def evolve_cluster_in_galaxy(N, W0, Rinit, tend, timestep, M, R):
galaxy_code = MilkyWay_galaxy()
converter = nbody_system.nbody_to_si(M, R)
cluster_code = drift_without_gravity(convert_nbody=converter)
bodies = new_king_model(N, W0, convert_nbody=converter)
cluster_code.particles.add_particles(bodies)
stars = cluster_code.particles.copy()
stars.x += Rinit
stars.vy = 0.8 * galaxy_code.circular_velocity(Rinit)
channel = stars.new_channel_to(cluster_code.particles)
channel.copy_attributes(["x", "y", "z", "vx", "vy", "vz"])
system = bridge(verbose=False)
system.add_system(cluster_code, (galaxy_code, ))
times = quantities.arange(0 | units.Myr, tend, 100 * timestep)
for i, t in enumerate(times):
print("Time=", t.in_(units.Myr))
system.evolve_model(t, timestep=timestep)
x = system.particles.x.value_in(units.kpc)
y = system.particles.y.value_in(units.kpc)
cluster_code.stop()
return x, y
def evolve_cluster_in_galaxy(N, W0, Rinit, tend, timestep, M, R):
###BOOKLISTSTART2###
Rgal = 1. | units.kpc
Mgal = 1.6e10 | units.MSun
alpha = 1.2
galaxy_code = GalacticCenterGravityCode(Rgal, Mgal, alpha)
cluster_code = make_king_model_cluster(BHTree, N, W0, M, R,
parameters=[("epsilon_squared",
(0.01 | units.parsec)**2)])
stars = cluster_code.particles.copy()
stars.x += Rinit
stars.vy = 0.8*galaxy_code.circular_velocity(Rinit)
channel = stars.new_channel_to(cluster_code.particles)
channel.copy_attributes(["x","y","z","vx","vy","vz"])
system = bridge(verbose=False)
system.add_system(cluster_code, (galaxy_code,))
times = quantities.arange(0|units.Myr, tend, timestep)
for i,t in enumerate(times):
system.evolve_model(t,timestep=timestep)
x = system.particles.x.value_in(units.parsec)
y = system.particles.y.value_in(units.parsec)
cluster_code.stop()
###BOOKLISTSTOP2###
return x, y
def evolve_cluster_in_galaxy(N, W0, Rinit, tend, timestep, M, R):
galaxy_code = MilkyWay_galaxy()
converter = nbody_system.nbody_to_si(M, R)
cluster_code = drift_without_gravity(convert_nbody=converter)
bodies = new_king_model(N, W0, convert_nbody=converter)
cluster_code.particles.add_particles(bodies)
stars = cluster_code.particles.copy()
stars.x += Rinit
stars.vy = 0.8*galaxy_code.circular_velocity(Rinit)
channel = stars.new_channel_to(cluster_code.particles)
channel.copy_attributes(["x","y","z","vx","vy","vz"])
system = bridge(verbose=False)
system.add_system(cluster_code, (galaxy_code,))
times = quantities.arange(0|units.Myr, tend, 100*timestep)
for i,t in enumerate(times):
print "Time=", t.in_(units.Myr)
system.evolve_model(t, timestep=timestep)
x = system.particles.x.value_in(units.kpc)
y = system.particles.y.value_in(units.kpc)
cluster_code.stop()
return x, y
def evolve_cluster_in_galaxy(N, W0, Rinit, tend, timestep, M, R):
###BOOKLISTSTART2###
Rgal = 1. | units.kpc
Mgal = 1.6e10 | units.MSun
alpha = 1.2
galaxy_code = GalacticCenterGravityCode(Rgal, Mgal, alpha)
cluster_code = make_king_model_cluster(BHTree, N, W0, M, R,
parameters=[("epsilon_squared",
(0.01 | units.parsec)**2)])
stars = cluster_code.particles.copy()
stars.x += Rinit
stars.vy = 0.8*galaxy_code.circular_velocity(Rinit)
channel = stars.new_channel_to(cluster_code.particles)
channel.copy_attributes(["x","y","z","vx","vy","vz"])
system = bridge(verbose=False)
system.add_system(cluster_code, (galaxy_code,))
times = quantities.arange(0|units.Myr, tend, timestep)
for i,t in enumerate(times):
system.evolve_model(t,timestep=timestep)
x = system.particles.x.value_in(units.parsec)
y = system.particles.y.value_in(units.parsec)
cluster_code.stop()
###BOOKLISTSTOP2###
return x, y
def gravity_hydro_bridge(gravity, hydro, t_end, dt):
model_time = 0 | units.yr
filename = "gravhydro.hdf5"
#write_set_to_file(stars.savepoint(model_time), filename, 'amuse')
#write_set_to_file(gas, filename, 'amuse')
gravhydro = bridge.Bridge(use_threading=False)
gravhydro.add_system(gravity, (hydro, ))
gravhydro.add_system(hydro, (gravity, ))
gravhydro.timestep = 2 * hydro.get_timestep()
a_Jup = list()
e_Jup = list()
disk_size = list()
# start evolotuion
print 'Start evolving...'
times = quantities.arange(0. | units.yr, t_end + dt, dt)
while model_time < t_end:
stars = gravity.local_particles
orbit = orbital_elements_from_binary(stars, G=constants.G)
a = orbit[2].value_in(units.AU)
e = orbit[3]
if model_time.value_in(units.yr) % 50 == 0:
print "Time:", model_time.in_(units.yr), \
"ae=", a ,e
a_Jup.append(a)
e_Jup.append(e)
model_time += gravhydro.timestep
gravhydro.evolve_model(model_time)
gravity.copy_to_framework()
hydro.copy_to_framework()
sink = hydro.local_particles[0]
_ = hydro_sink_particles([sink], hydro.local_particles[1:])
Jupiter = gravity.local_particles[1]
Jupiter.mass += sink.mass
sink.position = Jupiter.position
sink.radius = a * (1 - e) * (
(1.0 | units.MJupiter).value_in(units.MSun) / 3.)**(1. /
3.) | units.au
gravity.copy_to_framework()
hydro.copy_to_framework()
write_set_to_file(stars.savepoint(model_time), filename, 'amuse')
write_set_to_file(ism, filename, 'amuse')
print "P=", model_time.in_(units.yr), gravity.particles.x.in_(units.au)
gravity.stop()
hydro.stop()
return a_Jup, e_Jup, times
def evolve_cluster(cluster,mCut,dt,tend,mCluster,rCluster,dump=False,dump_dir='data_dump'):
if dump:
print('Will be saving data in:'+dump_dir)
converter=nbody_system.nbody_to_si(mCluster,rCluster)
# Splitting particle according to mass_cut
low_mass_stars = cluster.select(lambda m: m < mCut,["mass"])
high_mass_stars = cluster.select(lambda m: m >= mCut,["mass"])
# Sanity checks
print('Number of low-mass stars:',low_mass_stars.__len__())
print('Number of high-mass stars:',high_mass_stars.__len__())
# Making models and assigning particles
code_tree = BHTree(converter)
code_direct = ph4(converter)
code_tree.particles.add_particles(low_mass_stars)
code_direct.particles.add_particles(high_mass_stars)
channel_from_code_tree = code_tree.particles.new_channel_to(low_mass_stars)
channel_from_code_direct = code_direct.particles.new_channel_to(high_mass_stars)
# Making bridge
combined_gravity = bridge()
combined_gravity.add_system(code_tree,(code_direct,))
combined_gravity.add_system(code_direct,(code_tree,))
combined_gravity.timestep = dt
# Making first snapshot
#plot_cluster(low_mass_stars,high_mass_stars,'t=0',save=True)
