tt=[]
for p in psr:
tt.append(np.min(p.toas))
# find reference time
tref = np.min(tt)
# now scale pulsar time
for p in psr:
p.toas -= tref
# create list of reference residuals
res = [p.res for p in psr]
# 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()
# define the pulsargroup
pulsargroup = pfile['Data']['Pulsars']
# fill in pulsar class
psr = [PALpulsarInit.pulsar(pulsargroup[key],addNoise=True, addGmatrix=True) \
for key in pulsargroup]
# number of pulsars
npsr = len(psr)
# create list of reference residuals
res = [p.res for p in psr]
# get list of R matrices
R = [PALutils.createRmatrix(p.dmatrix, p.err) for p in psr]
# pre-compute noise covariance matrices
ct = 0
D = []
Dmatrix = []
print 'Computing diagonalized auto-covariance matrices'
for key in pulsargroup:
# get noise values from file TODO: change this to read directly from pulsar class
Amp = pulsargroup[key]['Amp'].value
gam = pulsargroup[key]['gam'].value
efac = pulsargroup[key]['efac'].value
equad = pulsargroup[key]['equad'].value
try:
# TODO: is this a very round about way to do this?
index = []
for ct,p in enumerate(pp):
if p.name == psr[ct].name:
index.append(ct)
else:
for ii in range(npsr):
if pp[ii].name == psr[ct].name:
index.append(ii)
pp = [pp[ii] for ii in index]
M = [PALutils.createQSDdesignmatrix(p.toas) for p in psr]
RQ = [PALutils.createRmatrix(M[ct], p.err) for ct, p in enumerate(psr)]
# construct noise matrix for new noise realizations
print 'Constructing noise cholesky decompositions'
L = []
for ct, p in enumerate(psr):
Amp = p.Amp
gam = p.gam
efac = p.efac
equad = p.equad
cequad = p.cequad
avetoas, U = PALutils.exploderMatrix(p.toas)
Tspan = p.toas.max()-p.toas.min()
F, f = PALutils.createfourierdesignmatrix(p.toas, 10, freq=True, Tspan=Tspan)
# TODO: is this a very round about way to do this?
index = []
for ct, p in enumerate(pp):
if p.name == psr[ct].name:
index.append(ct)
else:
for ii in range(npsr):
if pp[ii].name == psr[ct].name:
index.append(ii)
pp = [pp[ii] for ii in index]
M = [PALutils.createQSDdesignmatrix(p.toas) for p in psr]
RQ = [PALutils.createRmatrix(M[ct], p.err) for ct, p in enumerate(psr)]
# construct noise matrix for new noise realizations
print 'Constructing noise cholesky decompositions'
L = []
for ct, p in enumerate(psr):
Amp = p.Amp
gam = p.gam
efac = p.efac
equad = p.equad
cequad = p.cequad
avetoas, U = PALutils.exploderMatrix(p.toas)
Tspan = p.toas.max() - p.toas.min()
F, f = PALutils.createfourierdesignmatrix(p.toas,
