def fractal_model(N, F=1.6, x_label='x [length]', y_label='y [length]'):
fig = single_frame(x_label, y_label, xsize=8, ysize=8)
ax = pyplot.gca()
model = new_fractal_cluster_model(N=N,
fractal_dimension=1.6,
random_seed=42)
plot_projected_density(model, col=2)
pyplot.savefig("fractal_model")
def fractal_model(N, F=1.6, x_label = 'x [length]', y_label='y [length]'):
fig = single_frame(x_label, y_label, xsize=8, ysize=8)
ax = pyplot.gca()
model = new_fractal_cluster_model(N=N, fractal_dimension=1.6,
random_seed=42)
plot_projected_density(model, col=2)
file = "fractal_model.png"
pyplot.savefig(file)
print('Saved figure in file', file)
def fractal_model(N, F=1.6, x_label = 'x [length]', y_label='y [length]'):
fig = single_frame(x_label, y_label, xsize=8, ysize=8)
ax = pyplot.gca()
model = new_fractal_cluster_model(N=N, fractal_dimension=1.6,
random_seed=42)
plot_projected_density(model, col=2)
file = "fractal_model.png"
pyplot.savefig(file)
print 'Saved figure in file', file
def make_fractal_cluster(masses, name, converter, Fd=1.6):
stars = new_fractal_cluster_model(N=len(masses),
convert_nbody=converter,
do_scale=False,
fractal_dimension=Fd)
stars.type = "star"
stars.name = name
stars.mass = masses
stars.move_to_center()
return stars
def main(N, Rvir, Qvir, Fd, t_end, filename):
masses = new_kroupa_mass_distribution(N, 100 | units.MSun)
converter = nbody_system.nbody_to_si(masses.sum(), Rvir)
bodies = new_fractal_cluster_model(N=N,
fractal_dimension=Fd,
convert_nbody=converter)
bodies.scale_to_standard(converter, virial_ratio=Qvir)
bodies.stellar_mass = masses
bodies.disk_mass = 0.01 * bodies.stellar_mass
bodies.mass = bodies.stellar_mass + bodies.disk_mass
bodies.accreted_mass = 0 | units.MSun
bodies.disk_radius = 400 | units.AU
bodies.radius = 10 * bodies.disk_radius
gravity = ph4(converter, number_of_workers=2)
gravity.parameters.epsilon_squared = (100 | units.AU)**2
gravity.particles.add_particles(bodies)
channel_from_gravity = gravity.particles.new_channel_to(bodies)
channel_to_gravity = bodies.new_channel_to(gravity.particles)
stopping_condition = gravity.stopping_conditions.collision_detection
stopping_condition.enable()
write_set_to_file(bodies.savepoint(0 | units.Myr),
filename,
'hdf5',
append_to_file=False)
Etot_init = gravity.kinetic_energy + gravity.potential_energy
Etot_prev = Etot_init
###BOOKLISTSTOP1###
###BOOKLISTSTART0###
dt = t_end / 10.
time = 0 | units.yr
while gravity.model_time < t_end:
time += dt
evolve_system_to(time, gravity, bodies, stopping_condition,
channel_from_gravity, channel_to_gravity)
write_set_to_file(bodies.savepoint(gravity.model_time), filename,
'hdf5')
Etot = gravity.kinetic_energy + gravity.potential_energy
print "T=", gravity.model_time,
print "E= ", Etot, "Q= ", \
gravity.kinetic_energy/gravity.potential_energy
print "dE=", (Etot - Etot_init) / Etot, "ddE=", (Etot -
Etot_prev) / Etot
Etot_init -= (Etot_prev - Etot)
Etot_prev = Etot
gravity.stop()
def _main(N=10, W=None):
f, ax1, ax2, ax3, ax4 = quad_frame("X [length]", "Y [length]")
model = new_plummer_model(N)
plot_projected_density(model, ax1)
model = new_king_model(N, 9.0)
plot_projected_density(model, ax2)
model = new_halogen_model(N, alpha=1., beta=5., gamma=0.5)
plot_projected_density(model, ax3)
model = new_fractal_cluster_model(N=N, fractal_dimension=1.6)
plot_projected_density(model, ax4)
# pyplot.show()
pyplot.savefig("density_distributions.eps", bbox_inches="tight")
