def test_stream_particles():
num_particles = 100000
domain_dims = (64, 64, 64)
dens = np.random.random(domain_dims)
x = np.random.uniform(size=num_particles)
y = np.random.uniform(size=num_particles)
z = np.random.uniform(size=num_particles)
m = np.ones(num_particles)
# Field operators and cell flagging methods
fo = []
fo.append(ic.TopHatSphere(0.1, [0.2, 0.3, 0.4], {"density": 2.0}))
fo.append(ic.TopHatSphere(0.05, [0.7, 0.4, 0.75], {"density": 20.0}))
rc = [fm.flagging_method_registry["overdensity"](1.0)]
# Check that all of this runs ok without particles
ug0 = load_uniform_grid({"density": dens}, domain_dims, 1.0, nprocs=8)
amr0 = refine_amr(ug0, rc, fo, 3)
grid_data = []
for grid in amr0.index.grids:
data = dict(
left_edge=grid.LeftEdge,
right_edge=grid.RightEdge,
level=grid.Level,
dimensions=grid.ActiveDimensions,
)
for field in amr0.field_list:
data[field] = grid[field]
grid_data.append(data)
amr0 = load_amr_grids(grid_data, domain_dims)
# Now add particles
fields1 = {
"density": dens,
"particle_position_x": x,
"particle_position_y": y,
"particle_position_z": z,
"particle_mass": m,
}
fields2 = fields1.copy()
ug1 = load_uniform_grid(fields1, domain_dims, 1.0)
ug2 = load_uniform_grid(fields2, domain_dims, 1.0, nprocs=8)
# Check to make sure the number of particles is the same
number_of_particles1 = np.sum([grid.NumberOfParticles for grid in ug1.index.grids])
number_of_particles2 = np.sum([grid.NumberOfParticles for grid in ug2.index.grids])
assert_equal(number_of_particles1, num_particles)
assert_equal(number_of_particles1, number_of_particles2)
for grid in ug2.index.grids:
tot_parts = grid["io", "particle_position_x"].size
tot_all_parts = grid["all", "particle_position_x"].size
assert tot_parts == grid.NumberOfParticles
assert tot_all_parts == grid.NumberOfParticles
# Check to make sure the fields have been defined correctly
for ptype in ("all", "io"):
assert (
ug1._get_field_info(ptype, "particle_position_x").sampling_type
== "particle"
)
assert (
ug1._get_field_info(ptype, "particle_position_y").sampling_type
== "particle"
)
assert (
ug1._get_field_info(ptype, "particle_position_z").sampling_type
== "particle"
)
assert ug1._get_field_info(ptype, "particle_mass").sampling_type == "particle"
assert not ug1._get_field_info("gas", "density").sampling_type == "particle"
for ptype in ("all", "io"):
assert (
ug2._get_field_info(ptype, "particle_position_x").sampling_type
== "particle"
)
assert (
ug2._get_field_info(ptype, "particle_position_y").sampling_type
== "particle"
)
assert (
ug2._get_field_info(ptype, "particle_position_z").sampling_type
== "particle"
)
assert ug2._get_field_info(ptype, "particle_mass").sampling_type == "particle"
assert not ug2._get_field_info("gas", "density").sampling_type == "particle"
# Now refine this
amr1 = refine_amr(ug1, rc, fo, 3)
for field in sorted(ug1.field_list):
assert field in amr1.field_list
grid_data = []
for grid in amr1.index.grids:
data = dict(
left_edge=grid.LeftEdge,
right_edge=grid.RightEdge,
level=grid.Level,
dimensions=grid.ActiveDimensions,
)
for field in amr1.field_list:
if field[0] not in ("all", "nbody"):
data[field] = grid[field]
grid_data.append(data)
amr2 = load_amr_grids(grid_data, domain_dims)
# Check everything again
number_of_particles1 = [grid.NumberOfParticles for grid in amr1.index.grids]
number_of_particles2 = [grid.NumberOfParticles for grid in amr2.index.grids]
assert_equal(np.sum(number_of_particles1), num_particles)
assert_equal(number_of_particles1, number_of_particles2)
for grid in amr1.index.grids:
tot_parts = grid["io", "particle_position_x"].size
