import numpy as np
from hyperion.model import Model
from hyperion.util.constants import pc, lsun
# Initialize model
m = Model()
# Set one-cell cartesian grid
w = np.linspace(-pc, pc, 32)
m.set_cartesian_grid(w, w, w)
# Add density grid with constant density
m.add_density_grid(np.ones(m.grid.shape) * 4.e-20, 'kmh_lite.hdf5')
# Add a point source in the center
s = m.add_point_source()
s.luminosity = 1000 * lsun
s.temperature = 6000.
# Add 10 SEDs for different viewing angles
image = m.add_peeled_images(sed=True, image=False)
image.set_wavelength_range(250, 0.01, 5000.)
image.set_viewing_angles(np.linspace(0., 90., 10), np.repeat(20., 10))
image.set_track_origin('basic')
# Add multi-wavelength image for a single viewing angle
image = m.add_peeled_images(sed=False, image=True)
image.set_wavelength_range(30, 1., 1000.)
image.set_viewing_angles([30.], [20.])
image.set_image_size(200, 200)
import numpy as np
from hyperion.model import Model
from hyperion.util.constants import au, lsun, rsun
from hyperion.dust import SphericalDust
# Model
m = Model()
dist = 20000 * au
x = np.linspace(-dist, dist, 101)
y = np.linspace(-dist, dist, 101)
z = np.linspace(-dist, dist, 101)
m.set_cartesian_grid(x,y,z)
# Dust
d = SphericalDust('kmh.hdf5')
d.set_sublimation_temperature('fast', temperature=1600.)
m.add_density_grid(np.ones((100,100,100)) * 1.e-18,'kmh.hdf5')
# Alpha centauri
sourceA = m.add_spherical_source()
sourceA.luminosity = 1.519 * lsun
sourceA.radius = 1.227 * rsun
sourceA.temperature = 5790.
sourceA.position = (0., 0., 0.)
# Beta centauri
sourceB = m.add_spherical_source()
sourceB.luminosity = 0.5 * lsun
sourceB.radius = 0.865 * rsun
sourceB.temperature = 5260.
# A simple model with no dust, just sources, to check that the Doppler Shifting # is working correctly. This model consists of a disk of sources that is # rotating in a solid body fashion around the origin. All sources have a # spectrum that consists of a single spectral line that is narrow enough that we # can easily see the rotation in a multi-wavelength image. We check that the # image looks sensible in both binned and peeled images. # Same as setup_indiv but using a point source collection import numpy as np from hyperion.model import Model from hyperion.util.constants import c m = Model() m.set_cartesian_grid([-1., 1], [-1., 1.], [-1., 1]) N = 100000 w = np.random.random(N)**0.5 p = np.random.uniform(0, 2 * np.pi, N) z = np.random.uniform(-0.1, 0.1, N) x = w * np.cos(p) y = w * np.sin(p) # solid body with 1000 km/s on the outside v = w * 1e8 # cm / s vx = - v * np.sin(p) vy = + v * np.cos(p) vz = np.repeat(0, N)
import numpy as np from hyperion.model import Model from hyperion.util.constants import pc, lsun # Initialize model m = Model() # Set up 64x64x64 cartesian grid w = np.linspace(-pc, pc, 64) m.set_cartesian_grid(w, w, w) # Add density grid with constant density and add a higher density cube inside to # cause a shadow. density = np.ones(m.grid.shape) * 1e-21 density[26:38, 26:38, 26:38] = 1.e-18 m.add_density_grid(density, 'kmh_lite.hdf5') # Add a point source in the center s = m.add_point_source() s.position = (0.4 * pc, 0., 0.) s.luminosity = 1000 * lsun s.temperature = 6000. # Add multi-wavelength image for a single viewing angle image = m.add_peeled_images(sed=False, image=True) image.set_wavelength_range(1, 190., 210.) image.set_viewing_angles(np.repeat(45., 36), np.linspace(5., 355., 36)) image.set_image_size(400, 400) image.set_image_limits(-1.5 * pc, 1.5 * pc, -1.5 * pc, 1.5 * pc)
