def test_clump_field_parameters():
"""
Make sure clump finding on fields with field parameters works.
"""
def _also_density(field, data):
factor = data.get_field_parameter("factor")
return factor * data["density"]
ds = data_dir_load(i30)
ds.add_field("also_density",
function=_also_density,
units=ds.fields.gas.density.units,
sampling_type="cell",
validators=[ValidateParameter("factor")])
data_source = ds.disk([0.5, 0.5, 0.5], [0., 0., 1.], (8, 'kpc'),
(1, 'kpc'))
data_source.set_field_parameter("factor", 1)
step = 2.0
field = ("gas", "density")
c_min = 10**np.floor(np.log10(data_source[field]).min())
c_max = 10**np.floor(np.log10(data_source[field]).max() + 1)
master_clump_1 = Clump(data_source, ("gas", "density"))
master_clump_1.add_validator("min_cells", 20)
master_clump_2 = Clump(data_source, ("gas", "also_density"))
master_clump_2.add_validator("min_cells", 20)
find_clumps(master_clump_1, c_min, c_max, step)
find_clumps(master_clump_2, c_min, c_max, step)
leaf_clumps_1 = get_lowest_clumps(master_clump_1)
leaf_clumps_2 = get_lowest_clumps(master_clump_2)
for c1, c2 in zip(leaf_clumps_1, leaf_clumps_2):
assert_array_equal(c1["gas", "density"], c2["gas", "density"])
def test_clump_finding():
n_c = 8
n_p = 1
dims = (n_c, n_c, n_c)
density = np.ones(dims)
high_rho = 10.
# add a couple disconnected density enhancements
density[2, 2, 2] = high_rho
density[6, 6, 6] = high_rho
# put a particle at the center of one of them
dx = 1. / n_c
px = 2.5 * dx * np.ones(n_p)
data = {
"density": density,
"particle_mass": np.ones(n_p),
"particle_position_x": px,
"particle_position_y": px,
"particle_position_z": px
}
ds = load_uniform_grid(data, dims)
ad = ds.all_data()
master_clump = Clump(ad, ("gas", "density"))
master_clump.add_validator("min_cells", 1)
find_clumps(master_clump, 0.5, 2. * high_rho, 10.)
# there should be two children
assert_equal(len(master_clump.children), 2)
leaf_clumps = get_lowest_clumps(master_clump)
# two leaf clumps
assert_equal(len(leaf_clumps), 2)
# check some clump fields
assert_equal(master_clump.children[0]["density"][0].size, 1)
assert_equal(master_clump.children[0]["density"][0], ad["density"].max())
assert_equal(master_clump.children[0]["particle_mass"].size, 1)
assert_array_equal(master_clump.children[0]["particle_mass"],
ad["particle_mass"])
assert_equal(master_clump.children[1]["density"][0].size, 1)
assert_equal(master_clump.children[1]["density"][0], ad["density"].max())
assert_equal(master_clump.children[1]["particle_mass"].size, 0)
def test_clump_tree_save():
tmpdir = tempfile.mkdtemp()
curdir = os.getcwd()
os.chdir(tmpdir)
ds = data_dir_load(i30)
data_source = ds.disk([0.5, 0.5, 0.5], [0.0, 0.0, 1.0], (8, "kpc"),
(1, "kpc"))
field = ("gas", "density")
step = 2.0
c_min = 10**np.floor(np.log10(data_source[field]).min())
c_max = 10**np.floor(np.log10(data_source[field]).max() + 1)
master_clump = Clump(data_source, field)
master_clump.add_info_item("center_of_mass")
master_clump.add_validator("min_cells", 20)
find_clumps(master_clump, c_min, c_max, step)
