def eval_baryon_density(self, p):
if isinstance(p, list) or isinstance(p, np.ndarray):
rho = np.zeros(len(p))
for i, pres in enumerate(p):
rho [i] = lalsim.SimNeutronStarEOSRestMassDensityOfPseudoEnthalpy(
lalsim.SimNeutronStarEOSPseudoEnthalpyOfPressure(pres,self.eos), self.eos)
else:
rho = lalsim.SimNeutronStarEOSRestMassDensityOfPseudoEnthalpy(
lalsim.SimNeutronStarEOSPseudoEnthalpyOfPressure(p,self.eos), self.eos)
return rho
def pressure_density_on_grid(self,
logrho_grid,
reference_pair=None,
enforce_causal=False):
"""
pressure_density_on_grid.
Input and output grid units are in SI (rho: kg/m^3; p = N/m^2)
POTENTIAL PROBLEMS OF USING LALSUITE
- lalinference_o2 / master: Unless patched, the *rest mass* density is not reliable.
To test with the unpatched LI version, use reference_pair to specify a low-density EOS.
This matching is highly suboptimal, so preferably test either (a) a patched code or (b) the alternative code below
"""
dat_out = np.zeros(len(logrho_grid))
fam = self.eos_fam
eos = self.eos
npts_internal = 10000
p_internal = np.zeros(npts_internal)
rho_internal = np.zeros(npts_internal)
hmax = lalsim.SimNeutronStarEOSMaxPseudoEnthalpy(eos)
if enforce_causal:
# strip out everything except the causal part.
hmax = lalsim.SimNeutronStarEOSMinAcausalPseudoEnthalpy(eos)
h = np.linspace(0.0001, hmax, npts_internal)
for indx in np.arange(npts_internal):
rho_internal[
indx] = lalsim.SimNeutronStarEOSRestMassDensityOfPseudoEnthalpy(
h[indx], eos) # SI. Multiply by 10^(-3) to get CGS
p_internal[
indx] = lalsim.SimNeutronStarEOSPressureOfPseudoEnthalpy(
h[indx], eos) # SI. Multiply by 10 to get CGS
if not (reference_pair is None):
indx_match = np.argmin(
np.abs(np.log10(p_internal) - np.log10(reference_pair[1]))
) # force agreement of densities at target pressure, if requested! Addresses bug /ambiguity in scaling of rest mass estimate; intend to apply in highly nonrelativistic regime
delta_rho = np.log10(reference_pair[0]) - np.log10(
rho_internal[indx_match])
rho_internal *= np.power(10, delta_rho)
# print np.log10(np.c_[rho_internal,p_internal])
logp_of_logrho = interp.interp1d(
np.log10(rho_internal),
np.log10(p_internal),
kind='linear',
bounds_error=False,
fill_value=np.inf) # should change to Monica's spline
# print logrho_grid,
return logp_of_logrho(logrho_grid)
logp1[i] - 1, gamma1[i], gamma2[i], gamma3[i])
if model == 'spectral':
eos = lalsim.SimNeutronStarEOSSpectralDecomposition_for_plot(
sd_gamma0[i], sd_gamma1[i], sd_gamma2[i], sd_gamma3[i],
spec_size)
assert eos is not None
fam = lalsim.CreateSimNeutronStarFamily(eos)
h = np.linspace(0.0001, lalsim.SimNeutronStarEOSMaxPseudoEnthalpy(eos),
10000)
rho = []
p = []
# Populates p(h) and rho(h) arrays given your enthalpy array
for k in range(len(h)):
# With CGS conversions
rho.append(
lalsim.SimNeutronStarEOSRestMassDensityOfPseudoEnthalpy(
h[k], eos) * .001)
#print h[k], "here 1"
p.append(
lalsim.SimNeutronStarEOSPressureOfPseudoEnthalpy(h[k], eos) *
10)
#print h[k], "here 2"
# Creates a callable function for logp(logrho)
logp_of_logrho = interp.interp1d(np.log10(rho),
np.log10(p),
kind='linear')
# Loop over density (rho) bins
for j in range(len(logr)):
if logr[j] <= max(np.log10(rho)):
logp["%g" % logr[j]].append(logp_of_logrho(logr[j]))
#else:
# logp["%g"%logr[j]].append(None)