def main(N, Rvir, Qvir, Fd):
numpy.random.seed(12345)
masses = new_kroupa_mass_distribution(N, 100 | units.MSun)
converter = nbody_system.nbody_to_si(masses.sum(), Rvir)
bodies = new_fractal_cluster_model(N=N,
fractal_dimension=Fd,
random_seed=1234,
convert_nbody=converter)
print "N all=", len(bodies)
clumps = find_clumps_with_hop(bodies, converter)
print "N blob=", len(clumps)
bodies.scale_to_standard(converter, virial_ratio=Qvir)
for clump in clumps:
clump.scale_to_standard(converter, virial_ratio=0.5)
lim = 10
plot_single_image(clumps, lim)
def main(N, Rvir, Qvir, Fd, seed):
numpy.random.seed(seed)
masses = new_kroupa_mass_distribution(N)
converter = nbody_system.nbody_to_si(masses.sum(), Rvir)
bodies = new_fractal_cluster_model(N=N, fractal_dimension=Fd,
random_seed=seed,
convert_nbody=converter)
bodies.mass = masses
bodies.move_to_center()
bodies.scale_to_standard(converter, virial_ratio=Qvir)
clumps = find_clumps_with_hop(bodies, converter)
for clump in clumps:
clump.scale_to_standard(converter, virial_ratio=0.5)
plot_single_image(clumps, lim=50)
def main(N, Rvir, Qvir, Fd, seed):
numpy.random.seed(seed)
masses = new_kroupa_mass_distribution(N)
converter = nbody_system.nbody_to_si(masses.sum(), Rvir)
bodies = new_fractal_cluster_model(N=N, fractal_dimension=Fd,
random_seed=seed,
convert_nbody=converter)
bodies.mass = masses
bodies.move_to_center()
bodies.scale_to_standard(converter, virial_ratio=Qvir)
clumps = find_clumps_with_hop(bodies, converter)
for clump in clumps:
clump.scale_to_standard(converter, virial_ratio=0.5)
plot_single_image(clumps, lim=50)
def main(N, Rvir, Qvir, Fd):
filename = 'Cl_N%g_R%gpc_Q%g_F%g.h5' % (N, Rvir.value_in(
units.parsec), Qvir, Fd)
t_end = 1.0 | units.Myr
dt = 0.1 | units.Myr
Mmax = 100 | units.MSun
masses = new_kroupa_mass_distribution(N, Mmax)
Mtot_init = masses.sum()
converter = nbody_system.nbody_to_si(Mtot_init, Rvir)
bodies = new_fractal_cluster_model(N=N,
fractal_dimension=Fd,
convert_nbody=converter)
bodies.scale_to_standard(converter, virial_ratio=Qvir)
bodies.stellar_mass = masses
bodies.disk_mass = 0.1 * bodies.stellar_mass
bodies.mass = bodies.stellar_mass + bodies.disk_mass
bodies.accreted_mass = 0 | units.MSun
bodies.disk_radius = 400 | units.AU
bodies.radius = 10 * bodies.disk_radius
gravity = ph4(converter)
gravity.parameters.epsilon_squared = (100 | units.AU)**2
gravity.particles.add_particles(bodies)
channel_from_gd_to_framework = gravity.particles.new_channel_to(bodies)
channel_from_framework_to_gd = bodies.new_channel_to(gravity.particles)
stopping_condition = gravity.stopping_conditions.collision_detection
stopping_condition.enable()
Johannes = Kepler(converter)
Johannes.initialize_code()
write_set_to_file(bodies.savepoint(0 | units.Myr),
filename,
'hdf5',
append_to_file=False)
Etot_init = gravity.kinetic_energy + gravity.potential_energy
Etot_prev = Etot_init
Nenc = 0
dEk_enc = zero
dEp_enc = zero
time = 0.0 | t_end.unit
while time < t_end:
time += dt
gravity.evolve_model(time)
Etot_prev_se = gravity.kinetic_energy + gravity.potential_energy
while stopping_condition.is_set():
channel_from_gd_to_framework.copy()
Ek_enc = gravity.kinetic_energy
Ep_enc = gravity.potential_energy
for ci in range(len(stopping_condition.particles(0))):
particles_in_encounter = Particles(particles=[
stopping_condition.particles(0)[ci],
stopping_condition.particles(1)[ci]
])
local_particles_in_encounter = particles_in_encounter.get_intersecting_subset_in(