tot_all_parts = grid["all", "particle_position_x"].size
assert tot_parts == grid.NumberOfParticles
assert tot_all_parts == grid.NumberOfParticles
for grid in amr2.index.grids:
tot_parts = grid["io", "particle_position_x"].size
tot_all_parts = grid["all", "particle_position_x"].size
assert tot_parts == grid.NumberOfParticles
assert tot_all_parts == grid.NumberOfParticles
assert (
amr1._get_field_info("all", "particle_position_x").sampling_type == "particle"
)
assert (
amr1._get_field_info("all", "particle_position_y").sampling_type == "particle"
)
assert (
amr1._get_field_info("all", "particle_position_z").sampling_type == "particle"
)
assert amr1._get_field_info("all", "particle_mass").sampling_type == "particle"
assert not amr1._get_field_info("gas", "density").sampling_type == "particle"
assert (
amr2._get_field_info("all", "particle_position_x").sampling_type == "particle"
)
assert (
amr2._get_field_info("all", "particle_position_y").sampling_type == "particle"
)
assert (
amr2._get_field_info("all", "particle_position_z").sampling_type == "particle"
)
assert amr2._get_field_info("all", "particle_mass").sampling_type == "particle"
assert not amr2._get_field_info("gas", "density").sampling_type == "particle"
# Now perform similar checks, but with multiple particle types
num_dm_particles = 30000
xd = np.random.uniform(size=num_dm_particles)
yd = np.random.uniform(size=num_dm_particles)
zd = np.random.uniform(size=num_dm_particles)
md = np.ones(num_dm_particles)
num_star_particles = 20000
xs = np.random.uniform(size=num_star_particles)
ys = np.random.uniform(size=num_star_particles)
zs = np.random.uniform(size=num_star_particles)
ms = 2.0 * np.ones(num_star_particles)
dens = np.random.random(domain_dims)
fields3 = {
"density": dens,
("dm", "particle_position_x"): xd,
("dm", "particle_position_y"): yd,
("dm", "particle_position_z"): zd,
("dm", "particle_mass"): md,
("star", "particle_position_x"): xs,
("star", "particle_position_y"): ys,
("star", "particle_position_z"): zs,
("star", "particle_mass"): ms,
}
fields4 = fields3.copy()
ug3 = load_uniform_grid(fields3, domain_dims, 1.0)
ug4 = load_uniform_grid(fields4, domain_dims, 1.0, nprocs=8)
# Check to make sure the number of particles is the same
number_of_particles3 = np.sum([grid.NumberOfParticles for grid in ug3.index.grids])
number_of_particles4 = np.sum([grid.NumberOfParticles for grid in ug4.index.grids])
assert_equal(number_of_particles3, num_dm_particles + num_star_particles)
assert_equal(number_of_particles3, number_of_particles4)
for grid in ug4.index.grids:
tot_parts = grid["dm", "particle_position_x"].size
tot_parts += grid["star", "particle_position_x"].size
tot_all_parts = grid["all", "particle_position_x"].size
assert tot_parts == grid.NumberOfParticles
assert tot_all_parts == grid.NumberOfParticles
# Check to make sure the fields have been defined correctly
for ptype in ("dm", "star"):
assert (
ug3._get_field_info(ptype, "particle_position_x").sampling_type
== "particle"
)
assert (
ug3._get_field_info(ptype, "particle_position_y").sampling_type
== "particle"
)
assert (
ug3._get_field_info(ptype, "particle_position_z").sampling_type
== "particle"
)
assert ug3._get_field_info(ptype, "particle_mass").sampling_type == "particle"
assert (
ug4._get_field_info(ptype, "particle_position_x").sampling_type
== "particle"
)
assert (
ug4._get_field_info(ptype, "particle_position_y").sampling_type
== "particle"
)
assert (
ug4._get_field_info(ptype, "particle_position_z").sampling_type
== "particle"
)
