def planetplot():
sun, planets = new_solar_system_for_mercury()
timerange = units.day(numpy.arange(0, 120 * 365.25, 12))
instance = MercuryWayWard()
instance.initialize_code()
instance.central_particle.add_particles(sun)
instance.orbiters.add_particles(planets)
instance.commit_particles()
channels = instance.orbiters.new_channel_to(planets)
for time in timerange:
err = instance.evolve_model(time)
channels.copy()
planets.savepoint(time)
instance.stop()
for planet in planets:
t, x = planet.get_timeline_of_attribute_as_vector("x")
t, y = planet.get_timeline_of_attribute_as_vector("y")
plot(x, y, '.')
native_plot.show()
def planetplot():
sun, planets = new_solar_system_for_mercury()
timerange = units.day(numpy.arange(0, 120 * 365.25, 12))
instance = MercuryWayWard()
instance.initialize_code()
instance.central_particle.add_particles(sun)
instance.orbiters.add_particles(planets)
instance.commit_particles()
channels = instance.orbiters.new_channel_to(planets)
for time in timerange:
err = instance.evolve_model(time)
channels.copy()
planets.savepoint(time)
instance.stop()
for planet in planets:
t, x = planet.get_timeline_of_attribute_as_vector("x")
t, y = planet.get_timeline_of_attribute_as_vector("y")
plot(x, y, '.')
native_plot.show()
def monitor_density_profile(system, i_step, time, n_steps, memory=Memory()):
if i_step == 0:
memory.xlimits = (None, None)
memory.ylimits = (None, None)
position = system.gas_particles.position - system.gas_particles.center_of_mass()
loglog(position.lengths_squared(), system.gas_particles.density, 'gs')
native_plot.title("{0}: t={1}".format(i_step, time.as_quantity_in(units.yr)))
native_plot.xlim(memory.xlimits)
native_plot.ylim(memory.ylimits)
native_plot.pause(0.0001)
memory.xlimits = native_plot.gca().get_xlim()
memory.ylimits = native_plot.gca().get_ylim()
if i_step == n_steps-1:
native_plot.show(block=True)
native_plot.cla()
def planetplot():
sun, planets = new_solar_system_for_mercury()
initial = 12.2138 | units.Gyr
final = 12.3300 | units.Gyr
step = 10000.0 | units.yr
timerange = VectorQuantity.arange(initial, final, step)
gd = MercuryWayWard()
gd.initialize_code()
# gd.stopping_conditions.timeout_detection.disable()
gd.central_particle.add_particles(sun)
gd.orbiters.add_particles(planets)
gd.commit_particles()
se = SSE()
# se.initialize_code()
se.commit_parameters()
se.particles.add_particles(sun)
se.commit_particles()
channelp = gd.orbiters.new_channel_to(planets)
channels = se.particles.new_channel_to(sun)
for time in timerange:
err = gd.evolve_model(time-initial)
channelp.copy()
# planets.savepoint(time)
err = se.evolve_model(time)
channels.copy()
gd.central_particle.mass = sun.mass
print(
sun[0].mass.value_in(units.MSun),
time.value_in(units.Myr),
planets[4].x.value_in(units.AU),
planets[4].y.value_in(units.AU),
planets[4].z.value_in(units.AU)
)
gd.stop()
se.stop()
for planet in planets:
t, x = planet.get_timeline_of_attribute_as_vector("x")
t, y = planet.get_timeline_of_attribute_as_vector("y")
plot(x, y, '.')
native_plot.gca().set_aspect('equal')
native_plot.show()
def polyevolve():
sun, planets = Solarsystem.new_solarsystem()
gd, se = setup_codes(sun, planets)
channelp = gd.orbiters.new_channel_to(planets)
channels = se.particles.new_channel_to(sun)
prev_mass = sun[0].mass
massrange = units.MSun(numpy.arange(0.9, 0.89999, -1e-9))
masses = [] | units.MSun
timerange = [] | units.Myr
for i, mass in enumerate(massrange):
time, dummymass = se.evolve_mass(mass)
if i == 0:
initialtime = time
print(time, mass, "evolving gd")
gdtime = time - initialtime
print(gdtime)
err = gd.evolve_model(gdtime)
channelp.copy()
planets.savepoint(time)
channels.copy()
gd.central_particle.mass = sun[0].mass
print(sun[0].mass)
print(
sun[0].mass.value_in(units.MSun),
time.value_in(units.Myr),
planets[4].x.value_in(units.AU),
planets[4].y.value_in(units.AU),
planets[4].z.value_in(units.AU),
)
gd.stop()
se.stop()
for planet in planets:
t, x = planet.get_timeline_of_attribute_as_vector("x")
t, y = planet.get_timeline_of_attribute_as_vector("y")
t, z = planet.get_timeline_of_attribute_as_vector("z")
plot3(x, y, z, '.')
