Quick Start¶

Set-up¶

Install Hoki¶

To install the most recent stable release of hoki you can use:

sudo pip3 install --user hoki

If you are feeling adventurous and want the most recent (in development) version of hoki, you can clone our GitHub repository

Download the tutorials¶

They can be found in the side-bar to read, but you can dowload the jupyter notebooks so you can play with them later. For the SED fitting tutorials that were released with v1.7.1, since they have a large data file they have been put on Zenodo:

Download the BPASS models¶

For the BPASSv2.2.1 starter kit with the stellar library and fiducial model outputs:

Full BPASS models can be downloaded from:

Download	Hoki Compatible	Release Date	Reference
BPASSv2.2	Yes	July 2018	Stanway & Eldridge (2018)
BPASSv2.1	untested	October 2017	Eldridge, Stanway, Xiao, et al. (2017)
BPASSv2.0	untested	–	–
BPASSv1	untested	–	–

hoki is dedicated to being an interface with the BPASS models, but given the substancial size of the entire set of models, they are not downloaded upon installation of hoki, and you should download the models you want to work on.

Loading in Data¶

Tip

More details on the outputs mentioned below can be found in the BPASS manual.

Stellar Population Outputs¶

A stellar output file can be loaded in using the model_output() function in the load module.

from hoki import load

output = load.model_output('path_to_output')

The function will figure out based on the file name what data is being loaded in and will return the appropriate data format: pandas.DataFrames in most cases, apart from HR diagrams, which have their own HRDiagrams class – because they’re quite a complex data structure.

Here we summarise the shape of the outputs (51 time bins) for a given metalicity and IMF.

Output	File Name Root	Shape
Massive star type numbers	numbers	51 x 21
Supernova Rates	supernova	51 x 18
Energy and elemental yields	yields	51 x 9
Stellar mass remaining at the end	starmass	51 x 3
HR diagrams	hrs	51 x 100 x 100 x 3 x 3

Spectral Synthesis Outputs¶

The spectral synthesis output files can be also loaded in using the model_output() function in the load module. All outputs are returned as pandas.DataFrames with sensible column names.

from hoki import load

output = load.model_output('path_to_output')

Output	File Name Root	Shape
Spectra (SEDs)	spectra	52x10E5
Ionizing flux predictions	ionizing	51x5
Colours (broad-band)	colours	51x26

The full suite of stellar models is also available from the BPASS website (careful, the file is big ~50GB), and they are required to make colour magnitude diagram (CMD) such as in Figure 24 of BPASSv2.1. Creating these CMD and exploring these files is very tricky - in a future release hoki will offer features to make this straight forward.

Stellar Models¶

In addition to the population and spectral synthesis outputs, the stellar models are also available as a BPASS data product. They can be downloaded from the google drive: the name of the folder containing the most recent models is bpass-v2.2-newmodels.

Warning

These folder is ~50 GB. Make sure you have a good internet connection and sufficient space.

The stellar models are required to make Colour-Magnitude Diagrams (see RECIPES) and other deeper searches within the models that are not summarised in the population or spectral synthesis outputs.

Note

This is where the files names model_input become necesary. They are not human readable but are used within hoki to apply the correct algorithm to the stellar models in order to collate them correctly. (So don’t panic if you open them and wonder what is going on).

Citing Hoki¶

Hoki has been reviewed and published by the Journal Of Open Source Software! Click the button below to access the online publication.

https://joss.theoj.org/papers/10.21105/joss.01987/status.svg

If you use hoki for your science, please include the following reference in your paper:

@ARTICLE{2020JOSS....5.1987S,
    author = {{Stevance}, Heloise and {Eldridge}, J. and {Stanway}, Elizabeth},
    title = "{Hoki: Making BPASS accessible through Python}",
    journal = {The Journal of Open Source Software},
  keywords = {Python, galaxies, Batchfile, SED, astronomy, binary stars, Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics},
     year = "2020",
     month = "Jan",
     volume = {5},
     number = {45},
     eid = {1987},
     pages = {1987},
     doi = {10.21105/joss.01987},
     archivePrefix = {arXiv},
     eprint = {2001.11069},
     primaryClass = {astro-ph.SR},
     adsurl = {https://ui.adsabs.harvard.edu/abs/2020JOSS....5.1987S},
    adsnote = {Provided by the SAO/NASA Astrophysics Data System}
 }