def _do_selection(self, psr, priorfn, basisfn, coefficients,
selection):
sel = selection(psr)
self._keys = list(sorted(sel.masks.keys()))
self._masks = [sel.masks[key] for key in self._keys]
self._prior, self._bases = {}, {}
self._params, self._coefficients = {}, {}
for key, mask in zip(self._keys, self._masks):
pnames = [psr.name, name, key]
pname = '_'.join([n for n in pnames if n])
self._prior[key] = priorfn(pname, psr=psr)
self._bases[key] = basisfn(pname, psr=psr)
for par in itertools.chain(self._prior[key]._params.values(),
self._bases[key]._params.values()):
self._params[par.name] = par
if coefficients and pyv3:
# we can only create GPCoefficients parameters if the basis
# can be constructed with default arguments
# (and does not change size)
self._construct_basis()
for key in self._keys:
pname = '_'.join([n for n in [psr.name, name, key] if n])
chain = itertools.chain(self._prior[key]._params.values(),
self._bases[key]._params.values())
priorargs = {
par.name: self._params[par.name]
for par in chain
}
logprior = parameter.Function(
functools.partial(self._get_coefficient_logprior, key),
**priorargs)
size = self._slices[key].stop - self._slices[key].start
cpar = parameter.GPCoefficients(logprior=logprior,
size=size)(pname +
'_coefficients')
self._coefficients[key] = cpar
self._params[cpar.name] = cpar
def __init__(self, psr):
super(BasisCommonGP, self).__init__(psr)
self.name = self.psrname + "_" + self.signal_id
pname = "_".join([psr.name, name])
self._bases = basisFunction(pname, psr=psr)
self._params, self._coefficients = {}, {}
for par in itertools.chain(self._prior._params.values(),
self._orf._params.values(),
self._bases._params.values()):
self._params[par.name] = par
rand_state = np.int(np.abs(np.sum(psr.pos)) * 10000)
ra = uniform.rvs(loc=0, scale=2 * np.pi, random_state=rand_state)
dec = cosine.rvs(loc=0, scale=0.5, random_state=rand_state + 11)
newpos = np.array(SkyCoord(ra=ra*u.rad, \
dec=dec*u.rad).cartesian.xyz)
self._psrpos = psr.pos
self._psrpos_scrambled = newpos
if coefficients:
self._construct_basis()
# if we're given an instantiated coefficient vector
# that's what we will use
if isinstance(coefficients, parameter.Parameter):
self._coefficients[""] = coefficients
self._params[coefficients.name] = coefficients
return
chain = itertools.chain(self._prior._params.values(),
self._orf._params.values(),
self._bases._params.values())
priorargs = {par.name: self._params[par.name] for par in chain}
logprior = parameter.Function(self._get_coefficient_logprior,
**priorargs)
size = self._basis.shape[1]
cpar = parameter.GPCoefficients(
logprior=logprior, size=size)(pname + "_coefficients")
self._coefficients[""] = cpar
self._params[cpar.name] = cpar
def __init__(self, psr):
super(BasisCommonGP, self).__init__(psr)
self.name = self.psrname + '_' + self.signal_id
pname = '_'.join([psr.name, name])
self._bases = basisFunction(pname, psr=psr)
self._params, self._coefficients = {}, {}
for par in itertools.chain(self._prior._params.values(),
self._orf._params.values(),
self._bases._params.values()):
self._params[par.name] = par
self._psrpos = psr.pos
if coefficients and pyv3:
self._construct_basis()
# if we're given an instantiated coefficient vector
# that's what we will use
if isinstance(coefficients, parameter.Parameter):
self._coefficients[''] = coefficients
self._params[coefficients.name] = coefficients
return
chain = itertools.chain(self._prior._params.values(),
self._orf._params.values(),
self._bases._params.values())
priorargs = {par.name: self._params[par.name] for par in chain}
logprior = parameter.Function(self._get_coefficient_logprior,
**priorargs)
size = self._basis.shape[1]
cpar = parameter.GPCoefficients(
logprior=logprior, size=size)(pname + '_coefficients')
self._coefficients[''] = cpar
self._params[cpar.name] = cpar