# Evolving the model
times = quantities.arange(0|units.Myr, tend, dt)
mCut_str = str(mCut.value_in(units.MSun))
for i,t in enumerate(times):
print "Time=", t.in_(units.Myr)
channel_from_code_tree.copy()
channel_from_code_direct.copy()
combined_gravity.evolve_model(t, timestep=dt)
snapshot_name = 't_'+str(t.in_(units.Myr))
plot_cluster(low_mass_stars,high_mass_stars,snapshot_name,save=True)
time = str(t.value_in(units.Myr))
if dump:
pkl.dump(low_mass_stars,
open(dump_dir+'/t'+time+'_m'+mCut_str+'_low_mass.p',
'wb'))
pkl.dump(high_mass_stars,
open(dump_dir+'/t'+time+'_m'+mCut_str+'_high_mass.p',
'wb'))
code_tree.stop()
code_direct.stop()
def evolve_cluster_in_galaxy(N, W0, Rinit, tend, timestep, M, R):
R_galaxy = 0.1 | units.kpc
M_galaxy = 1.6e10 | units.MSun
converter = nbody_system.nbody_to_si(M_galaxy, R_galaxy)
galaxy = new_plummer_model(10000, convert_nbody=converter)
print "com:", galaxy.center_of_mass().in_(units.kpc)
print "comv:", galaxy.center_of_mass_velocity().in_(units.kms)
print len(galaxy)
galaxy_code = BHTree(converter, number_of_workers=2)
galaxy_code.parameters.epsilon_squared = (0.01 | units.kpc)**2
channe_to_galaxy = galaxy_code.particles.new_channel_to(galaxy)
channe_to_galaxy.copy()
galaxy_code.particles.add_particles(galaxy)
inner_stars = galaxy.select(lambda r: r.length() < Rinit, ["position"])
Minner = inner_stars.mass.sum()
print "Minner=", Minner.in_(units.MSun)
print "Ninner=", len(inner_stars)
vc_inner = (constants.G * Minner / Rinit).sqrt()
converter = nbody_system.nbody_to_si(Mcluster, Rcluster)
stars = new_king_model(N, W0, convert_nbody=converter)
masses = new_powerlaw_mass_distribution(N, 0.1 | units.MSun,
100 | units.MSun, -2.35)
stars.mass = masses
stars.scale_to_standard(converter)
stars.x += Rinit
stars.vy += 0.8 * vc_inner
cluster_code = ph4(converter, number_of_workers=2)
cluster_code.particles.add_particles(stars)
channel_to_stars = cluster_code.particles.new_channel_to(stars)
system = bridge(verbose=False)
system.add_system(cluster_code, (galaxy_code, ))
system.add_system(galaxy_code, (cluster_code, ))
system.timestep = 0.1 * timestep
times = quantities.arange(0 | units.Myr, tend, timestep)
for i, t in enumerate(times):
print "Time=", t.in_(units.Myr)
channe_to_galaxy.copy()
channel_to_stars.copy()
inner_stars = galaxy.select(lambda r: r.length() < Rinit, ["position"])
print "Minner=", inner_stars.mass.sum().in_(units.MSun)
system.evolve_model(t, timestep=timestep)
plot_galaxy_and_stars(galaxy, stars)
galaxy_code.stop()
cluster_code.stop()
def evolve_cluster_in_galaxy(N, W0, Rinit, tend, timestep, M, R):
R_galaxy=0.1 | units.kpc
M_galaxy=1.6e10 | units.MSun
converter=nbody_system.nbody_to_si(M_galaxy, R_galaxy)
galaxy=new_plummer_model(10000,convert_nbody=converter)
print "com:", galaxy.center_of_mass().in_(units.kpc)
print "comv:", galaxy.center_of_mass_velocity().in_(units.kms)
print len(galaxy)
galaxy_code = BHTree(converter, number_of_workers=2)
galaxy_code.parameters.epsilon_squared = (0.01 | units.kpc)**2
channe_to_galaxy = galaxy_code.particles.new_channel_to(galaxy)
channe_to_galaxy.copy()
galaxy_code.particles.add_particles(galaxy)
inner_stars = galaxy.select(lambda r: r.length()<Rinit,["position"])
Minner = inner_stars.mass.sum()
print "Minner=", Minner.in_(units.MSun)
print "Ninner=", len(inner_stars)
vc_inner = (constants.G*Minner/Rinit).sqrt()
converter=nbody_system.nbody_to_si(Mcluster,Rcluster)
stars=new_king_model(N,W0,convert_nbody=converter)
masses = new_powerlaw_mass_distribution(N, 0.1|units.MSun, 100|units.MSun, -2.35)
stars.mass = masses
stars.scale_to_standard(converter)
stars.x += Rinit
stars.vy += 0.8*vc_inner
cluster_code=ph4(converter, number_of_workers=2)
cluster_code.particles.add_particles(stars)
channel_to_stars=cluster_code.particles.new_channel_to(stars)
system=bridge(verbose=False)
system.add_system(cluster_code, (galaxy_code,))
system.add_system(galaxy_code, (cluster_code,))
system.timestep = 0.1*timestep
times = quantities.arange(0|units.Myr, tend, timestep)
for i,t in enumerate(times):
print "Time=", t.in_(units.Myr)
channe_to_galaxy.copy()
channel_to_stars.copy()
inner_stars = galaxy.select(lambda r: r.length()<Rinit,["position"])
print "Minner=", inner_stars.mass.sum().in_(units.MSun)
system.evolve_model(t,timestep=timestep)
plot_galaxy_and_stars(galaxy, stars)
galaxy_code.stop()
cluster_code.stop()
def evolve_cluster(cluster,mCut,dt,tend,mCluster,rCluster):
converter=nbody_system.nbody_to_si(mCluster,rCluster)
# Splitting particle according to mass_cut
low_mass_stars = cluster.select(lambda m: m < mCut,["mass"])
high_mass_stars = cluster.select(lambda m: m >= mCut,["mass"])
# Sanity checks
print('dynamical timescale:', cluster.dynamical_timescale().value_in(units.Myr))
print('Number of low-mass stars:',low_mass_stars.__len__())
print('Number of high-mass stars:',high_mass_stars.__len__())
#plot_cluster(low_mass_stars, high_mass_stars)
# Making models and assigning particles
code_tree = BHTree(converter)
code_direct = ph4(converter)
code_tree.particles.add_particles(low_mass_stars)
code_direct.particles.add_particles(high_mass_stars)
channel_from_code_tree = code_tree.particles.new_channel_to(low_mass_stars)
channel_from_code_direct = code_direct.particles.new_channel_to(high_mass_stars)
# Making bridge
combined_gravity = bridge()
combined_gravity.add_system(code_tree,(code_direct,))
combined_gravity.add_system(code_direct,(code_tree,))
combined_gravity.timestep = dt
# Evolving the model
time_series = []
half_mass_radii = []
core_radii = []
times = quantities.arange(0.|units.Myr, tend, dt)
for i,t in enumerate(times):
print "Time =", t.in_(units.Myr)
channel_from_code_tree.copy()
channel_from_code_direct.copy()
time_series.append(t.value_in(units.Myr))
pos,coreradius,coredens=cluster.densitycentre_coreradius_coredens(converter)
lr,mf=cluster.LagrangianRadii(converter) # outputs are radii, mass fractions
half_mass_radii.append(lr[5].value_in(units.parsec)) # 5th argument attributes to half-mass radius
core_radii.append(coreradius.value_in(units.parsec))
combined_gravity.evolve_model(t, timestep=dt)
code_tree.stop()
code_direct.stop()
# Plotting results
#plot_cluster(low_mass_stars, high_mass_stars)
