def create_N_vs_t(filename, N_list=None):
""" Iteratively runs run_hydrodynamics for several N in order to
create the data for the N vs. wallclock-time plot. Writes data to
hdf5 file."""
if N_list:
N = N_list
else:
a = range(100,1000,100)
b = range(1000,10000,1000)
N = a+b
total_runtimes = AdaptingVectorQuantity()
for nr_particles in N:
start_time = time.time() |units.s
run_hydrodynamics(N=nr_particles, n_steps=1)
end_time = time.time() |units.s
total_runtime = end_time - start_time
total_runtimes.append(total_runtime)
N_as_vq = N | units.no_unit
data = {'N':N_as_vq, 'runtimes':total_runtimes}
results = HydroResults(data)
write_to_hdf5('hydroresults/'+filename,\
results.__dict__)
pngfilename = options.N_vs_t.split('.')[0]+'.png'
plot_steptimes(results, filepath = "plots/"+pngfilename)
def create_N_vs_t(filename, N_list=None):
""" Iteratively runs run_hydrodynamics for several N in order to
create the data for the N vs. wallclock-time plot. Writes data to
hdf5 file."""
if N_list:
N = N_list
else:
a = range(100, 1000, 100)
b = range(1000, 10000, 1000)
N = a + b
total_runtimes = AdaptingVectorQuantity()
for nr_particles in N:
start_time = time.time() | units.s
run_hydrodynamics(N=nr_particles, n_steps=1)
end_time = time.time() | units.s
total_runtime = end_time - start_time
total_runtimes.append(total_runtime)
N_as_vq = N | units.no_unit
data = {'N': N_as_vq, 'runtimes': total_runtimes}
results = HydroResults(data)
write_to_hdf5('hydroresults/'+filename,\
results.__dict__)
pngfilename = options.N_vs_t.split('.')[0] + '.png'
plot_steptimes(results, filepath="plots/" + pngfilename)
def create_N_vs_E(filename, N_list=None):
""" Iteratively runs run_hydrodynamics for several N in order to
create the data for the N vs. Energy error plot. Writes data to hdf5
file."""
if N_list:
N = N_list
else:
N = range(100, 1000, 50)
energy_errors = AdaptingVectorQuantity()
for nr_particles in N:
results = run_hydrodynamics(N=nr_particles, n_steps=50)
energy_begin = results.total_energy[0]
energy_end = results.total_energy[-1]
energy_error = (energy_begin - energy_end) / energy_end
energy_error = energy_error | units.no_unit
energy_errors.append(energy_error)
N_as_vq = N | units.no_unit
data = {'N': N_as_vq, 'energy_errors': energy_errors}
results = HydroResults(data)
write_to_hdf5('hydroresults/'+filename,\
results.__dict__)
pngfilename = options.N_vs_E.split('.')[0] + '.png'
plot_energy(results, filepath="plots/" + pngfilename)
def create_N_vs_E(filename, N_list = None):
""" Iteratively runs run_hydrodynamics for several N in order to
create the data for the N vs. Energy error plot. Writes data to hdf5
file."""
if N_list:
N = N_list
else:
N = range(100, 1000, 50)
energy_errors = AdaptingVectorQuantity()
for nr_particles in N:
results = run_hydrodynamics(N=nr_particles, n_steps=50)
energy_begin = results.total_energy[0]
energy_end = results.total_energy[-1]
energy_error = (energy_begin-energy_end)/energy_end
energy_error = energy_error |units.no_unit
energy_errors.append(energy_error)
N_as_vq = N | units.no_unit
data = {'N':N_as_vq, 'energy_errors':energy_errors}
results = HydroResults(data)
write_to_hdf5('hydroresults/'+filename,\
results.__dict__)
pngfilename = options.N_vs_E.split('.')[0]+'.png'
plot_energy(results, filepath = "plots/"+pngfilename)
def get_potential_at_point(self,radius,x,y,z):
part=Particles(0)
for s in self.systems:
part.add_particles(s.particles)
phi=AdaptingVectorQuantity()
for rr,xx,yy,zz in zip(radius,x,y,z):
dr2=((part.x-xx)**2+(part.y-yy)**2+(part.z-zz)**2+rr**2+part.radius**2)
phi.append( (-self.G*part.mass/dr2**0.5).sum() )
return phi
def get_gravity_at_point(self, pos):
phi_0 = self.get_potential_at_point(pos)
grav = AdaptingVectorQuantity()
dpos = 0.001*pos.length()
for ii in range(len(pos)):
ppos = 1.0*pos
ppos[ii] += dpos
phi_1 = self.get_potential_at_point(ppos)
grav.append((phi_1 - phi_0)/dpos)
return grav
def get_gravity_at_point(self, pos):
phi_0 = self.get_potential_at_point(pos)
grav = AdaptingVectorQuantity()
dpos = 0.001 * pos.length()
for ii in range(len(pos)):
ppos = 1.0 * pos
ppos[ii] += dpos
phi_1 = self.get_potential_at_point(ppos)
grav.append((phi_1 - phi_0) / dpos)
return grav
def run_pyth(te=100):
dt = 0.01 | nbody_system.time
t_end = te | nbody_system.time
code = ph4()
code.parameters.timestep_parameter = dt.value_in(nbody_system.time)
code.particles.add_particles(new_particles())
x = AdaptingVectorQuantity()
y = AdaptingVectorQuantity()
t = 0. | nbody_system.time
eccents_12 = []
eccents_23 = []
eccents_31 = []
semmajaxs_12 = []
semmajaxs_23 = []
semmajaxs_31 = []
times = []