leaf_clumps = master_clump.leaves
fn = master_clump.save_as_dataset(fields=[
("gas", "density"),
("index", "x"),
("index", "y"),
("index", "z"),
("all", "particle_mass"),
])
ds2 = load(fn)
# compare clumps in the tree
t1 = [c for c in master_clump]
t2 = [c for c in ds2.tree]
mt1 = ds.arr([c.info["cell_mass"][1] for c in t1])
mt2 = ds2.arr([c["clump", "cell_mass"] for c in t2])
it1 = np.array(np.argsort(mt1).astype(int))
it2 = np.array(np.argsort(mt2).astype(int))
assert_array_equal(mt1[it1], mt2[it2])
for i1, i2 in zip(it1, it2):
ct1 = t1[i1]
ct2 = t2[i2]
assert_array_equal(ct1["gas", "density"], ct2["grid", "density"])
assert_array_equal(ct1["all", "particle_mass"], ct2["all",
"particle_mass"])
# compare leaf clumps
c1 = [c for c in leaf_clumps]
c2 = [c for c in ds2.leaves]
mc1 = ds.arr([c.info["cell_mass"][1] for c in c1])
mc2 = ds2.arr([c["clump", "cell_mass"] for c in c2])
ic1 = np.array(np.argsort(mc1).astype(int))
ic2 = np.array(np.argsort(mc2).astype(int))
assert_array_equal(mc1[ic1], mc2[ic2])
os.chdir(curdir)
shutil.rmtree(tmpdir)
def master_clump(self):
if not self._master_clump:
clump_file = os.path.join(CLUMP_DIR,
'{}_clumps.h5'.format(self.max_level))
# TODO: Fix file format -- saved dataset loses attributes/isn't
# loaded as the right type
orig_file_cache = self.file_cache
self.file_cache = False
if self.file_cache and os.path.isfile(clump_file):
self._master_clump = yt.load(clump_file)
else:
self._master_clump = Clump(self.disk, ('gas', "density"))
find_clumps(
clump=self._master_clump,
min_val=self.disk["density"].min(),
max_val=self.disk["density"].max(),
d_clump=8.0, # Step size
)
if self.file_cache:
self._master_clump.save_as_dataset(clump_file, [
'density',
])
self.file_cache = orig_file_cache
return self._master_clump
class ClumpFinder:
def __init__(self, max_level, label="", file_cache=True):
if not os.path.exists(CUBE_DIR):
os.makedirs(CUBE_DIR)
if not os.path.exists(PLOT_DIR):
os.makedirs(PLOT_DIR)
if not os.path.exists(CLUMP_DIR):
os.makedirs(CLUMP_DIR)
self._cube_data = {}
self._ramses_ds = None
self._cube_ds = None
self._disk = None
self._master_clump = None
self._leaf_clumps = None
self._clump_quantities = None
self._molecular_clouds = None
self.max_level = int(max_level)
self.file_cache = file_cache
if label:
self.label = label
else:
self.label = max_level
@property
def ramses_ds(self):
if not self._ramses_ds:
self._ramses_ds = yt.load(RAMSES_INPUT_INFO)
return self._ramses_ds
def cube_data(self, sim_type):
if not sim_type in self._cube_data:
self._cube_data[sim_type] = RamsesData(
idir=RAMSES_INPUT_DIR,
sim_type=sim_type,
xmin=GALAXY_CENTRE[0] - CUBE_PADDING,
xmax=GALAXY_CENTRE[0] + CUBE_PADDING,
ymin=GALAXY_CENTRE[1] - CUBE_PADDING,
ymax=GALAXY_CENTRE[1] + CUBE_PADDING,
zmin=GALAXY_CENTRE[2] - CUBE_PADDING,
zmax=GALAXY_CENTRE[2] + CUBE_PADDING,
lmax=self.max_level,
save_dir=CUBE_DIR,
use_file_cache=self.file_cache,
)
return self._cube_data[sim_type]
@property
def cube_ds(self):
if not self._cube_ds:
self._cube_ds = yt.load_uniform_grid(
dict(
density=self.cube_data(SimTypes.DENSITY).cube,
velocity_x=self.cube_data(SimTypes.X_VELOCITY).cube,
velocity_y=self.cube_data(SimTypes.Y_VELOCITY).cube,
velocity_z=self.cube_data(SimTypes.Z_VELOCITY).cube,
pressure=self.cube_data(SimTypes.PRESSURE).cube,
),
self.cube_data(SimTypes.DENSITY).cube.shape,
# TODO: Fix scaling. Doesn't find many clumps with this enabled.
#length_unit=self.ramses_ds.length_unit/512,#3080*6.02,
)
return self._cube_ds
@property
def disk(self):
if not self._disk:
self._disk = self.cube_ds.disk(
GALAXY_CENTRE,
[0., 0., 1.],
(1, 'kpc'),
(0.5, 'kpc'),
)
return self._disk
@property
def master_clump(self):
if not self._master_clump:
clump_file = os.path.join(CLUMP_DIR,
'{}_clumps.h5'.format(self.max_level))
# TODO: Fix file format -- saved dataset loses attributes/isn't
# loaded as the right type
orig_file_cache = self.file_cache
self.file_cache = False
if self.file_cache and os.path.isfile(clump_file):
self._master_clump = yt.load(clump_file)
else:
self._master_clump = Clump(self.disk, ('gas', "density"))
find_clumps(
clump=self._master_clump,
min_val=self.disk["density"].min(),
max_val=self.disk["density"].max(),
d_clump=8.0, # Step size
)
if self.file_cache:
self._master_clump.save_as_dataset(clump_file, [
'density',
])
self.file_cache = orig_file_cache
return self._master_clump
@property
def leaf_clumps(self):
if not self._leaf_clumps:
self._leaf_clumps = self.master_clump.leaves
return self._leaf_clumps
@property
def clump_quantities(self):
if not self._clump_quantities:
self._clump_quantities = []
for clump in self.leaf_clumps:
self._clump_quantities.append({
'clump':
clump,
'volume':
clump.data.volume().to_value(),
'mass':
clump.data.quantities.total_mass().to_value()[0],
'velocity_x_mean':
clump.data['velocity_x'].mean(),
'velocity_y_mean':
clump.data['velocity_y'].mean(),
'velocity_z_mean':
clump.data['velocity_z'].mean(),
'velocity_x_var':
clump.data['velocity_x'].var(),
'velocity_y_var':
clump.data['velocity_y'].var(),
'velocity_z_var':
clump.data['velocity_z'].var(),
'pressure_mean':
clump.data['pressure'].mean(),
})
self._clump_quantities[-1]['density'] = (
self._clump_quantities[-1]['mass'] /
self._clump_quantities[-1]['volume'])
(
self._clump_quantities[-1]['bulk_velocity_0'],
self._clump_quantities[-1]['bulk_velocity_1'],
self._clump_quantities[-1]['bulk_velocity_2'],
) = clump.quantities.bulk_velocity().to_value()
return self._clump_quantities
@property
def molecular_clouds(self):
if not self._molecular_clouds:
self._molecular_clouds = [
cq for cq in self.clump_quantities
if cq['density'] >= CLOUD_DENSITY_THRESHOLD
]
return self._molecular_clouds
data_source = ds.disk([0.5, 0.5, 0.5], [0.0, 0.0, 1.0], (8, "kpc"), (1, "kpc"))
# the field to be used for contouring
field = ("gas", "density")
# This is the multiplicative interval between contours.
step = 2.0
# Now we set some sane min/max values between which we want to find contours.
# This is how we tell the clump finder what to look for -- it won't look for
# contours connected below or above these threshold values.
c_min = 10**np.floor(np.log10(data_source[field]).min())
c_max = 10**np.floor(np.log10(data_source[field]).max() + 1)
# Now find get our 'base' clump -- this one just covers the whole domain.
master_clump = Clump(data_source, field)
# Add a "validator" to weed out clumps with less than 20 cells.
# As many validators can be added as you want.
master_clump.add_validator("min_cells", 20)
# Calculate center of mass for all clumps.
master_clump.add_info_item("center_of_mass")
# Begin clump finding.
find_clumps(master_clump, c_min, c_max, step)
# Save the clump tree as a reloadable dataset
fn = master_clump.save_as_dataset(fields=[("gas",
"density"), ("all",
"particle_mass")])
ylim = -1.79040182984184e21
bounds = {
'xmin': 2.1 * pow(10, 22),
'xmax': 2.5 * pow(10, 22),
'ymin': float(min(ad['y']).value),
'ymax': ylim
}
dsSelect = ad.include_inside('x', bounds['xmin'], bounds['xmax'])
dsSelect = dsSelect.include_inside('y', bounds['ymin'], bounds['ymax'])
#%%
c_min = 10**np.floor(np.log10(dsSelect['density']).min())
c_max = 10**np.floor(np.log10(dsSelect['density']).max() + 1)
master_clump = Clump(dsSelect, 'density')
#satisfy this condition to be your own clump
#pre-made validators are minimum cells and gravitational boundedness
master_clump.add_validator("min_cells", 20)
#add a custom validator
def _minimum_temp(clump, min_temp):
return False not in (clump['temp'] >= min_temp)
add_validator("min_temp", _minimum_temp)
master_clump.add_validator("min_temp", (10**4))
#if you get keyerror 1350, rerun/setup the code from the top.
