def initialPT2(date_dir, params, pressfile, mode, PTfunc, tepfile, tint=100.0):
"""
Compute a Temperature profile.
Parameters:
-----------
params: 1D Float ndarray
Array of fitting parameters.
pressfile: String
File name of the pressure array.
mode: String
Chose the PT model: 'madhu' or 'line'.
tepfile: String
Filename of the planet's TEP file.
tint: Float
Internal planetary temperature.
"""
# Read pressures from file:
pressure = pt.read_press_file(pressfile)
# For extra PT arguments:
PTargs = None
# Read the TEP file:
tep = rd.File(tepfile)
# Stellar radius (in meters):
rstar = float(tep.getvalue('Rs')[0]) * c.Rsun
# Stellar temperature in K:
tstar = float(tep.getvalue('Ts')[0])
# Semi-major axis (in meters):
sma = float(tep.getvalue( 'a')[0]) * sc.au
# Planetary radius (in meters):
rplanet = float(tep.getvalue('Rp')[0]) * c.Rjup
# Planetary mass (in kg):
mplanet = float(tep.getvalue('Mp')[0]) * c.Mjup
if mode == "line":
# Planetary surface gravity (in cm s-2):
gplanet = 100.0 * sc.G * mplanet / rplanet**2
# Additional PT arguments for Line case:
PTargs = [rstar, tstar, tint, sma, gplanet]
# Calculate temperature
Temp = pt.PT_generator(pressure, params, PTfunc, PTargs)
# Plot PT profile
plt.figure(1)
plt.semilogy(Temp, pressure, '-', color = 'r')
plt.xlim(0.9*min(Temp), 1.1*max(Temp))
plt.ylim(max(pressure), min(pressure))
plt.title('Initial PT Line', fontsize=14)
plt.xlabel('T (K)' , fontsize=14)
plt.ylabel('logP (bar)', fontsize=14)
# Save plot to current directory
plt.savefig(date_dir + 'InitialPT.png')
return Temp
def callTransit(atmfile,
tepfile,
MCfile,
stepsize,
molfit,
solution,
p0,
tconfig,
date_dir,
burnin,
abun_file,
PTtype,
PTfunc,
T_int,
T_int_type,
filters,
ctf=None,
fs=15):
"""
Call Transit to produce best-fit outputs.
Plot MCMC posterior PT plot.
Parameters:
-----------
atmfile: String
Atmospheric file.
tepfile: String
Transiting extra-solar planet file.
MCfile: String
File with MCMC log and best-fitting results.
stepsize: 1D float ndarray
Specified step sizes for each parameter.
molfit: 1D String ndarray
List of molecule names to modify their abundances.
solution: String
Flag to indicate transit or eclipse geometry
p0: Float
Atmosphere's 'surface' pressure level.
tconfig: String
Transit configuration file.
date_dir: String
Directory where to store results.
burnin: Integer
abun_file: String
Elemental abundances file.
PTtype: String
Pressure-temperature profile type ('line' for Line et al. 2013,
'madhu_noinv' or 'madhu_inv' for Madhusudhan & Seager 2009,
'iso' for isothermal)
PTfunc: pointer to function
Determines the method of evaluating the PT profile's temperature
T_int: float.
Internal temperature of the planet.
T_int_type: string.
Method to evaluate `T_int`.
'const' for constant value of `T_int`,
'thorngren' for Thorngren et al. (2019)
filters: list, strings.
Filter files associated with the eclipse/transit depths
ctf: 2D array.
Contribution or transmittance functions corresponding to `filters`
fs: int
Font size for plots.
