def create_giant_molecular_cloud(Ngas, Mgas, Rgas):
converter = nbody_system.nbody_to_si(Mgas, Rgas)
particles = molecular_cloud(targetN=Ngas, convert_nbody=converter).result
particles.u = 1. | units.ms**2
particles.velocity *= 0.6
particles.move_to_center()
return particles, converter
def create_giant_molecular_cloud(Ngas, Mgas, Rgas):
converter = nbody_system.nbody_to_si(Mgas, Rgas)
particles = molecular_cloud(targetN=Ngas, convert_nbody=converter).result
particles.u = 1. | units.ms**2
particles.velocity *= 0.6
particles.move_to_center()
return particles, converter
def run_molecular_cloud(N=100, Mcloud=100. | units.MSun, Rcloud=1. | units.parsec):
conv = nbody_system.nbody_to_si(Mcloud,Rcloud)
rho_cloud = 3.*Mcloud/(4.*numpy.pi*Rcloud**3)
print rho_cloud
tff = 0.5427/numpy.sqrt(constants.G*rho_cloud)
print "t_ff=", tff.value_in(units.Myr), 'Myr'
dt = 0.05 | units.Myr
tend=1.0 | units.Myr
parts=molecular_cloud(targetN=N,convert_nbody=conv,
base_grid=body_centered_grid_unit_cube, seed=100).result
sph = Hydro(Fi, parts)
#sph = Hydro(Gadget2, parts)
eps = 0.1 | units.parsec
expected_dt = 0.2*numpy.pi*numpy.power(eps, 1.5)/numpy.sqrt(constants.G*Mcloud/N)
print "dt_exp=", expected_dt.value_in(units.Myr)
print "dt=", dt
print "eps=", sph.parameters.gas_epsilon.in_(units.parsec)
i=0
L=6
E0 = 0.0
ttarget = 0.0 | units.Myr
plot_hydro(ttarget, sph, i, L)
while ttarget < tend:
ttarget=float(i)*dt
print "Evolve to time=", ttarget.in_(units.Myr)
# print "N=", len(sph.gas_particles), len(sph.dm_particles)
# print "Masses of dm particles:", sph.dm_particles.mass.in_(units.MSun)
sph.evolve_model(ttarget)
E = sph.gas_particles.kinetic_energy()+sph.gas_particles.potential_energy() + sph.gas_particles.thermal_energy()
E_th = sph.gas_particles.thermal_energy()
if i==0:
E0 = E
Eerr = (E-E0)/E0
print 'energy=', E, 'energy_error=', Eerr, 'e_th=', E_th
print "maximal_density:",parts.rho.max().in_(units.MSun/units.parsec**3)
"""
filename = 'm400k_r10pc_e01_'+ str(i).zfill(2) + '.dat'
print filename
parts_sorted = parts.sorted_by_attribute('rho')
write_output(filename, parts_sorted, conv)
"""
plot_hydro(ttarget, sph, i, L)
i=i+1
sph.stop()
return parts
def cloud_init(N=100, M=100. | units.MSun, R=1. | units.parsec):
'''Initialises the cloud'''
converter = nbody_system.nbody_to_si(M, R)
cloud = molecular_cloud(targetN=N, convert_nbody=converter,\
base_grid=body_centered_grid_unit_cube,\
).result
#cloud = new_plummer_model(N, convert_nbody=converter)
return cloud, converter
def test3(self):
mc=molecular_cloud(targetN=1000,ekep_ratio=2.,base_grid=sobol_unit_cube).result
self.assertEqual(len(mc),995)
ek=mc.kinetic_energy()
ep=mc.potential_energy(G=nbody_system.G)
eth=mc.thermal_energy()
self.assertAlmostRelativeEqual(eth/ep, -0.01,2)
self.assertAlmostRelativeEqual(ek/ep, -2.,2)
def test1(self):
mc = molecular_cloud(targetN=1000, base_grid=sobol_unit_cube).result
self.assertEqual(len(mc), 995)
ek = mc.kinetic_energy()
ep = mc.potential_energy(G=nbody_system.G)
eth = mc.thermal_energy()
self.assertAlmostRelativeEqual(eth / ep, -0.01, 2)
self.assertAlmostRelativeEqual(ek / ep, -1., 2)
def main():
"Test class with a molecular cloud"
from amuse.ext.molecular_cloud import molecular_cloud
converter = nbody_system.nbody_to_si(
100000 | units.MSun,
10.0 | units.parsec,
)
numpy.random.seed(11)
temperature = 30 | units.K
from plotting_class import temperature_to_u
u = temperature_to_u(temperature)
gas = molecular_cloud(targetN=200000, convert_nbody=converter).result
gas.u = u
print("We have %i gas particles" % (len(gas)))
# gastwo = molecular_cloud(targetN=100000, convert_nbody=converter).result
# gastwo.u = u
# gastwo.x += 12 | units.parsec
# gastwo.y += 3 | units.parsec
# gastwo.z -= 1 | units.parsec
# gastwo.vx -= ((5 | units.parsec) / (1 | units.Myr))
# gas.add_particles(gastwo)
print("Number of gas particles: %i" % (len(gas)))
model = GasCode(converter=converter, )
model.gas_particles.add_particles(gas)
print(model.parameters)
# print(model.gas_code.gas_particles[0])
# exit()
timestep = 0.01 | units.Myr # model.gas_code.parameters.timestep
times = [] | units.Myr
# kinetic_energies = [] | units.J
# potential_energies = [] | units.J
# thermal_energies = [] | units.J
time = 0 | units.Myr
step = 0
while time < 0.3 | units.Myr:
time += timestep
print("Starting at %s, evolving to %s" % (
model.model_time.in_(units.Myr),
time.in_(units.Myr),
))
model.evolve_model(time)
print("Evolved to %s" % model.model_time.in_(units.Myr))
print("Maximum density / stopping density = %s" %
(model.gas_particles.density.max() /
model.parameters.stopping_condition_maximum_density, ))
if not model.sink_particles.is_empty():
print("Largest sink mass: %s" %
(model.sink_particles.mass.max().in_(units.MSun)))
times.append(time)
step += 1
def create_giant_molecular_clouds(Ngas, Mgas, Rgas, Nclouds):
converter = nbody_system.nbody_to_si(Mgas, Rgas)
clouds = []
for i in xrange(Nclouds):
particles = molecular_cloud(targetN=Ngas, convert_nbody=converter).result
particles.u = 1. | units.ms**2
particles.velocity *= 0.6
particles.move_to_center()
clouds.append(particles)
return clouds, converter
def GMC_model(N, M, R):
converter = nbody_system.nbody_to_si(M, R)
parts=molecular_cloud(targetN=N, convert_nbody=converter, seed=100).result
sph=Fi(converter)
sph.gas_particles.add_particle(parts)
sph.evolve_model(1|units.day)
ch = sph.gas_particles.new_channel_to(parts)
ch.copy()
sph.stop()
return parts
def GMC_model(N, M, R):