assert ug4._get_field_info(ptype, "particle_mass").sampling_type == "particle"
# Now refine this
amr3 = refine_amr(ug3, rc, fo, 3)
for field in sorted(ug3.field_list):
assert field in amr3.field_list
grid_data = []
for grid in amr3.index.grids:
data = dict(
left_edge=grid.LeftEdge,
right_edge=grid.RightEdge,
level=grid.Level,
dimensions=grid.ActiveDimensions,
)
for field in amr3.field_list:
if field[0] not in ("all", "nbody"):
data[field] = grid[field]
grid_data.append(data)
amr4 = load_amr_grids(grid_data, domain_dims)
# Check everything again
number_of_particles3 = [grid.NumberOfParticles for grid in amr3.index.grids]
number_of_particles4 = [grid.NumberOfParticles for grid in amr4.index.grids]
assert_equal(np.sum(number_of_particles3), num_star_particles + num_dm_particles)
assert_equal(number_of_particles3, number_of_particles4)
for ptype in ("dm", "star"):
assert (
amr3._get_field_info(ptype, "particle_position_x").sampling_type
== "particle"
)
assert (
amr3._get_field_info(ptype, "particle_position_y").sampling_type
== "particle"
)
assert (
amr3._get_field_info(ptype, "particle_position_z").sampling_type
== "particle"
)
assert amr3._get_field_info(ptype, "particle_mass").sampling_type == "particle"
assert (
amr4._get_field_info(ptype, "particle_position_x").sampling_type
== "particle"
)
assert (
amr4._get_field_info(ptype, "particle_position_y").sampling_type
== "particle"
)
assert (
amr4._get_field_info(ptype, "particle_position_z").sampling_type
== "particle"
)
assert amr4._get_field_info(ptype, "particle_mass").sampling_type == "particle"
for grid in amr3.index.grids:
tot_parts = grid["dm", "particle_position_x"].size
tot_parts += grid["star", "particle_position_x"].size
tot_all_parts = grid["all", "particle_position_x"].size
assert tot_parts == grid.NumberOfParticles
assert tot_all_parts == grid.NumberOfParticles
for grid in amr4.index.grids:
tot_parts = grid["dm", "particle_position_x"].size
tot_parts += grid["star", "particle_position_x"].size
tot_all_parts = grid["all", "particle_position_x"].size
assert tot_parts == grid.NumberOfParticles
assert tot_all_parts == grid.NumberOfParticles
def test_stream_particles():
num_particles = 100000
domain_dims = (64, 64, 64)
dens = np.random.random(domain_dims)
x = np.random.uniform(size=num_particles)
y = np.random.uniform(size=num_particles)
z = np.random.uniform(size=num_particles)
m = np.ones(num_particles)
# Field operators and cell flagging methods
fo = []
fo.append(ic.TopHatSphere(0.1, [0.2, 0.3, 0.4], {"density": 2.0}))
fo.append(ic.TopHatSphere(0.05, [0.7, 0.4, 0.75], {"density": 20.0}))
# Add particles
fields1 = {
"density": dens,
"particle_position_x": x,
"particle_position_y": y,
"particle_position_z": z,
"particle_mass": m,
}
fields2 = fields1.copy()
ug1 = load_uniform_grid(fields1, domain_dims, 1.0)
ug2 = load_uniform_grid(fields2, domain_dims, 1.0, nprocs=8)
# Check to make sure the number of particles is the same
number_of_particles1 = np.sum(
[grid.NumberOfParticles for grid in ug1.index.grids])
number_of_particles2 = np.sum(
[grid.NumberOfParticles for grid in ug2.index.grids])
assert_equal(number_of_particles1, num_particles)
assert_equal(number_of_particles1, number_of_particles2)
for grid in ug2.index.grids:
tot_parts = grid["io", "particle_position_x"].size
tot_all_parts = grid["all", "particle_position_x"].size
assert tot_parts == grid.NumberOfParticles
assert tot_all_parts == grid.NumberOfParticles
# Check to make sure the fields have been defined correctly
for ptype in ("all", "io"):
assert (ug1._get_field_info(