"""
# make sure burnin is an integer
burnin = int(burnin)
# read atmfile
molecules, pressure, temp, abundances = mat.readatm(atmfile)
# get surface gravity
grav, Rp = mat.get_g(tepfile)
# get star data if needed
if PTtype == 'line':
R_star, T_star, sma, gstar = get_starData(tepfile)
PTargs = [R_star, T_star, T_int, sma, grav * 1e2, T_int_type]
else:
PTargs = None # For non-Line profiles
# Get best parameters
bestP, uncer = read_MCMC_out(MCfile)
allParams = bestP
# get PTparams and abundances factors
nparams = len(allParams)
nmol = len(molfit)
nradfit = int(solution == 'transit')
nPTparams = nparams - nmol - nradfit
PTparams = allParams[:nPTparams]
# call PT profile generator to calculate temperature
best_T = pt.PT_generator(pressure, PTparams, PTfunc, PTargs)
# Plot best PT profile
plt.figure(1)
plt.clf()
plt.semilogy(best_T, pressure, '-', color='r')
plt.xlim(0.9 * min(best_T), 1.1 * max(best_T))
plt.ylim(max(pressure), min(pressure))
plt.title('Best PT', fontsize=fs)
plt.xlabel('T (K)', fontsize=fs)
plt.ylabel('logP (bar)', fontsize=fs)
# Save plot to current directory
plt.savefig(date_dir + 'Best_PT.png')
# Update R0, if needed:
if nradfit:
Rp = allParams[nPTparams]
# write best-fit atmospheric file
write_atmfile(atmfile, abun_file, molfit, best_T,
allParams[nPTparams + nradfit:], date_dir, p0, Rp, grav)
# write new bestFit Transit config
if solution == 'transit':
bestFit_tconfig(tconfig, date_dir, allParams[nPTparams])
else:
bestFit_tconfig(tconfig, date_dir)
# Call Transit with the best-fit tconfig
Transitdir = os.path.join(os.path.dirname(os.path.realpath(__file__)),
"..", "modules", "transit", "")
bf_tconfig = os.path.join(date_dir, 'bestFit_tconfig.cfg')
Tcall = os.path.join(Transitdir, "transit", "transit")
subprocess.call(["{:s} -c {:s}".format(Tcall, bf_tconfig)],
shell=True,
cwd=date_dir)
# ========== plot MCMC PT profiles ==========
# get MCMC data:
MCMCdata = os.path.join(date_dir, "output.npy")
data = np.load(MCMCdata)
nchains, npars, niter = np.shape(data)
# stuck chains:
data_stack = data[0, :, burnin:]
for c in np.arange(1, nchains):
data_stack = np.hstack((data_stack, data[c, :, burnin:]))
# create array of PT profiles
PTprofiles = np.zeros((np.shape(data_stack)[1], len(pressure)))
# current PT parameters for each chain, iteration
curr_PTparams = PTparams
# fill-in PT profiles array
if ctf is None:
print(" Plotting MCMC PT profile figure.")
for k in np.arange(0, np.shape(data_stack)[1]):
j = 0
for i in np.arange(len(PTparams)):
if stepsize[i] != 0.0:
curr_PTparams[i] = data_stack[j, k]
j += 1
else:
pass
PTprofiles[k] = pt.PT_generator(pressure, curr_PTparams, PTfunc,
PTargs)
# get percentiles (for 1,2-sigma boundaries):
low1 = np.percentile(PTprofiles, 15.87, axis=0)
hi1 = np.percentile(PTprofiles, 84.13, axis=0)
low2 = np.percentile(PTprofiles, 2.28, axis=0)
hi2 = np.percentile(PTprofiles, 97.72, axis=0)
median = np.median(PTprofiles, axis=0)
# plot figure
plt.figure(2, dpi=300)
plt.clf()
if ctf is not None:
plt.subplots_adjust(wspace=0.15)
ax1 = plt.subplot(121)
else:
ax1 = plt.subplot(111)
ax1.fill_betweenx(pressure,
low2,
hi2,
facecolor="#62B1FF",
edgecolor="0.5")
ax1.fill_betweenx(pressure,
low1,
hi1,
facecolor="#1873CC",
edgecolor="#1873CC")
plt.semilogy(median, pressure, "-", lw=2, label='Median', color="k")
plt.semilogy(best_T, pressure, "-", lw=2, label="Best fit", color="r")
plt.ylim(pressure[0], pressure[-1])
plt.legend(loc="best")
plt.xlabel("Temperature (K)", size=fs)
plt.ylabel("Pressure (bar)", size=fs)
if ctf is not None:
nfilters = len(filters)
# Add contribution or transmittance functions
ax2 = plt.subplot(122, sharey=ax1)
colormap = plt.cm.rainbow(np.linspace(0, 1, len(filters)))
ax2.set_prop_cycle(plt.cycler('color', colormap))
# Plot with filter labels
for i in np.arange(len(filters)):
