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_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., 1.],
(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 = get_lowest_clumps(master_clump)
fn = master_clump.save_as_dataset(fields=["density", "x", "y", "z",
"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.argsort(mt1).d.astype(int)
it2 = np.argsort(mt2).d.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.argsort(mc1).d.astype(int)
ic2 = np.argsort(mc2).d.astype(int)
assert_array_equal(mc1[ic1], mc2[ic2])
os.chdir(curdir)
shutil.rmtree(tmpdir)
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 ytclumpfind_H2(ds, dd, field, n_cut, c_max=None, step=3, N_cell_min=10, save=False, plot=False, saveplot=False, fold_out='./'):
'''
The way it's implemented now only works for single "density" field.
Parameter
---------
ds: yt StreamDataset
dd: YTRegion
field: tuple
tuple of str, e.g., ("gas", "density") or ("io", "....") or ("gas", "averaged_density"), etc... or just ("density") or ("stream", "density")
n_cut: float or int
defines lowest contour level to start searching from.
e.g., density to cut the clouds.
step: int
multiplicative interval between subsequent contours
N_cell_min: int
min. number of cell s.t. clump identified is not spurious
save: Boolean
if true, save the clump tree as a reloadable dataset
plot: Boolean
if true, will plot leaf clump
saveplot: boolean
if true, will save figure instead of showing it
fold_out: str
directory to save figures
Return
------
master_clump: the top of a hierarchy of clumps
leaf_clumps: list of individual clumps that have no children of their own
'''
if plot:
assert saveplot is True
# c_min = 10**np.floor(np.log10(dd[field]).min() )
# c_max = 10**np.floor(np.log10(dd[field]).max()+1)
# if n_cut < 1.e-5:
# n_cut = 1.0 # to make sure whatever comes out after multiplicative by
# step won't be too small
if step <= 1.0:
step += 1
c_min = n_cut
if c_max is None:
c_max = (dd[field]).max()
# assert np.isnan(c_min) is False and np.isnan(c_max) is False
print "min/max value for finding contours: ", c_min, c_max
# this "base clump" just covers the whole domain.
master_clump = Clump(dd, field)
# weed out clumps < N_cell_min cells.
master_clump.add_validator("min_cells", N_cell_min)
find_clumps(master_clump, c_min, c_max, step)
if save:
fn = master_clump.save_as_dataset(
fields=list(field)), # "particle_mass"])
# # To reload the clump dataset
# cds = yt.load(fn)
# leaf_clumps_reloaded = cds.leaves
# traverse clump hierarchy to get list of all 'leaf' clumps, which are the
# individual clumps that have no children of their own
leaf_clumps = get_lowest_clumps(master_clump)
# print "printing sth here...", ds.tree["clump", field]
# # *** AttributeError: 'StreamDataset' object has no attribute 'tree'
if plot:
plotclumps(ds=ds, leaf_clumps=leaf_clumps, field=field, master_clump=master_clump, saveplot=saveplot, fold_out=fold_out, n_cut=n_cut, N_cell_min=N_cell_min, step=step
)
return master_clump, leaf_clumps