# A simple model to check what happens when a source is moving towards dust and # we observe both the source and the dust. If we observe the source such that # the dust is directly behind, and the source is moving towards the dust, we # should see red-shifted emission from the source and blue-shifted scattered # light emission. import numpy as np from hyperion.model import Model from hyperion.util.constants import c m = Model() m.set_cartesian_grid([-1., 0, 1], [-1., 1.], [-1., 1]) density = np.zeros(m.grid.shape) density[:, :, 0] = 1. m.add_density_grid(density, 'kmh_lite.hdf5') # narrow emission line spectrum at 1 micron wav = np.array([0.9999, 1.0001]) fnu = np.array([1., 1.]) nu = c / (wav * 1.e-4) s = m.add_spherical_source() s.position = 0.5, 0., 0. s.velocity = -1e8, 0., 0. s.spectrum = nu[::-1], fnu[::-1] s.luminosity = 1 s.radius = 0.1
def run_thermal_hyperion(self, nphot=1e6, mrw=False, pda=False, \
niterations=20, percentile=99., absolute=2.0, relative=1.02, \
max_interactions=1e8, mpi=False, nprocesses=None):
d = []
for i in range(len(self.grid.dust)):
d.append(IsotropicDust( \
self.grid.dust[i].nu[::-1].astype(numpy.float64), \
self.grid.dust[i].albedo[::-1].astype(numpy.float64), \
self.grid.dust[i].kext[::-1].astype(numpy.float64)))
m = HypModel()
if (self.grid.coordsystem == "cartesian"):
m.set_cartesian_grid(self.grid.w1*AU, self.grid.w2*AU, \
self.grid.w3*AU)
elif (self.grid.coordsystem == "cylindrical"):
m.set_cylindrical_polar_grid(self.grid.w1*AU, self.grid.w3*AU, \
self.grid.w2)
elif (self.grid.coordsystem == "spherical"):
m.set_spherical_polar_grid(self.grid.w1*AU, self.grid.w2, \
self.grid.w3)
for i in range(len(self.grid.density)):
if (self.grid.coordsystem == "cartesian"):
m.add_density_grid(numpy.transpose(self.grid.density[i], \
axes=(2,1,0)), d[i])
if (self.grid.coordsystem == "cylindrical"):
m.add_density_grid(numpy.transpose(self.grid.density[i], \
axes=(1,2,0)), d[i])
if (self.grid.coordsystem == "spherical"):
m.add_density_grid(numpy.transpose(self.grid.density[i], \
axes=(2,1,0)), d[i])
sources = []
for i in range(len(self.grid.stars)):
sources.append(m.add_spherical_source())
sources[i].luminosity = self.grid.stars[i].luminosity * L_sun
sources[i].radius = self.grid.stars[i].radius * R_sun
sources[i].temperature = self.grid.stars[i].temperature
m.set_mrw(mrw)
m.set_pda(pda)
m.set_max_interactions(max_interactions)
m.set_n_initial_iterations(niterations)
m.set_n_photons(initial=nphot, imaging=0)
m.set_convergence(True, percentile=percentile, absolute=absolute, \
relative=relative)
m.write("temp.rtin")
m.run("temp.rtout", mpi=mpi, n_processes=nprocesses)
n = ModelOutput("temp.rtout")
grid = n.get_quantities()
self.grid.temperature = []
temperature = grid.quantities['temperature']
for i in range(len(temperature)):
if (self.grid.coordsystem == "cartesian"):
self.grid.temperature.append(numpy.transpose(temperature[i], \
axes=(2,1,0)))
if (self.grid.coordsystem == "cylindrical"):
self.grid.temperature.append(numpy.transpose(temperature[i], \
axes=(2,0,1)))
if (self.grid.coordsystem == "spherical"):
self.grid.temperature.append(numpy.transpose(temperature[i], \
axes=(2,1,0)))
os.system("rm temp.rtin temp.rtout")
def run_thermal_hyperion(self, nphot=1e6, mrw=False, pda=False, \
niterations=20, percentile=99., absolute=2.0, relative=1.02, \
max_interactions=1e8, mpi=False, nprocesses=None):
d = []
for i in range(len(self.grid.dust)):
d.append(IsotropicDust( \
self.grid.dust[i].nu[::-1].astype(numpy.float64), \
self.grid.dust[i].albedo[::-1].astype(numpy.float64), \
