pyread-swift 1.0.3

An MPI read routine for Swift simulation snapshots

pyread_swift is an MPI read routine for swiftsim snapshots, very similar in style to John Helly's read_eagle code to read EAGLE snapshots.

The package can read swiftsim snapshots both in "collective" (i.e., multiple MPI ranks read from a single file simultaneously) and "distributed" (i.e., each MPI reads an individual snapshot file part in isolation) modes.

Installation

Requirements

• OpenMPI or other MPI library
• python>=3.8

Recommended modules when working on COSMA7:

module load gnu_comp/11.1.0 openmpi/4.1.4 parallel_hdf5/1.12.0 python/3.9.1-C7

Given the need for a parallel HDF5 installation, it is recommended you install pyread_swift within a virtual/conda environment. However you can ofcourse also install directly into your base Python environment if you prefer.

First make sure your pip is up-to-date:

python3 -m pip install --upgrade pip

Method 1) Installation from PyPi

The easiest method is to install from PyPI

python3 -m pip install pyread-swift

Method 2) Installation from source

Or, you can install directly from source.

First clone the repo, then you can install the pyread_swift package by typing the following in the root git directory:

git clone https://github.com/stuartmcalpine/pyread_swift.git
cd pyread_swift
python3 -m pip install .

which will install pyread_swift and any dependencies.

MPI installation for collective reading

If you are using pyread_swift to load large snapshots over MPI collectively (i.e., multiple cores read in parallel from the same file), a bit of additional setup is required.

Make sure you have hdf5 installed with parallel compatibility (see here for details).

Then, uninstall any versions of h5py and reinstall from source:

python3 -m pip uninstall h5py
MPICC=mpicc CC=mpicc HDF5_MPI="ON" python3 -m pip install --no-binary=h5py h5py

If pip struggles to find your HDF5 libraries automatically, e.g., error: libhdf5.so: cannot open shared object file: No such file or directory. You may have to specify the path to the HDF5 installation manually, i.e., HDF5_DIR=/path/to/hdf5/lib (see here for more details).

For our COSMA7 setup, that would be:

HDF5_DIR="/cosma/local/parallel-hdf5//gnu_11.1.0_ompi_4.1.4/1.12.0/"

Usage

pyread_swift is build around a primary read wrapper, called SwiftSnapshot. The snapshot particles are loaded into, stored, and manipulated by this object.

Reading follows these four steps (see also the examples below):

• Initialize a SwiftSnapshot object pointing to the location of the HDF5 file.

• Select the spatial region you want to extract the particles from using the select_region() routine.

• Split the selection over the MPI ranks using the split_selection() routine.

• Read a selected property of the particles using the read_dataset() routine.

Input parameters to SwiftSnapshot

Example usage (No MPI case)

from pyread_swift import SwiftSnapshot

# Set up pyread_swift object pointing at HDF5 snapshot file (or a file part). 
snapshot = "/path/to/snap/part.0.hdf5"
swift = SwiftSnapshot(snapshot)

# Select region to load from.
parttype = 1 # Dark matter
region = [0,100,0,100,0,100] # [xlo,xhi,ylo,yhi,zlo,zhi]
swift.select_region(parttype, *region)

# Divide selection between ranks (needs to be invoked even for non-mpi case).
swift.split_selection()

# Read data.
ids = swift.read_dataset(parttype, "ParticleIDs")

Example usage (MPI case)

from mpi4py import MPI
from pyread_swift import SwiftSnapshot

# MPI communicator.
comm = MPI.COMM_WORLD

# Set up read_swift object pointing at HDF5 snapshot file (or a file part). 
snapshot = "/path/to/snap/part.0.hdf5"
swift = SwiftSnapshot(snapshot, comm=comm)

# Select region to load from.
parttype = 1 # Dark matter
region = [0,100,0,100,0,100] # [xlo,xhi,ylo,yhi,zlo,zhi]
swift.select_region(parttype, *region)

# Divide selection between ranks.
swift.split_selection()

# Read data.
ids = swift.read_dataset(parttype, "ParticleIDs")