def evolve_cluster_in_galaxy(N, W0, Rinit, tend, timestep, M, R):
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=numpy.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()
from prepare_figure import single_frame, get_distinct
colors = get_distinct(1)
f = single_frame('X [pc]', 'Y [pc]')
pyplot.xlim(-60, 60)
pyplot.ylim(-60, 60)
pyplot.scatter(x,y, c=colors[0], s=50, lw=0)
pyplot.savefig("Arches")
def test1(self):
convert = nbody_system.nbody_to_si(1.e5 | units.MSun, 1.0 | units.parsec)
eps=2.e-4 | nbody_system.length
test_class=PhiGRAPE
number_of_particles = 50
stars = new_king_model(number_of_particles, W0=7, convert_nbody=convert)
stars.radius = 0.0 | units.RSun
cluster=test_class(convert)
cluster.parameters.epsilon_squared = eps**2
cluster.particles.add_particles(stars)
cluster.synchronize_model()
Ep1=convert.to_nbody(cluster.potential_energy).number
Ek1=convert.to_nbody(cluster.kinetic_energy).number
parts=cluster.particles.copy()
parts1=parts.select_array(lambda x: (x > 0 | units.m), ['x'] )
parts2=parts.select_array(lambda x: (x < 0 | units.m), ['x'] )
cluster1=sys_from_parts(test_class, parts1, convert, eps)
cluster2=sys_from_parts(test_class, parts2, convert, eps)
cluster1.synchronize_model()
cluster2.synchronize_model()
bridgesys=bridge()
bridgesys.add_system(cluster1, (cluster2,) )
bridgesys.add_system(cluster2, (cluster1,) )
Ep2=convert.to_nbody(bridgesys.potential_energy).number
Ek2=convert.to_nbody(bridgesys.kinetic_energy).number
self.assertAlmostEqual(Ek1,Ek2,12)
self.assertAlmostEqual(Ep1,Ep2,12)
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):
###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(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 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, W0, Rinit, tend, timestep, M, R):
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 = numpy.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()
from prepare_figure import single_frame, get_distinct
colors = get_distinct(1)
f = single_frame('X [pc]', 'Y [pc]')
pyplot.xlim(-60, 60)
pyplot.ylim(-60, 60)
pyplot.scatter(x, y, c=colors[0], s=50, lw=0)
pyplot.savefig("Arches")
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 test1(self):
convert = nbody_system.nbody_to_si(1.e5 | units.MSun,
1.0 | units.parsec)
eps = 2.e-4 | nbody_system.length
test_class = PhiGRAPE
number_of_particles = 50
stars = new_king_model(number_of_particles,
W0=7,
convert_nbody=convert)
stars.radius = 0.0 | units.RSun
cluster = test_class(convert)
cluster.parameters.epsilon_squared = eps**2
cluster.particles.add_particles(stars)
cluster.synchronize_model()
Ep1 = convert.to_nbody(cluster.potential_energy).number
Ek1 = convert.to_nbody(cluster.kinetic_energy).number
parts = cluster.particles.copy()
parts1 = parts.select_array(lambda x: (x > 0 | units.m), ['x'])
parts2 = parts.select_array(lambda x: (x < 0 | units.m), ['x'])
cluster1 = sys_from_parts(test_class, parts1, convert, eps)
cluster2 = sys_from_parts(test_class, parts2, convert, eps)
cluster1.synchronize_model()
cluster2.synchronize_model()
bridgesys = bridge()
bridgesys.add_system(cluster1, (cluster2, ))
bridgesys.add_system(cluster2, (cluster1, ))
Ep2 = convert.to_nbody(bridgesys.potential_energy).number
Ek2 = convert.to_nbody(bridgesys.kinetic_energy).number
self.assertAlmostEqual(Ek1, Ek2, 12)
self.assertAlmostEqual(Ep1, Ep2, 12)
cluster = PhiGRAPE(converter, parameters=[("epsilon_squared", (0.01 | units.parsec)**2)])
# create the external potential of the Galaxy
galaxy = Agama(converter, type="Dehnen", gamma=1.8, \
rscale=1000.| units.parsec, mass=1.6e10 | units.MSun, channel_type='sockets')
# shift the cluster to an orbit around Galactic center
acc,_,_ = galaxy.get_gravity_at_point(0|units.kpc, Rinit, 0|units.kpc, 0|units.kpc)
vcirc = (-acc * Rinit)**0.5
print "Vcirc=", vcirc.value_in(units.kms), "km/s"
particles.x += Rinit
particles.vy += vcirc
cluster.particles.add_particles(particles)
# set up bridge; cluster is evolved under influence of the galaxy
sys = bridge(verbose=False)
sys.add_system(cluster, (galaxy,), False)
# evolve and make plots
times = units.Myr([0.,0.2,0.4,0.6,0.8,1.0,1.2,1.4])
f = pyplot.figure(figsize=(8,16))
for i,t in enumerate(times):
sys.evolve_model(t, timestep=timestep)
print "Evolved the system to time",t
x=sys.particles.x.value_in(units.parsec)
y=sys.particles.y.value_in(units.parsec)
subplot=f.add_subplot(4,2,i+1)
subplot.plot(x,y,'r .')