native_plot.gca().set_aspect('equal')
native_plot.show()
def polyevolve():
sun, planets = Solarsystem.new_solarsystem()
gd, se = setup_codes(sun, planets)
channelp = gd.orbiters.new_channel_to(planets)
channels = se.particles.new_channel_to(sun)
prev_mass = sun[0].mass
massrange = units.MSun(numpy.arange(0.9, 0.89999, -1e-9))
masses = [] | units.MSun
timerange = [] | units.Myr
for i, mass in enumerate(massrange):
time, dummymass = se.evolve_mass(mass)
if i == 0:
initialtime = time
print time, mass, "evolving gd"
gdtime = time-initialtime
print gdtime
err = gd.evolve_model(gdtime)
channelp.copy()
planets.savepoint(time)
channels.copy()
gd.central_particle.mass = sun[0].mass
print sun[0].mass
print(
sun[0].mass.value_in(units.MSun),
time.value_in(units.Myr),
planets[4].x.value_in(units.AU),
planets[4].y.value_in(units.AU),
planets[4].z.value_in(units.AU),
)
gd.stop()
se.stop()
for planet in planets:
t, x = planet.get_timeline_of_attribute_as_vector("x")
t, y = planet.get_timeline_of_attribute_as_vector("y")
t, z = planet.get_timeline_of_attribute_as_vector("z")
plot3(x, y, z, '.')
native_plot.gca().set_aspect('equal')
native_plot.show()
def monitor_density_profile(system, i_step, time, n_steps, memory=Memory()):
if i_step == 0:
memory.xlimits = (None, None)
memory.ylimits = (None, None)
position = system.gas_particles.position - system.gas_particles.center_of_mass(
)
loglog(position.lengths_squared(), system.gas_particles.density, 'gs')
native_plot.title("{0}: t={1}".format(i_step,
time.as_quantity_in(units.yr)))
native_plot.xlim(memory.xlimits)
native_plot.ylim(memory.ylimits)
native_plot.pause(0.0001)
memory.xlimits = native_plot.gca().get_xlim()
memory.ylimits = native_plot.gca().get_ylim()
if i_step == n_steps - 1:
native_plot.show(block=True)
native_plot.cla()
def planetplot():
sun, planets = new_solar_system_for_mercury()
initial = 12.2138 | units.Gyr
final = 12.3300 | units.Gyr
step = 10000.0 | units.yr
timerange = VectorQuantity.arange(initial, final, step)
gd = MercuryWayWard()
gd.initialize_code()
# gd.stopping_conditions.timeout_detection.disable()
gd.central_particle.add_particles(sun)
gd.orbiters.add_particles(planets)
gd.commit_particles()
se = SSE()
# se.initialize_code()
se.commit_parameters()
se.particles.add_particles(sun)
se.commit_particles()
channelp = gd.orbiters.new_channel_to(planets)
channels = se.particles.new_channel_to(sun)
for time in timerange:
err = gd.evolve_model(time - initial)
channelp.copy()
# planets.savepoint(time)
err = se.evolve_model(time)
channels.copy()
gd.central_particle.mass = sun.mass
print(
(sun[0].mass.value_in(units.MSun), time.value_in(units.Myr),
planets[4].x.value_in(units.AU), planets[4].y.value_in(units.AU),
planets[4].z.value_in(units.AU)))
gd.stop()
se.stop()
for planet in planets:
t, x = planet.get_timeline_of_attribute_as_vector("x")
t, y = planet.get_timeline_of_attribute_as_vector("y")
plot(x, y, '.')
native_plot.gca().set_aspect('equal')
native_plot.show()
def testsse():
sse = SSEWithMassEvolve()
sse.commit_parameters()
sun, planets = new_solar_system_for_mercury()
sse.particles.add_particles(sun)
sse.commit_particles()
channel = sse.particles.new_channel_to(sun)
channel.copy()
massrange = units.MSun(numpy.arange(1, 0.8, -0.001))
masses = [] | units.MSun
timerange = [] | units.Myr
for mass in massrange:
sse.evolve_mass(mass)
t, m = sse.evolve_mass(mass)
timerange.append(t)
channel.copy()
masses.append(sse.particles[0].mass)
sse.stop()
plot(massrange, timerange, '.')
