def test16(self):
particles = new_plummer_model(200)
particles.scale_to_standard()
instance = Hermite()
instance.initialize_code()
instance.parameters.epsilon_squared = 0.00000 | nbody_system.length**2
instance.particles.add_particles(particles)
x = numpy.arange(-1,1,0.1) | nbody_system.length
zero = numpy.zeros(len(x)) | nbody_system.length
potential0 = instance.get_potential_at_point(zero, x , zero, zero)
instance.stop()
for n in (2, 3, 4):
instance = Hermite(number_of_workers = n)
instance.initialize_code()
instance.parameters.epsilon_squared = 0.00000 | nbody_system.length**2
instance.particles.add_particles(particles)
potential = instance.get_potential_at_point(zero, x , zero, zero)
self.assertAlmostRelativeEquals(potential0, potential, 8)
instance.stop()
def test16(self):
particles = new_plummer_model(200)
particles.scale_to_standard()
instance = Hermite()
instance.initialize_code()
instance.parameters.epsilon_squared = 0.00000 | nbody_system.length**2
instance.particles.add_particles(particles)
x = numpy.arange(-1, 1, 0.1) | nbody_system.length
zero = numpy.zeros(len(x)) | nbody_system.length
potential0 = instance.get_potential_at_point(zero, x, zero, zero)
instance.stop()
for n in (2, 3, 4):
instance = Hermite(number_of_workers=n)
instance.initialize_code()
instance.parameters.epsilon_squared = 0.00000 | nbody_system.length**2
instance.particles.add_particles(particles)
potential = instance.get_potential_at_point(zero, x, zero, zero)
self.assertAlmostRelativeEquals(potential0, potential, 8)
instance.stop()
def test14(self):
instance = Hermite()
instance.initialize_code()
instance.parameters.epsilon_squared = 0.00001 | nbody_system.length**2
particles = datamodel.Particles(2)
particles.mass = [1.0, 1.0] | nbody_system.mass
particles.radius = [0.0001, 0.0001] | nbody_system.length
particles.position = [[0.0, 0.0, 0.0], [2.0, 0.0, 0.0]
] | nbody_system.length
particles.velocity = [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]
] | nbody_system.speed
instance.particles.add_particles(particles)
zero = 0.0 | nbody_system.length
fx, fy, fz = instance.get_gravity_at_point(zero,
1.0 | nbody_system.length,
zero, zero)
self.assertAlmostEqual(fx, 0.0 | nbody_system.acceleration, 6)
self.assertAlmostEqual(fy, 0.0 | nbody_system.acceleration, 6)
self.assertAlmostEqual(fz, 0.0 | nbody_system.acceleration, 6)
for x in (0.25, 0.5, 0.75):
x0 = x | nbody_system.length
x1 = (2.0 - x) | nbody_system.length
potential0 = instance.get_potential_at_point(zero, x0, zero, zero)
potential1 = instance.get_potential_at_point(zero, x1, zero, zero)
fx0, fy0, fz0 = instance.get_gravity_at_point(zero, x0, zero, zero)
fx1, fy1, fz1 = instance.get_gravity_at_point(zero, x1, zero, zero)
self.assertAlmostEqual(fy0, 0.0 | nbody_system.acceleration, 6)
self.assertAlmostEqual(fz0, 0.0 | nbody_system.acceleration, 6)
self.assertAlmostEqual(fy1, 0.0 | nbody_system.acceleration, 6)
self.assertAlmostEqual(fz1, 0.0 | nbody_system.acceleration, 6)
self.assertAlmostEqual(fx0, -1.0 * fx1, 5)
fx = (-1.0 / (x0**2) + 1.0 /
(x1**2)) * (1.0
| nbody_system.length**3 / nbody_system.time**2)
self.assertAlmostEqual(fx, fx0, 2)
self.assertAlmostEqual(potential0, potential1, 5)
instance.stop()
def test14(self):