self.grid.dust[i].kext[::-1].astype(numpy.float64)))
m = HypModel()
if (self.grid.coordsystem == "cartesian"):
m.set_cartesian_grid(self.grid.w1*AU, self.grid.w2*AU, \
self.grid.w3*AU)
elif (self.grid.coordsystem == "cylindrical"):
m.set_cylindrical_polar_grid(self.grid.w1*AU, self.grid.w3*AU, \
self.grid.w2)
elif (self.grid.coordsystem == "spherical"):
m.set_spherical_polar_grid(self.grid.w1*AU, self.grid.w2, \
self.grid.w3)
for i in range(len(self.grid.density)):
if (self.grid.coordsystem == "cartesian"):
m.add_density_grid(numpy.transpose(self.grid.density[i], \
axes=(2,1,0)), d[i])
if (self.grid.coordsystem == "cylindrical"):
m.add_density_grid(numpy.transpose(self.grid.density[i], \
axes=(1,2,0)), d[i])
if (self.grid.coordsystem == "spherical"):
m.add_density_grid(numpy.transpose(self.grid.density[i], \
axes=(2,1,0)), d[i])
sources = []
for i in range(len(self.grid.stars)):
sources.append(m.add_spherical_source())
sources[i].luminosity = self.grid.stars[i].luminosity * L_sun
sources[i].radius = self.grid.stars[i].radius * R_sun
sources[i].temperature = self.grid.stars[i].temperature
m.set_mrw(mrw)
m.set_pda(pda)
m.set_max_interactions(max_interactions)
m.set_n_initial_iterations(niterations)
m.set_n_photons(initial=nphot, imaging=0)
m.set_convergence(True, percentile=percentile, absolute=absolute, \
relative=relative)
m.write("temp.rtin")
m.run("temp.rtout", mpi=mpi, n_processes=nprocesses)
n = ModelOutput("temp.rtout")
grid = n.get_quantities()
self.grid.temperature = []
temperature = grid.quantities['temperature']
for i in range(len(temperature)):
if (self.grid.coordsystem == "cartesian"):
self.grid.temperature.append(numpy.transpose(temperature[i], \
axes=(2,1,0)))
if (self.grid.coordsystem == "cylindrical"):
self.grid.temperature.append(numpy.transpose(temperature[i], \
axes=(2,0,1)))
if (self.grid.coordsystem == "spherical"):
self.grid.temperature.append(numpy.transpose(temperature[i], \
axes=(2,1,0)))
os.system("rm temp.rtin temp.rtout")
# A simple model to check what happens when a source is moving towards dust and # we observe both the source and the dust. If we observe the source such that # the dust is directly behind, and the source is moving towards the dust, we # should see red-shifted emission from the source and blue-shifted scattered # light emission. import numpy as np from hyperion.model import Model from hyperion.util.constants import c m = Model() m.set_cartesian_grid([-1.0, 0, 1], [-1.0, 1.0], [-1.0, 1]) density = np.zeros(m.grid.shape) density[:, :, 0] = 1.0 m.add_density_grid(density, "kmh_lite.hdf5") # narrow emission line spectrum at 1 micron wav = np.array([0.9999, 1.0001]) fnu = np.array([1.0, 1.0]) nu = c / (wav * 1.0e-4) s = m.add_spherical_source() s.position = 0.5, 0.0, 0.0 s.velocity = -1e8, 0.0, 0.0 s.spectrum = nu[::-1], fnu[::-1] s.luminosity = 1 s.radius = 0.1
# Global geometry:
#
# * slab
# * system size = 10x10x10 pc
# * system coordinates (x,y,z min/max) = -5 to +5 pc
# * slab z extent = -2 to -5 pc
# * slab xy extend = -5 pc to 5 pc
# * z optical depth @0.55um in slab = 0.1, 1, 20
# * optical depth outside slab = 0
x = np.linspace(-5 * pc, 5 * pc, 100)
y = np.linspace(-5 * pc, 5 * pc, 100)
z = np.hstack([np.linspace(-5 * pc, -2 * pc, 100), 5 * pc])
m.set_cartesian_grid(x, y, z)
# Grain Properties:
d = SphericalDust('integrated_hg_scattering.hdf5')
chi_v = d.optical_properties.interp_chi_wav(0.55)
# Determine density in slab
rho0 = tau_v / (3 * pc * chi_v)
# Set up density grid
density = np.ones(m.grid.shape) * rho0
density[-1,:,:] = 0.
