def test_covmodel_spline_prior(use_spline, prior_spline_monotonicity,
prior_spline_convexity,
prior_spline_num_constraint_points,
prior_spline_maxder_gaussian,
prior_spline_maxder_uniform, mrdata):
covmodel = CovModel(
'cov1',
use_spline=use_spline,
prior_spline_monotonicity=prior_spline_monotonicity,
prior_spline_convexity=prior_spline_convexity,
prior_spline_num_constraint_points=prior_spline_num_constraint_points,
prior_spline_maxder_gaussian=prior_spline_maxder_gaussian,
prior_spline_maxder_uniform=prior_spline_maxder_uniform)
covmodel.attach_data(mrdata)
num_constraints = ((prior_spline_monotonicity is not None) +
(prior_spline_convexity
is not None)) * prior_spline_num_constraint_points
num_constraints += (prior_spline_maxder_uniform
is not None) * covmodel.spline.num_intervals
num_regularizers = (prior_spline_maxder_gaussian
is not None) * covmodel.spline.num_intervals
assert covmodel.num_constraints == num_constraints
assert covmodel.num_regularizations == num_regularizers
def test_covmodel_spline(spline_knots, spline_degree, spline_l_linear,
spline_r_linear, use_re, use_re_mid_point, mrdata):
covmodel = CovModel('cov1',
use_re=use_re,
use_re_mid_point=use_re_mid_point,
use_spline=True,
spline_knots=spline_knots,
spline_degree=spline_degree,
spline_l_linear=spline_l_linear,
spline_r_linear=spline_r_linear)
assert all(
covmodel.spline_knots_template == np.array([0.0, 0.25, 0.75, 1.0]))
assert covmodel.spline_degree == spline_degree
assert covmodel.spline_l_linear == spline_l_linear
assert covmodel.spline_r_linear == spline_r_linear
covmodel.attach_data(mrdata)
assert covmodel.num_x_vars == covmodel.spline.num_spline_bases - 1
if use_re and use_re_mid_point:
assert covmodel.num_z_vars == 1
elif use_re and not use_re_mid_point:
assert covmodel.num_z_vars == covmodel.num_x_vars
elif not use_re:
assert covmodel.num_z_vars == 0
def test_covmodel_beta_uprior(prior_beta_uniform, use_spline, mrdata):
covmodel = CovModel('cov1',
use_spline=use_spline,
prior_beta_uniform=prior_beta_uniform)
covmodel.attach_data(mrdata)
assert covmodel.prior_beta_uniform.ndim == 2
assert np.all(covmodel.prior_beta_uniform[0] == 0.0)
assert np.all(covmodel.prior_beta_uniform[1] == 1.0)
def test_covmodel_beta_lprior(prior_beta_laplace, use_spline, mrdata):
covmodel = CovModel('cov1',
use_spline=use_spline,
prior_beta_laplace=prior_beta_laplace)
covmodel.attach_data(mrdata)
assert covmodel.prior_beta_laplace.ndim == 2
assert np.all(covmodel.prior_beta_laplace[0] == 0.0)
assert np.all(covmodel.prior_beta_laplace[1] == 1.0)
def test_covmodel_beta_gprior(prior_beta_gaussian, use_spline, mrdata):
covmodel = CovModel('cov1',
use_spline=use_spline,
prior_beta_gaussian=prior_beta_gaussian)
covmodel.attach_data(mrdata)
assert covmodel.prior_beta_gaussian.ndim == 2
assert np.all(covmodel.prior_beta_gaussian[0] == 0.0)
assert np.all(covmodel.prior_beta_gaussian[1] == 1.0)
def test_covmodel_gamma_uprior(prior_gamma_uniform, use_spline, use_re,
use_re_mid_point, mrdata):
covmodel = CovModel('cov1',
use_spline=use_spline,
prior_gamma_uniform=prior_gamma_uniform,
use_re=use_re,
use_re_mid_point=use_re_mid_point)
covmodel.attach_data(mrdata)
assert covmodel.prior_gamma_uniform.ndim == 2
assert np.all(covmodel.prior_gamma_uniform[0] == 0.0)
assert np.all(covmodel.prior_gamma_uniform[1] == 1.0)
def test_covmodel_gamma_gprior(prior_gamma_gaussian, use_spline, use_re,
use_re_mid_point, mrdata):
covmodel = CovModel('cov1',
use_spline=True,
prior_gamma_gaussian=prior_gamma_gaussian,
use_re=use_re,
use_re_mid_point=use_re_mid_point)
covmodel.attach_data(mrdata)
assert covmodel.prior_gamma_gaussian.ndim == 2
assert np.all(covmodel.prior_gamma_gaussian[0] == 0.0)
assert np.all(covmodel.prior_gamma_gaussian[1] == 1.0)
def test_covmodel_default():
covmodel = CovModel('cov0')
# direct priors
assert all(covmodel.prior_beta_gaussian == DUMMY_GPRIOR)
assert all(covmodel.prior_beta_laplace == DUMMY_LPRIOR)
assert all(covmodel.prior_beta_uniform == DUMMY_UPRIOR)
assert covmodel.prior_gamma_gaussian.size == 0
assert covmodel.prior_gamma_laplace.size == 0
assert covmodel.prior_gamma_uniform.size == 0
# spline priors
assert covmodel.prior_spline_monotonicity is None
assert covmodel.prior_spline_convexity is None
assert covmodel.prior_spline_num_constraint_points == 20
assert covmodel.prior_spline_maxder_gaussian is None
assert covmodel.prior_spline_maxder_uniform is None
# spline settings
assert np.all(covmodel.spline_knots_template == np.linspace(0.0, 1.0, 4))
assert covmodel.spline_degree == 3
assert not covmodel.spline_l_linear
assert not covmodel.spline_r_linear
# check dimensions
assert covmodel.num_x_vars == 1
assert covmodel.num_z_vars == 0
assert covmodel.num_constraints == 0
assert covmodel.num_regularizations == 0
def test_covmodel_re(use_re):
covmodel = CovModel('cov0', use_re=use_re)
assert covmodel.num_x_vars == 1
if use_re:
assert covmodel.num_z_vars == 1
assert all(covmodel.prior_gamma_gaussian == DUMMY_GPRIOR)
assert all(covmodel.prior_gamma_laplace == DUMMY_LPRIOR)
assert all(covmodel.prior_gamma_uniform == np.array([[0.0], [np.inf]]))
else:
assert covmodel.num_z_vars == 0
assert covmodel.prior_gamma_gaussian.size == 0
assert covmodel.prior_gamma_laplace.size == 0
assert covmodel.prior_gamma_uniform.size == 0
