def test2(self):
random.seed(1001)
hop = Hop()
hop.initialize_code()
hop.parameters.number_of_neighbors_for_local_density = 7
hop.commit_parameters()
particles = new_plummer_model(1000)
hop.particles.add_particles(particles)
#distance_to_center = (particles.position - particles.center_of_mass()).lengths()
#print distance_to_center
ds = {0: 0.482308834791, 1: 0.4885137677192688, 2: 0.27442726492881775}
for method in [0, 1, 2]:
hop.set_density_method(method)
hop.calculate_densities()
d = hop.particles[0].density
self.assertAlmostRelativeEquals(d,
ds[method] | nbody_system.density,
5)
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].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 test7(self):
print "Testing Hop states"
unit_converter = nbody_system.nbody_to_si(1.0 | units.MSun,
1.0 | units.AU)
particles = new_plummer_model(200, convert_nbody=unit_converter)
print "First do everything manually:",
instance = Hop(unit_converter=unit_converter)
self.assertEquals(instance.get_name_of_current_state(),
'UNINITIALIZED')
instance.initialize_code()
self.assertEquals(instance.get_name_of_current_state(), 'INITIALIZED')
instance.commit_parameters()
self.assertEquals(instance.get_name_of_current_state(), 'EDIT')
instance.particles.add_particles(particles)
instance.commit_particles()
self.assertEquals(instance.get_name_of_current_state(), 'RUN')
instance.cleanup_code()
self.assertEquals(instance.get_name_of_current_state(), 'END')
instance.stop()
print "ok"
print "initialize_code(), commit_parameters(), (re)commit_particles(), " \
"and cleanup_code() should be called automatically:",
instance = Hop(unit_converter=unit_converter)
self.assertEquals(instance.get_name_of_current_state(),
'UNINITIALIZED')
instance.parameters.number_of_neighbors_for_local_density = 50
self.assertEquals(instance.get_name_of_current_state(), 'INITIALIZED')
instance.particles.add_particles(particles[:100])
self.assertEquals(instance.get_name_of_current_state(), 'EDIT')
mass = instance.particles[0].mass
self.assertEquals(instance.get_name_of_current_state(), 'RUN')
instance.particles.add_particles(particles[100:])
self.assertEquals(instance.get_name_of_current_state(), 'UPDATE')
mass = instance.particles[100].mass
self.assertEquals(instance.get_name_of_current_state(), 'RUN')
instance.stop()
self.assertEquals(instance.get_name_of_current_state(), 'STOPPED')
print "ok"
def test7(self):
print "Testing Hop states"
unit_converter = nbody_system.nbody_to_si(1.0 | units.MSun, 1.0 | units.AU)
particles = new_plummer_model(200, convert_nbody=unit_converter)
print "First do everything manually:",
instance = Hop(unit_converter=unit_converter)
self.assertEquals(instance.get_name_of_current_state(), 'UNINITIALIZED')
instance.initialize_code()
self.assertEquals(instance.get_name_of_current_state(), 'INITIALIZED')
instance.commit_parameters()
self.assertEquals(instance.get_name_of_current_state(), 'EDIT')
instance.particles.add_particles(particles)
instance.commit_particles()
self.assertEquals(instance.get_name_of_current_state(), 'RUN')
instance.cleanup_code()
self.assertEquals(instance.get_name_of_current_state(), 'END')
instance.stop()
print "ok"
print "initialize_code(), commit_parameters(), (re)commit_particles(), " \
"and cleanup_code() should be called automatically:",
instance = Hop(unit_converter=unit_converter)
self.assertEquals(instance.get_name_of_current_state(), 'UNINITIALIZED')
instance.parameters.number_of_neighbors_for_local_density = 50
self.assertEquals(instance.get_name_of_current_state(), 'INITIALIZED')
instance.particles.add_particles(particles[:100])
self.assertEquals(instance.get_name_of_current_state(), 'EDIT')
mass = instance.particles[0].mass
self.assertEquals(instance.get_name_of_current_state(), 'RUN')
instance.particles.add_particles(particles[100:])
self.assertEquals(instance.get_name_of_current_state(), 'UPDATE')
mass = instance.particles[100].mass
self.assertEquals(instance.get_name_of_current_state(), 'RUN')
instance.stop()
self.assertEquals(instance.get_name_of_current_state(), 'STOPPED')
print "ok"
def test2(self):
random.seed(1001)
hop = Hop()
hop.initialize_code()
hop.parameters.number_of_neighbors_for_local_density = 7
hop.commit_parameters()
particles = new_plummer_model(1000)
hop.particles.add_particles(particles)
#distance_to_center = (particles.position - particles.center_of_mass()).lengths()
#print distance_to_center
ds = {0: 0.482308834791, 1:0.4885137677192688, 2:0.27442726492881775}
for method in [0,1,2]:
hop.set_density_method(method)
hop.calculate_densities()
d = hop.particles[0].density
self.assertAlmostRelativeEquals(d, ds[method] | nbody_system.density, 5)
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()