bodies)
resolve_close_encounter(gravity.model_time,
local_particles_in_encounter, Johannes)
Nenc += 1
print("At time=", gravity.model_time.value_in(units.Myr),
"Nenc=", Nenc, "Rdisk=",
local_particles_in_encounter.disk_radius.in_(units.AU))
channel_from_framework_to_gd.copy_attributes(["radius"])
dEk_enc += Ek_enc - gravity.kinetic_energy
dEp_enc += Ep_enc - gravity.potential_energy
gravity.evolve_model(time)
channel_from_framework_to_gd.copy_attributes(["mass"])
write_set_to_file(bodies.savepoint(time), filename, 'hdf5')
Ekin = gravity.kinetic_energy
Epot = gravity.potential_energy
Etot = Ekin + Epot
dE = Etot_prev - Etot
dE_se = Etot_prev_se - Etot
Mtot = bodies.mass.sum()
print("T=", time, end=' ')
print("M=", Mtot, "(dM[SE]=", Mtot / Mtot_init, ")", end=' ')
print("E= ", Etot, "Q= ", Ekin / Epot, end=' ')
print("dE=", (Etot_init - Etot) / Etot,
"ddE=", (Etot_prev - Etot) / Etot,
end=' ')
print("(dE[SE]=", dE_se / Etot, ")")
print("dE(enc)=", dEk_enc, dEp_enc)
Etot_init -= dE
Etot_prev = Etot
gravity.stop()
Johannes.stop()
def main(N, Rvir, Qvir, Fd):
filename= 'Cl_N%g_R%gpc_Q%g_F%g.h5'%(N, Rvir.value_in(units.parsec), Qvir, Fd)
t_end = 1.0 | units.Myr
dt = 0.1 | units.Myr
Mmax = 100 | units.MSun
masses = new_kroupa_mass_distribution(N, Mmax)
Mtot_init = masses.sum()
converter=nbody_system.nbody_to_si(Mtot_init,Rvir)
bodies = new_fractal_cluster_model(N=N, fractal_dimension=Fd,
convert_nbody=converter)
bodies.scale_to_standard(converter, virial_ratio=Qvir)
bodies.stellar_mass = masses
bodies.disk_mass = 0.1*bodies.stellar_mass
bodies.mass = bodies.stellar_mass + bodies.disk_mass
bodies.accreted_mass = 0 | units.MSun
bodies.disk_radius = 400 | units.AU
bodies.radius = 10 * bodies.disk_radius
gravity = ph4(converter)
gravity.parameters.epsilon_squared = (100|units.AU)**2
gravity.particles.add_particles(bodies)
channel_from_gd_to_framework = gravity.particles.new_channel_to(bodies)
channel_from_framework_to_gd = bodies.new_channel_to(gravity.particles)
stopping_condition = gravity.stopping_conditions.collision_detection
stopping_condition.enable()
Johannes = Kepler(converter)
Johannes.initialize_code()
write_set_to_file(bodies.savepoint(0|units.Myr), filename, 'hdf5', append_to_file=False)
Etot_init = gravity.kinetic_energy + gravity.potential_energy
Etot_prev = Etot_init
Nenc = 0
dEk_enc = zero
dEp_enc = zero
time = 0.0 | t_end.unit
while time < t_end:
time += dt
gravity.evolve_model(time)
Etot_prev_se = gravity.kinetic_energy + gravity.potential_energy
while stopping_condition.is_set():
channel_from_gd_to_framework.copy()
Ek_enc = gravity.kinetic_energy
Ep_enc = gravity.potential_energy
for ci in range(len(stopping_condition.particles(0))):
particles_in_encounter = Particles(particles=[stopping_condition.particles(0)[ci], stopping_condition.particles(1)[ci]])
local_particles_in_encounter = particles_in_encounter.get_intersecting_subset_in(bodies)
resolve_close_encounter(gravity.model_time, local_particles_in_encounter, Johannes)
Nenc+=1
print "At time=", gravity.model_time.value_in(units.Myr), "Nenc=", Nenc, "Rdisk=", local_particles_in_encounter.disk_radius.in_(units.AU)
channel_from_framework_to_gd.copy_attributes(["radius"])
dEk_enc += Ek_enc - gravity.kinetic_energy
dEp_enc += Ep_enc - gravity.potential_energy
gravity.evolve_model(time)
channel_from_framework_to_gd.copy_attributes(["mass"])
write_set_to_file(bodies.savepoint(time), filename, 'hdf5')
Ekin = gravity.kinetic_energy
