def test4(self):
print "Testing GalactICsInterface generate_particles"
number_of_particles_halo = 1000
instance = GalactICsInterface(**default_options)
self.assertEquals(instance.initialize_code(), 0)
self.assertEquals(instance.set_output_path(instance.get_output_directory()), 0)
self.assertEquals(instance.set_halo_number_of_particles(number_of_particles_halo), 0)
self.assertEquals(instance.set_generate_bulge_flag(False), 0)
self.assertEquals(instance.set_generate_disk_flag(False), 0)
self.assertEquals(instance.set_order_of_multipole_expansion(0), 0)
self.assertEquals(instance.commit_parameters(), 0)
self.assertEquals(instance.get_number_of_particles_updated().values(), [0, 0])
self.assertEquals(instance.generate_particles(), 0)
self.assertEquals(instance.get_number_of_particles_updated().values(), [number_of_particles_halo, 0])
masses, errors = instance.get_mass(range(number_of_particles_halo))
self.assertEquals(errors, numpy.zeros(number_of_particles_halo))
self.assertAlmostRelativeEquals(masses, numpy.ones(number_of_particles_halo) * masses[0])
total_mass = masses.sum()
expected_mean_pos = numpy.array([73.768384103536604, 76.03533643054962, 75.176319462463255])
expected_mean_vel = numpy.array([0.92904859858192501, 0.94953939936682585, 0.92897711758688095])
x_positions, y_positions, z_positions, errors = instance.get_position(range(number_of_particles_halo))
self.assertEquals(errors, numpy.zeros(number_of_particles_halo))
self.assertAlmostEquals(
numpy.array([numpy.mean(x_positions), numpy.mean(y_positions), numpy.mean(z_positions)]),
numpy.array([0.0] * 3),
5,
)
self.assertAlmostRelativeEquals(
numpy.array([numpy.mean(abs(x_positions)), numpy.mean(abs(y_positions)), numpy.mean(abs(z_positions))]),
expected_mean_pos,
4,
)
x_velocities, y_velocities, z_velocities, errors = instance.get_velocity(range(number_of_particles_halo))
self.assertEquals(errors, numpy.zeros(number_of_particles_halo))
self.assertAlmostEquals(
numpy.array([numpy.mean(x_velocities), numpy.mean(y_velocities), numpy.mean(z_velocities)]),
numpy.array([0.0] * 3),
)
self.assertAlmostRelativeEquals(
numpy.array([numpy.mean(abs(x_velocities)), numpy.mean(abs(y_velocities)), numpy.mean(abs(z_velocities))]),
expected_mean_vel,
4,
)
self.assertEquals(instance.cleanup_code(), 0)
instance.stop()
def test4(self):
print "Testing GalactICsInterface generate_particles"
number_of_particles_halo = 1000
instance = GalactICsInterface(**default_options)
self.assertEquals(instance.initialize_code(), 0)
self.assertEquals(instance.set_output_path(instance.get_output_directory()), 0)
self.assertEquals(instance.set_halo_number_of_particles(number_of_particles_halo), 0)
self.assertEquals(instance.set_generate_bulge_flag(False), 0)
self.assertEquals(instance.set_generate_disk_flag(False), 0)
self.assertEquals(instance.set_order_of_multipole_expansion(0), 0)
self.assertEquals(instance.commit_parameters(), 0)
self.assertEquals(instance.get_number_of_particles_updated().values(), [0, 0])
self.assertEquals(instance.generate_particles(), 0)
self.assertEquals(instance.get_number_of_particles_updated().values(), [number_of_particles_halo, 0])
masses, errors = instance.get_mass(range(number_of_particles_halo))
self.assertEquals(errors, numpy.zeros(number_of_particles_halo))
self.assertAlmostRelativeEquals(masses, numpy.ones(number_of_particles_halo)*masses[0])
total_mass = masses.sum()
if platform.processor() == 'ppc64le':
# on ppc64le, the model generation has small differences from intel
# change expected pos
expected_mean_pos = numpy.array([73.5628, 76.251034, 75.53434])
else:
expected_mean_pos = numpy.array([73.768384103536604, 76.03533643054962, 75.176319462463255])
expected_mean_vel = numpy.array([0.92904859858192501, 0.94953939936682585, 0.92897711758688095])
x_positions, y_positions, z_positions, errors = instance.get_position(range(number_of_particles_halo))
self.assertEquals(errors, numpy.zeros(number_of_particles_halo))