while(t < t_end-dt/2):
t=t+dt
code.evolve_model(t)
x.append(code.particles.x)
y.append(code.particles.y)
mass1, mass2, semimajor_axis_12, eccentricity_12, true_anomaly, inclination, long_asc_node, arg_per = orbital_elements_from_binary([code.particles[0], code.particles[1]])
mass2, mass3, semimajor_axis_23, eccentricity_23, true_anomaly, inclination, long_asc_node, arg_per = orbital_elements_from_binary([code.particles[1], code.particles[2]])
mass3, mass1, semimajor_axis_31, eccentricity_31, true_anomaly, inclination, long_asc_node, arg_per = orbital_elements_from_binary([code.particles[2], code.particles[0]])
eccents_12.append(eccentricity_12)
eccents_23.append(eccentricity_23)
eccents_31.append(eccentricity_31)
semmajaxs_12.append(semimajor_axis_12.value_in(nbody_system.length))
semmajaxs_23.append(semimajor_axis_23.value_in(nbody_system.length))
semmajaxs_31.append(semimajor_axis_31.value_in(nbody_system.length))
times.append(t.value_in(nbody_system.time))
code.stop()
return x,y,times,semmajaxs_12,semmajaxs_23,semmajaxs_31,eccents_12,eccents_23,eccents_31
def run_pyth(interface, tend=100, dt=0.125, parameters=[]):
code = interface()
for name, value in parameters:
setattr(code.parameters, name, value)
code.particles.add_particles(new_particles())
code.commit_particles()
x = AdaptingVectorQuantity()
y = AdaptingVectorQuantity()
t = 0. | nbody_system.time
while(t < tend-dt/2):
t = t+dt
code.evolve_model(t)
x.append(code.particles.x)
y.append(code.particles.y)
code.stop()
return x, y
def run_pyth(interface, tend=100, dt=0.125, parameters=[]):
code = interface()
for name, value in parameters:
setattr(code.parameters, name, value)
code.particles.add_particles(new_particles())
code.commit_particles()
x = AdaptingVectorQuantity()
y = AdaptingVectorQuantity()
t = 0. | nbody_system.time
while (t < tend - dt / 2):
t = t + dt
code.evolve_model(t)
x.append(code.particles.x)
y.append(code.particles.y)
code.stop()
return x, y
def run_pyth(interface,tend=100,dt=0.125, label=""):
code = interface()
code.parameters.timestep_parameter = dt.value_in(nbody_system.time)
code.particles.add_particles(new_particles())
Ekin = code.kinetic_energy
Epot = code.potential_energy
Einit = Ekin + Epot
Energy = [Einit.value_in(nbody_system.energy)]
x = AdaptingVectorQuantity()
y = AdaptingVectorQuantity()
t = 0. | nbody_system.time
Times = [t.value_in(nbody_system.time)]
while(t < tend-dt/2):
t=t+dt
code.evolve_model(t)
x.append(code.particles.x)
y.append(code.particles.y)
Ekin = code.kinetic_energy
Epot = code.potential_energy
Etot = Ekin + Epot
Energy.append(Etot.value_in(nbody_system.energy))
Times.append(t.value_in(nbody_system.time))
code.stop()
return x,y,Times,Energy
def get_gravity_at_point(self,radius,x,y,z):
part=Particles(0)
for s in self.systems:
part.add_particles(s.particles)
ax=AdaptingVectorQuantity()
ay=AdaptingVectorQuantity()
az=AdaptingVectorQuantity()
for rr,xx,yy,zz in zip(radius,x,y,z):
dr2=((part.x-xx)**2+(part.y-yy)**2+(part.z-zz)**2+rr**2+part.radius**2)
ax.append( (self.G*part.mass*(part.x-xx)/dr2**1.5).sum() )
ay.append( (self.G*part.mass*(part.y-yy)/dr2**1.5).sum() )
az.append( (self.G*part.mass*(part.z-zz)/dr2**1.5).sum() )
return ax,ay,az
def aggregate_mass(self,too_close):
corrected_masses = AdaptingVectorQuantity()
corrected_positions = AdaptingVectorQuantity()
corrected_velocities = AdaptingVectorQuantity()
corrected_angular_momenta = AdaptingVectorQuantity()
for subset, m, pos, vel, Lin in zip(too_close, self.mass, self.position, self.velocity, self.angular_momentum):
if len(subset):
total_mass = subset.total_mass() + m
cmpos=(m*pos + subset.total_mass()*subset.center_of_mass())/total_mass
cmvel=(m*vel + subset.total_mass()*subset.center_of_mass_velocity())/total_mass
L=Lin+angular_momentum(m,pos-cmpos,vel-cmvel)+angular_momentum(subset.mass,subset.position-cmpos,subset.velocity-cmvel).sum(axis=0)
corrected_masses.append(total_mass)
corrected_positions.append(cmpos)
corrected_velocities.append(cmvel)
corrected_angular_momenta.append(L)
else:
corrected_masses.append(m)
corrected_positions.append(pos)
corrected_velocities.append(vel)
corrected_angular_momenta.append(Lin)
self.mass = corrected_masses
self.position = corrected_positions
self.velocity = corrected_velocities
self.angular_momentum = corrected_angular_momenta
def calculate_escape_time(index, number_of_systems):
numpy.random.seed()
# from amuse.community.smallN.muse_dynamics_mpi import SmallN
print "start of subprocess", index
x0 = AdaptingVectorQuantity()
y0 = AdaptingVectorQuantity()
x1 = AdaptingVectorQuantity()
y1 = AdaptingVectorQuantity()
