inputIsDouble, gridsize):
ion = rf.read_ion(infile, isPadded, inputIsDouble, gridsize)
dens = rf.read_dens(densfile, isPadded, double_precision, gridsize)
meanIon = np.mean(ion * dens, dtype=np.float64) / np.mean(dens,
dtype=np.float64)
return meanIon
inifile = sys.argv[1]
inputIsDouble = np.int32(sys.argv[2])
outputfile = sys.argv[3]
lines = rp.read_inifile(inifile)
redshiftfile = rp.identify_string(lines, rp.redshiftfile_str,
rp.splitting_str) #sys.argv[4]
ionfile = rp.identify_string(lines, rp.ionfile_str,
rp.splitting_str) #sys.argv[1]
densfile = rp.identify_string(lines, rp.densfile_str, rp.splitting_str)
double_precision = rp.identify_int(lines, rp.double_precision_str,
rp.splitting_str)
isPadded = rp.identify_int(lines, rp.padded_str,
rp.splitting_str) #np.int32(sys.argv[3])
isPadded_factor = isPadded**(1. / 3.)
if (isPadded != 0):
gridsize = np.int32(
rp.identify_int(lines, rp.gridsize_str, rp.splitting_str) /
isPadded_factor)
boxsize = rp.identify_float(lines, rp.boxsize_str,
rp.splitting_str) / isPadded_factor
def redshift_from_time_flatuniverse(zmax, time):
tmp = (omega_l / omega_m)**0.5
tmp2 = np.sinh(1.5 * H0 * omega_l**0.5 * time +
np.arcsinh(tmp * (1. + zmax)**-1.5))
return (tmp / tmp2)**(2. / 3.) - 1.
inifile = sys.argv[1]
inputIsDouble = np.int32(sys.argv[2])
cut_slice = int(sys.argv[3])
lines = rp.read_inifile(inifile)
redshiftfile = rp.identify_string(lines, rp.redshiftfile_str, rp.splitting_str)
ionfile = rp.identify_string(lines, rp.ionfile_str, rp.splitting_str)
double_precision = rp.identify_int(lines, rp.double_precision_str,
rp.splitting_str)
isPadded = rp.identify_int(lines, rp.padded_str, rp.splitting_str)
isPadded_factor = isPadded**(1. / 3.)
if (isPadded != 0):
gridsize = np.int32(
rp.identify_int(lines, rp.gridsize_str, rp.splitting_str) /
isPadded_factor)
boxsize = rp.identify_float(lines, rp.boxsize_str,
rp.splitting_str) / isPadded_factor
else:
gridsize = rp.identify_int(lines, rp.gridsize_str, rp.splitting_str)
boxsize = rp.identify_float(lines, rp.boxsize_str, rp.splitting_str)