mirror of
https://github.com/SheffieldML/GPy.git
synced 2026-05-05 01:32:40 +02:00
migrate likelihood_tests to pytest
This commit is contained in:
Martin Bubel
parent
4df152048c
commit
58f61d5a5c
1 changed files with 14 additions and 47 deletions
|
|
@ -121,15 +121,12 @@ def dparam_checkgrad(
|
|||
return gradchecking
|
||||
|
||||
|
||||
from nose.tools import with_setup
|
||||
|
||||
|
||||
class TestNoiseModels(object):
|
||||
class TestNoiseModels:
|
||||
"""
|
||||
Generic model checker
|
||||
"""
|
||||
|
||||
def setUp(self):
|
||||
def setup(self):
|
||||
np.random.seed(fixed_seed)
|
||||
self.N = 15
|
||||
self.D = 3
|
||||
|
|
@ -418,13 +415,8 @@ class TestNoiseModels(object):
|
|||
"""
|
||||
model[regex].constrain_bounded(lower, upper)
|
||||
|
||||
def tearDown(self):
|
||||
self.Y = None
|
||||
self.f = None
|
||||
self.X = None
|
||||
|
||||
def test_scale2_models(self):
|
||||
self.setUp()
|
||||
self.setup()
|
||||
|
||||
for name, attributes in self.noise_models.items():
|
||||
model = attributes["model"]
|
||||
|
|
@ -503,12 +495,12 @@ class TestNoiseModels(object):
|
|||
yield self.t_dexp_dmu, 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):
|
||||
print("\n{}".format(inspect.stack()[0][3]))
|
||||
print(model)
|
||||
|
|
@ -518,7 +510,6 @@ class TestNoiseModels(object):
|
|||
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):
|
||||
print("\n{}".format(inspect.stack()[0][3]))
|
||||
self.description = "\n{}".format(inspect.stack()[0][3])
|
||||
|
|
@ -529,7 +520,6 @@ class TestNoiseModels(object):
|
|||
print(model)
|
||||
assert grad.checkgrad(verbose=1)
|
||||
|
||||
@with_setup(setUp, tearDown)
|
||||
def t_d2logpdf_df2(self, model, Y, f, Y_metadata):
|
||||
print("\n{}".format(inspect.stack()[0][3]))
|
||||
dlogpdf_df = functools.partial(model.dlogpdf_df, y=Y, Y_metadata=Y_metadata)
|
||||
|
|
@ -539,7 +529,6 @@ class TestNoiseModels(object):
|
|||
print(model)
|
||||
assert grad.checkgrad(verbose=1)
|
||||
|
||||
@with_setup(setUp, tearDown)
|
||||
def t_d3logpdf_df3(self, model, Y, f, Y_metadata):
|
||||
print("\n{}".format(inspect.stack()[0][3]))
|
||||
d2logpdf_df2 = functools.partial(model.d2logpdf_df2, y=Y, Y_metadata=Y_metadata)
|
||||
|
|
@ -552,7 +541,6 @@ class TestNoiseModels(object):
|
|||
##############
|
||||
# df_dparams #
|
||||
##############
|
||||
@with_setup(setUp, tearDown)
|
||||
def t_dlogpdf_dparams(
|
||||
self, model, Y, f, Y_metadata, params, params_names, param_constraints
|
||||
):
|
||||
|
|
@ -569,7 +557,6 @@ class TestNoiseModels(object):
|
|||
verbose=True,
|
||||
)
|
||||
|
||||
@with_setup(setUp, tearDown)
|
||||
def t_dlogpdf_df_dparams(
|
||||
self, model, Y, f, Y_metadata, params, params_names, param_constraints
|
||||
):
|
||||
|
|
@ -586,7 +573,6 @@ class TestNoiseModels(object):
|
|||
verbose=True,
|
||||
)
|
||||
|
||||
@with_setup(setUp, tearDown)
|
||||
def t_d2logpdf2_df2_dparams(
|
||||
self, model, Y, f, Y_metadata, params, params_names, param_constraints
|
||||
):
|
||||
|
|
@ -606,7 +592,6 @@ class TestNoiseModels(object):
|
|||
################
|
||||
# dpdf_dlink's #
|
||||
################
|
||||
@with_setup(setUp, tearDown)
|
||||
def t_dlogpdf_dlink(self, model, Y, f, Y_metadata, link_f_constraints):
|
||||
print("\n{}".format(inspect.stack()[0][3]))
|
||||
logpdf = functools.partial(model.logpdf_link, y=Y, Y_metadata=Y_metadata)
|
||||
|
|
@ -624,7 +609,6 @@ class TestNoiseModels(object):
|
|||
print(model)
|
||||
assert grad.checkgrad(verbose=1)
|
||||
|
||||
@with_setup(setUp, tearDown)
|
||||
def t_d2logpdf_dlink2(self, model, Y, f, Y_metadata, link_f_constraints):
|
||||
print("\n{}".format(inspect.stack()[0][3]))
|
||||
dlogpdf_dlink = functools.partial(
|
||||
|
|
@ -644,7 +628,6 @@ class TestNoiseModels(object):
|
|||
print(model)
|
||||
assert grad.checkgrad(verbose=1)
|
||||
|
||||
@with_setup(setUp, tearDown)
|
||||
def t_d3logpdf_dlink3(self, model, Y, f, Y_metadata, link_f_constraints):
