{}".format(inspect.stack()[0][3]))
print(model) print(model)
@ -518,7 +510,6 @@ class TestNoiseModels(object):
np.exp(model.logpdf(f.copy(), Y.copy(), Y_metadata=Y_metadata).sum()), np.exp(model.logpdf(f.copy(), Y.copy(), Y_metadata=Y_metadata).sum()),
) )
@with_setup(setUp, tearDown)
def t_dlogpdf_df(self, model, Y, f, Y_metadata): def t_dlogpdf_df(self, model, Y, f, Y_metadata):
print("\n{}".format(inspect.stack()[0][3])) print("\n{}".format(inspect.stack()[0][3]))
self.description = "\n{}".format(inspect.stack()[0][3]) self.description = "\n{}".format(inspect.stack()[0][3])
@ -529,7 +520,6 @@ class TestNoiseModels(object):
print(model) print(model)
assert grad.checkgrad(verbose=1) assert grad.checkgrad(verbose=1)
@with_setup(setUp, tearDown)
def t_d2logpdf_df2(self, model, Y, f, Y_metadata): def t_d2logpdf_df2(self, model, Y, f, Y_metadata):
print("\n{}".format(inspect.stack()[0][3])) print("\n{}".format(inspect.stack()[0][3]))
dlogpdf_df = functools.partial(model.dlogpdf_df, y=Y, Y_metadata=Y_metadata) dlogpdf_df = functools.partial(model.dlogpdf_df, y=Y, Y_metadata=Y_metadata)
@ -539,7 +529,6 @@ class TestNoiseModels(object):
print(model) print(model)
assert grad.checkgrad(verbose=1) assert grad.checkgrad(verbose=1)
@with_setup(setUp, tearDown)
def t_d3logpdf_df3(self, model, Y, f, Y_metadata): def t_d3logpdf_df3(self, model, Y, f, Y_metadata):
print("\n{}".format(inspect.stack()[0][3])) print("\n{}".format(inspect.stack()[0][3]))
d2logpdf_df2 = functools.partial(model.d2logpdf_df2, y=Y, Y_metadata=Y_metadata) d2logpdf_df2 = functools.partial(model.d2logpdf_df2, y=Y, Y_metadata=Y_metadata)
@ -552,7 +541,6 @@ class TestNoiseModels(object):
############## ##############
# df_dparams # # df_dparams #
############## ##############
@with_setup(setUp, tearDown)
def t_dlogpdf_dparams( def t_dlogpdf_dparams(
self, model, Y, f, Y_metadata, params, params_names, param_constraints self, model, Y, f, Y_metadata, params, params_names, param_constraints
): ):
@ -569,7 +557,6 @@ class TestNoiseModels(object):
verbose=True, verbose=True,
) )
@with_setup(setUp, tearDown)
def t_dlogpdf_df_dparams( def t_dlogpdf_df_dparams(
self, model, Y, f, Y_metadata, params, params_names, param_constraints self, model, Y, f, Y_metadata, params, params_names, param_constraints
): ):
@ -586,7 +573,6 @@ class TestNoiseModels(object):
verbose=True, verbose=True,
) )
@with_setup(setUp, tearDown)
def t_d2logpdf2_df2_dparams( def t_d2logpdf2_df2_dparams(
self, model, Y, f, Y_metadata, params, params_names, param_constraints self, model, Y, f, Y_metadata, params, params_names, param_constraints
): ):
@ -606,7 +592,6 @@ class TestNoiseModels(object):
################ ################
# dpdf_dlink's # # dpdf_dlink's #
################ ################
@with_setup(setUp, tearDown)
def t_dlogpdf_dlink(self, model, Y, f, Y_metadata, link_f_constraints): def t_dlogpdf_dlink(self, model, Y, f, Y_metadata, link_f_constraints):
print("\n{}".format(inspect.stack()[0][3])) print("\n{}".format(inspect.stack()[0][3]))
logpdf = functools.partial(model.logpdf_link, y=Y, Y_metadata=Y_metadata) logpdf = functools.partial(model.logpdf_link, y=Y, Y_metadata=Y_metadata)
@ -624,7 +609,6 @@ class TestNoiseModels(object):
print(model) print(model)
assert grad.checkgrad(verbose=1) assert grad.checkgrad(verbose=1)
@with_setup(setUp, tearDown)
def t_d2logpdf_dlink2(self, model, Y, f, Y_metadata, link_f_constraints): def t_d2logpdf_dlink2(self, model, Y, f, Y_metadata, link_f_constraints):
print("\n{}".format(inspect.stack()[0][3])) print("\n{}".format(inspect.stack()[0][3]))
dlogpdf_dlink = functools.partial( dlogpdf_dlink = functools.partial(
@ -644,7 +628,6 @@ class TestNoiseModels(object):
print(model) print(model)
assert grad.checkgrad(verbose=1) assert grad.checkgrad(verbose=1)
@with_setup(setUp, tearDown)
def t_d3logpdf_dlink3(self, model, Y, f, Y_metadata, link_f_constraints): def t_d3logpdf_dlink3(self, model, Y, f, Y_metadata, link_f_constraints):
print("\n{}".format(inspect.stack()[0][3])) print("\n{}".format(inspect.stack()[0][3]))
d2logpdf_dlink2 = functools.partial( d2logpdf_dlink2 = functools.partial(
@ -667,7 +650,6 @@ class TestNoiseModels(object):
################# #################
# dlink_dparams # # dlink_dparams #
################# #################
@with_setup(setUp, tearDown)
def t_dlogpdf_link_dparams( def t_dlogpdf_link_dparams(
self, model, Y, f, Y_metadata, params, param_names, param_constraints self, model, Y, f, Y_metadata, params, param_names, param_constraints
): ):
@ -684,7 +666,6 @@ class TestNoiseModels(object):
verbose=True, verbose=True,
) )