native_plot.show()
def testsse():
sse = SSEWithMassEvolve()
sse.commit_parameters()
sun, planets = new_solar_system_for_mercury()
sse.particles.add_particles(sun)
sse.commit_particles()
channel = sse.particles.new_channel_to(sun)
channel.copy()
massrange = units.MSun(numpy.arange(1, 0.8, -0.001))
masses = [] | units.MSun
timerange = [] | units.Myr
for mass in massrange:
sse.evolve_mass(mass)
t, m = sse.evolve_mass(mass)
timerange.append(t)
channel.copy()
masses.append(sse.particles[0].mass)
sse.stop()
plot(massrange, timerange, '.')
native_plot.show()
y1 = quantities.new_quantity(
np.sin(np.arange(0, 1.5, 0.03)), 1e50*units.erg)
y2 = -(1e43 | units.J) - y1
native_plot.subplot(2, 2, 2)
plot(x, y1, label='$E_\mathrm{kin}$')
plot(x, y2, label='$E_\mathrm{pot}$')
xlabel('t')
ylabel('E')
native_plot.legend()
x = range(7) | units.day
y1 = [0, 4, 2, 3, 2, 5, 1]
y2 = [3, 0, 2, 2, 3, 0, 4]
native_plot.subplot(2, 2, 3)
plot(x, y1, 'ks', label='coffee')
plot(x, y2, 'yo', label='tea')
xlabel('time')
ylabel('consumption / day')
native_plot.legend()
y1 = units.N.new_quantity(np.random.normal(0.0, 1.0, 100))
x = units.N.new_quantity(np.arange(-3, 3, 0.1))
y2 = np.exp(-np.arange(-3, 3, 0.1)**2)/np.sqrt(np.pi)
native_plot.subplot(2, 2, 4)
plot(x, y2, 'y--', label='model')
hist(y1, bins=12, range=(-3, 3), normed=True, label='data')
xlabel('force')
ylabel('pdf')
native_plot.legend()
native_plot.show()
def test4(self):
random.seed(1001)
print "Test 4: complicated density field."
# A separate group below peak_density_threshold -> should be dropped
particles0 = new_plummer_model(90,
convert_nbody=nbody_system.nbody_to_si(
0.9 | units.MSun, 1.0 | units.RSun))
# A nearby group below peak_density_threshold -> should be attached to proper group
particles1 = new_plummer_model(80,
convert_nbody=nbody_system.nbody_to_si(
0.8 | units.MSun, 1.0 | units.RSun))
particles1.x += 10 | units.RSun
# A proper group very nearby other proper group -> groups should merge
particles2a = new_plummer_model(200,
convert_nbody=nbody_system.nbody_to_si(
2.0 | units.MSun,
1.0 | units.RSun))
particles2b = new_plummer_model(300,
convert_nbody=nbody_system.nbody_to_si(
3.0 | units.MSun,
1.0 | units.RSun))
particles2a.x += 11.0 | units.RSun
particles2b.x += 11.2 | units.RSun
# A separate proper group other proper group -> groups should be preserved
particles3 = new_plummer_model(400,
convert_nbody=nbody_system.nbody_to_si(
4.0 | units.MSun, 1.0 | units.RSun))
particles3.x += 20 | units.RSun
hop = Hop(
unit_converter=nbody_system.nbody_to_si(10.7 | units.MSun, 1.0
| units.RSun))
hop.parameters.number_of_neighbors_for_local_density = 100
hop.parameters.saddle_density_threshold_factor = 0.5
hop.parameters.relative_saddle_density_threshold = True
hop.commit_parameters()
for set in [
particles0, particles1, particles2a, particles2b, particles3
]:
hop.particles.add_particles(set)
hop.calculate_densities()
hop.parameters.outer_density_threshold = 0.1 * hop.particles.density.mean(
)
hop.parameters.peak_density_threshold = hop.particles.density.amax(
) / 4.0
hop.recommit_parameters()
hop.do_hop()
groups = list(hop.groups())
self.assertEquals(len(hop.particles), 1070)
self.assertEquals(len(groups), 2)
self.assertEquals(
hop.particles.select(lambda x: x < 5 | units.RSun, "x").group_id,
-1)
self.assertEquals(hop.get_number_of_particles_outside_groups(), 299)
self.assertEquals(1070 - len(groups[0]) - len(groups[1]), 299)
expected_size = [
477, 294
] # Less than [580, 400], because particles below outer_density_threshold are excluded
expected_average_x = [11.0, 20] | units.RSun
for index, group in enumerate(groups):
self.assertEquals(group.id_of_group(), index)
self.assertAlmostEquals(group.center_of_mass()[0],
expected_average_x[index], 1)
