"""
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
scm.potential.export("simple_scm.coef_mul")
iniFileName = os.path.dirname(os.path.realpath(sys.argv[0])) + "/../data/SCM3.ini"
ini = RawConfigParser()
#ini.optionxform=str # do not convert key to lowercase
ini.read(iniFileName)
iniPotenHalo = dict(ini.items("Potential halo"))
iniPotenBulge = dict(ini.items("Potential bulge"))
iniPotenDisk = dict(ini.items("Potential disk"))
iniPotenBH = dict(ini.items("Potential BH"))
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 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()
ha='right',
va='center',
transform=ax.transAxes)
ax.set_ylabel('f(V)', labelpad=3)
plt.savefig('nsd_model.pdf')
plt.show()
if __name__ == '__main__':
agama.setUnits(length=1, velocity=1, mass=1e10) # 1 kpc, 1 km/s, 1e10 Msun
# initialize the SelfConsistentModel object (only the potential expansion parameters)
model = agama.SelfConsistentModel(RminCyl=0.005,
RmaxCyl=1.0,
sizeRadialCyl=25,
zminCyl=0.005,
zmaxCyl=1.0,
sizeVerticalCyl=25)
# construct a two component model: NSD + NSC
# NSD -> generated self-consistently
# NSC -> kept fixed as an external potential
# NSC best-fitting model from Chatzopoulos et al. 2015 (see Equation 28 here: https://arxiv.org/pdf/2007.06577.pdf)
density_NSC_init = agama.Density(type='Dehnen',
mass=6.1e-3,
gamma=0.71,
scaleRadius=5.9e-3,
axisRatioZ=0.73)
# NSD model 3 from Sormani et al. 2020 (see Equation 24 here: https://arxiv.org/pdf/2007.06577.pdf)
