iniSCMHalo = dict(ini.items("SelfConsistentModel halo"))
iniSCMBulge = dict(ini.items("SelfConsistentModel bulge"))
iniSCMDisk = dict(ini.items("SelfConsistentModel disk"))
iniSCM = dict(ini.items("SelfConsistentModel"))
# initialize the SelfConsistentModel object (only the potential expansion parameters)
model = agama.SelfConsistentModel(**iniSCM)
# create initial density profiles of all components
densityDisk = agama.Density(**iniPotenDisk)
densityBulge = agama.Density(**iniPotenBulge)
densityHalo = agama.Density(**iniPotenHalo)
potentialBH = agama.Potential(**iniPotenBH)
# add components to SCM - at first, all of them are static density profiles
model.components.append(agama.Component(density=densityDisk, disklike=True))
model.components.append(agama.Component(density=densityBulge, disklike=False))
model.components.append(agama.Component(density=densityHalo, disklike=False))
model.components.append(agama.Component(potential=potentialBH))
# compute the initial potential
model.iterate()
printoutInfo(model,'init')
# construct the DF of the disk component, using the initial (non-spherical) potential
dfDisk = agama.DistributionFunction(potential=model.potential, **iniDFDisk)
# initialize the DFs of spheroidal components using the Eddington inversion formula
# for their respective density profiles in the initial potential
dfBulge = agama.DistributionFunction(type='QuasiSpherical', potential=model.potential, density=densityBulge)
dfHalo = agama.DistributionFunction(type='QuasiSpherical', potential=model.potential, density=densityHalo)
# define external unit system describing the data (including the parameters in INI file)
agama.setUnits(length=1, velocity=1, mass=1) # in Kpc, km/s, Msun
# initialize the SelfConsistentModel object (only the potential expansion parameters)
model = agama.SelfConsistentModel(**iniSCM)
# create initial ('guessed') density profiles of all components
densityBulge = agama.Density(**iniPotenBulge)
densityDarkHalo = agama.Density(**iniPotenDarkHalo)
densityThinDisk = agama.Density(**iniPotenThinDisk)
densityThickDisk = agama.Density(**iniPotenThickDisk)
densityGasDisk = agama.Density(**iniPotenGasDisk)
densityStellarDisk = agama.Density(densityThinDisk, densityThickDisk) # composite
# add components to SCM - at first, all of them are static density profiles
model.components.append(agama.Component(density=densityStellarDisk, disklike=True))
model.components.append(agama.Component(density=densityBulge, disklike=False))
model.components.append(agama.Component(density=densityDarkHalo, disklike=False))
model.components.append(agama.Component(density=densityGasDisk, disklike=True))
# compute the initial potential
model.iterate()
printoutInfo(model, "init")
print("\033[1;33m**** STARTING MODELLING ****\033[0m\nInitial masses of density components: " \
"Mdisk=%g Msun, Mbulge=%g Msun, Mhalo=%g Msun, Mgas=%g Msun" % \
(densityStellarDisk.totalMass(), densityBulge.totalMass(), \
densityDarkHalo.totalMass(), densityGasDisk.totalMass()))
# create the dark halo DF
dfHalo = agama.DistributionFunction(potential=model.potential, **iniDFDarkHalo)
determined by its distribution function in terms of actions
"""
import agama, numpy, matplotlib.pyplot as plt
# the distribution function defining the model
df = agama.DistributionFunction(type="DoublePowerLaw", J0=1, slopeIn=0, slopeOut=6, norm=30)
mass = df.totalMass()
scaleradius = 2. # educated guess
# initial guess for the density profile
dens = agama.Density(type='Plummer', mass=mass, scaleRadius=scaleradius)
print "DF mass=", mass, ' Density mass=', dens.totalMass() # should be identical
# define the self-consistent model consisting of a single component
params = dict(rminSph=0.01, rmaxSph=100., sizeRadialSph=25, lmaxAngularSph=0)
comp = agama.Component(df=df, density=dens, disklike=False, **params)
scm = agama.SelfConsistentModel(**params)
scm.components=[comp]
# prepare visualization
r=numpy.logspace(-2.,2.)