instance = Hermite()
instance.initialize_code()
instance.parameters.epsilon_squared = 0.00001 | nbody_system.length**2
particles = datamodel.Particles(2)
particles.mass = [1.0, 1.0] | nbody_system.mass
particles.radius = [0.0001, 0.0001] | nbody_system.length
particles.position = [[0.0,0.0,0.0], [2.0,0.0,0.0]] | nbody_system.length
particles.velocity = [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]] | nbody_system.speed
instance.particles.add_particles(particles)
zero = 0.0 | nbody_system.length
fx, fy, fz = instance.get_gravity_at_point(zero, 1.0 | nbody_system.length, zero, zero)
self.assertAlmostEqual(fx, 0.0 | nbody_system.acceleration, 6)
self.assertAlmostEqual(fy, 0.0 | nbody_system.acceleration, 6)
self.assertAlmostEqual(fz, 0.0 | nbody_system.acceleration, 6)
for x in (0.25, 0.5, 0.75):
x0 = x | nbody_system.length
x1 = (2.0 - x) | nbody_system.length
potential0 = instance.get_potential_at_point(zero, x0, zero, zero)
potential1 = instance.get_potential_at_point(zero, x1, zero, zero)
fx0, fy0, fz0 = instance.get_gravity_at_point(zero, x0, zero, zero)
fx1, fy1, fz1 = instance.get_gravity_at_point(zero, x1, zero, zero)
self.assertAlmostEqual(fy0, 0.0 | nbody_system.acceleration, 6)
self.assertAlmostEqual(fz0, 0.0 | nbody_system.acceleration, 6)
self.assertAlmostEqual(fy1, 0.0 | nbody_system.acceleration, 6)
self.assertAlmostEqual(fz1, 0.0 | nbody_system.acceleration, 6)
self.assertAlmostEqual(fx0, -1.0 * fx1, 5)
fx = (-1.0 / (x0**2) + 1.0 / (x1**2)) * (1.0 | nbody_system.length ** 3 / nbody_system.time ** 2)
self.assertAlmostEqual(fx, fx0, 2)
self.assertAlmostEqual(potential0, potential1, 5)
instance.stop()
def hydro_grid_in_potential_well(mass=1 | units.MSun, length=100 | units.AU):
converter = nbody_system.nbody_to_si(mass, length)
# calculate density in field based on solar wind
# gives a very low number
molar_mass_hydrogen_proton = 1 | units.g / units.mol
density_hydrogen_in_stellar_wind = 10 | 1 / units.cm**3
particles_per_mol = 6.022e23 | 1 / units.mol
density_hydrogen_in_stellar_wind_in_moles = (
density_hydrogen_in_stellar_wind
/ particles_per_mol
)
density_gas = 100 * (
density_hydrogen_in_stellar_wind_in_moles
* molar_mass_hydrogen_proton
).as_quantity_in(units.MSun / units.AU**3)
# override with higher number for plotting
density_gas = 1e-3 | units.MSun / units.AU**3
instance = Athena(converter)
instance.initialize_code()
instance.parameters.nx = 50
instance.parameters.ny = 50
instance.parameters.nz = 1
instance.parameters.length_x = length
instance.parameters.length_y = length
instance.parameters.length_z = length
instance.parameters.x_boundary_conditions = ("periodic", "periodic")
instance.parameters.y_boundary_conditions = ("periodic", "periodic")
instance.parameters.z_boundary_conditions = ("outflow", "outflow")
# instance.stopping_conditions.number_of_steps_detection.enable()
instance.set_has_external_gravitational_potential(1)
instance.commit_parameters()
grid_in_memory = instance.grid.copy()
grid_in_memory.rho = density_gas
pressure = 1 | units.Pa
grid_in_memory.energy = pressure / (instance.parameters.gamma - 1)
channel = grid_in_memory.new_channel_to(instance.grid)
channel.copy()
instance.initialize_grid()
particle = Particle(
mass=mass,
