Description

Python package for reading and analyzing simulations generated using the Gizmo code, in particular, the FIRE cosmological simulations of galaxy formation.

Requirements

python 3, numpy, scipy, h5py, matplotlib

This package also requires the utilities/ Python package for various utility functions.

Contents

gizmo_analysis

gizmo_io.py

• read particles from Gizmo snapshot files

gizmo_plot.py

• analyze and plot particle data

gizmo_track.py

• track star particles and gas cells across snapshots

gizmo_file.py

• clean, compress, delete, or transfer Gizmo snapshot files

gizmo_diagnostic.py

• run diagnostics on Gizmo simulations

gizmo_ic.py

• generate cosmological zoom-in initial conditions from existing snapshot files

gizmo_star.py

• models of stellar evolution as implemented in FIRE-2 and FIRE-3: rates and yields from supernovae (core-collapse and white-dwarf) and stellar winds

gizmo_enrichtracer.py

• generate elemental abundances in star particles and gas cells in post-processing, using the enrichment-tracer model

tutorials

gizmo_tutorial_read.ipynb

• Jupyter notebook tutorial for reading particle data, understanding its data structure and units

gizmo_tutorial_analysis.ipynb

• Jupyter notebook tutorial for analyzing and plotting particle data

transcript.txt

• Transcript of Zach Hafen's video tutorial (https://www.youtube.com/watch?v=bl-rpzE8hrU) on using this package to read FIRE simulations.

data

snapshot_times.txt

• example file for storing information about snapshots: scale-factors, redshifts, times, etc

Units

Unless otherwise noted, this package stores all quantities in (combinations of) these base units

• mass [M_sun]
• position [kpc comoving]
• distance, radius [kpc physical]
• time [Gyr]
• temperature [K]
• magnetic field [Gauss]
• elemental abundance [linear mass fraction]

These are the common exceptions to those standards

• velocity [km/s]
• acceleration [km/s / Gyr]
• gravitational potential [km^2 / s^2]
• rates (star formation, cooling, accretion) [M_sun / yr]
• metallicity (if converted from stored massfraction) [log10(mass_fraction / mass_fraction_solar)], using Asplund et al 2009 for Solar

Installing

The easiest way to install this packages and all of its dependencies is by using pip:

python -m pip install gizmo_analysis

Alternately, and especially if you want to ensure that you have the latest version, you can clone and install from bitbucket, in one of two ways:

using HTTPS:

git clone https://awetzel@bitbucket.org/awetzel/gizmo_analysis.git

or using SSH:

git clone git@bitbucket.org:awetzel/gizmo_analysis.git

Then do one of the following:

1. either point your PYTHONPATH to this repository (and also install and point PYTHONPATH to the utilities/ repository that it depends on)

2. or build and install this project via pip by going inside the top-level gizmo_analysis/ directory and doing:

python -m pip install .

Using

Once installed, you can call individual modules like this:

import gizmo_analysis as gizmo
gizmo.io

Citing

If you use this package, please cite it, along the lines of: 'This work used GizmoAnalysis (http://ascl.net/2002.015), which first was used in Wetzel et al. 2016 (https://ui.adsabs.harvard.edu/abs/2016ApJ...827L..23W).'