@with_setup(setUp, tearDown)
def t_dlogpdf_dlink_dparams( def t_dlogpdf_dlink_dparams(
self, model, Y, f, Y_metadata, params, param_names, param_constraints self, model, Y, f, Y_metadata, params, param_names, param_constraints
): ):
@ -701,7 +682,6 @@ class TestNoiseModels(object):
verbose=True, verbose=True,
) )
@with_setup(setUp, tearDown)
def t_d2logpdf2_dlink2_dparams( def t_d2logpdf2_dlink2_dparams(
self, model, Y, f, Y_metadata, params, param_names, param_constraints self, model, Y, f, Y_metadata, params, param_names, param_constraints
): ):
@ -721,7 +701,6 @@ class TestNoiseModels(object):
################ ################
# laplace test # # laplace test #
################ ################
@with_setup(setUp, tearDown)
def t_laplace_fit_rbf_white( def t_laplace_fit_rbf_white(
self, model, X, Y, f, Y_metadata, step, param_vals, param_names, constraints self, model, X, Y, f, Y_metadata, step, param_vals, param_names, constraints
): ):
@ -761,7 +740,6 @@ class TestNoiseModels(object):
########### ###########
# EP test # # EP test #
########### ###########
@with_setup(setUp, tearDown)
def t_ep_fit_rbf_white( def t_ep_fit_rbf_white(
self, model, X, Y, f, Y_metadata, step, param_vals, param_names, constraints self, model, X, Y, f, Y_metadata, step, param_vals, param_names, constraints
): ):
@ -794,7 +772,6 @@ class TestNoiseModels(object):
################ ################
# variational expectations # # variational expectations #
################ ################
@with_setup(setUp, tearDown)
def t_varexp(self, model, Y, Y_metadata): def t_varexp(self, model, Y, Y_metadata):
# Test that the analytic implementation (if it exists) matches the generic gauss # Test that the analytic implementation (if it exists) matches the generic gauss
# hermite implementation # hermite implementation
@ -826,7 +803,6 @@ class TestNoiseModels(object):
np.testing.assert_almost_equal(expectation, expectation_gh, decimal=5) np.testing.assert_almost_equal(expectation, expectation_gh, decimal=5)
@with_setup(setUp, tearDown)
def t_dexp_dmu(self, model, Y, Y_metadata): def t_dexp_dmu(self, model, Y, Y_metadata):
print("\n{}".format(inspect.stack()[0][3])) print("\n{}".format(inspect.stack()[0][3]))
# Make mu and var (marginal means and variances of q(f)) draws from a GP # Make mu and var (marginal means and variances of q(f)) draws from a GP
@ -857,7 +833,6 @@ class TestNoiseModels(object):
print(model) print(model)
assert grad.checkgrad(verbose=1) assert grad.checkgrad(verbose=1)
@with_setup(setUp, tearDown)
def t_dexp_dvar(self, model, Y, Y_metadata): def t_dexp_dvar(self, model, Y, Y_metadata):
print("\n{}".format(inspect.stack()[0][3])) print("\n{}".format(inspect.stack()[0][3]))
# Make mu and var (marginal means and variances of q(f)) draws from a GP # Make mu and var (marginal means and variances of q(f)) draws from a GP
@ -890,12 +865,12 @@ class TestNoiseModels(object):
assert grad.checkgrad(verbose=1) assert grad.checkgrad(verbose=1)
class LaplaceTests(unittest.TestCase): class LaplaceTests:
""" """
Specific likelihood tests, not general enough for the above tests Specific likelihood tests, not general enough for the above tests
""" """
def setUp(self): def setup(self):
np.random.seed(fixed_seed) np.random.seed(fixed_seed)
self.N = 15 self.N = 15
self.D = 1 self.D = 1
@ -916,14 +891,9 @@ class LaplaceTests(unittest.TestCase):
# Make a bigger step as lower bound can be quite curved # Make a bigger step as lower bound can be quite curved
self.step = 1e-6 self.step = 1e-6
def tearDown(self):
self.stu_t = None
self.gauss = None
self.Y = None
self.f = None
self.X = None
def test_gaussian_d2logpdf_df2_2(self): def test_gaussian_d2logpdf_df2_2(self):
self.setup()
print("\n{}".format(inspect.stack()[0][3])) print("\n{}".format(inspect.stack()[0][3]))
self.Y = None self.Y = None
@ -943,6 +913,8 @@ class LaplaceTests(unittest.TestCase):
self.assertTrue(grad.checkgrad(verbose=1)) self.assertTrue(grad.checkgrad(verbose=1))
def test_laplace_log_likelihood(self): def test_laplace_log_likelihood(self):
self.setup()
debug = False debug = False
real_std = 0.1 real_std = 0.1
initial_var_guess = 0.5 initial_var_guess = 0.5
@ -1046,10 +1018,5 @@ class LaplaceTests(unittest.TestCase):
# Check they are checkgradding # Check they are checkgradding
# m1.checkgrad(verbose=1) # m1.checkgrad(verbose=1)
# m2.checkgrad(verbose=1) # m2.checkgrad(verbose=1)
self.assertTrue(m1.checkgrad(verbose=True)) assert m1.checkgrad(verbose=True)
self.assertTrue(m2.checkgrad(verbose=True)) assert m2.checkgrad(verbose=True)
if __name__ == "__main__":
print("Running unit tests")
unittest.main()