converter = nbody_system.nbody_to_si(M, R)
sph_particles = molecular_cloud(targetN=N, convert_nbody=converter).result
sph = Fi(converter)
sph.gas_particles.add_particle(sph_particles)
sph.evolve_model(1 | units.day)
ch = sph.gas_particles.new_channel_to(sph_particles)
ch.copy()
sph.stop()
return sph_particles
def create_giant_molecular_clouds(Ngas, Mgas, Rgas, Nclouds):
converter = nbody_system.nbody_to_si(Mgas, Rgas)
clouds = []
for i in xrange(Nclouds):
particles = molecular_cloud(targetN=Ngas,
convert_nbody=converter).result
particles.u = 1. | units.ms**2
particles.velocity *= 0.6
particles.move_to_center()
clouds.append(particles)
return clouds, converter
def cloud_init(Ngas, Mgas, Rgas, use_plummer=True, seed=1):
'''Initialises the cloud'''
np.random.seed(seed)
converter = nbody_system.nbody_to_si(Mgas, Rgas)
if use_plummer == True:
cloud = new_plummer_gas_model(Ngas, convert_nbody=converter)
else:
cloud = molecular_cloud(targetN=Ngas, convert_nbody=converter,\
base_grid=body_centered_grid_unit_cube).result
return cloud, converter
def create_molecular_cloud(N, Mcloud, Rcloud, t_end):
converter = nbody_system.nbody_to_si(Mcloud,Rcloud)
parts=molecular_cloud(targetN=N,convert_nbody=converter,
base_grid=body_centered_grid_unit_cube, seed=100).result
# parts = new_plummer_gas_model(N, convert_nbody=converter)
sph=Fi(converter)
sph.gas_particles.add_particle(parts)
sph.evolve_model(t_end)
ch = sph.gas_particles.new_channel_to(parts)
ch.copy()
sph.stop()
return parts
def create_molecular_cloud(N, Mcloud, Rcloud, t_end):
converter = nbody_system.nbody_to_si(Mcloud,Rcloud)
parts=molecular_cloud(targetN=N,convert_nbody=converter,
base_grid=body_centered_grid_unit_cube, seed=100).result
# parts = new_plummer_gas_model(N, convert_nbody=converter)
sph=Fi(converter)
sph.gas_particles.add_particle(parts)
sph.evolve_model(t_end)
ch = sph.gas_particles.new_channel_to(parts)
ch.copy()
sph.stop()
return parts
def run_molecular_cloud(N=100, Mcloud=100. | units.MSun, Rcloud=1. | units.parsec):
conv = nbody_system.nbody_to_si(Mcloud,Rcloud)
gas=molecular_cloud(targetN=N,convert_nbody=conv,
base_grid=body_centered_grid_unit_cube, seed=100).result
gas.name = "gas"
hydro = Hydro(Fi, gas)
rho_cloud = 3.*Mcloud/(4.*numpy.pi*Rcloud**3)
print rho_cloud
tff = 0.5427/numpy.sqrt(constants.G*rho_cloud)
print "Freefall timescale=", tff.in_(units.Myr)
dt = 0.1*tff
tend=4.0*tff
i=0
L=6
E0 = 0.0
time = 0.0 | units.Myr
while time < tend:
time += dt
print "Evolve to time=", time.in_(units.Myr)
# print "N=", len(sph.gas_particles), len(sph.dm_particles)
# print "Masses of dm particles:", sph.dm_particles.mass.in_(units.MSun)
hydro.evolve_model(time)
E = hydro.gas_particles.kinetic_energy()+hydro.gas_particles.potential_energy() + hydro.gas_particles.thermal_energy()
E_th = hydro.gas_particles.thermal_energy()
if i==0:
E0 = E
Eerr = (E-E0)/E0
print 'energy=', E, 'energy_error=', Eerr, 'e_th=', E_th
print "maximal_density:",gas.rho.max().in_(units.MSun/units.parsec**3)
hydro.write_set_to_file(i)
i=i+1
hydro.stop()
return gas
def new_molecular_cloud(
nf=32,
power=-3.,
targetN=10000,
ethep_ratio=0.01,
convert_nbody=None,
ekep_ratio=1.,
seed=None,
base_grid=None,
):
return molecular_cloud(
nf=nf,
power=power,
targetN=targetN,
ethep_ratio=ethep_ratio,
convert_nbody=convert_nbody,
ekep_ratio=ekep_ratio,
seed=seed,
base_grid=base_grid,
).result
def run_mc(N=5000, Mcloud=10000. | units.MSun, Rcloud=1. | units.parsec):
timestep = 0.005 | units.Myr
end_time = 0.12 | units.Myr
conv = nbody_system.nbody_to_si(Mcloud, Rcloud)
parts = molecular_cloud(targetN=N, convert_nbody=conv,
ethep_ratio=0.05, ekep_ratio=0.5).result
rho_cloud = Mcloud/(4/3.*numpy.pi*Rcloud**3)
tff = 1/(4*numpy.pi*constants.G*rho_cloud)**0.5
parts.density = rho_cloud
update_chem(parts, parts)
print("Tcloud:", parts.temperature.max().in_(units.K))
print("cloud n_H:", parts.number_density.max().in_(units.cm**-3))
print("freefall time:", tff.in_(units.Myr))
sph = Fi(conv)
chem = Krome(redirection="none")
sph.parameters.self_gravity_flag = True
sph.parameters.use_hydro_flag = True
sph.parameters.isothermal_flag = True
sph.parameters.integrate_entropy_flag = False
sph.parameters.gamma = 1
sph.parameters.verbosity = 0
sph.parameters.timestep = timestep/2
sph.gas_particles.add_particles(parts)
chem.particles.add_particles(parts)
tnow = sph.model_time
f = pyplot.figure()
pyplot.ion()
pyplot.show()
i = 0
while i < (end_time/timestep+0.5):
evolve_sph_with_chemistry(sph, chem, i*timestep)
tnow = sph.model_time
print("done with step:", i, tnow.in_(units.Myr))
i += 1
n = (sph.particles.density/meanmwt).value_in(units.cm**-3)
fh2 = chem.particles.abundances[:, chem.species["H2"]]
co = chem.particles.abundances[:, chem.species["CO"]]
f.clear()
pyplot.loglog(n, fh2, 'r.')
pyplot.loglog(n, co, 'g.')
pyplot.xlim(1.e3, 1.e6)
pyplot.ylim(1.e-6, 1)
pyplot.xlabel("density (cm**-3)")
pyplot.ylabel("H_2,CO abundance")
pyplot.draw()
print("done. press key to exit")
raw_input()
def run_cloud(x):
cloud = molecular_cloud(32, -4., x, base_grid=regular_grid_unit_cube)
mass, x, y, z, vx, vy, vz, u = cloud.new_model()
smooth = numpy.zeros_like(mass)
nb = interface.FiInterface(redirection="none")
nb.initialize_code()
nb.set_stepout(99999)
nb.set_steplog(99999)
nb.set_use_hydro(1)
nb.set_radiate(0)
nb.set_dtime(0.05)
nb.set_gdgop(1)
nb.set_uentropy(0)
nb.set_isotherm(1)
nb.set_gamma(1.0)
nb.set_verbosity(0)
nb.set_unitl_in_kpc(0.01)
nb.set_unitm_in_msun(10000.)
