from interface import NearestNeighbor
from amuse.units import units, nbody_system
from amuse.ext import plummer
from amuse.io import text
number_of_particles = 1000
mass_per_particle = 1 | units.MSun
convert_nbody = nbody_system.nbody_to_si(
number_of_particles * mass_per_particle, 1.0 | units.parsec)
uc = plummer.MakePlummerModel(number_of_particles, convert_nbody)
particles = uc.result
nn = NearestNeighbor()
nn.particles.add_particles(particles)
print "number of particles:", len(nn.particles)
nn.find_nearest_neighbors()
local_particles = nn.particles.copy()
for p in local_particles:
delta = p.neighbor1.position - p.position
p.distance_to_neighbor = delta.length()
p.dx = delta.x
p.dy = delta.y
p.dz = delta.z
output = text.TableFormattedText("output.txt", set=local_particles)
output.attribute_names = ['x', 'y', 'z', 'dx', 'dy', 'dz']
output.attribute_types = [units.parsec] * 6
from interface import NearestNeighbor
from amuse.lab import *
from amuse.io import text
if __name__ == '__main__':
number_of_particles = 1000
particles = new_plummer_sphere(1000)
code = NearestNeighbor()
code.particles.add_particles(particles)
code.run()
local_particles = code.particles.copy()
delta = local_particles.neighbor1.as_set().position - local_particles.position
local_particles.dx = delta[...,0]
local_particles.dy = delta[...,1]
local_particles.dz = delta[...,2]
output = text.TableFormattedText("output.txt", set = local_particles)
output.attribute_names = ['x','y','z', 'dx', 'dy','dz']
output.store()
from interface import NearestNeighbor
from amuse.lab import *
from amuse.io import text
if __name__ == '__main__':
number_of_particles = 1000
particles = new_plummer_sphere(1000)
code = NearestNeighbor()
code.set_maximum_number_of_particles(5000)
code.commit_parameters
code.particles.add_particles(particles)
code.run()
local_particles = code.particles.copy()
delta = local_particles.neighbor1.position - local_particles.position
local_particles.dx = delta[..., 0]
local_particles.dy = delta[..., 1]
local_particles.dz = delta[..., 2]
output = text.TableFormattedText("output.txt", set=local_particles)
output.attribute_names = ['x', 'y', 'z', 'dx', 'dy', 'dz']
output.store()
from interface import NearestNeighbor
from amuse.lab import *
from amuse.io import text
if __name__ == '__main__':
number_of_particles = 1000
particles = new_plummer_sphere(1000)
code = NearestNeighbor()
code.particles.add_particles(particles)
code.run()
local_particles = code.particles.copy()
delta = local_particles.neighbor1.as_set(
).position - local_particles.position
local_particles.dx = delta[..., 0]
local_particles.dy = delta[..., 1]
local_particles.dz = delta[..., 2]
output = text.TableFormattedText("output.txt", set=local_particles)
output.attribute_names = ['x', 'y', 'z', 'dx', 'dy', 'dz']
output.store()
from interface import NearestNeighbor
from amuse.lab import *
from amuse.io import text
if __name__ == '__main__':
number_of_particles = 1000
particles = new_plummer_sphere(1000)
code = NearestNeighbor()
code.set_maximum_number_of_particles(5000)
code.commit_parameters
code.particles.add_particles(particles)
code.run()
local_particles = code.particles.copy()
delta = local_particles.neighbor1.as_set().position - local_particles.position
local_particles.dx = delta[...,0]
local_particles.dy = delta[...,1]
local_particles.dz = delta[...,2]
output = text.TableFormattedText("output.txt", set = local_particles)
output.attribute_names = ['x','y','z', 'dx', 'dy','dz']
output.store()
from interface import NearestNeighbor
from amuse.units import units, nbody_system
from amuse.ext import plummer
from amuse.io import text
number_of_particles = 1000
mass_per_particle = 1 | units.MSun
convert_nbody = nbody_system.nbody_to_si(number_of_particles * mass_per_particle, 1.0 | units.parsec)
uc = plummer.MakePlummerModel(number_of_particles, convert_nbody)
particles = uc.result
nn = NearestNeighbor()
nn.particles.add_particles(particles)
print "number of particles:", len(nn.particles)
nn.find_nearest_neighbors()
local_particles = nn.particles.copy()
for p in local_particles:
delta = p.neighbor1.position - p.position
p.distance_to_neighbor = delta.length()
p.dx = delta.x
p.dy = delta.y
p.dz = delta.z
output = text.TableFormattedText("output.txt", set = local_particles)
output.attribute_names = ['x','y','z', 'dx', 'dy','dz']