data_dir = os.path.dirname(os.path.abspath(ds.directory))
hfn = os.path.join(data_dir, 'halo_catalogs/profile_catalogs',
'%s.0.h5' % ds.parameter_filename)
hds = yt.load(hfn)
center = reunit(ds, hds.r['particle_position'][0], 'unitary')
radius = 0.1 * reunit(ds, hds.r['virial_radius'][0], 'unitary')
yt.mylog.info('Finding clumps within %s.' % radius.to('pc'))
data_source = ds.sphere(center, radius)
field = ("gas", "density")
step = 2.0
c_min = 10**np.floor(np.log10(data_source[field]).min())
c_max = 10**np.floor(np.log10(data_source[field]).max() + 1)
master_clump = Clump(data_source, field)
output_dir = "clumps/"
ensure_dir(output_dir)
master_clump.add_validator("future_bound",
use_thermal_energy=True,
truncate=True,
include_cooling=True)
master_clump.add_info_item("center_of_mass")
master_clump.add_info_item("min_number_density")
master_clump.add_info_item("max_number_density")
master_clump.add_info_item("jeans_mass")
find_clumps(master_clump, c_min, c_max, step)
#%%
### Experiment with clumps
ds = yt.load(filename)
ylim = -1.79040182984184e21
bounds = {
'xmin': 2.1 * pow(10, 22),
'xmax': 2.5 * pow(10, 22),
'ymin': float(min(ad['y']).value),
'ymax': ylim
}
ad = ds.all_data()
dsSelect = ad.include_inside('x', bounds['xmin'], bounds['xmax'])
dsSelect = dsSelect.include_inside('y', bounds['ymin'], bounds['ymax'])
#%%
### Clumps cont'd
c_min = 10**np.floor(np.log10(dsSelect['temp']).min())
c_max = 10**np.floor(np.log10(dsSelect['temp']).max() + 1)
master_clump = Clump(dsSelect, 'temp')
master_clump.add_validator("min_cells", 20)
## this takes a VERY long time!
find_clumps(master_clump, c_min, c_max, 2.0)
leaf_clumps = master_clump.leaves
prj = yt.ProjectionPlot(ds, "z", 'temp', center="c", width=(20, "kpc"))
prj.annotate_clumps(leaf_clumps)
slc.save(
"/Users/wongb/Documents/Python_Scripts/YT_Test_Plots/HDF5/clump_test_80B")
def test_clump_finding():
n_c = 8
n_p = 1
dims = (n_c, n_c, n_c)
density = np.ones(dims)
high_rho = 10.0
# add a couple disconnected density enhancements
density[2, 2, 2] = high_rho
density[6, 6, 6] = high_rho
# put a particle at the center of one of them
dx = 1.0 / n_c
px = 2.5 * dx * np.ones(n_p)
data = {
"density": density,
"particle_mass": np.ones(n_p),
"particle_position_x": px,
"particle_position_y": px,
"particle_position_z": px,
}
ds = load_uniform_grid(data, dims)
ad = ds.all_data()
master_clump = Clump(ad, ("gas", "density"))
master_clump.add_validator("min_cells", 1)
def _total_volume(clump):
total_vol = clump.data.quantities.total_quantity(["cell_volume"
]).in_units("cm**3")
return "Cell Volume: %6e cm**3.", total_vol
add_clump_info("total_volume", _total_volume)
master_clump.add_info_item("total_volume")
find_clumps(master_clump, 0.5, 2.0 * high_rho, 10.0)
# there should be two children
assert_equal(len(master_clump.children), 2)
leaf_clumps = master_clump.leaves
for l in leaf_clumps:
keys = l.info.keys()
assert "total_cells" in keys
assert "cell_mass" in keys
assert "max_grid_level" in keys
assert "total_volume" in keys
# two leaf clumps
assert_equal(len(leaf_clumps), 2)
# check some clump fields
assert_equal(master_clump.children[0]["density"][0].size, 1)
assert_equal(master_clump.children[0]["density"][0], ad["density"].max())
assert_equal(master_clump.children[0]["particle_mass"].size, 1)
assert_array_equal(master_clump.children[0]["particle_mass"],
ad["particle_mass"])
assert_equal(master_clump.children[1]["density"][0].size, 1)
assert_equal(master_clump.children[1]["density"][0], ad["density"].max())
assert_equal(master_clump.children[1]["particle_mass"].size, 0)
# clean up global registry to avoid polluting other tests
del clump_info_registry["total_volume"]