ids, error = nb.new_sph_particle(mass, x, y, z, vx, vy, vz, u, smooth)
if filter(lambda x: x != 0, error) != []: raise Exception
nb.commit_particles()
if hasattr(nb, "viewer"):
nb.viewer()
dt = 0.05
tnow = 0.
nb.synchronize_model()
time, Ek, Ep, Eth = [], [], [], []
time.append(tnow)
e, ret = nb.get_kinetic_energy()
Ek.append(e)
e, ret = nb.get_potential_energy()
Ep.append(e)
e, ret = nb.get_thermal_energy()
Eth.append(e)
while tnow < .8:
tnow = tnow + dt
nb.evolve_model(tnow)
nb.synchronize_model()
tnow, err = nb.get_time()
time.append(tnow)
e, ret = nb.get_kinetic_energy()
Ek.append(e)
e, ret = nb.get_potential_energy()
Ep.append(e)
e, ret = nb.get_thermal_energy()
Eth.append(e)
nb.stop()
time = numpy.array(time)
Ek = numpy.array(Ek)
Ep = numpy.array(Ep)
Eth = numpy.array(Eth)
energy_plot(time, Ek, Ep, Eth)
def main():
numpy.random.seed(42)
evo_headstart = 0.0 | units.Myr
dt_base = 0.001 | units.Myr
dt = dt_base
time = 0 | units.Myr
time_end = 8 | units.Myr
Tmin = 22 | units.K
gas_density = 5e3 | units.amu * units.cm**-3
increase_vol = 2
Ngas = increase_vol**3 * 10000
Mgas = increase_vol**3 * 1000 | units.MSun # Mgas = Ngas | units.MSun
volume = Mgas / gas_density # 4/3 * pi * r**3
radius = (volume / (pi * 4/3))**(1/3)
radius = increase_vol * radius # 15 | units.parsec
gasconverter = nbody_system.nbody_to_si(Mgas, radius)
# gasconverter = nbody_system.nbody_to_si(1 | units.pc, 1 | units.MSun)
# gasconverter = nbody_system.nbody_to_si(1e10 | units.cm, 1e10 | units.g)
# NOTE: make stars first - so that it remains the same random
# initialisation even when we change the number of gas particles
if len(sys.argv) > 1:
gas = read_set_from_file(sys.argv[1], "amuse")
stars = read_set_from_file(sys.argv[2], "amuse")
stars.position = stars.position * 3
else:
# stars = new_star_cluster(
# stellar_mass=1000 | units.MSun, effective_radius=3 | units.parsec
# )
# stars.velocity = stars.velocity * 2.0
from amuse.datamodel import Particles
Nstars = 100
stars = Particles(Nstars)
stars.position = [0, 0, 0] | units.pc
stars.velocity = [0, 0, 0] | units.kms
stars.mass = new_kroupa_mass_distribution(Nstars, mass_min=1 | units.MSun).reshape(Nstars)
# 25 | units.MSun
gas = molecular_cloud(targetN=Ngas, convert_nbody=gasconverter).result
# gas.velocity = gas.velocity * 0.5
gas.u = temperature_to_u(100 | units.K)
# gas.x = gas.x
# gas.y = gas.y
# gas.z = gas.z
# gas.h_smooth = (gas.mass / gas_density / (4/3) / pi)**(1/3)
# print(gas.h_smooth.mean())
# gas = read_set_from_file("gas_initial.hdf5", "amuse")
# gas.density = gas_density
# print(gas.h_smooth.mean())
# exit()
u_now = gas.u
#print(gasconverter.to_nbody(gas[0].u))
#print(constants.kB.value_in(units.erg * units.K**-1))
#print((constants.kB * 6.02215076e23).value_in(units.erg * units.K**-1))
#print(gasconverter.to_nbody(temperature_to_u(10 | units.K)))
#tempiso = 2.d0/3.d0*ui/(Rg/gmwvar/uergg)
# print(nbody_system.length**2 / nbody_system.time**2)
# print(gasconverter.to_si(1 | nbody_system.length**2 / nbody_system.time**2).value_in(units.kms**2))
# print(gasconverter.to_nbody(temperature_to_u(Tmin)))
# Rg = (constants.kB * 6.02214076e23).value_in(units.erg * units.K**-1)
# gmwvar = 1.2727272727
# uergg = nbody_system.length**2 * nbody_system.time**-2
# uergg = 6.6720409999999996E-8
# print(Rg)
# print(
# 2.0/3.0*gasconverter.to_nbody(temperature_to_u(Tmin))/(Rg/gmwvar/uergg)
# )
# #tempiso, ui, Rg, gmwvar, uergg, udist, utime 1.7552962911187030E-018 2.5778500859241771E-003 83140000.000000000 1.2727272727272725 6.6720409999999996E-008 1.0000000000000000 3871.4231866737564
# u = 3./2. * Tmin.value_in(units.K) * (Rg/gmwvar/uergg)
# print(u)
# print(
# 2.0/3.0*u/(Rg/gmwvar/uergg)
# )
# print(u, Rg, gmwvar, uergg)
# print(temperature_to_u(10 | units.K).value_in(units.kms**2))
u = temperature_to_u(20 | units.K)
#print(gasconverter.to_nbody(u))
#print(u_to_temperature(u).value_in(units.K))
# exit()
# gas.u = u | units.kms**2
# exit()
# print(gasconverter.to_nbody(gas.u.mean()))
# print(gasconverter.to_si(gas.u.mean()).value_in(units.kms**2))
# exit()
gas.du_dt = (u_now - u_now) / dt # zero, but in the correct units
# stars = read_set_from_file("stars.amuse", "amuse")
# write_set_to_file(stars, 'stars.amuse', 'amuse', append_to_file=False)
# stars.velocity *= 3
# stars.vx += 0 | units.kms
# stars.vy += 0 | units.kms
M = stars.total_mass() + Mgas
R = stars.position.lengths().mean()
converter = nbody_system.nbody_to_si(M, R)
# exit()
# gas = new_plummer_gas_model(Ngas, gasconverter)
# gas = molecular_cloud(targetN=Ngas, convert_nbody=gasconverter).result
# gas.u = temperature_to_u(Tmin)
# gas = read_set_from_file("gas.amuse", "amuse")
# print(stars.mass == stars.mass.max())
print(len(stars.mass))
print(len(stars.mass == stars.mass.max()))
print(stars[0])
print(stars[stars.mass == stars.mass.max()])
mms = stars[stars.mass == stars.mass.max()]
print("Most massive star: %s" % mms.mass)
print("Gas particle mass: %s" % gas[0].mass)
evo = SeBa()
# sph = Fi(converter, mode="openmp")
phantomconverter = nbody_system.nbody_to_si(
default_settings.gas_rscale,
default_settings.gas_mscale,
)
sph = Phantom(phantomconverter, redirection="none")
sph.parameters.ieos = 2
sph.parameters.icooling = 1
sph.parameters.alpha = 0.1
sph.parameters.gamma = 5/3
sph.parameters.rho_crit = 1e17 | units.amu * units.cm**-3
sph.parameters.h_soft_sinkgas = 0.1 | units.parsec
sph.parameters.h_soft_sinksink = 0.1 | units.parsec
sph.parameters.h_acc = 0.1 | units.parsec
# print(sph.parameters)
stars_in_evo = evo.particles.add_particles(stars)
channel_stars_evo_from_code = stars_in_evo.new_channel_to(
stars,
attributes=[
"age", "radius", "mass", "luminosity", "temperature",
"stellar_type",
],
)
channel_stars_evo_from_code.copy()