x2 = AdaptingVectorQuantity()
y2 = AdaptingVectorQuantity()
m0 = AdaptingVectorQuantity()
m1 = AdaptingVectorQuantity()
m2 = AdaptingVectorQuantity()
tends = AdaptingVectorQuantity()
try:
for x in range(number_of_systems):
gravity = Hermite()
particles = new_initial_system()
code = SimulateTripleSystemUntilDecay(gravity, particles, index, x)
tend = code.evolve_model_until_escape()
print index, x, tend
code.stop()
x0.append(particles[0].x)
y0.append(particles[0].y)
x1.append(particles[1].x)
y1.append(particles[1].y)
x2.append(particles[2].x)
y2.append(particles[2].y)
m0.append(particles[0].mass)
m1.append(particles[1].mass)
m2.append(particles[2].mass)
tends.append(tend)
except KeyboardInterrupt:
pass
print "end of subprocess", index
return x0, y0, x1, y1, x2, y2, m0, m1, m2, tends
print "doing statistics"
sorted_times = data[-1].sorted()
t = 0 | nbody_system.time
tend = 1000 | nbody_system.time
dt = 1 | nbody_system.time
while t < tend:
i = 0
while i < len(sorted_times):
tn = sorted_times[i]
i += 1
if tn < t:
continue
else:
break
times.append(t)
counts.append((len(sorted_times) - i) | units.none)
t += dt
output = text.CsvFileText(
filename="triple_statistics_{0:03}.csv".format(rank))
output.quantities = (times, counts)
output.attribute_names = ("t", "n(t)")
output.store()
print "done"
"""
set logscale xy
"""
def main():
dots = Dots()
line = Line()
f = h5py.File(args.filename, 'r')
fig = plt.figure()
ax1 = fig.add_subplot(211)
ax2 = fig.add_subplot(212)
for intr in f.values():
timesteps_vq = AdaptingVectorQuantity()
final_smas_p0_vq = AdaptingVectorQuantity()
final_smas_p1_vq = AdaptingVectorQuantity()
for sim in intr.values():
timesteps_vq.append(sim['timestep'][0] | retrieve_unit(sim['timestep']))
final_smas_p0_vq.append(sim['p0/sma'][-1]| retrieve_unit(sim['p0/sma']))
final_smas_p1_vq.append(sim['p1/sma'][-1]| retrieve_unit(sim['p1/sma']))
timesteps = timesteps_vq.value_in(units.yr)
final_smas_p0 = final_smas_p0_vq.value_in(units.AU)
final_smas_p1 = final_smas_p1_vq.value_in(units.AU)
ax1.plot(timesteps, final_smas_p0, marker='o', label=intr.name, picker=5)
ax2.plot(timesteps, final_smas_p1, marker='o', label=intr.name, picker=5)
ax1.set_xlabel('Mass update interval [yr]')
ax2.set_xlabel('Mass update interval [yr]')
ax1.set_ylabel('final sma inner [AU]')
ax2.set_ylabel('final sma outer [AU]')
dset = f.values()[0].values()[0] #first dset available
time = quantify_dset(dset['time']).value_in(units.yr)
mass = quantify_dset(dset['mass']).value_in(units.MSun)
inner_sma0 = quantify_dset(dset['p0/sma']).value_in(units.AU)
outer_sma0 = quantify_dset(dset['p1/sma']).value_in(units.AU)
inner_sma_final_adiabatic_approx = sma_analytical(inner_sma0[0], 1.244e-5, time[-1], mass[0].sum() )
outer_sma_final_adiabatic_approx = sma_analytical(outer_sma0[0], 1.244e-5, time[-1], mass[0].sum() )
ax1.axhline(inner_sma_final_adiabatic_approx, xmin=0, xmax=1, c='m', label='adiabatic approx')
ax1.legend(loc='best')
ax2.axhline(outer_sma_final_adiabatic_approx, xmin=0, xmax=1, c='m', label='adiabatic approx')
ax2.legend(loc='best')
if args.logscale:
ax1.set_xscale('log')
ax2.set_xscale('log')
if args.ylim1:
ax1.set_ylim(args.ylim1)
if args.ylim2:
ax2.set_ylim(args.ylim2)
if args.xlim1:
ax1.set_xlim(args.xlim1)
if args.xlim2:
ax2.set_xlim(args.xlim2)
def onpick(event):
print("artist:{} ind:{}".format(event.artist, event.ind))
print("button: {}".format(event.mouseevent.button))
intr = f[event.artist.get_label()]
sim = intr.values()[event.ind]
time_vq = quantify_dset(sim['time'])
time = time_vq.value_in(units.yr)
position_vq = quantify_dset(sim['position'])
position = position_vq.value_in(units.AU)
CM_position_vq = quantify_dset(sim['CM_position'])
CM_position = CM_position_vq.value_in(units.AU)
x, y = 0, 1
central_x, central_y = position[:, 0, x] - CM_position[:,x], position[:, 0, y] - CM_position[:,y]
inner_x, inner_y = position[:, 1, x] - CM_position[:,x], position[:, 1, y] - CM_position[:,y]
outer_x, outer_y = position[:, 2, x] - CM_position[:,x], position[:, 2, y] - CM_position[:,y]
mass_vq = quantify_dset(sim['mass'])
mass = mass_vq[:,0].value_in(units.MSun)
if event.mouseevent.button == 1:
mu0 = quantify_dset(sim['mass'])[0].sum()
period_vq = quantify_dset(sim['p0/period'])
period = period_vq.value_in(units.yr)
true_anomaly = sim['p0/true_anomaly'].value
argument_of_periapsis = sim['p0/argument_of_periapsis'].value
sma_vq = quantify_dset(sim['p0/sma'])
sma = sma_vq.value_in(units.AU)
sma_an_vq = sma_analytical(sma_vq[0], 1.244e-5|(units.MSun/units.yr), time_vq, mu0)
sma_an = sma_an_vq.value_in(units.AU)