def validate_bridge():
convert_clu = nbody_system.nbody_to_si(
1.e5 | units.MSun, 1.0 | units.parsec)
convert_gal = nbody_system.nbody_to_si(
1.e7 | units.MSun, 10. | units.parsec)
def convert_gal_to_clu(x): return convert_clu.to_nbody(
convert_gal.to_si(x))
def convert_clu_to_gal(x): return convert_gal.to_nbody(
convert_clu.to_si(x))
total_sim_time = convert_clu_to_gal(200 | nbody_system.time)
total_sim_time = 200 | nbody_system.time
sim_step = 1./128 | nbody_system.time
dt_diag = 1./64 | nbody_system.time
eps_clu = convert_gal_to_clu(2.e-4 | nbody_system.length)
eps_gal = 6.25e-3 | nbody_system.length
cluster = sys_from_king(PhiGRAPE, 1000, 7, convert_clu,
eps_clu, usegl=False, mode="gpu")
galaxy = sys_from_king(Fi, 10000, 9, convert_gal,
eps_gal, sim_step, usegl=False)
shift_sys(
cluster,
convert_clu.to_si(
convert_gal_to_clu(
2.5 | nbody_system.length
)
),
0 | units.m,
0 | units.m,
0 | units.m/units.s,
convert_clu.to_si(
convert_gal_to_clu(0.65 | nbody_system.speed)
),
0 | units.m/units.s)
if hasattr(cluster, "start_viewer"):
cluster.start_viewer()
if hasattr(galaxy, "viewer"):
galaxy.viewer()
clustercopy = copycat(BHTree, cluster, convert_clu)
bridgesys = bridge(verbose=False)
bridgesys.add_system(galaxy, (clustercopy,), False)
bridgesys.add_system(cluster, (galaxy,), True)
t = 0. | nbody_system.time
if os.path.exists("cluster.hdf"):
os.remove("cluster.hdf")
storage = store.StoreHDF("cluster.hdf")
bridgesys.synchronize_model()
Ep0 = bridgesys.potential_energy
Ek0 = bridgesys.kinetic_energy
Esp0 = cluster.kinetic_energy
Esk0 = cluster.potential_energy
tc = cluster.model_time
tg = galaxy.model_time
print(convert_gal.to_nbody(tg))
print(0.)
# print Ep0,Ek0
# print Esp0,Esk0
for x in cluster.get_center_of_mass_position():
print(convert_gal.to_nbody(x), end=' ')
print()
part = bridgesys.particles.copy()
part.savepoint(tg)
storage.store(part.previous_state())
while(t < total_sim_time):
t = t+dt_diag
bridgesys.evolve_model(convert_gal.to_si(t),
timestep=convert_gal.to_si(sim_step))
bridgesys.synchronize_model()
Ep = bridgesys.potential_energy
Ek = bridgesys.kinetic_energy
Esp = cluster.kinetic_energy
Esk = cluster.potential_energy
tc = cluster.model_time
tg = galaxy.model_time
print(convert_gal.to_nbody(tg))
print((Ep+Ek-Ep0-Ek0)/(Ep0+Ek0))
# print (Esp+Esk-Esp0-Esk0)/(Esp0+Esk0)
for x in cluster.get_center_of_mass_position():
print(convert_gal.to_nbody(x), end=' ')
print()
part = bridgesys.particles.copy()
part.savepoint(tg)
storage.store(part.previous_state())
# Galaxy model with 1.6x10^10 MSun within 1 kpc, and power law scaling with index 1.2
galaxy_gravity = GalacticPotential(1. | al.units.kpc, 1.6E10 | al.units.MSun,
1.2)
# Place cluster in galaxy
bodies.x += RSun
bodies.vy += galaxy_gravity.circular_velocity(RSun)
cluster_gravity = al.ph4(converter)
cluster_gravity.particles.add_particles(bodies)