position=length * [0.5, 0.5, 0.5],
velocity=[0.0, 0.0, 0.0] | units.kms
)
gravity = Hermite(converter)
dx = (grid_in_memory.x[1][0][0] - grid_in_memory.x[0]
[0][0]).as_quantity_in(units.AU)
gravity.parameters.epsilon_squared = dx**2
gravity.particles.add_particle(particle)
potential = gravity.get_potential_at_point(
0 * instance.potential_grid.x.flatten(),
instance.potential_grid.x.flatten(),
instance.potential_grid.y.flatten(),
instance.potential_grid.z.flatten()
)
potential = potential.reshape(instance.potential_grid.x.shape)
instance.potential_grid.potential = potential
instance.evolve_model(100 | units.yr)
print(instance.get_timestep().value_in(units.yr))
value_to_plot = instance.grid.rho[:, :, 0].value_in(
units.MSun / units.AU**3)
# value_to_plot = potential[...,...,0].value_in(potential.unit)
plot_grid(value_to_plot)
def hydro_grid_in_potential_well(mass=1 | units.MSun, length=100 | units.AU):
converter = nbody_system.nbody_to_si(mass, length)
# calculate density in field based on solar wind
# gives a very low number
molar_mass_hydrogen_proton = 1 | units.g / units.mol
density_hydrogen_in_stellar_wind = 10 | 1 / units.cm**3
particles_per_mol = 6.022e23 | 1 / units.mol
density_hydrogen_in_stellar_wind_in_moles = (
density_hydrogen_in_stellar_wind / particles_per_mol)
density_gas = 100 * (density_hydrogen_in_stellar_wind_in_moles *
molar_mass_hydrogen_proton).as_quantity_in(
units.MSun / units.AU**3)
# override with higher number for plotting
density_gas = 1e-3 | units.MSun / units.AU**3
instance = Athena(converter)
instance.initialize_code()
instance.parameters.nx = 50
instance.parameters.ny = 50
instance.parameters.nz = 1
instance.parameters.length_x = length
instance.parameters.length_y = length
instance.parameters.length_z = length
instance.parameters.x_boundary_conditions = ("periodic", "periodic")
instance.parameters.y_boundary_conditions = ("periodic", "periodic")
instance.parameters.z_boundary_conditions = ("outflow", "outflow")
# instance.stopping_conditions.number_of_steps_detection.enable()
instance.set_has_external_gravitational_potential(1)
instance.commit_parameters()
grid_in_memory = instance.grid.copy()
grid_in_memory.rho = density_gas
pressure = 1 | units.Pa
grid_in_memory.energy = pressure / (instance.parameters.gamma - 1)
channel = grid_in_memory.new_channel_to(instance.grid)
channel.copy()
instance.initialize_grid()
particle = Particle(mass=mass,
position=length * [0.5, 0.5, 0.5],
velocity=[0.0, 0.0, 0.0] | units.kms)
gravity = Hermite(converter)
dx = (grid_in_memory.x[1][0][0] -
grid_in_memory.x[0][0][0]).as_quantity_in(units.AU)
gravity.parameters.epsilon_squared = dx**2
gravity.particles.add_particle(particle)
potential = gravity.get_potential_at_point(
0 * instance.potential_grid.x.flatten(),
instance.potential_grid.x.flatten(),
instance.potential_grid.y.flatten(),
instance.potential_grid.z.flatten())
potential = potential.reshape(instance.potential_grid.x.shape)
instance.potential_grid.potential = potential
instance.evolve_model(100 | units.yr)
print(instance.get_timestep().value_in(units.yr))
value_to_plot = instance.grid.rho[:, :,
0].value_in(units.MSun / units.AU**3)
# value_to_plot = potential[...,...,0].value_in(potential.unit)
plot_grid(value_to_plot)
