def test_free_spec_prior(self):
"""Test that red noise signal returns correct values."""
# set up signal parameter
pr = gp_priors.free_spectrum(
log10_rho=parameter.Uniform(-10, -4, size=30))
basis = gp_bases.createfourierdesignmatrix_red(nmodes=30)
rn = gp_signals.BasisGP(priorFunction=pr,
basisFunction=basis,
name="red_noise")
rnm = rn(self.psr)
# parameters
rhos = np.random.uniform(-10, -4, size=30)
params = {"B1855+09_red_noise_log10_rho": rhos}
# basis matrix test
F, f2 = gp_bases.createfourierdesignmatrix_red(self.psr.toas,
nmodes=30)
msg = "F matrix incorrect for free spectrum."
assert np.allclose(F, rnm.get_basis(params)), msg
# spectrum test
phi = gp_priors.free_spectrum(f2, log10_rho=rhos)
msg = "Spectrum incorrect for free spectrum."
assert np.all(rnm.get_phi(params) == phi), msg
# inverse spectrum test
msg = "Spectrum inverse incorrect for free spectrum."
assert np.all(rnm.get_phiinv(params) == 1 / phi), msg
# test shape
msg = "F matrix shape incorrect"
assert rnm.get_basis(params).shape == F.shape, msg
def test_turnover_knee_prior(self):
"""Test that red noise signal returns correct values."""
# set up signal parameter
pr = gp_priors.turnover_knee(
log10_A=parameter.Uniform(-18, -12),
gamma=parameter.Uniform(1, 7),
lfb=parameter.Uniform(-9, -7.5),
lfk=parameter.Uniform(-9, -7.5),
kappa=parameter.Uniform(2.5, 5),
delta=parameter.Uniform(0.01, 1),
)
basis = gp_bases.createfourierdesignmatrix_red(nmodes=30)
rn = gp_signals.BasisGP(priorFunction=pr,
basisFunction=basis,
name="red_noise")
rnm = rn(self.psr)
# parameters
log10_A, gamma, lfb = -14.5, 4.33, -8.5
lfk, kappa, delta = -8.5, 3, 0.5
params = {
"B1855+09_red_noise_log10_A": log10_A,
"B1855+09_red_noise_gamma": gamma,
"B1855+09_red_noise_lfb": lfb,
"B1855+09_red_noise_lfk": lfk,
"B1855+09_red_noise_kappa": kappa,
"B1855+09_red_noise_delta": delta,
}
# basis matrix test
F, f2 = gp_bases.createfourierdesignmatrix_red(self.psr.toas,
nmodes=30)
msg = "F matrix incorrect for turnover."
assert np.allclose(F, rnm.get_basis(params)), msg
# spectrum test
phi = gp_priors.turnover_knee(f2,
log10_A=log10_A,
gamma=gamma,
lfb=lfb,
lfk=lfk,
kappa=kappa,
delta=delta)
msg = "Spectrum incorrect for turnover."
assert np.all(rnm.get_phi(params) == phi), msg
# inverse spectrum test
msg = "Spectrum inverse incorrect for turnover."
assert np.all(rnm.get_phiinv(params) == 1 / phi), msg
# test shape
msg = "F matrix shape incorrect"
assert rnm.get_basis(params).shape == F.shape, msg
def set_Fmat_auxiliaries(self):
"""Set Fourier design matrix and array of corresponding Fourier mode
frequencies
"""
Fmat, self.Ffreqs = createfourierdesignmatrix_red(self.psr.toas)
self.Fmat = np.zeros_like(Fmat)
self.Fmat[:, 1::2] = Fmat[:, ::2]
self.Fmat[:, ::2] = Fmat[:, 1::2]
def test_adapt_t_process_prior(self):
"""Test that red noise signal returns correct values."""
# set up signal parameter
pr = gp_priors.t_process_adapt(
log10_A=parameter.Uniform(-18, -12),
gamma=parameter.Uniform(1, 7),
alphas_adapt=gp_priors.InvGamma(),
nfreq=parameter.Uniform(5, 25),
)
basis = gp_bases.createfourierdesignmatrix_red(nmodes=30)
rn = gp_signals.BasisGP(priorFunction=pr,
basisFunction=basis,
name="red_noise")
rnm = rn(self.psr)
# parameters
alphas = scipy.stats.invgamma.rvs(1, scale=1, size=1)
log10_A, gamma, nfreq = -15, 4.33, 12
params = {
"B1855+09_red_noise_log10_A": log10_A,
"B1855+09_red_noise_gamma": gamma,
"B1855+09_red_noise_alphas_adapt": alphas,
"B1855+09_red_noise_nfreq": nfreq,
}
# basis matrix test
F, f2 = gp_bases.createfourierdesignmatrix_red(self.psr.toas,
nmodes=30)
msg = "F matrix incorrect for free spectrum."
assert np.allclose(F, rnm.get_basis(params)), msg
# spectrum test
phi = gp_priors.t_process_adapt(f2,
log10_A=log10_A,
gamma=gamma,
alphas_adapt=alphas,
nfreq=nfreq)
msg = "Spectrum incorrect for free spectrum."
assert np.all(rnm.get_phi(params) == phi), msg
# inverse spectrum test
msg = "Spectrum inverse incorrect for free spectrum."
assert np.all(rnm.get_phiinv(params) == 1 / phi), msg
# test shape
msg = "F matrix shape incorrect"
assert rnm.get_basis(params).shape == F.shape, msg