def test8(self):
random.seed(1001)
print "Test 8: SI vs nbody units."
converter = nbody_system.nbody_to_si(1.0 | units.MSun, 1.0 | units.RSun)
numpy.random.seed(1234)
particles = new_plummer_model(1000, convert_nbody=converter)
hop = Hop(unit_converter=converter)
hop.particles.add_particles(particles)
hop.calculate_densities()
hop.parameters.outer_density_threshold = 0.1 | nbody_system.mass / nbody_system.length**3
hop.do_hop()
groups = list(hop.groups())
self.assertEquals(len(hop.particles), 1000)
self.assertEquals(len(groups), 1)
self.assertEquals(len(groups[0]), 511)
self.assertEquals(len(hop.no_group()), 489)
hop.stop()
numpy.random.seed(1234)
particles = new_plummer_model(1000)
hop = Hop()
hop.particles.add_particles(particles)
hop.calculate_densities()
hop.parameters.outer_density_threshold = 0.1 | nbody_system.mass / nbody_system.length**3
hop.do_hop()
groups = list(hop.groups())
self.assertEquals(len(hop.particles), 1000)
self.assertEquals(len(groups), 1)
self.assertEquals(len(groups[0]), 511)
self.assertEquals(len(hop.no_group()), 489)
hop.stop()
def test8(self):
random.seed(1001)
print "Test 8: SI vs nbody units."
converter = nbody_system.nbody_to_si(1.0 | units.MSun,
1.0 | units.RSun)
numpy.random.seed(1234)
particles = new_plummer_model(1000, convert_nbody=converter)
hop = Hop(unit_converter=converter)
hop.particles.add_particles(particles)
hop.calculate_densities()
hop.parameters.outer_density_threshold = 0.1 | nbody_system.mass / nbody_system.length**3
hop.do_hop()
groups = list(hop.groups())
self.assertEquals(len(hop.particles), 1000)
self.assertEquals(len(groups), 1)
self.assertEquals(len(groups[0]), 511)
self.assertEquals(len(hop.no_group()), 489)
hop.stop()
numpy.random.seed(1234)
particles = new_plummer_model(1000)
hop = Hop()
hop.particles.add_particles(particles)
hop.calculate_densities()
hop.parameters.outer_density_threshold = 0.1 | nbody_system.mass / nbody_system.length**3
hop.do_hop()
groups = list(hop.groups())
self.assertEquals(len(hop.particles), 1000)
self.assertEquals(len(groups), 1)
self.assertEquals(len(groups[0]), 511)
self.assertEquals(len(hop.no_group()), 489)
hop.stop()
def find_clusters(
stars,
convert_nbody=None,
scale_mass=1 | units.MSun,
scale_radius=1 | units.parsec,
mean_density=None,
):
if convert_nbody == None:
convert_nbody = nbody_system.nbody_to_si(scale_mass, scale_radius)
groupfinder = Hop(convert_nbody)
groupfinder.particles.add_particles(stars)
groupfinder.calculate_densities()
if mean_density is None:
mean_density = groupfinder.particles.density.mean()
groupfinder.parameters.peak_density_threshold = 10 * mean_density
groupfinder.parameters.saddle_density_threshold = 0.99 * mean_density
groupfinder.parameters.outer_density_threshold = 0.01 * mean_density
print("Mean density: %s" % mean_density)
groupfinder.do_hop()
result = [
x.get_intersecting_subset_in(stars) for x in groupfinder.groups()
]
groupfinder.stop()
return result
def test6(self):
print("Test with different masses")
# Particles on a cubic grid with masses according to a gaussian density profile
grid = numpy.mgrid[-1:1:21j, -1:1:21j, -1:1:21j] | units.m
particles = Particles(9261, x=grid[0].flatten(), y=grid[1].flatten(), z=grid[2].flatten())
peak_positions = [[0.2, -0.4, 0.3], [-0.6, 0.2, 0.7]] | units.m
particles.mass = 2*numpy.exp(-(particles.position-peak_positions[0]).lengths_squared() / (0.1|units.m**2)) | units.kg
particles.mass += numpy.exp(-(particles.position-peak_positions[1]).lengths_squared() / (0.1|units.m**2)) | units.kg
self.assertAlmostEqual(particles.position[particles.mass.argmax()], peak_positions[0])
self.assertAlmostEqual(particles[:4000].position[particles[:4000].mass.argmax()], peak_positions[1])
hop = Hop(unit_converter=nbody_system.nbody_to_si(particles.mass.sum(), 1.0 | units.m))#, redirection="none")
hop.parameters.density_method = 2
hop.parameters.number_of_neighbors_for_local_density = 50
hop.parameters.relative_saddle_density_threshold = True
hop.commit_parameters()
hop.particles.add_particles(particles)
hop.calculate_densities()
self.assertAlmostEqual(hop.particles.position[hop.particles.density.argmax()], peak_positions[0])
self.assertAlmostEqual(hop.particles[:4000].position[hop.particles[:4000].density.argmax()], peak_positions[1])
hop.do_hop()
groups = list(hop.groups())
self.assertEqual(len(groups), 2)
for group, peak_position in zip(groups, peak_positions):
self.assertAlmostEqual(group.center_of_mass(), peak_position, 1)
hop.stop()
def test6(self):
print "Test with different masses"
# Particles on a cubic grid with masses according to a gaussian density profile
grid = numpy.mgrid[-1:1:21j, -1:1:21j, -1:1:21j] | units.m
particles = Particles(9261, x=grid[0], y=grid[1], z=grid[2])
peak_positions = [[0.2, -0.4, 0.3], [-0.6, 0.2, 0.7]] | units.m
particles.mass = 2*numpy.exp(-(particles.position-peak_positions[0]).lengths_squared() / (0.1|units.m**2)) | units.kg
