Offset files are utility files designed to allow an easy navigation between other files. There is one such file for each snapshot of each run.
They provide a mapping between halo or particle indices and their memory position (i.e. array indices in the files).
The available dataset (organized in three groups) are described in the table below (click to open).
import numpy as np
import h5py
def get_global_index(simpath, snap, offset_type, local_index, chunk):
"""
Returns the global index (i.e. across all chunks, considered sequentially) of a particle/group/subgroup.
Parameters
----------
simpath : string
path to the base simulation directory
snap : int
number of the snapshot to consider
offset_type : string
string identifying the type of object considered. Accepted values: 'particle', 'group', 'subhalo'
local_index : int
index of the object in the chunk file
chunk : int
number of the chunk file the object resides in
Returns
-------
global_index : int
index of the object across all chunk files
"""
assert(offset_type in ['particle', 'group', 'subhalo'])
if offset_type == 'particle':
offset_file_key = 'FileOffsets/SnapByType'
elif offset_type == 'group':
offset_file_key = 'FileOffsets/Group'
elif offset_type == 'subhalo':
offset_file_key = 'FileOffsets/Subhalo'
with h5py.File(f'{simpath}/postprocessing/offsets/offsets_{snap:03d}.hdf5', 'r') as offset_file:
global_index = offset_file[offset_file_key][chunk] + local_index
return global_index
def get_chunk_and_local_index(simpath, snap, offset_type, global_index, ptype=-1):
"""
Returns the chunk file number and local index (i.e. within the chunk file) of a particle/group/subgroup.
Parameters
----------
simpath : string
path to the base simulation directory
snap : int
number of the snapshot to consider
offset_type : string
string identifying the type of object considered. Accepted values: 'particle', 'group', 'subhalo'
global_index : int
index of the object across all chunk files
ptype : int, required for offset_type == 'particle', ignored otherwise
: particle type
Returns
-------
chunk : int
number of the first chunk file the object resides in
local_index : int
index of the object in the chunk file
"""
assert(offset_type in ['particle', 'group', 'subhalo'])
if offset_type == 'particle':
assert(ptype>=0 and ptype<6)
if offset_type == 'particle':
offset_file_key = 'FileOffsets/SnapByType'
elif offset_type == 'group':
offset_file_key = 'FileOffsets/Group'
elif offset_type == 'subhalo':
offset_file_key = 'FileOffsets/Subhalo'
with h5py.File(f'{simpath}/postprocessing/offsets/offsets_{snap:03d}.hdf5', 'r') as offset_file:
if offset_type == 'particle':
chunk = np.where(offset_file[offset_file_key][:, ptype] <= global_index)[0][-1]
local_index = global_index - offset_file[offset_file_key][chunk, ptype]
else:
chunk = np.where(offset_file[offset_file_key][()] <= global_index)[0][-1]
local_index = global_index - offset_file[offset_file_key][chunk]
return chunk, local_index
def get_particles_global_index_for_halo(sim, snap, halo_type, global_index):
"""
Returns the chunk file number and local index (i.e. within the chunk file) of a particle/group/subgroup.
Parameters
----------
simpath : string
path to the base simulation directory
snap : int
number of the snapshot to consider
halo_type : string
string identifying the type of halo considered. Accepted values: 'group', 'subhalo'
global_index : int
index of the halo in the snapshot (across all chunk files)
Returns
-------
global_particle_index : [int]*6
global index of the first particle of the halo, for each particle type
"""
assert(halo_type in ['group', 'subhalo'])
if halo_type == 'group':
offset_file_key = 'Group/SnapByType'
elif halo_type == 'subhalo':
offset_file_key = 'Subhalo/SnapByType'
with h5py.File(f'{simpath}/simulations.hdf5', 'r') as sim_file:
Nchunks = sim_file[f'Snapshot/{snap}/Header'].attrs['NumFilesPerSnapshot']
with h5py.File(f'{simpath}/postprocessing/offsets/offsets_{snap:03d}.hdf5', 'r') as offset_file:
global_particle_index = offset_file[offset_file_key][global_index]
return global_particle_index
def get_location_of_particles_in_halo(sim, snap, halo_type, global_index, verbose=False):
"""
Returns the particles that belong to a group/subgroup.
Parameters
----------
simpath : string
path to the base simulation directory
snap : int
number of the snapshot to consider
halo_type : string
string identifying the type of halo considered. Accepted values: 'group', 'subhalo'
global_index : int
index of the halo in the snapshot (across all chunk files)
verbose : bool, optional (default=False)
print info to stdout
Returns
-------
files : list of lists of strings
filenames of the snapshot chunk files containing particle of a given ptype
start_index : list of lists of int
initial index in the chunk file for particles of the halo
final_index : list of lists of int
final index in the chunk file for particles of the halo
Example usage
-------------
files, start_index, final_index = get_location_of_particles_in_halo('Thesan-1', 80, 'subhalo', 43)
gas_positions = []
for filename, i_start, i_end in zip(files[0], start_index[0], final_index[0]):
with h5py.File(filename, 'r') as f:
gas_positions.append( f['PartType0/Coordinates'][i_start:i_end] )
gas_positions = np.concatenate( gas_positions )
"""
assert(halo_type in ['group', 'subhalo'])
if halo_type == 'group':
group_file_key = 'Group/GroupLenType'
elif halo_type == 'subhalo':
group_file_key = 'Subhalo/SubhaloLenType'
with h5py.File(f'{simpath}/simulations.hdf5', 'r') as sim_file:
Nchunks = sim_file[f'Snapshot/{snap}/Header'].attrs['NumFilesPerSnapshot']
ichunk, ihalo = get_chunk_and_local_index(simpath, snap, halo_type, global_index)
with h5py.File(f'{path}/output/groups_{snap:03d}/fof_subhalo_tab_{snap:03d}.{ichunk}.hdf5', 'r') as groups_file:
halo_num_particles = groups_file[group_file_key][ihalo]
nonzero_ptypes = np.where(halo_num_particles>0)[0]
global_particle_index = get_particles_global_index_for_halo(simpath, snap, halo_type, global_index)
particle_chunks = np.array([-1]*6)
particle_local_index = np.array([-1]*6)
for ptype in range(6):
if ptype in nonzero_ptypes:
c, li = get_chunk_and_local_index(simpath, snap, 'particle', global_particle_index[ptype], ptype=ptype)
particle_chunks[ptype] = c
particle_local_index[ptype] = li
if verbose:
print(f"ichunk = {ichunk}, ihalo = {ihalo}")
print(f"global_index = {global_index}, global_particle_index = {global_particle_index}, particle_chunks = {particle_chunks}, particle_local_index = {particle_local_index}, halo_num_particles = {halo_num_particles}")
files = [[], [], [], [], [], []]
start_index = [[], [], [], [], [], []]
final_index = [[], [], [], [], [], []]
for ptype in nonzero_ptypes:
num_read = 0
extra_snap_chunk = 0
while(num_read < halo_num_particles[ptype]):
snapshot_file_name = f"{path}/output/snapdir_{snap:03d}/snap_{snap:03d}.{particle_chunks[ptype]+extra_snap_chunk}.hdf5"
with h5py.File(snapshot_file_name, 'r') as snapshot_file:
particles_here = min(halo_num_particles[ptype]-num_read, snapshot_file['Header'].attrs['NumPart_ThisFile'][ptype]-particle_local_index[ptype])
if verbose:
print( f" ptype = {ptype}, extra_snap_chunk = {extra_snap_chunk}, num_read = {num_read}, particles_here = {particles_here}, halo_num_particles[ptype] = {halo_num_particles[ptype]}, particle_local_index[ptype] = {particle_local_index[ptype]}" )
#particle_local_index[ptype]:particle_local_index[ptype]+particles_here]
files[ptype].append( snapshot_file_name )
start_index[ptype].append( particle_local_index[ptype] )
final_index[ptype].append( particle_local_index[ptype]+particles_here )
#update quantities
num_read += particles_here
extra_snap_chunk += 1
particle_local_index[ptype] = 0
return files, start_index, final_index