(head, tail) = os.path.split(filters[i])
lbl = tail[:-4]
ax2.semilogy(ctf[i], pressure, '--', linewidth=1, label=lbl)
# Hide y axis tick labels
plt.setp(ax2.get_yticklabels(), visible=False)
# Place legend off figure in case there are many filters
lgd = ax2.legend(loc='center left',
bbox_to_anchor=(1.05, 0.5),
ncol=nfilters // 25 + int(nfilters % 25 != 0),
prop={'size': 8})
if solution == 'eclipse':
ax2.set_xlabel('Normalized Contribution\nFunctions', fontsize=fs)
else:
ax2.set_xlabel('Transmittance', fontsize=fs)
# save figure
if ctf is not None:
savefile = date_dir + "MCMC_PTprofiles_cf.png"
plt.savefig(savefile, bbox_extra_artists=(lgd, ), bbox_inches='tight')
else:
savefile = date_dir + "MCMC_PTprofiles.png"
plt.savefig(savefile)
plt.close()
def main(comm):
"""
This is a hacked version of MC3's func.py.
This function directly call's the modeling function for the BART project.
"""
# Parse arguments:
cparser = argparse.ArgumentParser(
description=__doc__,
add_help=False,
formatter_class=argparse.RawDescriptionHelpFormatter)
# Add config file option:
cparser.add_argument("-c",
"--config_file",
help="Configuration file",
metavar="FILE")
# Remaining_argv contains all other command-line-arguments:
args, remaining_argv = cparser.parse_known_args()
# Get parameters from configuration file:
cfile = args.config_file
if cfile:
config = ConfigParser.SafeConfigParser()
config.optionxform = str
config.read([cfile])
defaults = dict(config.items("MCMC"))
else:
defaults = {}
parser = argparse.ArgumentParser(parents=[cparser])
parser.add_argument("--func",
dest="func",
type=mu.parray,
action="store",
default=None)
parser.add_argument("--indparams",
dest="indparams",
type=mu.parray,
action="store",
default=[])
parser.add_argument("--params",
dest="params",
type=mu.parray,
action="store",
default=None,
help="Model-fitting parameters [default: %(default)s]")
parser.add_argument("--molfit",
dest="molfit",
type=mu.parray,
action="store",
default=None,
help="Molecules fit [default: %(default)s]")
parser.add_argument(
"--Tmin",
dest="Tmin",
type=float,
action="store",
default=400.0,
help="Lower Temperature boundary [default: %(default)s]")
parser.add_argument(
"--Tmax",
dest="Tmax",
type=float,
action="store",
default=3000.0,
help="Higher Temperature boundary [default: %(default)s]")
parser.add_argument("--quiet",
action="store_true",
help="Set verbosity level to minimum",
dest="quiet")
# Input-Converter Options:
group = parser.add_argument_group("Input Converter Options")
group.add_argument("--atmospheric_file",
action="store",
help="Atmospheric file [default: %(default)s]",
dest="atmfile",
type=str,
default=None)
group.add_argument("--PTtype",
action="store",
help="PT profile type.",
dest="PTtype",
type=str,
default="none")
group.add_argument("--tint",
action="store",
help="Internal temperature of the planet [default: "
"%(default)s].",
dest="tint",
type=float,
default=100.0)
# transit Options:
group = parser.add_argument_group("transit Options")
group.add_argument(
"--config",
action="store",
help="transit configuration file [default: %(default)s]",
dest="config",
type=str,
default=None)
# Output-Converter Options:
group = parser.add_argument_group("Output Converter Options")
group.add_argument("--filters",
action="store",
help="Waveband filter name [default: %(default)s]",
dest="filters",
type=mu.parray,
default=None)
group.add_argument("--tep_name",
action="store",
help="A TEP file [default: %(default)s]",
dest="tep_name",
type=str,
default=None)
group.add_argument("--kurucz_file",
action="store",
help="Stellar Kurucz file [default: %(default)s]",
dest="kurucz",
type=str,
default=None)
group.add_argument("--solution",
action="store",
help="Solution geometry [default: %(default)s]",