self.assertEquals(len(group), expected_size[index])
if False: # Make a plot
original = hop.particles.copy()
from amuse.plot import scatter, native_plot
colors = ["r", "g", "b", "y", "k", "w"] * 100
for group, color in zip(hop.groups(), colors):
scatter(group.x, group.y, c=color)
original -= group
scatter(original.x, original.y, c="m", marker="s")
native_plot.show()
hop.stop()
instance.particles.add_particles(particles)
channelp = instance.particles.new_channel_to(particles)
start = 0 | units.yr
end = 150 | units.yr
step = 10 | units.day
timerange = VectorQuantity.arange(start, end, step)
masses = [] | units.MSun
for i, time in enumerate(timerange):
instance.evolve_model(time)
channelp.copy()
particles.savepoint(time)
if (i % 220 == 0):
instance.particles[0].mass = simulate_massloss(time)
masses.append(instance.particles[0].mass)
instance.stop()
particle = particles[1]
t, pos = particle.get_timeline_of_attribute_as_vector("position")
distances = pos.lengths().as_quantity_in(units.AU)
plot(timerange, distances, timerange, masses)
native_plot.show()
def test4(self):
random.seed(1001)
print "Test 4: complicated density field."
# A separate group below peak_density_threshold -> should be dropped
particles0 = new_plummer_model(90, convert_nbody=nbody_system.nbody_to_si(0.9 | units.MSun, 1.0 | units.RSun))
# A nearby group below peak_density_threshold -> should be attached to proper group
particles1 = new_plummer_model(80, convert_nbody=nbody_system.nbody_to_si(0.8 | units.MSun, 1.0 | units.RSun))
particles1.x += 10 | units.RSun
# A proper group very nearby other proper group -> groups should merge
particles2a = new_plummer_model(200, convert_nbody=nbody_system.nbody_to_si(2.0 | units.MSun, 1.0 | units.RSun))
particles2b = new_plummer_model(300, convert_nbody=nbody_system.nbody_to_si(3.0 | units.MSun, 1.0 | units.RSun))
particles2a.x += 11.0 | units.RSun
particles2b.x += 11.2 | units.RSun
# A separate proper group other proper group -> groups should be preserved
particles3 = new_plummer_model(400, convert_nbody=nbody_system.nbody_to_si(4.0 | units.MSun, 1.0 | units.RSun))
particles3.x += 20 | units.RSun
hop = Hop(unit_converter=nbody_system.nbody_to_si(10.7 | units.MSun, 1.0 | units.RSun))
hop.parameters.number_of_neighbors_for_local_density = 100
hop.parameters.saddle_density_threshold_factor = 0.5
hop.parameters.relative_saddle_density_threshold = True
hop.commit_parameters()
for set in [particles0, particles1, particles2a, particles2b, particles3]:
hop.particles.add_particles(set)
hop.calculate_densities()
hop.parameters.outer_density_threshold = 0.1 * hop.particles.density.mean()
hop.parameters.peak_density_threshold = hop.particles.density.amax() / 4.0
hop.recommit_parameters()
hop.do_hop()
groups = list(hop.groups())
self.assertEquals(len(hop.particles), 1070)
self.assertEquals(len(groups), 2)
self.assertEquals(hop.particles.select(lambda x: x < 5|units.RSun, "x").group_id, -1)
self.assertEquals(hop.get_number_of_particles_outside_groups(), 299)
self.assertEquals(1070 - len(groups[0]) - len(groups[1]), 299)
expected_size = [477, 294] # Less than [580, 400], because particles below outer_density_threshold are excluded
expected_average_x = [11.0, 20] | units.RSun
for index, group in enumerate(groups):
self.assertEquals(group.id_of_group(), index)
self.assertAlmostEquals(group.center_of_mass()[0], expected_average_x[index], 1)
self.assertEquals(len(group), expected_size[index])
if False: # Make a plot
original = hop.particles.copy()
from amuse.plot import scatter, native_plot
colors = ["r", "g", "b", "y", "k", "w"]*100
for group, color in zip(hop.groups(), colors):
scatter(group.x, group.y, c=color)
original -= group
scatter(original.x, original.y, c="m", marker="s")
native_plot.show()
hop.stop()