# Bridge couples a number of gravitational codes to another code. In this case,
# the cluster evolves under its own gravity and under that of the galaxy.
# The galaxy is represented by just a smooth potential, and its forces are updated
# every timestep dt.
bridge_gravity = bridge.bridge()
bridge_gravity.add_system(
cluster_gravity,
(galaxy_gravity,
)) # The codes in the bracket (1 in this case) influence the first code
# Plot initial conditions
plot_cluster(bridge_gravity.particles.x.value_in(al.units.kpc),
bridge_gravity.particles.y.value_in(al.units.kpc),
num=1)
bridge_gravity.evolve_model(t_end, timestep=dt)
# Plot outcome
plot_cluster(bridge_gravity.particles.x.value_in(al.units.kpc),
bridge_gravity.particles.y.value_in(al.units.kpc),
def validate_bridge():
convert_clu = nbody_system.nbody_to_si(
1.e5 | units.MSun, 1.0 | units.parsec)
convert_gal = nbody_system.nbody_to_si(
1.e7 | units.MSun, 10. | units.parsec)
def convert_gal_to_clu(x): return convert_clu.to_nbody(
convert_gal.to_si(x))
def convert_clu_to_gal(x): return convert_gal.to_nbody(
convert_clu.to_si(x))
total_sim_time = convert_clu_to_gal(200 | nbody_system.time)
total_sim_time = 200 | nbody_system.time
sim_step = 1./128 | nbody_system.time
dt_diag = 1./64 | nbody_system.time
eps_clu = convert_gal_to_clu(2.e-4 | nbody_system.length)
eps_gal = 6.25e-3 | nbody_system.length
cluster = sys_from_king(PhiGRAPE, 1000, 7, convert_clu,
eps_clu, usegl=False, mode="gpu")
galaxy = sys_from_king(Fi, 10000, 9, convert_gal,
eps_gal, sim_step, usegl=False)
shift_sys(
cluster,
convert_clu.to_si(
convert_gal_to_clu(
2.5 | nbody_system.length
)
),
0 | units.m,
0 | units.m,
0 | units.m/units.s,
convert_clu.to_si(
convert_gal_to_clu(0.65 | nbody_system.speed)
),
0 | units.m/units.s)
if hasattr(cluster, "start_viewer"):
cluster.start_viewer()
if hasattr(galaxy, "viewer"):
galaxy.viewer()
clustercopy = copycat(BHTree, cluster, convert_clu)
bridgesys = bridge(verbose=False)
bridgesys.add_system(galaxy, (clustercopy,), False)
bridgesys.add_system(cluster, (galaxy,), True)
t = 0. | nbody_system.time
if os.path.exists("cluster.hdf"):
os.remove("cluster.hdf")
storage = store.StoreHDF("cluster.hdf")
bridgesys.synchronize_model()
Ep0 = bridgesys.potential_energy
Ek0 = bridgesys.kinetic_energy
Esp0 = cluster.kinetic_energy
Esk0 = cluster.potential_energy
tc = cluster.model_time
tg = galaxy.model_time
print convert_gal.to_nbody(tg)
print 0.
# print Ep0,Ek0
# print Esp0,Esk0
for x in cluster.get_center_of_mass_position():
print convert_gal.to_nbody(x),
print
part = bridgesys.particles.copy()
part.savepoint(tg)
storage.store(part.previous_state())
while(t < total_sim_time):
t = t+dt_diag
bridgesys.evolve_model(convert_gal.to_si(t),
timestep=convert_gal.to_si(sim_step))
bridgesys.synchronize_model()
Ep = bridgesys.potential_energy
Ek = bridgesys.kinetic_energy
Esp = cluster.kinetic_energy
Esk = cluster.potential_energy
tc = cluster.model_time
tg = galaxy.model_time
print convert_gal.to_nbody(tg)
print (Ep+Ek-Ep0-Ek0)/(Ep0+Ek0)
# print (Esp+Esk-Esp0-Esk0)/(Esp0+Esk0)
for x in cluster.get_center_of_mass_position():
print convert_gal.to_nbody(x),
print
part = bridgesys.particles.copy()
part.savepoint(tg)
storage.store(part.previous_state())
# create the external potential of the Galaxy
galaxy = Agama(converter, type="Dehnen", gamma=1.8, \
rscale=1000.| units.parsec, mass=1.6e10 | units.MSun, channel_type='sockets')
# shift the cluster to an orbit around Galactic center
acc, _, _ = galaxy.get_gravity_at_point(0 | units.kpc, Rinit,
0 | units.kpc, 0 | units.kpc)
vcirc = (-acc * Rinit)**0.5
print("Vcirc=%f km/s" % vcirc.value_in(units.kms))
particles.x += Rinit
particles.vy += vcirc
cluster.particles.add_particles(particles)
# set up bridge; cluster is evolved under influence of the galaxy
sys = bridge(verbose=False)
sys.add_system(cluster, (galaxy, ), False)
# evolve and make plots
times = units.Myr([0., 0.2, 0.4, 0.6, 0.8, 1.0, 1.2, 1.4])
f = pyplot.figure(figsize=(16, 8))
for i, t in enumerate(times):
sys.evolve_model(t, timestep=timestep)
print("Evolved the system to time %f" % t)
x = sys.particles.x.value_in(units.parsec)
y = sys.particles.y.value_in(units.parsec)
subplot = f.add_subplot(2, 4, i + 1)
subplot.plot(x, y, 'r .')
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