eccentricity = sim['p0/eccentricity'].value
newfig = plt.figure()
newax1 = newfig.add_subplot(511)
newax2 = newfig.add_subplot(512)
newax3 = newfig.add_subplot(513)
newax4 = newfig.add_subplot(514)
newax5 = newfig.add_subplot(515)
newax1.plot(time, sma, label='numerical')
newax1.plot(time, sma_an, label='analytical_adiabatic')
newax1.set_xlabel('time [yr]')
newax1.set_ylabel('sma [AU]')
newax1.legend(loc='best')
newax2.plot(time, eccentricity)
newax2.set_xlabel('time [yr]')
newax2.set_ylabel('eccentricity ')
newax3.plot(time, true_anomaly)
newax3.set_xlabel('time [yr]')
newax3.set_ylabel('true anomaly [degrees] ')
newax4.plot(time, argument_of_periapsis)
newax4.set_xlabel('time [yr]')
newax4.set_ylabel('argument of periapsis [degrees] ')
newax5.plot(time, period)
newax5.set_xlabel('time [yr]')
newax5.set_ylabel('period')
else:
newfig = plt.figure()
newax1 = newfig.add_subplot(321)
newax2 = newfig.add_subplot(322)
newax3 = newfig.add_subplot(323)
newax4 = newfig.add_subplot(324)
newax5 = newfig.add_subplot(325)
newax6 = newfig.add_subplot(326)
mass_vq = quantify_dset(sim['mass'])
mass = mass_vq.value_in(units.MSun)
kinetic_energy = sim['kinetic_energy'].value
potential_energy = sim['potential_energy'].value
total_energy = sim['total_energy'].value
CM_velocity_vq = quantify_dset(sim['CM_velocity'])
CM_velocity_mod = CM_velocity_vq.lengths().value_in(units.km/units.hour)
walltime = sim['walltime'].value - sim['walltime'][0]
newax1.plot(time, mass)
newax1.set_ylabel('central mass [MSun]')
newax1.set_xlabel('time [yr]')
newax2.plot(time, kinetic_energy, label='kinetic', **line.red)
newax2.plot(time, potential_energy,label='potential', **line.orange)
newax2.plot(time, total_energy, label='total', **line.white)
newax2.set_xlabel('time [yr]')
newax2.legend()
newax3.plot(central_x, central_y, **dots.white)
newax3.plot(inner_x, inner_y, **dots.red)
newax3.plot(outer_x, outer_y, **dots.yellow)
newax3.set_xlabel('x [AU]')
newax3.set_ylabel('y [AU]')
newax4.plot(CM_position[:, x], CM_position[:, y] )
newax4.set_xlim(-5, 5)
newax4.set_xlabel('CM position x [AU]')
newax4.set_ylabel('CM position y [AU]')
newax5.plot(time, CM_velocity_mod)
newax5.set_ylim(20, 30)
newax5.set_xlabel('time [yr]')
newax5.set_ylabel('CM velocity [km/hour]')
newax6.plot(time, walltime)
newax6.set_xlabel('time [yr]')
newax6.set_ylabel('walltime [s]')
newfig.show()
fig.canvas.mpl_connect('pick_event', onpick)
plt.show()
def calculate_escape_time(index, number_of_systems):
numpy.random.seed()
# from amuse.community.smallN.muse_dynamics_mpi import SmallN
print "start of subprocess", index
x0 = AdaptingVectorQuantity()
y0 = AdaptingVectorQuantity()
x1 = AdaptingVectorQuantity()
y1 = AdaptingVectorQuantity()
x2 = AdaptingVectorQuantity()
y2 = AdaptingVectorQuantity()
m0 = AdaptingVectorQuantity()
m1 = AdaptingVectorQuantity()
m2 = AdaptingVectorQuantity()
tends = AdaptingVectorQuantity()
try:
for x in range(number_of_systems):
gravity = Hermite()
particles = new_initial_system()
code = SimulateTripleSystemUntilDecay(gravity, particles, index, x)
tend = code.evolve_model_until_escape()
print index, x, tend
code.stop()
x0.append(particles[0].x)
y0.append(particles[0].y)
x1.append(particles[1].x)
y1.append(particles[1].y)
x2.append(particles[2].x)
y2.append(particles[2].y)
m0.append(particles[0].mass)
m1.append(particles[1].mass)
m2.append(particles[2].mass)
tends.append(tend)
except KeyboardInterrupt:
pass
print "end of subprocess", index
return x0, y0, x1, y1, x2, y2, m0, m1, m2, tends
def evolve_gravity(bodies, number_of_planets, converter, t_end, n_steps, n_snapshots, path):
#Particles that will be saved in the file
bodies_to_save = Particles(number_of_planets+2)
#Positions and velocities centered on the center of mass
bodies.move_to_center()
time = 0. | nbody_system.time
dt = t_end / float(n_steps)
dt_snapshots = t_end / float(n_snapshots)
gravity = initialize_code(bodies, timestep_parameter = dt.value_in(nbody_system.time))
channel_from_gr_to_framework = gravity.particles.new_channel_to(bodies)
x = AdaptingVectorQuantity()
y = AdaptingVectorQuantity()
times = AdaptingVectorQuantity()
system_energies = AdaptingVectorQuantity()
E_initial = gravity.kinetic_energy + gravity.potential_energy
DeltaE_max = 0.0 | nbody_system.energy
snapshot_number = 1
os.system('mkdir ./files/'+path)
while time<=t_end:
gravity.evolve_model(time)
channel_from_gr_to_framework.copy()
bodies.collection_attributes.timestamp = time
gravity.particles.collection_attributes.timestamp = time
x.append(bodies.x)
y.append(bodies.y)
times.append(time)
E = gravity.kinetic_energy + gravity.potential_energy