# try:
# sph.parameters.timestep = dt
# except:
# print("SPH code doesn't support setting the timestep")
sph.parameters.stopping_condition_maximum_density = \
5e-16 | units.g * units.cm**-3
# sph.parameters.beta = 1.
# sph.parameters.C_cour = sph.parameters.C_cour / 4
# sph.parameters.C_force = sph.parameters.C_force / 4
print(sph.parameters)
stars_in_sph = stars.copy() # sph.sink_particles.add_particles(stars)
# stars_in_sph = sph.sink_particles.add_particles(stars)
channel_stars_grav_to_code = stars.new_channel_to(
# sph.sink_particles,
# sph.dm_particles,
stars_in_sph,
attributes=["mass"]
)
channel_stars_grav_from_code = stars_in_sph.new_channel_to(
stars,
attributes=["x", "y", "z", "vx", "vy", "vz"],
)
# We don't want to accrete gas onto the stars/sinks
stars_in_sph.radius = 0 | units.RSun
# stars_in_sph = sph.dm_particles.add_particles(stars)
# try:
# sph.parameters.isothermal_flag = True
# sph.parameters.integrate_entropy_flag = False
# sph.parameters.gamma = 1
# except:
# print("SPH code doesn't support setting isothermal flag")
gas_in_code = sph.gas_particles.add_particles(gas)
# print(gasconverter.to_nbody(gas_in_code[0].u).value_in(nbody_system.specific_energy))
# ui = temperature_to_u(10 | units.K)
# Rg = constants.kB * 6.02214179e+23
# gmwvar = (1.4/1.1) | units.g
# uergg = 1.# | nbody_system.specific_energy
# print("gmwvar = %s"%gasconverter.to_si(gmwvar))
# print("Rg = %s"% gasconverter.to_si(Rg))
# print("ui = %s"% gasconverter.to_si(ui))
# #print("uergg = %s"% gasconverter.to_nbody(uergg))
# print("uergg = %s" % gasconverter.to_si(1 | nbody_system.specific_energy).in_(units.cm**2 * units.s**-2))
# print("****** %s" % ((2.0/3.0)*ui/(Rg/gmwvar/uergg)) + "*****")
# print(gasconverter.to_nbody(Rg))
# print((ui).in_(units.cm**2*units.s**-2))
# #exit()
# sph.evolve_model(1 | units.day)
# write_set_to_file(sph.gas_particles, "gas_initial.hdf5", "amuse")
# exit()
channel_gas_to_code = gas.new_channel_to(
gas_in_code,
attributes=[
"x", "y", "z", "vx", "vy", "vz", "u",
]
)
# mass is never updated, and if sph is in isothermal mode u is not reliable
channel_gas_from_code = gas_in_code.new_channel_to(
gas,
attributes=[
"x", "y", "z", "vx", "vy", "vz", "density", "pressure", "rho",
"u", "h_smooth",
],
)
channel_gas_from_code.copy() # Initialise values for density etc
sph_particle_mass = gas[0].mass # 0.1 | units.MSun
r_max = 0.1 | units.parsec
wind = stellar_wind.new_stellar_wind(
sph_particle_mass,
mode="heating",
r_max=r_max,
derive_from_evolution=True,
tag_gas_source=True,
# target_gas=gas,
# timestep=dt,
)
stars_in_wind = wind.particles.add_particles(stars)
channel_stars_wind_to_code = stars.new_channel_to(
stars_in_wind,
attributes=[
"x", "y", "z", "vx", "vy", "vz", "age", "radius", "mass",
"luminosity", "temperature", "stellar_type",
],
)
channel_stars_wind_to_code.copy()
# reference_mu = 2.2 | units.amu
gasvolume = (4./3.) * numpy.pi * (
gas.position - gas.center_of_mass()
).lengths().mean()**3
rho0 = gas.total_mass() / gasvolume
print(rho0.value_in(units.g * units.cm**-3))
# exit()
# cooling_flag = "thermal_model"
# cooling = Cooling(
cooling = SimplifiedThermalModelEvolver(
# gas_in_code,
gas,
Tmin=Tmin,
# T0=30 | units.K,
# n0=rho0/reference_mu
)
cooling.model_time = sph.model_time
# cooling_to_code = cooling.particles.new_channel_to(gas
start_mass = (
stars.mass.sum()
+ (gas.mass.sum() if not gas.is_empty() else 0 | units.MSun)
)
step = 0
plotnr = 0
com = stars_in_sph.center_of_mass()
plot_hydro_and_stars(
time,
sph,
stars=stars,
sinks=None,
L=20,
# N=100,
filename="phantom-coolthermalwindtestplot-%04i.png" % step,
title="time = %06.2f %s" % (time.value_in(units.Myr), units.Myr),
gasproperties=["density", "temperature"],
# colorbar=True,
starscale=1,
offset_x=com[0].value_in(units.parsec),
offset_y=com[1].value_in(units.parsec),
thickness=5 | units.parsec,
)
dt = dt_base
sph.parameters.time_step = dt
delta_t = phantomconverter.to_si(2**(-16) | nbody_system.time)
print("delta_t: %s" % delta_t.in_(units.day))
# small_step = True
small_step = False
plot_every = 100
subplot_factor = 10
subplot_enabled = False
subplot = 0
while time < time_end:
time += dt
print("Gas mean u: %s" % (gas.u.mean().in_(units.erg/units.MSun)))
print("Evolving to t=%s (%s)" % (time, gasconverter.to_nbody(time)))
step += 1
evo.evolve_model(evo_headstart+time)
print(evo.particles.stellar_type.max())
channel_stars_evo_from_code.copy()
channel_stars_grav_to_code.copy()
if COOLING:
channel_gas_from_code.copy()
cooling.evolve_for(dt/2)
channel_gas_to_code.copy()
print(
"min/max temp in gas: %s %s" % (
u_to_temperature(gas_in_code.u.min()).in_(units.K),
u_to_temperature(gas_in_code.u.max()).in_(units.K),
)
)
if small_step:
# Take small steps until a full timestep is done.
# Each substep is 2* as long as the last until dt is reached
print("Doing small steps")
# print(u_to_temperature(sph.gas_particles[0].u))
# print(sph.gas_particles[0].u)
old_dt = dt_base
substeps = 2**8
dt = old_dt / substeps
dt_done = 0 * old_dt
sph.parameters.time_step = dt
print("adjusted dt to %s, base dt is %s" % (
dt.in_(units.Myr),
dt_base.in_(units.Myr),
)
)
sph.evolve_model(sph.model_time + dt)
dt_done += dt
while dt_done < old_dt:
sph.parameters.time_step = dt
print("adjusted dt to %s, base dt is %s" % (
dt.in_(units.Myr),
dt_base.in_(units.Myr),
)
)
sph.evolve_model(sph.model_time + dt)
dt_done += dt
dt = min(2*dt, old_dt-dt_done)
dt = max(dt, old_dt/substeps)
dt = dt_base
sph.parameters.time_step = dt
print(
"adjusted dt to %s" % sph.parameters.time_step.in_(units.Myr)
)
small_step = False
print("Finished small steps")
# print(u_to_temperature(sph.gas_particles[0].u))
# print(sph.gas_particles[0].u)
# exit()
else:
sph.evolve_model(time)
channel_gas_from_code.copy()
channel_stars_grav_from_code.copy()
u_previous = u_now
u_now = gas.u
gas.du_dt = (u_now - u_previous) / dt
channel_stars_wind_to_code.copy()
wind.evolve_model(time)
# channel_stars_wind_from_code.copy()
if COOLING:
channel_gas_from_code.copy()
cooling.evolve_for(dt/2)
channel_gas_to_code.copy()
if wind.has_new_wind_particles():
subplot_enabled = True
wind_p = wind.create_wind_particles()
# nearest = gas.find_closest_particle_to(wind_p.x, wind_p.y, wind_p.z)
# wind_p.h_smooth = nearest.h_smooth
wind_p.h_smooth = 100 | units.au
print("u: %s / T: %s" % (wind_p.u.mean(), u_to_temperature(wind_p.u.mean())))
# max_e = (1e44 | units.erg) / wind_p[0].mass
# max_e = 10 * gas.u.mean()
# max_e = (1.e48 | units.erg) / wind_p[0].mass
# wind_p[wind_p.u > max_e].u = max_e
# wind_p[wind_p.u > max_e].h_smooth = 0.1 | units.parsec
# print(wind_p.position)
print(
"time: %s, wind energy: %s"
% (time, (wind_p.u * wind_p.mass).sum())
)
print(
"wind temperature: %s"
% (u_to_temperature(wind_p.u))
)
print(
"gas particles: %i (total mass %s)"
% (len(wind_p), wind_p.total_mass())
)
# for windje in wind_p:
# # print(windje)
# source = stars[stars.key == windje.source][0]
# windje.position += source.position
# windje.velocity += source.velocity
# # print(source)
# # print(windje)
# # exit()
gas.add_particles(wind_p)
gas_in_code.add_particles(wind_p)
# for wp in wind_p:
# print(wp)
print("Wind particles added")
if True: # wind_p.u.max() > gas_in_code.u.max():
print("Setting dt to very short")
small_step = True # dt = 0.1 | units.yr
h_min = gas.h_smooth.min()
# delta_t = determine_short_timestep(sph, wind_p, h_min=h_min)
# print("delta_t is set to %s" % delta_t.in_(units.yr))
# else:
# small_step = True
print(
"time: %s sph: %s dM: %s" % (
time.in_(units.Myr),
sph.model_time.in_(units.Myr),
(
stars.total_mass()
+ (
gas.total_mass()
if not gas.is_empty()
else (0 | units.MSun)
)
- start_mass
)
)
)
# com = sph.sink_particles.center_of_mass()
# com = sph.dm_particles.center_of_mass()
com = stars.center_of_mass()
print("STEP: %i step%%plot_every: %i" % (step, step % plot_every))
if step % plot_every == 0:
plotnr = plotnr + 1
plot_hydro_and_stars(
time,
sph,
# stars=sph.sink_particles,
# stars=sph.dm_particles,
stars=stars,
sinks=None,
L=20,
# N=100,
# image_size_scale=10,
filename="phantom-coolthermalwindtestplot-%04i.png" % plotnr, # int(step/plot_every),
title="time = %06.2f %s" % (time.value_in(units.Myr), units.Myr),
gasproperties=["density", "temperature"],
# colorbar=True,
starscale=1,
offset_x=com[0].value_in(units.parsec),
offset_y=com[1].value_in(units.parsec),
thickness=5 | units.parsec,
)
# write_set_to_file(gas, "gas.amuse", "amuse", append_to_file=False)
# write_set_to_file(stars, "stars.amuse", "amuse", append_to_file=False)
elif (
subplot_enabled
and ((step % (plot_every/subplot_factor)) == 0)
):
plotnr = plotnr + 1
subplot += 1
plot_hydro_and_stars(
time,
sph,
# stars=sph.sink_particles,
# stars=sph.dm_particles,
stars=stars,
sinks=None,
L=20,
# N=100,
# image_size_scale=10,
filename="phantom-coolthermalwindtestplot-%04i.png" % plotnr, # int(step/plot_every),
title="time = %06.2f %s" % (time.value_in(units.Myr), units.Myr),
gasproperties=["density", "temperature"],
# colorbar=True,
starscale=1,
offset_x=com[0].value_in(units.parsec),
offset_y=com[1].value_in(units.parsec),
thickness=5 | units.parsec,
)
if subplot % subplot_factor == 0:
subplot_enabled = False
print(
"Average temperature of gas: %s" % (
u_to_temperature(gas.u).mean().in_(units.K)
)
)
return
def run_molecular_cloud(N=100,
Mcloud=100. | units.MSun,
Rcloud=1. | units.parsec):
conv = nbody_system.nbody_to_si(Mcloud, Rcloud)
rho_cloud = 3. * Mcloud / (4. * numpy.pi * Rcloud**3)
print rho_cloud
tff = 0.5427 / numpy.sqrt(constants.G * rho_cloud)
print "t_ff=", tff.value_in(units.Myr), 'Myr'
dt = 5.e-2 | units.Myr
tend = 1.0 | units.Myr
# tend=2.0 | units.Myr
parts = molecular_cloud(targetN=N,
convert_nbody=conv,
base_grid=body_centered_grid_unit_cube,
seed=100).result
sph = Fi(conv, number_of_workers=3)
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
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
parts.h_smooth = eps
print 'eps-h flag', sph.get_eps_is_h(), sph.get_consthsm()
expected_dt = 0.2 * numpy.pi * numpy.power(eps, 1.5) / numpy.sqrt(
constants.G * Mcloud / N)
