def test_qscale():
spec = np.array(["H2", "He", "H2O", "CO", "CO2", "CH4"])
bulk = np.array(['H2', 'He'])
molmodel = ['vert', 'scale']
molfree = ['H2O', 'CO']
molpars = [-4, 1.0]
q2 = pa.qscale(q0, spec, molmodel, molfree, molpars, bulk)
nlayers, nspec = np.shape(q0)
# All H2O abundances set to constant value:
np.testing.assert_equal(q2[:, 2], np.tile(10**molpars[0], nlayers))
# All CO abundances scaled by value:
np.testing.assert_allclose(q2[:, 3], q0[:, 3] * 10**molpars[1], rtol=1e-7)
def ZX(params, pyrat):
"""Compute metals mass fraction relative to solar."""
q2 = pa.qscale(pyrat.atm.qbase,
pyrat.mol.name,
pyrat.atm.molmodel,
pyrat.atm.molfree,
params[pyrat.ret.imol],
pyrat.atm.bulk,
iscale=pyrat.atm.ifree,
ibulk=pyrat.atm.ibulk,
bratio=pyrat.atm.bulkratio,
invsrat=pyrat.atm.invsrat)[0]
mu = pa.mean_weight(q2, pyrat.mol.name, mass=pyrat.mol.mass)[0]
Y = pyrat.mol.mass[iHe] * q2[iHe]
X = pyrat.mol.mass[iH] * (2 * q2[iH2] + q2[iH] + 2 * q2[iH2O] + q2[iHCN] +
4 * q2[iCH4])
Z = mu - X - Y
return np.log10(Z / X / (Zsun / Xsun))
def ZX(params, pyrat):
Zsun = 0.0134 # Asplund et al. 2009
Xsun = 0.7381
q2 = pa.qscale(pyrat.atm.qbase,
pyrat.mol.name,
pyrat.atm.molmodel,
pyrat.atm.molfree,
params[pyrat.ret.imol],
pyrat.atm.bulk,
iscale=pyrat.atm.ifree,
ibulk=pyrat.atm.ibulk,
bratio=pyrat.atm.bulkratio,
invsrat=pyrat.atm.invsrat)[0]
mu = pa.mean_weight(q2, pyrat.mol.name, mass=pyrat.mol.mass)[0]
Y = pyrat.mol.mass[iHe] * q2[iHe]
X = pyrat.mol.mass[iH] * (2 * q2[iH2] + q2[iH] + 2 * q2[iH2O] + q2[iHCN] +
4 * q2[iCH4])
Z = mu - X - Y
return np.log10(Z / X / (Zsun / Xsun))
posterior[:, itemp], pyrat.atm.tmodel,
pyrat.ret.params[pyrat.ret.itemp], ifree, pyrat.atm.press)
band_wl = 1.0 / (pyrat.obs.bandwn * pc.um)
contrib = np.zeros((nphase, nlayers))
abunds = atm_models[k]['abund']
temps = atm_models[k]['temp']
for i in range(nphase):
if k != 2 and i > 8:
continue
q2 = pa.qscale(pyrat.atm.qbase,
pyrat.mol.name,
pyrat.atm.molmodel,
pyrat.atm.molfree,
np.log10(abunds[4 * i]),
pyrat.atm.bulk,
iscale=pyrat.atm.ifree,
ibulk=pyrat.atm.ibulk,
bratio=pyrat.atm.bulkratio,
invsrat=pyrat.atm.invsrat)
pyrat.run(temps[4 * i], q2)
cf = ps.contribution_function(pyrat.od.depth, pyrat.atm.press, pyrat.od.B)
bcf = ps.band_cf(cf, pyrat.obs.bandtrans, pyrat.spec.wn, pyrat.obs.bandidx)
bcf = np.sum(bcf, axis=1)
contrib[i] = bcf / np.amax(bcf)
molecs = 'H2O CO CO2 CH4'.split()
nmol = len(molecs)
ranges = [(-5.5, -1.0), (-12.0, -1.0), (-12.0, -1.0), (-12.0, -1.0)]
nbins = 100
npars = np.shape(post)[1]
# Unique posterior values:
utemp, uind, uinv = np.unique(post[:, 0],
return_index=True,
return_inverse=True)
nunique = np.size(uind)
upost = post[uind]
# Base atmospheric model:
spec, press, t, q = pa.readatm("../run01/uniform_1500K_1xsolar.atm")
# Get mean molecular mass:
mu = np.zeros(nunique, np.double)
for i in np.arange(nunique):
q2 = pa.qscale(q, spec, upost[i, 2:7], molscale, bulk)
mu[i] = pa.meanweight(q2, spec)[0]
# Radius in Jupiter radii:
post[:, 1] *= pc.km / pc.rjup
# Move mols one position up:
post[:, 3] = post[:, 4] # CH4
post[:, 4] = post[:, 5] # HCN
post[:, 5] = post[:, 6] # NH3
# Replace with mean molecular weight:
post[:, 6] = mu[uinv]
pname = [
r"$T$ (K)", "Radius ($R_{\\rm Jup}$)", "$\log_{10}({\\rm H2O})$",
"$\log_{10}({\\rm CH4})$", "$\log_{10}({\\rm HCN})$",