# This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program. If not, see . # # Copyright(C) 2013-2019 Max-Planck-Society # # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik. import numpy as np import pytest import nifty5 as ift from itertools import product # Currently it is not possible to parametrize fixtures. But this will # hopefully be fixed in the future. # https://docs.pytest.org/en/latest/proposals/parametrize_with_fixtures.html SPACES = [ ift.GLSpace(15), ift.RGSpace(64, distances=.789), ift.RGSpace([32, 32], distances=.789) ] SEEDS = [4, 78, 23] PARAMS = product(SEEDS, SPACES) @pytest.fixture(params=PARAMS) def field(request): np.random.seed(request.param[0]) S = ift.ScalingOperator(1., request.param[1]) s = S.draw_sample() return ift.MultiField.from_dict({'s1': s})['s1'] def test_gaussian(field): energy = ift.GaussianEnergy(domain=field.domain) ift.extra.check_value_gradient_consistency(energy, field) def test_inverse_gamma(field): field = field.exp() space = field.domain d = np.random.normal(10, size=space.shape)**2 d = ift.Field.from_global_data(space, d) energy = ift.InverseGammaLikelihood(d) ift.extra.check_value_gradient_consistency(energy, field, tol=1e-7) def testPoissonian(field): field = field.exp() space = field.domain d = np.random.poisson(120, size=space.shape) d = ift.Field.from_global_data(space, d) energy = ift.PoissonianEnergy(d) ift.extra.check_value_gradient_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_value_gradient_consistency(hamiltonian, field) S = ift.ScalingOperator(1., space) samps = [S.draw_sample() for i in range(3)] kl = ift.AveragedEnergy(hamiltonian, samps) ift.extra.check_value_gradient_consistency(kl, field) def test_bernoulli(field): field = field.sigmoid() space = field.domain d = np.random.binomial(1, 0.1, size=space.shape) d = ift.Field.from_global_data(space, d) energy = ift.BernoulliEnergy(d) ift.extra.check_value_gradient_consistency(energy, field, tol=1e-6)