system_energies.append(E)
DeltaE = abs(E-E_initial)
if ( DeltaE > DeltaE_max ):
DeltaE_max = DeltaE
#Orbital Elements
star = bodies[0]
ffp = bodies[1]
bp = bodies[2]
#Star and FFP
binary = [star, ffp]
m1, m2, sma_star_ffp, e_star_ffp = my_orbital_elements_from_binary(binary)
bodies[1].eccentricity = e_star_ffp
bodies[1].semimajoraxis = sma_star_ffp
#Star and BP
binary = [star, bp]
m1, m2, sma_star_bp, e_star_bp = my_orbital_elements_from_binary(binary)
bodies[2].eccentricity = e_star_bp
bodies[2].semimajoraxis = sma_star_bp
save_particles_to_file(bodies, bodies_to_save, './files/'+path+'/'+str(snapshot_number)+'.hdf5', time, converter)
# if (snapshot_number == 5):
# break
time += dt_snapshots
snapshot_number += 1
#To get last orbital elements
#Star and FFP
binary = [star, ffp]
b1_mass1, b1_mass2, b1_semimajor_axis, b1_eccentricity, b1_true_anomaly, b1_inclination, b1_long_asc_node, b1_arg_per = orbital_elements_from_binary(binary)
#Star and BP
binary = [star, bp]
b2_mass1, b2_mass2, b2_semimajor_axis, b2_eccentricity, b2_true_anomaly, b2_inclination, b2_long_asc_node, b2_arg_per = orbital_elements_from_binary(binary)
#To check Hill stability
#Star+BP and FFP
cm_x = (star.mass*star.x + bp.mass*bp.x)/(star.mass+bp.mass)
cm_y = (star.mass*star.y + bp.mass*bp.y)/(star.mass+bp.mass)
cm_vx = (star.mass*star.vx + bp.mass*bp.vx)/(star.mass+bp.mass)
cm_vy = (star.mass*star.vy + bp.mass*bp.vy)/(star.mass+bp.mass)
star_bp = Particles(1)
star_bp.mass = star.mass + bp.mass
star_bp.position = [cm_x, cm_y, 0.0 | nbody_system.length]
star_bp.velocity = [cm_vx, cm_vy, 0.0 | nbody_system.speed]
binary = [star_bp[0], ffp]
m1, m2, sma_starbp_ffp, e_starbp_ffp = my_orbital_elements_from_binary(binary)
bodies[1].eccentricity = e_starbp_ffp
bodies[1].semimajoraxis = sma_starbp_ffp
max_energy_change = DeltaE_max/E_initial
is_stable = is_hill_stable(bodies.mass, bodies.semimajoraxis, bodies.eccentricity, converter)
gravity.stop()
return x, y, times, system_energies, max_energy_change, is_stable,converter.to_si(b1_semimajor_axis).value_in(units.AU), b1_eccentricity, b1_true_anomaly, b1_inclination, b1_long_asc_node, b1_arg_per, converter.to_si(b2_semimajor_axis).value_in(units.AU), b2_eccentricity, b2_true_anomaly, b2_inclination, b2_long_asc_node, b2_arg_per
def evolve_gravity(bodies, number_of_planets, converter, t_end, n_steps):
#Positions and velocities centered on the center of mass
bodies.move_to_center()
time = 0. | nbody_system.time
dt = t_end / float(n_steps)
gravity = initialize_code(bodies, timestep_parameter = dt.value_in(nbody_system.time))
channel_from_gr_to_framework = gravity.particles.new_channel_to(bodies)
x = AdaptingVectorQuantity()
y = AdaptingVectorQuantity()
times = AdaptingVectorQuantity()
#Order: 12, 23, 31
eccentricities = []
semimajoraxes = []
Etot_init = gravity.kinetic_energy + gravity.potential_energy
Etot = Etot_init
DeltaE_max = 0.0 | nbody_system.energy
times.append(time)
system_energies = [Etot.value_in(nbody_system.energy)]
while time<=t_end:
gravity.evolve_model(time)
channel_from_gr_to_framework.copy()
bodies.collection_attributes.timestamp = time
gravity.particles.collection_attributes.timestamp = time
x.append(bodies.x)
y.append(bodies.y)
times.append(time)
for i in range(0,number_of_planets+2):
for j in range(i+1,number_of_planets+2):
binary = [bodies[i], bodies[j]]
massA, massB, semimajor_axis, eccentricity, true_anomaly, inclination, long_asc_node, arg_per = orbital_elements_from_binary(binary)
eccentricities.append(eccentricity)
semimajoraxes.append(semimajor_axis.value_in(nbody_system.length))
Etot = gravity.kinetic_energy + gravity.potential_energy
DeltaE = abs(Etot-Etot_init)
system_energies.append(Etot.value_in(nbody_system.energy))
if ( DeltaE > DeltaE_max ):
DeltaE_max = DeltaE
time += dt
print "Energy Change: max(|E_j - E_initial|)/E_initial = ", DeltaE_max/Etot_init
results = ['flyby', 'temporary capture', 'exchange','nothing']
#results = [0,1,2,-1]
planets_star_energies = []
for i in range(0,number_of_planets):
planet_star_energy = energies_binaries(bodies, 0, i+2).value_in(nbody_system.energy)
planets_star_energies.append(planet_star_energy)
planets_star_energy = sum(planets_star_energies)
ffp_star_energy = energies_binaries(bodies, 0, 1).value_in(nbody_system.energy)
if (planets_star_energy<0 and ffp_star_energy>0):
res = results[0]
elif (planets_star_energy<0 and ffp_star_energy<0):
res = results[1]
elif (planets_star_energy>0 and ffp_star_energy<0):
res = results[2]
else:
#res = 'something that is not flyby, exchange or temporary capture has happened!'
