# get list of R matrices
R = [PALutils.createRmatrix(p.dmatrix, p.err) for p in psr]
L = []
for ct, p in enumerate(psr):
Amp = p.Amp
gam = p.gam
efac = p.efac
equad = p.equad
try:
cequad = p.cequad
except AttributeError:
cequad = 0
avetoas, U = PALutils.exploderMatrix(p.toas)
Tspan = p.toas.max()-p.toas.min()
F, f = PALutils.createfourierdesignmatrix(p.toas, 10, freq=True, Tspan=Tspan)
f1yr = 1/3.16e7
rho = (Amp**2/12/np.pi**2 * f1yr**(gam-3) * f**(-gam)/Tspan)
tmp = np.zeros(20)
tmp[0::2] = rho
tmp[1::2] = rho
phi = np.diag(tmp)
white = PALutils.createWhiteNoiseCovarianceMatrix(p.err, efac**2, equad)
cequad_mat = cequad**2 * np.dot(U,U.T)
# get list of R matrices
R = [PALutils.createRmatrix(p.dmatrix, p.err) for p in psr]
L = []
for ct, p in enumerate(psr):
Amp = p.Amp
gam = p.gam
efac = p.efac
equad = p.equad
try:
cequad = p.cequad
except AttributeError:
cequad = 0
avetoas, U = PALutils.exploderMatrix(p.toas)
Tspan = p.toas.max() - p.toas.min()
F, f = PALutils.createfourierdesignmatrix(p.toas,
10,
freq=True,
Tspan=Tspan)
f1yr = 1 / 3.16e7
rho = (Amp**2 / 12 / np.pi**2 * f1yr**(gam - 3) * f**(-gam) / Tspan)
tmp = np.zeros(20)
tmp[0::2] = rho
tmp[1::2] = rho
phi = np.diag(tmp)