m.add_density_grid(density, d)
def __init__(self, par, **kwargs):
#Set up dust model for Hyperion
# Initalize the model
m = Model()
#Set central source position
m.add_spherical_source(luminosity = par.get('lsource',1.0*lsun),
radius = par.get('rsource',1.0*rsun),
mass = par.get('msource',1.0*msun),
temperature = par.get('tsource',5784.0),
position = par.get('position',(0.0,0.0,0.0))
# Use raytracing to improve s/n of thermal/source emission
m.set_raytracing(par.get('raytracing',True))
# Use the modified random walk
m.set_mrw(par.get('modrndwlk',True), gamma=par.get('mrw_gamma',2))
# Set up spatial grid
x = np.linspace(-1.5*par.get('rmax',100.*u.au), 1.5*par.get('rmax',100.*u.au), par.get('ngrid',257))
y = np.linspace(-1.5*par.get('rmax',100.*u.au), 1.5*par.get('rmax',100.*u.au), par.get('ngrid',257))
z = np.linspace(-1.5*par.get('rmax',100.*u.au), 1.5*par.get('rmax',100.*u.au), par.get('ngrid',257))
m.set_cartesian_grid(x,y,z)
print("Spatial grid set up.")
#Set up density grid
rho0 = par.get('rho0',1.5e-19)
alpha_in = par.get('alpha_in',-5.)
alpha_out = par.get('alpha_out',5.)
scaleheight= par.get('scaleheight',0.1)
rmin = par.get('rmin',70.*u.au)
rmax = par.get('rmax',100.*u.au)
rmid = (rmax + rmin) / 2
rr = np.sqrt(m.grid.gx ** 2 + m.grid.gy ** 2 + m.grid.gz ** 2)
#define density grid
density = np.zeros(m.grid.shape)
density = rho0 * ( (rr/rmid)**(2.*alpha_in) + (rr/rmid)**(2.*alpha_out) )**(-0.5) * np.exp(-((abs(m.grid.gz)/rr)**2/scaleheight**2)/2.0)
m.add_density_grid(density, d)
print("Density grid set up.")
# Set up SED for 10 viewing angles
sed = m.add_peeled_images(sed=par.get('api_sed',True), image=par.get('api_img',False))
sed.set_viewing_angles(np.linspace(0., 90., 10), np.repeat(45., 10))
sed.set_wavelength_range(par.get('nl',101), par.get('lmin',0.1), par.get('lmax',1000.))
sed.set_track_origin('basic')
# Set number of photons
m.set_n_photons(initial=par.get('nph_initial',1e4), imaging=par.get('nph_imging',1e5),
raytracing_sources=par.get('nph_rtsrcs',1e5), raytracing_dust=par.get('nph_rtdust',1e5))
# Set number of temperature iterations
m.set_n_initial_iterations(par.get('niter',5))
# Write out file
m.write('HyperionRT_sed.rtin')
print("Hyperion RT model created.")
def __call__(self, *args, **kwargs):
m.run('HyperionRT_sed.rtout', mpi=True,n_processes=6,overwrite=True)
print("Hyperion RT model executed.")