self.assertAlmostEquals(numpy.array([numpy.mean(x_positions), numpy.mean(y_positions),
numpy.mean(z_positions)]), numpy.array([0.0]*3), 5)
self.assertAlmostRelativeEquals(numpy.array([numpy.mean(abs(x_positions)), numpy.mean(abs(y_positions)),
numpy.mean(abs(z_positions))]), expected_mean_pos, 3)
x_velocities, y_velocities, z_velocities, errors = instance.get_velocity(range(number_of_particles_halo))
self.assertEquals(errors, numpy.zeros(number_of_particles_halo))
self.assertAlmostEquals(numpy.array([numpy.mean(x_velocities), numpy.mean(y_velocities),
numpy.mean(z_velocities)]), numpy.array([0.0]*3))
self.assertAlmostRelativeEquals(numpy.array([numpy.mean(abs(x_velocities)), numpy.mean(abs(y_velocities)),
numpy.mean(abs(z_velocities))]), expected_mean_vel, 2)
self.assertEquals(instance.cleanup_code(), 0)
instance.stop()
def slowtest3(self):
print "Testing GalactICsInterface generate_particles"
n_particles_halo = 100
n_particles_bulge = 100
n_particles_disk = 100
number_of_particles = n_particles_disk + n_particles_bulge + n_particles_halo
instance = GalactICsInterface(**default_options)
self.assertEquals(instance.initialize_code(), 0)
self.assertEquals(
instance.set_output_path(instance.get_output_directory()), 0)
self.assertEquals(
instance.set_halo_number_of_particles(n_particles_halo), 0)
self.assertEquals(
instance.set_bulge_number_of_particles(n_particles_bulge), 0)
self.assertEquals(
instance.set_disk_number_of_particles(n_particles_disk), 0)
self.assertEquals(instance.commit_parameters(), 0)
self.assertEquals(instance.get_number_of_particles_updated().values(),
[0, 0])
self.assertEquals(instance.generate_particles(), 0)
self.assertEquals(instance.get_number_of_particles_updated().values(),
[number_of_particles, 0])
mass_disk, mass_bulge, mass_halo = 26.578816771507263, 14.632800221443176, 1184.2350006103516
masses, errors = instance.get_mass(range(number_of_particles))
self.assertEquals(errors, numpy.zeros(number_of_particles))
self.assertAlmostRelativeEquals(
masses,
numpy.concatenate((
numpy.ones(n_particles_disk) * mass_disk / n_particles_disk,
numpy.ones(n_particles_bulge) * mass_bulge / n_particles_bulge,
numpy.ones(n_particles_halo) * mass_halo / n_particles_halo,
)), 3)
x_positions, y_positions, z_positions, errors = instance.get_position(
range(number_of_particles))
self.assertEquals(errors, numpy.zeros(number_of_particles))
self.assertAlmostEquals(
numpy.array([
numpy.mean(x_positions),
numpy.mean(y_positions),
numpy.mean(z_positions)
]), numpy.array([0.0] * 3), 5)
self.assertAlmostRelativeEquals(
numpy.array([
numpy.mean(abs(x_positions[:n_particles_disk])),
numpy.mean(abs(y_positions[:n_particles_disk])),
numpy.mean(abs(z_positions[:n_particles_disk]))
]),
numpy.array(
[7.3994484072923656, 7.1570298135280606, 0.33854196755215527]),
3)
self.assertAlmostRelativeEquals(
numpy.array([
numpy.mean(
abs(x_positions[n_particles_disk:n_particles_disk +
n_particles_bulge])),
numpy.mean(
abs(y_positions[n_particles_disk:n_particles_disk +
n_particles_bulge])),
numpy.mean(
abs(z_positions[n_particles_disk:n_particles_disk +
n_particles_bulge]))
]),
numpy.array(
[1.244429082274437, 1.1639373835548759, 0.8550614269822836]),
3)
self.assertAlmostRelativeEquals(
numpy.array([
numpy.mean(abs(x_positions[-n_particles_halo:])),
numpy.mean(abs(y_positions[-n_particles_halo:])),
numpy.mean(abs(z_positions[-n_particles_halo:]))
]),
numpy.array(
[94.242819476127622, 88.41320479869843, 85.234394512176507]),
3)
x_velocities, y_velocities, z_velocities, errors = instance.get_velocity(
range(number_of_particles))
self.assertEquals(errors, numpy.zeros(number_of_particles))
self.assertAlmostEquals(
numpy.array([
numpy.mean(x_velocities),
numpy.mean(y_velocities),
numpy.mean(z_velocities)
]), numpy.array([0.0] * 3))
self.assertAlmostRelativeEquals(
numpy.array([
numpy.mean(abs(x_velocities[:n_particles_disk])),
numpy.mean(abs(y_velocities[:n_particles_disk])),
numpy.mean(abs(z_velocities[:n_particles_disk]))
]),
numpy.array(