# Plotting radii
plot_radii(time_series, half_mass_radii, x_label='time(Myr)', y_label='half-mass radius (pc)')
plot_radii(time_series, core_radii, x_label='time(Myr)', y_label='core radius (pc)')
def test4(self):
x = quantities.arange(0 | units.yr, 10 | units.yr, 1 | units.yr)
y = (2.0 | units.km) * (x / (2.0 | units.yr))**2 + (20.0 | units.km)
fit = quantities.polyfit(x, y, 2)
self.assertEquals(len(fit), 3)
self.assertEquals(fit[0].unit, units.km / units.yr**2)
fit_values = quantities.polyval(fit, x)
self.assertEquals(fit_values.shape, x.shape)
self.assertEquals(y.unit, fit_values.unit)
self.assertAlmostRelativeEquals(y, fit_values, 1)
def test4(self):
x = quantities.arange(0 | units.yr, 10 | units.yr, 1 | units.yr)
y = (2.0|units.km) * (x/ (2.0|units.yr))**2 + (20.0|units.km)
fit = quantities.polyfit(x, y, 2)
self.assertEquals(len(fit), 3)
self.assertEquals(fit[0].unit, units.km/units.yr**2)
fit_values = quantities.polyval(fit, x)
self.assertEquals(fit_values.shape, x.shape)
self.assertEquals(y.unit, fit_values.unit)
self.assertAlmostRelativeEquals(y, fit_values, 1)
def evolve_cloud_in_galaxy(N, RinitA, RinitB, tend, timestep, MA, RA, MB, RB):
Rgal = 1 | units.kpc
Mgal = 7.22e9 | units.MSun
alpha = 1.2
galaxy_code = GalacticCenterGravityCode(Rgal, Mgal, alpha)
cloud_codeA = plummer_model_A(BHTree,
N,
MA,
RA,
parameters=[("epsilon_squared",
(0.01 | units.parsec)**2)])
cloud_codeB = plummer_model_B(BHTree,
N,
MB,
RB,
parameters=[("epsilon_squared",
(0.01 | units.parsec)**2)])
cloudA = cloud_codeA.particles.copy()
cloudB = cloud_codeA.particles.copy()
cloudA.x += RinitA
cloudB.x += RinitB
cloudA.vy = 0.01 * galaxy_code.circular_velocity(RinitA)
cloudB.vy = 0.05 * galaxy_code.circular_velocity(RinitB)
channelA = cloudA.new_channel_to(cloud_codeA.particles)
channelA.copy_attributes(["x", "y", "z", "vx", "vy", "vz"])
channelB = cloudB.new_channel_to(cloud_codeB.particles)
channelB.copy_attributes(["x", "y", "z", "vx", "vy", "vz"])
system = bridge(verbose=False)
system.add_system(cloud_codeA, (galaxy_code, ))
system.add_system(cloud_codeB, (galaxy_code, ))
times = quantities.arange(0 | units.Myr, tend, timestep)
for i, t in enumerate(times):
system.evolve_model(t, timestep=timestep)
x = system.particles.x.value_in(units.parsec)
y = system.particles.y.value_in(units.parsec)
cloud_codeA.stop()
cloud_codeB.stop()
return x, y
def evolve_cluster_in_galaxy(N, pot, Rinit, Vinit, tstart, tend, timestep, M,
R):
galaxy_code = galpy_profile(pot, tgalpy=tstart)
cluster_code = setup_cluster(BHTree,
N,
Mcluster,
Rcluster,
Rinit,
Vinit,
parameters=[("epsilon_squared",
(0.1 | units.parsec)**2),
("timestep", 0.1 | units.Myr),
("opening_angle", 0.6)])
stars = cluster_code.particles.copy()
particles = []
channel_from_stars_to_cluster_code = stars.new_channel_to(
cluster_code.particles, attributes=["x", "y", "z", "vx", "vy", "vz"])
channel_from_cluster_code_to_stars = cluster_code.particles.new_channel_to(
stars, attributes=["x", "y", "z", "vx", "vy", "vz"])
system = bridge(verbose=False)
system.add_system(cluster_code, (galaxy_code, ))
system.add_system(galaxy_code)
times = quantities.arange(0 | units.Myr, tend - tstart, timestep)
for i, t in enumerate(times):
if (t.value_in(units.Myr) % 10 < timestep.value_in(units.Myr)):
print(t)
particles.append([
cluster_code.particles.position,
cluster_code.particles.velocity
])
system.evolve_model(t, timestep=timestep)
particles.append(
[cluster_code.particles.position, cluster_code.particles.velocity])
cluster_code.stop()
return particles
def evolve_sun_jupiter(particles, tend, dt):
SunJupiter = Particles()
SunJupiter.add_particle(particles[0])
SunJupiter.add_particle(particles[1])
converter = nbody_system.nbody_to_si(particles.mass.sum(),
particles[1].position.length())
gravity = ph4(converter)
gravity.particles.add_particles(particles)
channel_from_to_SunJupiter = gravity.particles.new_channel_to(SunJupiter)
semi_major_axis = []
eccentricity = []
times = quantities.arange(0 | units.yr, tend, dt)
for i, t in enumerate(times):
print "Time=", t.in_(units.yr)
channel_from_to_SunJupiter.copy()
orbital_elements = orbital_elements_from_binary(SunJupiter,
G=constants.G)
a = orbital_elements[2]
e = orbital_elements[3]
semi_major_axis.append(a.value_in(units.AU))
eccentricity.append(e)
gravity.evolve_model(t, timestep=dt)
# Plot
fig = plt.figure(figsize=(8, 6))
ax1 = fig.add_subplot(211,
xlabel='time(yr)',
ylabel='semi major axis (AU)')
ax1.plot(times.value_in(units.yr), semi_major_axis)
ax2 = fig.add_subplot(212, xlabel='time(yr)', ylabel='eccentriity')
ax2.plot(times.value_in(units.yr), eccentricity)
plt.show()
gravity.stop()
def evolve_sun_jupiter(particles, tend, dt):
SunJupiter = Particles()
SunJupiter.add_particle(particles[0])
SunJupiter.add_particle(particles[1])
converter=nbody_system.nbody_to_si(particles.mass.sum(), particles[1].position.length())
gravity = ph4(converter)
gravity.particles.add_particles(particles)
channel_from_to_SunJupiter = gravity.particles.new_channel_to(SunJupiter)
semi_major_axis = list()
eccentricity = list()
times = quantities.arange(0|units.yr, tend+dt, dt)
for i,t in enumerate(times):
#print "Time =", t.in_(units.yr)
channel_from_to_SunJupiter.copy()
orbital_elements = orbital_elements_from_binary(SunJupiter, G=constants.G)
a = orbital_elements[2]
e = orbital_elements[3]
semi_major_axis.append(a.value_in(units.AU))
eccentricity.append(e)
gravity.evolve_model(t, timestep=dt)
gravity.stop()
# save the data: times, semi_major_axis and eccentricity of Jupiter's orbit
t_a_e = np.column_stack((times.value_in(units.yr), semi_major_axis, eccentricity))
np.savetxt('t_a_e.txt', t_a_e, delimiter=',')
# make plots
fig = plt.figure(figsize = (8, 6))
ax1 = fig.add_subplot(211, xlabel = 'time(yr)', ylabel = 'semi major axis (AU)')
ax1.plot(times.value_in(units.yr), semi_major_axis)
ax2 = fig.add_subplot(212, xlabel = 'time(yr)', ylabel = 'eccentriity')
ax2.plot(times.value_in(units.yr), eccentricity)
plt.show()
def evolve(cluster, cloud, t_end, dt_bridge, dt_diag):
converter = nbody_system.nbody_to_si(1. | units.MSun, 1. | units.parsec)
# Initialising the direct N-body integrator
print('Setting up the gravity code and the hydro code...')