ptype, "particle_position_x").sampling_type == "particle")
assert (ug1._get_field_info(
ptype, "particle_position_y").sampling_type == "particle")
assert (ug1._get_field_info(
ptype, "particle_position_z").sampling_type == "particle")
assert ug1._get_field_info(ptype,
"particle_mass").sampling_type == "particle"
assert not ug1._get_field_info("gas",
"density").sampling_type == "particle"
for ptype in ("all", "io"):
assert (ug2._get_field_info(
ptype, "particle_position_x").sampling_type == "particle")
assert (ug2._get_field_info(
ptype, "particle_position_y").sampling_type == "particle")
assert (ug2._get_field_info(
ptype, "particle_position_z").sampling_type == "particle")
assert ug2._get_field_info(ptype,
"particle_mass").sampling_type == "particle"
assert not ug2._get_field_info("gas",
"density").sampling_type == "particle"
# Now perform similar checks, but with multiple particle types
num_dm_particles = 30000
xd = np.random.uniform(size=num_dm_particles)
yd = np.random.uniform(size=num_dm_particles)
zd = np.random.uniform(size=num_dm_particles)
md = np.ones(num_dm_particles)
num_star_particles = 20000
xs = np.random.uniform(size=num_star_particles)
ys = np.random.uniform(size=num_star_particles)
zs = np.random.uniform(size=num_star_particles)
ms = 2.0 * np.ones(num_star_particles)
dens = np.random.random(domain_dims)
fields3 = {
"density": dens,
("dm", "particle_position_x"): xd,
("dm", "particle_position_y"): yd,
("dm", "particle_position_z"): zd,
("dm", "particle_mass"): md,
("star", "particle_position_x"): xs,
("star", "particle_position_y"): ys,
("star", "particle_position_z"): zs,
("star", "particle_mass"): ms,
}
fields4 = fields3.copy()
ug3 = load_uniform_grid(fields3, domain_dims, 1.0)
ug4 = load_uniform_grid(fields4, domain_dims, 1.0, nprocs=8)
# Check to make sure the number of particles is the same
number_of_particles3 = np.sum(
[grid.NumberOfParticles for grid in ug3.index.grids])
number_of_particles4 = np.sum(
[grid.NumberOfParticles for grid in ug4.index.grids])
assert_equal(number_of_particles3, num_dm_particles + num_star_particles)
assert_equal(number_of_particles3, number_of_particles4)
for grid in ug4.index.grids:
tot_parts = grid["dm", "particle_position_x"].size
tot_parts += grid["star", "particle_position_x"].size
tot_all_parts = grid["all", "particle_position_x"].size
assert tot_parts == grid.NumberOfParticles
assert tot_all_parts == grid.NumberOfParticles
# Check to make sure the fields have been defined correctly
for ptype in ("dm", "star"):
assert (ug3._get_field_info(
ptype, "particle_position_x").sampling_type == "particle")
assert (ug3._get_field_info(
ptype, "particle_position_y").sampling_type == "particle")
assert (ug3._get_field_info(
ptype, "particle_position_z").sampling_type == "particle")
assert ug3._get_field_info(ptype,
"particle_mass").sampling_type == "particle"
assert (ug4._get_field_info(
ptype, "particle_position_x").sampling_type == "particle")
assert (ug4._get_field_info(
ptype, "particle_position_y").sampling_type == "particle")
assert (ug4._get_field_info(
ptype, "particle_position_z").sampling_type == "particle")
assert ug4._get_field_info(ptype,
"particle_mass").sampling_type == "particle"
def test_stream_particles():
num_particles = 100000
domain_dims = (64, 64, 64)
dens = np.random.random(domain_dims)
x = np.random.uniform(size=num_particles)
y = np.random.uniform(size=num_particles)
z = np.random.uniform(size=num_particles)
m = np.ones((num_particles))
# Field operators and cell flagging methods
fo = []
fo.append(ic.TopHatSphere(0.1, [0.2, 0.3, 0.4], {"density": 2.0}))