particles.mass += numpy.exp(-(particles.position-peak_positions[1]).lengths_squared() / (0.1|units.m**2)) | units.kg
self.assertAlmostEquals(particles.position[particles.mass.argmax()], peak_positions[0])
self.assertAlmostEquals(particles[:4000].position[particles[:4000].mass.argmax()], peak_positions[1])
hop = Hop(unit_converter=nbody_system.nbody_to_si(particles.mass.sum(), 1.0 | units.m))#, redirection="none")
hop.parameters.density_method = 2
hop.parameters.number_of_neighbors_for_local_density = 50
hop.parameters.relative_saddle_density_threshold = True
hop.commit_parameters()
hop.particles.add_particles(particles)
hop.calculate_densities()
self.assertAlmostEquals(hop.particles.position[hop.particles.density.argmax()], peak_positions[0])
self.assertAlmostEquals(hop.particles[:4000].position[hop.particles[:4000].density.argmax()], peak_positions[1])
hop.do_hop()
groups = list(hop.groups())
self.assertEquals(len(groups), 2)
for group, peak_position in zip(groups, peak_positions):
self.assertAlmostEquals(group.center_of_mass(), peak_position, 1)
hop.stop()
def identify_subgroups(
unit_converter,
particles,
saddle_density_threshold=None,
outer_density_threshold=None,
peak_density_threshold="auto",
logger=None,
):
"Identify groups of particles by particle densities"
# print(peak_density_threshold)
# exit()
logger = logger or logging.getLogger(__name__)
hop = Hop(unit_converter)
hop.particles.add_particles(particles)
logger.info("particles added to Hop")
hop.calculate_densities()
logger.info("densities calculated")
try:
mean_density = hop.particles.density.mean()
except:
print("error")
# if peak_density_threshold == "auto":
# peak_density_threshold = mean_density
hop.parameters.peak_density_threshold = peak_density_threshold
logger.info(
"peak density threshold set to %s",
peak_density_threshold,
)
print(peak_density_threshold / mean_density)
saddle_density_threshold = (0.9 * peak_density_threshold
if saddle_density_threshold is None else
saddle_density_threshold)
hop.parameters.saddle_density_threshold = saddle_density_threshold
logger.info(
"saddle density threshold set to %s",
saddle_density_threshold,
)
outer_density_threshold = (0.01 * peak_density_threshold
if outer_density_threshold is None else
outer_density_threshold)
hop.parameters.outer_density_threshold = outer_density_threshold
logger.info(
"outer density threshold set to %s",
saddle_density_threshold,
)
hop.do_hop()
logger.info("doing hop")
result = [x.get_intersecting_subset_in(particles) for x in hop.groups()]
hop.stop()
print("hop done")
logger.info("stopping hop")
return result
def find_clumps(particles, unit_converter):
hop = Hop(unit_converter)
hop.particles.add_particles(particles)
hop.calculate_densities()
hop.do_hop()
result = [x.get_intersecting_subset_in(particles) for x in hop.groups()]
hop.stop()
return result
def test3(self):
random.seed(1001)
print "Third test: densest neighbors and groups."
hop = Hop()
hop.parameters.number_of_neighbors_for_local_density = 5
particles1 = new_plummer_model(10)
particles2 = new_plummer_model(10)
particles3 = new_plummer_model(10)
particles2.position += (10, 0, 0) | nbody_system.length
particles3.position += (0, 20, 0) | nbody_system.length
hop.particles.add_particles(particles1)
hop.particles.add_particles(particles2)
hop.particles.add_particles(particles3)
hop.calculate_densities()
hop.do_hop()
print hop.particles.group_id
groups = list(hop.groups())
self.assertEquals(len(groups), 3)
self.assertEquals(hop.get_number_of_particles_outside_groups(), 0)
#densities = (0,0,0) | nbody_system.density
for index, group in enumerate(groups):
self.assertEquals(len(group), 10)
self.assertEquals(group.id_of_group(), index)
#self.assertEquals(group.get_density_of_group(), densities[index])
hop.stop()
def test3(self):
random.seed(1001)
print "Third test: densest neighbors and groups."
hop = Hop()
hop.parameters.number_of_neighbors_for_local_density = 5
particles1 = new_plummer_model(10)
particles2 = new_plummer_model(10)
particles3 = new_plummer_model(10)
particles2.position += (10,0,0) | nbody_system.length
particles3.position += (0,20,0) | nbody_system.length
hop.particles.add_particles(particles1)
hop.particles.add_particles(particles2)
hop.particles.add_particles(particles3)
hop.calculate_densities()
hop.do_hop()
print hop.particles.group_id
groups = list(hop.groups())
self.assertEquals(len(groups), 3)
self.assertEquals(hop.get_number_of_particles_outside_groups(), 0)
#densities = (0,0,0) | nbody_system.density
for index, group in enumerate(groups):
self.assertEquals(len(group), 10)
self.assertEquals(group.id_of_group(), index)
#self.assertEquals(group.get_density_of_group(), densities[index])
hop.stop()
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()
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()