gravity = ph4(converter)
gravity.particles.add_particles(cluster)
# Initialising the hydro code
sph = Fi(converter, mode="openmp")
sph.gas_particles.add_particles(cloud)
#sph.parameters.use_hydro_flag = True
#sph.parameters.radiation_flag = False
#sph.parameters.gamma = 1
#sph.parameters.isothermal_flag = True
#sph.parameters.integrate_entropy_flag = False
sph.parameters.timestep = dt_diag
#sph.parameters.verbosity = 0
#sph.parameters.eps_is_h_flag = False # h_smooth is constant
#eps = 0.1 | units.parsec
#sph.parameters.gas_epsilon = eps
#sph.parameters.sph_h_const = eps
#cloud.h_smooth= eps
print("cloud:", sph.gas_particles)
plt.scatter(
np.log10(sph.gas_particles.density.value_in(units.g / units.cm**3)),
sph.gas_particles.pressure.value_in(units.kg / units.m / units.s**2),
s=10)
plt.show()
# Building a bridge between hydro and grav
print('Bridging...')
grav_sph = bridge.Bridge(use_threading=False)
grav_sph.add_system(gravity, (sph, ))
grav_sph.add_system(sph, (gravity, ))
grav_sph.timestep = dt_bridge
# Setting up channels from code to cloud and cluster
channel_from_grav_to_cluster = gravity.particles.new_channel_to(cluster)
channel_from_sph_to_cloud = sph.gas_particles.new_channel_to(cloud)
# Initializing 90 percent lagrangian radius
lr9 = []
lr9.append(L9_radius(cloud, converter))
# Evolving
print('Start evolving the molecular cloud...')
times = quantities.arange(0. | units.Myr, t_end, dt_diag)
for i, t in enumerate(times):
print(t.in_(units.Myr))
grav_sph.evolve_model(t, dt_diag)
channel_from_grav_to_cluster.copy()
channel_from_sph_to_cloud.copy()
plot_cloud_cluster(cluster, sph, title='{0}'.format(float(t.value_in(units.Myr))),\
L=400, vrange=[-5,1])
lr9.append(L9_radius(cloud, converter))
#print("cloud:", sph.gas_particles)
#xx
#plt.scatter(np.log10(sph.gas_particles.density.value_in(units.g/units.cm**3)),
# sph.gas_particles.pressure.value_in(units.kg/units.m/units.s**2), s=10)
plt.show()
gravity.stop()
sph.stop()
return lr9
def gravity_hydro_bridge(gravity,
hydro,
sink,
local_particles,
Rmin,
t_end=1000. | units.yr,
dt=10. | units.yr):
Sun_and_Jupiter, disk_gas = local_particles
Mstar = 1.0 | units.MSun
print 'Bridging...'
# Build up the bridge between gravity and hydrodynamics
grav_hydro = bridge.Bridge(use_threading=False)
grav_hydro.add_system(gravity, (hydro, ))
grav_hydro.add_system(hydro, (gravity, ))
grav_hydro.timestep = dt
# Set up channels for updating the particles
channel_from_grav = gravity.particles.new_channel_to(Sun_and_Jupiter)
channel_from_hydro = hydro.gas_particles.new_channel_to(disk_gas)
channel_to_grav = Sun_and_Jupiter.new_channel_to(gravity.particles)
channel_to_hydro = disk_gas.new_channel_to(hydro.gas_particles)
# Preparing lists for data-recording
a_Jup = []
e_Jup = []
disk_size = []
accreted_mass = []
accreted_mass.append((sink.mass).value_in(units.MJupiter)[0])
sink0_mass = 0 | units.MJupiter
# Start evolution
print 'Start evolving...'
times = quantities.arange(0. | units.yr, t_end + 1 * dt, dt)
model_time = 0.0 | units.yr
while model_time <= t_end:
# Save the data for plots
orbit = orbital_elements_from_binary(Sun_and_Jupiter, G=constants.G)
a = orbit[2].value_in(units.AU)
e = orbit[3]
lr9 = return_L9_radius(disk_gas, Mstar, Rmin | units.AU)
a_Jup.append(a)
e_Jup.append(e)
disk_size.append(lr9)
am = (sink.mass[0]).value_in(units.MJupiter)
accreted_mass.append(am)
# Plotting system
print 'Time = %.1f yr:'%model_time.value_in(units.yr), \
'a = %.2f au, e = %.2f,'%(a, e), \
'disk size = %.2f au'%lr9
plot_map(hydro,
Sun_and_Jupiter,
'{0}'.format(int(model_time.value_in(units.yr))),
show=False)
# Evolve the bridge system for one step
model_time += dt
grav_hydro.evolve_model(model_time)
channel_from_grav.copy()
channel_from_hydro.copy()
# Calculating accreted mass in new position
Jupiter = gravity.particles[0]
sink.position = Jupiter.position
sink.radius = Hill_radius(a, e, Sun_and_Jupiter) | units.AU
removed_particles = hydro_sink_particles(sink, disk_gas)
Jupiter.mass += sink.mass - sink0_mass
sink0_mass = sink.mass.copy()
channel_to_grav.copy()
channel_to_hydro.copy()
gravity.stop()
hydro.stop()
return a_Jup, e_Jup, disk_size, times, accreted_mass
def test1(self):
array = quantities.arange(0 | units.kg, 10 | units.kg, 1 | units.kg)
self.assertEquals(len(array), 10)
self.assertAlmostRelativeEquals(array, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] | units.kg)
def evolve(cluster,cloud, converter_grav,converter_sph, t_end, dt_sph, dt_diag,\
sink=True, merge=False):
with open(printout_file, 'a') as pf:
pf.write('Setting up the gravity code and the hydro code...\n')
'''# Initialising the direct N-body integrator
gravity = ph4(converter_grav)
gravity.particles.add_particles(cluster)'''
# Initialising the hydro code
sph = Fi(converter_sph, mode="openmp")
sph.gas_particles.add_particles(cloud)
sph.dm_particles.add_particles(cluster)
sph.parameters.radiation_flag = False
#sph.parameters.isothermal_flag = True
#sph.parameters.integrate_entropy_flag = False #should we consider isothermal process or adiabatic one?
sph.parameters.timestep = dt_sph
#sph.parameters.eps_is_h_flag = False # h_smooth is constant
#eps = 0.1 | units.parsec
#sph.parameters.gas_epsilon = eps
#sph.parameters.sph_h_const = eps
#cloud.h_smooth= eps
'''# Building a bridge between hydro and grav
with open(printout_file, 'a') as pf:
pf.write('Bridging...\n')
grav_sph = bridge.Bridge(use_threading=False)
grav_sph.add_system(gravity, (sph,))
grav_sph.add_system(sph, (gravity,))
grav_sph.timestep = dt_bridge'''
# Setting up channels from code to cloud and cluster
#channel_from_grav_to_cluster = gravity.particles.new_channel_to(cluster)
channel_from_sph_to_cloud = sph.gas_particles.new_channel_to(cloud)
channel_from_sph_to_cluster = sph.dm_particles.new_channel_to(cluster)
# consider star formation
if sink == True:
with open(printout_file, 'a') as pf:
pf.write('[Star formation is considered.]\n')
stars = Particles(0)
sph.dm_particles.add_particles(stars)
density_threshold = Jeans_density(M=sph.gas_particles.mass.max())
sph.parameters.stopping_condition_maximum_density = density_threshold
density_limit_detection = sph.stopping_conditions.density_limit_detection
density_limit_detection.enable()
if merge == True:
merge_radius = 1e-4 | units.parsec # 1 pc = 206265 AU
with open(printout_file, 'a') as pf:
pf.write('[Star merging is considered.]\n')
# Initialize data lists (Lagrangian radii and relative total energy)
lr_cloud_list = [Lagrange_radii(cloud, converter_sph)]
lr_cluster_list = [Lagrange_radii(cluster, converter_grav)]
E0_cloud = get_energy(cloud)
Etot0_cloud = E0_cloud[-1]
E_cloud_list = [E0_cloud / Etot0_cloud]
E0_cluster = get_energy(cluster)
Etot0_cluster = E0_cluster[-1]
E_cluster_list = [E0_cluster / Etot0_cluster]
n_formed_star = [0]