m = ModelOutput('HyperionRT_sed.rtout')
self.modelFlux = sed.value
def lnprior(self, theta, **kwargs):
if self.flatprior:
if (self.lims[0,0] < theta[0] < self.lims[0,1]) and \
(self.lims[1,0] < theta[1] < self.lims[1,1]) and \
(self.lims[2,0] < theta[2] < self.lims[2,1]) and \
(self.lims[3,0] < theta[3] < self.lims[3,1]) and \
np.sum(10**theta[4:]) <= 1. and np.all(theta[4:] < 0.):
return 0
else:
return -np.inf
else:
raise NotImplementedError()
def __str__(self, **kwargs):
raise NotImplementedError()
def __repr__(self, **kwargs):
raise NotImplementedError()
def inputFile(self, **kwargs):
#Create a dictionary with which to setup and run Hyperion RT models
#Dust parameters
par = {'dust':'"astrosilicate"',
'format':2,
'size':0.5,
'amin':0.5,
'amax':1000.,
'na':101,
'nang':91,
'nanx':11,
'nchem':1,
'gtd':0,
'lmin':0.1,
'lmax':1000.0,
'nl':101,
'massfrac':1.0,
'rho0':1.5e-19,
'optconst':'"silicate_d03.lnk"',
'disttype':'power',
'q':3.5,
#Source parameters
'lsource': 1.0*u.lsun,
'rsource': 1.0*u.rsun,
'msource': 1.0*u.msun,
'tsource': 5784.,
'position':[0.0,0.0,0.0],
#Disc parameters
'rmin': 70.*u.au,
'rmax': 100.*u.au,
'alpha_in': -5.,
'alpha_out': 5.,
'scaleheight': 0.1,
#RT parameters
'niter':5,
'nph_initial':1e4,
'nph_imging':1e5,
'nph_rtsrcs':1e5,
'nph_rtdust':1e5,
#Peel photons to get images
'api_sed':True,
'api_img':False,
}
return par
#convenience function to plot the SED of the Hyperion RT output
def plot_sed(par):
#Set up figure
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
#Read in Hyperion model output
try:
m = ModelOutput('HyperionRT_sed.rtout')
#Total SED
sed = m.get_sed(inclination=0, aperture=-1, distance=par['distance'],
component='total',units='Jy')
ax.loglog(sed.wav, sed.val, color='black', lw=3, alpha=0.5)
# Direct stellar photons
sed = m.get_sed(inclination=0, aperture=-1, distance=par['distance'],
component='source_emit',units='Jy')
ax.loglog(sed.wav, sed.val, color='blue')
# Scattered stellar photons
sed = m.get_sed(inclination=0, aperture=-1, distance=par['distance'],
component='source_scat',units='Jy')
ax.loglog(sed.wav, sed.val, color='teal')
# Direct dust photons
sed = m.get_sed(inclination=0, aperture=-1, distance=par['distance'],
component='dust_emit',units='Jy')
ax.loglog(sed.wav, sed.val, color='red')
# Scattered dust photons
sed = m.get_sed(inclination=0, aperture=-1, distance=par['distance'],
component='dust_scat',units='Jy')
ax.loglog(sed.wav, sed.val, color='orange')
ax.set_xlabel(r'$\lambda$ [$\mu$m]')
ax.set_ylabel(r'Flux [Jy]')
ax.set_xlim(par.get('lmin',0.1), par.get('lmax',1000.))
ax.set_ylim(1e-6*np.max(sed.value),1.1*np.max(sed.value))
fig.savefig('HyperionRT_sed_plot_components.png')
plt.close(fig)
except IOError:
print("No Hyperion RT output found, SED not plotted.")
#convenience function to write dust parameter file '<dust>.params' for Hyperion BHDust calculator (separate program)
def write_bhmie_file(par):
f=open(par.get('dust','astrosilicate')+'.params','w')
f.write('"'+par['dust']+'_'+str(par['size'])+'"'+'\n')
f.write(str(par['format'])+'\n')
f.write(str(par['amin'])+'\n')
f.write(str(par['amax'])+'\n')
f.write(str(par['na'])+'\n')
f.write(str(par['nang'])+'\n')
f.write(str(par['nanx'])+'\n')
f.write(str(par['nchem'])+'\n')
f.write(str(par['gtd'])+'\n')
f.write(str(par['lmin'])+' '+str(par['lmax'])+' '+str(par['nl'])+'\n')
f.write(''+'\n')
f.write(str(par['massfrac'])+'\n')
f.write(str(par['rho0'])+'\n')
f.write(str(par['optconst'])+'\n')
f.write(str(par['disttype'])+'\n')
f.write(str(par['amin'])+' '+str(par['amax'])+' '+str(par['q'])+'\n')
f.close()
print("BHMie dust input file created.")
import subprocess
subprocess.run(['bhmie',param_file])
print("BHMie dust output file created")
