The snapshots are stored using the HDF5 format and are almost compatible with Gadget-2 (fully compatible outside of cosmological runs). They do, however, contain a large set of extensions including units, meta-data about the code and runs as well as facilities to quickly access the particles in a specific region of the simulation volume.

Meta-data about the code and run

Several groups at the root of the files only contain attributes and are used to store some meta-data about the simulation and the code itself.


The group /Code contains basic information about the version of the code that was used to run the simulation that dumped this snapshot. Versions of the libraries used to compile the code as well as information about the compiler and the flags used are stored. The most important element here are the git SHA and configuration parameters of the code. Alongside the compiler flags, policies and used parameters, these allow to reproduce exactly an older run.


The group /Cosmology contains information about the cosmological model used for this simulation. The first important field is the attribute Cosmological run which is set to 1 for cosmological runs and to 0 otherwise. This allows users to quickly distinguish between these two main modes. Most values in this section only make sense for cosmological runs.

All quantities are expressed in the internal system of units (note that this may differ from the units used in the particle arrays). Values like the look-back time are given for the redshift (or scale-factor) of this snapshot.


The group /Policy list the engine policies (defined in src/engine.h) that were activated in the run that dumped this snapshot. The policies roughly translate to the main run-time parameters of SWIFT.





This section of the meta-data mainly contains basic information about the flavour of sub-grid schemes used in the simulation. This is typically a list of attributes describing the parameters of the model. Users willing to add information can edit the functions chemistry_write_flavour(), cooling_write_flavour(), etc. located in the i/o header of each scheme.

The other important output stored in that group is the NamedColumns sub-group. In it, we store the names of the columns of larger particle arrays that are stored as large n-dimensional arrays. For instance, in the EAGLE model, the individual chemical element fractions of each particles are stored as a Nx9 array, where N is the number of particles (See Chemical tracers). This array is labeled ElementMassFractions and is used instead of 9 individual 1-d arrays. In the NamedColumns sub-group we store as an array of strings the name of each of the 9 individual columns. In this case, the name of the 9 elements traced by the model. This array has the same name as the particle array it corresponds to; here ElementMassFractions. The same mechanism is used for other quantities stored in a similar fashion. This allows external tools reading SWIFT snapshots to give meaningful names to more complex entries of the particle arrays.

Unit systems

The snapshots contain two groups at the root containing information about the unit systems used in the snapshots.

The main one Units contains the units used in the snapshot. In a similar fashion to what is done for the parameter files (see Internal Unit System), SWIFT specifies only the basic units. These are the units of mass (U_M), length (U_L), time (U_t), electric current (U_I) and temperature (U_T). These are specified in units of their CGS equivalents (gram, centimeter, second, Ampere, Kelvin). All the quantities present in the particle arrays are expressed in this system of units. For each quantity, SWIFT gives the conversion factor in terms of these units. For instance, the internal energy per unit mass would be expressed as U_L^2 U_t^-2, which in the CGS unit system translates to \(cm/s^2 = erg/g\).

The second group InternalCodeUnits contains the unit system that was used internally by the code when running the simulation. This is in most cases the same system as given in Units but since users can specify a different system for the snapshots, there might be cases where they differ. As this system only relates to what was used inside the code and not in the snapshots themselves, this group is mostly here to report on the code’s run-time behaviour and is used to express all the quantities in the meta-data (e.g. in the cosmology group or the softening lengths in the gravity group).

Used and unused run-time parameters

The groups /Parameters and UnusedParameters located at the root of the file contain the list of all the run-time parameters used by the run with their values and the list of parameters that were in the YAML but were not read. The content of these two groups is identical to the used_parameters.yml and unused_parameters.yml files produced by SWIFT when starting a run (See the File format and basic information section of the documentation).

Structure of the particle arrays

There are several groups that contain ‘auxiliary’ information, such as Header. Particle data is placed in separate groups depending of the type of the particles. The type use the naming convention of Gadget-2 (with the OWLS and EAGLE extensions). A more intuitive naming convention is given in the form of aliases within the file. The aliases are shown in the third column of the table.

HDF5 Group Name Physical Particle Type HDF5 alias In code enum part_type
/PartType0/ Gas /GasParticles/ swift_type_gas
/PartType1/ Dark Matter /DMParticles/ swift_type_dark_matter
/PartType2/ Background Dark Matter /DMBackgroundParticles/ swift_type_dark_matter_background
/PartType4/ Stars /StarsParticles/ swift_type_star
/PartType5/ Black Holes /BHParticles/ swift_type_black_hole

The last column in the table gives the enum value from part_type.h corresponding to a given entry in the files.

Each group contains a series of arrays corresponding to each field of the particles stored in the snapshots. The exact list of fields depends on what compile time options were used and what module was activated. A full list can be obtained by running SWIFT with the -o runtime option (See Output Selection for details). Each field contains a short description attribute giving a brief summary of what the quantity represents.

All the individual arrays created by SWIFT have had the Fletcher 32 check-sum filter applied by the HDF5 library when writing them. This means that any eventual data corruption on the disks will be detected and reported by the library when attempting to read the data.

Additionally, some compression filter may have been applied to the fields. See the Snapshots section of the parameter file description for more details.

Unit information for individual fields

Each particle field contains meta-data about the units and how to convert it to CGS in physical or co-moving frames. The meta-data is in part designed for users to directly read and in part for machine reading of the information. Each field contains the exponent of the scale-factor, reduced Hubble constant [1] and each of the 5 base units that is required to convert the field values to physical CGS units. These fields are:

Meta-data field name Description
U_L exponent Power of the length unit
U_M exponent Power of the mass unit
U_t exponent Power of the time unit
U_I exponent Power of the current unit
U_T exponent Power of the temperature unit
a-scale exponent Power of the scale-factor
h-scale exponent Power of the reduced Hubble constant

These are used by the swiftsimio python library to read units and we encourage users to use this meta-data directly in their automated tools.