# Start Evolving!
# unify the unit of times
unit_time = units.Myr
t_end = t_end.in_(unit_time)
dt_diag = dt_diag.in_(unit_time)
dt_sph = dt_sph.in_(unit_time)
times = quantities.arange(0. | unit_time, t_end + dt_diag, dt_diag)
with open(printout_file, 'a') as pf:
pf.write('\nStart evolving the molecular cloud...\n')
pf.write(
f'End time = {t_end}; Diagnostic timestep = {dt_diag}; sph code timestep = {dt_sph}.\n'
)
for i, t in enumerate(times):
with open(printout_file, 'a') as pf:
pf.write(f'---------- Time = {t.in_(units.Myr)} ----------\n')
# calculate the dynamical(dyn), half-mass relaxation(rh), and free-fall(ff) timescales
# of both the cloud and the cluster systems
t_dyn_cloud, t_rh_cloud, t_ff_cloud = timescale(cloud, unit_time)
t_dyn_cluster, t_rh_cluster, t_ff_cluster = timescale(
cluster, unit_time)
all_timescales = [
t_dyn_cloud, t_rh_cloud, t_ff_cloud, t_dyn_cluster, t_rh_cluster,
t_ff_cluster
] | unit_time
# check if the bridge timestep should be reduced
if all_timescales.amax() < 10 * dt_sph:
dt_sph_old = dt_sph
dt_sph = all_timescales.amax() / 10.
with open(printout_file, 'a') as pf:
pf.write(
f'Change the bridge timestep from {dt_sph_old} to {dt_sph}.\n'
)
if sink == True:
# make sure at this time, elements in 'stars' and 'sph.gas_particles' are the same
resolve_sinks(sph, stars, cloud, density_threshold, t)
# evolve for one diagnostic timestep
#grav_sph.evolve_model(t, timestep=dt_bridge)
sph.evolve_model(t, timestep=dt_sph)
#channel_from_grav_to_cluster.copy()
channel_from_sph_to_cloud.copy()
channel_from_sph_to_cluster.copy()
if len(stars) > 0:
newstars = cluster.select_array(
lambda birth_age: birth_age >= 0. | unit_time, ["birth_age"])
cluster.remove_particles(newstars)
# merge two stars if they are too close to each other (distance < merge_radius)
# typically we don't consider merging event since it is very rare given a reasonable merge radius
if merge == True:
merge_stars(sph, stars, merge_radius)
with open(printout_file, 'a') as pf:
pf.write('Number of stars in `cluster`= %d; in `stars` = %d; in `sph.dm_particles`= %d.\n'\
%(len(cluster), len(stars), len(sph.dm_particles)))
# make snapshots
plot_cloud_cluster(cluster, sph, stars, title='{0}'.format(float(t.value_in(units.Myr))),\
vrange=[-5,3])
# save data (energy will be added afterwards)
lr_cloud = Lagrange_radii(cloud, converter_sph)
lr_cloud_list.append(lr_cloud)
lr_cluster = Lagrange_radii(cluster, converter_grav)
lr_cluster_list.append(lr_cluster)
E_cloud = get_energy(cloud, norm=Etot0_cloud)
E_cloud_list.append(E_cloud)
E_cluster = get_energy(cluster, norm=Etot0_cluster)
E_cluster_list.append(E_cluster)
n_formed_star.append(len(stars))
# save data instantaneously
lr_data = np.concatenate(
([t.value_in(unit_time)], lr_cloud, lr_cluster))
E_data = np.concatenate(([t.value_in(unit_time)], E_cloud, E_cluster))
with open('lr_data.txt', 'a') as f_lr_data:
f_lr_data.write(','.join(str(x) for x in lr_data) + '\n')
with open('E_data.txt', 'a') as f_E_data:
f_E_data.write(','.join(str(x) for x in E_data) + '\n')
with open('formed_star_data.txt', 'a') as f_fs_data:
f_fs_data.write('%f,%d\n' % (t.value_in(unit_time), len(stars)))
with open(printout_file, 'a') as pf:
pf.write(f'Finished.\n')
#gravity.stop()
sph.stop()
return times.value_in(
unit_time
), n_formed_star, lr_cloud_list, lr_cluster_list, E_cloud_list, E_cluster_list
def gravity_hydro_bridge(gravity,
hydro,
local_particles,
Rmin,
t_end=1000. | units.yr,
dt=10. | units.yr):
Sun_and_Jupiter, disk_gas = local_particles
Mstar = gravity.particles[1].mass.in_(units.MSun)
print 'Bridging...'
# build up the bridge between gravity and hydrodynamics
grav_hydro = bridge.Bridge(use_threading=False)
grav_hydro.add_system(gravity, (hydro, ))
grav_hydro.add_system(hydro, (gravity, ))
#grav_hydro.timestep = dt
# set up channels for updating the particles
channel_from_grav = gravity.particles.new_channel_to(Sun_and_Jupiter)
channel_from_hydro = hydro.gas_particles.new_channel_to(disk_gas)
a_Jup = list()
e_Jup = list()
disk_size = list()
# start evolotuion
print 'Start evolving...'
times = quantities.arange(0. | units.yr, t_end + 1 * dt, 2 * dt)
model_time = 0.0 | units.yr
while model_time <= t_end:
# save the data for plots
orbit = orbital_elements_from_binary(Sun_and_Jupiter, G=constants.G)
a = orbit[2].value_in(units.AU)
e = orbit[3]
lr9 = return_L9_radius(disk_gas, Mstar, Rmin | units.AU)
a_Jup.append(a)
e_Jup.append(e)
disk_size.append(lr9)
if model_time.value_in(units.yr) % 50 == 0:
print 'Time = %.1f yr:'%model_time.value_in(units.yr), \
'a = %.2f au, e = %.2f,'%(a, e), \
'disk size = %.2f au'%lr9
# evolve the bridge system for one step
model_time += dt
grav_hydro.evolve_model(model_time, timestep=2 * dt)
channel_from_grav.copy()
channel_from_hydro.copy()
# add the 'sinked' mass to Jupiter & keep the sink particle along with Jupiter
sink = hydro.particles[0]
_ = hydro_sink_particles([sink], disk_gas)
Jupiter = gravity.particles[1]
Jupiter.mass += sink.mass
sink.position = Jupiter.position
sink.radius = a * (1 - e) * (
(1.0 | units.MJupiter).value_in(units.MSun) / 3.)**(1. /
3.) | units.au
channel_from_grav.copy()
channel_from_hydro.copy()
gravity.stop()
hydro.stop()
return a_Jup, e_Jup, disk_size, times
def evolve(Sun_Jupiter, disk_gas, sink, Pstar, dt_gravity, dt_sph,
dt_diagnostic, dt_bridge, tend):
Sun = Sun_Jupiter[0]
Jupiter = Sun_Jupiter[1]
# Initialising the SPH code
sph_converter = nbody_system.nbody_to_si(1 | units.MSun, 1 | units.AU)
sph = Fi(sph_converter, mode="openmp")
sph.gas_particles.add_particles(disk_gas)
sph.dm_particles.add_particle(Sun)
sph.dm_particles.add_particle(Jupiter)
sph.dm_particles.add_particle(Pstar)
# Set up channels for updating the particles
sph_to_disk = sph.gas_particles.new_channel_to(disk_gas)
sph_to_Sun_Jupiter = sph.dm_particles.new_channel_to(Sun_Jupiter)
sph_to_Pstar = sph.dm_particles.new_channel_to(Pstar)
Sun_Jupiter_to_sph = Sun_Jupiter.new_channel_to(sph.dm_particles)
disk_to_sph = disk_gas.new_channel_to(sph.gas_particles)
Pstar_to_sph = Pstar.new_channel_to(sph.dm_particles)
# Preparing lists for data-recording
a_Jup = []
e_Jup = []
disk_size = []
accreted_mass = []
accreted_mass.append((sink.mass).value_in(units.MJupiter)[0])
sink0_mass = 0 | units.MJupiter
# Start evolution
print 'Start evolving...'