res = results[3]
print res
gravity.stop()
return x,y,times,numpy.array(system_energies),numpy.array(eccentricities),numpy.array(semimajoraxes)
def aggregate_mass(self,too_close):
corrected_masses = AdaptingVectorQuantity()
corrected_positions = AdaptingVectorQuantity()
corrected_velocities = AdaptingVectorQuantity()
corrected_angular_momenta = AdaptingVectorQuantity()
for subset, m, pos, vel, Lin in zip(too_close, self.mass, self.position, self.velocity, self.angular_momentum):
if len(subset):
total_mass = subset.total_mass() + m
cmpos=(m*pos + subset.total_mass()*subset.center_of_mass())/total_mass
cmvel=(m*vel + subset.total_mass()*subset.center_of_mass_velocity())/total_mass
L=Lin+angular_momentum(m,pos-cmpos,vel-cmvel)+angular_momentum(subset.mass,subset.position-cmpos,subset.velocity-cmvel).sum(axis=0)
corrected_masses.append(total_mass)
corrected_positions.append(cmpos)
corrected_velocities.append(cmvel)
corrected_angular_momenta.append(L)
else:
corrected_masses.append(m)
corrected_positions.append(pos)
corrected_velocities.append(vel)
corrected_angular_momenta.append(Lin)
self.mass = corrected_masses
self.position = corrected_positions
self.velocity = corrected_velocities
self.angular_momentum = corrected_angular_momenta
def main():
dots = Dots()
line = Line()
f = h5py.File(args.filename, 'r')
fig = plt.figure()
ax1 = fig.add_subplot(211)
ax2 = fig.add_subplot(212)
for intr in f.values():
etas = []
final_smas_p0_vq = AdaptingVectorQuantity()
final_smas_p1_vq = AdaptingVectorQuantity()
for sim in intr.values():
etas.append(sim['eta'][0])
final_smas_p0_vq.append(sim['p0/sma'][-1]| retrieve_unit(sim['p0/sma']))
final_smas_p1_vq.append(sim['p1/sma'][-1]| retrieve_unit(sim['p1/sma']))
final_smas_p0 = final_smas_p0_vq.value_in(units.AU)
final_smas_p1 = final_smas_p1_vq.value_in(units.AU)
ax1.plot(etas, final_smas_p0, marker='o', label=intr.name, picker=5)
ax2.plot(etas, final_smas_p1, marker='o', label=intr.name, picker=5)
ax1.set_xlabel('eta')
ax2.set_xlabel('eta')
ax1.set_ylabel('final sma inner [AU]')
ax2.set_ylabel('final sma outer [AU]')
dset = f.values()[0].values()[0] #first dset available
time = quantify_dset(dset['time']).value_in(units.yr)
mass = quantify_dset(dset['mass']).value_in(units.MSun)
inner_sma0 = quantify_dset(dset['p0/sma']).value_in(units.AU)
outer_sma0 = quantify_dset(dset['p1/sma']).value_in(units.AU)
inner_sma_final_adiabatic_approx = sma_analytical(inner_sma0[0], 1.244e-5, time[-1], mass[0].sum() )
outer_sma_final_adiabatic_approx = sma_analytical(outer_sma0[0], 1.244e-5, time[-1], mass[0].sum() )
ax1.axhline(inner_sma_final_adiabatic_approx, xmin=0, xmax=1, c='m', label='adiabatic approx')
ax1.legend(loc='best')
ax2.axhline(outer_sma_final_adiabatic_approx, xmin=0, xmax=1, c='m', label='adiabatic approx')
ax2.legend(loc='best')
if args.logscale:
ax1.set_xscale('log')
ax2.set_xscale('log')
if args.ylim1:
ax1.set_ylim(args.ylim1)
if args.ylim2:
ax2.set_ylim(args.ylim2)
if args.xlim1:
ax1.set_xlim(args.xlim1)
if args.xlim2:
ax2.set_xlim(args.xlim2)
def onpick(event):
print("artist:{} ind:{}".format(event.artist, event.ind))
print("button: {}".format(event.mouseevent.button))
intr = f[event.artist.get_label()]
sim = intr.values()[event.ind]
time_vq = quantify_dset(sim['time'])
time = time_vq.value_in(units.yr)
position_vq = quantify_dset(sim['position'])
position = position_vq.value_in(units.AU)
CM_position_vq = quantify_dset(sim['CM_position'])
CM_position = CM_position_vq.value_in(units.AU)
x, y = 0, 1
central_x, central_y = position[:, 0, x] - CM_position[:,x], position[:, 0, y] - CM_position[:,y]
inner_x, inner_y = position[:, 1, x] - CM_position[:,x], position[:, 1, y] - CM_position[:,y]
outer_x, outer_y = position[:, 2, x] - CM_position[:,x], position[:, 2, y] - CM_position[:,y]
mass_vq = quantify_dset(sim['mass'])
mass = mass_vq[:,0].value_in(units.MSun)
if event.mouseevent.button == 1:
mu0 = quantify_dset(sim['mass'])[0].sum()
period_vq = quantify_dset(sim['p0/period'])
period = period_vq.value_in(units.yr)
true_anomaly = sim['p0/true_anomaly'].value
argument_of_periapsis = sim['p0/argument_of_periapsis'].value
sma_vq = quantify_dset(sim['p0/sma'])
sma = sma_vq.value_in(units.AU)
sma_an_vq = sma_analytical(sma_vq[0], 1.244e-5|(units.MSun/units.yr), time_vq, mu0)
sma_an = sma_an_vq.value_in(units.AU)
eccentricity = sim['p0/eccentricity'].value
newfig = plt.figure()
newax1 = newfig.add_subplot(511)
newax2 = newfig.add_subplot(512)
newax3 = newfig.add_subplot(513)
newax4 = newfig.add_subplot(514)
newax5 = newfig.add_subplot(515)
newax1.plot(time, sma, label='numerical')
newax1.plot(time, sma_an, label='analytical_adiabatic')
newax1.set_xlabel('time [yr]')
newax1.set_ylabel('sma [AU]')
newax1.legend(loc='best')
newax2.plot(time, eccentricity)
newax2.set_xlabel('time [yr]')
newax2.set_ylabel('eccentricity ')
newax3.plot(time, true_anomaly)
newax3.set_xlabel('time [yr]')
newax3.set_ylabel('true anomaly [degrees] ')
newax4.plot(time, argument_of_periapsis)
newax4.set_xlabel('time [yr]')
newax4.set_ylabel('argument of periapsis [degrees] ')
newax5.plot(time, period)
newax5.set_xlabel('time [yr]')
newax5.set_ylabel('period')
else:
newfig = plt.figure()
newax1 = newfig.add_subplot(321)
newax2 = newfig.add_subplot(322)
newax3 = newfig.add_subplot(323)
newax4 = newfig.add_subplot(324)
newax5 = newfig.add_subplot(325)
newax6 = newfig.add_subplot(326)
mass_vq = quantify_dset(sim['mass'])
mass = mass_vq.value_in(units.MSun)
kinetic_energy = sim['kinetic_energy'].value
potential_energy = sim['potential_energy'].value
total_energy = sim['total_energy'].value
CM_velocity_vq = quantify_dset(sim['CM_velocity'])
CM_velocity_mod = CM_velocity_vq.lengths().value_in(units.km/units.hour)
walltime = sim['walltime'].value - sim['walltime'][0]
newax1.plot(time, mass)
newax1.set_ylabel('central mass [MSun]')
newax1.set_xlabel('time [yr]')
newax2.plot(time, kinetic_energy, label='kinetic', **line.red)
newax2.plot(time, potential_energy,label='potential', **line.orange)
newax2.plot(time, total_energy, label='total', **line.white)
newax2.set_xlabel('time [yr]')
newax2.legend()
newax3.plot(central_x, central_y, **dots.white)
newax3.plot(inner_x, inner_y, **dots.red)
newax3.plot(outer_x, outer_y, **dots.yellow)
newax3.set_xlabel('x [AU]')
newax3.set_ylabel('y [AU]')
newax4.plot(CM_position[:, x], CM_position[:, y] )
newax4.set_xlim(-5, 5)
newax4.set_xlabel('CM position x [AU]')
newax4.set_ylabel('CM position y [AU]')
newax5.plot(time, CM_velocity_mod)
newax5.set_ylim(20, 30)
newax5.set_xlabel('time [yr]')
newax5.set_ylabel('CM velocity [km/hour]')
newax6.plot(time, walltime)
newax6.set_xlabel('time [yr]')
newax6.set_ylabel('walltime [s]')
newfig.show()
fig.canvas.mpl_connect('pick_event', onpick)
plt.show()
def test_run():
three=binary_with_planet(
m1=0.6897 | units.MSun,m2=0.20255 | units.MSun,m_planet=0.333 | units.MJupiter,
r1=0.6489 | units.RSun,r2=0.22623 | units.RSun,r_planet=0.754 | units.RJupiter,
ecc_binary=0.15944,P_binary=41.08| units.day,ecc_planet=0.00685,a_planet=.7048 | units.AU,
pangle_planet=0.)