dest="solution",
type=str,
default="None",
choices=('transit', 'eclipse'))
parser.set_defaults(**defaults)
args2, unknown = parser.parse_known_args(remaining_argv)
# Quiet all threads except rank 0:
rank = comm.Get_rank()
verb = rank == 0
# Get (Broadcast) the number of parameters and iterations from MPI:
array1 = np.zeros(2, np.int)
mu.comm_bcast(comm, array1)
npars, niter = array1
# ::::::: Initialize the Input converter ::::::::::::::::::::::::::
atmfile = args2.atmfile
molfit = args2.molfit
PTtype = args2.PTtype
params = args2.params
tepfile = args2.tep_name
tint = args2.tint
Tmin = args2.Tmin
Tmax = args2.Tmax
solution = args2.solution # Solution type
# Dictionary of functions to calculate temperature for PTtype
PTfunc = {
'iso': pt.PT_iso,
'line': pt.PT_line,
'madhu_noinv': pt.PT_NoInversion,
'madhu_inv': pt.PT_Inversion
}
# Extract necessary values from the TEP file:
tep = rd.File(tepfile)
# Stellar temperature in K:
tstar = float(tep.getvalue('Ts')[0])
# Stellar radius (in meters):
rstar = float(tep.getvalue('Rs')[0]) * c.Rsun
# Semi-major axis (in meters):
sma = float(tep.getvalue('a')[0]) * sc.au
# Planetary radius (in meters):
rplanet = float(tep.getvalue('Rp')[0]) * c.Rjup
# Planetary mass (in kg):
mplanet = float(tep.getvalue('Mp')[0]) * c.Mjup
# Number of fitting parameters:
nfree = len(params) # Total number of free parameters
nmolfit = len(molfit) # Number of molecular free parameters
nradfit = int(solution == 'transit') # 1 for transit, 0 for eclipse
nPT = nfree - nmolfit - nradfit # Number of PT free parameters
# Read atmospheric file to get data arrays:
species, pressure, temp, abundances = mat.readatm(atmfile)
# Reverse pressure order (for PT to work):
pressure = pressure[::-1]
nlayers = len(pressure) # Number of atmospheric layers
nspecies = len(species) # Number of species in the atmosphere
mu.msg(verb,
"There are {:d} layers and {:d} species.".format(nlayers, nspecies))
# Find index for Hydrogen and Helium:
species = np.asarray(species)
iH2 = np.where(species == "H2")[0]
iHe = np.where(species == "He")[0]
# Get H2/He abundance ratio:
ratio = (abundances[:, iH2] / abundances[:, iHe]).squeeze()
# Find indices for the metals:
imetals = np.where((species != "He") & (species != "H2") & \
(species != "H-") & (species != 'e-'))[0]
# Index of molecular abundances being modified:
imol = np.zeros(nmolfit, dtype='i')
for i in np.arange(nmolfit):
imol[i] = np.where(np.asarray(species) == molfit[i])[0]
# Pressure-Temperature profile:
if PTtype == "line":
# Planetary surface gravity (in cm s-2):
gplanet = 100.0 * sc.G * mplanet / rplanet**2
# Additional PT arguments:
PTargs = [rstar, tstar, tint, sma, gplanet]
else:
PTargs = None
# Allocate arrays for receiving and sending data to master:
freepars = np.zeros(nfree, dtype='d')
profiles = np.zeros((nspecies + 1, nlayers), dtype='d')
# This are sub-sections of profiles, containing just the temperature and
# the abundance profiles, respectively:
tprofile = profiles[0, :]
aprofiles = profiles[1:, :]
# Store abundance profiles:
for i in np.arange(nspecies):
aprofiles[i] = abundances[:, i]
# ::::::: Spawn transit code :::::::::::::::::::::::::::::::::::::
# # transit configuration file:
transitcfile = args2.tconfig
# Initialize the transit python module:
transit_args = ["transit", "-c", transitcfile]
trm.transit_init(len(transit_args), transit_args)
# Get wavenumber array from transit:
nwave = trm.get_no_samples()
specwn = trm.get_waveno_arr(nwave)
# ::::::: Output Converter :::::::::::::::::::::::::::::::::::::::
ffile = args2.filters # Filter files
kurucz = args2.kurucz # Kurucz file
# Log10(stellar gravity)
gstar = float(tep.getvalue('loggstar')[0])
# Planet-to-star radius ratio:
rprs = rplanet / rstar
nfilters = len(ffile) # Number of filters:
# FINDME: Separate filter/stellar interpolation?
# Get stellar model:
starfl, starwn, tmodel, gmodel = w.readkurucz(kurucz, tstar, gstar)
# Read and resample the filters:
nifilter = [] # Normalized interpolated filter
istarfl = [] # interpolated stellar flux
wnindices = [] # wavenumber indices used in interpolation
for i in np.arange(nfilters):
# Read filter:
filtwaven, filttransm = w.readfilter(ffile[i])
# Check that filter boundaries lie within the spectrum wn range:
if filtwaven[0] < specwn[0] or filtwaven[-1] > specwn[-1]:
mu.exit(message="Wavenumber array ({:.2f} - {:.2f} cm-1) does not "
"cover the filter[{:d}] wavenumber range ({:.2f} - {:.2f} "
"cm-1).".format(specwn[0], specwn[-1], i, filtwaven[0],
filtwaven[-1]))
# Resample filter and stellar spectrum:
nifilt, strfl, wnind = w.resample(specwn, filtwaven, filttransm,
starwn, starfl)
nifilter.append(nifilt)
istarfl.append(strfl)
wnindices.append(wnind)
# Allocate arrays for receiving and sending data to master:
spectrum = np.zeros(nwave, dtype='d')
bandflux = np.zeros(nfilters, dtype='d')
# Allocate array to receive parameters from MPI:
params = np.zeros(npars, np.double)
# :::::: Main MCMC Loop ::::::::::::::::::::::::::::::::::::::::::
# ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
while niter >= 0:
niter -= 1
# Receive parameters from MCMC:
mu.comm_scatter(comm, params)
# Check for the MCMC-end flag:
if params[0] == np.inf:
break
# Input converter calculate the profiles:
try:
tprofile[:] = pt.PT_generator(pressure, params[0:nPT],
PTfunc[PTtype], PTargs)[::-1]
except ValueError:
mu.msg(verb, 'Input parameters give non-physical profile.')
# FINDME: what to do here?
# If the temperature goes out of bounds:
if np.any(tprofile < Tmin) or np.any(tprofile > Tmax):
mu.comm_gather(comm, -np.ones(nfilters), MPI.DOUBLE)
continue
# Scale abundance profiles:
for i in np.arange(nmolfit):
m = imol[i]
# Use variable as the log10:
aprofiles[m] = abundances[:, m] * 10.0**params[nPT + nradfit + i]
# Update H2, He abundances so sum(abundances) = 1.0 in each layer:
q = 1.0 - np.sum(aprofiles[imetals], axis=0)
if np.any(q < 0.0):
mu.comm_gather(comm, -np.ones(nfilters), MPI.DOUBLE)
continue
aprofiles[iH2] = ratio * q / (1.0 + ratio)
aprofiles[iHe] = q / (1.0 + ratio)
# Set the 'surface' level:
if solution == "transit":
trm.set_radius(params[nPT])
# Let transit calculate the model spectrum:
spectrum = trm.run_transit(profiles.flatten(), nwave)
# Calculate the band-integrated intensity per filter:
for i in np.arange(nfilters):
if solution == "eclipse":
fluxrat = (spectrum[wnindices[i]] / istarfl[i]) * rprs * rprs
bandflux[i] = w.bandintegrate(fluxrat, specwn, nifilter[i],
wnindices[i])
elif solution == "transit":
bandflux[i] = w.bandintegrate(spectrum[wnindices[i]], specwn,
nifilter[i], wnindices[i])
# Send resutls back to MCMC:
mu.comm_gather(comm, bandflux, MPI.DOUBLE)
# :::::: End main Loop :::::::::::::::::::::::::::::::::::::::::::
# ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
# Close communications and disconnect:
mu.comm_disconnect(comm)
trm.free_memory()
