gizmo-analysis 1.0.1

read and analyze Gizmo simulations

Description

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

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Requirements

python 3, numpy, scipy, h5py, matplotlib

This package also requires the utilities/ Python package for low-level utility functions.

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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_elementtracer.py

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

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

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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

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Installing

The easiest way to install this packages and all its dependencies is by using pip or conda.

python -m pip install gizmo_analysis

To install from source, you can clone the latest version of gizmo_analysis from bitbucket using git:

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

To build and install the project, inside the cloned gizmo_analysis directory:

python -m pip install .

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Using

Once installed, you can call individual modules like this:

import gizmo_analysis
gizmo_analysis.gizmo_io

or more succinctly like this

import gizmo_analysis as gizmo
gizmo.io

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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).'