convert=nbody_system.nbody_to_si(1|units.MSun,1|units.AU)
code=Huayno(convert)
code.parameters.inttype_parameter=code.inttypes.SHARED4
code.parameters.timestep_parameter=0.1
# tend=100. | units.yr
tend=100. | units.day
snapfreq=1
dt=10. | units.day
# dt=convert.to_si( 1. | nbody_system.time).in_(units.day)
code.particles.add_particles(three)
x = AdaptingVectorQuantity()
y = AdaptingVectorQuantity()
z = AdaptingVectorQuantity()
vx = AdaptingVectorQuantity()
vy = AdaptingVectorQuantity()
vz = AdaptingVectorQuantity()
x.append(code.particles.x)
y.append(code.particles.y)
z.append(code.particles.z)
vx.append(code.particles.vx)
vy.append(code.particles.vy)
vz.append(code.particles.vz)
ts=[0.]
E0=code.potential_energy+code.kinetic_energy
dE=[1.e-14]
t=0. | units.day
i=0
while(t < tend-dt/2):
i+=1
t=t+dt
if i%snapfreq==0:
print t
ts.append(t.value_in(units.day))
code.evolve_model(t)
x.append(code.particles.x)
y.append(code.particles.y)
z.append(code.particles.z)
vx.append(code.particles.vx)
vy.append(code.particles.vy)
vz.append(code.particles.vz)
E=code.potential_energy+code.kinetic_energy
dE.append(abs(((E-E0)/E0)))
code.stop()
a,eps,pangle=elements(three.total_mass(),
x[:,2],
y[:,2],
z[:,2],
vx[:,2],
vy[:,2],
vz[:,2])
x=x.value_in(units.AU)
y=y.value_in(units.AU)
a=a.value_in(units.AU)
eps=eps
print a[-1],eps[-1],pangle[-1]
f=pyplot.figure(figsize=(8,8))
pyplot.plot(x[:,0],y[:,0],'r.')
pyplot.plot(x[:,1],y[:,1],'g.')
pyplot.plot(x[:,2],y[:,2],'b.')
pyplot.xlim(-3,3)
pyplot.ylim(-3,3)
pyplot.xlabel('AU')
pyplot.savefig('three_16b.eps')
f=pyplot.figure(figsize=(8,8))
pyplot.semilogy(ts,dE,'g.')
pyplot.xlabel('time (day)')
pyplot.ylabel('dE/E0')
pyplot.savefig('three_16b_eerr.eps')
f=pyplot.figure(figsize=(8,8))
pyplot.plot(ts,a,'g.')
pyplot.xlabel('time (day)')
pyplot.ylabel('a (AU)')
pyplot.savefig('three_16b_a.eps')
f=pyplot.figure(figsize=(8,8))
pyplot.plot(ts,eps,'g.')
pyplot.xlabel('time (day)')
pyplot.ylabel('eccentricity')
pyplot.savefig('three_16b_ecc.eps')
f=pyplot.figure(figsize=(8,8))
pyplot.plot(ts,pangle,'g.')