|
||||
print("\n{}".format(inspect.stack()[0][3]))
|
||||
d2logpdf_dlink2 = functools.partial(
|
||||
|
|
@ -667,7 +650,6 @@ class TestNoiseModels(object):
|
|||
#################
|
||||
# dlink_dparams #
|
||||
#################
|
||||
@with_setup(setUp, tearDown)
|
||||
def t_dlogpdf_link_dparams(
|
||||
self, model, Y, f, Y_metadata, params, param_names, param_constraints
|
||||
):
|
||||
|
|
@ -684,7 +666,6 @@ class TestNoiseModels(object):
|
|||
verbose=True,
|
||||
)
|
||||
|
||||
@with_setup(setUp, tearDown)
|
||||
def t_dlogpdf_dlink_dparams(
|
||||
self, model, Y, f, Y_metadata, params, param_names, param_constraints
|
||||
):
|
||||
|
|
@ -701,7 +682,6 @@ class TestNoiseModels(object):
|
|||
verbose=True,
|
||||
)
|
||||
|
||||
@with_setup(setUp, tearDown)
|
||||
def t_d2logpdf2_dlink2_dparams(
|
||||
self, model, Y, f, Y_metadata, params, param_names, param_constraints
|
||||
):
|
||||
|
|
@ -721,7 +701,6 @@ class TestNoiseModels(object):
|
|||
################
|
||||
# laplace test #
|
||||
################
|
||||
@with_setup(setUp, tearDown)
|
||||
def t_laplace_fit_rbf_white(
|
||||
self, model, X, Y, f, Y_metadata, step, param_vals, param_names, constraints
|
||||
):
|
||||
|
|
@ -761,7 +740,6 @@ class TestNoiseModels(object):
|
|||
###########
|
||||
# EP test #
|
||||
###########
|
||||
@with_setup(setUp, tearDown)
|
||||
def t_ep_fit_rbf_white(
|
||||
self, model, X, Y, f, Y_metadata, step, param_vals, param_names, constraints
|
||||
):
|
||||
|
|
@ -794,7 +772,6 @@ class TestNoiseModels(object):
|
|||
################
|
||||
# variational expectations #
|
||||
################
|
||||
@with_setup(setUp, tearDown)
|
||||
def t_varexp(self, model, Y, Y_metadata):
|
||||
# Test that the analytic implementation (if it exists) matches the generic gauss
|
||||
# hermite implementation
|
||||
|
|
@ -826,7 +803,6 @@ class TestNoiseModels(object):
|
|||
|
||||
np.testing.assert_almost_equal(expectation, expectation_gh, decimal=5)
|
||||
|
||||
@with_setup(setUp, tearDown)
|
||||
def t_dexp_dmu(self, model, Y, Y_metadata):
|
||||
print("\n{}".format(inspect.stack()[0][3]))
|
||||
# Make mu and var (marginal means and variances of q(f)) draws from a GP
|
||||
|
|
@ -857,7 +833,6 @@ class TestNoiseModels(object):
|
|||
print(model)
|
||||
assert grad.checkgrad(verbose=1)
|
||||
|
||||
@with_setup(setUp, tearDown)
|
||||
def t_dexp_dvar(self, model, Y, Y_metadata):
|
||||
print("\n{}".format(inspect.stack()[0][3]))
|
||||
# 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)
|
||||
|
||||
|
||||
class LaplaceTests(unittest.TestCase):
|
||||
class LaplaceTests:
|
||||
"""
|
||||
Specific likelihood tests, not general enough for the above tests
|
||||
"""
|
||||
|
||||
def setUp(self):
|
||||
def setup(self):
|
||||
np.random.seed(fixed_seed)
|
||||
self.N = 15
|
||||
self.D = 1
|
||||
|
|
@ -916,14 +891,9 @@ class LaplaceTests(unittest.TestCase):
|
|||
# Make a bigger step as lower bound can be quite curved
|
||||
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):
|
||||
self.setup()
|
||||
|
||||
print("\n{}".format(inspect.stack()[0][3]))
|
||||
self.Y = None
|
||||
|
||||
|
|
@ -943,6 +913,8 @@ class LaplaceTests(unittest.TestCase):
|
|||
self.assertTrue(grad.checkgrad(verbose=1))
|
||||
|
||||
def test_laplace_log_likelihood(self):
|
||||
self.setup()
|
||||
|
||||
debug = False
|
||||
real_std = 0.1
|
||||
initial_var_guess = 0.5
|
||||
|
|
@ -1046,10 +1018,5 @@ class LaplaceTests(unittest.TestCase):
|
|||
# Check they are checkgradding
|
||||
# m1.checkgrad(verbose=1)
|
||||
# m2.checkgrad(verbose=1)
|
||||
self.assertTrue(m1.checkgrad(verbose=True))
|
||||
self.assertTrue(m2.checkgrad(verbose=True))
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
print("Running unit tests")
|
||||
unittest.main()
|
||||
assert m1.checkgrad(verbose=True)
|
||||
assert m2.checkgrad(verbose=True)
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue