import numpy as np
from yt.funcs import mylog
from yt.utilities.io_handler import BaseParticleIOHandler
from yt.utilities.on_demand_imports import _h5py as h5py
_pos_names = ["CenterOfMass", "CentreOfMass"]
[docs]
class IOHandlerOWLSSubfindHDF5(BaseParticleIOHandler):
_dataset_type = "subfind_hdf5"
_position_name = None
def __init__(self, ds):
super().__init__(ds)
self.offset_fields = set()
def _read_fluid_selection(self, chunks, selector, fields, size):
raise NotImplementedError
def _read_particle_coords(self, chunks, ptf):
# This will read chunks and yield the results.
for data_file in self._sorted_chunk_iterator(chunks):
with h5py.File(data_file.filename, mode="r") as f:
for ptype in sorted(ptf):
pcount = data_file.total_particles[ptype]
coords = f[ptype][self._position_name][()].astype("float64")
coords = np.resize(coords, (pcount, 3))
x = coords[:, 0]
y = coords[:, 1]
z = coords[:, 2]
yield ptype, (x, y, z), 0.0
def _yield_coordinates(self, data_file):
ptypes = self.ds.particle_types_raw
with h5py.File(data_file.filename, mode="r") as f:
for ptype in sorted(ptypes):
pcount = data_file.total_particles[ptype]
coords = f[ptype][self._position_name][()].astype("float64")
coords = np.resize(coords, (pcount, 3))
yield ptype, coords
def _read_offset_particle_field(self, field, data_file, fh):
field_data = np.empty(data_file.total_particles["FOF"], dtype="float64")
fofindex = (
np.arange(data_file.total_particles["FOF"]) + data_file.index_start["FOF"]
)
for offset_file in data_file.offset_files:
if fh.filename == offset_file.filename:
ofh = fh
else:
ofh = h5py.File(offset_file.filename, mode="r")
subindex = np.arange(offset_file.total_offset) + offset_file.offset_start
substart = max(fofindex[0] - subindex[0], 0)
subend = min(fofindex[-1] - subindex[0], subindex.size - 1)
fofstart = substart + subindex[0] - fofindex[0]
fofend = subend + subindex[0] - fofindex[0]
field_data[fofstart : fofend + 1] = ofh["SUBFIND"][field][
substart : subend + 1
]
return field_data
def _read_particle_fields(self, chunks, ptf, selector):
# Now we have all the sizes, and we can allocate
for data_file in self._sorted_chunk_iterator(chunks):
with h5py.File(data_file.filename, mode="r") as f:
for ptype, field_list in sorted(ptf.items()):
pcount = data_file.total_particles[ptype]
if pcount == 0:
continue
coords = f[ptype][self._position_name][()].astype("float64")
coords = np.resize(coords, (pcount, 3))
x = coords[:, 0]
y = coords[:, 1]
z = coords[:, 2]
mask = selector.select_points(x, y, z, 0.0)
del x, y, z
if mask is None:
continue
for field in field_list:
if field in self.offset_fields:
field_data = self._read_offset_particle_field(
field, data_file, f
)
else:
if field == "particle_identifier":
field_data = (
np.arange(data_file.total_particles[ptype])
+ data_file.index_start[ptype]
)
elif field in f[ptype]:
field_data = f[ptype][field][()].astype("float64")
else:
fname = field[: field.rfind("_")]
field_data = f[ptype][fname][()].astype("float64")
my_div = field_data.size / pcount
if my_div > 1:
field_data = np.resize(
field_data, (int(pcount), int(my_div))
)
findex = int(field[field.rfind("_") + 1 :])
field_data = field_data[:, findex]
data = field_data[mask]
yield (ptype, field), data
def _count_particles(self, data_file):
with h5py.File(data_file.filename, mode="r") as f:
pcount = {"FOF": get_one_attr(f["FOF"], ["Number_of_groups", "Ngroups"])}
if "SUBFIND" in f:
# We need this to figure out where the offset fields are stored.
data_file.total_offset = get_one_attr(
f["SUBFIND"], ["Number_of_groups", "Ngroups"]
)
pcount["SUBFIND"] = get_one_attr(
f["FOF"], ["Number_of_subgroups", "Nsubgroups"]
)
else:
data_file.total_offset = 0
pcount["SUBFIND"] = 0
return pcount
def _identify_fields(self, data_file):
fields = []
pcount = data_file.total_particles
if sum(pcount.values()) == 0:
return fields, {}
with h5py.File(data_file.filename, mode="r") as f:
for ptype in self.ds.particle_types_raw:
if data_file.total_particles[ptype] == 0:
continue
self._identify_position_name(f[ptype])
fields.append((ptype, "particle_identifier"))
my_fields, my_offset_fields = subfind_field_list(
f[ptype], ptype, data_file.total_particles
)
fields.extend(my_fields)
self.offset_fields = self.offset_fields.union(set(my_offset_fields))
return fields, {}
def _identify_position_name(self, fh):
if self._position_name is not None:
return
for pname in _pos_names:
if pname in fh:
self._position_name = pname
return
[docs]
def get_one_attr(fh, attrs, default=None, error=True):
"""
Try getting from a list of attrs. Return the first one that exists.
"""
for attr in attrs:
if attr in fh.attrs:
return fh.attrs[attr]
if error:
raise RuntimeError(
f"Could not find any of these attributes: {attrs}. "
f"Available attributes: {fh.attrs.keys()}"
)
return default
[docs]
def subfind_field_list(fh, ptype, pcount):
fields = []
offset_fields = []
for field in fh.keys():
if "PartType" in field:
# These are halo member particles
continue
elif isinstance(fh[field], h5py.Group):
my_fields, my_offset_fields = subfind_field_list(fh[field], ptype, pcount)
fields.extend(my_fields)
my_offset_fields.extend(offset_fields)
else:
if not fh[field].size % pcount[ptype]:
my_div = fh[field].size / pcount[ptype]
fname = fh[field].name[fh[field].name.find(ptype) + len(ptype) + 1 :]
if my_div > 1:
for i in range(int(my_div)):
fields.append((ptype, "%s_%d" % (fname, i)))
else:
fields.append((ptype, fname))
elif (
ptype == "SUBFIND"
and not fh[field].size % fh["/SUBFIND"].attrs["Number_of_groups"]
):
# These are actually FOF fields, but they were written after
# a load balancing step moved halos around and thus they do not
# correspond to the halos stored in the FOF group.
my_div = fh[field].size / fh["/SUBFIND"].attrs["Number_of_groups"]
fname = fh[field].name[fh[field].name.find(ptype) + len(ptype) + 1 :]
if my_div > 1:
for i in range(int(my_div)):
fields.append(("FOF", "%s_%d" % (fname, i)))
else:
fields.append(("FOF", fname))
offset_fields.append(fname)
else:
mylog.warning(
"Cannot add field (%s, %s) with size %d.",
ptype,
fh[field].name,
fh[field].size,
)
continue
return fields, offset_fields