times = quantities.arange(0. | units.yr, tend, dt_diagnostic)
for i, t in enumerate(times):
# Save the data for plots
orbit = orbital_elements_from_binary(Sun_Jupiter, G=constants.G)
a = orbit[2].value_in(units.AU)
e = orbit[3]
lr9 = return_L9_radius(disk_gas, Sun_Jupiter[0].mass, Rmin)
a_Jup.append(a)
e_Jup.append(e)
disk_size.append(lr9)
# Plotting system
print 'Time = %.1f yr:'%t.value_in(units.yr), \
'a = %.2f au, e = %.2f,'%(a, e), \
'disk size = %.2f au'%lr9
plot_map(sph,
Sun_Jupiter,
Pstar,
'distribution_plot_passing_star_full_hydro_4k/{0}.png'.format(
int(t.value_in(units.yr))),
show=False)
# Evolve the bridge system for one step
sph.evolve_model(t, dt_diagnostic)
sph_to_disk.copy()
sph_to_Sun_Jupiter.copy()
sph_to_Pstar.copy()
# Calculating accreted mass in new position
sink.position = Jupiter.position
sink.radius = Hill_radius(a, e, Sun_Jupiter) | units.AU
removed_particles = hydro_sink_particles(sink, disk_gas)
Jupiter.mass += sink.mass - sink0_mass
accreted_mass.append((sink.mass).value_in(units.MJupiter)[0])
sink0_mass = sink.mass.copy()
Sun_Jupiter_to_sph.copy()
disk_to_sph.copy()
Sun_Jupiter_to_sph.copy()
Pstar_to_sph.copy()
sph.stop()
return times, a_Jup, e_Jup, disk_size, accreted_mass
def evolve(cluster,cloud, converter_grav,converter_sph, t_end, dt_sph, dt_diag,\
sink=True, merge=False):
with open(printout_file, 'a') as pf:
pf.write('Setting up the hydro code...\n')
'''# Initialising the direct N-body integrator
gravity = ph4(converter_grav)
gravity.particles.add_particles(cluster)'''
# Initialising the hydro code
sph = Fi(converter_sph, mode="openmp")
sph.gas_particles.add_particles(cloud)
sph.dm_particles.add_particles(cluster)
sph.parameters.radiation_flag = False
#sph.parameters.isothermal_flag = True
#sph.parameters.integrate_entropy_flag = False #should we consider isothermal process or adiabatic one?
sph.parameters.timestep = dt_sph
#sph.parameters.eps_is_h_flag = False # h_smooth is constant
#eps = 0.1 | units.parsec
#sph.parameters.gas_epsilon = eps
#sph.parameters.sph_h_const = eps
#cloud.h_smooth= eps
'''# Building a bridge between hydro and gravity
with open(printout_file, 'a') as pf:
pf.write('Bridging...\n')
grav_sph = bridge.Bridge(use_threading=False)
grav_sph.add_system(gravity, (sph,))
grav_sph.add_system(sph, (gravity,))
grav_sph.timestep = dt_bridge'''
# Setting up channels from code to cloud and cluster
#channel_from_grav_to_cluster = gravity.particles.new_channel_to(cluster)
channel_from_sph_to_cloud = sph.gas_particles.new_channel_to(cloud)
channel_from_sph_to_cluster = sph.dm_particles.new_channel_to(cluster)
# considers star formation
if sink == True:
with open(printout_file, 'a') as pf:
pf.write('[Star formation is considered.]\n')
# `stars` is initialized as a particle set for potential new stars forming in the cloud
stars = Particles(0)
sph.dm_particles.add_particles(stars)
# set a density threshold (Jeans density) in the sph code
density_threshold = Jeans_density(M=sph.gas_particles.mass.max())
with open('cloud_data.txt', 'a') as f_cd_data:
f_cd_data.write('# Jeans density of the cloud = %.5e kg/m^3\n' %
density_threshold.value_in(units.kg / units.m**3))
sph.parameters.stopping_condition_maximum_density = density_threshold
density_limit_detection = sph.stopping_conditions.density_limit_detection
density_limit_detection.enable()
# considers star merging
if merge == True:
merge_radius = 1e-4 | units.parsec # 1 pc = 206265 AU
with open(printout_file, 'a') as pf:
pf.write('[Star merging is considered.]\n')
# Initializing data lists
lr_cloud_list = [Lagrange_radii(cloud, converter_sph)]
lr_cluster_list = [Lagrange_radii(cluster, converter_grav)]
E_norm = 1e42 | (units.kg * units.m**2 / units.s**2)
E0_cloud = get_energy(cloud, E_norm)
#Etot0_cloud = E0_cloud[-1]
E_cloud_list = [E0_cloud]
E0_cluster = get_energy(cluster)
#Etot0_cluster = E0_cluster[-1]
E_cluster_list = [E0_cluster]
n_formed_star = [0]
max_gas_density = [
sph.gas_particles.density.max().value_in(units.kg / units.m**3)
]
# unify the unit of times
unit_time = units.Myr
t_end = t_end.in_(unit_time)
dt_diag = dt_diag.in_(unit_time)
dt_sph = dt_sph.in_(unit_time)
times = quantities.arange(0. | unit_time, t_end + dt_diag, dt_diag)
with open(printout_file, 'a') as pf:
pf.write('\nStart evolving the molecular cloud...\n')
pf.write(
f'End time = {t_end}; Diagnostic timestep = {dt_diag}; Initial SPH timestep = {dt_sph}.\n'
)