xyz=numpy.vstack((r,r*0,r*0)).T
plt.plot(r, dens.density(xyz), label='Init density')
# perform several iterations of self-consistent modelling procedure
for i in range(5):
scm.iterate()
print 'Iteration', i, ' Phi(0)=', scm.potential.potential(0,0,0), ' Mass=', scm.potential.totalMass()
plt.plot(r, scm.potential.density(xyz), label='Iteration #'+str(i))
# save the final density/potential profile
iniDFDisk = dict(ini.items("DF disk"))
iniSCMHalo = dict(ini.items("SelfConsistentModel halo"))
iniSCMBulge = dict(ini.items("SelfConsistentModel bulge"))
iniSCMDisk = dict(ini.items("SelfConsistentModel disk"))
iniSCM = dict(ini.items("SelfConsistentModel"))
# initialize the SelfConsistentModel object (only the potential expansion parameters)
model = agama.SelfConsistentModel(**iniSCM)
# create initial ('guessed') density profiles of all components
densityBulge = agama.Density(**iniPotenBulge)
densityHalo = agama.Density(**iniPotenHalo)
densityDisk = agama.Density(**iniPotenDisk)
# add components to SCM - at first, all of them are static density profiles
model.components.append(agama.Component(dens=densityHalo, disklike=False))
model.components.append(agama.Component(dens=densityBulge, disklike=False))
model.components.append(agama.Component(dens=densityDisk, disklike=True))
# compute the initial potential
model.iterate()
writeRotationCurve("rotcurve_init", model.pot)
# initialize the DFs of spheroidal components using the Eddington inversion formula
# for their respective density profiles in the spherically-symmetric initial guess for the potential
pot_sph = agama.Potential(type='Multipole',
density=model.pot,
lmax=0,
gridsizer=100,
rmin=1e-3,
rmax=1e3)
cutoffStrength=0.7194)
d2 = agama.Density(type='Spheroid',
DensityNorm=0.9 * 169.975,
gamma=0,
beta=0,
axisRatioZ=0.37,
outerCutoffRadius=0.0246,
cutoffStrength=0.7933)
density_NSD_init = agama.Density(d1, d2)
# add both NSC and NSD components as static density profiles for the moment:
# assign both of them to a single CylSpline potential solver by setting disklike=True
# and thus avoid creating an additional Multipole potential, which is typically used
# for spheroidal components - this reduces computational cost by roughly a half
model.components.append(
agama.Component(density=density_NSC_init, disklike=True))
model.components.append(
agama.Component(density=density_NSD_init, disklike=True))
# compute the initial guess for the potential
model.iterate()
plotVcirc(model, 0)
# introduce DF for the NSD component
mass = 0.097
Rdisk = 0.075
Hdisk = 0.025
sigmar0 = 75.0
Rsigmar = 1.0
sigmamin = 2.0
Jmin = 10.0
# initialize the SelfConsistentModel object (only the potential expansion parameters)
model = agama.SelfConsistentModel(**iniSCM)
# create initial ('guessed') density profiles of all components
densityBulge = agama.Density(**iniPotenBulge)
densityDarkHalo = agama.Density(**iniPotenDarkHalo)
densityThinDisc = agama.Density(**iniPotenThinDisc)
densityThickDisc = agama.Density(**iniPotenThickDisc)
densityGasDisc = agama.Density(**iniPotenGasDisc)
densityStellarDisc = agama.Density(densityThinDisc,
densityThickDisc) # composite
# add components to SCM - at first, all of them are static density profiles
model.components.append(
agama.Component(dens=densityDarkHalo, disklike=False))
model.components.append(
agama.Component(dens=densityStellarDisc, disklike=True))
model.components.append(agama.Component(dens=densityBulge, disklike=False))
model.components.append(agama.Component(dens=densityGasDisc,
disklike=True))
# compute the initial potential
model.iterate()
writeRotationCurve("rotcurve_init", model.pot)
print "**** STARTING ONE-COMPONENT MODELLING ****\nMasses are: " \
"Mbulge=%g Msun,"% densityBulge.totalMass(), \
"Mgas=%g Msun," % densityGasDisc.totalMass(), \
"Mdisc=%g Msun," % densityStellarDisc.totalMass(), \
"Mhalo=%g Msun" % densityDarkHalo.totalMass()