fo.append(ic.TopHatSphere(0.05, [0.7, 0.4, 0.75], {"density": 20.0}))
rc = [fm.flagging_method_registry["overdensity"](1.0)]
# Check that all of this runs ok without particles
ug0 = load_uniform_grid({"density": dens}, domain_dims, 1.0, nprocs=8)
amr0 = refine_amr(ug0, rc, fo, 3)
grid_data = []
for grid in amr0.index.grids:
data = dict(left_edge=grid.LeftEdge,
right_edge=grid.RightEdge,
level=grid.Level,
dimensions=grid.ActiveDimensions,
number_of_particles=grid.NumberOfParticles)
for field in amr0.field_list:
data[field] = grid[field]
grid_data.append(data)
amr0 = load_amr_grids(grid_data, domain_dims, 1.0)
# Now add particles
fields1 = {
"density": dens,
"particle_position_x": x,
"particle_position_y": y,
"particle_position_z": z,
"particle_mass": m,
"number_of_particles": num_particles
}
fields2 = fields1.copy()
ug1 = load_uniform_grid(fields1, domain_dims, 1.0)
ug2 = load_uniform_grid(fields2, domain_dims, 1.0, nprocs=8)
# Check to make sure the number of particles is the same
number_of_particles1 = np.sum(
[grid.NumberOfParticles for grid in ug1.index.grids])
number_of_particles2 = np.sum(
[grid.NumberOfParticles for grid in ug2.index.grids])
yield assert_equal, number_of_particles1, num_particles
yield assert_equal, number_of_particles1, number_of_particles2
# Check to make sure the fields have been defined correctly
for ptype in ("all", "io"):
assert ug1._get_field_info(ptype, "particle_position_x").particle_type
assert ug1._get_field_info(ptype, "particle_position_y").particle_type
assert ug1._get_field_info(ptype, "particle_position_z").particle_type
assert ug1._get_field_info(ptype, "particle_mass").particle_type
assert not ug1._get_field_info("gas", "density").particle_type
for ptype in ("all", "io"):
assert ug2._get_field_info(ptype, "particle_position_x").particle_type
assert ug2._get_field_info(ptype, "particle_position_y").particle_type
assert ug2._get_field_info(ptype, "particle_position_z").particle_type
assert ug2._get_field_info(ptype, "particle_mass").particle_type
assert not ug2._get_field_info("gas", "density").particle_type
# Now refine this
amr1 = refine_amr(ug1, rc, fo, 3)
for field in sorted(ug1.field_list):
yield assert_equal, (field in amr1.field_list), True
grid_data = []
for grid in amr1.index.grids:
data = dict(left_edge=grid.LeftEdge,
right_edge=grid.RightEdge,
level=grid.Level,
dimensions=grid.ActiveDimensions,
number_of_particles=grid.NumberOfParticles)
for field in amr1.field_list:
data[field] = grid[field]
grid_data.append(data)
amr2 = load_amr_grids(grid_data, domain_dims, 1.0)
# Check everything again
number_of_particles1 = [
grid.NumberOfParticles for grid in amr1.index.grids
]
number_of_particles2 = [
grid.NumberOfParticles for grid in amr2.index.grids
]
yield assert_equal, np.sum(number_of_particles1), num_particles
yield assert_equal, number_of_particles1, number_of_particles2
assert amr1._get_field_info("all", "particle_position_x").particle_type
assert amr1._get_field_info("all", "particle_position_y").particle_type
assert amr1._get_field_info("all", "particle_position_z").particle_type
assert amr1._get_field_info("all", "particle_mass").particle_type
assert not amr1._get_field_info("gas", "density").particle_type
assert amr2._get_field_info("all", "particle_position_x").particle_type
assert amr2._get_field_info("all", "particle_position_y").particle_type
assert amr2._get_field_info("all", "particle_position_z").particle_type
assert amr2._get_field_info("all", "particle_mass").particle_type
assert not amr2._get_field_info("gas", "density").particle_type