[1.5026254250109197, 1.5649469271302223, 0.20230436498299242]),
5)
self.assertAlmostRelativeEquals(
numpy.array([
numpy.mean(abs(x_velocities[n_particles_disk:])),
numpy.mean(abs(y_velocities[n_particles_disk:])),
numpy.mean(abs(z_velocities[n_particles_disk:]))
]),
numpy.array(
[0.99470628838986164, 0.95913934175856408,
0.9359876788407564]), 5)
self.assertEquals(instance.cleanup_code(), 0)
instance.stop()
def slowtest3(self):
print "Testing GalactICsInterface generate_particles"
n_particles_halo = 100
n_particles_bulge = 100
n_particles_disk = 100
number_of_particles = n_particles_disk + n_particles_bulge + n_particles_halo
instance = GalactICsInterface(**default_options)
self.assertEquals(instance.initialize_code(), 0)
self.assertEquals(instance.set_output_path(instance.get_output_directory()), 0)
self.assertEquals(instance.set_halo_number_of_particles(n_particles_halo), 0)
self.assertEquals(instance.set_bulge_number_of_particles(n_particles_bulge), 0)
self.assertEquals(instance.set_disk_number_of_particles(n_particles_disk), 0)
self.assertEquals(instance.commit_parameters(), 0)
self.assertEquals(instance.get_number_of_particles_updated().values(), [0, 0])
self.assertEquals(instance.generate_particles(), 0)
self.assertEquals(instance.get_number_of_particles_updated().values(), [number_of_particles, 0])
mass_disk, mass_bulge, mass_halo = 26.578816771507263, 14.632800221443176, 1184.2350006103516
masses, errors = instance.get_mass(range(number_of_particles))
self.assertEquals(errors, numpy.zeros(number_of_particles))
self.assertAlmostRelativeEquals(
masses,
numpy.concatenate(
(
numpy.ones(n_particles_disk) * mass_disk / n_particles_disk,
numpy.ones(n_particles_bulge) * mass_bulge / n_particles_bulge,
numpy.ones(n_particles_halo) * mass_halo / n_particles_halo,
)
),
3,
)
x_positions, y_positions, z_positions, errors = instance.get_position(range(number_of_particles))
self.assertEquals(errors, numpy.zeros(number_of_particles))
self.assertAlmostEquals(
numpy.array([numpy.mean(x_positions), numpy.mean(y_positions), numpy.mean(z_positions)]),
numpy.array([0.0] * 3),
5,
)
self.assertAlmostRelativeEquals(
numpy.array(
[
numpy.mean(abs(x_positions[:n_particles_disk])),
numpy.mean(abs(y_positions[:n_particles_disk])),
numpy.mean(abs(z_positions[:n_particles_disk])),
]
),
numpy.array([7.3994484072923656, 7.1570298135280606, 0.33854196755215527]),
3,
)
self.assertAlmostRelativeEquals(
numpy.array(
[
numpy.mean(abs(x_positions[n_particles_disk : n_particles_disk + n_particles_bulge])),
numpy.mean(abs(y_positions[n_particles_disk : n_particles_disk + n_particles_bulge])),
numpy.mean(abs(z_positions[n_particles_disk : n_particles_disk + n_particles_bulge])),
]
),
numpy.array([1.244429082274437, 1.1639373835548759, 0.8550614269822836]),
3,
)
self.assertAlmostRelativeEquals(
numpy.array(
[
numpy.mean(abs(x_positions[-n_particles_halo:])),
numpy.mean(abs(y_positions[-n_particles_halo:])),
numpy.mean(abs(z_positions[-n_particles_halo:])),
]
),
numpy.array([94.242819476127622, 88.41320479869843, 85.234394512176507]),
3,
)
x_velocities, y_velocities, z_velocities, errors = instance.get_velocity(range(number_of_particles))
self.assertEquals(errors, numpy.zeros(number_of_particles))
self.assertAlmostEquals(
numpy.array([numpy.mean(x_velocities), numpy.mean(y_velocities), numpy.mean(z_velocities)]),
numpy.array([0.0] * 3),
)
self.assertAlmostRelativeEquals(
numpy.array(
[
numpy.mean(abs(x_velocities[:n_particles_disk])),
numpy.mean(abs(y_velocities[:n_particles_disk])),
numpy.mean(abs(z_velocities[:n_particles_disk])),
]
),
numpy.array([1.5026254250109197, 1.5649469271302223, 0.20230436498299242]),
5,
)
self.assertAlmostRelativeEquals(
numpy.array(
[
numpy.mean(abs(x_velocities[n_particles_disk:])),
numpy.mean(abs(y_velocities[n_particles_disk:])),
numpy.mean(abs(z_velocities[n_particles_disk:])),
]
),
numpy.array([0.99470628838986164, 0.95913934175856408, 0.9359876788407564]),
5,
)
self.assertEquals(instance.cleanup_code(), 0)
instance.stop()