print "dt_exp=", expected_dt.value_in(units.Myr)
print "dt=", dt
print "eps=", sph.parameters.gas_epsilon.in_(units.parsec)
sph.gas_particles.add_particles(parts)
#grav=copycat(Fi, sph, conv)
#sys=bridge(verbose=False)
#sys.add_system(sph,(grav,),False)
channel_from_sph_to_parts = sph.gas_particles.new_channel_to(parts)
channel_from_parts_to_sph = parts.new_channel_to(sph.gas_particles)
i = 0
L = 6
E0 = 0.0
ttarget = 0.0 | units.Myr
plot_hydro(ttarget, sph, i, L)
while ttarget < tend:
ttarget = float(i) * dt
print ttarget
sph.evolve_model(ttarget, timestep=dt)
E = sph.gas_particles.kinetic_energy(
) + sph.gas_particles.potential_energy(
) + sph.gas_particles.thermal_energy()
E_th = sph.gas_particles.thermal_energy()
if i == 0:
E0 = E
Eerr = (E - E0) / E0
print 'energy=', E, 'energy_error=', Eerr, 'e_th=', E_th
channel_from_sph_to_parts.copy()
"""
filename = 'm400k_r10pc_e01_'+ str(i).zfill(2) + '.dat'
print filename
parts_sorted = parts.sorted_by_attribute('rho')
write_output(filename, parts_sorted, conv)
"""
plot_hydro(ttarget, sph, i, L)
i = i + 1
plot_hydro_and_stars(ttarget, sph, L)
sph.stop()
return parts
def run_mc(N=5000, Mcloud=10000. | units.MSun, Rcloud=1. | units.parsec):
timestep = 0.005 | units.Myr
end_time = 0.12 | units.Myr
conv = nbody_system.nbody_to_si(Mcloud, Rcloud)
parts = molecular_cloud(targetN=N,
convert_nbody=conv,
ethep_ratio=0.05,
ekep_ratio=0.5).result
rho_cloud = Mcloud / (4 / 3. * numpy.pi * Rcloud**3)
tff = 1 / (4 * numpy.pi * constants.G * rho_cloud)**0.5
parts.density = rho_cloud
update_chem(parts, parts)
print("Tcloud:", parts.temperature.max().in_(units.K))
print("cloud n_H:", parts.number_density.max().in_(units.cm**-3))
print("freefall time:", tff.in_(units.Myr))
sph = Fi(conv)
chem = Krome(redirection="none")
sph.parameters.self_gravity_flag = True
sph.parameters.use_hydro_flag = True
sph.parameters.isothermal_flag = True
sph.parameters.integrate_entropy_flag = False
sph.parameters.gamma = 1
sph.parameters.verbosity = 0
sph.parameters.timestep = timestep / 2
sph.gas_particles.add_particles(parts)
chem.particles.add_particles(parts)
tnow = sph.model_time
f = pyplot.figure()
pyplot.ion()
pyplot.show()
i = 0
while i < (end_time / timestep + 0.5):
evolve_sph_with_chemistry(sph, chem, i * timestep)
tnow = sph.model_time
print("done with step:", i, tnow.in_(units.Myr))
i += 1
n = (sph.particles.density / meanmwt).value_in(units.cm**-3)
fh2 = chem.particles.abundances[:, chem.species["H2"]]
co = chem.particles.abundances[:, chem.species["CO"]]
f.clear()
pyplot.loglog(n, fh2, 'r.')
pyplot.loglog(n, co, 'g.')
pyplot.xlim(1.e3, 1.e6)
pyplot.ylim(1.e-6, 1)
pyplot.xlabel("density (cm**-3)")
pyplot.ylabel("H_2,CO abundance")
pyplot.draw()
print("done. press key to exit")
raw_input()
from amuse.ext.evrard_test import body_centered_grid_unit_cube
from amuse.community.simplex.interface import SimpleX
Mcloud = 1000. | units.MSun
Rcloud = 3. | units.pc
Tcloud = 100. | units.K
N = 1000
sigma = 0.01 | units.pc
box_size = 10. | units.pc
converter = nbody_system.nbody_to_si(Mcloud, Rcloud)
gas_particles = molecular_cloud(targetN=N,
convert_nbody=converter,
base_grid=body_centered_grid_unit_cube).result
gas_particles.x += np.random.normal(size=len(gas_particles)) * sigma
gas_particles.y += np.random.normal(size=len(gas_particles)) * sigma
gas_particles.z += np.random.normal(size=len(gas_particles)) * sigma
gas_particles.flux = 0. | units.s**-1
gas_particles.u = (Tcloud * constants.kB) / (1.008 * constants.u)
gas_particles.rho = Mcloud / (4. / 3. * np.pi * Rcloud**3)
gas_particles.xion = 0.
radiative = SimpleX(redirection='none', number_of_workers=8)
radiative.parameters.blackbody_spectrum_flag = True
def run_molecular_cloud(N=100, Mcloud=100. | units.MSun,
Rcloud=1. | units.parsec):
conv = nbody_system.nbody_to_si(Mcloud,Rcloud)
rho_cloud = 3.*Mcloud/(4.*numpy.pi*Rcloud**3)
print rho_cloud
tff = 0.5427/numpy.sqrt(constants.G*rho_cloud)
print "t_ff=", tff.value_in(units.Myr), 'Myr'
dt = 5.e-2 | units.Myr
t_end = 1.0 | units.Myr
parts = molecular_cloud(targetN=N,convert_nbody=conv,
base_grid=body_centered_grid_unit_cube,
seed=100).result
sph = Fi(conv)
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
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
parts.h_smooth= eps
print 'eps-h flag', sph.get_eps_is_h(), sph.get_consthsm()
expected_dt = 0.2*numpy.pi*numpy.power(eps, 1.5) \
/ numpy.sqrt(constants.G*Mcloud/N)
print "dt_exp=", expected_dt.value_in(units.Myr)
print "dt=", dt
print "eps=", sph.parameters.gas_epsilon.in_(units.parsec)
sph.gas_particles.add_particles(parts)
channel_from_sph_to_parts= sph.gas_particles.new_channel_to(parts)
channel_from_parts_to_sph= parts.new_channel_to(sph.gas_particles)
i = 0
L = 6
E0 = 0.0
ttarget = 0.0 | units.Myr
plot_hydro(ttarget, sph, i, L)
while ttarget < t_end:
ttarget = float(i)*dt
print ttarget
sph.evolve_model(ttarget, timestep=dt)
E = sph.gas_particles.kinetic_energy() \
+ sph.gas_particles.potential_energy() \
+ sph.gas_particles.thermal_energy()
E_th = sph.gas_particles.thermal_energy()
if i == 0:
E0 = E
Eerr = (E-E0)/E0
print 'energy=', E, 'energy_error=', Eerr, 'e_th=', E_th
channel_from_sph_to_parts.copy()
plot_hydro(ttarget, sph, i, L)
i += 1
sph.stop()
return parts
def run_molecular_cloud(N=100, Mcloud=100. | units.MSun,
Rcloud=1. | units.parsec):
conv = nbody_system.nbody_to_si(Mcloud,Rcloud)
