From 743e98c9e262e6aa37cb958190b57763d592c52c Mon Sep 17 00:00:00 2001
From: Philipp Arras <parras@mpa-garching.mpg.de>
Date: Mon, 9 Mar 2020 12:22:30 +0100
Subject: [PATCH] MultiField tests for energies
---
test/test_energy_gradients.py | 66 ++++++++++++++++++++---------------
1 file changed, 38 insertions(+), 28 deletions(-)
diff --git a/test/test_energy_gradients.py b/test/test_energy_gradients.py
index 3344bdbb1..5f82ee5fe 100644
--- a/test/test_energy_gradients.py
+++ b/test/test_energy_gradients.py
@@ -28,26 +28,18 @@ from itertools import product
SPACES = [ift.GLSpace(15),
ift.RGSpace(64, distances=.789),
ift.RGSpace([32, 32], distances=.789)]
+for sp in SPACES[:3]:
+ SPACES.append(ift.MultiDomain.make({'asdf': sp}))
SEEDS = [4, 78, 23]
PARAMS = product(SEEDS, SPACES)
pmp = pytest.mark.parametrize
-# FIXME Test also with multifields in domain
@pytest.fixture(params=PARAMS)
def field(request):
np.random.seed(request.param[0])
S = ift.ScalingOperator(request.param[1], 1.)
- s = S.draw_sample()
- return ift.MultiField.from_dict({'s1': s})['s1']
-
-
-def test_variablecovariancegaussian(field):
- dc = {'a': field, 'b': field.exp()}
- mf = ift.MultiField.from_dict(dc)
- energy = ift.VariableCovarianceGaussianEnergy(field.domain, 'a', 'b')
- ift.extra.check_jacobian_consistency(energy, mf, tol=1e-6)
- energy(ift.Linearization.make_var(mf, want_metric=True)).metric.draw_sample()
+ return S.draw_sample()
def test_gaussian(field):
@@ -55,26 +47,52 @@ def test_gaussian(field):
ift.extra.check_jacobian_consistency(energy, field)
-@pmp('icov', [lambda dom:ift.ScalingOperator(dom, 1.),
- lambda dom:ift.SandwichOperator.make(ift.GeometryRemover(dom))])
-def test_ScaledEnergy(field, icov):
- icov = icov(field.domain)
+def test_ScaledEnergy(field):
+ icov = ift.ScalingOperator(field.domain, 1.2)
energy = ift.GaussianEnergy(inverse_covariance=icov)
ift.extra.check_jacobian_consistency(energy.scale(0.3), field)
lin = ift.Linearization.make_var(field, want_metric=True)
met1 = energy(lin).metric
met2 = energy.scale(0.3)(lin).metric
- np.testing.assert_allclose(met1(field).val, met2(field).val/0.3, rtol=1e-12)
+ res1 = met1(field)
+ res2 = met2(field)/0.3
+ ift.extra.assert_allclose(res1, res2, 0, 1e-12)
met2.draw_sample()
def test_studentt(field):
+ if isinstance(field.domain, ift.MultiDomain):
+ return
energy = ift.StudentTEnergy(domain=field.domain, theta=.5)
ift.extra.check_jacobian_consistency(energy, field, tol=1e-6)
+def test_hamiltonian_and_KL(field):
+ field = field.exp()
+ space = field.domain
+ lh = ift.GaussianEnergy(domain=space)
+ hamiltonian = ift.StandardHamiltonian(lh)
+ ift.extra.check_jacobian_consistency(hamiltonian, field)
+ S = ift.ScalingOperator(space, 1.)
+ samps = [S.draw_sample() for i in range(3)]
+ kl = ift.AveragedEnergy(hamiltonian, samps)
+ ift.extra.check_jacobian_consistency(kl, field)
+
+
+def test_variablecovariancegaussian(field):
+ if isinstance(field.domain, ift.MultiDomain):
+ return
+ dc = {'a': field, 'b': field.exp()}
+ mf = ift.MultiField.from_dict(dc)
+ energy = ift.VariableCovarianceGaussianEnergy(field.domain, 'a', 'b')
+ ift.extra.check_jacobian_consistency(energy, mf, tol=1e-6)
+ energy(ift.Linearization.make_var(mf, want_metric=True)).metric.draw_sample()
+
+
def test_inverse_gamma(field):
+ if isinstance(field.domain, ift.MultiDomain):
+ return
field = field.exp()
space = field.domain
d = np.random.normal(10, size=space.shape)**2
@@ -84,6 +102,8 @@ def test_inverse_gamma(field):
def testPoissonian(field):
+ if isinstance(field.domain, ift.MultiDomain):
+ return
field = field.exp()
space = field.domain
d = np.random.poisson(120, size=space.shape)
@@ -92,19 +112,9 @@ def testPoissonian(field):
ift.extra.check_jacobian_consistency(energy, field, tol=1e-7)
-def test_hamiltonian_and_KL(field):
- field = field.exp()
- space = field.domain
- lh = ift.GaussianEnergy(domain=space)
- hamiltonian = ift.StandardHamiltonian(lh)
- ift.extra.check_jacobian_consistency(hamiltonian, field)
- S = ift.ScalingOperator(space, 1.)
- samps = [S.draw_sample() for i in range(3)]
- kl = ift.AveragedEnergy(hamiltonian, samps)
- ift.extra.check_jacobian_consistency(kl, field)
-
-
def test_bernoulli(field):
+ if isinstance(field.domain, ift.MultiDomain):
+ return
field = field.sigmoid()
space = field.domain
d = np.random.binomial(1, 0.1, size=space.shape)
--
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