# grid of scalar radius from center (in units of cell size)
rr = numpy.sqrt((x - xc)**2 + (y - yc)**2 + (z - zc)**2)
# components of unit radius vector from center
ux, uy, uz = (x - xc) / rr, (y - yc) / rr, (z - zc) / rr
# rescale radius to be in parsecs
rr *= args.boxsize/nx
# radial velocity is dot product of vector velocity with unit radius vector
vr = vx*ux + vy*uy + vz*uz
# rescale velocities to be in km/s
vr /= 1.e5
import molfrac
xmol = molfrac.molfrac(AV)
# List of weights will produce RGB pdf images
weights = [
xn*xmol, # molecular
xn*(1.0-xmol), # neutral
1.0-xn # ionized
]
# Now make the plots
import pyx
pyx.text.set(mode="latex")
# pyx.text.preamble("""\usepackage{mathptmx}""")
bivar.printextra = 0
bivar.Graph.figwidth = 6
raise NotImplementedError("Only Ostar and Bstar are implemented, sorry!")
savedir = "lya-%s-%4.4i" % (args.runid, args.itime)
if not os.path.isdir(savedir):
os.mkdir(savedir)
vx, vy, vz, xn, av, dd, te = [load_fits(id) for id in ["vx", "vy", "vz", "xn", "AV", "dd", "te"]]
x, y, z, = numpy.ogrid[0 : star.nxg, 0 : star.nyg, 0 : star.nzg] # grid coordinates
# grid of scalar radius from center (in units of cell size)
rr = numpy.sqrt((x - star.i0) ** 2 + (y - star.j0) ** 2 + (z - star.k0) ** 2)
rr[rr == 0] = 1.0
rr *= star.xmax / star.nxg # convert to cm
mm = molfrac.molfrac(av)
ni = dd * (1.0 - xn) / MP / MU
nn = dd * xn * (1.0 - mm) / MP / MU
nm = dd * xn * mm / MP / MU
ly = lya_emissivity(ni, te)
jc = fuv_field(av, rr)
print jc.max(), jc.min()
jc *= star.qh0 * star.fuv_euv_ratio / (4 * pi)
print jc.max(), jc.min()
for id, data in [
["temperature", te],
["vel_x", vx],
["vel_y", vy],
["vel_z", vz],
["n_hi", nn],