gas=molecular_cloud(targetN=N,convert_nbody=conv,
base_grid=body_centered_grid_unit_cube).result
gas.name = "gas"
rho_cloud = Mcloud/Rcloud**3
tff = 0.5427/numpy.sqrt(constants.G*rho_cloud)
print "Freefall timescale=", tff.in_(units.Myr)
stars = Particles(0)
hydro = Hydro(Fi, gas, stars)
rho_cloud = 3.*Mcloud/(4.*numpy.pi*Rcloud**3)
print rho_cloud
dt = 0.02 | units.Myr
tend= 10.0 | units.Myr
dt_diag = 0.1 | units.Myr
t_diag = 0 | units.Myr
i=0
E0 = 0.0
time = 0.0 | units.Myr
while time < tend:
time += dt
print "Evolve to time=", time.in_(units.Myr)
Mtot = 0|units.MSun
if len(hydro.star_particles) > 0:
print "Mass conservation: Slocal:", time.in_(units.Myr), \
hydro.gas_particles.mass.sum().in_(units.MSun), \
hydro.star_particles.mass.sum().in_(units.MSun), \
"sum=", (hydro.gas_particles.mass.sum() \
+ hydro.star_particles.mass.sum()).in_(units.MSun)
print "Mass conservation: Shydro:", time.in_(units.Myr), \
hydro.code.gas_particles.mass.sum().in_(units.MSun), \
hydro.code.dm_particles.mass.sum().in_(units.MSun), \
"sum=", \
(hydro.code.gas_particles.mass.sum() \
+ hydro.code.dm_particles.mass.sum()).in_(units.MSun), \
"S=", hydro.star_particles.mass.sum().in_(units.MSun)
Mtot = hydro.gas_particles.mass.sum() \
+ hydro.star_particles.mass.sum()
else:
print "Mass conservation: local:", time.in_(units.Myr), \
hydro.gas_particles.mass.sum().in_(units.MSun)
print "Mass conservation: hydro:", time.in_(units.Myr), \
hydro.code.gas_particles.mass.sum().in_(units.MSun)
Mtot = hydro.gas_particles.mass.sum()
if Mtot < Mcloud-(1.e-5|units.MSun):
print "Mass is not conserved:", Mtot.in_(units.MSun), \
Mcloud.in_(units.MSun)
exit(-1)
hydro.evolve_model(time)
E = hydro.gas_particles.kinetic_energy() \
+ hydro.gas_particles.potential_energy() \
+ hydro.gas_particles.thermal_energy()
E_th = hydro.gas_particles.thermal_energy()
if i==0:
E0 = E
Eerr = (E-E0)/E0
print 'energy=', E, 'energy_error=', Eerr, 'e_th=', E_th
print "maximal_density:",gas.rho.max().in_(units.MSun/units.parsec**3)
hydro.print_diagnostics()
if time>t_diag:
t_diag += dt_diag
hydro.write_set_to_file(i)
i=i+1
hydro.stop()
return gas
def run_molecular_cloud(N=100,
Mcloud=100. | units.MSun,
Rcloud=1. | units.parsec):
conv = nbody_system.nbody_to_si(Mcloud, Rcloud)
gas = molecular_cloud(targetN=N,
convert_nbody=conv,
base_grid=body_centered_grid_unit_cube).result
gas.name = "gas"
rho_cloud = Mcloud / Rcloud**3
tff = 0.5427 / numpy.sqrt(constants.G * rho_cloud)
print "Freefall timescale=", tff.in_(units.Myr)
#omega = 1./tff
#print "Omega=", omega.in_(units.yr**-1)
#gas.add_spin(omega)
stars = Particles(0)
hydro = Hydro(Fi, gas, stars)
rho_cloud = 3. * Mcloud / (4. * numpy.pi * Rcloud**3)
print rho_cloud
# dt = 0.1*tff
# tend=40.0*tff
dt = 0.02 | units.Myr
tend = 10.0 | units.Myr
dt_diag = 0.1 | units.Myr
t_diag = 0 | units.Myr
i = 0
E0 = 0.0
time = 0.0 | units.Myr
while time < tend:
time += dt
print "Evolve to time=", time.in_(units.Myr)
# print "N=", len(sph.gas_particles), len(sph.dm_particles)
# print "Masses of dm particles:", sph.dm_particles.mass.in_(units.MSun)
hydro.evolve_model(time)
E = hydro.gas_particles.kinetic_energy(
) + hydro.gas_particles.potential_energy(
) + hydro.gas_particles.thermal_energy()
E_th = hydro.gas_particles.thermal_energy()
if i == 0:
E0 = E
Eerr = (E - E0) / E0
print 'energy=', E, 'energy_error=', Eerr, 'e_th=', E_th
print "maximal_density:", gas.rho.max().in_(units.MSun /
units.parsec**3)
hydro.print_diagnostics()
if time > t_diag:
t_diag += dt_diag
hydro.write_set_to_file(i)
i = i + 1
hydro.stop()
return gas
def run_mc(N=5000,Mcloud=10000. | units.MSun,Rcloud=1. | units.parsec):
conv = nbody_system.nbody_to_si(Mcloud,Rcloud)
interaction_timestep = 0.01 | units.Myr
time_end=0.36 | units.Myr
parts=molecular_cloud(targetN=N,convert_nbody=conv,
base_grid=body_centered_grid_unit_cube).result
sph=Fi(conv)
# need to turn off self gravity, the bridge will calculate this
sph.parameters.self_gravity_flag=False
# some typical Fi flags (just for reference, most are default values)
sph.parameters.use_hydro_flag=True
sph.parameters.isothermal_flag=True
sph.parameters.integrate_entropy_flag=False
sph.parameters.gamma=1
sph.parameters.verbosity = 0
# setting the hydro timestep is important
# the sph code will take 2 timesteps every interaction timestep
sph.parameters.timestep=interaction_timestep/2
sph.gas_particles.add_particles(parts)
def new_code_to_calculate_gravity_of_gas_particles():
result = BHTree(conv)
return result
calculate_gravity_code=bridge.CalculateFieldForCodes(
new_code_to_calculate_gravity_of_gas_particles, # the code that calculates the acceleration field
input_codes = [sph] # the codes to calculate the acceleration field of
)
bridged_system = bridge.Bridge()
bridged_system.timestep=interaction_timestep
bridged_system.add_system(
sph, # the code to move the particles of
[calculate_gravity_code] # the codes that provide the acceleration field
)
fig=pyplot.figure(figsize=(12,12))
ncolumn=2
nrow=2
nplot=ncolumn*nrow
grid_size = 3 | units.parsec
extent = (grid_size * (-0.5, 0.5, -0.5, 0.5)).value_in(units.parsec)
if nplot > 1:
plot_timestep = time_end / (nplot - 1)
else:
plot_timestep = time_end
for i in range(nplot):
ttarget=i*plot_timestep
print("evolving to time:", ttarget.as_quantity_in(units.Myr))
bridged_system.evolve_model(ttarget)
rho=make_map(sph,N=200,grid_size=grid_size)