As an example, the fluid densities (which are written in the co-moving frame) have the following (non-zero) conversion factors:

  • U_L exponent: -3
  • U_M exponent: 1
  • a-scale exponent: -3

This condensed information is stored in the string Expression for physical CGS units, which in the case of the densities would read a^-3 U_M U_L^-3 [ g cm^-3 ]. The values of the U_x can be found in the Units System group at the root of the snapshot (see above). Note that only unit factors with non-zero exponents are printed to this string.

Additionally, the meta-data contains the numerical conversion factor from the field to co-moving CGS and physical CGS assuming the units in the Unit System group. These are:

  • Conversion factor to CGS (not including cosmological corrections
  • Conversion factor to phyical CGS (including cosmological corrections)

These are designed for the users to directly use if they don’t want to compute the individual exponents themselves. As an example, in the case of the densities and assuming the usual system of units (\(10^{10} \rm{M}_\odot\), \(100 \rm{km/s}\), \(\rm{Mpc}\)) at redshift 0.1, the conversion factors are:

  • Conversion to CGS: \(6.76814403 \times 10^{-31}\)
  • Conversion to physical CGS: \(9.00808555 \times 10^{-31}\)

In the case of a non-cosmological simulation, these two expressions are identical since \(a=1\).

Quick access to particles via hash-tables

The particles are not sorted in a specific order when they are written to the snapshots. However, the particles are sorted into the top-level cell structure used internally by the code every time a tree rebuild is triggered. The top-level cells are a coarse-grained mesh but knowing which particle belongs to which cell can nevertheless be useful to rapidly access particles in a given region only.

One important caveat is that particles are free to drift out of their cells between rebuilds of the tree (but not by more than one cell-length). If one wants to have all the particles in a given cell, one has to read all the neighbouring cells as well. We note that for image making purposes, for instance to generate a slice, this is typically not necessary and reading just the cells of interest is sufficient.

At the root of the HDF5 file, the Cells group contains all the relevant information. The dimension of the top-level grid (a triplet of integers) is given by the attribute Cells/Meta-data/dimension and the size of each cell (a triplet of floating-point numbers) is given by the attribute Cells/Meta-data/size. All the cells have the same size but for non-cubic simulation volumes the cells themselves can have different sizes along each axis.

The /Cells/Centres array gives the centre of each of the top-level cells in the simulation volume. Both the cell sizes and positions of the centres are expressed in the unit system used for the snapshots (see above) and are hence consistent with the particle positions themselves.

Once the cell(s) containing the region of interest has been located, users can use the /Cells/Offsets/PartTypeN/Files, /Cells/Offsets/PartTypeN/Counts and /Cells/Offsets/PartTypeN/OffsetsInFile to retrieve the location of the particles of type N in the /PartTypeN arrays. These contain information about which file contains the particles of a given cell. It also gives the offset from the start of the /PartTypeN array in that file at which the particles of that cell are located and how many particles are in the cell. This allows to read a single contiguous section of the whole array by directly reading the slab starting at the offset and with the given length.

The cells, files, offsets in file and counts arrays are sorted spatially using C-style ordering. That means the inner-most loop runs over the z axis, then y axis and x is the slowest varying dimension.

In the case of a single-file snapshot, the Files array is just an array of zeroes since all the particles will be in the 0-th file. Note also that in the case of a multi-files snapshot, a cell is always contained in a single file.

As an example, if one is interested in retriving all the densities of the gas particles in the cell around the position [1, 1, 1] in a single-file snapstshot one could use a piece of code similar to:

import numpy as np
import h5py

snapshot_file = h5py.File("snapshot.hdf5", "r")

my_pos = [1, 1, 1]

# Read in the cell centres and size
nr_cells = f["/Cells/Meta-data"].attrs["nr_cells"]
centres = f["/Cells/Centres"][:,:]
size = f["/Cells/Meta-data"].attrs["size"]
half_size = size / 2.

# Look for the cell containing the position of interest.
# Note that since the cells are sorted spatially, we would formally
# not need to do this search and could jump directly to the correct 'i'.
my_cell = -1
for i in range(nr_cells):
   if my_pos[0] > centres[i, 0] - half_size[0] and my_pos[0] < centres[i, 0] + half_size[0] and
      my_pos[1] > centres[i, 1] - half_size[1] and my_pos[1] < centres[i, 1] + half_size[1] and
      my_pos[2] > centres[i, 2] - half_size[2] and my_pos[2] < centres[i, 2] + half_size[2]:
      my_cell = i

# Print the position of the centre of the cell of interest
centre = snapshot_file["/Cells/Centres"][my_cell, :]
print("Centre of the cell:", centre)

# Retrieve the offset and counts
my_offset = snapshot_file["/Cells/OffsetsInFile/PartType0"][my_cell]
my_count = snapshot_file["/Cells/Counts/PartType0"][my_cell]

# Get the densities of the particles in this cell
rho = snapshot_file["/PartType0/Density"][my_offset:my_offset + my_count]

For large simulations, this vastly reduces the amount of data that needs to be read from the disk.

Note that this is all automated in the swiftsimio python library and we highly encourage its use.

[1]Note that all quantities in SWIFT are always “h-free” in the sense that they are expressed in units withouy any h terms. This implies that the h-scale exponent field value is always 0. SWIFT nevertheless includes this field to be comprehensive and to prevent confusion with other software packages that express their quantities with h-full units.