def gas_particles(self):
array = []
for x in self.codes:
if hasattr(x, "gas_particles"):
array.append(x.gas_particles)
if len(array) == 0:
raise AttributeError
elif len(array) == 1:
return array[0]
return datamodel.ParticlesSuperset(array)
def particles(self):
arr=[]
for x in self.systems:
if hasattr(x,"particles"):
arr.append(x.particles)
particles=datamodel.ParticlesSuperset(arr)
return TransformedParticles(particles,
["x","y","vx","vy"],
self.transform_rotating_to_inertial,
["x","y","vx","vy"],
self.transform_inertial_to_rotating,
)
def test7(self):
print("Testing HDF5 io with a ParticlesSuperset")
if os.path.exists("test_unit.hdf5"):
os.remove("test_unit.hdf5")
set1 = datamodel.Particles(2)
set2 = datamodel.Particles(2)
superset = datamodel.ParticlesSuperset([set1, set2])
superset.mass = [1.0, 2.0, 3.0, 4.0] | units.kg
superset.radius = [3.0, 4.0, 5.0, 6.0] | units.m
superset.position = [[1,2,3], [3,5,6], [3,2,1], [-3,-5,-6]] | units.m
superset.velocity = [[1,2,3], [3,5,6], [3,2,1], [-3,-5,-6]] | units.m / units.s
io.write_set_to_file(superset, "test_unit.hdf5","hdf5")
y = io.read_set_from_file("test_unit.hdf5","hdf5")
self.assertAlmostEqual(superset.mass, y.mass, 8)
self.assertAlmostEqual(superset.radius, y.radius, 8)
self.assertAlmostEqual(superset.position, y.position,8)
self.assertAlmostEqual(superset.velocity, y.velocity,8)
os.remove("test_unit.hdf5")
def gas_particles(self):
arr=[]
for x in self.systems:
if hasattr(x,"gas_particles"):
arr.append(x.gas_particles)
return datamodel.ParticlesSuperset(arr)
def Run(N_CORES, DM_halo_r_limit, star_disk_R_limit, star_disk_z_limit,
star_bulge_r_limit):
start_time = time.time()
Print("Generating dark matter halo...", start_time)
DM_halo_particles = gen_particles_Einasto(N=10**2,
mass=2 * 10**12,
N_CORES=N_CORES,
r_limit=DM_halo_r_limit)
Print("Generating disk stars...", start_time)
star_disk_particles = gen_particles_exp_sech(N=10**2,
mass=4 * 10**10,
N_CORES=N_CORES,
R_limit=star_disk_R_limit,
z_limit=star_disk_z_limit)
Print("Generating bulge stars...", start_time)
star_bulge_particles = gen_particles_Jaffe(N=10**1,
mass=2 * 10**10,
N_CORES=N_CORES,
r_limit=star_bulge_r_limit)
Print("Generating disc gas...", start_time)
gas_disk_particles = gen_particles_exp_sech(N=10**2,
mass=1 * 10**10,
N_CORES=N_CORES,
R_limit=star_disk_R_limit,
z_limit=star_disk_z_limit)
Print("Generating halo gas...", start_time)
gas_halo_particles = gen_particles_Einasto(N=10**2,
mass=1 * 10**10,
N_CORES=N_CORES,
r_limit=star_disk_R_limit * 2)
for p in datamodel.ParticlesSuperset(
[gas_disk_particles.as_set(),
gas_halo_particles.as_set()]):
p.u = 1 | units.km**2 / units.s**2
Print("Assigning velocities to non-halo particles...", start_time)
assign_star_velocities(
datamodel.ParticlesSuperset([
star_disk_particles, star_bulge_particles, gas_disk_particles,
gas_halo_particles
]),
datamodel.ParticlesSuperset([
star_disk_particles, star_bulge_particles, gas_disk_particles,
gas_halo_particles, DM_halo_particles
]), 2 * math.sqrt(star_disk_R_limit**2 + star_disk_z_limit**2))
Print("Assigning velocities to halo particles...", start_time)
assign_halo_velocities(
datamodel.ParticlesSuperset([DM_halo_particles, gas_halo_particles]))
Print("Initializing Gadget2 code...", start_time)
SE = Gadget2(number_of_workers=N_CORES - 1)
Gadget_config(SE)
Print("Adding particles to the code...", start_time)
SE.dm_particles.add_particles(DM_halo_particles)
SE.dm_particles.add_particles(star_disk_particles)
SE.dm_particles.add_particles(star_bulge_particles)
SE.gas_particles.add_particles(gas_disk_particles)
SE.gas_particles.add_particles(gas_halo_particles)
#io.write_set_to_file(SE.particles, 'output.dat', 'gadget')
Print("Starting the simulation...", start_time)
for t in np.arange(0, 1000, 1):
SE.evolve_model(t | units.Myr)
Plots(SE.dm_particles, SE.gas_particles, t)
Print("Timestep " + str(t + 1) + ", screenshots saved!", start_time)