# Real start for evolution!
for i, t in enumerate(times):
with open(printout_file, 'a') as pf:
pf.write(f'---------- Time = {t.in_(units.Myr)} ----------\n')
# calculates the dynamical(dyn), half-mass relaxation(rh), and free-fall(ff) timescales
# for both the cloud and the cluster
t_dyn_cloud, t_rh_cloud, t_ff_cloud = timescale(cloud, unit_time)
t_dyn_cluster, t_rh_cluster, t_ff_cluster = timescale(
cluster, unit_time)
all_timescales = [
t_dyn_cloud, t_rh_cloud, t_ff_cloud, t_dyn_cluster, t_rh_cluster,
t_ff_cluster
] | unit_time
shortest_ts = all_timescales.amin()
dt_sph = np.round(
(shortest_ts / 10.).value_in(unit_time), 2) | unit_time
with open(printout_file, 'a') as pf:
pf.write(
'Current evolve timestep: %.2f Myr; Shortest timescale: %.2f Myr.\n'
%
(dt_sph.value_in(unit_time), shortest_ts.value_in(unit_time)))
# considers star information
# (make sure that at this time, elements in 'stars' and 'sph.gas_particles' are the same)
if sink == True:
resolve_sinks(sph, stars, cloud, density_threshold, t)
# evolve for one diagnostic timestep
#grav_sph.evolve_model(t, timestep=dt_bridge)
sph.evolve_model(t, timestep=dt_sph)
#channel_from_grav_to_cluster.copy()
channel_from_sph_to_cloud.copy()
channel_from_sph_to_cluster.copy()
# remove newly formed stars from `cluster` after using channels
# (since both `stars` and `cluster` are added as dm_particles in sph, we have to distinguish them by `birth_age`)
if len(stars) > 0:
newstars = cluster.select_array(
lambda birth_age: birth_age >= 0. | unit_time, ["birth_age"])
cluster.remove_particles(newstars)
# merge two stars if they are too close to each other (distance < merge_radius)
# typically we don't consider merging event since it is very rare given a reasonable merge radius
if merge == True:
merge_stars(sph, stars, merge_radius)
# sanity check
with open(printout_file, 'a') as pf:
pf.write('Number of stars in `cluster`= %d; in `stars` = %d; in `sph.dm_particles`= %d.\n'\
%(len(cluster), len(stars), len(sph.dm_particles)))
# make snapshots
plot_cloud_cluster(cluster, sph, stars, title='{0}'.format(float(t.value_in(units.Myr))),\
vrange=[-5,3])
# save data
lr_cloud = Lagrange_radii(cloud, converter_sph)
lr_cloud_list.append(lr_cloud)
lr_cluster = Lagrange_radii(cluster, converter_grav)
lr_cluster_list.append(lr_cluster)
E_cloud = get_energy(cloud, norm=E_norm)
E_cloud_list.append(E_cloud)
E_cluster = get_energy(cluster, norm=E_norm)
E_cluster_list.append(E_cluster)
n_formed_star.append(len(stars))
max_gas_density.append(sph.gas_particles.density.max().value_in(
units.kg / units.m**3))
# save data instantaneously
lr_data = np.concatenate(
([t.value_in(unit_time)], lr_cloud, lr_cluster))
E_data = np.concatenate(([t.value_in(unit_time)], E_cloud, E_cluster))
with open('lr_data.txt', 'a') as f_lr_data:
f_lr_data.write(','.join(str(x) for x in lr_data) + '\n')
with open('E_data.txt', 'a') as f_E_data:
f_E_data.write(','.join(str(x) for x in E_data) + '\n')
with open('cloud_data.txt', 'a') as f_cd_data:
f_cd_data.write('%.2f,%d,%.5e\n'%(t.value_in(unit_time), len(stars),\
sph.gas_particles.density.max().value_in(units.kg/units.m**3)))
with open(printout_file, 'a') as pf:
pf.write(f'Finished.\n')
#gravity.stop()
sph.stop()
return times.value_in(unit_time), n_formed_star, max_gas_density,\
lr_cloud_list, lr_cluster_list, E_cloud_list, E_cluster_list
def test1(self):
array = quantities.arange(0 | units.kg, 10 | units.kg, 1 | units.kg)
self.assertEquals(len(array), 10)
self.assertAlmostRelativeEquals(array, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
| units.kg)
def evolve(Sun_Jupiter, disk_gas, sink, Pstar, dt_gravity, dt_sph,
dt_diagnostic, dt_bridge, tend):
Sun = Sun_Jupiter[0]
Jupiter = Sun_Jupiter[1]
# Initialising the direct N-body integrator
#gravity_converter = nbody_system.nbody_to_si(Jupiter.mass, Jupiter.position.length())
gravity_converter = nbody_system.nbody_to_si(1 | units.MSun, 1 | units.AU)
gravity = ph4(gravity_converter)
gravity.particles.add_particle(Jupiter)
#gravity.particles.add_particle(Pstar)
gravity.timestep = dt_gravity
# Initialising the SPH code
sph_converter = nbody_system.nbody_to_si(1 | units.MSun, 1 | units.AU)
#sph_converter = nbody_system.nbody_to_si(Pstar.mass.sum(), Rmin)
sph = Fi(sph_converter, mode="openmp")
sph.gas_particles.add_particles(disk_gas)
sph.dm_particles.add_particle(Sun)
#sph.dm_
sph.dm_particles.add_particle(Pstar)
sph.parameters.timestep = dt_sph
print 'Bridging...'
# Build up the bridge between gravity and hydrodynamics
grav_sph = bridge.Bridge(use_threading=False)
grav_sph.add_system(gravity, (sph, ))
grav_sph.add_system(sph, (gravity, ))
grav_sph.timestep = dt_bridge
# Set up channels for updating the particles
gravity_to_Jupiter = gravity.particles.new_channel_to(Sun_Jupiter)
sph_to_disk = sph.gas_particles.new_channel_to(disk_gas)
sph_to_Sun = sph.dm_particles.new_channel_to(Sun_Jupiter)
sph_to_Pstar = sph.dm_particles.new_channel_to(Pstar)
Jupiter_to_gravity = Sun_Jupiter.new_channel_to(gravity.particles)
disk_to_sph = disk_gas.new_channel_to(sph.gas_particles)
Sun_to_sph = Sun_Jupiter.new_channel_to(sph.dm_particles)
Pstar_to_sph = Pstar.new_channel_to(sph.dm_particles)
'''
gravity_to_Jupiter = gravity.particles.new_channel_to(Sun_Jupiter)
gravity_to_Pstar = gravity.particles.new_channel_to(Pstar)
sph_to_disk = sph.gas_particles.new_channel_to(disk_gas)
sph_to_Sun = sph.dm_particles.new_channel_to(Sun_Jupiter)
Jupiter_to_gravity = Sun_Jupiter.new_channel_to(gravity.particles)
Pstar_to_gravity = Pstar.new_channel_to(gravity.particles)
disk_to_sph = disk_gas.new_channel_to(sph.gas_particles)
Sun_to_sph = Sun_Jupiter.new_channel_to(sph.dm_particles)
'''
# Sanity checks:
print('Sanity checks:')
#print('Star coordinates (AU)',Pstar.x.value_in(units.AU),
# Pstar.y.value_in(units.AU),
# Pstar.z.value_in(units.AU))
print('Disk particle map saved to: initial_check_disk.png')
#plot_map(sph, Sun_Jupiter, Pstar,'initial_check_disk.png',show=True)
a_Jup = []
e_Jup = []
disk_size = []
accreted_mass = []
# start evolotuion
print 'Start evolving...'