pyplot.xlabel('time (day)')
pyplot.ylabel('long. of periapsis')
pyplot.savefig('three_16b_pangle.eps')
print "doing statistics"
sorted_times = data[-1].sorted()
t = 0 | nbody_system.time
tend = 1000 | nbody_system.time
dt = 1 | nbody_system.time
while t < tend:
i = 0
while i < len(sorted_times):
tn = sorted_times[i]
i += 1
if tn < t:
continue
else:
break
times.append(t)
counts.append((len(sorted_times) - i) | units.none)
t += dt
output = text.CsvFileText(
filename="triple_statistics_{0:03}.csv".format(rank))
output.quantities = (times, counts)
output.attribute_names = ("t", "n(t)")
output.store()
print "done"
"""
set logscale xy
"""
def evolve_gravity(bodies, number_of_planets, converter, t_end, n_steps, n_snapshots, bodies_filename):
#Particles that will be saved in the file
bodies_to_save = Particles(number_of_planets+2)
#Positions and velocities centered on the center of mass
bodies.move_to_center()
time = 0. | nbody_system.time
dt = t_end / float(n_steps)
dt_snapshots = t_end / float(n_snapshots)
gravity = initialize_code(bodies, timestep_parameter = dt.value_in(nbody_system.time))
channel_from_gr_to_framework = gravity.particles.new_channel_to(bodies)
x = AdaptingVectorQuantity()
y = AdaptingVectorQuantity()
times = AdaptingVectorQuantity()
system_energies = AdaptingVectorQuantity()
E_initial = gravity.kinetic_energy + gravity.potential_energy
DeltaE_max = 0.0 | nbody_system.energy
while time<=t_end:
gravity.evolve_model(time)
channel_from_gr_to_framework.copy()
bodies.collection_attributes.timestamp = time
gravity.particles.collection_attributes.timestamp = time
x.append(bodies.x)
y.append(bodies.y)
times.append(time)
star = bodies[0]
ffp = bodies[1]
bp = bodies[2]
#Orbital elements for star and bounded_planet
binary = [star, bp]
m1, m2, sma, e, ta, i, lan, ap = orbital_elements_from_binary(binary)
bodies[2].eccentricity = e
bodies[2].semimajoraxis = sma
#Orbital elements for star+bp and ffp
cm_x = (star.mass*star.x + bp.mass*bp.x)/(star.mass+bp.mass)
cm_y = (star.mass*star.y + bp.mass*bp.y)/(star.mass+bp.mass)
cm_vx = (star.mass*star.vx + bp.mass*bp.vx)/(star.mass+bp.mass)
cm_vy = (star.mass*star.vy + bp.mass*bp.vy)/(star.mass+bp.mass)
star_bp = Particles(1)
star_bp.mass = star.mass + bp.mass
star_bp.position = [cm_x, cm_y, 0.0 | units.AU]
star_bp.velocity = [cm_vx, cm_vy, 0.0 | units.kms]
binary = [star_bp, ffp]
m1, m2, sma, e, ta, i, lan, ap = orbital_elements_from_binary(binary)
bodies[1].eccentricity = e
bodies[1].semimajoraxis = sma
print star.mass, bp.mass, ffp.mass
print m1, m2
E = gravity.kinetic_energy + gravity.potential_energy
system_energies.append(E)
DeltaE = abs(E-E_initial)
if ( DeltaE > DeltaE_max ):
DeltaE_max = DeltaE
save_particles_to_file(bodies, bodies_to_save, bodies_filename, time, converter)
time += dt_snapshots
max_energy_change = DeltaE_max/E_initial
gravity.stop()
return x,y,times,system_energies,max_energy_change
def test_run():
three = binary_with_planet(m1=0.6897 | units.MSun,
m2=0.20255 | units.MSun,
m_planet=0.333 | units.MJupiter,
r1=0.6489 | units.RSun,
r2=0.22623 | units.RSun,
r_planet=0.754 | units.RJupiter,
ecc_binary=0.15944,
P_binary=41.08 | units.day,
ecc_planet=0.00685,
a_planet=.7048 | units.AU,
pangle_planet=0.)
convert = nbody_system.nbody_to_si(1 | units.MSun, 1 | units.AU)
code = Huayno(convert)
code.parameters.inttype_parameter = code.inttypes.SHARED4
code.parameters.timestep_parameter = 0.1
# tend=100. | units.yr
tend = 100. | units.day
snapfreq = 1
dt = 10. | units.day
# dt=convert.to_si( 1. | nbody_system.time).in_(units.day)
code.particles.add_particles(three)
x = AdaptingVectorQuantity()
y = AdaptingVectorQuantity()
z = AdaptingVectorQuantity()
vx = AdaptingVectorQuantity()
vy = AdaptingVectorQuantity()
vz = AdaptingVectorQuantity()
x.append(code.particles.x)
y.append(code.particles.y)
z.append(code.particles.z)
vx.append(code.particles.vx)
vy.append(code.particles.vy)
vz.append(code.particles.vz)
ts = [0.]
E0 = code.potential_energy + code.kinetic_energy
dE = [1.e-14]
t = 0. | units.day
i = 0
while (t < tend - dt / 2):
i += 1
t = t + dt
if i % snapfreq == 0:
print t
ts.append(t.value_in(units.day))
code.evolve_model(t)
x.append(code.particles.x)
y.append(code.particles.y)
z.append(code.particles.z)
vx.append(code.particles.vx)
vy.append(code.particles.vy)
vz.append(code.particles.vz)
E = code.potential_energy + code.kinetic_energy
dE.append(abs(((E - E0) / E0)))
code.stop()
a, eps, pangle = elements(three.total_mass(), x[:, 2], y[:, 2], z[:, 2],
vx[:, 2], vy[:, 2], vz[:, 2])
x = x.value_in(units.AU)
y = y.value_in(units.AU)
a = a.value_in(units.AU)
eps = eps
print a[-1], eps[-1], pangle[-1]
f = pyplot.figure(figsize=(8, 8))
pyplot.plot(x[:, 0], y[:, 0], 'r.')
pyplot.plot(x[:, 1], y[:, 1], 'g.')
pyplot.plot(x[:, 2], y[:, 2], 'b.')
pyplot.xlim(-3, 3)
pyplot.ylim(-3, 3)
pyplot.xlabel('AU')
pyplot.savefig('three_16b.eps')
f = pyplot.figure(figsize=(8, 8))
pyplot.semilogy(ts, dE, 'g.')
pyplot.xlabel('time (day)')
pyplot.ylabel('dE/E0')
pyplot.savefig('three_16b_eerr.eps')
f = pyplot.figure(figsize=(8, 8))
pyplot.plot(ts, a, 'g.')
pyplot.xlabel('time (day)')
pyplot.ylabel('a (AU)')
pyplot.savefig('three_16b_a.eps')
f = pyplot.figure(figsize=(8, 8))
pyplot.plot(ts, eps, 'g.')
pyplot.xlabel('time (day)')
pyplot.ylabel('eccentricity')
pyplot.savefig('three_16b_ecc.eps')
f = pyplot.figure(figsize=(8, 8))
pyplot.plot(ts, pangle, 'g.')
pyplot.xlabel('time (day)')
pyplot.ylabel('long. of periapsis')
pyplot.savefig('three_16b_pangle.eps')