subplot=fig.add_subplot(ncolumn,nrow,i+1)
subplot.imshow(
numpy.log10(1.e-5+rho.value_in(units.amu/units.cm**3)),
extent = extent,
vmin=1,
vmax=5
)
subplot.set_title(ttarget.as_quantity_in(units.Myr))
sph.stop()
pyplot.show()
def run_molecular_cloud(N=100, Mcloud=100. | units.MSun, Rcloud=1. | units.parsec):
conv = nbody_system.nbody_to_si(Mcloud,Rcloud)
rho_cloud = 3.*Mcloud/(4.*numpy.pi*Rcloud**3)
print rho_cloud
tff = 0.5427/numpy.sqrt(constants.G*rho_cloud)
print "t_ff=", tff.value_in(units.Myr), 'Myr'
dt = 5.e-2 | units.Myr
tend=1.0 | units.Myr
parts=molecular_cloud(targetN=N,convert_nbody=conv,
base_grid=body_centered_grid_unit_cube, seed=100).result
#sph=Fi(conv, number_of_workers=3)
sph=Fi(conv)
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
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
parts.h_smooth= eps
print 'eps-h flag', sph.get_eps_is_h(), sph.get_consthsm()
expected_dt = 0.2*numpy.pi*numpy.power(eps, 1.5)/numpy.sqrt(constants.G*Mcloud/N)
print "dt_exp=", expected_dt.value_in(units.Myr)
print "dt=", dt
print "eps=", sph.parameters.gas_epsilon.in_(units.parsec)
sph.gas_particles.add_particles(parts)
channel_from_sph_to_parts= sph.gas_particles.new_channel_to(parts)
channel_from_parts_to_sph= parts.new_channel_to(sph.gas_particles)
i=0
L=6
E0 = 0.0
ttarget = 0.0 | units.Myr
plot_hydro(ttarget, sph, i, L)
while ttarget < tend:
ttarget=float(i)*dt
print ttarget
sph.evolve_model(ttarget, timestep=dt)
E = sph.gas_particles.kinetic_energy()+sph.gas_particles.potential_energy() + sph.gas_particles.thermal_energy()
E_th = sph.gas_particles.thermal_energy()
if i==0:
E0 = E
Eerr = (E-E0)/E0
print 'energy=', E, 'energy_error=', Eerr, 'e_th=', E_th
channel_from_sph_to_parts.copy()
"""
filename = 'm400k_r10pc_e01_'+ str(i).zfill(2) + '.dat'
print filename
parts_sorted = parts.sorted_by_attribute('rho')
write_output(filename, parts_sorted, conv)
"""
plot_hydro(ttarget, sph, i, L)
i=i+1
sph.stop()
return parts
def run_cloud(x):
cloud = molecular_cloud(32, -4., x, base_grid=regular_grid_unit_cube)
mass, x, y, z, vx, vy, vz, u = cloud.new_model()
smooth = numpy.zeros_like(mass)
nb = interface.FiInterface(redirection="none")
nb.initialize_code()
nb.set_stepout(99999)
nb.set_steplog(99999)
nb.set_use_hydro(1)
nb.set_radiate(0)
nb.set_dtime(0.05)
nb.set_gdgop(1)
nb.set_uentropy(0)
nb.set_isotherm(1)
nb.set_gamma(1.0)
nb.set_verbosity(0)
nb.set_unitl_in_kpc(0.01)
nb.set_unitm_in_msun(10000.)
ids, error = nb.new_sph_particle(mass, x, y, z, vx, vy, vz, u, smooth)
if filter(lambda x: x != 0, error) != []: raise Exception
nb.commit_particles()
if hasattr(nb, "viewer"):
nb.viewer()
dt = 0.05
tnow = 0.
nb.synchronize_model()
time, Ek, Ep, Eth = [], [], [], []
time.append(tnow)
e, ret = nb.get_kinetic_energy()
Ek.append(e)
e, ret = nb.get_potential_energy()
Ep.append(e)
e, ret = nb.get_thermal_energy()
Eth.append(e)
while tnow < .8:
tnow = tnow+dt
nb.evolve_model(tnow)
nb.synchronize_model()
tnow, err = nb.get_time()
time.append(tnow)
e, ret = nb.get_kinetic_energy()
Ek.append(e)
e, ret = nb.get_potential_energy()
Ep.append(e)
e, ret = nb.get_thermal_energy()
Eth.append(e)
nb.stop()
time = numpy.array(time)
Ek = numpy.array(Ek)
Ep = numpy.array(Ep)
Eth = numpy.array(Eth)
energy_plot(time, Ek, Ep, Eth)
def run_mc(N=5000, Mcloud=10000. | units.MSun, Rcloud=1. | units.parsec):
conv = nbody_system.nbody_to_si(Mcloud, Rcloud)
interaction_timestep = 0.01 | units.Myr
time_end = 0.36 | units.Myr
parts = molecular_cloud(targetN=N,
convert_nbody=conv,
base_grid=body_centered_grid_unit_cube).result
sph = Fi(conv)
# need to turn off self gravity, the bridge will calculate this
sph.parameters.self_gravity_flag = False
# some typical Fi flags (just for reference, most are default values)
sph.parameters.use_hydro_flag = True
sph.parameters.isothermal_flag = True
sph.parameters.integrate_entropy_flag = False
sph.parameters.gamma = 1
sph.parameters.verbosity = 0
# setting the hydro timestep is important
# the sph code will take 2 timesteps every interaction timestep
sph.parameters.timestep = interaction_timestep / 2
sph.gas_particles.add_particles(parts)
def new_code_to_calculate_gravity_of_gas_particles():
result = BHTree(conv)
return result
calculate_gravity_code = bridge.CalculateFieldForCodes(
new_code_to_calculate_gravity_of_gas_particles, # the code that calculates the acceleration field
input_codes=[sph] # the codes to calculate the acceleration field of
)
bridged_system = bridge.Bridge()
bridged_system.timestep = interaction_timestep
bridged_system.add_system(
sph, # the code to move the particles of
[calculate_gravity_code
] # the codes that provide the acceleration field
)
fig = pyplot.figure(figsize=(12, 12))
ncolumn = 2
nrow = 2
nplot = ncolumn * nrow
grid_size = 3 | units.parsec
extent = (grid_size * (-0.5, 0.5, -0.5, 0.5)).value_in(units.parsec)
if nplot > 1:
plot_timestep = time_end / (nplot - 1)
else:
plot_timestep = time_end
for i in range(nplot):
ttarget = i * plot_timestep
print("evolving to time:", ttarget.as_quantity_in(units.Myr))
bridged_system.evolve_model(ttarget)
rho = make_map(sph, N=200, grid_size=grid_size)
subplot = fig.add_subplot(ncolumn, nrow, i + 1)
subplot.imshow(numpy.log10(1.e-5 +
rho.value_in(units.amu / units.cm**3)),
extent=extent,
vmin=1,
vmax=5)
subplot.set_title(ttarget.as_quantity_in(units.Myr))
sph.stop()
pyplot.show()