Epot = gravity.potential_energy
Etot = Ekin + Epot
dE = Etot_prev-Etot
dE_se = Etot_prev_se-Etot
Mtot = bodies.mass.sum()
print "T=", time,
print "M=", Mtot, "(dM[SE]=", Mtot/Mtot_init, ")",
print "E= ", Etot, "Q= ", Ekin/Epot,
print "dE=", (Etot_init-Etot)/Etot, "ddE=", (Etot_prev-Etot)/Etot,
print "(dE[SE]=", dE_se/Etot, ")"
print "dE(enc)=", dEk_enc, dEp_enc
Etot_init -= dE
Etot_prev = Etot
gravity.stop()
Johannes.stop()
def generate_initial_conditions(
number_of_stars = 100,
number_of_gas_particles = 10**5,
star_formation_efficiency = 0.1,
virial_radius = 0.33 | units.parsec,
virial_ratio = 1.0,
use_fractal = False):
numpy.random.seed(12345678)
seed_fractal = 312357271
masses = new_salpeter_mass_distribution(number_of_stars,
mass_min=1|units.MSun)
# masses = new_kroupa_mass_distribution(number_of_stars
total_stellar_mass = masses.sum()
total_mass = total_stellar_mass / star_formation_efficiency
converter = nbody_system.nbody_to_si(total_mass, virial_radius)
if use_fractal:
stars = new_fractal_cluster_model(number_of_stars,
convert_nbody=converter,
do_scale=False,
fractal_dimension=1.6,
random_seed=seed_fractal)
else:
stars = new_plummer_model(number_of_stars, convert_nbody=converter,
do_scale=False)
stars.mass = masses
stars.move_to_center()
print("scaling positions to match virial_radius")
stars.position *= virial_radius / stars.virial_radius()
print("scaling velocities to match virial_ratio")
stars.velocity *= numpy.sqrt(virial_ratio * converter.to_si(0.5|nbody_system.energy) * star_formation_efficiency / stars.kinetic_energy())
print("new_gas_plummer_distribution")
gas = new_gas_plummer_distribution(
number_of_gas_particles,
total_mass = (total_mass - total_stellar_mass),
virial_radius = virial_radius,
type = "fcc")
gas.h_smooth = 0.0 | units.parsec
# eat away gas.
mgas = gas[0].mass
print("Ngas=", len(gas))
for si in stars:
m = si.mass
nremoved = 0
while m>mgas:
gi = si.as_set().nearest_neighbour(gas)
nremoved += 1
m-= gi.mass
gas -= gi
print("removed:", nremoved, si.mass.in_(units.MSun))
print("Ngas=", len(gas))
filename = "YSC_{0}_stars{1}_gas{2}k_" \
.format("fractal" if use_fractal else "plummer",
number_of_stars, number_of_gas_particles/1000)
print("Writing initial conditions to", filename, "+ stars/gas.amuse")
write_set_to_file(stars, filename+"stars.amuse", "amuse",
append_to_file=False)
write_set_to_file(gas, filename+"gas.amuse", "amuse", append_to_file=False)
with open(filename+"info.pkl", "wb") as outfile:
pickle.dump([converter], outfile)
return stars, gas, filename
pyplot.ylim((-lim, lim))
save_file = 'FractalCluster.png'
pyplot.savefig(save_file)
print '\nSaved figure in file', save_file, '\n'
pyplot.show()
N = 2000 # Number of particles (stars) for the cluster
Rvir = 0.5 | units.parsec # Virial radius of the cluster
Qvir = 0.5 # Virial ratio of the cluster (Q=0.5 == equilibrium)
Fd = 1.6 # Fractal dimension
numpy.random.seed(1234) # Random seed for star positions
masses = new_kroupa_mass_distribution(N) # Stellar masses
converter = nbody_system.nbody_to_si(
masses.sum(),
Rvir) # Converter, turn n-body system units into relevant physical units
# Create new fractal cluster
bodies = new_fractal_cluster_model(N=N,
fractal_dimension=Fd,
random_seed=1234,
convert_nbody=converter)
bodies.mass = masses # Assign stellar masses to cluster particles
bodies.move_to_center()
bodies.scale_to_standard(converter, virial_ratio=Qvir)
plot_single_image(bodies, lim=1)