times = quantities.arange(0. | units.yr, tend, dt_diagnostic)
for i, t in enumerate(times):
# Save the data for plots
orbit = orbital_elements_from_binary(Sun_Jupiter, G=constants.G)
a = orbit[2].value_in(units.AU)
e = orbit[3]
lr9 = return_L9_radius(disk_gas, Sun_Jupiter[0].mass, Rmin)
a_Jup.append(a)
e_Jup.append(e)
disk_size.append(lr9)
accreted_mass.append((sink.mass).value_in(units.MJupiter)[0])
# Plotting
#print('Star coordinates (AU)',Pstar.x.value_in(units.AU),
# Pstar.y.value_in(units.AU),
# Pstar.z.value_in(units.AU))
print 'Time = %.1f yr:'%t.value_in(units.yr), \
'a = %.2f au, e = %.2f,'%(a, e), \
'disk size = %.2f au'%lr9
plot_map(sph,
Sun_Jupiter,
Pstar,
'distribution_plot_passing_star_grav/{0}.png'.format(
int(t.value_in(units.yr))),
show=False)
# Evolve the bridge system for one step
grav_sph.evolve_model(t, dt_diagnostic)
gravity_to_Jupiter.copy()
sph_to_disk.copy()
sph_to_Sun.copy()
sph_to_Pstar.copy()
# Add the 'sinked' mass to Jupiter & keep the sink particle along with Jupiter
removed_particles = hydro_sink_particles(sink, disk_gas)
Jupiter = gravity.particles[0]
Jupiter.mass += sink.mass
sink.position = Jupiter.position
sink.radius = Hill_radius(a, e, Sun_Jupiter) | units.AU
Jupiter_to_gravity.copy()
disk_to_sph.copy()
Sun_to_sph.copy()
Pstar_to_sph.copy()
gravity.stop()
sph.stop()
return t, a_Jup, e_Jup, disk_size, accreted_mass
def evolve_cluster(cluster,mCut,dt,tend,mCluster,rCluster):
print 'Start evolving the cluster with mCut =', mCut
# timing
t1 = time()
converter=nbody_system.nbody_to_si(mCluster,rCluster)
# split particle according to mass_cut
low_mass_stars = cluster.select(lambda m: m < mCut,["mass"])
high_mass_stars = cluster.select(lambda m: m >= mCut,["mass"])
print 'Number of low-mass stars:', low_mass_stars.__len__()
print 'Number of high-mass stars:', high_mass_stars.__len__()
# make models and assigning particles
code_tree = BHTree(converter)
code_direct = ph4(converter)
code_tree.particles.add_particles(low_mass_stars)
code_direct.particles.add_particles(high_mass_stars)
channel_from_code_tree = code_tree.particles.new_channel_to(low_mass_stars)
channel_from_code_direct = code_direct.particles.new_channel_to(high_mass_stars)
# make bridge
combined_gravity = bridge()
combined_gravity.add_system(code_tree,(code_direct,))
combined_gravity.add_system(code_direct,(code_tree,))
combined_gravity.timestep = dt
# the initial total energy
E0 = combined_gravity.potential_energy + combined_gravity.kinetic_energy
# evolve the model
times = quantities.arange(0.|units.Myr, tend+dt, dt)
n_step = len(times)
dE = np.empty(n_step)
Qs = np.empty(n_step)
for i,t in enumerate(times):
if t.value_in(units.Myr)%1 == 0:
print "Time =", t.in_(units.Myr)
channel_from_code_tree.copy()
channel_from_code_direct.copy()
combined_gravity.evolve_model(t, timestep=dt)
U = cluster.potential_energy()
T = cluster.kinetic_energy()
Et = U + T
dE[i] = np.abs((E0-Et)/E0)
Qs[i] = -T / U
code_tree.stop()
code_direct.stop()
t2 = time()
print 'Finished. Time cost: %.2f s'%(t2-t1)
output_filename = 'ee_q_%.1f.txt'%mCut.value_in(units.MSun)
with open(output_filename, 'w'):
np.savetxt(output_filename, np.append(dE,Qs).reshape(2,n_step).transpose())
print 'Saved the data of energy error and virial ratios in', output_filename
# plot energy
plot_energy_error(times.value_in(units.Myr), dE, Qs, mCut)
return dE[-1], Qs[-1], t2-t1
def evolve(cluster,cloud, converter_grav,converter_sph, t_end, dt_bridge, dt_diag,\
sink=False):
with open('print_out.txt', 'a') as pf:
pf.write('Setting up the gravity code and the hydro code...\n')
converter = nbody_system.nbody_to_si(1. | units.MSun, 1. | units.parsec)
# Initialising the direct N-body integrator
#gravity = ph4(converter_grav)
#gravity.particles.add_particles(cluster)
# Initialising the hydro code
sph = Fi(converter, mode="openmp")
#sph.gas_particles.add_particles(cloud)
sph.dm_particles.add_particles(cluster)
#sph.parameters.use_hydro_flag = True
sph.parameters.radiation_flag = False
#sph.parameters.isothermal_flag = True
#sph.parameters.integrate_entropy_flag = False
sph.parameters.timestep = dt_bridge
#sph.parameters.verbosity = 0
#sph.parameters.eps_is_h_flag = False # h_smooth is constant
#eps = 0.1 | units.parsec
#sph.parameters.gas_epsilon = eps
#sph.parameters.sph_h_const = eps
#cloud.h_smooth= eps
#print("cloud:", sph.gas_particles)
#plt.scatter(np.log10(sph.gas_particles.density.value_in(units.g/units.cm**3)),
# sph.gas_particles.pressure.value_in(units.kg/units.m/units.s**2), s=10)
#plt.show()
# Setting up channels from code to cloud and cluster
#channel_from_grav_to_cluster = gravity.particles.new_channel_to(cluster)
channel_from_sph_to_cluster = sph.dm_particles.new_channel_to(cluster)
#channel_from_sph_to_cloud = sph.gas_particles.new_channel_to(cloud)
'''
if sink == True:
with open('print_out.txt','a') as pf:
pf.write('star formation is considered\n')
stars = Particles(0)
sph.dm_particles.add_particles(stars)
channel_from_sph_to_star = sph.dm_particles.new_channel_to(stars)
density_threshold = Jeans_density(M=sph.gas_particles.mass.max())
sph.parameters.stopping_condition_maximum_density = density_threshold
density_limit_detection = sph.stopping_conditions.density_limit_detection
density_limit_detection.enable()
merge_radius = 1e-2 | units.parsec # around 20 AU
'''
# Initializing 90 percent lagrangian radius
#lr_cloud = []
#lr_cloud.append(Lagrang_radii(cloud, converter))
lr_cluster = []
lr_cluster.append(Lagrang_radii(cluster, converter))
# Evolving
with open('print_out.txt', 'a') as pf:
pf.write('Start evolving the molecular cloud...\n')
with open('l_radii.txt', 'w') as lr_txt:
lr_txt.write('#lr0.2 cloud, lr0.5 cloud, lr0.9 cloud, lr0.2 cluster, lr0.5 cluster, lr0.9 cluster \n')
times = quantities.arange(0.|units.Myr, t_end, dt_diag)
for i,t in enumerate(times):
with open('print_out.txt', 'a') as pf:
pf.write(str(t.value_in(units.Myr))+' Myr\n')
'''
if sink == True:
# make sure at this time 'stars' and 'sph.gas_particles' are the same
resolve_sinks(sph, stars, cloud, density_threshold, t)
'''
sph.evolve_model(t, dt_diag)
#gravity.evolve_model(t, dt_diag)
#channel_from_grav_to_cluster.copy()
channel_from_sph_to_cluster.copy()
#channel_from_sph_to_cloud.copy()
'''
if sink == True:
merge_stars(sph, stars, merge_radius)
'''
# make plots
#plot_cloud_cluster(cluster, sph, title='{0}'.format(float(t.value_in(units.Myr))),\
# vrange=[-5,3])
plot_cluster(cluster, title='cluster_{0}'.format(float(t.value_in(units.Myr))),\
vrange=[-5,3])
#plot_cloud(sph, title='cloud_{0}'.format(float(t.value_in(units.Myr))),\
# vrange=[-5,3])
# save data (energy will be added afterwards)
#lr_cloud.append(Lagrang_radii(cloud, converter))
lr_cluster.append(Lagrang_radii(cluster, converter))
#gravity.stop()
sph.stop()
return lr_cluster #lr_cloud