Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to content

jobovy/kimmy

Repository files navigation

kimmy

Galactic chemical evolution in python

image Binder

Overview

kimmy contains simple tools to study chemical evolution in galaxies.

Author

Jo Bovy (University of Toronto): bovy - at - astro - dot - utoronto - dot - ca

Installation

Install the latest release with pip

pip install kimmy

or install the latest version by cloning/forking/downloading the repository and installing using

sudo python setup.py install

or locally using

python setup.py install --user

Usage

For an example of usage, see the example notebook. You can also launch a Binder instance and directly play around with this notebook. Or you can use this pyodide-compatible version of the same notebook in JupyterLite.

Currently, the only implemented feature is a simple one-zone chemical model with two elements O (for oxygen) and Fe (for iron). Initialize this model as

import kimmy
oz= kimmy.OneZone()

then for example compute the evolution of the default model and plot the [O/Fe] vs. [Fe/H] sequence

ts= numpy.linspace(0.001,10.,1001)*u.Gyr
plot(oz.Fe_H(ts),oz.O_Fe(ts))

To compute the distribution of [Fe/H], do for example,

FeHs= numpy.linspace(-1.525,1.225,56)
FeH_dist= [oz.Fe_H_DF(f) for f in FeHs]

and similar for the distribution of [O/H] and [O/Fe]. You can directly update the main parameters of the model and the model will be re-computed. For example, to set the outflow mass-loading parameter to one and plot the [O/Fe] vs. [Fe/H] sequence, do

ts= numpy.linspace(0.001,10.,1001)*u.Gyr
oz.eta= 1.
plot(oz.Fe_H(ts),oz.O_Fe(ts))

Keep in mind that once you change a parameter, it remains changed in the model. If you want to go back to the initial set of parameters that you used to initialize the instance, use oz.initial(); if you want to go back to the default set of parameters, use oz.default(). If you want to print the model you are using at any time, do

print(oz)

which prints a nicely formatted list of all of the model parameters.